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EXoPERT has developed a liquid biopsy-based in vitro diagnostic medical device that can diagnose cancer through blood. The in vitro diagnostic medical device for this clinical performance trial is a test device that applies a technology that measures Raman spectroscopic signals of extracellular vesicles in the blood and classifies high-risk and low-risk patients for breast cancer through artificial intelligence analysis.
The test device used in this clinical performance trial is expected to assist in the differential diagnosis of high-risk and low-risk breast cancer patients by developing a software algorithm for an in vitro diagnostic medical device for auxiliary diagnosis that classifies high-risk and low-risk breast cancer patients and confirming the clinical efficacy and safety of the device through this clinical performance trial.
According to the Korean Breast Cancer Society, when comparing the five-year survival rate of breast cancer patients by stage from 2001 to 2012, the survival rate is 98.3% for stage 0, 96.6% for stage 1, and 91.8% for stage 2, but the survival rate for stage 4 patients with systemic metastasis is 34%. Therefore, early detection and accurate diagnosis are very important for breast cancer treatment.
Currently, breast cancer is diagnosed through breast ultrasound and mammography. These imaging modalities are defined by the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS) to define the specificity and various characteristics of the lesion. BI-RADS is divided into six categories: Category 1 is no abnormality, Category 2 is a definite benign tumor, Category 3 is a high likelihood of benign tumor (≤2% positive predictive value), Category 4 is a low likelihood of malignancy (≤2% positive predictive value), except for Category 0, which is an incomplete determination, Category 4 is a moderate suspicion of malignancy (2< positive predictive value <95%), Category 5 is a very high probability of malignancy (positive predictive value ≥95%), and Category 6 is a pathologically diagnosed malignancy.
In the Breast Imaging Reporting and Data System (BI-RADS), biopsy is not required in category 3 because the likelihood of malignancy is 2% or less, so a 6-month follow-up is recommended, and biopsy is recommended starting from category 4A, where the frequency of malignancy is 3 - 10%. However, the BI-RADS criteria have a significant number of false-positive results, which leads to an increase in unnecessary biopsies. The need for complementary diagnostic tests that can overcome the limitations of conventional imaging tests and compensate for unnecessary biopsies is being emphasized.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Breast malignant nodule group |
| ||
| Breast benign nodule group |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ExoPred | Diagnostic Test | Performing in vitro diagnostics with devices developed by EXoPERT |
|
| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity | through study completion, an average of 1 year | |
| Specificity | through study completion, an average of 1 year |
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Inclusion Criteria(Breast malignant nodule group)
Inclusion Criteria(Breast benign nodule group)
Exclusion Criteria:
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Patients categorized as BI-RADS category 4,5,6
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Jongwon Choi | Contact | +82-10-3931-2941 | necain1003@exopert.com |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Korea University Anam Hospital | Recruiting | Seoul | South Korea |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 41918185 | Derived | Song SE, Shin H, Park Y, Choi Y, Jung SP. Artificial Intelligence-Based Exosome Analysis for Improving Diagnostic Performance of Breast Lesions on Ultrasound: Protocol of a Prospective, Multicenter Cohort Study. J Breast Cancer. 2026 Apr;29(2):183-191. doi: 10.4048/jbc.2025.0206. Epub 2026 Apr 1. |
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plasma
| Korea University Guro Hospital | Recruiting | Seoul | South Korea |
|
| ID | Term |
|---|---|
| D001943 | Breast Neoplasms |
| D009369 | Neoplasms |
| ID | Term |
|---|---|
| D009371 | Neoplasms by Site |
| D001941 | Breast Diseases |
| D012871 | Skin Diseases |
| D017437 | Skin and Connective Tissue Diseases |
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