Magnetic Resonance-Based Radiomic Analysis of Radiofrequency Lesion Predicts Outcomes After Percutaneous Cordotomy: A Feasibility Study

To date, there is limited data on evaluation of the cordotomy lesion and predicting clinical outcome.

To evaluate the utility of magnetic resonance (MR)-based radiomic analysis to quantify microstructural changes created by the cordotomy lesion and predict outcome in patients undergoing percutaneous cordotomy for medically refractory cancer pain.

This is a retrospective interpretation of prospectively acquired data in 10 patients (5 males, age range 43-76 yr) who underwent percutaneous computed tomography-guided high cervical cordotomy for medically refractory cancer pain between 2015 and 2016. All patients underwent magnetic resonance imaging (MRI) of the cordotomy lesion on postoperative day 1. After segmentation of T2-weighted images, 310 radiomic features were extracted. Pain outcomes were recorded on postoperative day 1 and day 7 using the visual analog scale. R software was used to build statistical models based on MRI radiomic features for prediction of pain outcomes.

A total of 20 relevant radiomic features were identified using the maximum relevance minimum redundanc method. Radiomics predicted postoperative day 1 pain scores with an accuracy of 90% (P = .046), 100% sensitivity, 75% specificity, 85.7% positive predictive value, and 100% negative predictive value. The radiomics model also predicted if the postoperative day 1 pain score was sustained on postoperative day 7 with an accuracy of 100% (P = .028), 100% sensitivity, 100% specificity, and 100% positive and negative predictive value.

MR-based radiomic analysis of the cordotomy lesion was predictive of pain outcomes at 1 wk after percutaneous cordotomy for intractable cancer pain.