Sim4Life & Functionalized Anatomical ModelsSim4Life & Functionalized Anatomical Models: MRI Safety,...

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Sim4Life & Functionalized Anatomical Models:MRI Safety, Thermal Therapies, and Neurostimulation

IT’IS Computational Life Sciences Group

Visit, Prof. Snedeker November 24th,.2016

Introduction

• advances in imaging and simulation technology permit the generation of functionalized (personalized) patient models

• this opens novel and powerful possibilities in:- device & therapy innovation- personalized medicine & treatment

planning- in silico clinical trials

(safety & effectivity assessment)- …

• Sim4Life is a computational life sciences platform optimized for the modeling physical and physiological/biological process in and around the human body

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Solvers

physics

• electro-magnetics

• thermodynamics

• acoustics

• fluid dynamics

• CRD

• (mechanics

tissue models

• neuronal dynamics

• perfusion models

• tissue damage / growth models

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High Performance Computing

• (multi-)GPU HW

acceleration

• MPI/OMP parallelization

(clusters, supercomp.…)

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FUNCTIONALIZED ANATOMICAL MODELS

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Medical Image Data (MRI)

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Virtual Population

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Parameterization for Comprehensive Coverage

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Morphing for Personalization

Thelonious TheloniousObese ChildObese Child

• surface-based (ICP) / image-based (registration) / physics-based (biomechanical)

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Images Provide more than Anatomy: MHD

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Images Provide more than Anatomy: MHD

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High Resolution MIDA Head Model (0.5mm, 160 struct.)

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Images Provide more than Anatomy : TACS

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Images Provide more than Anatomy : TACS

Multiscale: Top-Down

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Neuronal Excitability: Anysotropy, Timing, Location

0.2

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Monopolar Pulse

Bipolar Pulse

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Multiscale Modeling

Single-Cell In-Situ

Monophasic

Biphasic

10 Hz

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Neuronal Excitability: Anysotropy, Timing, Location

Complete Tr<0,75 0,75<Tr<1,25 Tr>1,25

Complete Tr<0,75 0,75<Tr<1,25 Tr>1,25

Biphasic

Monophasic

Cathodic

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Stimulation Localization & Timing

Monophasic Biphasic

1,8

[ms]

0,5

100

[ms]

0

Exci

tabi

lity

0,5 [ms]

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Field / Stimulation: Correlation

Ba

ll a

nd

Sti

ck

CA

1

R2=0,9998

R2=0,9997

R2=0,6859

R2=0,7478

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Image-Based Functionalization: Neurons with DTI

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MRI Gradient Coil Safety

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EM Induced Neuron Stimulation – Results

SENN22 SENN37 & SENN(T)

end-node center-type

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EM Induced Neuron Stimulation – Results • calculated peak gradient coil E-field (in fat & overall), dB/dt comparable to

previously reported values [Turk2012, So2004];slightly higher as expected due to increased resolution & detail [So2004]

• onset of stimulation slightly above realistically occurring switching rates

• end- and center-type stimulation occur at similar thresholds

‣ E-field not sole criterium

• potential distribution along nerve has influence on stimulation threshold

• local foci occur and matter

• detailed motor neuron model has in some cases lower threshold than SENN

• temperature strongly affects dynamics, but only minimally threshold (<20% except for very short pulses)

• neuron trajectory should be smoothed to avoid falsely lowering predicted stimulation onset, but

• field smoothing should be avoided

• dielectric contrast at tissue interfaces related issues are naturally handled (sampling by nodes)

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PERSONALIZED MEDICINE: THERMAL THERAPIES

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Thermal Therapies

• hyperthermic oncology (aims at >42C, benefits shown at 40-42C)

• ablation (55 - >100C)

Erasmus MC, Rotterdam

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Personalized Treatment Planning

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Novel Applicator, Design&QA&TP by Modeling

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Superparamagnetic Nano-Particle HT

Multiscale:

Bottom-Up

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Thermal Modeling: From Physics to Physiology

• based on widely employed Pennes Bioheat Equation

• extensions:- coupling to 1D vessel networks to account for directivity & discreteness of

blood flow (increased accuracy & x100 acceleration)- local thermoregulation (vasodilation & vascular shut-down)- coupling to whole body thermoregulation model- accounting for body core temperature increase- supporting MR perfusion maps & MR flow field

maps (personalization)

• for high T (ablation): evaporation, rehydration, coagulation

Multiscale:

Hybrid/Parallel

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Treatment Effect on Tumor Evolution

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IN SILICO CLINICAL TRIALS:MRI IMPLANTATE SICHERHEIT

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The Problem: MRI Implant Safety

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AIMD Expositionssicherheitsabklärung

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in vivo RF Feldverteilung: Populationsabdeckung

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Trajektorienabdeckung

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Kombination

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Kombination

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Statistische Auswertung

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Auszug aus der Unsicherheitsanalyse

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Auszug aus der Unsicherheitsanalyse

Neufeld, et al., Phys. Med. Biol. 54 (2009) 4151–4169

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VERIFICATION AND VALIDATION

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Verification & Validation

Method of Manufactured Solutions, benchmarks, published data, measurements

- sharp contrasts

- anisotropic tensorial conductivity

- conductivity inhomogeneity

- source term inhomogeneity

- pulse shape

- stimulation thresholds(center-type and end-node stimulation)

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Patch Clamp Measurements

ax

on

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Neuroprosthetics: Selective Muscle Activation

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Verification & Quality Assurance• documented solver&algorithm verification (available for regulatory purposes)

- following standards where available (e.g., IEC/IEEE 62704-1 for EM FDTD)

• automated test suit running nightly on large number of systems, unit tests

• quality assurance measures:- e.g., cross-checking & external expert review for ViP models, - automated checks (e.g., change of tissue property values, organ weight)- requirements & checklists & guidance documents

• bug & feature tracking system, version control

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Torso Phantom and Model

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Generic (FDA) Implant

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In Vivo Heating

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Validation: Gamma Method & GUM

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CONCLUSIONS

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Conclusions• advances in imaging, HPC, and computational life sciences permit

computable, functionalized anatomical phantoms

• these have been successfully applied for:- device & therapy innovation- personalized medicine & treatment planning- in silico clinical trials

(safety & effectivity assessment)

• requires:

- image-based generation of personalized / population-covering models

- (image-based) functionalization (properties, BC, dynamics)

- simulating physical interactions with living tissue within complex, inhomogeneous anatomy

- modeling induced physiological/biological impact

- identification of optimal therapy, worst-case configuration

- quantification of confidence interval & V&V