Micrima MARIA Data Collection for Machine Learning Study

Previous and existing trials have been focused on and designed to assess sensitivity of different versions of MARIA® when used on symptomatic subjects. This study will consider those measures, but the primary endpoint will be the collection of the data required for developing and validating machine learning-based enhancements of the MARIA® system. Data that are diverse in terms of subject characteristics, including disease state, presentation of disease, and variation of normal anatomy are requisite for the creation of accurate and well-characterized machine intelligence. As such, the recruitment criteria is broad in order to encompass all kinds of subjects that are representative as possible of the general population. At the current stage in development of the MARIA® system a need has been identified to acquire additional data for validation of a lesion classification algorithm specific to women with larger breasts. This need has guided the study size calculation; however, additional data from all shell sizes continues to be important for further lesion classifier development and the development of additional functionality, including automated breast density assessment. Therefore, as part of this study subjects across the entire intended use population will be recruited. The data points that are collected via this study have been selected as those that are required for the purposes of machine learning first and foremost, with any secondary endpoints utilising only existing available information. In addition to this data, a questionnaire will be provided to each participant to obtain valuable feedback on the scan experience. All subjects will undertake the same scan procedure, requiring them to have both breasts scanned using the MARIA® system. The MARIA® scan will be in addition to any standard diagnostic procedures, including imaging, that comprise the standard of care and will have no effect on the participant's diagnosis or treatment. While there is no direct benefit nor detrimental effect from this study to the participants, the study has potentially significant implications for future learning and for the breast imaging landscape.