血液活度動態(tài)在線分析系統(tǒng)（二代）
該系統(tǒng)適用于動力學血液放射活度實時測量研究（可配合于PET、SPE、PET/MRI系統(tǒng)）
Twilite 是由 Swisstrace 公司所研發(fā)設計的高靈敏度自動血液取樣系統(tǒng)。此系統(tǒng)可與 PET 、SPE、或 PET/MR 影像系統(tǒng)結合使用，無論是小至實驗動物、大至其他更大的個體，均能夠在線高分辨率采集血液活度實時變化數(shù)據(jù)。
Twilite 系統(tǒng)的是一個設計精巧的偵測頭（探測器），由 LYSO 晶體與屏蔽外來輻射用的級鎢加工製成，因此與 MR 影像系統(tǒng)相容。閃爍信號透過兩條可自訂長度的率光導管傳輸至光子偵測單元。此設計的偵測頭端沒有任何電子件，所以能夠避免來自其他設備所造成的電磁干擾問題。此外，這樣的設計也能夠將人體研究實驗的潛在風險小化。
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)鬏敚试S同時記錄多套 Swisstrace 系統(tǒng)的訊號，例如可同時使用 Twilite 系統(tǒng)與 Twin beta probe 系統(tǒng)。此外，尚有兩個類比訊號輸入孔可同時記錄來自其他儀器的訊號，例如Laser Doppler Flowprobes、ECG 或來自輔助設備的觸發(fā)訊號。 PMOD 軟件的功能模塊可對取得的放射活度信號進行離線處理分析。
此系統(tǒng)也脫離計算機工作。儀器前方的觸摸式面板可直接進行操作，并即時顯示測量數(shù)據(jù)。
Twilite 系統(tǒng)性能。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)人員在放射定量實驗方面具有相當深厚的經驗。系統(tǒng)設計乃針對 PET 系統(tǒng)（包含小動物與人）化。偵測頭精巧的尺寸尤其適合使用于小動物正子造影系統(tǒng)中，搭配動、靜脈分流管（arterio-venous shunt）， Twilite 系統(tǒng)可測得全血的動脈輸入函數(shù)（arterial input funion, AIF）而不將血液抽離體外。
圖1 圖2 圖3
儀器結構組成（1-9項為產品標配）：
1、連接股動脈與股靜脈的分流管 （自購）
2、蠕動幫浦（Peristaltic Pump）（自購）
3、Twilite 鎢制探測器
4、LYSO 晶體1
5、LYSO 晶體2
6、光導管：傳輸光子訊號至PMT。標準長度2 m，若需使用于MR 系統(tǒng)可延長至10 m
7、光子偵測單元
8、兩個模擬訊號輸入孔（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)傳輸或直接與計算機連接，使用PMOD 軟件PSAMPLE 模塊進行數(shù)據(jù)采集
10、安裝PMOD 軟件的計算機，進行數(shù)據(jù)采集與分析（自購）
結構說明：動靜脈分流管（小鼠用PE10，大鼠用PE50）可同時用于血壓量測、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管上劃一個小口，在采集時間點將導管往缺口方向推，即可取得血液樣本。
●結構與曲線函數(shù)（如下圖）
左圖為實驗架構。血流以蠕動泵驅動，從股動脈流出體外，經過耦合訊號偵測頭后，再由股靜脈回到體內。t1與t2兩個三向閥分別用來進行血液取樣與。右圖為Twilite 系統(tǒng)所測得的小鼠動脈輸入曲線。
四、用戶名單
五、合作伙伴
PMOD Technologies Ltd. Unitera
Zurich, Switzerland Zurich, Switzerland
University of Zurich CSEM
Zurich, Switzerland Neuchatel, Switzerland
六、動力學實驗論文(部分摘要)
Quantification of Brain Glucose Metaboli by 18F-FDG PET
with Real-Time Arterial and Image-Derived Input Funion 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 Funional 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 funion (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 ysis 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 essed by the residuals, fit parameter SD, and Bland–Altman ysis. 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 lonudinal or high-throughput studies, the use of a minimally invasive IDIF based on ensemble-learning independent component ysis represents a suitable alternative.
Key Words: energy metaboli; 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 metaboli 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–aivity curve) and in arterial plaa (input funion, 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 all animals, the all 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 all volumes via a microfluidic chip (4) or the use of b-probes for measuring the blood radioaivity (5,6). Despite these new physical methods, the main research focus has been on developing the use of IDIFs, where blood radioaivity is estimated direly from the dynamic PET images. IDIF generation from simple ysis 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 effes. Compensation can be achieved to varying degrees by image processing methods such as faor ysis (7), modelbased techniques (8), independent component ysis (9), so-called hybrid IDIFs (e.g., 10,11), and cardiac gating combined with improved image reconstruion 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 dire blood radioaivity measurements and an approach for the generation of IDIFs for use in mice. We acquired real-time blood radioaivity 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 ysis (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.
該系統(tǒng)適用于動力學血液放射活度實時測量研究（可配合于PET、SPE、PET/MRI系統(tǒng)）
Twilite 是由 Swisstrace 公司所研發(fā)設計的高靈敏度自動血液取樣系統(tǒng)。此系統(tǒng)可與 PET 、SPE、或 PET/MR 影像系統(tǒng)結合使用，無論是小至實驗動物、大至其他更大的個體，均能夠在線高分辨率采集血液活度實時變化數(shù)據(jù)。
Twilite 系統(tǒng)的是一個設計精巧的偵測頭（探測器），由 LYSO 晶體與屏蔽外來輻射用的級鎢加工製成，因此與 MR 影像系統(tǒng)相容。閃爍信號透過兩條可自訂長度的率光導管傳輸至光子偵測單元。此設計的偵測頭端沒有任何電子件，所以能夠避免來自其他設備所造成的電磁干擾問題。此外，這樣的設計也能夠將人體研究實驗的潛在風險小化。
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)鬏敚试S同時記錄多套 Swisstrace 系統(tǒng)的訊號，例如可同時使用 Twilite 系統(tǒng)與 Twin beta probe 系統(tǒng)。此外，尚有兩個類比訊號輸入孔可同時記錄來自其他儀器的訊號，例如Laser Doppler Flowprobes、ECG 或來自輔助設備的觸發(fā)訊號。 PMOD 軟件的功能模塊可對取得的放射活度信號進行離線處理分析。
此系統(tǒng)也脫離計算機工作。儀器前方的觸摸式面板可直接進行操作，并即時顯示測量數(shù)據(jù)。
Twilite 系統(tǒng)性能。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)人員在放射定量實驗方面具有相當深厚的經驗。系統(tǒng)設計乃針對 PET 系統(tǒng)（包含小動物與人）化。偵測頭精巧的尺寸尤其適合使用于小動物正子造影系統(tǒng)中，搭配動、靜脈分流管（arterio-venous shunt）， Twilite 系統(tǒng)可測得全血的動脈輸入函數(shù)（arterial input funion, AIF）而不將血液抽離體外。
圖1 圖2 圖3儀器結構組成（1-9項為產品標配）：
1、連接股動脈與股靜脈的分流管 （自購）
2、蠕動幫浦（Peristaltic Pump）（自購）
3、Twilite 鎢制探測器
4、LYSO 晶體1
5、LYSO 晶體2
6、光導管：傳輸光子訊號至PMT。標準長度2 m，若需使用于MR 系統(tǒng)可延長至10 m
7、光子偵測單元
8、兩個模擬訊號輸入孔（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)傳輸或直接與計算機連接，使用PMOD 軟件PSAMPLE 模塊進行數(shù)據(jù)采集
10、安裝PMOD 軟件的計算機，進行數(shù)據(jù)采集與分析（自購）
結構說明：動靜脈分流管（小鼠用PE10，大鼠用PE50）可同時用于血壓量測、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管上劃一個小口，在采集時間點將導管往缺口方向推，即可取得血液樣本。
●結構與曲線函數(shù)（如下圖）
左圖為實驗架構。血流以蠕動泵驅動，從股動脈流出體外，經過耦合訊號偵測頭后，再由股靜脈回到體內。t1與t2兩個三向閥分別用來進行血液取樣與。右圖為Twilite 系統(tǒng)所測得的小鼠動脈輸入曲線。
| 序號 | |||
| 1 | 偵測頭 | 尺寸 | 80 × 62 × 56 mm (L ×W × H). 約5 kg |
| 材質 | 由級鎢加工制成 | ||
| 閃爍晶體 | LYSO | ||
| 聯(lián)機 | 兩條率光導管，長度2 -- 10 m | ||
| 2 | 性能 | 靈敏度 | 導管內徑0.28 mm: 0.2 cps/kBq/ml（小鼠） |
| 導管內徑0.58 mm: 0.8 cps/kBq/ml（大鼠） | |||
| 導管內徑1.00 mm: 2.4 cps/kBq/ml（更大個體） | |||
| 3 | 線性度 | 6000 cps 以下線性（無誤差），在10000 cps以上，誤差小于1% | |
| 4 | 光子偵測單元 | 光子檢測裝置 | 19英寸光子計數(shù)裝置與采集系統(tǒng) |
| 操作 | 可單獨操作，執(zhí)行系統(tǒng)檢查與校正等功能，觸摸屏實時數(shù)據(jù)顯[cps] | ||
| 5 | 輸入 | 輔助模擬輸入 | 面板前方提供兩個BNC 規(guī)格模擬訊號輸入孔（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 | 客戶 | 儀器數(shù)量 |
| 1 | University of Zurich | 1 |
| 2 | Federal Institute of Technology, Zurich | 1 |
| 3 | Research Institution Juelich Germany | 1 |
| 4 | University of Antwerp, Belgium | 1 |
| 5 | Research Institute, Paris | 1 |
| 6 | University of Hannover | 1 |
| 7 | University of Oslo | 1 |
| 8 | Genentech, San Francisco | 2 |
| 9 | Amgen Biotechnology | 1 |
五、合作伙伴
PMOD Technologies Ltd. Unitera
Zurich, Switzerland Zurich, Switzerland
University of Zurich CSEM
Zurich, Switzerland Neuchatel, Switzerland
六、動力學實驗論文(部分摘要)
Quantification of Brain Glucose Metaboli by 18F-FDG PET
with Real-Time Arterial and Image-Derived Input Funion 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 Funional 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 funion (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 ysis 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 essed by the residuals, fit parameter SD, and Bland–Altman ysis. 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 lonudinal or high-throughput studies, the use of a minimally invasive IDIF based on ensemble-learning independent component ysis represents a suitable alternative.
Key Words: energy metaboli; 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 metaboli 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–aivity curve) and in arterial plaa (input funion, 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 all animals, the all 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 all volumes via a microfluidic chip (4) or the use of b-probes for measuring the blood radioaivity (5,6). Despite these new physical methods, the main research focus has been on developing the use of IDIFs, where blood radioaivity is estimated direly from the dynamic PET images. IDIF generation from simple ysis 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 effes. Compensation can be achieved to varying degrees by image processing methods such as faor ysis (7), modelbased techniques (8), independent component ysis (9), so-called hybrid IDIFs (e.g., 10,11), and cardiac gating combined with improved image reconstruion 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 dire blood radioaivity measurements and an approach for the generation of IDIFs for use in mice. We acquired real-time blood radioaivity 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 ysis (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.
