臺灣博碩士論文加值系統

心肌胞外比容的定量計算可以用於評估心肌纖維化，透過磁共振造影儀器掃描得到施予對比劑前後的T1映像，加上經由血液檢查得到的血球容積比，逐一計算出每一個像素的心肌胞外比容。AHA-17模型已廣泛的運用於臨床研究，AHA-17模型是利用牛眼圖來呈現出左心室心肌各區域內的數值，以利找出病灶之處。為了能夠分類是否有法洛氏四合症，透過迴歸分析來訓練及測試資料集，並利用混淆矩陣來得到判別的準確率。本研究提出了全自動化的左心室壁切割及心肌胞外比容的計算，將整個計算系統封裝於雲端運算系統平台，加上自動化切割AHA-17模型與迴歸分析，並應用於區辨法洛氏四合症。

Quantitative estimation of extracellular volume fraction (ECV) allows evaluations of myocardial fibrosis. ECV mapping relies on pixel-by-pixel comparisons of myocardial T1 constants obtained before and after contrast administration and the hematocrit measured by using a blood sample. AHA-17 segments model has been widely used in clinical research. AHA-17 segments model used bullseye to present the values of left ventricular wall is useful for the assessment of myocardial lesion in patients. We aim to discriminate Tetralogy of Fallot (TOF) patients from the control group. Therefore, we use the confusion matrix to calculate the area under the curve of receiver operating characteristic curve (AUC) and used regression analysis and cross-validation to evaluate the regression results. In this thesis, we proposed a fully automatic pipeline to produce ECV and T1 maps and global ECV and T1 values of LV wall. We also combined quantitative analysis with machine learning approaches to distinguish TOF patients from normal controls.

中文摘要 i
Abstract ii
目錄 iii
表目錄 iv
圖目錄 v
第一章 簡介 1
1.1 心肌胞外比容 1
1.2 法洛氏四合症 3
1.3 AHA-17 5
第二章 方法與材料 8
2.1 資料來源 8
2.2 ECV分析流程 9
2.3 雲端計算 11
2.4 AHA-17分割流程 13
2.5 手動區域圈選 14
2.6 迴歸分析 15
第三章 實驗結果 18
第四章 討論與結論 33
參考文獻 36
附件一：迴歸公式 39

[1] Kellman, P et al. Extracellular volume fraction mapping in the myocardium, part 1: evaluation of an automated method. Journal of Cardiovascular Magnetic Resonance. 2012; 14:63.
[2] Lee, JJ et al. Myocardial T1 and Extracellular Volume Fraction Mapping at 3 Tesla. Journal of Cardiovascular Magnetic Resonance. 2011 Jun; 13:75.
[3] McDiarmid, AC et al. Effect of changes to Modified Look-Locker Inversion (MOLLI) sequence on T1 Mapping at 3.0 Tesla in healthy volunteers. Journal of Cardiovascular Magnetic Resonance. 2014 Jan; 16(Suppl 1): P3.
[4] Apitz, C et al. Tetralogy of Fallot. The Lancet. 2009 Oct; 374:1462-71.
[5] Geva, T. Repaired tetralogy of Fallot: the roles of cardiovascular magnetic resonance in evaluating pathophysiology and for pulmonary valve replacement decision support. Journal of Cardiovascular Magnetic Resonance. 2011 Jan; 13-9.
[6] Cerqueira, MD et al. Standardized Myocardial Segmentation and Nomenclature for Tomographic Imaging of the Heart. Circulation. 2002 Jan; 105:539-542.
[7] Ortiz-Pérez, JT et al. Correspondence Between the 17-Segment Model and Coronary Arterial Anatomy Using Contrast-Enhanced Cardiac Magnetic Resonance Imaging. JACC: Cardiovascular imaging. 2008 May; 1(3):282-93.
[8] Messroghli, DR et al. Modified Look-Locker inversion recovery (MOLLI) for high-resolution T1 mapping of the heart. Magn Reson Med. 2004 Jul; 52(1):141-6.
[9] Chen, CN et al. Automatic extracellular volume fraction mapping in the myocardium: multiple initial T1 values and deformable image registration combined with LV segmentation. ISMRM, 2016.
[10] Chen, CN. Automatic extracellular volume fraction mapping in the myocardium: deformable image registration combined with short-axis Left Ventricle segmentation. National Taiwan University of Science and Technology, Master Thesis, 2016.
[11] Wang, YW et al. Fully automatic bullseye analysis on short-axis MOLLI mapping: LV segmentation and AHA 17 parcellation. ISMRM, 2017.
[12] Huang, CY. Fully automatic AHA-17 parcellation for myocardial T1 mapping in short-axis slices. National Taiwan University of Science and Technology, Master Thesis, 2016.
[13] Broberg, CS et al. Diffuse LV Myocardial Fibrosis and its Clinical Associations in Adults With Repaired Tetralogy of Fallot. JACC: Cardiovascular imaging. 2016 Jan; 9(1):86-7.
[14] Nakamori, S et al. Native T1 Mapping and Extracellular Volume Mapping for the Assessment of Diffuse Myocardial Fibrosis in Dilated Cardiomyopathy. JACC: Cardiovascular imaging. 2017 Jun.
[15] Nickander, J et al. Blood correction reduces variability and gender differences in native myocardial T1 values at 1.5 T cardiovascular magnetic resonance – a derivation/validation approach. Journal of Cardiovascular Magnetic Resonance. 2017 Apr; 19(1):41.
[16] Goebel, J et al. Can Native T1 Mapping Differentiate between Healthy and Diffuse Diseased Myocardium in Clinical Routine Cardiac MR Imaging? PLoS One. 2016 May; 11(5):e0155591.
[17] Yi, CJ et al. The association between cardiovascular risk and cardiovascular magnetic resonance measures of fibrosis: the Multi-Ethnic Study of Atherosclerosis (MESA). Journal of Cardiovascular Magnetic Resonance. 2015 Feb; 17(1):15.
[18] Liu, CY et al. Evaluation of Age-Related Interstitial Myocardial Fibrosis With Cardiac Magnetic Resonance Contrast-Enhanced T1 Mapping. Journal of the American College of Cardiology. 2013 Oct; 62(14):1280-7.