Evidence map›Paper›PMID 33282722›Full record

ArticleFrontiers in oncology2020

Radiomics-Assisted Presurgical Prediction for Surgical Portal Vein-Superior Mesenteric Vein Invasion in Pancreatic Ductal Adenocarcinoma.

Fangming Chen, Yongping Zhou, Xiumin Qi, Rui Zhang, Xin Gao, Wei Xia, Lei Zhang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

8 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
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  8. The impact of radiomics in diagnosis and staging of pancreatic cancer.Therapeutic advances in gastrointestinal endoscopy
    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

7 authors at 4 institutions in 1 country.

Fangming ChenDepartment of Radiology, The Affiliated Wuxi No.2 People's Hospital of Nanjing Medical University, Wuxi, China.
Yongping ZhouDepartment of Hepatobiliary Surgery, The Affiliated Wuxi No.2 People's Hospital of Nanjing Medical University, Wuxi, China.
Xiumin QiDepartment of Pathology, The Affiliated Wuxi No.2 People's Hospital of Nanjing Medical University, Wuxi, China.
Rui ZhangSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.
Xin GaoSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.
Wei XiaSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.
Lei ZhangDepartment of Radiology, The Affiliated Wuxi No.2 People's Hospital of Nanjing Medical University, Wuxi, China.
Nanjing Medical University · CNSuzhou Institute of Biomedical Engineering and Technology · CNChinese Academy of Sciences · CNWuxi No.2 People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo develop a radiomics signature for predicting surgical portal vein-superior mesenteric vein (PV-SMV) in patients with pancreatic ductal adenocarcinoma (PDAC) and measure the effect of providing the predictions of radiomics signature to radiologists with different diagnostic experiences during imaging interpretation.

methodsBetween February 2008 and June 2020, 146 patients with PDAC in pancreatic head or uncinate process from two institutions were retrospectively included and randomly split into a training (n = 88) and a validation (n =58) cohort. Intraoperative vascular exploration findings were used to identify surgical PV-SMV invasion. Radiomics features were extracted from the portal venous phase CT images. Radiomics signature was built with a linear elastic-net regression model. Area under receiver operating characteristic curve (AUC) of the radiomics signature was calculated. A senior and a junior radiologist independently review CT scans and made the diagnosis for PV-SMV invasion both with and without radiomics score (Radscore) assistance. A 2-sided Pearson's chi-squared test was conducted to evaluate whether there was a difference in sensitivity, specificity, and accuracy between the radiomics signature and the unassisted radiologists. To assess the incremental value of providing Radscore predictions to the radiologists, we compared the performance between unassisted evaluation and Radscore-assisted evaluation by using the McNemar test.

resultsNumbers of patients identified as presence of surgical PV-SMV invasion were 33 (37.5%) and 19 (32.8%) in the training and validation cohort, respectively. The radiomics signature achieved an AUC of 0.848 (95% confidence interval, 0.724-0.971) in the validation cohort and had a comparable sensitivity, specificity, and accuracy as the senior radiologist in predicting PV-SMV invasion (all

conclusionsThe radiomics signature can predict surgical PV-SMV invasion in patients with PDAC and may have incremental value to the diagnostic performance of radiologists during imaging interpretation.

Indexed as

neoplasm invasionpancreatic ductal adenocarcinomaspresurgical evaluationradiomicstomographyX-ray computed

Identifiers

PMID33282722
PMCPMC7706539
OpenAlexW3098585559

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LicenceCC BY
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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.