TY - JOUR
T1 - Microwave imaging for breast cancer screening: protocol for an open, multicentric, interventional, prospective, non-randomised clinical investigation to evaluate cancer detection capabilities of MammoWave system on an asymptomatic population across multiple European countries
AU - Álvarez Sánchez-Bayuela, Daniel
AU - Fernández Martín, Juan
AU - Tiberi, Gianluigi
AU - Ghavami, Navid
AU - Giovanetti González, Rubén
AU - Cruz Hernánez, Lina Marcela
AU - Aguilar Angulo, Paul Martín
AU - Martínez Gómez, Aarón Darío
AU - Rodríguez Sánchez, Ana
AU - Bigotti, Alessandra
AU - Khalesi, Banafsheh
AU - Pontoriero, Letizia
AU - Calabrese, Massimo
AU - Tagliafico, Alberto Stefano
AU - Romero Castellano, Cristina
PY - 2024/11/1
Y1 - 2024/11/1
N2 - Introduction: 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. Methods and analysis: 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. Ethics and dissemination: 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. Trial registration number: NCT06291896.
AB - Introduction: 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. Methods and analysis: 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. Ethics and dissemination: 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. Trial registration number: NCT06291896.
KW - Algorithms
KW - Artificial Intelligence
KW - Artificial intelligence
KW - Breast Imaging
KW - Breast Neoplasms
KW - Early Detection of Cancer
KW - Europe
KW - Female
KW - Humans
KW - Mammography
KW - Mass Screening
KW - Microwave Imaging
KW - Microwaves
KW - Multicenter Studies as Topic
KW - Prospective Studies
KW - Sensitivity and Specificity
UR - https://bmjopen.bmj.com/content/14/11/e088431
U2 - 10.1136/bmjopen-2024-088431
DO - 10.1136/bmjopen-2024-088431
M3 - Article
SN - 2044-6055
VL - 14
SP - e088431
JO - BMJ Open
JF - BMJ Open
IS - 11
M1 - e088431
ER -