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
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 imagi...
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| Published in: | BMJ open Vol. 14; no. 11; p. e088431 |
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| Main Authors: | , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
BMA House, Tavistock Square, London, WC1H 9JR
BMJ Publishing Group
01-11-2024
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| Online Access: | Get full text |
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| Summary: | 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.INTRODUCTIONMicrowave 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.METHODS AND ANALYSIS10 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.ETHICS AND DISSEMINATIONThis 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.TRIAL REGISTRATION NUMBERNCT06291896. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Undefined-3 NG, GT, BK and Alessandra Bigotti are employed by UBT—Umbria Bioengineering Technologies Srl. NG and GT are shareholders of UBT—Umbria Bioengineering Technologies. UBT—Umbria Bioengineering Technologies Srl manufactured the microwave imaging device known as MammoWave. This does not alter our adherence to BMJ Open policies. Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise. |
| ISSN: | 2044-6055 2044-6055 |
| DOI: | 10.1136/bmjopen-2024-088431 |