진단에 유용한 관류 자기 공명 영상에 대한 많은 연구가 진행되고있으나 아직 실제 상황에서의 기초적 이해가 부족하여 이를 해결하고자 본 연구를 진행하였다.
기존의 방법으로 얻은 관류 정보는 조영제에 의한 T1, T2*
감소 효과 중 하나는 무 시하고 다른 하나를 강조하여 각각 얻었으나, 본 논문에서 새로 개발한 방법을 이 용하여 두 가지 효과를 동시에 획득하고, 수학적으로 이 둘을 구별하였다. 구별된 T1, T2*
감소 효과로부터 관류 영상에서 Gd-DTPA에 의한 시간에 따른 신호 변화 를 이해할 수 있었다. 관류 영상은 이제까지 자화율 대조법을 이용한 실험에서 보 고된 바 없는 관류 팬텀을 고안하여 얻었다. 기존의 방법과 본 논문에서 개발한 방법으로 관류 정보(관류량, 투과도)를 구해 비교하면, 기존의 방법으로 얻은 값이 무시한 다른 하나의 T1 혹은 T2*
감소 효과의 영향으로 작게 나왔다. 따라서, 새 로 개발한 방법으로 구별된 두가지 효과로부터 좀더 정확한 관류 정보를 얻을 수 있었고, 이를 컴퓨터 가상 실험을 통해 확인할 수 있었다.
본 실험에서 개발한 방법으로 Gd-DTPA에 의한 신호 변화를 올바로 이해하여, 혈관 투과도와 같은 미세한 변화를 정확하게 얻을 수 있었고, 이와 같이 개선된 관류 자기 공명 영상과 관류 정보는 혈류, 미소 순환과 관련된 질환, 종양 성장 등에 관한 중요한 정보를 제공할 것으로 기대된다.
참고문헌
1. Robert DA, Detre JA, Bolinger L, Insko EK, Leigh JS. Quantitative magnetic resonance imaging of human brain perfusion at 1.5 T using steady-state inversion of arterial water. Porc Nat Acad Sci.(USA) 1994;91:33-37.
2. Reith W, Heiland S, Erb G, Benner T, Forsting M, Sartor K. Dynamic contrast-enhanced T2*-weighted MRI in patients with cerebrovascular disease.
Neuroradiology 1997;39:250-257.
3. Belliveau JW, Rosen BR, Kantor HL, Rzedzian RR, Kennedy DN, McKinstry RC, et al. Functional cerebral imaging by susceptibility-contrast NMR. Magn Reson Med 1990;14:538-546.
4. Haraldseth O, Jones RA, Müller TB, Fahlvik AK, Øksendal AN. Comparison of dysprosium DTPA BMA and superparamagnetic iron oxid particles as susceptibility contrast agents for perfusion imaging of regional cerebral ischemia in the Rat. J Magn Reson Imaging 1996;6:714-717.
5. Knopp EA, Cha S, Johnson G, Mazumdar A, Golfinos JG, Zagzag D, et al.
Glial neoplasms : Dynamic contrast-enhanced T2*-weighted MR imaging.
Radiology 1999;211:791-798.
6. Aronen HJ, Gazit IE, Louis DN, Buchbinder BR, Pardo FS, Weisskoff RM, et al. Cerebral blood volume maps of gliomas: Comparison with tumor grade and histologic findings. Radiology 1994;191:41-51.
7. Donahue KM, Krouwer HGJ, Rand SD, Pathak AP, et al. Utility of
simultaneously acquired gradient-echo and spin-echo cerebral blood volume and morphology maps in brain tumor patients. Magn Reson Med 2000;43: 845-853.
8. Sugahara T, Korogi Y, Kochi M, Ikushima I, Hirai T, Okuda T, et al.
Relationship of MR determined cerebral blood volume maps to histologic and angiographic vascularities of gliomas. AJR 1998;171:1479-1486.
9. Miyati T, Banno T, Mase M, Kasai H, Shundo H, Imazawa M, et al. Dual
dynamic contrast-enhanced MR imaging. J Magn Reson Imaging 1997;7:230-235.
10. Vonken EJ, van Osch MJ, Bakker CJ, Viergever MA. Simultaneous
quantitative cerebral perfusion and Gd-DTPA extravasation measurement with dual-echo dynamic susceptibility contrast MRI. Magn Reson Med 2000;43:820 -827.
11. Erlemann R, Reiser MF, Peters PE, Vasallo P, Nommensen B, Kusnierz-Glax CR, et al. Musculoskeletal neoplasms: static and dynamic Gd-DTPA-enhanced MRI. Radiology 1989;171:767-773.
12. Verstraete KL, Van der Woude HJ, Hogendoorn PC, De-Deene Y, Kunnen M, Bloem JL. Dynamic contrast-enhanced MRI of musculoskeletal tumors : basic principles and clinical applications. J Magn Reson Imaging 1996:6:311-321.
13. Hawighorst H, Libicher M, Knopp MV, Moehler T, Kauffmann GW, Kaick G. Evaluation of angiogenesis and perfusion of bone marrow lesions : Role of semiquantitiative and quantitative dynamic MRI. J Magn Reson Imaging 1999;10:286-294.
14. Shamens D, Kuwatsuru R, Vexler V, Muhler A, Brasch RC. Measurement of capillary permeability to macromolecules by dynamic magnetic resonance imaging:a quantitative non-invasive technique. Magn Reson Med 1993;29:616 -622.
15. Brasch R, PhamC, Shames D, Roberts T, van Dijke K, vanBruggen N, et al.
Assessing tumor angiogenesis using macromolecular MR imaging contrast media. J Magn Reson Imaging 1997;7:68-74.
16. Su MY, Jao JC, Nalcioglu O. Measurement of vascular volume fraction and blood-tissue permeability constants with a pharmacokinetic model : Studies in rat muscle tumors with dynamic Gd-DTPA enhanced MRI. Magn Reson Med 1994;32:714-724.
18. Crone C. The permeability of capillaries in varioius organs determined by the use of the "indicator diffusion" method. Acta Physiol Scand 1963;58:292-305.
19. Pham CD, Roberts TP, van Bruggen N, Melnyk O, Mann J, Ferrara N, et al. Magnetic resonance imaging detects suppression of tumor vascular
permeability after administration of antibody to vascular endothelial growth factor. Cancer Invest 1998;16:225-230.
20. Padhani AR, MacVicar AD, Gapinski CJ, Dearnaley DP, Parker GJ, Suckling J, et al. Effects of androgen deivation on prostatic morphology and vascular permeability evaluated with MR imaging. Radiology 2001;218:365-374.
21. Bogdanov A Jr, Marecos E, Cheng HC, Chandrasekaran L, Krutzsch HC, Roberts DD, et al. Treatment of experimental brain tumors with
trombospondin-1 derived peptides: An in vivo imaging study. Neoplasia 1999;1:438-445.
22. van Vaals JJ, Brummer ME, Dixon WT, Tuithof HH, Engels H, Nelson RC, et al. "Keyhole" method for accelerating imaging of contrast agent uptake. J Magn Reson Imaging 1993;3(4):671-675.
23. Dwight G. Nishimura. Principles of Magnetic Resonance Imaging, 1996.
24. Hashemi RH, Bradley jr WG, MRI the basics, Williams & Wilkins, 1997.
25. 김대홍. 투영 영상화를 이용한 3차원 자기 공명 혈관 영상법, 박사학위논문, 연세대학교대학원 물리학과; 2002.
26. Haacke EM, Brown RW, Thompson MR, Venkatesan R. Magnetic Resonance imaging physical principles and sequence design. Wiley-Liss;1999.
27. Solomon I. Relaxation processes in a system of two spins. Phys Rev 1955;
99:559-565.
28. Bolembergen N, Purcell Em, Pound RV. Relaxation effects in nuclear magnetic resonance absorption. Phys Rev 1948;73:679-710.
29. Bloembergen N. Proton relaxation times in paramagnetic solutions. J Chem
Phys 1957; 572-593, 595-596.
30. Rosen BR, Belliveau JW, Vevea JM, Brady TJ. Perfusion imaging with NMR contrast agents. Magn Reson Med. 1990;14(2):249-65.
31. Jackson JD. Classical electrodynamics, 2nd ed. New York : John Wiley &
Sons;1975. p168-327
32. James TL. Nuclear magnetic resonance in biochemistry. Academic Press;
1975.
33. Pedersen M, Morkenborg J, Jensen FT, Stodkilde-Jorgensen H, Djurhuus JC, Frokiaer J. In vivo measurements of relaxivities in the rat kidney cortex. J Magn Reson Imaging 2000;12:289-296.
34. Hendrick RE, Haacke EM. Basic physics of MR contrast agents and maximization of image contrast. J Magn Reson Imaging 1993;3:137-48.
35. Weisskoff RM, Zuo CS, Boxerman JL, Rosen BR. Microscopic susceptibility variation and transverse relaxation : Theory and experiment. Magn Reson Med 1994;31: 601-610.
36. Thomas Benner, Sabine Heiland, Gunter Erb, Michael Forsting, Klaus Sartor.
Accuracy of gamma-variate fits to concentration-time curves from dynamic susceptibility-contrast enhanced MRI: influence of time resolution, maximal signal drop and signal-to-noise. Magnetic Resonance Imaging. 1998;15(3), 307-317.
37. Kazuro Iwata. Alternative Method for calculating right ventricular ejection fraction from first-pass time-activity curves. J Nucl Med. 1990;29:1990-1997.
38. Lu D, Monahan WG. Effect of sample numbers on the kinetic data analysis of MR contrast agents. Magn Reson Med. 1993;30:131-134.
39. Tofts PS. Modeling tracer kinetics in dynamic Gd-DTPA MR imaging. J Magn Reson Imaging 1997;7:1-4.
41. Tofts PS, Kermode AG. Measurement of the blood-brain barrier
permeability and leakage space using dynamic MR imaging-1. Fundamental concepts. Magn Reson Med 1991;17:357-367.
42. Larsson HBW, Christiansen P, Stubgaard M, et al. In-vivo calculation of the unidirectional influx constant across the blood-brain barrier using MRI. in : Proceddings of the SMRM 9th Annual Metting, New York, 1990;2:752.
43. Brix G, Semmler W, Port R, Schad LR, Layer G, Lorenz WJ.
Pharmacokinetic parameters in CNS Gd-DTPA enhanced MR imaging. J Comput Assist Tomogr 1991;15:621-628.
44. Bihan DL. Diffusion and perfusion magnetic resonance imaging. New york:
Raven Press; 1995. p. 201-215.
45. 김은주. 뇌의 관류 자기 공명 영상으로부터의 측부 혈류 영상 재구성.
석사학위논문, 이화여자대학교 대학원 물리학과; 2000.
46. Kremmer T, Boross Lasxlo. Gel chromatography. Wiley-Interscience Publication. 1979.
부록
부록 1. Sephadex의 SQUID 측정 결과
SQUID(Superconducting QUantum Interference Device, 초전도양자간섭소자) 를 이용하여 dry powder Sephadex의 magnetization을 측정하였다. 측정 장치는 Quantum Design 사의 MPMS이다. 그림 (부록1)과 같은 SQUID 측정용 tube에 마 른 Sephadex 분말을 넣고, 300 K에서 자기장을 0.3 ~2.0 Tesla까지 변화시키면서 4번씩 측정하였다. 그림 (부록2)에 나타난 것과 같이 자기장의 세기가 커질수록 magnetization이 감소하는 반자성 물질(diamagnetic material)이다(측정은 한국 기 초과학지원센터에 의뢰한 결과이다).
그림 (부록 1). SQUID 측정 장치에
사용한 tube 내에 들어있는
Sephadex G10. 측정에 사용된 Sephadex 마른 분말의 질량은 0.1288 g이다.
그림 (부록 2). SQUID를 사용하여 측정한 Sephadex G10, G25 마른 분말의 magnetization.
(emu = Gauss/cm3)
SQUID
Field (Tesla)
0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2
Magnetization (emu)
-1.6x10-3 -1.4x10-3 -1.2x10-3 -1.0x10-3 -800.0x10-6 -600.0x10-6 -400.0x10-6 -200.0x10-6 0.0
G10 G25
부록 2. 투석기 용어 해설
UF (Ultrafilteration; 한외 여과)
한외여과는 "미세한 구멍을 가진 여과기를 통하여 극단적으로 미세한 물질을 분리하는 여과:로 정의되며 모세혈관벽에서 일어나는 혈장의 여과가 가장 대표적 인 예이다. 한외여과는 막간정수압(transmembrane pressure) 뿐만이 아니라 투석 막의 두께, 구멍의 크기등에도 좌우되는데 이러한 투과성을 한외여과계수 (ultrafiltration coefficient ; UFR : Kuf)로 나타내며, Kuf는 mmHg 압력당, 분당 빠 져 나오는 물의 양(mililiter)으로 표시된다[ml/min/mmHg].
투석기내의 정수압은 혈액 투석시에 혈액쪽의 압력은 50 내지 100 mmHg이며 투석액쪽의 압력은 -450 mmHg까지 낮출 수 있으며 양쪽의 압력 차이를 이용하 여 한외여과를 얻을 수 있다. 막간정수압은 0에서 500 mmHg까지 조절이 가능하 다문헌1.
1. 한외여과계수로부터 한외여과의 계산
혈액투석 과정에서 과잉의 체액을 빼내기 위해 한외 여과를 유도하는데 이때 수분 이동량의 계산에 한외여과계수가 필요하다. 한외여과 계수와 막통과압 사이 에는 다음과 같은 관계가 있다.
Kuf (ml/min/mmHg) = water flux/ΔP = Qf/(Pb-Pd) Qf : 수분이동, Pb:평균혈액측 압력, Pd: 평균 투석액측 압력
2. 투석방법
전형적인 혈액투석에서는 혈액과 투석액을 계속적으로 서로 반대방향으로 투 석기에 펌프질하여 농도경사를 외대로 해주며, 혈류는 300∼400 ml/min, 투석액 유속은 500∼800 ml/min으로 해준다.
표준 투석막은 cellulose나 cuprophane으로 만든것인데, 수분 투과성이 적고, 한외 여과계수는 8 ml/mmHg/hr 이하이다. 고효율 혈액투석은 표준 혈액 투석기 의 투석막을 사용하되 한외여과계수가 약간 큰 (8∼20 ml/mmHg/hr) 투석막을
사용하며, 요소 청소율을 높이기 위하여 투석기의 표면적을 높이고 (1.5∼2.0 m2), 혈류량을 평균 400 ml/min로 증가시키는 투석 방법이다문헌2.
참고 문헌
문헌1. http://www.ksod.co.kr/Ksb.htm 김 순 배, 혈액투석의 원리 (Principles of Hemodialysis) ; 용질 및 수분이동의 기전 (Mechanisms of solute and water transport)
문헌2. 연세대학교 신장질환연구소 편저, 신장학 말기신부전증의 치료 ; 혈액투 석, 의학문화사; 1999. p.861-899
부록 3. 영상 후처리 과정 프로그램 (일부)
동시 획득 T1/T2*
강조 경사 자장 펄스열을 사용하여 얻은 P-file로부터 영상 재구성, 관심 영역으로부터 신호 강도 곡선을 얻는 프로그램의 일부분이다. IDL 이용하여 프로그래밍하였다.
READ,set,num,PROMPT = '# image sets & # images in a set [3,80] ' filen = sindgen(set)
name1 = sindgen(set) & name2 = sindgen(set) for j=0, set-1 do begin
print, ' Select rawdata..(P File)'
filen_p = pickfile(/read,/noconfirm,filter='*', GET_PATH = Dir) filen(j) = filen_p
print, j, filen(j)
opt0 = ''
READ,opt0,PROMPT = 'The name of P-file begin with 0 (yes/no = 1/0) '
opt = ''
READ,opt,PROMPT = 'Enter the name option (1-name1 / 2- name1, name2) '
IF (opt eq 1) THEN BEGIN
READ,name1_p,PROMPT = 'Enter the number of P(name1-#####) ' name1(j) = name1_p
ENDIF ELSE BEGIN
READ,name1_p,name2_p,PROMPT='Enter the number of P(name1-##)(name2-###) ' name1(j) = name1_p & name2(j) = name2_p
ENDELSE PUSHD, Dir
head = bytarr(39940)
;--- read head if (j eq 0) then begin
openr,1,filen(0) readu,1,head
ExamPtr = 36872 & SerPtr = 37896 & ImgPtr = 38916 fovx = FLOAT(head,ImgPtr+34)
fovy = FLOAT(head,ImgPtr+38) TR = LONG(head, ImgPtr+194) TE = LONG(head,ImgPtr+202) TE2 = LONG(head,ImgPtr+206)
nex = FLOAT(head, ImgPtr+218) slquant = FIX(head, ImgPtr+398) fphases = LONG(head, ImgPtr+738)
b1 = intarr(xres,yres,slquant) c1 = intarr(xres,yres,slquant) b2 = intarr(xres,yres,slquant) c2 = intarr(xres,yres,slquant) r1 = complexarr(xres,yres,slquant) r2 = complexarr(xres,yres,slquant) img1 = FLTARR(xres, yres, slquant) img2 = FLTARR(xres, yres, slquant) Timg1 = FLTARR(xres, yres, slquant*set) Timg2 = FLTARR(xres, yres, slquant*set) Timg2_c = FLTARR(xres, yres, slquant*set)
readu,1,a1 close,1
IF (!VERSION.OS eq 'linux') OR (!VERSION.OS eq 'Win32') OR $
(!VERSION.OS eq 'windows') THEN BYTEORDER,a1,/SSWAP
b1(0:(xres-1),0:(yres-1),0) = a1(0,0:(xres-1),0:yres-1) c1(0:(xres-1),0:(yres-1),0) = a1(1,0:(xres-1),0:yres-1) b2(0:(xres-1),0:(yres-1),0) = a1(0,xres:(2*xres-1),0:yres-1) c2(0:(xres-1),0:(yres-1),0) = a1(1,xres:(2*xres-1),0:yres-1)
r1(*,*,0) = complex(b1(*,*,0),c1(*,*,0)) r2(*,*,0) = complex(b2(*,*,0),c2(*,*,0))
img1(*,*,0) = abs(shift(fft((r1(*,*,0)),-1), xres/2,0 ))
endif ; read head j=0
endif else begin ind = yres endelse
b1(0:(xres-1),0:(ind-1),i) = 0 c1(0:(xres-1),0:(ind-1),i) = 0 b2(0:(xres-1),0:(ind-1),i) = 0 c2(0:(xres-1),0:(ind-1),i) = 0
b1(0:(xres-1),ind:(ind2-1),i) = a1(0,0:(xres-1),0:ind2-ind-1) c1(0:(xres-1),ind:(ind2-1),i) = a1(1,0:(xres-1),0:ind2-ind-1) b2(0:(xres-1),ind:(ind2-1),i) = a1(0,xres:(2*xres-1),0:ind2-ind-1) c2(0:(xres-1),ind:(ind2-1),i) = a1(1,xres:(2*xres-1),0:ind2-ind-1) endelse
r1(*,*,i) = complex(b1(*,*,i),c1(*,*,i)) r2(*,*,i) = complex(b2(*,*,i),c2(*,*,i))
endfor ; slquant
---for i=1, slquant-1 do begin
img1(*,*,i) = abs(shift(fft((r1(*,*,i)),-1), xres/2,0 )) img2(*,*,i) = abs(shift(fft((r2(*,*,i)),-1), xres/2,0 ))
endfor
Timg1(*,*,slquant*j:slquant*(j+1)-1) = img1 Timg2(*,*,slquant*j:slquant*(j+1)-1) = img2 print, 'Number of Set = ', j
endfor ; set ---WINDOW, 1, XSIZE=2*xres, YSIZE=set*yres+1
for j=0, set-1 do begin
tvscl, abs(Timg1(*,*,j*slquant)),j*2 tvscl, abs(Timg2(*,*,j*slquant)),j*2+1 endfor
PROFILES,[Timg1(*,*,0), Timg2(*,*,0)], wsize = 0.6
;--- curve
!P.MULTI = [0, 1, 2]
index = indgen(sd(3))
BOX_CURSOR,x0,y0,nx,ny,/INIT x0 = x0/zoom & y0 = y0/zoom
DR2_c = 1000000.* ALOG((Dimg1*R2_ref)/(Dimg2*R1_ref))/(TE2-TE)
;---M0 = FLTARR(slquant*set) T22 = FLTARR(slquant*set)
for k=0, (slquant*set)-1 do begin ; linfit to get mo at each t
M0(k) = exp((alog(dimg1(k))*TE2 - alog(dimg2(k))*TE)/ (TE2-TE)) T22(k) = 1000000.* (ALOG(Dimg1(k))-ALOG(Dimg2(k)))/(TE2-TE) endfor
;---PLOT,index, Dimg1,title='Signal Intensity vs. time', $
XTITLE='phase -> time', YTITLE='Sig Int', /XSTYLE oplot,index, Dimg2, color=128
plot, index, DR2,title='DR2 vs. time', $
XTITLE='phase -> time', YTITLE='DR2', /XSTYLE oplot, index, DR2_c, color=128
oplot, index, M0, color=15000 oplot, index, T22, color=30000
READ,NewBox,PROMPT='Want to try new box?(1=yes,0=no) ' ENDWHILE
READ, numROI, PROMPT="Want to another ROI to save ROI"
endwhile ; write ROI curve (grp(zth))
end
Abstract
The method of MRI for understanding of hemodynamics using simultaneous T
1/T
2*weighted gradient echo pulse
Eun-Ju Kim
Department of Medical Science The Graduate School, Yonsei University
(Directed by Professor Jin-Suck Suh)
The perfusion images provided useful information about grade of tumor and prognosis, but the basic principle was not fully understood yet. To understand these basic principles, we developed a simultaneous T1/T2*
weighted gradient echo pulse sequence, perfusion phantoms and post processing method.
The simultaneous T1/T2*
weighted gradient echo pulse sequence based on conventional dual gradient echo pulse, and multi-phases method for dynamic scan and key-hole technique for improving temporal resolution were added.
The perfusion information by conventional methods was obtained from simply weighted T2*
shortening or T1 shortening effect by bolus injection of Gd-DTPA respectively. In this study, using simultaneous T1/T2*
weighted gradient echo pulse sequence, both T2*
shortening and T1 shortening effects could be obtained during one injection. These two effects were separated perfectly.
Through post processing, corrected ΔR*2(=1/T2* ,t-1/T2*
,0) could be acquired from separated T2*
shortening effect, and corrected ΔR1
(=1/T1,t-1/T1,0) from separated T1 shortening effect. These corrected ΔR*2
and ΔR1-curves satisfied linear correlation corresponding to Gd-DTPA concentration. The relaxivity ℜ2*
, ℜ1 (mM-1sec-1) values from corrected ΔR*2 and ΔR1-Gd concentration curves were greater than those from uncorrected
ΔR*2 and ΔR1 curves.
Sephadex and dialyzer were used as a perfusion phantom. The Sephadex phantom perfusion images were acquired during a bolus injection of Gd-DTPA. The water volume could be obtained from⌠
⌡ΔR1dt. The ratio (Sephadex G25/G10) of⌠⌡( correcte d ΔR1)dt was included in the tolerance of the theoretical value.
To obtain permeability, the hollow fiber type dialyzer was used as a blood vessel phantom. The outside of hollow fiber was filled with high concentration of Gd-DTPA solution (about 4 mM). The low concentration Gd solution (1.0~2.0 mM) was perfused through the inside of hollow fiber. The uncorrected ΔR1values were less than corrected ΔR1 values, which was confirmed by computer-simulation using MathematicaⓇ4. The permeability from outside to inside of hollow fiber was obtained by fitting of biexponential function which was based on two compartments model. When the flow rate was high, the permeability was greater than that of low flow rate and it was independent of Gd-concentration inside of fiber. The permeability obtained from corrected ΔR1-time curve was greater than that from uncorrected ΔR1-time curve.
In this study, T2*
and T1 shortening effects by Gd-DTPA were separated
sequence. The perfusion values (water volume, permeability) calculated by our method using corrected ΔR*2 or ΔR1 were greater than those by conventional methods. These improved results gave more practical information related with angiogenesis.
ꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏꠏ Key Words : simultaneous T1/T2*
weighted gradient echo pulse sequence, Gd-DTPA, water volume, permeability