Radiomics talk at TROG 2017 Auckland

1. Radiomics for Oncology
Andre Dekker
Department of Radiation Oncology (MAASTRO)
GROW - Maastricht University Medical Centre +
Maastricht,The Netherlands
SLIDES AVAILABLE ON SLIDESHARE
(slideshare.net/AndreDekker)

2. 2
Disclosures
• Research collaborations incl. funding and speaker honoraria
– Varian (VATE, SAGE, ROO, chinaCAT, euroCAT), Siemens (euroCAT), Sohard (SeDI,
CloudAtlas), Mirada Medical (CloudAtlas), Philips (EURECA,TraIT, SWIFT-RT, BIONIC),
Xerox (EURECA), De Praktijkindex (DLRA), ptTheragnostic (DART, Strategy), CZ (My
BestTreatment), OncoRadiomics
• Public research funding
– Radiomics (USA-NIH/U01CA143062), euroCAT(EU-Interreg), duCAT&Strategy (NL-
STW), EURECA (EU-FP7), SeDI & CloudAtlas & DART (EU-EUROSTARS),TraIT (NL-
CTMM), DLRA (NL-NVRO), BIONIC (NWO)
• Spin-offs and commercial ventures
– MAASTRO Innovations B.V. (CSO)
– Various patents on medical machine learning

3. 3
This talk
• Rationale (animation)
• Radiomics workflow & challenges
• New directions

4. 4
Rationale
• https://www.youtube.com/watch?v=Vf0F7q8vaS4

5. Radiomics workflow & (some)
challenges
Andre Dekker
Department of Radiation Oncology (MAASTRO)
GROW - Maastricht University Medical Centre +
Maastricht,The Netherlands

6. 6
RadiomicsWorkflow
Lambin,Walsh et al., Nat Rev Clin Oncol (in-press)
Larue, et al., Br J Radiol 2017

7. 7
Feature Extraction – Dimensionality reduction
Gillies et al., Radiology 2016;278(2).
219 features in 235 patients
Aerts et al., NatureCommunications 5, 4006

8. 8
Feature Extraction – Imaging Protocols
Oliver et al. ,TranslationalOncology (2015) 8, 524–534

9. 9
Feature Extraction – Robust Segmentation
Parmar et al., PLoS One. 2014; 9(7): e102107.
Approaches
1. Perform semi-automatic segmentation
2. Remove features which are too sensitive to the exact segmentation
Larue, et al., Br J Radiol 2017

10. 10
Feature Extraction - Software
Non-texture-based features:
Histogram, Geometry
Texture-based features: GLCM,
GLRLM
Sample capacity:
31
51
33
Correlation Coefficients Distribution
correlation coefficient range
Fudan University Cancer Hospital (unpublished)

11. 11
Feature Extraction – Phantom / Ontology

12. 12
So, Radiomics needs a lot of training data….
Aerts et al., NatureCommunications 5, 4006

13. 13
…. and a lot of validation data
Aerts et al., NatureCommunications 5, 4006
Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis

14. 14
Radiomics – End result

15. New directions
Andre Dekker
Department of Radiation Oncology (MAASTRO)
GROW - Maastricht University Medical Centre +
Maastricht,The Netherlands

16. 16
Radiomics – Preclinical

17. 17
Radiomics – PET

18. 18
Radiomics - MRI
• Rectal cancer - Chemoradiation
• Pathological response
• Training n=173,Validation n=25
• AUC 0.79 (validation)
1) MRGTVdelineation
2) GTVROI extraction
3) LoGfilter application
accordingdifferents
0.3 0.5 1.0 2.0 3.0 4.0
4) Dataanalysis
|||cT
234
Points
| | |cN
||||||||||||||SKE0485
−0.6−0.4−0.200.20.40.6
| | | | | | | | | |ENT0344
1.6 1.8 2 2.2 2.4
| | | | | | | || | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |Total Points
320 330 340 350 360 370 380 390
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
TRG1
Probability
0 1 2
0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200

19. 19
Radiomics – Delta Radiomics
p = 0.0054 (pCT) and p = 0.00099 (CBCT-FX1)

20. 20
Radiogenomics –Virtual Biopsy
Wu et al., Front Oncol 2016

21. 21
Distributed Radiomics

22. 22
Rapid Learning Health Care

23. 23
Conclusion
• We are still in the very early phase
• A lot of underpowered, exploratory
papers out there
• A lot of dials to control (medical physics
needs to get involved)
• Prospective validation as a decision
support system needed
• TROG can help by collection of highly
standardized images in their trials
• But the promise is HUGE
0
20
40
60
80
100
120
140
160
1 2 3 4 5 6
Pubmed Radiomics
Radiomics

24. 24
Acknowledgements
• MAASTRO Clinic, Maastricht,The Netherlands
– Philippe Lambin, Ralph Leijenaar,….
• Moffitt Cancer Center,Tampa, FL, USA
– Bob Gillies, Bob Gatenby,…
• Dana-Farber Cancer Institute, Brigham andWomen’s Hospital, Harvard Medical School, Boston
– Hugo Aerts, Emmanuel RiosVelazquez, …
• Radboud University Medical Center, Nijmegen,The Netherlands
• VU University Medical Center, Amsterdam,The Netherlands
More info on: www.radiomics.org

25. Thank you for your attention
Andre Dekker
Department of Radiation Oncology (MAASTRO)
GROW - Maastricht University Medical Centre +
Maastricht,The Netherlands