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AI analysis for Chest x-ray
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Proper detection of lung nodules, which includes lung cancer, is a challenging task when interpreting chest radiographs, with miss rates reported to be 20-30%. 1, 2 This is especially true for radiologists who need to read high volumes of images at limited amount of time, as well as for non-specialists who lack expertise in reading difficult cases, such as chest radiographs of small or hidden nodules. Missed lung cancer has serious clinical implications, with over 50% in reduction of 5-year survival rate when left undetected for around 1 year.3
Developed using Lunit’s cutting-edge deep learning technology,4 Lunit INSIGHT CXR-Nodule accurately detects lung nodules in the form of diagnostic support tool. The AI solution generates (1) location information of detected lesions in the form of heatmaps and (2) abnormality scores reflecting the probability that the detected lesion is abnormal. The solution is indicated to be directly involved in the primary interpretation process of radiologists or clinicians.
Primary value proposition
- Prevent nodules, especially small or hidden nodules, from being missed upon reading chest radiographs.
- Help physicians make early diagnosis of lung cancer in chest radiographs.
- Enable non-specialists to perform at specialist level in detecting lung nodules in chest radiographs.
Training & Validation
- Trained with a large-scale (>70,000 cases), high-quality (clinically/CT-proven cases) training set.
- Demonstrated to perform at a standalone accuracy of 97% in ROC AUC.5
- Clinically validated to significantly improve the interpretive capabilities of clinicians and radiologists upto 20%.
- Initial observer performance study published in Radiology.6
- MFDS approved for clinical use in Korea (Computer-aided detection software; Approval No.18-574).
CASE #1. A nodule, diagnosed as lung cancer, hidden behind the heart is properly detected, with an abnormality score of 44%. This case was missed by 8 out of 15 radiologists.
CASE #2. A nodule, diagnosed as lung cancer, in the right upper lung field is properly detected, with an abnormality score of 66%. This case was missed by 9 out of 9 radiologists.
CASE #3. A nodule, diagnosed as lung cancer, hidden behind the diaphragm is properly detected, with an abnormality score of 96%. This case was missed by 5 out of 9 radiologists.