ThermoBreast - Non-contact Breast Cancer Imaging Using AI-enhanced Thermography. An International, Multicenter, Prospective Development and Validation Trial.
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 28,000
- 试验地点
- 1
- 主要终点
- Sensitivity (true-positive rate)
研究概览
简要总结
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.
详细描述
This study is designed as a multicenter, prospective, blinded, three cohorts, diagnostic trial. Patients will be recruited at 11 centers in France, Germany, Ireland, Israel, Slovenia, Lithuania, and the US.
The primary objective is to compare the diagnostic performance of advanced image processing AI models to automatically predict breast malignancy based on thermograms and individual patient data collected during breast examination (ThermoBreast) with routine breast cancer screening and imaging.
The study population consists of women undergoing routine screening for breast cancer or diagnostic evaluation of suspicious breast masses. The study will recruit women into three cohorts: Screening cohort, High-Risk Screening, and Diagnostics cohort. Participants recruited for the study will be assigned to a dedicated cohort based on the reason of the visit.
There will be two visits for study participants, partially including study specific and routine procedures, who meet the inclusion criteria in the screening procedure.
The first trial visit (V1.1) will take place to provide the patient with detailed information on the study, its aims, the ThermoBreast procedure, and its risks. In- and exclusion criteria will be checked. Informed consent will be obtained. If the patient consents, the study specific ThermoBreast procedure (index test) and a study specific questionnaire regarding user experience will be performed. Moreover, the patient will undergo the routine first breast cancer screening round (screening cohort) or the routine first breast cancer diagnostics round (diagnostic cohort) according to national guidelines which serve as a reference test. In the screening cohort, the patient may undergo routine breast diagnostics following an irregular first screening round (V1.2) according to national guidelines.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Diagnostic
- 盲法
- Double (Participant, Care Provider)
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- Female
- 接受健康志愿者
- 是
入选标准
- 未提供
排除标准
- 未提供
结局指标
主要结局
Sensitivity (true-positive rate)
时间窗: up to 2 years of follow-up
As our primary outcome we will use true-positive ThermoBreast results, i.e. detected invasive breast cancer by ThermoBreast (=index test) compared to histopathologically confirmed invasive breast cancer during routine breast cancer screening/imaging (=reference test). We will report this outcome as the true-positive rate (=TPR, rate of patients with non-detected invasive breast cancer by ThermoBreast compared to histopathologically confirmed invasive breast cancer during routine breast cancer screening/imaging) which is a commonly used and validated measure in diagnostic studies.
Specificity (true-negative rate)
时间窗: up to 2 years of follow-up
As a co-primary outcome we will measure the specificity of the ThermoBreast screening modality. The specificity will be defined as the rate of true-negative ThermoBreast results, i.e., the number of correctly identified absence of invasive breast cancer by ThermoBreast, when compared to the number of absence of histopathologically confirmed invasive breast cancer or regular follow-up imaging during routine breast cancer screening/imaging. This outcome will be reported as the true-negative rate (=TNR, rate of patients for whom ThermoBreast correctly identifies the absence of invasive breast cancer in alignment with the results from routine breast cancer screening/imaging).
次要结局
- Detection rate of tumor category pT1(up to 2 years of follow-up)
- Specificity(up to 2 years of follow-up)
- Positive-predictive value(up to 2 years of follow-up)
- Screening time(Screening visit)
- Lived Experience(Screening visit)
- Effect of ethnicity on diagnostic performance(up to 2 years of follow-up)
- Recall rate(up to 2 years of follow-up)
- Negative-predictive value(up to 2 years of follow-up)
- Diagnostic performance in the three trial cohorts(up to 2 years of follow-up)
- Cost-effectiveness(up to 2 years of follow-up)
- Sensitivity(up to 2 years of follow-up)
- Proportion of correct histopathologic subtype identification(up to 2 years of follow-up)
- Cancer detection rate(up to 2 years of follow-up)
- Detection rate of ductal carcinoma in situ (DCIS)(up to 2 years of follow-up)
- Proportion of breast quadrant localization(Screening visit)
- Effect of breast density on diagnostic performance(up to 2 years of follow-up)
- Proportion of correct tumorbiologic subtype identification(up to 2 years of follow-up)
- Proportion of correct axillary lymph node involvement identification(up to 2 years of follow-up)
- Effect of hormonal status on diagnostic performance(up to 2 years of follow-up)
- Timing of ThermoBreast(up to 2 years of follow-up)