ArticleAJNR. American journal of neuroradiology2022
Radio-Pathomic Maps of Cell Density Identify Brain Tumor Invasion beyond Traditional MRI-Defined Margins.
Article in AJNR. American journal of neuroradiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Unique Peritumoral Patterns Unveiled by Quantitative Multiparametric MRI and Their Diagnostic and Prognostic Value in Treated Malignant Gliomas.NMR in biomedicine · 2026Article
- The role of diffusion-weighted MRI in biological image-guided radiation therapy: a roadmap.Physics in medicine and biology · 2026Review
- Review
- Altered perivascular diffusivity in glioblastoma: integrating DTI-ALPS index with radio-pathomic and histopathologic correlates.Journal of neuro-oncology · 2026Article
- Radio-pathomic maps of histo-morphometric features trained with whole mount prostate histology distinguish prostate cancer on MP-MRI.medRxiv : the preprint server for health sciences · 2026Article
- Altered Perivascular Diffusivity in Glioblastoma:Integrating DTI-ALPS Index with Radio-Pathomicand Histopathologic Correlates.Research square · 2025Article
- Independent histological validation of MR-derived radio-pathomic maps of tumor cell density using image-guided biopsies in human brain tumors.Journal of neuro-oncology · 2025Article
- Pilot research on predicting the sub-volume with high risk of tumor recurrence inside peritumoral edema using the ratio-maxiADC/meanADC from the advanced MRI.Discover oncology · 2025Article
- Multi-site retrospective analysis of diffusion and perfusion magnetic resonance imaging correlates to glioma characteristics derived from radio-pathomic maps.Neuro-oncology · 2025Article
- Tumor cells upregulate neurotransmitter GABA in the choroid plexus through STAT6-Bestrophin1 signaling, promoting leptomeningeal dissemination.Neuro-oncology · 2025Article
- Radiomics in glioma: emerging trends and challenges.Annals of clinical and translational neurology · 2025Review
- Radio-pathomic estimates of cellular growth kinetics predict survival in recurrent glioblastoma.CNS oncology · 2024Article
- Exploratory Analysis of Radiomics and Pathomics in Uterine Corpus Endometrial Carcinoma.Scientific reports · 2024Article
- Simultaneous quantification of perfusion, permeability, and leakage effects in brain gliomas using dynamic spin-and-gradient-echo echoplanar imaging MRI.European radiology · 2024Article
- Radio-pathomic maps of glioblastoma identify phenotypes of non-enhancing tumor infiltration associated with bevacizumab treatment response.Journal of neuro-oncology · 2024Article
- Advances in Neuro-Oncological Imaging: An Update on Diagnostic Approach to Brain Tumors.Cancers · 2024Review
- Radio-pathomic maps of glioblastoma identify phenotypes of non-enhancing tumor infiltration associated with bevacizumab treatment response.Research square · 2024Article
- The BrainboxBrain communications · 2023Article
- The relationship between radiomics and pathomics in Glioblastoma patients: Preliminary results from a cross-scale association study.Frontiers in oncology · 2022Article
- Initial Condition Assessment for Reaction-Diffusion Glioma Growth Models: A Translational MRI-Histology (In)Validation Study.Tomography (Ann Arbor, Mich.) · 2021Article
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Authors and funding
13 authors.
Funding
Abstract
background and purposeCurrently, contrast-enhancing margins on T1WI are used to guide treatment of gliomas, yet tumor invasion beyond the contrast-enhancing region is a known confounding factor. Therefore, this study used postmortem tissue samples aligned with clinically acquired MRIs to quantify the relationship between intensity values and cellularity as well as to develop a radio-pathomic model to predict cellularity using MR imaging data. MATERIALS AND
methodsThis single-institution study used 93 samples collected at postmortem examination from 44 patients with brain cancer. Tissue samples were processed, stained with H&E, and digitized for nuclei segmentation and cell density calculation. Pre- and postgadolinium contrast T1WI, T2 FLAIR, and ADC images were collected from each patient's final acquisition before death. In-house software was used to align tissue samples to the FLAIR image via manually defined control points. Mixed-effects models were used to assess the relationship between single-image intensity and cellularity for each image. An ensemble learner was trained to predict cellularity using 5 × 5 voxel tiles from each image, with a two-thirds to one-third train-test split for validation.
resultsSingle-image analyses found subtle associations between image intensity and cellularity, with a less pronounced relationship in patients with glioblastoma. The radio-pathomic model accurately predicted cellularity in the test set (root mean squared error = 1015 cells/mm
conclusionsA radio-pathomic model for cellularity trained with tissue samples acquired at postmortem examination is able to identify regions of hypercellular tumor beyond traditional imaging signatures.
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