Providing a computationally derived, mechanically optimised target correction during preoperative planning can improve joint contact mechanics of hip dysplasia treated with periacetabular osteotomy

AIM

Preoperative identification of acetabular corrections that optimally improve joint stability and reduce elevated contact stresses could further reduce osteoarthritis progression in patients with hip dysplasia who are treated with periacetabular osteotomy (PAO). The purpose of this study was to investigate how providing patient-specific, mechanically optimal acetabular reorientations to the surgeon during preoperative planning affected the surgically achieved correction.

METHODS

Preoperative CT scans were used to create patient-specific hip models for 6 patients scheduled for PAO. A simulated acetabular fragment was extracted from the preoperative pelvis model and computationally rotated to simulate candidate acetabular reorientations. For each candidate, discrete element analysis was used to compute contact stresses during walking, which were summed over the gait cycle and scaled by patient age to obtain chronic contact stress-time exposure. The ideal patient-specific reorientation was identified using a cost function that balances minimising chronic stress exposures and achieving surgically acceptable acetabular coverage angles. The optimal reorientation angles and associated contact mechanics were provided to the surgeon preoperatively. After PAO was performed, a model of the surgically achieved correction was created from a postoperative CT scan. Radiographic coverage and contact mechanics were compared between preoperative, optimal, and surgically achieved orientations.

RESULTS

While surgically achieved reorientations were not significantly different from optimal reorientations in radiographically measured lateral (p = 0.094) or anterior (p = 0.063) coverage, surgically achieved reorientations had significantly (p = 0.031) reduced total contact area compared to optimal reorientations. The difference in lateral coverage and peak chronic exposure between surgically achieved and optimal reorientations decreased with increasing surgeon experience using the models (R² = 0.758, R2 = 0.630, respectively).

CONCLUSIONS

Providing hip surgeons with a patient-specific, computationally optimal reorientation during preoperative planning may improve contact mechanics after PAO, which may help reduce osteoarthritis progression in patients with hip dysplasia.

Radiographically successful periacetabular osteotomy does not achieve optimal contact mechanics in dysplastic hips

BACKGROUND

Optimal correction of hip dysplasia via periacetabular osteotomy may reduce osteoarthritis development by reducing damaging contact stress. The objective of this study was to computationally determine if patient-specific acetabular corrections that optimize contact mechanics can improve upon contact mechanics resulting from clinically successful, surgically achieved corrections.

METHODS

Preoperative and postoperative hip models were retrospectively created from CT scans of 20 dysplasia patients treated with periacetabular osteotomy. A digitally extracted acetabular fragment was computationally rotated in 2-degree increments around anteroposterior and oblique axes to simulate candidate acetabular reorientations. From discrete element analysis of each patient's set of candidate reorientation models, a mechanically optimal reorientation that minimized chronic contact stress exposure and a clinically optimal reorientation that balanced improving mechanics with surgically acceptable acetabular coverage angles was selected. Radiographic coverage, contact area, peak/mean contact stress, and peak/mean chronic exposure were compared between mechanically optimal, clinically optimal, and surgically achieved orientations.

FINDINGS

Compared to actual surgical corrections, computationally derived mechanically/clinically optimal reorientations had a median[IQR] 13[4-16]/8[3-12] degrees and 16[6-26]/10[3-16] degrees more lateral and anterior coverage, respectively. Mechanically/clinically optimal reorientations had 212[143-353]/217[111-280] mm2 more contact area and 8.2[5.8-11.1]/6.4[4.5-9.3] MPa lower peak contact stresses than surgical corrections. Chronic metrics demonstrated similar findings (p ≤ 0.003 for all comparisons).

INTERPRETATION

Computationally selected orientations achieved a greater mechanical improvement than surgically achieved corrections; however, many predicted corrections would be considered acetabular over-coverage. Identifying patient-specific corrections that balance optimizing mechanics with clinical constraints will be necessary to reduce the risk of osteoarthritis progression after periacetabular osteotomy.

Design and testing of a personalized noise monitoring system

Agricultural workers are more prone to noise-induced hearing loss than are many other workers. Hearing protection device use among agricultural workers is low, but training can increase hearing protection device use. This work proposes a system designed to automatically inform agricultural workers when they were exposed to noises that exceed the National Institute for Occupational Safety and Health (NIOSH) recommended exposure level. The smartphone-based system worn on the arm uses a noise dosimeter to measure noise exposures throughout the day to within ±2 A-weighted decibels of a Class 2 sound level meter. The device collects location and audio data, which are transferred to a server and presented to the worker on a locally hosted website. The website details noise exposure and helps the worker identify where exposure occurred and what specific tasks exceed NIOSH's recommended exposure limit, putting them at higher risk of noise-induced hearing loss. With this understanding, the worker is expected to adopt behavior changes and better hearing protection use at critical places and times. This pilot study evaluates the accuracy of the noise dosimeter and GPS relative to gold-standard instruments. The system was tested on a farm with outputs compared with gold-standard instruments. A-weighted, 1-sec averaged sound pressure levels and position data were collected while users were performing a variety of tasks indoors and outdoors. The smartphone's external noise dosimeter read within ±2 A-weighted decibels of the Class 2 reference dosimeter 59% of the time. The positioning devices had an average error of sub-4 m. While not perfectly matching gold-standard instruments, the device is capable of identifying and collecting information relative to loud noise events that promote noise-induced hearing loss.

Combining physics-based and Kriging models to improve the estimation of noise exposure

Worker exposure to occupational hazards is traditionally measured by equipping workers with wearable exposure monitors. An emerging alternative measurement first generates time-varying hazard maps from permanent monitors within the facility, then estimating worker exposure by integrating hazard levels traversed in map, following the tracked movement of workers. Complex environments may require many monitors to produce a hazard map with the necessary accuracy, but effective interpolation functions can reduce the required number of monitors needed. This work assesses the effectiveness of three models for accurately interpolating hazard levels among monitors: a traditional Kriging model, a physics-based model, and a hybrid model that combines the Kriging and physics-based models. The effectiveness of each interpolation function was tested with sound levels collected in four environmental settings. These detailed experimental data were used to generate over 10,000 simulation trials, where each trial configured the experimental data into a unique arrangement of simulated monitoring and sampling positions. For each simulation trial, the effectiveness of the three models was assessed with the root mean square error of the sound levels at the simulated sampling positions, using the simulated monitoring positions as input. The interpolated values between the monitored positions were analyzed separately from the extrapolated values beyond the monitored positions. The hybrid model consistently reported among the lowest errors in each trial. The Kriging model performed best for the densest networks (those with the most monitors). Even in these cases, the hybrid model performed within 10% of the Kriging model with less than a third of the monitors. The experiment demonstrates that the hybrid model is highly effective at estimating hazardous sound levels; future work may demonstrate similar advantages for gas and aerosol hazards.

Minimally Trained Analysts Can Perform Fast, Objective Assessment of Orthopedic Technical Skill from Fluoroscopic Images

Skill assessment in orthopedics has traditionally relied on subjective impressions from a supervising surgeon. The feedback derived from these tools may be limited by bias and other practical issues. Objective analysis of intraoperative fluoroscopic images offers an inexpensive, repeatable, and precise assessment strategy without bias. Assessors generally refrain from using the scores of images obtained throughout the operation to evaluate skill for practical reasons. A new system was designed to facilitate rapid analysis of this fluoroscopy via minimally trained analysts. Four expert and four novice analysts independently measured one objective metric for skill using both a custom analysis software and a commercial alternative. Analysts were able to measure the objective metric three times faster when using the custom software, and without a practical difference in accuracy in comparison to the expert analysts using the commercial software. These results suggest that a well-designed fluoroscopy analysis system can facilitate inexpensive, reliable, and objective assessment of surgical skills.

A Vision for Using Simulation & Virtual Coaching to Improve the Community Practice of Orthopedic Trauma Surgery

BACKGROUND

Many orthopedic surgeries involve the challenging integration of fluoroscopic image interpretation with skillful tool manipulation to enable procedures to be performed through less invasive approaches. Simulation has proved beneficial for teaching and improving these skills for residents, but similar benefits have not yet been realized for practicing orthopedic surgeons. A vision is presented to elevate community orthopedic practice and improve patient safety by advancing the use of simulators for training and assessing surgical skills.

METHODS

Key elements of this vision that are established include 1) methods for the objective and rigorous assessment of the performance of practicing surgeons now exist, 2) simulators are sufficiently mature and sophisticated that practicing surgeons will use them, and 3) practicing surgeons can improve their performance with appropriate feedback and coaching.

RESULTS

Data presented indicate that surgical performance can be adequately and comparably measured using structured observations made by experts or non-expert crowds, with the crowdsourcing approach being more expedient and less expensive. Rigorous measures of the surgical result and intermediate objectives obtained semi-automatically from intra-operative fluoroscopic image sequences can distinguish performances of experts from novices. Experience suggests that practicing orthopedic surgeons are open to and can be constructively engaged by a family of mature simulators as a means to evaluate and improve their surgical skills.

CONCLUSIONS

The results presented support our contention that new objective assessment measures are sufficient for evaluating the performance of working surgeons. The novel class of orthopedic surgical simulators available were tested and approved by practicing physicians. There exists a clear opportunity to combine purpose-designed simulator exercises with virtual coaching to help practicing physicians retain, retrain, and improve their technical skills. This will ultimately reduce cost, increase the quality of care, and decrease complication rates.

CLINICAL RELEVANCE

This vision articulates a means to boost the confidence of practitioners and ease their anxiety so that they perform impactful procedures more often in community hospitals, which promises to improve treatment and reduce the cost of care while keeping patients closer to their homes and families.

Modification of Enrichment Protocols for TECRA Listeria Visual Immunoassay Method 995.22: Collaborative Study

A collaborative study was conducted to validate new enrichment methods for the TECRA Listeria Visual Immunoassay (TLVIA). These new methods incorporate a newly formulated medium, TECRA Listeria Enrichment Broth, which does not contain the highly toxic antifungal agent, cycloheximide. The new procedures will provide an alternative to the enrichment procedures described in AOAC Method 995.22. Three food types (raw ground beef, lettuce, and ice cream) were analyzed in the United States, and 2 food types (cooked turkey and cooked fish fillets) were analyzed in Australasia. Thirty collaborators participated in the study, 16 in Australasia and 14 in the United States. With the exception of one batch of ground beef, comparison of the proportion of positive test portions (p ≥ 0.05) showed no significant difference between the TLVIA and the reference method for the 5 foods at 3 inoculation levels. For the one batch of naturally contaminated raw ground beef, the TLVIA gave significantly more confirmed positive results than the reference method.

Mapping Occupational Hazards with a Multi-sensor Network in a Heavy-Vehicle Manufacturing Facility

Due to their small size, low-power demands, and customizability, low-cost sensors can be deployed in collections that are spatially distributed in the environment, known as sensor networks. The literature contains examples of such networks in the ambient environment; this article describes the development and deployment of a 40-node multi-hazard network, constructed with low-cost sensors for particulate matter (SHARP GP2Y1010AU0F), carbon monoxide (Alphasense CO-B4), oxidizing gases (Alphasense OX-B421), and noise (developed in-house) in a heavy-vehicle manufacturing facility. Network nodes communicated wirelessly with a central database in order to record hazard measurements at 5-min intervals. Here, we report on the temporal and spatial measurements from the network, precision of network measurements, and accuracy of network measurements with respect to field reference instruments through 8 months of continuous deployment. During typical production periods, 1-h mean hazard levels ± standard deviation across all monitors for particulate matter (PM), carbon monoxide (CO), oxidizing gases (OX), and noise were 0.62 ± 0.2 mg m-3, 7 ± 2 ppm, 155 ± 58 ppb, and 82 ± 1 dBA, respectively. We observed clear diurnal and weekly temporal patterns for all hazards and daily, hazard-specific spatial patterns attributable to general manufacturing processes in the facility. Processes associated with the highest hazard levels were machining and welding (PM and noise), staging (CO), and manual and robotic welding (OX). Network sensors exhibited varying degrees of precision with 95% of measurements among three collocated nodes within 0.21 mg m-3 for PM, 0.4 ppm for CO, 9 ppb for OX, and 1 dBA for noise of each other. The median percent bias with reference to direct-reading instruments was 27%, 11%, 45%, and 1%, for PM, CO, OX, and noise, respectively. This study demonstrates the successful long-term deployment of a multi-hazard sensor network in an industrial manufacturing setting and illustrates the high temporal and spatial resolution of hazard data that sensor and monitor networks are capable of. We show that network-derived hazard measurements offer rich datasets to comprehensively assess occupational hazards. Our network sets the stage for the characterization of occupational exposures on the individual level with wireless sensor networks.

Efficacy of Paired Electrochemical Sensors for Measuring Ozone Concentrations

Typical low-cost electrochemical sensors for ozone (O3) are also highly responsive to nitrogen dioxide (NO2). Consequently, a single sensor's response to O3 is indistinguishable from its response to NO2. Recently, a method for quantifying O3 concentrations became commercially available (Alphasense Ltd., Essex, UK): collocating a pair of sensors, a typical oxidative gas sensor that responds to both O3 and NO2 (model OX-B431) and a second similar sensor that filters O3 and responds only to NO2 (model NO2-B43F). By pairing the two sensors, O3 concentrations can be calculated. We calibrated samples of three NO2-B43F sensors and three OX-B431 sensors with NO2 and O3 exclusively and conducted mixture experiments over a range of 0-1.0 ppm NO2 and 0-125 ppb O3 to evaluate the ability of the paired sensors to quantify NO2 and O3 concentrations in mixture. Although the slopes of the response among our samples of three sensors of each type varied by as much as 37%, the individual response of the NO2-B43F sensors to NO2 and OX-B431 sensors to NO2 and O3 were highly linear over the concentrations studied (R2 ≥ 0.99). The NO2-B43F sensors responded minimally to O3 gas with statistically non-significant slopes of response. In mixtures of NO2 and O3, quantification of NO2 was generally accurate with overestimates up to 29%, compared to O3, which was generally underestimated by as much as 187%. We observed changes in sensor baseline over 4 days of experiments equivalent to 34 ppb O3, prompting an alternate method of calculating concentrations by baseline-correcting sensor signal. The baseline-correction method resulted in underestimates of NO2 up to 44% and decreases in the underestimation of O3 up to 107% for O3. Both methods for calculating gas concentrations progressively underestimated O3 concentrations as the ratio of NO2 signal to O3 signal increased. Our results suggest that paired NO2-B43F and OX-B431 sensors permit quantification of NO2 and O3 in mixture, but that O3 concentration estimates are less accurate and precise than those for NO2.

Low-Cost, Distributed Environmental Monitors for Factory Worker Health

An integrated network of environmental monitors was developed to continuously measure several airborne hazards in a manufacturing facility. The monitors integrated low-cost sensors to measure particulate matter, carbon monoxide, ozone and nitrogen dioxide, noise, temperature and humidity. The monitors were developed and tested in situ for three months in several overlapping deployments, before a full cohort of 40 was deployed in a heavy vehicle manufacturing facility for a year of data collection. The monitors collect data from each sensor and report them to a central database every 5 min. The work includes an experimental validation of the particle, gas and noise monitors. The R² for the particle sensor ranges between 0.98 and 0.99 for particle mass densities up to 300 μg/m³. The R² for the carbon monoxide sensor is 0.99 for concentrations up to 15 ppm. The R² for the oxidizing gas sensor is 0.98 over the sensitive range from 20 to 180 ppb. The noise monitor is precise within 1% between 65 and 95 dBA. This work demonstrates the capability of distributed monitoring as a means to examine exposure variability in both space and time, building an important preliminary step towards a new approach for workplace hazard monitoring.

An inexpensive sensor for noise

Noise is a pervasive workplace hazard that varies spatially and temporally. The cost of direct-reading instruments for noise hampers their use in a network. The objectives for this work were to: (1) develop an inexpensive noise sensor (<$100) that measures A-weighted sound pressure levels within ±2 dBA of a Type 2 sound level meter (SLM; ∼$1,800); and (2) evaluate 50 noise sensors for use in an inexpensive sensor network. The inexpensive noise sensor consists of an electret condenser microphone, an amplifier circuit, and a microcontroller with a small form factor (28 mm by 47 mm by 9 mm) than can be operated as a stand-alone unit. Laboratory tests were conducted to evaluate 50 of the new sensors at 5 sound levels: (1) ambient sound in a quiet office; (2) 3 pink noise test signals from 65-85 dBA in 10 dBA increments; and (3) 94 dBA using a SLM calibrator. Ninety-four percent of the noise sensors (n = 46) were within ±2 dBA of the SLM for sound levels from 65-94 dBA. As sound level increased, bias decreased, ranging from 18.3% in the quiet office to 0.48% at 94 dBA. Overall bias of the sensors was 0.83% across the 75 dBA to 94 dBA range. These sensors are available for a variety of uses and can be customized for many applications, including incorporation into a stationary sensor network for continuous monitoring of noise in manufacturing environments.

DESIGN OF A PERCUTANEOUS ARTICULAR FRACTURE REDUCTION SIMULATOR

The American Board of Orthopaedic Surgery has mandated dedicated skills training for first-year orthopedic surgical residents.1 Most residency programs address this requirement with training exercises with cadavers and plastic foam bones. Some programs incorporate one or more simulators in their skills training, including several sophisticated virtual reality simulators and a variety of low-tech simulators. Simulators are helpful because they can provide repeatable educational experiences and quantitative performance assessment. Unfortunately, few simulators have been developed for orthopedic trauma skills training. Even fewer simulators have been developed and validated with more advanced students, such as residents in their 3rd or 4th year of training, and for more complex surgeries. In contrast to the completely virtual surgical simulation using haptic feedback devices and sophisticated renderings of soft tissue deformation, our group has chosen to use physical models, real surgical instruments and position tracking in conjunction with virtual reality.2–4 The physical models provide experience with the surgical tools, and enable more realistic hand movements and haptic cue feedback.

Evaluation of low-cost electro-chemical sensors for environmental monitoring of ozone, nitrogen dioxide, and carbon monoxide

Development of an air quality monitoring network with high spatio-temporal resolution requires installation of a large number of air pollutant monitors. However, state-of-the-art monitors are costly and may not be compatible with wireless data logging systems. In this study, low-cost electro-chemical sensors manufactured by Alphasense Ltd. for detection of CO and oxidative gases (predominantly O₃ and NO₂) were evaluated. The voltages from three oxidative gas sensors and three CO sensors were recorded every 2.5 sec when exposed to controlled gas concentrations in a 0.125-m³ acrylic glass chamber. Electro-chemical sensors for detection of oxidative gases demonstrated sensitivity to both NO₂ and O₃ with similar voltages recorded when exposed to equivalent environmental concentrations of NO₂ or O₃ gases, when evaluated separately. There was a strong linear relationship between the recorded voltages and target concentrations of oxidative gases (R² > 0.98) over a wide range of concentrations. Although a strong linear relationship was also observed for CO concentrations below 12 ppm, a saturation effect was observed wherein the voltage only changes minimally for higher CO concentrations (12-50 ppm). The nonlinear behavior of the CO sensors implied their unsuitability for environments where high CO concentrations are expected. Using a manufacturer-supplied shroud, sensors were tested at 2 different flow rates (0.25 and 0.5 Lpm) to mimic field calibration of the sensors with zero air and a span gas concentration (2 ppm NO2 or 15 ppm CO). As with all electrochemical sensors, the tested devices were subject to drift with a bias up to 20% after 9 months of continuous operation. Alphasense CO sensors were found to be a proper choice for occupational and environmental CO monitoring with maximum concentration of 12 ppm, especially due to the field-ready calibration capability. Alphasense oxidative gas sensors are usable only if it is valuable to know the sum of the NO₂ and O₃ concentrations.

An autoimmune-associated variant in PTPN2 reveals an impairment of IL-2R signaling in CD4(+) T cells

The IL-2/IL-2R signaling pathway has an important role in autoimmunity. Several genes identified in genome-wide association (GWA) studies encode proteins in the IL-2/IL-2R signaling cascade that are associated with autoimmune diseases. One of these, PTPN2, encodes a protein tyrosine phosphatase that is highly expressed in T cells and regulates cytokine signaling. An intronic risk allele in PTPN2, rs1893217(C), correlated with decreased IL-2R signaling in CD4(+) T cells as measured by phosphorylation of STAT5 (phosphorylated STAT5 (pSTAT5)). We modeled an additive single nucleotide polymorphism (SNP) genotype, in which each copy of the risk allele conferred a decrease in IL-2R signaling (P=4.4 × 10(-8)). Decreased pSTAT5 impacted IL-2Rβ chain signaling resulting in reduced FOXP3 expression in activated cells. This phenotype was not due to overt differences in expression of the IL-2R, molecules in the IL-2R signaling cascade or defects in STAT5. However, the rs1893217(C) risk variant did correlate with decreased PTPN2 expression in CD4(+)CD45RO T cells (P=0.0002). Thus, the PTPN2rs1893217(C) risk allele associated with reduced pSTAT5 in response to IL-2 and reduced PTPN2 expression. Together, these data suggest that decreased expression of PTPN2 may indirectly modulate IL-2 responsiveness. These findings, identified through genotype/phenotype relationships, may lead to identification of novel mechanisms underlying dysregulation of cytokine signaling in autoimmunity.