Accuracy of custom temporomandibular joint replacement surgery using a virtual surgical planning protocol.

BACKGROUND: Accurate placement of TMJ implant components may be facilitated by virtual surgical planning (VSP) technologies. The aim of this study was to assess the accuracy of a typical VSP protocol and describe the pattern of surgical error associated with total alloplastic TMJ replacement. METHODS: A retrospective analysis was undertaken on 40 adult patients who were implanted with a fully customised, 3D printed TMJ prosthesis due to end-stage TMJ disease. Planned TMJ implant position based on preoperative CBCT images was compared with final position on postoperative OPGs using a previously validated linear rescaling method. Translational discrepancy was described in the anterior-posterior direction and superior-inferior direction. Rotational discrepancy was described as anterior or posterior. RESULTS: Lin's concordance between preoperative and postoperative position was 0.97, with no significant differences (p > 0.05). The Bland-Altman analysis showed a 95% limit of agreement between planned and final position of - 5.9 to 5.4 mm. Overall, final implant position was more anterior (0.4 mm), superior (0.4 mm) and posteriorly rotated (2.4°) compared with planned position. CONCLUSION: The use of VSP in TMJ replacement surgery results in accurate implant placement with good agreement between planned and final implant position. Discrepancies in planned and final implant position tended to result in the mandibular component of the implant being translated anterior superiorly and rotated posteriorly, with potential implications for the biomechanical performance of the implant and overall device longevity. These results should be used to assist TMJ surgeons pre- and intraoperatively to facilitating accurate implant positioning and optimal surgical rehabilitation.

Accuracy of orthopantomograms in the assessment of implant position following alloplastic temporomandibular joint replacement.

PURPOSE: The aim of this study was to determine the accuracy of orthopantomograms (OPGs) when assessing post-operative temporomandibular joint (TMJ) implant position, compared with cone beam computerized tomography (CBCT). METHODS: A retrospective analysis was undertaken on six adult patients who were implanted with a custom TMJ prosthesis due to end-stage TMJ disease. Post-operative CBCT was compared with post-operative OPGs. Overall magnification of each OPG was calculated and used to linearly rescale each image. Implant position was assessed by measuring the gonion angle and the distance between each surgical screw and the mandibular gonion (SG length). RESULTS: Mean magnification for OPGs was 24.2%. There were no significant differences (p > 0.05) in the gonion angle on OPGs compared with CBCT images. There was a mean decrease in SG lengths of 0.02 mm on OPGs, corresponding to error level of 5.31%. The 95% limits of agreement between OPGs and CBCT images for SG lengths were 1.65 mm and - 1.73 mm. CONCLUSION: This study presents a clinically applicable and accurate first-line radiographic screening tool to assess TMJ implant position. When combined with clinical assessment, OPGs can help reduce the need for further imaging and radiation exposure post-operatively.

Data-Driven Development of Predictive Models for Sustained Drug Release.

Mathematical modeling of drug release can aid in the design and development of sustained delivery systems, but the parameter estimation of such models is challenging owing to the nonlinear mathematical structure and complexity and interdependency of the physical processes considered. Highly parameterized models often lead to overfitting, strong parameter correlations, and as a consequence, inaccurate model predictions for systems not explicitly part of the fitting database. Here, we show that an efficient stochastic optimization algorithm can be used not only to find robust estimates of global minima to such complex problems but also to generate metadata that allow quantitative evaluation of parameter sensitivity and correlation, which can be used for further model refinement and development. A practical methodology is described through the analysis of a predictive drug release model on published experimental data sets. The model is then used to design a zeroth-order release profile in an experimental system consisting of an antibody fragment in a poly(lactic-co-glycolic acid) solvent depot, which is validated experimentally. This approach allows rational decision-making when developing new models, selecting models for a specific application, or designing formulations for experimental trials.