ArticleLa Radiologia medica2023
CT-based radiomics can identify physiological modifications of bone structure related to subjects' age and sex.
Article in La Radiologia medica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Delta radiomics: an updated systematic review.La Radiologia medica · 2024Pooled it
- Artificial intelligence on opportunistic computed tomography for predicting vertebral fracture risk in women undergoing estrogen deprivation therapy for breast cancer.La Radiologia medica · 2026Article
- Deep Learning-Assisted Radiomics for Predicting Thoracolumbar Osteoporotic Vertebral Fractures.Clinical interventions in aging · 2026Article
- Ultrasound radiomics for identifying microstructural changes in the femoral head with developmental dysplasia of the hip.Pediatric radiology · 2025Article
- Insights into radiomics: a comprehensive review for beginners.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Review
- Novel CT-based vertebral three-dimensional Hounsfield unit for assessment of bone mineral density.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025Article
- Artificial intelligence in fracture detection on radiographs: a literature review.Japanese journal of radiology · 2025Review
- Survival outcome prediction of esophageal squamous cell carcinoma patients based on radiomics and mutation signature.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Bone Age Assessment Using Various Medical Imaging Techniques Enhanced by Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2025Review
- A reference framework for standardization and harmonization of CT radiomics features on cadaveric sample.Scientific reports · 2024Article
- An approach leveraging radiomics and model checking for the automatic early diagnosis of adhesive capsulitis.Scientific reports · 2024Article
- CT Cadaveric dataset for Radiomics features stability assessment in lumbar vertebrae.Scientific data · 2024Article
- Determining rib fracture age from CT scans with a radiomics-based combined model: a multicenter retrospective study.Insights into imaging · 2023Article
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Authors and funding
17 authors.
Funding
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Abstract
purposeRadiomics of vertebral bone structure is a promising technique for identification of osteoporosis. We aimed at assessing the accuracy of machine learning in identifying physiological changes related to subjects' sex and age through analysis of radiomics features from CT images of lumbar vertebrae, and define its generalizability across different scanners. MATERIALS AND
methodsWe annotated spherical volumes-of-interest (VOIs) in the center of the vertebral body for each lumbar vertebra in 233 subjects who had undergone lumbar CT for back pain on 3 different scanners, and we evaluated radiomics features from each VOI. Subjects with history of bone metabolism disorders, cancer, and vertebral fractures were excluded. We performed machine learning classification and regression models to identify subjects' sex and age respectively, and we computed a voting model which combined predictions.
resultsThe model was trained on 173 subjects and tested on an internal validation dataset of 60. Radiomics was able to identify subjects' sex within single CT scanner (ROC AUC: up to 0.9714), with lower performance on the combined dataset of the 3 scanners (ROC AUC: 0.5545). Higher consistency among different scanners was found in identification of subjects' age (R2 0.568 on all scanners, MAD 7.232 years), with highest results on a single CT scanner (R2 0.667, MAD 3.296 years).
conclusionRadiomics features are able to extract biometric data from lumbar trabecular bone, and determine bone modifications related to subjects' sex and age with great accuracy. However, acquisition from different CT scanners reduces the accuracy of the analysis.
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