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Register a new userDevelopment of a proton Computed Tomography Detector System
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Computer tomography is one of the most promising new methods to image abnormal tissues inside the human body. Tomography is also used to position the patient accurately before radiation therapy. Hadron therapy for treating cancer has become one of the most advantageous and safe options. In order to fully utilize the advantages of hadron therapy, there is a necessity of performing radiography with hadrons as well. In this paper we present the development of a proton computed tomography system. Our second-generation proton tomography system consists of two upstream and two downstream trackers made up of fibers as active material and a range detector consisting of plastic scintillators. We present details of the detector system, readout electronics, and data acquisition system as well as the commissioning of the entire system. We also present preliminary results from the test beam of the range detector.
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We describe the development of a proton Computed Tomography (pCT) scanner at Northern Illinois University (NIU) in collaboration with Fermilab and Delhi University. This paper provides an overview of major components of the scanner and a detailed description of the data acquisition system (DAQ).
Precise quantitative delineation of tumor hypoxia is essential in radiation therapy treatment planning to improve the treatment efficacy by targeting hypoxic sub-volumes. We developed a combined imaging system of positron emission tomography (PET) and electron para-magnetic resonance imaging (EPRI) of molecular oxygen to investigate the accuracy of PET imaging in assessing tumor hypoxia. The PET/EPRI combined imaging system aims to use EPRI to precisely measure the oxygen partial pressure in tissues. This will evaluate the validity of PET hypoxic tumor imaging by (near) simultaneously acquired EPRI as ground truth. The combined imaging system was constructed by integrating a small animal PET scanner (inner ring diameter 62 mm and axial field of view 25.6 mm) and an EPRI subsystem (field strength 25 mT and resonant frequency 700 MHz). The compatibility between the PET and EPRI subsystems were tested with both phantom and animal imaging. Hypoxic imaging on a tumor mouse model using $^{18}$F-fluoromisonidazole radio-tracer was conducted with the developed PET/EPRI system. We report the development and initial imaging results obtained from the PET/EPRI combined imaging system.
SPECT systems using pinhole apertures permit radiolabeled molecular distributions to be imaged in vivo in small animals. Nevertheless studying cardiovascular diseases by means of small animal models is very challenging. Specifically, submillimeter spatial resolution, good energy resolution and high sensitivity are required. We designed what we consider the optimal radionuclide detector system for this task. It should allow studying both detection of unstable atherosclerotic plaques and monitoring the effect of therapies. Using mice is particularly challenging in situations that require several intravenous injections of radiotracers, possibly for week or even months, in chronically ill animals. Thus, alternative routes of delivering the radiotracer in tail vein should be investigated. In this study we have performed preliminary measurements of detection of atherosclerotic plaques in genetically modified mice with high-resolution prototype detector. We have also evaluated the feasibility of assessing left ventricular perfusion by intraperitoneal delivering of MIBI-Tc in healthy mice.
Previous work showed that total variation superiorization (TVS) improves reconstructed image quality in proton computed tomography (pCT). The structure of the TVS algorithm has evolved since then and this work investigated if this new algorithmic structure provides additional benefits to pCT image quality. Structural and parametric changes introduced to the original TVS algorithm included: (1) inclusion or exclusion of TV reduction requirement, (2) a variable number, $N$, of TV perturbation steps per feasibility-seeking iteration, and (3) introduction of a perturbation kernel $0<alpha<1$. The structural change of excluding the TV reduction requirement check tended to have a beneficial effect for $3le Nle 6$ and allows full parallelization of the TVS algorithm. Repeated perturbations per feasibility-seeking iterations reduced total variation (TV) and material dependent standard deviations for $3le Nle 6$. The perturbation kernel $alpha$, equivalent to $alpha=0.5$ in the original TVS algorithm, reduced TV and standard deviations as $alpha$ was increased beyond $alpha=0.5$, but negatively impacted reconstructed relative stopping power (RSP) values for $alpha>0.75$. The reductions in TV and standard deviations allowed feasibility-seeking with a larger relaxation parameter $lambda$ than previously used, without the corresponding increases in standard deviations experienced with the original TVS algorithm. This work demonstrates that the modifications related to the evolution of the original TVS algorithm provide benefits in terms of both pCT image quality and computational efficiency for appropriately chosen parameter values.
A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 Italian project. One of the main goals of this project is to build a distributed database of lung CT scans in order to enable automated image analysis through a data and cpu GRID infrastructure. The basic modules of our lung-CAD system, a dot-enhancement filter for nodule candidate selection and a neural classifier for false-positive finding reduction, are described. The system was designed and tested for both internal and sub-pleural nodules. The results obtained on the collected database of low-dose thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.
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