Clinical practice guidelines for pre-operative evaluation of breast cancer: Chinese Society of Breast Surgery (CSBrS) practice guidelines 2021

Ultrasound-based deep learning in the establishment of a breast lesion risk stratification system: a multicenter study

OBJECTIVES

To establish a breast lesion risk stratification system using ultrasound images to predict breast malignancy and assess Breast Imaging Reporting and Data System (BI-RADS) categories simultaneously.

METHODS

This multicenter study prospectively collected a dataset of ultrasound images for 5012 patients at thirty-two hospitals from December 2018 to December 2020. A deep learning (DL) model was developed to conduct binary categorization (benign and malignant) and BI-RADS categories (2, 3, 4a, 4b, 4c, and 5) simultaneously. The training set of 4212 patients and the internal test set of 416 patients were from thirty hospitals. The remaining two hospitals with 384 patients were used as an external test set. Three experienced radiologists performed a reader study on 324 patients randomly selected from the test sets. We compared the performance of the DL model with that of three radiologists and the consensus of the three radiologists.

RESULTS

In the external test set, the DL model achieved areas under the receiver operating characteristic curve (AUCs) of 0.980 and 0.945 for the binary categorization and six-way categorizations, respectively. In the reader study set, the DL BI-RADS categories achieved a similar AUC (0.901 vs. 0.933, p = 0.0632), sensitivity (90.98% vs. 95.90%, p = 0.1094), and accuracy (83.33% vs. 79.01%, p = 0.0541), but higher specificity (78.71% vs. 68.81%, p = 0.0012) than those of the consensus of the three radiologists.

CONCLUSIONS

The DL model performed well in distinguishing benign from malignant breast lesions and yielded outcomes similar to experienced radiologists. This indicates the potential applicability of the DL model in clinical diagnosis.

KEY POINTS

• The DL model can achieve binary categorization for benign and malignant breast lesions and six-way BI-RADS categorizations for categories 2, 3, 4a, 4b, 4c, and 5, simultaneously. • The DL model showed acceptable agreement with radiologists for the classification of breast lesions. • The DL model performed well in distinguishing benign from malignant breast lesions and had promise in helping reduce unnecessary biopsies of BI-RADS 4a lesions.

Surgical Planning after Neoadjuvant Treatment in Breast Cancer: A Multimodality Imaging-Based Approach Focused on MRI

Neoadjuvant chemotherapy (NACT) today represents a cornerstone in the treatment of locally advanced breast cancer and highly chemo-sensitive tumors at early stages, increasing the possibilities of performing more conservative treatments and improving long term outcomes. Imaging has a fundamental role in the staging and prediction of the response to NACT, thus aiding surgical planning and avoiding overtreatment. In this review, we first examine and compare the role of conventional and advanced imaging techniques in preoperative T Staging after NACT and in the evaluation of lymph node involvement. In the second part, we analyze the different surgical approaches, discussing the role of axillary surgery, as well as the possibility of non-operative management after-NACT, which has been the subject of recent trials. Finally, we focus on emerging techniques that will change the diagnostic assessment of breast cancer in the near future.

Chinese Society of Breast Surgery (CSBrS) Practice Guideline 2022

Background

The Chinese Society of Breast Surgery (CSBrS) Practice Guideline 2021 was published nearly one year ago. The new guideline was revised based on comprehensive feedback of the previous publication. The aim is to provide a better reference suitable for Chinese breast surgeons.

Methods

Referred to GRADE (Grading of Recommendations Assessment, Development and Evaluation) system, evidences accepted by the Guideline were classified into four categories: I, II, III and IV, which reflected the reliability of the evidences quantitatively. The guideline also comprehensively considered the accessibility of the guideline in clinical practice in China and gave recommendations with different strengths.

Results

The guideline emphasized the basic idea that a curative surgical approach falls under the category of radical tumor surgery. Six chapters, including "Diagnosis and treatment of patients with invasive breast cancer", "Sentinel lymph node biopsy in patients with early-stage breast cancer", "Breast-conserving surgery in patients with early-stage breast cancer", "Modified radical mastectomy of breast cancer", "Central venous access for the systemic treatment of breast cancer", and "Breast cancer in pregnancy and postpartum breast cancer" were revised.

Conclusions

Compared with the 2021 edition, the new guideline has been revised in six chapters based on the latest research evidence and clinical needs.