Skip to main content

Main menu

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
Journal of Nuclear Medicine
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Journal of Nuclear Medicine

Advanced Search

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • View or Listen to JNM Podcast
  • Visit JNM on Facebook
  • Join JNM on LinkedIn
  • Follow JNM on Twitter
  • Subscribe to our RSS feeds
Research ArticleBRIEF COMMUNICATION
Open Access

ChatGPT: Can You Prepare My Patients for [18F]FDG PET/CT and Explain My Reports?

Julian M.M. Rogasch, Giulia Metzger, Martina Preisler, Markus Galler, Felix Thiele, Winfried Brenner, Felix Feldhaus, Christoph Wetz, Holger Amthauer, Christian Furth and Imke Schatka
Journal of Nuclear Medicine December 2023, 64 (12) 1876-1879; DOI: https://doi.org/10.2967/jnumed.123.266114
Julian M.M. Rogasch
1Department of Nuclear Medicine, Charité–Universitätsmedizin Berlin, Berlin, Germany;
2Berlin Institute of Health, Charité–Universitätsmedizin Berlin, Berlin, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Giulia Metzger
1Department of Nuclear Medicine, Charité–Universitätsmedizin Berlin, Berlin, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Martina Preisler
3Charité Comprehensive Cancer Center, Charité–Universitätsmedizin Berlin, Berlin, Germany; and
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Markus Galler
1Department of Nuclear Medicine, Charité–Universitätsmedizin Berlin, Berlin, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Felix Thiele
1Department of Nuclear Medicine, Charité–Universitätsmedizin Berlin, Berlin, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Winfried Brenner
1Department of Nuclear Medicine, Charité–Universitätsmedizin Berlin, Berlin, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Felix Feldhaus
4Department of Radiology, Charité–Universitätsmedizin Berlin, Berlin, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christoph Wetz
1Department of Nuclear Medicine, Charité–Universitätsmedizin Berlin, Berlin, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Holger Amthauer
1Department of Nuclear Medicine, Charité–Universitätsmedizin Berlin, Berlin, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christian Furth
1Department of Nuclear Medicine, Charité–Universitätsmedizin Berlin, Berlin, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Imke Schatka
1Department of Nuclear Medicine, Charité–Universitätsmedizin Berlin, Berlin, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF
Loading

Visual Abstract

Figure
  • Download figure
  • Open in new tab
  • Download powerpoint

Abstract

We evaluated whether the artificial intelligence chatbot ChatGPT can adequately answer patient questions related to [18F]FDG PET/CT in common clinical indications before and after scanning. Methods: Thirteen questions regarding [18F]FDG PET/CT were submitted to ChatGPT. ChatGPT was also asked to explain 6 PET/CT reports (lung cancer, Hodgkin lymphoma) and answer 6 follow-up questions (e.g., on tumor stage or recommended treatment). To be rated “useful” or “appropriate,” a response had to be adequate by the standards of the nuclear medicine staff. Inconsistency was assessed by regenerating responses. Results: Responses were rated “appropriate” for 92% of 25 tasks and “useful” for 96%. Considerable inconsistencies were found between regenerated responses for 16% of tasks. Responses to 83% of sensitive questions (e.g., staging/treatment options) were rated “empathetic.” Conclusion: ChatGPT might adequately substitute for advice given to patients by nuclear medicine staff in the investigated settings. Improving the consistency of ChatGPT would further increase reliability.

  • GPT-4
  • FDG PET/CT
  • artificial intelligence
  • chatbot
  • patient communication

The use of PET/CT is expected to increase because of a growing awareness of its value in clinical decision-making (1). With limited staff resources and mounting individual workloads, there is a need to increase efficiency, such as through use of artificial intelligence (AI) (2). Specifically, large language models such as OpenAI’s generative pretrained transformer (GPT) 4 might represent an information tool for patients to answer their questions when preparing for an examination or when reviewing the subsequent report.

However, the reliability of GPT can be undermined by false and potentially harmful responses termed hallucinations (3,4). False responses occur less often with more advanced versions such as GPT-4 (5) but have still been observed by Lee et al. (3).

Within the discipline of nuclear medicine, Buvat and Weber recently reported a brief interview with the AI chatbot ChatGPT. While remaining cautious in providing recommendations or solutions, they found that ChatGPT could answer technical questions well (6). It is neither foreseeable nor desirable that AI tools will replace physicians for informed consent. Furthermore, use of such tools by nuclear medicine departments is currently limited by unsolved liability issues (7). However, if validated in a clinical context, such a tool might still be used by patients to obtain information and general advice currently given by nuclear medicine staff (mainly technologists and physicians) and thereby enhance patient compliance (8).

To our knowledge, ours was the first systematic investigation of ChatGPT (with GPT-4) for patient communications related to PET/CT with [18F]FDG. We evaluated whether ChatGPT provides adequate, consistent responses and explanations to questions frequently asked by patients.

MATERIALS AND METHODS

ChatGPT Responses

OpenAI ChatGPT Plus was used in the May 24 version of GPT-4 (https://openai.com/chatgpt). ChatGPT was accessed on May 25 and 26, 2023. All questions and PET/CT reports were entered as single prompts in separate chats. Each prompt was repeated twice using the regenerate-response function, resulting in 3 trials per prompt. In addition, ChatGPT was asked to provide references (19 tasks).

Rating Process

Three nuclear medicine physicians, all of them native German speakers, rated the ChatGPT responses independently using the rating scale shown in Table 1. Appropriateness and usefulness were assessed with 4-point scales to prevent neutral responses and to facilitate binarization of results. Two readers were board-certified nuclear medicine physicians with more than 10 y of experience in PET/CT reading. The third reader was a resident in nuclear medicine with 2 y of PET/CT experience. The criterion “empathetic” was used only to rate the follow-up questions related to PET/CT reports. A binary item was used to avoid ambiguous or artificial grading with a multipoint scale.

View this table:
  • View inline
  • View popup
TABLE 1.

Criteria and Categories Used for Rating

In addition, 1 reader rated the level of inconsistency among the 3 responses generated for each question and checked and rated the validity of all references provided by ChatGPT.

Generating Questions and PET/CT Reports

Thirteen questions frequently asked by patients concerning [18F]FDG PET/CT imaging (Table 2; Q1–Q13) were formulated using simple, nontechnical language (e.g., “PET scan”).

View this table:
  • View inline
  • View popup
TABLE 2.

All 25 Tasks Submitted to ChatGPT and Majority Rating

Five PET/CT reports (Table 2; R1–R5) were derived from fictitious reports based on templates from our institution. The German reports were first translated with DeepL and then edited. Additionally, a sample report, “Sample Normal Report #2—Negative SPN,” provided by the Society of Nuclear Medicine and Molecular Imaging (9) was used (R6). In R1–R6, the same prompt, “Please explain my PET report to me: [full text of the report],” was used. Since the PET/CT reports were fictitious, no ethical approval was needed.

Statistical Analysis

The final rating for each task was selected by majority vote (except for “inconsistency” and “validity of references,” which were assessed by only 1 rater). When 3 different ratings arose, the middle category was chosen.

RESULTS

All questions, PET/CT reports, and ChatGPT responses can be found in Supplemental Files 1 and 2 (supplemental materials are available at http://jnm.snmjournals.org).

Rating of ChatGPT Responses

Responses by ChatGPT to 23 of 25 tasks were deemed “quite appropriate” or “fully appropriate” (92%, Table 2), whereas responses to 2 tasks (8%), R1Q1 and R4Q1, were rated “quite inappropriate.” Both questions queried tumor stage on the basis of a PET/CT report that did not explicitly state the tumor stage but contained information that would have enabled determining it using established staging systems. In both instances, ChatGPT identified 2 potential tumor stages, one of which was correct.

ChatGPT responses were rated “very helpful” or “quite helpful” by majority vote for 24 of 25 tasks (96%). The response to Q4 was rated “quite unhelpful” because ChatGPT did not caution against breastfeeding after a PET/CT scan, which might still be relevant for patients who are caretakers of toddlers.

In 5 of 6 follow-up questions (83%) related to the potential consequences of the PET/CT findings, ChatGPT responses were rated “empathetic.”

General Observations

ChatGPT answers were structured so as to form intelligible responses. ChatGPT framed responses that are likely to cause emotional reactions such as anxiety in a reassuring way (e.g., when revealing an advanced stage of metastatic lung cancer [R4Q1]). This is one of the aspects that the raters regarded as general signs of natural and humanlike responses (Supplemental File 3; Supplemental Table 1).

When PET/CT reports were being explained, the level of certainty conveyed by the ChatGPT responses seemed to depend on the clarity and extent of interpretation given in the report itself. We did not observe responses that were unrelated to the specific content of the PET/CT reports (hallucinations).

In 1 response, ChatGPT was able to provide a correct interpretation when explaining the PET/CT report of metastatic lung cancer (R5), although this interpretation was not explicitly provided in the report (Supplemental File 3; Supplemental Table 1).

Variation Among Trials

In responses to 21 of 25 tasks (84%), the 3 trials showed “irrelevant” or “minor” differences (Table 2). Responses to 4 tasks (16%)—3 of which were follow-up questions—were rated as showing “considerable” inconsistencies because ChatGPT addressed the specific tumor stage of the patient inconsistently.

Validity of References

In 2 of the 19 tasks (11%), 1 reference was considered invalid (hallucination) because the article could not be found by a manual search (details in Supplemental File 3; Supplemental Table 2).

References were fully valid in only 4 of 19 investigated tasks (21%). In 11 tasks (58%), at least 1 reference contained an outdated uniform resource locator or was only generic (e.g., “National Institute of Health’s U.S. National Library of Medicine”). In responses to 2 of 19 tasks (11%), the referenced article could be found only via a manual search.

DISCUSSION

None of the answers generated by ChatGPT would have caused harm or left the patient uninformed if the questions and PET/CT reports had been real patient inquiries.

Specifically, ChatGPT responses to more than 90% of questions were adequate and useful even by the standards expected of general advice given by nuclear medicine staff. In the 3 responses rated “quite unhelpful” or “quite inappropriate,” answers in at least one of the repeated trials were precise and correct. Although this observation shows that ChatGPT is per se capable of providing appropriate answers to all 25 tasks, this variation in responses led to a rating of “considerable inconsistency.” With future advances in AI models, the focus should be on reducing variation between responses so as to increase predictability and thus reliability.

The question of liability for AI-generated content still needs to be addressed. In a medical context, ChatGPT may be best regarded as an information tool rather than an advisory or decision tool. Every response from ChatGPT included a statement that the findings and their consequences should always be discussed with the treating physician (Supplemental File 3; Supplemental Table 3). Questions targeting crucial information, such as staging or treatment, were answered with the necessary empathy and an optimistic outlook.

We focused on the most common PET/CT tracer and on indications with a relatively large database of information available to GPT-4. The responses might be less helpful or reliable in the case of rare indications or new tracers, especially if the relevant literature has been published after the model training threshold (GPT-4: September 2021) (6). Validation in other contexts will therefore be required.

The issue of 2 invalid references to original articles that seem to have been hallucinated also demands further investigation.

CONCLUSION

ChatGPT may offer an adequate substitute for informational counseling to patients in lieu of that provided by nuclear medicine staff in the currently investigated setting of [18F]FDG PET/CT for Hodgkin lymphoma or lung cancer. With ever-decreasing time available for communication between staff and patients, readily accessible AI tools might provide a valuable means of improving patient involvement, the quality of patient preparation, and the patient’s understanding of nuclear medicine reports. The predictability and consistency of responses from AI tools should be further increased, such as by restricting their sources of information to peer-reviewed medical databases.

DISCLOSURE

No potential conflict of interest relevant to this article was reported.

KEY POINTS

QUESTION: Might ChatGPT substitute for advice given to patients on [18F]FDG PET/CT?

PERTINENT FINDINGS: ChatGPT responses were appropriate and useful, but we observed some inconsistency between trials.

IMPLICATIONS FOR PATIENT CARE: Proper use of AI tools might improve patients’ involvement and their understanding of PET/CT reports.

Footnotes

  • Published online Sep. 14, 2023.

  • © 2023 by the Society of Nuclear Medicine and Molecular Imaging.

Immediate Open Access: Creative Commons Attribution 4.0 International License (CC BY) allows users to share and adapt with attribution, excluding materials credited to previous publications. License: https://creativecommons.org/licenses/by/4.0/. Details: http://jnm.snmjournals.org/site/misc/permission.xhtml.

REFERENCES

  1. 1.↵
    Rate of PET examinations in the United States from 2004 to 2020 (per 1,000 population). Statista website. https://www.statista.com/statistics/962337/pet-examinations-in-united-states-rate-per-one-thousand/. Published August 28, 2023. Accessed August 30, 2023.
  2. 2.↵
    1. van Leeuwen KG,
    2. de Rooij M,
    3. Schalekamp S,
    4. van Ginneken B,
    5. Rutten M
    . How does artificial intelligence in radiology improve efficiency and health outcomes? Pediatr Radiol. 2022;52:2087–2093.
    OpenUrlCrossRefPubMed
  3. 3.↵
    1. Lee P,
    2. Bubeck S,
    3. Petro J
    . Benefits, limits, and risks of GPT-4 as an AI chatbot for medicine. N Engl J Med. 2023;388:1233–1239.
    OpenUrlCrossRefPubMed
  4. 4.↵
    1. González-Corbelle J,
    2. Alonso-Moral J,
    3. Bugarín-Diz A,
    4. Taboada J
    . Dealing with hallucination and omission in neural Natural Language Generation: a use case on meteorology. In: Proceedings of the 15th International Conference on Natural Language Generation. Association for Computational Linguistics; 2022:122–130.
  5. 5.↵
    Open AI. GPT-4 technical report. arXiv website. https://arxiv.org/abs/2303.08774. Published March 15, 2023. Revised March 27, 2023. Accessed August 30. 2023.
  6. 6.↵
    1. Buvat I,
    2. Weber W
    . Nuclear medicine from a novel perspective: Buvat and Weber talk with OpenAI’s ChatGPT. J Nucl Med. 2023;64:505–507.
    OpenUrlFREE Full Text
  7. 7.↵
    1. Minssen T,
    2. Vayena E,
    3. Cohen IG
    . The challenges for regulating medical use of ChatGPT and other large language models. JAMA. 2023;330:315–316.
    OpenUrlCrossRef
  8. 8.↵
    1. Rockall AG,
    2. Justich C,
    3. Helbich T,
    4. Vilgrain V
    . Patient communication in radiology: moving up the agenda. Eur J Radiol. 2022;155:110464.
    OpenUrlCrossRef
  9. 9.↵
    Elements of PET/CT reporting. SNMMI website. http://s3.amazonaws.com/rdcms-snmmi/files/production/public/docs/PET_PROS/ElementsofPETCTReporting.pdf. Published May 2009. Accessed August 30. 2023.
  • Received for publication June 2, 2023.
  • Revision received August 22, 2023.
PreviousNext
Back to top

In this issue

Journal of Nuclear Medicine: 64 (12)
Journal of Nuclear Medicine
Vol. 64, Issue 12
December 1, 2023
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
  • Complete Issue (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Journal of Nuclear Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
ChatGPT: Can You Prepare My Patients for [18F]FDG PET/CT and Explain My Reports?
(Your Name) has sent you a message from Journal of Nuclear Medicine
(Your Name) thought you would like to see the Journal of Nuclear Medicine web site.
Citation Tools
ChatGPT: Can You Prepare My Patients for [18F]FDG PET/CT and Explain My Reports?
Julian M.M. Rogasch, Giulia Metzger, Martina Preisler, Markus Galler, Felix Thiele, Winfried Brenner, Felix Feldhaus, Christoph Wetz, Holger Amthauer, Christian Furth, Imke Schatka
Journal of Nuclear Medicine Dec 2023, 64 (12) 1876-1879; DOI: 10.2967/jnumed.123.266114

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
ChatGPT: Can You Prepare My Patients for [18F]FDG PET/CT and Explain My Reports?
Julian M.M. Rogasch, Giulia Metzger, Martina Preisler, Markus Galler, Felix Thiele, Winfried Brenner, Felix Feldhaus, Christoph Wetz, Holger Amthauer, Christian Furth, Imke Schatka
Journal of Nuclear Medicine Dec 2023, 64 (12) 1876-1879; DOI: 10.2967/jnumed.123.266114
Twitter logo Facebook logo LinkedIn logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

  • Article
    • Visual Abstract
    • Abstract
    • MATERIALS AND METHODS
    • RESULTS
    • DISCUSSION
    • CONCLUSION
    • DISCLOSURE
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF

Related Articles

  • PubMed
  • Google Scholar

Cited By...

  • Is ChatGPT a Reliable Ghostwriter?
  • Artificial Intelligence in Healthcare: 2023 Year in Review
  • Systematic Review of Large Language Models for Patient Care: Current Applications and Challenges
  • Google Scholar

More in this TOC Section

  • Bioanalytic Hybrid System Merging 3-Dimensional Cell Culture and Chromatographic Precision for Unprecedented Preclinical Insights in Molecular Imaging
  • Radiances of Cerenkov-Emitting Radionuclides on the In Vivo Imaging System
  • Measuring Total Metabolic Tumor Volume from 18F-FDG PET: A Reality Check
Show more BRIEF COMMUNICATION

Similar Articles

Keywords

  • GPT-4
  • FDG PET/CT
  • artificial intelligence
  • chatbot
  • patient communication
SNMMI

© 2025 SNMMI

Powered by HighWire