ArticleEuropean radiology2022
Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on contrast-enhanced spectral mammography.
Article in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
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Who cites it
72 citing papers in PubMed, 95 citations in OpenAlex.
- AI-assisted digital breast tomosynthesis as a decision-support tool for post-neoadjuvant surgical planning in breast cancer.Langenbeck's archives of surgery · 2026Article
- Development and internal validation of mammography feature-based prognostic models for distant recurrence-free survival of invasive breast cancer in a screening cohort.NPJ breast cancer · 2026Article
- The study of nomogram model based on CT radiomics and clinical features for histological classification of parotid gland tumors.Scientific reports · 2026Article
- CT-based subregional and peritumoral radiomics for predicting pathological T stage of clear cell renal cell carcinoma: an exploratory study of biological mechanisms.Insights into imaging · 2026Article
- Deep-learning-based radiomics of intratumoral and peritumoral CT images to differentiate benign from malignant parotid tumors.American journal of cancer research · 2026Article
- Intra- and peritumoral radiomics for predicting equivocal HER2 status of breast cancer on contrast-enhanced mammography.Frontiers in oncology · 2026Article
- Preoperative prediction of tumor deposits in advanced gastric cancer using intratumoral and peritumoral CT radiomics: development and validation of an ensemble model.Frontiers in oncology · 2026Article
- Achieving single-contrast administration for enhanced chest CT and contrast-enhanced spectral mammography without compromising diagnostic quality: a comparative study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Preoperative stratification of Ki-67 proliferation index in intrahepatic mass-forming cholangiocarcinoma via tumor-halo radiomic phenotyping on biparametric MRI: a multicenter diagnostic model.BMC medical imaging · 2025Article
- Development and validation of a novel disulfidptosis-related gene signature for prediction of survival and immune microenvironment in osteosarcoma by WGCNA analysis.Discover oncology · 2025Article
- Predicting breast cancer response to neoadjuvant chemotherapy with ultrasound-based deep learning radiomics models -- dual-center study.BMC cancer · 2025Article
- 조영증강 유방촬영술: 현재의 임상적 활용과 미래 방향에 대한 종합적 고찰.Journal of the Korean Society of Radiology · 2025Review
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- Machine learning model for predicting tertiary lymphoid structures and treatment response in triple-negative breast cancer.NPJ precision oncology · 2025Article
- Machine learning prediction of pathological complete response to neoadjuvant chemotherapy with peritumoral breast tumor ultrasound radiomics: compare with intratumoral radiomics and clinicopathologic predictors.Breast cancer research and treatment · 2025Article
- Multi-modal radiomics model based on four imaging modalities for predicting pathological complete response to neoadjuvant treatment in breast cancer.BMC cancer · 2025Article
- Development of radiomics-based models on mammograms with mass lesions to predict prognostically relevant characteristics of invasive breast cancer in a screening cohort.British journal of cancer · 2025Article
- Multi-center strain elastography radiomics for breast cancer diagnosis: integrating intratumoral and peritumoral regions.Discover oncology · 2025Article
- A multimodal and fully automated system for prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer.Science advances · 2025Article
12 more citing papers are in PubMed but not listed here.
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveTo investigative the performance of intratumoral and peritumoral radiomics based on contrast-enhanced spectral mammography (CESM) to preoperatively predict the effect of the neoadjuvant chemotherapy (NAC) of breast cancers. MATERIALS AND
methodsA total of 118 patients with breast cancer who underwent preoperative CESM and NAC from July 2017 to June 2020 were retrospectively analyzed, and the patients were grouped into training (n = 81) and test sets (n = 37) according to the CESM examination time. NAC effect for each patient was assessed by pathology. Intratumoral and peritumoral radiomics features were extracted from CESM images, and feature selection was performed through the Mann-Whitney U test and least absolute shrinkage and selection operator regression (LASSO). Five radiomics signatures based on intratumoral regions, 5-mm peritumoral regions, 10-mm peritumoral regions, intratumoral regions + 5-mm peritumoral regions, and intratumoral regions + 10-mm peritumoral regions were calculated through a linear combination of selected features weighted by their respective coefficients. The prediction performance of radiomics signatures was assessed by the area under the receiver operator characteristic (ROC) curve, the precision-recall (P-R) curve, the calibration curve, and decision curve analysis (DCA).
resultsTen radiomics features were selected to establish the radiomics signature of intratumoral regions + 5-mm peritumoral regions, which yielded a maximum AUC of 0.85 (95% CI, 0.72-0.98) in the test set. The calibration curves, P-R curves, and DCA showed favorable predictive performance of the five radiomics signatures.
conclusionThe intratumoral and peritumoral radiomics based on CESM exhibited potential for predicting the NAC effect in breast cancer, which could guide treatment decisions. KEY POINTS: • The intratumoral and peritumoral CESM-based radiomics signatures show good performance in predicting the NAC effect in breast cancer.
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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.