Reproducibility and postacquisition correction methods for quantitative magnetic resonance imaging of the anterior cruciate ligament (ACL).

Quantitative magnetic resonance imaging has been used to evaluate the structural integrity of knee joint structures. However, variations in acquisition parameters between scanners pose significant challenges. Understanding the effect of small differences in acquisition parameters for quantitative sequences is vital to the validity of cross-institutional studies, and for the harmonization of large, heterogeneous datasets to train machine learning models. The study objective was to assess the reproducibility of T2 * relaxometry and the constructive interference in steady-state sequence (CISS) across scanners, with minimal hardware-necessitated changes to acquisition parameters. It was hypothesized that there would be no significant differences between scanners in anterior cruciate ligament T2 * relaxation times and CISS signal intensities (SI). Secondarily, it was hypothesized that differences could be corrected by rescaling the SI distribution to harmonize between scanners. Seven volunteers were scanned on 3T Prisma and Tim Trio scanners (Siemens). Three correction methods were evaluated for T2 *: inverse echo time scaling, z-scoring, and Nyúl histogram matching. For CISS, scans were normalized to cortical bone, scaled by the background noise ratio, and log-transformed. Before correction, significant mean differences of 6.0 ± 3.2 ms (71.8%; p = 0.02) and 0.49 ± 0.15 units (40.7%; p = 0.02) for T2 * and CISS across scanners were observed, respectively. After rescaling, T2 * differences decreased to 2.6 ± 2.7 ms (23.9%; p = 0.03), 1.3 ± 2.5 ms (10.9%; p = 0.13), and 1.27 ± 3.0 ms (19.6%; p = 0.40) for inverse echo time, z-scoring, and Nyúl, respectively, while CISS decreased to 0.01 ± 0.11 units (4.0%; p = 0.87). These findings suggest that small acquisition parameter differences may lead to large changes in T2 * and SI values that must be reconciled to compare data across magnets.