Tianyou Yang1, Shuwen Lin2, Tianbao Tan1, Jiliang Yang1, Jing Pan1, Chao Hu1, Jiahao Li1, Yan Zou3. 1. Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, No. 9 Jinsui Rd., Tianhe District, Guangzhou, 510623, China. 2. The Fifth People's Hospital of Dongguan City, Dongguan, China. 3. Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, No. 9 Jinsui Rd., Tianhe District, Guangzhou, 510623, China. monknut@126.com.
Abstract
OBJECTIVES: To investigate the impact of 3D printed model on understanding of surgical anatomy of retroperitoneal tumor. MATERIALS AND METHODS: Three-dimensional model was printed, based on multi-detectors computed tomography (MDCT) of a retroperitoneal tumor. Participants (10 students, 10 residents and 10 surgeons) were asked to identify vasculatures which were important in resection of the tumor, after viewing MDCT images, 3D visualization model and 3D printed model, respectively. Regarding this tumor, left renal vein (LRV), right renal pedicles (RRP) and inferior vena cava (IVC) were chosen as indicators to assess participants' performances. Identification of vasculatures was evaluated and a score was given (1 point = success; 0 point = failure). The total number and percentage of correct identification were used to measure how these three types of anatomic presentation were able to transfer in terms of anatomical recognition. Recorded data were analyzed both pooling together data from three groups of participants and separately for each group. RESULTS: In analysis of overall comparison among 3D printing, 3D visualization and MDCT, recognition of all three vasculatures simultaneously was 83.33, 73.33 and 46.67%, respectively (P = 0.007); recognition of LRV was 90, 80 and 63.33% (P = 0.043), respectively; recognition of RRP was 96.67, 83.33 and 73.33% (P = 0.035), respectively; recognition of IVC was 93.33, 90 and 80% (P = 0.366), respectively. In subgroup analysis of performances of three groups of participants, no significant differences regarding anatomic recognition were observed among MDCT, 3D visualization and 3D printed model for each group of participants. CONCLUSION: Three-dimensional printed model improved the understanding of surgical anatomy of retroperitoneal tumor.
OBJECTIVES: To investigate the impact of 3D printed model on understanding of surgical anatomy of retroperitoneal tumor. MATERIALS AND METHODS: Three-dimensional model was printed, based on multi-detectors computed tomography (MDCT) of a retroperitoneal tumor. Participants (10 students, 10 residents and 10 surgeons) were asked to identify vasculatures which were important in resection of the tumor, after viewing MDCT images, 3D visualization model and 3D printed model, respectively. Regarding this tumor, left renal vein (LRV), right renal pedicles (RRP) and inferior vena cava (IVC) were chosen as indicators to assess participants' performances. Identification of vasculatures was evaluated and a score was given (1 point = success; 0 point = failure). The total number and percentage of correct identification were used to measure how these three types of anatomic presentation were able to transfer in terms of anatomical recognition. Recorded data were analyzed both pooling together data from three groups of participants and separately for each group. RESULTS: In analysis of overall comparison among 3D printing, 3D visualization and MDCT, recognition of all three vasculatures simultaneously was 83.33, 73.33 and 46.67%, respectively (P = 0.007); recognition of LRV was 90, 80 and 63.33% (P = 0.043), respectively; recognition of RRP was 96.67, 83.33 and 73.33% (P = 0.035), respectively; recognition of IVC was 93.33, 90 and 80% (P = 0.366), respectively. In subgroup analysis of performances of three groups of participants, no significant differences regarding anatomic recognition were observed among MDCT, 3D visualization and 3D printed model for each group of participants. CONCLUSION: Three-dimensional printed model improved the understanding of surgical anatomy of retroperitoneal tumor.
Authors: Stefania Marconi; Luigi Pugliese; Marta Botti; Andrea Peri; Emma Cavazzi; Saverio Latteri; Ferdinando Auricchio; Andrea Pietrabissa Journal: Surg Endosc Date: 2017-03-09 Impact factor: 4.584
Authors: Nizar N Zein; Ibrahim A Hanouneh; Paul D Bishop; Maggie Samaan; Bijan Eghtesad; Cristiano Quintini; Charles Miller; Lisa Yerian; Ryan Klatte Journal: Liver Transpl Date: 2013-10-21 Impact factor: 5.799
Authors: W Lamadé; G Glombitza; L Fischer; P Chiu; C E Cárdenas; M Thorn; H P Meinzer; L Grenacher; H Bauer; T Lehnert; C Herfarth Journal: Arch Surg Date: 2000-11