Disease Background
- 828,000 new cases of lung cancer and 657,000 of deaths from lung cancer[1] .
- The 5-year survival rate is above 90% for earlystage lung cancer and less than 10% for late stages.
- Imaging diagnosis talent resources are in short supply.
- It takes a long time for radiologists to read images, and the efficiency of reading needs to be improved.
- There are errors in traditional qualitative analysis, and many small quantitative changes are difficult to judge with the naked eye.
Product Advantages
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95%Detectable rate
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87.4%Accuracy
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30sAutomatic analysis
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Identification
Accurate detection of pulmonary nodules
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Monitoring
Intelligent and precise tracking, and dynamic follow-up assessment of pulmonary nodule lesions
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Insight
Accurately discriminating between benign and malignant pulmonary nodules
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Algorithm
Accurate, automatic and quantitative analysis of image indicators (size, density, etc.)
Professional Certification
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Large-scale sample size for modeling and validation; Excellent performance in assessment of pulmonary nodules
Training and validation of model based on preoperative CT images data of pulmonary nodule from more than 20,000 of pathologically confirmed cases. Accurately outline the lesion in seconds, and the volume calculation is accurate to 0.001 mm3.
Target Users
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Patients with pulmonary nodules
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People at a high risk of lung cancer who undergo LDCT/CT screening
Sample Collection and Service Process
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CT-DICOM data
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Test
counseling -
CT-DICOM
data upload -
Testing
and Analysis -
Report
issuance -
Report
interpretation
References
- [1] Report of Cancer Epidemiology in China, 2015. Chinese Journal of Oncology, 2019;41(1).