DOI: 10.1097/rmr.0000000000000324 ISSN: 1536-1004

A Postprocessing Software Tool for 1H and 31P MRI Data Analysis

Victor B. Kassey, Matthias Walle, Jonathan Egan, Daniel V. Kassey, Diana Yeritsyan, Yaotang Wu, Brian D. Snyder, Edward K. Rodriguez, Jerome L. Ackerman, Ara Nazarian

Abstract

Objectives:

Quantitative multinuclear MRI of bone is hindered by magnetic field (B 0 and B 1 ) inhomogeneities, calibration inconsistencies, and segmentation challenges. We developed a comprehensive and versatile MATLAB-based graphical interface that integrates voxel-wise B 1 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 1 H and 31 P ZTE MRI.

Materials and Methods:

The postprocessing package was developed in MATLAB using a modular architecture comprising multiple m-files for B 1 field correction, B 0 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 B 1 and B 0 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.

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