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Development of a Novel Data Acquisition Technique and a Software Tool for Quantitative Diffusion Imaging

機(jī)譯：新型數(shù)據(jù)采集技術(shù)和定量擴(kuò)散成像軟件工具的開(kāi)發(fā)

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As a specialized Magnetic Resonance Imaging (MRI) technique, diffusion imaging is sensitive to diffusion process of Nuclear Magnetic Resonance (NMR)-active nuclei in biological tissues. Studying the diffusion process of water molecules can reveal structural and environmental differences in normal versus diseased tissues at a microscopic (e.g. cellular) level. Diffusion-weighted magnetic resonance images (DWI) can be analyzed to obtain parameters such as Apparent Diffusion Coefficient (ADC), Fractional Anisotropy (FA), Radial Diffusivity (RD), Axial Diffusivity (AD), and others to be used as imaging markers in disease diagnosis and treatment assessment. To accurately obtain and reliably use these parameters, high spatial resolution with an adequate image quality must be achieved. Currently, the standard techniques for acquisition of diffusion images compromise on either image resolution or acquisition efficiency. The goal of this project is to develop a novel image acquisition technique for producing high-resolution and high-quality DWI within clinically acceptable scan duration (e.g. less than 3 minutes), and demonstrate its impact on the development of imaging markers for clinical applications. In order to accomplish this goal, three specific aims were defined.;In the first, we designed and implemented a new gradient and spin-echo (GRASE) based PROPELLER (periodically rotated overlapping parallel lines with enhanced reconstruction) pulse sequence, which we call "Steer-PROP". Experiments conducted for validating this sequence has proven that it is capable of producing high-resolution T2 and DWI in less than 2.5 minutes.;Second, we have identified the different kinds of phase errors that adversely impacted the image quality, and designed the corresponding correction methods to remove these phase errors during image reconstruction. Such phase correction has considerably improved the quality of diffusion-weighted images from the steer-PROP pulse sequence. Lastly, we have developed a software package, which we call Diffusion Imaging Visualization Environment (DIVE), for facilitating the calculation of a set of diffusion parameters that can be used to address clinical problems. The software provides a comprehensive diffusion image processing toolbox, capable of producing conventional parameters such as ADC and FA as well as a novel white matter characterization metric, which we call regional Fiber Coherence Index (r-FCI). The clinical significance of these parameters have been demonstrated through a diffusion tensor imaging study, designed to show the application of r-FCI and FA as markers for tumor cell infiltration along white matter fiber tracts. We have successfully completed this project and accomplished the goals defined in the three specific aims. We now have the necessary technical capabilities to produce high-resolution diffusion images that can be used to develop targeted imaging markers for specific clinical applications.
機(jī)譯：作為一種專(zhuān)門(mén)的磁共振成像（MRI）技術(shù)，擴(kuò)散成像對(duì)生物組織中核磁共振（NMR）活性核的擴(kuò)散過(guò)程敏感。研究水分子的擴(kuò)散過(guò)程可以揭示正常組織與患病組織在微觀（例如細(xì)胞）水平上的結(jié)構(gòu)和環(huán)境差異?？梢詫?duì)擴(kuò)散加權(quán)磁共振圖像（DWI）進(jìn)行分析以獲得諸如表觀擴(kuò)散系數(shù)（ADC），分?jǐn)?shù)各向異性（FA），徑向擴(kuò)散率（RD），軸向擴(kuò)散率（AD）等參數(shù)，以用作成像標(biāo)記在疾病的診斷和治療評(píng)估中。為了準(zhǔn)確地獲得并可靠地使用這些參數(shù)，必須實(shí)現(xiàn)具有足夠圖像質(zhì)量的高空間分辨率。當(dāng)前，用于獲取擴(kuò)散圖像的標(biāo)準(zhǔn)技術(shù)在圖像分辨率或獲取效率上都有折衷。該項(xiàng)目的目的是開(kāi)發(fā)一種新穎的圖像采集技術(shù)，以在臨床上可接受的掃描時(shí)間內(nèi)（例如少于3分鐘）產(chǎn)生高分辨率和高質(zhì)量的DWI，并展示其對(duì)臨床應(yīng)用成像標(biāo)記物開(kāi)發(fā)的影響。為了實(shí)現(xiàn)此目標(biāo)，定義了三個(gè)具體目標(biāo)。首先，我們?cè)O(shè)計(jì)并實(shí)現(xiàn)了一種新的基于梯度和自旋回波（GRASE）的PROPELLER（周期性旋轉(zhuǎn)的重疊平行線，具有增強(qiáng)的重構(gòu)）脈沖序列，我們稱之為“ Steer-PROP”。為驗(yàn)證此序列而進(jìn)行的實(shí)驗(yàn)證明，它能夠在不到2.5分鐘的時(shí)間內(nèi)產(chǎn)生高分辨率T2和DWI。其次，我們確定了對(duì)圖像質(zhì)量有不利影響的各種相位誤差，并設(shè)計(jì)了相應(yīng)的校正方法圖像重建過(guò)程中消除這些相位誤差的方法。這種相位校正已大大改善了來(lái)自轉(zhuǎn)向PROP脈沖序列的擴(kuò)散加權(quán)圖像的質(zhì)量。最后，我們開(kāi)發(fā)了一個(gè)名為“擴(kuò)散成像可視化環(huán)境”（DIVE）的軟件包，用于簡(jiǎn)化一組可用于解決臨床問(wèn)題的擴(kuò)散參數(shù)的計(jì)算。該軟件提供了一個(gè)全面的擴(kuò)散圖像處理工具箱，能夠產(chǎn)生諸如ADC和FA之類(lèi)的常規(guī)參數(shù)，以及一種新穎的白質(zhì)表征指標(biāo)，我們稱其為區(qū)域光纖相干指數(shù)（r-FCI）。這些參數(shù)的臨床意義已通過(guò)擴(kuò)散張量成像研究得到證實(shí)，旨在顯示r-FCI和FA作為腫瘤細(xì)胞沿白質(zhì)纖維束浸潤(rùn)的標(biāo)志物的應(yīng)用。我們已經(jīng)成功完成了該項(xiàng)目，并且完成了三個(gè)特定目標(biāo)中定義的目標(biāo)?，F(xiàn)在，我們擁有必要的技術(shù)能力，可以生成高分辨率的擴(kuò)散圖像，可用于開(kāi)發(fā)針對(duì)特定臨床應(yīng)用的目標(biāo)成像標(biāo)記。

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  • 作者

    Srinivasan, Girish.;

  • 作者單位

    University of Illinois at Chicago.;

  • 授予單位 University of Illinois at Chicago.;
  • 學(xué)科 Biomedical engineering.;Medical imaging.
  • 學(xué)位 Ph.D.
  • 年度 2017
  • 頁(yè)碼 146 p.
  • 總頁(yè)數(shù) 146
  • 原文格式 PDF
  • 正文語(yǔ)種 eng
  • 中圖分類(lèi) 遙感技術(shù);
  • 關(guān)鍵詞

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