Thoracic Radiology Revisited. Challenges and Solutions in an Evolving World

Date: 12 June 2019

Venue: Antwerp University Hospital (UZA) - Auditorium Kinsbergen (route 12) - Wilrijkstraat 10 - 2650 EDEGEM

Time: 4:45 PM

PhD candidate: Annemiek Snoeckx

Principal investigator: Prof P. Parizel, Prof J. Van Meerbeeck

Short description: PhD defence Annemiek Snoeckx - Faculty of Medicine and Health Sciences (Presentation in Dutch)


For decades, Computed Tomography imaging has had a key role in diagnosis and management of patients with lung cancer, unfortunately often presenting in advanced disease stages. Early detection is however crucial to improve outcome and survival. Where imaging of advanced disease is often straightforward, diagnosis of early lung cancers – often presenting as pulmonary nodules- as well as uncommon manifestations and mimickers, is far more challenging. The first part of this thesis tries to answer the following questions: what are the morphological features that are important to differentiate benign from malignant pulmonary nodules? What are the imaging manifestations of primary lung cancer mimicking benign diseases and what are the imaging and clinical characteristics of the uncommon entity ‘lung cancer associated with cystic airspaces’? Imaging technology has made radical changes over the past decades.

The (r)evolution of multidetector CT and transition to PACS caused an increase in images to read. This triggered the idea of merging multiple conventional window settings into a single ‘All-In-One’ (AIO) window. The AIO-window is a novel technique that fuses multiple conventional window settings such as mediastinal, lung and bone, into a single window to read. To investigate the possible clinical value, two studies were performed in the second part of this thesis, trying to answer the following questions: first, is lesion detection on a combined AIO-window as good as on conventional window settings? Secondly, what is the effect on intra-and interobserver variability on lesion measurement on this novel window?

Currently, AI is reshaping the imaging world with radiologists on the frontline of AI innovation in the medical sector. It will play a role in many aspects of lung cancer imaging and will force us to come out of the dark. The last part of this thesis deals with two projects that are related to the role of radiologists as clinician in an imaging world that is changing at high speed. In this regard, we investigated two topics: the role for radiologists in communication, focused on the imaging features of urgencies and emergencies in the lung cancer patient and secondly, we explored if the presence of a radiologist as co-author in case reports containing radiological images influences quality.

Entrance fee: free

Registration: not required