Advanced Imaging of Inflammation in Knee Osteoarthritis

This thesis focuses on imaging methods to study the role of inflammation in knee osteoarthritis. The aims of this thesis are I) to evaluate disturbed perfusion patterns in subchondral bone and the infrapatellar fat pad using perfusion MRI, and II) to assess new magnetic resonance and ultrasound imaging methods for diagnosis of synovitis in knee osteoarthritis

Imaging of Osteoarthritis

Osteoarthritis (OA) is the most prevalent joint disorder in the elderly, and there is no effective treatment. Imaging is essential for evaluating the synovial joint structures (including cartilage, meniscus, subchondral bone marrow and synovium) for diagnosis, prognosis, and follow-up. This article describes the roles and limitations of both conventional radiography and magnetic resonance (MR) imaging, and considers the use of other modalities (eg, ultrasonography, nuclear medicine, computed tomography [CT], and CT/MR arthrography) in clinical practice and OA research. The emphasis throughout is on OA of the knee. This article emphasizes research developments and literature evidence published since 2008

Artificial intelligence in musculoskeletal ultrasound imaging

Ultrasonography (US) is noninvasive and offers real-time, low-cost, and portable imaging that facilitates the rapid and dynamic assessment of musculoskeletal components. Significant technological improvements have contributed to the increasing adoption of US for musculoskeletal assessments, as artificial intelligence (AI)-based computer-aided detection and computer-aided diagnosis are being utilized to improve the quality, efficiency, and cost of US imaging. This review provides an overview of classical machine learning techniques and modern deep learning approaches for musculoskeletal US, with a focus on the key categories of detection and diagnosis of musculoskeletal disorders, predictive analysis with classification and regression, and automated image segmentation. Moreover, we outline challenges and a range of opportunities for AI in musculoskeletal US practice.11Nsciescopu

Three-dimensional Ultrasound Imaging For Quantifying Knee Cartilage Volume

Arthritis is the most common chronic health condition in Canada, with the most common form being osteoarthritis (OA). There is a great clinical need for an objective imaging-based point-of-care tool to assess OA status, progression, and response to treatment. This thesis aims to validate a handheld mechanical three-dimensional (3D) ultrasound (US) device against the current clinical standard of magnetic resonance imaging (MRI) for quantifying femoral articular cartilage (FAC) volume. Knee images of 25 healthy volunteers were acquired using 3D US and 3.0 Tesla MRI scans. Two raters manually segmented the trochlear FAC during separate sessions to assess intra- and inter-rater reliabilities. The results demonstrated that 3D US has excellent reliability and strong concurrent validity with MRI for measuring healthy FAC volume. 3D US is a promising, inexpensive, and widely accessible imaging modality that will enable clinicians and researchers to obtain additional information without added complexity or discomfort to patients

Multispectral imaging for preclinical assessment of rheumatoid arthritis models

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune condition affecting multiple body systems. Murine models of RA are vital in progressing understanding of the disease. The severity of arthritis symptoms is currently assessed in vivo by observations and subjective scoring which are time-consuming and prone to bias and inaccuracy. The main aim of this thesis is to determine whether multispectral imaging of murine arthritis models has the potential to assess the severity of arthritis symptoms in vivo in an objective manner. Given that pathology can influence the optical properties of a tissue, changes may be detectable in the spectral response. Monte Carlo modelling of reflectance and transmittance for varying levels of blood volume fraction, blood oxygen saturation, and water percentage in the mouse paw tissue demonstrated spectral changes consistent with the reported/published physiological markers of arthritis. Subsequent reflectance and transmittance in vivo spectroscopy of the hind paw successfully detected significant spectral differences between normal and arthritic mice. Using a novel non-contact imaging system, multispectral reflectance and transmittance images were simultaneously collected, enabling investigation of arthritis symptoms at different anatomical paw locations. In a blind experiment, Principal Component (PC) analysis of four regions of the paw was successful in identifying all 6 arthritic mice in a total sample of 10. The first PC scores for the TNF dARE arthritis model were found to correlate significantly with bone erosion ratio results from microCT, histology scoring, and the manual scoring method. In a longitudinal study at 5, 7 and 9 weeks the PC scores identified changes in spectral responses at an early stage in arthritis development for the TNF dARE model, before clinical signs were manifest. Comparison of the multispectral image data with the Monte Carlo simulations suggest that in this study decreased oxygen saturation is likely to be the most significant factor differentiating arthritic mice from their normal littermates. The results of the experiments are indicative that multispectral imaging performs well as an assessor of arthritis for RA models and may outperform existing techniques. This has implications for better assessment of preclinical arthritis and hence for better experimental outcomes and improvement of animal welfare

Quantification of temporomandibular joint space in patients with juvenile idiopathic arthritis assessed by cone beam computerized tomography

Objective To describe a method to calculate the total intra-articular volume (inter-osseous space) of the temporomandibular joint (TMJ) determined by cone-beam computed tomography (CBCT). This could be used as a marker of tissue proliferation and different degrees of soft tissue hyperplasia in juvenile idiopathic arthritis (JIA) patients. Materials and Methods Axial single-slice CBCT images of cross-sections of the TMJs of 11 JIA patients and 11 controls were employed. From the top of the glenoid fossa, in the caudal direction, an average of 26 slices were defined in each joint (N = 44). The interosseous space was manually delimited from each slice by using dedicated software that includes a graphic interface. TMJ volumes were calculated by adding the areas measured in each slice. Two volumes were defined: Ve−i and Vi, where Ve−i is the inter-osseous space, volume defined by the borders of the fossa and Vi is the internal volume defined by the condyle. An intra-articular volume filling index (IF) was defined as Ve−i/Vi, which represents the filling of the space. Results The measured space of the intra-articular volume, corresponding to the intra-articular soft tissue and synovial fluid, was more than twice as large in the JIA group as in the control group. Conclusion The presented method, based on CBCT, is feasible for assessing inter-osseus joint volume of the TMJ and delimits a threshold of intra-articular changes related to intra-articular soft tissue proliferation, based on differences in volumes. Intra-articular soft tissue is found to be enlarged in JIA patientsS