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Abstract #2655

Texture Analysis of T2-weighted Lumbar Spine MRI Predicts Presence of Low Back Pain

Juuso Heikki Jalmari Ketola1, Satu Irene Inkinen1, Jaro Karppinen2, Jaakko Niinimäki1,2,3, Osmo Tervonen1,2,3, and Miika Tapio Nieminen1,2,3
1Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland, 2Medical Research Center, University of Oulu and Oulu University Hospital, Oulu, Finland, 3Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland

We applied texture analysis to T2-weighted MRI of the lumbar spine in a population-based sample. The extracted features were used in a logistic regression pipeline to predict whether the subjects (N=200) suffered from clinically relevant low back pain. Best results were obtained by combining features from intervertebral discs and vertebrae with receiver operating characteristics area under curve of 0.86, accuracy of 0.84, and recall of 0.83. This preliminary work shows that texture analysis and machine learning may be used to predict pain from T2-weighted images. Thus, a connection between MRI textural features and clinically relevant low back pain may exist.

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