ArticleEuropean journal of nuclear medicine and molecular imaging2019
PET/CT radiomics in breast cancer: promising tool for prediction of pathological response to neoadjuvant chemotherapy.
Article in European journal of nuclear medicine and molecular imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 94 papers, 2 of them syntheses that pooled it.
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Who cites it
94 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence-assisted PET imaging for predicting neoadjuvant chemotherapy response in breast cancer: a systematic review and meta-analysis.European journal of nuclear medicine and molecular imaging · 2026Pooled it
- PET-Derived Radiomics and Artificial Intelligence in Breast Cancer: A Systematic Review.International journal of molecular sciences · 2022Pooled it
- Clinicopathological and molecular predictors of [European journal of nuclear medicine and molecular imaging · 2024Trial
- Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer.European journal of nuclear medicine and molecular imaging · 2022Trial
- PET/CT-based quantification of intratumoral heterogeneity for predicting pathological complete response in breast cancer patients treated with neoadjuvant chemotherapy: A multicentre study.European journal of nuclear medicine and molecular imaging · 2026Article
- Novel 4D radiomics applied to dynamic FES PET images to improve prediction of breast cancer response to ER-targeted therapy.European journal of nuclear medicine and molecular imaging · 2026Article
- Fusion model integrating multi-sequence MRI radiomics and habitat imaging for predicting pathological complete response in breast cancer treated with neoadjuvant therapy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
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- Predictive risk factors of recurrence in breast cancer after neoadjuvant treatment: the NEORISK study.Future oncology (London, England) · 2025Article
- Breast Cancer: Habitat imaging based on intravoxel incoherent motion for predicting pathologic complete response to neoadjuvant chemotherapy.Medical physics · 2025Article
- Identification of HER2-over-expression, HER2-low-expression, and HER2-zero-expression statuses in breast cancer based onCancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- A multimodal and fully automated system for prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer.Science advances · 2025Article
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- Integrating artificial intelligence into radiological cancer imaging: from diagnosis and treatment response to prognosis.Cancer biology & medicine · 2025Article
- New progress in imaging diagnosis and immunotherapy of breast cancer.Frontiers in immunology · 2025Review
- The use of ADC histogram analysis in the diagnosis and determination of aggressiveness of peripheral zone prostate cancer.Polish journal of radiology · 2025Article
- Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based onJournal of cancer research and clinical oncology · 2024Article
- Radiomics in breast cancer: Current advances and future directions.Cell reports. Medicine · 2024Review
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34 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo assess the role of radiomics parameters in predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer.
methodsSeventy-nine patients who had undergone pretreatment staging
resultsNineteen patients (24%) had pCR to NAC. Different models were generated on complete information and imputed datasets, using univariable and multivariable logistic regression and least absolute shrinkage and selection operator (lasso) regression. All models could predict pCR to NAC, with area under the curve values ranging from 0.70 to 0.73. All models agreed that tumor molecular subtype is the primary predictor of the primary endpoint.
conclusionsOur models predicted that patients with subtype 2 and subtype 3 (HER2+ and triple negative, respectively) are more likely to have a pCR to NAC than those with subtype 1 (luminal). The association between PET imaging features and pCR suggested that PET imaging features could be considered as potential predictors of pCR in locally advanced breast cancer patients.
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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.