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

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.

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Publication Details

Journal
Topics in Magnetic Resonance Imaging
Published
2026-08-17
DOI
https://doi.org/10.1097/rmr.0000000000000324
Primary Topic
Bone health and osteoporosis research
Type
article
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article

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

Jonathan Egan, Matthias Walle, Ara Nazarian, Diana Yeritsyan et al.
Topics in Magnetic Resonance Imaging
Bone health and osteoporosis research
article

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

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

Abstract

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.

Topics in Magnetic Resonance ImagingVol. 35(1)
Boston Children's Hospital (US), Beth Israel Deaconess Medical Center (US), Harvard University (US), Athinoula A. Martinos Center for Biomedical Imaging (US), Yerevan State Medical University (AM)
Openalex Percentile: Top 8%
Bone health and osteoporosis research
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