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HST.583 Functional Magnetic Resonance Imaging: Data Acquisition and Analysis
Fall 2006
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HST.583: Functional Magnetic Resonance Imaging: Data Acquisition and Analysis, Fall 2006
Harvard-MIT Division of Health Sciences and Technology
Course Director: Dr. Randy Gollub
Cerebral MR
Perfusion Imaging
2006
A. G. Sorensen MD
MGH-HST Center for Biomarkers in Imaging
A. A. Martinos Center
Massachusetts General Hospital
Harvard Medical School &
Massachusetts Institute of Technology
Division of Health Sciences and Technology
Why Perfusion With MRI?
• A number of neurological illnesses
can be traced to abnormal blood flow
– Ischemic Stroke
– Cerebral Neoplasia
– Many, many others, from Alzheimer’s to MS
• MRI is heavily used already
• It works!
Tracer Measurement over time
Dynamic DSC Perfusion Data
Seconds
MRI image removed due to copyright restrictions.
See Sorensen, A. G., and P. Reimer. Cerebral MR Perfusion Imaging.
Stuttgart, Germany: Thieme Medical Publishers, 2000.
DWI / PWI mismatch vs.
Final Infarct
Four MRI images removed due to copyright restrictions.
See Figure 2 (D, E, G, H) in Sorensen A. G., et al. Radiology 210 (1999): 519-527.
Better
outcomes
with earlier
treatment
Time = Brain
Meta-analysis of 6
trials, 2775
patients
The ATLANTIS, ECASS, and
NINDS rt-PA Study Group
Investigators. "Association of
outcome with early stroke
treatment: pooled analysis of
ATLANTIS, ECASS, and NINDS
rt-PA stroke trials." Lancet 363 no.
9411 (2004): 768-774.
Courtesy Elsevier, Inc., http://www.sciencedirect.com. Used with permission.
Diffusion and Perfusion in
Stroke
• DWI is now widely used
• PWI is in increasing use
– No approved contrast agent
– Most use some sort of timing map (e.g., time to
peak)
– ASL continues its testing / development
• Desmoteplase or other innovations
suggest MRI use may become more
widespread
The so-called ‘ischemic penumbra’ -now accepted (too widely?)
Initial core ?= DWI Lesion
Or maybe CT edema?
Initial PWI Lesion
Follow-up Infarct
(can be variable)
MGH / AGS
MTT ≠ Tissue at Risk
N= 90; see Schaefer et al AJNR 24 (2003): 436
Courtesy of Dr. Pamela Schaefer. Used with permission.
• DWI is core, but PWI not penumbra when PET is used.
Heiss et al Stroke 2004 35(11 Suppl 1)2671
Problems (and Potential Solutions)
• Monitoring Treatment?
• Closing the gap between imaging and clinical outcome
– Location matters!
• MTT as currently calculated may be overestimating
due to delay
– Choice of AIF? (delay, dispersion)
– New CBF approaches: Local AIF, circular deconvolution
• Other markers besides perfusion
– Microvascular status
– Vasomotion
• Imaging Time: still too much time in the scanner
Monitoring Treatment with
Diffusion / Perfusion MRI
• A number of clinical trials have
DWI/PWI now as endpoints
• One new treatment: hyperoxia for
ischemic stroke
• Evidence that treatment with 100%
oxygen at room pressure widens the
therapeutic window
Example: NBO attenuates DWI abnormalities
72-yr woman with right MCA stroke, treated with NBO
Baseline (13 hrs after onset)
Large DWI lesion
Larger MTT lesion
RMCA occlusion
Images removed due to copyright restrictions.
See figure 2 in Singhal, A. B., et al. "A Pilot Study of Normobaric
Oxygen Therapy in Acute Ischemic Stroke." Stroke 36 (2005): 797.
During NBO (after 4 hrs)
DWI lesion smaller (arrows)
Stable MTT
Stable RMCA occlusion
Post-treatment (after 24 hrs)
DWI lesion growing
MTT smaller
Stable RMCA occlusion
Singhal et al MGH
NBO:
mostly
transient
effects!
Images removed due to copyright restrictions.
See figure 1a,c in Singhal, A. B., et al. "A Pilot Study of Normobaric
Oxygen Therapy in Acute Ischemic Stroke." Stroke 36 (2005): 797.
Problems (and Potential Solutions)
• Monitoring Treatment?
• Closing the gap between imaging and clinical outcome
– Location matters!
• MTT as currently calculated may be overestimating due
to delay
– Choice of AIF? (delay, dispersion)
– New CBF approaches: Local AIF, circular deconvolution
• Other markers besides perfusion
– Microvascular status
– Vasomotion
• Imaging Time: still too much time in the scanner
Lesion Size Alone Correlates
Moderately
• RANTTAS (Stroke 1999 30:293-298):
Outcome measure
All infarcts (95% CI)
Visible infarcts only (95% CI)
BI (n=150)
0.43 (0.28-0.58)
0.46 (0.29-0.64)
GOS (n=170)
0.53 (0.40-0.65)
0.59 (0.47-0.71)
NIHSS (n=131)
0.54 (0.41-0.68)
0.56 (0.40-0.71)
Mortality (n=191)
0.31 (0.18-0.45)
0.32 (0.16-0.49)
Figure by MIT OpenCourseWare.
Courtesy of Lippincott Williams & Wilkins. Used with permission.
• ASPECTS (Lancet 2000 355:1670): r=0.56
Why doesn’t imaging better
predict / improve outcome?
• Specificity of techniques
– Not all lesions are equal
• The Real Estate factor:
–Location
–Location
–Location
This is in part because location
matters…
Day 8 NIHSS = 11
Volume ~ 2 cm3
Day 8 NIHSS = 2
Volume ~ 2 cm3
Atlas-based approach
markedly improves
imaging-based
predictions of outcome
(n=46, p<0.01)
30
R=0.53
Hybrid Atlas scores (predictions)
Volume scores (predictions)
Menezes / Ay /
Martinos - MGH -HST
30
25
20
15
10
5
0
0
5
10
15
Measured NIHSS score
20
25
R=0.82
25
20
15
10
5
0
0
5
10
15
20
25
Measured NIHSS score
Figure by MIT OpenCourseWare.
Problems (and Potential Solutions)
• Monitoring Treatment?
• Closing the gap between imaging and clinical outcome
– Location matters!
• MTT as currently calculated may be overestimating
due to delay
– Choice of AIF? (delay, dispersion)
– New CBF approaches: Local AIF, circular deconvolution
• Other markers besides perfusion
– Microvascular status
– Vasomotion
• Imaging Time: still too much time in the scanner
Global versus local AIF
Lorenz / Benner / Sorensen - Martinos MGH + HST
Lorenz, C., et al. "Automated Perfusion-Weighted MRI Using Localized Arterial Input Functions.“
Journal of Magnetic Resonance Imaging 24, no. 5 (2006): 1133-1139.
Copyright © 2006 Wiley-Liss Inc. Reprinted with permission of John Wiley & Sons., Inc.
Estimation of CBF vs. AIFs
Estimation of CBF vs. AIFs
Global Ipsi
Global Contral
Local
Follow-up
Lorenz / Benner / Sorensen - Martinos MGH + HST
Lorenz, C., et al. "Automated Perfusion-Weighted MRI Using Localized Arterial Input Functions.“
Journal of Magnetic Resonance Imaging 24, no. 5 (2006): 1133-1139.
Copyright © 2006 Wiley-Liss Inc. Reprinted with permission of John Wiley & Sons., Inc.
Lorenz, C., et al. "Automated Perfusion-Weighted MRI Using Localized Arterial Input Functions.“
Journal of Magnetic Resonance Imaging 24, no. 5 (2006): 1133-1139.
Copyright © 2006 Wiley-Liss Inc. Reprinted with permission of John Wiley & Sons., Inc.
Problems (and Potential Solutions)
• Monitoring Treatment?
• Closing the gap between imaging and clinical outcome
– Location matters!
• MTT as currently calculated may be overestimating
due to delay
– Choice of AIF? (delay, dispersion)
– New CBF approaches: Local AIF, circular deconvolution
• Other markers besides perfusion
– Microvascular status
– Vasomotion
• Imaging Time: still too much time in the scanner
MRI Measure of Vasomotion
„
Shot-to-shot variability of SI in MRI time series due to noise:
Non-physiological (e.g., thermal, scanner)
§
Physiological (e.g., cardiac, respiratory, vasomotion)
§
SI
FT
Time (Image #)
Hz
Wang / Martinos MGH -HST
MRI Measure of Vasomotion
„
SI
Noise quantified via standard
deviation (SD) or variance
maps
„No
spatial distribution for
non-physiological noise
Time (Image #)
SD Map
Rescaled
®Regional
differences in
SD reflect physiological
noise
„CSF:
cardiac, respiration
„Parenchyma:
vasomotion
Methods
„
Subjects: 32 acute stroke patients
„
MRI (1.5 T): • Acute Perfusion: <12 h, TR=1.5s, 1.7 mm resolution
• Follow-up T2: >5 d
„
CBF and CBV maps calculated from PWI
„
Pre-bolus PWI (~15 images) used to calculate SD maps
pre-bolus
Wang / Martinos MGH -HST
SD Differences in Normal Tissue
„
SD-PWI differences seen in normal tissue regions
„
Normal white SD < normal gray SD (31 of 32 patients)
DWI
CBF
CBV
Gray
F/U T2
White
SI
Wang / Martinos MGH -HST
Image #
SD
Image #
See: Wang, H. H., A. G. Sorensen, et al. J Magn Reson Imaging 27 no. 4 (2008): 866-71.
SD Differences in Ischemia
DWI
CBF
CBV
F/U
T2
SD
SI
Image #
„
®
No clear boundary with which to draw outlines
Applied CBF, CBV lesion outlines to SD maps
See: Wang, H. H., A. G. Sorensen, et al. J Magn Reson Imaging 27 no. 4 (2008): 866-71.
Problems (and Potential Solutions)
• Monitoring Treatment?
• Closing the gap between imaging and clinical outcome
– Location matters!
• MTT as currently calculated may be overestimating
due to delay
– Choice of AIF? (delay, dispersion)
– New CBF approaches: Local AIF, circular deconvolution
• Other markers besides perfusion
– Microvascular status
– Vasomotion
• Imaging Time: still too much time in the scanner
A Key to Speeding Up Scans?
Photos removed due to copyright restrictions.
See, for example, http://www.nmr.mgh.harvard.edu/~fhlin/reprints/abstracts/ismrm2005_96channel_array.pdf
Why Perfusion MRI In Cancer?
• Correlation of angiogenesis with
tumor grade
• Perfusion measures capillary
hemodynamics, which may in turn
reflect angiogenesis
• Measure:
CBV = cerebral blood volume
CBF = cerebral blood flow
The first in vivo images of tumor
angiogenesis
Image removed due to copyright restrictions.
American Journal of Roentgenology
1939 42:891-899
Ide AG, Baker NH, Warren, SL. Vascularization of the Brown Pearce rabbit epithelioma transplant as seen in
the transparent ear chamber
Tumor Perfusion MRI:
Two basic types
• Dynamic Susceptibility Contrast MRI
– Traditional PWI like in stroke
– First pass of Gd, T2 or T2* imaging
– CBV, CBF, plus others like MTT, permeability, etc.
• Dynamic Contrast Enhanced MRI
– Newer
– T1-based
– Permeability
35 year old male with 3 years of
intermittent headache and
intermittent speech difficulties
T2 FSE
T1 post Gd
Dynamic Susceptibility Contrast
MRI - using Gd as T2 agent
MRI image removed due to copyright restrictions.
See Sorensen, A. G., and P. Reimer. Cerebral MR Perfusion Imaging.
Stuttgart, Germany: Thieme Medical Publishers, 2000.
70% Oligodendroglioma, 30%
Grade 3 astrocytoma
MRI image removed due to copyright restrictions.
See Sorensen, A. G., and P. Reimer. Cerebral MR Perfusion Imaging.
Stuttgart, Germany: Thieme Medical Publishers, 2000.
High Grade Glioma
MRI image removed due to copyright restrictions.
See Sorensen, A. G., and P. Reimer. Cerebral MR Perfusion Imaging.
Stuttgart, Germany: Thieme Medical Publishers, 2000.
Low Grade Glioma
.
26 year old female with III/IV
glioma
MRI image removed due to copyright restrictions.
See Sorensen, A. G., and P. Reimer. Cerebral MR Perfusion Imaging.
Stuttgart, Germany: Thieme Medical Publishers, 2000.
rCBV and 18FDG over time
Pre XRT
6 weeks post XRT
5 months post XRT
Another potential maker: Mean
SE EPI
Vessel Radius
0.2 mmol/kg
Signal
change
30.
0
25.
0
20.
0
15.
0
10.
0
5.
0
0.
0 1.
0
Gd-DTPA
GE, Sim
GE, Exp
SE, Sim
SE, Exp
Vessel Radius
(µm)
10.
0
FLASH (GE)
Iron Oxide
Gradient Echo versus Spin Echo EPI:
simultaneous acquisition approach
3.0 Tesla, TR 1.5s, TE for GE: 28, TE for SE: 105
0.2 mmol/l Gd-DTPA.
GE CBV
SE CBV
GE vs SE
DSC
Pilocytic
astrocytoma
4.4 : 1
tumor/white on
GE
T1 p Gad
vs 1.75 : 1
tumor/white on
SE
M Pescitides /
Martinos - MGH -HST
Ratio Map
DCE MRI
•Dynamic Contrast Enhanced MRI
•Rapid imaging during small dose of Gd
•T1 based, not T2
•Attempts to map “permeability”
•Analysis: analytic versus empiric (‘curvology’)
•Popular in assessing drug therapy
Sample DCE Time Course
Injection at about 1.5 times real speed
Images every ~5 seconds
Choroid Plexus
Cortex
Sub-cutaneous fat
Example Mapping Permeability
(“Ktrans ”)
Day -2
Day 1
Day 26
Post Gd and Ktrans both show change; Ktrans will quantify
Ktrans:
3T TimTrio
Day -5
Day -2
Day 1
(second baseline - note AutoAlign)
Day 26
MGH-Martinos
Mechanistic Insights from MRI?
• Testing the “Vascular Normalization” hypothesis
• Blocking VEGF should result in:
– Smaller vessels
– Less permeability
– Less edema
– Decreased mass effect
– Probably no survival benefit without combination therapy, though…
Vascular Normalization after Anti-angiogenic treatment
Winkler et al, Cancer Cell 6 no. 6 (2004): 553-563
Courtesy Elsevier, Inc., http://www.sciencedirect.com. Used with permission.
Summary
• Perfusion MRI: Active, and still
going strong
• New developments to watch out
for:
• Vasomotion
• Therapy monitoring (stroke, tumor)
• Location
Acknowledgements
• Larry Wald, Anders Dale, Bruce Rosen, and
many students, faculty, and staff of the HST
Martinos Center
Special Thanks to:
Ona Wu
Timothy Reese
Thomas Benner Bill Copen
Suzanne Komili Mette Wiegell
Raymond Huang Tara Ullrich
and many, many more...
Chris Wiggins
Thierry Huisman
Ruopeng Wang
Dave Tuch
Andreas Potthast
Takashi Yoshiura
Megan Salhus
Van Wedeen