Development of an Intra- and Peritumoral Radiomics Nomogram Using Digital Breast Tomosynthesis for Preoperative Assessment of Ki-67 Expression in Invasive Breast Cancer

Academic Radiology, Год журнала: 2025, Номер unknown

Опубликована: Фев. 1, 2025

Язык: Английский

---

Revolutionizing HER-2 assessment: multidimensional radiomics in breast cancer diagnosis

BMC Cancer, Год журнала: 2025, Номер 25(1)

Опубликована: Фев. 14, 2025

Язык: Английский

---

Radiomics Integration of Mammography and DCE-MRI for Predicting Molecular Subtypes in Breast Cancer Patients

Breast Cancer Targets and Therapy, Год журнала: 2025, Номер Volume 17, С. 187 - 200

Опубликована: Фев. 1, 2025

Accurate identification of the molecular subtypes breast cancer is essential for effective treatment selection and prognosis prediction. This study aimed to evaluate diagnostic performance a radiomics model, which integrates mammography dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting cancer. We retrospectively included 462 female patients with pathologically confirmed cancer, including 53 cases triple-negative, 94 HER2 overexpression, 95 luminal A, 215 B Radiomics analysis was performed using FAE software, wherein radiomic features were examined about hormone receptor status. The model evaluated area under receiver operating characteristic curve (AUC) accuracy. In multivariate analysis, only independent predictive factors subtypes. that incorporates multimodal fusion from DCE-MRI images exhibited superior overall compared either modality independently. AUC values (or accuracies) six pairings as follows: 0.648 (0.627) A vs B, 0.819 (0.793) 0.725 (0.696) triple-negative subtype, 0.644 (0.560) 0.625 (0.636) 0.598 (0.500) subtype overexpression. radionics utilizing combined showed high distinguishing It significance accurately predict determine strategy by classification.

Язык: Английский

---

Evaluating dynamic contrast-enhanced MRI for differentiating HER2-zero, HER2-low, and HER2-positive breast cancers in patients undergoing neoadjuvant chemotherapy

European journal of medical research, Год журнала: 2025, Номер 30(1)

Опубликована: Фев. 25, 2025

To quantitatively assess the differences in parameters of dynamic contrast-enhanced MRI (DCE–MRI) HER2-zero, HER2-low, or HER2-positive tumors, and to build optimal model for early prediction HER2-low breast cancer (BC). Clinical DCE–MRI data from 220 BC patients receiving neoadjuvant chemotherapy (NACT) were retrospectively analyzed. Quantitative semi-quantitative compared groups before after NACT. Empirical models developed predict using logistic regression analysis receiver operating characteristic (ROC) analysis. Patients have a lower pCR rate with HER2-zero (17.9% vs. 10.4% 29.5%, p < 0.001), predominantly HR (hormone receptor) negative group (22.2% 7.7% 40.5%, 0.001). Before NACT, exhibited higher Kep, Ktrans, Washin, TME intratumoral perfusion characteristics, Kep peritumoral region patients. Notably, changes (Kep) (Ktrans, Washin) more pronounced group. The ROC curves (AUC) pre-NACT intratumoral, peritumoral, combined 0.675(95% CI 0.600–0.750), 0.661(95% 0.585–0.738), 0.731(95% 0.660–0.802). pre-and-post-NACT further improved predictive performance accordingly, AUCs 0.764 (95% 0.637–0.865), 0.795 0.711–0.878), 0.850 0.774–0.926). study revealed heterogeneity between different HER2 statuses identified best imaging as non-invasive tool BC, which can help pre-treatment clinical decision-making.

Язык: Английский

---

Intra- and peri-tumoral radiomics based on dynamic contrast-enhanced MRI for prediction of benign disease in BI-RADS 4 breast lesions: a multicentre study

Radiation Oncology, Год журнала: 2025, Номер 20(1)

Опубликована: Фев. 28, 2025

The study aimed to create a radiomics model based on breast intra- and peri-tumoral regions in dynamic contrast-enhanced (DCE) MRI distinguish benign from malignant lesions of Breast Imaging Reporting Data System (BI-RADS) 4. A total 516 patients Hospital 1 were assigned the training cohort. Then, 146 52 enrolled 2 3, respectively, as internal external test Seven classification models built, using features extracted regions. Diagnostic performance was evaluated by receiver operating characteristics (ROC) analysis compared DeLong test. Subgroup performed after stratifying all enhancement pattern subdivision BI-RADS Comb2 model, built with mm intra-tumoral region, demonstrated best AUCs 0.828 0.844 cohort, respectively. robust both mass non-mass (NME) lesions. At three exploratory cutoff values ROC curve, identified 9.1% (sensitivity C1 ≥ 98%), 27.3% C2 95%) 36.4% C3 90%) Applying cohort showed potential lower number unnecessary biopsies An MRI-based region combined reduce false-positive diagnoses may avoid low underestimate risk.

Язык: Английский

---

Intratumoral and peritumoral ultrasound-based radiomics for preoperative prediction of HER2-low breast cancer: a multicenter retrospective study

Insights into Imaging, Год журнала: 2025, Номер 16(1)

Опубликована: Март 7, 2025

Recent advances in human epidermal growth factor receptor 2 (HER2)-targeted therapies have opened up new therapeutic options for HER2-low cancers. This study aimed to establish an ultrasound-based radiomics model identify three different HER2 states noninvasively. Between May 2018 and December 2023, a total of 1257 invasive breast cancer patients were enrolled from hospitals. The status was divided into classes: positive, low, zero. Four peritumoral regions interest (ROI) auto-generated by dilating the manually segmented intratumoral ROI thicknesses 5 mm, 10 15 20 mm. After image preprocessing, 4720 features extracted each every patient. least absolute shrinkage selection operator LightBoost algorithm utilized construct single- multi-region signatures (RS). A clinical-radiomics combined developed integrating discriminative clinical-sonographic factors with optimal RS. data stitching strategy used build patient-level models. Shapley additive explanations (SHAP) approach explain contribution internal prediction. RS constructed 12 tumor 9 peritumoral-15mm features. Age, size, seven qualitative ultrasound retained In training, validation, test cohorts, showed best discrimination ability macro-AUCs 0.988 (95% CI: 0.983-0.992), 0.915 0.851-0.965), 0.862 0.820-0.899), respectively. built robust interpretable evaluate classes based on images. Ultrasound-based method can noninvasively HER2, which may guide treatment decisions implementation personalized HER2-targeted patients. Determination affect cancer. discriminate statuses. Our assist providing recommendations novel therapies.

Язык: Английский

---

The value of intratumoral and peritumoral radiomics features based on multiparametric MRI for predicting molecular staging of breast cancer

Frontiers in Oncology, Год журнала: 2025, Номер 15

Опубликована: Март 11, 2025

Purpose A model for preoperative prediction of molecular subtypes breast cancer using tumor and peritumor radiomics features from multiple magnetic resonance imaging (mMRI) sequences, combined with semantic features. Materials methods total 254 female patients pathogically confirmed were enrolled in this study. Preoperative mMRI, including T2-weighted (T2WI), diffusion-weighted (DWI), dynamic contrast-enhanced MRI (DCE) covered the entire breast. To analyze different identify independent predictive risk factors. Thirty-three binary classification models established based on radiomic sequences peritumoral ranges. The best was selected by comparing performance above models. At same time, sequence extent extracted target features, score calculated, factors predicted. Finally, a nomogram Triple-Negative Breast Cancer (TNBC), Hormone Receptor (HR) positive HER2 negative (HR+/HER2−), HER2+ staging types cancer. Results Tumor length, edge enhancement, edema predicting DCE margin 6 mm. AUC optimal sequence(DCE) range (6 mm) 0.910, 0.909, 0.845, respectively. Conclusion predictors intratumoral scores can be used as an auxiliary diagnostic tool subtype

Язык: Английский

---

The qualitative and quantitative characteristics of serous endometrial carcinoma on MRI: applying a novel nomogram for predicting an aggressive histological type

Frontiers in Oncology, Год журнала: 2025, Номер 15

Опубликована: Март 14, 2025

To comprehensively describe MRI characteristics of serous endometrial carcinoma (SEC) and distinguish SEC from endometrioid (EEC). We retrospectively recruited 62 patients a tertiary center with pathologically proven cancers (37 25 EEC) as the training set. image interpretation was blindly interpreted by two experienced radiologists consensus reading. Both qualitative quantitative on were recorded case case. Histological findings retrieved hospital information system. Fifty-four samples (27 27 external treated testing The had no statistical difference between EEC groups in more often invaded deep myometrium than (p = 0.03). signal intensity (SI)T2Ratio, SIcontrastRatio, LesionareaRatio, VolumeareaRatio group 1.35 ± 0.36, 0.77 0.18, 0.25 0.24, 0.22 0.26, respectively. SIT2Ratio, showed statistically significant differences < 0.05). highest discriminative index for distinguishing SIcontrastRatio an area under curve (AUC) 0.7533 (95% CI: 0.627-0.878). A predictive nomogram achieved AUC 0.814 0.614-0.968), sensitivity 1.0, specificity 0.60 This study developed validated model to predict based clinical features, which can be used EEC.

Язык: Английский

---

DCE-MRI radiomics of primary breast lesions combined with ipsilateral axillary lymph nodes for predicting efficacy of NAT

BMC Cancer, Год журнала: 2025, Номер 25(1)

Опубликована: Апрель 1, 2025

This study aimed to assess the predictive value of radiomic analysis derived from primary lesions and ipsilateral axillary suspicious lymph nodes (SLN) on dynamic contrast-enhanced MRI (DCE-MRI) for evaluating response neoadjuvant therapy (NAT) in early high-risk advanced breast cancer (BC) patients. A retrospective was conducted 222 BC patients (192 Center I 30 II) who underwent NAT. Radiomic features were extracted lesion (intra- peritumoral regions) SLN develop signatures (RS-primary, RS-SLN). An integrated signature (RS-Com) combined both regions. Feature selection performed using correlation analysis, Mann-Whitney U test, least absolute shrinkage operator (LASSO) regression. diagnostic nomogram constructed by integrating RS-Com with key clinical factors. Model performance evaluated receiver operating characteristic (ROC) decision curve (DCA). demonstrated superior compared RS-primary RS-SLN alone. The DeLong test confirmed that SLNs provide supplementary information lesion. Among factors, N staging HER2 status significant contributors. nomogram, RS-Com, staging, status, achieved highest training (AUC: 0.926), validation 0.868), 0.839) cohorts, outperforming models offer valuable predicting NAT proposed incorporating radiomics provides a robust tool individualized treatment planning.

Язык: Английский

---

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, Год журнала: 2025, Номер unknown

Опубликована: Апрель 6, 2025

Язык: Английский

---