SE Sequence: 90º, 180º RF Pulses, Readout Gradient e.g., 256 voxels in a row

Transcription

1 Ouline for Today Inroducion o MRI Quanum NMR and MRI in 0D Magneizaion, m(x,), in a Voxel Proon T1 Spin Relaxaion in a Voxel Proon Densiy MRI in 1D MRI Case Sudy, and Cavea Skech of he MRI Device Classical NMR in a Voxel Free Inducion Decay in 1D T2 Spin-Relaxaion Spin-Echo Acquisiion Tissue Conras-Weighing in SE Spin-Echo / Spin-Warp in 2D

2 Spin-Echo

3 SE Sequence: 90º, 180º RF Pulses, Readou Gradien e.g., 256 voxels in a row RF pulses 90º 180º S() Echo G x v Larmor (B 0 ± G x ½ FOV) readou

4 Spin-Echo Generaes an Echo SE inroduces a 180º inversion pulse o refocus he spins and creae an echo. 90º z m z (=0 - ) = m 0 y x m xy () = 0 + Also resuls in higher SNR reducion of suscepibiliy conaminaion. 180º = ½ TE m xy (=TE) ~ m 0 e TE/T2 s() = TE

5 Kenucky Turle-Teleporaion Derby (illusraion of S-E) i = 0 ii iii = ½ TE iv v = TE

6 Muli-SE Pulse Sequence (e.g., wha happens o m z?) n n>1 RF 90º 180º 90º 180º G x readou

7 Spin-Echo Generaes an Echo n=1 A end of firs exciaion, magneizaion (m z ) may no have fully recovered. 90º z m z (=0 - ) = m 0 y x m xy () = 0 + Depends on he issue T1 and sequence TR. 180º = ½ TE This magneizaion is passed on o he nex exciaion (n>1). m z (=TR - ) ~ m 0 (1 - e TR/T1 ) = TR (TR>>½TE)

8 Spin-Echo Generaes an Echo n>1 Afer subsequen exciaion, longiudinal magneizaion ipped ino ransverse plane is a consan funcion of issue T1 & TR. 90º z m z (=0 - ) = m 0 (1 e TR/T1 ) y x m xy () = 0 + Addiional differences in he signal resul of issue T2-induced changes unil measuremen a TE. 180º = ½ TE m z (=0 - ) ~ m 0 (1 e TR/T1 ) m xy (=TE) ~ m z (=0 - ) e TE/T2 s() = TE

9 MRI Signal Srengh a = TE Depends on. s( = TE) ~ PD (1 e TR / T1 ) e TE / T2 proon densiy prior regrowh along z-axis curren dephasing in x-y plane Inheren Parameers T1 T2 PD Operaor Seings TR TE ime since previous exciaion

10 Tissue Conras-Weighing in SE T1-w, T2-w, and PD-w

11 Three Differen MRI Conras Weighings creaed by, and reflecing, hree quie differen physical processes T1 T2 PD

12 For T2-w imaging T2-w Long TR o Minimize T1 Differences Long TR: eliminae T1 impac TE a mid-t2: maximize conras S(~TE) ~ PD (1 e TR 1 / T1 ) e TE / T2 prior regrowh along z-axis curren de-phasing in x-y plane T2-w WM = Whie Maer CSF = Cerebral Spinal Fluid WM CSF Long-T2 issues brigh T2 long

13 T2-w Long TR o Minimize T1 Differences TE ~ mid-t2 o maximize T2 conras TR n m z () TR n+1 m xy () WM CSF WM CSF m xy (=TE) 90 TR 4000 ms WM CSF 90 TE ~ ms ime

14 T1-weighed Shor TE o Minimize T2 Changes TR ~ T1 av o maximize conras Shor TE o minimize T2 differences S(~TE) ~ PD (1 e TR / T1 ) e TE / T2 1 proon densiy prior regrowh along z-axis curren de-phasing in x-y plane T1-w WM CSF T1shor For T1-w: Shor-T1 issues are Brigh

15 T1-weighed Shor TE o Minimize T2 Changes TR ~ T1 avg o maximize T1 conras TR n m z () TR n+1 m xy () WM CSF m xy (=TE) T1-w: Shor T1 Brigh ime 90 TR 500 ms 90 TE CSF WM <20 ms

16 PD-, T1-, & T2-Weighed Spin-Echo Images (1.5 T) Conras T1-weighed T2-weighed PD-weighed TR (ms) TE (ms) Mid Shor < 20 ~T1 avg Long > 2,000 Mid ~T2 avg Long > 2,000 Shor < 20 Brigh Shor T1 Long T2 High PD SNR Middle Lower Bes

17 Spin-Echo / Spin-Warp in 2D

18 Signal Modulaion in 2D Spaial Encoding Signal in 2D plane afer slice exciaion (roaing frame) S S( x, y) dx dy Wha happens if we urn on our linear gradiens? S( G, G ) S( x, y) exp[ 2 i G x G y d ] dx dy This equaion can be expressed in he form of a 2D FT of S(x,y) x y x y S( k, k ) S( x, y) exp[ 2 i k x k y ] dx dy x y x y wih k ( ) G ( ) d and k ( ) G ( ) d x x y y

19 Fourier Transform of MRI Daa in k-space o Real Space S(k x,k y ) Complex k-space S(x,y) ~ FT{S(k x,k y )} Real-space F

20 2D Spaial Encoding So, wha does his mean? k ( ) G ( ) d and k ( ) G ( ) d x x y y Gradien ON: spins precess a differen raes as funcion of locaion Gradien OFF: accumulaed phase as a funcion of locaion encoded ino signal Received signal phase modulaed as funcion of spaial frequency sae Spaial frequency = area under gradien-ime curve. Careful coordinaion of how/when gradiens urn on/off faciliaes navigaion hrough k-space abiliy o sample S(k x,k y ) over necessary k-space domain Le s walk hrough an example

21 k G ( ) d and k G ( ) d 2D Spaial Encoding x x y y x y G x k y G y 0 T echo ro k x

22 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x y G x phase encode k y G y 0 T echo ro k x

23 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y + x G y y - G x k y G y 0 T echo ro k x

24 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y + x G y y - G x k y G y 0 T echo ro k x

25 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x y G x k y G y 0 T echo ro k x

26 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x y G x prephaser k y G y 0 T echo ro k x

27 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x y + G x - G x k y G y 0 T echo ro k x

28 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x y + G x - G x k y G y 0 T echo ro k x

29 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x frequency encode y - G x + G x k y G y 0 T echo ro (READOUT PERIOD) k x

30 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x y - G x + G x k y G y 0 T echo ro (READOUT PERIOD) k x

31 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x y - G x + G x k y G y 0 T echo ro (READOUT PERIOD) k x

32 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x y - G x + G x k y G y 0 T echo ro (READOUT PERIOD) k x

33 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x y - G x + G x k y G y 0 T echo ro (READOUT PERIOD) k x

34 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x y G x k y G y 0 T echo ro k x

35 2D Spaial Encoding k G ( ) d and k G ( ) d x x y y x y G x k y G y 0 T echo ro k x

36 Fourier Transform of MRI Daa in k-space o Real Space S(k x,k y ) Complex k-space (e.g., marix) S(x,y) ~ FT{S(k x,k y )} Real-space 192 lines 256 poins k y y k x x F

37 2D Spin-Echo Sequence s( = TE) ~ PD (1 e TR / T1 ) e TE / T2 TE TR RF G z... G y... G x Signal spin echo ime......

38 Creaion of an MRI Image in 2D k-space each line in k-space from daa obained during one M xy (TE) readou; differen lines for differen phase-encode gradien srengh hen, 2D FT from k-space o real space G y #96 Ampliude G y #1 G y # 96 frequency (k x )

39 Fourier Transform from Pars of k-space o Real Space Fully sampled k-space Cener of k-space (SNR, conras) Ouer k-space (edges, resoluion) F

40 Fourier Transform from Pars of k-space o Real Space Spike in k-space (paern funcion of locaion & inensiy) spike RF Conaminaion (door seal, device in-room, ec) signal leakage Periodic k-space Errors (moion, gradien error, ec) N/2 PE errors F line arifacs RF arifacs FOV/2 ghoss

41 Some Imporan Topics No Addressed Today 3D, 4D Imaging Gradien-Recalled Echo Acquisiion Inversion Recovery (FLAIR and STIR) Fa Sauraion & Suppression Fas Imaging (e.g., EPI) Dynamic Conras Techniques MR Angiography & Flow MRI-Elasography Image SNR Consideraions Image QA, and ACR Accrediaion MRI Safey