phd presentation: computer graphics and vision techniques for the study of the muscular fiber...

Computer Graphics and Vision Techniques for the Study of the MuscularFiber Architecture of the MyocardiumPhD Thesis Ferran Poveda

Advisors: Enric Martí Debora Gil

PhD Thesis Ferran PovedaMotivation

Yearly deaths directly related to heart conditions in the World*:

9.6 milion by 2015

*Data of the World Health Organization

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PhD Thesis Ferran PovedaMotivation

Yearly deaths directly related to heart conditions in the World*:

9.6 milion by 2015

11.7 million by 2030

*Data of the World Health Organization

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PhD Thesis Ferran PovedaForm and Function

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Structure

• Dilated Cardiomyopathy

• Cardiac ischemia

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Spatial distribution of myocites (architecture) plays a crucial part in cardiac function


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Structure



Rhythm

• Arrythmogenesis

• Ventricular dyssyncrony

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Structure



Rhythm

• Arrythmogenesis

• Ventricular dyssyncrony

Dynamics

• Diastolic heart failure


1891

PhD Thesis Ferran PovedaControversy

• No consensus on an architectural model

• Surgical and Histological exploration

• Criticised in its repeatability and subjectivity

1669 1749 1957Lower Senac Kherl Torrent-Guasp

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PhD Thesis Ferran PovedaDT-MRI

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Objective measurement of the biological structure


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PhD Thesis Ferran PovedaCurrent Challenges

• Complete and objective:

• segmented volumes

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Use of tractography for representation of cardiac architecture:




• partial reconstructions

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• Simplify structure representation

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• Simplify structure representation

• Validation of reconstructions

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PhD Thesis Ferran PovedaGoal and contributions

Goal:

• Provide cardiologists a simplified, objective and validated representation of the myocardial architecture.

Contributions:

• Simplification: Achieve more abstract reconstructions

• Validation: Measure quality and confidence of fiber tracts

• Objective: Visualization tools and study of the myocardial architecture

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PhD Thesis Ferran PovedaOutline

• Fiber tracking and multi-resolution tractography

• Validation Framework

• Visualization and evaluation of a conceptual model of the myocardium

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PhD Thesis Ferran PovedaFiber Tracking

• Reconstruction of discrete measurement of cardiac architecture. Integration of curves on DT-MRI vector field.

Runge-Kutta integration

• Initiation

• Vector orientation

• Termination

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PhD Thesis Ferran PovedaFiber Tracking: Initiation

• Coherence measure: LoCoh = max(σeig11, σeig12, σeig13)

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PhD Thesis Ferran PovedaFiber Tracking: Initiation

• Coherence measure: LoCoh = max(σeig11, σeig12, σeig13)

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PhD Thesis Ferran PovedaFiber Tracking: Orientation

• Orientation problem:

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Automatically computed anatomical axis


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Automatically computed anatomical axis

PhD Thesis Ferran PovedaFiber tracking: Termination

• Termination based solely on RK estimation

• Noise in thin/unstable structures

• Not impose structural restrictions

• Later confidence measures

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PhD Thesis Ferran PovedaMulti-resolution

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F1 R1 F2 R2Origin FN RN

• Multi-resolution pyramid:

PhD Thesis Ferran PovedaMultiresolution tractography

• Application to DT-MRI/Tractography:

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F1 R1 F2 R2Origin FN RN

PhD Thesis Ferran PovedaMulti-resolution Methods

• Gaussian pyramids: Isotropic + subsampling

• Structure Preserving Diffusion operator: Anisotropic + subsampling

• Discrete Wavelet Transform: Haar Wavelet decomposition

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PhD Thesis Ferran PovedaGaussian Pyramid

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F2 R2Origin FN RNF1 R1

Gaussian Filtering

PhD Thesis Ferran PovedaStructure Preserving Diffusion

• Use anatomical information to guide filtering and preserve structure: 1st eigenvector guiding diffusion process

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PhD Thesis Ferran PovedaStructure Preserving Diffusion

Input data Filtered dataIterative processing

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• Use anatomical information to guide filtering and preserve structure: 1st eigenvector guiding diffusion process


PhD Thesis Ferran PovedaWavelet Transform

• We use low frequency bands of the pyramid (less detail)

• Gaussian can also be seen as an application of the family of Mexican Hat Wavelet Transforms:

• Specialized in valleys and ridges

• Rather than discontinuities like Haar DWT

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• Visualization and evaluation of a conceptual model of the myocardium

PhD Thesis Ferran PovedaDatabase

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• All results obtained over the Johns Hopkins University database

• 7 healthy specimens

• Beagle breed dogs

• Ex-vivo fixed hearts

• DT-MRI adquisitions

PhD Thesis Ferran PovedaValidation framework

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Local image analysis Global geometric analysis


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Structure Preservation

Angular Variation

PhD Thesis Ferran PovedaLocal: Angular

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• Angular variance in multi-resolution:

Methods Hearts


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• Localization:

PhD Thesis Ferran PovedaLocal: Structure

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Coherence Measure


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Coherence Measure Segmentation


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Coherence Measure Segmentation Distribution of classes


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Coherence Measure Segmentation Distribution of classes

• Separability based on Linear Fisher Discriminant


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PhD Thesis Ferran PovedaGlobal: Geometric contextualization

Interest in the study of geometric contextualization

• Contexts of fibers for the study of geometrical behaviour

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• Spline fitting for arc-parameter matching

PhD Thesis Ferran Poveda

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• 3D geometric descriptor for each context

• Curvature, Torsion and Distancesof contexts fibers vs representative

• 1D metric based on Mahalanobis distance

Global: Geometric contextualization


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• Mahalanobis metric for comparison

OriginalOriginal

Contextualization



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• Mahalanobis metric for comparison

OriginalProcessed

SummarizationContextualization



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• Preservation of geometric contextualization:

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• Statistical study of variability (ANOVA)

Global: Experimental Setup

~


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• Study variability according to different factors:

A. Specimens (quality of capture)

B. Methods (all levels of the pyramids in the different methodologies)

Group data according to factors and multiple test on each factor mean

Ho: μheart_1 = μheart_2 = · · · = μheart_7

μmethod_1 = μmethod_2 = · · · = μmethod_N

Detect interaction between factors



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• Study variability according to different factors:

A. Specimens (quality of capture)

B. Methods (all levels of the pyramids in the different methodologies)

Group data according to factors and multiple test on each factor mean

Ho: μheart_1 = μheart_2 = · · · = μheart_7

μmethod_1 = μmethod_2 = · · · = μmethod_N

Detect interaction between factors



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Two experiments:

1. Stability across specimens and methods: Mahalanobis

2. Preservation of geometrical features: Difference of Mahalanobis


PhD Thesis Ferran PovedaGlobal: Exp 1

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2-way ANOVA:

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1-way ANOVA:

Heart Factor: Method Method:

Interaction:

p < 0.000 p < 0.000 p = 0.028

α = 0.05

Analysis for complete dataset

MethodsHearts


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2-way ANOVA:

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1-way ANOVA:


Interaction:

p < 0.000 p < 0.000 p = 0.028

α = 0.05

Analysis for complete dataset

MethodsHearts


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2-way ANOVA:

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1-way ANOVA:


Interaction:

p < 0.000 p < 0.000 p = 0.476

α = 0.05

Analysis discardingoutlying methods

MethodsHearts


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2-way ANOVA:

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1-way ANOVA:


Interaction:

p < 0.000 p < 0.000 p = 0.731

α = 0.05

Analysis discardingoutlying methods

MethodsHearts


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• Visualization and Interpretation

• Visualization Tools

• Evaluation of a conceptual model of the myocardium

PhD Thesis Ferran PovedaVisualization

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• Fiber color coding

• Multi-resolution

• Reconstruction confidence


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• Global coordinate axes of reference

Visualization: Fiber coloring


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• Local coordinate axes of reference



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• Local coordinate axes of reference

• Anatomically coherent color mapping



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Binary color coding Binary transparency coding



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Visualization: Multi-resolution


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Multi-resolution visualization


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Visualization: Multi-resolution

PhD Thesis Ferran PovedaVisualization: Confidence

• Context vs geometric mean:

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Geometric mean Original


• Context vs geometric mean:

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• Local geometric metric:

OriginalGeometric mean

Visualization: Confidence


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• Control streamtube

• Thickness

• Color

• Noise reduction

• Ease interpretation

Visualization: Confidence

PhD Thesis Ferran PovedaEvaluation of a conceptual model: HVMB

• poseso

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F. Torrent-Guasp

Helical Ventricular Myocardial Band


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• Key-points of the Helical Ventricular Myocardial Band:

• Four segments of the conceptual model

• Helicoidal connectivity across myocardium

Evaluation of a conceptual model: HVMB

PhD Thesis Ferran PovedaSegments

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Right Segment Left Segment

Descendent Segment Ascendent Segment

Rubber band modelFull-scale reconstruction


A

BC

D

E

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Basal Loop Apical Loop

Lateral superior view Inferior view


A

DE

H

I C

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Anterior view Posterior view


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Superior view

PhD Thesis Ferran PovedaBand connectivity

• a multi-res una sola fibra

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Schematic of the HVB

PhD Thesis Ferran PovedaBand connectivity


A

A

BB

C

C

D

DE

E

F

fG

G

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Schematic of the HVB

PhD Thesis Ferran PovedaRepeatability


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PhD Thesis Ferran PovedaRepeatability


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PhD Thesis Ferran PovedaConclusions: Simplification

• Multi-resolution is a good tool heart architecture interpretation and representation

• Wavelet, best to contextualize anatomical information

• SPD, best to filter data

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PhD Thesis Ferran PovedaConclusions: Validation

• Validation framework comprehensive measures

• Local measures able to detect worst captures but are not enough

• Global geometric features must be taken into account

• First level of reduction

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Conclusions: Visualization and interpretation

• Visualization tools allowed showing evidences of the structure of the HVMB of Torrent-Guasp

• Band segments

• Helical continuity

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PhD Thesis Ferran PovedaFuture Work

• Broaden database (species, conditions, specimens)

• Use of geometrical descriptors

• Shapes/Configurations

• Applications

• Scale-space

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• F. Poveda, D. Gil, E. Martí-Godia, A. Andaluz, M. Ballester, F. Carreras. Helical Structure of the Cardiac Ventricular Anatomy Assessed by Diffusion Tensor Magnetic Resonance Imaging Multi-Resolution Tractography. Revista Española de Cardiología., 66(10):782-790, 2013. + Cover Image - IF 3.204

• F. Poveda, D. Gil, E. Martí-Godia, M. Ballester, F. Carreras. Helical structure of ventricular anatomy by diffusion tensor cardiac MR tractography. Journal of the American College of Cardiology: Cardiovascular Imaging, 5(7):754-5, 2012. + Cover Image - IF 6.703

• F. Poveda, D. Gil, E. Martí-Godia. Multi-resolution DT-MRI Cardiac Tractography. In book Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 270-277, 2013.

• F. Poveda, D. Gil, T. Gurguí, E. Martí-Godia. Multi-resolution myocardial architecture study. In proceedings of Congreso Español de Informática Gráfica. 165-6, 2012.

Publications!82

Computer Graphics and Vision Techniques for the Study of the MuscularFiber Architecture of the MyocardiumPhD Thesis Ferran Poveda

Advisors: Enric Martí Debora Gil

phd presentation: computer graphics and vision techniques for the study of the muscular fiber...

Technology

objective measurement

cardiac functionform

muscular fiber architecture

eig13fiber tracking

orientation problem

anatomical axisfiber

diffusion operator

diffusion processstructure