State of the Art Symposium
SA 3 - Assessment of incidental and screen-detected pulmonary nodules
Lectures
1
SA 3 - Diagnosis and overdiagnosis of subsolid nodules
15:17A. Nair, London / UK
Learning Objectives
1. To become familiar with the characteristics of subsolid nodules and their risk of cancer.
2. To learn about the differential diagnosis of subsolid nodules.
3. To understand current management strategies for the diagnosis, classification, and follow-up of subsolid nodules.
2
SA 3 - Radiomics and AI performance in lung nodule assessment
16:22G. Chassagnon, Paris / FR
Learning Objectives
1. To become familiar with the deep learning methods used and their possibilities.
2. To learn what the current state-of-the-art applications of AI are in detection, classification, and follow-up of pulmonary nodules.
3. To appreciate what the impact of these advancements may be on the role of radiologists.
SA 3-1
15 min
Diagnosis and overdiagnosis of subsolid nodules
Arjun Nair, London / United Kingdom
Learning Objectives
1. To become familiar with the characteristics of subsolid nodules and their risk of cancer.
2. To learn about the differential diagnosis of subsolid nodules.
3. To understand current management strategies for the diagnosis, classification, and follow-up of subsolid nodules.
2. To learn about the differential diagnosis of subsolid nodules.
3. To understand current management strategies for the diagnosis, classification, and follow-up of subsolid nodules.
SA 3-2
15 min
Diagnosis and follow-up of solid nodules
Anna Rita Larici, Roma / Italy
Learning Objectives
1. To become familiar with the characteristics of solid nodules and their risk of cancer.
2. To learn about the differential diagnosis of solid nodules.
3. To understand current management strategies for the diagnosis, classification, and follow-up of solid nodules.
2. To learn about the differential diagnosis of solid nodules.
3. To understand current management strategies for the diagnosis, classification, and follow-up of solid nodules.
SA 3-3
15 min
Radiomics and AI performance in lung nodule assessment
Guillaume Chassagnon, Paris / France
Learning Objectives
1. To become familiar with the deep learning methods used and their possibilities.
2. To learn what the current state-of-the-art applications of AI are in detection, classification, and follow-up of pulmonary nodules.
3. To appreciate what the impact of these advancements may be on the role of radiologists.
2. To learn what the current state-of-the-art applications of AI are in detection, classification, and follow-up of pulmonary nodules.
3. To appreciate what the impact of these advancements may be on the role of radiologists.
10 min
Live Q&A: The requirements of a nodule MDT board