Passive resonators have been widely used in MRI to manipulate RF field distributions. However, optimizing these structures using full-wave electromagnetic (EM) simulations is computationally prohibitive, particularly for massive-element passive resonator arrays with many degrees of freedom. While EM and RF circuit co-simulation methods have previously been applied to RF coil design, this work presents a co-simulation framework specifically tailored for the analysis and optimization of passive resonators. The framework performs a single full-wave EM simulation in which the resonator's lumped components are replaced by ports, followed by circuit-level computations to evaluate arbitrary capacitor/inductor configurations. This allows integration with a genetic algorithm to rapidly optimize the resonator parameters to enhance B1 fields in a targeted region of interest. The proposed method was validated across three scenarios of increasing complexity: (1) a single-loop passive resonator on a spherical phantom, (2) a two-loop array on a cylindrical phantom, and (3) a two-loop array on a human head model. In all cases, the co-simulation results showed excellent agreement with full-wave EM simulations, with relative errors below 1%. The genetic-algorithm-driven optimization, involving tens of thousands of capacitor combinations, completed in under 5 minutes-whereas equivalent full-wave EM sweeps would require an impractically long computation time. To the best of our knowledge, this work represents the first systematic extension of the co-simulation methodology to passive resonator design, enabling fast, accurate, and scalable optimization. The approach significantly reduces computational burden while preserving full-wave accuracy, making it a powerful tool for passive RF structure development in MRI.

To assess variability of maximum diameter measurements of prostate lesions in MRI assessing patient repositioning, rater and sequence effects. Forty-two patients were included retrospectively, who received a clinical bi-/multiparametric prostate MRI examination and agreed to have the T2-weighted (T2WI) and diffusion weighted-imaging (DWI) sequences scanned twice. Maximum diameter measurements of prostate lesions mentioned in the clinical radiologist reports were performed by four readers in multiple reading sessions for determination of inter-sequence (between two DWI sequences), inter-scan (between clinical and additional scan), intra-rater and inter-rater variability. The primary calculated metrics were the repeatability and reproducibility coefficient (RC/RDC), including pooled RC/RDC. Variability measured by RCs/RDCs was lowest for measurements obtained within the same reading session, with inter-scan RCs up to 5.6mm/6.5mm for T2WI/DWI, pooled RCs of 4.8mm/5.8mm, respectively, and inter-sequence RDCs of 5.4mm-5.9mm, pooled RDC 5.8mm. Measurements performed in separate reading sessions demonstrated significantly higher variability for both settings in the majority of cases (RCs: up to 10.9mm/11.7mm/10.2mm for T2WI/DWI/inter-sequence, p≤0.002), pooled RCs/RDCs 9.2mm-9.9mm. Measurements necessarily generated in different reading sessions, i.e., intra-rater or inter-rater, demonstrated high variability (RCs/RDCs up to 11.4mm/11.5mm for T2WI/DWI). Prostate lesion measurements demonstrate considerable variability. When measured in one reading session by one rater, lesion diameter differences below the pooled RCs of 4.8mm, 95%-CI [3.9, 5.6] for T2WI and 5.8mm, 95%-CI [4.7, 7.1] for DWI should not necessarily assumed to be true biological change, as these differences may result from measurement- or repositioning-based variability alone. Caution needs to be taken assessing size changes.