Assessment of Generative Artificial Intelligence (AI) Models in Creating Medical Illustrations for Various Corneal Transplant Procedures.

Autor:	Moin KA; Hoopes Vision Research Center, Hoopes Vision, Draper, USA.; School of Medicine, American University of the Caribbean, Cupecoy, SXM., Nasir AA; Ophthalmology, University of Louisville School of Medicine, Louisville, USA., Petroff DJ; Ophthalmology, Idaho College of Osteopathic Medicine, Meridian, USA., Loveless BA; Ophthalmology, Rocky Vista University College of Osteopathic Medicine, Ivins, USA.; Hoopes Vision Research Center, Hoopes Vision, Draper, USA., Moshirfar OA; Sam Fox School of Design and Visual Art, Washington University in St. Louis, St. Louis, USA., Hoopes PC; Hoopes Vision Research Center, Hoopes Vision, Draper, USA., Moshirfar M; Hoopes Vision Research Center, Hoopes Vision, Draper, USA.; John A. Moran Eye Center, University of Utah School of Medicine, Salt Lake City, USA.; Eye Banking and Corneal Transplantation, Utah Lions Eye Bank, Murray, USA.
Jazyk:	angličtina
Zdroj:	Cureus [Cureus] 2024 Aug 26; Vol. 16 (8), pp. e67833. Date of Electronic Publication: 2024 Aug 26 (Print Publication: 2024).
DOI:	10.7759/cureus.67833
Abstrakt:	Purpose: This study aimed to task and assess generative artificial intelligence (AI) models in creating medical illustrations for corneal transplant procedures such as Descemet's stripping automated endothelial keratoplasty (DSAEK), Descemet's membrane endothelial keratoplasty (DMEK), deep anterior lamellar keratoplasty (DALK), and penetrating keratoplasty (PKP).  Methods: Six engineered prompts were provided to Decoder-Only Autoregressive Language and Image Synthesis 3 (DALL-E 3) and Medical Illustration Manager (MIM) to guide these generative AI models in creating a final medical illustration for each of the four corneal transplant procedures. Control illustrations were created by the authors for each transplant technique for comparison. A grading system with five categories with a maximum score of 3 points each (15 points total) was designed to objectively assess AI's performance. Four independent reviewers analyzed and scored the final images produced by DALL-E 3 and MIM as well as the control illustrations. All AI-generated images and control illustrations were then provided to Chat Generative Pre-Trained Transformer-4o (ChatGPT-4o), which was tasked with grading each image with the grading system described above. All results were then tabulated and graphically depicted. Results: The control illustration images received significantly higher scores than produced images from DALL-E 3 and MIM in legibility, anatomical realism and accuracy, procedural step accuracy, and lack of fictitious anatomy (p<0.001). For detail and clarity, the control illustrations and images produced by DALL-E 3 and MIM received statistically similar scores of 2.75±0.29, 2.19±0.24, and 2.50±0.29, respectively (p=0.0504). With regard to mean cumulative scores for each transplant procedure image, the control illustrations received a significantly higher score than DALL-E 3 and MIM (p<0.001). Additionally, the overall mean cumulative score for the control illustrations was significantly higher than DALL-E 3 and MIM (14.56±0.51 (97.1%), 4.38±1.2 (29.2%), and 5.63±1.82 (37.5%), respectively (p<0.001)). When assessing AI's grading performance, ChatGPT-4o scored the images produced by DALL-E 3 and MIM significantly higher than the average scores of the independent reviewers (DALL-E 3: 10.0±0.0 (66.6%) vs. 4.38±1.20 (29.2%), p<0.001; MIM: 10.0±0.0 (66.6%) vs. 5.63±1.82 (37.5%), p<0.001). However, mean scores for the control illustrations between ChatGPT-4o and the independent reviewers were comparable (15.0±0.0 (100%) vs. 14.56±0.13 (97.1%); p>0.05). Conclusion: AI is an extremely powerful and efficient tool for many tasks, but it is currently limited in producing accurate medical illustrations for corneal transplant procedures. Further development is required for generative AI models to create medically sound and accurate illustrations for use in ophthalmology. Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Hoopes Vision Ethics Committee and Biomedical Research Alliance of New York (BRANY) Institutional Review Board (IRB) issued approval A20-12-547-823. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work. (Copyright © 2024, Moin et al.)
Databáze:	MEDLINE
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