Evidence map›Paper›PMID 38902675›Full record

ArticleBMC gastroenterology2024

Comparison of conventional MRI analysis versus MRI-based radiomics to predict the circumferential margin resection involvement of rectal cancer.

Hong Liang, Dongnan Ma, Yanqing Ma, Yuan Hang, Zheng Guan, Yang Zhang, Yuguo Wei, Peng Wang, Ming Zhang

Abstract readComparative Study
In one paragraph

Article in BMC gastroenterology, 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

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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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.

Hong Liang *Department of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, No. 277, Yanta West Road, Xi'an, 710061, China.
Dongnan Ma *Yangming College of Ningbo University, Ningbo, China.
Yanqing MaDepartment of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China.
Yuan HangDepartment of Colorectal Surgery, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China.
Zheng GuanDepartment of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China.
Yang ZhangDepartment of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China.
Yuguo WeiGE Healthcare, Precision Health Institution, Hangzhou, China.
Peng WangDepartment of Radiology, 411 Hospital of Shanghai University, No.15, Dongjiangwan Road, Shanghai, 200080, China. wangpeng050908@163.com.
Ming ZhangDepartment of Medical Imaging, The First Affiliated Hospital of Xi'an Jiaotong University, No. 277, Yanta West Road, Xi'an, 710061, China. zhangming01@xjtu.edu.cn.

Funding

Medical and Health Research Projects of Health Commission of Zhejiang Province 2022KY040National Natural Science Foundation of China 61976075National Natural Science Foundation of China 82071879Zhejiang Provincial Natural Science Foundation of China LTGY24H180017
6 · The paper itself

Abstract

backgroundTo compare the application of conventional MRI analysis and MRI-based radiomics to identify the circumferential resection margin (CRM) status of rectal cancer (RC).

methodsA cohort of 301 RC patients with 66 CRM invloved status and 235 CRM non-involved status were enrolled in this retrospective study between September 2017 and August 2022. Conventional MRI characteristics included gender, age, diameter, distance to anus, MRI-based T/N phase, CEA, and CA 19 - 9, then the relevant logistic model (Logistic-cMRI) was built. MRI-based radiomics of rectal cancer and mesorectal fascia were calculated after volume of interest segmentation, and the logistic model of rectal cancer radiomics (Logistic-rcRadio) and mesorectal fascia radiomics (Logistic-mfRadio) were constructed. And the combined nomogram (nomo-cMRI/rcRadio/mfRadio) containing conventional MRI characteristics, radiomics of rectal cancer and mesorectal fascia was developed. The receiver operator characteristic curve (ROC) was delineated and the area under curve (AUC) was calculated the efficiency of models.

resultsThe AUC of Logistic-cMRI was 0.864 (95%CI, 0.820 to 0.901). The AUC of Logistic-rcRadio was 0.883 (95%CI, 0.832 to 0.928) in the training set and 0.725 (95%CI, 0.616 to 0.826) in the testing set. The AUCs of Logistic-mfRadio was 0.891 (95%CI, 0.838 to 0.936) in the training set and 0.820 (95%CI, 0.725 to 0.905) in the testing set. The AUCs of nomo-cMRI/rcRadio/mfRadio were the highest in both the training set of 0.942 (95%CI, 0.901 to 0.969) and the testing set of 0.909 (95%CI, 0.830 to 0.959).

conclusionMRI-based radiomics of rectal cancer and mesorectal fascia showed similar efficacy in predicting the CRM status of RC. The combined nomogram performed better in assessment.

Indexed as

Magnetic Resonance ImagingMargins of ExcisionRectal NeoplasmsAdultAgedArea Under CurveFasciaFemaleHumansLogistic ModelsMaleMiddle AgedNomogramsRadiomicsRectumRetrospective StudiesMagnetic resonance imagingMesorectal fasciaRadiomicsRectal cancer

Identifiers

PMID38902675
PMCPMC11191295

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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.