COMPARISON OF TWO OPTICAL IMAGING SYSTEMS TO REDUCE RADIATION IN ADOLESCENTS WITH SCOLIOSIS
Notice bibliographique
Résumé
INTRODUCTION Adolescent Idiopathic Scoliosis (AIS) is a three-dimensional (3D) deformity of the spine characterized by abnormal lateral curvature and vertebral rotation affecting 2-3% of adolescents [1]. The current clinical diagnostic and monitoring method consists of full torso X-rays where the Cobb angle, a measure of spinal deviation from the vertical, is used to determine the magnitude of the deformity. Two major limitations are associated with this approach. First, the routine exposure to radiation has been linked to an increased risk of cancer in scoliotic patients [2]. Second, the Cobb angle is inadequate to fully define the deformity because it is a two-dimensional measure. A holistic approach to define the deformity and reduce radiation exposure is needed. Changes in spinal curvature alter torsal shape making the use of surface topography (ST) a potential alternative to detect and monitor AIS progression in 3D [3] as well as reduce periodic radiation exposure. The majority of recent attempts to validate ST for clinical implementation have used commercial fringe topographic (FT) methods, which are expensive and take prolonged captures. A novel low-cost photogrammetric system that takes instantaneous captures has been developed to remove errors resulting from movement during a capture and increase torso reconstruction accuracy [4]. The effect of the improved accuracy on the ST measures in the new system is not yet understood . The aim of this study was to compare FT and photogrammetric data, thereby providing context for ST measures resulting from the new system. METHODS Models of four AIS (1M, 3F) and four normal (1M, 3F) subjects between the ages of 9-16 were reconstructed via FT (InSpeck Inc, Montreal; now owned by Creaform, Levis) and photogrammetric methods in order to compare ST measures in three regions, i.e. upper (T7), middle (T12) and lower (L4). Captures from the two systems were taken consecutively while subjects were in a positioning frame to reduce movement artifacts between systems. MeshLab was used to generate meshes from the photogrammetric point clouds. A custom scoliosis code [5] calculated ST measures from meshes between T1 and S1 (Fig 1.). Anatomical landmarks determined each individual’s fixed reference frame. RESULTS A repeated measures multivariate analysis of variability compared 11 distinct ST indices calculated from torsal cross-sections (Fig. 1) [6]. There were two subject groups, normal and scoliosis; two optical methods, FT and photogrammetry; and three analyzed levels, T7, T12 and L4. Statistically significant (SS) differences were found in ST measures between methods (p < 0.001) and spinal levels (p = 0.032). Further tests revealed SS difference in both the normal (p = 0.006) and scoliosis (p = 0.002) groups ST measures from the two methods. DISCUSSION AND CONCLUSIONS The photogrammetry method produced different ST measures from the FT method. Further method comparison includes distorting photogrammetry data until it matches FT data. Increasing sample size will provide SS information on interaction effects and the effects of improved accuracy and repeatability of the novel system vs. InSpeck (accuracy: 0.3 mm vs. 1.29+/- 0.45mm; repeatability: 0.19mm vs. 1.4mm; [4,6]) on ST measures.
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 | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».