ArticleNeurosurgical review2025
Lumbar spine deformation between prone and supine CTs.
Article in Neurosurgical review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spinal navigation systems improve pedicle screw placement accuracy, but their reliance on supine preoperative imaging can introduce errors due to positional differences between preoperative and intraoperative spinal alignment. These misalignments may compromise surgical outcomes, particularly in lumbar spine procedures. This study investigates how key lumbar and lumbopelvic parameters differ between prone and supine positions, aiming to refine imaging workflows and surgical navigation practices. A retrospective cohort study analyzed paired prone and supine CT images from 85 adult patients in the ACRIN database. Key parameters-pelvic tilt, lumbar lordosis, L1 slope, pelvic incidence, and L1-L5 Cobb angle-were measured. Statistical significance was assessed using two-tailed t-tests, with pairwise comparisons conducted to evaluate positional differences. Significant differences were observed in pelvic tilt (mean prone-supine difference: 4.27°, p = 0.0002) and L1 slope (mean prone-supine difference: 3.16°, p = 0.001). Other parameters, including lumbar lordosis, pelvic incidence, and L1-L5 Cobb angle, showed no significant differences. Our study provides the first comprehensive analysis of prone versus supine alignment in the lumbar spine, addressing a critical gap in spinal navigation research. The findings underscore the limitations of supine preoperative imaging in reflecting intraoperative conditions. Incorporating these insights into navigation workflows can improve registration accuracy and surgical outcomes. Future innovations, such as AI-based predictive modeling, may further address positional discrepancies and optimize lumbar spine surgeries. This work highlights the importance of advancing imaging protocols to align with intraoperative realities.
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