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Computational Fluid Dynamics (CFD) Analysis for Automated Distal Anastomosis in Coronary Bypass Grafting: Need of In-Vitro Training with Quantitative Anastomotic Quality Assessment
YOUNG KWANG PARK1, Tadashi Motomura2, Daisuke Ogawa1, Naohiko Kanemitsu1, Gustavo G. Salinas2, Basel Ramlawi2, Limael Rodriguez2, Mitsuo Umezu1, Mahesh Ramchandani2.
1Waseda University, TOKYO, Japan, 2Methodist DeBakey Heart & Vascular Center, Houston, TX, USA.

OBJECTIVE: Proximal automated suture devices are clinically used for off-pump coronary bypass grafting (OPCAB). Beyond standard OPCAB methods, an even less invasive approach has been applied, the so called minimally invasive coronary artery bypass (MICS-CAB). Due to the small surgical field in MICS-CAB, distal anastomoses in the circumflex or right coronary artery territory are technically challenging. Distal coronary automated anastomosis devices are clinically available and offer a promising option for the MICS-CAB operation. However, in vitro imaging analysis and the need for device deployment training are not well investigated. This study aims to clarify characteristics of automated sutures in comparison with hand-sewn anastomoses using rapid computational fluid dynamics (CFD) analysis.
METHODS: A tissue-mimicking silicone-rubber coronary model was used by a cardiac surgeon to create 2 hand-sewn models and 2 automated suture models each. For morphological assessment, minimum cross-sectional area (CSA) was measured by Micro CT using a special 50 µm resolution. Energy loss value was calculated using CFD techniques to assess the degree of anastomotic stenosis (where high energy loss represents high stenosis). These parameters were compared for the first and second automated suture models.
RESULTS: Inadequate installation of automated device encompassed poor anastomosis with high energy loss (489.8 µW) and a narrowed anastomosis (1.64 mm2), as opposed to hand suture group (mean energy loss of 87.5 µW and mean CAS of 9.4 mm2). In contrast, properly installed graft to the automated device significantly improved energy loss (93.1 µW, 81% improvement) and a CSA (7.80 mm2, 475% improvement). This result was comparable with hand sewn group and suggested importance of graft installation training as well as final deployment techniques.


CONCLUSIONS: Automated suturing of distal anastomoses showed equivalent anastomotic qualities compared with conventional hand suture anastomosis. As well as hand sewing skills, it is equally important to maintain consistent anastomosis quality for automated device. Particularly, graft installation and automated clip deployment maneuvering may require systematic in-vitro training and imaging/quantitative assessment prior to device clinical implementation.


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