Radiomics
A.Y. 2021/2022
Learning objectives
"Learn the basis of radiobiology
Learn the fundamentals of the different imaging techniques
Learn how to select target lesions
Learn the use of different segmentation tools
Know the value of the different radiomic features
Know the role of radiotherapy in oncology, its work flow and mechanism of tumor control and normal tissue toxicity
Know the clinical applications of radiomics and radiogenomics and their methodological challenges
"
Learn the fundamentals of the different imaging techniques
Learn how to select target lesions
Learn the use of different segmentation tools
Know the value of the different radiomic features
Know the role of radiotherapy in oncology, its work flow and mechanism of tumor control and normal tissue toxicity
Know the clinical applications of radiomics and radiogenomics and their methodological challenges
"
Expected learning outcomes
"The student will know the basis of radiobiology
The student will know the fundamentals of the different imaging techniques
The student will be able to select target lesions
The student will be able to use of different segmentation tools
The student will know the value of the different radiomic features
The student will know the indications to radiotherapy, its work flow and the role of imaging
The student will be able to describe the clinical applications of radiomics and radiogenomics and their methodological challenges "
The student will know the fundamentals of the different imaging techniques
The student will be able to select target lesions
The student will be able to use of different segmentation tools
The student will know the value of the different radiomic features
The student will know the indications to radiotherapy, its work flow and the role of imaging
The student will be able to describe the clinical applications of radiomics and radiogenomics and their methodological challenges "
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
More specific information on the delivery modes of training activities for academic year 2021/22 will be provided over the coming months, based on the evolution of the public health situation.
Course syllabus
1. Radiobiology
Interactions of ionising radiation with matter
Radiation effects on healthy and tumour tissue
Radiosensitivity and radioresistance of tissue
2. Imaging acquisition techniques
Digital diagnostic images: matrix, spatial resolution, contrast resolution, archive and distribution
Processing of digital images
Ultrasound
- Mechanical waves and ultrasound image formation
- Doppler phenomenon
- Ultrasound contrast media and harmonic imaging
Computerized tomography
- Technological evolution of the equipment, reconstruction through sinograms and back projection
- Hounsfield unit and window concept
Magnetic Resonance
- Signal genesis, relaxation time T1 and T2, spatial encoding
- Contrast agents in radiology and MR
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
Discovering DICOM attributes - overview of anonymization strategies
Radiomic goals
Radiologic images are biomarkers for oncologic response evaluation and for response prediction
Radiomic pathways
Image normalization techniques
Target lesions identification
Target lesions contouring
Atlas-based autosegmentation
Extraction of target lesions
Radiomic analysis
Radiomic features description
Radiomic features variability and causes of variability
Influence of image acquisition parameters
5. Radiomics and radiogenomics
Clinical applications
Treatment personalisation
Methodological challenges
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
Interactions of ionising radiation with matter
Radiation effects on healthy and tumour tissue
Radiosensitivity and radioresistance of tissue
2. Imaging acquisition techniques
Digital diagnostic images: matrix, spatial resolution, contrast resolution, archive and distribution
Processing of digital images
Ultrasound
- Mechanical waves and ultrasound image formation
- Doppler phenomenon
- Ultrasound contrast media and harmonic imaging
Computerized tomography
- Technological evolution of the equipment, reconstruction through sinograms and back projection
- Hounsfield unit and window concept
Magnetic Resonance
- Signal genesis, relaxation time T1 and T2, spatial encoding
- Contrast agents in radiology and MR
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
Discovering DICOM attributes - overview of anonymization strategies
Radiomic goals
Radiologic images are biomarkers for oncologic response evaluation and for response prediction
Radiomic pathways
Image normalization techniques
Target lesions identification
Target lesions contouring
Atlas-based autosegmentation
Extraction of target lesions
Radiomic analysis
Radiomic features description
Radiomic features variability and causes of variability
Influence of image acquisition parameters
5. Radiomics and radiogenomics
Clinical applications
Treatment personalisation
Methodological challenges
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
Prerequisites for admission
No prior knowledge is required.
Teaching methods
The course is based on frontal lessons. Lectures could be held in presence and/or online (Microsoft Teams). Lectures will be accompanied by practicals, group work and time for reflection and collective discussion.
Teaching Resources
Radiomics and Radiogenomics: Technical Basis and Clinical Applications (Imaging in Medical Diagnosis and Therapy) 1st Edition
By Ruijiang Li, Lei Xing, Sandy Napel, Daniel L. Rubin
ISBN 9780815375852
Published June 28, 2019 by Chapman and Hall/CRC
By Ruijiang Li, Lei Xing, Sandy Napel, Daniel L. Rubin
ISBN 9780815375852
Published June 28, 2019 by Chapman and Hall/CRC
Assessment methods and Criteria
Oral examination on the items that have been described during classes.
MED/04 - EXPERIMENTAL MEDICINE AND PATHOPHYSIOLOGY
MED/36 - IMAGING AND RADIOTHERAPY
MED/36 - IMAGING AND RADIOTHERAPY
Lessons: 48 hours
Professors:
Jereczek Barbara Alicja, Vanzulli Angelo
Professor(s)