Impact of 3D Printing Technology on Comprehension of Surgical Anatomy of Retroperitoneal Tumor
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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.
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.
Three-dimensional printed model improved the understanding of surgical anatomy of retroperitoneal tumor.
This study was funded by National Natural Science Foundation of China (Grant No. 81602199), Guangzhou Science Technology and Innovation Commission (Grant No. 201607010395), Natural Science Foundation of Guangdong Province, China (Grant No. 2016A030313496).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no competing interests.