Building AI Capability in Medical Imaging: A Co-Designed Continuing Professional Development Framework and Evaluation

Building AI Capability in Medical Imaging: A Co-Designed Continuing Professional Development Framework and Evaluation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Building AI Capability in Medical Imaging: A Co-Designed Continuing Professional Development Framework and Evaluation Shereen Fouad, Abdallah Abdelhameed, Aniko Ekart, Arvind Rajasekaran, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9379301/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background: Artificial intelligence (AI) is increasingly embedded in medical imaging workflows, yet many imaging professionals report limited preparation to evaluate, implement, and govern AI tools safely. This educational gap risks inappropriate reliance on AI systems and undermines effective clinical oversight and patient safety. Methods: We undertook a Three-phase mixed-methods study to co-design and evaluate a tiered AI education framework for healthcare professionals, with an emphasis on medical imaging. A hybrid co-design workshop involving 52 healthcare stakeholders identified AI knowledge gaps, role-specific needs, and training preferences, informing a Three-pathway framework spanning foundational AI literacy, imaging-focused proficiency, and policy and governance. Two continuing professional development courses - AI Literacy in Healthcare and AI in Medical Imaging – were subsequently designed and delivered to over 300 healthcare professionals. Pre- and post-course surveys (132/59 responses for AI literacy; 26/30 for AI in medical imaging) captured self-reported changes in knowledge, confidence, and understanding of ethical and regulatory issues; quantitative data were analysed descriptively and qualitative free-text responses thematically. Results: Workshop participants reported widespread gaps in foundational AI literacy, critical appraisal skills, and awareness of governance and regulatory requirements, and strongly endorsed the need for structured, role-specific training. For the AI literacy course, participants reported substantial short-term gains in core AI concepts, clinical use cases, and responsible AI principles, alongside increased confidence in discussing AI with colleagues and patients. Among imaging professionals, the AI in medical imaging course was associated with marked perceived improvements in understanding AI model training and validation, performance metrics, AI explainability, bias, and workflow integration with PACS/RIS, and in readiness to engage with AI-enabled imaging tools under appropriate human oversight. Conclusion: A co-designed, tiered AI education framework can address heterogeneous AI literacy and capability needs across the healthcare and medical imaging workforce, strengthening confidence and perceived preparedness for safe AI adoption. The proposed pathways offer a clinically grounded, governance-aware, and scalable structure that healthcare organisations and educators can adapt to support progressive, role-aligned AI capability building in medical imaging and related domains. Artificial intelligence education AI literacy Continuing professional development Co-designed curriculum Full Text Additional Declarations No competing interests reported. Supplementary Files AdditionalFile1PreandPostCourseSurveyInstruments.pdf Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 12 May, 2026 Reviewers invited by journal 12 May, 2026 Editor assigned by journal 11 May, 2026 Editor invited by journal 17 Apr, 2026 Submission checks completed at journal 16 Apr, 2026 First submitted to journal 16 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9379301","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":625842812,"identity":"9edae65f-464a-4fdf-b0e8-fe77c1eb10fe","order_by":0,"name":"Shereen Fouad","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYFACxgdAglkOSYSNkBZmAxBhDMQkaklsIFqLfAMz42OeGuv0/v7zBx8XMNjJM0ikJeDVYnCAmdmY51h67owbyczGMxiSDRsk0g7g18LAf0yah+1wbsMNZjZpHgbmBAaJ9AZCDgOq/Hc4Xf78YZCWesJaGA4AtfC2HU4wOJAM0nIYqIWQww4zMxvO7Us33Hgj2diYx+C4YRvPswT8DmtvZnzw5pu1vNz5gw8f81RUy/OzpxngdxgzCs+AiIgcBaNgFIyCUUAYAADM/jbJz67vyQAAAABJRU5ErkJggg==","orcid":"","institution":"Aston University","correspondingAuthor":true,"prefix":"","firstName":"Shereen","middleName":"","lastName":"Fouad","suffix":""},{"id":625842814,"identity":"ed278f02-f021-41e4-a965-0b0d16306344","order_by":1,"name":"Abdallah Abdelhameed","email":"","orcid":"","institution":"Aston University","correspondingAuthor":false,"prefix":"","firstName":"Abdallah","middleName":"","lastName":"Abdelhameed","suffix":""},{"id":625842815,"identity":"09f0602b-07e2-401e-89ce-8c9060a4aa9d","order_by":2,"name":"Aniko Ekart","email":"","orcid":"","institution":"Aston University","correspondingAuthor":false,"prefix":"","firstName":"Aniko","middleName":"","lastName":"Ekart","suffix":""},{"id":625842816,"identity":"189c1722-bac0-4d83-806f-d704dfc9f003","order_by":3,"name":"Arvind Rajasekaran","email":"","orcid":"","institution":"Sandwell \u0026 West Birmingham Hospitals NHS Trust","correspondingAuthor":false,"prefix":"","firstName":"Arvind","middleName":"","lastName":"Rajasekaran","suffix":""},{"id":625842817,"identity":"0f98b5cf-f7e2-4aa1-a3f3-afe7cf816840","order_by":4,"name":"John Morlese","email":"","orcid":"","institution":"Sandwell \u0026 West Birmingham Hospitals NHS Trust","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Morlese","suffix":""},{"id":625842820,"identity":"3c112cc1-d529-4ef6-a36b-b1d35dfd3951","order_by":5,"name":"Bahadar Bhatia","email":"","orcid":"","institution":"Sandwell \u0026 West Birmingham Hospitals NHS Trust","correspondingAuthor":false,"prefix":"","firstName":"Bahadar","middleName":"","lastName":"Bhatia","suffix":""}],"badges":[],"createdAt":"2026-04-10 12:08:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9379301/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9379301/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108804187,"identity":"2fc85652-b5ae-4726-98f8-e366a502d92f","added_by":"auto","created_at":"2026-05-08 15:17:29","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":19071940,"visible":true,"origin":"","legend":"","description":"","filename":"BuildingAICapabilityinMedicalImagingACoDesignedContinuingProfessionalDevelopmentFrameworkandEvaluation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9379301/v1_covered_120933e0-e223-43c7-a31f-03981eb4f003.pdf"},{"id":108389209,"identity":"62adbf07-a2d6-4647-a884-68f90ce2cebd","added_by":"auto","created_at":"2026-05-04 06:47:38","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":642150,"visible":true,"origin":"","legend":"","description":"","filename":"AdditionalFile1PreandPostCourseSurveyInstruments.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9379301/v1/c27928a906d765d4a0bc5373.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Building AI Capability in Medical Imaging: A Co-Designed Continuing Professional Development Framework and Evaluation","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Artificial intelligence education, AI literacy, Continuing professional development, Co-designed curriculum","lastPublishedDoi":"10.21203/rs.3.rs-9379301/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9379301/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Artificial intelligence (AI) is increasingly embedded in medical imaging workflows, yet many imaging professionals report limited preparation to evaluate, implement, and govern AI tools safely. This educational gap risks inappropriate reliance on AI systems and undermines effective clinical oversight and patient safety.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethods: We undertook a Three-phase mixed-methods study to co-design and evaluate a tiered AI education framework for healthcare professionals, with an emphasis on medical imaging. A hybrid co-design workshop involving 52 healthcare stakeholders identified AI knowledge gaps, role-specific needs, and training preferences, informing a Three-pathway framework spanning foundational AI literacy, imaging-focused proficiency, and policy and governance. Two continuing professional development courses - AI Literacy in Healthcare and AI in Medical Imaging – were subsequently designed and delivered to over 300 healthcare professionals. Pre- and post-course surveys (132/59 responses for AI literacy; 26/30 for AI in medical imaging) captured self-reported changes in knowledge, confidence, and understanding of ethical and regulatory issues; quantitative data were analysed descriptively and qualitative free-text responses thematically.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: Workshop participants reported widespread gaps in foundational AI literacy, critical appraisal skills, and awareness of governance and regulatory requirements, and strongly endorsed the need for structured, role-specific training. For the AI literacy course, participants reported substantial short-term gains in core AI concepts, clinical use cases, and responsible AI principles, alongside increased confidence in discussing AI with colleagues and patients. Among imaging professionals, the AI in medical imaging course was associated with marked perceived improvements in understanding AI model training and validation, performance metrics, AI explainability, bias, and workflow integration with PACS/RIS, and in readiness to engage with AI-enabled imaging tools under appropriate human oversight.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusion: A co-designed, tiered AI education framework can address heterogeneous AI literacy and capability needs across the healthcare and medical imaging workforce, strengthening confidence and perceived preparedness for safe AI adoption. The proposed pathways offer a clinically grounded, governance-aware, and scalable structure that healthcare organisations and educators can adapt to support progressive, role-aligned AI capability building in medical imaging and related domains.\u003c/p\u003e","manuscriptTitle":"Building AI Capability in Medical Imaging: A Co-Designed Continuing Professional Development Framework and Evaluation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-04 06:47:29","doi":"10.21203/rs.3.rs-9379301/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"11027542841886016078823205712124899558","date":"2026-05-12T11:43:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-12T10:16:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-11T07:59:36+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-17T16:28:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-16T14:52:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2026-04-16T14:17:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0c5ccc2c-9940-4fb6-84d2-1b9213e33b45","owner":[],"postedDate":"May 4th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"11027542841886016078823205712124899558","date":"2026-05-12T11:43:11+00:00","index":44,"fulltext":""},{"type":"reviewersInvited","content":"15","date":"2026-05-12T10:16:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-11T07:59:36+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T10:32:04+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-04 06:47:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9379301","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9379301","identity":"rs-9379301","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}