SM (@sdkm.bsky.social)

3D T1 turbo spin echo improves detection of gadolinium-enhancing multiple-sclerosis lesions - Insights into Imaging Objectives To compare the performance of 3D T1 turbo spin echo (3DT1TSE) and 3D T1 turbo field echo (3DT1TFE) MRI in detecting gadolinium-enhancing lesions in multiple sclerosis (MS). Materials and methods We retrospectively analyzed 255 3-T MRIs from MS patients, each including post-contrast 3DT1TSE and 3DT1TFE sequences. Two blinded readers independently assessed enhancing lesions per sequence. A consensus review, incorporating longitudinal imaging and additional sequences, served as the reference standard. Results The consensus identified 70 enhancing lesions in 31 patients. All 70 were visible on 3DT1TSE, while 64 (91%) were detectable on 3DT1TFE. Reader sensitivity was higher for 3DT1TSE (84% and 90%) than 3DT1TFE (45% and 40%) (p < 0.01). Inter-reader agreement was excellent for 3DT1TSE (ICC = 0.90) and moderate for 3DT1TFE (intraclass correlation coefficient = 0.69). Although false positives were more common with 3DT1TSE, they were readily excluded during consensus reading. In six patients, enhancing lesions were detected only on 3DT1TSE, with treatment escalation in two. Conclusion 3DT1TSE outperformed 3DT1TFE in sensitivity and reader agreement for enhancing lesion detection in MS. Incorporating 3DT1TSE into standard MRI protocols may improve disease activity assessment and clinical decision-making. Critical relevance statement Replacing 3D gradient-echo with post-contrast 3D T1 turbo spin-echo brain MRI greatly improves the detection of gadolinium-enhancing multiple-sclerosis lesions, boosting diagnostic sensitivity and reader agreement and directly influencing treatment-escalation decisions in routine practice. Key Points Detecting and enhancing MS lesions is limited by standard 3D T1 turbo field echo (3DT1TFE) MRI. 3D T1 turbo spin echo detects significantly more gadolinium-enhancing MS lesions than conventional 3DT1TFE. Greater lesion detection allows more precise activity assessment and optimal treatment management. Graphical Abstract https://insightsimaging.springeropen.com/articles/10.1186/s13244-025-02093-4