Evidence map›Paper›PMID 33180166›Full record

ArticleEuropean radiology2021

Multiparametric MRI-based radiomics signature for preoperative estimation of tumor-stroma ratio in rectal cancer.

Chongpeng Cai, Tingdan Hu, Jing Gong, Dan Huang, Fangqi Liu, Caixia Fu, Tong Tong

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In one paragraph

Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
2.0field-weighted citation impact, top 11% 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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 40 citations in OpenAlex.

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  16. Ultra-high b-Value DWI in predicting progression risk of locally advanced rectal cancer: a comparative study with routine DWI.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023
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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 at 3 institutions in 1 country.

Chongpeng Cai *Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
Tingdan Hu *Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
Jing GongDepartment of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
Dan HuangDepartment of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
Fangqi LiuDepartment of Colorectal Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
Caixia FuMR Applications Development, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China.
Tong TongDepartment of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China. t983352@126.com.ORCID http://orcid.org/0000-0002-9180-8181
Shanghai Medical College of Fudan University · CNFudan University Shanghai Cancer Center · CNSiemens (China) · CN

Funding

National Natural Science Foundation of China 81971687Shanghai Sailing program 19YF1409900
6 · The paper itself

Abstract

objectiveTo determine whether a radiomics signature (rad-score) outperforms ADC in TSR estimation by developing a radiomics biomarker for preoperative TSR diagnosis in rectal cancer.

methodsThis study included 149 patients (119 and 30 in the training and validation cohorts, respectively). All patients underwent T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted imaging. A rad-score was generated using the least absolute shrinkage and selection operator (LASSO) algorithm and stepwise multivariate logistic regression. Meanwhile, the mean ADCs were calculated from ADC maps. For both the mean ADC and rad-score, binary logistic regression and Spearman correlation coefficients were used to determine associations with the TSR, and the area under the receiver operating characteristic (ROC) curve was used to assess the diagnostic performance. The reliability of the rad-score was quantified by comparing the imaging-estimated TSR with the actual TSR of each patient.

resultsBoth the mean ADC and rad-score were positively correlated with the TSR in the training cohort (mean ADC: p < 0.001, r = 0.566; rad-score: p < 0.001, r = 0.559) and validation cohort (mean ADC: p < 0.001, r = 0.671; rad-score: p = 0.002, r = 0.536). The rad-score, with AUCs of 0.917 (95% CI 0.869-0.965) and 0.787 (95% CI 0.602-0.972) in the training and validation cohorts, respectively, outperformed the mean ADC (training cohort: AUC = 0.776, 95% CI 0.693-0.859; validation cohort: AUC = 0.764, 95% CI 0.592-0.936) in TSR estimation.

conclusionThe ADC possesses potential diagnostic value for TSR estimation in rectal cancer, and the rad-score shows increased diagnostic value over the ADC and may be a promising supplemental tool for patient stratification and informing decision-making. KEY POINTS: • Tumor-stroma ratio has been verified as an independent prognostic factor for various solid tumors including rectal cancer. • The ADC and multiparametric MRI-based radiomics features were significantly and positively correlated with the tumor-stroma ratio in rectal cancer. • The radiomics signature outperformed the ADC in discriminating TSR in rectal cancer.

Indexed as

Multiparametric Magnetic Resonance ImagingRectal NeoplasmsDiffusion Magnetic Resonance ImagingHumansReproducibility of ResultsROC CurveApparent diffusion coefficientMagnetic resonance imagingRectal neoplasmsTumor microenvironment

Identifiers

PMID33180166
OpenAlexW3100102076

What OpenQuestion holds

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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.