Radiologists' perceptions on AI integration: An in-depth survey study

被引:7
|
作者
Ce, Maurizio [1 ]
Ibba, Simona [2 ]
Cellina, Michaela [3 ]
Tancredi, Chiara [4 ]
Fantesini, Arianna [5 ]
Fazzini, Deborah [2 ]
Fortunati, Alice [1 ]
Perazzo, Chiara [1 ]
Presta, Roberta [4 ]
Montanari, Roberto [4 ,5 ]
Forzenigo, Laura [6 ]
Carrafiello, Gianpaolo [1 ,6 ,7 ]
Papa, Sergio [2 ]
All, Marco [2 ,8 ]
机构
[1] Univ Milan, Postgrad Sch Radiodiagnost, Via Festa Perdono 7, I-20122 Milan, Italy
[2] CDI Ctr Diagnost Italiano SpA, Unit Diagnost Imaging & Stereotact Radiosurg, Via Simone St Bon 20, I-20147 Milan, Italy
[3] ASST Fatebenefratelli Sacco, Radiol Dept, Piazza Principessa Clotilde 3, I-20121 Milan, Italy
[4] Univ Suor Orsola Benincasa, Corso Vittorio Emanuele 292, I-80135 Naples, Italy
[5] RE LAB srl, Via Tamburini 5, I-42122 Reggio Emilia, Italy
[6] Fdn IRCCS Ca Granda Osped Maggiore Policlin, Radiol Dept, Via Francesco Sforza 35, I-20122 Milan, Italy
[7] Univ Milan, Dept Biomed Sci Hlth, Via Mangiagalli 31, I-20133 Milan, Italy
[8] Bracco Imaging SpA, Via Caduti Marcinelle, I-20134 Milan, Italy
关键词
Artificial Intelligence; AI; Radiologists perceptions; CAD; Automatic detection; ARTIFICIAL-INTELLIGENCE;
D O I
10.1016/j.ejrad.2024.111590
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
Purpose: To assess the perceptions and attitudes of radiologists toward the adoption of artificial intelligence (AI) in clinical practice. Methods: A survey was conducted among members of the SIRM Lombardy. Radiologists' attitudes were assessed comprehensively, covering satisfaction with AI-based tools, propensity for innovation, and optimism for the future. The questionnaire consisted of two sections: the first gathered demographic and professional information using categorical responses, while the second evaluated radiologists' attitudes toward AI through Likert-type responses ranging from 1 to 5 (with 1 representing extremely negative attitudes, 3 indicating a neutral stance, and 5 reflecting extremely positive attitudes). Questionnaire refinement involved an iterative process with expert panels and a pilot phase to enhance consistency and eliminate redundancy. Exploratory data analysis employed descriptive statistics and visual assessment of Likert plots, supported by non-parametric tests for subgroup comparisons for a thorough analysis of specific emerging patterns. Results: The survey yielded 232 valid responses. The findings reveal a generally optimistic outlook on AI adoption, especially among young radiologist (<30) and seasoned professionals (>60, p<0.01). However, while 36.2 % (84 out 232) of subjects reported daily use of AI-based tools, only a third considered their contribution decisive (30 %, 25 out of 84). AI literacy varied, with a notable proportion feeling inadequately informed (36 %, 84 out of 232), particularly among younger radiologists (46 %, p < 0.01). Positive attitudes towards the potential of AI to improve detection, characterization of anomalies and reduce workload (positive answers > 80 %) and were consistent across subgroups. Radiologists' opinions were more skeptical about the role of AI in enhancing decision-making processes, including the choice of further investigation, and in personalized medicine in general. Overall, respondents recognized AI's significant impact on the radiology profession, viewing it as an opportunity (61 %, 141 out of 232) rather than a threat (18 %, 42 out of 232), with a majority expressing belief in AI's relevance to future radiologists' career choices (60 %, 139 out of 232). However, there were some concerns, particularly among breast radiologists (20 of 232 responders), regarding the potential impact of AI on the profession. Eighty-four percent of the respondents consider the final assessment by the radiologist still to be essential. Conclusion: Our results indicate an overall positive attitude towards the adoption of AI in radiology, though this is moderated by concerns regarding training and practical efficacy. Addressing AI literacy gaps, especially among younger radiologists, is essential. Furthermore, proactively adapting to technological advancements is crucial to fully leverage AI's potential benefits. Despite the generally positive outlook among radiologists, there remains significant work to be done to enhance the integration and widespread use of AI tools in clinical practice.
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页数:13
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