Evidence map›Paper›PMID 32034488›Full record

ArticleEuropean radiology2020

Value of combined multiparametric MRI and FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation.

Niels W Schurink, Lisa A Min, Maaike Berbee, Wouter van Elmpt, Joost J M van Griethuysen, Frans C H Bakers, Sander Roberti, Simon R van Kranen, Max J Lahaye, Monique Maas and 3 more

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Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Predictive value ofReports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2025
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  8. Review
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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.

Niels W SchurinkDepartment of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Lisa A MinDepartment of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Maaike BerbeeGROW School for Oncology and Developmental Biology, University of Maastricht, Maastricht, The Netherlands.
Wouter van ElmptGROW School for Oncology and Developmental Biology, University of Maastricht, Maastricht, The Netherlands.
Joost J M van GriethuysenDepartment of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Frans C H BakersDepartment of Radiology, Maastricht University Medical Center, Maastricht, The Netherlands.
Sander RobertiDepartment of Epidemiology and Biostatistics, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Simon R van KranenDepartment of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Max J LahayeDepartment of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Monique MaasDepartment of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Geerard L BeetsGROW School for Oncology and Developmental Biology, University of Maastricht, Maastricht, The Netherlands.
Regina G H Beets-TanDepartment of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
Doenja M J LambregtsDepartment of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands. d.lambregts@nki.nl.ORCID http://orcid.org/0000-0003-2990-0099

Funding

KWF Kankerbestrijding 10138
6 · The paper itself

Abstract

objectivesTo explore the value of multiparametric MRI combined with FDG-PET/CT to identify well-responding rectal cancer patients before the start of neoadjuvant chemoradiation.

methodsSixty-one locally advanced rectal cancer patients who underwent a baseline FDG-PET/CT and MRI (T2W + DWI) and received long-course neoadjuvant chemoradiotherapy were retrospectively analysed. Tumours were delineated on MRI and PET/CT from which the following quantitative parameters were calculated: T2W volume and entropy, ADC mean and entropy, CT density (mean-HU), SUV maximum and mean, metabolic tumour volume (MTV

resultsThe optimal multivariable prediction model consisted of a combination of baseline + quantitative imaging parameters and included mrT-stage (OR 0.004, p < 0.001), T2W-signal entropy (OR 7.81, p = 0.0079) and T2W volume (OR 1.028, p = 0.0389) as the selected predictors. AUC in the study dataset was 0.88 and 0.83 after LOOCV. No PET/CT features were selected as predictors.

conclusionsA multivariable model incorporating mrT-stage and quantitative parameters from baseline MRI can aid in identifying well-responding patients before the start of treatment. Addition of FDG-PET/CT is not beneficial. KEY POINTS: • A multivariable model incorporating the mrT-stage and quantitative features derived from baseline MRI can aid in identifying well-responding patients before the start of neoadjuvant chemoradiotherapy. • mrT-stage was the strongest predictor in the model and was complemented by the tumour volume and signal entropy calculated from T2W-MRI. • Adding quantitative features derived from pre-treatment PET/CT or DWI did not contribute to the model's predictive performance.

Indexed as

AgedAged, 80 and overChemoradiotherapyFemaleFluorodeoxyglucose F18HumansMaleMiddle AgedMultiparametric Magnetic Resonance ImagingNeoadjuvant TherapyNeoplasm StagingPositron Emission Tomography Computed TomographyRadiopharmaceuticalsRectal NeoplasmsRetrospective StudiesFluorodeoxyglucose F18RadiopharmaceuticalsLogistic modelsMagnetic resonance imagingNeoadjuvant therapyPositron emission tomography computed tomographyRectal neoplasms

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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.