Institut Pascal, UMR6602, Endoscopy and Computer Vision Group, Faculté de Médecine, Bâtiment 3C, 28 place Henri Dunant, 63000, Clermont-Ferrand, France.
Department of Digestive and Hepatobiliary Surgery, University Hospital Clermont-Ferrand, 1 Place Lucie et Raymond Aubrac, 63003, Clermont-Ferrand Cedex, France.
Surg Endosc. 2022 Jan;36(1):833-843. doi: 10.1007/s00464-021-08798-z. Epub 2021 Nov 3.
The aim of this study was to assess the performance of our augmented reality (AR) software (Hepataug) during laparoscopic resection of liver tumours and compare it to standard ultrasonography (US).
Ninety pseudo-tumours ranging from 10 to 20 mm were created in sheep cadaveric livers by injection of alginate. CT-scans were then performed and 3D models reconstructed using a medical image segmentation software (MITK). The livers were placed in a pelvi-trainer on an inclined plane, approximately perpendicular to the laparoscope. The aim was to obtain free resection margins, as close as possible to 1 cm. Laparoscopic resection was performed using US alone (n = 30, US group), AR alone (n = 30, AR group) and both US and AR (n = 30, ARUS group). R0 resection, maximal margins, minimal margins and mean margins were assessed after histopathologic examination, adjusted to the tumour depth and to a liver zone-wise difficulty level.
The minimal margins were not different between the three groups (8.8, 8.0 and 6.9 mm in the US, AR and ARUS groups, respectively). The maximal margins were larger in the US group compared to the AR and ARUS groups after adjustment on depth and zone difficulty (21 vs. 18 mm, p = 0.001 and 21 vs. 19.5 mm, p = 0.037, respectively). The mean margins, which reflect the variability of the measurements, were larger in the US group than in the ARUS group after adjustment on depth and zone difficulty (15.2 vs. 12.8 mm, p < 0.001). When considering only the most difficult zone (difficulty 3), there were more R1/R2 resections in the US group than in the AR + ARUS group (50% vs. 21%, p = 0.019).
Laparoscopic liver resection using AR seems to provide more accurate resection margins with less variability than the gold standard US navigation, particularly in difficult to access liver zones with deep tumours.
本研究旨在评估我们的增强现实（AR）软件（Hepataug）在腹腔镜肝肿瘤切除术中的性能，并将其与标准超声（US）进行比较。
在羊尸体肝脏中通过注射藻酸盐创建了 90 个从 10 到 20mm 的假性肿瘤。然后进行 CT 扫描，并使用医学图像分割软件（MITK）重建 3D 模型。肝脏被放置在骨盆训练器上的倾斜平面上，大约垂直于腹腔镜。目的是获得尽可能靠近 1cm 的自由切除边缘。使用仅超声（n=30，US 组）、仅 AR（n=30，AR 组）和超声和 AR 联合（n=30，ARUS 组）进行腹腔镜切除。在组织病理学检查后评估 R0 切除、最大边缘、最小边缘和平均边缘，并根据肿瘤深度和肝区难度水平进行调整。
三组的最小边缘没有差异（US、AR 和 ARUS 组分别为 8.8、8.0 和 6.9mm）。在调整深度和区域难度后，US 组的最大边缘大于 AR 和 ARUS 组（21 对 18mm，p=0.001 和 21 对 19.5mm，p=0.037）。反映测量变异性的平均边缘在调整深度和区域难度后，US 组大于 ARUS 组（15.2 对 12.8mm，p<0.001）。当仅考虑最困难的区域（难度 3）时，US 组的 R1/R2 切除率高于 AR+ARUS 组（50%对 21%，p=0.019）。
与金标准超声导航相比，使用 AR 进行腹腔镜肝切除似乎提供了更准确的切除边缘，且变异性更小，特别是在难以触及的深部肿瘤肝脏区域。
