321 research outputs found

    Development of a Practical Calibration Procedure for a Clinical SPECT/MRI System Using a Single INSERT Prototype Detector and Multi-Mini Slit-Slat Collimator

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    In the context of the INSERT project, we have been developing a clinical SPECT insert for an MRI system, in order to perform simultaneous SPECT/MRI of the human brain. This system will consist of 20 CsI:Tl scintillation detectors, 5 cm wide and 10 cm long, with a 72-channel SiPM readout per detector, and a multi-mini slit-slat (MSS) collimator set up in a stationary partial ring. Additionally the system has a custom-built transmit/receive MR coil to ensure compatibility with the SPECT system. Due to the novel design of the system/collimator, existing geometric calibration methods are not suitable. Therefore we propose a novel and practical calibration procedure that consists of a set of specific independent measurements to determine the geometric parameters of the collimator. This procedure was developed utilising a prototype system that consists of a reduced-size single detector with a 36-channel SiPM-based readout and a single MSS collimator module. Validation was performed by reconstructing different imaging phantoms, using a rotating stage to simulate a tomographic acquisition. Regarding uniformity, the COV for the cylinder phantom reconstructed with correct calibration parameters is 6.7%, whereas the COV using incorrect parameters is 9.4%. The quality of the phantom reconstructions provide evidence of the applicability of the proposed method to the calibration of the prototype system. This procedure can be easily adapted for the final INSERT system

    ALBIRA: A small animal PET/SPECT/CT imaging system

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    Purpose: The authors have developed a trimodal PET/SPECT/CT scanner for small animal imaging. The gamma ray subsystems are based on monolithic crystals coupled to multianode photomultiplier tubes (MA-PMTs), while computed tomography (CT) comprises a commercially available microfocus x-ray tube and a CsI scintillator 2D pixelated flat panel x-ray detector. In this study the authors will report on the design and performance evaluation of the multimodal system. Methods: X-ray transmission measurements are performed based on cone-beam geometry. Individual projections were acquired by rotating the x-ray tube and the 2D flat panel detector, thus making possible a transaxial field of view (FOV) of roughly 80 mm in diameter and an axial FOV of 65 mm for the CT system. The single photon emission computed tomography (SPECT) component has a dual head detector geometry mounted on a rotating gantry. The distance between the SPECT module detectors can be varied in order to optimize specific user requirements, including variable FOV. The positron emission tomography (PET) system is made up of eight compact modules forming an octagon with an axial FOV of 40 mm and a transaxial FOV of 80 mm in diameter. The main CT image quality parameters (spatial resolution and uniformity) have been determined. In the case of the SPECT, the tomographic spatial resolution and system sensitivity have been evaluated with a99mTc solution using single-pinhole and multi-pinhole collimators. PET and SPECT images were reconstructed using three-dimensional (3D) maximum likelihood and ordered subset expectation maximization (MLEM and OSEM) algorithms developed by the authors, whereas the CT images were obtained using a 3D based FBP algorithm. Results: CT spatial resolution was 85ฮผm while a uniformity of 2.7% was obtained for a water filled phantom at 45 kV. The SPECT spatial resolution was better than 0.8 mm measured with a Derenzo-like phantom for a FOV of 20 mm using a 1-mm pinhole aperture collimator. The full width at half-maximum PET radial spatial resolution at the center of the field of view was 1.55 mm. The SPECT system sensitivity for a FOV of 20 mm and 15% energy window was 700 cps/MBq (7.8 ร— 10โˆ’2%) using a multi-pinhole equipped with five apertures 1 mm in diameter, whereas the PET absolute sensitivity was 2% for a 350โ€“650 keV energy window and a 5 ns timing window. Several animal images are also presented. Conclusions: The new small animal PET/SPECT/CT proposed here exhibits high performance, producing high-quality images suitable for studies with small animals. Monolithic design for PET and SPECT scintillator crystals reduces cost and complexity without significant performance degradation.This study was supported by the Spanish Plan Nacional de Investigacion Cientifica, Desarrollo e Innovacion Tecnologica (I+D+I) under Grant No. FIS2010-21216-CO2-01 and Valencian Local Government under Grant PROMETEO 2008/114. The authors also thank Brennan Holt for checking and correcting the text.Sรกnchez Martรญnez, F.; Orero Palomares, A.; Soriano Asensi, A.; Correcher Salvador, C.; Conde Castellanos, PE.; Gonzรกlez Martรญnez, AJ.; Hernรกndez Hernรกndez, L.... (2013). ALBIRA: A small animal PET/SPECT/CT imaging system. Medical Physics. 40(5):5190601-5190611. https://doi.org/10.1118/1.4800798S5190601519061140

    SPECT System Design Optimisation for a Simultaneous SPECT/MRI Clinical Scanner

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    The aim of this project was to optimize the design of a Single Photon Emission Computed Tomography (SPECT) insert based on high-resolution detectors and a high-sensitivity collimator, for a Magnetic Resonance Imaging (MRI) scanner, in order to perform simultaneous human brain SPECT/MRI and improve radionuclide-based therapies for glioma patients. The radionuclides of interest are 99mTc, 111In and 123I. Specific emphasis was given to the collimator and overall system design, data simulation and performance assessment, which would feed directly into the European-funded INSERT project. The SPECT insert was to consist of a stationary system with SiPM-based photodetectors, insensitive to magnetic fields. Regarding the design, a number of system and collimator geometries were evaluated considering the restricted space in the MRI bore and the limited angular sampling. High sensitivity was prioritised over high spatial resolution, because of the clinical application. Gamma shielding design was also addressed. Analytical calculations of system sensitivity and resolution, in addition to Monte Carlo simulations, were performed to compare various slit-slat and pinhole collimator designs. A new collimator design was proposed: multi-mini-slit slit-slat (MSS) collimator. The MSS has multiple mini-slits, some of which are shared between adjacent detectors, and they are embedded in the slat component, allowing for longer slats in comparison to a standard slit-slat collimator. The MSS design demonstrated to have the best overall performance, and the final system design consisted of a partial ring with 20 detectors. A framework for geometrical calibration of the system was developed and assessed, utilising a single prototype detector equipped with a prototype collimator. This framework takes advantage of the specific collimator design to estimate geometrical parameters from independent measurements of calibration phantoms. Experimental evaluation with tomographic acquisition of phantoms demonstrated the applicability of the new collimation concept, confirming the superiority of the MSS design over equivalent pinhole collimation

    Preclinical SPECT imaging based on compact collimators and high resolution scintillation detectors

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    Stationary, MR-compatible brain SPECT imaging based on multi-pinhole collimators

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    Doctor of Philosophy

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    dissertationSingle Photon Emission Computed Tomography (SPECT) myocardial perfusion imaging (MPI), a noninvasive and effective method for diagnosing coronary artery disease (CAD), is the most commonly performed SPECT procedure. Hence, it is not surprising that there is a tremendous market need for dedicated cardiac SPECT scanners. In this dissertation, a novel dedicated stationary cardiac SPECT system that using a segmented-parallel-hole collimator is investigated in detail. This stationary SPECT system can acquire true dynamic SPECT images and is inexpensive to build. A segmented-parallel-hole collimator was designed to fit the existing general-purpose SPECT cameras without any mechanical modifications of the scanner while providing higher detection sensitivity. With a segmented-parallel-hole collimator, each detector was segmented to seven sub-detector regions, providing seven projections simultaneously. Fourteen view-angles over 180 degree were obtained in total with two detectors positioned at 90 degree apart. The whole system was able to provide an approximate 34-fold gain in sensitivity over the conventional single-head SPECT system. The potential drawbacks of the stationary cardiac SPECT system are data truncation from small field of view (FOV) and limited number of view angles. A tailored maximum-likelihood expectation-maximization (ML-EM) algorithm was derived for reconstruction of truncated projections with few view angles. The artifacts caused by truncation and insufficient number of views were suppressed by reducing the image updating step sizes of the pixels outside the FOV. The performance of the tailored ML-EM algorithm was verified by computer simulations and phantom experiments. Compared with the conventional ML-EM algorithm, the tailored ML-EM algorithm successfully suppresses the streak artifacts outside the FOV and reduces the distortion inside the FOV. At 10 views, the tailored ML-EM algorithm has a much lower mean squared error (MSE) and higher relative contrast. In addition, special attention was given to handle the zero-valued projections in the image reconstruction. There are two categories of zero values in the projection data: one is outside the boundary of the object and the other is inside the object region, which is caused by count starvation. A positive weighting factor c was introduced to the ML-EM algorithm. By setting c>1 for zero values outside the projection, the boundary in the image is well preserved even at extremely low iterations. The black lines, caused by the zero values inside the object region, are completely removed by setting 0< c<1. Finally, the segmented-parallel-hole collimator was fabricated and calibrated using a point source. Closed-form explicit expressions for the slant angles and rotation radius were derived from the proposed system geometry. The geometric parameters were estimated independently or jointly. Monte Carlo simulations and real emission data were used to evaluate the proposed calibration method and the stationary cardiac system. The simulation results show that the difference between the estimated and the actual value is less than 0.1 degree for the slant angles and the 5 mm for the rotation radius, which is well below the detector's intrinsic resolution

    Development of Pinhole X-ray Fluorescence Imaging System to Measure in vivo Biodistribution of Gold Nanoparticles

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์œตํ•ฉ๊ณผํ•™๋ถ€,2019. 8. ์˜ˆ์„ฑ์ค€.๋ชฉ์ : ๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉํ‘œ๋Š” ๊ธˆ๋‚˜๋…ธ์ž…์ž์˜ ์ฒด๋‚ด ๋†๋„ ๋ถ„ํฌ ์ธก์ •์„ ์œ„ํ•œ ํ•€ํ™€ ์—‘์Šค์„  ํ˜•๊ด‘ ์˜์ƒ์‹œ์Šคํ…œ์„ ๊ฐœ๋ฐœํ•˜๊ณ , ์‹œ๊ฐ„์— ๋”ฐ๋ฅธ ์ฅ์˜ ์ฒด๋‚ด ๊ธˆ๋‚˜๋…ธ์ž…์ž ๋ถ„ํฌ ์˜์ƒ์„ ํš๋“ํ•˜์—ฌ ๊ฐœ๋ฐœ ์˜์ƒ์‹œ์Šคํ…œ์ด ์ „์ž„์ƒ์‹œํ—˜์— ํ™œ์šฉ ๊ฐ€๋Šฅํ•จ์„ ์‹คํ—˜์ ์œผ๋กœ ์ฆ๋ช…ํ•˜๋Š” ๊ฒƒ์ด๋‹ค. 2์ฐจ์› cadmium zinc telluride (CZT) ๊ฐ๋งˆ ์นด๋ฉ”๋ผ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ K-shell ์—‘์Šค์„  ํ˜•๊ด‘ ์‹ ํ˜ธ๋ฅผ ์ธก์ •ํ•จ์œผ๋กœ์จ, ์˜์ƒ ํš๋“ ์‹œ๊ฐ„๊ณผ ํ”ผํญ ๋ฐฉ์‚ฌ์„ ๋Ÿ‰์„ ์ค„์ผ ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ๋ณธ ์—ฐ๊ตฌ๋Š” ์ƒ˜ํ”Œ์˜ ๋ณต์žกํ•œ ์ „์ฒ˜๋ฆฌ ๊ณผ์ • ์—†์ด ๊ธˆ๋‚˜๋…ธ์ž…์ž์˜ ์ฒด์™ธ ๋†๋„๋ฅผ ์ธก์ •ํ•  ์ˆ˜ ์žˆ๋Š” silicon drift detector (SDD)๋ฅผ ์‚ฌ์šฉํ•œ L-shell ์—‘์Šค์„  ํ˜•๊ด‘ ์ธก์ • ์‹œ์Šคํ…œ์„ ๊ฐœ๋ฐœํ•˜๊ณ ์ž ํ•œ๋‹ค. ๋ฐฉ๋ฒ•: ๊ธˆ๋‚˜๋…ธ์ž…์ž์˜ ๋†๋„์™€ K-shell ์—‘์Šค์„  ํ˜•๊ด‘ ์‹ ํ˜ธ ์‚ฌ์ด์˜ ๊ต์ • ๊ณก์„ ์„ ํš๋“ํ•˜๊ธฐ ์œ„ํ•ด 0.0 wt%, 0.125 wt%, 0.25 wt%, 0.5 wt%, 1.0 wt%, 2.0 wt%์˜ ๊ธˆ๋‚˜๋…ธ์ž…์ž ์ƒ˜ํ”Œ์„ ๋ฐ˜์ง€๋ฆ„ 2.5 cm์ธ ์•„ํฌ๋ฆด ํŒฌํ†ฐ์— ์‚ฝ์ž…ํ•˜์—ฌ 140 kVp ์—‘์Šค์„ ์„ 1๋ถ„์”ฉ ์กฐ์‚ฌํ•˜์˜€๋‹ค. K-shell ์—‘์Šค์„  ํ˜•๊ด‘ ์‹ ํ˜ธ๋Š” ๊ธˆ๋‚˜๋…ธ์ž…์ž๊ฐ€ ์‚ฝ์ž…๋˜์–ด ์žˆ๋Š” ์•„ํฌ๋ฆด ํŒฌํ†ฐ์œผ๋กœ๋ถ€ํ„ฐ ์ธก์ •ํ•œ ์—‘์Šค์„  ์ŠคํŽ™ํŠธ๋Ÿผ์—์„œ ๊ธˆ๋‚˜๋…ธ์ž…์ž๊ฐ€ ์‚ฝ์ž…๋˜์–ด ์žˆ์ง€ ์•Š์€ ์•„ํฌ๋ฆด ํŒฌํ†ฐ์œผ๋กœ๋ถ€ํ„ฐ ์ธก์ •ํ•œ ์—‘์Šค์„  ์ŠคํŽ™ํŠธ๋Ÿผ์˜ ์ฐจ์ด๋ฅผ ํ†ตํ•ด ์ถ”์ถœํ•˜์˜€๋‹ค. ๊ธˆ๋‚˜๋…ธ์ž…์ž ์ฃผ์ž… ํ›„ ์ธก์ • ๋ฐ์ดํ„ฐ๋งŒ์œผ๋กœ ๊ธˆ๋‚˜๋…ธ์ž…์ž์˜ ์—‘์Šค์„  ํ˜•๊ด‘ ์˜์ƒ์„ ํš๋“ํ•˜๊ธฐ ์œ„ํ•ด ์ธ๊ณต์ง€๋Šฅ convolutional neural network (CNN) ๋ชจ๋ธ์„ ๊ฐœ๋ฐœํ•˜๊ณ  ์ ์šฉํ•˜์˜€๋‹ค. ์‹คํ—˜์šฉ ์ฅ๋กœ๋ถ€ํ„ฐ ์ถ”์ถœํ•œ ์žฅ๊ธฐ์˜ ๊ธˆ๋‚˜๋…ธ์ž…์ž ๋†๋„ ์ธก์ •์„ ์œ„ํ•ด L-shell ์—‘์Šค์„  ํ˜•๊ด‘ ์‹œ์Šคํ…œ์ธก์ •์„ ๊ฐœ๋ฐœํ•˜์˜€์œผ๋ฉฐ, ์ด ์‹œ์Šคํ…œ์€ SDD ์ธก์ •๊ธฐ์™€ 40 kVp์˜ ์„ ์›์„ ์ด์šฉํ•˜์—ฌ 2.34 ฮผg โ€“ 300 ฮผg (๊ธˆ๋‚˜๋…ธ์ž…์ž)/30 mg (๋ฌผ) (0.0078 wt%-1.0 wt%)์˜ ๊ธˆ๋‚˜๋…ธ์ž…์ž์™€ L-shell ์—‘์Šค์„  ํ˜•๊ด‘ ์‹ ํ˜ธ ์‚ฌ์ด์˜ ๊ต์ • ๊ณก์„ ์„ ์–ป์–ด ์žฅ๊ธฐ ๋‚ด ์ถ•์ ๋œ ๊ธˆ๋‚˜๋…ธ์ž…์ž์˜ ์งˆ๋Ÿ‰์„ ์ธก์ •ํ•˜์˜€๋‹ค. ํ•€ํ™€ ์—‘์Šค์„  ํ˜•๊ด‘ ์˜์ƒ์‹œ์Šคํ…œ์„ ์ด์šฉํ•˜์—ฌ ์‹คํ—˜์šฉ ์ฅ์— ๊ธˆ๋‚˜๋…ธ์ž…์ž๋ฅผ ์ฃผ์ž… ํ›„ ์‹œ๊ฐ„์— ๋”ฐ๋ฅธ ์‹ ์žฅ ๋‚ด ๊ธˆ๋‚˜๋…ธ์ž…์ž ๋†๋„ ์˜์ƒ์„ ํš๋“ํ•˜์˜€๋‹ค. ์•ˆ๋ฝ์‚ฌ ํ›„ ์ ์ถœํ•œ ์–‘์ชฝ ์‹ ์žฅ, ๊ฐ„, ๋น„์žฅ, ํ˜ˆ์•ก์˜ ๊ธˆ๋‚˜๋…ธ์ž…์ž ๋†๋„๋ฅผ L-shell ์—‘์Šค์„  ํ˜•๊ด‘ ์ฒด์™ธ ์ธก์ • ์‹œ์Šคํ…œ๊ณผ ICP-AES๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ธก์ •ํ•˜์˜€๊ณ  ์˜์ƒ์‹œ์Šคํ…œ์„ ํ†ตํ•ด ํš๋“ํ•œ ๋†๋„์™€ ๋น„๊ตยท๊ฒ€์ฆํ•˜์˜€๋‹ค. ์˜์ƒ ํš๋“ ์‹œ ์‹คํ—˜์šฉ ์ฅ์— ์กฐ์‚ฌ๋˜๋Š” ๋ฐฉ์‚ฌ์„ ๋Ÿ‰์€ TLD๋ฅผ ์‹คํ—˜์šฉ ์ฅ์˜ ํ”ผ๋ถ€์— ๋ถ™์—ฌ ์ธก์ •ํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ: ์—‘์Šค์„  ํ˜•๊ด‘ ์˜์ƒ ๋ถ„์„์„ ํ†ตํ•ด ์ธก์ •ํ•œ ์‹คํ—˜์šฉ ์ฅ์˜ ์˜ค๋ฅธ์ชฝ ์‹ ์žฅ ๋‚ด ๊ธˆ๋‚˜๋…ธ์ž…์ž์˜ ๋†๋„๋Š” ์ฃผ์ž… ์งํ›„ 1.58ยฑ0.15 wt%์˜€์œผ๋ฉฐ, 60๋ถ„ ํ›„ ๊ทธ ๋†๋„๋Š” 0.77ยฑ0.29 wt%๋กœ ๊ฐ์†Œํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœํ•œ ์ธ๊ณต์ง€๋Šฅ CNN ๋ชจ๋ธ์„ ์ ์šฉํ•ด ๊ธˆ๋‚˜๋…ธ์ž…์ž ์ฃผ์ž… ์ „ ์˜์ƒ์˜ ํš๋“ ์—†์ด ๊ธˆ๋‚˜๋…ธ์ž…์ž์˜ ์—‘์Šค์„  ํ˜•๊ด‘ ์˜์ƒ์„ ์ƒ์„ฑํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ ์ถœํ•œ ์žฅ๊ธฐ์—์„œ ์ธก์ •๋œ ๊ธˆ๋‚˜๋…ธ์ž…์ž์˜ ์‹ ์žฅ ๋‚ด ๋†๋„๋Š” L-shell ์—‘์Šค์„  ํ˜•๊ด‘ ์ธก์ •๋ฒ•์œผ๋กœ 0.96ยฑ0.22 wt%, ICP-AES๋กœ๋Š” 1.00ยฑ0.50 wt% ์˜€๋‹ค. ์˜์ƒ ํš๋“ ์‹œ ์‹คํ—˜์šฉ ์ฅ์˜ ํ”ผ๋ถ€์— ์ „๋‹ฌ๋œ ๋ฐฉ์‚ฌ์„ ๋Ÿ‰์€ ๊ธˆ๋‚˜๋…ธ์ž…์ž ์ฃผ์ž… ์ „๊ณผ ํ›„ ์˜์ƒ์„ ๋ชจ๋‘ ํš๋“ ์‹œ(์ด 2๋ถ„) 107ยฑ4 mGy, CNN ๋ชจ๋ธ ์ ์šฉ ์‹œ(1๋ถ„) 53ยฑ2 mGy๋กœ ์ธก์ •๋˜์—ˆ๋‹ค. ๊ฒฐ๋ก : 2์ฐจ์› CZT ๊ฐ๋งˆ ์นด๋ฉ”๋ผ์™€ ํ•€ํ™€ ์ฝœ๋ฆฌ๋ฉ”์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•œ ์—‘์Šค์„  ํ˜•๊ด‘ ์˜์ƒ์‹œ์Šคํ…œ์€ ์˜์ƒ ํš๋“ ์‹œ๊ฐ„๊ณผ ํ”ผํญ ๋ฐฉ์‚ฌ์„ ๋Ÿ‰์„ ํฌ๊ฒŒ ๊ฐ์†Œ์‹œ์ผฐ์œผ๋ฉฐ, ์‚ด์•„์žˆ๋Š” ์ฅ์˜ ์‹œ๊ฐ„์— ๋”ฐ๋ฅธ ์ฒด๋‚ด ๊ธˆ๋‚˜๋…ธ์ž…์ž ๋ถ„ํฌ ๋ณ€ํ™”๋ฅผ ์˜์ƒํ™” ํ•  ์ˆ˜ ์žˆ์Œ์„ ์ฆ๋ช…ํ•˜์˜€๋‹ค. ๋˜ํ•œ L-shell ์—‘์Šค์„  ํ˜•๊ด‘ ์ธก์ • ์‹œ์Šคํ…œ์€ ๋ณต์žกํ•œ ์ „์ฒ˜๋ฆฌ ๊ณผ์ • ์—†์ด ์ฒด์™ธ ๊ธˆ๋‚˜๋…ธ์ž…์ž์˜ ๋†๋„๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ์ธก์ •ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ณธ ๊ฐœ๋ฐœ ์‹œ์Šคํ…œ์„ ๊ธˆ์†๋‚˜๋…ธ์ž…์ž์˜ ์ฒด๋‚ด ๋ถ„ํฌ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•œ ์ „์ž„์ƒ์‹œํ—˜์šฉ ๋ถ„์ž์˜์ƒ์žฅ๋น„๋กœ์„œ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค.Purpose: This work aims to show the experimental feasibility for a dynamic in vivo X-ray fluorescence (XRF) imaging of gold in living mice exposed to gold nanoparticles (GNPs) using polychromatic X-rays. By collecting K-shell XRF photons using a 2D cadmium zinc telluride (CZT) gamma camera, the imaging system was expected to have a short image acquisition time and deliver a low radiation dose. This study also investigated the feasibility of using an L-shell XRF detection system with a single-pixel silicon drift detector (SDD) to measure ex vivo GNP concentrations from biological samples. Methods: Six GNP columns of 0 % by weight (wt%), 0.125 wt%, 0.25 wt%, 0.5 wt%, 1.0 wt% and 2.0 wt% inserted in a 2.5 cm diameter polymethyl methacrylate (PMMA) phantom were used for acquiring a linear regression curve between the concentrations of GNPs and the K-shell XRF photons emitted from GNPs. A fan-beam of 140 kVp X-rays irradiated the phantom for 1 min in each GNP sample. The photon spectra were measured by the CZT gamma camera. The K-shell XRF counts were derived by subtracting the photon counts of the 0 wt% PMMA phantom (i.e., pre-scanning) from the photon counts of the GNP-loaded phantom (i.e., post-scanning). Furthermore, a 2D convolutional neural network (CNN) was applied to generate the K-shell XRF counts from the post-scanned data without the pre-scanning. For a more sensitive detection of the ex vivo concentrations of GNPs in the biological samples, the L-shell XRF detection system using the single-pixel SDD was developed. Six GNP samples of 2.34 ฮผgโ€“300 ฮผg Au/30 mg water (i.e., 0.0078 wt%โ€“1.0 wt% GNPs) were used for acquiring a calibration curve to correlate the GNP mass to the L-shell XRF counts. The kidney slices of three Balb/C mice were scanned at various periods after the injection of GNPs in order to acquire the quantitative information of GNPs. The concentrations of GNPs measured by the CZT gamma camera and the SDD were cross-compared and then validated by inductively coupled plasma atomic emission spectroscopy (ICP-AES). The radiation dose was assessed by the measurement of TLDs attached to the skin of the mice. Results: The K-shell XRF images showed that the concentration of GNPs in the right kidneys from the mice was 1.58ยฑ0.15 wt% at T = 0 min after the injection. At T = 60 min after the injection, the concentration of GNPs in the right kidneys was reduced to 0.77ยฑ0.29 wt%. The K-shell XRF images generated by the 2D CNN were similar to those derived by the direct subtraction method. The measured ex vivo concentration of GNPs was 0.96ยฑ0.22 wt% by the L-shell XRF detection system while it was 1.00ยฑ0.50 wt% by ICP-AES. The radiation dose delivered to the skin of the mice was 107ยฑ4 mGy for acquiring one slice image by using the direct subtraction method while it was 53ยฑ2 mGy by using the 2D CNN. Conclusions: A pinhole K-shell XRF imaging system with a 2D CZT gamma camera showed a dramatically reduced scan time and delivered a low radiation dose. Hence, a dynamic in vivo XRF imaging of gold in living mice exposed to GNPs was technically feasible in a benchtop configuration. In addition, an L-shell XRF detection system can be used to measure ex vivo concentrations of GNPs in biological samples. This imaging system could provide a potential in vivo molecular imaging for metal nanoparticles to emerge as a radiosensitizer and a drug-delivery agent in preclinical studies.CHAPTER I. INTRODUCTION 1 I.1 Applications of Metal Nanoparticles in Medicine 1 I.2 Molecular Imaging of Metal Nanoparticles 3 I.3 X-ray Fluorescence Imaging 5 I.3.1 Principle of X-ray Fluorescence Imaging 5 I.3.2 History of X-ray Fluorescence Imaging 8 I.3.3 Specific Aims 12 CHAPTER II. MATERIAL AND METHODS 15 II.1 Monte Carlo Model 15 II.1.1 Geometry of Monte Carlo Simulations 15 II.1.2 Image Processing 21 II.1.3 Radiation Dose 27 II.2 Development of Pinhole K-shell XRF Imaging System 28 II.2.1 System Configuration and Operation Scheme 28 II.2.2 Pinhole K-shell XRF Imaging System 31 II.2.2.1 Experimental Setup 31 II.2.2.2 Measurement of K-shell XRF Signal 36 II.2.2.3 Signal Processing: Correction Factors 39 II.2.2.4 Application of Convolutional Neural Network 42 II.2.3 K-shell XRF Detection System 45 II.2.3.1 Experimental Setup 45 II.2.3.2 Signal Processing 47 II.2.4 L-shell XRF Detection System 49 II.2.4.1 Experimental Setup 49 II.2.4.2 Signal Processing 51 II.3 In vivo Study in Mice 53 II.3.1 Experimental Setup 53 II.3.2 Dose Measurement 56 CHAPTER III. RESULTS 57 III.1 Monte Carlo Model 57 III.1.1 Geometric Efficiency, System and Energy Resolution 57 III.1.2 K-shell XRF Image by Monte Carlo Simulations 59 III.1.3 Radiation Dose 69 III.2. Development of Pinhole XRF Imaging System 70 III.2.1 Pinhole K-shell XRF Imaging System 70 III.2.1.1 Energy Calibration and Measurement of Field Size 70 III.2.1.2 Raw K-shell XRF Signal 73 III.2.1.3 Correction Factors 78 III.2.1.4 K-shell XRF Image 81 III.2.2 K-shell XRF Detection System 85 III.2.3 L-shell XRF Detection System 89 III.3 In vivo Study in Mice 92 III.3.1 In vivo K-shell XRF Image 92 III.3.2 Quantification of GNPs in Living Mice 96 III.3.3 Dose Measurement 101 CHAPTER IV. DISCUSSION 102 IV.1 Monte Carlo Model 102 IV.2 Development of Pinhole K-shell XRF Imaging System 104 IV.2.1 Quantification of GNPs 105 IV.2.2 Comparison between MC and Experimental Results 107 IV.2.3 Limitations 108 IV.2.3.1 Concentration 108 IV.2.3.2 System Resolution 110 IV.2.3.3 Radiation Dose 111 IV.2.4 Application of CNN 112 IV.2.5 Future Work 114 CHAPTER V. CONCLUSIONS 115 REFERENCES 116 ABSTRACT (in Korean) 123Docto

    Organ-Dedicated Molecular Imaging Systems

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    [EN] In this review, we will cover both clinical and technical aspects of the advantages and disadvantages of organ specific (dedicated) molecular imaging (MI) systems, namely positron emission tomography (PET) and single photon emission computed tomography, including gamma cameras. This review will start with the introduction to the organ-dedicated MI systems. Thereafter, we will describe the differences and their advantages/disadvantages when compared with the standard large size scanners. We will review time evolution of dedicated systems, from first attempts to current scanners, and the ones that ended in clinical use. We will review later the state of the art of these systems for different organs, namely: breast, brain, heart, and prostate. We will also present the advantages offered by these systems as a function of the special application or field, such as in surgery, therapy assistance and assessment, etc. Their technological evolution will be introduced for each organ-based imager. Some of the advantages of dedicated devices are: higher sensitivity by placing the detectors closer to the organ, improved spatial resolution, better image contrast recovery (by reducing the noise from other organs), and also lower cost. Designing a complete ring-shaped dedicated PET scanner is sometimes difficult and limited angle tomography systems are preferable as they have more flexibility in placing the detectors around the body/organ. Examples of these geometries will be presented for breast, prostate and heart imaging. Recently achievable excellent time of flight capabilities below 300-ps full width at half of the maximum reduce significantly the impact of missing angles on the reconstructed images.This work was supported in part by the European Research Council through the European Union's Horizon 2020 Research and Innovation Program under Grant 695536, in part by the EU through the FP7 Program under Grant 603002, and in part by the Spanish Ministerio de Economia, Industria y Competitividad through PROSPET (DTS15/00152) funded by the Ministerio de Economia y Competitividad under Grant TEC2016-79884-C2-1-R.Gonzรกlez Martรญnez, AJ.; Sรกnchez, F.; Benlloch Baviera, JM. (2018). Organ-Dedicated Molecular Imaging Systems. IEEE Transactions on Radiation and Plasma Medical Sciences. 2(5):388-403. https://doi.org/10.1109/TRPMS.2018.2846745S3884032

    Integration of advanced 3D SPECT modelling for pinhole collimators into the open-source STIR framework

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    Single-photon emission computed tomography (SPECT) systems with pinhole collimators are becoming increasingly important in clinical and preclinical nuclear medicine investigations as they can provide a superior resolution-sensitivity trade-off compared to conventional parallel-hole and fanbeam collimators. Previously, open-source software did not exist for reconstructing tomographic images from pinhole-SPECT datasets. A 3D SPECT system matrix modelling library specific for pinhole collimators has recently been integrated into STIRโ€”an open-source software package for tomographic image reconstruction. The pinhole-SPECT library enables corrections for attenuation and the spatially variant collimatorโ€“detector response by incorporating their effects into the system matrix. Attenuation correction can be calculated with a simple single line-of-response or a full model. The spatially variant collimatorโ€“detector response can be modelled with point spread function and depth of interaction corrections for increased system matrix accuracy. In addition, improvements to computational speed and memory requirements can be made with image masking. This work demonstrates the flexibility and accuracy of STIRโ€™s support for pinhole-SPECT datasets using measured and simulated single-pinhole SPECT data from which reconstructed images were analysed quantitatively and qualitatively. The extension of the open-source STIR project with advanced pinhole-SPECT modelling will enable the research community to study the impact of pinhole collimators in several SPECT imaging scenarios and with different scanners
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