Robert S. Miyaoka

Depth of interaction decoding of a continuous crystal detector module

We present a clustering method to extract the depth of interaction (DOI) information from an 8 mm thick crystal version of our continuous miniature crystal element (cMiCE) small animal PET detector. This clustering method, based on the maximum-likelihood (ML) method, can effectively build look-up tables (LUT) for different DOI regions. Combined with our statistics-based positioning (SBP) method, which uses a LUT searching algorithm based on the ML method and two-dimensional mean-variance LUTs of light responses from each photomultiplier channel with respect to different gamma ray interaction positions, the position of interaction and DOI can be estimated simultaneously. Data simulated using DETECT2000 were used to help validate our approach. An experiment using our cMiCE detector was designed to evaluate the performance. Two and four DOI region clustering were applied to the simulated data. Two DOI regions were used for the experimental data. The misclassification rate for simulated data is about 3.5% for two DOI regions and 10.2% for four DOI regions. For the experimental data, the rate is estimated to be approximately 25%. By using multi-DOI LUTs, we also observed improvement of the detector spatial resolution, especially for the corner region of the crystal. These results show that our ML clustering method is a consistent and reliable way to characterize DOI in a continuous crystal detector without requiring any modifications to the crystal or detector front end electronics. The ability to characterize the depth-dependent light response function from measured data is a major step forward in developing practical detectors with DOI positioning capability.

Design of a depth of interaction (DOI) PET detector module

A method to determine depth of interaction (DOI) from a PET detector module is described and evaluated. The basic element of the DOI detector module is a two crystal detector unit. The hypothesis is that by controlling how light is shared between two crystals (A and B) DOI information can be extracted from the ratio of light collected using simple Anger logic [(A-B)/(A+B)]. The interface between crystals is designed so that a significant amount of light is shared when a photon interacts near the front face of a crystal and very little light is shared when an interaction occurs near the back of a crystal. The effects of surface treatment (e.g., polished, roughened) and optical coupling compounds are investigated. BGO, GSO and LSO detector units have been evaluated. A DOI uncertainty of /spl sim/6 mm was attained for the front section (/spl sim/4 mm) of a 2/spl times/2/spl times/20 mm LSO detector unit. A method to decode a 64 crystal detector module (32 detector units) using a 16 channel multi-anode photomultiplier tube is described.

Pet imaging using dual-headed gamma cameras: An update

Interest in clinical fluorodeoxyglucose (FDG) imaging with dual-headed gamma cameras continues to grow. In 1996, Jarritt and Acton published a review article of the use of gamma-camera systems for FDG imaging [1]. Since that article was published, considerable progress has been made in the adaptation of dual-headed camera systems for coincidence imaging. We review the basic principles of dual-headed coincidence imaging and some of the major limitations and challenges in the development of such technology. Since much of the current clinical experience with FDG imaging is based on the use of dedicated position emission tomographic (PET) systems, some comparisons of the performance limitations between dual-headed gamma-camera and dedicated PET systems are provided.

Performance Comparisons of Continuous Miniature Crystal Element (cMiCE) Detectors

In this paper, we investigated the performance characteristics of continuous miniature crystal element (cMiCE) detectors. Versions with a 25 mm by 25 mm by 4 mm-thick LSO crystal and with a 50 mm by 50 mm by 8 mm-thick LYSO crystal were evaluated. Both detectors utilize a 64-channel flat panel photomultiplier tube (PMT). The intrinsic spatial resolution for the detectors was evaluated using Anger (i.e., simple centroid) positioning and a statistics based positioning (SBP) algorithm. We also compared the intrinsic spatial resolution for the 8-mm-thick LYSO crystal using different reflective materials (e.g., TFE Teflon, white paint, and a polymer mirror film) applied on the entrance surface of the crystal. The average energy resolution was 20% for the 4-mm-thick LSO crystal and ranged from 16% to 21%, depending upon reflective material, for the 8-mm-thick LYSO crystal. The average intrinsic spatial resolution for the 4-mm-thick crystal was 1.8-mm full width at half maximum (FWHM) for Anger positioning to within 3 mm of the crystals edge and 1.14-mm FWHM for SBP to within 2 mm of the edge. The average intrinsic spatial resolution for the 8-mm-thick crystal was 2.2-mm FWHM for Anger positioning to within 8 mm of the crystals edge and 1.3- to 1.5-mm FWHM (depending on reflective material used) for SBP to within 2 mm of the edge. Intrinsic spatial resolution is reported without correcting for point source size. The point spot flux had a FWHM of about 0.52 mm. The SBP algorithm resulted in significant improvement in intrinsic spatial resolution, linearity of positioning result, and effective field of view (FOV) for our cMiCE detector

Pragmatic fully 3D image reconstruction for the MiCES mouse imaging PET scanner

We present a pragmatic approach to image reconstruction for data from the micro crystal elements system (MiCES) fully 3D mouse imaging positron emission tomography (PET) scanner under construction at the University of Washington. Our approach is modelled on fully 3D image reconstruction used in clinical PET scanners, which is based on Fourier rebinning (FORE) followed by 2D iterative image reconstruction using ordered-subsets expectation-maximization (OSEM). The use of iterative methods allows modelling of physical effects (e.g., statistical noise, detector blurring, attenuation, etc), while FORE accelerates the reconstruction process by reducing the fully 3D data to a stacked set of independent 2D sinograms. Previous investigations have indicated that non-stationary detector point-spread response effects, which are typically ignored for clinical imaging, significantly impact image quality for the MiCES scanner geometry. To model the effect of non-stationary detector blurring (DB) in the FORE+OSEM(DB) algorithm, we have added a factorized system matrix to the ASPIRE reconstruction library. Initial results indicate that the proposed approach produces an improvement in resolution without an undue increase in noise and without a significant increase in the computational burden. The impact on task performance, however, remains to be evaluated.

Brain imaging reveals neuronal circuitry underlying the crow’s perception of human faces

Crows pay close attention to people and can remember specific faces for several years after a single encounter. In mammals, including humans, faces are evaluated by an integrated neural system involving the sensory cortex, limbic system, and striatum. Here we test the hypothesis that birds use a similar system by providing an imaging analysis of an awake, wild animal’s brain as it performs an adaptive, complex cognitive task. We show that in vivo imaging of crow brain activity during exposure to familiar human faces previously associated with either capture (threatening) or caretaking (caring) activated several brain regions that allow birds to discriminate, associate, and remember visual stimuli, including the rostral hyperpallium, nidopallium, mesopallium, and lateral striatum. Perception of threatening faces activated circuitry including amygdalar, thalamic, and brainstem regions, known in humans and other vertebrates to be related to emotion, motivation, and conditioned fear learning. In contrast, perception of caring faces activated motivation and striatal regions. In our experiments and in nature, when perceiving a threatening face, crows froze and fixed their gaze (decreased blink rate), which was associated with activation of brain regions known in birds to regulate perception, attention, fear, and escape behavior. These findings indicate that, similar to humans, crows use sophisticated visual sensory systems to recognize faces and modulate behavioral responses by integrating visual information with expectation and emotion. Our approach has wide applicability and potential to improve our understanding of the neural basis for animal behavior.

Improving the efficiency of emission tomography simulations using variance reduction techniques

The development for public distribution of a general-purpose code, SIMSET, for the modeling of positron-emission and single-photon-emission tomographs (PET and SPECT) is discussed. An important part of the SIMSET project is the development of methods for efficient photon simulation which can handle heterogeneous distributions of activity and attenuation. For both positron and single-photon tomographs, the solid angle of acceptance of the detector array is small, due to collimation and to the size of the detector array itself. This results in significant computational inefficiencies with conventional Monte Carlo simulation, because only a few percent of the photons generated and tracked will actually be detected. A similar kind of problem arises in radiation shielding calculations, where the flux through the shield, although significant, may correspond to only a tiny fraction of the initial emitted photons. To improve the efficiency problem of simulations, some techniques from the radiation shielding literature have been adapted to increase the yield of detected photons. >

The Tuberous Sclerosis Complex Regulates Trafficking of Glucose Transporters and Glucose Uptake

Human cancers often display an avidity for glucose, a feature that is exploited in clinical staging and response monitoring by using (18)F-fluoro-deoxyglucose (FDG) positron emission tomography. Determinants of FDG accumulation include tumor blood flow, glucose transport, and glycolytic rate, but the underlying molecular mechanisms are incompletely understood. The phosphoinositide-3 kinase/Akt/mammalian target of rapamycin complex (mTORC) 1 pathway has been implicated in this process via the hypoxia-inducible factor alpha-dependent expression of vascular endothelial growth factor and glycolytic enzymes. Thus, we predicted that tumors with elevated mTORC1 activity would be accompanied by high FDG uptake. We tested this hypothesis in eight renal angiomyolipomas in which the loss of tuberous sclerosis complex (TSC) 1/2 function gave rise to constitutive mTORC1 activation. Surprisingly, these tumors displayed low FDG uptake on positron emission tomography. Exploring the underlying mechanisms in vitro revealed that Tsc2 regulates the membrane localization of the glucose transporter proteins (Glut)1, Glut2, and Glut4, and, therefore, glucose uptake. Down-regulation of cytoplasmic linker protein 170, an mTOR effector, rescued Glut4 trafficking in Tsc2(-/-) cells, whereas up-regulation of Akt activity in these cells was insufficient to redistribute Glut4 to the plasma membrane. The effect of mTORC1 on glucose uptake was confirmed using a liver-specific Tsc1- deletion mouse model in which FDG uptake was reduced in the livers of mutant mice compared with wild-type controls. Together, these data show that mTORC1 activity is insufficient for increased glycolysis in tumors and that constitutive mTOR activity negatively regulates glucose transporter trafficking.

Parametric positioning of a continuous crystal PET detector with depth of interaction decoding

Here we demonstrate a parametric positioning method on a continuous crystal detector. Three different models for the light distribution were tested. Diagnosis of the residues showed that the parametric model fits the experimental data better than Gaussian and Cauchy models in our particular experimental setup. Based on the correlation between the spread and the peak value of the light distribution model with the depth of interaction (DOI), we were able to estimate the three-dimensional position of a scintillation event. On our continuous miniature crystal element (cMiCE) detector module with 8 mm thick LYSO crystal, the intrinsic spatial resolution is 1.06 mm at the center and 1.27 mm at the corner using a maximum-likelihood estimation (MLE) method and the parametric model. The DOI resolution (full width at half maximum) is estimated to be approximately 3.24 mm. The positioning method using the parametric model outperformed the Gaussian and Cauchy models, in both MLE and weighted least-squares (WLS) fitting methods. The key feature of this technique is that it requires very little calibration of the detector, but still retains high resolution and high sensitivity.

Impact of system design parameters on image figures of merit for a mouse PET scanner

In this study, an analytical simulation model was developed to investigate how system design parameters affect image figures of merit and task performance for small animal positron emission tomography (PET) scanners designed to image mice. For a very high resolution imaging system, important physical effects that may impact image quality are positron range, annihilation photon acollinearity, detector point-spread function (PSF) and coincident photon count levels (i.e., statistical noise). Modeling of these effects was included in an analytical simulation that generated multiple realizations of sinograms with varying levels of each effect. To evaluate image quality with respect to quantitation and detection task performance, four different figures of merit were measured: 1) root mean square error (RMSE); 2) a region of interest SNR (SNR/sub ROI/); 3) nonprewhitening matched filter SNR (SNR/sub NPW/); and 4) recovery coefficient. The results indicate that for very high resolution imaging systems, the increase in positron range of C-11 compared to F-18 radiolabeling causes a significant reduction of quantitation (SNR/sub ROI/) and detection (SNR/sub NPW/) accuracy for small regions. In addition, changing the shape of the detector PSF, which depends on crystal thickness, causes significant variations in quantitation and detection performance. However, while increasing noise levels significantly increase RMSE and decrease detectability (SNR/sub NPW/), the quantitation task performance (SNR/sub ROI/), is less sensitive to noise levels. These results imply that resolution is more important than sensitivity for quantitation task performance, while sensitivity is a more significant issue for detection. The analytical simulation model can be used for estimating task performance of small animal PET systems more rapidly than existing full Monte Carlo methods, although Monte Carlo methods are needed to estimate system parameters.