Multimodality & 4 D Imaging

Multimodality & 4D Imaging:Registration and Fusion for

Treatment Planning and Delivery

Multimodality & 4D Imaging:Registration and Fusion for

Treatment Planning and Delivery

Marc L Kessler, PhD The University of MichiganMarc L Kessler, PhD The University of Michigan

ASTRO 2007 - 49th Annual MeetingWednesday, October 31, 2007

1:30 – 2:45 PM

ASTRO 2007 - 49th Annual MeetingWednesday, October 31, 2007

1:30 – 2:45 PM

Laura A Dawson, MD Princess Margaret HospitalLaura A Dawson, MD Princess Margaret Hospital

DisclosuresDisclosures

• Research Grant- Varian Medical Systems

ObjectivesObjectives

Understand the basic mechanics of multimodality and 4D image registration techniques

Understand the different techniques used to combine, display and interact with multimodality and 4D image and dose data

Understand the clinical use and limitations of these techniques for Tx planning, Txdelivery and plan adaptation

Understand the basic mechanics of multimodality and 4D image registration techniques

Understand the different techniques used to combine, display and interact with multimodality and 4D image and dose data

Understand the clinical use and limitations of these techniques for Tx planning, Txdelivery and plan adaptation

Marc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

OutlineOutline

Motivation

Mechanics!

Clinical Use

Motivation

Mechanics!

Clinical Use


MotivationMotivation

Precision radiation therapy requires accurate delineation of the tumor and normal tissues in the planning phase and accurate localization of these structures during the delivery phase

Precision radiation therapy requires accurate delineation of the tumor and normal tissues in the planning phase and accurate localization of these structures during the delivery phase

…with the aid of imaging…with the aid of imaging


MotivationMotivation

DeliveryDelivery

ImagingImaging

PlanningPlanningImagingImaging

entireentireOptimization of the radiotherapy process requires that we anticipate, measure & adapt to changes in the patient

Optimization of the radiotherapy process requires that we anticipate, measure & adapt to changes in the patient

on-lineon-line

off-lineoff-line


Multimodality TargetingMultimodality TargetingGregoire / St-LucGregoire / St-Luc

??

We now have many cameras available… which provide complementary data! We now have many cameras available… which provide complementary data!


X-ray CTX-ray CT MRIMRI Nuc MedNuc Med

??

??

Normal TissuesNormal Tissues Target VolumesTarget VolumesMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

Repeat ImagingRepeat Imaging

Balter / UMBalter / UM

4-D Imaging4-D Imaging

… assess motion… assess motion


Varian OBI™Varian OBI™

Elekta Synergy™

Elekta Synergy™

Siemens PRIMATOM™

Siemens PRIMATOM™

TomoTherapyHi-Art™

TomoTherapyHi-Art™

ViewRayRenaissance™

ViewRayRenaissance™

Resonant Restitu™Resonant Restitu™

Image Guided TreatmentImage Guided TreatmentDawson / PMHDawson / PMH


The Big PictureThe Big Picture

MRMR

Tx Plan3D DoseTx Plan3D Dose

NMNM

CTCT

CBCT1…n

CBCT1…n

PortalImagesPortal

Images

4D CBCT4D

CBCT

USUS

3D DoseDay n

3D DoseDay nUSUS

“Adapting”PatientModel

“Adapting”PatientModel


The GoalThe Goal

Ideally, we would like to have a timedependent vector of information for every “point” in an anatomic object

Ideally, we would like to have a timedependent vector of information for every “point” in an anatomic object

image information (MR, CT, NM, … )

physiologic information ( )

anatomic label information

dose information … with time stamp !

image information (MR, CT, NM, … )

physiologic information ( )

anatomic label information

dose information … with time stamp !

ττ


The GoalThe Goal

Scalar DataScalar DataCT+ MR + NM + Dose CT+ MR + NM + Dose (τ)(τ)

PET

MR

CT

4-D Vectors4-D VectorsMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

MechanicsMechanics… determine the geometric transformation that maps corresponding points from one image series to another

… determine the geometric transformation that maps corresponding points from one image series to another

Form of the transformation TForm of the transformation T

Number of degrees of freedoms βNumber of degrees of freedoms β

… from rigid to fully freeform… from rigid to fully freeform

… from 3 to 3 x N*… from 3 to 3 x N*

*N = number of voxels*N = number of voxelsMarc L Kessler, PhD - ASTRO 2007 Refresher Course Marc L Kessler, PhD - ASTRO 2007 Refresher Course

TransformationTransformation… determine the geometric transformation that maps corresponding points from one image series to another

… determine the geometric transformation that maps corresponding points from one image series to another

XB = T ( XA , { ß })XB = T ( XA , { ß })(x,y,z) coordinates of a point in Series B(x,y,z) coordinates of a point in Series B (x,y,z) coordinates

of a point in Series A(x,y,z) coordinates of a point in Series A


Degrees of FreedomDegrees of Freedom

FewFew ManyManyNone ?None ?

PET/CTPET/CT MR - CTMR - CT 4D CT4D CT


What is T ?What is T ?

Rigid / Affine

Full 3D / 4D Deformation

Parametric models

Free-form models

Rigid / Affine

Full 3D / 4D Deformation

Parametric models

Free-form models

Global, regional, or piecewiseGlobal, regional, or piecewise


What is T ?What is T ?

Rigid / Affine Rigid / Affine

Global, regional, or piecewiseGlobal, regional, or piecewise

xB = A xA + b (up to 12 DOF)xB = A xA + b (up to 12 DOF)

y = m x + b … in 3Dy = m x + b … in 3D


A SquareA Square

Study AStudy A

Study BStudy B

Affine TransformationsAffine Transformationswww.gnome.orgwww.gnome.org

RotationRotation ScalingScaling ShearingShearingTranslationTranslation

Parallel lines stay parallel !Parallel lines stay parallel !

3 3 3 3


A SquareA Square

Study AStudy A

Study BStudy B



Parallel lines stay parallel !Parallel lines stay parallel !

6 DOF6 DOF


A SquareA Square

Study AStudy A

Study BStudy B



Parallel lines stay parallel !Parallel lines stay parallel !3 or 4 DOF3 or 4 DOF


Affine TransformationsAffine Transformationsnon-non-

Parallel lines don’t stay parallel!Parallel lines don’t stay parallel!

Study AStudy A Study BStudy B



XB = T ( XA , { ß })XB = T ( XA , { ß })




XB = T ( XA , { ß(XA)})XB = T ( XA , { ß(XA)})





XB = T ( XA , { ß(XA)})XB = T ( XA , { ß(XA)})

Transformation parameters to apply to a particular point depends on the location of the point !

Transformation parameters to apply to a particular point depends on the location of the point !


Balter / UMBalter / UM


phase dependent ?phase dependent ?

XB = T ( XA , { ß(XA, φ )})XB = T ( XA , { ß(XA, φ )})Marc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

Full 3D / 4D DeformationFull 3D / 4D Deformation

ParametricParametric FreeformFreeform

… up to 3 x N… up to 3 x N



Various splines ( TPS , B-splines )

Other basis functions

Various splines ( TPS , B-splines )

Other basis functions

ParametricParametric

Finite element models

Flow models ( optical, viscous )

Finite element models

Flow models ( optical, viscous )

FreeformFreeform



B-Splines … local

Thin-Plate splines … global

Finite element … bio-mechanical

Intensity flow … image forces

B-Splines … local

Thin-Plate splines … global

Finite element … bio-mechanical

Intensity flow … image forces

Each have some distinct propertiesEach have some distinct properties

( mono-modality )( mono-modality )



ParametricParametric FreeformFreeform

Warp Space /… Drag Objects

Warp Space /… Drag Objects

Warp Objects /… Drag Space

Warp Objects /… Drag Space

Brock / PMH


How Do We Compute { } ?How Do We Compute { } ?

Construct a metric that measures the mismatch (or similarity) between a pair of datasets

Construct a metric that measures the mismatch (or similarity) between a pair of datasets

Apply an optimization algorithm to determine the parameters (DOF) that minimize (maximize) this metric

Apply an optimization algorithm to determine the parameters (DOF) that minimize (maximize) this metric

22

11

ββ


How Do We Compute { } ?How Do We Compute { } ?ββ

{ β }Marc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

Registration MetricsRegistration Metrics

Geometry-basedGeometry-based Intensity-basedIntensity-based

??

??


Geometry-Based MetricsGeometry-Based Metrics

Point MatchingLeast Squares

Point MatchingLeast Squares

( XB - XA ) 2( XB - XA ) 2ΣΣ

min distance 2min distance 2ΣΣSurface MatchingChamfer Matching

Surface MatchingChamfer Matching

… depends on image segmentation!… depends on image segmentation!Marc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

Intensity-Based MetricsIntensity-Based Metrics

Mono-modalitySum Squared Difference

Mono-modalitySum Squared Difference

( IB - IA ) 2( IB - IA ) 2ΣΣ

Multimodality DataMutual Information

Multimodality DataMutual Information

p(IA, IB)p(IA, IB)

p(IA) p(IB)p(IA) p(IB)ΣΣ p(IA, IB)p(IA, IB) loglog

… depends on the image characteristics!… depends on the image characteristics!Marc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

How About An Example?How About An Example?

CTCT

PETPETTransformation

Rotate - Translate

Registration Metric

Mutual Information

Optimizer

Simplex Algorithm

Transformation

Rotate - Translate

Registration Metric

Mutual Information

Optimizer

Simplex Algorithm



CTCT

PETPET



CTCT

PETPET


How About Deformations ?How About Deformations ?Balter / UMBalter / UM

Multiphasic CT DataMultiphasic CT Data


Exhale StateExhale State Inhale StateInhale State

Transformation

B-Splines ( multi-resolution )

Registration Metric

Sum Squared Difference

Optimizer

Gradient decent

Transformation

B-Splines ( multi-resolution )

Registration Metric

Sum Squared Difference

Optimizer

Gradient decent

How About Deformations ?How About Deformations ?


Multiresolution DeformationsMultiresolution Deformations

Only small additional computation cost when increasing the number of knots. Only small additional computation cost when increasing the number of knots.

Successively increase the resolution of the knot spacingSuccessively increase the resolution of the knot spacing


Multiresolution DeformationsMultiresolution DeformationsSuccessively increase the resolution of the image dataSuccessively increase the resolution of the image data

CoarseCoarse

¼ Resolution¼ Resolution Full ResolutionFull Resolution

FineFineMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

Multiresolution DeformationsMultiresolution DeformationsSuccessively increase the resolution of the image dataSuccessively increase the resolution of the image data

60 x 60 x 48 mm60 x 60 x 48 mm 4 x 4 x 3 mm4 x 4 x 3 mm

CoarseCoarse FineFineMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

Multiresolution DeformationsMultiresolution Deformations

1.81.8

1.91.9

2.02.0

2.12.1

2.22.2

2.32.3

2.42.4

2.52.5

00 2020 4040 6060 8080 100100 120120 140140 160160 180180

Iteration NumberIteration Number

1.81.8

1.91.9

2.02.0

2.12.1

2.22.2

2.32.3

2.42.4

2.52.5

00 2020 4040 6060 8080 100100 120120 140140 160160 1801801.81.8

1.91.9

2.02.0

2.12.1

2.22.2

2.32.3

2.42.4

2.52.5

00 2020 4040 6060 8080 100100 120120 140140 160160 180180

Iteration NumberIteration Number

Reg

istr

atio

n M

etri

cR

egis

trat

ion

Met

ric

Registration Metric vs. IterationRegistration Metric vs. Iteration

Change inknot spacing Change inknot spacing

Low ResLow Res

High ResHigh Res


Multiresolution B-SplinesMultiresolution B-Splines

Exhale StateExhale State Inhale Statedeformed

Inhale Statedeformed



Multiresolution B-SplinesMultiresolution B-Splines

Exhale StateExhale State Inhale Statedeformed

Inhale Statedeformed



We Are Not Really Splines !We Are Not Really Splines !Ruan / UMRuan / UM

No “stiffness”information

No “stiffness”information

ExtractedRibcageExtractedRibcage

ExhaleExhaleDeform InhaleDeform Inhale


Add Some Physics?Add Some Physics?

tissue-dependent regularizationtissue-dependent regularization

Etotal = Esimilarity + α EstiffnessEtotal = Esimilarity + α Estiffness

intensity similarity measureintensity similarity measure

∫∫ wc(x) |det JT(x) – 1|2 dxwc(x) |det JT(x) – 1|2 dxEvol = Evol =


Spatially Variant StiffnessSpatially Variant Stiffness


“Stiffness” Weighting“Stiffness” Weighting

wc(x)wc(x)


using “stiffness”information

using “stiffness”information

Using “Prior” InformationUsing “Prior” InformationRuan / UMRuan / UM

ExtractedRibcageExtractedRibcage

ExhaleExhaleDeform InhaleDeform Inhale


Tissue SlidingTissue SlidingBalter / UMBalter / UM

Deal with different organs individually?Deal with different organs individually?


Tissue SlidingTissue SlidingBalter / UMBalter / UM

Deal with different organs individually?Deal with different organs individually?


Ribs driven by large lung deformations

Ribs driven by large lung deformations

Ribs not affected by lung registrationRibs not affected

by lung registration

Segmentation + RegistrationSegmentation + Registration

No maskingNo masking MaskingMasking


Finite Element ModelingFinite Element ModelingBrock / UMBrock / UM

ExhaleExhale

InhaleInhale

Take into account physical tissue properties (directly)Take into account physical tissue properties (directly)


Finite Element ModelingFinite Element ModelingBrock / PMHBrock / PMH

… thorough segmentation is necessary… thorough segmentation is necessaryMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

The Future ?The Future ?

Family of Generalized, Customizable,Patient Models

Family of Generalized, Customizable,Patient Models


Is The Future Here Already?Is The Future Here Already?

Marc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributePresenter has no commercial interest in this companyPresenter has no commercial interest in this company

…from Atlas to Individual…from Atlas to Individualwww.mimvista.comwww.mimvista.com

Marc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributePresenter has no commercial interest in this companyPresenter has no commercial interest in this company

…from Individuals to Atlas…from Individuals to AtlasThompson / UCLAThompson / UCLA

Brain Mapping: The Disorders, Academic Press, 1999Brain Mapping: The Disorders, Academic Press, 1999


Meyer/UMMeyer/UM

Segment /register / averageSegment /register / average

withoutwithout withwith

Segment using atlasSegment using atlasMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

In The Meantime …In The Meantime …

ImageImage DoseDoseAnatomyAnatomyMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

Anatomy MappingAnatomy Mapping

Boolean ORBoolean OR

… map to CT… map to CT

Use superior MR contrast for targetingUse superior MR contrast for targetingMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

Anatomy MappingAnatomy MappingDong / MDACCDong / MDACC

Planning CTPlanning CT “Delivery” CT“Delivery” CT

Drawn ContoursDrawn Contours Simple Overlay(no transform)Simple Overlay(no transform)


Anatomy MappingAnatomy MappingDong / MDACCDong / MDACC

Planning CTPlanning CT

Drawn ContoursDrawn Contours Transformed andresampled

Transformed andresampled

“Delivery” CT“Delivery” CTSegmentation done w/ the aid of a registration!Segmentation done w/ the aid of a registration!Marc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

More Than DeformationsMore Than Deformations

… not just deformation!… not just deformation!

deformationdeformation

resectionresection

weight lossweight loss

Δ vascularΔ vascular

shrinkageshrinkage


Dose MappingDose MappingDealing with volume elements that may:Dealing with volume elements that may:

change shape / appear / disappear

… need proper spatial re-sampling

don’t necessarily add in a linear fashion

… need some sort of radiobiology

exist in homogenous intensity regions

… hard to evaluate registration

change shape / appear / disappear

… need proper spatial re-sampling

don’t necessarily add in a linear fashion

… need some sort of radiobiology

exist in homogenous intensity regions

… hard to evaluate registration


ValidationValidation

How do we know how well these registration methods perform?

build phantoms and test them

we can know the truth!

provide tools to examine results

we don’t know the truth!

How do we know how well these registration methods perform?

build phantoms and test them

we can know the truth!

provide tools to examine results

we don’t know the truth!


Validation PhantomsValidation PhantomsCTCT

MRMR

19861986


Validation PhantomsValidation PhantomsKashani / UMKashani / UM


Validation ToolsValidation ToolsQualitative ToolsQualitative Tools

Color gel or wash overlay

Split /dual screen displays

Anatomic boundary overlay!

Color gel or wash overlay

Split /dual screen displays

Anatomic boundary overlay!


Validation ToolsValidation Tools

all values in cm.all values in cm.

Point DescriptionX Y Z X Y Z

1 2nd branch of bronchial tree -5.37 0.98 -3.42 -4.62 -0.22 -2.922 3rd branch of bronchial tree -5.73 2.12 -5.42 -5.40 0.74 -5.923 4th branch of bronchial tree -6.50 2.77 -8.42 -6.24 0.80 -9.424 Vessel bifurcation 1 -8.12 3.37 -9.92 -8.12 1.40 -11.425 Vessel bifurcation 2 -8.06 -1.95 -4.42 -7.67 -3.20 -3.926 Vessel bifurcation 3 -10.69 2.47 0.58 -10.78 1.16 1.08

ΔX ΔY ΔZ-4.71 -0.47 -3.36 -0.09 -0.25 -0.44-5.35 0.58 -5.83 0.05 -0.16 0.09-6.27 0.69 -9.51 -0.03 -0.11 -0.09-8.19 0.91 -11.60 -0.07 -0.49 -0.18-7.27 -2.83 -3.63 0.40 0.37 0.29-10.85 0.87 1.24 -0.07 -0.29 0.16

σ 0.19 0.29 0.26

Exhale Inhale

Exhale' ( w/ TPS alignment )Exhale' - Inhale

Study AStudy AStudy A

*(xA, yA, zA)

*(xA, yA, zA)

Study BStudy BStudy B

*(xB, yB, zB)

*(xB, yB, zB)

Quantitative ToolsQuantitative Tools


AAPM Task Group 132AAPM Task Group 132

Methods to assess the accuracy of image registration and fusion

Issues related to acceptance testing and quality assurance for image registration and fusion

Methods to assess the accuracy of image registration and fusion

Issues related to acceptance testing and quality assurance for image registration and fusion

Use of Image Registration and Data Fusion Algorithms and Techniques in Radiotherapy

Use of Image Registration and Data Fusion Algorithms and Techniques in Radiotherapy


Opportunities & ChallengesOpportunities & ChallengesT2T2 FlairFlair

T1T1 GdGd DiffDiff


More than just mechanics!More than just mechanics!What Now ?What Now ?

MR volumes mapped to CT studyMR volumes mapped to CT studyMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistributeMarc L Kessler, PhD - ASTRO 2007 Refresher Course - Please do not redistribute

SummarySummary

GeometryGeometry IntensityIntensity

InteractiveInteractive AutomatedAutomated

AffineAffine non-Affinenon-Affine

Taxonomy of Registration ProcessTaxonomy of Registration Process


SummarySummaryTools are now available to register and integrate image, anatomy & dose for both Tx planning and Tx delivery

These tools can be used to help build better models of the patient and to help customize and adapt therapy

Work towards more standard and robust tools and validations methods (for non-rigid) situations continues

Tools are now available to register and integrate image, anatomy & dose for both Tx planning and Tx delivery

These tools can be used to help build better models of the patient and to help customize and adapt therapy

Work towards more standard and robust tools and validations methods (for non-rigid) situations continues


Multimodality and 4D Imaging: Multimodality and 4D Imaging: Registration and Fusion for Registration and Fusion for

Treatment Planning and Treatment Planning and Delivery: The clinical Delivery: The clinical

perspectiveperspective……

Laura Dawson, TorontoLaura Dawson, TorontoMarc Kessler, Ann ArborMarc Kessler, Ann Arbor

ASTRO 2007 ASTRO 2007 –– 4949thth meeting; Wed Oct 31, 2007, 1:30 meeting; Wed Oct 31, 2007, 1:30 –– 2:45 PM2:45 PM

DisclosuresDisclosures

• Research Grant, Elekta

Challenges in Radiation TherapyChallenges in Radiation Therapy

1. Seeing the tumor2. Defining the target3. Hitting the target4. Knowing when the tumor is dead

Imaging and image registration is key for addressing these

challenges

• Planning– Planning CT-MR– Planning CT-Contrast CT– Planning CT-PET– Planning CT-SPECT

• Delivery– kV simulation film-MV EPI– DRR - MV or kV PI

• Bones• Fiducial markers

– Planning CT - MV or kV volumetric imaging

Spatial change Temporal change

• Planning– 4D CT

• Delivery– MV / kV fluoroscopy– 4D cone beam CT – Shape change during RT

• Follow-up– Diagnostic CT/ MR/ PET

to planning CT– Dose accumulation– Patterns of recurrence– NTCP, TCP

Clinical Use of Image RegistrationClinical Use of Image Registration

• Planning– Facilitate contouring

(e.g. map atlases to pt dataset)

Spatial change Temporal change

• Planning– Accumulating daily dose(e.g. adaptive therapy)

Other Future Uses of Image Other Future Uses of Image RegistrationRegistration

Planning: PETCTPlanning: PETCT--MRMR

• 56 yo man with clinical T3N0 SCC of oropharynx• PET-CT and MR obtained in treatment position,

on hard table top with mask, on study• Rigid image registration in region of interest

including vertebral bodies

• Benefits:• MR helped define primary tumor superiorly in

region of CT with dental artifact• PET helped confirm suspicious node on CT as

high risk

Courtesy of John Waldron and Stephen Breen, PMH

CT


MR


PET

? physiologic

uptake

GTV

?tumor


PET-CT

physiologic uptake:• muscle • tonsil• vesselGTV

muscle

The fused images are most useful when all information can be

evaluated together

Good alignment in region of tumorAlignment in base of skull not perfect

Good alignment in region of tumor


Planning: CTPETPlanning: CTPET--MRMR

• Looking at CT-PET fusion far more helpful than PET alone

• CT-PET registration not perfect in entire field of view, due to residual rotations, deformation

• Many normal variances of PET

Clinical interpretation of fused images important!

Planning: CTPlanning: CT--MR ProstateMR Prostate

• Advantages of MR for prostate cancer RT– Improve inter-observer variability– Provide more anatomy for organ /nerve sparing

approaches etc.

• New opportunities with MRS, diffusion MR, …– Better knowledge of gross disease– ‘Functional imaging’– Dose painting– Monitoring of change during RT and adaptation


• MR can improve contouring in patients with bilateral hip replacements

Charnley et al, British J Radiology, 2005

Excellent localization of ‘sensitive’ structuresExcellent localization of ‘sensitive’ structures

Allows delineation not possible or difficult on CT aloneAllows delineation not possible or difficult on CT alone

McLaughlin / UMMcLaughlin / UM

… potency sparing?… potency sparing?


MR with endorectal coilMR with endorectal coil

Courtesy of Cynthia Menard and Kristy Brock, PMH

1. MRI, no endorectal coil2. Planning CT3. MRI, endorectal coil

Deformable registration to planning CT

4. Regions of tumor burden, functional data can then be visualized in planning CT space

Liver cancer: MRI can show different volumes, more foci of tumor, especially for HCC

Tumors often easier to see

Necessary for GTV definition if CT contrast allergy

Planning: CTPlanning: CT--MR LiverMR Liver

Auto-fuse whole field of view

Planning: CTPlanning: CT--MR for liver cancerMR for liver cancer

CT MR CT MR

Vertebral body match


CT MR CT MR

Liver match


CT MR

• Once CT and MR liver are registered, the GTV on both can be compared

• Different phases of CT and MR can be complimentary

CT-arterial CT-venous MR-venous

Voroney, et al, IJROBP, 2006


Before AfterLiver Deformable Registration

coronal

sagittal

Prior to Deformable Registration

GTV VolumeCT = 13.9 ccMR = 6.7 ccΔVol = 7.2 cc

(52%)

Planning: CTPlanning: CT--MR for liver cancerMR for liver cancerLiver deformation ?

MR and CT GTV comparison

GTV VolumeCT = 13.9 ccMR = 6.7 ccΔVol = 7.2 cc

(52%)FEM deformable IR, Kristy Brock, PMH

Planning: CTPlanning: CT--MR liver GTV MR liver GTV comparisoncomparison

• 26 patients with liver cancer investigated• GTV defined on CT and MR• CT Liver-MR Liver deformable registration• Med % surface of GTVs differed > 5 mm = 26%• Largest differences for HCC and

cholangiocarcinoma

Voroney, et al, IJROBP, 2006

DeformationDeformation

• Even though deformation is ‘scary’ and challenging to validate, measure,describe, we need to be aware that deformation and other volumetric change exists.

• Volume change and deformation is another source of error and there are strategies to deal with it

• Deformable image registration tools not available commercially.

MV EPID kV Fluoroscopy + markers Ultrasound kV CT

MV CT kV Cone-beam CT

Image Guided Radiotherapy (IGRT)

MV cone beam CT

and more… Dawson, Jaffray, JCO, 2007

Electronic Portal Imaging DevicesElectronic Portal Imaging Devices

• Types of image registration– In your head – Manual– Dot gradicule– Template– Automated– Limited ROI

• Even if you didn’t know it, you have been doing image registration for years

A B

C

x

x

x

x

xx

Courtesy of Kristy Brock, Peter Chung, PMH

• Manual point matching

• Automated matching

EPIDsEPIDs -- FiducialsFiducials

Volumetric imaging: kV cone beam Volumetric imaging: kV cone beam CTCTBone match, then prostate match using

prostate contour from cone beam CT

Head & Neck kV Cone-beam

CT

IGRT: Head and neck cancerIGRT: Head and neck cancer• T4N2 NPC for combined modality therapy. GTV

‘hugging’ brainstem and chiasm• Clivus and cavernous sinus chosen as ROI

IGRT: Head and neck cancerIGRT: Head and neck cancer• Spine curvature not reproducible• Change in tumor• Dosimetric consequence?

L Johnston, J Waldron, PMH

Week 3

Dose Difference (%) >5%>10%

Week 1Doses

25 Gy45 Gy54 Gy70 Gy74 Gy

Courtesy of J Pouliot, UCSF

IGRT Head and Neck: MV Cone Beam CT

Change in shape

Increased cord dose

CBCT Fx #1CBCT Fx #1

Reconstructed CBCT Dataset sent to

Pinnacle

Reconstructed CBCT Dataset sent to

Pinnacle

Verification by MV Portal Imaging and/or

kV Fluoroscopy

Verification by MV Portal Imaging and/or

kV Fluoroscopy

CBCT DatasetRegistered w/ GTV

from Planning

CBCT DatasetRegistered w/ GTV

from Planning

Determine Couch ShiftDetermine Couch Shift

Lung Cancer IGRT (SBRT 20Gyx3)Lung Cancer IGRT (SBRT 20Gyx3)

GTVGTVPTVPTV

Verification by MV Portal Imaging and/or kV Fluoroscopy and/or

CBCT

Verification by MV Portal Imaging and/or kV Fluoroscopy and/or

CBCT

Cone beam CT #1

Courtesy of T Purdie, PMH

Non peripheral lung tumors not always well visualized

Surrogates for tumor can improve setup accuracy

e.g carina for central tumors

Non peripheral lung tumors not always well visualized

Surrogates for tumor can improve setup accuracy

e.g carina for central tumors

Lung Cancer IGRTLung Cancer IGRT

Courtesy of J Higgins,PMH

Setup based on skinSetup based on skinLung Cancer IGRTLung Cancer IGRT

Courtesy of J Higgins, PMH

Carina MatchCarina MatchLung Cancer IGRTLung Cancer IGRT

Courtesy of J Higgins, PMH

Bone matchBone matchLung Cancer IGRTLung Cancer IGRT

Carina MatchCarina MatchLung Cancer IGRTLung Cancer IGRT

Pre-correction setup (online & template)Courtesy of G Hugo, WBH, Michigan

Prior to IGRT

residuals (online & template)Courtesy of G Hugo, WBH, MichiganTumor IGRT

A note of cautionA note of caution

• When region of interest for image matchigis small, watch what happens to critical normal tissues outside of matching volume!

Respiratory Correlated CT (4DCT) for Planning

Respiration Correlated CBCT on Treatment Unit

4D image matching4D image matching

Liver Cancer IGRT Liver Cancer IGRT -- PMHPMH• MV, kV orthogonal imaging

– Diaphragm, exhale – CC positioning– Vertebral body – ML and AP positioning

• kV CBCT - liver and/or liver tumor for 3D guidance• Real time MV BEV images

MV imaging kV fluoroscopy kV CBCT

MV Orthogonal Image Alignment

MV Orthogonal Image Alignment

DRR (exhale) MV Portal Image (exhale)

Diaphragm used for CC alignment

Vertebral bodies used for AP,ML alignment

AP

Lat

+ +

+ +

MV Real Time ImagingMV Real Time Imaging

• 47 MV BEV movies from treatment fields including air-diaphragm interface– Manual check – Automated comparison of MV exit field to

planned field

BEV DRR BEV PI

Dawson, IJROBP, 2005

kV Orthogonal Image Alignment kV Orthogonal Image Alignment DRR (exhale) kV image (exhale)

Diaphragm used for CC alignment

Vertebral bodies used for AP,ML alignment

AP

Lat

Repositioning for offsets > 3 mm

Liver-liver registration for planning and IGRT

Liver-liver registration for planning and IGRT

• The liver can be used as a surrogate for the GTV, as it is most often not visible on cone beam CT

Planning CT MR kV cone beam CT

Volumetric Image Guidance automated liver to liver

registration

Pre-RT Post-RTPre-RT Post-RTIntraIntra--fraction Change in positionfraction Change in position

Difference Display

Free breathing cone beam CT

Planning CT: Metastases with calcifications

kV Cone beam CT

Natural Natural fiducialfiducial markersmarkers

Iatrogenic fiducial markersIatrogenic fiducial markers• TACE: Trans hepatic arterial chemo-embolizationLipiodol contrast stable in tumor for > 1 year

• Ave. residual deformation: 95% volume deforming < 2.3 mm in each direction

• 4 cases : deformation > 5mm in CC and ML

Liver position following MV Liver position following MV guidanceguidance

Hawkins, Dawson et al, IJROBP 2006

Challenges with Registration in Challenges with Registration in IGRTIGRT

• Rotations• Deformations• New artifacts• Free breathing changes • Need for clinical input as to what region of interest

matters most for registration• Do not forget rest of tissues, as they may move

MORE as smaller volume is used for registration

What do differences in images What do differences in images mean?mean?

Daisne et al. 233 (1): 93. (2004) Daisne et al. 233 (1): 93. (2004)

Daisne / St -LucDaisne / St -Luc

Ceci est une tumeur?Ceci est une tumeur?FD

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Jean-François Daisne MD, et al. Radiology 2004;233:93-100Jean-François Daisne MD, et al. Radiology 2004;233:93-100

RadiologyRadiology--pathology correlation: pathology correlation: LiverLiver

Dawson, ASTRO 2007Dawson, ASTRO 2007

ConclusionsConclusions• Image registration (IR) is a mandatory tool for

multi-modality planning and IGRT.• IR is not perfect; impossible to represent the

‘whole patient’ at ‘all times’.• As volume for matching is smaller, critical organ

doses outside matching volume may increase.• IR can facilitate research in rad-path correlation

studies, patterns of recurrence analysis, autocontouring, dose accumulation, adaptive therapy, observer variability studies,…

• Clinical input and QA important despite technological advances and automation in IR.

AcknowledgementsPMHCynthia MenardAndrea BezjakJohn WaldronCharles CattonDavid Jaffray Mike SharpeDoug MoseleyJeff SiewerdsenTom PurdieJean Pierre BissonnetteKristy BrockCynthia EcclesJane HigginsRobert Case Regina TseMaria HawkinsMark Lee

Outside PMHJJ Sonke, NKIGeoff Hugo, WBHJake Van Dyk, LondonJean Pouliot, UCSF

The 100s of people we have ever discussed image registration, multimodality imaging or IGRT with

Funding:ASCO CDANCICCanadian Cancer SocietyElekta

Health & Medicine

Multimodality & 4 D Imaging