Statistical shape modelling of the human lumbar spine: a scoping review characterising the research landscape and potential clinical applications
Abstract
Objective: A systematic scoping review was conducted to characterise the current research landscape of statistical shape modelling of the lumbar spine, focusing on the proposed clinical applications of the method.
Methods: MEDLINE, Embase, IEEE Xplore, and Scopus were searched for sources published before 17 June 2026. Sources were screened against predefined inclusion and exclusion criteria and data were extracted using a structured form in Covidence.
Results: 2,930 records were identified for review. Following duplicate removal and screening, 85 studies remained for data extraction. Most studies were exploratory (57%) or descriptive (14%) in nature. The vertebral body was the most frequently isolated region, with L5 often excluded due to its anatomical distinctiveness. Reporting of population demographics and dataset composition was highly inconsistent, highlighting substantial heterogeneity in both methodology and population selection.
Conclusion: The use of lumbar spine statistical shape models (SSMs) has been predominantly exploratory or descriptive. Whilst prognostic, diagnostic, and therapeutic applications have been proposed, none of the reviewed studies demonstrated a direct change to clinical practice or impact on patient care. No consensus exists on optimal approaches to multi-level modelling, vertebral level pooling, or anatomical boundary definition, and training datasets are predominantly drawn from Western, female-skewed populations. In the short term, SSMs…
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Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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