Evidence map›Paper›PMID 37115215›Full record

ArticleEuropean radiology2023

Diagnostic accuracy of state-of-the-art rectal MRI sequences for the diagnosis of extramural vascular invasion in locally advanced rectal cancer after preoperative chemoradiotherapy: dos or maybes?

Filippo Crimì, Raimondo Angelone, Antonio Corso, Quoc Riccardo Bao, Giulio Cabrelle, Federica Vernuccio, Gaya Spolverato, Salvatore Pucciarelli, Emilio Quaia

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Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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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 1 institution in 1 country.

Filippo Crimì *Institute of Radiology, Department of Medicine-DIMED, University of Padova, Via Niccolò Giustiniani N.2, 35128, Padua, Italy.
Raimondo Angelone *Institute of Radiology, Department of Medicine-DIMED, University of Padova, Via Niccolò Giustiniani N.2, 35128, Padua, Italy.
Antonio Corso *Institute of Radiology, Department of Medicine-DIMED, University of Padova, Via Niccolò Giustiniani N.2, 35128, Padua, Italy.
Quoc Riccardo BaoGeneral Surgery 3, Department of Surgical, Oncological, and Gastroenterological Sciences, University of Padova, 35128, Padua, Italy.
Giulio CabrelleDepartment of Radiology, University Hospital of Padova, 35128, Padova, Italy.
Federica VernuccioDepartment of Radiology, University Hospital of Padova, 35128, Padova, Italy. federicavernuccio@gmail.com.ORCID http://orcid.org/0000-0003-0350-1794
Gaya SpolveratoGeneral Surgery 3, Department of Surgical, Oncological, and Gastroenterological Sciences, University of Padova, 35128, Padua, Italy.
Salvatore PucciarelliGeneral Surgery 3, Department of Surgical, Oncological, and Gastroenterological Sciences, University of Padova, 35128, Padua, Italy.
Emilio QuaiaInstitute of Radiology, Department of Medicine-DIMED, University of Padova, Via Niccolò Giustiniani N.2, 35128, Padua, Italy.
University of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe aim of this study was to determine the accuracy of three state-of-the-art MRI sequences for the detection of extramural venous invasion (EMVI) in locally advanced rectal cancer (LARC) patients after preoperative chemoradiotherapy (pCRT).

methodsThis retrospective study included 103 patients (median age 66 years old [43-84]) surgically treated with pCRT for LARC and submitted to preoperative contrast-enhanced pelvic MRI after pCRT. T2-weighted, DWI, and contrast-enhanced sequences were evaluated by two radiologists with expertise in abdominal imaging, blinded to clinical and histopathological data. Patients were scored according to the probability of EMVI presence on each sequence using a grading score ranging from 0 (no evidence of EMVI) to 4 (strong evidence of EMVI). Results from 0 to 2 were ranked as EMVI negative and from 3 to 4 as EMVI positive. ROC curves were drawn for each technique, using histopathological results as reference standard.

resultsT2-weighted, DWI, and contrast-enhanced sequences demonstrated an area under the ROC curve (AUC) respectively of 0.610 (95% CI: 0.509-0.704), 0.729 (95% CI: 0.633-0.812), and 0.624 (95% CI: 0.523-0.718). The AUC of DWI sequence was significantly higher than that of T2-weighted (p = 0.0494) and contrast-enhanced (p = 0.0315) sequences.

conclusionsDWI is more accurate than T2-weighted and contrast-enhanced sequences for the identification of EMVI following pCRT in LARC patients. CLINICAL RELEVANCE STATEMENT: MRI protocol for restaging locally advanced rectal cancer after preoperative chemoradiotherapy should routinely include DWI due to its higher accuracy for the diagnosis of extramural venous invasion compared to high-resolution T2-weighted and contrast-enhanced T1-weighted sequences. KEY POINTS: • MRI has a moderately high accuracy for the diagnosis of extramural venous invasion in locally advanced rectal cancer after preoperative chemoradiotherapy. • DWI is more accurate than T2-weighted and contrast-enhanced T1-weighted sequences in the detection of extramural venous invasion after preoperative chemoradiotherapy of locally advanced rectal cancer. • DWI should be routinely included in the MRI protocol for restaging locally advanced rectal cancer after preoperative chemoradiotherapy.

Indexed as

Rectal NeoplasmsAgedChemoradiotherapyHumansMagnetic Resonance ImagingNeoadjuvant TherapyNeoplasm InvasivenessRetrospective StudiesDiffusion weighted MRIMagnetic resonance imagingMultiparametric magnetic resonance imagingNeoadjuvant chemoradiation therapyRectal cancer

Identifiers

PMID37115215
OpenAlexW4367320523

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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.