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探索女性对传统乳房X光检查的看法以及人工智能驱动的热成像技术在改善乳腺癌筛查过程中的概念:混合方法研究。

Exploring Women's Perceptions of Traditional Mammography and the Concept of AI-Driven Thermography to Improve the Breast Cancer Screening Journey: Mixed Methods Study.

作者信息

Sirka Kacafírková Kristýna, Poll Anneleen, Jacobs An, Cardone Antonella, Ventura Juan-Jose

机构信息

imec-SMIT, Vrije Universiteit Brussel, Pleinlaan 9, Brussels, 1050, Belgium, 32 026148540.

Cancer Patients Europe, Rue de l'Industrie 24, Brussels, 1000, Belgium.

出版信息

JMIR Cancer. 2025 Sep 10;11:e64954. doi: 10.2196/64954.

DOI:10.2196/64954
PMID:40929578
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12422528/
Abstract

BACKGROUND

Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, radiation exposure, and accessibility issues. Thermography, particularly when driven by artificial intelligence (AI), is being explored as a noninvasive, radiation-free alternative. However, its acceptance, reliability, and impact on the screening experience remain underexplored.

OBJECTIVE

This study aimed to explore women's perceptions of AI-enhanced thermography (ThermoBreast) as an alternative to mammography. It aims to identify barriers and motivators related to breast cancer screening and assess how ThermoBreast might improve the screening experience.

METHODS

A mixed methods approach was adopted, combining an online survey with follow-up focus groups. The survey captured women's knowledge, attitudes, and experiences related to breast cancer screening and was used to recruit participants for qualitative exploration. After the focus groups, the survey was relaunched to include additional respondents. Quantitative data were analyzed using SPSS (IBM Corp), and qualitative data were analyzed in MAXQDA (VERBI software). Findings from both strands were synthesized to redesign the breast cancer screening journey.

RESULTS

A total of 228 valid survey responses were analyzed. Of 228, 154 women (68%) had previously undergone mammography, while 74 (32%) had not. The most reported motivators were belief in prevention (69/154, 45%), invitations from screening programs (68/154, 44%), and doctor recommendations (45/154, 29%). Among nonscreeners, key barriers included no recommendation from a doctor (39/74, 53%), absence of symptoms (27/74, 36%), and perceived age ineligibility (17/74, 23%). Pain, long appointment waits, and fear of radiation were also mentioned. In total, 18 women (mean age 45.3 years, SD 13.6) participated in 6 focus groups. Participants emphasized the importance of respectful and empathetic interactions with medical staff, clear communication, and emotional comfort-factors they perceived as more influential than the screening technology itself. ThermoBreast was positively received for being contactless, radiation-free, and potentially more comfortable. Participants described it as "less traumatic," "easier," and "a game changer." However, concerns were raised regarding its novelty, lack of clinical validation, and data privacy. Some participants expressed the need for human oversight in AI-supported procedures and requested more information on how AI is used. Based on these insights, an updated screening journey was developed, highlighting improvements in preparation, appointment booking, privacy, and communication of results.

CONCLUSIONS

While AI-driven thermography shows promise as a noninvasive, user-friendly alternative to mammography, its adoption depends on trust, clinical validation, and effective communication from health care professionals. It may expand screening access for populations underserved by mammography, such as younger and immobile women, but does not eliminate all participation barriers. Long-term studies and direct comparisons between mammography and thermography are needed to assess diagnostic accuracy, patient experience, and their impact on screening participation and outcomes.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe23/12422528/d7af68c9c163/cancer-v11-e64954-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe23/12422528/e173ce7b4845/cancer-v11-e64954-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe23/12422528/4e6c3b7550a5/cancer-v11-e64954-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe23/12422528/5eb95a5c477b/cancer-v11-e64954-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe23/12422528/d7af68c9c163/cancer-v11-e64954-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe23/12422528/e173ce7b4845/cancer-v11-e64954-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe23/12422528/4e6c3b7550a5/cancer-v11-e64954-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe23/12422528/5eb95a5c477b/cancer-v11-e64954-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe23/12422528/d7af68c9c163/cancer-v11-e64954-g004.jpg
摘要

背景

乳腺癌是女性中最常见的癌症,也是欧洲主要的死亡原因之一。通过筛查进行早期检测可降低死亡率,但由于不适、辐射暴露和可及性问题,基于乳腺X线摄影的筛查项目参与率仍不理想。热成像,特别是在人工智能(AI)驱动下,正被探索作为一种无创、无辐射的替代方法。然而,其接受度、可靠性以及对筛查体验的影响仍未得到充分研究。

目的

本研究旨在探索女性对人工智能增强热成像(ThermoBreast)作为乳腺X线摄影替代方法的看法。旨在识别与乳腺癌筛查相关的障碍和动机,并评估ThermoBreast如何改善筛查体验。

方法

采用混合方法,将在线调查与后续焦点小组相结合。该调查收集了女性与乳腺癌筛查相关的知识、态度和经历,并用于招募参与者进行定性探索。焦点小组讨论后,重新开展调查以纳入更多受访者。定量数据使用SPSS(IBM公司)进行分析,定性数据在MAXQDA(VERBI软件)中进行分析。将两方面的结果综合起来重新设计乳腺癌筛查流程。

结果

共分析了228份有效的调查回复。在这228名女性中,154名(68%)之前接受过乳腺X线摄影,而74名(32%)没有。最常提及的动机是对预防的信念(69/154,45%)、筛查项目的邀请(68/154,44%)以及医生的建议(45/154,29%)。在未进行筛查的人群中,主要障碍包括没有医生的建议(39/74,53%)、没有症状(27/74,36%)以及认为年龄不符合条件(17/74,23%)。还提到了疼痛、预约等待时间长以及对辐射的恐惧。共有18名女性(平均年龄45.3岁,标准差13.6)参加了6个焦点小组。参与者强调了与医护人员进行尊重和共情互动、清晰沟通以及情感舒适的重要性,她们认为这些因素比筛查技术本身更具影响力。ThermoBreast因其非接触、无辐射且可能更舒适而受到好评。参与者将其描述为“创伤性较小”“更轻松”和 “改变游戏规则者”。然而,人们对其新颖性、缺乏临床验证以及数据隐私提出了担忧。一些参与者表示在人工智能支持的程序中需要人工监督,并要求提供更多关于人工智能如何使用的信息。基于这些见解,制定了更新后的筛查流程,突出了在准备、预约、隐私以及结果沟通方面的改进。

结论

虽然人工智能驱动的热成像作为乳腺X线摄影的无创、用户友好替代方法显示出前景,但其采用取决于信任、临床验证以及医护人员的有效沟通。它可能会扩大乳腺X线摄影服务不足人群(如年轻女性和行动不便的女性)的筛查机会,但并不能消除所有参与障碍。需要进行长期研究以及乳腺X线摄影和热成像之间的直接比较,以评估诊断准确性、患者体验及其对筛查参与率和结果的影响。

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