Krishnendu Saha

UNLABELLED: The objectives of this study were to examine the effective dose range and the test-retest reliability of florbetapir F 18 using, first, visual assessment by independent raters masked to clinical information and, second, semiautomated quantitative measures of cortical target area to cerebellum standardized uptake value ratios (SUVr) as primary outcome measures. Visual ratings of PET image quality and tracer retention or β-amyloid (Aβ) binding expressed as SUVrs were compared after intravenous administration of either 111 MBq (3 mCi) or 370 MBq (10 mCi) of florbetapir F 18 in patients with Alzheimer's disease (AD) (n = 9) and younger healthy controls (YHCs) (n = 11). In a separate set of subjects (AD, n = 10; YHCs, n = 10), test-retest reliability was evaluated by comparing intrasubject visual read ratings and SUVrs for 2 PET images acquired within 4 wk of each other. RESULTS: There were no meaningful differences between the 111-MBq (3-mCi) and 370-MBq (10-mCi) dose in the visual rating or SUVr. The difference in the visual quality across 111 and 370 MBq showed a trend toward lower image quality, but no statistical significance was achieved (t test; t(1) = -1.617, P = 0.12) in this relatively small sample of subjects. At both dose levels, visual ratings of amyloid burden identified 100% of AD subjects as Aβ-positive and 100% of YHCs as Aβ-negative. Mean intrasubject test-retest variability for cortical average SUVrs with the cerebellum as a reference over the 50- to 70-min period was 2.4% ± 1.41% for AD subjects and 1.5% ± 0.84% for controls. The overall SUVr test-retest correlation coefficient was 0.99. The overall κ-statistic for test-retest agreement for Aβ classification of the masked reads was 0.89 (95% confidence interval, 0.69-1.0). CONCLUSION: Florbetapir F 18 appears to have a wide effective dose range and a high test-retest reliability for both quantitative (SUVr) values and visual assessment of the ligand. These imaging performance properties provide important technical information on the use of florbetapir F 18 and PET to detect cerebral amyloid aggregates.

The acquisition and processing of the Jaszczak phantom is a recommended test by the American College of Radiology for evaluation of gamma camera system performance. To produce the reconstructed phantom image for quality evaluation, attenuation correction is applied. The attenuation of counts originating from the center of the phantom is greater than that originating from the periphery of the phantom causing an artifactual appearance of inhomogeneity in the reconstructed image and complicating phantom evaluation. Chang's mathematical formulation is a common method of attenuation correction applied on most gamma cameras that do not require an external transmission source such as computed tomography, radionuclide sources installed within the gantry of the camera or a flood source. Tomographic acquisition can be obtained in two different acquisition modes for dual-detector gamma camera; one where the two detectors are at 180° configuration and acquire projection images for a full 360°, and the other where the two detectors are positioned at a 90° configuration and acquire projections for only 180°. Though Chang's attenuation correction method has been used for 360° angle acquisition, its applicability for 180° angle acquisition remains a question with one vendor's camera software producing artifacts in the images. This work investigates whether Chang's attenuation correction technique can be applied to both acquisition modes by the development of a Chang's formulation-based algorithm that is applicable to both modes. Assessment of attenuation correction performance by phantom uniformity analysis illustrates improved uniformity with the proposed algorithm (22.6%) compared to the camera software (57.6%).

The development of an 18F amyloid imaging biomarker will facilitate the evaluation of individuals with late-life cognitive impairment, by distinguishing those free of AD pathology as evidenced by the absence of Aβ aggregates from those with substantial Aβ deposition in an AD-like pattern. Preliminary studies demonstrated the ability of florpiramine to detect cerebral amyloid with a test-retest variance of 5.1% in AD patients and 2.2% in cognitively normal subjects. Objective: The objective of this study was evaluate the performance characteristics of florpiramine in individuals with probable Alzheimer's disease (AD), mild cognitive impairment (MCI) and normal cognitively intact elderly subjects (NC). Subjects meeting established diagnostic criteria for NC (78), MCI (60), or AD (45), received a clinical, cognitive, and functional evaluation using standardized assessment methods and a 10 minute PET image, acquired 50 minutes following iv injection of 10 mCi (370 MBq) of 18F-AV-45. PET images were rated visually without knowledge of the subject's age or clinical category, on the basis of overall ligand retention in cortical gray matter (scale 0 - 4). In addition, a semi-automated algorithm calculated standard uptake values (SUV) in pre-defined anatomically relevant cortical regions, relative to cerebellar gray matter (SUVr). Demographic of the cohort are listed in Table 1. Mean 18F-AV-45 retention values in cortical gray matter for the NC and AD groups differed significantly (p<0.001) for both the blinded visual PET rating and the automated SUVr values. As expected, there was overlap in florpiramine retention between some subjects in the AD and NC groups. Values for subjects in the MCI group were intermediate those in the NC and AD groups. In general, 18F-AV-45 retention tended to increase with increasing age of the subject. Florpiramine (18F-AV-45) is a sensitive marker for the presence of amyloid in cortical gray matter in elderly individuals, and can differentiate groups of subjects meeting standard diagnostic criteria for AD, MCI, and normal cognitive function. Given the known prevalence of amyloid pathology in cognitively normal older subjects, this information may be of greatest clinical utility when demonstrating the absence of amyloid, thus ruling out AD, in patients undergoing evaluation for late-life cognitive impairment.

To maximize sensitivity, it is desirable that ring Positron Emission Tomography (PET) systems dedicated for imaging the breast have a small bore. Unfortunately, due to parallax error this causes substantial degradation in spatial resolution for objects near the periphery of the breast. In this work, a framework for computing and incorporating an accurate system matrix into iterative reconstruction is presented in an effort to reduce spatial resolution degradation towards the periphery of the breast. The GATE Monte Carlo Simulation software was utilized to accurately model the system matrix for a breast PET system. A strategy for increasing the count statistics in the system matrix computation and for reducing the system element storage space was used by calculating only a subset of matrix elements and then estimating the rest of the elements by using the geometric symmetry of the cylindrical scanner. To implement this strategy, polar voxel basis functions were used to represent the object, resulting in a block-circulant system matrix. Simulation studies using a breast PET scanner model with ring geometry demonstrated improved contrast at 45% reduced noise level and 1.5 to 3 times resolution performance improvement when compared to MLEM reconstruction using a simple line-integral model. The GATE based system matrix reconstruction technique promises to improve resolution and noise performance and reduce image distortion at FOV periphery compared to line-integral based system matrix reconstruction.

In this paper we introduce a new algorithm for multi-focus image fusion based on edge information of the source images and K-mean segmentation. The basic idea is to extract the edge information of the source images, divide the images into blocks and then select the blocks with higher edge information to construct the resultant fused image. The pixels in the unallocated blocks of the fused image are then selected from the source images by recursive K-mean segmentation and comparison of the corresponding segments of the source images. The major achievement of this algorithm is its excellent sharpness, clarity, superior edge preservation with minimum fusion artifacts.