Three‐dimensional ultrasound to investigate synovitis in first carpometacarpal osteoarthritis: A feasibility study
Notice bibliographique
Résumé
Abstract Background Synovitis is one of the defining characteristics of osteoarthritis (OA) in the carpometacarpal (CMC1) joint of the thumb. Quantitative characterization of synovial volume is important for furthering our understanding of CMC1 OA disease progression, treatment response, and monitoring strategies. In previous studies, three‐dimensional ultrasound (3‐D US) has demonstrated the feasibility of being a point‐of‐care system for monitoring knee OA. However, 3‐D US has not been tested on the smaller joints of the hand, which presents unique physiological and imaging challenges. Purpose To develop and validate a novel application of 3‐D US to monitor soft‐tissue characteristics of OA in a CMC1 OA patient population compared to the current gold standard, magnetic resonance imaging (MRI). Methods A motorized submerged transducer moving assembly was designed for this device specifically for imaging the joints of the hands and wrist. The device used a linear 3‐D scanning approach, where a 14L5 2‐D transducer was translated over the region of interest. Two imaging phantoms were used to test the linear and volumetric measurement accuracy of the 3‐D US device. To evaluate the accuracy of the reconstructed 3‐D US geometry, a multilayer monofilament string‐grid phantom (10 mm square grid) was scanned. To validate the volumetric measurement capabilities of the system, a simulated synovial tissue phantom with an embedded synovial effusion was fabricated and imaged. Ten CMC1 OA patients were imaged by our 3‐D US and a 3.0 T MRI system to compare synovial volumes. The synovial volumes were manually segmented by two raters on the 2D slices of the 3D US reconstruction and MR images, to assess the accuracy and precision of the device for determining synovial tissue volumes. The Standard Error of Measurement and Minimal Detectable Change was used to assess the precision and sensitivity of the volume measurements. Paired sample t‐tests were used to assess statistical significance. Additionally, rater reliability was assessed using Intra‐Class Correlation (ICC) coefficients. Results The largest percent difference observed between the known physical volume of synovial extrusion in the phantom and the volume measured by our 3D US was 1.1% (p‐value = 0.03). The mean volume difference between the 3‐D US and the gold standard MRI was 1.78% (p‐value = 0.48). The 3‐D US synovial tissue volume measurements had a Standard Error Measurement (SEm) of 11.21 mm3 and a Minimal Detectible Change (MDC) of 31.06 mm3, while the MRI synovial tissue volume measurements had an SEM of 16.82 mm3 and an MDC of 46.63 mm3. Excellent inter‐ and intra‐rater reliability (ICCs = 0.94–0.99) observed across all imaging modalities and raters. Conclusion Our results indicate the feasibility of applying 3‐D US technology to provide accurate and precise CMC1 synovial tissue volume measurements, similar to MRI volume measurements. Lower MDC and SEm values for 3‐D US volume measurements indicate that it is a precise measurement tool to assess synovial volume and that it is sensitive to variation between volume segmentations. The application of this imaging technique to monitor OA pathogenesis and treatment response over time at the patient's bedside should be thoroughly investigated in future studies.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».