Prediction of Residual Malignancy After Excisional Biopsy for Breast Cancer With Suspicious Microcalcifications: Comparison of Mammography and Magnetic Resonance Imaging

ACR Appropriateness Criteria® Imaging After Breast Surgery

Given that 20% to 40% of women who have percutaneous breast biopsy subsequently undergo breast surgery, knowledge of imaging women with a history of benign (including high-risk) disease or breast cancer is important. For women who had surgery for nonmalignant pathology, the surveillance recommendations are determined by their overall risk. Higher-than-average risk women with a history of benign surgery may require screening mammography starting at an earlier age before 40 and may benefit from screening MRI. For women with breast cancer who have undergone initial excision and have positive margins, imaging with diagnostic mammography or MRI can sometimes guide additional surgical planning. Women who have completed breast conservation therapy for cancer should get annual mammography and may benefit from the addition of MRI or ultrasound to their surveillance regimen. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances in which peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Computer-aided classification of MRI for pathological complete response to neoadjuvant chemotherapy in breast cancer

Background: To determine suitable optimal classifiers and examine the general applicability of computer-aided classification to compare the differences between a computer-aided system and radiologists in predicting pathological complete response (pCR) from patients with breast cancer receiving neoadjuvant chemotherapy. Methods: We analyzed a total of 455 masses and used the U-Net network and ResNet to execute MRI segmentation and pCR classification. The diagnostic performance of radiologists, the computer-aided system and a combination of radiologists and computer-aided system were compared using receiver operating characteristic curve analysis. Results: The combination of radiologists and computer-aided system had the best performance for predicting pCR with an area under the curve (AUC) value of 0.899, significantly higher than that of radiologists alone (AUC: 0.700) and computer-aided system alone (AUC: 0.835). Conclusion: An automated classification system is feasible to predict the pCR to neoadjuvant chemotherapy in patients with breast cancer and can complement MRI.

Background Parenchymal Enhancement on Breast MRI: Assessment and Clinical Implications

Purpose of Review

To present recent literature regarding the assessment and clinical implications of background parenchymal enhancement on breast MRI.

Recent Findings

The qualitative assessment of BPE remains variable within the literature, as well as in clinical practice. Several different quantitative approaches have been investigated in recent years, most commonly region of interest-based and segmentation-based assessments. However, quantitative assessment has not become standard in clinical practice to date. Numerous studies have demonstrated a clear association between higher BPE and future breast cancer risk. While higher BPE does not appear to significantly impact cancer detection, it may result in a higher abnormal interpretation rate. BPE is also likely a marker of pathologic complete response after neoadjuvant chemotherapy, with decreases in BPE during and after neoadjuvant chemotherapy correlated with pCR. In contrast, pre-treatment BPE does not appear to be predictive of pCR. The association between BPE and prognosis is less clear, with heterogeneous results in the literature.

Summary

Assessment of BPE continues to evolve, with heterogeneity in approaches to both qualitative and quantitative assessment. The level of BPE has important clinical implications, with associations with future breast cancer risk and treatment response. BPE may also be an imaging marker of prognosis, but future research is needed on this topic.

Role of Magnetic Resonance Imaging in Predicting Residual Breast Cancer After Vacuum-Assisted Breast Biopsy

PURPOSE

This study aims to evaluate the effectiveness of breast magnetic resonance imaging (MRI) in detecting residual breast cancer in patients after vacuum-assisted breast biopsy (VABB).

METHODS

Between 2012 and 2019, 26 patients with breast cancer who underwent VABB were enrolled. Breast MRI was conducted after VABB. Imaging findings were then compared with the histopathological results. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated.

RESULTS

Residual cancer was confirmed histologically in 8 of the 26 patients after VABB. The overall sensitivity, specificity, PPV, NPV, and accuracy of MRI for diagnosing residual cancer were 79.9%, 73.0%, 87.1%, 61.3%, and 77.8%, respectively. The sensitivity and NPV improved to 100%, when the number of biopsy specimens was larger than five.

CONCLUSION

Breast MRI showed high sensitivity and NPV in detecting residual breast tumor after VABB.