Instituto de Investigación Sanitaria de Castilla - La Mancha, Toledo, Spain.
University Hospital of Toledo, Servicio de Salud de Castilla - La Mancha, Toledo, Spain.
BMJ Open. 2024 Nov 2;14(11):e088431. doi: 10.1136/bmjopen-2024-088431.
Microwave imaging presents several potential advantages including its non-ionising and harmless nature. This open, multicentric, interventional, prospective, non-randomised trial aims to validate MammoWave's artificial intelligence (AI)-based classification algorithm, leveraging microwave imaging, to achieve a sensitivity exceeding 75% and a specificity exceeding 90% in breast screening.
10 000 volunteers undergoing regular mammographic breast cancer screening will be recruited across 9 European centres and invited to participate in the clinical study, involving MammoWave testing on both breasts. MammoWave results will be checked against the reference standard, to be intended as the output of conventional breast examination path (with histological confirmation of cancer cases) with 2 years follow-up. Anonymised clinical and MammoWave's results, including microwave images, associated features and a label provided by the AI-based classification algorithm, will be collected and stored in a dedicated electronic case report form. The prospective study will involve a comparative analysis between the output of the conventional breast examination path (control intervention) and the labels provided by MammoWave's AI system (experimental intervention). These labels will categorise breasts into two groups: breast With Suspicious Finding, indicating the presence of a suspicious lesion or No Suspicious Finding, indicating the absence of a lesion or the presence of a low-suspicion lesion. This trial aims to provide evidence regarding the novel MammoWave's AI system for detecting breast cancer in asymptomatic populations during screening.
This study was approved by the Research Ethics Committee of the Liguria Region (CET), Italy (CET-Liguria: 524/2023-DB id 13399), the Research Ethics Committee of Complejo Hospitalario de Toledo (CEIC), Spain (CEIC-1094), the National Ethics Committee for Clinical Research (CEIC), Portugal (CEIC-2311KC814), the Bioethical Committee of Pomeranian Medical University in Szczecin, Poland (KB-006/23/2024) and the Zurich Cantonal Ethics Commission, Switzerland (BASEC 2023-D0101). The findings of this study will be disseminated through academic and scientific conferences as well as peer-reviewed journals.
NCT06291896.
微波成像是一种具有潜在优势的技术,包括非电离性和无害性。本项开放性、多中心、介入性、前瞻性、非随机临床试验旨在验证 MammoWave 基于人工智能(AI)的分类算法,利用微波成像实现乳腺筛查的灵敏度超过 75%,特异性超过 90%。
将在 9 个欧洲中心招募 10000 名接受常规乳腺 X 线摄影乳腺癌筛查的志愿者,并邀请他们参与这项临床研究,对双侧乳房进行 MammoWave 检测。MammoWave 的结果将与参考标准进行对照,参考标准将作为常规乳腺检查路径的输出(伴有癌症病例的组织学确认),并进行 2 年随访。将收集和存储匿名化的临床和 MammoWave 结果,包括微波图像、相关特征以及基于人工智能分类算法提供的标签。这项前瞻性研究将比较常规乳腺检查路径(对照干预)和 MammoWave 的 AI 系统提供的标签(实验干预)的输出。这些标签将乳房分为两类:有可疑发现的乳房和无可疑发现的乳房,前者表示存在可疑病变,后者表示无病变或存在低可疑病变。本试验旨在为筛查无症状人群中乳腺癌的新型 MammoWave AI 系统提供证据。
本研究得到了意大利利古里亚地区研究伦理委员会(CET)(CET-Liguria:524/2023-DB id 13399)、西班牙托莱多综合医院研究伦理委员会(CEIC)、葡萄牙国家临床研究伦理委员会(CEIC)、波兰什切青波美拉尼亚医科大学伦理委员会(KB-006/23/2024)和瑞士苏黎世州伦理委员会(BASEC 2023-D0101)的批准。本研究的结果将通过学术和科学会议以及同行评议期刊进行传播。
NCT06291896。