Medial Cartilage Surface Integrity as a Surrogate Measure for Incident Radiographic Knee Osteoarthritis following Weight Changes

Runhaar, Jos; Dam, Erik B.; Oei, Edwin H.G.; Bierma-Zeinstra, Sita M A

doi:10.1177/1947603519892305

Cited by 3 publications

(3 citation statements)

References 16 publications

(22 reference statements)

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“…The Challenges in the Primary Prevention of OA on MRI was significantly affected by weight loss and that its change was related to long-term knee OA development. 72 Unfortunately, in another study, none of the changes in structural MRI features were related to long-term pain progression among patients with knee pain and a meniscal tear that were randomized over after meniscal surgery and physical therapy. 73 Exploring and validating more potential surrogate outcomes for different target groups and different potential preventive interventions is deemed a top priority for the field of OA prevention research.…”

Section: The Need For Surrogate Outcomesmentioning

confidence: 97%

The Challenges in the Primary Prevention of Osteoarthritis

Runhaar

Bierma-Zeinstra

2022

Clinics in Geriatric Medicine

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Section: The Need For Surrogate Outcomesmentioning

confidence: 97%

The Challenges in the Primary Prevention of Osteoarthritis

Runhaar

Bierma-Zeinstra

2022

Clinics in Geriatric Medicine

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“…The lack of RCTs in early-stage OA hamper this validation strategy and initiating new trials is very time consuming. Level 2 evidence for surrogate outcomes can be obtained from longitudinal cohort studies, where the short-term changes in a potential surrogate outcomes can be evaluated against the long-term development of established OA [ 53 – 55 ].…”

Section: Progression Of Early-stage Oamentioning

confidence: 99%

Imaging of early-stage osteoarthritis: the needs and challenges for diagnosis and classification

Oei

Runhaar

2023

Skeletal Radiol

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In an effort to boost the development of new management strategies for OA, there is currently a shift in focus towards the diagnosis and treatment of early-stage OA. It is important to distinguish diagnosis from classification of early-stage OA. Diagnosis takes place in clinical practice, whereas classification is a process to stratify participants with OA in clinical research. For both purposes, there is an important opportunity for imaging, especially with MRI. The needs and challenges differ for early-stage OA diagnosis versus classification. Although it fulfils the need of high sensitivity and specificity for making a correct diagnosis, implementation of MRI in clinical practice is challenged by long acquisition times and high costs. For classification in clinical research, more advanced MRI protocols can be applied, such as quantitative, contrast-enhanced, or hybrid techniques, as well as advanced image analysis methods including 3D morphometric assessments of joint tissues and artificial intelligence approaches. It is necessary to follow a step-wise and structured approach that comprises, technical validation, biological validation, clinical validation, qualification, and cost-effectiveness, before new imaging biomarkers can be implemented in clinical practice or clinical research.

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“…12 Runhaar et al demonstrated that change in the cartilage cavity score, a measure of cartilage surface integrity based on a 3D sagittal water excitation MRI sequence, was significantly associated with radiographic knee OA development in the subsequent period of 4 years. 13 Also, 3D MRI can be used to map spatial differences in cartilage thickness across the joint surface (►Fig. 3).…”

Section: Quantitative Morphometric Cartilage Analysis In Oamentioning

confidence: 99%

3D MRI in Osteoarthritis

Oei

Zadelhoff

Eijgenraam

et al. 2021

Semin Musculoskelet Radiol

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Osteoarthritis (OA) is among the top 10 burdensome diseases, with the knee the most affected joint. Magnetic resonance imaging (MRI) allows whole-knee assessment, making it ideally suited for imaging OA, considered a multitissue disease. Three-dimensional (3D) MRI enables the comprehensive assessment of OA, including quantitative morphometry of various joint tissues. Manual tissue segmentation on 3D MRI is challenging but may be overcome by advanced automated image analysis methods including artificial intelligence (AI). This review presents examples of the utility of 3D MRI for knee OA, focusing on the articular cartilage, bone, meniscus, synovium, and infrapatellar fat pad, and it highlights several applications of AI that facilitate segmentation, lesion detection, and disease classification.

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Medial Cartilage Surface Integrity as a Surrogate Measure for Incident Radiographic Knee Osteoarthritis following Weight Changes

Cited by 3 publications

References 16 publications

The Challenges in the Primary Prevention of Osteoarthritis

The Challenges in the Primary Prevention of Osteoarthritis

Imaging of early-stage osteoarthritis: the needs and challenges for diagnosis and classification

3D MRI in Osteoarthritis

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