ClinicalTrials.gov
public full text
Public Domain
Vertebral Bone Quality and Prediction of Screw Loosening in Spine Fusion
Finding a way to use Vertebral CT scan will help to predict screw loosing risk in spinal fusion for degenerative spine disease. Patients who will undergo at least two spine fusion levels for degenerative spine disease will be enrolled in. Before surgery, patients will undergo a spinal QCT scan with a calibrated phantom. The calibrated bone density, at bone-implant interface, will be assessed using dual energy CT scan immediately after surgery, and six months later. The primary outcomes will be the difference between the two values of the bone implant interface. The difference between density values will be correlated to the pre-op bone density value.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Interbody vs Instrumented Posterolateral Fusion Following Decompression for Lumbar Spinal Stenosis With Degenerative Spondylolisthesis#900815
- Radiostereometric Analysis of Spine Arthrodesis#807453
- Spineology Clinical Outcomes Trial: An IDE Investigation#979063
- Unilateral Versus Bilateral TLIF for Degenerative Lumbar Spondylolisthesis#808132
- Cortical Bone Trajectory Screws vs. Traditional Pedicle Screws Fixation#801634
Record · ID 1007979
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive