Canada’s Early Experiences With Low-Field MRI: Insights From a Cross-Country Survey
Notice bibliographique
Résumé
What Is the Issue? Canada’s Drug Agency (CDA-AMC) received a request to investigate the experiences of health care institutions with their low-field MRI units, including portable or point-of-care units, to support facilities that are considering this technology. Low-field MRI systems operate using lower-strength magnetic fields and have seen a resurgence due to recent innovations improving image quality. They can supplement existing MRI capacity, expand access in resource-limited settings, and may be an option for patients who have certain contraindications or cannot tolerate conventional MRI systems. We identified 1 previous study that examined portable MRI use in a remote hospital in Ontario. Our findings build on that work, incorporating data from facilities across a range of settings and jurisdictions, and providing a broader view of how these units were being used in the Canadian context at the time the survey was conducted. What Did We Do? CDA-AMC conducted a survey of the 6 known health care facilities identified through the 2022–2023 Canadian Medical Imaging Inventory National Survey as having low-field MRI units. The report summarizes the experiences of 5 respondents to the survey, which explored the following themes: technical specifications and operations staffing and training needs clinical applications perceived impacts on patient care experiences perceived benefits and challenges. What Did We Find? Respondents provided valuable insights into low-field MRI use in Canada. According to the survey: 4 of 5 respondents said they had access to a conventional MRI unit, and 1 respondent indicated that low-field MRI units are often used to complement existing imaging services all respondents reported few technical issues with low-field MRI units and no adverse events that affect patients or staff 4 of 5 respondents said that minimal training was required to operate low-field MRI units, whereas 1 respondent indicated that more extensive training was required all respondents said that the body areas most commonly imaged with low-field MRI are the head and neck 3 of 5 respondents reported improved imaging capabilities with low-field MRI, whereas 2 indicated no improvement 4 of 5 respondents cited portability and compact size as advantages of low-field MRI units over conventional MRI units 2 of 5 respondents mentioned image resolution as a challenge for low-field MRI units, with another respondent reporting challenges with staffing capacity. What Does This Mean? This report covers 5 of 6 facilities known to have low-field MRI systems at the time of this survey, providing the first national-level examination of their use in a variety of settings and jurisdictions, and encompassing both research and clinical practice. The findings highlight how low-field MRI units are being used — not as replacements for conventional MRI systems, but as complementary tools suited to specific clinical needs or use in space-limited or high-acuity environments. An understanding of the perceived strengths and weaknesses of these units may help decision-makers make planning decisions regarding new imaging capacity.
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 | 0,005 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,016 | 0,005 |
| Communication savante | 0,006 | 0,002 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,004 |
| 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 ».