Patient perspectives on the use of artificial intelligence in prostate cancer diagnosis on MRI

被引:0
|
作者
Fransen, Stefan J. [1 ]
Kwee, T. C. [1 ]
Rouw, D. [2 ]
Roest, C. [1 ]
van Lohuizen, Q. Y. [1 ]
Simonis, F. F. J. [3 ]
van Leeuwen, P. J. [4 ]
Heijmink, S. [4 ]
Ongena, Y. P. [5 ]
Haan, M. [5 ]
Yakar, D. [1 ,4 ]
机构
[1] Univ Med Ctr Groningen, Groningen, Netherlands
[2] Martini Hosp, Groningen, Netherlands
[3] Tech Univ Twente, Enschede, Netherlands
[4] Dutch Canc Inst, Amsterdam, Netherlands
[5] Univ Groningen, Groningen, Netherlands
关键词
Patient preference; Artificial intelligence; Questionnaire; Prostate cancer; Magnetic resonance imaging;
D O I
10.1007/s00330-024-11012-y
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
Objectives This study investigated patients' acceptance of artificial intelligence (AI) for diagnosing prostate cancer (PCa) on MRI scans and the factors influencing their trust in AI diagnoses. Materials and methods A prospective, multicenter study was conducted between January and November 2023. Patients undergoing prostate MRI were surveyed about their opinions on hypothetical AI assessment of their MRI scans. The questionnaire included nine items: four on hypothetical scenarios of combinations between AI and the radiologist, two on trust in the diagnosis, and three on accountability for misdiagnosis. Relationships between the items and independent variables were assessed using multivariate analysis. Results A total of 212 PCa suspicious patients undergoing prostate MRI were included. The majority preferred AI involvement in their PCa diagnosis alongside a radiologist, with 91% agreeing with AI as the primary reader and 79% as the secondary reader. If AI has a high certainty diagnosis, 15% of the respondents would accept it as the sole decision-maker. Autonomous AI outperforming radiologists would be accepted by 52%. Higher educated persons tended to accept AI when it would outperform radiologists (p < 0.05). The respondents indicated that the hospital (76%), radiologist (70%), and program developer (55%) should be held accountable for misdiagnosis. Conclusions Patients favor AI involvement alongside radiologists in PCa diagnosis. Trust in AI diagnosis depends on the patient's education level and the AI performance, with autonomous AI acceptance by a small majority on the condition that AI outperforms a radiologist. Respondents held the hospital, radiologist, and program developers accountable for misdiagnosis in descending order of accountability.
引用
收藏
页码:769 / 775
页数:7
相关论文
共 50 条
  • [1] The use of artificial intelligence for the diagnosis of bladder cancer: a review and perspectives
    Chan, Erica On-Ting
    Pradere, Benjamin
    Teoh, Jeremy Yuen-Chun
    [J]. CURRENT OPINION IN UROLOGY, 2021, 31 (04) : 397 - 403
  • [2] Patient Perspectives on the Use of Artificial Intelligence
    Kovarik, Carrie L.
    [J]. JAMA DERMATOLOGY, 2020, 156 (05) : 493 - 494
  • [3] Artificial Intelligence Algorithm-Based MRI for Differentiation Diagnosis of Prostate Cancer
    Luo, Rui
    Zeng, Qingxiang
    Chen, Huashan
    [J]. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2022, 2022
  • [4] AUTOMATED DIAGNOSIS OF PROSTATE CANCER LOCATION AND FORM BY ARTIFICIAL INTELLIGENCE IN MULTIPARAMETRIC MRI
    Oishi, Yuichiro
    Kitta, Takeya
    Shinohara, Nobuo
    Nosato, Hirokazu
    Sakanashi, Hidenori
    Murakawa, Masahiro
    [J]. JOURNAL OF UROLOGY, 2018, 199 (04): : E253 - E253
  • [5] Patient Perspectives and Understanding of MRI-directed Prostate Cancer Diagnosis
    Norris, Joseph M.
    Ball, Rhys
    Freeman, Alex
    Ghei, Maneesh
    Kirkham, Alex
    Oldroyd, Robert
    Whitaker, Hayley C.
    Emberton, Mark
    [J]. UROLOGY, 2021, 153 : 6 - 7
  • [6] The application of artificial intelligence in the diagnosis of prostate cancer
    Dovbysh, A.
    Savchenko, T.
    Moskalenko, R.
    Romaniuk, A.
    [J]. VIRCHOWS ARCHIV, 2022, 481 (SUPPL 1) : S302 - S303
  • [7] Artificial intelligence development for detecting prostate cancer in MRI
    Chalida Aphinives
    Potchavit Aphinives
    [J]. Egyptian Journal of Radiology and Nuclear Medicine, 52
  • [8] Artificial intelligence development for detecting prostate cancer in MRI
    Aphinives, Chalida
    Aphinives, Potchavit
    [J]. EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE, 2021, 52 (01):
  • [9] Patient Perspectives on the Use of Artificial Intelligence for Skin Cancer Screening A Qualitative Study
    Nelson, Caroline A.
    Perez-Chada, Lourdes Maria
    Creadore, Andrew
    Li, Sara Jiayang
    Lo, Kelly
    Manjaly, Priya
    Pournamdari, Ashley Bahareh
    Tkachenko, Elizabeth
    Barbieri, John S.
    Ko, Justin M.
    Menon, Alka V.
    Hartman, Rebecca Ivy
    Mostaghimi, Arash
    [J]. JAMA DERMATOLOGY, 2020, 156 (05) : 501 - 512
  • [10] Application of artificial intelligence in diagnosis and therapy of prostate cancer
    Rovcanin, A.
    Skopljak, S.
    Suleiman, S.
    Smajovic, A.
    Becic, E.
    Becic, F.
    Becirovic, L. Spahic
    Pokvic, L. Gurbeta
    Badnjevic, A.
    [J]. IFAC PAPERSONLINE, 2022, 55 (04): : 74 - 79