Magnetic resonance imaging · 2025
R-index: A robust metric for IVIM parameter estimation on clinical MRI scanners.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
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Dai Yan, Jia Xun, Liao Yen-Peng, Jie Deng
Аннотация
PURPOSE: Intravoxel Incoherent Motion (IVIM) model characterizes both water diffusion and perfusion in tissues, providing quantitative biomarkers valuable for tumor characterization. However, parameter estimation through nonlinear fitting of this bi-exponential model is challenging for its ill-posed nature, resulting in poor reproducibility, particularly at low signal to noise ratios (SNRs) in a clinic scenario. This study analyzes the uncertainty of IVIM model fitting, quantifies parameter collinearity, and introduces a new index with enhanced robustness to enhance clinical applicability of the IVIM model.
METHODS: The probability distributions of estimated IVIM parameters were evaluated across a clinically relevant range. Collinearity among parameters was assessed and a metric, R-index, was proposed. The R-index linearly combines individual IVIM parameters to mitigate collinearity and reduce estimation uncertainty. Simulation, volunteer, and patient studies were conducted to validate the presence of parameter collinearity and to assess the robustness of the R-index.
RESULTS: In simulations under typical clinical conditions (SNR = 20), normalized IVIM parameters exhibited mean standard deviations (Std) of 0.107-0.269 and the expected mean Std for R was 0.120, whereas the R-index showed a lower Std of 0.064. Same-day repeat scans in a healthy volunteer (1.5 T MRI) and multi-day scans in six brain tumor patients (1.5 T MR-Linac) confirmed parameter collinearity: Across the volunteer and patients, the mean Std of R-index was lower than the expected mean Std assuming independence between individual IVIM parameters.
CONCLUSIONS: The R-index provides a robust metric for IVIM model fitting under low SNR in typical clinical conditions, offering improved reproducibility and potential for broader clinical applicability.
METHODS: The probability distributions of estimated IVIM parameters were evaluated across a clinically relevant range. Collinearity among parameters was assessed and a metric, R-index, was proposed. The R-index linearly combines individual IVIM parameters to mitigate collinearity and reduce estimation uncertainty. Simulation, volunteer, and patient studies were conducted to validate the presence of parameter collinearity and to assess the robustness of the R-index.
RESULTS: In simulations under typical clinical conditions (SNR = 20), normalized IVIM parameters exhibited mean standard deviations (Std) of 0.107-0.269 and the expected mean Std for R was 0.120, whereas the R-index showed a lower Std of 0.064. Same-day repeat scans in a healthy volunteer (1.5 T MRI) and multi-day scans in six brain tumor patients (1.5 T MR-Linac) confirmed parameter collinearity: Across the volunteer and patients, the mean Std of R-index was lower than the expected mean Std assuming independence between individual IVIM parameters.
CONCLUSIONS: The R-index provides a robust metric for IVIM model fitting under low SNR in typical clinical conditions, offering improved reproducibility and potential for broader clinical applicability.