CT Perfusion Imaging CT Perfusion Imaging Ivan Yeung, Ph.D. Dept - - PowerPoint PPT Presentation

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CT Perfusion Imaging CT Perfusion Imaging Ivan Yeung, Ph.D. Dept of Radiation Physics, Princess Margaret Hospital Dept of Radiation Oncology, University of Toronto University of Toronto st Commercial CT Unit 1 st 1 Commercial CT Unit

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SLIDE 1

CT Perfusion Imaging CT Perfusion Imaging

Ivan Yeung, Ph.D.

Dept of Radiation Physics, Princess Margaret Hospital Dept of Radiation Oncology, University of Toronto

University of Toronto

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SLIDE 2

1st

st Commercial CT Unit

Commercial CT Unit 1 Commercial CT Unit Commercial CT Unit

  • In 1972, Sir Godfrey Hounsfield introduced the first EMI

In 1972, Sir Godfrey Hounsfield introduced the first EMI In 1972, Sir Godfrey Hounsfield introduced the first EMI In 1972, Sir Godfrey Hounsfield introduced the first EMI CT scanner. CT scanner.

  • It takes 5 min to scan and 2.5 hours to reconstruct.

It takes 5 min to scan and 2.5 hours to reconstruct.

  • Designed as a revolutionary

Designed as a revolutionary anatomical anatomical imaging tool. imaging tool.

EMI scanner

PMH 50th Anniversary Conference 2 2

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SLIDE 3

Development of CT Development of CT Development of CT Development of CT

  • CT was quickly development, during the 80’s, CT

CT was quickly development, during the 80’s, CT has become a work horse in almost every radiology has become a work horse in almost every radiology y gy y gy department. department.

  • Due to presence of cables, the fastest CT scan was

Due to presence of cables, the fastest CT scan was done every 4 done every 4-6 seconds 6 seconds done every 4 done every 4-6 seconds. 6 seconds.

  • First attempt to use CT to measure function

First attempt to use CT to measure function – – tissue tissue perfusion perfusion – – is with stable Xenon is with stable Xenon-

  • 133.

133.

  • ‘Messy’ experiment: patient breathes in Xenon, it

‘Messy’ experiment: patient breathes in Xenon, it diffuses from lung to blood, then carry to tissue diffuses from lung to blood, then carry to tissue

  • Nice property

Nice property – high diffusion coefficient across high diffusion coefficient across Nice property Nice property high diffusion coefficient across high diffusion coefficient across capillary. capillary.

  • Can be described by one

Can be described by one-

  • compartment model.

compartment model. Hence less computational demand and sparse Hence less computational demand and sparse

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Hence less computational demand and sparse Hence less computational demand and sparse sampling is ok. sampling is ok.

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SLIDE 4

One One-Compartment Model Compartment Model One One Compartment Model Compartment Model

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SLIDE 5

Slip Ring Technology (mid 90’s) Slip Ring Technology (mid 90’s) Slip Ring Technology (mid 90 s) Slip Ring Technology (mid 90 s)

  • Power and data transfer via

Power and data transfer via contact around gantry contact around gantry

  • Gantry moves in one

Gantry moves in one di ti di ti direction direction

  • Gantry can move up to 1/3

Gantry can move up to 1/3 sec per rotation sec per rotation sec per rotation sec per rotation

  • High temporal resolution

High temporal resolution

  • Data able to handle more

Data able to handle more Data able to handle more Data able to handle more complex model complex model – – exchange exchange

  • f contrast agent
  • f contrast agent

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SLIDE 6

Distributed Model Distributed Model Distributed Model Distributed Model

  • F

F – – Perfusion, blow flow through the capillary Perfusion, blow flow through the capillary

  • PS

PS – – Leakiness from intravascular to extravascular space Leakiness from intravascular to extravascular space

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  • MTT

MTT – – Time to take bolus to travel across the capillary Time to take bolus to travel across the capillary

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SLIDE 7

Perfusion CT Perfusion CT

contrast injector Model AIF(t) Tissue(t)

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SLIDE 8

Tracer Kinetics Models Tracer Kinetics Models Tracer Kinetics Models Tracer Kinetics Models

Model AIF(t) Tissue(t) GE P f i GE Perfusion …

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SLIDE 9

Non Non-linear Curve Fitting linear Curve Fitting Non Non linear Curve Fitting linear Curve Fitting

Model AIF(t) Tissue(t) Model ( ) ssue( )

F PS Vb F1, PS1, Vb1…. F2, PS2, Vb2…. F3 PS3 Vb3

Measured Fitted

F3, PS3, Vb3…. . Fn, PSn, Vbn…

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n, n, n

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Patients received Sorafenib + Rad Patients received Sorafenib + Rad Pt # 1 Pt # 1

Baseline Day 7 Day 21

CT

0.018 0.02 0.022

Perfusion Map

0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016

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0.002

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Patients received Sorafenib + Rad Patients received Sorafenib + Rad Patients received Sorafenib + Rad Patients received Sorafenib + Rad Pt # 2 Pt # 2

Baseline Day 7 Day 21

CT

0.05

Perfusion Map

0.01 0.02 0.03 0.04

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Preclinical Cervix Tumor xenograft in mice Preclinical Cervix Tumor xenograft in mice Preclinical Cervix Tumor xenograft in mice Preclinical Cervix Tumor xenograft in mice

Perfusion Perfusion

High

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Low

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SLIDE 13

Perfusion CT on Mouse 1 (anti Perfusion CT on Mouse 1 (anti-

  • vascular drug)

vascular drug)

Enhanced CT Blood Flow Blood Volume MTT Enhanced CT

  • od
  • Blood Volume

MTT

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SLIDE 14

Advancement in Perfusion CT Advancement in Perfusion CT Advancement in Perfusion CT Advancement in Perfusion CT

  • True 4D CT

True 4D CT – True 3D volume scan is possible True 3D volume scan is possible True 4D CT True 4D CT True 3D volume scan is possible True 3D volume scan is possible

  • Dose reduction schemes: intermittent X

Dose reduction schemes: intermittent X-

  • ray on, low

ray on, low dose CT, less frequent sampling dose CT, less frequent sampling dose CT, less frequent sampling dose CT, less frequent sampling

  • Optimization of protocol

Optimization of protocol

  • Limited speed cone

Limited speed cone beam CT perfusion beam CT perfusion

  • Limited speed cone

Limited speed cone-beam CT perfusion beam CT perfusion

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Dynamic Contrast Enhanced Perfusion CT Dynamic Contrast Enhanced Perfusion CT C t t CBCT C t t CBCT vs Contrast CBCT vs Contrast CBCT

CT Acquisition over time Multiple CT images at different time different time

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CBCT Single contrast enhanced CBCT image Acquisition over time

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SLIDE 16

DCE DCE-CBCT CBCT DCE DCE CBCT CBCT

  • Assume each voxel behaves as a single compartment with its wash

Assume each voxel behaves as a single compartment with its wash-

  • in

in and washout behaviour and washout behaviour

where Cb(t) where Cb(t) – – contrast enhancement in each voxel contrast enhancement in each voxel t t – – time time I, I, α, k , k – – unknown parameters unknown parameters

] 2 2 2 [ ) (

2 2 2

α α α

α α α

− + − =

− t t t kt b

e e t e t Ie t C

, , p

  • Reconstruct the kinetics behavior

Reconstruct the kinetics behavior according to the formula for each according to the formula for each voxel by optimization to determine the voxel by optimization to determine the

t=0s, 0o t = 1 s , 3o t=2s,

voxel by optimization to determine the voxel by optimization to determine the 3 unknown parameters (I, 3 unknown parameters (I, α, k) with , k) with projection data projection data

, 6o

  • 640 projections were obtained in 2

640 projections were obtained in 2

  • min. The
  • min. The net

net (i.e. contrast (i.e. contrast – – baseline) baseline) contrast projections were used for contrast projections were used for

PMH 50th Anniversary Conference 16 16

  • ptimization in Matlab for a volume of
  • ptimization in Matlab for a volume of

128x128x40. 128x128x40.

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SLIDE 17

Results: CT and Results: CT and Estimated Estimated CBCT Tissue CBCT Tissue E h t d P f i E h t d P f i Enhancement and Perfusion Enhancement and Perfusion

CT CBCT N t Net Enhancement Perfusion

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SLIDE 18

Conclusions Conclusions Conclusions Conclusions

  • CT originally designed for anatomy

CT originally designed for anatomy CT originally designed for anatomy CT originally designed for anatomy

  • Functional measurement (F, PS, MTT) can be

Functional measurement (F, PS, MTT) can be performed for clinical and preclinical studies performed for clinical and preclinical studies performed for clinical and preclinical studies performed for clinical and preclinical studies

  • On

On-

  • going Advancement in perfusion CT

going Advancement in perfusion CT

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Acknowledgement Acknowledgement Acknowledgement Acknowledgement

Lab members (past/present) Lab members (past/present) Collaborators Collaborators (p p ) (p p )

  • Sunmo Kim

Sunmo Kim

  • Brian Lim

Brian Lim

  • Richard Hill

Richard Hill

  • Mike Milosevic

Mike Milosevic

  • Masoom Haider

Masoom Haider

  • Doug Moseley

Doug Moseley

  • Richard Clarkson

Richard Clarkson

  • Qiulin Tang

Qiulin Tang

  • Rob Bristow

Rob Bristow

  • Anthony Fyles

Anthony Fyles g y g y

  • Young

Young-

  • Bin Cho

Bin Cho

  • Ting

Ting-Yim Lee Yim Lee g

  • Bill Qian

Bill Qian y y y y

  • David Hedley

David Hedley

  • David Jaffray

David Jaffray g

Funding Sources Funding Sources

  • Terry Fox Foundation

Terry Fox Foundation

y

  • Jeff Siewerdsen

Jeff Siewerdsen

  • Young

Young-Bin Cho Bin Cho

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  • Canadian Institute of Health Research

Canadian Institute of Health Research

g