Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions.
| Publication Type | Academic Article |
| Authors | Zhang S, Nguyen T, Zhao Y, Gauthier S, Wang Y, Gupta A |
| Journal | Neuroimage Clin |
| Volume | 18 |
| Pagination | 143-148 |
| Date Published | 01/28/2018 |
| ISSN | 2213-1582 |
| Keywords | Brain, Image Processing, Computer-Assisted, Multiple Sclerosis, White Matter |
| Abstract | PURPOSE: To evaluate the diagnostic accuracy of a novel non-contrast brain MRI method based on semiautomatic lesion detection using T2w FLAIR subtraction image, the statistical detection of change (SDC) algorithm (T2w + SDC), and quantitative susceptibility mapping (QSM). This method identifies new lesions and discriminates between enhancing and nonenhancing lesions in multiple sclerosis (MS). METHODS: Thirty three MS patients who had MRIs at two different time points with at least one new Gd-enhancing lesion on the 2nd MRI were included in the study. For a reference standard, new lesions were identified by two neuroradiologists on T2w and post-Gd T1w images with the help of T2w + SDC. The diagnostic accuracy of the proposed method based on QSM and T2w + SDC lesion detection (T2w + SDC + QSM) for assessing lesion enhancement status was determined. Receiver operating characteristic (ROC) analysis was performed to compute the optimal lesion susceptibility cutoff value. RESULTS: A total of 165 new lesions (54 enhancing, 111 nonenhancing) were identified. The sensitivity and specificity of T2w + SDC + QSM in predicting lesion enhancement status were 90.7% and 85.6%, respectively. For lesions ≥50 mm3, ROC analysis showed an optimal QSM cutoff value of 13.5 ppb with a sensitivity of 88.4% and specificity of 88.6% (0.93, 95% CI, 0.87-0.99). For lesions ≥15 mm3, the optimal QSM cutoff was 15.4 ppb with a sensitivity of 77.9% and specificity of 94.0% (0.93, 95% CI, 0.89-0.97). CONCLUSION: The proposed T2w + SDC + QSM method is highly accurate for identifying and predicting the enhancement status of new MS lesions without the use of Gd injection. |
| DOI | 10.1016/j.nicl.2018.01.013 |
| PubMed ID | 29387531 |
| PubMed Central ID | PMC5790036 |