ArticleNeuro-oncology2025
Multi-site retrospective analysis of diffusion and perfusion magnetic resonance imaging correlates to glioma characteristics derived from radio-pathomic maps.
Article in Neuro-oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Altered perivascular diffusivity in glioblastoma: integrating DTI-ALPS index with radio-pathomic and histopathologic correlates.Journal of neuro-oncology · 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
- Enhanced detection of glioblastoma vasculature with superparamagnetic iron oxide nanoparticles and MRI.Scientific reports · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
12 authors.
Funding
Abstract
backgroundThis study determines the relationship between diffusion and perfusion-based magnetic resonance imaging signatures and radio-pathomic maps of tumor pathology in a large, multi-site cohort.
methodsThis study included perfusion imaging from presurgical relative cerebral blood volume (rCBV) images from the UPenn-GBM dataset and presurgical arterial spin labeling (ASL) imaging from the UCSF-PDGM dataset. Diffusion imaging included fractional anisotropy (FA) estimates derived from diffusion tensor imaging for each subject from each institution. A previously validated autopsy-based model was applied to the structural images from each patient to generate quantitative radio-pathomic maps of cell density and extracellular fluid (ECF). Mean cell density, ECF density, FA, rCBV calculated from dynamic susceptibility contrast imaging, and rCBF calculated from ASL were computed for each patient and statistically compared within contrast-enhancement (CE) and the non-enhancing peritumor FLAIR hyperintensity (FH).
resultsBoth rCBV and ASL showed a positive correlation with cell density within CE (rCBV: R = 0.280, P < .001; ASL: R = 0.117, P = .023). However, both perfusion metrics also showed no association with cell density within the FH region at the group level (rCBV: R = 0.0162, P = .731; ASL: R = -0.020, P = .652). Negative correlations were observed between FA and ECF density across both CE and FH in both the UPenn-GBM (CE: r = -.204, P < .001, FH: r = -.332, P < .001) and the UCSF-PDGM (CE:r = -.179, P < .001, FH:-0.355, P < .001). Additionally, a positive ASL-cell density association per subject within FH was associated with a worse survival prognosis (HR = 5.58, P = .022).
conclusionsThese results suggest that radio-pathomic maps of tumor pathology provide complementary information to other MR signatures that reveal prognostically valuable signatures of the non-enhancing tumor margin.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.