Attention-based deep neural network for partial volume correction in brain 18F-FDG PET imaging.

PURPOSE: This work set out to propose an attention-based deep neural network to predict partial volume corrected images from PET data not utilizing anatomical information. METHODS: An attention-based convolutional neural network (ATB-Net) is developed to predict PVE-corrected images in brain PET imaging by concentrating on anatomical areas of the brain. The performance of the deep neural network for performing PVC without using anatomical images was evaluated for two PVC methods, including iterative Yang (IY) and reblurred Van-Cittert (RVC) approaches. The RVC and IY PVC approaches were applied to PET images to generate the reference images. The training of the U-Net network for the partial volume correction was trained twice, once without using the attention module and once with the attention module concentrating on the anatomical brain regions. RESULTS: Regarding the peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and root mean square error (RMSE) metrics, the proposed ATB-Net outperformed the standard U-Net model (without attention compartment). For the RVC technique, the ATB-Net performed just marginally better than the U-Net; however, for the IY method, which is a region-wise method, the attention-based approach resulted in a substantial improvement. The mean absolute relative SUV difference and mean absolute relative bias improved by 38.02 % and 91.60 % for the RVC method and 77.47 % and 79.68 % for the IY method when using the ATB-Net model, respectively. CONCLUSIONS: Our results propose that without using anatomical data, the attention-based DL model could perform PVC on PET images, which could be employed for PVC in PET imaging.

Correction of multiplexing artefacts in multi-pinhole SPECT through temporal shuttering, de-multiplexing of projections, and alternating reconstruction.

Objective.Single-photon emission computed tomography (SPECT) with pinhole collimators can provide high-resolution imaging, but is often limited by low sensitivity. Acquiring projections simultaneously through multiple pinholes affords both high resolution and high sensitivity. However, the overlap of projections from different pinholes on detectors, known as multiplexing, has been shown to cause artefacts which degrade reconstructed images.Approach.Multiplexed projection sets were considered here using an analytic simulation model of AdaptiSPECT-C-a brain-dedicated multi-pinhole SPECT system. AdaptiSPECT-C has fully adaptable aperture shutters, so can acquire projections with a combination of multiplexed and non-multiplexed frames using temporal shuttering. Two strategies for reducing multiplex artefacts were considered: an algorithm to de-multiplex projections, and an alternating reconstruction strategy for projections acquired with a combination of multiplexed and non-multiplexed frames. Geometric and anthropomorphic digital phantoms were used to assess a number of metrics.Main results.Both de-multiplexing strategies showed a significant reduction in image artefacts and improved fidelity, image uniformity, contrast recovery and activity recovery (AR). In all cases, the two de-multiplexing strategies resulted in superior metrics to those from images acquired with only mux-free frames. The de-multiplexing algorithm provided reduced image noise and superior uniformity, whereas the alternating strategy improved contrast and AR.Significance.The use of these de-multiplexing algorithms means that multi-pinhole SPECT systems can acquire projections with more multiplexing without degradation of images.

Deep learning-based partial volume correction in standard and low-dose positron emission tomography-computed tomography imaging.

Background: Positron emission tomography (PET) imaging encounters the obstacle of partial volume effects, arising from its limited intrinsic resolution, giving rise to (I) considerable bias, particularly for structures comparable in size to the point spread function (PSF) of the system; and (II) blurred image edges and blending of textures along the borders. We set out to build a deep learning-based framework for predicting partial volume corrected full-dose (FD + PVC) images from either standard or low-dose (LD) PET images without requiring any anatomical data in order to provide a joint solution for partial volume correction and de-noise LD PET images. Methods: We trained a modified encoder-decoder U-Net network with standard of care or LD PET images as the input and FD + PVC images by six different PVC methods as the target. These six PVC approaches include geometric transfer matrix (GTM), multi-target correction (MTC), region-based voxel-wise correction (RBV), iterative Yang (IY), reblurred Van-Cittert (RVC), and Richardson-Lucy (RL). The proposed models were evaluated using standard criteria, such as peak signal-to-noise ratio (PSNR), root mean squared error (RMSE), structural similarity index (SSIM), relative bias, and absolute relative bias. Results: Different levels of error were observed for these partial volume correction methods, which were relatively smaller for GTM with a SSIM of 0.63 for LD and 0.29 for FD, IY with an SSIM of 0.63 for LD and 0.67 for FD, RBV with an SSIM of 0.57 for LD and 0.65 for FD, and RVC with an SSIM of 0.89 for LD and 0.94 for FD PVC approaches. However, large quantitative errors were observed for multi-target MTC with an RMSE of 2.71 for LD and 2.45 for FD and RL with an RMSE of 5 for LD and 3.27 for FD PVC approaches. Conclusions: We found that the proposed framework could effectively perform joint de-noising and partial volume correction for PET images with LD and FD input PET data (LD vs. FD). When no magnetic resonance imaging (MRI) images are available, the developed deep learning models could be used for partial volume correction on LD or standard PET-computed tomography (PET-CT) scans as an image quality enhancement technique.

Cerebral SPECT imaging with different acquisition schemes using varying levels of multiplexing versus sensitivity in an adaptive multi-pinhole brain-dedicated scanner.

Application of multi-pinhole collimator in pinhole-based SPECT increases detection sensitivity. The presence of multiplexing in projection images due to the usage of multiple pinholes can further improve the sensitivity at the cost of adding data ambiguity. We are developing a next-generation adaptive brain-dedicated SPECT system -AdaptiSPECT-C. The AdaptiSPECT-C can adapt the multiplexing level and system sensitivity using adaptable pinhole modules. In this study, we investigated the performance of 4 data acquisition schemes with different multiplexing levels and sensitivities on cerebral SPECT imaging. Schemes #1, #2, and #3 have <1%, 67%, and 31% overall multiplexing, respectively, while the 4th scheme without multiplexing is considered as ground truth. The ground-truth and schemes #1-3 have 1.0, 1.7, 5.1, and 4.0 times higher sensitivity, respectively, compared to a dual-headed parallel-hole SPECT system at matched spatial resolution. A customized XCAT brain perfusion digital phantom emulating the distribution of I-123 N-isopropyl iodoamphetamine (IMP) in a 99th percentile size male was used for simulations. Data acquisition for each scheme was performed at two count levels (low-count and high-count relative to the recommended clinical count level). The normalized root-mean-square error (NRMSE) for schemes #1, #2, and #3 with the low-count (high-count) scenario showed 11%, 4%, and 5% (10%, 5%, and 6%) deviation, respectively, from that of the multiplex-free ground truth. For both the low-count and high-count scenarios, scheme #1 resulted in the least accurate activity ratio (AR) for almost all the analyzed gray-matter brain regions. Further schemes #2 or #3 led to the most accurate AR values with both low-count and high-count scenarios for all the analyzed gray-matter regions. It was thus observed that even with this large head size which leads to significant multiplexing levels, the higher sensitivity from multiplexing could to some extent mitigate the data ambiguity and be translated into reconstructed images of higher quality.

Improved Performance of a Multipinhole SPECT for DAT Imaging by Increasing Number of Pinholes at the Expense of Increased Multiplexing.

SPECT imaging of dopamine transporters (DAT) in the brain is a widely utilized study to improve the diagnosis of Parkinsonian syndromes, where conventional (parallel-hole and fan-beam) collimators on dual-head scanners are commonly employed. We have designed a multi-pinhole (MPH) collimator to improve the performance of DAT imaging. The MPH collimator focuses on the striatum and hence offers a better trade-off for sensitivity and spatial resolution than the conventional collimators within this clinically most relevant region for DAT imaging. Our original MPH design consisted of 9 pinholes with a background-to-striatal (Bkg/Str) projection multiplexing of 1% only. In this simulation study, we investigated whether further improvements in the performance of MPH imaging could be obtained by increasing the number of pinholes, hence by enhancing the sensitivity and sampling, despite the ambiguity in reconstructing images due to increased multiplexing. We performed analytic simulations of the MPH configurations with 9, 13, and 16 pinholes (aperture diameters: 4-6mm) using a digital phantom modeling DAT imaging. Our quantitative analyses indicated that using 13 (Bkg/Str: 12%) and 16 (Bkg/Str: 22%) pinholes provided better performance than the original 9-pinhole configuration for the acquisition with 2 or 4 angular views, but a similar performance with 8 and 16 views.

Inclusion of quasi-vertex views in a brain-dedicated multi-pinhole SPECT system for improved imaging performance.

With brain-dedicated multi-detector systems employing pinhole apertures the usage of detectors facing the top of the patient's head (i.e. quasi-vertex (QV) views) can provide the advantage of additional viewing from close to the brain for improved detector coverage. In this paper, we report the results of simulation and reconstruction studies to investigate the impact of the QV views on the imaging performance of AdaptiSPECT-C, a brain-dedicated stationary SPECT system under development. In this design, both primary and scatter photons from regions located inferior to the brain can contribute to SPECT projections acquired by the QV views, and thus degrade AdaptiSPECT-C imaging performance. In this work, we determined the proportion, origin, and nature (i.e. primary, scatter, and multiple-scatter) of counts emitted from structures within the head and throughout the body contributing to projections from the different AdaptiSPECT-C detector rings, as well as from a true vertex view detector. We simulated phantoms used to assess different aspects of image quality (i.e. uniform activity concentration sphere, and Derenzo), as well as anthropomorphic phantoms with different count levels emulating clinical 123I activity distributions (i.e. DaTscan and perfusion). We determined that attenuation and scatter in the patient's body greatly diminish the probability of the photons emitted outside the volume of interest reaching to detectors and being recorded within the 15% photopeak energy window. In addition, we demonstrated that the inclusion of the residual of such counts in the system acquisition does not degrade visual interpretation or quantitative analysis. The addition of the QV detectors improves volumetric sensitivity, angular sampling, and spatial resolution leading to significant enhancement in image quality, especially in the striato-thalamic and superior regions of the brain. Besides, the use of QV detectors improves the recovery of clinically relevant metrics such as the striatal binding ratio and mean activity in selected cerebral structures. Our findings proving the usefulness of the QV ring for brain imaging with 123I agents can be generalized to other commonly used SPECT imaging agents labelled with isotopes, such as 99mTc and likely 111In.

Improvement in sampling and modulation of multiplexing with temporal shuttering of adaptable apertures in a brain-dedicated multi-pinhole SPECT system.

We are developing a multi-detector pinhole-based stationary brain-dedicated SPECT system: AdaptiSPECT-C. In this work, we introduced a new design prototype with multiple adaptable pinhole apertures for each detector to modulate the multiplexing by employing temporal shuttering of apertures. Temporal shuttering of apertures over the scan time provides the AdaptiSPECT-C with the capability of multiple-frame acquisition. We investigated, through analytic simulation, the impact of projection multiplexing on image quality using several digital phantoms and a customized anthropomorphic phantom emulating brain perfusion clinical distribution. The 105 pinholes in the collimator of the system were categorized into central, axial, and lateral apertures. We generated, through simulation, collimators of different multiplexing levels. Several data acquisition schemes were also created by changing the imaging time share of the acquisition frames. Sensitivity increased by 35% compared to the single-pinhole-per-detector base configuration of the AdaptiSPECT-C when using the central, axial, and lateral apertures with equal acquisition time shares within a triple-frame scheme with a high multiplexing scenario. Axial and angular sampling of the base configuration was enhanced by adding the axial and lateral apertures. We showed that the temporal shuttering of apertures can be exploited, trading the sensitivity, to modulate the multiplexing and to acquire a set of non-multiplexed non-truncated projections. Our results suggested that reconstruction benefited from utilizing both non-multiplexed projections and projections with modulated multiplexing resulting in a noticeably reduction in the multiplexing-induced image artefacts. Contrast recovery factor improved by 20% (9%) compared to the base configuration for a Defrise (hot-rod) phantom study when the central and axial (lateral) apertures with equal time shares were combined. The results revealed that, as an overall trend at each simulated multiplexing level, lowest normalized root-mean-square errors for the brain gray-matter regions were achieved with the combined usage of the central apertures and axial/lateral apertures.

Investigation of Axial and Angular Sampling in Multi-Detector Pinhole-SPECT Brain Imaging.

We designed a dedicated multi-detector multi-pinhole brain SPECT scanner to generate images of higher quality compared to general-purpose systems. The system, AdaptiSPECT-C, is intended to adapt its sensitivity-resolution trade-off by varying its aperture configurations allowing both high-sensitivity dynamic and high-spatial-resolution static imaging. The current system design consists of 23 detector heads arranged in a truncated spherical geometry. In this work, we investigated the axial and angular sampling capability of the current stationary system design. Two data acquisition schemes using limited rotation of the gantry and two others using axial translation of the imaging bed were also evaluated concerning their impact on image quality through improved sampling. Increasing both angular and axial sampling in the current prototype system resulted in quantitative improvements in image quality metrics and qualitative appearance of the images as determined in studies with specifically selected phantoms. Visual improvements for the brain phantoms with clinical distributions were less pronounced but presented quantitative improvements in the fidelity (normalized root-mean-square error (NRMSE)) and striatal specific binding ratio (SBR) for a dopamine transporter (DAT) distribution, and in NRMSE and activity recovery for a brain perfusion distribution. More pronounced improvements with increased sampling were seen in contrast recovery coefficient, bias, and coefficient of variation for a lesion in the brain perfusion distribution. The negligible impact of the most cranial ring of detectors on axial sampling, but its significant impact on sensitivity and angular sampling in the cranial portion of the imaging volume-of-interest were also determined.

Primary, scatter, and penetration characterizations of parallel-hole and pinhole collimators for I-123 SPECT.

Multi-pinhole (MPH) collimators are known to provide better trade-off between sensitivity and resolution for preclinical, as well as for smaller regions in clinical SPECT imaging compared to conventional collimators. In addition to this geometric advantage, MPH plates typically offer better stopping power for penetration than the conventional collimators, which is especially relevant for I-123 imaging. The I-123 emits a series of high-energy (>300 keV, ~2.5% abundance) gamma photons in addition to the primary emission (159 keV, 83% abundance). Despite their low abundance, high-energy photons penetrate through a low-energy parallel-hole (LEHR) collimator much more readily than the 159 keV photons, resulting in large downscatter in the photopeak window. In this work, we investigate the primary, scatter, and penetration characteristics of a single pinhole collimator that is commonly used for I-123 thyroid imaging and our two MPH collimators designed for I-123 DaTscan imaging for Parkinson's Disease, in comparison to three different parallel-hole collimators through a series of experiments and Monte Carlo simulations. The simulations of a point source and a digital human phantom with DaTscan activity distribution showed that our MPH collimators provide superior count performance in terms of high primary counts, low penetration, and low scatter counts compared to the parallel-hole and single pinhole collimators. For example, total scatter, multiple scatter, and collimator penetration events for the LEHR were 2.5, 7.6 and 14 times more than that of MPH within the 15% photopeak window. The total scatter fraction for LEHR was 56% where the largest contribution came from the high-energy scatter from the back compartments (31%). For the same energy window, the total scatter for MPH was 21% with only 1% scatter from the back compartments. We therefore anticipate that using MPH collimators, higher quality reconstructions can be obtained in a substantially shorter acquisition time for I-123 DaTscan and thyroid imaging.

Simulations of a Multi-Pinhole SPECT Collimator for Clinical Dopamine Transporter (DAT) Imaging.

SPECT imaging of the dopamine transporter (DAT) is used for diagnosis and monitoring progression of Parkinson's Disease (PD), and differentiation of PD from other neurological disorders. The diagnosis is based on the DAT binding in the caudate and putamen structures in the striatum. We previously proposed a relatively inexpensive method to improve the detection and quantification of these structures for dual-head SPECT by replacing one of the fan-beam collimators with a specially designed multi-pinhole (MPH) collimator. In this work, we developed a realistic model of the proposed MPH system using the GATE simulation package and verified the geometry with an analytic simulator. Point source projections from these simulations closely matched confirming the accuracy of the pinhole geometries. The reconstruction of a hot-rod phantom showed that 4.8 mm resolution is achievable. The reconstructions of the XCAT brain phantom showed clear separation of the putamen and caudate, which is expected to improve the quantification of DAT imaging and PD diagnosis. Using this GATE model, point spread functions modeling physical factors will be generated for use in reconstruction. Also, further improvements in geometry are being investigated to increase the sensitivity of this base system while maintaining a target spatial resolution of 4.5-5 mm.

Development and Evaluation of Image Reconstruction Algorithms for a Novel Desktop SPECT System.

OBJECTIVE S: Various iterative reconstruction algorithms in nuclear medicine have been introduced in the last three decades. For each new imaging system, it is wise to select appropriate image reconstruction algorithms and evaluate their performance. In this study, three approaches of image reconstruction were developed for a novel desktop open-gantry SPECT system, PERSPECT, to assess their performance in terms of the quality of the resultant reconstructed images. METHODS: In the present work, a proposed image reconstruction algorithm for the PERSPECT, referred to as quasi-simultaneous multiplicative algebraic reconstruction technique (qSMART), together with two popular image reconstruction methods, maximum-likelihood expectation-maximization (MLEM) and ordered-subsets EM (OSEM), were implemented and compared. Analytic and Monte Carlo simulations were applied for data acquisition of various phantoms including a micro-Derenzo phantom. All acquired data were reconstructed by the three algorithms using different number of iterations (1-40 ). A thorough set of figures-of-merit was utilized to quantitatively compare the generated images. RESULTS: OSEM depicted reconstructed images of higher (or matching) quality in comparison to qSMART. MLEM also reached nearly similar quality as OSEM but at higher number of iterations. The graph of data discrepancy revealed that the ranking of the three approaches in terms of convergence speed is as qSMART, OSEM, and MLEM. Furthermore, bias-versus-noise curves indicated that optimal bias-noise results were achieved using OSEM. CONCLUSION: The results showed that although qSMART can be applied for image reconstruction if being halted in the early iterations (up to 5), the best achievable quality of images is obtained using the OSEM.

Design and assessment of a novel SPECT system for desktop open-gantry imaging of small animals: A simulation study.

PURPOSE: Given increasing efforts in biomedical research utilizing molecular imaging methods, development of dedicated high-performance small-animal SPECT systems has been growing rapidly in the last decade. In the present work, we propose and assess an alternative concept for SPECT imaging enabling desktop open-gantry imaging of small animals. METHODS: The system, PERSPECT, consists of an imaging desk, with a set of tilted detector and pinhole collimator placed beneath it. The object to be imaged is simply placed on the desk. Monte Carlo (MC) and analytical simulations were utilized to accurately model and evaluate the proposed concept and design. Furthermore, a dedicated image reconstruction algorithm, finite-aperture-based circular projections (FABCP), was developed and validated for the system, enabling more accurate modeling of the system and higher quality reconstructed images. Image quality was quantified as a function of different tilt angles in the acquisition and number of iterations in the reconstruction algorithm. Furthermore, more complex phantoms including Derenzo, Defrise, and mouse whole body were simulated and studied. RESULTS: The sensitivity of the PERSPECT was 207 cps/MBq. It was quantitatively demonstrated that for a tilt angle of 30°, comparable image qualities were obtained in terms of normalized squared error, contrast, uniformity, noise, and spatial resolution measurements, the latter at ∼0.6 mm. Furthermore, quantitative analyses demonstrated that 3 iterations of FABCP image reconstruction (16 subsets/iteration) led to optimally reconstructed images. CONCLUSIONS: The PERSPECT, using a novel imaging protocol, can achieve comparable image quality performance in comparison with a conventional pinhole SPECT with the same configuration. The dedicated FABCP algorithm, which was developed for reconstruction of data from the PERSPECT system, can produce high quality images for small-animal imaging via accurate modeling of the system as incorporated in the forward- and back-projection steps. Meanwhile, the developed MC model and the analytical simulator of the system can be applied for further studies on development and evaluation of the system.

Design and development of a dedicated portable gamma camera system for intra-operative imaging.

PURPOSE: We developed a high performance portable gamma camera platform dedicated to identification of sentinel lymph nodes (SLNs) and radio-guided surgery for cancer patients. In this work, we present the performance characteristics of SURGEOSIGHT-I, the first version of this platform that can intra-operatively provide high-resolution images of the surveyed areas. METHODS: At the heart of this camera, there is a 43×43 array of pixelated sodium-activated cesium iodide (CsI(Na)) scintillation crystal with 1×1mm(2) pixel size and 5mm thickness coupled to a Hamamatsu H8500 flat-panel multi-anode (64 channels) photomultiplier tube. The probe is equipped with a hexagonal parallel-hole lead collimator with 1.2mm holes. The detector, collimator, and the associated front-end electronics are encapsulated in a common housing referred to as head. RESULTS: Our results show a count rate of ∼41kcps for 20% count loss. The extrinsic energy resolution was measured as 20.6% at 140keV. The spatial resolution and the sensitivity of the system on the collimator surface was measured as 2.2mm and 142cps/MBq, respectively. In addition, the integral and differential uniformity, after uniformity correction, in useful field-of-view (UFOV) were measured 4.5% and 4.6%, respectively. CONCLUSIONS: This system can be used for a number of clinical applications including SLN biopsy and radiopharmaceutical-guided surgery.

Resolution-recovery-embedded image reconstruction for a high-resolution animal SPECT system.

The small-animal High-Resolution SPECT (HiReSPECT) is a dedicated dual-head gamma camera recently designed and developed in our laboratory for imaging of murine models. Each detector is composed of an array of 1.2 × 1.2 mm(2) (pitch) pixelated CsI(Na) crystals. Two position-sensitive photomultiplier tubes (H8500) are coupled to each head's crystal. In this paper, we report on a resolution-recovery-embedded image reconstruction code applicable to the system and present the experimental results achieved using different phantoms and mouse scans. Collimator-detector response functions (CDRFs) were measured via a pixel-driven method using capillary sources at finite distances from the head within the field of view (FOV). CDRFs were then fitted by independent Gaussian functions. Thereafter, linear interpolations were applied to the standard deviation (σ) values of the fitted Gaussians, yielding a continuous map of CDRF at varying distances from the head. A rotation-based maximum-likelihood expectation maximization (MLEM) method was used for reconstruction. A fast rotation algorithm was developed to rotate the image matrix according to the desired angle by means of pre-generated rotation maps. The experiments demonstrated improved resolution utilizing our resolution-recovery-embedded image reconstruction. While the full-width at half-maximum (FWHM) radial and tangential resolution measurements of the system were over 2 mm in nearly all positions within the FOV without resolution recovery, reaching around 2.5 mm in some locations, they fell below 1.8 mm everywhere within the FOV using the resolution-recovery algorithm. The noise performance of the system was also acceptable; the standard deviation of the average counts per voxel in the reconstructed images was 6.6% and 8.3% without and with resolution recovery, respectively.