Simulation of the objective occlusion effect induced by bone-conducted stimulation using a three-dimensional finite-element model of a human head.

The occlusion effect (OE) refers to the phenomenon that more bone-conducted physiological sounds are transmitted into the earcanal when it is blocked and may cause discomfort on users of hearing protection devices. Models have been proposed to study the OE as they can help understand the physical mechanisms and can be used to evaluate the individual contribution on the OE of the factors that may affect it (i.e., occlusion device, ear anatomy, and stimulation). The existing finite element models developed to study the OE are limited by their truncated ear geometries. In order to progress in the understanding of the OE, the goal of this paper is to develop a finite element model of an entire head to predict the sound pressure field in its earcanals, open or occluded by earplugs. The model is evaluated by comparing the computed input mechanical impedances and OEs in various configurations with literature data. It is able to reproduce common behavior of the OE reported in the literature. In addition, the model is used to assess the effects on the simulated OEs of several parameters, including the modeling of the external air, the boundary condition at the head base and the material properties.

Neuroimage signature from salient keypoints is highly specific to individuals and shared by close relatives.

Neuroimaging studies typically adopt a common feature space for all data, which may obscure aspects of neuroanatomy only observable in subsets of a population, e.g. cortical folding patterns unique to individuals or shared by close relatives. Here, we propose to model individual variability using a distinctive keypoint signature: a set of unique, localized patterns, detected automatically in each image by a generic saliency operator. The similarity of an image pair is then quantified by the proportion of keypoints they share using a novel Jaccard-like measure of set overlap. Experiments demonstrate the keypoint method to be highly efficient and accurate, using a set of 7536 T1-weighted MRIs pooled from four public neuroimaging repositories, including twins, non-twin siblings, and 3334 unique subjects. All same-subject image pairs are identified by a similarity threshold despite confounds including aging and neurodegenerative disease progression. Outliers reveal previously unknown data labeling inconsistencies, demonstrating the usefulness of the keypoint signature as a computational tool for curating large neuroimage datasets.

Potential of iterative reconstruction for maxillofacial cone beam CT imaging: technical note.

Iterative reconstruction has been proven to be an effective tool for low-dose computed tomography imaging. However, this technology is currently not available in commercial diagnostic maxillofacial cone beam CT. For this technical note, an iterative reconstruction technique was applied to cone beam CT raw data of two maxillofacial clinical cases to explore its potential for dose reduction and metal artifact reduction. Low-dose imaging was emulated by using only fractions of the clinical projection dataset. The reconstruction algorithms tested were filtered backprojection (FBP) as a reference method, and a total variation minimization (TV) regularized ordered subsets convex (OSC-TV) method as the iterative technique. Upon qualitative examination, the OSC-TV technique was found to conserve most diagnostic information using half the projections. Test images have also shown that at 1/4 of the projections, OSC-TV was more robust than FBP with respect to streaking and metal artifacts.

Iterative reconstruction for image enhancement and dose reduction in diagnostic cone beam CT imaging.

BACKGROUND: Iterative reconstruction is well-established in diagnostic multidetector computed tomography (MDCT) for dose reduction and image quality enhancement. Its application to diagnostic cone beam computed tomography (CBCT) is only emerging and warrants a quantitative evaluation. METHODS: Several phantoms and a canine head specimen were imaged using a commercially available small-field CBCT scanner. Raw projection data were reconstructed using the Feldkamp-Davis-Kress (FDK) method with different filters, including denoising via total variation (TV) minimization (FDK-TV). Iterative reconstruction was carried out using the TV-regularized ordered subsets convex technique (OSC-TV). Signal-to-noise ratio (SNR), noise power spectrum (NPS) and spatial resolution of images were estimated. Dose levels were measured via the weighted computed tomography dose index, while low-dose image quality degradation was estimated via structural similarity (SSIM). RESULTS: OSC-TV and FDK-TV were shown to significantly improve image signal-to-noise ratio (SNR) compared to FDK with a standard filter, 5.8 and 4.0 times, respectively. Spatial resolution attained with different algorithms varied moderately across different experiments. For low-dose acquisitions, image quality decreased dramatically for FDK but not for FDK-TV nor OSC-TV. For low-dose canine head images acquired using about 1/5 of the dose compared to a reference image, SSIM dropped to about 0.3 for FDK, while remaining at 0.92 for FDK-TV and 0.96 for OSC-TV. CONCLUSION: OSC-TV was shown to improve image quality compared to FDK and FDK-TV. Moreover, this iterative approach allowed for significant dose reduction while maintaining image quality.

A perceptual map for gait symmetry quantification and pathology detection.

BACKGROUND: The gait movement is an essential process of the human activity and the result of collaborative interactions between the neurological, articular and musculoskeletal systems, working efficiently together. This explains why gait analysis is important and increasingly used nowadays for the diagnosis of many different types (neurological, muscular, orthopedic, etc.) of diseases. This paper introduces a novel method to quickly visualize the different parts of the body related to an asymmetric movement in the human gait of a patient for daily clinical usage. The proposed gait analysis algorithm relies on the fact that the healthy walk has (temporally shift-invariant) symmetry properties in the coronal plane. The goal is to provide an inexpensive and easy-to-use method, exploiting an affordable consumer depth sensor, the Kinect, to measure the gait asymmetry and display results in a perceptual way. METHOD: We propose a multi-dimensional scaling mapping using a temporally shift invariant distance, allowing us to efficiently visualize (in terms of perceptual color difference) the asymmetric body parts of the gait cycle of a subject. We also propose an index computed from this map and which quantifies locally and globally the degree of asymmetry. RESULTS: The proposed index is proved to be statistically significant and this new, inexpensive, marker-less, non-invasive, easy to set up, gait analysis system offers a readable and flexible tool for clinicians to analyze gait characteristics and to provide a fast diagnostic. CONCLUSION: This system, which estimates a perceptual color map providing a quick overview of asymmetry existing in the gait cycle of a subject, can be easily exploited for disease progression, recovery cues from post-operative surgery (e.g., to check the healing process or the effect of a treatment or a prosthesis) or might be used for other pathologies where gait asymmetry might be a symptom.

A rule-based algorithm can output valid surgical strategies in the treatment of AIS.

BACKGROUND: Variability in surgical strategies for the treatment of adolescent idiopathic scoliosis (AIS) has been demonstrated despite the existence of classifications to guide selection of AIS curves to include in fusion. Decision trees and rule-based algorithms have demonstrated their potential to improve reliability of AIS classification because of their systematic approach and they have also been proposed in algorithms for selection of instrumentation levels in scoliosis. Our working hypothesis is that a rule-based algorithm with a knowledge base extracted from the literature can efficiently output surgical strategies alternatives for a given AIS case. Our objective is to develop a rule-based algorithm based on peer-reviewed literature to output alternative surgical strategies for approach and levels of fusion. METHODS: A literature search of all English Manuscripts published between 2000 and December 2009 with Pubmed and Google scholar electronic search using the following keywords: "adolescent idiopathic scoliosis" and "surgery" alternatively with "levels of fusion" or "approach". All returned abstracts were screened for contents that could contain rules to include in the knowledge base. A dataset of 1,556 AIS cases treated surgically was used to test the surgical strategy rule-based algorithm (SSRBA) and evaluate how many surgical treatments are covered by the algorithm. The SSRBA was programmed using Matlab. Descriptive statistic was used to evaluate the ability of the rule-based algorithm to cover all treatment alternatives. RESULTS: A SSRBA was successfully developed following Lenke classification's concept that the spine is divided into three curve segments [proximal thoracic (PT), main thoracic (MT) and thoracolumbar/lumbar (TL)]. Each of the 1,556 AIS patients in the dataset was ran through the SSRBA. It proposed an average of 3.78 (±2.06) surgical strategies per case. Overall, the SSRBA is able to match the treatment offered by the surgeon in approach and level of fusion 70 % of the time (with one vertebral level leeway). CONCLUSION: This study is to the author's knowledge the first attempt at proposing an algorithm to output all surgical alternatives for a given AIS case. It uses a rule-based algorithm with a knowledge base extracted from peer-reviewed literature in an area with great variability. When tested against a database of AIS patients treated surgically, the SSRBA developed has the ability to propose a surgical plan with respect to approach and levels of fusion that match the surgeon's plan in a great majority of cases. Since this SSRBA seems to output multiple valid surgical strategies, it could allow the comparisons of various strategies and the outcomes achieved in similar cases in large databases for a given case and guide surgical treatment.

Quantitative pivot shift assessment using combined inertial and magnetic sensing.

PURPOSE: The purpose of the study was to demonstrate the feasibility of a new measurement system using micro-electromechanical systems (MEMS)-based sensors for quantifying the pivot shift phenomenon. METHODS: The pivot shift test was performed on 13 consecutive anterior cruciate ligament-deficient subjects by an experienced examiner while femur and tibia kinematics were recorded using two inertial sensors each composed of an accelerometer, gyroscope and magnetometer. The gravitational component of the acquired data was removed using a novel method for estimating sensor orientations. Correlation between the clinical pivot shift grade and acceleration and velocity parameters was measured using Spearman's rank correlation coefficients. RESULTS: The pivot shift phenomenon was best characterized as a drop in femoral acceleration observed at the time of reduction. The correlation between the femoral acceleration drop and the clinical grade was shown to be very strong (r = 0.84, p < 0.0001). CONCLUSIONS: The present study demonstrates the feasibility of quantifying the pivot shift using MEMS-based sensors and removing the gravitational component of acceleration using an estimation of sensor orientation for improved correlation to the clinical grade.

Automatic lower limb bone segmentation in radiographs with different orientations and fields of view based on a contextual network.

PURPOSE: Bone identification and segmentation in X-ray images are crucial in orthopedics for the automation of clinical procedures, but it often involves some manual operations. In this work, using a modified SegNet neural network, we automatically identify and segment lower limb bone structures on radiographs presenting various fields of view and different patient orientations. METHODS: A wide contextual neural network architecture is proposed to perform a high-quality pixel-wise semantic segmentation on X-ray images presenting structures with a similar appearance and strong superposition. The proposed architecture is based on the premise that every output pixel on the label map has a wide receptive field. This allows the network to capture both global and local contextual information. The overlapping between structures is handled with additional labels. RESULTS: The proposed approach was evaluated on a test dataset composed of 70 radiographs with entire and partial bones. We obtained an average detection rate of 98.00% and an average Dice coefficient of 95.25 ± 9.02% across all classes. For the challenging subset of images with high superposition, we obtained an average detection rate of 96.36% and an average Dice coefficient of 93.81 ± 10.03% across all classes. CONCLUSION: The results show the effectiveness of the proposed approach in segmenting and identifying lower limb bone structures and overlapping structures in radiographs with strong bone superposition and highly variable configurations, as well as in radiographs containing only small pieces of bone structures.

Automatic Pulp and Teeth Three-Dimensional Modeling of Single and Multi-Rooted Teeth Based on Cone-Beam Computed Tomography Imaging: A Promising Approach With Clinical and Therapeutic Outcomes.

Background Cone-beam computed tomography (CBCT) imaging offers high-quality three-dimensional (3D) acquisition with great spatial resolution, given by the use of isometric voxels, when compared with conventional computed tomography (CT). The current literature supports a median reduction of 76% (up to 85% reduction) of patients' radiation exposure when imaged by CBCT versus CT. Clinical applications of CBCT imaging can benefit both medical and dental professions. Because these images are digital, the use of algorithms can facilitate the diagnosis of pathologies and the management of patients. There is pertinence to developing rapid and efficient segmentation of teeth from facial volumes acquired with CBCT. Methodology In this paper, a segmentation algorithm using heuristics based on pulp and teeth anatomy as a pre-personalized model is proposed for both single and multi-rooted teeth. Results A quantitative analysis was performed by comparing the results of the algorithm to a gold standard obtained from manual segmentation using the Dice index, average surface distance (ASD), and Mahalanobis distance (MHD) metrics. Qualitative analysis was also performed between the algorithm and the gold standard of 78 teeth. The Dice index average for all pulp segmentation (n = 78) was 83.82% (SD = 6.54%). ASD for all pulp segmentation (n = 78) was 0.21 mm (SD = 0.34 mm). Pulp segmentation compared with MHD averages was 0.19 mm (SD = 0.21 mm). The results of teeth segmentation metrics were similar to pulp segmentation metrics. For the total teeth (n = 78) included in this study, the Dice index average was 92% (SD = 13.10%), ASD was low at 0.19 mm (SD = 0.15 mm), and MHD was 0.11 mm (SD = 0.09 mm). Despite good quantitative results, the qualitative analysis yielded fair results due to large categories. When compared with existing automatic segmentation methods, our approach enables an effective segmentation for both pulp and teeth. Conclusions Our proposed algorithm for pulp and teeth segmentation yields results that are comparable to those obtained by the state-of-the-art methods in both quantitative and qualitative analysis, thus offering interesting perspectives in many clinical fields of dentistry.

Computer algorithms and applications used to assist the evaluation and treatment of adolescent idiopathic scoliosis: a review of published articles 2000-2009.

Adolescent idiopathic scoliosis (AIS) is a complex spinal deformity whose assessment and treatment present many challenges. Computer applications have been developed to assist clinicians. A literature review on computer applications used in AIS evaluation and treatment has been undertaken. The algorithms used, their accuracy and clinical usability were analyzed. Computer applications have been used to create new classifications for AIS based on 2D and 3D features, assess scoliosis severity or risk of progression and assist bracing and surgical treatment. It was found that classification accuracy could be improved using computer algorithms that AIS patient follow-up and screening could be done using surface topography thereby limiting radiation and that bracing and surgical treatment could be optimized using simulations. Yet few computer applications are routinely used in clinics. With the development of 3D imaging and databases, huge amounts of clinical and geometrical data need to be taken into consideration when researching and managing AIS. Computer applications based on advanced algorithms will be able to handle tasks that could otherwise not be done which can possibly improve AIS patients' management. Clinically oriented applications and evidence that they can improve current care will be required for their integration in the clinical setting.

Passive contribution of the rotator cuff to abduction and joint stability.

PURPOSE: The purpose of this study is to compare shoulder joint biomechanics during abduction with and without intact non-functioning rotator cuff tissue. METHODS: A cadaver model was devised to simulate the clinical findings seen in patients with a massive cuff tear. Eight full upper limb shoulder specimens were studied. Initially, the rotator cuff tendons were left intact, representing a non-functional rotator cuff, as seen in suprascapular nerve paralysis or in cuff repair with a patch. Subsequently, a massive rotator cuff tear was re-created. Three-dimensional kinematics and force requirements for shoulder abduction were analyzed for each condition using ten abduction cycles in the plane of the scapula. RESULTS: Mediolateral displacements of the glenohumeral rotation center (GHRC) during abduction with an intact non-functioning cuff were minimal, but massive cuff tear resulted in significant lateral displacement of the GHRC (p < 0.013). Similarly, massive cuff tear caused increased superior migration of the GHRC during abduction compared with intact non-functional cuff (p < 0.01). From 5 to 30° of abduction, force requirements were significantly less with an intact non-functioning cuff than with massive cuff tear (p < 0.009). CONCLUSION: During abduction, an intact but non-functioning rotator cuff resulted in decreased GHRC displacement in two axes as well as lowered the force requirement for abduction from 5 to 30° as compared with the results following a massive rotator cuff tear. This provides insight into the potential biomechanical effect of repairing massive rotator cuff tears with a biological or synthetic "patch," which is a new treatment for massive cuff tear.

Tibial Tunnel Placement in ACL Reconstruction Using a Novel Grid and Biplanar Stereoradiographic Imaging.

BACKGROUND: Nonanatomic graft placement is a frequent cause of anterior cruciate ligament reconstruction (ACLR) failure, and it can be attributed to either tibial or femoral tunnel malposition. To describe tibial tunnel placement in ACLR, we used EOS, a low-dose biplanar stereoradiographic imaging modality, to create a comprehensive grid that combines anteroposterior (AP) and mediolateral (ML) coordinates. PURPOSE: To (1) validate the automated grid generated from EOS imaging and (2) compare the results with optimal tibial tunnel placement. STUDY DESIGN: Descriptive laboratory study. METHODS: Using EOS, 3-dimensional models were created of the knees of 37 patients who had undergone ACLR. From the most medial, lateral, anterior, and posterior points on the tibial plateau of the EOS 3-dimensional model for each patient, an automated and personalized grid was generated from 2 independent observers' series of reconstructions. To validate this grid, each observer also manually measured the ML and AP distances, the medial proximal tibial angle (MPTA), and the tibial slope for each patient. The ideal tibial tunnel placement, as described in the literature, was compared with the actual tibial tunnel grid coordinates of each patient. RESULTS: The automated grid metrics for observer 1 gave a mean (95% CI) AP depth of 54.7 mm (53.4-55.9), ML width of 75.0 mm (73.3-76.6), MPTA of 84.9° (83.7-86.0), and slope of 7.2° (5.4-9.0). The differences with corresponding manual measurements were means (95% CIs) of 2.4 mm (1.4-3.4 mm), 0.5 mm (-1.3 to 2.2 mm), 1.2° (-0.4° to 2.9°), and -0.4° (-2.1° to 1.2°), respectively. The correlation between automated and manual measurements was r = 0.78 for the AP depth, r = 0.68 for the ML width, r = 0.18 for the MPTA, and r = 0.44 for the slope. The center of the actual tibial aperture on the plateau was a mean of 5.5 mm (95% CI, 4.8-6.1 mm) away from the referenced anatomic position, with a tendency toward more medial placement. CONCLUSION: The automated grid created using biplanar stereoradiographic imaging provided a novel, precise, and reproducible description of the tibial tunnel placement in ACLR. CLINICAL RELEVANCE: This technique can be used during preoperative planning, intraoperative guidance, and postoperative evaluation of tibial tunnel placement in ACLR.

Clinical Evaluation of In-House-Produced 3D-Printed Nasopharyngeal Swabs for COVID-19 Testing.

3D-printed alternatives to standard flocked swabs were rapidly developed to provide a response to the unprecedented and sudden need for an exponentially growing amount of diagnostic tools to fight the COVID-19 pandemic. In light of the anticipated shortage, a hospital-based 3D-printing platform was implemented in our institution for the production of swabs for nasopharyngeal and oropharyngeal sampling based on the freely available, open-source design provided to the community by University of South Florida's Health Radiology and Northwell Health System teams as a replacement for locally used commercial swabs. Validation of our 3D-printed swabs was performed with a head-to-head diagnostic accuracy study of the 3D-printed "Northwell model" with the cobas PCR Media® swab sample kit. We observed an excellent concordance (total agreement 96.8%, Kappa 0.936) in results obtained with the 3D-printed and flocked swabs, indicating that the in-house 3D-printed swab could be used reliably in the context of a shortage of flocked swabs. To our knowledge, this is the first study to report on autonomous hospital-based production and clinical validation of 3D-printed swabs.

Ultrasound B-scan image simulation, segmentation, and analysis of the equine tendon.

PURPOSE: The hypothesis is that an imaging technique based on decompression and segmentation of B-scan images with morphological operators can provide a measurement of the integrity of equine tendons. METHODS: Two complementary approaches were used: (i) Simulation of B-scan images to better understand the relationship between image properties and their underlying biological structural contents and (ii) extraction and quantification from B-scan images of tendon structures identified in step (i) to diagnose the status of the superficial digital flexor tendon (SDFT) by using the proposed imaging technique. RESULTS: The simulation results revealed that the interfascicular spaces surrounding fiber fascicle bundles were the source of ultrasound reflection and scattering. By extracting these fascicle bundles with the proposed imaging technique, quantitative results from clinical B-scan images of eight normal and five injured SDFTs revealed significant differences in fiber bundle number and areas: mean values were 50 (+/- 11) and 1.33(+/- 0.36) mm2 for the normal SDFT data set. Different values were observed for injured SDFTs where the intact mean fiber bundle number decreased to 40 (+/- 7) (p = 0.016); inversely, mean fiber bundle areas increased to 1.83 (+/- 0.25) mm2 (p = 0.008), which indicate disruption of the thinnest interfascicular spaces and of their corresponding fiber fascicle bundles where lesions occurred. CONCLUSIONS: To conclude, this technique may provide a tool for the rapid assessment and characterization of tendon structures to enable clinical identification of the integrity of the SDFT.

Developmental spondylolisthesis: is slip angle related to quality of life?

Lumbosacral kyphosis (LSK) is considered to be an important aspect of the deformity in adolescent developmental spondylolisthesis, but its clinical impact is not known. The purpose of this study was to clarify if slip angle (SA), a parameter commonly used to measure LSK, has a significant impact on the quality of life of patient with spondylolisthesis. Eighty-six patients with lumbosacral developmental spondylolisthesis were evaluated. There were 67 low-grade and 19 high-grade spondylolisthesis. All patients completed the SF-12v2 questionnaires. The score of the mental and physical component summary (MCS and PCS) of SF-12v2 were correlated with the slip angle. The correlation of SA was only significant with PCS and not with MCS. PCS decreased significantly with increasing SA (Spearman's rho=-0.40, p<0.001). LSK has a significant impact on the physical aspect of the quality of life of adolescent with spondylolisthesis. LSK is an important part of the deformity in developmental spondylolisthesis and should be included in the routine radiological evaluation of patient with spondylolisthesis.

The effect of anterolateral ligament reconstruction on knee constraint: A computer model-based simulation study.

BACKGROUND: To determine the influence of anterolateral ligament reconstruction (ALLR) on knee constraint through the analysis of knee abduction (valgus) moment when the knee is subjected to external translational (anterior) or rotational (internal) loads. METHODS: A knee computer model simulated from a three-dimensional computed tomography scan of healthy male was implemented for this study. Three groups were designed: (1) intact knee, (2) combined Anterior Cruciate Ligament (ACL) and Antero-Lateral Complex (ALC) deficient knee, and (3) combined ACL and Antero- lateral Ligament (ALL) reconstructed knee. The reconstructed knee group was subdivided into four groups according to attachment of reconstructed anterolateral ligament to the femoral epicondyle. Each group of simulated knees was placed at 0°, 10°, 20°, 30°, 40° and 50° of knee flexion. For each position an external anterior (drawer) 90-N force or a five-newton meter internal rotation moment was applied to the tibia. The interaction effect between the group of knees and knee flexion angle (0-50°) on knee kinematics and knee abduction moment under external loads was tested. RESULTS: When reconstructed knees were subjected to a 90-N anterior force or a five-newton meter internal rotation moment there was significant reduction in anterior translation and internal rotation compared with deficient knees. Only the ALLR procedure using posterior and proximal femoral attachment sites for graft fixation combined with ACL reconstruction allowed similar mechanical behavior to that observed in the intact knee. CONCLUSIONS: Combined ACL and ALLR using a minimally invasive method in an anatomically reproducible manner prevents excessive anterior translation and internal rotation. Using postero-proximal femoral attachment tunnel for reconstruction of ALL does not produce overconstraint of the lateral tibiofemoral compartment.

Femoral Tunnel Placement Analysis in ACL Reconstruction Through Use of a Novel 3-Dimensional Reference With Biplanar Stereoradiographic Imaging.

BACKGROUND: The femoral-sided anatomic footprint of the anterior cruciate ligament (ACL) has been widely studied during the past decades. Nonanatomic placement is an important cause of ACL reconstruction (ACLR) failure. PURPOSE: To describe femoral tunnel placement in ACLR through use of a comprehensive 3-dimensional (3D) cylindrical coordinate system combining both the traditional clockface technique and the quadrant method. Our objective was to validate this technique and evaluate its reproducibility. STUDY DESIGN: Descriptive laboratory study. METHODS: The EOS Imaging System was used to make 3D models of the knee for 37 patients who had undergone ACLR. We designed an automated cylindrical reference software program individualized to the distal femoral morphology of each patient. Cylinder parameters were collected from 2 observers' series of 3D models. Each independent observer also manually measured the corresponding parameters using a lateral view of the 3D contours and a 2-dimensional stereoradiographic image for the corresponding patient. RESULTS: The average cylinder produced from the first observer's EOS 3D models had a 30.0° orientation (95% CI, 28.4°-31.5°), 40.4 mm length (95% CI, 39.3-41.4 mm), and 19.3 mm diameter (95% CI, 18.6-20.0 mm). For the second observer, these measurements were 29.7° (95% CI, 28.1°-31.3°), 40.7 mm (95% CI, 39.7-41.8 mm), and 19.7 mm (95% CI, 18.8-20.6 mm), respectively. Our method showed moderate intertest intraclass correlation among all 3 measuring techniques for both length (r = 0.68) and diameter (r = 0.63) but poor correlation for orientation (r = 0.44). In terms of interobserver reproducibility of the automated EOS 3D method, similar results were obtained: moderate to excellent correlations for length (r = 0.95; P < .001) and diameter (r = 0.66; P < .001) but poor correlation for orientation (r = 0.29; P < .08). With this reference system, we were able to describe the placement of each individual femoral tunnel aperture, averaging a difference of less than 10 mm from the historical anatomic description by Bernard et al. CONCLUSION: This novel 3D cylindrical coordinate system using biplanar, stereoradiographic, low-irradiation imaging showed a precision comparable with standard manual measurements for ACLR femoral tunnel placement. Our results also suggest that automated cylinders issued from EOS 3D models show adequate accuracy and reproducibility. CLINICAL RELEVANCE: This technique will open multiple possibilities in ACLR femoral tunnel placement in terms of preoperative planning, postoperative feedback, and even intraoperative guidance with augmented reality.

Predictive Modeling for Personalized Three-Dimensional Burn Injury Assessments.

For patients with major burn injuries, an accurate burn size estimation is essential to plan appropriate treatment and minimize medical and surgical complications. However, current clinical methods for burn size estimation lack accuracy and reliability. To overcome these limitations, this paper proposes a 3D-based approach-with personalized 3D models from a limited set of anthropometric measurements-to accurately assess the percent TBSA affected by burns. First, a reliability and feasibility study of the anthropometric measuring process was performed to identify clinically relevant measurements. Second, a large representative stratified random sample was generated to output several anthropometric features required for predictive modeling. Machine-learning algorithms assessed the importance and the subsets of anthropometric measurements for predicting the BSA according to specific patient morphological features. Then, the accuracy of both the morphology and BSA of 3D models built from a limited set of measurements was evaluated using error metrics and maximum distances 3D color maps. Results highlighted the height and circumferences of the bust, neck, hips, and waist as the best predictors for BSA. 3D models built from three to four anthropometric measurements showed good accuracy and were geometrically close to gold standard 3D scans. Outcomes of this study aim to decrease medical and surgical complications by decreasing errors in percent TBSA assessments and, therefore, improving patient outcomes by personalizing care.

A Predictive Model of Progression for Adolescent Idiopathic Scoliosis Based on 3D Spine Parameters at First Visit.

MINI: The aim of this prospective cohort study was to improve the prediction of curve progression in AIS. By adding the 3D morphology parameters at first visit, the predictive model explains 65% of the variability. It is one of the greatest advances in the understanding of scoliosis progression in the last 30 years. STUDY DESIGN: Prospective cohort study. OBJECTIVE: The objective of the present study was to design a model of AIS progression to predict Cobb angle at full skeletal maturity, based on curve type, skeletal maturation, and 3D spine parameters available at first visit. SUMMARY OF BACKGROUND DATA: Adolescent idiopathic scoliosis (AIS) is a three-dimensional (3D) spinal deformity that affects 1% of adolescents. Curve severity is assessed using the Cobb angle. Prediction of scoliosis progression remains challenging for the treating physician and is currently based on curve type, severity, and maturity. The objective of this study was to develop a predictive model of final Cobb angle, based on 3D spine parameters at first visit, to optimize treatment. METHODS: A prospective cohort of AIS patients at first orthopedic visit was enrolled between 2006 and 2010, all with 3D reconstructions. Measurements of five types of descriptors were obtained: angle of plane of maximum curvature, Cobb angles, 3D wedging, rotation, and torsion. A general linear model analysis with backward selection was done with final Cobb angle (either just before surgery or at skeletal maturity) as outcome and 3D spine parameters and clinical parameters as predictors. RESULTS: Of 195 participants, 172 (88%) were analyzed; average age at presentation was 12.5 ±â€Š1.3 years and mean follow-up to outcome, 3.2 years. The final model includes significant predictors: initial skeletal maturation, curve type, frontal Cobb angle, angle of plane of maximal curvature, and 3D disk wedging (T3-T4, T8-T9) and achieved a determination coefficient (R) = 0.643. Positive and negative predictive values to identify a curve of 35 degrees are 79% and 94%. CONCLUSION: This study developed a predictive model of spinal curve progression in scoliosis based on first-visit information. The model will help the treating physician to initiate appropriate treatment at first visit. LEVEL OF EVIDENCE: 3.

Prospective cohort study. The objective of the present study was to design a model of AIS progression to predict Cobb angle at full skeletal maturity, based on curve type, skeletal maturation, and 3D spine parameters available at first visit. Adolescent idiopathic scoliosis (AIS) is a three-dimensional (3D) spinal deformity that affects 1% of adolescents. Curve severity is assessed using the Cobb angle. Prediction of scoliosis progression remains challenging for the treating physician and is currently based on curve type, severity, and maturity. The objective of this study was to develop a predictive model of final Cobb angle, based on 3D spine parameters at first visit, to optimize treatment. A prospective cohort of AIS patients at first orthopedic visit was enrolled between 2006 and 2010, all with 3D reconstructions. Measurements of five types of descriptors were obtained: angle of plane of maximum curvature, Cobb angles, 3D wedging, rotation, and torsion. A general linear model analysis with backward selection was done with final Cobb angle (either just before surgery or at skeletal maturity) as outcome and 3D spine parameters and clinical parameters as predictors. Of 195 participants, 172 (88%) were analyzed; average age at presentation was 12.5 ±â€Š1.3 years and mean follow-up to outcome, 3.2 years. The final model includes significant predictors: initial skeletal maturation, curve type, frontal Cobb angle, angle of plane of maximal curvature, and 3D disk wedging (T3-T4, T8-T9) and achieved a determination coefficient (R2) = 0.643. Positive and negative predictive values to identify a curve of 35 degrees are 79% and 94%. This study developed a predictive model of spinal curve progression in scoliosis based on first-visit information. The model will help the treating physician to initiate appropriate treatment at first visit. Level of Evidence: 3.

Comparison of methods to assess quadriceps muscle volume using magnetic resonance imaging.

PURPOSE: To compare the precision of four methods to estimate the volume of quadriceps muscles using axial MRI. MATERIALS AND METHODS: Entire legs of 10 healthy young subjects were scanned using a 1.5 Tesla magnetic resonance imaging scanner and 4-mm-thick sections without any gaps. Quadriceps muscles were outlined on all of the slices to obtain the MRI reference standard measure of quadriceps muscle volume. This MRI reference standard was compared with the volume estimated using (i) the truncated cone formula, (ii) the Cavalieri method, (iii) a cubic spline interpolation of missing cross sectional areas, and, (iv) the deformation of a parametric specific object. For each method, 3 to 21 slices were used. RESULTS: The average volume error was significantly (P < 0.001) different in comparing the four methods (4.4%, 2.3%, 1.1%, and 1.2%, respectively). In addition, the number of slices required to reach a given volume error was significantly (P < 0.001) different across all methods (respectively, 12, 9, 5, and 7 slices required to reach a volume error of 1.1%). CONCLUSION: While methods based on interpolation and deformation of a parametric specific object have not been used in literature, these two methods are the most precise approaches to reach a given level of precision.