Identification of A0 minimum ablative margins for colorectal liver metastases: multicentre, retrospective study using deformable CT registration and artificial intelligence-based autosegmentation
A minimum ablative margin of 5 mm or larger demonstrates optimal local oncological outcomes. It is proposed that an intraprocedural minimum ablative margin of 5 mm or larger, confirmed using biomechanical deformable image registration, serves as the A0 for colorectal liver metastasis thermal ablation.
Authors
- Kristy K. Brock (ORCID: https://orcid.org/0000-0001-9364-5040)
- Marco Calandri (ORCID: https://orcid.org/0000-0002-0297-0700)
- Caleb S. O’Connor (ORCID: https://orcid.org/0009-0003-2871-6692)
- Márcio Meira (ORCID: https://orcid.org/0000-0002-0988-1620)
- Alexander Shieh (ORCID: https://orcid.org/0009-0005-7450-2702)
- A. Kyle Jones (ORCID: https://orcid.org/0000-0001-8245-8573)
- Bruno Calazans Odisio (ORCID: https://orcid.org/0000-0002-1771-8233)
- Reto Bale (ORCID: https://orcid.org/0000-0003-0021-5792)
- Yuan‐Mao Lin (ORCID: https://orcid.org/0000-0002-0275-9593)
- Carlo Gazzera
- Paolo Fonio (ORCID: https://orcid.org/0000-0002-1106-2990)
- Jéssica Albuquerque Marques Silva (ORCID: https://orcid.org/0000-0003-0616-982X)
- Gregor Laimer (ORCID: https://orcid.org/0000-0002-6116-4901)
- Francesca Menchini (ORCID: https://orcid.org/0000-0003-2156-7631)
- Iwan Paolucci (ORCID: https://orcid.org/0000-0002-9393-3015)
- Valentina Cignini (ORCID: https://orcid.org/0000-0001-5962-8896)
- Marcos Roberto de Menezes (ORCID: https://orcid.org/0000-0001-7548-8774)
Institutions
- The University of Texas MD Anderson Cancer Center (US)
- Innsbruck Medical University (AT)
- Universität Innsbruck (AT)
- Azienda Ospedaliera Citta' della Salute e della Scienza di Torino (IT)
- Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (BR)
- University of Turin (IT)
Publication Details
- Journal
- British journal of surgery
- Published
- 2024-08-30
- DOI
- https://doi.org/10.1093/bjs/znae165
- Citations
- 24
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 9.70
Funders
- National Science Foundation
- Good Food Institute
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- National Institutes of Health
- University of Texas MD Anderson Cancer Center
- National Cancer Institute