Diagnosing abdominal neoplasms using a T2 mapping radial turbo spin-echo technique with partial volume correction

作者：Mahesh Keerthivasan, Brian Toner, Jean‐Philippe Galons, Kevin M. Johnson, Ali Bilgin, Diego R. Martín, María I. Altbach · 发表于：European Radiology · 年份：2025 · DOI：10.1007/s00330-025-11931-4 · 被引用次数：1 · 研究领域：Advanced MRI Techniques and Applications、Hepatocellular Carcinoma Treatment and Prognosis、MRI in cancer diagnosis

OBJECTIVE: T2 mapping allows for the classification of focal liver lesions, differentiating malignancies from the most common benign liver lesions, hemangiomas, and bile duct hamartomas (BDH). Partial volume (PV) due to the presence of liver and lesion within the same voxel confounds the classification of small lesions. Our objective is to develop a robust two-component T2 estimation technique (SEPG2-SP) to enable accurate T2 estimation in the presence of PV. MATERIALS AND METHODS: T2 estimation accuracy was evaluated using computer simulations, physical phantom data, and in vivo in 27 subjects with focal liver lesions (16 males, 62.4 ± 14.3 years old; 11 females, 66.8 ± 5.8 years old) imaged at 1.5 T with a radial turbo spin-echo (RADTSE) technique. The SEPG2-SP model was compared to a single-component model, which does not account for PV. The area under the receiver operator characteristic curve (AUROC) was used to analyze lesion classification. RESULTS: Phantom data showed that the SEPG2-SP model had a T2 estimation error of 2-9% while the single component model had a larger error of 9-23%. Analysis of in vivo data from 68 focal liver lesions (33 malignancies, 7 hemangiomas, and 28 BDH) showed that the SEPG2-SP model classified all lesions correctly (AUROC = 1), regardless of their size. On the other hand, with the single-component model, there was overlap between malignancies and benign lesions driven by misclassification of hemangiomas as malignancies (AUROC = 0.84). CON...