8/2/2012

1

Molecular Imaging in Radiation Oncology: What and Where?

Robert JerajAssociate Professor of Medical Physics, Human Oncology,

Radiology and Biomedical Engineering

Imaging and Radiation Sciences Program

University of Wisconsin Carbone Cancer Center, Madison, WI

rjeraj@wisc.edu

Current state of affairs…

Hong and Harari, 2005

FDG PET/CT or CT?

GTVPET < GTVCT

75%

GTVPET > GTVCT

20%

Paulino et al 2005, Int J Radiat Oncol Biol Phys 61: 1385

8/2/2012

2

FDG PET/CT or CT?

“Physicians B and C used contradictory techniques. Physician B would

contour the suspected GTV on the basis of the CT but often totally disregard this information when given the PET information and contour

only PET avidity. Physician C, on the other hand, would contour the

suspected GTV on the basis of the CT, and then, for the fusion contour, draw the union of the CT contour and PET avidity.”

“Physician A’s method tended to be a mixture of the methods of Physicians B and C. Often, Physician A would “split the difference” and

contour the compromise between the drawn CT contour and PET avidity.”

Riegel et al 2006, Int J Radiat Oncol Biol Phys 65: 726

Whatever, adding PET info HELPS!

Steenbakkers et al 2006, Int J Rad Oncol Biol Phys 64: 435

CT PET/CT

50% (30%-70%) decrease of the contouring standard deviation!

How to increase reproducibility?

� AAPM TG211 - Classification, Advantages and Limitations of the Auto-Segmentation Approaches

for PET

– Manual segmentation is NOT the way to go!

– Auto segmentation

• Thresholding (Erdi 1997, Paulino 2004)

• Gradient-based (Geets 2007)

• Region-growing (Drever 2006)

• Feature-based (Yu 2009)

• …

– Reference benchmark dataset

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3

Auto-segmentation, but which one?

Troost et al 2010, Radiother Oncol, 96(3): 328

CTVisual

SUV40%

SUV50%

SUV2.5

SBR

There are inherent uncertainties

SUV10

5

0

256, 2 iterations 256, 2 iterations 128, 2 iterations 128, 2 iterations 128,4 iterations

3 mm filter width 6 mm filter width 3mm filter width 6 mm filter width 6 mm filter width

256, 2 iterations 256, 2 iterations 128, 2 iterations 128, 2 iterations 128,4 iterations

3 mm filter width 6 mm filter width 3mm filter width 6 mm filter width 6 mm filter width

2D

OS

EM

3

D IT

ER

SUV measure CV (%) min - max (%)

SUVmax9 4 - 15

SUVmean5 1 - 8

B C D E F G I J K L M N-100

-50

0

50

100

150

2D Acquisition

Threshold-based

Gradient-based

Region-growing

Vo

lum

e V

ari

ati

on

s (

%)

Segmentation Techniques

128x128 Grid-Size256x256 Grid-Size

3D Acquisition

Impact of post-reconstruction filter width on target volumes

Impact on volume definition

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4

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

1

2

3

4

5

Av

g. M

arg

in A

xia

l P

lan

e (

mm

)

Patients 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

5

10

15

20

25

30

Ma

x.

Marg

in A

xia

l P

lan

e

(mm

)

Patients

Marginplane

Mean ±SD (mm)

Maximum (mm)

Avg. Max ±SD (mm)

Maximum (mm)

Axial 1.0 ± 0.4 1.8 8.4 ± 6.0 26.0

Coronal 0.5 ± 0.3 1.2 10.6 ± 6.1 26.7

Sagittal 0.5 ± 0.3 1.2 10.2 ± 5.3 22.1

Need for imaging margins

Is imaging itself enough?

Thiagarajan et al 2012, Int J Radiat Oncol Biol Phys, 83: 220

CT MRI PET

CT+PETCT+MRI CT+MRI+PET+Physical examination

CT+MRI+PET+P.E. > CT+PET or CT+MRICI (CT+PET, CT+MRI) = 0.62

Using FDG PET for target definition helps

because:

20%

19%

21%

20%

20% 1. It better defines where the tumor is

2. Increases consistency of target definition

3. It will make hospital administrators happy (more

revenue)

4. Doctors think so

5. It actually doesn’t help

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5

And here comes DOSE PAINTING…

Ling et al 2000, Int J Rad Oncol Biol Phys 47: 551

Dose painting workflow

Tumorbiology

Biological imaging1

Bio-basedprescription2

Planning & delivery3

Clinicaloutcome4

What are extra challenges?

Microscopy → Macroscopy

1 mm 5 cm

Proliferation

Hypoxia

Microscopy PET/CT imaging

Courtesy of A. van der Kogel, Nijmegen, NL

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Spatial resolution

40 µm 0.5 mm 1 mm 2 mm

We do not see small heterogeneities

0 5 10 15 20 25 300.0

0.2

0.4

0.6

0.8

1.0

1.2

Reco

ve

ry C

oe

ffic

ien

t

Sphere Diameter (mm)

Partial volume effects Recovery coefficients

Extraction of biological information

1 min

15 min

60 min

FLT PET/CT

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FDG PET/CT(metabolism)

What to dose paint?

FLT PET/CT(proliferation)

Cu-ATSM PET/CT(hypoxia)

FDG PET vs Time-to-progression

FDG SUV measure

Pre-treatmentp-val (N=19)

3 months post RTp-val (N=16)

6 months post RTp-val (N=11)

SUVmean 0.94 0.005 0.0002

SUVmax 0.86 0.017 0.003

SUVpeak 0.90 0.046 0.004

SUVtotal 0.51 0.047 0.006

1 2 3 4

100

200

300

400

Days to P

rogre

ssio

n

Pre FDG SUVmean

1 2 3

0

100

200

300

400

Days to

Pro

gre

ssio

n

3 mo FDG SUVmean1 2 3

100

200

300

400

Days to

Pro

gre

ssio

n

6 mo FDG SUVmean

Pre-treatment 3 months post RT 6 months post RT

Regression analysis

3mo FDG Regression, N=11

β-FDGpre β-FLTpre β-CuPre β-FLTmid β-CuMid

mean 0.15 -0.25 -0.14 0.21 0.47

P-val 0.11 0.01 0.24 0.45 0.001

3mo FDG Regression, N=7

β-FDGpre β-FLTpre β-CuPre β-FLTmid β-CuMid

mean 0.42 -0.23 0.03 0.21 0.25

P-val 0.01 0.35 0.84 0.29 0.13

Sarcomas

Carcinomas

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Which tracer to assess biology?

ATSMCu ATSMCuIIII

⇔

CR O2

H3O+ H2O

RSH

RSCu

ATSMH

I

2⇔ ATSMH2

NR O2

2FRNO FMISO ⇔

-2FRNO •

FRNO

NR

2FRNH

MM

REDOX

compartment

BOUND

compartment

DISSOCIATION

compartment

Bowen et al 2011, Nucl Med Biol, 38:771

pO2 transformation functions

0 1 2 3 4 5 6 7 80

10

20

30

40

50

60

Cu-ATSM model

1 SD CI

Cu-ATSM meas.

Lewis et al. 1999

SUV

PO

2 (

mm

Hg

)

0 1 2 3 4 5 6 7 8

10

20

30

40

50

60

SUV

FMISO model

1 SD CI

FMISO meas.

Lewis et al. 1999

FMISO meas.

Piert et al. 2000

Bowen et al 2011, Nucl Med Biol, 38:771

Cu-ATSM FMISO

0 1 2 3 4 5 660

64

68

72

76

80

84

88

92

Pmid = 3 mmHg, OERmax = 1.4

pH = 7.1

pH = 7.2

pH = 7.3

Pre

scri

bed

Do

se (

Gy

)

Cu-ATSM SUV0 1 2 3 4 5 6

60

64

68

72

76

80

84

88

92

pH = 7.2

Pre

scri

bed

Dose

(G

y)

Cu-ATSM SUV

Prescription function

Cu-ATSM

pH = 7.1

pH = 7.2

pH = 7.3

Dose

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Overall uncertainty in a patient

� Mean uncertainty of 20 % (max 60 %) in prescribed dose to individual patient

0 1 2 3 4 5 660

70

80

90

100

110

120

Pre

scri

bed

Dose

(G

y)

Cu-ATSM SUV

Upper Limit

Average

Lower Limit

Uncertainties in population

Symbol Parameter RangeDose Uncertainty

Mean (Max)

pH Intracellular Acidity 7.1 – 7.3 4 % (10 %)

HP2.5 FitDose Boost vs. Hypoxic

Proportion Function95 % CI 5 % (14 %)

Pmid Half-max Sensitization pO2 2 – 5 mmHg 1 % (2 %)

OERmax

Max Oxygen Enhancement

Ratio1.4 – 3.0 1 % (2 %)

Overall 10 % (17 %)

Patient 20 % (60 %)

(Gerweck 1998)

(Nilsson 2002)

(Chan 2008)

How many patients need dose painting?

� Imaging � 1/12 or 8.3%

� Eppendorf � 6/69 or 8.7%

0 1 2 3 4 555

60

65

70

75

80

85

90

95

Do

se (

Gy)

SUV0 10 20 30 40 50 60

55

60

65

70

75

80

85

90

95

Do

se

(G

y)

pO2 (mmHg)

N = 12 N = 69

Imaging patients Microelectrode patients

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Motion impact on dose painting

Dose painting workflow

Tumorbiology

Biological imaging1

Bio-basedprescription2

Planning & delivery3

Clinicaloutcome4

Micro→Macro

Which biology

Tracer

Extraction of biology

Set-up

Motion

Outcome uncertainties

Heuristic Modeling and Empirical Data

Uncertainty Characterization and Validation

What phenotype should we dose paint?

21%

19%

19%

20%

21% 1. Hypoxia (Cu-ATSM PET)

2. Metabolism (FDG PET)

3. Proliferation (FLT PET)

4. It depends on the histology

5. Whatever we have available in the hospital

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WHAT AND WHERE TO TARGET?

� Using molecular imaging helps in target definition, but still many issues to resolve:

– Choice of molecular imaging

– Image quantification

– Automatic segmentation

– Validation clinical trials

� Molecular imaging-assisted target definition using molecular imaging in qualitative way is the way to go at present!

� Dose painting is an extremely exciting concept, but we are just at the beginning

Response during radiation therapy

Mid-RT CTPre-RT CT

0 10 20 30 40 50 60 70

0

2

4

6

8

10

12

14

16

SU

Vm

ax

Time [days]

Average

FDG PET and radiation therapy

RT

Baardwijk et al 2007, Radiother Oncol, 82: 145.

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FDG PET and radiation therapy

0 10 20 30 40 50 60 70

0

2

4

6

8

10

12

14

16

SU

Vm

ax

Time [days]

Average

Metabolic non-responders

Metabolic responders

RT

Baardwijk et al 2007, Radiother Oncol, 82: 145.

FDG PET and radiation therapy

nSUVpost = nSUVduring- 20%

Kong et al 2007, J Clin Oncol, 25: 3116.

~30 days ~3 months

Radiation induced inflammation

� Radiation induced inflammation is a known effect –temporal and spatial dependence

� Not known how much it is a confounding factor in treatment assessment

� FDG PET shows increased uptake post therapy

FDG PET/CT

3 months post RT

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FDG PET late response

� HNSCC: Negative FDG PET results post chemoRT have a high NPV (95%), but low PPV (50%) (Schöder et al 2009, J Nucl Med, 50:74S)

� NSCLC: 80% decrease in FDG PET SUVmax post chemoRT has 90% sensitivity, 100% specificity, and 96% accuracy for predicting pathologic response (Cerfolio et al 2004, Ann Thorac Surg, 78:1903)

� Rectal cancer: 70% decrease in FDG PET SUVmax post chemoRT has 79% specificity, 81% sensitivity, 77% PPV, 89% NPV and 80% accuracy for predicting pathological response (Caprici et al 2007, Eur J Nucl Med Mol Imaging, 34:1583)

� Esophageal cancer: Mixed results - in adenocarcinomasnegative FDG PET post chemoRT has a high PPV, elsewhere inconclusive (Krause et al 2009, J Nucl Med, 50:89S)

FLT PET and radiation therapy

Everitt et al 2009, Int J Rad Oncol Biol Phys, 75: 1098.

Pre

-tre

atm

en

tM

id-t

rea

tme

nt

(1 w

k o

f X

RT

)

FLT-PET/CT

Application: Treatment adaptation

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Pre

-tre

atm

en

tM

id-t

rea

tme

nt

(1 w

k o

f X

RT

)

FLT-PET/CT

Application: Treatment adaptation

Application: Dose painting

Pre

-tre

atm

en

tM

id-t

rea

tme

nt

Treatment response

Prescription function

Should we use FDG PET for treatment

response assessment?

20%

20%

20%

22%

18% 1. Absolutely

2. Yes, for post-treatment assessment

3. Yes, for early-treatment assessment

4. If there are enough hospital resources

5. If the physician requests it, it doesn’t matter

anyway

8/2/2012

15

WHAT AND WHERE TO ASSESS?

� PET imaging for response assessment in RT still in its infancy, but with some encouraging results– Late FDG PET response assessment has high

predicting value of pathological response in many tumors

– Early FDG PET response assessment limited because of radiation-induced inflammation

– Alternatives, especially early FLT PET response assessment promising for early assessment but lacks clinical validation

� Many applications for assessment (treatment adaptation, dose painting), but much more appealing with early treatment assessment

� Normal tissue assessment should not be forgotten

Thanks to:

� Image-guided therapy group– Vikram Adhikarla

– Tyler Bradshaw– Enrique Cuna– Ngoneh Jallow– Matt La Fontaine

– Paulina Galavis– Stephanie Harmon– Courtney Morrison– Surendra Prajapati

– Urban Simoncic– Peter Scully– Benny Titz– Natalie Weisse

– Koala Yip– Stephen Yip– Former students…

� Funding– NIH, PCF, UWCCC, Pfizer,

AstraZeneca, Amgen, EntreMed

� Medical Oncology/Hematology– Glenn Liu– George Wilding– Mark Juckett– Brad Kahl– Anne Traynor

� Human Oncology– Søren Bentzen– Paul Harari– Mark Ritter

� Radiology– Scott Perlman– Chris Jaskowiak

� Veterinary School– Lisa Forrest– David Vail

� Medical Physics– Rock Mackie– Jerry Nickles– Onofre DeJesus

� Phase I Office