Prediction of the Acuity of Vertebral Compression Fractures on CT Using Radiologic and Radiomic Features.

Acad Radiol

Department of Radiology and Research Institute of Radiology (A.Y.K., M.A.Y., S.J.H., C.G.C., M.H.L., S.H.L., H.W.C.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Korea; Biomedical Research Center (Y.C.C., Y.K.), Asan Institute for Life Sciences, Asan Medical Center, Songpa-gu, Seoul, Korea; Health Innovation Big Data Center (B.P.), Asan Institute for Life Sciences, Asan Medical Center, Songpa-gu, Seoul, Korea; Department of Clinical Epidemiology and Biostatistics (S.K.), Asan Medical Center, Songpa-gu, Seoul, Korea; Department of Radiology (E.L.), Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Korea; Department of Radiology (R.W.L.), Inha University Hospital, Jung-gu, Incheon, Korea.

Published: October 2022

Rationale And Objectives: To develop and validate prediction models to differentiate acute and chronic vertebral compression fractures based on radiologic and radiomic features on CT.

Materials And Methods: This study included acute and chronic compression fractures in patients who underwent both spine CT and MRI examinations. For each fractured vertebra, three CT findings ([1] cortical disruption, [2] hypoattenuating cleft or sclerotic line, and [3] relative bone marrow attenuation) were assessed by two radiologists. A radiomic score was built from 280 radiomic features extracted from non-contrast-enhanced CT images. Weighted multivariable logistic regression analysis was performed to build a radiologic model based on CT findings and an integrated model combining the radiomic score and CT findings. Model performance was evaluated and compared. Models were externally validated using an independent test cohort.

Results: A total to 238 fractures (159 acute and 79 chronic) in 122 patients and 58 fractures (39 acute and 19 chronic) in 32 patients were included in the training and test cohorts, respectively. The AUC of the radiomic score was 0.95 in the training and 0.93 in the test cohorts. The AUC of the radiologic model was 0.89 in the training and 0.83 in the test cohorts. The discriminatory performance of the integrated model was significantly higher than the radiologic model in both the training (AUC, 0.97; p<0.01) and the test (AUC, 0.95; p=0.01) cohorts.

Conclusion: Combining radiomics with radiologic findings significantly improved the performance of CT in determining the acuity of vertebral compression fractures.

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Source
http://dx.doi.org/10.1016/j.acra.2021.12.008DOI Listing

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