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Orthopaedic surgeons need to correctly identify bone fragments using 2D/3D CT images before trauma surgery. Advances in deep learning technology provide good insights into trauma surgery over manual diagnosis. This study demonstrates the application of the DeepLab v3+ -based deep learning model for the automatic segmentation of fragments of the fractured tibia and fibula from CT images and the results of the evaluation of the performance of the automatic segmentation. The deep learning model, which was trained using over 11 million images, showed good performance with a global accuracy of 98.92%, a weighted intersection over the union of 0.9841, and a mean boundary F1 score of 0.8921. Moreover, deep learning performed 5–8 times faster than the experts' recognition performed manually, which is comparatively inefficient, with almost the same significance. This study will play an important role in preoperative surgical planning for trauma surgery with convenience and speed. [ABSTRACT FROM AUTHOR]

Pelvic bone fracture is highly complex, and its anatomical reduction is difficult. Therefore, patient-specific customized plates have been developed using three-dimensional (3D) printing technology and are being increasingly used. In this study, the reduction status in five representative pelvic fracture models was compared between two groups: the 3D printing plate (3DP) group using a patient-specific 3D printed plate after virtual reduction and the conventional plate (CP) group using a conventional plate by manual bending. The 3DP and CP groups included 10 and 5 cases, respectively. The fractured models were reduced virtually and their non-locking metal plates were customized using 3D printing. The process of contouring the conventional plates to fit the contact surface of the bone with the bending tool was conducted by an experienced pelvic bone trauma surgeon. The reduction and fixation achieved using the two different plate groups was compared, and the significance of differences in the results was analyzed using paired t-tests, after verifying the normality of data distribution. The vertex distances between the surface of the bone and the contact surface of the plate were significantly lower in the 3DP group than in the CP group (0.407 ± 0.342 and 2.195 ± 1.643, respectively, P = 0.008). Length and angular variations, which are measurements of the reduction state, were also lower in the 3DP group than in the CP group (length variation: 3.211 ± 2.497 and 5.493 ± 3.609, respectively, P = 0.051; angular variation: 2.958 ± 1.977 and 4.352 ± 1.947, respectively, P = 0.037). The customized 3D printed plate in the virtual reduction model provided a highly accurate reduction of pelvic bone fractures, suggesting that the customized 3D printed plate may help ensure easy and accurate reduction. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Structural analysis of customized 3D printed plate for pelvic bone by comparison with conventional plate based on bending process" published in Scientific Reports. The correction addresses an error in the affiliation of the authors. The correct affiliation is listed as the Department of Orthopaedic Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, 222, Banpo-Daero, Seocho-Gu, Korea. The original article has been corrected. The authors of the article are Woo-Lam Jo, Yang-Guk Chung, Seung-Han Shin, Jae-hak Lim, Moo-Sub Kim, and Do-Kun Yoon. [Extracted from the article]

This study analyzed the effectiveness attained through generation of three alpha particles in proton-boron fusion therapy (PBFT) based on a Monte Carlo simulation. PBFT is based on a fusion reaction between protons and boron. Three alpha particles are emitted from this reaction. The three alpha particles cause greater damage to tumor cells than the single alpha particle produced in the boron neutron capture reaction or conventional therapy. In addition, the intrinsic proton dose pattern follows Bragg-peak curve. We confirmed an energy deposition by the alpha particle and verified the therapeutic effect of the PBFT. [ABSTRACT FROM AUTHOR]