Evidence map›Paper›PMID 37839066›Full record

ArticleAbdominal radiology (New York)2024

T1 mapping in evaluation of clinicopathologic factors for rectal adenocarcinoma.

Juan Li, Peisi Kou, Liangjie Lin, Yunfei Xiao, Hongrui Jin, Yong Zhang, Jingliang Cheng

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Article in Abdominal radiology (New York), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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

7 authors.

Juan LiDepartment of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China. 15838213628@126.com.ORCID 0000-0001-5770-8788
Peisi KouDepartment of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China.
Liangjie LinAdvanced Technical Support, Philips Healthcare, Beijing, China.
Yunfei XiaoDepartment of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China.
Hongrui JinDepartment of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China.
Yong ZhangDepartment of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China.
Jingliang ChengDepartment of MRI, The First Affiliated Hospital of Zhengzhou University, No. 1, Jianshe Dong Road, Zhengzhou, 450052, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveT1 mapping has been increasingly applied in the study of tumor. The purpose of this study was to evaluate the value of T1 mapping in evaluating clinicopathologic factors for rectal adenocarcinoma. MATERIALS AND

methodsEighty-six patients with rectal adenocarcinoma confirmed by surgical pathology who underwent preoperative pelvic MRI were retrospectively analyzed. High-resolution T

resultsT1 value showed significant difference between high- and low-grade tumors ([1531.5 ± 84.7 ms] vs. [1437.1 ± 80.3 ms], P < 0.001). T1 value was significant higher in positive than in negative perineural invasion ([1495.7 ± 89.2 ms] vs. [1449.4 ± 88.8 ms], P < 0.05). No significant difference of T1 or ADC was observed in different CEA, CA199, T stage, N stage, lymphovascular invasions, extramural vascular invasion (EMVI), and circumferential resection margin (CRM) (P > 0.05). The AUC under ROC curve of T1 value were 0.796 in distinguishing high- from low-grade rectal adenocarcinoma. The AUC of T1 value in distinguishing perineural invasion was 0.637.

conclusionT1 value was helpful in assessing pathologic grade and perineural invasion correlated with rectal cancer.

Indexed as

AdenocarcinomaRectal NeoplasmsDiffusion Magnetic Resonance ImagingHumansMagnetic Resonance ImagingRetrospective StudiesClinicopathologic factorsMagnetic resonance imagingRectal cancerT1 mapping

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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.