A THREE-DIMENSIONAL STATISTICAL SHAPE MODEL TO DESCRIBE CLINICAL SHAPE VARIATION OF THE PROXIMAL FEMUR IN PATIENTS WITH LEGG-CALVÉ-PERTHES DISEASE DEFORMITY
Notice bibliographique
Résumé
Legg-Calvé-Perthes Disease (LCPD) is a pediatric hip condition that affects approximately 1 in 10,000 children. In LCPD the femoral head is deformed by osteonecrosis, often resulting in a permanent residual hip deformity. Residual LCPD is associated with at least a 20 times greater risk of early-onset OA in affected hips, even in patients with only mild radiographic deformity. Current routine assessment using 2D radiographic imaging does not adequately describe the complex 3D pathomorphology of LCPD. Statistical shape modeling (SSM) provides an objective and compact description of 3D shape variability, which may be used to better describe patient specific LCPD deformity and identify which features lead to early OA. 1) Construct and evaluate a compact and accurate shape model of LCPDs pathomorphology using open-source SSM software. 2) Examine the relationship between 3D LCPD pathomorphology and corresponding clinical radiographic measurements. MR images (N=13 hips, 11 patients, 3 F/8 M) of affected hips were obtained in a previous study from patients with LCPD (age range: 6-12 years, stage II-IV). Imaging was performed using a GE 1.5T HDxt scanner (Waukesha, WI) with a coronal 3D FSPGR sequence: TR=8.9 ms, TE 2.8ms, flip angle 10°, 1.0mm slice thickness, 288 × 288 matrix. For this study, MR volumes were resampled isotropically to the smallest voxel dimension (.47 - .63 mm), and two raters manually segmented the proximal femurs. The ShapeWorks SSM software (SCI Institute, University of Utah, Salt Lake City, UT) was used to produce an SSM with 512 particles using an incremental optimization routine. Shapes were aligned and scaled with generalized Procrustes analysis. Modes of shape variation were quantified using principal component analysis. The SSM's generalizability to unfamiliar shapes was evaluated with a leave-one-out cross-validation analysis. The relationship between neck-shaft angle, articulo-trochanteric distance and femoral head asphericity with principal component scores was examined with Spearman's rank correlation coefficient (ρ). The first four shape modes, describing 87.5% of the population variability, were selected to form a compact shape model. With these modes, the generalizability (point-to-point reconstruction error) was <1 mm. Notable associations were observed between mode IV and femoral head asphericity (ρ = 0.79), modes II and IV with neck-shaft angle (ρ = -0.43, 0.63 respectively), and modes I and II with articulo-trochanteric distance (ρ = 0.58, -0.63 respectively). This SSM provides a compact and accurate representation of 3D shape variation in LCPD. Limitations to this model include a small sample size, but nonetheless it generalizes well to unfamiliar LCPD examples. The robust and repeatable methodology will allow the model to be supplemented with additional shapes in future. With this SSM, we aim to evaluate how well clinical metrics based on 2D projections of anatomy can represent the anatomical changes that may lead to OA, and to determine why some patients with little to no radiographic deformity still develop early-onset OA. Canadian Institutes of Health Research, Funding reference #165956 L.G. Johnson is supported by Arthritis Society Canada. CORRESPONDENCE ADDRESS: [email protected]
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».