Osteoarthritis year in review 2019: imaging Kijowski, R.; Demehri, S.; Roemer, F. ...
Osteoarthritis and cartilage,
March 2020, 2020-03-00, 20200301, Letnik:
28, Številka:
3
Journal Article
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To provide a narrative review of original articles on osteoarthritis (OA) imaging published between April 1, 2018 and March 30, 2019.
All original research articles on OA imaging published in English ...between April 1, 2018 and March 30, 2019 were identified using a PubMed database search. The search terms of “Osteoarthritis” or “OA” were combined with the search terms “Radiography”, “X-Rays”, “Magnetic Resonance Imaging”, “MRI”, “Ultrasound”, “US”, “Computed Tomography”, “Dual Energy X-Ray Absorptiometry”, “DXA”, “DEXA”, “CT”, “Nuclear Medicine”, “Scintigraphy”, “Single-Photon Emission Computed Tomography”, “SPECT”, “Positron Emission Tomography”, “PET”, “PET-CT”, or “PET-MRI”. Articles were reviewed to determine relevance based upon the following criteria: 1) study involved human subjects with OA or risk factors for OA and 2) study involved imaging to evaluate OA disease status or OA treatment response. Relevant articles were ranked according to scientific merit, with the best publications selected for inclusion in the narrative report.
The PubMed search revealed a total of 1257 articles, of which 256 (20.4%) were considered relevant to OA imaging. Two-hundred twenty-six (87.1%) articles involved the knee joint, while 195 (76.2%) articles involved the use of magnetic resonance imaging (MRI). The proportion of published studies involving the use of MRI was higher than previous years. An increasing number of articles were also published on imaging of subjects with joint injury and on deep learning application in OA imaging.
MRI and other imaging modalities continue to play an important role in research studies designed to better understand the pathogenesis, progression, and treatment of OA.
Summary Objective To identify the independent relation of synovitis with incident radiographic knee osteoarthritis (OA) after adjusting for other structural factors known to cause synovitis. Design ...We examined MRIs from knees that developed incident radiographic OA from the Multicenter Osteoarthritis Study (MOST) and compared these case knees with controls that did not develop OA. We examined baseline MRIs for knees developing OA at any time up to 84 months follow-up. We scored lesions in cartilage, meniscus, bone marrow and synovitis. Synovitis scores were summed (0–9) across three regions, suprapatellar, infrapatellar and intercondylar region, each of which was scored 0–3. After bivariate analyses examining each factor's association with incidence, we carried out multivariable regression analyses adjusting for age, sex, BMI, alignment and cartilage and meniscal damage. Results We studied 239 case and 731 control knees. In bivariate analyses, cartilage lesions, meniscal damage, synovitis and bone marrow lesions were all risk factors for OA. After multivariable analyses, synovitis was associated with incident OA. A higher synovitis score increased the risk of incident OA (adjusted OR per unit increase 1.1; (95% CI 1.0, 1.2, P = .02)), but increased risk was associated only with synovitis scores of ≥3 (adjusted OR 1.6; 95% CI 1.2, 2.1, P = .003). Conclusions Synovitis, especially when there is a substantial volume within the knee, is an independent cause of OA.
Cortical disease has emerged as a critical aspect of the pathogenesis of multiple sclerosis, being associated with disease progression and cognitive impairment. Most studies of cortical lesions have ...focused on autopsy findings in patients with long-standing, chronic, progressive multiple sclerosis, and the noninflammatory nature of these lesions has been emphasized. Magnetic resonance imaging studies indicate that cortical damage occurs early in the disease.
We evaluated the prevalence and character of demyelinating cortical lesions in patients with multiple sclerosis. Cortical tissues were obtained in passing during biopsy sampling of white-matter lesions. In most cases, biopsy was done with the use of stereotactic procedures to diagnose suspected tumors. Patients with sufficient cortex (138 of 563 patients screened) were evaluated for cortical demyelination. Using immunohistochemistry, we characterized cortical lesions with respect to demyelinating activity, inflammatory infiltrates, the presence of meningeal inflammation, and a topographic association between cortical demyelination and meningeal inflammation. Diagnoses were ascertained in a subgroup of 77 patients (56%) at the last follow-up visit (at a median of 3.5 years).
Cortical demyelination was present in 53 patients (38%) (104 lesions and 222 tissue blocks) and was absent in 85 patients (121 tissue blocks). Twenty-five patients with cortical demyelination had definite multiple sclerosis (81% of 31 patients who underwent long-term follow-up), as did 33 patients without cortical demyelination (72% of 46 patients who underwent long-term follow-up). In representative tissues, 58 of 71 lesions (82%) showed CD3+ T-cell infiltrates, and 32 of 78 lesions (41%) showed macrophage-associated demyelination. Meningeal inflammation was topographically associated with cortical demyelination in patients who had sufficient meningeal tissue for study.
In this cohort of patients with early-stage multiple sclerosis, cortical demyelinating lesions were frequent, inflammatory, and strongly associated with meningeal inflammation. (Funded by the National Multiple Sclerosis Society and the National Institutes of Health.).
Summary Osteoarthritis (OA), a leading cause of disability, affects 27 million people in the United States and its prevalence is rising along with the rise in obesity. So far, biomechanical or ...behavioral interventions as well as attempts to develop disease-modifying OA drugs have been unsuccessful. This may be partly due to antiquated imaging outcome measures such as radiography, which are still endorsed by regulatory agencies such as the United States Food and Drug Administration (FDA) for use in clinical trials. Morphological magnetic resonance imaging (MRI) allows unparalleled multi-feature assessment of the OA joint. Furthermore, advanced MRI techniques also enable evaluation of the biochemical or ultrastructural composition of articular cartilage relevant to OA research. These compositional MRI techniques have the potential to supplement clinical MRI sequences in identifying cartilage degeneration at an earlier stage than is possible today using morphologic sequences only. The purpose of this narrative review is to describe compositional MRI techniques for cartilage evaluation, which include T2 mapping, T2* Mapping, T1 rho, dGEMRIC, gagCEST, sodium imaging and diffusion weighted imaging (DWI). We also reviewed relevant clinical studies that have utilized these techniques for the study of OA. The different techniques are complementary. Some focus on isotropy or the collagen network (e.g., T2 mapping) and others are more specific in regard to tissue composition, e.g., gagCEST or dGEMRIC that convey information on the GAG concentration. The application and feasibility of these techniques is also discussed, as they will play an important role in implementation in larger clinical trials and eventually clinical practice.
Magnetic resonance imaging (MRI)-based spin-spin relaxation time (T2) mapping has been shown to be associated with cartilage matrix composition (hydration, collagen content &orientation). To ...determine the impact of early radiographic knee osteoarthritis (ROA) and ROA risk factors on femorotibial cartilage composition, we studied baseline values and one-year change in superficial and deep cartilage T2 layers in 60 subjects (age 60.6 ± 9.6 y; BMI 27.8 ± 4.8) with definite osteophytes in one knee (earlyROA, n = 32) and with ROA risk factors in the contralateral knee (riskROA, n = 28), and 89 healthy subjects (age 55.0 ± 7.5 y; BMI 24.4 ± 3.1) without signs or risk factors of ROA. Baseline T2 did not differ significantly between earlyROA and riskROA knees in the superficial (48.0 ± 3.5 ms vs. 48.1 ± 3.1 ms) or the deep layer (37.3 ± 2.5 ms vs. 37.3 ± 1.8 ms). However, healthy knees showed significantly lower superficial layer T2 (45.4 ± 2.3 ms) than earlyROA or riskROA knees (p ≤ 0.001) and significantly lower deep layer T2 (35.8 ± 1.8 ms) than riskROA knees (p = 0.006). Significant longitudinal change in T2 (superficial: 0.5 ± 1.4 ms; deep: 0.8 ± 1.3 ms) was only detected in healthy knees. These results do not suggest an association of early ROA (osteophytes) with cartilage composition, as assessed by T2 mapping, whereas cartilage composition was observed to differ between knees with and without ROA risk factors.
Imaging in Osteoarthritis Roemer, F.W.; Guermazi, A.; Demehri, S. ...
Osteoarthritis and cartilage,
07/2022, Letnik:
30, Številka:
7
Journal Article
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Osteoarthritis (OA) is the most frequent form of arthritis with major implications on both individual and public health care levels. The field of joint imaging, and particularly magnetic resonance ...imaging (MRI), has evolved rapidly due to the application of technical advances to the field of clinical research. This narrative review will provide an introduction to the different aspects of OA imaging aimed at an audience of scientists, clinicians, students, industry employees, and others who are interested in OA but who do not necessarily focus on OA. The current role of radiography and recent advances in measuring joint space width will be discussed. The status of cartilage morphology assessment and evaluation of cartilage biochemical composition will be presented. Advances in quantitative three-dimensional morphologic cartilage assessment and semi-quantitative whole-organ assessment of OA will be reviewed. Although MRI has evolved as the most important imaging method used in OA research, other modalities such as ultrasound, computed tomography, and metabolic imaging play a complementary role and will also be discussed.
Osteoarthritis year in review 2022: imaging Demehri, S.; Kasaeian, A.; Roemer, F.W. ...
Osteoarthritis and cartilage,
August 2023, 2023-08-00, 20230801, Letnik:
31, Številka:
8
Journal Article
Recenzirano
This narrative review summarizes original research focusing on imaging in osteoarthritis (OA) published between April 1st 2021 and March 31st 2022. We only considered English publications that were ...in vivo human studies.
The PubMed, Medline, Embase, Scopus, and ISI Web of Science databases were searched for “Osteoarthritis/OA” studies based on the search terms: “Radiography”, “Ultrasound/US”, “Computed Tomography/CT”, “DXA”, “Magnetic Resonance Imaging/MRI”, “Artificial Intelligence/AI”, and “Deep Learning”. This review highlights the anatomical focus of research on the structures within the tibiofemoral, patellofemoral, hip, and hand joints. There is also a noted focus on artificial intelligence applications in OA imaging.
Over the last decade, the increasing trend of using open-access large databases has reached a plateau (from 17 to 37). Compositional MRI has had the most prominent use in OA imaging and its biomarkers have been used in the detection of preclinical OA and prediction of OA outcomes. Most noteworthy, there has been an accelerated rate of publications on the implications of artificial intelligence, used in developing prediction models and performing trabecular texture analysis, in OA imaging (from 17 to 154).
While imaging has maintained its key role in OA research, publication trends have shown an emphasis on the integration of AI. During the past year, MRI has maintained the highest prevalence in usage while US and CT remain as readily available modalities. Finally, there has been a notable uptake in the development and validation of AI techniques used to perform texture analysis and predict OA progression.
It is unknown whether joint inflammation precedes other articular tissue damage in osteoarthritis. Therefore, this study aims to determine if synovitis precedes the development of radiographic knee ...osteoarthritis (ROA).
The participants in this nested case-control study were selected from persons in the Osteoarthritis Initiative with knees that had a Kellgren Lawrence grading (KLG)=0 at baseline (BL). These knees were evaluated annually with radiography and non-contrast-enhanced MRI over 4 years. MRIs were assessed for effusion-synovitis and Hoffa-synovitis. Case knees were defined by ROA (KLG≥2) on the postero-anterior knee radiographs at any assessment after BL. Radiographs were assessed at P0 (time of onset of ROA), 1 year prior to P0 (P-1) and at BL. Controls were participants who did not develop incident ROA (iROA) from BL to 48 months).
133 knees of 120 persons with ROA (83 women) were matched to 133 control knees (83 women). ORs for occurrence of iROA associated with the presence of effusion-synovitis at BL, P-1 and P0 were 1.56 (95% CI 0.86 to 2.81), 3.23 (1.72 to 6.06) and 4.7 (1.10 to 2.95), respectively. The ORs for the occurrence of iROA associated with the presence of Hoffa-synovitis at BL, P-1 and P0 were 1.80 (1.1 to 2.95), 2.47 (1.45 to 4.23) and 2.40 (1.43 to 4.04), respectively.
Effusion-synovitis and Hoffa-synovitis strongly predicted the development of iROA.
Summary Objective To test the hypothesis that quantitative measures of meniscus extrusion predict incident radiographic knee osteoarthritis (KOA), prior to the advent of radiographic disease. Methods ...206 knees with incident radiographic KOA (Kellgren Lawrence Grade (KLG) 0 or 1 at baseline, developing KLG 2 or greater with a definite osteophyte and joint space narrowing (JSN) grade ≥1 by year 4) were matched to 232 control knees not developing incident KOA. Manual segmentation of the central five slices of the medial and lateral meniscus was performed on coronal 3T DESS MRI and quantitative meniscus position was determined. Cases and controls were compared using conditional logistic regression adjusting for age, sex, BMI, race and clinical site. Sensitivity analyses of early (year Y 1/2) and late (Y3/4) incidence was performed. Results Mean medial extrusion distance was significantly greater for incident compared to non-incident knees (1.56 mean ± 1.12 mm SD vs 1.29 ± 0.99 mm; +21%, P < 0.01), so was the percent extrusion area of the medial meniscus (25.8 ± 15.8% vs 22.0 ± 13.5%; +17%, P < 0.05). This finding was consistent for knees restricted to medial incidence. No significant differences were observed for the lateral meniscus in incident medial KOA, or for the tibial plateau coverage between incident and non-incident knees. Restricting the analysis to medial incident KOA at Y1/2 differences were attenuated, but reached significance for extrusion distance, whereas no significant differences were observed at incident KOA in Y3/4. Conclusion Greater medial meniscus extrusion predicts incident radiographic KOA. Early onset KOA showed greater differences for meniscus position between incident and non-incident knees than late onset KOA.
Multidimensional harmonic retrieval problems are encountered in a variety of signal processing applications including radar, sonar, communications, medical imaging, and the estimation of the ...parameters of the dominant multipath components from MIMO channel measurements. R -dimensional subspace-based methods, such as R -D Unitary ESPRIT, R -D RARE, or R -D MUSIC, are frequently used for this task. Since the measurement data is multidimensional, current approaches require stacking the dimensions into one highly structured matrix. However, in the conventional subspace estimation step, e.g., via an SVD of the latter matrix, this structure is not exploited. In this paper, we define a measurement tensor and estimate the signal subspace through a higher-order SVD. This allows us to exploit the structure inherent in the measurement data already in the first step of the algorithm which leads to better estimates of the signal subspace. We show how the concepts of forward-backward averaging and the mapping of centro-Hermitian matrices to real-valued matrices of the same size can be extended to tensors. As examples, we develop the R -D standard Tensor-ESPRIT and the R -D Unitary Tensor-ESPRIT algorithms. However, these new concepts can be applied to any multidimensional subspace-based parameter estimation scheme. Significant improvements of the resulting parameter estimation accuracy are achieved if there is at least one of the R dimensions, which possesses a number of sensors that is larger than the number of sources. This can already be observed in the two-dimensional case.
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