MRI Analysis with Machine Learning Can Predict
Motor Impairment after Spinal Cord Injury, Study Shows

Study results to be presented at ARRS 2018 Annual Meeting

Leesburg, VA, April 5, 2018—A test of machine-learning algorithms shows promise for computer-aided prognosis of acute spinal cord injury, according to a study to be presented at the ARRS 2018 Annual Meeting, set for April 22-27 in Washington, DC.

The study to be presented by Jason Talbot, assistant professor of radiology at the University of California, San Francisco, involved using semiautomated image analysis with machine-learning algorithms to assess the accuracy of axial T2-weighted radiomic features for classifying patients by degree of neurologic injury.

Several machine-learning algorithms were tested for injury classification based on texture variables. For each trained model, the accuracy of predicting the testing set was recorded, as were variables important to the model.

This proof-of-principle study highlights the feasibility of applying a semiautomated MRI analysis pipeline for atlas-based texture feature extraction from T2-weighted MRI at the epicenter of acute spinal cord injury (SCI). The results show that exploratory application of five machine-learning algorithms integrated into the analysis pipeline can classify patients by degree of neurologic impairment with variable accuracy and identify potential prognostic texture features. These data show promise for computer-aided prognosis of acute SCI.

With educational activities representing the entire spectrum of radiology, ARRS will host leading radiologists from around the world at the ARRS 2018 Annual Meeting, April 22–27, at the Marriott Wardman Park Hotel in Washington, DC. For more information, visit:

Founded in 1900, ARRS is the first and oldest radiology society in the United States and is an international forum for progress in radiology. The Society's mission is to improve health through a community committed to advancing knowledge and skills in radiology. ARRS achieves its mission through an annual scientific and educational meeting, publication of the American Journal of Roentgenology (AJR) and InPractice magazine, topical symposia and webinars, and print and online educational materials. ARRS is located in Leesburg, VA.