1 CT Myocardial Perfusion Ting-Yim Lee, PhD, FCCPM, FCOMP Aaron So, PhD, FSCCT Gerald Wisenberg, MD, FRCPC Ali Islam, MD, FRCPC Lawson Health Research Institute Robarts research Institute The University of Western Ontario London, Ontario
Financial Disclosure T.-Y. Lee has licensing agreement with GE Healthcare 2
Outline Methods for CT myocardial perf. imaging Qualitative Semi-quantitative Quantitative model based Artifacts to avoid Applications Future directions Delayed enhancement edema Ultra-low radiation dose 3
CT Myocardial Perfusion Imaging - Methods Qualitative Visual interpretation of coronary CTA source images 1,2 Myocardial contrast enhancement (MCE) as surrogate measure of MBF relative to normal myocardium No additional contrast injection and radiation exposure Imaging window 1 Blankstein et al, JACC 54:1072-84, 2009 2 George et al, Circ Cardiovasc Imaging 2:174-182, 2009 4
CT Myocardial Perfusion Imaging - Methods Qualitative Visual interpretation of coronary CTA source images 1,2 Myocardial contrast enhancement (MCE) as surrogate measure of MBF relative to normal myocardium No additional contrast injection and radiation exposure Beam hardening Imaging window 1 Blankstein et al, JACC 54:1072-84, 2009 2 George et al, Circ Cardiovasc Imaging 2:174-182, 2009 5
CT Myocardial Perfusion Imaging - Methods Semi-quantitative Bolus injection of contrast Cine scanning with ECG gating time density curve (TDC) Upslope of myocardial TDC normalized by upslope of LV TDC as MBF 1 Moderate radiation exposure Linear fit Imaging window 1 George et al, Invest Radiol 42:815-822, 2007 6
CT Myocardial Perfusion Imaging - Methods Semi-quantitative Bolus injection of contrast Cine scanning with ECG gating time density curve (TDC) Upslope of myocardial TDC normalized by upslope of LV TDC as MBF 1 Moderate radiation exposure Linear fit No venous outflow Imaging window No leakage into myocardium F C a (t) Q(t) 1 George et al, Invest Radiol 42:815-822, 2007 7
CT Myocardial Perfusion Imaging - Methods Quantitative imaging Prospective ECG gating (mid-diastole) on Revolution (GE Healthcare) 100 kv, 100 ma, 0.28 s per gantry rotation (28 mas) 80 mm axial coverage; 5 mm non-overlapping slices Contrast 40-60 ml (300 mgi ml -1 ) at 5 ml s -1 20-24 gated scans in 30 s with breath-hold 2.5 to 3 msv (per CTP study covering 4 cm) Correction for beam hardening and motion CT Perfusion (GE Healthcare) to generate perfusion maps 200 150 100 HU aorta ml min-1 100g-1 200 50 0-50 myocardium sec 0 5 10 15 20 25 30 0 CT Perfusion images Time-density curves Perfusion map8
Vessels CT Myocardial Perfusion Imaging - Methods Deconvolve arterial (aortic) TDC from tissue TDC based on the Johnson- Wilson-Lee model F C A (t) Quantitative estimates of Perfusion (F), ml/min/100g Blood volume (V b ), ml/100g V b K 1 k 2 Myocardium Flow extraction product (K 1 ), ml/min/100g Backflux rate constant, 1/min F C V (t) 200 150 100 HU artery ml min-1 100g-1 200 50 0-50 myocardium sec 0 5 10 15 20 25 30 0 Contrast-enhanced heart images Time-density curves Perfusion map9
CT Myocardial Perfusion Imaging - Methods Validation Pig model of acute MI and reperfusion CT vs radiolabeled microspheres perfusion measurement in remote and ischemic/infarcted myocardium Without beam hardening correction With beam hardening correction 1 So et al. Int J Cardiovasc Imaging 2012; 28:1237-48 10
CT Myocardial Perfusion Imaging - Artifacts Beam Hardening (BH) High density contrast in heart chambers Hypodensity in apical and inferior wall Hyperdensity in septal wall WW:120 WL:80 LAD: 75% WW:120 WL:80 LAD: normal 1 So et al. J Cardiovasc Comput Tomogr 2011;5:467-481 11
CT Myocardial Perfusion Imaging - Artifacts BH correction with ECG triggered rapid switching kv High and low kv projections water and iodine projections Iodine and water images monoenergetic images at different kev 140 kvp 80 kvp 12
Projection Data Processing 80kVp 120kVp 80kVp 140kVp Projections Nonlinear Mapping Data Acquisition Interleaved High- and Low-kVp Projections Iodine Projections Water Projections Basis- Material Projections Image Reconstruction NIST table 140 kvp 70 kev Monochromatic images MD Iodine MD Water Basis-material density images 13 Courtesy of Dr. Jiang Hsieh
CT Myocardial Perfusion Imaging - Artifacts BH correction with ECG triggered rapid switching kv WW:50 WL:50 140 kv image of a nonischemic pig heart WW:50 WL:50 70 kev image of a nonischemic pig heart 14
CT Myocardial Perfusion Imaging - Artifacts BH correction with ECG triggered rapid switching kv 140 kv 70 kev 15
CT Myocardial Perfusion Imaging - Artifacts BH correction with ECG triggered rapid switching kv Myocardial perfusion with/out BH correction 5 normal pigs Lateral wall Apical wall Septal wall lateral apical septal 1 So et al. J Cardiovasc Comput Tomogr 2011;5:467-481 16
CT Myocardial Perfusion Imaging - Artifacts Dual energy CT current implementation GE Healthcare Single source, rapid switching kv Philips Healthcare Single source Layered detector Siemens Healthineers Two sources, different kv Simons et al. Eur Radiol 2014; 24:930 17
/ CT Myocardial Perfusion Imaging - Artifacts BH correction image-based processing Attenuation of a given material as a sum of two basis material bone 0.88 water 0.018 iodine CT bone = m w CT water + m iod CT iodine 100000 10000 1000 100 10 1 0.1 0 20 40 60 80 100 120 140 energy (kev) iodine bone water Courtesy of Dr. Jiang Hsieh 18
CT Myocardial Perfusion Imaging - Artifacts Partial scan Decrease the acq window to freeze heart motion 180 o +fan angle 200 msec from 280 msec gantry rotation ~60 HU fluctuations in time-density curve tissue aorta aorta tissue 19
CT Myocardial Perfusion Imaging - Artifacts Partial scan correction New image reconstruction algorithm HU in lateral region stable over 10 scans 20
Applications Normal LCx and sub-totally occluded LAD 450 450 0 Rest 0 Stress Aorta LAD LV LCx 21
Applications Functional significant stenosis (a)-(c) Occluded LAD with collaterals (d)-(f) LCX sub-totally occluded no collaterals (g)-(i) All three vessesl Moderate to severe stenosis So et al, Eur Radiol 22:39-50, 2012 22
Applications MITNEC multicenter trial Patients with high risk for CAD SPECT MIBI CTA & CT myocardial perfusion imaging Rest and adenosine stress Segmental myocardial perfusion reserve (MPR) Patient with an abnormal SPECT MIBI or MPR < 1.90 in CT FFR measured in the involved artery FFR < 0.8 functionally significant stenosis FFR > 0.8 significant stenosis MPR Condition MPR Score MPR Normal 0 >=2.30 Mild Reduction Moderate Reduction Severe Reduction Absent / Steal 1 1.90-2.29 2 1.50-1.89 3 1.01-1.49 4 <=1.00 23
Applications MITNEC multicenter trial No coronary stenosis. Myocardial perfusion increased 2-4 times after adenosine stress. 600 REST Perfusion RC LCx 0 ml/min/100g 600 STRESS Perfusion LAD ml/min/100g 24 Dr. Ben Chow, Ottawa Heart Institute
Applications MITNEC multicenter trial Extensive LCx and LAD stenoses/calcifications. Myocardial perfusion minimally or did not increased after adenosine stress in the LCx and LAD territories. 600 REST Perfusion RC LCx 0 ml/min/100g 600 STRESS Perfusion LAD 0 ml/min/100g 25 Dr. Ben Chow, Ottawa Heart Institute
MPR Applications MITNEC multicenter trial 23 patients enrolled at London had FFR measured in 28 coronary arteries 3.0 2.5 2.0 1.5 1.0 0.5 0.0 >0.8 < 0.8 FFR 26
Future Applications Extravascular Contrast Distribution Volume (ECDV) Increases in ischemic injury Expanded interstitium Enhanced leakiness of cell membrane Ischemic / infarcted tissue (acute phase post MI) 27
Enhancement (HU) Vessels Kinetic Model for ECDV Deconvolve arterial (aortic) TDC from tissue TDC based on the modified Johnson-Wilson-Lee model Quantitative estimates of Perfusion (F), ml/min/100g Blood volume (V b ), ml/100g FE product (K 1 ), ml/min/100g ECDV, ml/100g F C A (t) V b F C V (t) K 1 k 2 C E (t) Extracellular Myocardium k 3 k 4 C M (t) Intracellular Enhanced CT ECDV 50 40 Time Enhancement Curves At-risk Remote 30 20 10 0 Time (sec) 28 0 50 100 150 200 250
1.3 Future Applications At Risk (MAR) vs Salvageable Myocardium MAR is hypoperfused myocardium : reversible and irreversible injury Edema interstitial and intracellular a marker of injury Salvageable myocardium + Infarct Extravascular Contrast Distribution Volume (ECDV) Edema Perfusion Infarct Salvageable Myocardium = Edema infarct Ischemia and Salvageability from ONE rest perfusion ECDV 4 3 2 Myocardial perfusion 3 0 mlg -1 1 0 mlmin -1 g -1 Drs. Gerald Wisenberg and Frank Prato Salvageable Infarcted + Edematous Normal 29
Future Applications Extravascular Contrast Distribution Volume Pig model of acute LAD occlusion and reperfusion ECDV vs T2W MRI 3-d post : Edema (red arrow) T2W MRI images CT ECDV maps T2 weighted images 0 1.2 ml/g 30
Future Applications Extravascular Contrast Distribution Volume Pig model of acute LAD occlusion and reperfusion at 1-week post MAR as shown by MRI T1 mapping (yellow dotted region with T1 relaxation time > 1100 ms) Entire MAR showed ECDV > 2 times higher than normal Perfusion heterogeneous within MAR left region, 0.61 ml/min/g, likely salvageable right region, 0.35 ml/min/g, likely infarcted MRI T1 map CT ECDV map CT MP map 1 2 > 0.50 0.23 0.35 0.61 0.92 0 mlg -1 0 mlmin -1 g -1 31
Future Applications ECDV & Fibrosis Contrast enhanced CT ECDV map TTC stained tissue scar no fibrosis LV 1.2 0.79 0.32 0 ml/g scar with fibrosis 1.2 LV 0.55 1.00 Nonfibrotic fibrosis 0 ml/g 32
Future Applications Extravascular Contrast Distribution Volume Identifying ablation target of ventricular tachycardia causing arrhythmia Isthmus (Ischemic but viable region within scar) Catheter-based electroanatomical mapping (EAM) < 0.5 mv scar > 1.5 mv normal 0.5 1.5 mv isthmus Limitations of EAM Time consuming (3+ hours) Invasive Poor resolution 1.2 0 ml/g 0.55 1.00 33
Future Applications Radiation dose reduction Methods Statistical iterative reconstruction Decrease x-ray tube current (ma) Electronic noise Low signal-to-noise Unreliable perfusion and ECDV estimates Fewer projections (views) per gantry rotation 34
Future Applications Radiation dose reduction Sparse-view acquisition Standard CT scan 984 views over 360 o Radiation dose reduced in proportion to number of views collected per scan Full-view acquisition ½ view acquisition 1/3 view acquisition 35
Future Applications Radiation dose reduction Sparse-view acquisition Streaks (aliasing artifacts) with standard filtered backprojection (FBP) reconstruction FBP with 984 (full) projections FBP with 328 (1/3) projections 36
Future Applications Radiation dose reduction Sparse-view acquisition Compressed sensing (CS) can minimize streaks FBP with 984 (full) projections CS with 328 (1/3) projections 37
Future Applications Radiation dose reduction 5 pigs 2 infarct & 3 normal 140 kv, 80 ma, 0.35 s, 5 mm slice 328-view CS vs 984-view FBP Lateral, apical and septal wall over 8 slices compared Excellent correlation of perfusion Radiation dose reduce by 300% 38
Future Applications Radiation dose reduction Sparse-view acquisition with lower ma 984 views, 80 ma,fbp 328 views, 80 ma, CS 492 views, 20 ma, CS 8 msv 2.6 msv 1 msv 4 4 4 0 ml/min/g 0 ml/min/g 0 ml/min/g 39
Decreasing Trend in Radiation Dose Year Scanner Model Scanner z- Coverage (cm) # of Contrast Injection Required Effective Dose (msv) Information 2000 HiSpeed 2 4 20 Perfusion 2004 VCT 4 2 20 Perfusion 2008 CT750 HD 4 2 6 Perfusion 2017 and beyond Revolution 16 1 < 3 Perfusion, edema, scar, cardiac output, angiography 40
Conclusions Quantitative CT cardiac Imaging provides functional information to complement coronary CTA Perfusion infarct ECDV edema and MAR Newer iterative reconstruction methods coupled with sparse-view acquisition Reduce radiation dose by > 300% Whole heart perfusion and ECDV imaging possible ~ 3 msv With technology advancements, CT achieving onestop-shop assessment of acute and chronic MI to guide treatment is becoming a reality 41
Acknowledgement Lawson Health Res Inst Xiaogang Chen Feng Su Jennifer Hadway Laura Morrison MITNEC B5 Investigators Ottawa Heart Institute ( B. Chow et al) Lawson Health Res Inst (G Wisenberg et al) St. Paul s Hosp, Vancouver (J Leipsic et al) Univ Washington, Seattle (K Branch et al) GE Healthcare Jiang Hsieh Yasuhiro Imai Brian Nett John Jackson Saad Sirohey Bich Le 42
Research Funding Canadian Institutes of Health Research Canada Foundation for Innovation Ontario Research Fund Ontario Innovation Trust GE Healthcare 43