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| Name | Class |
|---|---|
| Assuta Medical Centers Ltd. | UNKNOWN |
| Hospital of Lithuanian University of Health Sciences Kaunas Clinics | UNKNOWN |
| Institut Gustav Roussy | UNKNOWN |
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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.
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.
The second trial visit (V2) serves as a follow-up visit for the reference test - no study specific interventions will be performed here. Patients will undergo routine breast cancer screening or diagnostics according to national guidelines which serve as a reference test. In the screening cohort, the patient may undergo routine breast diagnostics following an irregular second screening round (V2.2) according to national guidelines. No study specific interventions will be performed during this trial visit.
There will be no randomization within this study design. The findings of thermal screening will not be disclosed to patients and physicians, to avoid any anxiety or influence on the physicians' decision-making, as the proposed method is under study and development. The ThermoBreast system will only record the thermal imaging but will not automatically display any final assessment with respect to risk of breast cancer.
AI-based evaluation of dynamic breast thermography imaging (=ThermoBreast, index test) will serve as the outcome measure. The ThermoBreast evaluation will be performed independently of the routine breast diagnostic evaluation. Some baseline risk variables (e.g. patient age, hormonal status) may be included in the ThermoBreast evaluation. ThermoBreast will provide a risk score for invasive breast cancer on a per-patient basis (not per breast).
Routine breast diagnostics will serve as a reference test against which the ThermoBreast outcome will be compared. Depending on national guidelines and clinical scenarios, routine breast cancer diagnostics can consist of several routine procedures, including clinical examination, ultrasound, mammography, tomosynthesis, MRI, follow-up imaging, biopsy, surgical excision, and histopathologic evaluation. All procedures will be performed as indicated and specified by the respective, current national guidelines.
The AI-based evaluation will use state-of-the-art image analysis techniques. The algorithm will be trained on data acquired during the training phase of the trial. For the second 6 month validation phase of the trial, a data lock will ensure that outcomes with respect to the reference test (routine breast diagnostics) will not be available anymore for the team responsible for the ThermoBreast algorithm development.
A positive reference test is defined as histopathologic diagnosis of invasive breast cancer.
A negative reference test is defined as
Analyses will be performed on a per-patient basis. In case of multiple breast masses per patient, the one with the highest risk of breast cancer or histopathological confirmed invasive breast cancer will be considered for the primary efficacy analysis
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ThermoBreast - AI-based evaluation of dynamic breast thermography imaging | Diagnostic Test | Index test: AI-based evaluation of dynamic breast thermography imaging (ThermoBreast). The ThermoBreast evaluation will be performed independently of the routine breast cancer diagnostic evaluation. Some baseline risk variables (e.g. patient age, hormonal status) may be included in the ThermoBreast evaluation. Reference test: Routine breast diagnostics will serve as a reference test against which the ThermoBreast outcome will be compared. Depending on national guidelines and clinical scenarios, routine breast cancer diagnostics can consist of several routine procedures, including clinical examination, ultrasound, mammography, tomosynthesis, MRI, follow-up imaging, biopsy, surgical excision, and histopathologic evaluation. All procedures will be performed as indicated and specified by the respective, current national guidelines. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity (true-positive rate) | 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. | up to 2 years of follow-up |
| Specificity (true-negative rate) | 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). | up to 2 years of follow-up |
| Measure | Description | Time Frame |
|---|---|---|
| Cancer detection rate | To evaluate the invasive breast cancer detection rate per 1000 women screened of ThermoBreast and compare it with other standard breast cancer screening and diagnostic modalities (ultrasound, mammography, MRI) | up to 2 years of follow-up |
| Detection rate of ductal carcinoma in situ (DCIS) |
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Inclusion criteria
Screening cohort
High-risk screening cohort
Diagnostics cohort
Exclusion Criteria
• (High-risk) Screening and Diagnostics cohort
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Hakan Yesilmen | Contact | +972 547833599 | hakan@thermomind.io | |
| Larisa Adamyan, PhD | Contact | +972 547833599 | larisa@thermomind.io |
| Name | Affiliation | Role |
|---|---|---|
| Michael Golatta, MD | University Hospital Heidelberg | Study Director |
| André Pfob, MD | University Hospital Heidelberg | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Heidelberg University Hospital | Recruiting | Heidelberg | Germany |
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| Label | URL |
|---|---|
| Related Info | View source |
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| ID | Term |
|---|---|
| D001943 | Breast Neoplasms |
| ID | Term |
|---|---|
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D001941 | Breast Diseases |
| D012871 | Skin Diseases |
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| M.D. Anderson Cancer Center |
| OTHER |
| Sheba Medical Center | OTHER_GOV |
| Holy Family Hospital, Nazareth, Israel | OTHER |
| University College Cork | OTHER |
| Univerzitetni klinicni center Maribor | UNKNOWN |
| Academisch Ziekenhuis Groningen | OTHER |
| Technical University of Munich | OTHER |
| Technion, Israel Institute of Technology | OTHER |
| Vrije Universiteit Brussel | OTHER |
| Cancer Patients Europe | UNKNOWN |
| University Hospital Heidelberg | OTHER |
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Number of women with ThermoBreast screening-detected ductal carcinoma in situ (if the pT category of the TNM classification falls into the category pTis) divided by the number of all women screened. |
| up to 2 years of follow-up |
| Detection rate of tumor category pT1 | Number of women with ThermoBreast screening-detected invasive breast cancers of the category pT1 divided by the number of all women screened. A screening-detected breast cancer is classified as breast cancer of tumor category pT1 if tumor size is ≤ 20 mm in greatest dimension and the respective pT subcategory of the pTNM classification is one of the following: pT1mic, pT1a, pT1b, pT1c, pT1. | up to 2 years of follow-up |
| Recall rate | To evaluate the recall rate per 100 women screened of ThermoBreast and compare it with other standard breast cancer screening and diagnostic modalities (ultrasound, mammography, MRI) | up to 2 years of follow-up |
| Sensitivity | To evaluate the sensitivity of ThermoBreast and compare it with other standard breast cancer screening and diagnostic modalities (ultrasound, mammography, MRI) | up to 2 years of follow-up |
| Specificity | To evaluate the specificity of ThermoBreast and compare it with other standard breast cancer screening and diagnostic modalities (ultrasound, mammography, MRI) | up to 2 years of follow-up |
| Positive-predictive value | To evaluate the positive-predictive value of ThermoBreast and compare it with other standard breast cancer screening and diagnostic modalities (ultrasound, mammography, MRI) | up to 2 years of follow-up |
| Negative-predictive value | To evaluate the negative-predictive value of ThermoBreast and compare it with other standard breast cancer screening and diagnostic modalities (ultrasound, mammography, MRI) | up to 2 years of follow-up |
| Diagnostic performance in the three trial cohorts | To compare the diagnostic performance of ThermoBreast with routine breast cancer screening and imaging rate within the three cohorts ( (1) screening cohort, (2) high-risk screening cohort (3) diagnostics cohort) in terms of sensitivity, specificity, negative-predictive value, positive predictive value, recall rate, and cancer detection rate | up to 2 years of follow-up |
| Proportion of breast quadrant localization | Number of women with correct localization of breast masses by ThermoBreast (measured in breast quadrants: upper outer, upper inner, lower outer, lower inner) divided by all women with breast masses. | Screening visit |
| Proportion of correct histopathologic subtype identification | Number of women with correct diagnosis of histopathologic subtype by ThermoBreast (invasive-ductal, invasive-lobular, medullary, tubular, papillary, metaplastic, in-situ) divided by all women with the respective histopathologic subtype. | up to 2 years of follow-up |
| Proportion of correct tumorbiologic subtype identification | Number of women with correct diagnosis of tumorbiologic subtype by ThermoBreast (hormon receptor positive/ HER2neu negative, hormon receptor positive, HER2neu positive, hormon receptor negative/HER2neu positive, triple-negative breast cancer) divided by all women with the respective tumorbiologic subtype. | up to 2 years of follow-up |
| Proportion of correct axillary lymph node involvement identification | The compare the diagnostic performance of ThermoBreast to axillary ultrasound in the detection of axillary lymph node metastasis in terms of sensitivity and specificity | up to 2 years of follow-up |
| Effect of hormonal status on diagnostic performance | To compare the diagnostic performance of ThermoBreast and routine breast imaging modalities in women with pre-,peri-,and post-menopausal status in terms of sensitivity, specificity, negative-predictive value, positive predictive value, recall rate, and cancer detection rate | up to 2 years of follow-up |
| Effect of breast density on diagnostic performance | To compare the diagnostic performance of ThermoBreast and routine breast imaging modalities in women with different breast densities (ACR A-D) in terms of sensitivity, specificity, negative-predictive value, positive predictive value, recall rate, and cancer detection rate. | up to 2 years of follow-up |
| Effect of ethnicity on diagnostic performance | To compare the diagnostic performance of ThermoBreast and routine breast imaging modalities in women with different ethnicity in terms of sensitivity, specificity, negative-predictive value, positive predictive value, recall rate, and cancer detection rate | up to 2 years of follow-up |
| Timing of ThermoBreast | To estimate the possibility of ThermoBreast to replace versus precede routine breast cancer screening/imaging as an additional imaging technique in terms of diagnostic performance | up to 2 years of follow-up |
| Screening time | To estimate the possibility to reduce the screening time by evaluating the effect of screening duration on the performance of ThermoBreast | Screening visit |
| Cost-effectiveness | To evaluate the cost-effectiveness of ThermoBreast for breast cancer screening and diagnosis. A cost per QALY analysis will be conducted. | up to 2 years of follow-up |
| Lived Experience | The goal is to measure the difference between thermography and mammography by patients' self-assessment. Concretely, we will focus on the following areas: trust in the modality, perceived pain and discomfort, intention to use and willingness to pay. For trust and reliability, we are going to use the existing Likert scale made by Cahour and Forzy (2009). Perceived pain and comfort will be measured via the Likert scale made by indication of pain in the bodymap (van der Grinten, 1991) and the pain intensity scale (Jensen and Karoly, 1986). The willingness to pay question is based on van Helvoort-Postulart et al.'s study (2008). The results will be assessed by ANOVA and t-test by evaluating differences between thermography and mammography, as well as expectations before the test and the actual experience after the test. | Screening visit |
| D017437 |
| Skin and Connective Tissue Diseases |