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2 허미옥 외: 급성 뇌경색에서 확산 및 관류 MR 영상을 이용한 허혈성 반영부의 소생가능성 평가 후 수분 이내에 정확하게 찾아낼 수 있고 관류 MR 영상을 통 해 경색부위 주위의 혈류감소부위를 평가할 수 있는데 관류확산 불일치(perfusion-diffusion mismatch)부위가 허혈성 반 영부를 반영한다는 것이다. 그러나, 일반적으로 관류-확산 불 일치부위는 시간이 지나더라도 모두 경색으로 진행되는 것은 아니며 혈류가 감소되어 있지만 시간이 지나도 경색으로 이행 되지 않는 부위를 포함하므로 허혈성 반영부를 과다하게 평가 하는 것으로 알려져 있다(8). 따라서 관류 확산 불일치가 있 더라도 경색으로 진행될 부위와 생존할 부위를 구분하기 위해 서는 관류지도의 단순한 정성적 분석으로는 알기 어려우며 관 류 저하의 정도를 정량적으로 평가하여 두 부위를 구분하는 연구들이 시도되고 있다(9-11). 관류 정도를 정량적으로 평 가하는 데는 대체로 상대적 뇌혈류량(relative cerebral blood flow; rcbf), 뇌혈용적(relative cerebral blood volume; rcbv), 및 평균통과시간(mean transit time; MTT) 지도를 이 용하며 지도상 경색진행부위와 생존부위의 관류량을 측정하여 경계치를 찾는 방법이 주로 사용된다. 그러나 현재까지 나온 결과는 어떤 관류지도가 가장 유용한지, 경계치가 얼마인지에 대한 의견은 서로 일치되지 않는다(9-11). 또한, 경색 후 시 A B C D 간경과에 따라 각 부위의 측정치나 경계치가 달라질 수 있을 것으로 생각되나 이에 대한 연구는 찾기 어려웠다. 본 연구에서는 관류 MR 영상을 정성적으로 분석하여 1) 경 색위험부위를 저혈류 생존부위와 구분할 수 있는지 2) 시간 경 과에 따라 각 부위의 관류량에 차이가 있는지 알고자 하였다. 대상과 방법 대상환자 2003년 1월부터 2003년 12월까지 1년간 급성 뇌경색의 증 상으로 응급실로 내원한 환자 중 연구조건에 맞는 22명을 대 상으로 하였다. 연구에 포함시킨 조건은 1) 중뇌동맥영역의 뇌 경색 환자로 2) 증상 발생 후 12시간 이내에 확산 및 관류 영 상을 포함한 MR검사가 시행되었으며, 3) 1주일 이내에 추적 MR 또는 CT 검사를 시행했던 환자를 대상으로 하였고 1) 경 색부위 용적이 5mL 이하의 작은 경색, 2) MTT map상 관 류-확산 불일치가 없는 환자 및 3) 혈전용해술을 시행한 환 자는 제외하였다. 대상환자의 평균연령은 64.3세(23세-88세) 였고 성별은 남 11, 여 11명이었다. Fig. 1. A 40-year-old man with a rightsided weakness. Initial MR images were obtained at 4.8 hours from the onset of stroke. A. Initial diffusion-weighted image, B. the 4-day follow-up diffusion-weighted image, C. mean transit time(mtt) map, and D. diagram showing three regions of interest overlapped on the MTT map. Regions of interest on the left affected side and on the right unaffected side were outlined by a solid line. Region of interest 1 covers the initial lesion on the DWI (the ischemic core). Region of interest 2 covers the area of the final infarct on the followup image subtracted from the area of the initial infarct (the mismatch area that progressed to an infarct). Region of interest 3 covers the area of the perfusion abnormality on the MTT map but remained normal on the follow-up diffusion MR images. 424

3 425 Table 1. Mean( standard deviation) Perfusion Value in Each Region Compared to Contralateral Normal Region Region 1 Region 2 Region 3 p (ANOVA) rcbv * * p<0.01 rcbf * * p<0.01 MTT * * p<0.01 Region 1: ischemic core; region 2: area that progressed to infarction; and region 3: hypoperfused but survived area rcbv: relative cerebral blood volume; rcbf: relative cerebral blood flow; and MTT: mean transit time *: No significant difference between groups (Bonferroni post hoc analysis)

4 A B Fig. 2. Box plots of the perfusion values of the lesionto-contralateral normal area by percentage. A. Relative cerebral blood volume (rcbv) ratios, B. Relative cerebral blood flow (rcbf) ratios, and C. Mean transit time (MTT) ratios. The box extends from the first quartile to the third quartile of the data with the line in the center of each box represents the mean value. End point of each bar represents the smallest and largest values. Empty circle in the graph represents outliers. Mean perfusion value in each region showed significant different on all perfusion maps. Region 1: ischemic core; region 2: area that progressed to infarction; and region 3: hypoperfused but survived area C 426

5 Table 2. Comparison of rcbf Value in Each Region with Other Reports Region 1 Region 2 Region 3 Threshold* P-D mismatch Kim MTT Schaefer(2003) rcbf Rohl(2001) rcbf Grandin(2001) MTT Liu(2000) MTT 24hr Liu(2000) SPECT Schlaug(1999) hr Simosegawa(1994) SPECT 6hr Hatazawa(1999) hr Region 1: ischemic core; region 2: area that progressed to infarction; and region 3: hypoperfused but survived area rcbv: relative cerebral blood volume; rcbf: relative cerebral blood flow; and MTT: mean transit time P-D : Perfusion-Diffusion SPECT: single photon emission computed tomography; hr:hour * between regions 2 and 3 A B Fig. 3. Changes of mean relative value of each region according to the time duration after symptom onset. A. Mean relative CBV ratios, B. Mean relative CBF ratios, and C. Mean MTT ratios. There was no significant correlation between perfusion values and time duration after symptom onset in each region on all maps C 427

6 1. National Institute of Neurological Disorders and Stroke rt-pa Stroke Study Group. Tissue plasminogen activator for acute ischemic stroke. N Engl J Med 1995;333: Hacke W, Kaste M, Fieschi C, Toni D, Lesaffre E, von Kummer R, et al. Intravenous thrombolysis with recombinant tissue plasminogen activator for acute hemispheric stroke: the European 428

7 Cooperative Acute Stroke Study (ECASS). JAMA 1995;274: Furlan A, Higashida R, Wechsler L, Gent M, Rowley H, Kase C, et al. Intra-arterial prourokinase for acute ischemic stroke. The PROACT II study: a randomized controlled trial. Prolyse in acute cerebral thromboembolism. JAMA 1999;282: Schlaug G, Benfield A, Baird AE, Siewert B, Lovblad KO, Parker RA, et al. The ischemic penumbra: operationally defined by diffusion and perfusion MRI. Neurology 1999;53: Kidwell CS, Saver JL, Mattiello J, Starkman S, Vinuela F, Duckwiler G, et al. Thrombolytic reversal of acute human cerebral ischemic injury shown by diffusion/perfusion magnetic resonance imaging. Ann Neurol 2000;47: Sunshine JL, Tarr RW, Lanzieri CF, Landis DM, Selman WR, Lewin JS. Hyperacute stroke: ultrafast MR imaging to triage patients prior to therapy. Radiology 1999;212: Schellinger PD, Fiebach JB, Hacke W. Imaging-based decision making in thrombolytic therapy for acute ischemic stroke: present status. Stroke 2003;34: Kidwell CS, Alger JR, Saver JL. Beyond mismatch: evolving paradigms in imaging the ischemic penumbra with multimodal magnetic resonance imaging. Stroke 2003;34: Grandin CB, Duprez TP, Smith AM, Oppenheim C, Peeters A, Robert AR, et al. Which MR-derived perfusion parameters are the best predictors of infarct growth in hyperacute stroke? Comparative study between relative and quantitative measurements. Radiology 2002;223: Rohl L, Ostergaard L, Simonsen CZ, Vestergaard-Poulsen P, Andersen G, Sakoh M, et al. thresholds of ischemic penumbra of hyperacute stroke defined by perfusion-weighted MRI and apparent diffusion coefficient. Stroke 2001;32: Schaefer PW, Ozsunar Y, He J, Hamberg LM, Hunter GJ, Sorensen AG, et al. Assessing tissue viability with MR diffusion and perfusion imaging. AJNR Am J Neuroradiol 2003;24: Grandin CB, Duprez TP, Smith AM, Mataigne F, Peeters A, Oppenheim C, et al. Usefulness of magnetic resonance-derived quantitative measurements of cerebral blood flow and volume in prediction of infarct growth in hyperacute stroke. Stroke 2001;32: Liu Y, Karonen JO, Vanninen RL, Ostergaard L, Roivainen R, Nuutinen J, et al. Cerebral hemodynamics in human acute ischemic stroke: a study with diffusion- and perfusion-weighted magnetic resonance imaging and SPECT. J Cereb Blood Flow Metab 2000;20: Hatazawa J, Shimosegawa E, Toyoshima H, Ardekani BA, Suzuki A, Okudera T, et al. Cerebral blood volume in acute brain infarction: a combined study with dynamic susceptibility contrast MRI and 99mTc-HMPAO-SPECT. Stroke 1999;30: Powers W. Cerebral hemodynamics in ischemic cerebrovascular disease. Ann Neurol 1991;29: Sorensen AG, Copen WA, Ostergaard L, Buonanno FS, Gonzalez RG, Rordorf G, et al. Hyperacute stroke: simultaneous measurement of relative cerebral blood volume, relative cerebral blood flow, and mean tissue transit time. Radiology 1999;210: Neumann-Haefelin T, Wittsack HJ, Wenserski F, Siebler M, Seitz RJ, Modder U, et al. Diffusion- and perfusion-weighted MRI. The DWI/PWI mismatch region in acute stroke. Stroke 1999;30: Sorensen AG, Reimer P. Cerebral MR Perfusion Imaging: Principles and Current Applications. New York, NY: Thieme Med Pub; Barbier EL, Lamalle L, Decorps M. Methodology of brain perfusion imaging. J Magn Reson Imaging 2001;13: Rohl L, Sakoh M, Simonsen CZ, Vestergaard-Poulsen P, Sangill R, Sorensen JC, et al. Time evolution of cerebral perfusion and apparent diffusion coefficient measured by magnetic resonance imaging in a porcine stroke model. J Magn Reson Imaging 2002;15: Fiehler J, Kucinski T, Knudsen K, Rosenkranz M, Thomalla G, Weiller C, et al. Are there time-dependent differences in diffusion and perfusion within the first 6 hours after stroke onset? Stroke 2004;35: Lin W, Lee JM, Lee YZ, Vo KD, Pilgram T, Hsu CY. Temporal relationship between apparent diffusion coefficient and absolute measurements of cerebral blood flow in acute stroke patients. Stroke 2003;34:

8 Assessment of Tissue Viability in Hyperacute Infarction with Using the Diffusion- and Perfusion-weighted Images 1 Mi Ock Huh, M.D., Sang Joon Kim, M.D., Jeong Hyun Lee, M.D., Deok Hee Lee, M.D., Choong Gon Choi, M.D., Dae Chul Suh, M.D. 1 Department of Radiology, University of Ulsan, Asan Medical Center Purpose: The presence of a perfusion-diffusion mismatch is a useful indicator for predicting the progression of acute cerebral infarction. However, not all the area of the perfusion-diffusion mismatch progresses to infarction and a large proportion survives with hypoperfusion. The purpose of this study was to assess 1) whether tissue viability can be predicted using quantitative perfusion values and 2) whether there is correlation between the perfusion value and the time that elapsed after the onset of symptoms. Materials and Methods: Twenty-two patients with acute infarction in the middle cerebral artery territory within 12 hours after symptom onset were included in this study. We excluded those patients in whom thrombolysis was attempted or the lesion volume was less than 5 ml. Patients without perfusion-diffusion mismatch on the mean transit time (MTT) map were also excluded. We categorized the ischemic lesions into 3 areas: 1) the initial infarction, 2) the area that progressed to infarction, and 3) the hypoperfused but surviving area, based on the initial and follow up diffusion-weighted images and initial mean transit time (MTT) map. We obtained the relative cerebral blood volume (rcbv), the cerebral blood flow (rcbf) and the MTT in each area by comparing to the contralateral normal area. Statistical analysis was performed using one-way ANOVA to test whether there was a difference in perfusion values between each area. The threshold value was calculated between areas 2 and 3 using the receiver operating characteristics curve. We analyzed the correlation between the perfusion values of each area and the time that elapsed after the inset of symptoms. Results: The perfusion values among each region were significantly different on the rcbv, rcbf and MTT maps. Between regions 2 and 3, the rcbv and rcbf maps showed a significant difference (Bonferroni post hoc analysis), but in case of rcbv, the mean perfusion values in each region approached to the normal level and it was difficult to differentiate between the two regions on the rcbv map. The rcbf in the regions 1, 2 and 3 was 0.40, 0.64, and 0.84, respectively. The difference of the threshold values of the rcbf between regions 2 and 3 was There was no significant correlation between the time that elapsed after symptom onset and the perfusion values of each region on the rcbv, rcbf and MTT map. Conclusion: The perfusion values between the area of the initial infarction, the area that progressed to infarction and the hypoperfused but surviving area showed significant differences. The rcbf was the most useful parameter in differentiating between areas that progressed to infarction and the surviving areas. Quantitative measurement of the perfusion values may have a role in selecting the candidates for thrombolysis after they have suffered hyperacute stroke. Index words : Brain, diffusion Brain, Infarction Magnetic resonance (MR), diffusion study Magnetic resonance (MR), perfusion study Address reprint requests to : Sang Jun Kim, M.D. Department of Radiology, University of Ulsan, Asan Medical Center Poong Nap-dong, Songpa-gu, Seoul , Korea. Tel Fax sjkim@amc.seoul.ac.kr 430

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