A Prospective Study to Evaluate Clinical Performance of Thermalytix in Detecting Breast Cancers

Niramai Health Analytix Private Limited687 enrolled

Overview

The purpose of this study is to determine the clinical performance of AI-based Thermalytix with the current standard-of-care diagnostic modalities in women.

While mammography is the most accepted breast cancer screening test, it is less sensitive in women with dense breast tissue, who have a four fold high risk for developing breast cancer. Thermalytix is a novel automated breast cancer screening solution that uses artificial intelligence (AI) over thermal images to detect and localise breast cancer lesions in women. In this study the performance of Thermalytix over mammography is evaluated in women with dense and non-dense breast tissue who presented for a health check-up at a hospital. All women underwent Thermalytix and mammography, and participants who were reported as positive on either test were recommended for further investigations. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated across age-groups, menopausal status, and breast densities against the current standard-of-care diagnostic modalities.

Study Type

OBSERVATIONAL

Enrollment

687

Conditions

Breast Cancer Early Detection of Cancer

Interventions

ThermalytixDIAGNOSTIC_TEST

Thermalytix is an Artificial intelligence based automated breast screening solution that analyzes thermal distribution on the breast to generate a breast health score automatically. Thermal imaging was performed by a trained technician to capture thermal images of the participant in five views. These thermal images were uploaded to Thermalytix software on the cloud where it was automatically analyzed by AI-based Thermalytix computer-aided detection (CADe) engine. This CADe engine analyzes uploaded thermal images and outputs an interpretation report for each participant with quantitative scores corresponding to computed probability of malignancy based on the structural, vascular, areolar, thermal properties of the observed abnormality. Thermalytix also generates annotated images with markings of abnormal regions and an overall Thermalytix score suggesting likelihood of breast malignancy. The locked AI model Thermalytix algorithm version 3, dated December 2018 was used for the analysis.

Eligibility

Sex: FEMALEMin age: 18 YearsMax age: 80 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: 1. Female subjects equal to and above 18 years 2. Subjects who are willing to give written informed consent for study participation 3. Subjects who are ready to comply with the study related visits and procedures Exclusion Criteria: 1. Subjects who are pregnant 2. Subjects who are lactating 3. Subjects who have undergone either lumpectomy or mastectomy 4. Subjects who have undergone chemotherapy in the last 2 weeks at the time of study enrollment 5. Any active illness, psychological and/or pathological condition that would interfere with study participation in the opinion of the Investigator

Locations (1)

Max Healthcare Insititute Limited

New Delhi, India

Outcomes

Primary Outcomes

Sensitivity, Specificity, Positive Predictive Value and Negative Predictive Value of Thermalytix

To assess the clinical performance of Thermalytix as compared to standard screening modalities. Sensitivity, specificity, positive predictive value and negative predictive value of Thermalytix

Time frame: 2 days

Secondary Outcomes

Sensitivity and Specificity of Thermalytix for Women With Dense Breast Tissue (ACR Category C or D)

To assess the influence of patient characteristics (Breast density) on the diagnostic accuracy of Thermalytix.

Time frame: 2 days

Sensitivity and Specificity of Thermalytix in Women With Breast Density ACR Category "A" or "B"

To assess the influence of patient characteristics (Breast density) on the diagnostic accuracy of Thermalytix. Sensitivity and Specificity of Thermalytix in Women with Fatty Breasts - Breast Density ACR category "A" or "B"

Time frame: 2 days

Data from ClinicalTrials.gov

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