ArticleBioengineering (Basel, Switzerland)2022
A Population-Based 3D Atlas of the Pathological Lumbar Spine Segment.
Article in Bioengineering (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Statistical shape modelling of the human lumbar spine: a scoping review characterising the research landscape and potential clinical applications.Frontiers in bioengineering and biotechnology · 2026Pooled it
- Generation of a virtual cohort of TAVI patients for in silico trials: a statistical shape and machine learning analysis.Medical & biological engineering & computing · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
The spine is the load-bearing structure of human beings and may present several disorders, with low back pain the most frequent problem during human life. Signs of a spine disorder or disease vary depending on the location and type of the spine condition. Therefore, we aim to develop a probabilistic atlas of the lumbar spine segment using statistical shape modeling (SSM) and then explore the variability of spine geometry using principal component analysis (PCA). Using computed tomography (CT), the human spine was reconstructed for 24 patients with spine disorders and then the mean shape was deformed upon specific boundaries (e.g., by ±3 or ±1.5 standard deviation). Results demonstrated that principal shape modes are associated with specific morphological features of the spine segment such as Cobb's angle, lordosis degree, spine width and height. The lumbar spine atlas here developed has evinced the potential of SSM to investigate the association between shape and morphological parameters, with the goal of developing new treatments for the management of patients with spine disorders.
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Registered trials
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