neuroinformatics challenges in mri data integration hugo schnack rudolf magnus institute of...
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![Page 1: Neuroinformatics challenges in MRI data integration Hugo Schnack Rudolf Magnus Institute of Neuroscience Department of Psychiatry University Medical Centre](https://reader036.vdocument.in/reader036/viewer/2022062721/56649f275503460f94c3ec1f/html5/thumbnails/1.jpg)
Neuroinformatics challenges in MRI data integration
Hugo Schnack
Rudolf Magnus Institute of NeuroscienceDepartment of Psychiatry
University Medical Centre Utrechtwww.smri.nl ([email protected])
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Our recent acquisition:7 Tesla scanner
Officially opened, December 4th, 2007
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Our research
Investigation of morphological brain abnormalities in psychiatric disorders (schizophrenia)Q: Are brains of schizophrenia patients smaller?
Magnetic Resonance Imaging (MRI) scans of patients and healthy comparison subjects
Image processing and statistical analysesA: Yes, statistically they are.
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Schizophrenia patients have less gray matter than healthy subjects
N=310 for this resultLarge variation in brain morphology
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Heritability of brain changes in schizophrenia
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Heritable brain changes in schizophrenia
P-C N-N P-C N-N
N=2x44 for this result(Discordant) twins are sparse
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We Need More Twins!
International collaborations
EUTwinsS (European Twin Study Network on Schizophrenia)Germany, the UK, The Netherlands, Spain, Hungary and Switzerland
STAR (Schizophrenia Twin and Relatives) consortiumHeidelberg, Jena, London, Utrecht, Helsinki
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Can we combine brain scans from different scanners (machines, manufacturers, acquisition protocols, field strength, in time, …)?
What do we mean by ‘Can’? (increase in power; closer to ‘the truth’ – can we know the truth?)
Is there a measure of goodness for (processed) MRI scan?
Multicenter MRI
Goal: combine MRI data from different scanners
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Scanner
Truth
Derivatives:Segments, volumes, shapes, fiber tracts, …
Processing
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Another
ScannerScannerNow
ScannerTwo years later
TruthNow
TruthTwo years later
Derivatives:Segments, volumes, shapes, fiber tracts, …
Derivatives:Segments, volumes, shapes, fiber tracts, …
Processing (+2 yr)
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Multicenter MRI(STAR)
STAR multicenter MRI calibration study:Schnack et al. 2004. Human Brain Mapping 22: 312-320.
Site scanner manufacturer and type
acquisition summary
protocol / orientation / scan time
voxel dimensions (mm) / (no. slices)
TE
(ms)
TR
(ms)
flip
angle
Utrecht, reference
repeated 1
repeated 2
Philips NT 1.5 T 3D-FFE coronal 11 min
111.2 (180)4.6 30 30˚
London GE Signa 1.5 T 3D-SPGR coronal 19 min
0.7810.7811.5 (124)5 35 35˚
Heidelberg Picker Edge 1.5 T 3D-FLASH sagittal 13 min
111.5 (128)3 30 30˚
Jena Philips ACS II 1.5 T 3D-FFE sagittal 11 min
111 (256)5 13 25˚
Helsinki Siemens Magnetom Impact 1.0 T
MPRAGE sagittal 7 min
111.2 (128)4.4 11.4 12˚
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Multicenter MRI(STAR)
STAR multicenter MRI calibration study:Schnack et al. 2004. Human Brain Mapping 22: 312-320.
Site scanner manufacturer and type
acquisition summary
protocol / orientation / scan time
voxel dimensions (mm) / (no. slices)
TE
(ms)
TR
(ms)
flip
angle
Utrecht, reference
repeated 1
repeated 2
Philips NT 1.5 T 3D-FFE coronal 11 min
111.2 (180)4.6 30 30˚
London GE Signa 1.5 T 3D-SPGR coronal 19 min
0.7810.7811.5 (124)5 35 35˚
Heidelberg Picker Edge 1.5 T 3D-FLASH sagittal 13 min
111.5 (128)3 30 30˚
Jena Philips ACS II 1.5 T 3D-FFE sagittal 11 min
111 (256)5 13 25˚
Helsinki Siemens Magnetom Impact 1.0 T
MPRAGE sagittal 7 min
111.2 (128)4.4 11.4 12˚
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Multicenter MRI
6 healthy subjects scanned in Utrecht (twice), Heidelberg, Jena, London
Processed with image processing pipeline in Utrecht
1. Measure reliability (fixed algorithms)
2. Calibrate algorithms (tunable parameters)
Goal: combine MRI data from different scanners
Calibration study
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Multicenter MRI
Reliability of tissue volumes (ICC)
Gray White Utrecht repeated 0.97 1.00 Utrecht – London 0.94 0.99 London – Jena 0.85 0.94 Jena – Utrecht 0.88 0.94
ICC = true variation / (true variation + error) > 0.7 = “good”
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Voxelwise reliability (ICC)
Utrecht repeated scans:97% of the voxels has ICC > 0.7 (“good”)
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Multicenter MRI:Voxelwise reliability (ICC)
Neff (gain factor)
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ChallengesComparability of MR images (scanners)Comparability of analysis tools (software)Comparability of their interactions
Creation of gold standards (“truths”)Create better simulated MR images
Other “calibration” mechanisms (insteadof sending out 6 people around Europe?)
How to present / summarize /visualize reliability? (generalizable?)
Other modalities…
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Rudolf Magnus Institute of NeuroscienceDepartment of Psychiatry
University Medical Centre Utrechtwww.smri.nl ([email protected])
ContributorsHugo SchnackNeeltje van HarenRachel BrouwerHilleke Hulshoff Pol (head Neuroimaging Psychiatry)René Kahn (head Dept. Psychiatry)