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

NCT04688086 | Completed Results

• 1 other identifier: NIR-THERMA-02
• Study Type: observational
• Target: 687
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Breast Cancer; Early Detection of Cancer

Keywords

Breast cancer; Thermography; Thermalytix; Artificial Intelligence; Machine Learning; Dense Breasts; Breast Density; Mammography; Breast Cancer Screening

Outcome Measures

Primary Outcomes (1)

• 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

  2 days

Secondary Outcomes (2)

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

  2 days

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

  2 days

Study Arms (1)

Women with no personal history of breast cancer

Women who came in for a breast mammography between ages 30 and 80 years were invited to take part in the study. All the women included in the study underwent breast cancer screening first by Thermalytix, the AI-based thermal imaging test, followed by mammography.

Diagnostic Test: Thermalytix

Interventions

Thermalytix DIAGNOSTIC_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.

Women with no personal history of breast cancer

Eligibility Criteria

• Age: 18 Years - 80 Years
• Gender Eligibility Details: The participant eligibility is based on self-representation of gender identity
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Women who came in for a breast mammography at Max Super Speciality Hospital, Saket were invited to take part in the study.

You may qualify if:

• Female subjects equal to and above 18 years
• Subjects who are willing to give written informed consent for study participation
• Subjects who are ready to comply with the study related visits and procedures

You may not qualify if:

• Subjects who are pregnant
• Subjects who are lactating
• Subjects who have undergone either lumpectomy or mastectomy
• Subjects who have undergone chemotherapy in the last 2 weeks at the time of study enrollment
• Any active illness, psychological and/or pathological condition that would interfere with study participation in the opinion of the Investigator

Sponsors & Collaborators

• Niramai Health Analytix Private Limited: lead
• Max Healthcare Insititute Limited: collaborator

Study Sites (1)

Max Healthcare Insititute Limited

New Delhi, 110017, India

Location

MeSH Terms

Conditions

Breast Neoplasms

Condition Hierarchy (Ancestors)

Neoplasms by Site; Neoplasms; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases

Results Point of Contact

• Title: Dr Sathiakar Collison
• Organization: NIRAMAI Health Analytix Private Limited

sathiakar.collison@niramai.com

+919810823838

Study Officials

• Richa Bansal, MD

  Max Healthcare Insititute Limited

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: No
• Restrictive Agreement: No

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 23, 2020
• First Posted: December 29, 2020
• Study Start: December 15, 2018
• Primary Completion: January 6, 2020
• Study Completion: January 30, 2020
• Last Updated: October 17, 2024
• Results First Posted: October 17, 2024

Record last verified: 2024-10

Data Sharing

• IPD Sharing: Will not share

Locations

IN (1)