Evidence map›Paper›PMID 39578913›Full record

ArticleBreast cancer research : BCR2024

Quantification of intratumoral heterogeneity using habitat-based MRI radiomics to identify HER2-positive, -low and -zero breast cancers: a multicenter study.

Haoquan Chen, Yulu Liu, Jiaqi Zhao, Xiaoxuan Jia, Fan Chai, Yuan Peng, Nan Hong, Shu Wang, Yi Wang

Erratum issuedAbstract readMulticenter Study
In one paragraph

Article in Breast cancer research : BCR, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
–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

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Observational
  4. Article
  5. MRI-based perfusion-diffusion habitat analysis for characterizing intratumoral heterogeneity in rectal adenocarcinoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Predictions of Oncotype DXBioengineering (Basel, Switzerland) · 2026
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Haoquan Chen *Department of Radiology, Peking University People's Hospital, No. 11, Xizhimen South St, Beijing, 100044, China.
Yulu Liu *Department of Radiology, Peking University People's Hospital, No. 11, Xizhimen South St, Beijing, 100044, China.
Jiaqi ZhaoDepartment of Radiology, Jiangmen Central Hospital, Jiangmen, 529030, China.
Xiaoxuan JiaDepartment of Radiology, Peking University People's Hospital, No. 11, Xizhimen South St, Beijing, 100044, China.
Fan ChaiDepartment of Radiology, Peking University People's Hospital, No. 11, Xizhimen South St, Beijing, 100044, China.
Yuan PengDepartment of Breast Surgery, Peking University People's Hospital, No. 11, Xizhimen South St, Beijing, 100044, China.
Nan HongDepartment of Radiology, Peking University People's Hospital, No. 11, Xizhimen South St, Beijing, 100044, China.
Shu Wang *Department of Breast Surgery, Peking University People's Hospital, No. 11, Xizhimen South St, Beijing, 100044, China. shuwang@pkuph.edu.cn.
Yi Wang *Department of Radiology, Peking University People's Hospital, No. 11, Xizhimen South St, Beijing, 100044, China. wang_yi@hsc.pku.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHuman epidermal growth factor receptor 2-targeted (HER2) therapy with antibody-drug conjugates has proven effective for patients with HER2-low breast cancer. However, intratumoral heterogeneity (ITH) poses a great challenge in identifying HER2-low tumors. ITH signatures were developed by quantifying ITH to differentiate HER2-positive, -low and -zero breast cancers.

methodsThis retrospective study included 614 patients from two institutions. The study was structured into two primary tasks: task 1 was to differentiate between HER2-positive and -negative tumors, followed by task 2 to differentiate HER2-low and -zero tumors. Whole-tumor radiomics features and habitat radiomics features were extracted from MRI to construct the radiomics and ITH signatures. Multivariable logistic regression analysis was used to determine significant independent predictors. A combined model integrating significant clinicopathologic variables, radiomics signature, and ITH signature was developed for task (1) Subsequently, the better-performing model was established using the same approach for task (2) The area under the receiver operating characteristic curve (AUC) was used to assess the performance of each model.

resultsTask 1 comprised 614 patients (training, n = 348; validation, n = 149; and test cohorts, n = 117). Task 2 encompassed 501 patients (training, n = 283; validation, n = 122; and test cohorts, n = 96). For task1, the ITH signature showed outstanding performance, achieving AUCs of 0.81, 0.81, and 0.81 in the training, validation and test cohorts, respectively. The combined model achieved improved performance, with AUCs of 0.83, 0.84 and 0.83 across the three cohorts, respectively. For task2, the ITH signature maintained superior performance, with AUCs of 0.94, 0.93 and 0.84 across the training, validation and test cohorts, respectively. Multivariable logistic regression analysis indicated that none of the clinicopathologic characteristics were retained as predictors associated with odds of HER2-low tumors.

conclusionsOur study developed ITH signatures that quantified ITH using habitat-based MRI radiomics, achieving outstanding performance in differentiating HER2-postive and -negative tumors, and further differentiating HER2-low and -zero breast cancers.

Indexed as

Breast NeoplasmsErb-b2 Receptor Tyrosine KinasesMagnetic Resonance ImagingAdultAgedBiomarkers, TumorFemaleHumansMiddle AgedRadiomicsRetrospective StudiesROC CurveBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesBreast cancerHabitat imagingHER2Intratumoral heterogeneityMagnetic resonance imagingRadiomics

Identifiers

PMID39578913
PMCPMC11583526

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.