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Published in final edited form as: ACS Sens. 2025 May 26;10(6):4276–4285. doi: 10.1021/acssensors.5c00521 Search in PMC Search in PubMed View in NLM Catalog Add to search Performance Evaluation of a Miniaturized, Toothbrush-Shaped Ultrasound Transducer for Periodontal Imaging Suhel Khan Suhel Khan 1 Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States Find articles by Suhel Khan 1 , Pei Yun Tsai Pei Yun Tsai 2 Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States Find articles by Pei Yun Tsai 2 , Baiyan Qi Baiyan Qi 3 Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States Find articles by Baiyan Qi 3 , Casey Chen Casey Chen 4 Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, California 90089, United States Find articles by Casey Chen 4 , Jesse V Jokerst Jesse V Jokerst 5 Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States; Material Science and Engineering Program and Radiology Department, University of California, San Diego, California 92093, United States Find articles by Jesse V Jokerst 5 Author information Article notes Copyright and License information 1 Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States 2 Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States 3 Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States 4 Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, California 90089, United States 5 Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States; Material Science and Engineering Program and Radiology Department, University of California, San Diego, California 92093, United States Author Contributions The manuscript was written with contributions from all authors. All authors have given approval to the final version of the manuscript. ✉ Corresponding Author : Jesse V. Jokerst – Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States; Material Science and Engineering Program and Radiology Department, University of California, San Diego, California 92093, United States; [email protected] Issue date 2025 Jun 27. PMC Copyright notice PMCID: PMC13091309 NIHMSID: NIHMS2162983 PMID: 40420333 The publisher's version of this article is available at ACS Sens Abstract A miniature, high-frequency ultrasound transducer could have major value in dentistry and periodontal care. Still, most current ultrasound transducers use large form factors, which limit access to molars and premolars. This paper reports a compact side-facing, toothbrush-shaped ultrasound transducer with a portable handle for real-time imaging of anatomical structures. The 128-element, high-frequency (40 MHz) response of the transducer was utilized to characterize the axial and lateral resolution at 2–16 mm depths, as well as the impact of angulation. The mean axial and lateral resolutions were 49 ± 15 μ m and 149 ± 21 μ m, respectively. The impact of angulation on imaging quality was evaluated. An acceptable angular window of −15° to +20° in the roll and pitch axes was found to produce correct anatomical information. Angulation in the yaw axis loses control over the reference plane. The transducer soft tissue-related measurements (gingival thickness and gingival height) correlated with the gold-standard clinical measurements. The correlation coefficients, r = 0.7243 ( p = 0.0001) for gingival thickness and 0.7886 ( p < 0.0001) for gingival height, show a strong correlation with the clinical method. The Bland-Altman plot compared ultrasound imaging and manual periodontal probe measurements indicated a bias of −0.002 mm and −0.0263 mm, respectively, for gingival thickness and height, with a 95% limit of agreement. The miniaturized high-frequency transducer offers optimal adaptation to the tooth surface with a wide range of working axes, providing high-resolution and detailed ultrasound images for real-time scans of the periodontium. Keywords: periodontal imaging, miniaturized ultrasound transducer, transducer angulation, ultrasonography, anatomical biomarkers, statistical analysis Graphical Abstract Periodontal disease is a common oral health disorder that affects the gingiva, periodontal ligament, and alveolar bone. Gingivitis is the initial stage of periodontitis and is marked by gingival inflammation associated with dental plaque. 1 , 2 If left untreated, gingivitis may progress to periodontitis, characterized by the loss of attachment and alveolar bone, and the deepening of the periodontal sulcus creates periodontal pockets. These deep periodontal pockets promote microbial dysbiosis, which in turn leads to more tissue loss from the host’s inflammatory response. Over time, the self-perpetuating cycle of bacteria–host interaction may progress unabated, leading to tooth loss. 3 There are several diagnostic methods for periodontal disease and oral health monitoring, and each has unique benefits and drawbacks. Clinicians routinely assess periodontal health using a periodontal probe to measure pocket depths, gingival recession, and clinical attachment loss. 4 This method provides immediate results, is widely accessible, and is cost-effective, but it is subjective, with high inter- and intraexaminer variations associated with the clinician’s experience and training. In part due to these variations, periodontal probing has limited sensitivity for detecting early-stage diseases. 5 Additionally, probing can cause discomfort or bleeding. Radiographic imaging detects bone loss and other impaction issues but involves ionizing radiation exposure and lacks soft tissue contrast. 6 , 7 Radiography is also insensitive to minor changes in alveolar bone levels. 8 – 10 CBCT offers clinically acceptable anatomical information but has limitations, such as higher costs, low soft tissue contrast, image artifacts from proximal radio-dense (metallic) objects, and its inherent nonquantitative nature. 11 , 12 Microbiological testing identifies specific periodontal pathogens, enabling targeted treatment, but it is costly, complex, and not widely used in routine practice. 13 Emerging optical imaging techniques, such as optical coherence tomography (OCT) and near-infrared fluorescence (NIRF), can show high-resolution images of soft tissues. 14 , 15 However, these optical techniques are expensive and face low penetration depth (<2 mm) due to the high scattering of biological tissues. 16 – 20 In contrast, ultrasound is an affordable, nonionizing, and real-time tool for medical imaging. 21 – 27 Still, it is surprisingly rare in dentistry despite being ideally suited to evaluating soft tissue and bone. Ultrasound is employed as an adjunctive modality for the evaluation of tissue perfusion. 28 , 29 The basic principle is that ultrasound waves undergo scattering or reflection based on the acoustic impedance and the size of the encountered structures, thereby forming images with the reflected echoes detected by a transducer. Structures significantly smaller than the acoustic pulse scatter the waves in all directions, while larger structures reflect the waves under Snell’s Law 11 (acoustic waves reflect when traveling from one medium to another with a higher speed of sound). For example, if the transducer frequency is 24 MHz, then the acoustic pulse λ = 61.7 μ m in a water medium cannot resolve targets smaller than 61.7 μ m, which are commonly needed in oral health. Transducer resolution is a key characteristic that defines the smallest target size that can be resolved. An ultrasound transducer’s spatial resolution is predominantly determined by the center frequency and beam characteristics. Axial resolution is determined by half of the spatial pulse length (SPL), which is the product of the number of cycles in a pulse. 30 , 31 Higher center frequencies improve the axial resolution by producing shorter acoustic pulses. For example, a 40 MHz transducer with shorter pulses of approximately 37 μ m in water can resolve features of similar sizes of the targets. Lateral resolution, whereas, depends on beam width and is best at the focal zone. We and others have used ultrasound oral biomarkers, 30 , 32 , 33 but these approaches have two major obstacles: (i) low frequency, which leads to relatively poor resolution, and (ii) large size, which limits imaging of all teeth. Rodriguez et al. have discussed commercial ultrasound systems based on their frequency and transducer size, 34 which show a trade-off between transducer size and frequency. In prior work, Tavelli et al. used an L25–8 (24 MHz frequency, 20 × 18 × 30 mm dimensions) ultrasound transducer that offers 64 μ m axial resolution for estimating tissue perfusion. 35 Moore et al. used a commercial transducer (40 MHz, 40 × 50 × 30 mm dimensions), which increases the image quality with improved resolution, but the bulky design and very large footprint make it inaccessible to posterior teeth. 36 Qi et al. presented a customized ultrasound transducer to access full-mouth oral health, but it has limited resolution due to low-frequency operation. 37 A small footprint with a rotational tilt of the transducer could be helpful to correct the alignment between the tooth and transducer. Le et al. presented a rotatable ultrasound transducer (20 MHz, 18 × 13 mm dimensions), 31 which offers 150 μ m axial resolution with a rotation increment of ±15°. However, the transducer is limited to low-frequency operation, and a large rotational tilt increment limits alignment precision. Kripfgans et al. have imaged abutments and implant fixtures using an ultrasound transducer (L30–8). 38 The abutments were rotated ± 30°, keeping the transducer fixed. Real-time intraoral application requires the freedom to rotate a compact transducer and achieve a better and easier attachment with the posterior teeth. Other than the compact and high frequency of the transducer, accurate soft tissue-related measurements, such as gingival thickness, gingival height, and crestal bone thickness/level, are potentially useful for the early-stage detection of periodontitis. 33 , 39 – 41 Samal et al. discuss soft tissue-related measurements using ultrasound and histology. 42 Ultrasound has shown better accuracy compared with CBCT, and one additional benefit of ultrasound is that it does not use ionizing radiation. This is particularly important for cases that require longitudinal scans such as bone grafts. 43 , 44 Acoustic imaging could monitor the response to therapy with zero radiation dose. This is particularly important in light of the community’s renewed focus on reducing radiation dose. 45 – 47 Here, we report a custom-designed 128-element, 40 MHz transducer with excellent spatial resolution and an improved miniaturized design, which can be used to image all teeth in the mouth, including third molars. The line spread function of the nichrome-wire-based phantom characterized the spatial resolution of the transducer at different depths. Angular characterization showed the impact of transducer roll, pitch, and yaw angles on the posterior teeth. The transducer’s accuracy in measuring soft tissue-related measurements (gingival thickness and gingival height) was validated by imaging 14 swine teeth with intact gingiva, followed by comparisons with gold-standard transgingival probing measurements obtained from resected samples. To ensure robustness, a blinded test was performed to assess the reliability of the results. The results underscore the value of this new transducer for assessing oral health. MATERIALS AND METHODS Periodontal Transducer and Imaging System. The transducer (PL57x_1–128) was custom-built by VisualSonics. It has a 128-element linear array with a central frequency of 40 MHz and a bandwidth of 25–57 MHz. The linear array was sealed within the head cavity using a food-safe silicone adhesive (Dow DOWSIL 732 Multi-Purpose Sealant). The high-frequency transducer is housed in a toothbrush-shaped handpiece. The PL57x_1–128 was connected to a data acquisition (DAQ) system (Vevo-F2, VisualSonics, Inc., USA), which provides a power supply, electrical excitation control, and a beamformer to transmit delays configurable by a user. On the receiver side, the DAQ provides the front end with an ADC circuit, radiofrequency signal decoding, and a real-time ultrasound imaging display (discussed in detail. 36 The PL57x-1–128 was interfaced with the DAQ by using a universal transducer adapter. The DAQ provided a 5.6 V power supply and controlled the electrical excitation time delay for each channel. The DAQ sampled the radio frequency data from all 128 channels and processed the ultrasound images. The DAQ supports a frequency range of 0 to 71 MHz, utilizes 16-bit A/D converters with a sampling rate of 384 MHz, and can image at rates of up to 100,000 frames per second. Evaluation of Imaging Resolution Using Phantoms. The lateral and axial resolution of the transducer was determined by scanning nichrome wires (diameter: 30 μ m and wire gauge: 48 AWG, manufactured by uxcell) placed underwater. These wires were held on a plastic phantom at depths of 2.2, 4.4, 6.6, 8.8, 11, 13.2, and 15.4 mm from the surface. The line spread function of the ultrasound image of the nichrome wires was obtained. The smallest full width at half-maximum (FWHM) of the line spread function was measured to determine the lateral and axial resolution of the PL57x_1–128. A tissue-mimicking phantom was also prepared using a 0.2 mm pencil lead (spare lead by Pentel. Co., Ltd.) to demonstrate the performance of the ultrasound image 48 in measuring a larger target size and comparing the pencil lead diameter with the image-based diameter measurement. Angulation of the Periodontal PL57x_1–128 Transducer on Roll, Pitch, and Yaw Axis. A high-precision 9-axis gyroscope angle measurement module (WT9011DCL, WiTMotion Shenzhen Co., China) studied the transducer’s angular movement by imaging a pencil lead (0.2 mm diameter) (see Figure S1 ) as well as swine teeth. Porcine/swine jaws were selected due to their anatomical similarities to human jaw anatomy (see Figure S2 ). Both species exhibit similar tooth root structures and jaw dimensions, making the swine model a widely accepted surrogate for studying human oral and maxillofacial conditions. 49 – 51 Swine jaws were purchased from a local butcher and sliced to size using a bandsaw. We imaged up to a ± 30° tilt of the transducer with an increment of 5°. Angular tilt was measured from the images of the pencil lead and compared with the readings of the gyroscope module. Later, swine teeth were used to image and measure the distances among the gingival margin (GM), cementoenamel junction (CEJ), and alveolar bone crest (ABC) for each angular change. Two steel balls were placed on the crown and gingiva of the tooth to establish a reference plane for imaging the swine teeth at different angles. Swine Jaw Imaging and Soft Tissue-Related Measurements. Swine teeth were imaged by using ultrasound gel as an ultrasound coupling medium. Soft tissue measurements of the gingival thickness (GT) and gingival height (GH) were performed. Values of gingival thickness were compared by PL57x_1–128 ultrasound imaging and a 28-gauge periodontal probe with digital calipers (transgingival probing; gold standard method). 52 – 54 The GT measurement point was defined as 2 mm below the GM. In the ultrasound imaging method, the GT was obtained by measuring the distance between the gingival surface and the tooth surface via VevoLAB software. In the clinical periodontal probing method, a clinical periodontal probe was inserted into the gingiva perpendicularly until it made contact with the tooth. A line was marked on the periodontal probe, and the distance between the marked line and the tip of the periodontal probe was measured to find the GT with a 0.1 mm precision caliper. GH was measured with ultrasound and calipers on 14 swine teeth. In the ultrasound imaging method, the gingival height was obtained by measuring the distance between the GM and ABC via VevoLAB software. In the manual method, first, we manually annotated the GM with a permanent marker on the enamel. We then resected the gingival tissue and measured the distance from the GM annotation to ABC with a digital caliper. Bland-Altman plot and Pearson correlation were analyzed by GraphPad Prism 10 (GraphPad Software, San Diego, California, USA, www.graphpad.com ) to compare gingival thickness/height measurement via PL57x_1–128 and periodontal probing method. Statistical Analysis. We assessed how consistently measurements within each group agreed using intraclass correlation coefficient (ICC) analysis with a 95% confidence interval (CI), applying an average-measure, absolute agreement, two-way mixed model. ICC values were interpreted as follows: < 0.5 = poor, 0.5–0.75 = moderate, 0.75–0.90 = good, and >0.9 = excellent reliability. 55 The statistical analysis was conducted using IBM SPSS 30.0.0.0 (IBM, NY, USA). RESULTS Performance Evaluation of the Periodontal Transducer Using Phantoms. Figure 1a shows a 3D schematic of the periodontal transducer (PL57x_1–128) for real-time oral health monitoring. PL57x_1–128 has a side-facing view to ensure proper alignment with the gingiva and tooth surface. The transducer array is 7 mm × 2.5 mm (lateral × elevation) wide, creating a field of view of 7 mm × 20 mm (lateral × elevation), and the head size is 20 mm × 14 mm × 19 mm (length × width × height; Figure 1b ). Figure 1c , d compares PL57x_1–128 to the low-frequency L38xp ultrasound transducer. The ultrasound images of the swine teeth in Figure 1e , f shows enhanced resolution at higher frequencies. Figure 1. Open in a new tab High-frequency toothbrush-shaped periodontal transducer. (a) Schematic diagram of the side facing miniaturized transducer (PL57x_1–128). (b) Photograph of the PL57x_1–128 and the adaptor with sensing head dimensions (20 mm × 14 mm × 19 mm (length x width x height dimensions), (c,d) Schematic diagram to represent high-frequency PL57x_1–128 vs UHF5x, and (e,f) ultrasound images acquired from UHF5x (5 MHz) and PL57x_1–128 (40 MHz) transducers and shows improved image resolution and better detection of the biomarkers with the high-frequency response. Figure 2a details the phantom in which the nichrome wires were placed at different depths. Figure 2b shows an ultrasound image of pencil leads, which demonstrates lateral and axial diameters of 0.23 ± 0.03 mm and 0.25 ± 0.04 mm, respectively, at 7 mm depth, which is comparable with the actual diameter (0.2 mm) of the pencil lead. The ultrasound image ( Figure 2c ) shows the nichrome wires (30 μ m diameter) to check the smallest target size at different depths ranging from 2.2 to 15.4 mm when the focal depth was 7 mm. The transducer exhibited optimal lateral resolution at the 7 mm focal depth. Circular wires appear elliptical, with the major axis becoming wider beyond an 8 mm depth. Figure 2d , e shows the line spread function plot of the ellipses. Circularity was measured at depths of 2.2 mm, 4.4 mm, 6.6 mm, 8.8 mm, 11 mm, 13.2 mm, and 15.4 mm, yielding values of 0.456, 0.676, 0.912, 0.648, 0.532, 0.431, and 0.345, respectively. The highest circularity (0.912) appeared at the 7 mm focal depth, suggesting optimal shape retention at the focal depth, with circularity becoming more elliptical (0.345) at the 15.4 mm depth. This trend highlights the impact of depth-dependent lateral resolution degradation on shape fidelity. Figure 2. Open in a new tab Resolution characterization at different depths. (a) Schematic diagram of a nichrome wire phantom immersed in water, (b) ultrasound image of pencil lead-based phantom to investigate real pencil diameter vs image-based pencil diameter comparison, and (c) ultrasound image showing different nichrome wires at different depths. (d, e) Line spread function of lateral and axial profile of the nichrome wire from 2.2 mm to 15.4 mm depths. (f, g) 149 ± 21 μ m Lateral and 49 ± 15 μ m axial resolution calculated from the line spread function of the nichrome wires at different depths. Lateral resolution at a 2.2 mm depth from the transducer was 149 ± 21 μ m, which decreased to 555 ± 81 μ m at a 15.4 mm depth, as shown in Figure 2f . Axial resolution at a 2.2 mm depth was 49 ± 15 μ m, which decreased to 111 ± 21 μ m at a 15.4 mm depth, as shown in Figure 2g . The error bars (indicating changes in resolution) shown in Figure 2f , g represents repeated ultrasound imaging performed at different focal depths ranging from 3 to 16 mm. For lateral resolution, the error bar was ± 30.72 μ m when the nichrome wire was positioned near the transducer’s focal depth (6.6 mm). However, the error increased to ± 81.59 μ m when the nichrome wire was placed at a depth of 15.4 mm, farther away from the focal depth. This demonstrates the influence of the transducer’s geometric focal depth (7 mm) in achieving accurate lateral resolution when the target is located near the focal depth. Imaging Impact of the Angulation of PL57x_1–128 Transducer on Roll, Pitch, and Yaw Axis. Figure 3a shows a photograph of the periodontal transducer with an attached gyroscope used to measure the impact of the roll, pitch, and yaw axes ( Figure 3b ). Figure 3c shows the change in the pitch axis with the images generated at angles ranging from −30° to +30°. The impact of the tilt angle was quantified by monitoring the distances between key anatomical biomarkers: gingival margin (GM), cementoenamel junction (CEJ), and alveolar bone crest (ABC), as shown in Figure 3d . These measurements were defined as follows: the distance between ABC and GM was termed image-guided gingival height (iGH), and the distance between CEJ and GM was termed image-guided gingival recession (iGR) 33 (note: clinically, a negative value is assigned to the iGR if the gingival margin is coronal to the CEJ.). The distance between ABC and CEJ was termed image-guided alveolar bone loss (iABL). Figure 3. Open in a new tab Impact of angulation of the transducer and statical analysis. (a) The photograph shows the transducer with a gyroscope sensor to track the angular movement of the transducer, (b) schematic represents roll, pitch, and yaw axis of the transducer movement, and (c) schematic represents −30 to +30 angulation in pitch axis with generated ultrasound images. (d) Schematic and ultrasound image shows the scheme for measuring biomarkers at different angles of the transducer. (e) The acceptable range of the transducer tilt was before the clear visualization of all biomarkers started disrupting. The optimal angle range of −15° to +20° was able to successfully produce iGH, iGT, and iABL. (f) We repeated the study for the roll axis, and (g) the image-based measurement produced mean values of iGH, iGR, and iABL were 3.69 ± 0.11 mm, 0.97 ± 0.15 mm, and 4.33 ± 0.24 mm, respectively, within the acceptable angle range (−15° to +20°). The acceptable pitch angle range was defined as the range before the clear visualization of all biomarkers was lost. The mean values of the iGH, iGR, and iABL were 5.29 ± 0.19, 0.92 ± 0.12, and 5.03 ± 0.18 mm, respectively. Figure 3e shows the effect of pitch angles on iGH, iGR, and iABL, identifying an acceptable range [−15° to +20°] where biomarker distances remain within a 0.195 mm standard deviation. This represents a 25.94% reduction compared to the 0.246 mm standard deviation observed beyond this acceptable range. Beyond this acceptable range, imaging all of the biomarkers was not feasible due to a mismatch between the ultrasound plane and the tooth anatomical plane, and the biomarkers started deteriorating. We repeated the experiments for the roll axis ( Figure 3f ) and found the acceptable roll angle range (−15° to +20°). The mean values of iGH, iGR, and iABL were 3.69 ± 0.11 mm, 0.97 ± 0.15 mm, and 4.33 ± 0.24 mm, respectively ( Figure 3g ). The acceptable angle range [−15° to +20°] maintained biomarker distances within a 0.24 mm standard deviation, reducing variability by 36.63% compared to the 0.38 mm deviation beyond this range, where the anatomical structure was also lost. The roll and pitch axes were analyzed to assess the effect of the transducer’s angular tilt. However, when the transducer was rotated along the yaw axis, the reference plane formed by the two steel balls was disrupted, leading to the loss of the anatomical structure of the teeth (see Supporting Information ). Figure S3a shows the ultrasound image at a 0° angle along the yaw axis, where the reference plane is intact. In contrast, Figure S3b , c shows the loss of the reference plane, with minimal or no visible steel balls. The measurements of iGH, iGR, and iABL at various angles were repeated three times to check reliability. Interrater and intrarater reliability experiments assessed reproducibility and precision across imaging angles (see Tables S2 and S3 ). All ICCs for rater 1 (R1) compared to rater 2 (R2) were excellent, with values above 0.9. All SD averages for R1 and R2 were close to each other, indicating the high reliability of the experiments Evaluation of Gingival Thickness Measurement Using a Clinical Periodontal Probe and the Periodontal Transducer PL57x_1–128. Gingival thickness (GT) was measured on 14 swine teeth with a PL57x_1–128 transducer, as shown in Figure 4a . A clinical periodontal probe (Williams probe) was also used to measure the gingival thickness manually. The gingival thickness measured with PL57x_1–128 was termed as GT-ultrasound, while the one measured with transgingival probing was termed as GT-manual, as shown in Figure 4b . The mean GT-ultrasound was 1.04 ± 0.02 mm, and the mean GT-manual was 1.03 ± 0.08 mm. Gingival thickness measurements correlated well between the manual and ultrasound methods ( r = 0.7243, p = 0.0001), as shown in Figure 4c . The Bland-Altman analysis for gingival thickness revealed a bias of −0.002 mm, an SD of 0.13 mm, and 95% limits of agreement ranging from −0.276 to 0.271 mm ( Figure 4d ). Figure 4. Open in a new tab Gingival thickness measurement on swine jaws and statical analysis. (a) PL57x_1–128 transducer imaged swine teeth with gingival thickness; the yellow line indicates the approximate measurement area. (b) The gingival thickness was measured using the clinical method and ultrasound images. (c) Pearson correlation ( r = 0.7243, p = 0.0001) between ultrasound imaging and clinical measurement. (d) Bland-Altman plot comparing ultrasound imaging and clinical probe measurement indicating a bias of −0.002 mm between two measurements with a 95% limit of the agreement. Evaluation of Gingival Height Measurement of Swine Jaw Using a Digital Caliper and the Periodontal Transducer PL57x_1–128. Another measurement of the gingival height (GH) was performed to evaluate the performance of the PL57x_1–128 transducer. The GH measurement was conducted on 14 swine teeth using PL57x_1–128 transducer’s image-based measurements (iGH) and digital caliper-based manual periodontal probing measurements, as shown in Figure 5a , b , and correlated the transducer with gold standard probing technique using Pearson correlation. The gingival height measured with PL57x_1–128 was termed GH-ultrasound (also mentioned as iGH), while the one measured with a digital caliper was termed GH-manual, as shown in Figure 5c . The mean GH-ultrasound was 4.01 ± 0.03 mm, and the mean GH-manual was 3.98 ± 0.19 mm. Gingival height measurements correlated well between the manual and ultrasound methods ( r = 0.7886, p < 0.0001), as shown in Figure 5d . The Bland-Altman analysis for gingival height revealed a bias of −0.0263 mm, an SD of 0.53 mm, and 95% limits of agreement ranging from −1.074 to 1.022 mm ( Figure 5e ). Figure 5. Open in a new tab Gingival height (GH) measurement on swine jaws and statical analysis. (a) Photograph showing a swine jaw. The blue line indicates the approximate measurement area from the GM to ABC. (b) PL57x_1–128 transducer imaged swine teeth and measurement of the iGH. (b) The gingival height using manual method and ultrasound images. (c) Pearson correlation ( r = 0.7886, p < 0.0001) between ultrasound imaging and manual needle measurement. (d) Bland-Altman plot comparing ultrasound imaging and manual needle measurement indicating a bias of −0.026 mm between two measurements with a 95% limit of the agreement. Interexaminer Reliability. Two blinded examiners independently identified the anatomical landmarks on the ultrasound images and measured iGH and iGT. The measurements were correlated with data points close to the line of equality (y = x). No significant differences were found between examiners for iGH ( r = 0.9692; p < 0.0001). However, we noted statistically significant differences for iGT measurements between examiners ( r = 0.6695, p = 0.0003). Nevertheless, the standard deviations (SD) of the differences between the two examiners were 0.03 mm for iGH and 0.08 mm for iGT, which are smaller than the SDs of clinical interexaminer tests 56 , 57 (see Figure S4 ). Buccal and Lingual Scan of the Swine Jaw. This swine jaw includes three molars and three premolars ( Figure 6a ). 58 In vitro, ultrasound imaging was performed on the buccal and lingual sides of the molars and premolars. Figure 6. Open in a new tab In vitro imaging on the mandibular swine jaw. (a) Photograph of the left mandibular swine jaw containing molars (M1, M2, and M3) and premolars (PM1, PM2, and PM3). (b) Buccal and (c) lingual side ultrasound imaging of the swine teeth clearly visualized all the biomedical landmarks, such as the GM, CEJ, alveolar bone, and ABC. I—Crown; II—GM; III—ABC; and IV – CEJ. Images represent the thick gingiva for molar teeth (M1–M3) ( Figure 6b ) and the thin gingiva for the premolars (PM1-PM3), particularly on the lingual side ( Figure 6c ). The mean gingival thickness for premolars was 0.78 ± 0.14 mm; however, the mean gingival thickness for molar teeth was 1.14 ± 0.35 mm. The schematic diagram of the swine teeth represents the buccal and lingual tooth orientation ( Figure 6b , c ) of the mandibular swine jaw. Quantitative differentiation was possible using high-resolution images of PL57x_1–128 for soft tissue measurements. DISCUSSION The PL57x_1–128 transducer is a miniaturized transducer designed in a side-facing toothbrush shape to improve contact with heterogeneous tooth structures and provide angular freedom over posterior teeth. The resolution of an ultrasound transducer is determined by its frequency and beam characteristics, with axial resolution depending on the spatial pulse length (SPL) 30 and lateral resolution on beam width. 31 Higher frequencies improve axial resolution by producing shorter pulses, enabling precise detection of tooth biomarkers. A theoretical measure of ~37 μ m acoustic pulse for the 40 MHz transducer (as calculated in Supporting Information ) in a water medium can effectively resolve biomarkers in oral health. This theoretical measure was close to the experimental measurement of a 49 ± 15 μ m axial resolution of the PL57x_1–128 transducer. The pencil leads (0.2 mm diameter) were also imaged accurately by utilizing the high resolution of the PL57x_1–128 ( Figure 2c ). This is the first transducer combining a compact head size with a 40 MHz high frequency, offering 49 ± 15 μ m resolution at a 7 mm depth, ideal for periodontal scanning. Compared to existing designs, 34 the proposed transducer successfully balances resolution and form factors, as highlighted in Table S1 . The major challenge faced by clinicians in periodontal imaging is the large form factor of the transducer that does not allow access and provides freedom to rotate and achieve uniform attachment with the heterogeneous tooth surface. In this work, we present a miniaturized PL57x_1–128 and examine the impact of angulation, which improves attachment with the tooth and provides three degrees of rotational freedom due to its small form factor. This study shows that the threshold range of −15° to +20° angular tilt is an acceptable range for optimal ultrasound imaging and biomarker accuracy (±0.249 mm SD) ( Figure 3 ). By understanding these thresholds, clinicians can optimize transducer contact with the heterogeneous tooth surface, thereby enhancing imaging quality and improving diagnostic accuracy for periodontal patients. In healthy patients, GT typically ranges from 0.5 to 2.5 mm. Gingival phenotype classification in clinical practice is often subjective, 59 , 60 typically using a periodontal probe to categorize tissue as ″thin if GT < 1 mm″ or ″thick if GT > 1.5 mm″, though the technique lacks precision for intermediate phenotypes. 61 GH in healthy individuals usually measures 3–4 mm from the crest of the GM to the ABC. Direct soft tissue-related measurements involve invasive methods like calipers or periodontal probes (needles), which face challenges such as improper angulation. 62 Currently, there is no noninvasive method for assessing soft tissue measurements, with techniques limited to bone sounding or direct measurement after flap reflection. 63 , 64 In this work, image-based soft tissue-related measurements were made and compared with a gold standard clinical periodontal probe. The significant correlation coefficient ( r = 0.7886, p < 0.0001) indicates that the ultrasound-based gingival Height/thickness measurements align closely with the manual technique, validating the reliability of ultrasound as a noninvasive method for assessing soft tissue measurements ( Figure 5d ). Considering that manual periodontal probing has >40% interoperator error, this can be a significant source of error in the experiments. 5 Traditional bite-wing radiographs are valuable for periodontal maintenance, as they can detect bone height differences of around 1 mm. 8 In contrast, our study, using a micrometer-based simulation setup, demonstrated that the PL57x_1–128 transducer could detect a change of 20 μ m in bone loss. Ultrasound images of the micrometer rod were acquired at different gaps (0–2000 μ m) created by the micrometer in steps of 20 μ m (see Figure S5 ). The high correlation ( r = 0.9806, p < 0.0001) between the micrometer’s display readings and the ultrasound measurements confirms the transducer’s ability to accurately quantify real-time, noninvasive monitoring of bone loss ( Figure S5e , f ). This capability is crucial for the early detection of bone resorption in dental and orthopedic applications. Additionally, interrater reliability and intrarater reliability experiments were conducted to assess the reproducibility and precision of measurements across various imaging angles ( Tables S2 and S3 ). The ICC result for the anatomical biomarker (iGH) measurement for rater 1 (R1) at three different repetitions (T1, T2, and T3) was 0.955 (with a 95% CI of 0.846–0.990). Under the same conditions, the ICC results for iABL and iGR measurements were 0.989 (95% CI of 0.963–0.998) and 0.945 (95% CI of 0.815–0.988). These results indicated excellent intrarater reliability for all three measurements. For all the samples, the average calculated SD was 0.422, 0.480, and 0.178 mm for iGH, iABL, and iGR, respectively ( Table S2 ). This paper was limited to in vitro imaging because the first goal was to characterize the transducer in terms of excellent resolution and evaluate its performance in soft tissue-related measurements. Our future goal is that transitioning to in vivo experiments will provide a clearer understanding of the transducer’s clinical translation. Factors such as tissue heterogeneity and motion artifacts will be addressed in future work. The potential of the transducer for real-time human imaging will also be performed with a full-mouth oral scan. The high-resolution images can be further used to automatically detect anatomical structures using machine learning algorithms. 65 One limitation of this study is that we did not compare it to CBCT. We simply do not have access to a preclinical system, but we will work to source a relevant system in future validations. Prior work in this space includes Corbea et al., 66 who demonstrated the effectiveness of 20 MHz US scanning using human teeth from three fresh cadavers via interrater and intrarater reliability assessments of distance measurement from the notch on the crown to the alveolar bone crest (ABC). They reported excellent intrarater reliability for both μ CT and US measurements, with mean standard deviations of 0.050 mm for μ CT and 0.057 mm for US, respectively. The existing adaptor of the transducer is compatible with the Vevo system but is not compatible with other manufacturers. This is a limitation of the work. CONCLUSION In conclusion, the PL57x_1–128 transducer demonstrated versatility and accuracy in measuring gingival height and gingival thickness, detecting minimal bone loss, and imaging the anatomical structures of the swine jaw. These findings support its potential for diverse dental and medical applications. The acceptable angle range was fixed to ensure correct imaging of swine teeth, independent of the transducer tilt angle within the range of −15° to +20°. The results suggest that the PL57x_1–128 transducer could be a potential tool for periodontal ultrasound imaging. Future work will focus on the implementation of this high-frequency transducer for full-mouth oral imaging with high resolution and automatic detection of biomarkers. Supplementary Material si NIHMS2162983-supplement-si.pdf (486.5KB, pdf) The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acssensors.5c00521 . Additional experimental results on transducer angulation and performance evaluation for minimum bone loss detection are included ( PDF ) ACKNOWLEDGMENTS The authors acknowledge Dr. Gulcan Gok for her suggestions on swine jaw anatomy. Funding This work was supported by the National Institutes of Health under grant numbers R01 DE031307 and S10 OD032268. ABBREVIATIONS GM gingival margin CEJ cementoenamel junction ABC alveolar bone crest GT gingival thickness GH gingival height Footnotes Complete contact information is available at: https://pubs.acs.org/10.1021/acssensors.5c00521 The authors declare no competing financial interest. Contributor Information Suhel Khan, Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States. Pei Yun Tsai, Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States. Baiyan Qi, Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, California 92093, United States. Casey Chen, Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, California 90089, United States. Jesse V. 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