protocolSection identificationModule nctId: NCT06266026, orgStudyIdInfo id: ThermoBreast, briefTitle: ThermoBreast - Non-contact Breast Cancer Imaging Using AI-enhanced Thermography., acronym: ThermoBreast, statusModule overallStatus: RECRUITING, startDateStruct date: 2023-12-11, primaryCompletionDateStruct date: 2028-12, completionDateStruct date: 2029-12, studyFirstPostDateStruct date: 2024-02-20, lastUpdatePostDateStruct date: 2024-02-20, sponsorCollaboratorsModule leadSponsor name: ThermoMind Ltd., class: INDUSTRY, collaborators name: Assuta Medical Centers Ltd., collaborators name: Hospital of Lithuanian University of Health Sciences Kaunas Clinics, collaborators name: Institut Gustav Roussy, collaborators name: M.D. Anderson Cancer Center, collaborators name: Sheba Medical Center, collaborators name: The Holy Family Hospital Nazareth, collaborators name: University College Cork, collaborators name: Univerzitetni klinicni center Maribor, collaborators name: Academisch Ziekenhuis Groningen, collaborators name: Technical University of Munich, collaborators name: Technion, Israel Institute of Technology, collaborators name: Vrije Universiteit Brussel, collaborators name: Cancer Patients Europe, collaborators name: University Hospital Heidelberg, descriptionModule briefSummary: Breast cancer is one of the most worrisome health concerns facing women. Early detection and active patient monitoring are crucial to survival. The chances of a cure are high when detected and treated in the early stages. Standard breast cancer diagnostic methods such as mammography, ultrasound, and MRI have limitations such as ionizing radiation, high false-positive rates, and/or high expenses.Medical Thermography might overcome these limitations: It is a non-invasive, adjunctive physiologic imaging technology that uses a high-resolution infrared camera and computer processing to produce an image (thermogram) of a patient's skin surface temperatures. It is a non-contact screening method, which does not involve radiation exposure or invasive procedures, and is safe for both the patient and the trained personnel performing the screening. While mammography and ultrasound depend primarily on structural and anatomical variation of the tumor from the surrounding breast tissue, thermography detects pathophysiological changes within the breast such as metabolic and vascular changes caused by cancer. The heat transfer in the body is conducted by the circulatory system; hence, pathologies identified by thermography are generally associated with changes in blood perfusion.To date, there has been no completed or ongoing large-scale, prospective, multicenter, international study that evaluates the diagnostic performance of thermal video streams coupled with advanced Artificial Intelligence algorithms for early-stage breast cancer screening and diagnosis. The proposed study will be crucial for the development of a new imaging modality that aims to be both cost-effective and to carry a minimal level of risk, facilitating screening of women of all age groups and breast densities, enabling early detection of abnormalities caused by malignant processes and improving patient monitoring., conditionsModule conditions: Breast Cancer, designModule studyType: INTERVENTIONAL, phases: NA, designInfo allocation: NA, interventionModel: SINGLE_GROUP, primaryPurpose: DIAGNOSTIC, maskingInfo masking: DOUBLE, whoMasked: PARTICIPANT, whoMasked: CARE_PROVIDER, enrollmentInfo count: 28000, type: ESTIMATED, armsInterventionsModule interventions name: ThermoBreast - AI-based evaluation of dynamic breast thermography imaging, outcomesModule primaryOutcomes measure: Sensitivity (true-positive rate), primaryOutcomes measure: Specificity (true-negative rate), secondaryOutcomes measure: Cancer detection rate, secondaryOutcomes measure: Detection rate of ductal carcinoma in situ (DCIS), secondaryOutcomes measure: Detection rate of tumor category pT1, secondaryOutcomes measure: Recall rate, secondaryOutcomes measure: Sensitivity, secondaryOutcomes measure: Specificity, secondaryOutcomes measure: Positive-predictive value, secondaryOutcomes measure: Negative-predictive value, secondaryOutcomes measure: Diagnostic performance in the three trial cohorts, secondaryOutcomes measure: Proportion of breast quadrant localization, secondaryOutcomes measure: Proportion of correct histopathologic subtype identification, secondaryOutcomes measure: Proportion of correct tumorbiologic subtype identification, secondaryOutcomes measure: Proportion of correct axillary lymph node involvement identification, secondaryOutcomes measure: Effect of hormonal status on diagnostic performance, secondaryOutcomes measure: Effect of breast density on diagnostic performance, secondaryOutcomes measure: Effect of ethnicity on diagnostic performance, secondaryOutcomes measure: Timing of ThermoBreast, secondaryOutcomes measure: Screening time, secondaryOutcomes measure: Cost-effectiveness, secondaryOutcomes measure: Lived Experience, eligibilityModule sex: FEMALE, minimumAge: 18 Years, stdAges: ADULT, stdAges: OLDER_ADULT, contactsLocationsModule locations facility: Heidelberg University Hospital, status: RECRUITING, city: Heidelberg, country: Germany, contacts name: André Pfob, MD, role: CONTACT, geoPoint lat: 49.40768, lon: 8.69079, hasResults: False