Tianyou Yang1, Shuwen Lin2, Qigen Xie3, Wenwei Ouyang4,5, Tianbao Tan1, Jiahao Li1, Zhiyuan Chen6, Jiliang Yang1, Huiying Wu7, Jing Pan1, Chao Hu1, Yan Zou8. 1. Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Jinsui Rd., Tianhe District, Guangzhou, 510623, China. 2. Department of Hepatobiliary Surgery, the Fifth People's Hospital of Dongguan City, Dongguan, China. 3. First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China. 4. Key Unit of Methodology in Clinical Research, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China. 5. The Second Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China. 6. Department of Radiology, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China. 7. Department of Radiology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China. 8. Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Jinsui Rd., Tianhe District, Guangzhou, 510623, China. monknut@126.com.
Abstract
BACKGROUND AND AIMS: Surgical planning in liver resection depends on the precise understanding of the three-dimensional (3D) relation of tumors to the intrahepatic vascular trees. This study aimed to investigate the impact of 3D printing (3DP) technology on the understanding of surgical liver anatomy. METHODS: We selected four hepatic tumors that were previously resected. For each tumor, a virtual 3D reconstruction (VIR) model was created from multi-detector computed tomography (MDCT) and was prototyped using a 3D printer. Forty-five surgical residents were evenly assigned to each group (3DP, VIR, and MDCT groups). After evaluation of the MDCT scans, VIR model, or 3DP model of each tumor, surgical residents were asked to assign hepatic tumor locations and state surgical resection proposals. The time used to specify the tumor location was recorded. The correct responses and time spent were compared between the three groups. RESULTS: The assignment of tumor location improved steadily from MDCT, to VIR, and to 3DP, with a mean score of 34.50, 55.25, and 80.92, respectively. These scores were out of 100 points. The 3DP group had significantly higher scores compared with other groups (p < 0.001). Furthermore, 3DP significantly improved the accuracy of surgical resection proposal (p < 0.001). The mean accuracy of the surgical resection proposal for 3DP, VIR, and MDCT was 57, 25, and 25%, respectively. The 3DP group took significantly less time, compared with other groups (p < 0.005). The mean time spent on assessing the tumor location for 3DP, VIR, and MDCT groups was 93, 223, and 286 s, respectively. CONCLUSIONS: 3D printing improves the understanding of surgical liver anatomy for surgical residents. The improved comprehension of liver anatomy may facilitate laparoscopy or open liver resection.
BACKGROUND AND AIMS: Surgical planning in liver resection depends on the precise understanding of the three-dimensional (3D) relation of tumors to the intrahepatic vascular trees. This study aimed to investigate the impact of 3D printing (3DP) technology on the understanding of surgical liver anatomy. METHODS: We selected four hepatic tumors that were previously resected. For each tumor, a virtual 3D reconstruction (VIR) model was created from multi-detector computed tomography (MDCT) and was prototyped using a 3D printer. Forty-five surgical residents were evenly assigned to each group (3DP, VIR, and MDCT groups). After evaluation of the MDCT scans, VIR model, or 3DP model of each tumor, surgical residents were asked to assign hepatic tumor locations and state surgical resection proposals. The time used to specify the tumor location was recorded. The correct responses and time spent were compared between the three groups. RESULTS: The assignment of tumor location improved steadily from MDCT, to VIR, and to 3DP, with a mean score of 34.50, 55.25, and 80.92, respectively. These scores were out of 100 points. The 3DP group had significantly higher scores compared with other groups (p < 0.001). Furthermore, 3DP significantly improved the accuracy of surgical resection proposal (p < 0.001). The mean accuracy of the surgical resection proposal for 3DP, VIR, and MDCT was 57, 25, and 25%, respectively. The 3DP group took significantly less time, compared with other groups (p < 0.005). The mean time spent on assessing the tumor location for 3DP, VIR, and MDCT groups was 93, 223, and 286 s, respectively. CONCLUSIONS: 3D printing improves the understanding of surgical liver anatomy for surgical residents. The improved comprehension of liver anatomy may facilitate laparoscopy or open liver resection.
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