In most women with invasive breast cancer, standard MRI without an additional comprehensive axillary scan is sufficient to exclude high-level or advanced axillary lymph node metastasis. Background In the post–American College of Surgeons Oncology Group Z0011 trial era, radiologists have increasingly focused on excluding high-level or advanced axillary lymph node metastasis (ALNM) ...

Background/Objectives: To develop a DL-based model predicting recurrence risk in HER2-low breast cancer patients and to compare performance of the MRI-alone, clinicopathologic-alone, and combined models. Methods: We analyzed 453 patients with HER2-low breast cancer who underwent surgery and preoperative breast MRI between May 2018 and April 2022. Patients were randomly assigned to either a training cohort (n = 331) or a test cohort (n = 122). Imaging features were extracted from DCE-MRI and ADC maps, with regions of interest manually annotated by radiologists. Clinicopathological features included tumor size, nodal status, histological grade, and hormone receptor status. Three DL prediction models were developed: a CNN-based MRI-alone model, a clinicopathologic-alone model based on a multi-layer perceptron (MLP) and a combined model integrating CNN-extracted MRI features with clinicopathological data via MLP. Model performance was evaluated using AUC, sensitivity, specificity, and F1-score. Results: The MRI-alone model achieved an AUC of 0.69 (95% CI, 0.68–0.69), with a sensitivity of 37.6% (95% CI, 35.7–39.4), specificity of 87.5% (95% CI, 86.9–88.2), and F1-score of 0.34 (95% CI, 0.33–0.35). The clinicopathologic-alone model yielded the highest AUC of 0.92 (95% CI, 0.92–0.92) and sensitivity of 93.6% (95% CI, 93.4–93.8), but showed the lowest specificity (72.3%, 95% CI, 71.8–72.8) and F1-score of 0.50 (95% CI, 0.49–0.50). The combined model demonstrated the most balanced performance, achieving an AUC of 0.90 (95% CI, 0.89–0.91), sensitivity of 80.0% (95% CI, 78.7–81.3), specificity of 83.2% (95% CI: 82.7–83.6), and the highest F1-score of 0.55 (95% CI, 0.54–0.57). Conclusions: The DL-based model combining MRI and clinicopathological features showed superior performance in predicting recurrence in HER2-low breast cancer. This multimodal approach offers a framework for individualized risk assessment and may aid in refining follow-up strategies.

Byon JH, et al. Korean J Radiol. 2023 Aug;24(8):739-751. https://doi.org/10.3348/kjr.2022.0846

Byon JH, et al. J Breast Cancer. 2021 Apr;24:e21. https://doi.org/10.4048/jbc.2021.24.e21

The cosmetic outcomes of breast-conserving surgery (BCS) have recently gained increasing attention, and surgeons are exploring the use of the acellular dermal matrix (ADM) as a safe and effective method of breast reconstruction. This study evaluated the clinical progress of patients with breast cancer following the application of sheet-type ADM for breast reconstruction after BCS. This retrospective study included 137 patients who underwent BCS using ADM at a single center between October 2019 and October 2021. During surgery, sheet-type ADM was folded and inserted into the excised defects. Complications and cancer recurrence were evaluated during surveillance follow-up until December 2023, and maintenance of the inserted ADM was quantitatively compared using volume analysis of the first and last follow-up computed tomography (CT). Of the 137 evaluated patients, 16 (11.6%) had minor complications, and 17 (12.4%) underwent biopsy during the surveillance period. One patient was diagnosed with recurrence. ADM volume was measured in 55 patients. The mean volume reduction between the first and last CT scans was 1.81 ± 2.06 cm³ (a decrease of 17.42 ± 19.82%), which was statistically significant (p < 0.001). The insertion of ADM after BCS is a safe and effective method for addressing volume defects, even though a slight reduction occurs in ADM volume.

Abbreviated breast magnetic resonance imaging (AB-MRI) has emerged as a supplementary screening tool, though protocols have not been standardized. The purpose of this study was to compare the diagnostic performance of modified and classic AB-MRI and determine MRI features affecting their diagnostic performance. Classic AB-MRI included one pre- and two post-contrast T1-weighted imaging (T1WI) scans, while modified AB-MRI included a delayed post-contrast axial T1WI scan and an axial T2-weighted interpolated scan obtained between the second and third post-contrast T1WI scans. Four radiologists (two specialists and two non-specialists) independently categorized the lesions. The MRI features investigated were lesion size, lesion type, and background parenchymal enhancement (BPE). The Wilcoxon rank-sum test, Fisher’s exact test, and bootstrap-based test were used for statistical analysis. The average area under the curve (AUC) for modified AB-MRI was significantly greater than that for classic AB-MRI (0.76 vs. 0.70, p = 0.010) in all reader evaluations, with a similar trend in specialist evaluations (0.83 vs. 0.76, p = 0.004). Modified AB-MRI demonstrated increased AUCs and better diagnostic performance than classic AB-MRI, especially for lesion size > 10 mm (p = 0.018) and mass lesion type (p = 0.014) in specialist evaluations and lesion size > 10 mm (p = 0.003) and mild (p = 0.026) or moderate BPE (p = 0.010) in non-specialist evaluations.