Background Surgeons are pursuing accurate head and neck reconstruction to enhance aesthetic and functional outcomes after oncologic resection. This study aimed to investigate whether accuracy of head and neck reconstruction is improved with the use of three-dimensionally (3D)-printed patient-specific surgical plates compared with conventional plates. Methods In this comparative study, patients were prospectively recruited into the study group (3DJP16) with 3D-printed patient-specific surgical plates. The patients in control group with conventional surgical plates were from a historic cohort in the same unit. The primary end point of the study was the accuracy of head and neck reconstruction. The secondary end points were accuracy of osteotomy, intraoperative blood loss, total operative time, and length of hospital stay. Results The study recruited of 33 patients, including 17 in the study group and 16 in the control group. The patients’ baseline characteristics were similar between the two groups. The absolute distance deviation of the maxilla or mandible was 1.5 ± 0.5 mm in the study group and 2.1 ± 0.7 mm in the control group [mean difference, − 0.7 mm; 95% confidence interval (CI) − 1.1 to − 0.3; p = 0.003], showing superior accuracy of reconstruction for the patients with 3D-printed patient-specific surgical plates. Improved accuracy of reconstruction also was detected in terms of bilateral mandibular angles and bone grafts. Concerning the secondary end points, the accuracy of the osteotomy was similar in the two groups. No difference was found regarding intraoperative blood loss, total operative time, or length of hospital stay. Conclusions This is the first study to prove that compared with conventional plates, 3D-printed patient-specific surgical plates improve the accuracy of oncologic head and neck reconstruction.

Background: Left atrial appendage (LAA) occlusion is an alternative to anticoagulation for stroke prevention in patients with atrial fibrillation. Accurate device sizing is crucial for optimal outcome. Patient-specific LAA models can be created using three-dimensional (3D) printing from 3D transesophageal echocardiographic (TEE) images, allowing in vitro model testing for device selection. The aims of this study were to assess the association of model-based device selection with procedural safety and efficacy and to determine if preprocedural model testing leads to superior outcomes. Methods: In 72 patients who underwent imaging-guided LAA occlusion, 3D models of the LAA were created from 3D TEE data sets retrospectively (retrospective cohort). The optimal device determined by in vitro model testing was compared with the actual device used. Associations of model-match and model-mismatch device sizing with outcomes were analyzed. In another 32 patients, device selection was prospectively guided by 3D models in adjunct to imaging (prospective cohort). The impact of model-based sizing on outcomes was assessed by comparing the two cohorts. Results: Patients in the retrospective cohort with model-mismatch sizing had longer procedure times, more implantation failures, more devices used per procedure, more procedural complications, more peridevice leak, more device thrombus, and higher cumulative incidence rates of ischemic stroke and cardiovascular or unexplained death (P < .05 for all) over 3.0 6 2.3 years after LAA occlusion. Compared with the retrospective imaging-guided cohort, the prospective model-guided patients achieved higher implantation success and shorter procedural times (P < .05) without complications. Clinical device compression (r = 0.92) and protrusion (r = 0.95) agreed highly with model testing (P < .0001). Predictors for sizing mismatch were nonwindsock morphology (odds ratio, 4.7) and prominent LAA trabeculations (odds ratio, 7.1). Conclusions: In patients undergoing LAA occlusion, device size selection in agreement with 3D-printed modelbased sizing is associated with improved safety and efficacy. Preprocedural device sizing with 3D models in adjunct to imaging guidance may lead to superior outcomes.

Bioinspired robotic structures comprising soft actuation units have attracted increasing research interest. Taking advantage of its inherent compliance, soft robots can assure safe interaction with external environments, provided that precise and effective manipulation could be achieved. Endoscopy is a typical application. However, previous model-based control approaches often require simplified geometric assumptions on the soft manipulator, but which could be very inaccurate in the presence of unmodeled external interaction forces. In this study, we propose a generic control framework based on nonparametric and online, as well as local, training to learn the inverse model directly, without prior knowledge of the robot's structural parameters. Detailed experimental evaluation was conducted on a soft robot prototype with control redundancy, performing trajectory tracking in dynamically constrained environments. Advanced element formulation of finite element analysis is employed to initialize the control policy, hence eliminating the need for random exploration in the robot's workspace. The proposed control framework enabled a soft fluid-driven continuum robot to follow a 3D trajectory precisely, even under dynamic external disturbance. Such enhanced control accuracy and adaptability would facilitate effective endoscopic navigation in complex and changing environments.