Whole-Body Multiparametric PET in Clinical Oncology: Current Status, Challenges, and Opportunities.

The interpretation of clinical oncologic PET studies has historically used static reconstructions based on SUVs. SUVs and SUV-based images have important limitations, including dependence on uptake times and reduced conspicuity of tracer-avid lesions in organs with high background uptake. The acquisition of dynamic PET images enables additional PET reconstructions via Patlak modeling, which assumes that a tracer is irreversibly trapped by tissues of interest. The resulting multiparametric PET images capture a tracer's net trapping rate (Ki) and apparent volume of distribution (VD), separating the contributions of bound and free tracer fractions to the PET signal captured in the SUV. Potential benefits of multiparametric PET include higher quantitative stability, superior lesion conspicuity, and greater accuracy for differentiating malignant and benign lesions. However, the imaging protocols necessary for multiparametric PET are inherently more complex and time-intensive, despite the recent introduction of automated or semiautomated scanner-based reconstruction packages. In this Review, we examine the current state of multiparametric PET in whole-body oncologic imaging. We summarize the Patlak methodology and relevant tracer kinetics, discuss clinical workflows and protocol considerations, and highlight clinical challenges and opportunities. We aim to help oncologic imagers make informed decisions about whether to implement multiparametric PET in their clinical practices.

Assessment of lesion insertion tool in pelvis PET/MR data with applications to attenuation correction method development.

BACKGROUND: In modern positron emission tomography (PET) with multi-modality imaging (e.g., PET/CT and PET/MR), the attenuation correction (AC) is the single largest correction factor for image reconstruction. One way to assess AC methods and other reconstruction parameters is to utilize software-based simulation tools, such as a lesion insertion tool. Extensive validation of these simulation tools is required to ensure results of the study are clinically meaningful. PURPOSE: To evaluate different PET AC methods using a synthetic lesion insertion tool that simulates lesions in a patient cohort that has both PET/MR and PET/CT images. To further demonstrate how lesion insertion tool may be used to extend knowledge of PET reconstruction parameters, including but not limited to AC. METHODS: Lesion quantitation is compared using conventional Dixon-based MR-based AC (MRAC) to that of using CT-based AC (CTAC, a "ground truth"). First, the pre-existing lesions were simulated in a similar environment; a total of 71 lesions were identified in 18 pelvic PET/MR patient images acquired with a time-of-flight simultaneous PET/MR scanner, and matched lesions were inserted contralaterally on the same axial slice. Second, synthetic lesions were inserted into four anatomic target locations in a cohort of four patients who didn't have any observed clinical lesions in the pelvis. RESULTS: The matched lesion insertions resulted in unity between the lesion error ratios (mean SUVs), demonstrating that the inserted lesions successfully simulated the original lesions. In the second study, the inserted lesions had distinct characteristics by target locations and demonstrated negative max-SUV%diff trends for bone-dominant sites across the patient cohort. CONCLUSIONS: The current work demonstrates that the applied lesion insertion tool can simulate uptake in pelvic lesions and their expected SUV values, and that the lesion insertion tool can be extended to evaluate further PET reconstruction corrections and algorithms and their impact on quantitation accuracy and precision.

A simplified method to correct saturation of arterial input function for cardiac magnetic resonance first-pass perfusion imaging: validation with simultaneously acquired PET.

BACKGROUND: First-pass perfusion imaging in magnetic resonance imaging (MRI) is an established method to measure myocardial blood flow (MBF). An obstacle for accurate quantification of MBF is the saturation of blood pool signal intensity used for arterial input function (AIF). The objective of this project was to validate a new simplified method for AIF estimation obtained from single-bolus and single sequence perfusion measurements. The reference MBF was measured simultaneously on 13N-ammonia positron emission tomography (PET). METHODS: Sixteen patients with clinically confirmed myocardial ischemia were imaged in a clinical whole-body PET-MRI system. PET perfusion imaging was performed in a 10-min acquisition after the injection of 10 mCi of 13N-ammonia. The MRI perfusion acquisition started simultaneously with the start of the PET acquisition after the injection of a 0.075 mmol/kg gadolinium contrast agent. Cardiac stress imaging was initiated after the administration of regadenoson 20 s prior to PET-MRI scanning. The saturation part of the MRI AIF data was modeled as a gamma variate curve, which was then estimated for a true AIF by minimizing a cost function according to various boundary conditions. A standard AHA 16-segment model was used for comparative analysis of absolute MBF from PET and MRI. RESULTS: Overall, there were 256 segments in 16 patients, mean resting perfusion for PET was 1.06 ± 0.34 ml/min/g and 1.04 ± 0.30 ml/min/g for MRI (P = 0.05), whereas mean stress perfusion for PET was 2.00 ± 0.74 ml/min/g and 2.12 ± 0.76 ml/min/g for MRI (P < 0.01). Linear regression analysis in MBF revealed strong correlation (r = 0.91, slope = 0.96, P < 0.001) between PET and MRI. Myocardial perfusion reserve, calculated from the ratio of stress MBF over resting MBF, also showed a strong correlation between MRI and PET measurements (r = 0.82, slope = 0.81, P < 0.001). CONCLUSION: The results demonstrated the feasibility of the simplified AIF estimation method for the accurate quantification of MBF by MRI with single sequence and single contrast injection. The MRI MBF correlated strongly with PET MBF obtained simultaneously. This post-processing technique will allow easy transformation of clinical perfusion imaging data into quantitative information.

MR-assisted PET respiratory motion correction using deep-learning based short-scan motion fields.

PURPOSE: We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patients. Moreover, we proposed and examined a PET MoCo approach using motion vector fields (MVFs) from a deep-learning reconstructed short MRI scan. METHODS: The evaluation of PET MoCo was performed in a respiratory motion phantom study with varying lesion sizes and tumor to background ratios (TBRs) using a static scan as the ground truth. MRI-based MVFs were derived from either 2000 spokes (MoCo2000 , 5-6 min acquisition time) using a Fourier transform reconstruction or 200 spokes (MoCoP2P200 , 30-40 s acquisition time) using a deep-learning Phase2Phase (P2P) reconstruction and then incorporated into PET MoCo reconstruction. For six patients with hepatic lesions, the performance of PET MoCo was evaluated using quantitative metrics (SUVmax , SUVpeak , SUVmean , lesion volume) and a blinded radiological review on lesion conspicuity. RESULTS: MRI-assisted PET MoCo methods provided similar results to static scans across most lesions with varying TBRs in the phantom. Both MoCo2000 and MoCoP2P200 PET images had significantly higher SUVmax , SUVpeak , SUVmean and significantly lower lesion volume than non-motion-corrected (non-MoCo) PET images. There was no statistical difference between MoCo2000 and MoCoP2P200 PET images for SUVmax , SUVpeak , SUVmean or lesion volume. Both radiological reviewers found that MoCo2000 and MoCoP2P200 PET significantly improved lesion conspicuity. CONCLUSION: An MRI-assisted PET MoCo method was evaluated using the ground truth in a phantom study. In patients with hepatic lesions, PET MoCo images improved quantitative and qualitative metrics based on only 30-40 s of MRI motion modeling data.

Chemokine Receptor 2-targeted Molecular Imaging in Pulmonary Fibrosis. A Clinical Trial.

Rationale: Idiopathic pulmonary fibrosis (IPF) is a progressive inflammatory lung disease without effective molecular markers of disease activity or treatment responses. Monocyte and interstitial macrophages that express the C-C motif CCR2 (chemokine receptor 2) are active in IPF and central to fibrosis.Objectives: To phenotype patients with IPF for potential targeted therapy, we developed 64Cu-DOTA-ECL1i, a radiotracer to noninvasively track CCR2+ monocytes and macrophages using positron emission tomography (PET).Methods: CCR2+ cells were investigated in mice with bleomycin- or radiation-induced fibrosis and in human subjects with IPF. The CCR2+ cell populations were localized relative to fibrotic regions in lung tissue and characterized using immunolocalization, single-cell mass cytometry, and Ccr2 RNA in situ hybridization and then correlated with parallel quantitation of lung uptake by 64Cu-DOTA-ECL1i PET.Measurements and Main Results: Mouse models established that increased 64Cu-DOTA-ECL1i PET uptake in the lung correlates with CCR2+ cell infiltration associated with fibrosis (n = 72). As therapeutic models, the inhibition of fibrosis by IL-1ß blockade (n = 19) or antifibrotic pirfenidone (n = 18) reduced CCR2+ macrophage accumulation and uptake of the radiotracer in mouse lungs. In lung tissues from patients with IPF, CCR2+ cells concentrated in perifibrotic regions and correlated with radiotracer localization (n = 21). Human imaging revealed little lung uptake in healthy volunteers (n = 7), whereas subjects with IPF (n = 4) exhibited intensive signals in fibrotic zones.Conclusions: These findings support a role for imaging CCR2+ cells within the fibrogenic niche in IPF to provide a molecular target for personalized therapy and monitoring.Clinical trial registered with www.clinicaltrials.gov (NCT03492762).

Heterogeneity in insulin-stimulated glucose uptake among different muscle groups in healthy lean people and people with obesity.

AIMS/HYPOTHESIS: It has been proposed that muscle fibre type composition and perfusion are key determinants of insulin-stimulated muscle glucose uptake, and alterations in muscle fibre type composition and perfusion contribute to muscle, and consequently whole-body, insulin resistance in people with obesity. The goal of the study was to evaluate the relationships among muscle fibre type composition, perfusion and insulin-stimulated glucose uptake rates in healthy, lean people and people with obesity. METHODS: We measured insulin-stimulated whole-body glucose disposal and glucose uptake and perfusion rates in five major muscle groups (erector spinae, obliques, rectus abdominis, hamstrings, quadriceps) in 15 healthy lean people and 37 people with obesity by using the hyperinsulinaemic-euglycaemic clamp procedure in conjunction with [2H]glucose tracer infusion (to assess whole-body glucose disposal) and positron emission tomography after injections of [15O]H2O (to assess muscle perfusion) and [18F]fluorodeoxyglucose (to assess muscle glucose uptake). A biopsy from the vastus lateralis was obtained to assess fibre type composition. RESULTS: We found: (1) a twofold difference in glucose uptake rates among muscles in both the lean and obese groups (rectus abdominis: 67 [51, 78] and 32 [21, 55] µmol kg-1 min-1 in the lean and obese groups, respectively; erector spinae: 134 [103, 160] and 66 [24, 129] µmol kg-1 min-1, respectively; median [IQR]) that was unrelated to perfusion or fibre type composition (assessed in the vastus only); (2) the impairment in insulin action in the obese compared with the lean group was not different among muscle groups; and (3) insulin-stimulated whole-body glucose disposal expressed per kg fat-free mass was linearly related with muscle glucose uptake rate (r2 = 0.65, p < 0.05). CONCLUSIONS/INTERPRETATION: Obesity-associated insulin resistance is generalised across all major muscles, and is not caused by alterations in muscle fibre type composition or perfusion. In addition, insulin-stimulated whole-body glucose disposal relative to fat-free mass provides a reliable index of muscle glucose uptake rate.

Deep learning-based T1-enhanced selection of linear attenuation coefficients (DL-TESLA) for PET/MR attenuation correction in dementia neuroimaging.

PURPOSE: The accuracy of existing PET/MR attenuation correction (AC) has been limited by a lack of correlation between MR signal and tissue electron density. Based on our finding that longitudinal relaxation rate, or R1 , is associated with CT Hounsfield unit in bone and soft tissues in the brain, we propose a deep learning T1 -enhanced selection of linear attenuation coefficients (DL-TESLA) method to incorporate quantitative R1 for PET/MR AC and evaluate its accuracy and longitudinal test-retest repeatability in brain PET/MR imaging. METHODS: DL-TESLA uses a 3D residual UNet (ResUNet) for pseudo-CT (pCT) estimation. With a total of 174 participants, we compared PET AC accuracy of DL-TESLA to 3 other methods adopting similar 3D ResUNet structures but using UTE R2∗ , or Dixon, or T1 -MPRAGE as input. With images from 23 additional participants repeatedly scanned, the test-retest differences and within-subject coefficient of variation of standardized uptake value ratios (SUVR) were compared between PET images reconstructed using either DL-TESLA or CT for AC. RESULTS: DL-TESLA had (1) significantly lower mean absolute error in pCT, (2) the highest Dice coefficients in both bone and air, (3) significantly lower PET relative absolute error in whole brain and various brain regions, (4) the highest percentage of voxels with a PET relative error within both ±3% and ±5%, (5) similar to CT test-retest differences in SUVRs from the cerebrum and mean cortical (MC) region, and (6) similar to CT within-subject coefficient of variation in cerebrum and MC. CONCLUSION: DL-TESLA demonstrates excellent PET/MR AC accuracy and test-retest repeatability.

Myocardial glucose and fatty acid metabolism is altered and associated with lower cardiac function in young adults with Barth syndrome.

BACKGROUND: Barth syndrome (BTHS) is a rare X-linked condition resulting in cardiomyopathy, however; the effects of BTHS on myocardial substrate metabolism and its relationships with cardiac high-energy phosphate metabolism and left ventricular (LV) function are unknown. We sought to characterize myocardial glucose, fatty acid (FA), and leucine metabolism in BTHS and unaffected controls and examine their relationships with cardiac high-energy phosphate metabolism and LV function. METHODS/RESULTS: Young adults with BTHS (n = 14) and unaffected controls (n = 11, Control, total n = 25) underwent bolus injections of 15O-water and 1-11C-glucose, palmitate, and leucine and concurrent positron emission tomography imaging. LV function and cardiac high-energy phosphate metabolism were examined via echocardiography and 31P magnetic resonance spectroscopy, respectively. Myocardial glucose extraction fraction (21 ± 14% vs 10 ± 8%, P = .03) and glucose utilization (828.0 ± 470.0 vs 393.2 ± 361.0 µmol·g-1·min-1, P = .02) were significantly higher in BTHS vs Control. Myocardial FA extraction fraction (31 ± 7% vs 41 ± 6%, P < .002) and uptake (0.25 ± 0.04 vs 0.29 ± 0.03 mL·g-1·min-1, P < .002) were significantly lower in BTHS vs Control. Altered myocardial metabolism was associated with lower cardiac function in BTHS. CONCLUSIONS: Myocardial substrate metabolism is altered and may contribute to LV dysfunction in BTHS. Clinical Trials #: NCT01625663.

Folate Receptor α-Targeted 89Zr-M9346A Immuno-PET for Image-Guided Intervention with Mirvetuximab Soravtansine in Triple-Negative Breast Cancer.

Folate receptor α (FRα) is a well-studied tumor biomarker highly expressed in many epithelial tumors such as breast, ovarian, and lung cancers. Mirvetuximab soravtansine (IMGN853) is the antibody-drug conjugate of FRα-binding humanized monoclonal antibody M9346A and cytotoxic maytansinoid drug DM4. IMGN853 is currently being evaluated in multiple clinical trials, in which the immunohistochemical evaluation of an archival tumor or biopsy specimen is used for patient screening. However, limited tissue collection may lead to inaccurate diagnosis due to tumor heterogeneity. Herein, we developed a zirconium-89 (89Zr)-radiolabeled M9346A (89Zr-M9346A) as an immuno-positron emission tomography (immuno-PET) radiotracer to evaluate FRα expression in triple-negative breast cancer (TNBC) patients, providing a novel means to guide intervention with therapeutic IMGN853. In this study, we verified the binding specificity and immunoreactivity of 89Zr-M9346A by in vitro studies in FRαhigh cells (HeLa) and FRαlow cells (OVCAR-3). In vivo PET/computed tomography (PET/CT) imaging in HeLa xenografts and TNBC patient-derived xenograft (PDX) mouse models with various levels of FRα expression demonstrated its targeting specificity and sensitivity. Following PET imaging, the treatment efficiencies of IMGN853, pemetrexed, IMGN853 + pemetrexed, paclitaxel, and saline were assessed in FRαhigh and FRαlow TNBC PDX models. The correlation between 89Zr-M9346A tumor uptake and treatment response using IMGN853 in FRαhigh TNBC PDX model suggested the potential of 89Zr-M9346A PET as a noninvasive tool to prescreen patients based on the in vivo PET imaging for IMGN853-targeted treatment.

Evaluation of [89Zr]trastuzumab-PET/CT in differentiating HER2-positive from HER2-negative breast cancer.

PURPOSE: To evaluate whether tumor uptake of [89Zr]trastuzumab can distinguish HER2-positive from HER2-negative breast cancer. METHODS: Women with HER2-positive (n = 34) and HER2-negative (n = 16) breast cancer underwent PET/CT 5 ± 2 days following [89Zr]trastuzumab administration. HER2 status was determined based on immunohistochemistry and/or fluorescence in situ hybridization of primary or metastatic/recurrent tumor. Tumor [89Zr]trastuzumab uptake was assessed qualitatively and semiquantitatively as maximum standardized uptake value (SUVmax), and correlated with HER2 status. Additionally, intrapatient heterogeneity of [89Zr]trastuzumab uptake was evaluated. RESULTS: On a per-patient basis, [89Zr]trastuzumab-PET/CT was positive in 30/34 (88.2%) HER2-positive and negative in 15/16 (93.7%) HER2-negative patients. Considering all lesions, the SUVmax was not significantly different in patients with HER2-positive versus HER2-negative disease (p = 0.06). The same was true of when only hepatic lesions were evaluated (p = 0.42). However, after excluding hepatic lesions, tumor SUVmax was significantly higher in HER2-positive compared to HER2-negative patients (p = 0.003). A cutoff SUVmax of 3.2, determined by ROC analysis, demonstrated positive-predictive value of 83.3% (95% CI 65.3%, 94.4%), sensitivity of 75.8% (57.7%, 88.9%), negative-predictive value of 50% (24.7%, 75.3%), and specificity of 61.5% (95% 31.6%, 86.1%) for differentiating HER2-positive from HER2-negative lesions. There was intrapatient heterogeneity of [89Zr]trastuzumab uptake in 20% of patients with multiple lesions. CONCLUSIONS: [89Zr]trastuzumab has the potential to characterize the HER2 status of the complete tumor burden in patients with breast cancer, thus obviating repeat or multiple tissue sampling to assess intrapatient heterogeneity of HER2 status.

First-in-Man Evaluation of 124I-PGN650: A PET Tracer for Detecting Phosphatidylserine as a Biomarker of the Solid Tumor Microenvironment.

PURPOSE: PGN650 is a F(ab')2 antibody fragment that targets phosphatidylserine (PS), a marker normally absent that becomes exposed on tumor cells and tumor vasculature in response to oxidative stress and increases in response to therapy. PGN650 was labeled with 124I to create a positron emission tomography (PET) agent as an in vivo biomarker for tumor microenvironment and response to therapy. In this phase 0 study, we evaluated the pharmacokinetics, safety, radiation dosimetry, and tumor targeting of this tracer in a cohort of patients with cancer. METHODS: Eleven patients with known solid tumors received approximately 140 MBq (3.8 mCi) 124I-PGN650 intravenously and underwent positron emission tomography-computed tomography (PET/CT) approximately 1 hour, 3 hours, and either 24 hours or 48 hours later to establish tracer kinetics for the purpose of calculating radiation dosimetry (from integration of the organ time-activity curves and OLINDA/EXM using the adult male and female models). RESULTS: Known tumor foci demonstrated mildly increased uptake, with the highest activity at the latest imaging time. There were no unexpected adverse events. The liver was the organ receiving the highest radiation dose (0.77 mGy/MBq); the effective dose was 0.41 mSv/MBq. CONCLUSION: Although 124I-PGN650 is safe for human PET imaging, the tumor targeting with this agent in patients was less than previously observed in animal studies.

PET of Poly (ADP-Ribose) Polymerase Activity in Cancer: Preclinical Assessment and First In-Human Studies.

Purpose To demonstrate that positron emission tomography (PET) with fluorine 18 (18F) fluorthanatrace (FTT) depicts activated poly (adenosine diphosphate-ribose)polymerase (PARP) expression and is feasible for clinical trial evaluation. Materials and Methods All studies were conducted prospectively from February 2012 through July 2015 under protocols approved by the local animal studies committee and institutional review board. The area under the receiver operating characteristic curve (AUC, in g/mL· min) for 18F-FTT was assessed in normal mouse organs before and after treatment with olaparib (n = 14), a PARP inhibitor, or iniparib (n = 11), which has no PARP inhibitory activity. Murine biodistribution studies were performed to support human translational studies. Eight human subjects with cancer and eight healthy volunteers underwent imaging to verify the human radiation dosimetry of 18F-FTT. The Wilcoxon signed rank test was used to assess for differences among treatment groups for the mouse studies. Results In mice, olaparib, but not iniparib, significantly reduced the 18F-FTT AUC in the spine (median difference before and after treatment and interquartile range [IQR]: -17 g/mL· min and 10 g/mL · min, respectively [P = .0001], for olaparib and -3 g/mL · min and 13 g/mL · min [P = .70] for iniparib) and in nodes (median difference and interquartile range [IQR] before and after treatment: -23 g/mL · min and 13 g/mL · min [P = .0001] for olaparib; -9 g/mL · min and 17 g/mL · min [P = .05] for iniparib). The effective dose was estimated at 6.9 mSv for a 370-MBq 18F-FTT dose in humans. In humans, the organs with the highest uptake on images were the spleen and pancreas. Among five subjects with measurable tumors, increased 18F-FTT uptake was seen in one subject with pancreatic adenocarcinoma and another with liver cancer. Conclusion The results suggest that 18F-FTT uptake reflects PARP expression and that its radiation dosimetry profile is compatible with those of agents currently in clinical use. © RSNA, 2016 Online supplemental material is available for this article.

Design and Modular Construction of a Polymeric Nanoparticle for Targeted Atherosclerosis Positron Emission Tomography Imaging: A Story of 25% (64)Cu-CANF-Comb.

PURPOSE: To assess the physicochemical properties, pharmacokinetic profiles, and in vivo positron emission tomography (PET) imaging of natriuretic peptide clearance receptors (NPRC) expressed on atherosclerotic plaque of a series of targeted, polymeric nanoparticles. METHODS: To control their structure, non-targeted and targeted polymeric (comb) nanoparticles, conjugated with various amounts of c-atrial natriuretic peptide (CANF, 0, 5, 10 and 25%), were synthesized by controlled and modular chemistry. In vivo pharmacokinetic evaluation of these nanoparticles was performed in wildtype (WT) C57BL/6 mice after (64)Cu radiolabeling. PET imaging was performed on an apolipoprotein E-deficient (ApoE(-/-)) mouse atherosclerosis model to assess the NPRC targeting efficiency. For comparison, an in vivo blood metabolism study was carried out in WT mice. RESULTS: All three (64)Cu-CANF-comb nanoparticles showed improved biodistribution profiles, including significantly reduced accumulation in both liver and spleen, compared to the non-targeted (64)Cu-comb. Of the three nanoparticles, the 25% (64)Cu-CANF-comb demonstrated the best NPRC targeting specificity and sensitivity in ApoE(-/-) mice. Metabolism studies showed that the radiolabeled CANF-comb was stable in blood up to 9 days. Histopathological analyses confirmed the up-regulation of NPRC along the progression of atherosclerosis. CONCLUSION: The 25% (64)Cu-CANF-comb demonstrated its potential as a PET imaging agent to detect atherosclerosis progression and status.

Evaluation of diagnostic performance of whole-body simultaneous PET/MRI in pediatric lymphoma.

BACKGROUND: Whole-body (18)F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is the standard of care for lymphoma. Simultaneous PET/MRI (magnetic resonance imaging) is a promising new modality that combines the metabolic information of PET with superior soft-tissue resolution and functional imaging capabilities of MRI while decreasing radiation dose. There is limited information on the clinical performance of PET/MRI in the pediatric setting. OBJECTIVE: This study evaluated the feasibility, dosimetry, and qualitative and quantitative diagnostic performance of simultaneous whole-body FDG-PET/MRI in children with lymphoma compared to PET/CT. MATERIALS AND METHODS: Children with lymphoma undergoing standard of care FDG-PET/CT were prospectively recruited for PET/MRI performed immediately after the PET/CT. Images were evaluated for quality, lesion detection and anatomical localization of FDG uptake. Maximum and mean standardized uptake values (SUVmax/mean) of normal organs and SUVmax of the most FDG-avid lesions were measured for PET/MRI and PET/CT. Estimation of radiation exposure was calculated using specific age-related factors. RESULTS: Nine PET/MRI scans were performed in eight patients (mean age: 15.3 years). The mean time interval between PET/CT and PET/MRI was 51 ± 10 min. Both the PET/CT and PET/MRI exams had good image quality and alignment with complete (9/9) concordance in response assessment. The SUVs from PET/MRI and PET/CT were highly correlated for normal organs (SUVmean r(2): 0.88, P<0.0001) and very highly for FDG-avid lesions (SUVmax r(2): 0.94, P=0.0002). PET/MRI demonstrated an average percent radiation exposure reduction of 39% ± 13% compared with PET/CT. CONCLUSION: Simultaneous whole-body PET/MRI is clinically feasible in pediatric lymphoma. PET/MRI performance is comparable to PET/CT for lesion detection and SUV measurements. Replacement of PET/CT with PET/MRI can significantly decrease radiation dose from diagnostic imaging in children.

Deep learning generation of preclinical positron emission tomography (PET) images from low-count PET with task-based performance assessment.

BACKGROUND: Preclinical low-count positron emission tomography (LC-PET) imaging offers numerous advantages such as facilitating imaging logistics, enabling longitudinal studies of long- and short-lived isotopes as well as increasing scanner throughput. However, LC-PET is characterized by reduced photon-count levels resulting in low signal-to-noise ratio (SNR), segmentation difficulties, and quantification uncertainties. PURPOSE: We developed and evaluated a novel deep-learning (DL) architecture-Attention based Residual-Dilated Net (ARD-Net)-to generate standard-count PET (SC-PET) images from LC-PET images. The performance of the ARD-Net framework was evaluated for numerous low count realizations using fidelity-based qualitative metrics, task-based segmentation, and quantitative metrics. METHOD: Patient Derived tumor Xenograft (PDX) with tumors implanted in the mammary fat-pad were subjected to preclinical [18F]-Fluorodeoxyglucose (FDG)-PET/CT imaging. SC-PET images were derived from a 10 min static FDG-PET acquisition, 50 min post administration of FDG, and were resampled to generate four distinct LC-PET realizations corresponding to 10%, 5%, 1.6%, and 0.8% of SC-PET count-level. ARD-Net was trained and optimized using 48 preclinical FDG-PET datasets, while 16 datasets were utilized to assess performance. Further, the performance of ARD-Net was benchmarked against two leading DL-based methods (Residual UNet, RU-Net; and Dilated Network, D-Net) and non-DL methods (Non-Local Means, NLM; and Block Matching 3D Filtering, BM3D). The performance of the framework was evaluated using traditional fidelity-based image quality metrics such as Structural Similarity Index Metric (SSIM) and Normalized Root Mean Square Error (NRMSE), as well as human observer-based tumor segmentation performance (Dice Score and volume bias) and quantitative analysis of Standardized Uptake Value (SUV) measurements. Additionally, radiomics-derived features were utilized as a measure of quality assurance (QA) in comparison to true SC-PET. Finally, a performance ensemble score (EPS) was developed by integrating fidelity-based and task-based metrics. Concordance Correlation Coefficient (CCC) was utilized to determine concordance between measures. The non-parametric Friedman Test with Bonferroni correction was used to compare the performance of ARD-Net against benchmarked methods with significance at adjusted p-value ≤0.01. RESULTS: ARD-Net-generated SC-PET images exhibited significantly better (p ≤ 0.01 post Bonferroni correction) overall image fidelity scores in terms of SSIM and NRMSE at majority of photon-count levels compared to benchmarked DL and non-DL methods. In terms of task-based quantitative accuracy evaluated by SUVMean and SUVPeak, ARD-Net exhibited less than 5% median absolute bias for SUVMean compared to true SC-PET and lower degree of variability compared to benchmarked DL and non-DL based methods in generating SC-PET. Additionally, ARD-Net-generated SC-PET images displayed higher degree of concordance to SC-PET images in terms of radiomics features compared to non-DL and other DL approaches. Finally, the ensemble score suggested that ARD-Net exhibited significantly superior performance compared to benchmarked algorithms (p ≤ 0.01 post Bonferroni correction). CONCLUSION: ARD-Net provides a robust framework to generate SC-PET from LC-PET images. ARD-Net generated SC-PET images exhibited superior performance compared other DL and non-DL approaches in terms of image-fidelity based metrics, task-based segmentation metrics, and minimal bias in terms of task-based quantification performance for preclinical PET imaging.

Joint regional uptake quantification of Thorium-227 and Radium-223 using a multiple-energy-window projection-domain quantitative SPECT method.

Thorium-227-based alpha-particle radiopharmaceutical therapies ({\alpha}-RPTs) are being investigated in several clinical and pre-clinical studies. After administration, Thorium-227 decays to Radium-223, another alpha-particle-emitting isotope, which redistributes within the patient. Reliable dose quantification of both Thorium-227 and Radium-223 is clinically important, and SPECT may perform this quantification as these isotopes also emit X- and gamma-ray photons. However, reliable quantification is challenged by the orders-of-magnitude lower activity compared to conventional SPECT, resulting in a very low number of detected counts, the presence of multiple photopeaks, substantial overlap in the emission spectra of these isotopes, and the image-degrading effects in SPECT. To address these issues, we propose a multiple-energy-window projection-domain quantification (MEW-PDQ) method that jointly estimates the regional activity uptake of both Thorium-227 and Radium-223 directly using the SPECT projection from multiple energy windows. We evaluated the method with realistic simulation studies using anthropomorphic digital phantoms, in the context of imaging patients with bone metastases of prostate cancer and treated with Thorium-227-based {\alpha}-RPTs. The proposed method yielded reliable (accurate and precise) regional uptake estimates of both isotopes and outperformed state-of-the-art methods across different lesion sizes and contrasts, in a virtual imaging trial, as well as with moderate levels of intra-regional heterogeneous uptake and with moderate inaccuracies in the definitions of the support of various regions. Additionally, we demonstrated the effectiveness of using multiple energy windows and the variance of the estimated uptake using the proposed method approached the Cram\'er-Rao-lower-bound-defined theoretical limit.

Test-Retest Repeatability of Patlak Slopes versus Standardized Uptake Values for Hypermetabolic Lesions and Normal Organs in an Oncologic PET/CT Population.

PURPOSE: We aimed to determine the test-retest repeatability of quantitative metrics based on the Patlak slope (PS) versus the standardized uptake value (SUV) among lesions and normal organs on oncologic [18F]FDG-PET/CT. PROCEDURES: This prospective, single-center study enrolled adults undergoing standard-of-care oncologic [18F]FDG-PET/CTs. Early (35-50 min post-injection) and late (75-90 min post-injection) SUV and PS images were reconstructed from dynamic whole-body PET data. Repeat imaging occurred within 7 days. Relevant quantitative metrics were extracted from lesions and normal organs. Repeatability was assessed via mean test-retest percent changes [T-RT %Δ], within-subject coefficients of variation (wCVs), and intra-class correlation coefficients (ICCs). RESULTS: Nine subjects (mean age, 61.7 ± 6.2 years; 6 females) completed the test-retest protocol. Four subjects collectively had 17 [18F]FDG-avid lesions. Lesion wCVs were higher (i.e., worse repeatability) for PS-early-max (16.2%) and PS-early-peak (15.6%) than for SUV-early-max (8.9%) and SUV-early-peak (8.1%), with similar early metric ICCs (0.95-0.98). Lesion wCVs were similar for PS-late-max (8.5%) and PS-late-peak (6.4%) relative to SUV-late-max (9.7%) and SUV-late-peak (7.2%), with similar late metric ICCs (0.93-0.98). There was a significant bias toward higher retest SUV and PS values in the lesion analysis (T-RT %Δ [95% CI]: SUV-late-max, 10.0% [2.6%, 17.0%]; PS-late-max, 20.4% [14.3%, 26.4%]) but not in the normal organ analysis. CONCLUSIONS: Among [18F]FDG-avid lesions, the repeatability of PS-based metrics is similar to equivalent SUV-based metrics at late post-injection time points, indicating that PS-based metrics may be suitable for tracking response to oncologic therapies. However, further validation is required in light of our study's limitations, including small sample size and bias toward higher retest values for some metrics.

DEMIST: A Deep-Learning-Based Detection-Task-Specific Denoising Approach for Myocardial Perfusion SPECT.

There is an important need for methods to process myocardial perfusion imaging (MPI) single-photon emission computed tomography (SPECT) images acquired at lower-radiation dose and/or acquisition time such that the processed images improve observer performance on the clinical task of detecting perfusion defects compared to low-dose images. To address this need, we build upon concepts from model-observer theory and our understanding of the human visual system to propose a detection task-specific deep-learning-based approach for denoising MPI SPECT images (DEMIST). The approach, while performing denoising, is designed to preserve features that influence observer performance on detection tasks. We objectively evaluated DEMIST on the task of detecting perfusion defects using a retrospective study with anonymized clinical data in patients who underwent MPI studies across two scanners (N = 338). The evaluation was performed at low-dose levels of 6.25%, 12.5%, and 25% and using an anthropomorphic channelized Hotelling observer. Performance was quantified using area under the receiver operating characteristics curve (AUC). Images denoised with DEMIST yielded significantly higher AUC compared to corresponding low-dose images and images denoised with a commonly used task-agnostic deep learning-based denoising method. Similar results were observed with stratified analysis based on patient sex and defect type. Additionally, DEMIST improved visual fidelity of the low-dose images as quantified using root mean squared error and structural similarity index metric. A mathematical analysis revealed that DEMIST preserved features that assist in detection tasks while improving the noise properties, resulting in improved observer performance. The results provide strong evidence for further clinical evaluation of DEMIST to denoise low-count images in MPI SPECT.

Accuracy and longitudinal consistency of PET/MR attenuation correction in amyloid PET imaging amid software and hardware upgrades.

BACKGROUND AND PURPOSE: Integrated PET/MR allows the simultaneous acquisition of PET biomarkers and structural and functional MRI to study Alzheimer disease (AD). Attenuation correction (AC), crucial for PET quantification, can be performed using a deep learning approach, DL-Dixon, based on standard Dixon images. Longitudinal amyloid PET imaging, which provides important information about disease progression or treatment responses in AD, is usually acquired over several years. Hardware and software upgrades often occur during a multiple-year study period, resulting in data variability. This study aims to harmonize PET/MR DL-Dixon AC amid software and head coil updates and evaluate its accuracy and longitudinal consistency. MATERIALS AND METHODS: Tri-modality PET/MR and CT images were obtained from 329 participants, with a subset of 38 undergoing tri-modality scans twice within approximately three years. Transfer learning was employed to fine-tune DL-Dixon models on images from two scanner software versions (VB20P and VE11P) and two head coils (16-channel and 32-channel coils). The accuracy and longitudinal consistency of the DL-Dixon AC were evaluated. Power analyses were performed to estimate the sample size needed to detect various levels of longitudinal changes in the PET standardized uptake value ratio (SUVR). RESULTS: The DL-Dixon method demonstrated high accuracy across all data, irrespective of scanner software versions and head coils. More than 95.6% of brain voxels showed less than 10% PET relative absolute error in all participants. The median [interquartile range] PET mean relative absolute error was 1.10% [0.93%, 1.26%], 1.24% [1.03%, 1.54%], 0.99% [0.86%, 1.13%] in the cortical summary region, and 1.04% [0.83%, 1.36%], 1.08% [0.84%, 1.34%], 1.05% [0.72%, 1.32%] in cerebellum using the DL-Dixon models for the VB20P-16-channel-coil, VE11P-16-channel-coil and VE11P-32-channel-coil data, respectively. The within-subject coefficient of variation and intra-class correlation coefficient of PET SUVR in the cortical regions were comparable between the DL-Dixon and CT AC. Power analysis indicated that similar numbers of participants would be needed to detect the same level of PET changes using DL-Dixon and CT AC. CONCLUSIONS: DL-Dixon exhibited excellent accuracy and longitudinal consistency across the two software versions and head coils, demonstrating its robustness for longitudinal PET/MR neuroimaging studies in AD. ABBREVIATIONS: AC = attenuation correction; AD = Alzheimer disease; HU = Hounsfield unit; ICC = intraclass correlation coefficient; MAE = mean absolute error; MRAE = mean relative absolute error; pCT = pseudo-CT; PiB = Pittsburgh Compound B; SD = standard deviation; SUVR = standardized uptake value ratio; wCV = within-subject coefficient of variation.