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Conventional Spin-echo
Multiparametric segmentation
Bruno Alfano
Multiparametric segmentation Conventional Spin-echo Bruno Alfano - - PowerPoint PPT Presentation
Multiparametric segmentation Conventional Spin-echo Bruno Alfano - - PowerPoint PPT Presentation
Multiparametric segmentation Conventional Spin-echo Bruno Alfano The Method T1-w T2-w PD-w Spin-echo signal Single echo: (TR TE 2)R1 TR R1 1 2e e + TE R2 S K N(H) e = TR(R2
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Spin-echo signal
Double echo: Single echo:
R2 TE R1) TR(R2 R1 TR 2)R1 TE (TR
e e 1 e 2e 1 N(H) K S
⋅ − + − ⋅ − − −
- +
+ −
- =
S = K• N(H)• 1− 2e −[TR −(TE1+TE2)/2]R1 + 2e −(TR−TE1/2)R1 −e−TR⋅R1 1+ e−TR(R2+R1)
- e−TE⋅R2
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R1 R2 PD
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Q M C I
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Cluster stability Advantages:
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Good separation between Brain tissues Advantages:
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Low sensitivity to RF inhomogeneity Advantages:
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Grey matter White matter Pallidus Putamen CSF Fat Muscle
Segmented image
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WD (mean, ml) MR (mean±SD) MR Var. Coeff. Simulated GM 370 376±12 3.2% Simulated WM 639 611±17 2.7% Isotonic saline 441 443±11 2.6% Total 1450 1430±15 1.1%
Validation
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Multiparametric segmentation
Alfano B, Brunetti A, Covelli EM, Quarantelli M, Panico MR, Ciarmiello A, Salvatore M. Unsupervised, automated segmentation of the normal brain using a multispectral relaxometric Magnetic Resonance approach Magn Reson Med 37 (1) 84-93, 1997 Alfano B, Quarantelli M, Brunetti A, Larobina M, Covelli E M, Tedeschi E, Salvatore M. Reproducibility of intracranial volume measurement by unsupervised multispectral brain segmentation Magn Reson Med 39(3) 497-9, 1998 Alfano B, Brunetti A, Larobina M, Quarantelli M, Tedeschi E, Ciarmiello A, Covelli EM, Salvatore M. Automated segmentation and measurement of global white matter lesion volume in patients with multiple sclerosis J Magn Reson Imaging 12 (6) 799-807, 2000 A Brunetti, A Postiglione, E Tedeschi, A Ciarmiello, M Quarantelli, E M Covelli, G Milan, M Larobina, A Soricelli, A Sodano, B Alfano. Measurement of global brain atrophy in Alzheimer's disease with unsupervised segmentation of Spin-Echo MRI studies J Magn Reson Imaging 11 260-266, 2000 Quarantelli M, Ciarmiello A, Morra VB, Orefice G, Larobina M, Lanzillo R, Schiavone V, Salvatore E, Alfano B, Brunetti A. Brain tissue volume changes in relapsing-remitting multiple sclerosis: correlation with lesion
- load. Neuroimage. 2003 Feb;18(2):360-6
Complete description in: Principal applications in:
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Applictions:
Ageing Alzheimer Disease Multiple Sclerosis
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0,1 0,2 0,3 0,4 0,5 0,6 10 20 30 40 50 60 70 80 %G %CSF y = 0,53336 + -0,0013319x R= 0,68523 y = 0,031075 + 0,0015967x R= 0,65099
%G Age
Age related changes Age related changes
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0,1 0,2 0,3 0,4 0,5 10 20 30 40 50 60 70 80 % W E/W y = 0,42165 + -0,00031626x R= 0,20917 y = 0,015078 + 9,3152e-05x R= 0,24235
%W Age
Age related changes Age related changes
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Applications:
Aging Alzheimer Disease Multiple Sclerosis
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0,1 0,2 0,3 0,4 0,5 0,6 10 20 30 40 50 60 70 80
ALZHEIMER
%G %CSF
%G Age
% GM and CSF
EARLY-ONSET AD (n = 8) Age
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0,1 0,2 0,3 0,4 0,5 10 20 30 40 50 60 70 80
ALZHEIMER
% W
%W Age
% Sostanza bianca
Età EARLY-ONSET AD (n = 8)
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Applications:
Aging Alzheimer Disease Multiple Sclerosis
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Multiple Sclerosis
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GM Atrophy vs. Lesion Load Δ f-GM (% ICV)
y = -2.3x + 0.02 R = 0.71
f-Plaques (% ICV)
- 16%
- 12%
- 8%
- 4%
0% 4%
0% 2% 4% 6%
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Major Advantages
Uses diagnostic images (no need of extra acquisitions for segmentation) Fully automated Compatible with low-end scanners Includes fully automated segmentation of pathologic WM (MS plaques and leukoarayosis)
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