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Background: Alt-sex practitioners are a diverse group with diverse unconventional sexual behaviors including consensual non-monogamy (CNM), kink, fetishism, and bondage/discipline dominance/submission, sadomasochism (BDSM). Perhaps because of their openness to non-normative sexuality, these communities often comprise a large proportion of lesbian, gay, bisexual, trans, queer, among others (LGBTQ+) individuals. LGBTQ+ individuals experience higher rates of sexual violence and consent violation than their cisgender, heterosexual peers both inside and outside of formalized alt-sex communities. Pleasure, including but not limited to sexual pleasure, is often a motivator for engaging in sexual and alt-sex activities. This study examines how consent violations influence pleasure among LGBTQ+ alt-sex members. Methods: We conducted an electronic one-time survey of LGBTQ+ alt-sex practitioners (N = 1354). In this study, we analyze open-ended responses for ways pleasure was described in response to questions about consent violations. We use thematic analyses in Dedoose online software. Results: Two subthemes emerged related to the violation itself, (a) pleasure as a motivator for violating consent and (b) pleasure in spite of consent violation. As the second theme that emerged, pleasure was a component of the aftereffects of the violation in two ways: (1) pleasure was reduced or inhibited by consent violations; (2) pleasure was a motivator for healing and advocacy. Conclusions: We discuss practical and research implications based on the complex relationships between violations and pleasure reported by participants.

In many communities, regions, or landscapes, there are numerous environmental groups working across different sectors and creating stewardship networks that shape the environment and the benefits people derive from it. The make-up of these networks can vary, but generally include organizations of different sizes and capacities. As the Covid-19 pandemic (2020 to the present) shuts down businesses and nonprofits, catalyzes new initiatives, and generally alters the day-to-day professional and personal lives, it is logical to assume that these stewardship networks and their environmental work are impacted; exactly how, is unknown. In this study, we analyze the self-reported effects of the Covid-19 pandemic on stewardship groups working in southeast New England, USA. Stewardship organizations were surveyed from November 2020 to April 2021 and asked, among other questions, “How is Covid-19 affecting your organization?” We analyzed responses using several qualitative coding approaches. Our analysis revealed group-level impacts including changes in group capacity, challenges in managing access to public green spaces, and altered forms of volunteer engagement. These results provide insights into the varied effects of the Covid-19 pandemic and government responses such as stay-at-home orders and social distancing policies on stewardship that can inform the development of programs to reduce negative outcomes and enhance emerging capacities and innovations.

BackgroundTo determine whether adjunctive dronabinol, a licensed form of delta-9-tetrahydrocannabinol, reduces opioid consumption when used off-label for managing acute pain following traumatic injury.MethodsThis matched cohort study included patients who were admitted with a traumatic injury between 1 March 2017 and 30 October 2017. The hospital pharmacy database was used to identify patients who received dronabinol (cases), and they were matched 1:1 to patients who did not receive dronabinol (controls) using age, cause of injury and hospital length of stay. The primary outcome, change in opioid consumption, was calculated using morphine milligram equivalents (MME). The change in MME was calculated for cases as total MME over 48 hours with adjunctive dronabinol minus 48 hours prior to dronabinol, and for controls as total MME 48–96 hours from admission minus 0–48 hours from admission. Data are presented as mean and SE or median and IQR. Statistical analysis was performed using paired t-tests and McNemar’s tests.ResultsThere were 66 patients included: 33 cases and 33 matched controls. Dronabinol was initiated 55 (28–107) hours from admission. Cases and controls were well matched. Cases had a significant reduction in opioid consumption with adjunctive dronabinol (−79 (20) MME, p

Background: Static [ 18 F]FDG-PET/CT is the imaging method of choice for the evaluation of indeterminate lung lesions and NSCLC staging; however, histological confirmation of PET-positive lesions is needed in most cases due to its limited specificity. Therefore, we aimed to evaluate the diagnostic performance of additional dynamic whole-body PET., Methods: A total of 34 consecutive patients with indeterminate pulmonary lesions were enrolled in this prospective trial. All patients underwent static (60 min p.i.) and dynamic (0-60 min p.i.) whole-body [ 18 F]FDG-PET/CT (300 MBq) using the multi-bed-multi-timepoint technique (Siemens mCT FlowMotion). Histology and follow-up served as ground truth. Kinetic modeling factors were calculated using a two-compartment linear Patlak model (FDG influx rate constant = Ki, metabolic rate = MR-FDG, distribution volume = DV-FDG) and compared to SUV using ROC analysis., Results: MR-FDG mean provided the best discriminatory power between benign and malignant lung lesions with an AUC of 0.887. The AUC of DV-FDG mean (0.818) and SUV mean (0.827) was non-significantly lower. For LNM, the AUCs for MR-FDG mean (0.987) and SUV mean (0.993) were comparable. Moreover, the DV-FDG mean in liver metastases was three times higher than in bone or lung metastases., Conclusions: Metabolic rate quantification was shown to be a reliable method to detect malignant lung tumors, LNM, and distant metastases at least as accurately as the established SUV or dual-time-point PET scans.

Whole-body dynamic FDG-PET imaging through continuous-bed-motion (CBM) mode multi-pass acquisition protocol is a promising metabolism measurement. However, inter-pass misalignment originating from body movement could degrade parametric quantification. We aim to apply a non-rigid registration method for inter-pass motion correction in whole-body dynamic PET. 27 subjects underwent a 90-min whole-body FDG CBM PET scan on a Biograph mCT (Siemens Healthineers), acquiring 9 over-the-heart single-bed passes and subsequently 19 CBM passes (frames). The inter-pass motion correction was executed using non-rigid image registration with multi-resolution, B-spline free-form deformations. The parametric images were then generated by Patlak analysis. The overlaid Patlak slope K i and y-intercept V b images were visualized to qualitatively evaluate motion impact and correction effect. The normalized weighted mean squared Patlak fitting errors (NFE) were compared in the whole body, head, and hypermetabolic regions of interest (ROI). In K i images, ROI statistics were collected and malignancy discrimination capacity was estimated by the area under the receiver operating characteristic curve (AUC). After the inter-pass motion correction was applied, the spatial misalignment appearance between K i and V b images was successfully reduced. Voxel-wise normalized fitting error maps showed global error reduction after motion correction. The NFE in the whole body (p = 0.0013), head (p = 0.0021), and ROIs (p = 0.0377) significantly decreased. The visual performance of each hypermetabolic ROI in K i images was enhanced, while 3.59% and 3.67% average absolute percentage changes were observed in mean and maximum K i values, respectively, across all evaluated ROIs. The estimated mean K i values had substantial changes with motion correction (p = 0.0021). The AUC of both mean K i and maximum K i after motion correction increased, possibly suggesting the potential of enhancing oncological discrimination capacity through inter-pass motion correction., Competing Interests: David Pigg and Michael E. Casey are employees of Siemens Medical Solutions USA, Inc. No other potential conflicts of interest relevant to this article exist.

Background: Accurate kinetic modeling of 18F-fluorodeoxyglucose ([ 18 F]-FDG) positron emission tomography (PET) data requires accurate knowledge of the available tracer concentration in the plasma during the scan time, known as the arterial input function (AIF). The gold standard method to derive the AIF requires collection of serial arterial blood samples, but the introduction of long axial field of view (LAFOV) PET systems enables the use of non-invasive image-derived input functions (IDIFs) from large blood pools such as the aorta without any need for bed movement. However, such protocols require a prolonged dynamic PET acquisition, which is impractical in a busy clinical setting. Population-based input functions (PBIFs) have previously shown potential in accurate Patlak analysis of [ 18 F]-FDG datasets and can enable the use of shortened dynamic imaging protocols. Here, we exploit the high sensitivity and temporal resolution of a LAFOV PET system and explore the use of PBIF with abbreviated protocols in [ 18 F]-FDG total body kinetic modeling., Methods: Dynamic PET data were acquired in 24 oncological subjects for 65 min following the administration of [ 18 F]-FDG. IDIFs were extracted from the descending thoracic aorta, and a PBIF was generated from 16 datasets. Five different scaled PBIFs (sPBIFs) were generated by scaling the PBIF with the AUC of IDIF curve tails using various portions of image data (35-65, 40-65, 45-65, 50-65, and 55-65 min post-injection). The sPBIFs were compared with the IDIFs using the AUCs and Patlak K i estimates in tumor lesions and cerebral gray matter. Patlak plot start time (t*) was also varied to evaluate the performance of shorter acquisitions on the accuracy of Patlak K i estimates. Patlak K i estimates with IDIF and t* = 35 min were used as reference, and mean bias and precision (standard deviation of bias) were calculated to assess the relative performance of different sPBIFs. A comparison of parametric images generated using IDIF and sPBIFs was also performed., Results: There was no statistically significant difference between AUCs of the IDIF and sPBIFs (Wilcoxon test: P > 0.05). Excellent agreement was shown between Patlak K i estimates obtained using sPBIF and IDIF. Using the sPBIF 55-65 with the Patlak model, 20 min of PET data (i.e., 45 to 65 min post-injection) achieved < 15% precision error in K i estimates in tumor lesions compared to the estimates with the IDIF. Parametric images reconstructed using the IDIF and sPBIFs with and without an abbreviated protocol were visually comparable. Using Patlak K i generated with an IDIF and 30 min of PET data as reference, Patlak K i images generated using sPBIF 55-65 with 20 min of PET data (t* = 45 min) provided excellent image quality with structural similarity index measure > 0.99 and peak signal-to-noise ratio > 55 dB., Conclusion: We demonstrate the feasibility of performing accurate [ 18 F]-FDG Patlak analysis using sPBIFs with only 20 min of PET data from a LAFOV PET scanner., (© 2022. The Author(s).)

Subject motion in whole-body dynamic PET introduces inter-frame mismatch and seriously impacts parametric imaging. Traditional non-rigid registration methods are generally computationally intense and time-consuming. Deep learning approaches are promising in achieving high accuracy with fast speed, but have yet been investigated with consideration for tracer distribution changes or in the whole-body scope. In this work, we developed an unsupervised automatic deep learning-based framework to correct inter-frame body motion. The motion estimation network is a convolutional neural network with a combined convolutional long short-term memory layer, fully utilizing dynamic temporal features and spatial information. Our dataset contains 27 subjects each under a 90-min FDG whole-body dynamic PET scan. Evaluating performance in motion simulation studies and a 9-fold cross-validation on the human subject dataset, compared with both traditional and deep learning baselines, we demonstrated that the proposed network achieved the lowest motion prediction error, obtained superior performance in enhanced qualitative and quantitative spatial alignment between parametric K i and V b images, and significantly reduced parametric fitting error. We also showed the potential of the proposed motion correction method for impacting downstream analysis of the estimated parametric images, improving the ability to distinguish malignant from benign hypermetabolic regions of interest. Once trained, the motion estimation inference time of our proposed network was around 460 times faster than the conventional registration baseline, showing its potential to be easily applied in clinical settings., Competing Interests: Declaration of Competing Interest David Pigg, Bruce Spottiswoode and Michael E. Casey are employees of Siemens Medical Solutions USA, Inc. No other potential conflicts of interest relevant to this article exist., (Copyright © 2022. Published by Elsevier B.V.)

The latest digital whole-body PET scanners provide a combination of higher sensitivity and improved spatial and timing resolution. We performed a lesion detectability study on two generations of Biograph PET/CT scanners, the mCT Flow and the Vision, to study the impact of improved physical performance on clinical performance. Our hypothesis was that the improved performance of the Vision would result in improved lesion detectability, allowing shorter imaging times or, equivalently, a lower injected dose. Methods: Data were acquired with the Society of Nuclear Medicine and Molecular Imaging Clinical Trials Network torso phantom combined with a 20-cm-diameter cylindrical phantom. Spherical lesions were emulated by acquiring sphere-in-air data and combining them with the phantom data to generate combined datasets with embedded lesions of known contrast. Two sphere sizes and uptakes were used: 9.89-mm-diameter spheres with 6:1 (lung) and 3:1 (cylinder) local activity concentration uptakes and 4.95-mm-diameter spheres with 9.6:1 (lung) and 4.5:1 (cylinder) local activity concentration uptakes. Standard image reconstruction was performed: an ordinary Poisson ordered-subsets expectation maximization algorithm with point-spread function and time-of-flight modeling and postreconstruction smoothing with a 5-mm gaussian filter. The Vision images were also generated without any postreconstruction smoothing. Generalized scan statistics methodology was used to estimate the area under the localized receiver-operating-characteristic curve (ALROC). Results: The higher sensitivity and improved time-of-flight performance of the Vision leads to reduced contrast in the background noise nodule distribution. Measured lesion contrast is also higher on the Vision because of its improved spatial resolution. Hence, the ALROC is noticeably higher for the Vision than for the mCT Flow. Conclusion: Improved overall performance of the Vision provides a factor of 4-6 reduction in imaging time (or injected dose) over the mCT Flow when using the ALROC metric for lesions at least 9.89 mm in diameter. Smaller lesions are barely detected in the mCT Flow, leading to even higher ALROC gains with the Vision. The improved spatial resolution of the Vision also leads to a higher measured contrast that is closer to the real uptake, implying improved quantification. Postreconstruction smoothing, however, reduces this improvement in measured contrast, thereby reducing the ALROC for small, high-uptake lesions., (© 2020 by the Society of Nuclear Medicine and Molecular Imaging.)

PET has the potential to perform absolute in vivo radiotracer quantitation. This potential can be compromised by voluntary body motion (BM), which degrades image resolution, alters apparent tracer uptakes, introduces CT-based attenuation correction mismatch artifacts and causes inaccurate parameter estimates in dynamic studies. Existing body motion correction (BMC) methods include frame-based image-registration (FIR) approaches and real-time motion tracking using external measurement devices. FIR does not correct for motion occurring within a pre-defined frame and the device-based method is generally not practical in routine clinical use, since it requires attaching a tracking device to the patient and additional device set up time. In this paper, we proposed a data-driven algorithm, centroid of distribution (COD), to detect BM. In this algorithm, the central coordinate of the time-of-flight (TOF) bin, which can be used as a reasonable surrogate for the annihilation point, is calculated for every event, and averaged over a certain time interval to generate a COD trace. We hypothesized that abrupt changes on the COD trace in lateral direction represent BMs. After detection, BM is estimated using non-rigid image registrations and corrected through list-mode reconstruction. The COD-based BMC approach was validated using a monkey study and was evaluated against FIR using four human and one dog studies with multiple tracers. The proposed approach successfully detected BMs and yielded superior correction results over conventional FIR approaches.

Purpose: In this article, we discuss dynamic whole-body (DWB) positron emission tomography (PET) as an imaging tool with significant clinical potential, in relation to conventional standard uptake value (SUV) imaging., Background: DWB PET involves dynamic data acquisition over an extended axial range, capturing tracer kinetic information that is not available with conventional static acquisition protocols. The method can be performed within reasonable clinical imaging times, and enables generation of multiple types of PET images with complementary information in a single imaging session. Importantly, DWB PET can be used to produce multi-parametric images of (i) Patlak slope (influx rate) and (ii) intercept (referred to sometimes as "distribution volume"), while also providing (iii) a conventional 'SUV-equivalent' image for certain protocols., Results: We provide an overview of ongoing efforts (primarily focused on FDG PET) and discuss potential clinically relevant applications., Conclusion: Overall, the framework of DWB imaging [applicable to both PET/CT(computed tomography) and PET/MRI (magnetic resonance imaging)] generates quantitative measures that may add significant value to conventional SUV image-derived measures, with limited pitfalls as we also discuss in this work.

Background: The effect of time-of-flight (TOF) and point spread function (PSF) modeling in image reconstruction has not been well studied for cardiac PET. This study assesses their separate and combined influence on 82 Rb myocardial perfusion imaging in obese patients., Methods: Thirty-six obese patients underwent rest-stress 82 Rb cardiac PET. Images were reconstructed with and without TOF and PSF modeling. Perfusion was quantitatively compared using the AHA 17-segment model for patients grouped by BMI, cross-sectional body area in the scanner field of view, gender, and left ventricular myocardial volume. Summed rest scores (SRS), summed stress scores (SSS), and summed difference scores (SDS) were compared., Results: TOF improved polar map visual uniformity and increased septal wall perfusion by up to 10%. This increase was greater for larger patients, more evident for patients grouped by cross-sectional area than by BMI, and more prominent for females. PSF modeling increased perfusion by about 1.5% in all cardiac segments. TOF modeling generally decreased SRS and SSS with significant decreases between 2.4 and 3.0 (P < .05), which could affect risk stratification; SDS remained about the same. With PSF modeling, SRS, SSS, and SDS were largely unchanged., Conclusion: TOF and PSF modeling affect regional and global perfusion, SRS, and SSS. Clinicians should consider these effects and gender-dependent differences when interpreting 82 Rb perfusion studies.

Respiratory motion degrades the detection and quantification capabilities of PET/CT imaging. Moreover, mismatch between a fast helical CT image and a time-averaged PET image due to respiratory motion results in additional attenuation correction artifacts and inaccurate localization. Current motion compensation approaches typically have 3 limitations: the mismatch among respiration-gated PET images and the CT attenuation correction (CTAC) map can introduce artifacts in the gated PET reconstructions that can subsequently affect the accuracy of the motion estimation; sinogram-based correction approaches do not correct for intragate motion due to intracycle and intercycle breathing variations; and the mismatch between the PET motion compensation reference gate and the CT image can cause an additional CT-mismatch artifact. In this study, we established a motion correction framework to address these limitations. Methods: In the proposed framework, the combined emission-transmission reconstruction algorithm was used for phase-matched gated PET reconstructions to facilitate the motion model building. An event-by-event nonrigid respiratory motion compensation method with correlations between internal organ motion and external respiratory signals was used to correct both intracycle and intercycle breathing variations. The PET reference gate was automatically determined by a newly proposed CT-matching algorithm. We applied the new framework to 13 human datasets with 3 different radiotracers and 323 lesions and compared its performance with CTAC and non-attenuation correction (NAC) approaches. Validation using 4-dimensional CT was performed for one lung cancer dataset. Results: For the 10 18 F-FDG studies, the proposed method outperformed ( P < 0.006) both the CTAC and the NAC methods in terms of region-of-interest-based SUV mean , SUV max , and SUV ratio improvements over no motion correction (SUV mean : 19.9% vs. 14.0% vs. 13.2%; SUV max : 15.5% vs. 10.8% vs. 10.6%; SUV ratio: 24.1% vs. 17.6% vs. 16.2%, for the proposed, CTAC, and NAC methods, respectively). The proposed method increased SUV ratios over no motion correction for 94.4% of lesions, compared with 84.8% and 86.4% using the CTAC and NAC methods, respectively. For the 2 18 F-fluoropropyl-(+)-dihydrotetrabenazine studies, the proposed method reduced the CT-mismatch artifacts in the lower lung where the CTAC approach failed and maintained the quantification accuracy of bone marrow where the NAC approach failed. For the 18 F-FMISO study, the proposed method outperformed both the CTAC and the NAC methods in terms of motion estimation accuracy at 2 lung lesion locations. Conclusion: The proposed PET/CT respiratory event-by-event motion-correction framework with motion information derived from matched attenuation-corrected PET data provides image quality superior to that of the CTAC and NAC methods for multiple tracers., (© 2018 by the Society of Nuclear Medicine and Molecular Imaging.)

We describe a long axial field-of-view (FOV) PET scanner for high-sensitivity and total-body imaging of nonhuman primates and present the physical performance and first phantom and animal imaging results. Methods: The mini-EXPLORER PET scanner was built using the components of a clinical scanner reconfigured with a detector ring diameter of 43.5 cm and an axial length of 45.7 cm. National Electrical Manufacturers Association (NEMA) NU-2 and NU-4 phantoms were used to measure sensitivity and count rate performance. Reconstructed spatial resolution was investigated by imaging a radially stepped point source and a Derenzo phantom. The effect of the wide acceptance angle was investigated by comparing performance with maximum acceptance angles of 14°-46°. Lastly, an initial assessment of the in vivo performance of the mini-EXPLORER was undertaken with a dynamic 18 F-FDG nonhuman primate (rhesus monkey) imaging study. Results: The NU-2 total sensitivity was 5.0%, and the peak noise-equivalent count rate measured with the NU-4 monkey scatter phantom was 1,741 kcps, both obtained using the maximum acceptance angle (46°). The NU-4 scatter fraction was 16.5%, less than 1% higher than with a 14° acceptance angle. The reconstructed spatial resolution was approximately 3.0 mm at the center of the FOV, with a minor loss in axial spatial resolution (0.5 mm) when the acceptance angle increased from 14° to 46°. The rhesus monkey 18 F-FDG study demonstrated the benefit of the high sensitivity of the mini-EXPLORER, including fast imaging (1-s early frames), excellent image quality (30-s and 5-min frames), and late-time-point imaging (18 h after injection), all obtained at a single bed position that captured the major organs of the rhesus monkey. Conclusion: This study demonstrated the physical performance and imaging capabilities of a long axial FOV PET scanner designed for high-sensitivity imaging of nonhuman primates. Further, the results of this study suggest that a wide acceptance angle can be used with a long axial FOV scanner to maximize sensitivity while introducing only minor trade-offs such as a small increase in scatter fraction and slightly degraded axial spatial resolution., (© 2018 by the Society of Nuclear Medicine and Molecular Imaging.)

Point-spread function (PSF) modeling offers the ability to account for resolution degrading phenomena within the PET image generation framework. PSF modeling improves resolution and enhances contrast, but at the same time significantly alters image noise properties and induces edge overshoot effect. Thus, studying the effect of PSF modeling on quantitation task performance can be very important. Frameworks explored in the past involved a dichotomy of PSF versus no-PSF modeling. By contrast, the present work focuses on quantitative performance evaluation of standard uptake value (SUV) PET images, while incorporating a wide spectrum of PSF models, including those that under- and over-estimate the true PSF, for the potential of enhanced quantitation of SUVs. The developed framework first analytically models the true PSF, considering a range of resolution degradation phenomena (including photon non-collinearity, inter-crystal penetration and scattering) as present in data acquisitions with modern commercial PET systems. In the context of oncologic liver FDG PET imaging, we generated 200 noisy datasets per image-set (with clinically realistic noise levels) using an XCAT anthropomorphic phantom with liver tumours of varying sizes. These were subsequently reconstructed using the OS-EM algorithm with varying PSF modelled kernels. We focused on quantitation of both SUV mean and SUV max , including assessment of contrast recovery coefficients, as well as noise-bias characteristics (including both image roughness and coefficient of-variability), for different tumours/iterations/PSF kernels. It was observed that overestimated PSF yielded more accurate contrast recovery for a range of tumours, and typically improved quantitative performance. For a clinically reasonable number of iterations, edge enhancement due to PSF modeling (especially due to over-estimated PSF) was in fact seen to lower SUV mean bias in small tumours. Overall, the results indicate that exactly matched PSF modeling does not offer optimized PET quantitation, and that PSF overestimation may provide enhanced SUV quantitation. Furthermore, generalized PSF modeling may provide a valuable approach for quantitative tasks such as treatment-response assessment and prognostication.

Calculating attenuation correction for brain PET imaging rather than using CT presents opportunities for low radiation dose applications such as pediatric imaging and serial scans to monitor disease progression. Our goal is to evaluate the iterative time-of-flight based maximum-likelihood activity and attenuation correction factors estimation (MLACF) method for clinical FDG brain PET imaging. FDG PET/CT brain studies were performed in 57 patients using the Biograph mCT (Siemens) four-ring scanner. The time-of-flight PET sinograms were acquired using the standard clinical protocol consisting of a CT scan followed by 10 min of single-bed PET acquisition. Images were reconstructed using CT-based attenuation correction (CTAC) and used as a gold standard for comparison. Two methods were compared with respect to CTAC: a calculated brain attenuation correction (CBAC) and MLACF based PET reconstruction. Plane-by-plane scaling was performed for MLACF images in order to fix the variable axial scaling observed. The noise structure of the MLACF images was different compared to those obtained using CTAC and the reconstruction required a higher number of iterations to obtain comparable image quality. To analyze the pooled data, each dataset was registered to a standard template and standard regions of interest were extracted. An SUVr analysis of the brain regions of interest showed that CBAC and MLACF were each well correlated with CTAC SUVrs. A plane-by-plane error analysis indicated that there were local differences for both CBAC and MLACF images with respect to CTAC. Mean relative error in the standard regions of interest was less than 5% for both methods and the mean absolute relative errors for both methods were similar (3.4%  ±  3.1% for CBAC and 3.5%  ±  3.1% for MLACF). However, the MLACF method recovered activity adjoining the frontal sinus regions more accurately than CBAC method. The use of plane-by-plane scaling of MLACF images was found to be a crucial step in order to obtain improved activity estimates. Presence of local errors in both MLACF and CBAC based reconstructions would require the use of a normal database for clinical assessment. However, further work is required in order to assess the clinical advantage of MLACF over CBAC based method.

Aim: To accurately quantify the radioactivity concentration measured by PET, emission data need to be corrected for photon attenuation; however, the MRI signal cannot easily be converted into attenuation values, making attenuation correction (AC) in PET/MRI challenging. In order to further improve the current vendor-implemented MR-AC methods for absolute quantification, a number of prototype methods have been proposed in the literature. These can be categorized into three types: template/atlas-based, segmentation-based, and reconstruction-based. These proposed methods in general demonstrated improvements compared to vendor-implemented AC, and many studies report deviations in PET uptake after AC of only a few percent from a gold standard CT-AC. Using a unified quantitative evaluation with identical metrics, subject cohort, and common CT-based reference, the aims of this study were to evaluate a selection of novel methods proposed in the literature, and identify the ones suitable for clinical use., Methods: In total, 11 AC methods were evaluated: two vendor-implemented (MR-AC DIXON and MR-AC UTE ), five based on template/atlas information (MR-AC SEGBONE (Koesters et al., 2016), MR-AC ONTARIO (Anazodo et al., 2014), MR-AC BOSTON (Izquierdo-Garcia et al., 2014), MR-AC UCL (Burgos et al., 2014), and MR-AC MAXPROB (Merida et al., 2015)), one based on simultaneous reconstruction of attenuation and emission (MR-AC MLAA (Benoit et al., 2015)), and three based on image-segmentation (MR-AC MUNICH (Cabello et al., 2015), MR-AC CAR-RiDR (Juttukonda et al., 2015), and MR-AC RESOLUTE (Ladefoged et al., 2015)). We selected 359 subjects who were scanned using one of the following radiotracers: [ 18 F]FDG (210), [ 11 C]PiB (51), and [ 18 F]florbetapir (98). The comparison to AC with a gold standard CT was performed both globally and regionally, with a special focus on robustness and outlier analysis., Results: The average performance in PET tracer uptake was within ±5% of CT for all of the proposed methods, with the average±SD global percentage bias in PET FDG uptake for each method being: MR-AC DIXON (-11.3±3.5)%, MR-AC UTE (-5.7±2.0)%, MR-AC ONTARIO (-4.3±3.6)%, MR-AC MUNICH (3.7±2.1)%, MR-AC MLAA (-1.9±2.6)%, MR-AC SEGBONE (-1.7±3.6)%, MR-AC UCL (0.8±1.2)%, MR-AC CAR-RiDR (-0.4±1.9)%, MR-AC MAXPROB (-0.4±1.6)%, MR-AC BOSTON (-0.3±1.8)%, and MR-AC RESOLUTE (0.3±1.7)%, ordered by average bias. The overall best performing methods (MR-AC BOSTON , MR-AC MAXPROB , MR-AC RESOLUTE and MR-AC UCL , ordered alphabetically) showed regional average errors within ±3% of PET with CT-AC in all regions of the brain with FDG, and the same four methods, as well as MR-AC CAR-RiDR , showed that for 95% of the patients, 95% of brain voxels had an uptake that deviated by less than 15% from the reference. Comparable performance was obtained with PiB and florbetapir., Conclusions: All of the proposed novel methods have an average global performance within likely acceptable limits (±5% of CT-based reference), and the main difference among the methods was found in the robustness, outlier analysis, and clinical feasibility. Overall, the best performing methods were MR-ACBOSTON, MR-ACMAXPROB, MR-ACRESOLUTE and MR-ACUCL, ordered alphabetically. These methods all minimized the number of outliers, standard deviation, and average global and local error. The methods MR-ACMUNICH and MR-ACCAR-RiDR were both within acceptable quantitative limits, so these methods should be considered if processing time is a factor. The method MR-ACSEGBONE also demonstrates promising results, and performs well within the likely acceptable quantitative limits. For clinical routine scans where processing time can be a key factor, this vendor-provided solution currently outperforms most methods. With the performance of the methods presented here, it may be concluded that the challenge of improving the accuracy of MR-AC in adult brains with normal anatomy has been solved to a quantitatively acceptable degree, which is smaller than the quantification reproducibility in PET imaging., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: Distribution of PET tracer uptake is elaborately modeled via a general equation used for solute transport modeling. This model can be used to incorporate various transport parameters of a solid tumor such as hydraulic conductivity of the microvessel wall, transvascular permeability as well as interstitial space parameters. This is especially significant because tracer delivery and drug delivery to solid tumors are determined by similar underlying tumor transport phenomena, and quantifying the former can enable enhanced prediction of the latter., Methods: We focused on the commonly utilized FDG PET tracer. First, based on a mathematical model of angiogenesis, the capillary network of a solid tumor and normal tissues around it were generated. The coupling mathematical method, which simultaneously solves for blood flow in the capillary network as well as fluid flow in the interstitium, is used to calculate pressure and velocity distributions. Subsequently, a comprehensive spatiotemporal distribution model (SDM) is applied to accurately model distribution of PET tracer uptake, specifically FDG in this work, within solid tumors., Results: The different transport mechanisms, namely convention and diffusion from vessel to tissue and in tissue, are elaborately calculated across the domain of interest and effect of each parameter on tracer distribution is investigated. The results show the convection terms to have negligible effect on tracer transport and the SDM can be solved after eliminating these terms., Conclusion: The proposed framework of spatiotemporal modeling for PET tracers can be utilized to comprehensively assess the impact of various parameters on the spatiotemporal distribution of PET tracers.

Whole-body (WB) dynamic PET has recently demonstrated its potential in translating the quantitative benefits of parametric imaging to the clinic. Post-reconstruction standard Patlak (sPatlak) WB graphical analysis utilizes multi-bed multi-pass PET acquisition to produce quantitative WB images of the tracer influx rate K i as a complimentary metric to the semi-quantitative standardized uptake value (SUV). The resulting K i images may suffer from high noise due to the need for short acquisition frames. Meanwhile, a generalized Patlak (gPatlak) WB post-reconstruction method had been suggested to limit K i bias of sPatlak analysis at regions with non-negligible (18)F-FDG uptake reversibility; however, gPatlak analysis is non-linear and thus can further amplify noise. In the present study, we implemented, within the open-source software for tomographic image reconstruction platform, a clinically adoptable 4D WB reconstruction framework enabling efficient estimation of sPatlak and gPatlak images directly from dynamic multi-bed PET raw data with substantial noise reduction. Furthermore, we employed the optimization transfer methodology to accelerate 4D expectation-maximization (EM) convergence by nesting the fast image-based estimation of Patlak parameters within each iteration cycle of the slower projection-based estimation of dynamic PET images. The novel gPatlak 4D method was initialized from an optimized set of sPatlak ML-EM iterations to facilitate EM convergence. Initially, realistic simulations were conducted utilizing published (18)F-FDG kinetic parameters coupled with the XCAT phantom. Quantitative analyses illustrated enhanced K i target-to-background ratio (TBR) and especially contrast-to-noise ratio (CNR) performance for the 4D versus the indirect methods and static SUV. Furthermore, considerable convergence acceleration was observed for the nested algorithms involving 10-20 sub-iterations. Moreover, systematic reduction in K i % bias and improved TBR were observed for gPatlak versus sPatlak. Finally, validation on clinical WB dynamic data demonstrated the clinical feasibility and superior K i CNR performance for the proposed 4D framework compared to indirect Patlak and SUV imaging.

Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image or the attenuation sinogram from time-of-flight (TOF) positron emission tomography (PET) data. In this contribution, we propose a method that addresses the possible alignment problem of the TOF-PET emission data and the computed tomography (CT) attenuation data, by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the pair of activity and attenuation images maximise the likelihood of the TOF emission sinogram. The algorithm is slow to converge, but some acceleration could be achieved by using Nesterov's momentum method and by applying a multi-resolution scheme for the non-rigid displacement estimation. The latter also helps to avoid local optima, although convergence to the global optimum cannot be guaranteed. The results are evaluated on 2D and 3D simulations as well as a respiratory gated clinical scan. Our experiments indicate that the proposed method is able to correct for possible misalignment of the CT-based attenuation image, and is therefore a very promising approach to suppressing attenuation artefacts in clinical PET/CT. When applied to respiratory gated data of a patient scan, it produced deformations that are compatible with breathing motion and which reduced the well known attenuation artefact near the dome of the liver. Since the method makes use of the energy-converted CT attenuation image, the scale problem of joint reconstruction is automatically solved.

We recently developed a dynamic multi-bed PET data acquisition framework to translate the quantitative benefits of Patlak voxel-wise analysis to the domain of routine clinical whole-body (WB) imaging. The standard Patlak (sPatlak) linear graphical analysis assumes irreversible PET tracer uptake, ignoring the effect of FDG dephosphorylation, which has been suggested by a number of PET studies. In this work: (i) a non-linear generalized Patlak (gPatlak) model is utilized, including a net efflux rate constant kloss, and (ii) a hybrid (s/g)Patlak (hPatlak) imaging technique is introduced to enhance contrast to noise ratios (CNRs) of uptake rate Ki images. Representative set of kinetic parameter values and the XCAT phantom were employed to generate realistic 4D simulation PET data, and the proposed methods were additionally evaluated on 11 WB dynamic PET patient studies. Quantitative analysis on the simulated Ki images over 2 groups of regions-of-interest (ROIs), with low (ROI A) or high (ROI B) true kloss relative to Ki, suggested superior accuracy for gPatlak. Bias of sPatlak was found to be 16-18% and 20-40% poorer than gPatlak for ROIs A and B, respectively. By contrast, gPatlak exhibited, on average, 10% higher noise than sPatlak. Meanwhile, the bias and noise levels for hPatlak always ranged between the other two methods. In general, hPatlak was seen to outperform all methods in terms of target-to-background ratio (TBR) and CNR for all ROIs. Validation on patient datasets demonstrated clinical feasibility for all Patlak methods, while TBR and CNR evaluations confirmed our simulation findings, and suggested presence of non-negligible kloss reversibility in clinical data. As such, we recommend gPatlak for highly quantitative imaging tasks, while, for tasks emphasizing lesion detectability (e.g. TBR, CNR) over quantification, or for high levels of noise, hPatlak is instead preferred. Finally, gPatlak and hPatlak CNR was systematically higher compared to routine SUV values.

Human mesenchymal stem cells (hMSCs) are an attractive cell source for tissue regeneration, given their self-renewal and multilineage potential. However, they are present in only small percentages in human bone marrow, and are generally propagated in vitro prior to downstream use. Previous work has shown that hMSC propagation can lead to alterations in cell behavior and differentiation potency, yet optimization of differentiation based on starting cell elastic modulus is an area still under investigation. To further advance the knowledge in this field, hMSCs were cultured and routinely passaged on tissue-culture polystyrene to investigate the correlation between cell stiffening and differentiation potency during in vitro aging. Local cell elastic modulus was measured at every passage using atomic force microscopy indentation. At each passage, cells were induced to differentiate down myogenic and osteogenic paths. Cells induced to differentiate, as well as undifferentiated cells were assessed for gene and protein expression using quantitative polymerase chain reaction and immunofluorescent staining, respectively, for osteogenic and myogenic markers. Myogenic and osteogenic cell potential are highly reliant on the elastic modulus of the starting cell population (of undifferentiated cells), and this potential appears to peak when the innate cell elastic modulus is close to that of differentiated tissue. However, the latent expression of the same markers in undifferentiated cells also appears to undergo a correlative relationship with cell elastic modulus, indicating some endogenous effects of cell elastic modulus and gene/protein expression. Overall, this study correlates age-related changes with regards to innate cell stiffening and gene/protein expression in commercial hMSCs, providing some guidance as to maintenance and future use of hMSCs in future tissue engineering applications., (Copyright © 2015 International Society of Differentiation. Published by Elsevier B.V. All rights reserved.)

Monte Carlo simulation provides a valuable tool in performance assessment and optimization of system design parameters for PET scanners. SimSET is a popular Monte Carlo simulation toolkit that features fast simulation time, as well as variance reduction tools to further enhance computational efficiency. However, SimSET has lacked the ability to simulate block detectors until its most recent release. Our goal is to validate new features of SimSET by developing a simulation model of the Siemens Biograph mCT PET scanner and comparing the results to a simulation model developed in the GATE simulation suite and to experimental results. We used the NEMA NU-2 2007 scatter fraction, count rates, and spatial resolution protocols to validate the SimSET simulation model and its new features. The SimSET model overestimated the experimental results of the count rate tests by 11-23% and the spatial resolution test by 13-28%, which is comparable to previous validation studies of other PET scanners in the literature. The difference between the SimSET and GATE simulation was approximately 4-8% for the count rate test and approximately 3-11% for the spatial resolution test. In terms of computational time, SimSET performed simulations approximately 11 times faster than GATE simulations. The new block detector model in SimSET offers a fast and reasonably accurate simulation toolkit for PET imaging applications.

Johne's disease, caused by infection with Mycobacterium avium subsp. paratuberculosis, (MAP), is a chronic intestinal disease of ruminants with serious economic consequences for cattle production in the United States and elsewhere. During infection, MAP bacilli are phagocytosed and subvert host macrophage processes, resulting in subclinical infections that can lead to immunopathology and dissemination of disease. Analysis of the host macrophage transcriptome during infection can therefore shed light on the molecular mechanisms and host-pathogen interplay associated with Johne's disease. Here, we describe results of an in vitro study of the bovine monocyte-derived macrophage (MDM) transcriptome response during MAP infection using RNA-seq. MDM were obtained from seven age- and sex-matched Holstein-Friesian cattle and were infected with MAP across a 6-h infection time course with non-infected controls. We observed 245 and 574 differentially expressed (DE) genes in MAP-infected versus non-infected control samples (adjusted P value ≤0.05) at 2 and 6 h post-infection, respectively. Functional analyses of these DE genes, including biological pathway enrichment, highlighted potential functional roles for genes that have not been previously described in the host response to infection with MAP bacilli. In addition, differential expression of pro- and anti-inflammatory cytokine genes, such as those associated with the IL-10 signaling pathway, and other immune-related genes that encode proteins involved in the bovine macrophage response to MAP infection emphasize the balance between protective host immunity and bacilli survival and proliferation. Systematic comparisons of RNA-seq gene expression results with Affymetrix(®) microarray data generated from the same experimental samples also demonstrated that RNA-seq represents a superior technology for studying host transcriptional responses to intracellular infection.

Unlabelled: Integrated whole-body PET/MR facilitates the implementation of a broad variety of respiratory motion correction strategies, taking advantage of the strengths of both modalities. The goal of this study was the quantitative evaluation with clinical data of different MR- and PET-data-based motion correction strategies for integrated PET/MR., Methods: The PET and MR data of 20 patients were simultaneously acquired for 10 min on an integrated PET/MR system after administration of (18)F-FDG or (68)Ga-DOTANOC. Respiratory traces recorded with a bellows were compared against MR self-gating signals and signals extracted from PET raw data with the sensitivity method, by applying principal component analysis (PCA) or Laplacian eigenmaps and by using a novel variation combining the former and either of the latter two. Gated sinograms and MR images were generated accordingly, followed by image registration to derive MR motion models. Corrected PET images were reconstructed by incorporating this information into the reconstruction. An optical flow algorithm was applied for PET-based motion correction. Gating and motion correction were evaluated by quantitative analysis of apparent tracer uptake, lesion volume, displacement, contrast, and signal-to-noise ratio., Results: The correlation between bellows- and MR-based signals was 0.63 ± 0.19, and that between MR and the sensitivity method was 0.52 ± 0.26. Depending on the PET raw-data compression, the average correlation between MR and PCA ranged from 0.25 ± 0.30 to 0.58 ± 0.33, and the range was 0.25 ± 0.30 to 0.42 ± 0.34 if Laplacian eigenmaps were applied. By combining the sensitivity method and PCA or Laplacian eigenmaps, the maximum average correlation to MR could be increased to 0.74 ± 0.21 and 0.70 ± 0.19, respectively. The selection of the best PET-based signal for each patient yielded an average correlation of 0.80 ± 0.13 with MR. Using the best PET-based respiratory signal for gating, mean tracer uptake increased by 17 ± 19% for gating, 13 ± 10% for MR-based motion correction, and 18 ± 15% for PET-based motion correction, compared with the static images. Lesion volumes were 76 ± 31%, 83 ± 18%, and 74 ± 22% of the sizes in the static images for gating, MR-based motion correction, and PET-based motion correction, respectively., Conclusion: Respiratory traces extracted from MR and PET data are comparable to those based on external sensors. The proposed PET-driven gating method improved respiratory signals and overall stability. Consistent results from MR- and PET-based correction methods enable more flexible PET/MR scan protocols while achieving higher PET image quality., (© 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.)

With the addition of variable bed speed capabilities, continuous bed motion (CBM) becomes an acquisition generalization for axial sensitivity modeling and therefore a flexible tool in axial local image quality adjustment. In this paper, we describe the principles behind CBM mode planning and its influence on image reconstruction. The data correction method underwent the most changes compared to the commonly used step and shoot (S&S) mode. The CBM normalization array accommodates for activity decay, dead time correction, and the fact that various detector pairs acquire the same data for different durations. The normalization array is computed by simulating the movement of an object through the scanner, assisted by the monitoring of basic scanner acquisition parameters such as the singles rate. The sensitivity, which is the number of counts acquired per image plane, is an intrinsic part of normalization computing. Basic equations to estimate acquisition time at matched sensitivity between single speed CBM and S&S mode are presented. The CBM feature was implemented on a Siemens clinical scanner and initial studies of phantoms and patients are presented. The equivalence of single speed CBM and S&S image quality is demonstrated.

Use of 15O labeled oxygen (15O2) and positron emission tomography (PET) allows quantitative assessment of the regional metabolic rate of oxygen (CMRO2) in vivo, which is essential to understanding the pathological status of patients with cerebral vascular and neurological disorders. The method has, however, been challenging, when a 3D PET scanner is employed, largely attributed to the presence of gaseous radioactivity in the trachea and the inhalation system, which results in a large amount of scatter and random events in the PET assessment. The present study was intended to evaluate the adequacy of using a recently available commercial 3D PET scanner in the assessment of regional cerebral radioactivity distribution during an inhalation of 15O2. Systematic experiments were carried out on a brain phantom. Experiments were also performed on a healthy volunteer following a recently developed protocol for simultaneous assessment of CMRO2 and cerebral blood flow, which involves sequential administration of 15O2 and C15O2. A particular intention was to evaluate the adequacy of the scatter-correction procedures. The phantom experiment demonstrated that errors were within 3% at the practically maximum radioactivity in the face mask, with the greatest radioactivity in the lung. The volunteer experiment demonstrated that the counting rate was at peak during the 15O gas inhalation period, within a verified range. Tomographic images represented good quality over the entire FOV, including the lower part of the cerebral structures and the carotid artery regions. The scatter-correction procedures appeared to be important, particularly in the process to compensate for the scatter originating outside the FOV. Reconstructed images dramatically changed if the correction was carried out using inappropriate procedures. This study demonstrated that accurate reconstruction could be obtained when the scatter compensation was appropriately carried out. This study also suggested the feasibility of using a state-of-the-art 3D PET scanner in the quantitative PET imaging during inhalation of 15O labeled oxygen.

A new data handling method is presented for improving the image noise distribution and reducing bias when reconstructing very short frames from low count dynamic PET acquisition. The new method termed 'Complementary Frame Reconstruction' (CFR) involves the indirect formation of a count-limited emission image in a short frame through subtraction of two frames with longer acquisition time, where the short time frame data is excluded from the second long frame data before the reconstruction. This approach can be regarded as an alternative to the AML algorithm recently proposed by Nuyts et al, as a method to reduce the bias for the maximum likelihood expectation maximization (MLEM) reconstruction of count limited data. CFR uses long scan emission data to stabilize the reconstruction and avoids modification of algorithms such as MLEM. The subtraction between two long frame images, naturally allows negative voxel values and significantly reduces bias introduced in the final image. Simulations based on phantom and clinical data were used to evaluate the accuracy of the reconstructed images to represent the true activity distribution. Applicability to determine the arterial input function in human and small animal studies is also explored. In situations with limited count rate, e.g. pediatric applications, gated abdominal, cardiac studies, etc., or when using limited doses of short-lived isotopes such as 15O-water, the proposed method will likely be preferred over independent frame reconstruction to address bias and noise issues.

Prostate cancer, one of the most common forms of cancer among men, can benefit from recent improvements in positron emission tomography (PET) technology. In particular, better spatial resolution, lower noise and higher detectability of small lesions could be greatly beneficial for early diagnosis and could provide a strong support for guiding biopsy and surgery. In this article, the impact of improved PET instrumentation with superior spatial resolution and high sensitivity are discussed, together with the latest development in PET technology: resolution recovery and time-of-flight reconstruction. Using simulated cancer lesions, inserted in clinical PET images obtained with conventional protocols, we show that visual identification of the lesions and detectability via numerical observers can already be improved using state of the art PET reconstruction methods. This was achieved using both resolution recovery and time-of-flight reconstruction, and a high resolution image with 2 mm pixel size. Channelized Hotelling numerical observers showed an increase in the area under the LROC curve from 0.52 to 0.58. In addition, a relationship between the simulated input activity and the area under the LROC curve showed that the minimum detectable activity was reduced by more than 23%.

Whole-body PET/CT scanners are important clinical and research tools to study tracer distribution throughout the body. In whole-body studies, respiratory motion results in image artifacts. We have previously demonstrated for brain imaging that, when provided with accurate motion data, event-by-event correction has better accuracy than frame-based methods. Therefore, the goal of this work was to develop a list-mode reconstruction with novel physics modeling for the Siemens Biograph mCT with event-by-event motion correction, based on the MOLAR platform (Motion-compensation OSEM List-mode Algorithm for Resolution-Recovery Reconstruction). Application of MOLAR for the mCT required two algorithmic developments. First, in routine studies, the mCT collects list-mode data in 32 bit packets, where averaging of lines-of-response (LORs) by axial span and angular mashing reduced the number of LORs so that 32 bits are sufficient to address all sinogram bins. This degrades spatial resolution. In this work, we proposed a probabilistic LOR (pLOR) position technique that addresses axial and transaxial LOR grouping in 32 bit data. Second, two simplified approaches for 3D time-of-flight (TOF) scatter estimation were developed to accelerate the computationally intensive calculation without compromising accuracy. The proposed list-mode reconstruction algorithm was compared to the manufacturer's point spread function + TOF (PSF+TOF) algorithm. Phantom, animal, and human studies demonstrated that MOLAR with pLOR gives slightly faster contrast recovery than the PSF+TOF algorithm that uses the average 32 bit LOR sinogram positioning. Moving phantom and a whole-body human study suggested that event-by-event motion correction reduces image blurring caused by respiratory motion. We conclude that list-mode reconstruction with pLOR positioning provides a platform to generate high quality images for the mCT, and to recover fine structures in whole-body PET scans through event-by-event motion correction.

The simultaneous PET data reconstruction of emission activity and attenuation coefficient distribution is presented, where the attenuation image is constrained by exploiting an external transmission source. Data are acquired in time-of-flight (TOF) mode, allowing in principle for separation of emission and transmission data. Nevertheless, here all data are reconstructed at once, eliminating the need to trace the position of the transmission source in sinogram space. Contamination of emission data by the transmission source and vice versa is naturally modeled. Attenuated emission activity data also provide additional information about object attenuation coefficient values. The algorithm alternates between attenuation and emission activity image updates. We also proposed a method of estimation of spatial scatter distribution from the transmission source by incorporating knowledge about the expected range of attenuation map values. The reconstruction of experimental data from the Siemens mCT scanner suggests that simultaneous reconstruction improves attenuation map image quality, as compared to when data are separated. In the presented example, the attenuation map image noise was reduced and non-uniformity artifacts that occurred due to scatter estimation were suppressed. On the other hand, the use of transmission data stabilizes attenuation coefficient distribution reconstruction from TOF emission data alone. The example of improving emission images by refining a CT-based patient attenuation map is presented, revealing potential benefits of simultaneous CT and PET data reconstruction.

Lesion-detection performance in oncologic PET depends in part upon count statistics, with shorter scans having higher noise and reduced lesion detectability. However, advanced techniques such as time-of-flight (TOF) and point spread function (PSF) modeling can improve lesion detection. This work investigates the relationship between reducing count levels (as a surrogate for scan time) and reconstructing with PSF model and TOF. A series of twenty-four whole-body phantom scans was acquired on a Biograph mCT TOF PET/CT scanner using the experimental methodology prescribed for the Utah PET Lesion Detection Database. Six scans were acquired each day over four days, with up to 23 (68)Ge shell-less lesions (diam. 6, 8, 10, 12, 16 mm) distributed throughout the phantom thorax and pelvis. Each scan acquired 6 bed positions at 240 s/bed in listmode format. The listmode files were then statistically pruned, preserving Poisson statistics, to equivalent count levels for scan times of 180 s, 120 s, 90 s, 60 s, 45 s, 30 s, and 15 s per bed field-of-view, corresponding to whole-body scan times of 1.5-24 min. Each dataset was reconstructed using ordinary Poisson line-of-response (LOR) OSEM, with PSF model, with TOF, and with PSF+TOF. Localization receiver operating characteristics (LROC) analysis was then performed using the channelized non-prewhitened (CNPW) observer. The results were analyzed to delineate the relationship between scan time, reconstruction method, and strength of post-reconstruction filter. Lesion-detection performance degraded as scan time was reduced, and progressively stronger filters were required to maximize performance for the shorter scans. PSF modeling and TOF were found to improve detection performance, but the degree of improvement for TOF was much larger than for PSF for the large phantom used in this study. Notably, the images using TOF provided equivalent lesion-detection performance to the images without TOF for scan durations 40% shorter, suggesting that TOF may offset, at least in part, the need for longer scan times in larger patients.

Time-of-flight (TOF) measurement capability promises to improve PET image quality. We characterized the physical and clinical PET performance of the first Biograph mCT TOF PET/CT scanner (Siemens Medical Solutions USA, Inc.) in comparison with its predecessor, the Biograph TruePoint TrueV. In particular, we defined the improvements with TOF. The physical performance was evaluated according to the National Electrical Manufacturers Association (NEMA) NU 2-2007 standard with additional measurements to specifically address the TOF capability. Patient data were analyzed to obtain the clinical performance of the scanner. As expected for the same size crystal detectors, a similar spatial resolution was measured on the mCT as on the TruePoint TrueV. The mCT demonstrated modestly higher sensitivity (increase by 19.7 ± 2.8%) and peak noise equivalent count rate (NECR) (increase by 15.5 ± 5.7%) with similar scatter fractions. The energy, time and spatial resolutions for a varying single count rate of up to 55 Mcps resulted in 11.5 ± 0.2% (FWHM), 527.5 ± 4.9 ps (FWHM) and 4.1 ± 0.0 mm (FWHM), respectively. With the addition of TOF, the mCT also produced substantially higher image contrast recovery and signal-to-noise ratios in a clinically-relevant phantom geometry. The benefits of TOF were clearly demonstrated in representative patient images.

The introduction of fast scintillators with good stopping power for 511-keV photons has renewed interest in time-of-flight (TOF) PET. The ability to measure the difference between the arrival times of a pair of photons originating from positron annihilation improves the image signal-to-noise ratio (SNR). The level of improvement depends upon the extent and distribution of the positron activity and the time resolution of the PET scanner. While specific estimates can be made for phantom imaging, the impact of TOF PET is more difficult to quantify in clinical situations. The results presented here quantify the benefit of TOF in a challenging phantom experiment and then assess both qualitatively and quantitatively the impact of incorporating TOF information into the reconstruction of clinical studies. A clear correlation between patient body mass index and gain in SNR was observed in this study involving 100 oncology patient studies, with a gain due to TOF ranging from 1.1 to 1.8, which is consistent with the 590-ps time resolution of the TOF PET scanner. The visual comparison of TOF and non-TOF images performed by two nuclear medicine physicians confirmed the advantages of incorporating TOF into the reconstruction, advantages that include better definition of small lesions and image details, improved uniformity, and noise reduction.

Unlabelled: Time-of-flight (TOF) PET uses very fast detectors to improve localization of events along coincidence lines-of-response. This information is then utilized to improve the tomographic reconstruction. This work evaluates the effect of TOF upon an observer's performance for detecting and localizing focal warm lesions in noisy PET images., Methods: An advanced anthropomorphic lesion-detection phantom was scanned 12 times over 3 days on a prototype TOF PET/CT scanner (Siemens Medical Solutions). The phantom was devised to mimic whole-body oncologic (18)F-FDG PET imaging, and a number of spheric lesions (diameters 6-16 mm) were distributed throughout the phantom. The data were reconstructed with the baseline line-of-response ordered-subsets expectation-maximization algorithm, with the baseline algorithm plus point spread function model (PSF), baseline plus TOF, and with both PSF+TOF. The lesion-detection performance of each reconstruction was compared and ranked using localization receiver operating characteristics (LROC) analysis with both human and numeric observers. The phantom results were then subjectively compared to 2 illustrative patient scans reconstructed with PSF and with PSF+TOF., Results: Inclusion of TOF information provides a significant improvement in the area under the LROC curve compared to the baseline algorithm without TOF data (P = 0.002), providing a degree of improvement similar to that obtained with the PSF model. Use of both PSF+TOF together provided a cumulative benefit in lesion-detection performance, significantly outperforming either PSF or TOF alone (P < 0.002). Example patient images reflected the same image characteristics that gave rise to improved performance in the phantom data., Conclusion: Time-of-flight PET provides a significant improvement in observer performance for detecting focal warm lesions in a noisy background. These improvements in image quality can be expected to improve performance for the clinical tasks of detecting lesions and staging disease. Further study in a large clinical population is warranted to assess the benefit of TOF for various patient sizes and count levels, and to demonstrate effective performance in the clinical environment.

Artificial insemination using cryopreserved semen is a common management tool of the contemporary livestock producer. The ability to determine post-thaw fertility from pre-freeze sperm function parameters would be of major benefit to producers. In this study computer-aided sperm head morphometry was used to determine whether there is any association between pre-freeze bull sperm head measurements and post-thaw non-return to oestrus rates. Sixteen commercial artificial insemination bulls were used for this study. Of the 16 bulls, eight had > or =69% non-return to oestrus rates while the remaining eight bulls had <69% non-return to oestrus rates, based on artificial insemination of cryopreserved semen from a minimum of 748 inseminations per bull. Microscope slides of extended or cryopreserved and thawed semen were prepared and stained by the MGZIN procedure. The morphometric dimensions for length, width, width/length, area and perimeter for a minimum of 200 sperm heads were analyzed from each slide by ASMA and the mean measurements and intra-analysis coefficients of variation (CV) recorded. The post-thaw non-return to oestrus rates for all bulls were correlated with pre-freeze measurements of width (r=0.53, P<0.05), and the change in width/length after cryopreservation (r=0.61, P<0.05). There were no significant differences in the mean pre-freeze or post-thaw sperm head measurements between the two groups. However, the mean post-thaw change in width/length was significantly (P=0.003) different between the groups. The mean post-thaw intra-analysis variability for width was significantly lower (P=0.03) in bulls with non-return to oestrus rates (NRR)> or =69%. Overall, the data suggests that pre-freeze and post-thaw bull sperm head morphometry measurements of individual bulls may have minimal predictive value of post-thaw fertility as determined by non-return to oestrus rates between groups of bulls with limited variance in non-return to oestrus rates. The clinical relationship of sperm head morphometry and fertility in bulls with a greater, clinically significant range of non-return to oestrus, remains to be studied.

The objective of this work was to evaluate the lesion detection performance of four fully-3D positron emission tomography (PET) reconstruction schemes using experimentally acquired data. A multi-compartment anthropomorphic phantom was set up to mimic whole-body (18)F-fluorodeoxyglucose (FDG) cancer imaging and scanned 12 times in 3D mode, obtaining count levels typical of noisy clinical scans. Eight of the scans had 26 (68)Ge "shell-less" lesions (6, 8-, 10-, 12-, 16-mm diameter) placed throughout the phantom with various target:background ratios. This provided lesion-present and lesion-absent datasets with known truth appropriate for evaluating lesion detectability by localization receiver operating characteristic (LROC) methods. Four reconstruction schemes were studied: 1) Fourier rebinning (FORE) followed by 2D attenuation-weighted ordered-subsets expectation-maximization, 2) fully-3D AW-OSEM, 3) fully-3D ordinary-Poisson line-of-response (LOR-)OSEM; and 4) fully-3D LOR-OSEM with an accurate point-spread function (PSF) model. Two forms of LROC analysis were performed. First, a channelized nonprewhitened (CNPW) observer was used to optimize processing parameters (number of iterations, post-reconstruction filter) for the human observer study. Human observers then rated each image and selected the most-likely lesion location. The area under the LROC curve ( A(LROC)) and the probability of correct localization were used as figures-of-merit. The results of the human observer study found no statistically significant difference between FORE and AW-OSEM3D ( A(LROC)=0.41 and 0.36, respectively), an increase in lesion detection performance for LOR-OSEM3D ( A(LROC)=0.45, p=0.076), and additional improvement with the use of the PSF model ( A(LROC)=0.55, p=0.024). The numerical CNPW observer provided the same rankings among algorithms, but obtained different values of A(LROC). These results show improved lesion detection performance for the reconstruction algorithms with more sophisticated statistical and imaging models as compared to the previous-generation algorithms.

The pukeko (Porphyrio porphyrio melanotus) is widespread in New Zealand, and is the closest living relative to the endangered takahe (Porphyrio mantelli), which has a relatively high rate of infertility. In this study, sperm collected from a number of pukeko was analysed in order to model the reproductive physiology of the male takahe. In addition, testicular parameters were measured. To ascertain the best method of sperm collection five techniques for harvesting sperm were used on two occasions during the breeding season. All five techniques resulted in the successful recovery of sperm. However, the float-out technique produced the best quality samples. Following collection, the morphometry of unstained sperm was assessed. Our findings suggest that pukeko sperm is non-motile in the male reproductive tract. We found the mean sperm head length in the pukeko is 16.9mum, but sperm head length varied significantly between birds. Testicular weight and length was significantly correlated with bird weight (P<0.05). Within each bird, testes weights were asymmetric. However, testes length was significantly correlated (P<0.05). There was a significant difference (P<0.05) in testes length between birds. The methodologies presented for obtaining and analysing pukeko sperm morphometry can be used to assist opportunistic studies of the reproductive biology of other New Zealand native birds.

This paper investigates data compression methods for time-of-flight (TOF) positron emission tomography (PET), which rebin the 3-D TOF measurements into a set of 2-D TOF data for a stack of transaxial slices. The goal of this work is to develop rebinning algorithms that are more accurate than the TOF single-slice-rebinning (TOF-SSRB) method proposed by Mullani in 1982. Two approaches are explored. The first one is based on a partial differential equation, which expresses a consistency condition for TOF-PET data with a Gaussian TOF profile. From this equation we derive an analytical rebinning algorithm, which is unbiased in the limit of continuous sampling. The second approach is discrete: each 2-D rebinned data sample is calculated as a linear combination of the 3-D TOF samples in the same axial plane parallel to the axis of the scanner. The coefficients of the linear combination are precomputed by optimizing a cost function which enforces both accuracy and good variance reduction, models the TOF profile, the axial PSF of the LORs, and the specific sampling scheme of the scanner. Measurements of a thorax phantom on a prototype TOF-PET scanner with a resolution of 550 ps show that the proposed discrete method improves the bias-variance trade-off and is a promising alternative to TOF-SSRB when data compression is required to achieve clinically acceptable reconstruction time.

Background: Improved survival for children with acute lymphocytic leukemia (ALL) has allowed investigators to focus on the adverse or side effects of treatment and to develop interventions that promote cure while decreasing the long-term effects of therapy. Although much attention has been given to the significant neurocognitive sequelae that can occur after ALL therapy, limited investigation is found addressing fine motor function in these children and motor function that may contribute to neurocognitive deficits in ALL survivors., Methods: Fine motor and sensory-perceptual performances were examined in 82 children with ALL within 6-months of diagnosis and annually for 2 years (year 1 and year 2, respectively) during therapy., Results: Purdue Pegboard assessments indicated significant slowing of fine motor speed and dexterity for the dominant hand, nondominant hand, and both hands simultaneously for children in this study. Mean Visual-Motor Integration (VMI) scores for children with low-risk and high-risk ALL decreased from the first evaluation to year 1 and again at year 2. Mean VMI scores for children with standard risk ALL increased from the first evaluation to year 1 and then decreased at year 2. Significant positive correlations were found between the Purdue and the VMI at both year 1 and year 2, suggesting that the Pegboard performance consistently predicts the later decline in visual-motor integration. Significant correlations were found between the Purdue Pegboard at baseline and the Performance IQ during year 1, though less consistently during year 2. A similar pattern was also observed between the baseline Pegboard performance and performance on the Coding and Symbol Search subtests during year 1 and year 2., Conclusions: In this study, children with ALL experienced significant and persistent visual-motor problems throughout therapy. These problems continued during the first and second years of treatment. These basic processing skills are necessary to the development of higher-level cognitive abilities, including nonverbal intelligence and academic achievement, particularly in arithmetic and written language.

Unlabelled: To optimize the injected dose of radiopharmaceutical in PET, one needs to know its relationship to some metric of data quality for individual patient scans, such as noise-equivalent counting rate (NECR). In this paper, we show how one may accurately model the clinical NECR response corresponding to specific patient scans much as if a counting-rate test had been performed on each patient. We apply this technique to patient data and show how it can lead to improved clinical scanning protocols., Methods: True and random coincidence rates expressed as functions of an appropriate measurable system parameter such as the detector single-event rate have functional forms that are largely independent of the object being scanned. Thus, reference true and random response functions may be scaled directly to the specific counting rates measured on a clinical scan, thereby yielding a curve of NECR versus injected dose. We have applied this technique to 2 groups of 163 clinical (18)F-FDG scans each. One of the groups was obtained on a lutetium oxyorthosilicate PET/CT scanner with conventional front-end electronics, and the other was obtained on a lutetium oxyorthosilicate PET/CT scanner with a new digital data processing system (Pico-3D)., Results: At 90%-95% of maximum signal-to-noise ratio (SNR), the mean optimal dose for a 60-min uptake period ranged from 366 to 717 MBq depending on the electronics and randoms processing method. There was only a slight (1 MBq/kg) dependence of optimal dose on patient weight but a larger dependence on position in the body. Pico-3D electronics improved optimal data SNR by 35% for a 70-kg person, but in both cases NECR fell rapidly with increasing weight (1.4%/kg). For an equivalent data SNR, a 120-kg person would have to be scanned 2.3 times longer than a 60-kg person. Over this range of weight, the mean scatter fraction increased by 12% whereas the ratio of mean randoms to trues increased by 48%., Conclusion: The methodology developed here allows one to directly estimate the optimal dose to inject for specific clinical scans and permits a detailed analysis of the sources of noise in PET data and of their variation with parameters such as patient weight.

This paper explores fast reconstruction strategies for 3D time-of-flight (TOF) positron emission tomography (PET), based on 2D data rebinning. Starting from pre-corrected 3D TOF data, a rebinning algorithm estimates for each transaxial slice the 2D TOF sinogram that would have been acquired by a single-ring scanner. The rebinned sinograms can then be reconstructed using any algorithm for 2D TOF reconstruction. We introduce TOF-FORE, an approximate rebinning algorithm obtained by extending the Fourier rebinning method for non-TOF data. In addition, we identify two partial differential equations that must be satisfied by consistent 3D TOF data, and use them to derive exact rebinning algorithms and to characterize the degree of the approximation in TOF-FORE. Numerical simulations demonstrate that TOF-FORE is more accurate than two different TOF extensions of the single-slice rebinning method, and suggest that TOF-FORE will be a valuable tool for practical TOF PET in the range of axial apertures and time resolutions typical of current scanners.

Performance tests on lutetium oxyorthosilicate (LSO)-based PET scanners cannot be conducted strictly according to the National Electrical Manufacturers Association (NEMA) NU 2 standards because of the presence of intrinsic radioactivity within the LSO crystal scintillator material. This background radiation gives rise mainly to random coincidence events but also to a small number of true coincidences, which cannot be eliminated from measurements on such scanners and must therefore be corrected for in the data analysis. The current NU 2 standards do not take account of these backgrounds and hence can lead to erroneous results on LSO-based machines. Nevertheless, the intent of the standards can be met with appropriate modifications to the acquisition and processing procedures. In this paper, we propose certain changes to the NEMA specifications to accommodate this class of scanners. These changes affect mainly the estimation of sensitivity, scatter, randoms, and count losses. Using these modified procedures, the NU 2 performance of LSO-based systems can accurately be measured.

Unlabelled: The NU 2-1994 standard document for PET performance measurements has recently been updated. The updated document, NU 2-2001, includes revised measurements for spatial resolution, intrinsic scatter fraction, sensitivity, counting rate performance, and accuracy of count loss and randoms corrections. The revised measurements are designed to allow testing of dedicated PET systems in both 2-dimensional and 3-dimensional modes as well as coincidence gamma cameras, conditions not considered in the original NU 2-1994 standard. In addition, the updated measurements strive toward being more representative of clinical studies, in particular, whole-body imaging., Methods: Performance measurements following the NU 2-1994 and NU 2-2001 standards were performed on several different PET scanners. Differences between the procedures and resulting performance characteristics, as well as the rationale for these changes, were noted., Results: Spatial resolution is measured with a point source in all 3 directions, rather than a line source, as specified previously. For the measurements of intrinsic scatter fraction, sensitivity, and counting rate performance, a 70-cm line source is now specified, instead of a 19-cm-long cylindric phantom. The longer configuration permits measurement of these performance characteristics over the entire axial field of view of all current PET scanners and incorporates the effects of activity outside the scanner. A measurement of image quality has been added in an effort to measure overall image quality under clinically realistic conditions. This measurement replaces the individual measurements of uniformity and of the accuracy of corrections for attenuation and scatter., Conclusion: The changes from the NU 2-1994 standard to the NU 2-2001 standard strive toward establishing relevance with clinical studies. The tests in the updated standard also are, in general, simpler and less time-consuming to perform than those in the NU 2-1994 standard.

The 'EXACT3D' positron tomograph, which is now in routine clinical research use, was developed with the aim of achieving unprecedented sensitivity, high spatial and temporal resolution and simplicity of design using proven detector technology. It consists of six rings of standard detector blocks (CTI/Siemens EXACT HR+) with 4.39 mm x 4.05 mm x 30 mm elements, giving an axial field of view (FOV) of 23.4 cm. This extended FOV and the absence of interplane septa and retractable transmission rod sources has allowed greatly simplified gantry and detector cassette design. Operation in exclusive 3D mode requires an alternative to the conventional coincidence method for transmission scanning, and a single photon approach using a hydraulically driven 137Cs point source has been implemented. The tomograph has no other moving parts. A single time frame of data without any compression is very large (> 300 Mbyte) and two approaches are employed to overcome this difficulty: (a) adjacent sinograms can be summed automatically into different combinations and (b) listmode (event-by-event) acquisition has been instituted, which is both storage efficient (particularly for acquisition of sparse data sets) and maximizes temporal resolution. The high-speed I/O and computing hardware can maintain a sustained acquisition rate of about 4 million coincidence events per second. A disadvantage of the large axial FOV in 3D is the increased sensitivity to activity outside the coincidence FOV. However, this can be minimized by additional side shielding. The mean spatial resolution is 4.8 +/- 0.2 mm FWHM (transaxial, 1 cm off-axis) and 5.6 +/- 0.5 mm (axial, on-axis). Its absolute efficiency is 5.8% for a line source in air (just spanning the axial FOV) and 10% for a central point source (with thresholds of 350-650 keV). For a uniform 20 cm diameter cylinder, the efficiency is 69 kcps kBq(-1) ml(-1) (after subtraction of a scatter fraction of 42%). Sensitivity relative to the EXACT HR+ (with four rings of blocks) is 2.5 (3D) and 12 (2D) times respectively. The rate of random events in blood flow studies in the brain and body, using 15O-labelled water, can be controlled by limiting the administered dose and inserting additional side shielding.

A technique determines the optimal window width for orbiting rod transmission studies in positron emission tomography (PET). Windowing reduces noise in orbiting rod transmission studies. Lines-of-response (LOR) which intersect the rods generate primarily true coincidence events. LOR which pass far from the rods generate random and scatter events. Since the angular position of the orbiting rods is known in real-time, LOR which produce mostly noise are gated off. When optimally determined, the rod window width maximizes the noise equivalent counts (NEC) collected in the transmission study. Transaxial rod projection profiles of trues, randoms, and scatter produce NEC versus window width plots. For the ECAT EXACT line of PET systems and a 20-cm water cylinder, optimal is five LOR wide.