Accurate lung nodule detection in low-dose CT (LDCT) is a prerequisite for the implementation of effective lung cancer screening programs [1]. Furthermore, also in clinical setting, the incidence and detection rate of pulmonary nodules has increased over the years [2], resulting in more work within the radiological workflow. Artificial Intelligence (AI) solutions have gained traction due to their potential of assisting radiologists in nodule evaluation in both settings. Given that most of these …