ArticleGland surgery2023
Transforming breast reconstruction: the pioneering role of artificial intelligence in preoperative planning.
Article in Gland surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed.
- [A brief discussion on microsurgery techniques and free perforator flaps for wound repair].Zhonghua shao shang yu chuang mian xiu fu za zhi · 2026Article
- Exploring the Balance Between Artificial Intelligence and Human Expertise in Shaping Breast Reconstruction Outcomes: A Comparative Reflection Study.Journal of clinical medicine · 2026Article
- Artificial intelligence for breast cancer management.Communications medicine · 2026Review
- Artificial intelligence in breast surgery: Current applications, challenges, and future perspectives.The Journal of international medical research · 2026Review
- Redefining Reconstruction: Technological Innovations in Microsurgical Breast Reconstruction.Cancers · 2025Review
- Artificial Intelligence in Breast Reconstruction: Enhancing Surgical Planning, Aesthetic Outcomes, and Patient-Centered Care.Journal of clinical medicine · 2025Review
- Artificial Intelligence as a Potential Tool for Predicting Surgical Margin Status in Early Breast Cancer Using Mammographic Specimen Images.Diagnostics (Basel, Switzerland) · 2025Article
- The Transformative Role of Artificial Intelligence in Plastic and Reconstructive Surgery: Challenges and Opportunities.Journal of clinical medicine · 2025Review
- Artificial Intelligence in Breast Reconstruction: A Narrative Review.Medicina (Kaunas, Lithuania) · 2025Review
- Artificial intelligence in plastic surgery, where do we stand?JPRAS open · 2024Review
- Imaging in Autologous Breast Reconstruction.Cancers · 2024Review
- Advancing DIEP Flap Monitoring with Optical Imaging Techniques: A Narrative Review.Sensors (Basel, Switzerland) · 2024Review
- Artificial Intelligence as a Triage Tool during the Perioperative Period: Pilot Study of Accuracy and Accessibility for Clinical Application.Plastic and reconstructive surgery. Global open · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Autologous breast reconstruction surgery is a vital part of the recovery process for patients with breast cancer. While various reconstructive options exist, the deep inferior epigastric artery perforator (DIEP) flap is often favoured for its ability to closely mimic natural breast tissue. However, the complex vascular anatomy associated with the deep inferior epigastric artery (DIEA) presents challenges for surgeons during DIEP flap execution. Preoperative imaging, such as computed tomography angiography (CTA), is commonly used to understand vascular architecture and aid in selecting appropriate perforators. Conventional reporting of CTA scans is a labour-intensive process that can be challenging and requires specific expertise. The integration of artificial intelligence (AI) and machine learning (ML) algorithms in medical imaging has the potential to address these challenges. AI can enhance CTA through improved data acquisition, image post-processing, and potentially interpretation. By automating the perforator selection process, AI applications can significantly reduce the time spent on preoperative imaging analysis and potentially improve accuracy and reliability. While AI shows promise in optimizing efficiency, accuracy, and reliability in breast reconstruction planning, challenges and ethical considerations need to be addressed. This article explores the challenges, opportunities, and future directions of using AI in the preoperative planning of autologous breast reconstruction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.