What Radiologists do?

Transcription

1 Multimodality Imaging in Oncology 2018 March 5 th 9th Diagnostic Imaging in Oncology What Radiologists do? Chikako Suzuki, MD, PhD Department of Diagnostic Radiology, KS Solna Department of Molecular Medicine and Surgery

2 Contents Imaging of Oncology? How tumors look like? Why? Novel imaging tools and parameters, Radiomics & artificial intelligence (AI), deep learning Mind the Gap!

3 Diagnostic Imaging of Oncology to see is to believe How cancers look like? Key characters of cancers, such as How to catch those characters? Novel imaging techniques, such as..

4 Oncological Imaging

5 Diagnostic Imaging of Oncology

6 Diagnostic Imaging of Oncology Anatomical imaging Functional imaging

7 How cancers (should) look like? A patient with uterine cancer 2014-May Which one is cancer/metastasis?

8 How cancers (should) look like? A patient with uterine cancer 2014-May 2015-July

9 How cancers (should) look like? A patient with uterine cancer 2014-May 2015-July Metastasis (Ca) Hamartoma (Benign)

10 How cancers (should) look like? 2015-March Is this cancer?

11 How cancers (should) look like? 2015-March 2015-August

12 How cancers (should) look like? Cancer (malignant, bad ones) Not Cancer (benign, good ones) Proliferation

13 How cancers (should) look like? Pat with abdominal pain Is this cancer?

14 How cancers (should) look like?

15 How cancers (should) look like? Metastasis = Cancer Cecal cancer with lung and lymph nodes metastases

16 How cancers (should) look like? Without contrast agent With contrast agent

17 How cancers (should) look like? Without contrast agent With contrast agent Renal cyst (Benign) Heterogenous enhancement Renal cancer (Malignant)

18 How cancers (should) look like? Without contrast agent With contrast agent Renal cyst (Benign) Angiogenesis Heterogenous enhancement Renal cancer (Malignant)

19 How cancers (should) look like? A patient with uterine cancer

20 How cancers (should) look like? 18FDG-PET FDG-hot FDG-cold

21 How cancers (should) look like? 18FDG-PET Metabolism FDG-hot FDG-cold

22 Diagnostic Imaging of Oncology to see is to believe How cancers look like? Key characters of cancers, such as Proliferation, Angiogenesis, Metabolism etc. How to catch those characters? Novel imaging techniques, such as..

23 Novel Imaging Techniques Dual Energy Multidetector CT

24 Novel Imaging Techniques Conventional CT Water material density image Iodine material density image Dual-Energy (Spectral) CT: applications in Abdominal Imaging, Silva et al, Radiographics 2011;31:

25 Novel Imaging Techniques Conventional CT Water material density image Iodine material density image Cysts Cancer Dual-Energy (Spectral) CT: applications in Abdominal Imaging, Silva et al, Radiographics 2011;31:

26 Novel Imaging Techniques CT Spectral attenuation curves Imaging of tumor vascularity A patient with multiple liver metastases after treatment Green: reference, Pink: a meta with high vascularity (viable tumor cells) Yellow: a meta with moderate vascl. Blue: with less vascl (close to necrosis) Dual-Energy (Spectral) CT: applications in Abdominal Imaging, Silva et al, Radiographics 2011;31:

27 Novel Imaging Techniques Magnetic resonance imaging (MRI) Magnetic field and radio frequency waves Superior contrast resolution compared to other imaging modalities Functional imaging capabilities 27

28 MRI

29 Diffusion-weighted MRI Water diffusion correlates with cell density. Tumor= high cell density=diffusion restriction Diffuson Weighted MRI in the Body, Koh et al, AJR 2007; 188:

30 Diffusion-weighted MRI Ovarian cancer with peritoneal dissemination CT

31 Diffusion-weighted MRI Ovarian cancer with peritoneal dissemination CT DWI

32 Diffusion-weighted MRI A patient with rectal cancer

33 Diffusion-weighted MRI A patient with prostate cancer T2WI DWI ADC map

34 Novel Imaging Techniques Magnetic resonance imaging (MRI) Prostate cancer T1, T2WI (morphology) DWI, ADC-map (cell density) Dynamic contrast enhanced MR (permeability, vascularity) MR spectroscopy (choline)

35 Cervical cancer, MR: Diffusion, ADC, Choline spectroscopy Garcia-Figueiras et al, Magn Reson Imaging Clin N Am 24 (2016) 261

36 Novel Imaging Techniques PET-CT, PET-MR Make positron emitting tracers, such as 18-FDG, via cyclotron Administrate tracers via injection/inhalation etc Image by PET camera t ½ 11 C 20 min 13 N 10 min 15 O 2 min 18 F 110 min 68 Ga 68 min

37 Novel Imaging Techniques PET-CT, PET-MR Basic principle of FDG-PET

38 PET/MR, Pancreatic cancer Pre treatment Post treatment

39 Diagnostic Imaging of Oncology to see is to believe How cancers look like? Key characters of cancers, such as Proliferation, Angiogenesis, Metabolism etc. How to catch those characters? Novel imaging techniques, such as.. CT (computed tomography), MRI (magnet resonance imaging), PET-CT (positron emission tomography-ct) etc

40 Can macroscopic imaging features correlate/indicate with genetic features?

41 Diagnostic Imaging of Oncology How cancers look like? Morphology: Reflection of DNA, RNA, genes, proteins etc. Function: increased/decreased metabolic level. Can macroscopic imaging features correlate/indicate with genetic features? Radiomics

42 Diagnostic Imaging of Oncology Radiomics Imaging feature correlates with long noncoding RNA (lncrna) expression And may indicate poor metastasis-free survival (Radiogenomic Biomarker Reveals Associations among Dynamic Contrastenhanced MR Imaging, Long Noncoding RNA, and Metastasis: Yamamot et al, Radiology vol 275; ) Measure ERF (enhancing rim fraction)

43 Diagnostic Imaging of Oncology ERF: enhancing rim fraction Triple negative br ca Metastasis free survival Radiogenomic Biomarker Reveals Associations among Dynamic Contrast-enhanced MR Imaging, Long Noncoding RNA, and Metastasis: Yamamot et al, Radiology vol 275;

44 AI, deep learning for diagnosis Ben-Cohen, Acad Radiolo 2017;24:

45 Radiomics, AI, deep learning for Health Care NEJM Gerlinger, 2012;366(10):883, Nature Clinical Oncology Lambin,2017;14:749

46 NEJM Gerlinger, 2012;366(10):883 What We Want to Do To catch the cancer s dynamic Clonal Evolution Intratumor Heterogenity Spatial and Temporal Heterogenity In One Patient

47 What We Want to Do A patient with multiple liver metastases after treatment Green: reference, Pink: a meta with high vascularity (viable tumor cells) Yellow: a meta with moderate vascl. Blue: with less vascl (close to necrosis) NEJM Gerlinger, 2012;366(10):883, Radiographics 2011;31:

48 What We Don t Want to Do A patient with multiple liver metastases after treatment Green: reference, Pink: a meta with high vascularity (viable tumor cells) Yellow: a meta with moderate vascl. Blue: with less vascl (close to necrosis) NEJM Gerlinger, 2012;366(10):883, Radiographics 2011;31:

49 Radiomics, AI, deep learning for Health Care Nature Clinical Oncology Lambin,2017;14:749

50 Contents Imaging of Oncology? How tumors look like? Why? Mind the Gap!

51 MIND THE GAP! Flow cytometry, tumor markers

52 MIND THE GAP!

53 Thank you!