Evidence map›Paper›PMID 38992094›Full record

ArticleScientific reports2024

Multiparametric MRI-based radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer.

Rania M Mohamed, Bikash Panthi, Beatriz E Adrada, Medine Boge, Rosalind P Candelaria, Huiqin Chen, Mary S Guirguis, Kelly K Hunt, Lei Huo, Ken-Pin Hwang and 19 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Application of Machine Learning to Breast MR Imaging.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    Review
  7. 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

29 authors.

Rania M MohamedDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA.
Bikash PanthiDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Beatriz E AdradaDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA.
Medine BogeDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA.
Rosalind P CandelariaDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA.
Huiqin ChenDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Mary S GuirguisDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA.
Kelly K HuntDepartment of Breast Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Lei HuoDepartment of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Ken-Pin HwangDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Anil KorkutDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Jennifer K LittonDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Tanya W MoseleyDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA.
Sanaz PashapoorDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA.
Miral M PatelDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA.
Brandy ReedDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Marion E ScogginsDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA.
Jong Bum SonDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Alastair ThompsonDepartment of Surgery, Baylor College of Medicine, Houston, TX, USA.
Debu TripathyDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Vicente ValeroDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Peng WeiDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Jason WhiteDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Gary J WhitmanDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA.
Zhan XuDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Wei YangDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA.
Clinton YamDepartment of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Jingfei MaDepartment of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Gaiane M RauchDepartment of Breast Imaging, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, # 1473, Houston, TX, 77030, USA. GMRauch@mdanderson.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) is often treated with neoadjuvant systemic therapy (NAST). We investigated if radiomic models based on multiparametric Magnetic Resonance Imaging (MRI) obtained early during NAST predict pathologic complete response (pCR). We included 163 patients with stage I-III TNBC with multiparametric MRI at baseline and after 2 (C2) and 4 cycles of NAST. Seventy-eight patients (48%) had pCR, and 85 (52%) had non-pCR. Thirty-six multivariate models combining radiomic features from dynamic contrast-enhanced MRI and diffusion-weighted imaging had an area under the receiver operating characteristics curve (AUC) > 0.7. The top-performing model combined 35 radiomic features of relative difference between C2 and baseline; had an AUC = 0.905 in the training and AUC = 0.802 in the testing set. There was high inter-reader agreement and very similar AUC values of the pCR prediction models for the 2 readers. Our data supports multiparametric MRI-based radiomic models for early prediction of NAST response in TNBC.

Indexed as

Multiparametric Magnetic Resonance ImagingNeoadjuvant TherapyTriple Negative Breast NeoplasmsAdultAgedFemaleHumansMagnetic Resonance ImagingMiddle AgedRadiomicsROC CurveTreatment OutcomeDiffusion-weighted imagingDynamic contrast-enhanced breast MRINeoadjuvant systemic therapyRadiomic featuresTreatment responseTriple-negative breast cancer

Identifiers

PMID38992094
PMCPMC11239818

What OpenQuestion holds

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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.