Comparative analysis of clearing methods for 3D imaging of the vasculature in mineralized mouse tissues.

Comparative analysis of clearing methods for 3D imaging of the vasculature in mineralized mouse tissues - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Official websites use .gov A .gov website belongs to an official government organization in the United States. Secure .gov websites use HTTPS A lock ( Lock Locked padlock icon ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites. Search Log in Dashboard Publications Account settings Log out Search… Search NCBI Primary site navigation Search Logged in as: Dashboard Publications Account settings Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide PERMALINK Copy As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice iScience . 2026 Mar 25;29(4):115464. doi: 10.1016/j.isci.2026.115464 Search in PMC Search in PubMed View in NLM Catalog Add to search Comparative analysis of clearing methods for 3D imaging of the vasculature in mineralized mouse tissues Azeez O Ishola Azeez O Ishola 1 Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA 22903, USA Find articles by Azeez O Ishola 1 , Athira Pillai Athira Pillai 1 Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA 22903, USA Find articles by Athira Pillai 1 , Taeyong Ahn Taeyong Ahn 1 Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA 22903, USA Find articles by Taeyong Ahn 1 ; RE-JOIN Consortium , Chih-Wei Hsu Chih-Wei Hsu 2 Department of Integrative Physiology, Optical Imaging and Vital Microscopy Core, Advanced Technology Cores, Department of Education, Innovation and Technology, Baylor College of Medicine, Houston, TX 77030, USA Find articles by Chih-Wei Hsu 2 , Brendan Lee Brendan Lee 3 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA Find articles by Brendan Lee 3 , Nele Haelterman Nele Haelterman 3 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA Find articles by Nele Haelterman 3 , Joshua D Wythe Joshua D Wythe 1 Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA 22903, USA 4 Department of Neuroscience, University of Virginia School of Medicine, Charlottesville, VA 22903, USA 5 Brain, Immunology, and Glia (BIG) Center, University of Virginia School of Medicine, Charlottesville, VA 22903, USA 6 Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22903, USA 7 University of Virginia Comprehensive Cancer Center, University of Virginia School of Medicine, Charlottesville, VA 22903, USA Find articles by Joshua D Wythe 1, 4, 5, 6, 7, 8, ∗ Author information Article notes Copyright and License information 1 Department of Cell Biology, University of Virginia School of Medicine, Charlottesville, VA 22903, USA 2 Department of Integrative Physiology, Optical Imaging and Vital Microscopy Core, Advanced Technology Cores, Department of Education, Innovation and Technology, Baylor College of Medicine, Houston, TX 77030, USA 3 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA 4 Department of Neuroscience, University of Virginia School of Medicine, Charlottesville, VA 22903, USA 5 Brain, Immunology, and Glia (BIG) Center, University of Virginia School of Medicine, Charlottesville, VA 22903, USA 6 Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine, Charlottesville, VA 22903, USA 7 University of Virginia Comprehensive Cancer Center, University of Virginia School of Medicine, Charlottesville, VA 22903, USA ∗ Corresponding author [email protected] 8 Lead contact Received 2025 Jul 3; Revised 2025 Nov 21; Accepted 2026 Mar 20; Collection date 2026 Apr 17. © 2026 The Author(s) This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). PMC Copyright notice PMCID: PMC13091420  PMID: 42006307 Summary Historically, visualization of vascular networks within the musculoskeletal system, particularly in mineralized tissues such as bones and joints, has been limited to conventional 2D histological approaches. Recent advances in optical tissue clearing technologies and fluorescence imaging approaches in whole, intact tissues offer an entrée to interrogate the vasculature at unprecedented resolution during both musculoskeletal development and in pathologic contexts in three dimensions. However, these clearing techniques were originally not developed for imaging hard mineralized tissues, such as the femur and tibia. Herein, we have optimized tissue decalcification conditions and compared aqueous- and solvent-based tissue clearing approaches to establish an optimal pipeline for clearing and imaging the vasculature in mineralized tissues of the adult mouse. Collectively, this work shows that optical clearing combined with light-sheet microscopy represents a powerful method for generating high-resolution images of the murine hindlimb vasculature, with potential applications in aging and disease modeling. Subject areas: Methodology in biological sciences, Model organism Graphical abstract Open in a new tab Highlights • This study identifies optimal methods for clearing adult mouse mineralized tissues • Extended decalcification time benefits clearing of adult, mineralized samples • RI-matching media and sample orientation impact overall 3D image quality • Tissue clearing and light-sheet imaging reveal more vascular detail than micro-CT Methodology in biological sciences; Model organism Introduction The World Health Organization estimates that more than 1.71 billion people worldwide suffer from musculoskeletal disease. 1 , 2 From rheumatoid arthritis to gout, osteoporosis, spinal disorders, lower back pain, and severe trauma, more than 150 unique musculoskeletal diseases impact people globally, leading to extensive health care expenditures. 3 Given the number of tissues that make up the musculoskeletal system—including the bones, muscles, ligaments, tendons, cartilage, and more—the prevalence of these ailments is perhaps unsurprising. Already the leading cause of physical disability, as the world population ages and risk factors increase, the number of individuals suffering from these diseases is only predicted to rise. 4 To combat the increased incidence and severity of these diseases, a deeper understanding is required of the tissues comprising the musculoskeletal system and how they interact in both health and disease, particularly osteoarthritis (OA). OA is a complex, chronic, degenerative disease affecting the whole synovial joint, characterized by structural defects and damage to the articular cartilage, loss of subchondral bone, tissue hypertrophy, increasing vascularity of the synovium, synovitis and immune cell recruitment and activation, fibrosis, and instability of the ligaments and tendons. 5 , 6 A multifaceted joint disease, OA involves systemic modifications and numerous comorbidities that influence overall health, including cardiovascular disease, obesity, type 2 diabetes, and more. 7 With over 500 million cases worldwide, OA is the fourth leading cause of disability, with an enormous socioeconomic burden globally due to health care costs, loss of work, and early retirement due to chronic pain and loss of mobility. 8 Currently, there is no cure for OA, and these patients account for 55.3% of all opioid prescriptions in the US, resulting in about $14 billion in lifetime opioid-related societal costs. 9 Accordingly, a more comprehensive understanding of tissue dynamics during OA initiation and progression is needed to more effectively treat this devastating disease. As a weight-bearing structure subjected to lifelong mechanical stressors and frequent pathological changes, the knee accounts for more than 260 million cases of OA. 10 , 11 , 12 Historically, studies of OA in the knee relied on thin serial sections followed by immunostaining and imaging. However, mechanical sectioning is labor-intensive, often destructive, and provides only a single snapshot, in one plane, of what is happening within and around the joint or bone. Alternatively, more recent studies have employed 3D imaging modalities, such as ultrasound or micro-computed tomography (micro-CT), to image this complicated structure. 13 However, increasing our understanding of OA pathogenesis necessitates defining anatomical maps of tissue relationships and cellular dynamics in healthy and diseased states through simultaneous imaging of the bones and associated tissues of the knee joint in three-dimensional space at a cellular resolution, which is beyond what is currently capable with imaging methods such as micro-CT and magnetic resonance imaging (MRI). Serendipitously, recent advances in tissue clearing 14 , 15 and light microscopy 16 have the potential to revolutionize the study of musculoskeletal biology. At a fundamental level, tissue clearing approaches render naturally opaque biological specimens optically clear. This transparency facilitates imaging large tissue volumes in their native, three-dimensional state using light microscopy modalities at imaging depths and resolutions that would otherwise not be possible due to the scattering and diffusion of light. 14 Regardless of the specific chemical reagents employed, all current tissue clearing techniques achieve transparency through similar physical principals. These approaches seek to minimize differences in refractive indices (RIs) throughout a sample, as well as between the sample and the imaging media, thereby facilitating the passage of photons from a light source (excitation) through a tissue (emission) to ultimately reach a detector. 14 , 17 The core principles of tissue clearing are the removal of light-scattering lipids (RI ∼ 1.47) and the exchange of intracellular and extracellular fluids (RI ∼ 1.35) for a solution with an RI equivalent to the protein and nucleic acid constituents that are left behind in the cell (RI > 1.50), with the goal of creating a uniform density of scatterers so that all wavelengths of light pass through a tissue. 17 As the underlying principles of tissue clearing have been well described in detail elsewhere, 18 and others have summarized recent clearing approaches, 14 we will only briefly discuss the logic underlying tissue clearing. At a gross level, tissue clearing techniques can be divided into either solvent-based (hydrophobic) or aqueous-based (hydrophilic) approaches. Early on, solvent-based methods were faster and generated a final RI more closely matched to that of the delipidated, protein-rich cleared sample. However, these methods also induced significant tissue shrinkage and generally eliminated signal from fluorescent reporters due to the requisite dehydration of the sample prior to delipidation. 19 However, aqueous-based methods preserved signal from endogenous fluorescent proteins and maintained (or, in some cases, increased) sample size due to osmosis. 18 The conceptual divide that once categorized these two approaches as incompatible has since been replaced with the understanding that steps from each methodology can, and should, be combined to optimize tissue transparency. As suggested by Richardson and colleagues, tissue clearing should be viewed as a pipeline consisting of the following modules: (1) sample fixation, (2) optional pre-treatment(s) (decolorization, decalcification, hydrogel embedding, dehydration), (3) delipidation (either active or passive), (4) optional fluorescent labeling (antibody, nanobody, dyes), (5) RI matching, and (6) image acquisition and analysis. 14 Early solvent- (i.e., BABB, 3DISCO), aqueous- (i.e., CUBIC, ClearT, ScaleAS, SeeDB), and aqueous hydrogel-based (CLARITY, PACT-PARS, SHIELD) clearing methods focused on RI matching and lipid removal in the murine brain. 20 However, these methods failed to clear thicker specimens, which blocked photons in the visible spectrum (400–600 nm) due to light scattering from mismatched RIs and light absorbance by endogenous chromophores such as hemoglobin and myoglobin. 21 Attempts to decolorize tissues through either peroxide bleaching, 22 or altering the pH of samples attenuates signal from GFP-related fluorescent proteins. 23 , 24 , 25 However, subsequent testing determined that amino alcohols could decolorize paraformaldehyde (PFA)-fixed tissues by eluting heme. 26 , 27 Overall, adapting clearing techniques for larger volumes presents a formidable challenge, particularly in samples containing muscle and mineralized tissues, such as bones or teeth. While the composition of dense collagen fibers embedded within a highly calcified extracellular matrix, primarily made of hydroxyapatite crystals, imparts bone with mechanical strength, it also scatters light, preventing photons from passing through the tissue. 28 , 29 Further, the extensive collagen fiber networks, minerals, and proteoglycans of bone and muscle produce high autofluorescence upon fixation, potentially obscuring fluorescence signals of interest. 30 , 31 , 32 In addition to these obstacles, the varying densities and mineral content of the honeycomb-like, porous network of plates and rods in trabecular bone versus the dense, solid cortical bone that resists decalcification and clearing can yield uneven clearing results, even within the same sample. 31 For example, the knee features several different RIs, including that of bone (RI ∼ 1.50), 33 articular cartilage (RI ∼ 1.35), 34 and surrounding muscles (RI ∼ 1.38). 35 Thus, a prerequisite to such imaging studies is the development of a robust tissue clearing protocol that renders all components of the knee (or any complex joint) optically transparent, as many of these early clearing methods achieved only modest imaging depths of around 200 μm when applied to bone. 29 Aqueous, hydrogel-based methods, such as PACT (passive CLARITY) 30 and PARS (perfusion-assisted agent release in situ ), 36 stabilize tissue during lipid extraction but fail to achieve optical access beyond a depth of 200–300 μm. The CLARITY variant PACT-deCAL incorporated EDTA decalcification at 37°C after hydrogel embedding and SDS delipidation, although only staining for DRAQ5 dye (which labels nuclei) was shown in this study. 37 However, Bone CLARITY surpassed these limitations by adding 2 weeks of decalcification prior to hydrogel stabilization and SDS-mediated delipidation, followed by amino alcohol (Quadrol) treatment to minimize heme autofluorescence, with all steps carried out under convective flow (via heat). 38 RI matching in RIMS (RI = 1.47) and light sheet fluorescence microscopy (LSFM) imaging allowed visualization of genetically labeled ( Sox9 CreER+ ; R26 lsl-tdTomato+ ) fluorescent cells in the femur, tibia, and vertebral column at reported depths of up to 1.5 mm, with a high signal-to-noise ratio (SNR). 38 Unfortunately, this method was only applied to isolated bones and not intact joints with encapsulating muscle, tendons, and ligaments, although more recent attempts using hydrogel have also provided encouraging results. In the hydrogel-based, passive clearing method Bone-mPACT+, Cho and colleagues decalcified bones for 11–13 days in one of four reagents (20% EDTA, Calci-Clear, 5% nitric acid, or 10% formic acid), which reduced the tissue damage associated with CLARITY-based methods by adding an additional detergent to the delipidation step. 39 Furthermore, they also included α-thioglycerol to prevent tissue discoloration, then removed heme with 25% triethanolamine (TEA) (rather than Quadrol) before RI matching in n RIMS (RI = 1.46), which yielded clear signal in Cx3cr1 GFP mouse humerus and femur. 30 While CLARITY-based clearing may not yield the optical transparency achievable with clearing methods using organic solvents (e.g., benzyl alcohol and benzoate (BABB) (Backspace, 3DISCO, iDISCO, and PEGASOS), 40 a comprehensive comparison of bone samples across various methods suggests that Bone-mPACT+ may be quite effective. 30 While these methods relied on genetically encoded fluorescent reporters, modified whole-body clearing approaches have been adapted to image structures in the bones, such as the 3DISCO variant uDISCO, which adds vitamin E to scavenge peroxides and employs tert -butanol (tB) (rather than tetrahydrofuran [THF]) for dehydration, followed by delipidation with dichloromethane (DCM) and RI matching in a mixture of BABB and diphenyl ether (BABB-D), rather than dibenzyl ether (DBE) or BABB (both of which can form peroxidase and quench the fluorescence signal due to the presence of reactive benzylic C-H and C-O bonds). While uDISCO preserved GFP signal better than several other methods (CUBIC, SeeDB, ScaleS, 3DISCO, and PACT), it induced significant isotropic shrinkage of tissues, and pigmented heme remained in the bones. 41 Notably, signal from endogenous fluorescent proteins may not overcome autofluorescence from skin, muscle, and calcified bone. Accordingly, whole-body clearing methods have been combined with immunostaining to enhance fluorescence signal. vDISCO (nanobody or V H H-boosted DISCO) employs whole-body perfusion-mediated nanobody immunolabelling in conjunction with whole-body tissue clearing. After fixation, samples are decolorized using amino alcohols (Quadrol), decalcified with EDTA, followed by nanobody perfusion and subsequent 3DISCO clearing (THF, DCM, BABB), and imaging. While vDISCO eliminates endogenous fluorophores, it enables robust nanobody labeling in the bone. 42 , 43 Continuing to expand these solvent-based approaches, Erturk and colleagues’ recent wildDISCO method combines perfusion-mediated fixation and decalcification with EDTA, followed by forced circulation of standard IgG antibodies in the presence of cyclodextrin and 3DISCO clearing (THF, DCM, BABB). The inclusion of cyclodextrin not only depletes cholesterol from membranes (rendering them more permeable to antibodies), but it also reduces antibody aggregation. This method successfully identified proliferating Ki67 + cells in the bone marrow. 44 Finally, PEGASOS employed 5 days of decalcification (20% EDTA), followed by decolorization with Quadrol and ammonium, delipidation through an increasing gradient of tB (uDISCO) in the presence of Quadrol (which raised the pH to over 9.5), dehydration in tB/polyethylene glycol (PEG), and RI-matching in benzyl benzoate/PEG/quadrol (RI = 1.54). Despite these extensive efforts, further optimization is needed to reduce autofluorescence from the surrounding muscle and bone and enable high-resolution imaging of complex joints. Neurovascular networks within the joint are thought to play critical roles in pain perception, inflammation, and tissue remodeling in OA. 45 , 46 Motivated by our interest in mapping vascular and nervous system innervation in health and disease, 47 and the fact that neurovascular remodeling due to aging and disease conditions is not yet fully explored in 3D, we sought to identify a robust clearing method that will allow for neurovascular imaging of joint tissue in situ . Our results demonstrate that extended decalcification and delipidation in a modified fDISCO- and iDISCO + -based clearing protocol most effectively render the murine hindlimb, and thus the knee joint, optically transparent. We also emphasize the critical role of RI-matching media in achieving optical transparency and provide recommendations for adapting protocols to aged and pathological bone samples. This work provides a refined framework for studying neurovascular and structural changes in bone, with implications for understanding the pathological progression of diseases such as OA. Results fDISCO, iDISCO + , and EZ Clear yield superior SNRs in mineralized tissues To visualize the complex network of vessels of the murine adult hindlimb, and specifically the vasculature surrounding and permeating the knee joint space, anesthetized mice were intravenously perfused with a far-red fluorescently conjugated lectin that specifically labels the endothelium, 48 , 49 , 50 or with Evans blue dye, which undergoes a conformational shift when it binds to serum albumen that produces fluorescence in the far-red spectrum 51 , 52 ( Figures 1 A–1C). Hindlimbs were then collected, fixed, and decalcified for 2 days in 10% EDTA at room temperature, followed by tissue clearing and 3D imaging ( Figures 1 D–1H). Figure 1. Open in a new tab Overview of the experimental workflow (A–D) Animal is anesthetized (A), followed by retro-orbital lectin injection (B). Animals then undergo transcardiac perfusion (C), followed by leg dissection and skin removal (D). (E–H) (E) Leg samples undergo fixation, decalcification, delipidation methods, and RI matching (tissue clearing) to render them transparent, as shown in (F). Cleared leg samples were imaged on a light-sheet fluorescence microscope (G) to view the vasculature, as shown in (H). We performed a side-by-side comparison of the clearing steps of nine different solvent-, aqueous-, and hybrid tissue clearing methods to determine their efficacy at clearing the complex structure of the mouse knee joint ( Figure 2 ). The solvent-based protocols we chose (iDISCO + , vDISCO, fDISCO, and uDISCO) are variations of the original 3DISCO approach, 53 as well as PEGASOS. 19 Whereas iDISCO + requires methanol dehydration and an overnight incubation in DCM for delipidation, followed by RI matching in DBE, 54 vDISCO delipidation uses THF and a brief incubation in DCM, followed by RI matching in BABB, 44 while fDISCO consists of THF-based delipidation prior to RI matching in DBE, 55 and uDISCO requires tB dehydration and a brief incubation in DCM, followed by RI matching in BABB-D4. 56 PEGASOS also employs tB for dehydration, along with overnight incubation in a mixture of tB and PEG (tB-PEG) for delipidation, and is finally RI-matched in BB-PEG. 19 We also included two hydrogel-based methods: mPACT + , which is a passive method, 39 and X-CLARITY, which utilizes a commercial electrophoretic machine. Finally, we also tested two aqueous-based clearing methods: Binaree Rapid Clearing, involving a commercial solution and machine, and an updated variation of EZ Clear, a non-commercial aqueous approach we recently described that relies on serial THF delipidation 57 unlike the original protocol, which relied on a single 20 h incubation in 50% THF. 58 Following delipidation, all samples were then equilibrated in their respective RI-matching media ( Figure 2 ). Figure 2. Open in a new tab Comparison of the different solvent- (red), aqueous- (blue), and hydrogel- (green) clearing methods used in this study A schematic showing the duration (hours and days), as well as the key steps and reagents, for iDISCO + , vDISCO, fDISCO, uDISCO, PEGASOS, EZ Clear, Binaree, CLARITY, and mPACT + optical clearing methods. Imaging by light microscopy showed that all the solvent-based tissue clearing methods—vDISCO, fDISCO, iDISCO + , uDISCO and PEGASOS—along with the aqueous-based EZ Clear, effectively rendered the mouse hindlimb optically transparent. Notably, heme was still evident within the bones using these methods, although less so in the vDISCO processed samples ( Figures 3 B–3E; Figures S1 A and S1B). While the recent hydrogel-based Bone-CLARITY approach has provided encouraging results, 38 it was not tested herein due to the extensive 2-week decalcification time. However, neither the electrophoretically assisted commercial X-CLARITY method nor the passive hydrogel-based mPACT + method achieved clearing comparable to iDISCO, fDISCO, vDISCO, or EZClear ( Figure 3 G; Figure S1 C). Relatedly, the aqueous electrophoretic commercial solution, Binaree, also failed to render the murine hindlimb transparent ( Figure 3 F). Similar to our results, a recent comparative study of tissue clearing approaches showed that 3–4 days of decalcification with 10% EDTA, followed by the original EZ Clear protocol (a single incubation in 50% THF), effectively cleared an isolated mouse tibia. 30 Figure 3. Open in a new tab Comparison of clearing methods on mouse hindlimb vascular visualization (A) Schematic diagram of the knee region indicating imaging orientation and planes of depth of view. (B–G) Light microscopy images of mouse hindlimbs cleared using either iDISCO + , vDISCO, fDISCO, EZ Clear, Binaree, or CLARITY. (H–M) Sagittal view of light-sheet fluorescent microscope (LSFM) images of mouse hindlimbs following perfusion with lectin-649 nm and processing with the indicated tissue clearing protocols (far left column). Yellow dashed box indicates the knee region. (N–S) Magnified view of the knee region corresponding to the samples shown in (H–M). (T–Y) Images showing the depth of view of the knee region (the yellow axis for the Z plane is indicated in each panel on the far left of the image). (Z–E′) Optical sections along the z axis of the knee region at increasing depths (from 1 to 3 mm) highlight the retention of crisp signal in the vessels within the iDISCO+ and EZ Clear processed samples. n = 5 samples per group; t test, p ≤ 0.05. Scale bars, 500 μm. See also Figures S1–S3 , Videos S1 , S2 , S3 , S4 , S5 , and S6 . Following clearing, these samples were imaged by LSFM, with the laser beam directed at the leg sample from an anteroposterior plane while the medial side of the leg faced the objective lens ( Figure 3 A). vDISCO, fDISCO, iDISCO + , and EZ Clear facilitated photon travel through the samples, as fluorescent signal from the conjugated lectin revealed an extensive, detailed vascular network in the cleared mouse hindlimb ( Figures 3 H–3K; Videos S1 , S2 , S3 , and S4 ). However, a limited vascular network was observed in uDISCO- and PEGASOS-cleared samples ( Figures S1 D and S1E). In contrast, the hydrogel and electrophoretic methods tested yielded less signal in the vasculature surrounding the mouse hindlimb, perhaps as expected given the light microscopy results ( Figures 3 L and 3M; Figure S1 F; Videos S5 and S6 ). Video S1. 3D video reconstruction of Figure 3H Volumetric rendering of 3D light-sheet fluorescence microscopy of a representative mouse hindlimb perfused with lectin-649 and cleared using iDISCO + reveals both the superficial and deep vascular networks within the mouse hindlimb. Download video file (21.3MB, mp4) Video S2. 3D video reconstruction of Figure 3I Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using the vDISCO protocol. Download video file (19.9MB, mp4) Video S3. 3D video reconstruction of Figure 3J Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using the fDISCO protocol, revealing both the superficial and deep vascular networks within the mouse hindlimb. Download video file (19.8MB, mp4) Video S4. 3D video reconstruction of Figure 3K Volumetric rendering of 3D light sheet-fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using EZ Clear. Download video file (11.3MB, mp4) Video S5. 3D video reconstruction of Figure 3L Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using the Binaree clearing protocol. Increased fluorescence signal (background) is observed in the bone, with diminished lectin fluorescence in the deeper part of the sample. Download video file (18MB, mp4) Video S6. 3D video reconstruction of Figure 3M Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using X-CLARITY. Download video file (11.7MB, mp4) Focusing within the hindlimb on the tissues comprising the knee joint, which undergo extensive pathogenic remodeling in joint diseases such as OA, revealed that fDISCO and iDISCO + , followed by EZ Clear, and, to a lesser extent, vDISCO and uDISCO-processed samples, featured intense fluorescent labeling in both the superficial and deep vessels within and around the knee joint, with signal also evident in the femur and tibia. Conversely, only the peripheral vessels showed clear, sharp signal within the knee joint space of PEGASOS-, hydrogel-, and electrophoretically cleared samples, with little fluorescence evident in either the bone or medial portion of the knee ( Figures 3 N–3S; Figures S1 H and S1I). To further characterize the efficiency of these clearing modalities, we evaluated photon penetration at various depths within the samples. Tissues cleared using the solvent-based tissue clearing methods (fDISCO, iDISCO + , and, to a lesser extent, vDISCO and uDISCO) featured photon penetration throughout the tissue ( Figures 3 T–3V; Figure S1 J). Conversely, Binaree- and CLARITY-processed samples showed elevated background signal and decreased photon penetration ( Figures 3 W and 3X), together with PEGASOS and mPACT + ( Figures S1 K and S1L), while EZ Clear allowed deeper photon penetration throughout the tissue, with some loss of signal at greater depths ( Figure 3 Y). Virtual sections along the z axis ( Figure 3 A) revealed that lectin-based fluorescent signal was present in all planes for vDISCO, fDISCO, iDISCO + , and EZ Clear, and, to a lesser degree, in uDISCO-processed samples ( Figures 3 Z–3C’; Figure S1 M), but diminished at deeper planes in PEGASOS-, Binaree-, X-CLARITY-, and mPACT + -treated hindlimbs ( Figures 3 D’ and 3E’; Figures S1 N and S1O). Quantification of signal-to-background ratio (SBR) on the LSFM images showed that fDISCO and iDISCO + exhibited the greatest SBR of all nine modalities ( Figures S1 P and S2 A). Consequentially, iDISCO + processed mouse hindlimbs had the highest vascular mean intensity and the lowest background signal compared to other modalities ( Figures S1 Q and S2 B). Furthermore, quantification of mean fluorescent intensity from optical Z sections showed a similar mean intensity in vDISCO-, fDISCO-, iDISCO +- , and EZ Clear-processed samples, which was significantly higher than Binaree and CLARITY modalities ( Figure S2 C). Given that fDISCO and iDISCO + robustly cleared the murine hindlimb knee joints (up to depths of 5 mm), we next tested the ability of these two solvent-based protocols to render other musculoskeletal structures (forelimb, thorax, and skull) optically transparent. fDISCO effectively cleared the murine forelimb despite extensive heme ( Figure S3 A) but failed to completely clear the spine and thoracic cage or an intact murine skull ( Figures S3 B and S3C). In contrast, similar to the hindlimb, iDISCO + also rendered these complex musculoskeletal structures optically clear ( Figures S3 J–S3L). Subsequent light-sheet imaging confirmed the superior performance of iDISCO + compared to fDISCO for visualizing 3D vascular structures in the forelimb, thoracic cage, and skull ( Figures S3 D–S3I and S3M–S3O). Higher-resolution imaging revealed detailed 3D vascular networks within the mouse palm and digits, the thoracic aorta and intercoastal arteries, and vascularization of the tongue and the teeth in iDISCO + cleared samples ( Figures S3 P–S3R), further highlighting the superiority of iDISCO + in clearing heterogeneous musculoskeletal structures. Aged mouse calcified tissues require increased decalcification While many risk factors, including obesity, prior joint injuries, biological sex, and genetic disposition (such as congenital bone or ligament abnormalities), correlate with the development of OA, the most critical risk factor is age. 59 Accordingly, OA disproportionately impacts the elderly. 60 , 61 The interplay between cellular senescence (particularly in articular chondrocytes and associated musculoskeletal cells), low-grade inflammation (especially in the synovium), and metabolic modifications synergize to drive the irreversible changes characteristic of age-related OA progression. 62 , 63 , 64 Given that iDISCO + optimally cleared hindlimbs and knee joints of 2-month-old mice, we wondered if this same processing pipeline could effectively clear 6-month-old samples, an age at which mice have reached peak bone mass. 65 Surprisingly, while light microscopy images suggested these aged tissues were of similar transparency as the 2-month-old samples ( Figure S4 A, left), LSFM revealed extensive background fluorescence signal (autofluorescence) in the femur, tibia, fibula, and patellar bones ( Figure 4 A, Video S7 ). Higher-magnification imaging of the knee joint showed that this high background fluorescence partially obscured lectin-mediated fluorescence signal in the vessels around the knee joint of aged animals ( Figure 4 B), decreasing the SNR. Furthermore, while the depth of view indicated that photons were able to penetrate the samples, fluorescent signal appeared distorted and blurry in the thickest part of the aged sample ( Figure 4 C). Hypothesizing that the increased autofluorescence may be due to the presence of mineralized tissue, the decalcification time of 6-month-old mouse samples was increased from 2 to 5 days prior to iDISCO + clearing. LSFM imaging showed a significant reduction in autofluorescence and increased signal-to-noise in the aged hindlimbs decalcified for 5 days ( Figure 4 D). Examination of the knee region revealed detailed vessel structures, with little background fluorescence signal evident from the bones in these extended decalcified samples ( Figure 4 E and Video S8 ). Furthermore, photon penetration was increased in the aged samples that were decalcified for 5 days ( Figure 4 F). Examination of virtual sections at varying depths along the z axis revealed non-specific background fluorescence at every depth examined in the 2-day decalcified tissues, particularly in deeper sections ( Figures 4 G and 4H). Conversely, the 5-day decalcified samples showed reduced autofluorescence in the bone and minimal non-specific background signal ( Figure 4 I). Quantification of lectin fluorescence indicates that 5-day decalcified samples featured higher signal and reduced background compared to 2-day decalcified samples ( Figure 4 J; Figure S4 B). Moreover, the mean fluorescent intensity across the Z-plane showed that 2-day decalcified samples had higher mean fluorescent intensity, which is due to high background fluorescence ( Figure S4 C). Thus, imaging-based studies of aged mouse samples will likely benefit from increased decalcification prior to iDISCO + -based tissue clearing and imaging. Figure 4. Open in a new tab Evaluation of decalcification duration for achieving optimal clearing and vascular visualization in aged mouse hindlimbs (A) A sagittal maximum intensity projection following LSFM imaging of a mouse hindlimb perfused with lectin-649 nm and cleared using iDISCO + with 2 days of decalcification in 10% EDTA. The yellow dashed area is magnified in (B) and represents the knee region, with the outline of the femur and tibia noted. (C) A depth-of-view image of the sample in (A) (note the z axis, in yellow, at the far left) showing how fluorescence signal diminishes at greater depths. (D) A similarly perfused mouse hindlimb processed for iDISCO + clearing after 5 days of decalcification. (E) A magnified view of the knee region from (A) and (F) a depth-of-view image showing improved signal intensity overall, less signal from bone, and more intense signal at greater imaging depths along the z axis. (G) Schematic of the knee region showing imaging orientation and planes of optical sections shown in (H) and (I). (H and I) Comparison of optical sections of the knee along the z axis. (J) Quantification of the signal-to-background fluorescence ratio (SBR) (expressed as mean ± SEM) in the mouse hindlimb showing increased SBR in the 5-day decalcification samples compared to 2-day decalcification. n = 5 samples per group (6-month-old mice; both sexes); t test, ∗∗∗∗ p ≤ 0.0001. Scale bars, 500 μm. See also Figure S4 , Videos S7 and S8 . Video S7. 3D video reconstruction of Figure 4A Volumetric rendering of 3D light-sheet fluorescence microscopy of a 6-month-old mouse hindlimb perfused with lectin-649 and cleared using the iDISCO + protocol after 2 days of EDTA-mediated decalcification. Download video file (15.9MB, mp4) Video S8. 3D video reconstruction of Figure 4D Volumetric rendering of 3D light-sheet fluorescence microscopy of a 6-month-old mouse hindlimb perfused with lectin 649 and cleared using the iDISCO + protocol after 5 days of EDTA-mediated decalcification. Download video file (22MB, mp4) DBE RI-matching media is superior to ECi and BABB for imaging iDISCO + -cleared knee samples We next set out to identify the optimal RI-matching media for iDISCO + -based LFSM imaging of musculoskeletal tissues that form the knee joint. Accordingly, we tested BABB (RI = 1.559), 66 DBE (RI = 1.562), 20 and the non-toxic DBE alternative, ethyl cinnamate (ECi) (RI = 1.558). 67 Light microscopy imaging showed that each of these three RI media rendered iDISCO + -cleared mouse hindlimbs optically transparent to transmitted light, although more pigment was evident in the bones and blood vessels of the DBE- and ECi-treated samples ( Figures 5 A–5C). LSFM imaging confirmed that all three RI media preserved lectin fluorescence ( Figures 5 D–5F). However, closer examination of the knee revealed that small-diameter, deeper vessels were difficult to resolve and appeared blurry in BABB- and ECi-matched samples compared to those in DBE ( Figures 5 G–5I, Videos S1 , S9 , and S10 ). Furthermore, examining photon penetration indicated that BABB yielded blurry pixels ( Figure 5 J), as did ECi ( Figure 5 K), whereas DBE showed clear penetration throughout the tissue ( Figure 5 L). Optical sectioning revealed reduced lectin signal intensity in deeper planes of BABB- and ECi-treated samples compared to those imaged in DBE ( Figures 5 M–5P). Quantification confirmed that DBE had a significantly higher SBR than to either BABB or ECi ( Figure S5 A). Relatedly, while the mean fluorescence intensity within vessels was similar across all RI media, DBE yielded the lowest background fluorescence intensity ( Figures S5 B and S5C). These data demonstrate that iDISCO + -cleared mineralized samples should be imaged in DBE for optimal penetration and superior signal-to-background noise intensity. Figure 5. Open in a new tab RI-matching media comparisons for iDiSCO + -cleared mouse hindlimb (A–C) Light microscopy images of mouse hindlimbs cleared with iDISCO + and RI-matched in either BABB, ethyl cinnamate (ECi), or dibenzyl ether (DBE). (D–F) Sagittal views of maximum intensity projections following LSFM imaging of mouse hindlimb RI-matched in different imaging medias. (G–I) Magnified views of the yellow boxed areas in (D–F) showing the knee region highlight the low background signal from the bone in DBE-matched samples (unlike ECi). (J–L) Depth-of-view images show aberrations and background signal (yellow arrows) in the BABB- and Eci-matched samples. (M) A schematic diagram showing the imaging orientation and planes of optical sections shown in (N–P) along the z axis. Note the background from bone and muscle in the BABB- and Eci-matched samples. n = 5 samples per group; t test, p ≤ 0.05. Scale bars, 500 μm. Panels under DBE were reused from the iDISCO + panels in Figure 3 . See also Figure S5 , Videos S1 , S9 and S10 . Video S9. 3D video reconstruction of Figure 5D Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using the iDISCO + protocol and RI-matched in BABB. Download video file (20.7MB, mp4) Video S10. 3D video reconstruction of Figure 5E Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using the iDISCO + protocol and RI-matched in ECi. Download video file (23MB, mp4) Previous works suggests that prolonged storage in DBE may compromise fluorescent signal. 68 To formally test this possibility, iDISCO + processed samples were imaged 1 day or 14 days after RI matching in DBE (day 1 vs. 14). As expected, fluorescence signal was severely diminished after 14 days of storage in DBE compared to 24 h, as were the SBR and mean fluorescent intensity ( Figures S6 A–S6D). This data suggests that samples should be imaged soon after RI matching in DBE, as prolonged storage significantly quenches fluorescence. iDISCO + allows different image orientation acquisitions compared to EZ Clear Light propagation through biological samples is in part dependent on the distance photons must travel and the heterogeneity of the tissue being imaged. 69 As tissue thickness and imaging depth increase, so too does light scattering and absorption, which in turn reduce image clarity and signal intensity. To evaluate if the distance photons travel through cleared knee joints affects the quality of the resulting image, we tested whether either imaging angle or sample orientation impacts image quality using the best-performing aqueous- (EZ clear) and solvent-based (iDISCO + ) clearing methods. Images obtained from an anterior orientation, where the laser beam is directed at the medial and lateral sides of the hindlimb while the collecting objective faces the anterior of the hindlimb, were compared to those obtained at a sagittal orientation, in which photons traveled from the anteroposterior plane and the objective faced the medial side of the hindlimb ( Figures 6 A and 6B). In the anterior orientation, superficial and peripheral vessels, such as the superior lateral and medial geniculate vessels (SLGV and SMGV) and inferior medial and lateral geniculate vessels (IMGV and ILGV), but not the deeper vessels of the hindlimb and knee region, such as the popliteal artery (PA), were clearly identified in the EZ Clear sample ( Figure 6 C and Video S11 ). Conversely, both peripheral and deep vascular structures of the hindlimb (SLGV, SMGV, ILGV, IMGV, and PA) were evident in iDISCO + samples ( Figure 6 D and Video S12 ). However, imaging in the sagittal orientation improved resolution in both the superficial and deep tissues processed with EZ Clear ( Figures 6 E and 6F). Thus, decreasing the distance of photon travel through the sample improved overall imaging of the vasculature in the knee of EZ Clear-processed samples ( Figures 6 G and 6I). However, both peripheral and deep blood vessels were evident following iDISCO + processing, regardless of sample orientation ( Figures 6 H–6J). Evaluation of photon penetration revealed decreased fluorescent signal at greater depths in the anteriorly oriented EZ Clear samples ( Figures 6 K and 6M). Conversely, photon penetration was not affected by sample orientation in the iDISCO + cleared samples ( Figures 6 L and 6N). Consistent with these observations, virtual sections demonstrated that EZ Clear samples imaged anteriorly showed a depth-dependent decrease in signal intensity and diminished resolution of small vessels, directly correlating with z axis depth ( Figure 6 O). Conversely, crisp, fluorescent signal from deep, small vessels was evident throughout the z axis in iDISCO + cleared samples imaged in the anterior orientation ( Figure 6 P). In the sagittal orientation, both methods successfully resolved small vessels throughout the depth of the sample ( Figures 6 Q and 6R). Quantification showed that the SBR in EZ Clear samples is reduced in the anterior orientation compared to the sagittal orientation, whereas iDISCO + shows a higher SBR in either orientation ( Figure S7 A). While both EZ Clear and iDISCO have similar background fluorescence, fluorescence signal within the vasculature was reduced for both views in the EZ Clear samples compared to iDISCO + processed tissues ( Figure S7 B). Furthermore, the mean fluorescent intensity of the optical sections across the Z-plane showed that EZ Clear-processed samples had higher mean fluorescence in both views than iDISCO + due to background fluorescence ( Figure S7 C). These findings demonstrate that iDISCO + provides superior optical clearing and imaging depth, regardless of imaging orientation, for complex musculoskeletal structures compared to EZ Clear. Figure 6. Open in a new tab Assessing the impact of imaging orientation between iDISCO + and EZ Clear in the mouse hindlimb (A and B) Schematics illustrate the different imaging orientations and planes of optical sections for (C–R). (C–F) Comparison of how an anterior or sagittal orientation of the sample relative to the microscope objective impacts fluorescence signal intensity and depth within the vasculature of the adult murine hindlimb following perfusion with lectin-649 and either EZ Clear or iDISCO + tissue clearing. (G–J) Optical sections of both views, with the femur and tibia indicated. (K–N) Depth-of-view images and (O–R) optical sections along the z axis of the knee region. Scale bars, 500 μm. SLGV, superior lateral geniculate vessel; SMGV, superior medial geniculate vessel; IMGV, inferior medial geniculate vessel; ILGV, inferior lateral geniculate vessel. n = 5 samples per group; t test, p ≤ 0.05. Scale bars, 500 μm. See also Figure S7 , Videos S1 , S4 , S11 , and S12 . Video S11. 3D video reconstruction of Figure 6C Volumetric rendering of 3D light-sheet fluorescence microscopy of an EZ Clear-cleared mouse hindlimb perfused with lectin-649, imaged using an anterior view. Download video file (21.9MB, mp4) Video S12. 3D video reconstruction of Figure 6D Volumetric rendering of a 3D light-sheet fluorescence microscopy image of an iDISCO + -cleared mouse hindlimb perfused with lectin-649 reveals both superficial and deep vascular networks. Download video file (20.8MB, mp4) iDISCO + -based clearing, followed by LSFM imaging of the vasculature in the mouse hindlimb, outperforms micro-CT Extensive studies of the mouse vasculature have been performed using micro-CT imaging. 70 , 71 , 72 , 73 Combined with a perfused contrast reagent to label the vasculature, this X-ray-based 3D-imaging modality, without the need for tissue clearing or extensive immunolabeling methods, has been the gold standard for capturing and analyzing vascular networks in mice. 47 , 73 , 74 However, micro-CT imaging has drawbacks, 75 as contrast agents may alter biological structures, potentially interfering with signal from dense tissues (such as bone) and masking details of interest (such as the microvasculature). Other potential confounds include exposure to potentially damaging X-rays (in the case of imaging living subjects), and the inability to resolve small-caliber blood vessels due to the limited resolution of this method. To evaluate how iDISCO + -based tissue clearing and LSFM compares to contrast-assisted micro-CT, we compared the hindlimb vascular networks in animals processed for these distinct imaging modalities ( Figure 7 ). Figure 7. Open in a new tab Comparison of the mouse hindlimb vascular network visualized by micro-CT or by iDISCO + clearing and light-sheet imaging (A and B) Anterior view of representative micro-CT images of the mouse hindlimb following perfusion with Vascupaint contrast agent and an LSFM image of a mouse hindlimb perfused with lectin-649 and cleared using iDISCO + . Bone in the micro-CT images is pseudocolored white, while vessels in both the micro-CT and light-sheet panels are color coded based on vessel diameter (the keys corresponding to vessel diameter are to the right of [E and F]). (C and D) Medial and (E and F) lateral views of the same samples. (G) Quantification of the frequency of different diameter vessels in micro-CT and LSFM-imaged samples, with error bars showing mean ± SEM. (H) Quantification of the difference in vessel volume relative to the sample volume (calculated as vessel volume ratio (%) = V e s s e l v o l u m e S a m p l e v o l u m e × 100%) between micro-CT and LSFM-imaged samples, with error bars showing mean ± SEM. F, femur; Fi, fibula; P, patella; T, tibia; IMGA, inferior medial geniculate artery; ILGA, inferior lateral geniculate artery; PA, popliteal artery; SMGA, superior medial genicular artery; SLGA, superior lateral genicular artery). n = 5 samples per group (2 month-old mice); t test, ∗∗∗∗ p ≤ 0.0001. Scale bars, 500 μm. See also Figure S8 . Large and medium-sized arterial vessels were easily identified in both the micro-CT and LSFM-imaged samples, as the superior medial and lateral genicular arteries (SMGA, SLGA) and inferior medial and lateral genicular arteries (IMGA, ILGA), which together form the genicular anastomosis that supplies the knee region, as well as the PA, were all evident ( Figure 7 ). 3D morphometric analysis revealed that micro-CT primarily captured arterial vessels larger than 45 μm in diameter, whereas vessels around 20 μm in diameter were readily evident in LSFM samples ( Figure 7 G). The overall number of vessels was greater in iDISCO + imaged samples ( Figure 7 H). This is not unexpected, given the inability of the contrast agent Vascupaint to cross small-diameter (5 μm) capillary vessels and enter the venous vasculature. Altogether, the ratio of vascular volume compared to total image volume was significantly higher in the lectin-labeled LSFM sample ( Figure 7 H). Together, these data demonstrated that tissue clearing, followed by LSFM imaging, enables visualization of a more extensive vascular network permeating the entire mouse hindlimb than micro-CT-based imaging. Discussion Studying the mouse hindlimb and knee joint has been incredibly challenging due to the distinct optical properties of the heterogeneous tissues that comprise the leg, including muscles, tendons, ligaments, and bones. Traditional histological approaches, such as hematoxylin and eosin staining of 2D paraffin sections, have provided limited insights into this complicated joint system. 76 Even advanced modalities, such as immunostaining combined with confocal imaging of cryosectioned tissue, which is both laborious and time consuming, are often challenging to interpret. Overall, these 2D imaging techniques restrict analysis to a narrow tissue region within the microscope’s field of view, failing to capture the 3D architecture of the hindlimb in general, and the knee in particular. As a result, spatial relationships of different tissues within the joint cannot be fully appreciated. To address these limitations, some researchers have explored 3D imaging modalities, such as micro-CT. 71 While this approach generates volumetric data, it suffers from limited resolution, and imaging at the cellular level is currently impossible using this modality. Furthermore, high-density bone tissue generates substantial background signals, often masking structures surrounding or embedded within the bone. 77 , 78 Tissue clearing methods have emerged as a promising solution to these obstacles, rendering tissue optically transparent through lipid removal (delipidation) and RI matching to reduce light scattering. 14 These techniques have been successfully applied to visualize vascular and neural networks in the brain, as well as other organs, such as the kidney and liver. 58 , 79 , 80 More recently, adaptations to these protocols have extended their utility to bony structures, 30 , 31 , 38 indicating their potential for detailed analysis of the mouse hindlimb. In this study, we systematically compared 5 organic solvent-based based methods (vDISCO, fDISCO, uDISCO, iDISCO + , and PEGASOS), two commercially available electrophoretic approaches (CLARITY and Binaree), one passive hydrogel-based clearing method (mPACT + ), and our previously established aqueous-based technique, EZ Clear. We also investigated how sample age, RI media, and sample orientation influence imaging results. Our results demonstrate that fDISCO, iDISCO + , and EZ Clear enable high-resolution 3D visualization of the murine hindlimb vasculature following perfusion with far-red, fluorescent tomato lectin. Notably, fDISCO and iDISCO + allowed for deeper photon penetration than all other methods tested. This indicates that the delipidation compound DCM used in iDISCO + , along with THF used in the EZ Clear approach, effectively removes lipids in the mouse hindlimb, allowing for effective tissue clearing, as previously reported. 20 , 53 , 79 We further observed that aged biological samples, which feature increased bone mineralization, 81 exhibited pronounced autofluorescence, which impaired image quality. This issue was mitigated by increasing the decalcification time, emphasizing the need for age- and tissue-specific optimization of any tissue clearing pipeline. Another key determinant of clearing success is the choice of RI-matching media. We compared several iDISCO +− compatible RI medias 44 , 67 , 80 and found that DBE consistently yielded the best imaging results, with enhanced photon depth and a greater SNR compared to BABB and ECi. Importantly, we also found that, depending on the tissue clearing modality, sample orientation during imaging significantly impacts downstream imaging results. While the sagittal orientation enabled high-quality imaging for both EZ Clear and iDISCO + , anterior-to-posterior imaging was only effective for iDISCO + -cleared samples. We attribute this difference to the anisotropic clearing efficiency of EZ Clear, particularly in thicker samples where complete delipidation and reaching RI equilibrium may be more difficult. 57 This result underscores the importance of optimizing sample orientation for each clearing protocol to ensure consistent and comprehensive visualization of structures of interest. Comparison of tissue-cleared LSFM samples to micro-CT determined that clearing and LSFM provides superior resolution of small- and medium-caliber vessels that are typically not resolved using micro-CT due to limited contrast agent perfusion and signal interference from the surrounding bone. Comparison to a blood-pool contrast agent, which could circulate through the entire vascular network (and not just the arterial endothelium, as was tested herein), may provide a more appropriate comparison to lectin and LSFM imaging. However, in our experience, these blood-pooling contrast agents induce significantly less signal attenuation than compounds such as Vascupaint, Microfil, or barium-based agents. 73 Overall, these findings show the promise of iDISCO + and LSFM as powerful tools not only for imaging the hindlimb vasculature but also for investigating musculoskeletal pathologies such as ischemia, vascular calcification, inflammation, and age-related tissue degeneration. Finally, our findings highlight the possibilities for integrating antibody-based immunostaining with tissue clearing to analyze region- and tissue-specific molecular changes in the knee. While immunostaining combined with clearing has been applied in other organs, 44 , 53 , 80 , 82 and even the femur, 39 , 83 few, if any, studies have demonstrated its effectiveness in intact musculoskeletal joints. Further optimization of antibody penetration, staining conditions, and decalcification protocols will be essential for enabling cell-type-specific and pathological studies of this complex anatomical region. Limitations of the study While this study aimed to identify the optimal clearing and imaging conditions for 3D imaging of musculoskeletal tissues using the murine knee as a case study, several important caveats remain. First, tomato lectin does not only bind the vascular endothelium, as in immunostaining-like approaches, it can label microglia, macrophages, and other cell types. As we did not perform immunostaining for co-labeling studies to validate that the observed lectin signal came from the endothelium, we cannot rule out that some fluorescence signal may have come from these non-endothelial cells. However, this concern is mitigated by the fact that lectin was perfused intravenously through the retroorbital sinus of the retina and delivered intracardially through the left ventricle, and samples were removed and quickly fixed thereafter. Thus, the possibility that lectin leaked from the vessel lumen, through the mural cells surrounding vessels, and into surrounding areas to label other tubular, vessel-like structures (which we observed, rather than diffuse, single labeled, non-vascular like structures) is minimal. A second limitation is that the blurriness observed with RI-matching solutions other than DBE may be a peculiarity of our light-sheet microscope, although the glass viewing chamber, objectives, and lasers are all standard equipment in the field and not unique to our particular commercially provided microscope (and we see optimal fluorescence across multiple channels when using DBE compared to other RI-matching media). A third concern is that our study only included 2- and 6-month-old mice and did not examine geriatric aged animals. While 6 months is the peak of bone density in mice, and our conclusions may very well extend to geriatric samples, we readily acknowledge that optimal clearing at these later ages may require further optimization. Resource availability Lead contact Requests for further information and resources should be directed to and will be fulfilled by the lead contact, Joshua D. Wythe ( [email protected] ). Materials availability This study did not generate new unique reagents. Data and code availability • All raw microscope and micro-CT image data are deposited on pennsieve.io ( https://doi.org/10.26275/qtp6-rfix ) and at the SPARC Portal ( https://sparc.science/datasets/651 ). • This paper does not report original code. • Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request. Acknowledgments The authors thank members of the RE-JOIN consortium. The RE-JOIN consortium consists of Armen Akopian, Kyle Allen, Alejandro Almarza, Benjamin Arenkiel, Basak Ayaz, Yangjin Bae, Bruna Balbino de Paula, Anita Bandrowski, Mario Danilo Boada, Jacqueline Boccanfuso, Jyl Boline, Dawen Cai, Carpio, Dellina Lane, Robert Caudle, Racel Cela, Yong Chen, Rui Chen, Brian Constantinescu, Cortez, Ibdanelo, Yenisel Cruz-Almeida, M. Franklin Dolwick, Chris Donnelly, Zelong Dou, Joshua Emrick, Malin Ernberg, Danielle Freburg-Hoffmeister, Spencer Fullam, Janak Gaire, Akash Gandhi, Benjamin Goolsby, Stacey Greene, Nele Haelterman, Michael Iadarola, Shingo Ishihara, Azeez Ishola, Sudhish Jayachandran, Zixue Jin, Frank Ko, Priya Kulkarni, Zhao Lai, Brendan Lee, Yona Levites, Carolina Leynes, Jun Li, Martin Lotz, Lindsey Macpherson, Tristan Maerz, Camilla Majano, Anne-Marie Malfait, Maryann Martone, Bella Mehta, Richard Miller, Rachel Miller, Michael Newton, Alia Obeidat, Merissa Olmer, Dana Orange, Miguel Otero, Kevin Otto, Folly Patterson, Marlena Pela, Sienna Perry, Theodore Price, Hernan Prieto, Russell Ray, Dongjun Ren, Margarete Ribeiro Dasilva, Alexus Roberts, Elizabeth Ronan, Oscar Ruiz, Shad Smith, Mairobys Soccorro, Kaitlin Southern, Joshua Stover, Michael Strinden, Hannah Swahn, Evelyne Tantry, Sue Tappan, Luis Tovias Sanchez, Airam Vivanco-Estela, Joost Wagenaar, Lai Wang, Kim Worley, Joshua Wythe, Jiansen Yan, and Julia Younis. This work was supported by grants from the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health through the NIH HEAL Initiative ( https://heal.nih.gov/ ) under award number UC2AR082200 to B.L. and J.D.W. and by the University of Virginia Comprehensive Cancer Center and Intelligent Imaging Innovations, Inc. (3i, Denver, CO, USA) and by the Molecular Imaging Core (MIC) at the University of Virginia. Author contributions J.D.W. conceptualized the study. J.D.W. and A.O.I. wrote the original draft. A.O.I., A.P., T.A., and C.-W.H. executed, imaged, and analyzed experiments. A.O.I., T.A., C.-W.H., and J.D.W. were involved in the design of experiments. N.H. revised the manuscript and provided helpful feedback and comments. All authors edited the manuscript and consented to its contents. B.L. and J.D.W. secured funding and oversaw the study. Declaration of interests The authors have no conflicts to declare. STAR★Methods Key resources table REAGENT or RESOURCE SOURCE IDENTIFIER Chemicals, peptides, and recombinant proteins Lycopersicon esculentum (tomato) lectin 649 nm Vector Laboratories DL-1178-1 Methanol Sigma-Aldrich 154903 Dichloromethane Sigma-Aldrich 270997 Dibenzyl ether ThermoScientific A18447.30 Tetrahydrofuran Sigma-Aldrich 186562 Benzyl alcohol Sigma-Aldrich 24122 Benzyl benzoate Sigma-Aldrich W213802 Nycodenz PROGEN 18003 Urea Sigma-Aldrich 51456 Sodium azide Sigma-Aldrich S2002 Heparin Mckesson 63739092025 Formalin Leica 3800598 Vascupaint MediLumine Inc MDL-121 Ethylenediaminetetraacetic acid (EDTA) Sigma-Aldrich E9884 Paraformaldehyde (PFA) Sigma-Aldrich P6148 tert-Butanol Sigma-Aldrich 360538 Diphenyl ether Sigma-Aldrich 240834 DL-alpha-tocopherol Sigma-Aldrich 258024 Quadrol Sigma-Aldrich 122262 Poly (ethylene glycol) methacrylate [PEGMMA500] Sigma-Aldrich 409357 Acrylamide Bio-Rad 1610140 Triton X-100 Sigma-Aldrich X100 2,2′-azobis[2-(2-imidazolin-2-yl)propane]dihydrochloride (VA-044) Sigma-Aldrich ALNH9A9D8A56 Sodium dodecyl sulfate (SDS) Sigma-Aldrich 436143 Sodium deoxycholate (SDC) Sigma-Aldrich D6750 Thioglycerol Sigma-Aldrich M1753 Triethanolamine Sigma-Aldrich T58300 Tween-20 Sigma-Aldrich P1379 Evans Blue Sigma-Aldrich E2129 Saline Solution Sigma-Aldrich S8776 Critical commercial assays Binaree Rapid Tissue Clearing System Binaree Inc. BDTC-003 Binaree Tissue Clearing Rapid Solution Binaree Inc. BRTC 402 X-CLARITY Hydrogel Solution Logos Biosystem C1310X Electrophoretic Tissue Clearing Solution Logos Biosystem C13001 X-CLARITY Tissue Clearing System Logos Biosystem C30001 micro-CT machine Bruker SkyScan 1276 CMOS EDITION Cleared Tissue Light Sheet XL microscope (CTLS XL) 3i Intelligent Imaging Innovations, USA Deposited data Light sheet and micro-CT data pennsieve.io and SPARC Portal https://doi.org/10.26275/qtp6-rfix ; https://sparc.science/datasets/651 Software and algorithms NRecon Bruker, Belgium Imaris Oxford Instrument UK Imaris 10.2.0 SlideBook Software Intelligent Imaging, USA SlideBook2024 Imaris File Converter Oxford Instruments, UK ImarisFileConverter 10.0 ImageJ imagej.net Prism GraphPad, USA Prism 10 Other Syringe pumps New Era Instruments InfusionONE NE-300 50 mL Falcon Tubes VWR 10025-682 20 mL Glass scintillation tubes Sigma-Aldrich DWK986546 25-guage syringe BD PrecisionGlide 305122 5 mL plastic vial Axygen Scientific ST-5ML Open in a new tab Experimental model and study participant details For all experiments, C57BL6 mice were bred either bred in house, or obtained from The Jackson Laboratory, and samples from both female and male mice were used for the current study. Mice were housed with ad libitum access to food (normal chow diet) and water and maintained a 12-h light–12-h dark cycle at 21°C and 50–60% humidity and were confirmed pathogen free by institutional veterinarian staff from the center for comparative medicine (CCM). Mice mated naturally as either pairs or a trio (one male to two females) and the day of birth was considered postnatal day 0 (P0). All adult mice were 8 weeks of age, or older, as indicated in the text. This study was approved by the Institutional Animal Care and Use Committee at the University of Virginia School of Medicine under IACUC protocol #4446. Method details Tomato lectin or Evans blue dye perfusion and vascular labeling Mice were processed for fluorescent labelling of the vascular endothelium as previously described. 57 Briefly, animals were transferred to a secure induction chamber (approximately 1 L in volume for an adult mouse) and anesthetized using 4.0% isoflurane (1-2 L/min flow rate). Once the animal failed to maintain its righting reflex, and breathing had slowed, they were removed from the induction chamber and placed on their back while a tight-fitting cone was placed over their nose, and anesthesia maintained using 2-3% vaporized isoflurane. After the depth of anesthesia was confirmed by absence of toe pinch reflex, mice were retro-orbitally injected with 50 μL Lycopersicon esculentum (tomato) lectin 649 nm (Vector Laboratories, USA DL-1178-1) or 50 uL of 2% Evans blue dye (Sigma-Aldrich E2129) in sterile saline solution (Sigma-Aldrich S8776) into the retro-bulbar sinus vein using a 31-gauge needle. The needle was then gently removed, and solution was allowed to circulate for 15 minutes. The animal was then transferred to a Styrofoam board, their extremities pinned, the chest sprayed with 70% ethanol, and the dermis, rib cage, and then peritoneum opened to allow access to the heart. Then 100-150 μL of lectin-649 nm, or 100 μL of Evans blue dye, was perfused transcardially through the left ventricle using a 27-gauge needle, and the lectin was allowed to circulate for 5 minutes with the needle in place at the site of injection. Next, the mice were perfused with 10 mL of 1x PBS, then 10 mL of ice-cold 4% PFA/1x PBS using a syringe pump (InfusionONE NE-300, New Era Instruments, USA) set at 0.4 mL/minute with the right atrium punctured to allow for venous blood to drain out of the animal and efficient perfusion of PBS and fixative. In the case of mice perfused with Evans blue dye, exsanguination was not performed (to retain the Evans blue bound to serum albumen within the vessels and preserve fluorescence signal). Hindlimb preparation and decalcification After perfusion, hindlimbs were dissected away from the mouse, the skin removed, and samples submerged in 50 mL of ice-cold 4% PFA/1x PBS in a 50 mL Falcon tube (VWR 10025-682) and kept on an orbital shaker set at 30 rpm, protected from light, overnight at 4°C. The following day, samples were washed 3 times in 1x PBS at room temperature, for 30 minutes each wash, on an orbital shaker set at 30 rpm. The hindlimbs were then decalcified in 50 mL of 10% EDTA/1x PBS in a 50 mL Falcon tube at room temperature on an orbital shaker set at 30 rpm for either 2 or 5 days (depending on the age of the sample). Samples were then washed 3 times with 1x PBS, for 30 minutes each wash, at room temperature on an orbital shaker set at 30 rpm and processed for tissue clearing as indicated below. iDISCO + tissue clearing Samples were processed following the clearing steps as described. 54 Briefly, fixed, decalcified hindlimbs in 50 mL Falcon tubes (VWR 10025-682) were serially dehydrated by 60-minute washes through an increasing gradient (20%, 40%, 60%, 80%, 100%) of methanol (Sigma-Aldrich 154903) diluted in water with gentle agitation, while protected from light, followed by overnight incubation in 100% methanol. Hindlimbs were then delipidated in 66% v/v dichloromethane (DCM) (Sigma-Aldrich 270997) prepared in methanol for 24 hours at room temperature on an orbital shaker. The following day, the samples were washed two times, for 15 minutes each wash, in 100% DCM to remove methanol. The samples were then incubated for 24 hours at room temperature, with gentle agitation, in 100% dibenzyl ether (DBE) (ThermoScientific, A18447.30) to render the samples transparent. The following day, the DBE was exchanged for fresh DBE and samples were placed on an orbital shaker at room temperature, protected from light, for another 24 hours. Samples were then stored in DBE at room temperature until they were imaged. vDISCO clearing Samples were processed following the clearing steps as described. 44 Briefly, samples were placed in a 20 mL glass scintillation tube (Sigma-Aldrich DWK986546) wrapped in foil to protect them from light. Samples were delipidated by a series of 12-hour washes through an increasing gradient (50%, 70%, 80%, 100%) of tetrahydrofuran (THF) (Sigma-Aldrich 186562) diluted in water with gentle agitation. Next, samples were gently washed in 100% DCM for 3 hours at room temperature on an orbital shaker. Samples were then rendered transparent in a 1:2 mixture of benzyl alcohol (Sigma-Aldrich 24122) and benzyl benzoate (Sigma-Aldrich W213802) (i.e. BABB), for 24 hours with gentle agitation in the same glass scintillation tube. Samples were stored in a fresh BABB solution at room temperature until they were imaged. fDISCO tissue clearing Samples were processed as reported, 55 with minor modifications. Briefly, the samples were placed in a 20 mL glass scintillation tube (Sigma-Aldrich DWK986546) wrapped in foil to protect them from light. Samples were dehydrated and delipidated by a series of overnight washes through an increasing gradient (50%, 70%, 80%, and 100%) of THF (Sigma-Aldrich 186562) diluted in water with gentle agitation at room temperature. After the last wash in 100% THF, samples were RI-matched in 100% DBE (ThermoScientific, A18447.30) at room temperature overnight. The samples were stored in fresh DBE next until they were imaged. uDISCO tissue clearing Decalcified mouse hindlimbs processed for modified uDISCO clearing as reported. 56 Briefly, samples were rinsed in 1x PBS three times, for 30 minutes each wash. Next, samples were incubated in an increasing gradient of tert -butanol (Sigma-Aldrich 360538) (30, 50, 70, 80, 90, 96, and 100%) in water at 35°C overnight each. Next, samples were incubated in 100% DCM (Sigma-Aldrich 270997) for 2 hours at room temperature. Samples were then RI-matched in BABB-D4 (mixture of benzyl alcohol [Sigma-Aldrich 24122] and benzyl benzoate [Sigma-Aldrich W213802] at a 1:2 ratio along with 25% diphenyl ether [Sigma-Aldrich 240834]) and 0.4% DL-alpha-tocopherol (Sigma-Aldrich 258024) overnight at room temperature. Samples were placed in fresh RI solution the following day and stored in this solution until imaging. PEGASOS tissue clearing Decalcified mouse hindlimbs were processed for modified PEGASOS clearing. 19 Briefly, decalcified hindlimbs were rinsed in 1x PBS three times, for 30 minutes each wash, then incubated in 25% quadrol (Sigma-Aldrich 122262) solution in water overnight at room temperature. The following day, samples were washed three times in 1x PBS, for 30 minutes each wash, at room temperature. Samples were then dehydrated in an increasing gradient of tert -butanol (Sigma-Aldrich 360538-2L) (30, 50 and 70%) in water overnight. Samples were then delipidated in tB-PEG solution containing 70% tert -butanol, 27% poly (ethylene glycol) methacrylate [PEGMMA500] [Sigma-Aldrich 409357], and 3% quadrol at room temperature for 2 days. Samples were then RI-matched in BB-PEG solution containing 75% benzyl benzoate (Sigma-Aldrich W213802), 25% PEGMMA500, and 3% quadrol at 37°C until they were optically cleared. EZ clear tissue clearing Samples were cleared as described previously. 57 , 58 Briefly, fixed, decalcified samples in of a 20 mL glass scintillation tube (Sigma-Aldrich DWK986546) were submerged in an increasing gradient (50%, 70%, then 80%) of Tetrahydrofuran (THF) (Sigma-Aldrich 186562-1L) diluted in ddH 2 O, with the exterior of the tube wrapped in foil to protect the samples from light, and then incubated for 12 hours in each solution on an orbital shaker set at 100 rpm at room temperature. Samples were then washed four times in ddH 2 O, for 60 minutes each wash, to remove the THF solution. The vial was left open after the last wash to allow for evaporation of ddH 2 O. Next, the samples were submerged in EZ View solution [80% nycodenz (PROGEN 18003) 7 M urea (Sigma-Aldrich 51456) 0.05% sodium azide (Sigma-Aldrich S2002) 0.02 M sodium phosphate buffer] in the same scintillation tube wrapped in foil to protect the samples from light. Samples were stored in fresh EZ View solution in the same 20 mL glass scintillation tube until imaging. Binaree tissue clearing Hindlimbs were processed using the Binaree Rapid Tissue Clearing system (Binaree, Inc., BDTC-003), as recommended by the manufacturer. Briefly, fixed, decalcified adult hindlimbs were placed in the sample chamber and a sponge was placed on top of the sample to keep it in place. Next, samples were submerged in 20 mL of Rapid Binaree Tissue Clearing Rapid Solution (Binaree, BRTC 402) that was pre-equilibrated to 37°C. The chamber was secured to the electrode, and the machine set to 100 V for 24 hours for electrophoretic clearing. The following day, samples were washed in ddH 2 O three times, for 10 minutes each wash, in a 20 mL glass scintillation tube wrapped in foil to protect them from light. The samples were then submerged in EZ View solution for 24 hours with gentle agitation at room temperature to render the samples transparent, while still protected from light. The EZ view solution was replaced the following morning, and samples were stored in EZ view at room temperature until imaging. CLARITY tissue clearing X-CLARITY clearing was performed according to the manufacturer’s instruction (Logos Biosystems). Briefly, decalcified mouse hindlimbs were rinsed three times in 1x PBS, for 30 minutes each wash, at room temperature. Next, the hindlimbs were immersed in 20 mL of X-CLARITY Hydrogel Solution with 0.25% (w/v) of polymerization initiator VA-044 (Logos Biosystems, C1310X) and incubated at 4°C for 24 hr. Cross-linking of the hydrogel was then thermally induced at 37°C under a vacuum (–90 kPa) for 3 hr. After crosslinking, the hydrogel solution was removed and the hindlimbs were washed three times in 1x PBS, for 1 hr each wash, followed by an additional overnight wash at 4°C. Hydrogel infused and crosslinked hindlimbs were then submerged in electrophoretic tissue clearing solution (Logos Biosystems, C13001 ) and cleared using the X-CLARITY Tissue Clearing System (Logos Biosystems, C30001 ) with the following settings: 1.0 A and 37°C for 24 hr. After electrophoresis, hindlimbs were washed three times in 50 mL of 1x PBS, 1 hr each wash, and washed once more overnight at room temperature. Samples were then RI matched in EZ View solution for 24 hours on an orbital shaker, then stored in fresh EZ view solution until they were imaged. Bone mPACT+ tissue clearing Decalcified mouse hindlimb were processed for modified Bone-mPACT+ clearing. 39 Briefly, decalcified hindlimbs were washed in PBST (1X PBS, 0.1% of Triton X-100 (Sigma-Aldrich X100)) three times, for 1 hour each wash. Next samples were submerged in 4% acrylamide (Bio-Rad 1610140) in 1x PBS at 45°C overnight. Samples were washed in PBST three times, for 1 hour each wash, were then transferred into 0.25% 2,2′-azobis[2-(2-imidazolin-2-yl)propane]dihydrochloride (VA-044) (Sigma-Aldrich ALNH9A9D8A56) in 1x PBS. The samples were then degassed under nitrogen for 10 minutes, placed under vacuum for another 10 minutes, and incubated at 45°C overnight. After embedding, the samples were washed in PBST three times at room temperature, for 1 hour each wash. Samples were then transferred into a mixture of 8% sodium dodecyl sulfate (SDS) [Sigma-Aldrich 436143], 10% sodium deoxycholate (SDC) [Sigma-Aldrich D6750], and 0.5% thioglycerol (Sigma-Aldrich M1753) in 1x PBS and incubated at 45°C. Clearing was not achieved after 5 days of incubation. Samples were then rinsed briefly in PBST three times for 30 minutes each, and transferred to 25% triethanolamine (Sigma-Aldrich T58300 ) solution in 1x PBS at 45°C for 2 days, then incubated in PBST three times for 1 hour each wash. Samples were then RI-matched overnight at room temperature in either nRIMS solution containing 0.8 g/mL of Nycodenz (PROGEN 18003) in base buffer containing 0.01% w/v of sodium azide (Sigma-Aldrich S2002), 0.1% v/v Tween-20 (Sigma-Aldrich P1379) in 1x PBS, or in EZ view solution. Vascupaint perfusion and Micro-CT imaging Adult C57BL/6 male and female mice were anesthetized using vaporized isoflurane until they were unresponsive to noxious stimuli. Afterward, their chest was opened, rib cage reflected, and right atrium opened. Then, the animal was transcardially perfused through the left ventricle using a blunted 25-gauge syringe (BD PrecisionGlide, #305122) with 8 mL warm 1x PBS / 20 U/mL heparin (Mckesson, #63739092025), followed by 8 mL 10% neutral buffered formalin (Leica, #3800598), and then 1 mL Vascupaint TM (MediLumine Inc, MDL-121). Vascupaint TM was prepared as follows: 1 mL silicone, 2 mL diluent, and 40 μL catalyst. The following day, the leg was removed from the spine near the hip joint, and then the skin and fur were removed. Hindlimbs were then embedded in 1% low melt agarose in ddH 2 O in a 5 mL plastic vial (Axygen Scientific, ST-5ML) to inhibit movement of the sample during imaging and to prevent tissue shrinkage from dehydration. Micro-CT images were obtained using a SkyScan 1276 CMOS EDITION (at the Molecular Imaging Core at the University of Virginia School of Medicine). Scans were performed using the following parameters: source voltage and current (60 kV and 80 μA) and an exposure time of 471 milliseconds with an angular rotation step of 0.3° and an imaging voxel size of 9 μm 3 and an AI filter of 0.25 μm. The distance of X-ray to object was set to 199.98 mm. Acquired images were then reconstructed using NRecon Reconstruction software (Bruker Micro CT, Kontich, Belgium). Micro-CT Tiff files were loaded in NRecon software, after which the preview setting was selected. Background noise was reduced using the slider on the histogram in the output window to reduce background noise and ring artefacts, the ‘HU’ and ‘Scale’ tab were unchecked, but the ROI was selected. The new set of ‘tiff’ files were then saved in a separate folder. The saved NRecon tiff files were imported into Imaris software V10.2.0 (Oxford Instrument UK) using the import file series function in Imaris to create a 3D volumetric image. Next, the bone was masked by using the surface creation function in Imaris using the machine learning algorithm to mask the signal from the bone by setting the voxel within the surface to zero and un-checking the box for determining voxel size outside the surface. The vessels were then traced using the filament tracing function in Imaris and the tracing was color-coded based on vessel diameter for visualization. The snapshot of the bone surface with the colour-coded vessel diameter tracing was captured using the snapshot function in Imaris. The images were then exported to Adobe Illustrator for creating figures. Vascular tracing data were obtained from Imaris by clicking on the statistics tab in the filament tracing window and the filter function on the filament tracing was used to obtain data for different vessel diameters by adding the segment mean diameter filter. Light sheet image acquisition All cleared mouse hindlimbs were imaged within 48 hours after RI-matching, unless noted otherwise in the text, using a Cleared Tissue Light Sheet XL microscope (CTLS XL) (3i Intelligent Imaging Innovations, USA). The samples were mounted on the sample holder secured by a screw. The sample holder was then attached to the stage anchor inside the imaging chamber of the microscope and secured by a magnet. The samples were placed so that they were submerged in the glass imaging chamber by the indicated refractive index matching solution. Images were captured using a 640 nm laser which was directed to the sample from both sides, with the power set to 200 mW, with an exposure time of 100 ms. The images were captured at a resolution of 0.8 μm and depth of view of 11.0 μm in a tiled sequence with 15% overlap. LSFM image processing and quantitative analysis Acquired tiled images were stitched together and merged into a 3D image using SlideBook Software (Intelligent Imaging Innovations). Merged images were converted to Imaris compatible files (.ims) using the ImarisFileConverter V10.1.0. (Oxford Instruments, UK). Images were then further processed using Imaris software V10.2.0 (Oxford Instruments, UK). Representative snapshots of maximum intensity projections (MIP) of the images were obtained using the snapshot function in Imaris, and snapshots of optical sections along the Z-axis were created using the oblique slicer function. For vascular analysis, the surface function in Imaris was used to trace vessels using the machine learning algorithm, then the surface tracing was masked by changing the voxel size within the surface to 200 and changing outside the surface to zero to produce a masked image of the vessels. Next, the filament tracing function in Imaris was used to color-code the vessels based on their diameter. All snapshot images were exported to Adobe Illustrator for creating figures. Mean fluorescence intensity of optical sections along the Z-axis was calculated using ImageJ software. 50 Quantification and statistical analysis Quantified data (signal to background ratio, mean intensities and vascular metrics) were presented as mean ± standard error of mean (SEM). Pair-wise analysis was done using t-test, analysis of variance (ANOVA), and multiple comparison tests were calculated using Prism 10 software (GraphPad). All n values, as well as what each data point represents, and the statistical test used, can be found in each figure legend. Published: March 25, 2026 Footnotes Supplemental information can be found online at https://doi.org/10.1016/j.isci.2026.115464 . Supplemental information Document S1. Figures S1–S8 mmc1.pdf (5.3MB, pdf) References 1. 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Supplementary Materials Video S1. 3D video reconstruction of Figure 3H Volumetric rendering of 3D light-sheet fluorescence microscopy of a representative mouse hindlimb perfused with lectin-649 and cleared using iDISCO + reveals both the superficial and deep vascular networks within the mouse hindlimb. Download video file (21.3MB, mp4) Video S2. 3D video reconstruction of Figure 3I Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using the vDISCO protocol. Download video file (19.9MB, mp4) Video S3. 3D video reconstruction of Figure 3J Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using the fDISCO protocol, revealing both the superficial and deep vascular networks within the mouse hindlimb. Download video file (19.8MB, mp4) Video S4. 3D video reconstruction of Figure 3K Volumetric rendering of 3D light sheet-fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using EZ Clear. Download video file (11.3MB, mp4) Video S5. 3D video reconstruction of Figure 3L Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using the Binaree clearing protocol. Increased fluorescence signal (background) is observed in the bone, with diminished lectin fluorescence in the deeper part of the sample. Download video file (18MB, mp4) Video S6. 3D video reconstruction of Figure 3M Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using X-CLARITY. Download video file (11.7MB, mp4) Video S7. 3D video reconstruction of Figure 4A Volumetric rendering of 3D light-sheet fluorescence microscopy of a 6-month-old mouse hindlimb perfused with lectin-649 and cleared using the iDISCO + protocol after 2 days of EDTA-mediated decalcification. Download video file (15.9MB, mp4) Video S8. 3D video reconstruction of Figure 4D Volumetric rendering of 3D light-sheet fluorescence microscopy of a 6-month-old mouse hindlimb perfused with lectin 649 and cleared using the iDISCO + protocol after 5 days of EDTA-mediated decalcification. Download video file (22MB, mp4) Video S9. 3D video reconstruction of Figure 5D Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using the iDISCO + protocol and RI-matched in BABB. Download video file (20.7MB, mp4) Video S10. 3D video reconstruction of Figure 5E Volumetric rendering of 3D light-sheet fluorescence microscopy of a mouse hindlimb perfused with lectin-649 and cleared using the iDISCO + protocol and RI-matched in ECi. Download video file (23MB, mp4) Video S11. 3D video reconstruction of Figure 6C Volumetric rendering of 3D light-sheet fluorescence microscopy of an EZ Clear-cleared mouse hindlimb perfused with lectin-649, imaged using an anterior view. Download video file (21.9MB, mp4) Video S12. 3D video reconstruction of Figure 6D Volumetric rendering of a 3D light-sheet fluorescence microscopy image of an iDISCO + -cleared mouse hindlimb perfused with lectin-649 reveals both superficial and deep vascular networks. Download video file (20.8MB, mp4) Document S1. Figures S1–S8 mmc1.pdf (5.3MB, pdf) Data Availability Statement • All raw microscope and micro-CT image data are deposited on pennsieve.io ( https://doi.org/10.26275/qtp6-rfix ) and at the SPARC Portal ( https://sparc.science/datasets/651 ). • This paper does not report original code. • Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request. 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