Assessing the Feasibility and Utility of Patient-Specific 3D Advanced Visualization Modeling in Cerebrovascular Disease: Retrospective Analysis and Prospective Survey Pilot Study
Notice bibliographique
Résumé
BACKGROUND: The prevalence, clinical burden, and health care costs (>US $100 billion) associated with cerebrovascular disease (CVD) will increase significantly as the US population grows and ages over the next 25 years. Existing 2D imaging modalities have inherent limitations in visualizing complex CVD, which may be mitigated with the use of patient-specific 3D advanced visualization (AV) technologies. There remain gaps in knowledge, however, regarding how and with what impact these technologies are being used in CVD. OBJECTIVE: The aim of this study was to characterize the clinical attributes and reported utility associated with the use of 3D AV modeling in CVDs, specifically intracerebral arteriovenous malformations. METHODS: This pilot study employs a combination of retrospective analysis and prospective surveys to describe the utilization and utility of patient-specific AV models at a single high-volume certified comprehensive stroke center. RESULTS: From July 2017 to February 2023, 25 AV models were created for 4 different clinicians. The average patient age was 37.4 years; 44% (11/25) of the patients were African Americans, 52% (13/25) were on public insurance, and 56% (14/25) were associated with a neurovascular procedure. In this study, 18 clinicians with diverse experience responded to AV model surveys, with a 92.2% (166/180) completion rate. There was an average reported utility of 8.0 on a 0-10 scale, with higher scores reflecting increased utility. Compared to 2D viewing, AV models allowed staff to appreciate novel abnormal anatomy, and therefore, they would have changed their therapeutic approach in 45% (23/51) of the cases. CONCLUSIONS: AV models were used in complex CVDs associated with young, publicly insured individuals requiring resource-intensive interventions. There was strong and diverse clinician engagement with overall report of substantial utility of AV models. Staff clinicians frequently reported novel anatomical and therapeutic insights based on AV models compared to traditional 2D viewing. This study establishes the infrastructure for future larger randomized studies that can be repeated for CVDs or other disease states and incorporate assessments of other AV modalities such as 3D printing and medical extended reality.
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 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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| 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 ».