Rapid patient-specific FEM meshes from 3D smart-phone based scans.

Objective.The objective of this study was to describe and evaluate a smart-phone based method to rapidly generate subject-specific finite element method (FEM) meshes. More accurate FEM meshes should lead to more accurate thoracic electrical impedance tomography (EIT) images.Approach.The method was evaluated on an iPhone®that utilized an app called Heges, to obtain 3D scans (colored, surface triangulations), a custom belt, and custom open-source software developed to produce the subject-specific meshes. The approach was quantitatively validated via mannequin and volunteer tests using an infrared tracker as the gold standard, and qualitatively assessed in a series of tidal-breathing EIT images recorded from 9 subjects.Main results.The subject-specific meshes can be generated in as little as 6.3 min, which requires on average 3.4 min of user interaction. The mannequin tests yielded high levels of precision and accuracy at 3.2 ± 0.4 mm and 4.0 ± 0.3 mm root mean square error (RMSE), respectively. Errors on volunteers were only slightly larger (5.2 ± 2.1 mm RMSE precision and 7.7 ± 2.9 mm RMSE accuracy), illustrating the practical RMSE of the method.Significance.Easy-to-generate, subject-specific meshes could be utilized in the thoracic EIT community, potentially reducing geometric-based artifacts and improving the clinical utility of EIT.

A particle filter approach to dynamic kidney pose estimation in robotic surgical exposure.

PURPOSE: Traditional soft tissue registration methods require direct intraoperative visualization of a significant portion of the target anatomy in order to produce acceptable surface alignment. Image guidance is therefore generally not available during the robotic exposure of structures like the kidneys which are not immediately visualized upon entry into the abdomen. This paper proposes guiding surgical exposure with an iterative state estimator that assimilates small visual cues into an a priori anatomical model as exposure progresses, thereby evolving pose estimates for the occluded structures of interest. METHODS: Intraoperative surface observations of a right kidney are simulated using endoscope tracking and preoperative tomography from a representative robotic partial nephrectomy case. Clinically relevant random perturbations of the true kidney pose are corrected using this sequence of observations in a particle filter framework to estimate an optimal similarity transform for fitting a patient-specific kidney model at each step. The temporal response of registration error is compared against that of serial rigid coherent point drift (CPD) in both static and simulated dynamic surgical fields, and for varying levels of observation persistence. RESULTS: In the static case, both particle filtering and persistent CPD achieved sub-5 mm accuracy, with CPD processing observations 75% faster. Particle filtering outperformed CPD in the dynamic case under equivalent computation times due to the former requiring only minimal persistence. CONCLUSION: This proof-of-concept simulation study suggests that Bayesian state estimation may provide a viable pathway to image guidance for surgical exposure in the abdomen, especially in the presence of dynamic intraoperative tissue displacement and deformation.

A retrieval analysis perspective on revision for infection.

BACKGROUND: Retrieval analysis has long served the orthopaedic community as a tool for understanding implant failure modes; however, what retrieval studies can reveal about the nature of prosthetic joint infection (PJI) remains unknown. We hypothesize that records from a comprehensive joint retrieval program should corroborate clinically-reported temporal characteristics of prosthesis-related infection. METHODS: We examined 2527 records documenting a decade of explanted hip and knee components to quantify the following: (1) the relative contribution of infection to revision arthroplasty; (2) the effects of joint type, revision status, and reason for retrieval on indwelling time; and (3) whether the temporal distribution of infected explants reflects clinical experience. RESULTS: In this series, 20% (507/2527) of explants were performed for infection, with PJI being more commonly implicated in the retrieval of revision implants than of primaries. Infected prostheses were explanted 23.2 months sooner on average than those retrieved for other causes. Within the subset of infected devices, revision components were explanted 11.2 months sooner than primaries, with no appreciable difference observed between hips and knees. Retrieval-based temporal distributions were most similar to PJI studies with endpoint enrollment or long duration follow-up, suggesting a later average onset of infection than reported in comparable clinical studies with short (<10-year) follow-up. CONCLUSIONS: Infection represents a major cause of revision arthroplasty, and is associated with shorter indwelling times in revision components than in primaries. Studies with less than 10 years of follow-up are likely to under-report late PJI.