Evidence map›Paper›PMID 30888488›Full record

ArticleEuropean radiology2019

Non-invasive assessment of glioma microstructure using VERDICT MRI: correlation with histology.

Fulvio Zaccagna, Frank Riemer, Andrew N Priest, Mary A McLean, Kieren Allinson, James T Grist, Carmen Dragos, Tomasz Matys, Jonathan H Gillard, Colin Watts and 3 more

Open access · hybridAbstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 53 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Engineering clinical translation of OGSE diffusion MRI.Magnetic resonance in medicine · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 4 institutions in 1 country.

Fulvio ZaccagnaDepartment of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK. fz247@cam.ac.uk.
Frank RiemerDepartment of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
Andrew N PriestDepartment of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
Mary A McLeanCancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
Kieren AllinsonDepartment of Pathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
James T GristDepartment of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
Carmen DragosDepartment of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
Tomasz MatysDepartment of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
Jonathan H GillardDepartment of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
Colin WattsInstitute of Cancer and Genomic Sciences, Birmingham Brain Cancer Program, University of Birmingham, Birmingham, UK.
Stephen J PriceNeurosurgery Unit, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Martin J GravesDepartment of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
Ferdia A GallagherDepartment of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
University of Cambridge · GBCambridge University Hospitals NHS Foundation Trust · GBCancer Research UK · GBUniversity of Birmingham · GB

Funding

Cancer Research UK 16465Cancer Research UK 16628Cancer Research UK 27150
6 · The paper itself

Abstract

purposeThis prospective study evaluated the use of vascular, extracellular and restricted diffusion for cytometry in tumours (VERDICT) MRI to investigate the tissue microstructure in glioma. VERDICT-derived parameters were correlated with both histological features and tumour subtype and were also used to explore the peritumoural region.

methodsFourteen consecutive treatment-naïve patients (43.5 years ± 15.1 years, six males, eight females) with suspected glioma underwent diffusion-weighted imaging including VERDICT modelling. Tumour cell radius and intracellular and combined extracellular/vascular volumes were estimated using a framework based on linearisation and convex optimisation. An experienced neuroradiologist outlined the peritumoural oedema, enhancing tumour and necrosis on T2-weighted imaging and contrast-enhanced T1-weighted imaging. The same regions of interest were applied to the co-registered VERDICT maps to calculate the microstructure parameters. Pathology sections were analysed with semi-automated software to measure cellularity and cell size.

resultsVERDICT parameters were successfully calculated in all patients. The imaging-derived results showed a larger intracellular volume fraction in high-grade glioma compared to low-grade glioma (0.13 ± 0.07 vs. 0.08 ± 0.02, respectively; p = 0.05) and a trend towards a smaller extracellular/vascular volume fraction (0.88 ± 0.07 vs. 0.92 ± 0.04, respectively; p = 0.10). The conventional apparent diffusion coefficient was higher in low-grade gliomas compared to high-grade gliomas, but this difference was not statistically significant (1.22 ± 0.13 × 10

conclusionThis feasibility study demonstrated that VERDICT MRI can be used to explore the tissue microstructure of glioma using an abbreviated protocol. The VERDICT parameters of tissue structure correlated with those derived on histology. The method shows promise as a potential test for diagnostic stratification and treatment response monitoring in the future. KEY POINTS: • VERDICT MRI is an advanced diffusion technique which has been correlated with histopathological findings obtained at surgery from patients with glioma in this study. • The intracellular volume fraction measured with VERDICT was larger in high-grade tumours compared to that in low-grade tumours. • The results were complementary to measurements from conventional diffusion-weighted imaging, and the technique could be performed in a clinically feasible timescale.

Indexed as

AdultAgedBrain NeoplasmsDiffusion Magnetic Resonance ImagingFeasibility StudiesFemaleGliomaHumansMagnetic Resonance AngiographyMaleMiddle AgedNeoplasm GradingProspective StudiesReproducibility of ResultsYoung AdultBrain neoplasmsCancerDiagnostic imagingDiffusion magnetic resonance imagingGlioma

Identifiers

PMID30888488
PMCPMC6719328
OpenAlexW2925027262

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.