Development and validation of a preoperative CT-based radiomic nomogram to predict pathology invasiveness in patients with a solitary pulmonary nodule: a machine learning approach, multicenter, diagnostic study

ConclusionsThis study demonstrated that a nomogram constructed by identified clinical –radiological signatures and combined radiomic signatures has the potential to precisely predict pathology invasiveness.Key Points• The radiomic signature from the perinodular area has the potential to predict pathology invasiveness of the solitary pulmonary nodule.• The new radiomic nomogram was useful in clinical decision-making associated with personalized surgical intervention and therapeutic regimen selection in patients with early-stage non-small-cell lung cancer.
Source: European Radiology - Category: Radiology Source Type: research