상이한 상용 소프트웨어를 사용한 CT 관류 맵에서의 경색 용적 측정: 급성 뇌졸중 환자에서 동일한 소스 데이터를 사용한 정량적 분석

학위논문(석사) -- 서울대학교대학원 : 의과대학 의학과, 2021.8. 손철호 .연구 목적: CT 관류 영상 (CT Perfusion map, CTP) 급성 허혈성 뇌졸중 환자의 치료 여부의 선택 결정과정에 실제로 널리 사용되고 있지만, 정확한 경색 중심부 용적을 예측하는 데 사용되는 최적의 임계값과 매개 변수에 대해서는 명확한 표준이 없다. 현재 rCBF <30 %의 임계값을 가진 경색 중심부(Infarct core) 용적이 일반적으로 사용되고 있다. 그러나 Follow-up diffusion-weighted imaging (DWI)와 경색 중심부(Infarct core) 용적의 일치를 평가하기 위해 CTP와 DWI 사이의 시간간격이 24 시간 이내인 여러 연구가 진행되었다. 본 연구의 목적은 RAPID, singular value decomposition+ (SVD+) VITREA, BAYESIAN VITREA 등의 CTP 소프트웨어 프로그램에서 다양한 Deconvolution 방법, 매개 변수, 임계값에 따라 측정된 경색 중심부 용적과 짧은 시간 간격으로 (60분 이내) 시행된 DWI에서 측정된 경색 중심부용적과의 일치율을 평가한다. 연구 방법: 전방 순환에 있어서 큰 혈관의 폐색증을 가진 42명의 급성 허혈성 뇌졸중 환자가 포함되었다. CT 관류 영상은 VITREA 및 RAPID의 SVD +와 Bayesian 알고리즘을 포함한 다양한 CT 관류 소프트웨어로 처리되었다. RAPID는 경색 중심부를 rCBF <20 % -38 %, rCBV <34 % -42 %을 가진 조직으로 식별하였다. SVD+ VITREA에서는 경색 중심부를 CBV의 26-56 % 감소로 정의하였다. BAYESIAN VITREA에서는 경색 중심부를 CBV의 28-48% 감소로 정의하였다. Olea Sphere는 DWI 경색 중심부 용적을 측정하는 데 사용되었다. CTP 중심부 용적의 측정값은 DWI에서 결정된 최종 경색 용적과 비교되었다. 연구 결과: CTP는 모든 환자에서 DWI 전에 실시되었고, CTP와 DWI 사이의 시간의 중앙값은 37.5 분(min)이었다 interquartile range (IQR) 20 -44. 42 명의 환자에서는 최종 경색 중심부 용적의 중앙값은 DWI에서 19.50 ml (IQR 6.91 - 69.72) 였다. RAPID rCBF <30% 기본 설정값에서 경색 중심부 용적 차이의 중앙값은 (IQR) 8.19 ml (3.95 – 30.70), spearman’s correlation coefficient (r) = 0.759를 얻을 수 있었으며; SVD+ VITREA CBV의 41% 감소 시 경색 중심부 용적 차이의 중앙값은 (IQR) 3.82 ml (-2.91 – 20.95), r = 0.717로, BAYESIAN VITREA CBV의 38% 감소 시 경색 중심부 용적 차이의 중앙값은 (IQR) 8.16 ml (1.58 – 25.46), r = 0.754이었다. 반면 각 소프트웨어에 대한 최적의 임계값은 경색 중심부 용적을 기본 설정보다 정확하게 추정하는 것으로 입증되었다. 각 소프트웨어의 가장 정확하고 최적의 경색 중심부 용적 차이의 임계값은 다음과 같았다: RAPID rCBF <38 % 경색 중심부 용적 차이는 4.87 ml (0.84 – 23.51), r = 0.752; SVD + VITREA CBV이 26 % 감소 시 경색 중심부 용적의 용적 차이가 -1.05 ml (-12.26 – 14.58), r = 0.679로 나타났으며; BAYESIAN VITREA CBV의 28 % 감소는 경색 중심부 용적 차이가 5.23 ml (-2.90 – 22.91), r = 0.685였다. 결론: 본 연구에서는 CBV 임계값은 CBF 임계값과 비교하여 급성 허혈성 뇌졸중 환자의 경색 중심부 용적을 예측하는 더 정확한 매개 변수를 제공하는 것으로 나타났다.Purpose: Although using Computed Tomography Perfusion (CTP) for selecting and guiding decision-making processes of a patient with acute ischemic stroke has its advantages, there is no clear standardization of the optimal threshold and parameters used to predict infarct core volume accurately. Nowadays, infarct core volume with a rCBF<30% threshold is commonly used. However, several studies have been performed to assess the volumetric agreement of CTP infarct core volume with follow-up Diffusion-Weighted Imaging (DWI); the time between CTP and DWI was within 24 hours. In this study, we aimed to assess the volumetric agreement of estimated infarct core volume with different deconvolution methods, parameters, and thresholds on CTP software programs, including: RAPID, singular value decomposition plus (SVD+) VITREA, BAYESIAN VITREA, and also the final infarct volume on DWI with an especially short interval time (within 60 min) between CTP and follow-up DWI. Materials and methods: Forty-two acute ischemic stroke patients with occlusion of a large artery in the anterior circulation were included in the study. The CT perfusion maps were processed with different CT perfusion software, including SVD+ and Bayesian algorithms in VITREA and RAPID. The RAPID identified infarct core as tissue rCBF < 20-38% and rCBV < 34-42%. The SVD+ VITREA defined infarct core as CBV reduction of 26% - 56%. The Bayesian VITREA quantified infarct core as tissue CBV reduction of 28% - 48%. Olea Sphere was used to measure the infarct core volume on DWI. The CTP infarct core volume measurements were compared with the final infarct volume, which was determined on DWI. Results: The CTP was performed before DWI in all patients, and the median time between CTP and DWI was 37.5 minutes, with an interquartile range (IQR) of 20 – 44. In 42 patients, the median final infarct volume was 19.50 ml (IQR 6.91 – 69.72) with DWI. The most commonly used thresholds for each kind of CTP software, including RAPID rCBF<30%, resulted in a median infarct volume difference (IQR) of 8.19 ml (3.95 – 30.70), spearman’s correlation coefficient (r) = 0.759; SVD+ VITREA CBV reduction of 41% demonstrated a median infarct volume difference (IQR) of 3.82 ml (-2.91 – 20.95), r = 0.717; and BAYESIAN VITREA CBV reduction of 38% resulted in a median infarct volume difference (IQR) of 8.16 ml (1.58 – 25.46), r = 0.754. On the other hand, the optimal thresholds for each kind of software ended up estimating infarct core volume more accurately than the commonly used thresholds with lower infarct core volume differences. The most accurate and optimal infarct core volume thresholds for each kind of software were as follows: median infarct core volume difference (IQR) for RAPID rCBF<38% was 4.87 ml (0.84 – 23.51), r = 0.752; SVD+ VITREA CBV reduction of 26% was -1.05 ml (-12.26 – 14.58), r = 0.679; BAYESIAN VITREA CBV reduction of 28% was 5.23 ml (-2.90 – 22.91), r = 0.685. Conclusions: Our study found that the CBV thresholds provide a more accurate parameter to predict infarct core volume in acute ischemic stroke patients compared with the CBF thresholds.Chapter 1. Introduction 1 Chapter 2. Materials and methods 13 Chapter 3. Results 18 Chapter 4. Discussions 57 Chapter 5. Conclusions 64 Bibliography 65 Abstract in Korean 71석

A Quantitative Comparison of Clinically Employed Parameters in the Assessment of Acute Cerebral Ischemia Using Dynamic Susceptibility Contrast Magnetic Resonance Imaging

Purpose: Perfusion magnetic resonance imaging (P-MRI) is part of the mismatch concept employed for therapy decisions in acute ischemic stroke. Using dynamic susceptibility contrast (DSC) MRI the time-to-maximum (Tmax) parameter is quite popular, but its inconsistently defined computation, arterial input function (AIF) selection, and the applied deconvolution method may introduce bias into the assessment. Alternatively, parameter free methods, namely, standardized time-to-peak (stdTTP), zf-score, and standardized-zf (stdZ) are also available, offering consistent calculation procedures without the need of an AIF or deconvolution.Methods: Tmax was compared to stdTTP, zf-, and stdZ to evaluate robustness of infarct volume estimation in 66 patients, using data from two different sites and MR systems (i.e., 1.5T vs. 3T; short TR (= 689 ms) vs. medium TR (= 1,390 ms); bolus dose 0.1 or 0.2 ml/kgBW, respectively).Results: Quality factors (QF) for Tmax were 0.54 ± 0.18 (sensitivity), 0.90 ± 0.06 (specificity), and 0.87 ± 0.05 (accuracy). Though not significantly different, best specificity (0.93 ± 0.05) and accuracy (0.90 ± 0.04) were found for stdTTP with a sensitivity of 0.56 ± 0.17. Other tested parameters performed not significantly worse than Tmax and stdTTP, but absolute values of QFs were slightly lower, except for zf showing the highest sensitivity (0.72 ± 0.16). Accordingly, in ROC-analysis testing the parameter performance to predict the final infarct volume, stdTTP and zf showed the best performance. The odds for stdTTP to obtain the best prediction of the final infarct size, was 6.42 times higher compared to all other parameters (odds-ratio test; p = 2.2*10–16).Conclusion: Based on our results, we suggest to reanalyze data from large cohort studies using the parameters presented here, particularly stdTTP and zf-score, to further increase consistency of perfusion assessment in acute ischemic stroke

Robust Low-Dose CT Perfusion Deconvolution via Tensor Total-Variation Regularization

Acute brain diseases such as acute strokes and transit ischemic attacks are the leading causes of mortality and morbidity worldwide, responsible for 9% of total death every year. Time is brain is a widely accepted concept in acute cerebrovascular disease treatment. Efficient and accurate computational framework for hemodynamic parameters estimation can save critical time for thrombolytic therapy. Meanwhile the high level of accumulated radiation dosage due to continuous image acquisition in CT perfusion (CTP) raised concerns on patient safety and public health. However, low-radiation leads to increased noise and artifacts which require more sophisticated and time-consuming algorithms for robust estimation. In this paper, we focus on developing a robust and efficient framework to accurately estimate the perfusion parameters at low radiation dosage. Specifically, we present a tensor total-variation (TTV) technique which fuses the spatial correlation of the vascular structure and the temporal continuation of the blood signal flow. An efficient algorithm is proposed to find the solution with fast convergence and reduced computational complexity. Extensive evaluations are carried out in terms of sensitivity to noise levels, estimation accuracy, contrast preservation, and performed on digital perfusion phantom estimation, as well as in vivo clinical subjects. Our framework reduces the necessary radiation dose to only 8% of the original level and outperforms the state-of-art algorithms with peak signal-to-noise ratio improved by 32%. It reduces the oscillation in the residue functions, corrects over-estimation of cerebral blood flow (CBF) and under-estimation of mean transit time (MTT), and maintains the distinction between the deficit and normal regions