Concepts, Applications, and Requirements for Quantitative SPECT/CT - - PDF document

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Concepts, Applications, and Requirements for Quantitative SPECT/CT

Eric C. Frey, Ph.D. (efrey@jhmi.edu)

Division of Medical Imaging Physics Russell H. Morgan Department of Radiology and Radiological Science Johns Hopkins University

Conflict of Interest Disclosure

Under a licensing agreement between the GE Healthcare and the Johns Hopkins University, Eric Frey is entitled to a share of royalty received by the University on sales of iterative reconstruction software used to obtain some results in this presentation. Eric Frey is a co-founder of Radiopharmaceutical Imaging and Dosimetry, LLC. This company was founded to provide quantitative imaging and dosimetry service to developers

• f radiopharmaceutical therapy agents.

These interests have been disclosed and are being managed by the Johns Hopkins University in accordance with its conflict of interest policies.

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Acknowledgements

• Funding: NIH Grants

– R01 EB 000288 – R01 CA 109234 – R01 EB 000168 – U01 CA 140204

• People

– Bin He, Ph.D. (now at New York Hospital) – Yong Du, Ph.D. – Na Song, Ph.D. (Now at Montefiore Medical Center) – Lishui Cheng – Xing Rong – Nadège Anizan, Ph.D. – George Sgouros, Ph.D.

Outline

• Introduction to SPECT
• Applications of Quantitative SPECT
• Requirements for Quantitative SPECT
• Obstacles to Achieving Standardization

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Single-Photon Emission Computed Tomography (SPECT)

γ-rays Gamma Camera Imaging Agent Gamma Camera Gamma Camera

Two-Camera SPECT/CT Systems

X-ray Tube X-ray Detector

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Gamma Cameras Matrix Formulation of Image Reconstruction

3D Activity Distribution Image Projection Matrix Mean Projection Data Measurement Noise (Quantum, Poisson Distributed) Reconstructed image (estimated activity distribution image) ‘Inverse’ of Projection Matrix

Projection Matrix C is

• Large (~4x1012 elements)
• Ill-Conditioned
• Patient-dependent

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Computed Tomography

p t,θ

( ) =

a x,t

( )δ ycosθ − xsinθ − t ( )dxdy

∫∫

θ y x p(t,θ) t a(x,y) This can be inverted analytically. The solution is known as Filtered Backprojection.

Physical Image Degrading Factors

• Attenuation
• Scatter
• Collimator-Detector Response (CDR)

– Geometric response – Septal penetration and scatter responses

• Partial Volume Effects
• Statistical Noise

}

Effects of high-energy emissions

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Ideal Projection from Point Source

Source Ideal Collimator

Attenuation in Patient

Absorbed Source Ideal Collimator Scattered

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Effects of Attenuation

• Without attenuation compensation,

sources at depth appear dimmer

• Reduces quantitative accuracy

Phantom FBP Reconstruction (no attenuation compensation)

Object Scatter

Scattered Source Ideal Collimator Unscattered Multiply Scattered Absorbed

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Quantitative Effects of Scatter

0.0 500.0 1000.0 1500.0 2000.0 2500.0 3000.0 8 16 24 32 40 48 56 64 Phantom Primary Primary+Scatter Pixel Number Reconstructed Intensity

Phantom Unscattered Scatter + Unscattered

Collimator-Detector Response (CDR)

Source Real Collimator Geometrically Collimated Septal Penetration Septal Scatter

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Properties of the Full CDR

I-131 Point Source MEGP Collimator HEGP Collimator Distance from Collimator Face 5 cm 10 cm 15 cm 20 cm 30 cm T

• tal detected counts are a function of distance

364 keV

Effects of CDR on Spatial Frequencies

• Analagous to spatially varying low-pass

filter

0.0 0.2 0.4 0.6 0.8 1.0 1.2 0.5 1 1.5 2 LEHR LEGP GTF Spatial Frquency (cm-1)

0.2 0.4 0.6 0.8 1 0.1 0.2 0.3 0.4 0.5 Relative Magnitude Frequency (cycle/pixel)

Rectangular, νm=0.5 Butterworth, νm=0.23, n=6 Hann, νm=0.5

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Effect of CDR on SPECT Images

Point Source Phantom FBP Reconstruction from Projections with LEHR Collimator 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 50 100 150 200 250 Phantom Reconstruction Image Intensity (Arbitrary Units) Pixel

Partial Volume Effects

Phantom Reconstruction

Spill Out Spill In

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Statistical (Quantum) Noise

Mean 2 kcounts 8 kcounts 32 kcounts 128 kcounts Described by Poisson Distribution

Poisson Noise

• Counts in pixels

are independent random variables

• Noise has equal

power at all frequencies

• Image has less

information at high frequencies due to CDR

0.0 0.2 0.4 0.6 0.8 1.0 1.2 0.5 1 1.5 2

LEHR LEGP

GTF Spatial Frquency (cm-1)

Noise power Spectrum: level depends on counts in image

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23

Effect of Poisson Noise on SPECT Images

• Ramp filter used in FBP amplifies high

frequencies

• Combine with low-pass to reduce high this

effect

0.1 0.2 0.3 0.4 0.5 0.1 0.2 0.3 0.4 0.5 Relative Magnitude Frequency (cycle/pixel)

Rectangular, νm=0.5 Ramp-Butterworth, νm=0.23, n=6 Ramp-Hann, νm=0.5 24

Effect of Poisson Noise FBP Reconstruction

• Ramp filter amplifies high frequencies
• Use low pass filter to reduce high

frequency noise

Noise Free FBP Ramp FBP w/ Ramp & Butterworth

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Reconstruction-Based Compensation

Initial Estimate New Estimate Project Each Angle Computed Projections Measured Projections Model Update Estimate Cost Function Compare Computed & Measured

Applications of Quantitative SPEC/CT

• Radiopharmaceutical Therapy Treatment

Planning (absolute, lateral)

• Diagnosis (relative, lateral)
• Response to Therapy (relative,

longitudinal)

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Radiopharmaceutical Therapy (RPT)

n Agents (e.g., monoclonal

antibodies, peptides, microspheres) that target tumors

n Bound to radionuclides whose

emissions can kill tumor cells

n Crossfire effect n Bystander effect

n Optimal dose is patient dependent n Treatment planning to determine

administered activity

Common Therapeutic Radionuclides for TRT

Radionuclide Halflife (hr) β- Energy (MeV) γ Energy (keV) (% yield) I-131 192.5 0.6 0 364 (82), … Y-90 64 .0 2.28 none Sm-153 46.3 0.81 103 (30), … Lu-177 161.5 0.50 208 (11), … Re-188 17.0 2.12 155 (15), …

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TRT Treatment Planning Flow Chart

Administer Planning Agent Measure Distribution

• ver Time

Calculate Organ and Tumor Doses Calculate Therapeutic Activity Administer Therapeutic Quantity

Cumulated Activity and Residence Time

 A: Cumulated activity (MBq ⋅sec) A

0 : Injected activity (MBq)

τ : Residence Time (sec)

 A= A t

( )dt

t

∫

= A

0τ

Activity A(t) (MBq)

 A

Time t (sec)

where τ =  A / A

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SPECT/CT VOI Activity Estimation

SPECT Reconstruction & Convert to Activity Sum Activity in VOI SPECT Proj. CT Total Liver Activity

Measurement Estimate

SPECT Residence Time Estimation

Residence Time CT SPECT Proj. Curve Fitting SPECT Activity Estimation

0 hr 4 hr 24 hr 72 hr 144 hr

0.02 0.04 0.06 0.08 0.1 0.12 50 100 150 Time (hours) ( )

A t A

• rgan

0.02 0.04 0.06 0.08 0.1 0.12 50 100 150 Time (hours)

( )

A t A

• rgan

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In-111 QSPECT

• 5%
• 3%
• 1%

1% 3% 5% QSPECT % Error in Residence Time Estimate (Estimated-True)/True *100% Heart Lungs Liver Kidneys Spleen Reconstructed using OS-EM w/attenuation, scatter, CDR and partial volume compensation 50 noise realizations Error bars show standard deviations of activity estimates due to quantum noise Precision better than accuracy for most

• rgans

Heart Lungs Liver Kidneys Spleen Marrow He B, Du Y , Song XY , Segars WP , Frey EC. A Monte Carlo and physical phantom evaluation of quantitative In-111SPECT. Phys Med Biol. 2005;50(17):4169-85.

• 20%
• 18%
• 16%
• 14%
• 12%
• 10%
• 8%
• 6%
• 4%
• 2%

0% 5 10 15 20 25 30 35 40 45 50 # of Iterations (24 subsets/iteration) % Error in Activity Estimates Tumor 3 (2.2 cm, ratio 5.2) Tumor 9 (2.2 cm, ratio 10.5)

• 2.2 cm diameter tumors

Precision for Small Objects

T9 T3

OS-EM w/attenuation, CDR and scatter compensation (no PVC)

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• 90%
• 85%
• 80%
• 75%
• 70%
• 65%
• 60%
• 55%
• 50%
• 45%
• 40%

5 10 15 20 25 30 35 40 45 50 # 0f Iterations (24 subsets/iteration) % Error in Activity Estimates Tumor 4 (0.9 cm, ratio 12) Tumor 2 (0.9 cm, ratio 11)

• 0.9 cm diameter tumors

Quantification of Very Small Objects

T2 T4

OS-EM w/attenuation, CDR and scatter compensation (no PVC)

§ 128 projection views § Acquisition time: 40s / view

Heart Chamber Myocardium Large Sphere Small Sphere Background Volume (ml) 59.7 115.3 17.5

(r =1.61 cm)

5.7

(r =1.11 cm)

9580 Activity(mCi) 0.562 0.471 0.136 0.044 8.15 Activity concentration (mCi/μl) 9.38 4.08 7.77 7.72 0.851

I-131 Physical Phantom

Philips Precedence SPECT/CT system with HEGP collimator

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I-131 QSPECT

(%) Heart Large sphere (r = 1.61 cm 17.5 ml) Small sphere (r = 1.11 cm 5.7 ml) AGS

• 15.21
• 26.12
• 32.72

ADS 4.75

• 17.63
• 25.77

ADS+Dwn+

• 5.20
• 21.10
• 31.17

ADS+Dwn+PVC*

• 2.88
• 15.49
• 19.28

Percent errors of activity estimates for Anthropomorphic torso phantom

50 iterations 24 subsets/iteration

AGS ADS ADS + Dwn ADS+Dwn+PVE

+DWN=model-based downscatter compensation

*PVC=reconstruction-based PVC compensation

Y-90 QSPECT

38

• Physical phantom experiment

– Elliptical phantom with 3 spheres – Philips Precedence SPECT/CT: HEGP – Acquisition time per view: 45s/view – Crystal thickness: 9.525 mm – 128 projection views over 360o – Matrix size per view: 128*128 – Pixel size: 4.664mm – VOIs defined from CT

38

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Y-90 Physical Phantom Study

39 39

Error = (EstimatedActivity – TrueActivity) / TrueActivity ×100%

5.5 cm diameter sphere 3.3 cm diameter sphere 1.5 cm diameter sphere % Error

• 7.0%
• 9.7%
• 10.2%

Quantitative SPECT Imaging in Diagnosis and Monitoring of Parkinsonism

• Neurotransmission in dopaminergic system

Ø Commercially available agent for SPECT (I-123 FP-CIT)

DAT D2R

T atsch, Nucl. Med. Commun. (2001) 22, p819-827.

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SPECT Imaging in Parkinsonism

Imaging assessment:

Ø Visual inspection Ø Quantitative studies

üDisease degree, progression, etc.

Huang, et. al, Euro. J. Nucl. Med. (2004) 31, p155-161.

Normal Stage I PD Stage II PD Stage III PD Stage IV PD Stage V PD

Quantitative brain SPECT Imaging

Huang, et. al, Euro. J. Nucl. Med. (2004) 31, p155-161.

T c99m-TRODAT imaging of Parkinson’s disease in different HYS stages

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Non-specific background uptake Left putamen Right putamen Left caudate Right caudate

• GE Millennium VG/Hawkeye

(5/8” thick crystal)

• LEHR Collimator
• 128 views/360°, 128*128

projection w/ 0.24 cm pixels

• CT attenuation maps
• Manually defined VOIs using

registered MR Images

• Activity concentrations:
• Bkg: 1

10 kBq/ml

• Left Caudate: 212 kBq/ml
• Left Putamen: 154 kBq/ml
• Right Caudate: 1770 kBq/ml
• Right Putamen: 222 kBq/ml

Accuracy of Activity Quantitation: I-123 Brain SPECT

RSD Striatal Phantom

Y . Du, B.M.W. Tsui, and E.C. Frey, "Model-based compensation for quantitative I-123 brain SPECT imaging," Phys Med Biol, 51(5): 1269-1282, 2006

Accuracy of Activity Quantitation: I-123 Brain SPECT

OS-EM w/ Attenuation Scatter & CDRF Compensation Post-Reconstruction pGTM PVC

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Requirements for Quantitative SPECT/CT

• Quality Control/Calibration
• Acquisition
• Reconstruction/Processing

Quality Control & Calibration

• Activity meter calibration and QC
• Routine Camera and CT QC
• Registration of SPECT and CT
• Calibration of QSPECT imaging

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Calibration Factor Measurement

• Planar calibration (sensitivity)

– Static image of standard source in air at known distance from camera – Sensitivity = std. counts/(std. activity * acq. time)

• Phantom-based Calibration

– Acquire SPECT study of object with known activity – Reconstruct and compute counts – Scale factor is true phantom activity/image counts – Should be consistent with planar calibration for “ideal” reconstruction/compensation

Limitations of Planar Calibration Quantitative Y-90 SPECT

• SPECT Calibration

Scanner Calibration Factor GE Discovery 670 1.21-1.23 Siemens Symbia 1.15-1.18 Phantom Dimensions Large Uniform Cylinder 20 cm diameter Small Uniform Cylinder 4.6 cm diameter Sphere in cold Elliptical Phantom 5.5 cm diameter sphere in 32x20 phantom

• Planar Calibration

Scanner Calibration Factor GE Discovery 670 1.14 Siemens Symbia 1.08

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Variations in Calibration Factor

1.8%

• Largest source of variation (77% of variance) was due to inter-source effects
• Suggests that consistent preparation and measurement of source activity is key

Acquisition Parameters

• Collimator selection
• Injected activity/acquisition time
• Voxel size
• Number of views
• Energy windows

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Reconstruction/Compensation

Factor Large Object Small Object Commercially Available Attenuation Yes Yes Yes Scatter Yes Yes Energy-based: yes Model-based: limited Geometric Response Compensation No Yes Yes Full CDR Compensation (High Energy) Desirable for HE, ME radionuclides Desirable for HE, ME radionuclides No Partial volume compensation No Yes No Noise Regularization No Yes? Filtering

Obstacles to Standardization

• Radioactivity measurement

– Variety of devices – Variety of radionuclides

• Compensation Methods

– Many systems are SPECT-only – Variety of imaging hardware – Variety of image reconstruction and compensation methods

• Clinical Practice

– Variation in protocols – Habits

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Summary

• Quantitative SPECT/CT is achievable now
• There are a number of emerging clinical

applications

• Limited commercial availability of state-of-

the-art reconstruction and compensation methods

• There is a need for standardization of

protocols and methods