Machine learning analysis of pretreatment CT radiomics features predicts risk of medication-related osteonecrosis of the jaw (MRONJ) in patients prior to bone resorption inhibitor therapy.
Key Details
- 1Retrospective study at Hiroshima University analyzed pretreatment CT scans of 94 patients.
- 2Radiomics features from jawbone CTs were used with machine learning models (RF, SVM, MLP).
- 3Models combining cancellous and cortical bone features significantly improved prediction—AUCs rose to as high as 0.931.
- 4The best model identified 88.6% of future MRONJ cases and 88.6% of controls.
- 5MRONJ affects up to 15% of patients on bone resorption inhibitors and is difficult to treat once developed.
- 6Study was limited by its retrospective nature and lack of comprehensive dental data.
Why It Matters
If validated, radiomics-based AI could enable early identification of high-risk patients, supporting tailored preventive strategies before starting bone resorption inhibitor treatment and potentially reducing severe, life-altering MRONJ complications.
Source
EurekAlert
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