Validation of DTI Analysis

NA-MICNational Alliance for Medical Image Computing http://na-mic.org

Validation of DTI Analysis

Guido Gerig, Clement Vachet, Isabelle Corouge, Casey Goodlett

UNC Chapel Hill

National Alliance for Medical Image Computing http://na-mic.org

Validation Concepts

• Validity: Comparison to truth / gold standard

• Reliability, Reproducibility: Repeated measures

• Outcome measures: Sufficient to answer clinical question


Validation: DTI Image Analysis

• Validity:– In vivo human imaging: Truth not known– Ex vivo pathological samples: tissue dynamics not

preserved– Animal imaging:

• Hi-res DT-MRI with animal scanner• Possibility to induce pathology: lesions, de-myelination

• Goldish or Silver Standard: Phantom– Nylon fibers embedded in water, interweaved to

simulate crossings: Far from simulation of axons and myelination sheaths

– Computational phantom: Simulated diffusion imaging?– Others?


Validation: DTI Image Analysis

• Reliability, reproducibility:– Reproducibility of scanning: Repeated scans single or

multi-site– Reproducibility of image analysis and/or individual steps

• Key Problems:– Metric to determine differences– Imaging and image analysis come with large set of

parameters– Validation of single processing steps versus validation

of whole system– Relation of validation metric to clinical question and

group findings


Very preliminary attempts

• Repeatability of quantitative tractography-based FA/MD (ISMRM 2005)

• Tool for geometric fidelity of fiber tract ROI (Casey Goodlett)


Validation: Fiber Tracking

• Goal: Evaluate the reproducibility of quantitative tractography (FiberViewer)

• Study: – 6 scans of the same patient with small motion

(MacFall, Duke)– 3 callosal fiber tracts

• Method: – Fiber Extraction

• Selection of a ROI on one scan• Registration for the 5 other scans• Tracking of Fibers

– Analysis across the 6 scans• Diffusion properties: FA, ADC, λ1, λ2, λ3

6 repeated scans DTI average


Validation: 6 repeated scans

Scan1

Scan2…

T B01B02

… Scan6

DTI Average

T B01B06

Extraction

Extraction

Extraction

Scan 2…

…Scan 6

DTI Average

Selection of a ROI

Registration of ROI


Scans' Comparison: Number of Fibers (ROI:essai3-th69)

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Dif 1 Dif 2 Dif 3 Dif 4 Dif 5 Dif 6 Average

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Number of “Fibers” (streamlines): Really not meaningful

DTI Average

The fallacy of #”fibers”


Tract-based diffusion propertiesScans' Comparison: FA (ROI: essai3-th69)

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FA

Mean Mean+std Mean-std

Scans' Comparison: ADC (ROI: essai3-th69)

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Statistics across 6 repeated scans:

Curves of MeanFA and MeanMD, with Standard Deviation

FA

FA

MD


Tract-based diffusion propertiesStatistics across 6 repeated scans: eigenvalues

1Scans' Comparison: Lambda2 (ROI: essai3-th69)

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Scans' Comparison:Lambda3 (ROI: essai3-th69)

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Scans' Comparison: Lambda1 (ROI: essai3-th69)

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Tract-based diffusion properties

FA

Scans' Comparison: FA (ROI: essai3-th69)

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FA

Mean-FA DTIAverage-FA

Scans' Comparison: ADC (ROI: essai3-th69)

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MeanADC DTIAverage-ADC

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MD

Curves of MeanFA and MeanMD in comparison to the Average DTI



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Mean-Lambda1 DTIAverage-Lambda1


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λ1

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Scans' Comparison:Lambda3 (ROI: essai3-th69)

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Tract-based diffusion properties

Curves of mean eigenvalues in comparison to the eigenvalues of the average DTI


Quantitative Results

Table: Results at the center, i.e. at the position of the midsagittal plane, are listed. The second row lists the number of streamlines obtained for each experiment. Although the number of streamlines varies due to the instability of tractography, the resulting diffusion tensor statistics are approximately within 5%std for FA and MD but only 2%std for the first eigenvalue λ1. The FA of the DTI average (last column) is slightly lower than the 6 case mean.

Guido Gerig , Isabelle Corouge, Clement Vachet, Ranga Krishnan and James MacFall, Quantitative Analysis of Diffusion Properties of White Matter Fiber Tracts: A Validation Study, International Society of Magnetic Resonance ISMRM, May 2005 (peer reviewed long abstract)


Geometric reproducibility of tracts

• How to compare geometry tractography results

• Proposed method (BIRN): Map tractography result to binary voxel map, binary overlap test (Dice, kappa stats))– very low enthusiasm

• Brainstorming with Casey Goodlett:– Streamline tracking unstable, ill-posed– Key question: Correspondence?


Work in progress

• Distance measure between sets of bundles

• Give up on point-to-point correspondence between streamlines

• Solution/Tool: Measure geometric distance of points in bundle A to closest point in bundle B

• Measure is non-symmetric


Validation: Tract Comparison

Comparison of scan 1 with original and modified tracking method


Validation: Tract Comparison

Comparison of scan 1 with scan 4


Conclusions

• NAMIC could develop concept, strategy and tools for validation of DTI

• Validation of reproducibility of diffusion properties (tensor stats)

• Validation of geometry of extracted bundles: Metric for bundle distance

• ….

Documents

Validation of DTI Analysis