Evidence map›Paper›PMID 37173965›Full record

ArticleCancers2023

Comprehensive Brain Tumour Characterisation with VERDICT-MRI: Evaluation of Cellular and Vascular Measures Validated by Histology.

Matteo Figini, Antonella Castellano, Michele Bailo, Marcella Callea, Marcello Cadioli, Samira Bouyagoub, Marco Palombo, Valentina Pieri, Pietro Mortini, Andrea Falini and 3 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

9 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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  3. Review
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  8. Article
  9. Differentiating brain metastasis from glioblastoma by time-dependent diffusion MRI.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023
    Article
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 5 institutions in 2 countries.

Matteo FiginiCentre for Medical Image Computing and Department of Computer Science, University College London, London WC1V 6LJ, UK.ORCID 0000-0002-8238-2262
Antonella CastellanoNeuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Vita-Salute San Raffaele University, 20132 Milan, Italy.ORCID 0000-0002-4137-9016
Michele BailoDepartment of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Vita-Salute San Raffaele University, 20132 Milan, Italy.ORCID 0000-0003-4151-2873
Marcella CalleaPathology Unit, IRCCS Ospedale San Raffaele, 20132 Milan, Italy.
Marcello CadioliPhilips Healthcare, 20126 Milan, Italy.
Samira BouyagoubClinical Imaging Sciences Centre, Brighton and Sussex Medical School, Brighton BN1 9RR, UK.
Marco PalomboCentre for Medical Image Computing and Department of Computer Science, University College London, London WC1V 6LJ, UK.
Valentina PieriNeuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Vita-Salute San Raffaele University, 20132 Milan, Italy.
Pietro MortiniDepartment of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Vita-Salute San Raffaele University, 20132 Milan, Italy.
Andrea FaliniNeuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Vita-Salute San Raffaele University, 20132 Milan, Italy.
Daniel C AlexanderCentre for Medical Image Computing and Department of Computer Science, University College London, London WC1V 6LJ, UK.
Mara CercignaniClinical Imaging Sciences Centre, Brighton and Sussex Medical School, Brighton BN1 9RR, UK.
Eleftheria PanagiotakiCentre for Medical Image Computing and Department of Computer Science, University College London, London WC1V 6LJ, UK.ORCID 0000-0002-2697-3447
Vita-Salute San Raffaele University · ITUniversity College London · GBBrighton and Sussex Medical School · GBIRCCS Ospedale San Raffaele · ITPhilips (Italy) · IT

Funding

Medical Research Council MR/T020296/1
6 · The paper itself

Abstract

The aim of this work was to extend the VERDICT-MRI framework for modelling brain tumours, enabling comprehensive characterisation of both intra- and peritumoural areas with a particular focus on cellular and vascular features. Diffusion MRI data were acquired with multiple b-values (ranging from 50 to 3500 s/mm

Indexed as

biophysical modelbrain tumourscell densitydiffusion MRImicrostructureMRImulti-compartmentoedemavascularityVERDICT

Identifiers

PMID37173965
PMCPMC10177485
OpenAlexW4367183635

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.