Evidence map›Paper›PMID 27271923›Full record

ArticleEuropean radiology2017

Diffusion-weighted magnetic resonance imaging predicts survival in patients with liver-predominant metastatic colorectal cancer shortly after selective internal radiation therapy.

Frederic Carsten Schmeel, Birgit Simon, Amir Sabet, Julian Alexander Luetkens, Frank Träber, Leonard Christopher Schmeel, Samer Ezziddin, Hans Heinz Schild, Dariusch Reza Hadizadeh

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Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
5.4field-weighted citation impact, top 4% 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

14 citing papers in PubMed, 27 citations in OpenAlex.

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  14. Imaging Evaluation FollowingKorean journal of radiology
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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

9 authors at 2 institutions in 1 country.

Frederic Carsten SchmeelDepartment of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Sigmund-Freud-Straße 25, 53127, Bonn, Germany. Carsten.Schmeel@ukb.uni-bonn.de.
Birgit SimonDepartment of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Sigmund-Freud-Straße 25, 53127, Bonn, Germany.
Amir SabetDepartment of Nuclear Medicine, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany.
Julian Alexander LuetkensDepartment of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Sigmund-Freud-Straße 25, 53127, Bonn, Germany.
Frank TräberDepartment of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Sigmund-Freud-Straße 25, 53127, Bonn, Germany.
Leonard Christopher SchmeelDepartment of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Sigmund-Freud-Straße 25, 53127, Bonn, Germany.
Samer EzziddinDepartment of Nuclear Medicine, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Bonn, Germany.
Hans Heinz SchildDepartment of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Sigmund-Freud-Straße 25, 53127, Bonn, Germany.
Dariusch Reza HadizadehDepartment of Radiology, University Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität Bonn, Sigmund-Freud-Straße 25, 53127, Bonn, Germany.
University Hospital Bonn · DEUniversity of Bonn · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate whether quantifications of apparent diffusion coefficient (ADC) on diffusion-weighted imaging (DWI) can predict overall survival (OS) in patients with liver-predominant metastatic colorectal cancer (CRC) following selective internal radiation therapy with

methodsForty-four patients underwent DWI 19 ± 16 days before and 36 ± 10 days after SIRT. Tumour-size and intratumoral minimal ADC (minADC) values were measured for 132 liver metastases on baseline and follow-up DWI. Optimal functional imaging response to treatment was determined by receiver operating characteristics and defined as ≥22 % increase in post-therapeutic minADC. Survival analysis was performed with the Kaplan-Meier method and Cox-regression comparing various variables with potential impact on OS.

resultsMedian OS was 8 months. The following parameters were significantly associated with median OS: optimal functional imaging response (18 vs. 5 months; p < 0.001), hepatic tumour burden <50 % (8 vs. 5 months; p = 0.018), Eastern Cooperative Oncology Group performance scale <1 (10 vs. 4 months; p = 0.012) and progressive disease according to Response and Evaluation Criteria in Solid Tumours (8 vs. 3 months; p = 0.001). On multivariate analysis, optimal functional imaging response and hepatic tumour burden remained independent predictors of OS.

conclusionFunctional imaging response assessment using minADC changes on DWI may predict survival in CRC shortly after SIRT. KEY POINTS: • Relative minADC changes may predict survival in liver-predominant metastatic colorectal cancer following SIRT • Intratumoral minADC changes by ≥22 % were best to predict an improved overall survival • Functional imaging response assessment is feasible before anatomic tumour-size changes occur • minADC changes might guide future therapy management in sequential lobar radioembolization approaches.

Indexed as

AgedAged, 80 and overBrachytherapyColorectal NeoplasmsDiffusion Magnetic Resonance ImagingFemaleHumansLiver NeoplasmsMaleMicrospheresMiddle AgedPredictive Value of TestsRetrospective StudiesROC CurveSurvival AnalysisTreatment OutcomeYttrium RadioisotopesApparent diffusion coefficientColorectal cancerFunctional imagingMRIRadioembolization

Identifiers

PMID27271923
OpenAlexW2416649554

What OpenQuestion holds

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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.