The Uses and Advances in Imaging for Psoriatic Arthritis: A Scoping Review
Notice bibliographique
Résumé
Objectives Psoriatic arthritis (PsA) is a chronic inflammatory condition characterized by variable involvement of the skin and musculoskeletal system. It is associated with significant comorbidities leading to disability, poor mental and physical health outcomes, and decreased quality of life.[1] With advances in treatment, early diagnosis has been key in early intervention and stopping disease progression.[2] Our review aims to map the literature on clinical trials with a focus on imaging modalities, advancements in imaging techniques, and identify gaps to propose directions for future research. Methods Following the Arksey and O’Malley framework for scoping reviews we conducted a comprehensive search of databases including MEDLINE, Embase, PubMed Central, CINAHL, Academic Search Complete, and ScienceDirect, covering the period from January 1, 2000, to June 27, 2024.[3] After deduplication, title and abstract screening, full-text review, and citation searching, a total of 53 peer-reviewed articles met our inclusion criteria for data extraction and analysis. Results Our search captured 1961 articles and after deduplication, title and abstract screening, and full-text review, 53 studies were included for analysis (Figure 1). Radiographs were used in 32/53 studies (60%) and the majority of these were randomized controlled trials (RCTs) (53%). Radiographic progression was most frequently measured with the PsA-modified Sharp/van der Heijde score (69%). Ultrasound (US), which included power doppler US (PD-US) and grayscale US (GS-US), was used in 11/53 studies (21%) to assess for synovial hypertrophy and inflammation. Though standardized scoring systems such as the GLOESS are available, they were only used in 3/11 studies (27%). Magnetic resonance imaging (MRI) was used in 16/53 (30%) studies and evaluated both peripheral and axial disease in PsA. Validated scoring systems such as PsAMRIS and SPARCC are becoming widely adopted in more recent trials. Dynamic contrast enhanced MRI (DCE-MRI) was also compared to computed tomography (CT) and demonstrated high sensitivity for bone erosions and inflammation. Multimodal imaging was used in 7/53 studies (13%) and CT was only used in 2/53 (4%). Fig 1. PRISMA flow chart of the review process Conclusion The development of PsA-specific scoring systems for X-ray and MRI has been instrumental in advancing imaging assessment in PsA. However, their application remains limited, particularly in ultrasound, where further standardization is needed. Future clinical trials should focus on increasing the adoption of PsA-specific scoring systems across modalities, exploring novel imaging techniques such as DCE-MRI, and using multi-modal imaging to improve disease monitoring in PsA. [1.] Haugeberg G. RMD Open 2020;6:e001223. [2.] Crespo-Rodríguez AM. Insights Imaging 2005;12:12. [3.] Arksey H. Int J Soc Res Method 2005:8:19-32.
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 | 0,013 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,005 |
| Bibliométrie | 0,033 | 0,030 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,005 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».