Evidence map›Paper›PMID 42799749›Full record

ReviewAbdominal radiology (New York)2026

Lateral pelvic lymph nodes in rectal cancer: a narrative review.

Daniel Linhares Cardoso, Cesar Gabriel Rocha da Costa Paloschi, Emanuela Mendes Junqueira de Barros, Anna Gabriela Dos Santos Souza, João Miranda, Zhaohui Jin, Yasamin Sharifzadeh, Ryan W Kendziora, Eric J Dozois, Natally Horvat

Abstract readReview
PubMed Publisher
In one paragraph

Review in Abdominal radiology (New York), 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

10 authors.

Daniel Linhares CardosoDepartment of Radiology, Hospital Sírio-Libanês, São Paulo, Brazil. daniellinharescardoso@gmail.com.
Cesar Gabriel Rocha da Costa PaloschiDepartment of Radiology, Hospital Sírio-Libanês, São Paulo, Brazil.
Emanuela Mendes Junqueira de BarrosDepartment of Radiology, Hospital Sírio-Libanês, São Paulo, Brazil.
Anna Gabriela Dos Santos SouzaDepartment of Radiology, Universidade Federal do Paraná, Curitiba, Brazil.
João MirandaDepartment of Radiology, Mayo Clinic, Rochester, USA.
Zhaohui JinDepartment of Oncology, Mayo Clinic, Rochester, USA.
Yasamin SharifzadehDepartment of Radiation Oncology, Mayo Clinic, Rochester, USA.ORCID https://orcid.org/0000-0003-3269-3107
Ryan W KendzioraDepartment of Pathology, Mayo Clinic, Rochester, USA.
Eric J DozoisDepartment of Surgery, Mayo Clinic, Rochester, USA.
Natally HorvatDepartment of Radiology, Mayo Clinic, Rochester, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lateral pelvic lymph node (LPLN) involvement represents a critical determinant of oncologic outcomes in rectal cancer, directly influencing the risks of local recurrence, distant metastasis, and overall survival. High-resolution rectal magnetic resonance imaging (MRI) is the modality of choice for both initial staging and post-treatment restaging. A comprehensive approach integrating nodal size, morphology and primary tumor characteristics and treatment response is indicated for accurate evaluation. The optimal management of LPLNs differs between Eastern and Western practices, although a convergence toward selective, risk-adapted strategies is increasingly recognized. Familiarity with the imaging anatomy of the lateral pelvis and current high-risk criteria are essential for radiologists involved in the multidisciplinary care of rectal cancer patients.

Indexed as

Lymph nodesMagnetic resonance imagingNeoadjuvant therapyRadiotherapyRectal neoplasm

Identifiers

PMID42799749

What OpenQuestion holds

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Registered trials

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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.