Imaging evaluation of clinical benefit in sarcomas: Dynamic MRI
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Transcript Imaging evaluation of clinical benefit in sarcomas: Dynamic MRI
Imaging evaluation of clinical
benefit in sarcomas: Dynamic MRI
Dr Anwar Padhani
[email protected]
Mount Vernon Cancer Centre
London
Montreal November 2004
Mount Vernon Cancer Centre &
Gray Cancer Institute
Jane Taylor, James Stirling
Gordon Rustin, Sue Galbraith, Kate Lankester,
Andreas Makris, Mei-Lin Ah-See
Ross Maxwell, Gill Tozer
Royal Marsden Hospital &
Institute of Cancer Research
Janet Husband and Martin Leach, David Collins,
James d’Arcy, Simon Walker-Samuel, Carmel
Hayes, Geoff Parker, John Suckling, Ian Judson
I acknowledge other contributors who have provided additional materials of their work in support of this lecture
Dr H Choi, MD Andersen Cancer Cemtre, Houston
Dr WE Reddick, St Jude Children Research Hospital, Memphis
Talk outline
Dynamic MRI – biological basis & quantification
Illustrate utility of dynamic MRI to assess benefit
of therapy in patients with bone sarcomas
– Predict response to neoadjuvant chemotherapy
– Assess activity of residual disease
Biomarker for assessing effects of treatment with
antiangiogenesis/vascular targeting drugs
Biomedical challenges in clinical implementation
specific to patients with sarcomas
Perfusion MR imaging of extracranial tumor angiogenesis. A DzikJurasz, AR Padhani. Top Magn Reson Imaging. 2004;15(1):41-57.
Talk outline
Dynamic MRI – biological basis & quantification
Illustrate utility of dynamic MRI to assess benefit
of therapy in patients with bone sarcomas
– Predict response to neoadjuvant chemotherapy
– Assess activity of residual disease
Biomarker for assessing effects of treatment with
antiangiogenesis/vascular targeting drugs
Biomedical challenges in clinical implementation
specific to patients with sarcomas
Perfusion MR imaging of extracranial tumor angiogenesis. A DzikJurasz, AR Padhani. Top Magn Reson Imaging. 2004;15(1):41-57.
Dynamic contrast enhanced MRI
(DCE-MRI)
Technique where
enhancement of a tissue or
organ is continuously
monitored using MRI after
bolus IV contrast medium
– Low molecular weight contrast
media (<1 kDa)
– Diffuse into extravascularextracellular space (does not
cross cell membranes)
– Experiment lasts a few minutes
7 minutes
Haemangiopericytoma
Data courtesy of David Collins and Ian
Judson, Institute of cancer Research,
London
Basis of dynamic contrast enhanced MRI
T2*W DCE-MRI of Mixed Mullerian Tumour
Typical acquisition 1-2 mins
T1W DCE-MRI of Mixed Mullerian Tumour
Typical acquisition 5-8 mins
T2*W versus T1W DCE-MRI
Evaluation of signal enhancement
during DCE-MRI
Qualitative - shape of signal intensity (SI) data
curve
Semi-quantitative - indices that describe one or
more parts of SI or [Gd] curves
Upslope gradient, max amplitude, washout rate or area
under curve at a fixed time point
True quantitative - indices from contrast medium
concentration changes using pharmacokinetic
modelling
Patterns of enhancement on T1W DCEMRI and histological correlates
Type I
Type II
Type III
(semi-necrotic with
reactive changes)
(viable tumour)
(rapidly proliferating
tumour edge)
kep
(min-1)
= 0.5
kep
(min-1)
= 3.4
kep
(min-1)
(Taylor and Reddick, Adv Drug Del Rev, 2000)
= 8.9
Pharmacokinetic modelling of
T1W DCE-MRI data
Transfer constant (Ktrans)
Extracellular leakage space
(ve) assumed for modelling
Figure cc. Compartments
epmethods*
Rate constant (kep)
K
k
ve
Bolus
injection of
Contrast
medium
trans
Whole body
extracellular
space
Blood plasma
Ktrans
kep
Tumour
extracellular
space (ve)
Renal
Excretion
Modified from Tofts 1995
Quantitative analysis with
pharmacokinetic modelling
Advantages
– Whole curve shape is analysed
– Biologically relevant physiological parameters
– Independent of scanner strength, manufacturer and
imaging routines
– Enables valid comparisons of serial measurements and
data exchange between different imaging centres
Disadvantages
– Data acquisition and analysis is more complex
– Lack of commercial software for analysis
– Models may not fit the data observed
Clinical indications for DCE-MRI in
patients with musculoskeletal lesions
To improve characterisation of lesions*
Monitoring response to treatment
– Conventional treatments
(chemotherapy/physical treatments)
– Novel biological treatments including
antiangiogenic/vascular targeting drugs
Assess activity of residual disease after
definitive treatment
*Ma LD, et al. Radiology 1997; 202(3):739-44
*van der Woude HJ et al. Radiology 1998; 208(3):821-8
*Verstraete KL, Radiology. 1994; 192(3):835-43
Importance of predicting early
tumour response to chemotherapy
If pathological response can be reliably
predicted after a few cycles of neoadjuvant
chemotherapy
– Treatment regimen could be adjusted (early surgery,
cryotherapy, isolated limb perfusion etc)
Pathological response rates may be improved
Changing treatment could increase expense
and exposes patients to greater toxicity
Good response to treatment (99% necrosis)
Baseline
120.00
SI (Baseline Corrected)
100.00
80.00
60.00
40.00
20.00
0.00
0
50000
100000
150000
200000
250000
300000
-20.00
Time (ms)
2 months on treatment
80.00
SUV 13.0
SI (Baseline Corrected)
70.00
60.00
50.00
40.00
30.00
20.00
FDG-PET scans
10.00
0.00
-10.00
0
50000
100000
150000
200000
250000
Time (ms)
Pre-operative
35.00
SUV 2.4
2A
SI (Baseline Corrected)
30.00
25.00
20.00
15.00
10.00
5.00
0.00
-5.00
0
50000
100000
150000
200000
250000
Time (ms)
Courtesy of Dr H Choi, MD Andersen Cancer Center, Houston
Correlation of DCEMRI and necrotic
fraction after
chemotherapy
Dyke JP, et al. Radiology 2003; 228:271-278
Disease-free Survival (%)
Tumors < 56 cm2
100
Prognostic value
of DCE-MRI in
osteosarcomas
kep < 1.167 min-1
80
kep 1.167
min-1
60
40
20
Change in kep as a function of pre-treatment
value. Higher permeability at presentation
results in greater decreases with therapy
0
0
1
2
3
5
4
6
100
80
kep < 1.167 min-1
60
kep > 1.167 min-1
40
20
P = 0.05
0
kep During Therapy (min -1)
Disease-free Survival (%)
Tumors > 56 cm2
2
0
-2
-4
-6
0
1
2
3
Year
4
5
6
Disease free survival for 31 patients stratified by
tumour size and DCE-MRI after 9 weeks of Rx;
0
1
2
3
4
5
6
kep at Presentation (min-1)
Reddick WE, et al. Cancer 2001; 91:2230-2237
7
Disease-free Survival (%)
Tumors < 56 cm2
100
Prognostic value
of DCE-MRI in
osteosarcomas
kep < 1.167 min-1
80
kep 1.167
min-1
60
40
20
Change in kep as a function of pre-treatment
value. Higher permeability at presentation
results in greater decreases with therapy
0
0
1
2
3
5
4
6
100
80
kep < 1.167 min-1
60
kep > 1.167 min-1
40
20
P = 0.05
0
kep During Therapy (min -1)
Disease-free Survival (%)
Tumors > 56 cm2
2
0
-2
-4
-6
0
1
2
3
Year
4
5
6
Disease free survival for 31 patients stratified by
tumour size and DCE-MRI after 9 weeks of Rx;
0
1
2
3
4
5
6
kep at Presentation (min-1)
Reddick WE, et al. Cancer 2001; 91:2230-2237
7
Poor access to contrast before treatment
Baseline
40.00
SI (Baseline Corrected)
35.00
30.00
25.00
20.00
15.00
10.00
5.00
0.00
-5.00
0
50000
100000
150000
200000
250000
300000
Tim e (m s)
SUV 5.9
FDG-PET scans
Poor response to treatment (75% necrosis)
20.00
18.00
SI (Baseline Corrected)
16.00
14.00
12.00
10.00
8.00
6.00
4.00
2.00
0.00
-2.00 0
50000
100000
150000
200000
250000
300000
Time (ms)
Pre-operative
Courtesy of Dr H Choi, MD Andersen Cancer Center, Houston
SUV 8.3
Drugs targeting tumour neovasculature
Permeability
rBV
or rBF
Probably
depends on drug
duration and
dose
Vascular targeting
drugs
Anti-VEGF
drugs
Permeability
rBV
rBF
Time course of Combretastatin
effects on microvasculature
IAP 10 mg/kg
2 hours post
CA4P
10 mg/kg
trans
K
100 mg/kg
125
Relative Change (%)
PreRx
trans
K
IAP 100 mg/kg
100
75
50
25
0
0
5
10
15
20
Time post treatment (hours)
Window chamber view
P22 Carcinosarcoma
B Vojnovic and G Tozer, Gray Cancer Institute
IAP - radiolabelled
iodoantipyrine
25
Morphological & kinetic changes
After 1st dose of CA4P (52mg/m2)
24 hrs
Pre
4 hrs
Post
tra n s
R e la tiv e C h a n g e K
(% )
D o s e m g /m
140
2 0 -4 0 -- -------5 2 ------- -------6 8 ------- -----8 8 ----- -----1 1 4 ----
*
Biologically active dose 52 mg/m2
120
20
0
2
DLT 114 mg/m2
MTD 88 mg/m2
*
*
*
*
-2 0
-4 0
-6 0
4 H o u rs
-8 0
-1 0 0
2 4 H o u rs
4 4 98 5 %
9 2C9 I3 f1o3r2 a3n3 i9n d2 3i v2i 5d 2u 8a 3l 0 9 1 2 1 4 1 6 1 7 1 9 2 0 2 1
P aGalbraith
t ie n t SM,
N uetmal.bJeClin
r Oncol – 2003;21:2831-42.
Galbraith SM, et al. J Clin Oncol – 2003;21:2831-42
Phase I goals and DCE-MRI
achievements in the CA4P study
Achievement
Goal
Modulation of vascular kinetics
+
Dose response relationship
+ (threshold)
Identify therapeutic window
+
Drug exposure kinetic response
relationship
+
Galbraith SM, et al. J Clin Oncol – 2003;21:2831-42
Dose response in Ki for PTK787/ZK in
colorectal cancer on Day 2
160
No maximum
tolerated
dose was
reached
140
Ki (% Baseline)
SEM bars, all
colorectal
liver
metastases
25 patients with
metastatic colon cancer
evaluated at baseline,
on day 2 and 28
120
100
80
60
40
20
0
50
300
500
750
1000
1200
Dose (mg)
Morgan, B., et al., J Clin Oncol, 2003. 21(21): p. 3955-3964.
Phase I goals and DCE-MRI
achievements in the PTK787/ZK study
Goal
Modulation of vascular kinetics
Achievement
+
Dose response relationship
+ (threshold)
Identify therapeutic window
+ (no MTD)
Drug exposure kinetic response
relationship
?
Morgan, B., et al., J Clin Oncol, 2003. 21(21): p. 3955-3964.
Conclusions
Dynamic MRI provides unique information on the
vascular characteristics of tumours
DCE-MRI can predict extent of histological
response to chemotherapy in patients with
osteosarcomas/Ewing tumours
Intriguingly, DCE-MRI may inform on drug access
(? predict responsiveness) and patient prognosis
Acts as a biomarker that provides
pharmacodynamic (PD) information in early trials
of antivascular drug and should be used for
evaluating combination therapies in sarcomas
Dynamic MR imaging of tumor perfusion: approaches and biomedical challenges.
DJ Collins, AR Padhani. IEEE Engineering in Medicine and Biology Magazine 2004