Ethical Considerations in Patient Privacy and Data Handling for AI in Cardiovascular Imaging and Radiology

Kaul V, Enslin S, Gross SA. History of artificial intelligence in medicine. Gastrointest Endosc. 2020;92(4):807-12.

Article  PubMed  Google Scholar 

Coiera EW. Artificial Intelligence in Medicine: The Challenges Ahead. Journal of the American Medical Informatics Association. 1996;3(6):363-6.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Jiang B, Guo N, Ge Y, Zhang L, Oudkerk M, Xie X. Development and application of artificial intelligence in cardiac imaging. British Journal of Radiology. 2020;93(1113):20190812.

Article  PubMed  PubMed Central  Google Scholar 

Bernard O, Lalande A, Zotti C, Cervenansky F, Yang X, Heng PA, et al. Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? IEEE Transactions on Medical Imaging. 2018;37(11):2514-25.

Article  PubMed  Google Scholar 

Sengupta PP, Dey D, Davies RH, Duchateau N, Yanamala N. Challenges for augmenting intelligence in cardiac imaging. The Lancet Digital Health. 2024;6(10):e739-e48.

Article  CAS  PubMed  Google Scholar 

Yang Y, Zhang H, Gichoya JW, Katabi D, Ghassemi M. The limits of fair medical imaging AI in real-world generalization. Nature Medicine. 2024;30(10):2838-48.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Eche T, Schwartz LH, Mokrane F-Z, Dercle L. Toward Generalizability in the Deployment of Artificial Intelligence in Radiology: Role of Computation Stress Testing to Overcome Underspecification. Radiology: Artificial Intelligence. 2021;3(6):e210097.

PubMed  PubMed Central  Google Scholar 

Kohli M, Prevedello LM, Filice RW, Geis JR. Implementing Machine Learning in Radiology Practice and Research. AJR Am J Roentgenol. 2017;208(4):754-60.

Article  PubMed  Google Scholar 

Erickson BJ, Korfiatis P, Akkus Z, Kline TL. Machine Learning for Medical Imaging. Radiographics. 2017;37(2):505-15.

Article  PubMed  Google Scholar 

Mittelstadt BD, Floridi L. The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts. Sci Eng Ethics. 2016;22(2):303-41.

Article  PubMed  Google Scholar 

Geis JR, Brady A, Wu CC, Spencer J, Ranschaert E, Jaremko JL, et al. Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement. Insights into Imaging. 2019;10(1):101.

Article  PubMed  PubMed Central  Google Scholar 

Murdoch B. Privacy and artificial intelligence: challenges for protecting health information in a new era. BMC Medical Ethics. 2021;22(1):122.

Article  PubMed  PubMed Central  Google Scholar 

Brady AP, Neri E. Artificial Intelligence in Radiology-Ethical Considerations. Diagnostics (Basel). 2020;10(4).

Kadam RA. Informed consent process: A step further towards making it meaningful! Perspectives in Clinical Research. 2017;8(3).

Geis J.R. BAP, Wu C.C., Spencer J., Ranschaert E., Jaremko J.L., Langer S.G., Borondy Kitts A., Birch J., Shields W.F., et al. Ethics of AI in Radiology: Joint European and North American Multisociety Statement. [(accessed on 16 April 2020)] [Available from: https://www.acr.org/-/media/ACR/Files/Informatics/Ethics-of-AI-in-Radiology-European-and-North-American-Multisociety-Statement%2D%2D6-13-2019.pdf.

Fotaki A, Puyol-Antón E, Chiribiri A, Botnar R, Pushparajah K, Prieto C. Artificial Intelligence in Cardiac MRI: Is Clinical Adoption Forthcoming? Front Cardiovasc Med. 2021;8:818765.

Article  PubMed  Google Scholar 

De-identification of Protected Health Information: How to Anonymize PHI [Available from: https://www.hipaajournal.com/de-identification-protected-health-information/.

Kalkman S, Mostert M, Gerlinger C, van Delden JJM, van Thiel G. Responsible data sharing in international health research: a systematic review of principles and norms. BMC Med Ethics. 2019;20(1):21.

Article  PubMed  PubMed Central  Google Scholar 

GDPR Versus PIPL – Key Differences and Implications for Compliance in China [Available from: https://www.china-briefing.com/news/pipl-vs-gdpr-key-differences-and-implications-for-compliance-in-china/.

Health Information Privacy [Available from: https://www.hhs.gov/hipaa/for-professionals/privacy/laws-regulations/index.html.

Tovino SA. Artificial Intelligence and the HIPAA Privacy Rule: A Primer. Houston Journal of Health Law & Policy. 2025;24(1):77-126.

Google Scholar 

Dankar FK, El Emam K, Neisa A, Roffey T. Estimating the re-identification risk of clinical data sets. BMC Medical Informatics and Decision Making. 2012;12(1):66.

Article  PubMed  PubMed Central  Google Scholar 

Garfinkel S. De-Identification of Personal Information. NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD; 2015.

Book  Google Scholar 

Sweeney L, Yoo JS, Perovich L, Boronow KE, Brown P, Brody JG. Re-identification Risks in HIPAA Safe Harbor Data: A study of data from one environmental health study. Technol Sci. 2017;2017.

Schwarz CG, Kremers WK, Therneau TM, Sharp RR, Gunter JL, Vemuri P, et al. Identification of Anonymous MRI Research Participants with Face-Recognition Software. N Engl J Med. 2019;381(17):1684-6.

Article  PubMed  PubMed Central  Google Scholar 

Schwarz CG, Kremers WK, Lowe VJ, Savvides M, Gunter JL, Senjem ML, et al. Face recognition from research brain PET: An unexpected PET problem. NeuroImage. 2022;258:119357.

Article  PubMed  Google Scholar 

Jwa AS, Koyejo O, Poldrack RA. Demystifying the likelihood of reidentification in neuroimaging data: A technical and regulatory analysis. Imaging Neuroscience. 2024;2:1-18.

Article  Google Scholar 

Aryanto KYE, Oudkerk M, van Ooijen PMA. Free DICOM de-identification tools in clinical research: functioning and safety of patient privacy. European Radiology. 2015;25(12):3685-95.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Williamson SM, Prybutok V. Balancing Privacy and Progress: A Review of Privacy Challenges, Systemic Oversight, and Patient Perceptions in AI-Driven Healthcare. Applied Sciences. 2024;14(2):675.

Article  CAS  Google Scholar 

Li T, Sahu AK, Talwalkar A, Smith V. Federated Learning: Challenges, Methods, and Future Directions. IEEE Signal Processing Magazine. 2020;37(3):50-60.

Article  CAS  Google Scholar 

Petersen SE, Abdulkareem M, Leiner T. Artificial Intelligence Will Transform Cardiac Imaging-Opportunities and Challenges. Front Cardiovasc Med. 2019;6:133.

Article  PubMed  PubMed Central  Google Scholar 

Yadav N, Pandey S, Gupta A, Dudani P, Gupta S, Rangarajan K. Data Privacy in Healthcare: In the Era of Artificial Intelligence. Indian Dermatol Online J. 2023;14(6):788-92.

Article  PubMed  PubMed Central  Google Scholar 

Lee RS, Gimenez F, Hoogi A, Miyake KK, Gorovoy M, Rubin DL. A curated mammography data set for use in computer-aided detection and diagnosis research. Sci Data. 2017;4:170177.

Article  PubMed  PubMed Central  Google Scholar 

Halling-Brown MD, Warren LM, Ward D, Lewis E, Mackenzie A, Wallis MG, et al. OPTIMAM Mammography Image Database: A Large-Scale Resource of Mammography Images and Clinical Data. Radiol Artif Intell. 2021;3(1):e200103.

Article  PubMed  Google Scholar 

Shandhi MMH, Singh K, Janson N, Ashar P, Singh G, Lu B, et al. Assessment of ownership of smart devices and the acceptability of digital health data sharing. NPJ Digit Med. 2024;7(1):44.

Article  PubMed  PubMed Central  Google Scholar 

Li M, Xu P, Hu J, Tang Z, Yang G. From challenges and pitfalls to recommendations and opportunities: Implementing federated learning in healthcare. Medical Image Analysis. 2025;101:103497.

Article  PubMed  Google Scholar 

McGraw D, Mandl KD. Privacy protections to encourage use of health-relevant digital data in a learning health system. NPJ Digital Medicine. 2021;4(1):2.

Article  PubMed  PubMed Central  Google Scholar 

Hu Y, Li Z, Liu Z, Zhang Y, Qin Z, Ren K, et al. Membership Inference Attacks Against Vision-Language Models2025.

El Emam K, Mosquera L, Bass J. Evaluating Identity Disclosure Risk in Fully Synthetic Health Data: Model Development and Validation. J Med Internet Res. 2020;22(11):e23139.

Article  PubMed  PubMed Central  Google Scholar 

Dar SUH, Seyfarth M, Ayx I, Papavassiliu T, Schoenberg SO, Siepmann RM, et al. Unconditional Latent Diffusion Models Memorize Patient Imaging Data: Implications for Openly Sharing Synthetic Data. 2025.

Paterick ZR, Paterick TE. Preparticipation Cardiovascular Screening of Student-Athletes with Echocardiography: Ethical, Clinical, Economic, and Legal Considerations. Current Cardiology Reports. 2019;21(3):16.

Comments (0)

No login
gif