ERS how to webinar series - Session two: Insights into HRCT-based radiomics for disease characterisation and outcome prediction in lung diseases

19 October | 18:00-19:00 CEST

Chair: Dr. Nahal Mansouri (Lausanne, Switzerland)
Speakers: Dr. Janine Gote-Schniering (Bern, Switzerland)

Educational need:
Recently, high-dimensional image analysis, termed "radiomics", has opened novel avenues for imaging-based disease subtyping and outcome prediction. Radiomic features are computationally retrieved, quantitative data derived from medical images which describe the tissue in terms of its intensity, texture and advanced statistical properties. Their unique and added value compared with visual or other quantitative imaging methodologies lies in the ability to capture tissue phenotypes on different spatial scales ranging from the radiological/macroscopic to the molecular/microscopic level, which adds another dimension. Thereby, they provide novel and complementary information compared with clinical reports, laboratory and functional tests.

Educational aim:
Understand the relevance for radiomics in disease characterisation and monitoring of progression
Learn which steps are required to assess potential of HRCT based radiomics

Topics:
- Radiomics
- Imaging based disease subtyping
- Interstitial Lung Diseases

Format:
Workshop with interactive quizzes, Q&A with audience, presentation of a clinical study on HRCT based radiomics for disease characterisation and outcome prediction in ILD.

Learning outcomes:
- Understand the relevance for radiomics in disease characterisation and monitoring of progression
- Learn which steps are required to assess potential of HRCT based radiomics
- Assess whether image based diseases subtyping may be used in their patient cohort.