Catastrophic structural changes. Chris Rorden Voxelwise Lesion Symptom Mapping Motivation: strengths and limitations. Should we examine acute or chronic injury? Visualizing injury. Mapping brain injury. Normalization lesion maps. Lesion mapping statistics.
“George Miller coined the term ‘cognitive neuroscience’…we already knew that neuropsychology was not what we had in mind…the bankruptcy and intellectual impoverishment of that idea seemed self evident.”
-Michael S. Gazzaniga, 2000
Different MRI modalities show different aspects of injury.
The quality of the MRI scans dramatically influences the analysis.Lesion visualization
T2 (pathological): slower to acquire, therefore usually lower resolution than T1. Excellent for finding lesions.Conventional MRI scans
T2 scans better for identifying extent of injury, but poor spatial resolution.
Acquire chronic T1 (>8 weeks)
Acquire both T1 and T2, use T2 to guide mapping on T1.
Acquire T2, map on normalized iconic brain (requires expert lesion mapper).
Aquire high resolution T2 image, use for both mapping and normalization (e.g. 1x1x1mm T2 ~9min). Requires latest generation MRI.
Note: Many clinicians like FLAIR as it attenuates CSF. Lesion signal similar to T2. Normalization tricky (thick slices, no standard template).
T1Lesion mapping: T1 vs T2
Acute: Subtle low signal on T1, often difficult to see, and high signal (hyperintense) on spin density and/or T2-weighted and proton density-weighted images starting 8 h after onset. Mass effect maximal at 24 h, sometimes starting 2 h after onset.
Subacute (1 wk or older): Low signal on T1, high signal on T2-weighted images. Follows vascular distribution. Revascularization and blood-brain barrier breakdown may cause enhancement with contrast agents.
Old (several weeks to years): Low signal on T1, high signal on T2. Mass effect disappears after 1 mo. Loss of tissue with large infarcts. Parenchymal enhancement fades after several months.
www.strokecenter.org/education/ct-mri_criteria/Imaging acute stroke
Diffusion and Perfusion weighted scans show acute injury:
Diffusion images show permanent injury. Perhaps good predictor of eventual recovery.
Perfusion scans show functional injury. Best correlate of acute behavior.
Difference between DWI and PWI is tissue that might survive.
Diaschisis: regions connected to damaged areas show acute hypoperfusion and dysfunction.
Hypoperfused regions may have enough collateral blood supply to survive but not function correctly (misery perfusion).Imaging Hyperacute Stroke
Static images can detect stenosis and aneurysms (MRA)
Dynamic images can measure perfusion (PWI)
Measure latency – acute latency appears to be strong predictor of functional deficits.
Perfusion imaging uses either Gadolinium or blood as contrast agent.
Gd offers strong signal. However, only a few boluses can be used and requires medical team in case of (very rare) anaphylaxis.
Arterial Spin Labelling can be conducted continuously (CASL). Good CASL requires good hardware.Perfusion imaging
DTI allows us to examine integrity and direction of fiber tracts.
This will allow us to examine disconnection syndromes (see Catani).
Analysis of DTI still in infancy.DTI in stroke
DTI - stroke
Hyperacute imaging will require PWI/DWI.
Older injuries seen on T1 and T2.
Different modalities provide different information: can we combine information across modalities?
Our analysis should be based on individuals with similar delay between injury and observation.Summary
Typically, variance between image and template is used as a measure of difference [variance= (image-template)2 ]
However, region of lesion appears different in image and template
Therefore, normalization will attempt to warp lesioned region
Image Template VarianceLesions disrupt normalization
Binomial analysis: if behavior falls into two mutually exclusive groups (e.g. Broca’s Aphasia, No Broca’s Aphasia).
Traditional test: Fisher-exact or Chi-squared test
Alternative test: Liebermeister quasi-exact test
Continuous analysis: if data is not binomial. (e.g. number of words starting with ‘b’ spontaneously reported in two minutes).
Traditional test: t-test
Alternative test: Brunner-Munzel test.Lesion analysis
People who detect <55 are considered to have a deficit.Binomial Data
We collect data scans and behavioral data from many stroke patients.
Consider 24 patients – half with deficits.
Statistics will identify regions that predict deficit.
12 people w. cancellation deficitStatistics
12 people wo cancellation deficit
The statistical test will differ if the behavioral data is binomial (deficit present or absent) or continuous (performance is graded continuum).Voxelwise statistics
The VLSM t-test is orthogonal to t-tests used for fMRI/VBM:
Deficit defines two groups.
Voxel intensity provides continuous variable.
Voxel intensity (lesion/no lesion) defines two groups.
Behavioral performance provides continuous variable.
Note VLSM group size varies from voxel-to-voxel.
Statistical tests provide optimal power both groups have the same number of observations (balanced).
Therefore, VLSM power fluctuates across voxels
We can not make inferences of voxels that are rarely damaged or always damaged (also true for binomial tests).T-test lesion analysis.
Continuous measure is number of ‘A’s detected.
Performance on neuropsychological tasks is rarely normal.
Skewed distribution: many at ceiling
Data: cancellation performance from 63 stroke patients.
Randomly select 30 patients and analyze, then threshold with FDR.
Repeat 1000 times.
Mean detection shown below: BM test is more sensitive.Brunner-Munzel test
Small lesions unlikely to knock out entire functional region.
Large lesions knock out more regions.
Therefore, previous tests can not distinguish between equipotentiality and localized function.
Logistic regression can covary out lesion volume: is location still a good predictor independent of volume? (Karnath et al., 2004).
As lesion volume correlates well with deficits, LR analysis offers poor statistical power but strong inference.Advanced VLSM statistics
Typical fMRI study uses 3x3x3mm voxels.
Typical VLSM study uses 1x1x1 voxels.
x27 the number of voxels.
Bonferroni correction leads to exceptionally low power.
The good news:
Lesions are large, contiguous across individuals, therefore less within-subject variability than fMRI.
Ideally suited for Permutation Thresholding (Frank et al. 1997; Kimberg et al. in press).
Solution: use either FDR or permutation thresholds.
My NPM provides both.Statistical thresholding
Lesions large and variable.
You will need to test many people to find effects.
You can dramatically increase power by conducting a region of interest analysis, pooling data within a pre-defined area.
E.G. Aron et al. (2003) examine medial, orbital, inferior, middle and superior frontal regions. Find IFG (red) strongly predicts go-nogo performance.Region of Interest Analysis
Bonilha et al, Arq Neuropsiquiatr 2004;62(1):15-20
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For example, if we flip a coin 4 times, we will not always observe exactly two heads and two tails.
There are 16 combinations.
Also, observer responses are not typically fixed. They will not always want to say heads twice and tails twice.
The chance of a psychic precisely guessing all four coin tosses correctly is 1/16.
Fisher’s exact test is much more conservative.
ttttPower of Fisher’s Exact Test
This mid-P is in practice much more accurate than the exact test.
Mathematicians dislike this test, as it is an inelegant kludge.Lancaster’s mid-P
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Fisher’s approach reports the chance of rolling a 7 or higher is (6+5+4+3+2+1)/36 = 58%
Lancaster’s approach says the percentile of 7 or higher is ((6/2)+5+4+3+2+1)/36 = 50%
In other words, there are 6 ways to roll a 7, and Lancaster assumes our observation is in the middle of these possibilities.