Predicting postoperative recovery in cervical spondylotic myelopathy: construction and interpretation of T2*-weighted radiomic-based extra trees models

ConclusionRadiomic features, especially wavelet-LL first-order variance, contribute to meaningful predictive models for CSM prognosis.Key Points• Conventional MRI features may not be ideal in predicting prognosis.• Radiomics provides greater predictive efficiency in the recovery from cervical spondylotic myelopathy.

http://link.springer.com/10.1007/s00330-021-08383-x

Source: European Radiology - April 26, 2022 Category: Radiology Source Type: research