Evidence map›Paper›PMID 33638019›Full record

ArticleEuropean radiology2021

Radiomics signature on dynamic contrast-enhanced MR images: a potential imaging biomarker for prediction of microvascular invasion in mass-forming intrahepatic cholangiocarcinoma.

Yang Zhou, Guofeng Zhou, Jiulou Zhang, Chen Xu, Xiaolin Wang, Pengju Xu

Abstract read
PubMed Publisher
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 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
12.1field-weighted citation impact, top 1% 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

44 citing papers in PubMed, 72 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. CT delta-radiomics predicts the risks of blood transfusion and massive bleeding during spinal tumor surgery.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

6 authors at 3 institutions in 1 country.

Yang Zhou *Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
Guofeng Zhou *Shanghai Institute of Medical Imaging, No.180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
Jiulou ZhangDepartment of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China.
Chen XuDepartment of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Xiaolin WangShanghai Institute of Medical Imaging, No.180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
Pengju XuShanghai Institute of Medical Imaging, No.180 Fenglin Road, Xuhui District, Shanghai, 200032, China. xpjbfc@163.com.ORCID http://orcid.org/0000-0002-0832-083X
Sun Yat-sen University · CNShanghai Institute of Hematology · CNJiangsu Province Hospital · CN

Funding

Shanghai Municipal Key Clinical Specialty W2019-018
6 · The paper itself

Abstract

objectiveTo develop a radiomics signature based on dynamic contrast-enhanced (DCE) MR images for preoperative prediction of microvascular invasion (MVI) in patients with mass-forming intrahepatic cholangiocarcinoma (IMCC).

methodsOne hundred twenty-six patients with surgically resected single IMCC (34 MVI-positive and 92 MVI-negative) were enrolled and allocated to training and validation cohorts (7:3 ratio). Findings of clinical characteristics and MR features were analyzed. A radiomics signature was built on the basis of reproducible features by using the least absolute shrinkage and selection operator (LASSO) regression algorithm in the training cohort. The prediction performance of radiomics signature was evaluated by receiver operating characteristics curve (ROC) analysis. Internal validation was performed on an independent cohort containing 38 patients.

resultsLarger tumor size and higher radiomics score were positively correlated with MVI in both training cohort (p < 0.001, < 0.001, respectively) and validation cohort (p = 0.008, 0.001, respectively). The radiomics signature, consisting of seven wavelet features, showed optimal prediction performance in both training (AUC = 0.873) and validation cohorts (AUC = 0.850).

conclusionA radiomics signature derived from DCE-MRI of the liver can be a reliable imaging biomarker for predicting MVI of IMCC, which could aid in tailoring treatment strategies. KEY POINTS: • The radiomics signature based on dynamic contrast-enhanced magnetic resonance imaging can be a useful tool to preoperatively predict MVI of IMCC. • Larger tumor size is positively correlated with MVI of IMCC.

Indexed as

Bile Duct NeoplasmsCholangiocarcinomaLiver NeoplasmsBiomarkersHumansMagnetic Resonance ImagingRetrospective StudiesBiomarkersDiagnosisIntrahepatic cholangiocarcinomaMagnetic resonance imagingRadiomics

Identifiers

PMID33638019
OpenAlexW3131197354

What OpenQuestion holds

Textmetadata
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.