View or Download Our Validation Resources Below
Optellum’s technology has been independently validated by world-leading lung cancer experts interested in verifying our claims and quantifying benefits to their own patient populations. Below is a selection of publications from high-quality pulmonary and respiratory journals.
Traditional clinical risk models such as the Mayo model give indeterminate scores to many incidentally-detected nodules, leaving many patients undergoing long follow-up and potentially delaying life-saving cancer treatment. In contrast, the LCP-CNN helps clarify the patient stratification, sending more patients correctly into low-risk and high-risk groups.
Independently validated on more than 16,000 indeterminate lung nodules 1, 2
- Baldwin DR, et al External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules Thorax 2020;75:306-312
- Massion P, et al Assessing the accuracy of a deep learning method to risk stratify indeterminate pulmonary nodules American Journal of Respiratory and Critical Care Medicine
*Up to, depending on the patient population
Example of two pulmonary nodules with the same diameter for which the Optellum LCP (Lung Cancer Prediction) score helps to correctly reclassify. Based on diameter only, both nodules would have been classified in the intermediate-risk category. However, with the support of the Optellum LCP score, the nodule on the left is correctly reclassified in the high-risk category while the nodule on the right in the low-risk category.
Optellum LCP Score
Optellum LCP score 9 = 84% risk of cancer
Optellum LCP score 1 = 0.2% risk of cancer