Ock Junhyeok, Moon Sojin, Kim MinKyeong, Ko Beom Seok, Kim Namkug
Department of Convergence Medicine, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, 388-1 Pungnap2-dong, Songpa-gu, Seoul, South Korea.
Department of Breast Surgery, Asan Medical Center, University of Ulsan College of Medicine, 388-1 Pungnap2-dong, Songpa-gu, Seoul, South Korea.
Comput Methods Programs Biomed. 2024 Mar;245:108002. doi: 10.1016/j.cmpb.2023.108002. Epub 2023 Dec 29.
Although magnetic resonance imaging (MRI) is commonly used for breast tumor detection, significant challenges remain in determining and presenting the three-dimensional (3D) morphology of tumors to guide breast-conserving surgery. To address this challenge, we have developed the augmented reality-breast surgery guide (AR-BSG) and compared its performance with that of a traditional 3D-printed breast surgical guide (3DP-BSG).
Based on the MRI results of a breast cancer patient, a breast phantom made of skin, body, and tumor was fabricated through 3D printing and silicone-casting. AR-BSG and 3DP-BSG were executed using surgical plans based on the breast phantom's computed tomography scan images. Three operators independently inserted a catheter into the phantom using each guide. Their targeting accuracy was then evaluated using Bland-Altman analysis with limits of agreement (LoA). Differences between the users of each guide were evaluated using the intraclass correlation coefficient (ICC).
The entry and end point errors associated with AR-BSG were -0.34±0.68 mm (LoA: -1.71-1.01 mm) and 0.81±1.88 mm (LoA: -4.60-3.00 mm), respectively, whereas 3DP-BSG was associated with entry and end point errors of -0.28±0.70 mm (LoA: -1.69-1.11 mm) and -0.62±1.24 mm (LoA: -3.00-1.80 mm), respectively. The AR-BSG's entry and end point ICC values were 0.99 and 0.97, respectively, whereas 3DP-BSG was associated with entry and end point ICC values of 0.99 and 0.99, respectively.
AR-BSG can consistently and accurately localize tumor margins for surgeons without inferior guiding accuracy AR-BSG can consistently and accurately localize tumor margins for surgeons without inferior guiding accuracy compared to 3DP-BSG. Additionally, when compared with 3DP-BSG, AR-BSG can offer better spatial perception and visualization, lower costs, and a shorter setup time.
尽管磁共振成像(MRI)常用于乳腺肿瘤检测,但在确定和呈现肿瘤的三维(3D)形态以指导保乳手术方面仍存在重大挑战。为应对这一挑战,我们开发了增强现实乳房手术指南(AR-BSG),并将其性能与传统的3D打印乳房手术指南(3DP-BSG)进行了比较。
根据一名乳腺癌患者的MRI结果,通过3D打印和硅胶铸造制作了一个由皮肤、身体和肿瘤组成的乳房模型。基于乳房模型的计算机断层扫描图像,使用手术计划执行AR-BSG和3DP-BSG。三名操作员分别使用每个指南将导管插入模型中。然后使用一致性界限(LoA)的布兰德-奥特曼分析评估他们的靶向准确性。使用组内相关系数(ICC)评估每个指南使用者之间的差异。
与AR-BSG相关的进入点和终点误差分别为-0.34±0.68毫米(LoA:-1.71-1.01毫米)和0.81±1.88毫米(LoA:-4.60-3.00毫米),而3DP-BSG的进入点和终点误差分别为-0.28±0.70毫米(LoA:-1.69-1.11毫米)和-0.62±1.24毫米(LoA:-3.00-1.80毫米)。AR-BSG的进入点和终点ICC值分别为0.99和0.97,而3DP-BSG的进入点和终点ICC值分别为0.99和0.99。
与3DP-BSG相比,AR-BSG可以为外科医生一致且准确地定位肿瘤边缘,且不会降低引导准确性。此外,与3DP-BSG相比,AR-BSG可以提供更好的空间感知和可视化效果,成本更低,设置时间更短。