患者和皮肤科医生对用于黑色素瘤筛查的人工智能的看法：一项前瞻性研究。

Patient and dermatologists' perspectives on augmented intelligence for melanoma screening: A prospective study.

机构信息

Department of Dermatology, University Hospital Basel, Basel, Switzerland.

Faculty of Medicine, University of Basel, Basel, Switzerland.

出版信息

J Eur Acad Dermatol Venereol. 2024 Dec;38(12):2240-2249. doi: 10.1111/jdv.19905. Epub 2024 Feb 27.

DOI:10.1111/jdv.19905

PMID:38411348

Abstract

BACKGROUND

Artificial intelligence (AI) shows promising potential to enhance human decision-making as synergistic augmented intelligence (AuI), but requires critical evaluation for skin cancer screening in a real-world setting.

OBJECTIVES

To investigate the perspectives of patients and dermatologists after skin cancer screening by human, artificial and augmented intelligence.

METHODS

A prospective comparative cohort study conducted at the University Hospital Basel included 205 patients (at high-risk of developing melanoma, with resected or advanced disease) and 8 dermatologists. Patients underwent skin cancer screening by a dermatologist with subsequent 2D and 3D total-body photography (TBP). Any suspicious and all melanocytic skin lesions ≥3 mm were imaged with digital dermoscopes and classified by corresponding convolutional neural networks (CNNs). Excisions were performed based on dermatologist's melanoma suspicion, study-defined elevated CNN risk-scores and/or melanoma suspicion by AuI. Subsequently, all patients and dermatologists were surveyed about their experience using questionnaires, including quantification of patient's safety sense following different examinations (subjective safety score (SSS): 0-10).

RESULTS

Most patients believed AI could improve diagnostic performance (95.5%, n = 192/201). In total, 83.4% preferred AuI-based skin cancer screening compared to examination by AI or dermatologist alone (3D-TBP: 61.3%; 2D-TBP: 22.1%, n = 199). Regarding SSS, AuI induced a significantly higher feeling of safety than AI (mean-SSS (mSSS): 9.5 vs. 7.7, p < 0.0001) or dermatologist screening alone (mSSS: 9.5 vs. 9.1, p = 0.001). Most dermatologists expressed high trust in AI examination results (3D-TBP: 90.2%; 2D-TBP: 96.1%, n = 205). In 68.3% of the examinations, dermatologists felt that diagnostic accuracy improved through additional AI-assessment (n = 140/205). Especially beginners (<2 years' dermoscopic experience; 61.8%, n = 94/152) felt AI facilitated their clinical work compared to experts (>5 years' dermoscopic experience; 20.9%, n = 9/43). Contrarily, in divergent risk assessments, only 1.5% of dermatologists trusted a benign CNN-classification more than personal malignancy suspicion (n = 3/205).

CONCLUSIONS

While patients already prefer AuI with 3D-TBP for melanoma recognition, dermatologists continue to rely largely on their own decision-making despite high confidence in AI-results.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT04605822).

摘要

背景

人工智能（AI）作为协同增强智能（AuI），在提高人类决策能力方面具有广阔的应用前景，但在实际环境中进行皮肤癌筛查时，仍需要进行严格的评估。

目的

探讨患者和皮肤科医生在接受人类、人工智能和增强人工智能（AuI）皮肤癌筛查后的观点。

方法

在巴塞尔大学医院进行了一项前瞻性比较队列研究，纳入了 205 名（有黑色素瘤高风险、有切除或晚期疾病的患者）和 8 名皮肤科医生。患者接受皮肤科医生进行皮肤癌筛查，随后进行二维和三维全身摄影（TBP）。对任何可疑和所有≥3mm 的黑素细胞性皮肤病变进行数字皮肤镜检查，并由相应的卷积神经网络（CNN）进行分类。根据皮肤科医生的黑色素瘤可疑性、研究定义的升高的 CNN 风险评分和/或 AuI 的黑色素瘤可疑性进行切除。随后，所有患者和皮肤科医生均通过问卷调查评估他们的体验，包括对不同检查后的患者安全意识进行量化（主观安全评分（SSS）：0-10）。

结果

大多数患者认为 AI 可以提高诊断性能（95.5%，n=192/201）。总共，83.4%的患者更喜欢基于 AuI 的皮肤癌筛查，而不是单独的 AI 或皮肤科医生筛查（3D-TBP：61.3%；2D-TBP：22.1%，n=199）。在 SSS 方面，AuI 引起的安全感明显高于 AI（平均 SSS（mSSS）：9.5 与 7.7，p<0.0001）或皮肤科医生单独筛查（mSSS：9.5 与 9.1，p=0.001）。大多数皮肤科医生对 AI 检查结果表示高度信任（3D-TBP：90.2%；2D-TBP：96.1%，n=205）。在 68.3%的检查中，皮肤科医生认为通过额外的 AI 评估提高了诊断准确性（n=140/205）。尤其是初学者（<2 年的皮肤镜检查经验；61.8%，n=94/152）与专家（>5 年的皮肤镜检查经验；20.9%，n=9/43）相比，感觉 AI 有助于他们的临床工作。相反，在分歧的风险评估中，只有 1.5%的皮肤科医生比个人恶性肿瘤怀疑更信任 CNN 良性分类（n=3/205）。