Emerging technologies in medical physics: the role of artificial intelligence in medical imaging and potential adoption in Ghana.

چکیده اصلی

BACKGROUND: Ghana's imaging services face rising demand, uneven digital infrastructure, and limited access to advanced modalities. Artificial intelligence (AI) could improve diagnostic accuracy, workflow efficiency, and access, but real-world adoption is early. OBJECTIVE: Assess Ghana's readiness to adopt AI in medical imaging, identify pathways and barriers, and propose a phased, context-specific roadmap. METHODS: A review of peer-reviewed and grey literature (2012-March 2025) using PubMed, IEEE Xplore, Scopus, Google Scholar, and Ghanaian institutional documents. The review emphasizes imaging AI, LMIC experiences, and Ghana-specific evidence on infrastructure, policy, and pilots, distinguishing Ghana-based findings from international evidence extrapolated to Ghana. RESULTS: Major gaps include digital infrastructure (limited PACS, variable DR/CR adoption, uneven connectivity), financing (license and maintenance costs), governance (SaMD pathways exist but AI-specific provisions are evolving; operational data protection needs strengthening), and workforce (limited AI literacy; urban - rural disparities). Ghana-relevant touchpoints include MinoHealth.AI chest radiography evaluations, the national imaging equipment inventory, Ghana Health Service digital health strategy (2023-2027), and FDA SaMD guidance. A phased roadmap is proposed: establish PACS and connectivity; implement AI governance and data stewardship; run targeted pilots in CXR triage, low-dose CT, and MRI acceleration; scale via public-private partnerships and pooled procurement; and sustain workforce development with human-in-the-loop oversight. CONCLUSIONS: AI can improve equity and efficiency in imaging in Ghana if adoption builds on strong digital foundations, robust governance, local validation, and clinician-led implementation. Priorities include PACS deployment, AI-specific regulatory strengthening, ethical data governance, and capacity building to support safe, equitable, and sustainable use.

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