Breast Cancer
Conditions
Brief summary
The purpose of this study is to evaluate the effectiveness of lesion detection and diagnosis-aiding software (CadAI-B for Breast) during ultrasound (US) examination
Detailed description
CadAI-B for Breast is a real-time AI diagnosis system designed to assist healthcare professionals in lesion detection and differential diagnosis during breast US examinations. The primary objective of the study is to evaluate the effectiveness of CadAI-B in the assistance of detection and diagnosis of breast cancer by comparing the clinical performance of physicians before and after using CadAI-B in their ultrasound reading. The secondary objective of this study is to evaluate the sensitivity and specificity using CadAI-B for US examinations.
Interventions
CadAI-B for Breast is designed to assist healthcare professionals in lesion detection and differential diagnosis during breast US examinations.
Sponsors
Study design
Eligibility
Inclusion criteria
* Women who underwent breast US examination * Women with breast cancer (DCIS or invasive cancer) diagnosed via biopsy * Women who had been followed for more than 2 years after initial US examination
Exclusion criteria
* women who had breast implants * women who had US images containing artifacts affecting the review of images
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Area Under the LROC Curve | 6 weeks | The area under the LROC curve (AUC\_LROC) on the diagnosis of suspicious lesions was computed and compared between the aided and unaided sessions. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Lesion detection sensitivity and specificity | 6 weeks | The mean sensitivity and specificity of 15 readers were calculated and compared between the aided and unaided sessions. |
Countries
South Korea