Hoffman 3D Brain Phantom Research Articles

Attenuation correction for phantom tests: an alternative to maximum-likelihood attenuation correction factor-based correction for clinical studies in time-of-flight PET.

This study evaluates the phantom attenuation correction (PAC) method as an alternative to maximum-likelihood attenuation correction factor (ML-ACF) correction in time-of-flight (TOF) brain positron emission tomography (PET) studies. In the PAC algorithm, a template emission image [Formula: see text] and a template attenuation coefficient image [Formula: see text] are prepared as a data set based on phantom geometry. Position-aligned attenuation coefficient image [Formula: see text] is derived by aligning [Formula: see text] using parameters that match the template emission image [Formula: see text] to measured emission image [Formula: see text]. Then, attenuation coefficient image [Formula: see text] combined with a headrest image is used for scatter and attenuation correction in the image reconstruction. To evaluate the PAC algorithm as an alternative to ML-ACF, Hoffman 3D brain and cylindrical phantoms were measured to obtain the image quality indexes of contrast and uniformity. These phantoms were also wrapped with a radioactive sheet to obtain attenuation coefficient images using ML-ACF. Emission images were reconstructed with attenuation correction by PAC and ML-ACF, and the results were compared using contrast and uniformity as well as visual assessment. CT attenuation correction (CT-AC) was also applied as a reference. The contrast obtained by ML-ACF was slightly overestimated due to its unique experimental condition for applying ML-ACF in Hoffman 3D brain phantom but the uniformity was almost equivalent among ML-ACF, CT-AC, and PAC. PAC showed reasonable result without overestimation compared to ML-ACF and CT-AC. PAC is an attenuation correction method that can ensure the performance in phantom test, and is considered to be a reasonable alternative to clinically used ML-ACF-based attenuation correction.

Determination of optimal regularization factor in Bayesian penalized likelihood reconstruction of brain PET images using [18 F]FDG and [11 C]PiB.

The Bayesian penalized likelihood (BPL) reconstruction algorithm, Q.Clear, can achieve a higher signal-to-noise ratio on images and more accurate quantitation than ordered subset-expectation maximization (OSEM). The reconstruction parameter (β) in BPL requires optimization according to the radiopharmaceutical tracer. The present study aimed to define the optimal β value in BPL required to diagnose Alzheimer disease from brain positron emission tomography (PET) images acquired using 18 F-fluoro-2-deoxy-D-glucose ([18 F]FDG) and 11 C-labeled Pittsburg compound B ([11 C]PiB). Images generated from Hoffman 3D brain and cylindrical phantoms were acquired using a Discovery PET/computed tomography (CT) 710 and reconstructed using OSEM+time-of-flight (TOF) under clinical conditions and BPL+TOF (β=20-1000). Contrast was calculated from images generated by the Hoffman 3D brain phantom, and noise and uniformity were calculated from those generated by the cylindrical phantom. Five cognitively healthy controls and five patients with Alzheimer disease were assessed using [18 F]FDG and [11 C]PiB PET to validate the findings from the phantom study. The β values were restricted by the findings of the phantom study, then one certified nuclear medicine physician and two certified nuclear medicine technologists visually determined optimal β values by scoring the quality parameters of image contrast, image noise, cerebellar stability, and overall image quality of PET images from 1 (poor) to 5 (excellent). The contrast in BPL satisfied the Japanese Society of Nuclear Medicine (JSNM) criterion of ≥55% and exceeded that of OSEM at ranges of β=20-450 and 20-600 for [18 F]FDG and [11 C]PiB, respectively. The image noise in BPL satisfied the JSNM criterion of ≤15% and was below that in OSEM when β=150-1000 and 400-1000 for [18 F]FDG and [11 C]PiB, respectively. The phantom study restricted the ranges of β values to 100-300 and 300-500 for [18 F]FDG and [11 C]PiB, respectively. The BPL scores for gray-white matter contrast and image noise, exceeded those of OSEM in [18 F]FDG and [11 C]PiB images regardless of β values. Visual evaluation confirmed that the optimal β values were 200 and 450 for [18 F]FDG and [11 C]PiB, respectively. The BPL achieved better image contrast and less image noise than OSEM, while maintaining quantitative standardized uptake value ratios (SUVR) due to full convergence, more rigorous noise control, and edge preservation. The optimal β values for [18 F]FDG and [11 C]PiB brain PET were apparently 200 and 450, respectively. The present study provides useful information about how to determine optimal β values in BPL for brain PET imaging.

Harmonisation of PET/CT contrast recovery performance for brain studies

PurposeIn order to achieve comparability of image quality, harmonisation of PET system performance is imperative. In this study, prototype harmonisation criteria for PET brain studies were developed.MethodsTwelve clinical PET/CT systems (4 GE, 4 Philips, 4 Siemens, including SiPM-based “digital” systems) were used to acquire 30-min PET scans of a Hoffman 3D Brain phantom filled with ~ 33 kBq·mL−1 [18F]FDG. Scan data were reconstructed using various reconstruction settings. The images were rigidly coregistered to a template (voxel size 1.17 × 1.17 × 2.00 mm3) onto which several volumes of interest (VOIs) were defined. Recovery coefficients (RC) and grey matter to white matter ratios (GMWMr) were derived for eroded (denoted in the text by subscript e) and non-eroded grey (GM) and white (WM) matter VOIs as well as a mid-phantom cold spot (VOIcold) and VOIs from the Hammers atlas. In addition, left-right hemisphere differences and voxel-by-voxel differences compared to a reference image were assessed.ResultsSystematic differences were observed for reconstructions with and without point-spread-function modelling (PSFON and PSFOFF, respectively). Normalising to image-derived activity, upper and lower limits ensuring image comparability were as follows: for PSFON, RCGMe = [0.97–1.01] and GMWMre = [3.51–3.91] for eroded VOI and RCGM = [0.78–0.83] and GMWMr = [1.77–2.06] for non-eroded VOI, and for PSFOFF, RCGMe = [0.92–0.99] and GMWMre = [3.14–3.68] for eroded VOI and RCGM = [0.75–0.81] and GMWMr = [1.72–1.95] for non-eroded VOI.ConclusionsTo achieve inter-scanner comparability, we propose selecting reconstruction settings based on RCGMe and GMWMre as specified in “Results”. These proposed standards should be tested prospectively to validate and/or refine the harmonisation criteria.

Direct comparison of brain [18F]FDG images acquired by SiPM-based and PMT-based PET/CT: phantom and clinical studies

BackgroundSilicon photomultiplier-positron emission tomography (SiPM-PET) has better sensitivity, spatial resolution, and timing resolution than photomultiplier tube (PMT)-PET. The present study aimed to clarify the advantages of SiPM-PET in 18F-fluoro-2-deoxy-D-glucose ([18F]FDG) brain imaging in a head-to-head comparison with PMT-PET in phantom and clinical studies.MethodsContrast was calculated from images acquired from a Hoffman 3D brain phantom, and image noise and uniformity were calculated from images acquired from a pool phantom using SiPM- and PMT-PET. Sequential PMT-PET and SiPM-PET [18F]FDG images were acquired over a period of 10 min from 22 controls and 10 patients. All images were separately normalized to a standard [18F]FDG PET template, then the mean standardized uptake values (SUVmean) and Z-score were calculated using MIMneuro and CortexID Suite, respectively.ResultsImage contrast, image noise, and uniformity in SiPM-PET changed 19.2, 3.5, and − 40.0% from PMT-PET, respectively. These physical indices of both PET scanners satisfied the criteria for acceptable image quality published by the Japanese Society of Nuclear Medicine of contrast > 55%, CV ≤ 15%, and SD ≤ 0.0249, respectively. Contrast was 70.0% for SiPM-PET without TOF and 59.5% for PMT-PET without TOF. The TOF improved contrast by 3.5% in SiPM-PET. The SUVmean using SiPM-PET was significantly higher than PMT-PET and did not correlate with a time delay. Z-scores were also significantly higher in images acquired from SiPM-PET (except for the bilateral posterior cingulate) than PMT-PET because the peak signal that was extracted by the calculation of Z-score in CortexID Suite was increased. The hypometabolic area in statistical maps was reduced and localized using SiPM-PET. The trend was independent of whether the images were derived from controls or patients.ConclusionsThe improved spatial resolution and sensitivity of SiPM-PET contributed to better image contrast and uniformity in brain [18F]FDG images. The SiPM-PET offers better quality and more accurate quantitation of brain PET images. The SUVmean and Z-scores were higher in SiPM-PET than PMT-PET due to improved PVE. [18F]FDG images acquired using SiPM-PET will help to improve diagnostic outcomes based on statistical image analysis because SiPM-PET would localize the distribution of glucose metabolism on Z-score maps.

Experimental study of the fast non-local means noise reduction algorithm using the Hoffman 3D brain phantom in nuclear medicine SPECT image

Gamma imaging of the brain in nuclear medicine usually contains a noise distribution owing to attenuation and scattering effects. This study aimed at improving the quality of the image of the brain acquired by single photon emission computed tomography (SPECT) by applying the fast non-local means (FNLM) algorithm, which an excellent noise reduction technique, using a Hoffman 3D brain phantom filled with 99mTc. Gaussian noise was added to the acquired image using MATLAB and the image quality evaluated using conventional noise reduction filters and the proposed FNLM algorithm. The contrast to noise ratio (CNR), peak signal to noise ratio, and root mean square error were used for quantitative evaluation. Comparing the image qualities obtained using various filters and algorithms, the CNR results of the images with Gaussian and median filters, and FNLM algorithm were found to surpass those of the noise image by 1.06, 1.22, and 1.41 times, respectively. In addition, similarity analysis indicated that the image evaluated using the FNLM algorithm showed excellent quality. Thus, our results demonstrated that the FNLM algorithm provided the greatest improvement in image quality based on quantitative evaluation results in the SPECT system.

Technical Note: A digital reference object representing Hoffman's 3D brain phantom for PET scanner simulations.

Physical and digital phantoms play a key role in the development and testing of nuclear medicine instrumentation and processing algorithms for clinical and research applications, including neuroimaging using positron emission tomography (PET). We have developed and tested a digital reference object (DRO) version of the original segmented magnetic resonance imaging (MRI) data used for the three-dimensional (3D) PET brain phantom developed by Hoffman et al., which is used as the basis of a commercially available physical test phantom. The DRO was constructed by subdividing the MRI image planes the original phantom was based on to create equal-thickness slices and re-labeling voxels. The digital data was then embedded in a PET Digital Imaging and Communications in Medicine format and tested for compliance. We then tested the DRO by comparing it to computed tomography (CT) images of the physical phantom summed to form composite slices with axial extent similar to the DRO, but with a factor of two better in-slice resolution. For composite slices, 91% of voxels were labeled in full agreement, 5% of the voxels were 50-75% accurate, and the remaining 4% of voxels had 25% or less agreement. This DRO can be used as an input for PET scanner simulation studies or for comparing simulations to measured Hoffman phantom images.

Simulation of Motion Induced SPECT Data with Developed Algorithm

In a Single Photon Emission Computed Tomography (SPECT) study, the data acquisition is performed over a relatively long time, typically in the range of 5-30 minutes. For longer period, patient movement frequently occurs in clinical procedure. This movement causes misalignment of the projection frames,which degrades the image quality. In this work, different SPECT studies by using Hoffman 3D brain phantom without motion were acquired and by using algorithm, the motion induced data were simulated from these real data. Different data without motion were acquired by using a Trionix Triad triple-head SPECT camera withthe phantom. Simulated data were evaluated and Mean Square Differences (MSD) was calculated using two differently developed algorithms. These simulated data were produced by adding projection framespartiallywith the aim to produce a new data set so that it simulates motion induced data. We calculated the MSD from the simulated data by analyzing each projection frame. The result showsthe significant MSD values between two different projection frames which were obtained from two different SPECT acquisitions. Motion induced simulated data is useful in quantifying motion estimation and to develop correction methods that will allow derivation of motion free data.
 Bangladesh J. Nuclear Med. 21(1): 31-34, January 2018

Phantom criteria for qualification of brain FDG and amyloid PET across different cameras.

BackgroundWhile fluorodeoxyglucose (FDG) and amyloid PET is valuable for patient management, research, and clinical trial of therapeutics on Alzheimer’s disease, the specific details of the PET scanning method including the PET camera model type influence the image quality, which may further affect the interpretation of images and quantitative capabilities. To make multicenter PET data reliable and to establish PET scanning as a universal diagnostic technique and a verified biomarker, we have proposed phantom test procedures and criteria for optimizing image quality across different PET cameras.ResultsAs the method, four physical parameters (resolution, gray-white contrast, uniformity, and image noise) were selected as essential to image quality for brain FDG and amyloid PET and were measured with a Hoffman 3D brain phantom and a uniform cylindrical phantom on a total of 12 currently used PET models. The phantom radioactivity and acquisition time were determined based on the standard scanning protocol for each PET drug (FDG, 11C-PiB, 18F-florbetapir, and 18F-flutemetamol). Reconstruction parameters were either determined based on the methods adopted in ADNI, J-ADNI, and other research and clinical trials or optimized based on measured phantom image parameters under various reconstruction conditions.As the result, phantom test criteria were proposed as follows: (i) 8 mm FWHM or better resolution and (ii) gray/white %contrast ≥55 % with the Hoffman 3D brain phantom and (iii) SD of 51 small region of interests (ROIs) ≤0.0249 (equivalent to 5 % variation) for uniformity and (iv) image noise (SD/mean) ≤15 % for a large ROI with the uniform cylindrical phantom. These criteria provided image quality conforming to those multicenter clinical studies and were also achievable with most of the PET cameras that are currently used.ConclusionsThe proposed phantom test criteria facilitate standardization and qualification of brain FDG and amyloid PET images and deserve further evaluation by future multicenter clinical studies.

Optimization of image reconstruction conditions with phantoms for brain FDG and amyloid PET imaging.

The purpose of this study was to optimize image reconstruction conditions for brain (18)F-FDG, (11)C-PiB, (18)F-florbetapir and (18)F-flutemetamol PET imaging with Discovery-690 PET/CT for diagnosis and research on Alzheimer's disease (AD) based on the standard imaging protocols and phantom test procedures and criteria published by the Japanese society of nuclear medicine (JSNM). A Hoffman 3D brain phantom and a cylindrical pool phantom were scanned according to the JSNM procedure, and the reconstruction conditions (iteration, subset, post-filter) were optimized so that the images satisfy the JSNM criteria regarding spatial resolution (FWHM ≤ 8 mm) and gray/white matter contrast (%contrast ≥ 55%) on the Hoffman phantom and uniformity (SD of small ROIs ≤ 0.0249) and image noise (coefficient of variation ≤ 15 %) on the pool phantom. Human images were acquired with (18)F-FDG (15-min scan starting at 30 min post-injection [p.i.] of 185 MBq), (11)C-PiB (20-min scan starting at 50 min p.i. of 555 MBq), (18)F-florbetapir (10-min scan starting at 50 min p.i. of 370 MBq) and (18)F-flutemetamol (30-min scan starting at 90 min p.i. of 185 MBq) on 1 or 2 subjects for each tracer and reconstructed with thus determined conditions to evaluate the image quality visually. The effect of reconstruction parameters on the standardized uptake value ratio (SUVR) was also evaluated on 5 amyloid-positive and 5 amyloid-negative PiB images. A sufficient image quality was obtained at an iterative update (product of iteration and subset) of 64 for (18)F-FDG. The same reconstruction parameters with an additional Gaussian filter of 5 mm FWHM was optimal for (11)C-PiB, (18)F-florbetapir and (18)F-flutemetamol to achieve the phantom criteria. Those optimal reconstruction conditions were confirmed with human images. The SUVR value was stable over a wide range of iterative updates around the optimal parameters both for positive and negative amyloid images. Optimal image reconstruction conditions were determined for brain (18)F-FDG and amyloid PET imaging with Discovery-690 PET/CT for diagnosis and research on AD based on the JSNM phantom criteria. This supports feasibility of the phantom criteria for standardization and harmonization of brain (18)F-FDG and amyloid PET for multicenter studies.

Qualitative and Quantitative Evaluation of Blob-Based Time-of-Flight PET Image Reconstruction in Hybrid Brain PET/MR Imaging.

PurposeMany neurological diseases affect small structures in the brain and, as such, reliable visual evaluation and accurate quantification are required. Recent technological developments made the clinical use of hybrid positron emission tomography/magnetic resonance (PET/MR) systems possible, providing both functional and anatomical information in a single imaging session. Nevertheless, there is a trade-off between spatial resolution and image quality (contrast and noise), which is dictated mainly by the chosen acquisition and reconstruction protocols. Image reconstruction algorithms using spherical symmetric basis functions (blobs) for image representation have a number of additional parameters that impact both the qualitative and quantitative image characteristics. Hence, a detailed investigation of the blob-based reconstruction characteristics using different parameters is needed to achieve optimal reconstruction results.ProceduresThis work evaluated the impact of a range of blob parameters on image quality and quantitative accuracy of brain PET images acquired on the Ingenuity Time-of-Flight (TOF) PET/MR system. Two different phantoms were used to simulate brain imaging applications. Image contrast and noise characteristics were assessed using an image quality phantom. Quantitative performance in a clinical setting was investigated using the Hoffman 3D brain phantom at various count levels. Furthermore, the visual quality of four clinical studies was scored blindly by two experienced physicians to qualitatively evaluate the influence of different reconstruction protocols, hereby providing indications on parameters producing the best image quality.ResultsQuantitative evaluation using the image quality phantom showed that larger basis function radii result in lower contrast recovery (∼2 %) and lower variance levels (∼15 %). The brain phantom and clinical studies confirmed these observations since lower contrast was seen between anatomical structures. High and low count statistics gave comparable values. The qualitative evaluation of the clinical studies, based on the assessment performed by the physicians, showed a preference towards lower image variance levels with a slightly lower contrast, favoring higher radii and four iterations.ConclusionThis study systematically evaluated a number of basis function parameters and their quantitative and qualitative effect within PET image reconstruction in the context of brain imaging. A range of blob parameters can minimize error and provided optimal image quality, where the anatomical structures could be recognized but the exact delineation of these structures is simplified in scans with lower image variance levels and thus, higher radii should be preferred. With the optimization of blob parameters, the reconstructed images were found to be qualitatively improved (optimum parameters {d = 2.0375, alpha = 10.4101, radius = 3.9451}) as assessed by the physicians compared to the current clinical protocol. However, this qualitative improvement is task specific, depending on the desired image characteristics to be extracted. Finally, this work could be used as a guide for application-specific optimal parameter selection.Electronic supplementary materialThe online version of this article (doi:10.1007/s11307-015-0824-x) contains supplementary material, which is available to authorized users.

Evaluation of the dependence of the exposure dose on the attenuation correction in brain PET/CT scans using 18F-FDG

This study examined whether scanning could be performed with minimum dose and minimum exposure to the patient after an attenuation correction. A Hoffman 3D Brain Phantom was used in BIO_40 and D_690 PET/CT scanners, and the CT dose for the equipment was classified as a low dose (minimum dose), medium dose (general dose for scanning) and high dose (dose with use of contrast medium) before obtaining the image at a fixed kilo-voltage-peak (kVp) and milliampere (mA) that were adjusted gradually in 17–20 stages. A PET image was then obtained to perform an attenuation correction based on an attenuation map before analyzing the dose difference. Depending on tube current in the range of 33–190 milliampere-second (mAs) when BIO_40 was used, a significant difference in the effective dose was observed between the minimum and the maximum mAs (p < 0.05). According to a Scheffe post-hoc test, the ratio of the minimum to the maximum of the effective dose was increased by approximately 5.26-fold. Depending on the change in the tube current in the range of 10–200 mA when D_690 was used, a significant difference in the effective dose was observed between the minimum and the maximum of mA (p < 0.05). The Scheffe posthoc test revealed a 20.5-fold difference. In conclusion, because effective exposure dose increases with increasing operating current, it is possible to reduce the exposure limit in a brain scan can be reduced if the CT dose can be minimized for a transmission scan.

Quantitative Evaluation of Half-Cone-Beam Scan Paths in Triple-Camera Brain SPECT

In this study related to human brain SPECT imaging, simulation of half-cone-beam (HCB) collimation with different scan paths is performed and compared with simulated fan-beam and parallel-hole circular orbit acquisitions of disk-phantom projection data. Acquisition types are quantitatively evaluated based on the photon detection efficiency, the root-mean-squared error, contrast and signal-to-noise ratio measurements of the reconstructed images. We demonstrate that a triple-camera SPECT system with half-cone-beam collimators and circle-and-helix scan paths can offer up to a 26% efficiency increase over fan-beam, and up to a 128% increase over parallel-hole collimators for equal spatial resolutions, and display no visible axial sampling artifacts in reconstructed disk-phantom images. In addition, we perform qualitative experimental evaluation of triple-HCB circle-and-helix acquisition using a Hoffman 3D brain phantom. Reconstructed brain phantom images show improved quality due to reduced noise and no apparent sampling artifacts. Triple-HCB circle-and-helix SPECT has a potential for improved brain imaging, producing higher image quality with a smaller reconstruction error and better lesion detectability due to increased efficiency for equal spatial resolution compared to conventional fan-beam and parallel-hole SPECT.

Assessment of the short-lived non-pure positron-emitting nuclide 120I for PET imaging

The non-pure positron-emitting iodine isotope (120)I (T(1/2)=81 min) is a short-lived alternative to (124)I. (120)I has a positron abundance more than twice that of (124)I and a maximum positron energy of 4 MeV. This study was undertaken to evaluate and characterise the qualitative and quantitative PET imaging of (120)I. (120)I was produced via the (120)Te(p,n) reaction on highly enriched (120)Te. The measurements were done with the Siemens scanner HR+ and the 2D PET scanner GE PC4096+. A cylinder containing three cold inserts and a phantom resembling a human brain slice were used to evaluate half-life, positron abundance and background correction. To analyse the image resolution, a -mm tube placed in water was filled with (120)I and (18)F. Comparisons with (18)F, (124)I and (123)I (measured with SPECT) were made using the Hoffman 3D brain phantom. The half-life of 81.1 min was reproduced by the PET measurements. The PET-based positron abundance ranged from 47.9% to 55.0%. The reconstructed image resolution found with the HR+ was 5.4 mm FWHM (12.3 mm FWTM), in contrast to 4.6 mm (8.6 mm) when using (18)F. Erroneous positive and negative numbers of radioactivity found in the cold inserts became nearly zero when the background of gamma-coincidences was corrected for. Images of the Hoffman phantom were inferior to those obtained when (18)F or (124)I was applied but superior to the (123)I-SPECT images. Our data show that (120)I of high radionuclidic purity can be regarded as a suitable nuclide for the PET imaging of radioiodine-labelled pharmaceuticals.

Brain FDG PET study of normal aging in Japanese: effect of atrophy correction

The aim of this study was to investigate the effects of atrophy correction on the results of 18F-fluorodeoxyglucose positron emission tomography (FDG PET) in the context of normal aging. Before the human study was performed, a Hoffman 3D brain phantom experiment was carried out in order to validate a newly developed correction method for partial volume effects (PVEs). Brain FDG PET was then performed in 139 healthy Japanese volunteers (71 men, 68 women; age 24-81 years). PET images were corrected for PVEs using grey matter volume, which was segmented from co-registered magnetic resonance images and convoluted with the spatial resolution of the PET scanner. We investigated the correlation between advancing age and relative regional FDG activity, which was normalised to the global activity before and after PVE correction using Statistical Parametric Mapping 99. The PET image, when corrected for PVEs, provided more homogeneous tracer distribution in the whole phantom than in the original PET image. The human PET study of both sexes revealed significant negative correlations between age and relative FDG activity in the bilateral perisylvian and medial frontal areas before PVE correction. However, these negative correlations were largely resolved after PVE correction. Correction for PVEs was effective in our FDG PET study. The reduction in FDG uptake with advancing age that was detected by FDG PET without PVE correction could be accounted for largely by an age-related cerebral volume loss in the bilateral perisylvian and medial frontal areas.

A practical 3D tomographic method for correcting patient head motion in clinical SPECT

Patient motion during brain SPECT studies can degrade resolution and introduce distortion. We have developed a correction method which incorporates a motion tracking system to monitor the position and orientation of the patient's head during acquisition. Correction is achieved by spatially repositioning projections according to the measured head movements and reconstructing these projections with a fully 3D algorithm. The method has been evaluated in SPECT studies of the Hoffman 3D brain phantom performed on a triple head camera with fan beam collimation. Movements were applied to the phantom and recorded by a head tracker during SPECT acquisition. Fully 3D reconstruction was performed using the motion data provided by the tracker. The correction accuracy was assessed by comparing the corrected and uncorrected studies with a motion-free study, both visually and by calculating the mean squared error (MSE). In all studies, motion correction reduced the distortion and improved the MSE by a factor of two or more. We conclude that this method can compensate for head motion under clinical SPECT imaging conditions.