Imaging-based features are needed to improve the characterization of degenerative IVD-changes and possibility of finding a linkage between features and pain.
Multiple T2w-imaging-features and Machine-Learning was used for classification of fissures involving outer annulus and for pain-positive discograms.
Fissures were classified with high accuracy/precision using regional/heterogeneity features with/without axial loading of the spine. For pain-positive discograms, a larger number of such MRI-features contributed to the classification.
Findings suggest that multiple MRI-features, extracted from T2w-imaging, improve the classifications, and that regional/heterogeneity features extracted with both conventional imaging with the spine unloaded and with axial loading of the spine are of importance.