Responsible Use of Artificial Intelligence Tools in Imaging Reporting: Practical Guidelines for Sonographers-A Narrative Review.
- 1Diagnostic Radiography Technology Department, College of Nursing and Health Sciences, Jazan University, Jazan 45142, Saudi Arabia.
Abstract
Artificial intelligence (AI) is rapidly entering diagnostic ultrasound, supporting image acquisition, automated measurement, computer-aided diagnosis, and report drafting. Sonographers are primary users of these tools, yet sonographer-oriented guidance on their responsible use in imaging reporting remains fragmented. This narrative review synthesizes current evidence, reporting guidelines, trustworthiness frameworks, regulations, and professional standards relevant to AI-assisted imaging reporting to distill practical guidance for sonographers. PubMed/MEDLINE, Scopus, and Google Scholar were searched, together with professional-body and regulatory documents published up to July 2026. The review maps AI applications across the reporting chain, from real-time acquisition guidance (AI-guided echocardiography achieving diagnostic-quality images in 98.8% of novice-obtained scans) to computer-aided diagnosis improving breast lesion assessment (area under the curve increasing from 0.83 to 0.87) and large language models drafting structured reports. Evidence on automation bias, deskilling, hallucinated content, algorithmic bias, and medico-legal accountability is critically appraised. Building on FUTURE-AI, CONSORT-AI, DECIDE-AI, and World Health Organization guidance, a phase-based good-practice framework is proposed, covering pre-use appraisal and training, verification during use, and documentation and audit after use. AI should augment, not replace, sonographer judgment; human oversight, verification of every AI output, transparent documentation, and continuing AI literacy are prerequisites for safe adoption in imaging reporting.
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BibTeX
@article{elnaeem2026responsible,
title = {{Responsible Use of Artificial Intelligence Tools in Imaging Reporting: Practical Guidelines for Sonographers-A Narrative Review.}},
author = {Mozdalifah Elnaeem},
journal = {Healthcare (Basel, Switzerland)},
year = {2026},
month = oct,
doi = {10.3390/healthcare14203548},
url = {https://europepmc.org/article/MED/42940593},
note = {CC BY},
}
RIS
TY - JOUR
TI - Responsible Use of Artificial Intelligence Tools in Imaging Reporting: Practical Guidelines for Sonographers-A Narrative Review.
AU - Mozdalifah Elnaeem
PY - 2026
DA - 2026/10/21
JO - Healthcare (Basel, Switzerland)
DO - 10.3390/healthcare14203548
UR - https://europepmc.org/article/MED/42940593
AB - Artificial intelligence (AI) is rapidly entering diagnostic ultrasound, supporting image acquisition, automated measurement, computer-aided diagnosis, and report drafting. Sonographers are primary users of these tools, yet sonographer-oriented guidance on their responsible use in imaging reporting remains fragmented. This narrative review synthesizes current evidence, reporting guidelines, trustworthiness frameworks, regulations, and professional standards relevant to AI-assisted imaging reporting to distill practical guidance for sonographers. PubMed/MEDLINE, Scopus, and Google Scholar were searched, together with professional-body and regulatory documents published up to July 2026. The review maps AI applications across the reporting chain, from real-time acquisition guidance (AI-guided echocardiography achieving diagnostic-quality images in 98.8% of novice-obtained scans) to computer-aided diagnosis improving breast lesion assessment (area under the curve increasing from 0.83 to 0.87) and large language models drafting structured reports. Evidence on automation bias, deskilling, hallucinated content, algorithmic bias, and medico-legal accountability is critically appraised. Building on FUTURE-AI, CONSORT-AI, DECIDE-AI, and World Health Organization guidance, a phase-based good-practice framework is proposed, covering pre-use appraisal and training, verification during use, and documentation and audit after use. AI should augment, not replace, sonographer judgment; human oversight, verification of every AI output, transparent documentation, and continuing AI literacy are prerequisites for safe adoption in imaging reporting.
SN - 2227-9032
ER -