ArticleBreast (Edinburgh, Scotland)2020
Automatic detection of perforators for microsurgical reconstruction.
Article in Breast (Edinburgh, Scotland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The usefulness of artificial intelligence in breast reconstruction: a systematic review.Breast cancer (Tokyo, Japan) · 2024Pooled it
- Comparison between mixed reality with artificial algorithms and ultrasound in localization of anterior thigh flap perforators: a prospective randomized controlled study.BMC medicine · 2025Trial
- Artificial Intelligence-predicted Outcomes of Breast Reconstruction: Progress, Pitfalls, and Path Forward.Plastic and reconstructive surgery. Global open · 2026Article
- Artificial Intelligence in Breast Reconstruction: A Scoping Review of Pre-, Intra-, and Postoperative Applications.Plastic and reconstructive surgery. Global open · 2026Article
- Artificial intelligence for breast cancer management.Communications medicine · 2026Review
- Development of an automatic segmentation system for anterolateral thigh flap perforators in maxillofacial reconstruction.PloS one · 2026Article
- AI-based planning for DIEAP flap procedures: exploring foundation models for artery perforators analysis.Frontiers in medicine · 2026Article
- Artificial Intelligence in Plastic Surgery: A Bibliometric and Visual Analysis of the 100 Most-Cited English-Language Publications.Aesthetic surgery journal. Open forum · 2026Review
- Artificial intelligence in breast surgery: Current applications, challenges, and future perspectives.The Journal of international medical research · 2026Review
- Artificial Intelligence in Breast Reconstruction: Enhancing Surgical Planning, Aesthetic Outcomes, and Patient-Centered Care.Journal of clinical medicine · 2025Review
- Review
- Advancing Preoperative Planning in Perforator Flap Surgery with Photon-Counting Computed Tomography Angiography: Less Challenges with More Precision.Aesthetic plastic surgery · 2025Article
- Artificial Intelligence and Machine Learning in Reconstructive Microsurgery.Seminars in plastic surgery · 2025Review
- Review
- Artificial Intelligence in Microsurgical Planning: A Five-Year Leap in Clinical Translation.Journal of clinical medicine · 2025Review
- Artificial Intelligence in Breast Reconstruction: A Narrative Review.Medicina (Kaunas, Lithuania) · 2025Review
- Prospective study on the localization of anterolateral thigh perforator vessel based on mixed reality and artificial algorithm.Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2024Article
- Decoding the Impact of AI on Microsurgery: Systematic Review and Classification of Six Subdomains for Future Development.Plastic and reconstructive surgery. Global open · 2024Article
- Automated thermographic detection of blood vessels for DIEP flap reconstructive surgery.International journal of computer assisted radiology and surgery · 2024Article
- Imaging in Autologous Breast Reconstruction.Cancers · 2024Review
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The deep inferior epigastric perforator (DIEP) is the most commonly used free flap in mastectomy reconstruction. Preoperative imaging techniques are routinely used to detect location, diameter and course of perforators, with direct intervention from the imaging team, who subsequently draw a chart that will help surgeons choosing the best vascular support for the reconstruction. In this work, the feasibility of using a computer software to support the preoperative planning of 40 patients proposed for breast reconstruction with a DIEP flap is evaluated for the first time. Blood vessel centreline extraction and local characterization algorithms are applied to identify perforators and compared with the manual mapping, aiming to reduce the time spent by the imaging team, as well as the inherent subjectivity to the task. Comparing with the measures taken during surgery, the software calibre estimates were worse for vessels smaller than 1.5 mm (P = 6e-4) but better for the remaining ones (P = 2e-3). Regarding vessel location, the vertical component of the software output was significantly different from the manual measure (P = 0.02), nonetheless that was irrelevant during surgery as errors in the order of 2-3 mm do not have impact in the dissection step. Our trials support that a reduction of the time spent is achievable using the automatic tool (about 2 h/case). The introduction of artificial intelligence in clinical practice intends to simplify the work of health professionals and to provide better outcomes to patients. This pilot study paves the way for a success story.
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