Table 1

- Exposure assessment to AI in radiology corresponding to gender, training level and familiar with big data.

Questions/categoryn (%)P-value
  GenderTraining levelBig data
Which radiological subspecialties do you foresee will be more influenced by AI in the next 5-10 years? (choose up to 3)
 Breast99 (64.3)   
 Molecular/nuclear imaging56 (36.4)   
 Neuroradiology54 (35.1)   
 Thoracic54 (35.1)   
 Emergency32 (20.8)   
 Musculoskeletal24 (15.6)   
 Cardiovascular22 (14.3)   
 General22 (14.3)   
 Gastrointestinal/abdominal20 (13)   
 Interventional17 (11)   
 Oncologic imaging16 (10.4)   
 Head and neck11 (7.1)   
 Urogenital3 (1.9)   
 Pediatric2 (1.3)   
Which techniques do you foresee will be the most important fields of AI applications in the next 5-10 years? (choose up to 3)
 Mammography91 (59.1)   
 PET/nuclear72 (46.8)   
 CT69 (44.8)   
 Radiography61 (39.6)   
 MRI46 (29.9)   
 DXA37 (24)   
 Angiography/fluoroscopy18 (11.7)   
 Hybrid imaging9 (5.8)   
 Ultrasound8 (5.2)   
 Experimental imaging (animal models)6 (3.9)   
 Optical imaging4 (2.6)   
Which of the following AI applications do you think are more relevant as aids to the radiological profession? (choose up to 3)
 Detection in asymptomatic subjects (screening)82 (53.2)   
 Detection of incidental findings74 (48.1)   
 Image post-processing73 (47.4)   
 Imaging protocol optimization54 (35.1)   
 Support to structured reporting44 (28.6)   
 Lesion characterization/diagnosis in symptomatic subjects43 (27.9)   
 Staging/restaging in oncology43 (27.9)   
 Quantitative measure of imaging biomarkers31 (20.1)   
 Prognosis12 (7.8)   
Do you foresee an impact of AI on the professional life of radiologists in terms of the number of job positions in the next 5-10 years?
 No67 (43.5)   
 Yes, job positions will be reduced64 (41.6)0.7420.919‡0.869
 Yes, job positions will increase23 (14.9)   
Do you foresee an impact of AI on the professional life of radiologist in terms of total reporting workload in the next 5-10 years?
 No29 (18.8)   
 Yes, it will increase43 (27.9)0.440.1920.905
 Yes, it will be reduced82 (53.2)   
In the next 5-10 years, the use of AI-based applications will make radiologists’ duties
 More technical28 (18.2)   
 More clinical38 (24.7)   
 Unchanged9 (5.8)0.566‡0.269‡0.244‡
 More technical and clinical79 (51.3)
Do you think that in the next 5-10 years, the use of AI-based applications will help to reduce the need for subspecializing?
 No, radiologists will be more focused on radiology subspecialties102 (66.2)   
 Yes, radiologists will be less focused on radiology subspecialties16 (10.4)0.6850.0330.065
 The rate of dedication to subspecialties will remain unchanged36 (23.4)   
In the next 5-10 years, who will take the legal responsibility of AI-system output?
 Radiologists105 (68.2)   
 Other physicians (namely, clinicians asking for the imaging study)9 (5.8)   
 Developers of AI applications79 (51.3)
 Insurance companies35 (22.7)
In the next 5-10 years, will patients accept a report from AI applications without supervision and approval by a physician?
 Yes17 (11)   
 No79 (51.3)0.3810.489‡0.847
 Difficult to estimate at present58 (37.7)   
What will be the role of radiologists in the development/validation of AI applications to medical imaging? (choose at most 3)
 Supervise all stages needed to develop an AI based application97 (63)0.3200.1690.687
 Help in task definition67 (43.5)0.2550.6630.381
 Develop AI-based applications59 (38.3)0.1750.0700.742
 Provide labelled images49 (31.8)0.1140.2680.762
 None7 (4.5)1.00‡0.452‡1.00‡

  • PET: positron emitted tomography, CT: computed tomography, MRI: magnetic resonance imaging, DXA: dual-energy x-ray absorptiometry, AI: artificial intelligence, ‡Fisher’s exact test