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        血液活度動(dòng)態(tài)在線分析系統(tǒng)(二代)

        一、產(chǎn)品介紹:

        該系統(tǒng)適用于藥物動(dòng)力學(xué)血液放射活度實(shí)時(shí)測(cè)量研究(可配合于PET、SPECT、PET/MRI系統(tǒng))

        Twilite 是由 Swisstrace 公司所研發(fā)設(shè)計(jì)的高靈敏度自動(dòng)血液取樣系統(tǒng)。此系統(tǒng)可與 PET 、SPECT、或 PET/MR 影像系統(tǒng)結(jié)合使用,無論是小至實(shí)驗(yàn)動(dòng)物、大至其他更大的個(gè)體,均能夠在線高分辨率采集血液活度實(shí)時(shí)變化數(shù)據(jù)。

        Twilite 系統(tǒng)的核心是一個(gè)設(shè)計(jì)精巧的偵測(cè)頭(探測(cè)器),由 LYSO 晶體與屏蔽外來輻射用的醫(yī)療級(jí)鎢加工製成,因此完全與 MR 影像系統(tǒng)相容。閃爍信號(hào)透過兩條可自訂長度的高效率光導(dǎo)管傳輸至光子偵測(cè)單元。此設(shè)計(jì)的偵測(cè)頭端完全沒有任何電子零件,所以能夠避免來自其他設(shè)備所造成的電磁干擾問題。此外,這樣的設(shè)計(jì)也能夠?qū)⑷梭w研究實(shí)驗(yàn)的潛在風(fēng)險(xiǎn)*小化。

        數(shù)據(jù)采集是使用 PMOD 公司所開發(fā)的 PSAMPLE 軟件,藉由 TCP/IP 介面?zhèn)鬏?,允許同時(shí)記錄多套 Swisstrace 系統(tǒng)的訊號(hào),例如可同時(shí)使用 Twilite 系統(tǒng)與 Twin beta probe 系統(tǒng)。此外,尚有兩個(gè)類比訊號(hào)輸入孔可同時(shí)記錄來自其他儀器的訊號(hào),例如Laser Doppler Flowprobes、ECG 或來自輔助設(shè)備的觸發(fā)訊號(hào)。 PMOD 軟件的功能模塊可對(duì)取得的放射活度信號(hào)進(jìn)行離線處理分析。

        此系統(tǒng)也脫離計(jì)算機(jī)獨(dú)立工作。儀器前方的觸摸式面板可直接進(jìn)行操作,并即時(shí)顯示測(cè)量數(shù)據(jù)。

        Twilite 系統(tǒng)性能優(yōu)越。除了擁有**的靈敏度外,即使在高輻射值的環(huán)境下,仍然呈現(xiàn)出穩(wěn)定的線性度與信噪比。

        Swisstrace 公司的開發(fā)人員在放射定量實(shí)驗(yàn)方面具有相當(dāng)深厚的經(jīng)驗(yàn)。系統(tǒng)設(shè)計(jì)乃針對(duì) PET 系統(tǒng)(包含小動(dòng)物與人)**化。偵測(cè)頭精巧的尺寸尤其適合使用于小動(dòng)物正子造影系統(tǒng)中,搭配動(dòng)、靜脈分流管(arterio-venous shunt), Twilite 系統(tǒng)可測(cè)得全血的動(dòng)脈輸入函數(shù)(arterial input function, AIF)而不必將血液抽離體外。

        二、實(shí)驗(yàn)結(jié)

        圖1 圖2 圖3

        儀器結(jié)構(gòu)組成(1-9項(xiàng)為產(chǎn)品標(biāo)配):

        1、連接股動(dòng)脈與股靜脈的分流管 (自購)

        2、蠕動(dòng)幫浦(Peristaltic Pump)(自購)

        3、Twilite 鎢制探測(cè)器

        4、LYSO 晶體1

        5、LYSO 晶體2

        6、光導(dǎo)管:傳輸光子訊號(hào)至PMT。標(biāo)準(zhǔn)長度2 m,若需使用于MR 系統(tǒng)可延長至10 m

        7、光子偵測(cè)單元

        8、兩個(gè)模擬訊號(hào)輸入孔(可與其他品牌儀器配合使用,監(jiān)控呼吸、ECG 或血壓等)

        9、TCP/IP 傳輸接口:可透過因特網(wǎng)傳輸或直接與計(jì)算機(jī)連接,使用PMOD 軟件PSAMPLE 模塊進(jìn)行數(shù)據(jù)采集

        10、安裝PMOD 軟件的計(jì)算機(jī),進(jìn)行數(shù)據(jù)采集與分析(自購)

        結(jié)構(gòu)說明:動(dòng)靜脈分流管(小鼠用PE10,大鼠用PE50)可同時(shí)用于血壓量測(cè)、藥物注射及血液樣本采集等其他功能,如圖3所示。血液樣本采集可用解剖刀在導(dǎo)管上劃一個(gè)小口,在采集時(shí)間點(diǎn)將導(dǎo)管往缺口方向推,即可取得血液樣本。

        ●結(jié)構(gòu)與曲線函數(shù)(如下圖)

        左圖為實(shí)驗(yàn)架構(gòu)。血流以蠕動(dòng)泵驅(qū)動(dòng),從股動(dòng)脈流出體外,經(jīng)過耦合訊號(hào)偵測(cè)頭后,再由股靜脈回到體內(nèi)。t1與t2兩個(gè)三向閥分別用來進(jìn)行血液取樣與藥物注射。右圖為Twilite 系統(tǒng)所測(cè)得的小鼠動(dòng)脈輸入曲線。

        三、系統(tǒng)規(guī)格

        序號(hào)
        1偵測(cè)頭尺寸80 × 62 × 56 mm (L ×W × H). 約5 kg
        材質(zhì)由醫(yī)療級(jí)鎢加工制成
        閃爍晶體LYSO
        聯(lián)機(jī)兩條高效率光導(dǎo)管,長度2 -- 10 m
        2性能靈敏度導(dǎo)管內(nèi)徑0.28 mm: 0.2 cps/kBq/ml(小鼠)
        導(dǎo)管內(nèi)徑0.58 mm: 0.8 cps/kBq/ml(大鼠)
        導(dǎo)管內(nèi)徑1.00 mm: 2.4 cps/kBq/ml(更大個(gè)體)
        3線性度6000 cps 以下完全線性(無誤差),在10000 cps以上,誤差小于1%
        4光子偵測(cè)單元光子檢測(cè)裝置19英寸光子計(jì)數(shù)裝置與采集系統(tǒng)
        操作可單獨(dú)操作,執(zhí)行系統(tǒng)檢查與校正等功能,觸摸屏實(shí)時(shí)數(shù)據(jù)顯[cps]
        5輸入輔助模擬輸入面板前方提供兩個(gè)BNC 規(guī)格模擬訊號(hào)輸入孔(0 -- 3.3 V)
        6數(shù)據(jù)擷取軟件軟件PMOD 軟件PSAMPLE 模塊
        操作系統(tǒng)Windows 7, XP, vista, MacOSX, Linux
        傳輸接口TCP/IP (可選配無線傳輸)

        四、用戶名單

        序號(hào)客戶儀器數(shù)量
        1University of Zurich1
        2Federal Institute of Technology, Zurich1
        3Research Institution Juelich Germany1
        4University of Antwerp, Belgium1
        5Research Institute, Paris1
        6University of Hannover1
        7University of Oslo1
        8Genentech, San Francisco2
        9Amgen Biotechnology1

        五、合作伙伴

        PMOD Technologies Ltd. Unitectra

        Zurich, Switzerland Zurich, Switzerland

        University of Zurich CSEM

        Zurich, Switzerland Neuchatel, Switzerland

        六、藥物動(dòng)力學(xué)實(shí)驗(yàn)論文(部分摘要)

        Quantification of Brain Glucose Metabolism by 18F-FDG PET

        with Real-Time Arterial and Image-Derived Input Function in Mice

        Malte F. Alf1,2, Matthias T. Wyss3,4, Alfred Buck3, Bruno Weber4, Roger Schibli1,5, and Stefanie D. Kr?mer11Center for

        Radiopharmaceutical Sciences of ETH, PSI, and USZ, Institute of Pharmaceutical Sciences, Department of Chemistry and

        Applied Biosciences, ETH Zurich, Zurich, Switzerland; 2Laboratory of Functional and Metabolic Imaging, Institute of Physics of

        Biological Systems, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; 3Department of Nuclear Medicine,

        University Hospital Zurich, Zurich, Switzerland; 4Institute of Pharmacology and Toxicology, University of Zurich, Zurich,Switzerland;

        and 5Center for Radiopharmaceutical Sciences of ETH, PSI, and USZ, Paul Scherrer Institute PSI, Villigen, Switzerla

        Kinetic modeling of PET data derived from mouse modelsremains hampered by thetechnical inaccessibility of an accurateinput function (IF).

        In this work, we tested the feasibility of IF measurement with an arteriovenous shunt and a coincidencecounter in mice and compared the method

        with an imagederived IF (IDIF) obtained by ensemble-learning independent component analysis of the heart region. Methods: 18F-FDG brain kinetics were quantified in 2 mouse strains, CD1 and C57BL/6, using the standard 2-tissue-compartment model. Fits obtained with the 2 IFs were compared regarding their goodness of fit as assessed by the residuals, fit parameter SD, and Bland–Altman analysis. Results: On average, cerebral glucose metabolic rate was 10% higher for IDIF-based quantification.The precision of model parameter fitting was significantly higher using the shunt-based IF, rendering the quantification of single process rate constants feasible. Conclusion: We demonstrated that the arterial IF can be measured in mice with a femoral arteriovenous shunt. This technique resulted in higher precision for kinetic modeling parameters than did use of the IDIF. However,for longitudinal or high-throughput studies, the use of a minimally invasive IDIF based on ensemble-learning independent component analysis represents a suitable alternative.

        Key Words: energy metabolism; PET; molecular imaging; glucose; kinetic modeling

        J Nucl Med 2013; 54:1–7 DOI: 10.2967/jnumed.112.107474

        PET with 18F-FDG is a commonly used method to determine glucose metabolism in animal and human tissues (1). Full quantification of 18F-FDG kinetics can be achieved by applying a 2-tissue-compartment model (2). The model requires the time course of the 18F-FDG concentration in the target organ(tissue time–activity curve) and in arterial plasma (input function, IF). In human brain PET, the IF is commonly measured from a catheter placed in the radial artery. An alternative is derivation of the IF from PET images via values measured in a volume of interest placed over the cardiac ventricles or a large vessel. A prerequisite of image-derived IFs (IDIFs) is the location of the blood pool and the organ of interest in the same field of view. In general, one or more arterial blood samples are measured to calibrate the IDIF. In a recent review article for human PET(3), the authors concluded that arterial blood sampling remains the preferred method to define the IF, because invasiveness is hardly reduced by the use of an IDIF.

        In small animals, the small blood volume is the major constraint for manual blood sampling. This constraint prompted the development of several alternative methods, such as the sampling of very small volumes via a microfluidic chip (4) or the use of b-probes for measuring the blood radioactivity (5,6). Despite these new physical methods, the main research focus has been on developing the use of IDIFs, where blood radioactivity is estimated directly from the dynamic PET images. IDIF generation from simple analysis of blood pool volumes such as the liver or the heart ventricles is flawed by 18F-FDG uptake by the liver or spillover from surrounding myocardium, cardiac motion, and partial-volume effects. Compensation can be achieved to varying degrees by image processing methods such as factor analysis (7), modelbased techniques (8), independent component analysis (9), so-called hybrid IDIFs (e.g., 10,11), and cardiac gating combined with improved image reconstruction algorithms (12). Most of these methods rely on at least 1 measure from a blood sample for scaling of the IDIF.Hence, blood sampling is not entirely obviated.

        To our knowledge, there is currently no gold standard to define the real-time 18F-FDG arterial IF in mice in a reliable and easily accessible manner. In this study, we adapted a method for direct blood radioactivity measurements and an approach for the generation of IDIFs for use in mice. We acquired real-time blood radioactivity curves by means of a new coincidence counter in combination with an arteriovenous shunt and compared the findings to IDIFs generated from PET data of the cardiac region with an ensemblelearning independent component analysis (EL-ICA) algorithm (13).We used 2 different mouse strains to explore the possible strain dependency of our methods: C57BL/6 mice, because they are relevant for studies of genetically modified animals, and CD1 mice, because they are valuable as disease models,such as cerebral ischemia (14). The purpose of this work was 2-fold. First, we evaluated whether the arteriovenous-shunt/ counter technique, which was previously demonstrated in rats (15), is also feasible in mice. Second, we compared 18F-FDG kinetic parameters and fit precisions obtained with the experimental shunt IF and the IDIF.

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