Topics in magnetic resonance imaging : TMRI · 2026
A Postprocessing Software Tool for 1H and 31P MRI Data Analysis.
СтатьяНазвание и аннотация: Перевод в очереди
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Kassey Victor B, Walle Matthias, Egan Jonathan, Kassey Daniel V, Yeritsyan Diana, Wu Yaotang, Snyder Brian D, Rodriguez Edward K, Ackerman Jerome L, Nazarian Ara
Аннотация
OBJECTIVES: Quantitative multinuclear MRI of bone is hindered by magnetic field (B0 and B1) inhomogeneities, calibration inconsistencies, and segmentation challenges. We developed a comprehensive and versatile MATLAB-based graphical interface that integrates voxel-wise B1 correction, auto and manual segmentation, coregistration, advanced visualization, and quantitative analysis with in-scan dual-density calibration, to generate reproducible bone matrix and mineral density maps from 1H and 31P ZTE MRI.
MATERIALS AND METHODS: The postprocessing package was developed in MATLAB using a modular architecture comprising multiple m-files for B1 field correction, B0 bias correction, auto and manual image registration, and segmentation for quantitative data analysis. Otsu-based thresholding with min-max intensity normalization was employed for tissue segmentation and bias correction. Data from control, ovariectomized, and vitamin D-deficient rat femurs were analyzed using normality (Shapiro-Wilk) and variance (Levene) tests. Between-group comparisons used the Kruskal-Wallis test or analysis of variance with Bonferroni or Tukey post hoc tests, respectively. Cross-modality correlation analyses were conducted between MRI-derived measures and reference measures (µCT and gravimetry) using Pearson and Spearman coefficients.
RESULTS: MRI-derived mineral density strongly correlated with µCT BMD (cortical [P = 0.22], trabecular [P = 0.31]), and the MRI matrix density correlated with the gravimetric data (cortical [P = 0.38], trabecular [P = 0.57]). No significant differences were observed between modalities for either cortical or trabecular bone.
CONCLUSION: This standardized pipeline enables reproducible, calibrated bone density mapping for data sizes ranging from 64 × 64 × 64 to 512 × 512 × 512, with B1 and B0 corrections assessing matrix and mineral densities. Its implementation as a user-guided graphical user interface promotes adoption for preclinical and clinical quantitative bone imaging across experimental conditions.
MATERIALS AND METHODS: The postprocessing package was developed in MATLAB using a modular architecture comprising multiple m-files for B1 field correction, B0 bias correction, auto and manual image registration, and segmentation for quantitative data analysis. Otsu-based thresholding with min-max intensity normalization was employed for tissue segmentation and bias correction. Data from control, ovariectomized, and vitamin D-deficient rat femurs were analyzed using normality (Shapiro-Wilk) and variance (Levene) tests. Between-group comparisons used the Kruskal-Wallis test or analysis of variance with Bonferroni or Tukey post hoc tests, respectively. Cross-modality correlation analyses were conducted between MRI-derived measures and reference measures (µCT and gravimetry) using Pearson and Spearman coefficients.
RESULTS: MRI-derived mineral density strongly correlated with µCT BMD (cortical [P = 0.22], trabecular [P = 0.31]), and the MRI matrix density correlated with the gravimetric data (cortical [P = 0.38], trabecular [P = 0.57]). No significant differences were observed between modalities for either cortical or trabecular bone.
CONCLUSION: This standardized pipeline enables reproducible, calibrated bone density mapping for data sizes ranging from 64 × 64 × 64 to 512 × 512 × 512, with B1 and B0 corrections assessing matrix and mineral densities. Its implementation as a user-guided graphical user interface promotes adoption for preclinical and clinical quantitative bone imaging across experimental conditions.