Search

Glioblastoma (GBM) is the most common and deadliest form of brain tumor and remains amongst the most difficult cancers to treat. Brevican (Bcan), a central nervous system (CNS)-specific extracellular matrix protein, is upregulated in high-grade glioma cells, including GBM. A Bcan isoform lacking most glycosylation, dg-Bcan, is found only in GBM tissues. Here, dg-Bcan is explored as a molecular target for GBM. In this study, a d-peptide library is screened to identify a small 8-amino acid dg-Bcan-Targeting Peptide (BTP) candidate, called BTP-7 that binds dg-Bcan with high affinity and specificity. BTP-7 is preferentially internalized by dg-Bcan-expressing patient-derived GBM cells. To demonstrate GBM targeting, BTP-7 is radiolabeled with 18F, a radioisotope of fluorine, and increased radiotracer accumulation is found in intracranial GBM established in mice using positron emission tomography (PET) imaging. dg-Bcan is an attractive molecular target for GBM, and BTP-7 represents a promising lead candidate for further development into novel imaging agents and targeted therapeutics.

Purpose Noise levels of brain SPECT images are highest in central regions, due to preferential attenuation of photons emitted from deep structures. To address this problem, the authors have designed a novel collimator for brain SPECT imaging that yields greatly increased sensitivity near the center of the brain without loss of resolution. This hybrid collimator consisted of ultrashort cone-beam holes in the central regions and slant-holes in the periphery (USCB). We evaluated this collimator for quantitative brain imaging tasks. Methods Owing to the uniqueness of the USCB collimation, the hole pattern required substantial variations in collimator parameters. To utilize the lead-casting technique, the authors designed two supporting plates to position about 37 000 hexagonal, slightly tapered pins. The holes in the supporting plates were modeled to yield the desired focal length, hole length, and septal thickness. To determine the properties of the manufactured collimator and to compute the system matrix, the authors prepared an array of point sources that covered the entire detector area. Each point source contained 32 μCi of Tc-99m at the first scan time. The array was imaged for 5 min at each of the 64 shifted locations to yield a 2-mm sampling distance, and hole parameters were calculated. The sensitivity was also measured using a point source placed along the central ray at several distances from the collimator face. High-count projection data from a five-compartment brain phantom were acquired with the three collimators on a dual-head SPECT/CT system. The authors calculated Cramer-Rao bounds on the precision of estimates of striatal and background activity concentration. In order to assess the new collimation system to detect changes in striatal activity, the authors evaluated the precision of measuring a 5% decrease in right putamen activity. The authors also reconstructed images of projection data obtained by summing data from the individual phantom compartments. Results The sensitivity of the novel cone-beam collimator varied with distance from the detector face; it was higher than that of the fan-beam collimator by factors ranging from 2.7 to 162. Examination of the projections of the point sources revealed that only a few holes were distorted or partially blocked, indicating that the intensive manual fabrication process was very successful. Better reconstructed phantom images were obtained from the USCB+FAN collimator pair than from either LEHR or FAN collimation. For the left caudate, located near the center of the brain, the detected counts were 9.8 (8.3) times higher for UCSB compared with LEHR (FAN), averaged over 60 views. The task-specific SNR for detecting a 5% decrease in putamen uptake was 7.4 for USCB and 3.2 for LEHR. Conclusions The authors have designed and manufactured a novel collimator for brain SPECT imaging. The sensitivity is much higher than that of a fan-beam collimator. Because of differences between the manufactured collimator and its design, reconstruction of the data requires a measured system matrix. The authors have demonstrated the potential of USCB collimation for improved precision in estimating striatal uptake. The novel collimator may be useful for early detection of Parkinson's disease, and for monitoring therapy response and disease progression.

We assessed improvements in performance in detection and estimation tasks due to a novel brain single photon computed tomography collimator. Data were acquired on the CeraSPECT{sup TM} scanner using both new and standard collimators. The new variable focusing collimator SensOgrade{sup TM} samples the projections unequally, with central regions more heavily represented, to compensate for attenuation of counts from central brain structures. Furthermore, it utilizes more of the cylindrical crystal surface. Two phantom studies were performed. The first phantom was a 21-cm-diameter cylindrical background containing nine spheres ranging from 0.5 to 5 cm{sup 3} in volume. {sup 99m}Tc sphere to background activity ratio was 10:1. Twenty-nine 10-min datasets were acquired with each collimator. The second phantom was the Radiology Support Devices (Long Beach, CA) striatal phantom with striatal-background ratios of 10:1 on the left and 5:1 on the right. Twenty-nine 4-min datasets were acquired with each collimator. Perfusion imaging using {sup 99m}Tc-HMPAO was also performed in three healthy volunteers using both collimators under identical simulations. Projections were reconstructed by filtered backprojection with an unwindowed ramp filter. The nonprewhitening matched filter signal-to-noise ratio (NPW-SNR) was computed as a surrogate for human performance in detecting spherical lesions. Sphere activity concentration, radius, and locationmore » coordinates were simultaneously estimated by fitting images to an assumed model using an iterative nonlinear algorithm. Resolution recovery was implicit in the estimation procedure, as the point spread function was incorporated into the model. NPW-SNR for sphere detection was 1.5 to 2 times greater with the new collimator; for the striatal phantom the improvement in SNR was 54%. The SNR for estimating sphere activity concentration improved by 46 to 89 % for spheres located more than 5 cm from the phantom center. Images acquired with the standard collimator were too noisy in the central regions to allow estimation of sphere activity. In {sup 99m}Tc-HMPAO human studies, SNR was improved by 21 to 41 % in the cortex, 66% in the basal ganglia, and 74% in the thalamus. The new collimator leads to substantially improved detection and estimation performance throughout the brain. The higher sensitivity will be particularly important for dynamic imaging.« less

Single-photon emission-computed tomography (SPECT) imaging of deep brain structures is compromised by loss of photons due to attenuation. We have previously shown that a centrally peaked collimator sensitivity function can compensate for this phenomenon, increasing sensitivity over most of the brain. For dual-head instruments, parallel-hole collimators cannot provide variable sensitivity without simultaneously degrading spatial resolution near the center of the brain; this suggests the use of converging collimators. We have designed collimator pairs for dual-head SPECT systems to increase sensitivity, particularly in the center of the brain, and compared the new collimation approach to existing approaches on the basis of performance in estimating activity concentration of small structures at various locations in the brain. The collimator pairs we evaluated included a cone-beam collimator, for increased sensitivity, and a fan-beam collimator, for data sufficiency. We calculated projections of an ellipsoidal uniform background, with 0.9-cm-radius spherical lesions at several locations in the background. From these, we determined ideal signal-to-noise ratios (SNRCRB) for estimation of activity concentration within the spheres, based on the Cramer-Rao lower bound on variance. We also reconstructed, by an ordered-subset expectation-maximization (OS-EM) procedure, images of this phantom, as well as of the Zubal brain phantom, to allow visual assessment and to ensure that they were free of artifacts. The best of the collimator pairs evaluated comprised a cone-beam collimator with 20 cm focal length, for which the focal point is inside the brain, and a fan-beam collimator with 40 cm focal length. This pair yielded increased SNRCRB, compared to the parallel-parallel pair, throughout the imaging volume. The factor by which SNRCRB increased ranged from 1.1 at the most axially extreme location to 3.5 at the center. The gains in SNRCRB were relatively robust to mismatches between the center of the brain and the center of the imaging volume. Artifact-free reconstructions of simulated data acquired using this pair were obtained. Combining fan-beam and short-focusing cone-beam collimation should greatly improve dual-head brain SPECT imaging, especially for centrally located structures.

Three algorithms for scatter compensation in Tc-99m brain single-photon emission computed tomography (SPECT) were optimized and compared on the basis of the accuracy and precision with which lesion and background activity could be simultaneously estimated. These performance metrics are directly related to the clinically important tasks of activity quantitation and lesion detection, in contrast to measures based solely on the fidelity of image pixel values. The scatter compensation algorithms were (a) the Compton-window (CW) method with a 20% photopeak window, a 92-126 keV scatter window, and an optimized "k-factor," (b) the triple-energy window (TEW) method, with optimized widths of the photopeak window and the abutting scatter window, and (c) a general spectral (GS) method using seventeen 4 keV windows with optimized energy weights. Each method was optimized by minimizing the sum of the mean-squared errors (MSE) of the estimates of lesion and background activity concentrations. The accuracy and precision of activity estimates were then determined for lesions of different size, location, and contrast, as well as for a more complex Bayesian estimation task in which lesion size was also estimated. For the TEW and GS methods, parameters optimized for the estimation task differed significantly from those optimized for global normalized pixel MSE. For optimal estimation, the CW bias of activity estimates was larger and varied more (-2% to 22%) with lesion location and size than that of the other methods. The magnitude of the TEW bias was less than 7% across most conditions, although its precision was worse than that of CW estimates. The GS method performed best, with bias generally less than 4% and the lowest variance; its root-mean square (rms) estimation error was within a few percent of that achievable from primary photons alone. For brain SPECT, estimation performance with an optimized, energy-based, subtractive correction may approach that of an ideal scatter-rejection procedure.

A Bayesian estimator has been developed as a paradigm for human observer performance in detecting lesions of unknown size in a uniform noisy background. The Bayesian observer used knowledge of the range of possible lesion sizes as a prior; its predictions agreed well with the results of a six-observer perceptual study. The average human response to changes in collimator resolution, as measured by the detectability index, dA, was tracked by the Bayesian detector's signal-to-noise ratio (SNR) somewhat better than by two other estimation models based, respectively, on lesser and greater degrees of lesion size uncertainty. As the range of possible lesion sizes increased, the Bayesian detector's SNR decreased and the optimal collimator resolution shifted towards better resolution. An analytic approximation for the variance of lesion activity estimates (which included the same prior) was shown to predict the variance of the Bayesian estimator over a wide range of collimator resolution values. Because the bias of the Bayesian estimator was small (1%), the analytic variance estimate permitted a rapid and convenient prediction of the Bayesian detection SNR. This calculation was then used to optimize the geometric parameters of a two-layer tungsten collimator being constructed from crossed grids for a new imaging detector. A Monte Carlo program was first run to estimate all contributions to the radial point-spread function for collimators of differing tungsten contents and spatial resolution values, imaging 140-keV photons emitted from the center of a 15-cm-diameter, water-filled attenuator. The optimal collimator design for detecting lesions with unknown diameters in the range 2.5-7.5 mm yielded a system resolution of approximately 8.5-mm FWHM, a geometric collimator efficiency of 1.21 x 10(-4), and a single-septum penetration probability of 1%.

Purpose: Large axial field-of-view (FOV) PET/CT scanners are valued for high sensitivity. Brain PET image quality may depend on the head position within the FOV. We investigated the precision of activity estimation for brain PET imaging when the brain was positioned at the end (END) and in the middle (CEN) of the FOV. The additional CT dose for the CEN position was recorded. Methods: An image quality (Jaszczak) phantom and a striatal phantom were filled with F-18 and positioned in END and CEN locations. For each phantom and each location, we acquired a ∼1-hr listmode PET, rebinned the data into 10 frames with equal number of coincidence events, and reconstructed each frame using an iterative algorithm. For the striatal phantom, END and CEN were compared by drawing on each image three regions of interest (ROI) in axially separated uniform areas. The standard deviation of the activity estimation within each ROI was averaged over the 10 images. The coefficient of variation (CV) for activity estimation was calculated at each position. Image quality was assessed by inspecting the resolution bar pattern in the Jaszczak phantom at two different head positions. Results: The CV was the lowest for ROIs near the center ofmore » the FOV. For slices near the end, not only was the CV highest, but also the resolution pattern was degraded. CTDIvol summarized in the dose report indicated that the CT dose was ∼ 10% higher for CEN as compared to END position. Conclusion: Positioning the brain in the middle of the FOV in a large FOV PET/CT scanner allows more precise measurement of tracer uptake and better image quality at the cost of increased CT dose. For the end location longer scan times may minimize image quality degradation without any additional CT dose.« less

Purpose: To determine the effect of liquid sample volume and geometry on counting efficiency in a gamma well-counter, and to assess the relative contributions of sample geometry and self-attenuation. Gamma wellcounters are standard equipment in clinical and preclinical studies, for measuring patient blood radioactivity and quantifying animal tissue uptake for tracer development and other purposes. Accurate measurements are crucial. Methods: Count rates were measured for aqueous solutions of 99m- Tc at four liquid volume values in a 1-cm-diam tube and at six volume values in a 2.2-cm-diam vial. Total activity was constant for all volumes, and data were corrected for decay. Count rates from a point source in air, supported by a filter paper, were measured at seven heights between 1.3 and 5.7 cm from the bottom of a tube. Results: Sample volume effects were larger for the tube than for the vial. For the tube, count efficiency relative to a 1-cc volume ranged from 1.05 at 0.05 cc to 0.84 at 3 cc. For the vial, relative count efficiency ranged from 1.02 at 0.05 cc to 0.87 at 15 cc. For the point source, count efficiency relative to 1.3 cm from the tube bottom ranged from 0.98 at 1.8more » cm to 0.34 at 5.7 cm. The relative efficiency of a 3-cc liquid sample in a tube compared to a 1-cc sample is 0.84; the average relative efficiency for the solid sample in air between heights in the tube corresponding to the surfaces of those volumes (1.3 and 4.8 cm) is 0.81, implying that the major contribution to efficiency loss is geometry, rather than attenuation. Conclusion: Volume-dependent correction factors should be used for accurate quantitation radioactive of liquid samples. Solid samples should be positioned at the bottom of the tube for maximum count efficiency.« less

Purpose: We have designed a novel collimator for brain SPECT imaging that yields greatly increased sensitivity near the center of the brain without loss of resolution. The collimator was manufactured and initial evaluation has been completed. Methods: The collimator was time-consuming and challenging to build. Because our desired hole pattern required substantial variations in hole angle, we designed two supporting plates to securely position about 34,000 hexagonal, slightly tapered, 75-mm long steel pins. The holes in the plates were modeled to yield the desired focal length, hole length and septal thickness. Molten lead was poured in between the plates, and all pins were removed after cooling. The sensitivity gain compared to a fan-beam collimator was measured using a point source placed along the central ray at several distances from the collimator face. Visual inspection of the holes was not possible as the collimator was sealed so it could be safely mounted on a SPECT system. Therefore, we prepared a 2D array of 768, ∼48μCi Tc-99m point sources, separated by 1.6 cm. The array was imaged for 10 minutes at 4 shifted locations to reduce sampling distance to 8 mm. Results: The sensitivity of the novel cone-beam collimator varied with distancemore » from the detector face; it was higher than that of the fan-beam collimator by factors ranging from 3 to 176. Examination of the projections of the 4×768 point sources revealed that fewer than 2% of the holes were fully or partially blocked, which indicates that the intensive manual fabrication process was very successful. Conclusion: We have designed and manufactured a novel collimator for brain SPECT imaging. As expected, the sensitivity is much higher than that of a fan-beam collimator. Because of differences between the manufactured collimator and its design, reconstruction of the data will require a measured system function.« less

Purpose: The authors have previously reported the advantages of high-sensitivity single-photon emission computed tomography (SPECT) systems for imaging structures located deep inside the brain. DaTscan (Isoflupane I-123) is a dopamine transporter (DaT) imaging agent that has shown potential for early detection of Parkinson disease (PD), as well as for monitoring progression of the disease. Realizing the full potential of DaTscan requires efficient estimation of striatal uptake from SPECT images. They have evaluated two SPECT systems, a conventional dual-head gamma camera with low-energy high-resolution collimators (conventional) and a dedicated high-sensitivity multidetector cardiac imaging system (dedicated) for imaging tasks related to PD. Methods: Cramer–Rao bounds (CRB) on precision of estimates of striatal and background activity concentrations were calculated from high-count, separate acquisitions of the compartments (right striata, left striata, background) of a striatal phantom. CRB on striatal and background activity concentration were calculated from essentially noise-free projection datasets, synthesized by scaling and summing the compartment projection datasets, for a range of total detected counts. They also calculated variances of estimates of specific-to-nonspecific binding ratios (BR) and asymmetry indices from these values using propagation of error analysis, as well as the precision of measuring changes in BR on the order of the average annual decline in early PD. Results: Under typical clinical conditions, the conventional camera detected 2 M counts while the dedicated camera detected 12 M counts. Assuming a normal BR of 5, the standard deviation of BR estimates was 0.042 and 0.021 for the conventional and dedicated system, respectively. For an 8% decrease to BR = 4.6, the signal-to-noise ratio were 6.8 (conventional) and 13.3 (dedicated); for a 5% decrease, they were 4.2 (conventional) and 8.3 (dedicated). Conclusions: This implies that PD can be detected earlier with the dedicated system than with the conventional system; therefore, earlier identification of PD progression should be possible with the high-sensitivity dedicated SPECT camera.

The spatial resolution and noise level of images produced by a commercial analog tomographic scanner have been measured and compared to those of imagesreconstructed digitally from projections from the same detector. The full width at half maximum of the line spread function was 3.6 mm for images from the analog scanner and 1.1 mm for the digitally reconstructed images. The standard deviation of the CT numbers over a 10‐cm2 circular area at the center of a large water phantom, calculated as a percentage of the linear attenuation coefficient of water, was 3.5% for the analog images, 15.4% for high‐resolution digital images, and 3.2% for digital imagesreconstructed using a convolution filter which reduced the resolution to that of the analog images. The data contributing to each digital image were fewer than those contributing to each analog image by a factor of 10. The noise level did not depend on tube current in either the analog or the digital images. The utility of this analog device in radiation therapy planning will depend upon whether errors in contour localization resulting from transferring data from diagnostic CTscanners exceed the errors due to its poorer image quality.

Misregistration of the projections in 360° computed tomographic (CT) scanners has been found to blur the image without generating artifacts. The effects of this error were investigated by analytical methods and by reconstruction of real and simulated data. The point‐spread function which results from shifting each projection by a constant distance e consists of a two‐dimensional impulse function surrounding a region of negative density. The locus of the impulse function is a circle for parallel‐beam geometry and a sixth‐order curve for fanbeam geometry. The anisotropy and position dependence of the point‐spread function in fanbeam geometry have been characterized. The line‐spread function due to the error in parallel‐beam geometry consists of two delta functions located at ±e. In fanbeam geometry, the line‐spread function consists of two delta functions separated by approximately 2e, with the locations of the impulses dependent on the position and orientation of the line. This error, combined with other sources of blurring, results in a system edge‐response function which contains a flat region at one‐half the maximum density.