Evidence map›Paper›PMID 41896438›Full record

ReviewJournal of gastrointestinal cancer2026

The Role of MRI in Non-Operative Management of Locally Advanced Rectal Cancer.

Eric Hsing Yu Lai, Erin Kennedy, Seng Thipphavong, Kartik Jhaveri

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of gastrointestinal cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Eric Hsing Yu LaiJoint Department of Medical Imaging, University of Toronto, University Health Network and Mount Sinai Hospital, Toronto, ON, Canada.
Erin KennedyDepartment of Surgery, University of Toronto, Mount Sinai Hospital, Toronto, ON, Canada.
Seng ThipphavongJoint Department of Medical Imaging, University of Toronto, University Health Network and Mount Sinai Hospital, Toronto, ON, Canada.
Kartik JhaveriJoint Department of Medical Imaging, University of Toronto, University Health Network and Mount Sinai Hospital, Toronto, ON, Canada. kartik.jhaveri@uhn.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in total neoadjuvant therapy have significantly increased complete response rates, and non-operative management of locally advanced rectal cancer has emerged as a viable alternative to traditional surgical resection for select patients achieving a complete clinical response after neoadjuvant therapy. There has been growing evidence in support of non-operative management, demonstrating promising survival outcomes and organ-preservation benefits. Appropriate patient selection at restaging and early detection of local tumor recurrence are key to positive oncological outcomes. High-resolution MRI, particularly when combined with diffusion-weighted imaging, can offer unmatched evaluation of treatment response, detection of residual disease, and identification of local recurrence. Standardized imaging protocols and emerging tools such as radiomics are further enhancing the precision of tumor assessment. This article provides a comprehensive synthesis of current evidence and reviews the critical role of MRI for the successful implementation of non-operative in clinical practice.

Indexed as

Magnetic Resonance ImagingNeoplasm Recurrence, LocalRectal NeoplasmsWatchful WaitingDiffusion Magnetic Resonance ImagingHumansNeoadjuvant TherapyNeoplasm, ResidualNeoplasm StagingPatient SelectionRadiomicsMagnetic Resonance ImagingRectal CancerWatch-and-wait

Identifiers

What OpenQuestion holds

Textmetadata
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.