156 research outputs found

    Analysis, Segmentation and Prediction of Knee Cartilage using Statistical Shape Models

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    Osteoarthritis (OA) of the knee is one of the leading causes of chronic disability (along with the hip). Due to rising healthcare costs associated with OA, it is important to fully understand the disease and how it progresses in the knee. One symptom of knee OA is the degeneration of cartilage in the articulating knee. The cartilage pad plays a major role in painting the biomechanical picture of the knee. This work attempts to quantify the cartilage thickness of healthy male and female knees using statistical shape models (SSMs) for a deep knee bend activity. Additionally, novel cartilage segmentation from magnetic resonance imaging (MRI) and estimation algorithms from computer tomography (CT) or x-rays are proposed to facilitate the efficient development and accurate analysis of future treatments related to the knee. Cartilage morphology results suggest distinct patterns of wear in varus, valgus, and neutral degenerative knees, and examination of contact regions during the deep knee bend activity further emphasizes these patterns. Segmentation results were achieved that were comparable if not of higher quality than existing state-of-the-art techniques for both femoral and tibial cartilage. Likewise, using the point correspondence properties of SSMs, estimation of articulating cartilage was effective in healthy and degenerative knees. In conclusion, this work provides novel, clinically relevant morphological data to compute segmentation and estimate new data in such a way to potentially contribute to improving results and efficiency in evaluation of the femorotibial cartilage layer

    APPLICATION OF THE CONE BEAM COMPUTED TOMOGRAPHY (CBCT) MODALITY WITH WEIGHT BEARING TECHNIQUE TO IDENTIFY OSTEOARTHRITIS (OA) IN THE KNEE JOINT

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    ABSTRACTBackground : Osteoarthritis (OA) is a degenerative joint disease that causes inflammation of the cartilage due to the load that is often received by the joints. The knee joint is a part that is often affected by OA. Radiographic and CT examinations can be used to check for OA of the knee. Radiographic examination has the advantage of optimally displaying OA because the examination is carried out under weight bearing conditions, and CT is superior in displaying anatomical details due to cross sectional and 3D reconstruction. Technological developments present Cone Beam CT (CBCT) weight bearings that combine the advantages of radiographic and CT examinations. The purpose of this study is to determine the role and benefits of CBCT weight bearing on knee joint image information in cases of OA.Method : This type of research is literature review research with a narrative review approach. The databases used in the review articles include Science Direct, ProQuest, PubMed, DOAJ, Google Scholar, Wiley Online Library, ISI Web of Knowledge, and the Oxford Journal. The articles that have been obtained will be processed in tabulated form for later extraction.Result : The results of this study indicate that weight bearing is able to assess degeneration causing internal rotation in the range of +/- 2.8-3.1o, lateral patellar shift up to +/- 0.4 mm, joint space width (JSW) up to +/- 0.5 mm, meniscal extrusion (ME) up to +/- 10.2 mm. Conclusion : CBCT is used to obtain volumetric and cross sectional 3D knee images, in order to obtain images with high spatial resolution with low doses, detailed bone structure images, short scan times, visualization of narrowing and progression of OA in JSW clearly, visualization of OA in the menisci, as well as visualizing the complexity of the joint and soft tissue images so that OA is easily identified

    An EMG-Assisted Muscle-Force Driven Finite Element Analysis Pipeline to Investigate Joint- and Tissue-Level Mechanical Responses in Functional Activities : Towards a Rapid Assessment Toolbox

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    Publisher Copyright: © 1964-2012 IEEE.Joint tissue mechanics (e.g., stress and strain) are believed to have a major involvement in the onset and progression of musculoskeletal disorders, e.g., knee osteoarthritis (KOA). Accordingly, considerable efforts have been made to develop musculoskeletal finite element (MS-FE) models to estimate highly detailed tissue mechanics that predict cartilage degeneration. However, creating such models is time-consuming and requires advanced expertise. This limits these complex, yet promising, MS-FE models to research applications with few participants and makes the models impractical for clinical assessments. Also, these previously developed MS-FE models have not been used to assess activities other than gait. This study introduces and verifies a semi-automated rapid state-of-the-art MS-FE modeling and simulation toolbox incorporating an electromyography- (EMG) assisted MS model and a muscle-force driven FE model of the knee with fibril-reinforced poro(visco)elastic cartilages and menisci. To showcase the usability of the pipeline, we estimated joint- and tissue-level knee mechanics in 15 KOA individuals performing different daily activities. The pipeline was verified by comparing the estimated muscle activations and joint mechanics to existing experimental data. To determine the importance of the EMG-assisted MS analysis approach, results were compared to those from the same FE models but driven by static-optimization-based MS models. The EMG-assisted MS-FE pipeline bore a closer resemblance to experiments compared to the static-optimization-based MS-FE pipeline. Importantly, the developed pipeline showed great potential as a rapid MS-FE analysis toolbox to investigate multiscale knee mechanics during different activities of individuals with KOA.Peer reviewe

    Automated Image Analysis of High-field and Dynamic Musculoskeletal MRI

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    Articular cartilage surface roughness as an imaging‐based morphological indicator of osteoarthritis: A preliminary investigation of osteoarthritis initiative subjects

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    Current imaging‐based morphometric indicators of osteoarthritis (OA) using whole‐compartment mean cartilage thickness (MCT) and volume changes can be insensitive to mild degenerative changes of articular cartilage (AC) due to areas of adjacent thickening and thinning. The purpose of this preliminary study was to evaluate cartilage thickness‐based surface roughness as a morphometric indicator of OA. 3D magnetic resonance imaging (MRI) datasets were collected from osteoarthritis initiative (OAI) subjects with Kellgren–Lawrence (KL) OA grades of 0, 2, and 4 (n = 10/group). Femoral and tibial AC volumes were converted to two‐dimensional thickness maps, and MCT, arithmetic surface roughness (Sa), and anatomically normalized Sa (normSa) were calculated. Thickness maps enabled visualization of degenerative changes with increasing KL grade, including adjacent thinning and thickening on the femoral condyles. No significant differences were observed in MCT between KL grades. Sa was significantly higher in KL4 compared to KL0 and KL2 in the whole femur (KL0: 0.55 ± 0.10 mm, KL2: 0.53 ± 0.09 mm, KL4: 0.79 ± 0.18 mm), medial femoral condyle (KL0: 0.42 ± 0.07 mm, KL2: 0.48 ± 0.07 mm, KL4: 0.76 ± 0.22 mm), and medial tibial plateau (KL0: 0.42 ± 0.07 mm, KL2: 0.43 ± 0.09 mm, KL4: 0.68 ± 0.27 mm). normSa was significantly higher in KL4 compared to KL0 and KL2 in the whole femur (KL0: 0.22 ± 0.02, KL2: 0.22 ± 0.02, KL4: 0.30 ± 0.03), medial condyle (KL0: 0.17 ± 0.02, KL2: 0.20 ± 0.03, KL4: 0.29 ± 0.06), whole tibia (KL0: 0.34 ± 0.04, KL2: 0.33 ± 0.05, KL4: 0.48 ± 0.11) and medial plateau (KL0: 0.23 ± 0.03, KL2: 0.24 ± 0.04, KL4: 0.40 ± 0.10), and significantly higher in KL2 compared to KL0 in the medial femoral condyle. Surface roughness metrics were sensitive to degenerative morphologic changes, and may be useful in OA characterization and early diagnosis. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2755–2764, 2017.A custom algorithm was used to create two‐dimensional articular cartilage thickness maps of patients from the Osteoarthritis Initiative. Thickness maps demonstrate significantly increased surface roughness as a function of increasing Kellgren–Lawrence (KL) osteoarthritis (OA) grade, particularly in the medial femoral condyle, though mean cartilage thickness was not found to differ significantly between KL grades. Surface roughness‐based metrics have potential utility as morphological indicators of OA.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141486/1/jor23588_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141486/2/jor23588.pd
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