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Objective Long axial field-of-view (LAFOV) PET/CT showed improved performance resulting from higher sensitivity. The aim was to quantify the impact of using the full acceptance angle (UHS) in image reconstructions with the Biograph Vision Quadra LAFOV PET/CT (Siemens Healthineers) compared to the limited acceptance angle (high sensitivity mode, HS). Methods 38 oncological patients examined on a LAFOV Biograph Vision Quadra PET/CT were analysed. 15 patients underwent [18F]FDG-PET/CT, 15 patients underwent [18F]PSMA-1007 PET/CT, and 8 patients underwent [68Ga]Ga-DOTA-TOC PET/CT. Signal-to-noise ratio (SNR) and standardised uptake values (SUVmean/max/peak) were used to compare UHS and HS with different acquisition times. Results The SNR was significantly higher for UHS compared to HS over all acquisition times (SNR UHS/HS [18F]FDG: 1.35 ± 0.02, p 18F]PSMA-1007: 1.25 ± 0.02, p 68Ga]Ga-DOTA-TOC: 1.29 ± 0.02, p Conclusion UHS showed significantly higher SNR opening the possibility of halving short acquisition times. This is of advantage in further reduction of whole-body PET/CT acquisition.

Purpose Performing 2-[18F]FDG PET/CT in addition to a PSMA-ligand PET/CT can assist in the detection of lesions with low PSMA expression and may help in prognostication and identification of patients who likely benefit from PSMA-radioligand therapy (PSMA-RLT). However, the cost and time needed for a separate PET/CT examination might hinder its routine implementation. In this communication, we present our initial experiences with additional low-dose 2-[18F]FDG PET/CT as part of a dual-tracer and same-day imaging protocol which exploits the higher sensitivity exhibited by long-axial field-of-view (LAFOV) and total-body PET/CT systems and demonstrates its feasibility. Methods Fourteen patients referred for evaluation for PSMA-RLT received [68 Ga]Ga-PSMA-11 PET/CT at 1 h p.i. with a standard activity of 150 MBq and an additional low-dose 2-[18F]FDG PET/CT with 40 MBq 1 h thereafter using a long-axial field-of-view PET/CT system in a single sitting and as per institutional protocol. Scans were scrutinized by two experienced nuclear medicine physicians for mismatch findings. Results The combined protocol identified additional lesions with low or absent PSMA-expression but high FDG-avidity in 1/14 (7%) patients. The protocol was easily implemented and well tolerated by all patients. Conclusion Additional low-dose 2-[18F]FDG-PET/CT is feasible as part of a same-day imaging protocol and can help reveal lesions of low PSMA avidity as part of therapy assessment for [177Lu]-PSMA radioligand therapy and demonstrates higher sensitivity compared to [68 Ga]Ga-PSMA-11 PET/CT alone in some patients.

Background Accurate kinetic modeling of 18F-fluorodeoxyglucose ([18F]-FDG) positron emission tomography (PET) data requires accurate knowledge of the available tracer concentration in the plasma during the scan time, known as the arterial input function (AIF). The gold standard method to derive the AIF requires collection of serial arterial blood samples, but the introduction of long axial field of view (LAFOV) PET systems enables the use of non-invasive image-derived input functions (IDIFs) from large blood pools such as the aorta without any need for bed movement. However, such protocols require a prolonged dynamic PET acquisition, which is impractical in a busy clinical setting. Population-based input functions (PBIFs) have previously shown potential in accurate Patlak analysis of [18F]-FDG datasets and can enable the use of shortened dynamic imaging protocols. Here, we exploit the high sensitivity and temporal resolution of a LAFOV PET system and explore the use of PBIF with abbreviated protocols in [18F]-FDG total body kinetic modeling. Methods Dynamic PET data were acquired in 24 oncological subjects for 65 min following the administration of [18F]-FDG. IDIFs were extracted from the descending thoracic aorta, and a PBIF was generated from 16 datasets. Five different scaled PBIFs (sPBIFs) were generated by scaling the PBIF with the AUC of IDIF curve tails using various portions of image data (35–65, 40–65, 45–65, 50–65, and 55–65 min post-injection). The sPBIFs were compared with the IDIFs using the AUCs and Patlak Ki estimates in tumor lesions and cerebral gray matter. Patlak plot start time (t*) was also varied to evaluate the performance of shorter acquisitions on the accuracy of Patlak Ki estimates. Patlak Ki estimates with IDIF and t* = 35 min were used as reference, and mean bias and precision (standard deviation of bias) were calculated to assess the relative performance of different sPBIFs. A comparison of parametric images generated using IDIF and sPBIFs was also performed. Results There was no statistically significant difference between AUCs of the IDIF and sPBIFs (Wilcoxon test: P > 0.05). Excellent agreement was shown between Patlak Ki estimates obtained using sPBIF and IDIF. Using the sPBIF55–65 with the Patlak model, 20 min of PET data (i.e., 45 to 65 min post-injection) achieved Ki estimates in tumor lesions compared to the estimates with the IDIF. Parametric images reconstructed using the IDIF and sPBIFs with and without an abbreviated protocol were visually comparable. Using Patlak Ki generated with an IDIF and 30 min of PET data as reference, Patlak Ki images generated using sPBIF55–65 with 20 min of PET data (t* = 45 min) provided excellent image quality with structural similarity index measure > 0.99 and peak signal-to-noise ratio > 55 dB. Conclusion We demonstrate the feasibility of performing accurate [18F]-FDG Patlak analysis using sPBIFs with only 20 min of PET data from a LAFOV PET scanner.

Background: Accurate kinetic modelling of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) data requires accurate knowledge of the available tracer concentration in the plasma during the scan time, known as the arterial input function (AIF). The gold standard method to derive the AIF requires collection of serial arterial blood samples but the introduction of long axial field of view (LAFOV) PET systems enables use of non-invasive image derived input functions (IDIF) from large blood pools such as the aorta without any need for bed movement. However, such protocols require a prolonged dynamic PET acquisition which is impractical in a busy clinical setting. Population-based input functions (PBIF) have previously shown potential in accurate Patlak analysis of 18F-FDG datasets and can enable the use of shortened dynamic imaging protocols. We not exploit the high sensitivity and temporal resolution of a LAFOV PET system and explore use of PBIF with abbreviated protocols in 18F-FDG total body kinetic modelling. Methods: Dynamic PET data were acquired in 24 oncological subjects for 65 minutes following the administration of 18F-FDG. IDIFs were extracted from the descending thoracic aorta and a PBIF was generated from 16 datasets. Five different scaled PBIFs (sPBIF) were generated by scaling the PBIF with AUC of IDIF curve tails using various portions of image data (35-65, 40-65, 45-65, 50-65 and 55-65 min post injection). The sPBIFs were compared with the IDIFs using the AUCs and Patlak Ki estimates in tumour lesions and cerebral grey matter. Patlak plot start time (t*) was also varied to evaluate the performance of shorter acquisitions on accuracy of Patlak Ki estimates. Patlak Ki estimates with IDIF and t*=35 min was used as reference and mean bias and precision (standard deviation of bias) were calculated to assess relative performance of different sPBIFs. Comparison of parametric images generated using IDIF and sPBIFs was also performed. Results: There was no statistically significant difference between AUCs of the IDIF and sPBIFs (Wilcoxon test: P>0.05). The sPBIF55-65 showed the best performance with 1.5% bias and %6.8 precision in tumour lesions. Using the sPBIF55-65 with Patlak model, 20 minutes of PET data (i.e. 45 to 65 min post injection) achieved i estimates in tumour lesions compared to the estimates with the IDIF. Parametric images reconstructed using the IDIF and sPBIFs with and without an abbreviated protocol were visually comparable. Using Patlak Ki generated with an IDIF and 30 mins of PET data as reference, Patlak Ki images generated using sPBIF55-65 with 20 minutes of PET data (t*=45 min) provided excellent image quality with structural similarity index measure > 0.99 and peak signal-to-noise ratio > 55 dB. Conclusion: We demonstrate the feasibility of performing accurate 18F-FDG Patlak analysis using sPBIFs with only 20 minutes of PET data from a LAFOV PET scanner.

Background We aimed to compare coronary artery calcium scoring (CACS) with computed tomography (CT) with 80 and 120 kVp in a large patient population and to establish whether there is a difference in risk classification between the two scores. Methods Patients with suspected CAD undergoing MPS were included. All underwent standard CACS assessment with 120-kVp tube voltage and with 80 kVp. Two datasets (low-dose and standard) were generated and compared. Risk classes (0 to 25, 25 to 50, 50 to 75, 75 to 90, and > 90%) were recorded. Results 1511 patients were included (793 males, age 69 ± 9.1 years). There was a very good correlation between scores calculated with 120 and 80 kVp (R = 0.94, R2 = 0.88, P P = .03) and with CACS = 0 differed between the two protocols (n = 264 vs 437, P Conclusion In a large patient population, despite a good correlation between CACS calculated with standard and low-dose CT, there is a systematic underestimation of CACS with the low-dose protocol. This may have an impact especially on the prognostic value of the calcium score, and the established “power of zero” may no longer be warranted if CACS is assessed with low-dose CT.

The non-invasive quantification of the cerebral metabolic rate for glucose (CMRGlc) and the characterization of cerebral metabolism in the cerebrovascular territories are helpful in understanding ischemic cerebrovascular disease (ICVD). Firstly, we investigated a non-invasive quantification approach based on an image-derived input function (IDIF) in ICVD. Second, we studied the metabolic changes in CMRGlc after surgical intervention. We evaluated the hypothesis that the IDIF method based on the unilateral internal carotid artery could address challenges in ICVD quantification. The CMRGlc and standardized uptake value ratio (SUVR) were used to measure glucose metabolism activity. Healthy controls showed no significant differences in CMRGlc values between bilateral and unilateral IDIF measurements (intraclass correlation coefficient [ICC]: 0.91-0.98). Patients with ICVD showed significantly increased CMRGlc values after surgical intervention for all territories (percentage changes: 7.4%-22.5%). In contrast, SUVR showed minor differences between postoperative and preoperative patients, indicating that it was a poor biomarker for the diagnosis of ICVD. A significant association between CMRGlc and the National Institutes of Health Stroke Scale (NIHSS) scores was observed (r=-0.54). Our findings suggested that IDIF could be a valuable tool for CMRGlc quantification in patients with ICVD and may advance personalized precision interventions.

Purpose While acquisition of images in [68 Ga]Ga-PSMA-11 following longer uptake times can improve lesion uptake and contrast, resultant imaging quality and count statistics are limited by the isotope’s half-life (68 min). Here, we present a series of cases demonstrating that when performed using a long axial field-of-view (LAFOV) PET/CT system, late imaging is feasible and can even provide improved image quality compared to regular acquisitions. Methods In this retrospective case series, we report our initial experiences with 10 patients who underwent standard imaging at 1 h p.i. following administration of 192 ± 36 MBq [68 Ga]Ga-PSMA-11 with additional late imaging performed at 4 h p.i. Images were acquired in a single bed position for 6 min at 1 h p.i. and 16 min p.i. at 4 h p.i. using a LAFOV scanner (106 cm axial FOV). Two experienced nuclear medicine physicians reviewed all scans in consensus and evaluated overall image quality (5-point Likert scale), lesion uptake in terms of standardised uptake values (SUV), tumour to background ratio (TBR) and target-lesion signal to background noise (SNR). Results Subjective image quality as rated on a 5-point Likert scale was only modestly lower for late acquisitions (4.2/5 at 4 h p.i.; 5/5 1 h p.i.), TBR was significantly improved (4 h: 3.41 vs 1 h: 1.93, p p = 0.062) at later imaging. Images were obtained with total acquisition times comparable to routine examinations on standard axial FOV scanners. Conclusion Late acquisition in tandem with a LAFOV PET/CT resulted in improvements in TBR and SNR and was associated with only modest impairment in subjective visual imaging quality. These data show that later acquisition times for [68 Ga]Ga-PSMA-11 may be preferable when performed on LAFOV systems.

The novel 1,3,4,11b-tetrahydro-1H-fluoreno[9,1-cd]azepine framework, a structurally rigidified variant of the 1-phenylbenzazepine template, was synthesized via direct arylation as a key reaction. Evaluation of the binding affinities of the rigidified compounds across a battery of serotonin, dopamine, and adrenergic receptors indicates that this scaffold unexpectedly has minimal affinity for D1 and other dopamine receptors and is selective for the 5-HT6 receptor. The affinity of these systems at the 5-HT6 receptor is significantly influenced by electronic and hydrophobic interactions as well as the enhanced rigidity of the ligands. Molecular docking studies indicate that the reduced D1 receptor affinity of the rigidified compounds may be due in part to weaker H-bonding interactions between the oxygenated moieties on the compounds and specific receptor residues. Key receptor-ligand H-bonding interactions, salt bridges, and π-π interactions appear to be responsible for the 5-HT6 receptor affinity of the compounds. Compounds 10 (6,7-dimethoxy-2,3,4,11b-tetrahydro-1H-fluoreno[9,1-cd]azepine) and 12 (6,7-dimethoxy-2-methyl-2,3,4,11b-tetrahydro-1H-fluoreno[9,1-cd]azepine) have been identified as structurally novel, high affinity (Ki = 5 nM), selective 5-HT6 receptor ligands.

Purpose Attenuation correction is a critically important step in data correction in positron emission tomography (PET) image formation. The current standard method involves conversion of Hounsfield units from a computed tomography (CT) image to construct attenuation maps (µ-maps) at 511 keV. In this work, the increased sensitivity of long axial field-of-view (LAFOV) PET scanners was exploited to develop and evaluate a deep learning (DL) and joint reconstruction-based method to generate µ-maps utilizing background radiation from lutetium-based (LSO) scintillators. Methods Data from 18 subjects were used to train convolutional neural networks to enhance initial µ-maps generated using joint activity and attenuation reconstruction algorithm (MLACF) with transmission data from LSO background radiation acquired before and after the administration of 18F-fluorodeoxyglucose (18F-FDG) (µ-mapMLACF-PRE and µ-mapMLACF-POST respectively). The deep learning-enhanced µ-maps (µ-mapDL-MLACF-PRE and µ-mapDL-MLACF-POST) were compared against MLACF-derived and CT-based maps (µ-mapCT). The performance of the method was also evaluated by assessing PET images reconstructed using each µ-map and computing volume-of-interest based standard uptake value measurements and percentage relative mean error (rME) and relative mean absolute error (rMAE) relative to CT-based method. Results No statistically significant difference was observed in rME values for µ-mapDL-MLACF-PRE and µ-mapDL-MLACF-POST both in fat-based and water-based soft tissue as well as bones, suggesting that presence of the radiopharmaceutical activity in the body had negligible effects on the resulting µ-maps. The rMAE values µ-mapDL-MLACF-POST were reduced by a factor of 3.3 in average compared to the rMAE of µ-mapMLACF-POST. Similarly, the average rMAE values of PET images reconstructed using µ-mapDL-MLACF-POST (PETDL-MLACF-POST) were 2.6 times smaller than the average rMAE values of PET images reconstructed using µ-mapMLACF-POST. The mean absolute errors in SUV values of PETDL-MLACF-POST compared to PETCT were less than 5% in healthy organs, less than 7% in brain grey matter and 4.3% for all tumours combined. Conclusion We describe a deep learning-based method to accurately generate µ-maps from PET emission data and LSO background radiation, enabling CT-free attenuation and scatter correction in LAFOV PET scanners.

Purpose: Uncertain bone lesions (UBL) with intensive radiopharmaceutical avidity are frequently observed in patients undergoing [18F]PSMA-1007 PET/CT for the detection of prostate cancer (PC). Such lesions can pose diagnostic conundrums and risk an incorrect staging. The aim of this short communication is to share the results of PET-guided biopsies of such lesions. Methods: A retrospective analysis revealed 10 patients who were referred to our department for PET-guided biopsy of UBL visible in a previous [18F]PSMA-1007 PET/CT. [18F]-PSMA-1007 PET-guided biopsy was conducted for 11 PSMA-avid bone lesions in these 10 patients. The biopsy materials were analysed for tissue typing and immunohistochemistry (IHC) was performed for prostate-specific-membrane-antigen (PSMA) expression. The scans were analysed by two experienced physicians in a consensus read for clinical characteristics and radiopharmaceutical uptake of lesions. Results: 1/11 (9.1%) of the lesions biopsied was confirmed as bone metastasis of PC with intense PSMA-expression while 10/11 (90.9%) lesions were revealed to be unremarkable bone tissue without evidence of PSMA-expression at IHC. Amongst all bone lesions assessed by biopsy, eight were visually classified as being at high risk of malignancy in the PET/CT (SUVmean 12.0 ± 8.1; SUVmax 18.8 ± 13.1), three as equivocal (SUVmean 4.6 ± 2.1; SUVmax 7.2 ± 3.0) and zero as low risk. No UBL had any CT correlate. Conclusions: In this cohort biopsy revealed that a small but relevant number of UBL are true metastases. For those confirmed as benign, no PSMA-expression at IHC was observed, suggesting a non-PSMA mediated cause for intensive [18F]PSMA-1007-uptake of which the reason remains unclear. Readers must interpret such lesions with caution in order to reduce the risk of erroneous staging and subsequent treatment. PET-guided biopsy, particularly in the absence of morphological changes in the CT, can be a useful method to clarify such lesions.

Uncertain focal bone uptake (UBU) with intensive radiopharmaceutical avidity are frequently observed in patients undergoing [A retrospective analysis revealed 10 patients who were referred to our department for PET-guided biopsy of UBU visible in a previous [One out of 11 (9.1%) of the foci biopsied was confirmed as bone metastasis of PC with intense PSMA-expression, while 10/11 (90.9%) foci were revealed to be unremarkable bone tissue without evidence of PSMA expression at IHC. Amongst all bone foci assessed by biopsy, eight were visually classified as being at high risk of malignancy in the PET/CT (SUVmean 12.0 ± 8.1; SUVmax 18.8 ± 13.1), three as equivocal (SUVmean 4.6 ± 2.1; SUVmax 7.2 ± 3.0) and zero as low risk. No UBU had any CT correlate.This cohort biopsy revealed that a small but relevant number of UBU are true metastases. For those confirmed as benign, no PSMA expression at IHC was observed, suggesting a non-PSMA mediated cause for intensive [

The clinical presentations of early idiopathic Parkinson disease (IPD) substantially overlap with those of atypical parkinsonian syndromes such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). This study aimed to develop metabolic imaging indices based on deep learning to support the differential diagnosis of these conditions. Methods: A benchmark Huashan parkinsonian PET imaging (HPPI, China) database including 1,275 parkinsonian patients and 863 nonparkinsonian subjects with (18)F-FDG PET images was established to support artificial intelligence development. A 3-dimensional deep convolutional neural network was developed to extract deep metabolic imaging (DMI) indices and blindly evaluated in an independent cohort with longitudinal follow-up from the HPPI and an external German cohort of 90 parkinsonian patients with different imaging acquisition protocols. Results: The proposed DMI indices had less ambiguity space in the differential diagnosis. They achieved sensitivities of 98.1%, 88.5%, and 84.5%, and specificities of 90.0%, 99.2%, and 97.8%, respectively, for the diagnosis of IPD, MSA, and PSP in the blind-test cohort. In the German cohort, they resulted in sensitivities of 94.1%, 82.4%, and 82.1%, and specificities of 84.0%, 99.9%, and 94.1%, respectively. Using the PET scans independently achieved a performance comparable to the integration of demographic and clinical information into the DMI indices. Conclusion: The DMI indices developed on the HPPI database show the potential to provide an early and accurate differential diagnosis for parkinsonism and are robust when dealing with discrepancies between populations and imaging acquisitions.

Aim Despite increasing use for the detection of biochemically recurrent prostate cancer (rPC), the diagnostic accuracy of positron emission tomography/computed tomography (PET/CT) with [18F]PSMA-1007 remains only partially investigated. The aim of this study was to determine the sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) for PC-local recurrence and metastases on a per region basis. Materials and methods One hundred seventy-seven consecutive patients undergoing [18F]PSMA-1007 PET/CT for rPC were retrospectively analysed. Six body regions were defined: prostate fossa, pelvic lymph nodes (LN), retroperitoneal LN, supradiaphragmatic LN, bones, and soft tissue. A region was counted positive if at least one PSMA-positive lesion suspicious for PC was observed. Confirmation of a true-positive PSMA-avid lesion was defined as positive by histopathology, fall in serum prostate-specific antigen (PSA) (> 50%) after targeted therapy or confirmatory further CT, MRI, PET/CT, or bone scan imaging. Regions where additional imaging was able to confirm the absence of suspicious PC lesions or regions outside exclusively targeted RT with serum PSA decline (> 50%) were counted as true-negative regions. SE, SP, PPV, and NPV were calculated for all six regions. Results The overall PET-positivity rate was 91%. Conclusive follow-up for affirmation or refutation of a PSMA-positive lesion was available for 81/152 patients on a per region basis. In this subgroup, overall sensitivity, specificity, PPV, and NPV were 95% (CI: 0.90–0.98), 89% (CI: 0.83–0.93), 86% (0.80–0.90), and 96% (CI: 0.92–0.98), respectively. On a per region basis, PPV was 97% (CI: 0.83–0.99) for local recurrence, 93% (CI: 0.78–0.98) for pelvic LN, 87% (CI: 0.62–0.96) for retroperitoneal LN, 82% (CI: 0.52–0.95) for supradiaphragmatic LN, and 79% (0.65–0.89) for bone lesions. The number of solid organ metastases (n = 6) was too small for an accurate statistical analysis. Conclusion The known high PET-positivity rate of [18F]PSMA-1007 PET/CT in rPC was confirmed, with corresponding high (> 90%) sensitivity and NPV on a per region basis. However, overall PPV was limited (86%), particularly for bone lesions (79%), which are a potential diagnostic weaknesses when using this tracer.

PURPOSE Kinetic parameters from dynamic 18F-fluorodeoxyglucose (FDG) imaging offer complementary insights to the study of disease compared to static clinical imaging. However, dynamic imaging protocols are cumbersome due to the long acquisition time. Long axial field-of-view (LAFOV) PET scanners (>���70��cm) have two advantages for dynamic imaging over clinical PET scanners with a standard axial field-of-view (SAFOV; 16-30��cm). The large axial coverage enables multi-organ dynamic imaging in a single bed position, and the high sensitivity may enable clinically routine abbreviated dynamic imaging protocols. METHODS In this work, we studied two abbreviated protocols using data from a 65-min dynamic 18F-FDG scan: (A) dynamic imaging immediately post-injection (p.i.) for variable durations, and (B) dynamic imaging immediately p.i. for variable durations plus a 1-h p.i. (5-min-long) datapoint. Nine cancer patients were imaged on the Biograph Vision Quadra (Siemens Healthineers). Time-activity curves over the lesions (N���=���39) were fitted using the Patlak graphical analysis and a 2-tissue-compartment (2C, k4���=���0) model for variable scan durations (5-60��min). Kinetic parameters from the complete dataset served as the reference. Lesions from all cancers were grouped into low, medium, and high flux groups, and bias and precision of Ki (Patlak) and Ki, K1, k2, and k3 (2C) were calculated for each group. RESULTS Using only early dynamic data with the 2C (or Patlak) model, accurate quantification of Ki required at least 50 (or 55) min of dynamic data for low flux lesions, at least 30 (or 40) min for medium flux lesions, and at least 15 (or 20) min for high flux lesions to achieve both 10% bias and precision. The addition of the final (5-min) datapoint allowed for accurate quantification of Ki with a bias and precision of 10% using only 10-15��min of early dynamic data for either model. CONCLUSION Dynamic imaging for 10-15��min immediately p.i. followed by a 5-min scan at 1-h p.i can accurately and precisely quantify 18F-FDG on a long axial FOV scanner, potentially allowing for more widespread use of dynamic 18F-FDG imaging.

Kinetic parameters from dynamicIn this work, we studied two abbreviated protocols using data from a 65-min dynamicUsing only early dynamic data with the 2C (or Patlak) model, accurate quantification of KDynamic imaging for 10-15 min immediately p.i. followed by a 5-min scan at 1-h p.i can accurately and precisely quantify

Gene Model for the ortholog of Tsc1 in the Drosophila yakuba DyakCAF1 assembly (GCA_000005975.1).

Purpose: Non-invasive quantification of cerebral metabolic rate for glucose (CMRGlc) and characterizing cerebral metabolism of cerebrovascular territories are useful for the understanding of ischemic cerebrovascular disease (ICVD). Here, we proposed a non-invasive quantification approach based on image-derived input function (IDIF) suitable for ICVD patients and monitored the pathophysiological changes after surgical intervention.Methods: Sixteen healthy controls and 26 ischemic cerebrovascular disease patients with baseline and after surgical visits underwent 18F-FDG PET/MR imaging. The voxel-wise CMRGlc maps were derived via our proposed IDIF method. The CMRGlc and standardized uptake value ratio (SUVR) maps were subsequently used to extract quantitative values within 7 volumes of interest (gray matter, white matter, anterior, middle, and posterior cerebral artery, basilar artery, and cerebellar artery territory). Intraclass correlation coefficient (ICC) and absolute percentage error were employed to measure consistency in healthy controls. The quantitative differences of healthy controls and patients at baseline and after surgical visits were statistically analyzed. Results: For healthy controls, there were no significant differences for region CMRGlc values across bilateral and unilateral IDIF measurements (ICC: 0.91-0.98). Significant differences in CMRGlc were observed across the cohorts in all territories (P< 0.001). The CMRGlc values in the ipsilateral side were significantly increased after surgery intervention (P < 0.05) for all territories (percentage changes: 7.4%~22.5%). Only the posterior cerebral artery and basilar artery territories (-2.8% and 1.9%) were significant differences for SUVR (P < 0.05). The diagnostic ability of CMRGlc in various territories (area under curve: 0.923-0.966) was significantly higher than of SUVR. There was a significant association between CMRGlc with the national institutes of health stroke scores (r: -0.54, P = 0.0041).Conclusion: These observations suggested the non-invasive quantification approach based on IDIF allowed the individual metabolism measurement of cerebrovascular territories after surgery and identified the glucose pathology changes underlying territories.

The 1-phenylbenzazepine scaffold has yielded several D1R targeting ligands, but some gaps remain in our understanding of the structure-activity relationships in this scaffold. In particular, there is a paucity of studies that have investigated the effects of substituents at the C2' position of 1-phenylbenzazepines on their affinity and selectivity towards D1R. In this study, a set of methyl- and fluoro- C2'-substituted 1-phenylbenzazepines, with ring A catechol or 8-hydroxy-7-methoxy moieties in tandem with N-methyl or N-allyl substituent groups, was synthesized and evaluated for affinity at a subset of dopamine receptors - D1R, D2R and D5R. These studies indicate that an N-methyl group is generally preferred over N-unsubstituted or N-allyl groups for strong D1R affinity. In addition, it was revealed that compounds with a ring A 8-hydroxy-7-methoxy motif displayed stronger D1R affinity than analogous compounds with a ring A catechol moiety. Furthermore, the presence of a C2' substituent does not significantly impact D1R selectivity over D5R. However, for all analogs assessed, D1R selectivity over D2R was maintained. D1R vs D5R selectivity was generally poor or modest (less than 10-fold) among members of the series. A new high affinity selective D1R ligand - 10b (K

Purpose Alzheimer’s disease (AD) studies revealed that abnormal deposition of tau spreads in a specific spatial pattern, namely Braak stage. However, Braak staging is based on post mortem brains, each of which represents the cross section of the tau trajectory in disease progression, and numerous studies were reported that do not conform to that model. This study thus aimed to identify the tau trajectory and quantify the tau progression in a data-driven approach with the continuous latent space learned by variational autoencoder (VAE). Methods A total of 1080 [18F]Flortaucipir brain positron emission tomography (PET) images were collected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. VAE was built to compress the hidden features from tau images in latent space. Hierarchical agglomerative clustering and minimum spanning tree (MST) were applied to organize the features and calibrate them to the tau progression, thus deriving pseudo-time. The image-level tau trajectory was inferred by continuously sampling across the calibrated latent features. We assessed the pseudo-time with regard to tau standardized uptake value ratio (SUVr) in AD-vulnerable regions, amyloid deposit, glucose metabolism, cognitive scores, and clinical diagnosis. Results We identified four clusters that plausibly capture certain stages of AD and organized the clusters in the latent space. The inferred tau trajectory agreed with the Braak staging. According to the derived pseudo-time, tau first deposits in the parahippocampal and amygdala, and then spreads to the fusiform, inferior temporal lobe, and posterior cingulate. Prior to the regional tau deposition, amyloid accumulates first. Conclusion The spatiotemporal trajectory of tau progression inferred in this study was consistent with Braak staging. The profile of other biomarkers in disease progression agreed well with previous findings. We addressed that this approach additionally has the potential to quantify tau progression as a continuous variable by taking a whole-brain tau image into account.

Despite increasing use for the detection of biochemically recurrent prostate cancer (rPC), the diagnostic accuracy of positron emission tomography/computed tomography (PET/CT) with [One hundred seventy-seven consecutive patients undergoing [The overall PET-positivity rate was 91%. Conclusive follow-up for affirmation or refutation of a PSMA-positive lesion was available for 81/152 patients on a per region basis. In this subgroup, overall sensitivity, specificity, PPV, and NPV were 95% (CI: 0.90-0.98), 89% (CI: 0.83-0.93), 86% (0.80-0.90), and 96% (CI: 0.92-0.98), respectively. On a per region basis, PPV was 97% (CI: 0.83-0.99) for local recurrence, 93% (CI: 0.78-0.98) for pelvic LN, 87% (CI: 0.62-0.96) for retroperitoneal LN, 82% (CI: 0.52-0.95) for supradiaphragmatic LN, and 79% (0.65-0.89) for bone lesions. The number of solid organ metastases (n = 6) was too small for an accurate statistical analysis.The known high PET-positivity rate of [

This study aimed to explore the potential of a combination of 18F-fluorodeoxyglucose positron emission tomography (This study enrolled 377 patients with MCI and 94 healthy control participants from 2 medical centers. Enrolment was based on the patients' brain MRI and PET images. Radiomic analysis was performed to evaluate the predictive performance of dual-modalityThe C-indices for the two test datasets were 0.77 and 0.80 for dual-modalityThese results indicate the value of imaging features in monitoring the progress of MCI in populations at high risk of developing AD. However, the incremental benefit of combining

To investigate the kinetics ofTwenty-four oncological patients underwent dynamicWe report estimates of kinetic parameters and metabolic rate of glucose consumption (MRWe performed pharmacokinetic modelling of multiple organs using linear and non-linear models using dynamic total-body

Background: Predicting the risk of disease progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) has important clinical significance. This study aims at providing a personalized MCI-to-AD conversion prediction via radiomics-based predictive modeling (RPM) with multicentre 18F-Fluorodeoxyglucose positron emission tomography (FDG PET) data. Method: Three cohorts of 18F-FDG PET data and neuropsychological assessments were gathered from patients examined at Huashan Hospital (n=22), Xuanwu Hospital (n=80), and from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (n=355). Of these, amyloid images were selected for the ADNI and Xuanwu cohorts. First, 430 radiomic features were extracted from the 80 regions of interest (ROIs) for all PET images. These features were then concatenated for feature selection and an RPM model was constructed on the ADNI dataset. In addition, we used clinical scale data to establish a clinical Cox model, and a combined model for comparison. Afterwards, the images from Huashan Hospital were used to validate the stability and reliability of RPM, and the images from Xuanwu Hospital were used to explore the differences of biomarkers at different cognitive stages. Finally, correlation analysis was conducted between the radiomic biomarkers, neuropsychological assessments, and amyloid burden. Results: Experimental results show that the predictive performance of the PET-modal cox model was better than clinical cox model. In the two test data sets, the C index of PET model is 0.75 and 0.73, respectively; The C index of clinical model is 0.68. Moreover, most crucial image biomarkers had significant differences at different cognitive stages, and were significantly correlated with cognitive ability and the amyloid global level standardized uptake value ratio.Conclusion: The preliminary results demonstrated that the developed RPM approach has the potential to monitor the progress in high-risk populations with AD.

Predicting the risk of disease progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) has important clinical significance. This study aimed to provide a personalized MCI-to-AD conversion prediction via radiomics-based predictive modelling (RPM) with multicenter 18F-fluorodeoxyglucose positron emission tomography (FDG PET) data.FDG PET and neuropsychological data of 884 subjects were collected from Huashan Hospital, Xuanwu Hospital, and from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. First, 34,400 radiomic features were extracted from the 80 regions of interest (ROIs) for all PET images. These features were then concatenated for feature selection, and an RPM model was constructed and validated on the ADNI dataset. In addition, we used clinical data and the routine semiquantification index (standard uptake value ratio, SUVR) to establish clinical and SUVR Cox models for further comparison. FDG images from local hospitals were used to explore RPM performance in a separate cohort of individuals with healthy controls and different cognitive levels (a complete AD continuum). Finally, correlation analysis was conducted between the radiomic biomarkers and neuropsychological assessments.The experimental results showed that the predictive performance of the RPM Cox model was better than that of other Cox models. In the validation dataset, Harrell's consistency coefficient of the RPM model was 0.703 ± 0.002, while those of the clinical and SUVR models were 0.632 ± 0.006 and 0.683 ± 0.009, respectively. Moreover, most crucial imaging biomarkers were significantly different at different cognitive stages and significantly correlated with cognitive disease severity.The preliminary results demonstrated that the developed RPM approach has the potential to monitor progression in high-risk populations with AD.

Purpose Many radiotracers are currently available for the detection of recurrent prostate cancer (rPC), yet many have not been compared head-to-head in comparative imaging studies. There is therefore an unmet need for evidence synthesis to guide evidence-based decisions in the selection of radiotracers. The objective of this study was therefore to assess the detection rate of various radiotracers for the rPC. Methods The PUBMED, EMBASE, and the EU and NIH trials databases were searched without date or language restriction for comparative imaging tracers for 13 radiotracers of principal interest. Key search terms included 18F-PSMA-1007, 18F-DCPFyl, 68Ga-PSMA-11, 18F-PSMA-11, 68Ga-PSMA-I&T, 68Ga-THP-PSMA, 64Cu-PSMA-617, 18F-JK-PSMA-7, 18F-Fluciclovine, 18F-FABC, 18F-Choline, 11C-Choline, and 68Ga-RM2. Studies reporting comparative imaging data in humans in rPC were selected. Single armed studies and matched pair analyses were excluded. Twelve studies with eight radiotracers were eligible for inclusion. Two independent reviewers screened all studies (using the PRISMA-NMA statement) for inclusion criteria, extracted data, and assessed risk of bias (using the QUADAS-2 tool). A network meta-analysis was performed using Markov-Chain Monte Carlo Bayesian analysis to obtain estimated detection rate odds ratios for each tracer combination. Results A majority of studies were judged to be at risk of publication bias. With the exception of 18F-PSMA-1007, little difference in terms of detection rate was revealed between the three most commonly used PSMA-radiotracers (68Ga-PSMA-11, 18F-PSMA-1007, 18F-DCFPyl), which in turn showed clear superiority to choline and fluciclovine using the derived network. Conclusion Differences in patient-level detection rates were observed between PSMA- and choline-radiotracers. However, there is currently insufficient evidence to favour one of the four routinely used PSMA-radioligands (PSMA-11, PSMA-1007, PSMA-I&T, and DCFPyl) over another owing to the limited evidence base and risk of publication bias revealed by our systematic review. A further limitation was lack of reporting on diagnostic accuracy, which might favour radiotracers with low specificity in an analysis restricted only to detection rate. The NMA derived can be used to inform the design of future clinical trials and highlight areas where current evidence is weak.

PURPOSE Digital PET/CT scanners represent a significant step forward in molecular imaging. We report here the clinical impact of digital PET in PSMA-PET/CT. METHODS In this retrospective study, 88 consecutive patients who underwent [68Ga]Ga-PSMA-11 PET/CT on a digital PET/CT (dPET/CT) scanner for recurrent prostate cancer (PC) were included in a first cohort. In a second step, 88 individuals who underwent an analogue [68Ga]Ga-PSMA-11 PET/CT (aPET/CT) were selected after they were matched to the first cohort for clinical parameters. Following consensus read by two nuclear medicine physicians, the number and type of PC lesions as well as benign, PSMA-positive lesions were recorded. The results were complemented by extensive [68Ga]Ga phantom measurements to determine imaging characteristics of both scanners. RESULTS dPET/CT revealed a greater number of PC lesions compared to aPET/CT (326 versus 142) as well as a proportional increase in benign causes of tracer-uptake (144 versus 65). A greater number of scans were noted as pathological for PC on dPET/CT (74/88) compared to aPET/CT (64/88, p < 0.05). The PSMA positivity rate for PC was significantly higher in dPET/CT for the lowest PSA values (PSA < 2.0 ng/ml, p < 0.05). CONCLUSION dPET/CT detected more PC lesions compared to aPET/CT. A significantly higher rate of pathological PET/CTs was noted in the group with the lowest PSA values. A higher number of benign PSMA-positive lesions were also noted in dPET/CT. The differences could be plausibly explained by the measured imaging characteristics of the scanners.

Die Positronenemissionstomographie/Computertomographie (PET/CT) mit Liganden des Prostataspezifischen Membranantigens (PSMA) und die PSMA-Therapie haben sich seit ihrer klinischen Einfuhrung in 2011 weltweit rasant ausgebreitet. Aktuelle Erkenntnisse sowohl uber die PSMA-PET/CT als auch uber die PSMA-Therapie werden zusammengefasst. Erkenntnisse aus der Literatur und Erfahrungen der Autoren wurden zusammengetragen. Es zeigt sich eine sehr hohe Sensitivitat und Spezifitat der PSMA-PET/CT sowohl beim Rezidivprostatakarzinom (‑PC) als auch beim Primarstaging des PC mit mittlerem und hohem Risikoprofil. Die Ergebnisse der PSMA-Therapie als Drittlinientherapie bei Patienten mit metastasiertem, kastrationsresistentem PC sind vielversprechend. Die PSMA-PET/CT hat sich mittlerweile als Goldstandard in der Diagnostik des Rezidiv-PC etabliert und ist dabei, dieselbe Rolle auch beim Primarstaging des PC mit mittlerem und hohem Risikoprofil zu ubernehmen. Die PSMA-Therapie wird in einer stets wachsenden Zahl an Zentren als Drittlinientherapie bei metastasiertem, kastrationsresistentem PC routinemasig durchgefuhrt.

PURPOSE Dual-time point PET/CT scanning with [68Ga]Ga-PSMA-11 in the diagnosis of prostate cancer (PC) has been advanced as a method to increase detection of PC lesions, particularly at early stages of biochemical recurrence and as a potential means to aid the discrimination between benign and pathological prostate-specific membrane antigen (PSMA) uptake. However, the assumption that all PC lesions uniformly exhibit increasing tracer uptake at delayed imaging has not yet been investigated, which this present study aims to address. METHODS One hundred consecutive patients with biochemically recurrent PC who received standard and late [68Ga]Ga-PSMA-11 PET/CT (by local protocol at 1.5 h "standard" and 2.5 h p.i. "late") underwent retrospective evaluation. All lesions with a tracer uptake above local background were analysed with regard to their maximum standardised uptake values at standard and late images (SUVmax) and characterised according to their morphological characteristics. RESULTS Seventy-nine of 100 patients had PSMA-positive scans, in whom a total of 185 individual PSMA-positive lesions were identified. These were morphologically characterised as bone lesions (n = 48), solid organ lesions (n = 3), lymph node (LN) lesions (n = 78) and locally recurrent lesions in the prostatic fossa or seminal vesicles (n = 56). The relative uptake between standard and late imaging was considered; all lesions classified as local recurrence presented with increasing (86%) or stable patterns of tracer uptake (14%). In contrast, only 58% of bone lesions exhibited increasing tracer uptake, with 21% exhibiting a stable pattern and 21% exhibiting a decreasing tracer uptake at late imaging. CONCLUSION A heterogeneous pattern of dynamic tracer uptake was observed, with a largely increasing pattern observed for locally recurrent lesions and lymph nodes and a significant proportion of bone lesions exhibiting decreasing tracer uptake. The results are of significance not only in the imaging and identification of PC lesions, but they also have implications for PSMA-directed ligand therapy.

PURPOSE So far, there have been very few studies which provide a direct comparison between MRI and PSMA-ligand PET/CT for the detection of recurrent prostate cancer (rPC). This present study therefore aims to provide further clinical data in order to resolve this urgent clinical question, and thereby strengthen clinical recommendations. METHODS A retrospective analysis was performed for patients who were scanned at our institution with whole-body PSMA-PET/CT (tracer: 68Ga-PSMA-11) between January 2017 and September 2018 in order to detect rPC. Amongst them, 43 underwent an additional pelvic MRI within 2 months. Both modalities were compared as follows: a consensus read of the PET data was performed by two nuclear physicians. All lesions were recorded with respect to their type and localization. The same process was conducted by two radiologists for pelvic MRI. Thereafter, both modalities were directly compared for every patient and lesion. RESULTS Overall, 30/43 patients (69.8%) presented with a pathologic MRI and 38/43 (88.4%) with a pathologic PSMA-PET/CT of the pelvis. MRI detected 53 pelvic rPC lesions (13 of them classified as "uncertain") and PSMA-PET/CT detected 75 pelvic lesions (three classified as "uncertain"). The superiority of PSMA-PET/CT was statistically significant only if uncertain lesions were classified as false-positive. CONCLUSIONS PSMA-PET/CT detected more pelvic lesions characteristic for rPC when compared to MRI. In order to detect rPC, a potential future scenario could be conducting first a PSMA-PET/CT. Combining the advantages of both modalities in hybrid PET/MRI scanners would be an ideal future scenario.

Abstract Purpose A critical bottleneck for the credibility of artificial intelligence (AI) is replicating the results in the diversity of clinical practice. We aimed to develop an AI that can be independently applied to recover high-quality imaging from low-dose scans on different scanners and tracers. Methods Brain [18F]FDG PET imaging of 237 patients scanned with one scanner was used for the development of AI technology. The developed algorithm was then tested on [18F]FDG PET images of 45 patients scanned with three different scanners, [18F]FET PET images of 18 patients scanned with two different scanners, as well as [18F]Florbetapir images of 10 patients. A conditional generative adversarial network (GAN) was customized for cross-scanner and cross-tracer optimization. Three nuclear medicine physicians independently assessed the utility of the results in a clinical setting. Results The improvement achieved by AI recovery significantly correlated with the baseline image quality indicated by structural similarity index measurement (SSIM) (r = −0.71, p < 0.05) and normalized dose acquisition (r = −0.60, p < 0.05). Our cross-scanner and cross-tracer AI methodology showed utility based on both physical and clinical image assessment (p < 0.05). Conclusion The deep learning development for extensible application on unknown scanners and tracers may improve the trustworthiness and clinical acceptability of AI-based dose reduction.

Objective The purpose of the study was to investigate the potential added value of 18F-FDG-PET/MRI (functional information derived from PET) over standard diagnostic liver MRI (excellent soft tissue characterization) in diagnosing and staging suspected primary hepatobiliary malignancies including extrahepatic cholangiocarcinoma (ECC), intrahepatic cholangiocellular carcinoma (ICC) and gallbladder cancer (GBCA). Methods Twenty consecutive patients with suspected hepatobiliary malignancy were included in this retrospective study. All patients underwent combined whole-body (WB) 18F-FDG-PET/MRI including contrast-enhanced MRI of the liver, contrast-enhanced WB-MRI and WB 18F-FDG-PET. Two experienced readers staged hepatobiliary disease using TNM criteria: first based on MRI alone and then based on combined 18F-FDG-PET/MRI. Subsequently, the impact of FDG-PET/MRI on clinical management compared to MRI alone was recorded. Histopathologic proof served as the reference standard. Results Hepatobiliary neoplasms were present in 16/20 patients (ECC n = 3, ICC n = 8, GBCA n = 5), two patients revealed benign disease, two were excluded. TNM staging with 18F-FDG-PET/MRI was identical to MRI alone in 11/18 (61.1 %) patients and correctly changed the stage in 4/18 (22.2 %), resulting in a change in management for 2/4 patients (11.1 %). 18F-FDG-PET/MRI was false-positive in 3/18 cases (16.7 %). Both MRI and 18F-FDG-PET/MRI were falsely positive in 1 case without malignancy. Conclusions A small incremental benefit of 18F-FDG-PET/MRI over standard MRI of the liver was observed. However, in some cases 18F-FDG-PET/MRI may lead to false-positive findings. Overall there is seemingly limited role of 18F-FDG-PET/MRI in patients with suspected hepatobiliary malignancy.