Ultrasound molecular imaging: oncology & cardiology applications - PowerPoint PPT Presentation

23rd floor Kirby Lattwein Therapeutic UCA Group, Dept. Biomedical Engineering, Thoraxcenter Ultrasound molecular imaging: oncology & cardiology applications

Medical ultrasound

Ultrasound: some parameters P_ λ f = c / λ c = speed of sound (m/s) P_ = peak negative pressure f = frequency P_ (in MPa) MI = mechanical index = f (in MHz)

Sound frequencies Humans can Cats can Bats use Dolphins use Diagnostic hear up to detect frequencies frequencies as Ultrasound: 20,000 Hz frequencies as high as high as 1-50 MHz as high as 210,000 Hz 150,000 Hz 60,000 Hz

How is an echo made?

Resolution Micro Ultrasound Scale (m) 10 -6 10 -5 10 -4 10 -3 10 -2 Optical Micro CT In vivo Micro PET Micro MRI Microscopy Optical

Why ultrasound in medicine? - Harmless to patients - Real-time images - Mobile - Versatile - No contra indications - Cost effective - Functional imaging (flow, motion, …)

Ultrasound molecular imaging

Ultrasound Molecular Imaging How? - Ultrasound Contrast Agent - Used in hospitals worldwide for more than decade + contrast agent B-mode Courtesy of Dr. O.I.I. Soliman, Dr. F.J. ten Cate, Erasmus MC

Ultrasound Contrast Agents Microbubbles - gas: air / N 2 / SF 6 / perfluorocarbon (C n F 2n+2 ) - shell: protein, lipids, polymers, sugars - 1 - < 8 µm diameter: blood pool markers

Ultrasound Contrast Agents Clinical use (non-targeted): - since 1990s - Perfusion imaging cardiology + radiology New direction: therapy - Molecular imaging - Drug delivery

Microbubble in ultrasound field Ultrasound Changes in bubble size time

Microbubble in ultrasound field 1 MHz, 80 kPa Ultrasound Changes in bubble size 13.3 Mfps time

Ultrasound Contrast Agent: molecular imaging non-targeted C 4 F 10 PEG biotinylated bubble biotin phospholipid

~10 5 per bubble + avidin biotinylated bubble a) b) c) RGD RGD a) antibody b) polymer c) peptide

Molecular imaging Blood vessel pathology

Markers for ultrasound molecular imaging α V β 3 and similar molecules cancer  Selectins (P-selectin, E-selectin) atherosclerosis  ICAM-1  VCAM-1 ischaemia  Phosphatidylserine inflammation  VEGF receptor; VEGF+receptor => are all endothelial markers because: injected UCA do not extravasate

Molecular imaging with ultrasound and microbubbles P-selectin targeted microbubbles Courtesy of Prof. J.R. Lindner, Oregon Health & Science University, USA Two options for using targeted microbubbles: • Target biomarkers to detect diseased tissue • Target and treat disease, i.e. therapy: local drug delivery

Using targeted microbubbles in vivo in oncology

Assessment of tumor vasculature markers (1) Baseline Just after injection 10 min after MI = 0.25 f = 7 MHz BR55 SonoVue Disease: patient-derived xenograft breast cancer Target: VEGFR2 (BR55) or non-targeted (SonoVue) UCA: lipid shell bubble (Bracco) Reference: Pochon et al., Invest Radiol 2010; 45: 89-95

Assessment of tumor vasculature markers (2) MI = 0.1 f = 7 MHz Phase 0 trial VEGFR2 BR55 by Bracco Courtesy of Prof. H. Wijkstra, AMC Smeenge et al., Invest Radiol 2017; 52: 419

Assessment of early response to therapy Drug: Aurora-A kinase inhibitor MI = 0.2 f = 15 MHz 2 weeks: non-targeted bubble MI = 0.18 4 weeks: volume measurements f = 15 MHz Disease: patient-derived xenograft pancreatic cancer α v β 3 Target: UCA: lipid shell bubble Reference: Streeter et al., Technol Cancer Res Treat 2013; 12: 311-321

Using targeted microbubbles in vivo in cardiology

Ischaemia-reperfusion heart 30 min after reperfusion 30 min 30 min MI = ? f = 1.3 MHz Disease: LAD coronary artery occlusion (10 min) Target: P-selectin UCA: lipid shell bubble Reference: Davidson et al., J Am Soc Echocardiogr 2014; 27: 786-793.e2

Atherosclerosis (1) Carotid Maximal Intensity Projection MI = 0.1 f = 18 MHz Disease: atherosclerosis (ApoE-/-) Target: α v β 3 on endothelial cells UCA: lipid shell bubble (MicroMarker) Reference: Daeichin, Kooiman et al., Ultrasound Med Biol 2016; 42: 2283- 2293

Atherosclerosis (2) Contrast Bmode mode plaque ROI salivary gland ROI no plaque ROI α v β 3 control

Atherosclerosis (3) control α v β 3 * p < 0.01

Using targeted microbubbles for cellular drug delivery

Microbubble-mediated drug delivery I: cell membrane pores (sonoporation) II: endocytosis III: opening cell-cell junctions Kooiman et al., Adv Drug Del Rev 2014; 72: 28

CD31 + + + Experiments: endothelial high-speed camera (Brandaris-128) videocamera PI uptake lens + PI 37 °C 1 MHz PI = propidium iodide (1 nm) 6x10 cycles Kooiman et al, J Contr Rel 2011; 154: 35

CD31 + + + Experiments: endothelial Brandaris-128 (frame rate 13.4 Mfps) 5 µ m : 1 MHz, 80 kPa MI = 0.08 PI Kooiman et al, J Contr Rel 2011; 154: 35

CD31 + + + Experiments: endothelial 5 µm before ultrasound after ultrasound PI uptake : 1 MHz, 80 kPa (MI = 0.08) PI Kooiman et al, J Contr Rel 2011; 154: 35

CellMask Orange + + Experiments: fibroblast : 1 MHz, 850 kPa, 10 cycles MI = 0.85 Hu et al., Ultrasound Med Biol 2013; 39: 2393-2405

α v β 3 + + + Experiment: % : 1 MHz, 150 kPa, 10,000 cycles MI = 0.15 α V β 3 Skachkov, Luan, van der Steen, de Jong, Kooiman, IEEE TUFFC 2014; 61: 1661-1667

P-selectin + + Experiment: Luciferase cDNA Hind limb ischemia skeletal muscle (20 min iliac ligation) 5x Bioluminescence (3 days) Immunohistochemistry : 1.6 MHz, 600 kPa, 25,000 cycles (MI = 0.6) for 9 min Xie et al., Jacc-Cardiovasc Imag 2013; 5: 1253-1262

Advantages of molecular imaging with UCA - Easy - Fast - Imaging is non-invasive and real-time - Excellent spatial and temporal resolution - Suitable for small animals (access during imaging + longitudinal) - Combination with drug delivery

Limitations of molecular imaging (of experimental animals) with UCA - Target on endothelial cells - Only in sonographically accessible tissue: * Not possible in lung (air) * Getting possible in intact brain (skull) MI = 0.4 f = 15 MHz Errico et al., Nature 2015; 527: 499-502

Acknowledgements Dept. of Biomedical Engineering: www.erasmusmc.nl/thoraxcenterbme Questions  k.lattwein@erasmusmc.nl Collaborators: Dr. Klazina Kooiman Prof. Nico de Jong Prof. Ton van der Steen Dr. Hans Bosch Dr. Ilya Skachkov Dr. Ying Luan Dr. Tom Kokhuis Dr. Verya Daeichin Dr. Tom van Rooij Prof. Alexander Klibanov (University of Virginia)