Continuous-time random walk MRI and pathological heterogeneity in intracranial tumours: a neuronavigation-guided study

Brain tumours are spatially heterogeneous, whereas MRI and histopathology interrogate tissue at different spatial scales. We developed a neuronavigation-guided radiology-pathology framework to test whether continuous-time random walk (CTRW) diffusion metrics measured at recorded sampling sites are associated with pathology-based structural heterogeneity and selected immune-cell proportions. We studied 98 surgically treated adults with high-grade glioma (HGG; n = 34), brain metastasis (BM; n = 34), or meningioma (MENI; n = 30). Each participant contributed one neuronavigation-recorded specimen of approximately 2 mm from the superficial margin within the solid contrast-enhancing tumour component, with a coordinate-centred 2-mm imaging ROI used for radiology-pathology matching. CTRW spatial heterogeneity (β), temporal heterogeneity (α), and anomalous diffusion coefficient (Dm) were derived from high-b-value DWI. Matched specimens underwent haematoxylin & eosin staining and immunofluorescence analysis. Pathologist scoring, pathomics, and immune-cell measurements were analysed at the patient level. Five regression families were compared using repeated tumour-type-stratified nested cross-validation. In malignant tumours, β decreased from contralesional brain to peritumoral brain oedema and contrast-enhancing tumour and was inversely associated with the manual H&E heterogeneity score (Spearman ρ = -0.948; FDR-adjusted q < 0.001). Random-forest regression had the highest internal cross-validation performance. In the 50-outer-fold sensitivity analysis, mean R² ± SD values were 0.984 ± 0.010 for neutrophils, 0.976 ± 0.013 for macrophages, and 0.943 ± 0.033 for B cells. Tumour-type-only models had lower mean R² values of 0.352, 0.295, and 0.320, whereas CTRW models retained mean R² values of 0.717, 0.767, and 0.671 after training-fold residualization for tumour type. At neuronavigation-recorded sampling sites, CTRW metrics were associated with pathology-defined structural heterogeneity and enabled internally validated estimation of selected immune-cell proportions. These findings support CTRW as a complementary imaging descriptor, although its incremental value beyond conventional diffusion metrics remains to be established. Importantly, the observed associations reflect radiology–pathology correspondence at the sampling-site scale rather than direct cellular-resolution imaging or validated clinical prediction. Nevertheless, the biologically anchored relationships identified here provide a rationale for the prospective evaluation of CTRW-derived imaging biomarkers for imaging-informed tumour characterization and stratification.

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Journal
Journal of Translational Medicine
Published
2026-10-13
DOI
https://doi.org/10.1186/s12967-026-09072-3
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
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article

Continuous-time random walk MRI and pathological heterogeneity in intracranial tumours: a neuronavigation-guided study

Min Gao, Yu Zhou, Hongjing Zang, Jun Liu et al.
Journal of Translational Medicine
Advanced Neuroimaging Techniques and Applications
article

Continuous-time random walk MRI and pathological heterogeneity in intracranial tumours: a neuronavigation-guided study

Min Gao, Yu Zhou, Hongjing Zang, Jun Liu, Wei Liu, W. Zhao, Enze Liu, Jianmin Yuan, Hai Lin, Jing Peng, Yizhong Yan, Yujin He
article en

Abstract

Brain tumours are spatially heterogeneous, whereas MRI and histopathology interrogate tissue at different spatial scales. We developed a neuronavigation-guided radiology-pathology framework to test whether continuous-time random walk (CTRW) diffusion metrics measured at recorded sampling sites are associated with pathology-based structural heterogeneity and selected immune-cell proportions. We studied 98 surgically treated adults with high-grade glioma (HGG; n = 34), brain metastasis (BM; n = 34), or meningioma (MENI; n = 30). Each participant contributed one neuronavigation-recorded specimen of approximately 2 mm from the superficial margin within the solid contrast-enhancing tumour component, with a coordinate-centred 2-mm imaging ROI used for radiology-pathology matching. CTRW spatial heterogeneity (β), temporal heterogeneity (α), and anomalous diffusion coefficient (Dm) were derived from high-b-value DWI. Matched specimens underwent haematoxylin & eosin staining and immunofluorescence analysis. Pathologist scoring, pathomics, and immune-cell measurements were analysed at the patient level. Five regression families were compared using repeated tumour-type-stratified nested cross-validation. In malignant tumours, β decreased from contralesional brain to peritumoral brain oedema and contrast-enhancing tumour and was inversely associated with the manual H&E heterogeneity score (Spearman ρ = -0.948; FDR-adjusted q < 0.001). Random-forest regression had the highest internal cross-validation performance. In the 50-outer-fold sensitivity analysis, mean R² ± SD values were 0.984 ± 0.010 for neutrophils, 0.976 ± 0.013 for macrophages, and 0.943 ± 0.033 for B cells. Tumour-type-only models had lower mean R² values of 0.352, 0.295, and 0.320, whereas CTRW models retained mean R² values of 0.717, 0.767, and 0.671 after training-fold residualization for tumour type. At neuronavigation-recorded sampling sites, CTRW metrics were associated with pathology-defined structural heterogeneity and enabled internally validated estimation of selected immune-cell proportions. These findings support CTRW as a complementary imaging descriptor, although its incremental value beyond conventional diffusion metrics remains to be established. Importantly, the observed associations reflect radiology–pathology correspondence at the sampling-site scale rather than direct cellular-resolution imaging or validated clinical prediction. Nevertheless, the biologically anchored relationships identified here provide a rationale for the prospective evaluation of CTRW-derived imaging biomarkers for imaging-informed tumour characterization and stratification.

Journal of Translational Medicine
National Engineering Research Center of Human Stem Cells (CN), Mayo Clinic in Arizona (US), Mayo Clinic Hospital (US), United Imaging Healthcare (China) (CN), Second Xiangya Hospital of Central South University (CN), Mayo Clinic Comprehensive Cancer Center (Arizona)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Hunan Province
Openalex Percentile: Top 13%
Advanced Neuroimaging Techniques and Applications
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