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BackgroundTotal-body positron emission tomography/computed tomography (PET/CT) scanners are characterized by higher signal collection efficiency and greater spatial resolution compared to conventional scanners, allowing for delayed imaging and improved image quality. These advantages may also lead to better detection of physiological processes that diagnostic imaging professionals should be aware of. The gallbladder (GB) is not usually visualized as an 18F-2-fluorodeoxyglucose (18F-FDG)-avid structure in routine clinical PET/CT studies; however, with the total-body PET/CT, we have been increasingly visualizing GB activity without it being involved in an inflammatory or neoplastic process. The aim of this study was to report visualization rates and characteristics of GB 18F-FDG uptake observed in both healthy and oncological subjects scanned on a total-body PET/CT system.Materials and methodsScans from 73 participants (48 healthy and 25 with newly diagnosed lymphoma) who underwent 18F-FDG total-body PET/CT were retrospectively reviewed. Subjects were scanned at multiple timepoints up to 3 h post-injection. Gallbladder 18F-FDG activity was graded using liver uptake as a reference, and the pattern was qualified as present in the wall, lumen, or both. Participants' characteristics, such as age, sex, body-mass index, blood glucose, and other clinical parameters, were collected to assess for any significant correlation with GB 18F-FDG uptake.ResultsAll 73 subjects showed GB uptake at one or more imaging timepoints. An increase in uptake intensity overtime was observed up until the 180-min scan, and the visualization rate of GB 18F-FDG uptake was 100% in the 120- and 180-min post-injection scans. GB wall uptake was detected in a significant number of patients (44/73, 60%), especially at early timepoint scans, whereas luminal activity was detected in 71/73 (97%) subjects, especially at later timepoint scans. No significant correlation was found between GB uptake intens

Deep learning (DL) has been proposed to automate image segmentation and provide accuracy, consistency, and efficiency. Accurate segmentation of lipomatous tumors (LTs) is critical for correct tumor radiomics analysis and localization. The major challenge of this task is data heterogeneity, including tumor morphological characteristics and multicenter scanning protocols. To mitigate the issue, we aimed to develop a DL-based Super Learner (SL) ensemble framework with different data correction and normalization methods. Pathologically proven LTs on pre-operative T1-weighted/proton-density MR images of 185 patients were manually segmented. The LTs were categorized by tumor locations as distal upper limb (DUL), distal lower limb (DLL), proximal upper limb (PUL), proximal lower limb (PLL), or Trunk (T) and grouped by 80%/9%/11% for training, validation and testing. Six configurations of correction/normalization were applied to data for fivefold-cross-validation trainings, resulting in 30 base learners (BLs). A SL was obtained from the BLs by optimizing SL weights. The performance was evaluated by dice-similarity-coefficient (DSC), sensitivity, specificity, and Hausdorff distance (HD95). For predictions of the BLs, the average DSC, sensitivity, and specificity from the testing data were 0.72 [Formula: see text] 0.16, 0.73 [Formula: see text] 0.168, and 0.99 [Formula: see text] 0.012, respectively, while for SL predictions were 0.80 [Formula: see text] 0.184, 0.78 [Formula: see text] 0.193, and 1.00 [Formula: see text] 0.010. The average HD95 of the BLs were 11.5 (DUL), 23.2 (DLL), 25.9 (PUL), 32.1 (PLL), and 47.9 (T) mm, whereas of SL were 1.7, 8.4, 15.9, 2.2, and 36.6 mm, respectively. The proposed method could improve the segmentation accuracy and mitigate the performance instability and data heterogeneity aiding the differential diagnosis of LTs in real clinical situations.

We introduce the Fast Algorithm for Motion Correction (FALCON) software, which allows correction of both rigid and nonlinear motion artifacts in dynamic whole-body (WB) images, irrespective of the PET/CT system or the tracer. Methods: Motion was corrected using affine alignment followed by a diffeomorphic approach to account for nonrigid deformations. In both steps, images were registered using multiscale image alignment. Moreover, the frames suited to successful motion correction were automatically estimated by calculating the initial normalized cross-correlation metric between the reference frame and the other moving frames. To evaluate motion correction performance, WB dynamic image sequences from 3 different PET/CT systems (Biograph mCT, Biograph Vision 600, and uEXPLORER) using 6 different tracers (18F-FDG, 18F-fluciclovine, 68Ga-PSMA, 68Ga-DOTA-TATE, 11C-Pittsburgh compound B, and 82Rb) were considered. Motion correction accuracy was assessed using 4 different measures: change in volume mismatch between individual WB image volumes to assess gross body motion, change in displacement of a large organ (liver dome) within the torso due to respiration, change in intensity in small tumor nodules due to motion blur, and constancy of activity concentration levels. Results: Motion correction decreased gross body motion artifacts and reduced volume mismatch across dynamic frames by about 50%. Moreover, large-organ motion correction was assessed on the basis of correction of liver dome motion, which was removed entirely in about 70% of all cases. Motion correction also improved tumor intensity, resulting in an average increase in tumor SUVs by 15%. Large deformations seen in gated cardiac 82Rb images were managed without leading to anomalous distortions or substantial intensity changes in the resulting images. Finally, the constancy of activity concentration levels was reasonably preserved (

We introduce the Fast Algorithm for Motion Correction (FALCON) software, which allows correction of both rigid and nonlinear motion artifacts in dynamic whole-body (WB) images, irrespective of the PET/CT system or the tracer. Methods: Motion was corrected using affine alignment followed by a diffeomorphic approach to account for nonrigid deformations. In both steps, images were registered using multiscale image alignment. Moreover, the frames suited to successful motion correction were automatically estimated by calculating the initial normalized cross-correlation metric between the reference frame and the other moving frames. To evaluate motion correction performance, WB dynamic image sequences from 3 different PET/CT systems (Biograph mCT, Biograph Vision 600, and uEXPLORER) using 6 different tracers (18F-FDG, 18F-fluciclovine, 68Ga-PSMA, 68Ga-DOTA-TATE, 11C-Pittsburgh compound B, and 82Rb) were considered. Motion correction accuracy was assessed using 4 different measures: change in volume mismatch between individual WB image volumes to assess gross body motion, change in displacement of a large organ (liver dome) within the torso due to respiration, change in intensity in small tumor nodules due to motion blur, and constancy of activity concentration levels. Results: Motion correction decreased gross body motion artifacts and reduced volume mismatch across dynamic frames by about 50%. Moreover, large-organ motion correction was assessed on the basis of correction of liver dome motion, which was removed entirely in about 70% of all cases. Motion correction also improved tumor intensity, resulting in an average increase in tumor SUVs by 15%. Large deformations seen in gated cardiac 82Rb images were managed without leading to anomalous distortions or substantial intensity changes in the resulting images. Finally, the constancy of activity concentration levels was reasonably preserved (

BackgroundTo prospectively demonstrate the feasibility of performing dual-phase SPECT/CT for the assessment of the small joints of the hands of rheumatoid arthritis (RA) patients, and to evaluate the reliability of the quantitative and qualitative measures derived from the resulting images.MethodsA SPECT/CT imaging protocol was developed in this pilot study to scan both hands simultaneously in participants with RA, in two phases of 99mTc-MDP radiotracer uptake, namely the soft-tissue blood pool phase (within 15 minutes after radiotracer injection) and osseous phase (after 3 hours). Joints were evaluated qualitatively (normal vs. abnormal uptake) and quantitatively [by measuring a newly developed metric, maximum corrected count ratio (MCCR)]. Qualitative and quantitative evaluations were repeated to assess reliability.ResultsFour participants completed seven studies (all four were imaged at baseline, and three of them at follow-up after 1-month of arthritis therapy). A total of 280 joints (20 per hand) were evaluated. The MCCR from soft-tissue phase scans was significantly higher for clinically abnormal joints compared to clinically normal ones; P<0.001, however the MCCR from the osseous phase scans were not different between the two joint groups. Intraclass Correlation Coefficient (ICC) for MCCR was excellent [0.9789, 95% confidence interval (CI): 0.9734-0.9833]. Intra-observer agreement for qualitative SPECT findings was substantial for both the soft-tissue phase (kappa =0.78, 95% CI: 0.72-0.83) and osseous-phase (kappa =0.70, 95% CI: 0.64-0.76) scans.ConclusionsExtracting reliable quantitative and qualitative measures from dual-phase 99mTc-MDP SPECT/CT hand scans is feasible in RA patients. SPECT/CT may provide a unique means for assessing both synovitis and osseous involvement in RA joints using the same radiotracer injection.

BackgroundPericardial disease can be a manifestation of infection and imaging can have a role in its diagnosis. coccidioidomycosis endemic fungal infection has been more frequently reported over the past few decades. Other than case reports or series, there has been no systemic study evaluating pericardial imaging findings in patients with coccidioidomycosis to the best of our knowledge. The purpose of this study was to evaluate intrathoracic computed tomographic (CT) imaging abnormalities in patients with coccidioidal infection with specific emphasis on the pericardium.MethodsRetrospective review of radiology reports and clinical chart review was performed to identify patients with coccidioidomycosis between January 2000 and September 2021 at our medical center. Diagnosis of infection was confirmed predominately with serology. Patients were excluded if a CT was not performed within 3 months of confirmed diagnosis date and if there was concomitant additional granulomatous or fungal infection. Chest CT was reviewed for pericardial and additional intrathoracic findings.ResultsThe final retrospective cohort consisted of 37 patients. Imaging findings included lung nodules (N = 33/37), consolidation (N = 25/37), mediastinal or hilar lymphadenopathy (N = 20/37) and pleural effusions (N = 13/37). Eleven of 37 patients (30%) had either trace pericardial fluid (N = 3/37) or small pericardial effusions (N = 8/37). One patient had pericardial enhancement/thickening and history of pericardial tamponade. No other patient had clinical pericarditis or pericardial tamponade. Pericardial calcifications were not seen in any patient. Pericardial effusion was statistically associated with presence of pleural effusion as 9/13 patients with pleural effusion had pericardial effusion versus 2/26 patients without pleural effusion had pericardial effusion (p < 0.001). Otherwise patients with and without pericardial imaging findings were similar in terms of demographics, comorbidities

BackgroundPericardial disease can be a manifestation of infection and imaging can have a role in its diagnosis. coccidioidomycosis endemic fungal infection has been more frequently reported over the past few decades. Other than case reports or series, there has been no systemic study evaluating pericardial imaging findings in patients with coccidioidomycosis to the best of our knowledge. The purpose of this study was to evaluate intrathoracic computed tomographic (CT) imaging abnormalities in patients with coccidioidal infection with specific emphasis on the pericardium.MethodsRetrospective review of radiology reports and clinical chart review was performed to identify patients with coccidioidomycosis between January 2000 and September 2021 at our medical center. Diagnosis of infection was confirmed predominately with serology. Patients were excluded if a CT was not performed within 3 months of confirmed diagnosis date and if there was concomitant additional granulomatous or fungal infection. Chest CT was reviewed for pericardial and additional intrathoracic findings.ResultsThe final retrospective cohort consisted of 37 patients. Imaging findings included lung nodules (N = 33/37), consolidation (N = 25/37), mediastinal or hilar lymphadenopathy (N = 20/37) and pleural effusions (N = 13/37). Eleven of 37 patients (30%) had either trace pericardial fluid (N = 3/37) or small pericardial effusions (N = 8/37). One patient had pericardial enhancement/thickening and history of pericardial tamponade. No other patient had clinical pericarditis or pericardial tamponade. Pericardial calcifications were not seen in any patient. Pericardial effusion was statistically associated with presence of pleural effusion as 9/13 patients with pleural effusion had pericardial effusion versus 2/26 patients without pleural effusion had pericardial effusion (p < 0.001). Otherwise patients with and without pericardial imaging findings were similar in terms of demographics, comorbidities

Quantitative dynamic PET with compartmental modeling has the potential to enable multiparametric imaging and more accurate quantification than static PET imaging. Conventional methods for parametric imaging commonly use a single kinetic model for all image voxels and neglect the heterogeneity of physiologic models, which can work well for single-organ parametric imaging but may significantly compromise total-body parametric imaging on a scanner with a long axial field of view. In this paper, we evaluate the necessity of voxelwise compartmental modeling strategies, including time delay correction (TDC) and model selection, for total-body multiparametric imaging. Methods: Ten subjects (5 patients with metastatic cancer and 5 healthy volunteers) were scanned on a total-body PET/CT system after injection of 370 MBq of 18F-FDG. Dynamic data were acquired for 60 min. Total-body parametric imaging was performed using 2 approaches. One was the conventional method that uses a single irreversible 2-tissue-compartment model with and without TDC. The second approach selects the best kinetic model from 3 candidate models for individual voxels. The differences between the 2 approaches were evaluated for parametric imaging of microkinetic parameters and the 18F-FDG net influx rate, KiResults: TDC had a nonnegligible effect on kinetic quantification of various organs and lesions. The effect was larger in lesions with a higher blood volume. Parametric imaging of Ki with the standard 2-tissue-compartment model introduced vascular-region artifacts, which were overcome by the voxelwise model selection strategy. Conclusion: The time delay and appropriate kinetic model vary in different organs and lesions. Modeling of the time delay of the blood input function and model selection improved total-body multiparametric imaging.

Objective.This work assessed the relationship between image signal-to-noise ratio (SNR) and total-body noise-equivalent count rate (NECR)-for both non-time-of-flight (TOF) NECR and TOF-NECR-in a long uniform water cylinder and 14 healthy human subjects using the uEXPLORER total-body PET/CT scanner.Approach.A TOF-NEC expression was modified for list-mode PET data, and both the non-TOF NECR and TOF-NECR were compared using datasets from a long uniform water cylinder and 14 human subjects scanned up to 12 h after radiotracer injection.Main results.The TOF-NECR for the uniform water cylinder was found to be linearly proportional to the TOF-reconstructed image SNR2in the range of radioactivity concentrations studied, but not for non-TOF NECR as indicated by the reducedR2value. The results suggest that the use of TOF-NECR to estimate the count rate performance of TOF-enabled PET systems may be more appropriate for predicting the SNR of TOF-reconstructed images.Significance.Image quality in PET is commonly characterized by image SNR and, correspondingly, the NECR. While the use of NECR for predicting image quality in conventional PET systems is well-studied, the relationship between SNR and NECR has not been examined in detail in long axial field-of-view total-body PET systems, especially for human subjects. Furthermore, the current NEMA NU 2-2018 standard does not account for count rate performance gains due to TOF in the NECR evaluation. The relationship between image SNR and total-body NECR in long axial FOV PET was assessed for the first time using the uEXPLORER total-body PET/CT scanner.

The world's first total-body PET scanner with an axial field of view (AFOV) of 194 cm is now in clinical and research use at our institution. The uEXPLORER PET/CT system is the first commercially available total-body PET scanner. Here we present a detailed physical characterization of this scanner based on National Electrical Manufacturers Association (NEMA) NU 2-2018 along with a new set of measurements devised to appropriately characterize the total-body AFOV. Methods: Sensitivity, count-rate performance, time-of-flight resolution, spatial resolution, and image quality were evaluated following the NEMA NU 2-2018 protocol. Additional measurements of sensitivity and count-rate capabilities more representative of total-body imaging were performed using extended-geometry phantoms based on the world-average human height (∼165 cm). Lastly, image quality throughout the long AFOV was assessed with the NEMA image quality (IQ) phantom imaged at 5 axial positions and over a range of expected total-body PET imaging conditions (low dose, delayed imaging, short scan duration). Results: Our performance evaluation demonstrated that the scanner provides a very high sensitivity of 174 kcps/MBq, a count-rate performance with a peak noise-equivalent count rate of approximately 2 Mcps for total-body imaging, and good spatial resolution capabilities for human imaging (≤3.0 mm in full width at half maximum near the center of the AFOV). Excellent IQ, excellent contrast recovery, and low noise properties were illustrated across the AFOV in both NEMA IQ phantom evaluations and human imaging examples. Conclusion: In addition to standard NEMA NU 2-2018 characterization, a new set of measurements based on extending NEMA NU 2-2018 phantoms and experiments was devised to characterize the physical performance of the first total-body PET system. The rationale for these extended measurements was evident from differences in sensitivity, count-rate-activity relationships, and noise-equivalent count

This work outlines the clinical implementation of total-body PET/CT from the time of installation at UC Davis EXPLORER Molecular Imaging Center in May 2019 to date (September 2020). This process has not been without challenges: logistical, technical, and medical problems were all encountered and are discussed. The mutual learning/teaching engagement among nuclear medicine technologists, research staff, radiologists, and referring physicians has been the key to the past year's achievements; these include development of ground-breaking clinical protocols for a range of Food and Drug Administration-approved radiotracers, and the attainment of a measure of expertise in clinical total-body PET/CT.

Magnetic resonance imaging is the primary method used to diagnose canine glial cell neoplasia and noninfectious inflammatory meningoencephalitis. Subjective differentiation of these diseases can be difficult due to overlapping imaging characteristics. This study utilizes texture analysis (TA) of intra-axial lesions both as a means to quantitatively differentiate these broad categories of disease and to help identify glial tumor grade/cell type and specific meningoencephalitis subtype in a group of 119 dogs with histologically confirmed diagnoses. Fifty-nine dogs with gliomas and 60 dogs with noninfectious inflammatory meningoencephalitis were retrospectively recruited and randomly split into training (n = 80) and test (n = 39) cohorts. Forty-five of 120 texture metrics differed significantly between cohorts after correcting for multiple testing (false discovery rate < 0.05). After training the random forest algorithm, the classification accuracy for the test set was 85% (sensitivity 89%, specificity 81%). TA was only partially able to differentiate the inflammatory subtypes (granulomatous meningoencephalitis [GME], necrotizing meningoencephalitis [NME], and necrotizing leukoencephalitis [NLE]) (out-of-bag error rate of 35.0%) and was unable to identify metrics that could correctly classify glioma grade or cell type (out-of-bag error rate of 59.6% and 47.5%, respectively). Multiple demographic differences, such as patient age, sex, weight, and breed were identified between disease cohorts and subtypes which may be useful in prioritizing differential diagnoses. TA of MR images with a random forest algorithm provided classification accuracy of inflammatory and neoplastic brain disease approaching the accuracy of previously reported subjective radiologist evaluation.

Absolute quantification of regional tissue concentration of radioactivity in positron emission tomography (PET) is a critical parameter-of-interest across various clinical and research applications and is affected by a complex interplay of factors including scanner calibration, data corrections, and image reconstruction. The emergence of long axial field-of-view (FOV) PET systems widens the dynamic range accessible to PET and creates new opportunities in reducing scan time and radiation dose, delayed or low radioactivity imaging, as well as kinetic modeling of the entire human. However, these imaging regimes impose challenging conditions for accurate quantification due to constraints from image reconstruction, low count conditions, as well as large and rapidly changing radioactivity distribution across a large axial FOV. We comprehensively evaluated the quantitative accuracy of the uEXPLORER total-body scanner in conditions that encompass existing and potential imaging applications (such as dynamic imaging and ultralow-dose imaging) using a set of total-body specific phantom and human measurements. Through these evaluations we demonstrated a relative count rate accuracy of ±3%-4% using the NEMA NU 2-2018 protocol, an axial uniformity spread of ±3% across the central 90% axial FOV, and a 3% activity bias spread from 17 to 474 MBq18F-FDG in a 210 cm long cylindrical phantom. Region-of-interest quantification spread of 1% was found by simultaneously scanning three NEMA NU 2 image quality phantoms, as well as relatively stable volume-of-interest quantification across 0.2%-100% of total counts through re-sampled datasets. In addition, an activity bias spread of -2% to +1% post-bolus injections in human subjects was found. Larger bias changes during the bolus injection phase in humans indicated the difficulty in providing accurate PET data corrections for complex activity distributions across a large dynamic range. Our results overall indicated that the quantita

We report the case of a 74-year-old man with seropositive rheumatoid arthritis (RA) and radiographic osteoarthritis (OA) who underwent dual-phase high-resolution Tc-MDP SPECT/CT. Early radiotracer enhancement was noted in 2 RA joints of the right hand, both presenting with a ring-like uptake pattern around the joint, consistent with synovitis. Insignificant early enhancement was noted at the first carpometacarpal joint, despite presentation of CT features of OA. The delayed-phase enhancement patterns were distinct, showing asymmetry in RA joints, but a symmetric, joint-centered pattern for the OA joint.