micrima maria data collection for machine learning study

Conditions: Breast Cancer

Summary: the maria® breast imaging system is a ce-marked radiofrequency (rf) medical imaging device. the system employs an electromagnetic imaging technique that exploits the dielectric contrast between normal and cancerous tissues. the use of artificial intelligence will provide additional, novel functionality to the maria® system but requires participant data in order to develop and validate the machine learning algorithms that aim to increase the accuracy and overall clinical utility of the device. this study aims to collect data from sites for this purpose.

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.

Eligibility criteria:
inclusion criteria to be eligible to participate in this study, a subject must meet all the following criteria: * attending a symptomatic clinic or other appointment at a participating site * female sex * 18 years or older * able to provide informed consent * not in any identified, vulnerable group exclusion criteria a potential subject who meets any of the following criteria will be excluded from participation in this study: * unable to mount maria® participant bed * unable to lie in the prone position for a period of up to 5 minutes * participants who have undergone biopsy less than 5 days before the maria® scan * participants with implanted electronics * participants with breast implants * participants with nipple piercings (unless they are removed prior to the maria® scan) * breast sizes too small or too large to be suitable

Keywords: breast imaging