robert s. macleod, yesim serinagaoglu*, bulent yilmaz, and dana h. brooks*

Epicardial Mapping from Venous Catheter Measurements,

Body Surface Potential Maps, and an Electrocardiographic Inverse Solution

Epicardial Mapping from Venous Catheter Measurements,

Body Surface Potential Maps, and an Electrocardiographic Inverse Solution

Robert S. MacLeod, Yesim Serinagaoglu*, Bulent Yilmaz,

and Dana H. Brooks*

NEH Cardiovascular Research and Training Institute (CVRTI), U of Utah*Communications and Digital Signal Processing (CDSP), Northeastern U

Combining Information SourcesCombining Information Sources

Forward

Inverse

Venous Catheter Based Mapping

Venous Catheter Based Mapping

Statistical EstimationStatistical Estimation

EstimationMatrix

Training Data

CovarianceMatrix

* =

Sparse Test DataEstimate

Estimated Activation MapsEstimated Activation MapsOriginal Mixed

RV-onlyLV-only

• Training set composition

• Lead selection

Augmented Inverse ProblemAugmented Inverse Problem

Forward

Inverse

Torso geometry

Body-Surface Potentials

Sparse Epicardial Potentials

Inverse Solution

Epicardial Map

+

+

+

Subtraction ApproachSubtraction ApproachKnownUnknown

Inverse(Tikhonov)

1) Subtract known epicardial potentials

2) Solve reduced inverse problem

Epicardial EstimationEpicardial Estimation

t1 t2 ….. ….tN

. . .

Estimation

Combined EstimationCombined Estimation

Estimation

Bayesian ApproachBayesian Approach

Inverse(MAP)

Hybrid ApproachHybrid Approach

Inverse(MAP)Estimate

Tank/Heart GeometryTank/Heart Geometry

Test Lead SetsTest Lead Sets

Anterior

Posterior

42 leads 21 leads 10 leads

Simulation StudySimulation Study

• 490 lead measured sock data

• Surrogate catheter potentials– 42 sites– + Gaussian noise

• Torso potentials– Calculated noise-free using forward model– + Gaussian noise

Leave-One-Experiment Out Protocol

Leave-One-Experiment Out Protocol

Training Data

Dec 13, 2000

Test Data

Dec 18, 2000

Dec 13, 2000

LV Paced Beats

Mixed Paced Beats

LV Pacing (LV-23 ms) LV Pacing (LV-23 ms) Orig Subt MAP

Est Epi Est All Hybrid MAP

31: LV-MEpiP-23 ms

LV Pacing (LV-38 ms)LV Pacing (LV-38 ms)Orig Subt MAP

Est Epi Est All Hybrid MAP

31: LV-MEpiP-38 ms

LV Pacing (LV-47 ms)LV Pacing (LV-47 ms)Orig Subt MAP

Est Epi Est All Hybrid MAP

31: LV-MEpiP-47 ms

LV Pacing (Mixed-23 ms)LV Pacing (Mixed-23 ms)Orig Subt MAP

Est Epi Est All Hybrid MAP

31: LV-RV-MEpiP-23 ms

LV Pacing (Mixed-38 ms)LV Pacing (Mixed-38 ms)Orig Subt MAP

Est Epi Est All Hybrid MAP

31: LV-RV-MEpiP-38 ms

LV Pacing (Mixed-47 ms)LV Pacing (Mixed-47 ms)Orig Subt MAP

Est Epi Est All Hybrid MAP

31: LV-RV-MEpiP-47 ms

Relative Error (31-LV)Relative Error (31-LV)

0 10 20 30 40 50 60 70 80 90 1000

0.2

0.4

0.6

0.8

1

1.2

1.4R

elat

ive

Err

or

Time [ms]

MAPEstim-Epi

Estim-AllMAP-HybridSubtr

Relative Error (31-Mixed)Relative Error (31-Mixed)

0 10 20 30 40 50 60 70 80 90 1000

0.2

0.4

0.6

0.8

1

1.2

1.4MAPEstim-EpiEstim-AllMAP-HybridSubtr

Rel

ativ

e E

rro

r

Time [ms]

Estimation FindingsEstimation Findings

• Estimation alone: noisy, unstable results

• Estimation + inverse: smoothing improves stability

Inverse Solution FindingsInverse Solution Findings

• All solutions better than simple Tikhonov

• MAP usually improved with addition of catheter measurements (Hybrid MAP)

Role of Statistics (Training)Role of Statistics (Training)

• Generally helps

• But can add artifacts, e.g., spurious breakthroughs or wavefronts

• Torso potentials can reduce artifacts

ConclusionConclusion

More (bigger) is better…..

… but not always