ChatGPT and radiology report: potential applications and limitations

被引:7
作者
Parillo, Marco [1 ]
Vaccarino, Federica [1 ,3 ]
Zobel, Bruno Beomonte [2 ,3 ]
Mallio, Carlo Augusto [2 ,3 ]
机构
[1] APSS Prov Autonoma Trento, Multizonal Unit Rovereto & Arco, Radiol, Trento, Italy
[2] Fdn Policlin Univ Campus Bio Med, Via Alvaro Portillo, 200, I-00128 Rome, Italy
[3] Univ Campus Bio Med Roma, Dept Med & Surg, Res Unit Diag Imaging & Intervent Radiol, Via Alvaro Portillo, 21, I-00128 Rome, Italy
来源
RADIOLOGIA MEDICA | 2024年 / 129卷 / 12期
关键词
Artificial intelligence; Generative pretrained transformer; Natural language processing; Medical imaging; Structured report; Radiological reporting;
D O I
10.1007/s11547-024-01915-7
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Large language models like ChatGPT, with their growing accessibility, are attracting increasing interest within the artificial intelligence medical field, particularly in the analysis of radiology reports. These present a valuable opportunity to explore the potential clinical applications of large language models, given their huge capabilities in processing and understanding written language. Early research indicates that ChatGPT could offer benefits in radiology reporting. ChatGPT can assist but not replace radiologists in achieving diagnoses, generating structured reports, extracting data, identifying errors or incidental findings, and can also serve as a support in creating patient-friendly reports. However, ChatGPT also has intrinsic limitations, such as hallucinations, stochasticity, biases, deficiencies in complex clinical scenarios, data privacy and legal concerns. To fully utilize the potential of ChatGPT in radiology reporting, careful integration planning and rigorous validation of their outputs are crucial, especially for tasks requiring abstract reasoning or nuanced medical context. Radiologists' expertise in medical imaging and data analysis positions them exceptionally well to lead the responsible integration and utilization of ChatGPT within the field of radiology. This article offers a topical overview of the potential strengths and limitations of ChatGPT in radiological reporting.
引用
收藏
页码:1849 / 1863
页数:15
相关论文
共 56 条
[1]   Potential Use Cases for ChatGPT in Radiology Reporting [J].
Abou Elkassem, Asser ;
Smith, Andrew D. .
AMERICAN JOURNAL OF ROENTGENOLOGY, 2023, 221 (03) :373-376
[2]   Using Artificial Intelligence to Label Free-Text Operative and Ultrasound Reports for Grading Pediatric Appendicitis [J].
Abu-Ashour, Waseem ;
Emil, Sherif ;
Poenaru, Dan .
JOURNAL OF PEDIATRIC SURGERY, 2024, 59 (05) :783-790
[3]   Leveraging GPT-4 for Post Hoc Transformation of Free-text Radiology Reports into Structured Reporting: A Multilingual Feasibility Study [J].
Adams, Lisa C. ;
Truhn, Daniel ;
Busch, Felix ;
Kader, Avan ;
Niehues, Stefan M. ;
Makowski, Marcus R. ;
Bressem, Keno K. .
RADIOLOGY, 2023, 307 (04)
[4]  
Amin KS, 2023, RADIOLOGY, V309, DOI 10.1148/radiol.232561
[5]   Chatbots and Large Language Models in Radiology: A Practical Primer for Clinical and Research Applications [J].
Bhayana, Rajesh .
RADIOLOGY, 2024, 310 (01)
[6]   Use of GPT-4 With Single-Shot Learning to Identify Incidental Findings in Radiology Reports [J].
Bhayana, Rajesh ;
Elias, Gavin ;
Datta, Daksh ;
Bhambra, Nishaant ;
Deng, Yangqing ;
Krishna, Satheesh .
AMERICAN JOURNAL OF ROENTGENOLOGY, 2024, 222 (03)
[7]   Can ChatGPT write radiology reports? [J].
Biswas, Som ;
Khan, Salman ;
Awal, Sandeep Singh .
CHINESE JOURNAL OF ACADEMIC RADIOLOGY, 2024, 7 (01) :102-106
[8]   Ability of ChatGPT to generate competent radiology reports for distal radius fracture by use of RSNA template items and integrated AO classifier [J].
Bosbach, Wolfram A. ;
Senge, Jan F. ;
Nemeth, Bence ;
Omar, Siti H. ;
Mitrakovic, Milena ;
Beisbart, Claus ;
Horvath, Andras ;
Heverhagen, Johannes ;
Daneshvar, Keivan .
CURRENT PROBLEMS IN DIAGNOSTIC RADIOLOGY, 2024, 53 (01) :102-110
[9]   The Radiology Report as Seen by Radiologists and Referring Clinicians: Results of the COVER and ROVER Surveys [J].
Bosmans, Jan M. L. ;
Weyler, Joost J. ;
De Schepper, Arthur M. ;
Parizel, Paul M. .
RADIOLOGY, 2011, 259 (01) :184-195
[10]   Accuracy of Information Provided by ChatGPT Regarding Liver Cancer Surveillance and Diagnosis [J].
Cao, Jennie J. ;
Kwon, Daniel H. ;
Ghaziani, Tara T. ;
Kwo, Paul ;
Tse, Gary ;
Kesselman, Andrew ;
Kamaya, Aya ;
Tse, Justin R. .
AMERICAN JOURNAL OF ROENTGENOLOGY, 2023, 221 (04) :556-559