Advances in AI Improve Lung Cancer Screening

Software is ever-evolving, as do user requirements. So it is only logical that companies benefit from the know-how of their customers. At least that's how contextflow views the product development process. The Vienna-based machine learning in radiology expert has implemented corresponding suggestions into its new version of ADVANCE Chest CT.

​​​​​​​Brand new for RSNA in Chicago is the name ADVANCE Chest CT. contextflow's core product was previously named SEARCH Lung CT, but additional features necessitated an update in the product's name, which also suggests an ADVANCEing forward of innovation to combat interstitial lung diseases, COPD and lung cancer. And these advances are paying off: contextflow will be shown or discussed at thirteen partner booths at RSNA22!

One of ADVANCE Chest CT's most-requested and newest features is TIMELINE for lung nodules. It automatically visualizes and quantifies changes in lung nodules over time, allowing radiologists to view multiple prior exams side-by-side. "Radiologists tell us they spend a lot of time preparing for follow-up examinations and tumor boards. With TIMELINE, they can view prior scans instantly, with consistent measurements of nodule characteristics, and we expect it will save radiologists a great deal of time," says Marcel Wassink, Chief Commercial Officer at contextflow.

Another innovation, the integration of RevealAI-Lung from RevealDx into ADVANCE Chest CT, also supports the diagnosis of lung cancer by indicating malignancy similarity index for each nodule. "Lung cancer screening is currently expensive and slow, and it often leads to unnecessary procedures and stress for the patient. Implementing the lung nodule characterization component from RevealAI-Lung was a no-brainer because its clinical evaluation showed it could significantly impact on clinical decision making," says contextflow Chief Product Officer Markus Krenn. In a clinical study published in September in the Journal of the American College of Radiology, it has been shown that the number of false positive and negative findings can be significantly reduced. When implemented in clinical routine, this could not only save resources, but also reduce stress for patients by avoiding unnecessary examinations.

In addition to RevealAI-Lung, Elsevier's STATdx is integrated into ADVANCE Chest CT: STATdx provides radiologists with a list of possible differential diagnoses for a defined finding. With 1,400 differential diagnosis modules, the software includes more than 4,700 common and complex diagnoses with 200,000 image examples. "Through this partnership, we can support our users in faster and simpler reporting. In addition, Elsevier provides a systematic approach that allows radiologists to earn CME points virtually on the side," says Marcel Wassink, describing the advantages of the integration.

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