使用相同算法测量和评价mri序列与b超成像中黑质回声级:先导比较研究

Jiri Blahuta, Tomás Soukup, J. Lavrincik, Lukáš Pavlík, J. Kozel
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引用次数: 0

摘要

诊断超声(US)和磁共振成像(MRI)是现代放射学中重要的医学成像方法。我们的研究重点是神经学中的脑结构成像。在本文中,我们提出了在使用相同算法的美国和MRI之间的黑质(SN)的数字图像分析的差异。过去,我们开发了一种应用程序来分析BMODE US图像中的黑质回声性。我们开发的应用程序是基于感兴趣区域(ROI)的二值阈值原理来评估回声级。SN回声增强是帕金森病(PD)进展的重要标志之一。本文的目的是分析US B-MODE成像的相同原理是否也适用于不同的MR序列,以发现SN的变化。从所取得的结果来看,MRI至少可以作为超声成像的补充检查。我们需要证明回声性指数(称为Echo-Index)在两个不同的MR序列之间是否具有良好的可重复性;SWI和T2-TSE;如何区分病理性SN和正常解剖。在第一个试点分析中,回声指数测量的原理似乎可以作为在该领域开展新的大型临床研究的起点。在本初步研究中,共分析了来自两个不同序列(T1和T2)的23张MR图像。然而,回声指数似乎不能区分正常和病变的SN。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MEASURING AND EVALUATION OF THE ECHOGENICITY GRADE OF SUBSTANTIA NIGRA IN MRI SEQUENCES VS B-MODE ULTRASOUND IMAGING USING THE SAME ALGORITHM: PILOT COMPARISON STUDY
Diagnostic ultrasound (US) and magnetic resonance imaging (MRI) are important medical imaging methods in modern radiology. Our research is focused on imaging brain structures in neurology. In this paper we present differences of digital image analysis of the substantia nigra (SN) between US and MRI using the same algorithm. In the past, we developed an application for analyzing substantia nigra echogenicity in BMODE US images. Our developed application is based on a principle of binary thresholding in Region of Interest (ROI) to evaluate echogenicity grade. Increased echogenicity of SN is one of important markers for Parkinson�s Disease (PD) progress. The goal of this paper is to analyze if the same principle used for US B-MODE imaging is also applicable for different MR sequences to find out SN changes. From the achieved results detectable SN changes using MRI are possible at least as a complementary examination to US imaging. We need to prove if echogenicity index (called Echo-Index) is well reproducible value between two different MR sequences; SWI and T2-TSE; how to distinguish between pathological SN and normal anatomy. In the first pilot analysis, it seems that the principle of Echo-Index measurement could be a starting point to create a new large clinical study in this field. Totally 23 MR images from two different sequences (T1 and T2) were analyzed in this pilot study. However, it seems that Echo-Index cannot distinguish normal and diseased SN.
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