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Optimization and Identification in Regional Hyperthermia Martin Weiser Zuse Institute Berlin DFG Research Center MATHEON OIPE 2008, Ilmenau, 2008-09-15

Optimization and Identification in Regional Hyperthermia · Optimization and Identification in Regional Hyperthermia Martin Weiser Zuse Institute Berlin DFG Research Center MATHEON

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Page 1: Optimization and Identification in Regional Hyperthermia · Optimization and Identification in Regional Hyperthermia Martin Weiser Zuse Institute Berlin DFG Research Center MATHEON

Optimization and Identification in Regional Hyperthermia 

Martin Weiser

Zuse Institute Berlin

DFG Research CenterMATHEON

OIPE 2008, Ilmenau, 2008­09­15

Page 2: Optimization and Identification in Regional Hyperthermia · Optimization and Identification in Regional Hyperthermia Martin Weiser Zuse Institute Berlin DFG Research Center MATHEON

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Contents

I Regional Hyperthermia

III Perfusion Identification

IV Antenna Profile Identification

II Treatment Planning

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I Regional Hyperthermia

Page 4: Optimization and Identification in Regional Hyperthermia · Optimization and Identification in Regional Hyperthermia Martin Weiser Zuse Institute Berlin DFG Research Center MATHEON

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Regional Hyperthermia

● tumors are susceptible to heat● support radio­ or chemotherapy by

heating tumors

● phased array microwave radiation● (focused) ultrasound● magnetic nanoparticle fluids● RF­ablation

Technology for Regional Hyperthermia

Principle

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Regional Hyperthermia

geometry acquisition

physical & physiolocalmodelling

rot H=iErot E=−iHdiv E =0div H =0

[ L xx −C−C ][ y

]=[ra

r c]

simulation & optimization

clinical implementation

quality assessment & online control

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II Therapy Planning

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Therapy Planning

Bio Heat Transfer Equation

tissue subdomains

[Pennes 1948]

Cost Functional

Constraints

Time­harmonic Maxwell's equation

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Cost Functionals

Ad hoc [Seebaß et al.]

Tumor control protein denaturation (Arrhenius law)

fraction of surviving cancer cells

[Mass et al.]

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Function Space Interior Point Methods

s.t.

s.t.

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Central Path

Convergence

for

Local self­concordance

● rational barrier function of suitable order● generic solution

linear convergence of short step pathfollowing

[Schiela 2008]

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Function Space Algorithms

Inexact Newton Method

Pathfollowing

Adaptive FE Discretization

Linear Algebra

cont

inuo

usdi

scre

te

homotopystepsize selection

linearizationtolerance selectionerror estimationmesh adaptation

linear equation solution

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Numerical Example: Prostate Tumor

isothermes 43.5°C

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Numerical Example: Applicator Comparison

Sigma­60, 8 antennas Sigma­Eye, 24 antennas

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Numerical Example: Applicator Comparison

Sigma­60, 8 antennas Sigma­Eye, 24 antennas

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III Perfusion Identification

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Perfusion Identification

MR thermometry

MR thermometry slice

coefficients depend on tissue type:● fat● muscle

Tichonov regularization

s.t.

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Tichonov Regularization

Gaussian white noise prior

Gaussian smoothness prior

Positivity

perfusion values spatially uncorrelated

perfusion values related to temperature

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2D Clinical Example

perfusion temperature

reference

identified

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3D Artificial Example

actual perfusion

reference perfusion

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High Noise Setting

actual

identified

measurement

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Low Noise Setting

actual

identified

measurement

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Nonconvexity and Nonuniqueness

Idealized situation

fat:

muscle:

globally non­unique identification in muscle regions where

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IV Antenna Profile Identification

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Identification of Antenna Profiles

Error sources● patient positioning, movement, and geometry● reflections in feed network● power generator behavior● bolus water pollution● electrical conductivity of tissues● ...

FDTD simulation measurement

ARD cross section

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Identification of Antenna Profiles

ARD computation

● FE or FDTD for solving time­harmonic Maxwell's equations● superposition of antenna profiles

ARD measurement in phantoms

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Identification of Antenna Profiles

MR thermometry in phantoms

Pointwise least squares fitting

Degrees of freedomrank defect: 5

highly underdetermined problem

Sigma­Eye applicator● channels● measurements

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Gauß­Newton Algorithm

Least change update

Closed loop control

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Closed Control Loop on Phantom

[Weihrauch et al. 2007]

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Closed Control "Loop" on Patient

comptued ARD 

computed ARD

measured ARD 

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Closed Control "Loop" on Patient

time (min)

temperature difference betweentumor and muscle

central FDTD focused adapted

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Conclusion

Thanks to...

● J. Gellermann, P. Wust, M. Weihrauch (Charité)● A. Schiela, P. Deuflhard (ZIB)● S. Volkwein (U Graz)

● regional hyperthermia poses several optimization & identification problems● the solution of most of which are essential for individually optimal therapy delivery● beneficial effect of identification even for simple models & sparse data● more data needed for perfusion identification