Use of artificial intelligence in breast surgery: a narrative review.

Background and Objective: We have witnessed tremendous advances in artificial intelligence (AI) technologies. Breast surgery, a subspecialty of general surgery, has notably benefited from AI technologies. This review aims to evaluate how AI has been integrated into breast surgery practices, to assess its effectiveness in improving surgical outcomes and operational efficiency, and to identify potential areas for future research and application. Methods: Two authors independently conducted a comprehensive search of PubMed, Google Scholar, EMBASE, and Cochrane CENTRAL databases from January 1, 1950, to September 4, 2023, employing keywords pertinent to AI in conjunction with breast surgery or cancer. The search focused on English language publications, where relevance was determined through meticulous screening of titles, abstracts, and full-texts, followed by an additional review of references within these articles. The review covered a range of studies illustrating the applications of AI in breast surgery encompassing lesion diagnosis to postoperative follow-up. Publications focusing specifically on breast reconstruction were excluded. Key Content and Findings: AI models have preoperative, intraoperative, and postoperative applications in the field of breast surgery. Using breast imaging scans and patient data, AI models have been designed to predict the risk of breast cancer and determine the need for breast cancer surgery. In addition, using breast imaging scans and histopathological slides, models were used for detecting, classifying, segmenting, grading, and staging breast tumors. Preoperative applications included patient education and the display of expected aesthetic outcomes. Models were also designed to provide intraoperative assistance for precise tumor resection and margin status assessment. As well, AI was used to predict postoperative complications, survival, and cancer recurrence. Conclusions: Extra research is required to move AI models from the experimental stage to actual implementation in healthcare. With the rapid evolution of AI, further applications are expected in the coming years including direct performance of breast surgery. Breast surgeons should be updated with the advances in AI applications in breast surgery to provide the best care for their patients.

Vasovasostomy: A systematic review and meta-analysis comparing macroscopic, microsurgical, and robot-assisted microsurgical techniques.

BACKGROUND AND OBJECTIVES: Vasovasostomy is a cost-effective procedure for the reversal of vasectomy. A water-tight adequately blood-supplied mucosal anastomosis is required for better outcomes. This review aimed to compare the outcome of vasovasostomy performed by three different techniques: macroscopic, pure microsurgical, and robot-assisted microsurgical techniques. METHODS: Scopus, Web of Science, PubMed, Embase, and Cochrane library databases were searched for relevant studies from January 1901 to June 2023. We conducted our quantitative syntheses using the inverse variance method in OpenMeta software. The study's protocol was registered on PROSPERO. RESULTS: This review involved 95 studies of different designs, with a total sample size of 48,132. The majority of operations were performed bilaterally, and participants were monitored for up to 10 years. The pooled patency rate was the highest following robot-assisted vasovasostomy (94.4%), followed by pure microsurgical vasovasostomy (87.5%), and macroscopic vasovasostomy (83.7%). The pooled pregnancy rate following purely microsurgical vasovasostomy was higher than that of macroscopic vasovasostomy (47.4 vs. 43.7%). Definitive pregnancy rates in robotic vasovasostomy are yet to be determined. CONCLUSION: Patency outcomes for vasovasostomy were best with robot-assisted microsurgical technique, followed by pure microsurgical technique, and conventional macroscopic technique. Further investigations of robot-assisted microsurgical vasovasostomy outcomes and randomized control trials are required to support this evidence.

Use of Artificial Intelligence in the Advancement of Breast Surgery and Implications for Breast Reconstruction: A Narrative Review.

BACKGROUND: Breast reconstruction is a pivotal part of the recuperation process following a mastectomy and aims to restore both the physical aesthetic and emotional well-being of breast cancer survivors. In recent years, artificial intelligence (AI) has emerged as a revolutionary technology across numerous medical disciplines. This narrative review of the current literature and evidence analysis explores the role of AI in the domain of breast reconstruction, outlining its potential to refine surgical procedures, enhance outcomes, and streamline decision making. METHODS: A systematic search on Medline (via PubMed), Cochrane Library, Web of Science, Google Scholar, Clinical Trials, and Embase databases from January 1901 to June 2023 was conducted. RESULTS: By meticulously evaluating a selection of recent studies and engaging with inherent challenges and prospective trajectories, this review spotlights the promising role AI plays in advancing the techniques of breast reconstruction. However, issues concerning data quality, privacy, and ethical considerations pose hurdles to the seamless integration of AI in the medical field. CONCLUSION: The future research agenda comprises dataset standardization, AI algorithm refinement, and the implementation of prospective clinical trials and fosters cross-disciplinary partnerships. The fusion of AI with other emergent technologies like augmented reality and 3D printing could further propel progress in breast surgery.

Trunk muscle activity and kinematics during boxing and battle rope exercise in people with motor-complete spinal cord injury.

CONTEXT: Recovery of seated balance is a rehabilitation priority for people with motor-complete spinal cord injury (mcSCI). Previous research has demonstrated that people with mcSCI can voluntarily engage their trunk muscles during different exercise programs that have the potential to improve seated balance control. Boxing and battle rope exercises could offer another opportunity to improve seated balance for people with mcSCI, but it is unknown if this type of exercise engages trunk musculature and challenges seated balance. OBJECTIVE: To describe the movement patterns of people with mcSCI compared to controls by characterizing the muscle activation patterns and kinematics of the trunk and upper-body during boxing and battle rope exercise. DESIGN: Cross-sectional study. PARTICIPANTS: 4 males with mcSCI between C7-T9, and 4 able-bodied controls. METHODS: Participants performed different boxing and battle rope exercises while kinematics and electromyography (EMG) from the trunk and arms were recorded. OUTCOME MEASURES: Trunk EMG amplitude, trunk and arm joint angles, and trunk curvature. RESULTS: Boxing and battle ropes elicited higher relative EMG activity in people with mcSCI compared to controls (P < 0.001). Participants with mcSCI had similar upper-limb kinematics during the exercises to controls, but demonstrated reduced trunk rotation and increased trunk curvature. CONCLUSIONS: These findings suggest that boxing and battle rope can elicit trunk activity in people with mcSCI, though they may adopt increased trunk curvatures. Future research should explore if such exercise programs may improve seated balance in people with mcSCI.