Quantitative Positron Emission Tomography Research Articles

Quantitative PSMA-PET parameters in localized prostate cancer: prognostic and potential predictive value

BackgroundPSMA-PET is increasingly used for staging prostate cancer (PCA) patients. However, it is not clear if quantitative imaging parameters of positron emission tomography (PET) have an impact on disease progression and are thus important for the prognosis of localized PCA.MethodsThis is a monocenter retrospective analysis of 86 consecutive patients with localized intermediate or high-risk PCA and PSMA-PET before treatment The quantitative PET parameters maximum standardized uptake value (SUVmax), tumor asphericity (ASP), PSMA tumor volume (PSMA-TV), and PSMA total lesion uptake (PSMA-TLU = PSMA-TV × SUVmean) were assessed for their prognostic significance in patients with radiotherapy or surgery. Cox regression analyses were performed for biochemical recurrence-free survival, overall survival (OS), local control, and loco-regional control (LRC).Results67% of patients had high-risk disease, 51 patients were treated with radiotherapy, and 35 with surgery. Analysis of metric PET parameters in the whole cohort revealed a significant association of PSMA-TV (p = 0.003), PSMA-TLU (p = 0.004), and ASP (p < 0.001) with OS. Upon binarization of PET parameters, several other parameters showed a significant association with clinical outcome. When analyzing high-risk patients according to the primary treatment approach, a previously published cut-off for SUVmax (8.6) showed a significant association with LRC in surgically treated (p = 0.048), but not in primary irradiated (p = 0.34) patients. In addition, PSMA-TLU (p = 0.016) seemed to be a very promising biomarker to stratify surgical patients.ConclusionOur data confirm one previous publication on the prognostic impact of SUVmax in surgically treated patients with high-risk PCA. Our exploratory analysis indicates that PSMA-TLU might be even better suited. The missing association with primary irradiated patients needs prospective validation with a larger sample size to conclude a predictive potential.Trial registration Due to the retrospective nature of this research, no registration was carried out.

Examination of the PET in vivo generator 134Ce as a theranostic match for 225Ac.

The radionuclide pair cerium-134/lanthanum-134 (134Ce/134La) was recently proposed as a suitable diagnostic counterpart for the therapeutic alpha-emitter actinium-225 (225Ac). The unique properties of 134Ce offer perspectives for developing innovative in vivo investigations that are not possible with 225Ac. In this work, 225Ac- and 134Ce-labelled tracers were directly compared using internalizing and slow-internalizing cancer models to evaluate their in vivo comparability, progeny meandering, and potential as a matched theranostic pair for clinical translation. Despite being an excellent chemical match, 134Ce/134La has limitations to the setting of quantitative positron emission tomography imaging. The precursor PSMA-617 and a macropa-based tetrazine-conjugate (mcp-PEG8-Tz) were radiolabelled with 225Ac or 134Ce and compared in vitro and in vivo using standard (radio)chemical methods. Employing biodistribution studies and positron emission tomography (PET) imaging in athymic nude mice, the radiolabelled PSMA-617 tracers were evaluated in a PC3/PIP (PC3 engineered to express a high level of prostate-specific membrane antigen) prostate cancer mouse model. The 225Ac and 134Ce-labelled mcp-PEG8-Tz were investigated in a BxPC-3 pancreatic tumour model harnessing the pretargeting strategy based on a trans-cyclooctene-modified 5B1 monoclonal antibody. In vitro and in vivo studies with both 225Ac and 134Ce-labelled tracers led to comparable results, confirming the matching pharmacokinetics of this theranostic pair. However, PET imaging of the 134Ce-labelled precursors indicated that quantification is highly dependent on tracer internalization due to the redistribution of 134Ce's PET-compatible daughter 134La. Consequently, radiotracers based on internalizing vectors like PSMA-617 are suited for this theranostic pair, while slow-internalizing 225Ac-labelled tracers are not quantitatively represented by 134Ce PET imaging. When employing slow-internalizing vectors, 134Ce might not be an ideal match for 225Ac due to the underestimation of tumour uptake caused by the in vivo redistribution of 134La. However, this same characteristic makes it possible to estimate the redistribution of 225Ac's progeny noninvasively. In future studies, this unique PET in vivo generator will further be harnessed to study tracer internalization, trafficking of receptors, and the progression of the tumour microenvironment.

Distinguishing thymic cysts from low-risk thymomas via [18F]FDG PET/CT

BackgroundThymic cysts are a rare benign disease that needs to be distinguished from low-risk thymoma. [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) is a non-invasive imaging technique used in the differential diagnosis of thymic epithelial tumours, but its usefulness for thymic cysts remains unclear. Our study evaluated the utility of visual findings and quantitative parameters of [18F]FDG PET/CT for differentiating between thymic cysts and low-risk thymomas.MethodsPatients who underwent preoperative [18F]FDG PET/CT followed by thymectomy for a thymic mass were retrospectively analyzed. The visual [18F]FDG PET/CT findings evaluated were PET visual grade, PET central metabolic defect, and CT shape. The quantitative [18F]FDG PET/CT parameters evaluated were PET maximum standardized uptake value (SUVmax), CT diameter (cm), and CT attenuation in Hounsfield units (HU). Findings and parameters for differentiating thymic cysts from low-risk thymomas were assessed using Pearson’s chi-square test, the Mann-Whitney U-test, and receiver operating characteristics (ROC) curve analysis.ResultsSeventy patients (18 thymic cysts and 52 low-risk thymomas) were finally included. Visual findings of PET visual grade (P < 0.001) and PET central metabolic defect (P < 0.001) showed significant differences between thymic cysts and low-risk thymomas, but CT shape did not. Among the quantitative parameters, PET SUVmax (P < 0.001), CT diameter (P < 0.001), and CT HU (P = 0.004) showed significant differences. In ROC analysis, PET SUVmax demonstrated the highest area under the curve (AUC) of 0.996 (P < 0.001), with a cut-off of equal to or less than 2.1 having a sensitivity of 100.0% and specificity of 94.2%. The AUC of PET SUVmax was significantly larger than that of CT diameter (P = 0.009) and CT HU (P = 0.004).ConclusionsAmong the [18F]FDG PET/CT parameters examined, low FDG uptake (SUVmax ≤ 2.1, equal to or less than the mediastinum) is a strong diagnostic marker for a thymic cyst. PET visual grade and central metabolic defect are easily accessible findings.

Development of New CD38 Targeted Peptides for Cancer Imaging

PurposeMultiple myeloma (MM) affects over 35,000 patients each year in the US. There remains a need for versatile Positron Emission Tomography (PET) tracers for the detection, accurate staging, and monitoring of treatment response of MM that have optimal specificity and translational attributes. CD38 is uniformly overexpressed in MM and thus represents an ideal target to develop CD38-targeted small molecule PET radiopharmaceuticals to address these challenges.ProceduresUsing phage display peptide libraries and pioneering algorithms, we identified novel CD38 specific peptides. Imaging bioconjugates were synthesized using solid phase peptide chemistry, and systematically analyzed in vitro and in vivo in relevant MM systems.ResultsThe CD38-targeted bioconjugates were radiolabeled with copper-64 (64Cu) with100% radiochemical purity and an average specific activity of 3.3 – 6.6 MBq/nmol. The analog NODAGA-PEG4-SL022-GGS (SL022: Thr-His-Tyr-Pro-Ile-Val-Ile) had a Kd of 7.55 ± 0.291 nM and was chosen as the lead candidate. 64Cu-NODAGA-PEG4-SL022-GGS demonstrated high binding affinity to CD38 expressing human myeloma MM.1S-CBR-GFP-WT cells, which was blocked by the non-radiolabeled version of the peptide analog and anti-CD38 clinical antibodies, daratumumab and isatuximab, by 58%, 73%, and 78%, respectively. The CD38 positive MM.1S-CBR-GFP-WT cells had > 68% enhanced cellular binding when compared to MM.1S-CBR-GFP-KO cells devoid of CD38. Furthermore, our new CD38-targeted radiopharmaceutical allowed visualization of tumors located in marrow rich bones, remaining there for up to 4 h. Clearance from non-target organs occurred within 60 min. Quantitative PET data from a murine disseminated tumor model showed significantly higher accumulation in the bones of tumor-bearing animals compared to tumor-naïve animals (SUVmax 2.06 ± 0.4 versus 1.24 ± 0.4, P = 0.02). Independently, tumor uptake of the target compound was significantly higher (P = 0.003) compared to the scrambled peptide, 64Cu-NODAGA-PEG4-SL041-GGS (SL041: Thr-Tyr-His-Ile-Pro-Ile-Val). The subcutaneous MM model demonstrated significantly higher accumulation in tumors compared to muscle at 1 and 4 h after tracer administration (SUVmax 0.8 ± 0.2 and 0.14 ± 0.04, P = 0.04 at 1 h; SUVmax 0.89 ± 0.01 and 0.09 ± 0.01, P = 0.0002 at 4 h).ConclusionsThe novel CD38-targeted, radiolabeled bioconjugates were specific and allowed visualization of MM, providing a starting point for the clinical translation of such tracers for the detection of MM.

Role of serial 18F-fludeoxyglucose positron emission tomography in determining the therapeutic efficacy of immunosuppression and clinical outcome in patients with cardiac sarcoidosis

BackgroundMyocardial inflammation and perfusion defects detected by 18F-fludeoxyglucose (FDG) and Rubidium-82 positron emission tomography (PET) may be associated with ventricular arrhythmias (VAs) in cardiac sarcoidosis (CS). The role of serial quantitative PET in determining the effect of treatment on myocardial inflammation and clinical outcomes is yet to be defined. MethodsNewly diagnosed CS patients with active myocardial inflammation (maximum standardised uptake value (SUVmax) ≥ 2.5) were treated with immunosuppression, then underwent repeat FDG-PET, Rubidium-82, and echocardiographic imaging 6–12 months later. Serial changes in SUVmax, SUVmean, inflammatory extent, perfusion defect (PD) extent, metabolism/perfusion mismatch extent, global cardiac metabolic activity, and left ventricular ejection fraction (LVEF) were assessed. The primary endpoint was a composite of all-cause mortality, serious VA and heart-failure (HF) hospitalisation. Event data were recorded from the date of the second FDG-PET. ResultsThe study population consisted of 113 patients (66% male, age: 55 ± 11 years, LVEF: 54 ± 13%). SUVmax reduced from 4.5 (interquartile range: 3.3–7.1) to 2.7 (2.2–3.6). Overall, 94 (83%) patients saw serial reduction in SUVmax, with 42 (37%) demonstrating complete response (SUVmax <2.5).Following a median of 46 (25–57) months, 28 (25%) patients reached the endpoint (8 deaths, 17 VAs, and 3 HF hospitalisations). PD extent (Hazard ratio 1.03, 95% confidence interval: 1.01–1.05; p = 0.035) was a significant predictor of outcome following treatment, even after accounting for LVEF and change in SUVmean. The risk of adverse events was the greatest in those with a pre-treatment or post-treatment PD extent of >10%. ConclusionIn our cohort with active CS, following a treatment-induced reduction in myocardial inflammation, PD extent was the main predictor of adverse events.

How to assess nonresponsiveness to vasodilator stress

Myocardial perfusion imaging (MPI) is a powerful tool for the functional assessment of ischemia in patients with suspected or known coronary artery disease (CAD). Given that the diagnostic accuracy and prognostic value of MPI and post-test management are highly dependent on achieving an adequate stress vasodilatory response, it is critical to identify those who may not have adequately responded to vasodilator pharmacological stress agents such as adenosine, dipyridamole, and regadenoson. Caffeine, a potent inhibitor of the adenosine receptor, is a compound that can affect vasodilatory hemodynamics, result in false negative studies, and potentially alter management in cases of inaccurate test results. Vasodilator non-responsiveness can be suspected by examining hemodynamics, quantitative positron emission tomography (PET) metrics such as myocardial flow reserve (MFR), and splenic response to stress. Quantitative MFR values of 1–1.2 should raise suspicion for nonresponsiveness in the setting of normal perfusion, along with the absence of a splenic switch off. Newer metrics, such as splenic response ratio, can be used to aid in the identification of potential nonresponders to pharmacologic vasodilators.

Development of the quantitative PET prostate phantom (Q3P) for improved quality assurance of 18F-PSMA PET imaging in metastatic prostate cancer.

Phantoms are commonly used to evaluate and compare the performance of imaging systems given the known ground truth. Positron emission tomography (PET) scanners are routinely validated using the NEMA image quality phantom, in which lesions are modeled using 10 to 37mm fillable spheres. The NEMA phantom neglects, however, to model focal (3-10-mm), high-uptake lesions that are increasingly observed in prostate-specific membrane antigen (PSMA) PET images. PSMA-targeting radiopharmaceuticals allow for enhanced detection of metastatic prostate cancers. As such, there is significant need to develop an updated phantom which considers both the quantitative and lesion detectability of this new paradigm in oncological PET imaging. In this work, we present the Quantitative PET Prostate Phantom (Q3P); a portable and modular phantom that can be used to improve and harmonize imaging protocols for 18F-PSMA PET scans. A one-piece cylindrical phantom was designed effectively in two halves, which we call modules. Module 1 was designed to mimic lesions in the presence of background, and Module 2 mimicked very high contrast conditions (i.e., very low background) that can be observed in 18F-PSMA PET scans. Shell-less radioactive spheres (3-16-mm) were cast using epoxy resin mixed with sodium-22 (22Na), a long half-life positron emitter with positron range similar to 18F. To establish realistic lesion contrast, the 22Na spheres were mounted in a cylindrical chamber that can be filled with an 18F background (module 1). Thirteen exchangeable spherical cavity inserts (3-37-mm) were machined in two parts and solvent welded together, and filled with 18F (50 kBq/mL) to model lesions with very high contrast (module 2). Five 2.5-min PET scans were acquired on a 5-ring GE Discovery MI PET/CT scanner (General Electric, USA). Lesions were segmented using 41% of SUVmax fixed thresholding (41% FT) and recovery coefficients (RCs) were computed from 5 noise realizations. The manufactured phantom is portable (5.7kg) and scan preparation takes less than 40min. The total 22Na activity is 250 kBq, allowing it to be shipped as an exempt package under International Atomic Energy Agency (IAEA) regulations. Recovery coefficients, computed using PSF modeling and no post-reconstruction smoothing, were 130.3% (16mm), 147.1% (10mm), 87.2% (6mm), and 7.0% (3mm) for RCmax, which decreased to 91.1% (16mm), 90.6% (10mm), 53.2% (6mm), and 3.6% (3mm) for RCmean in the 22Na spheres. Comparatively, 18F sphere recovery was 110.7% (17mm), 123.6% (10mm), 106.5% (7mm), and 23.3% (3mm) for RCmax, which was reduced to 76.7% (17mm), 77.7% (10mm), 66.8% (7mm), and 13.5% (3mm), for RCmean. A standardized imaging phantom was developed for lesion quantification assessment in 18F-PSMA PET images. The phantom is configurable, providing users with the opportunity to modify background activity levels or sphere sizes according to clinical demands. Distributed to the community, the Q3P phantom has the potential to enable better assessment of lesion quantification and harmonization of 18F-PSMA PET imaging, which may lead to more robust predictive metrics and better outcome prediction in metastatic prostate cancer.

Strategies for deep learning-based attenuation and scatter correction of brain 18 F-FDG PET images in the image domain.

Attenuation and scatter correction is crucial for quantitative positron emission tomography (PET) imaging. Direct attenuation correction (AC) in the image domain using deep learning approaches has been recently proposed for combined PET/MR and standalone PET modalities lacking transmission scanning devices or anatomical imaging. In this study, different input settings were considered in the model training to investigate deep learning-based AC in the image space. Three different deep learning methods were developed for direct AC in the image space: (i) use of non-attenuation-corrected PET images as input (NonAC-PET), (ii) use of attenuation-corrected PET images with a simple two-class AC map (composed of soft-tissue and background air) obtained from NonAC-PET images (PET segmentation-based AC [SegAC-PET]), and (iii) use of both NonAC-PET and SegAC-PET images in a Double-Channel fashion to predict ground truth attenuation corrected PET images with Computed Tomography images (CTAC-PET). Since a simple two-class AC map (generated from NonAC-PET images) can easily be generated, this work assessed the added value of incorporating SegAC-PET images into direct AC in the image space. A 4-fold cross-validation scheme was adopted to train and evaluate the different models based using 80 brain 18 F-Fluorodeoxyglucose PET/CT images. The voxel-wise and region-wise accuracy of the models were examined via measuring the standardized uptake value (SUV) quantification bias in different regions of the brain. The overall root mean square error (RMSE) for the Double-Channel setting was 0.157±0.08 SUV in the whole brain region, while RMSEs of 0.214±0.07 and 0.189±0.14 SUV were observed in NonAC-PET and SegAC-PET models, respectively. A mean SUV bias of 0.01±0.26% was achieved by the Double-Channel model regarding the activity concentration in cerebellum region, as opposed to 0.08±0.28% and 0.05±0.28% SUV biases for the network that uniquely used NonAC-PET or SegAC-PET as input, respectively. SegAC-PET images with an SUV bias of -1.15±0.54%, served as a benchmark for clinically accepted errors. In general, the Double-Channel network, relying on both SegAC-PET and NonAC-PET images, outperformed the other AC models. Since the generation of two-class AC maps from non-AC PET images is straightforward, the current study investigated the potential added value of incorporating SegAC-PET images into a deep learning-based direct AC approach. Altogether, compared with models that use only NonAC-PET and SegAC-PET images, the Double-Channel deep learning network exhibited superior attenuation correction accuracy.

18F]SynVesT-1 and [18F]FDG quantitative PET imaging in the presurgical evaluation of MRI-negative children with focal cortical dysplasia type II.

MRI-negative children with focal cortical dysplasia type II (FCD II) are one of the most challenging cases in surgical epilepsy management. We aimed to utilize quantitative positron emission tomography (QPET) analysis to complement [18F]SynVesT-1 and [18F]FDG PET imaging and facilitate the localization of epileptogenic foci in pediatric MRI-negative FCD II patients. We prospectively enrolled 17 MRI-negative children with FCD II who underwent [18F]SynVesT-1 and [18F]FDG PET before surgical resection. The QPET scans were analyzed using statistical parametric mapping (SPM) with respect to healthy controls. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of [18F]SynVesT-1 PET, [18F]FDG PET, [18F]SynVesT-1 QPET, and [18F]FDG QPET in the localization of epileptogenic foci were assessed. Additionally, we developed a multivariate prediction model based on dual trace PET/QPET assessment. The AUC values of [18F]FDG PET and [18F]SynVesT-1 PET were 0.861 (sensitivity = 94.1%, specificity = 78.2%, PPV = 38.1%, NPV = 98.9%) and 0.908 (sensitivity = 82.4%, specificity = 99.2%, PPV = 93.3%, NPV = 97.5%), respectively. [18F]FDG QPET showed lower sensitivity (76.5%) and NPV (96.6%) but higher specificity (95.0%) and PPV (68.4%) than visual assessment, while [18F]SynVesT-1 QPET exhibited higher sensitivity (94.1%) and NPV (99.1%) but lower specificity (97.5%) and PPV (84.2%). The multivariate prediction model had the highest AUC value (AUC = 0.996, sensitivity = 100.0%, specificity = 96.6%, PPV = 81.0%, NPV = 100%). The multivariate prediction model based on [18F]SynVesT-1 and [18F]FDG PET/QPET assessments holds promise in noninvasively identifying epileptogenic regions in MRI-negative children with FCD II. Furthermore, the combination of visual assessment and QPET may improve the sensitivity and specificity of diagnostic tests in localizing epileptogenic foci and achieving a preferable surgical outcome in MRI-negative FCD II.

Two birds with one stone: human SIRPα nanobodies for functional modulation and in vivo imaging of myeloid cells.

Signal-regulatory protein α (SIRPα) expressed by myeloid cells is of particular interest for therapeutic strategies targeting the interaction between SIRPα and the "don't eat me" ligand CD47 and as a marker to monitor macrophage infiltration into tumor lesions. To address both approaches, we developed a set of novel human SIRPα (hSIRPα)-specific nanobodies (Nbs). We identified high-affinity Nbs targeting the hSIRPα/hCD47 interface, thereby enhancing antibody-dependent cellular phagocytosis. For non-invasive in vivo imaging, we chose S36 Nb as a non-modulating binder. By quantitative positron emission tomography in novel hSIRPα/hCD47 knock-in mice, we demonstrated the applicability of 64Cu-hSIRPα-S36 Nb to visualize tumor infiltration of myeloid cells. We envision that the hSIRPα-Nbs presented in this study have potential as versatile theranostic probes, including novel myeloid-specific checkpoint inhibitors for combinatorial treatment approaches and for in vivo stratification and monitoring of individual responses during cancer immunotherapies.

The clinical value of quantitative cardiovascular molecular imaging: a step towards precision medicine.

Cardiovascular diseases (CVD) are the leading cause of death worldwide and have an increasing impact on society. Precision medicine, in which optimal care is identified for an individual or a group of individuals rather than for the average population, might provide significant health benefits for this patient group and decrease CVD morbidity and mortality. Molecular imaging provides the opportunity to assess biological processes in individuals in addition to anatomical context provided by other imaging modalities and could prove to be essential in the implementation of precision medicine in CVD. New developments in single-photon emission computed tomography (SPECT) and positron emission tomography (PET) systems, combined with rapid innovations in promising and specific radiopharmaceuticals, provide an impressive improvement of diagnostic accuracy and therapy evaluation. This may result in improved health outcomes in CVD patients, thereby reducing societal impact. Furthermore, recent technical advances have led to new possibilities for accurate image quantification, dynamic imaging, and quantification of radiotracer kinetics. This potentially allows for better evaluation of disease activity over time and treatment response monitoring. However, the clinical implementation of these new methods has been slow. This review describes the recent advances in molecular imaging and the clinical value of quantitative PET and SPECT in various fields in cardiovascular molecular imaging, such as atherosclerosis, myocardial perfusion and ischemia, infiltrative cardiomyopathies, systemic vascular diseases, and infectious cardiovascular diseases. Moreover, the challenges that need to be overcome to achieve clinical translation are addressed, and future directions are provided.

Pre-acquired CT-based attenuation correction with automated headrest removal for a brain-dedicated PET system.

Attenuation correction (AC) is essential for quantitative positron emission tomography (PET) images. Attenuation coefficient maps (μ-maps) are usually generated from computed tomography (CT) images when PET-CT combined systems are used. If CT has been performed prior to PET imaging, pre-acquired CT can be used for brain PET AC, because the human head is almost rigid. This pre-acquired CT-based AC approach is suitable for stand-alone brain-dedicated PET, such as VRAIN (ATOX Co. Ltd., Tokyo, Japan). However, the headrest of PET is different from the headrest in pre-acquired CT images, which may degrade the PET image quality. In this study, we prepared three different types of μ-maps: (1) based on the pre-acquired CT, where namely the headrest is different from the PET system (μ-map-diffHr); (2) manually removing the headrest from the pre-acquired CT (μ-map-noHr); and (3) artificially replacing the headrest region with the headrest of the PET system (μ-map-sameHr). Phantom images by VRAIN using each μ-map were investigated for uniformity, noise, and quantitative accuracy. Consequently, only the uniformity of the images using μ-map-diffHr was out of the acceptance criteria. We then proposed an automated method for removing the headrest from pre-acquired CT images. In comparisons of standardized uptake values in nine major brain regions from the 18F-fluoro-2-deoxy-D-glucose-PET of 10 healthy volunteers, no significant differences were found between the μ-map-noHr and the μ-map-sameHr. In conclusion, pre-acquired CT-based AC with automated headrest removal is useful for brain-dedicated PET such as VRAIN.

Positron Emission Tomography Quantitative Assessment of Off-Target Whole-Body Biodistribution of I-124-Labeled Adeno-Associated Virus Capsids Administered to Cerebral Spinal Fluid.

Based on studies in experimental animals demonstrating that administration of adeno-associated virus (AAV) vectors to the cerebrospinal fluid (CSF) is an effective route to transfer genes to the nervous system, there are increasing number of clinical trials using the CSF route to treat nervous system disorders. With the knowledge that the CSF turns over four to five times daily, and evidence in experimental animals that at least some of CSF administered AAV vectors are distributed to systemic organs, we asked: with AAV administration to the CSF, what fraction of the total dose remains in the nervous system and what fraction goes off target and is delivered systemically? To quantify the biodistribution of AAV capsids immediately after administration, we covalently labeled AAV capsids with iodine 124 (I-124), a cyclotron generated positron emitter, enabling quantitative positron emission tomography scanning of capsid distribution for up to 96 h after AAV vector administration. We assessed the biodistribution to nonhuman primates of I-124-labeled capsids from different AAV clades, including 9 (clade F), rh.10 (E), PHP.eB (F), hu68 (F), and rh91(A). The analysis demonstrated that 60-90% of AAV vectors administered to the CSF through either the intracisternal or intrathecal (lumbar) routes distributed systemically to major organs. These observations have potentially significant clinical implications regarding accuracy of AAV vector dosing to the nervous system, evoking systemic immunity at levels similar to that with systemic administration, and potential toxicity of genes designed to treat nervous system disorders being expressed in non-nervous system organs. Based on these data, individuals in clinical trials using AAV vectors administered to the CSF should be monitored for systemic as well as nervous system adverse events and CNS dosing considerations should account for a significant AAV systemic distribution.

Radiomics for the detection of diffusely impaired myocardial perfusion: A proof-of-concept study using 13N-ammonia positron emission tomography

AimThe current proof-of-concept study investigates the value of radiomic features from normal 13N-ammonia positron emission tomography (PET) myocardial retention images to identify patients with reduced global myocardial flow reserve (MFR). MethodsData from 100 patients with normal retention 13N-ammonia PET scans were divided into two groups, according to global MFR (i.e., < 2 and ≥ 2), as derived from quantitative PET analysis. We extracted radiomic features from retention images at each of five different gray-level (GL) discretization (8, 16, 32, 64, and 128 bins). Outcome independent and dependent feature selection and subsequent univariate and multivariate analyses was performed to identify image features predicting reduced global MFR. ResultsA total of 475 radiomic features were extracted per patient. Outcome independent and dependent feature selection resulted in a remainder of 35 features. Discretization at 16 bins (GL16) yielded the highest number of significant predictors of reduced MFR and was chosen for the final analysis. GLRLM_GLNU was the most robust parameter and at a cut-off of 948 yielded an accuracy, sensitivity, specificity, negative and positive predictive value of 67%, 74%, 58%, 64%, and 69%, respectively, to detect diffusely impaired myocardial perfusion. ConclusionA single radiomic feature (GLRLM_GLNU) extracted from visually normal 13N-ammonia PET retention images independently predicts reduced global MFR with moderate accuracy. This concept could potentially be applied to other myocardial perfusion imaging modalities based purely on relative distribution patterns to allow for better detection of diffuse disease.

Imaging increased metabolism in the spinal cord in mice after middle cerebral artery occlusion

Emerging evidence indicates crosstalk between the brain and hematopoietic system following cerebral ischemia. Here, we investigated metabolism and oxygenation in the spleen and spinal cord in a transient middle cerebral artery occlusion (tMCAO) model. Sham-operated and tMCAO mice underwent [18F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) to assess glucose metabolism. Naïve, sham-operated and tMCAO mice underwent multispectral optoacoustic tomography (MSOT) assisted by quantitative model-based reconstruction and unmixing algorithms for accurate mapping of oxygenation patterns in peripheral tissues at 24 h after reperfusion. We found increased [18F]FDG uptake and reduced MSOT oxygen saturation, indicating hypoxia in the thoracic spinal cord of tMCAO mice compared with sham-operated mice but not in the spleen. Reduced spleen size was observed in tMCAO mice compared with sham-operated mice ex vivo. tMCAO led to an increase in the numbers of mature T cells in femoral bone marrow tissues, concomitant with a stark reduction in these cell subsets in the spleen and peripheral blood. The combination of quantitative PET and MSOT thus enabled observation of hypoxia and increased metabolic activity in the spinal cord of tMCAO mice at 24 h after occlusion compared to sham-operated mice.

List-Mode PET Image Reconstruction Using Deep Image Prior.

List-mode positron emission tomography (PET) image reconstruction is an important tool for PET scanners with many lines-of-response and additional information such as time-of-flight and depth-of-interaction. Deep learning is one possible solution to enhance the quality of PET image reconstruction. However, the application of deep learning techniques to list-mode PET image reconstruction has not been progressed because list data is a sequence of bit codes and unsuitable for processing by convolutional neural networks (CNN). In this study, we propose a novel list-mode PET image reconstruction method using an unsupervised CNN called deep image prior (DIP) which is the first trial to integrate list-mode PET image reconstruction and CNN. The proposed list-mode DIP reconstruction (LM-DIPRecon) method alternatively iterates the regularized list-mode dynamic row action maximum likelihood algorithm (LM-DRAMA) and magnetic resonance imaging conditioned DIP (MR-DIP) using an alternating direction method of multipliers. We evaluated LM-DIPRecon using both simulation and clinical data, and it achieved sharper images and better tradeoff curves between contrast and noise than the LM-DRAMA, MR-DIP and sinogram-based DIPRecon methods. These results indicated that the LM-DIPRecon is useful for quantitative PET imaging with limited events while keeping accurate raw data information. In addition, as list data has finer temporal information than dynamic sinograms, list-mode deep image prior reconstruction is expected to be useful for 4D PET imaging and motion correction.

Lesion Analysis in PERCIST 1.0: Clinical Ease versus Research Requisite-Where Does the Balance Exist?

Background Semiqualitative parameter SUVmax has been the most frequently used semiquantitative positron emission tomography (PET) parameter for response evaluation, but only metabolic activity of a single (most metabolic) lesion is predicted. Newer response parameters such as tumor lesion glycolysis (TLG) incorporating lesions' metabolic volume or whole-body metabolic tumor burden (MTBwb) are being explored for response evaluation. Evaluation and comparison of response with different semiquantitative PET parameters such as SUVmax and TLG in most metabolic lesion, multiple lesions (max of five), and MTBwb in advanced non-small cell lung cancer (NSCLC) patients were made. The different PET parameters were analyzed for response evaluation, overall survival (OS), and progression-free survival (PFS). Methods 18 F-FDG-PET/CT (18-fluorine-fluorodeoxyglucose positron emission tomography/computed tomography) imaging was performed in 23 patients (M = 14, F = 9, mean age = 57.6 years) with stage IIIB-IV advanced NSCLC before initiation of therapy with oral estimated glomerular filtration rate-tyrosine kinase inhibitor for early and late response evaluation. The quantitative PET parameters such as SUVmax and TLG were measured in single (most metabolic) lesion, multiple lesions, and MTBwb. The parameters SUVmax, TLG, and MTBwb were compared for early and late response evaluation and analyzed for OS and PFS Results No significant difference in change in response evaluation was seen in patients evaluated with most metabolic lesion, multiple lesions, or MTBwb. Difference in early (DC 22, NDC 1) and late (DC 20, NDC 3) response evaluation was seen that remained unchanged when lesions were measured in terms of number of lesions or the MTBwb. The early imaging was seen to be statistically significant to the OS compared with late imaging. Conclusions Single (most metabolic) lesion shows similar disease response and OS to multiple lesions and MTBwb. Response evaluation by late imaging offered no significant advantage compared with early imaging. Thus, early response evaluation with SUVmax parameter offers a good balance between clinical ease and research requisition.

Need for objective task-based evaluation of AI-based segmentation methods for quantitative PET.

Artificial intelligence (AI)-based methods are showing substantial promise in segmenting oncologic positron emission tomography (PET) images. For clinical translation of these methods, assessing their performance on clinically relevant tasks is important. However, these methods are typically evaluated using metrics that may not correlate with the task performance. One such widely used metric is the Dice score, a figure of merit that measures the spatial overlap between the estimated segmentation and a reference standard (e.g., manual segmentation). In this work, we investigated whether evaluating AI-based segmentation methods using Dice scores yields a similar interpretation as evaluation on the clinical tasks of quantifying metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of primary tumor from PET images of patients with non-small cell lung cancer. The investigation was conducted via a retrospective analysis with the ECOG-ACRIN 6668/RTOG 0235 multi-center clinical trial data. Specifically, we evaluated different structures of a commonly used AI-based segmentation method using both Dice scores and the accuracy in quantifying MTV/TLG. Our results show that evaluation using Dice scores can lead to findings that are inconsistent with evaluation using the task-based figure of merit. Thus, our study motivates the need for objective task-based evaluation of AI-based segmentation methods for quantitative PET.

Quantitative PET tracking of intra-articularly administered 89Zr-peptide-decorated nanoemulsions.

Intra-articular (IA) administration of drugs for the treatment of diseases such as rheumatoid arthritis, osteoarthritis and psoriatic arthritis is a common strategy; however, the rapid clearance from the synovial fluid restricts their effectivity due to the limited retention time. Drug Delivery Systems (DDS) are currently being developed to increase their joint retention time. This study compares the biodistribution and retention time of a senolytic peptide (PEP), with potential application in osteoarthritis disease, and this senolytic peptide encapsulated in a DDS based on a lipid nanoemulsion (PEPNE) by using positron emission tomography (PET) imaging. To this aim, the PEP was conjugated with a chelating agent (DFO) and radiolabeled with zirconium-89 (89Zr). Then, [89Zr]-PEP was encapsulated in a novel nanoemulsion formulation, composed by vitamin E, sphingomyelin, and a lipid-PEG. Afterward, healthy rats were administered with either the [89Zr]-PEP or the [89Zr]-PEP-NE via IA injection and underwent PET scans at 0.5-, 24-, 48-, 72-, 168-, 240- and 336h post-injection. To assess the biodistribution of both radiotracers, several volume-of-interest were manually drawn in different organs of the rat body and the %ID/organ was calculated. The [89Zr]-PEP was successfully encapsulated in the NE and their physicochemical properties were minimally affected by the radiolabeling buffer. Adequate stability of both [89Zr]-PEP and [89Zr]-PEP-NE was found in synovial fluid over 72h. Quantitative data from PET images revealed a significantly higher [89Zr]-PEP-NE retention in the injected knee than with [89Zr]-PEP in all follow-up PET scans. The [89Zr]-PEP %ID/organ values in the liver and kidney were significantly higher than those from [89Zr]-PEP-NE, which might indicate a faster elimination of the [89Zr]-PEP. Therefore, the study highlights the higher retention time on the target site of the [89Zr]-PEP-NE which may improve the therapeutic effects of the peptide. Thereby, the novel nanoemulsion formulation seems to be a successful DDS for IA injection. In addition, these results represent the first study that evaluates the distribution of a PET-guided DDS after its IA administration.

PET scatter estimation using deep learning U-Net architecture

Objective. Positron emission tomography (PET) image reconstruction needs to be corrected for scatter in order to produce quantitatively accurate images. Scatter correction is traditionally achieved by incorporating an estimated scatter sinogram into the forward model during image reconstruction. Existing scatter estimated methods compromise between accuracy and computing time. Nowadays scatter estimation is routinely performed using single scatter simulation (SSS), which does not accurately model multiple scatter and scatter from outside the field-of-view, leading to reduced qualitative and quantitative PET reconstructed image accuracy. On the other side, Monte-Carlo (MC) methods provide a high precision, but are computationally expensive and time-consuming, even with recent progress in MC acceleration. Approach. In this work we explore the potential of deep learning (DL) for accurate scatter correction in PET imaging, accounting for all scatter coincidences. We propose a network based on a U-Net convolutional neural network architecture with 5 convolutional layers. The network takes as input the emission and computed tomography (CT)-derived attenuation factor (AF) sinograms and returns the estimated scatter sinogram. The network training was performed using MC simulated PET datasets. Multiple anthropomorphic extended cardiac-torso phantoms of two different regions (lung and pelvis) were created, considering three different body sizes and different levels of statistics. In addition, two patient datasets were used to assess the performance of the method in clinical practice. Main results. Our experiments showed that the accuracy of our method, namely DL-based scatter estimation (DLSE), was independent of the anatomical region (lungs or pelvis). They also showed that the DLSE-corrected images were similar to that reconstructed from scatter-free data and more accurate than SSS-corrected images. Significance. The proposed method is able to estimate scatter sinograms from emission and attenuation data. It has shown a better accuracy than the SSS, while being faster than MC scatter estimation methods.