Radiomics

1. Radiobiology

Interactions of ionising radiation with matter
Radiation effects on healthy and tumour tissue
Radiosensitivity and radioresistance of tissue

2. Imaging acquisition techniques

Principles of conventional radiography, magnetic resonance imaging, computed tomography, positron emission tomography and ultrasound:
- Form of energy involved
- Means of interaction (reflection, absorption, relaxation, etc.)
- Processes of data sampling and reconstruction
- Information contained in the images
- Key clinical applications

3. Oncological radiotherapy

Imaging for radiotherapy
Indications to radiotherapy in the most common solid tumors and hematological malignancies
Radiotherapy devices and modalities
Work flow in radiotherapy
Image guided radiotherapy
Tumour remission and normal tissue toxicity
Clinical research in oncology. How to write a scientific paper?
Radiomic applications in clinical Radiation Oncology
Journal club on clinical cases

4. Images are numbers

Diagnostic digital images: matrix, spatial resolution, contrast resolution
Image pre-processing
Imaging segmentation techniques
Filtering and processing of digital images in the spatial and frequency domains
Image statistics, texture and "features"

Structure of a DICOM Image file
PACS, HIS and RIS: meaning and characteristics

5. Radiomics and radiogenomics

Radiomic features extraction
Conventional and machine learning features selection and model development
Understanding model stability, robustness, bias and limits
Best practices for radiomics studies and scoring a radiomics study
Clinical applications
Treatment personalisation
Current challenges for application of radiomics in clinical practice

6. Basics of statistics for radiomics
How to set-up a robust radiomic study from a statistical perspective
How to recognize biases and how to mitigate their effect
Methods of statistical analysis

7. New frontiers in radiomics

Studies with phantoms
Dosomics
Deep learning for medical image analysis