本研究调查了患者对人工智能 (AI) 通过 MRI 扫描诊断前列腺癌 (PCa) 的接受程度以及影响他们对 AI 诊断信任度的因素。一项前瞻性多中心研究于 2023 年 1 月至 11 月期间进行。接受前列腺 MRI 的患者调查了他们对 MRI 扫描的假设人工智能评估的看法。调查问卷包括九个项目：四个关于人工智能和放射科医生之间组合的假设场景，两个关于对诊断的信任，三个关于误诊的责任。采用多变量分析评估项目与自变量之间的关系。共纳入212名接受前列腺MRI检查的PCa可疑患者。大多数人更喜欢人工智能与放射科医生一起参与前列腺癌诊断，91% 的人同意人工智能作为主要读者，79% 的人同意人工智能作为次要读者。如果人工智能有很高的确定性诊断，15%的受访者会接受它作为唯一的决策者。超过放射科医生的自主人工智能将被 52% 的人接受。当人工智能的表现优于放射科医生时，受过高等教育的人倾向于接受人工智能（p<<0.05）。受访者表示，医院（76%）、放射科医生（70%）和程序开发人员（55%）应对误诊负责。患者更喜欢人工智能与放射科医生一起参与PCa诊断。对人工智能诊断的信任取决于患者的教育水平和人工智能的表现，少数人对自主人工智能的接受程度是人工智能优于放射科医生的条件。受访者要求医院、放射科医生和程序开发人员按责任降序排列对误诊负责。患者对人工智能辅助 MRI 前列腺癌诊断表现出很高的接受度，无论是与放射科医生一起诊断还是完全自主诊断，特别是如果它表现出优于其他诊断的性能仅放射科医生。前列腺癌可疑患者可能会根据表现接受自主人工智能。患者更喜欢人工智能与放射科医生一起参与诊断前列腺癌。患者表示人工智能的责任应由多个利益相关者共同承担。© 2024。作者。

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.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.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.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.Patients show a high level of acceptance for AI-assisted prostate cancer diagnosis on MRI, either alongside radiologists or fully autonomous, particularly if it demonstrates superior performance to radiologists alone.Prostate cancer suspicious patients may accept autonomous AI based on performance. Patients prefer AI involvement alongside a radiologist in diagnosing prostate cancer. Patients indicate accountability for AI should be shared among multiple stakeholders.© 2024. The Author(s).