Next Article in Journal
Coexistence of Tripartite Accessory Navicular Bone and Os Subfibulare
Previous Article in Journal
Agreement of WebCeph-Based Automated and Expert-Adjusted Cephalometric Analyses with Manual and Dolphin Tracings
Previous Article in Special Issue
L5–S1 Anatomic Features Relevant to Minimally Invasive Decompression and Fusion: A Cadaveric and Imaging-Based Study
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Diagnostics
Volume 16
Issue 12
10.3390/diagnostics16121835
diagnostics-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Review

Beyond SINS: A Critical Review of Biomechanical, Microstructural, and Radiomic Biomarkers for Predicting Fracture Risk in Spinal Metastases

by
An Sen Tan
1,*,
Calvin Kai En Tjio
1,
Jonathan Jiong Hao Tan
2,
Naresh Kumar
2,
Wilson Ong
1,
Shuliang Ge
1,
Yi Liang Tan
1,
Eric Fang
1,
Balamurugan A Vellayappan
3 and
James Thomas Patrick Decourcy Hallinan
1,4
1
Department of Diagnostic Imaging, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
2
National University Spine Institute, Department of Orthopaedic Surgery, National University Hospital, 1E Lower Kent Ridge Road, Singapore 119228, Singapore
3
Department of Radiation Oncology, National University Hospital, 5 Lower Kent Ridge Rd, Singapore 119074, Singapore
4
Department of Diagnostic Radiology, Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Drive, Singapore 117597, Singapore
*
Author to whom correspondence should be addressed.
Diagnostics 2026, 16(12), 1835; https://doi.org/10.3390/diagnostics16121835 (registering DOI)
Submission received: 16 April 2026 / Revised: 10 June 2026 / Accepted: 12 June 2026 / Published: 13 June 2026
(This article belongs to the Special Issue Contemporary Spine Diagnostics and Management)
Versions Notes

Abstract

Background/Objectives: Although the Spinal Instability Neoplastic Score (SINS) is widely used to estimate spinal metastases fracture risk and guide decisions on stabilisation procedures, prior studies have demonstrated mixed results. Patients with the same score exhibit clinically heterogeneous outcomes, with some SINS criteria correlating less well with the estimated fracture risk than others. There are also barriers to implementation such as the time burden required for manual calculation and interobserver variability associated with qualitative morphological criteria. SINS also lacks sensitivity for detecting latent structural compromise in treatment-naive patients and those susceptible to the iatrogenic effects of stereotactic body radiation therapy. This review aims to evaluate emerging imaging, biomechanical, and microstructural markers with the potential to improve fracture risk stratification and prognostication for spinal oncology patients. Methods: We synthesise evidence across three innovative frontiers: (1) biomechanical modelling, including CT-derived finite element analysis and failure-load pattern models; (2) radiomics, utilizing radiomics features from radiological imaging to develop a predictive model; and (3) microstructural MRI biomarkers, exploring the translatability of the Vertebral Bone Quality score, fat fraction, and paraspinal muscle atrophy from osteoporosis to the metastatic spine. Results: Emerging biomechanical, radiomic and microstructural imaging markers show potential in addressing some limitations of traditional SINS criteria for fracture risk stratification across the spinal oncology treatment continuum, from initial diagnosis to post-radiation surveillance, thereby facilitating more precise risk assessment. However, current evidence remains largely retrospective and heterogeneous, and further validation is required before clinical adoption. Conclusions: We propose a framework that shifts the paradigm from conventional morphological scoring toward a multiparametric assessment of spinal stability.
Keywords: spinal metastases; spinal instability neoplastic score; pathologic fracture; spinal stability; radiation therapy; radiomics; biomechanical modelling; machine learning spinal metastases; spinal instability neoplastic score; pathologic fracture; spinal stability; radiation therapy; radiomics; biomechanical modelling; machine learning

Share and Cite

MDPI and ACS Style

Tan, A.S.; Tjio, C.K.E.; Tan, J.J.H.; Kumar, N.; Ong, W.; Ge, S.; Tan, Y.L.; Fang, E.; Vellayappan, B.A.; Hallinan, J.T.P.D. Beyond SINS: A Critical Review of Biomechanical, Microstructural, and Radiomic Biomarkers for Predicting Fracture Risk in Spinal Metastases. Diagnostics 2026, 16, 1835. https://doi.org/10.3390/diagnostics16121835

AMA Style

Tan AS, Tjio CKE, Tan JJH, Kumar N, Ong W, Ge S, Tan YL, Fang E, Vellayappan BA, Hallinan JTPD. Beyond SINS: A Critical Review of Biomechanical, Microstructural, and Radiomic Biomarkers for Predicting Fracture Risk in Spinal Metastases. Diagnostics. 2026; 16(12):1835. https://doi.org/10.3390/diagnostics16121835

Chicago/Turabian Style

Tan, An Sen, Calvin Kai En Tjio, Jonathan Jiong Hao Tan, Naresh Kumar, Wilson Ong, Shuliang Ge, Yi Liang Tan, Eric Fang, Balamurugan A Vellayappan, and James Thomas Patrick Decourcy Hallinan. 2026. "Beyond SINS: A Critical Review of Biomechanical, Microstructural, and Radiomic Biomarkers for Predicting Fracture Risk in Spinal Metastases" Diagnostics 16, no. 12: 1835. https://doi.org/10.3390/diagnostics16121835

APA Style

Tan, A. S., Tjio, C. K. E., Tan, J. J. H., Kumar, N., Ong, W., Ge, S., Tan, Y. L., Fang, E., Vellayappan, B. A., & Hallinan, J. T. P. D. (2026). Beyond SINS: A Critical Review of Biomechanical, Microstructural, and Radiomic Biomarkers for Predicting Fracture Risk in Spinal Metastases. Diagnostics, 16(12), 1835. https://doi.org/10.3390/diagnostics16121835

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop