Detection of individual brain tau deposition in Alzheimer's disease based on latent feature-enhanced generative adversarial network.

OBJECTIVE: The conventional methods for interpreting tau PET imaging in Alzheimer's disease (AD), including visual assessment and semi-quantitative analysis of fixed hallmark regions, are insensitive to detect individual small lesions because of the spatiotemporal neuropathology's heterogeneity. In this study, we proposed a latent feature-enhanced generative adversarial network model for the automatic extraction of individual brain tau deposition regions. METHODS: The latent feature-enhanced generative adversarial network we propose can learn the distribution characteristics of tau PET images of cognitively normal individuals and output the abnormal distribution regions of patients. This model was trained and validated using 1131 tau PET images from multiple centres (with distinct races, i.e., Caucasian and Mongoloid) with different tau PET ligands. The overall quality of synthetic imaging was evaluated using structural similarity (SSIM), peak signal to noise ratio (PSNR), and mean square error (MSE). The model was compared to the fixed templates method for diagnosing and predicting AD. RESULTS: The reconstructed images archived good quality, with SSIM = 0.967 ± 0.008, PSNR = 31.377 ± 3.633, and MSE = 0.0011 ± 0.0007 in the independent test set. The model showed higher classification accuracy (AUC = 0.843, 95 % CI = 0.796-0.890) and stronger correlation with clinical scales (r = 0.508, P < 0.0001). The model also achieved superior predictive performance in the survival analysis of cognitive decline, with a higher hazard ratio: 3.662, P < 0.001. INTERPRETATION: The LFGAN4Tau model presents a promising new approach for more accurate detection of individualized tau deposition. Its robustness across tracers and races makes it a potentially reliable diagnostic tool for AD in practice.

FDG imaging with long-axial field-of-view PET/CT in patients with high blood glucose-a matched pair analysis.

PURPOSE: High blood glucose (hBG) in patients undergoing [18F]FDG PET/CT scans often results in rescheduling the examination, which may lead to clinical delay for the patient and decrease productivity for the department. The aim of this study was to evaluate whether long-axial field-of-view (LAFOV) PET/CT can minimize the effect of altered bio-distribution in hBG patients and is able to provide diagnostic image quality in hBG situations. MATERIALS AND METHODS: Oncologic patients with elevated blood glucose (≥ 8.0 mmol/l) and normal blood glucose (< 8.0 mmol/l, nBG) levels were matched for tumor entity, gender, age, and BMI. hBG patients were further subdivided into two groups (BG 8-11 mmol/l and BG > 11 mmol/l). Tracer uptake in the liver, muscle, and tumor was evaluated. Furthermore, image quality was compared between long acquisitions (ultra-high sensitivity mode, 360 s) on a LAFOV PET/CT and routine acquisitions equivalent to a short-axial field-of-view scanner (simulated (sSAFOV), obtained with high sensitivity mode, 120 s). Tumor-to-background ratio (TBR) and contrast-to-noise ratio (CNR) were used as the main image quality criteria. RESULTS: Thirty-one hBG patients met the inclusion criteria and were matched with 31 nBG patients. Overall, liver uptake was significantly higher in hBG patients (SUVmean, 3.07 ± 0.41 vs. 2.37 ± 0.33; p = 0.03), and brain uptake was significantly lower (SUVmax, 7.58 ± 0.74 vs. 13.38 ± 3.94; p < 0.001), whereas muscle (shoulder/gluteal) uptake showed no statistically significant difference. Tumor uptake was lower in hBG patients, resulting in a significantly lower TBR in the hBG cohort (3.48 ± 0.74 vs. 5.29 ± 1.48, p < 0.001). CNR was higher in nBG compared to hBG patients (12.17 ± 4.86 vs. 23.31 ± 12.22, p < 0.001). However, subgroup analysis of nBG 8-11 mmol/l on sSAFOV PET/CT compared to hBG (> 11 mmol/l) patients examined with LAFOV PET/CT showed no statistical significant difference in CNR (19.84 ± 8.40 vs. 17.79 ± 9.3, p = 0.08). CONCLUSION: While elevated blood glucose (> 11 mmol) negatively affected TBR and CNR in our cohort, the images from a LAFOV PET-scanner had comparable CNR to PET-images acquired from nBG patients using sSAFOV PET/CT. Therefore, we argue that oncologic patients with increased blood sugar levels might be imaged safely with LAFOV PET/CT when rescheduling is not feasible.

The clinical acceptability of short versus long duration acquisitions for head and neck cancer using long-axial field-of-view PET/CT: a retrospective evaluation.

PURPOSE: To evaluate the utility of long duration (10 min) acquisitions compared to standard 4 min scans in the evaluation of head and neck cancer (HNC) using a long-axial field-of-view (LAFOV) system in 2-[18F]FDG PET/CT. METHODS: HNC patients undergoing LAFOV PET/CT were included retrospectively according to a predefined sample size calculation. For each acquisition, FDG avid lymph nodes (LN) which were highly probable or equivocal for malignancy were identified by two board certified nuclear medicine physicians in consensus. The aim of this study was to establish the clinical acceptability of short-duration (4 min, C40%) acquisitions compared to full-count (10 min, C100%) in terms of the detection of LN metastases in HNC. Secondary endpoints were the positive predictive value for LN status (PPV) and comparison of SUVmax at C40% and C100%. Histology reports or confirmatory imaging were the reference standard. RESULTS: A total of 1218 records were screened and target recruitment was met with n = 64 HNC patients undergoing LAFOV. Median age was 65 years (IQR: 59-73). At C40%, a total of 387 lesions were detected (highly probable LN n = 274 and equivocal n = 113. The total number of lesions detected at C100% acquisition was 439, of them 291 (66%) highly probable LN and 148 (34%) equivocal. Detection rate between the two acquisitions did not demonstrate any significant differences (Pearson's Chi-Square test, p = 0.792). Sensitivity, specificity, PPV, NPV and accuracy for C40% were 83%, 44%, 55%, 76% and 36%, whilst for C100% were 85%, 56%, 55%, 85% and 43%, respectively. The improved accuracy reached borderline significance (p = 0.057). At the ROC analysis, lower SUVmax was identified for C100% (3.5) compared to C40% (4.5). CONCLUSION: In terms of LN detection, C40% acquisitions showed no significant difference compared to the C100% acquisitions. There was some improvement for lesions detection at C100%, with a small increment in accuracy reaching borderline significance, suggestive that the higher sensitivity afforded by LAFOV might translate to improved clinical performance in some patients.

Long-axial field-of-view PET/CT for the assessment of inflammation in calcified coronary artery plaques with [68 Ga]Ga-DOTA-TOC.

PURPOSE: Inflamed, prone-to-rupture coronary plaques are an important cause of myocardial infarction and their early identification is crucial. Atherosclerotic plaques are characterized by overexpression of the type-2 somatostatin receptor (SST2) in activated macrophages. SST2 ligand imaging (e.g. with [68 Ga]Ga-DOTA-TOC) has shown promise in detecting and quantifying the inflammatory activity within atherosclerotic plaques. However, the sensitivity of standard axial field of view (SAFOV) PET scanners may be suboptimal for imaging coronary arteries. Long-axial field of view (LAFOV) PET/CT scanners may help overcome this limitation. We aim to assess the ability of [68 Ga]Ga-DOTA-TOC LAFOV-PET/CT in detecting calcified, SST2 overexpressing coronary artery plaques. METHODS: In this retrospective study, 108 oncological patients underwent [68 Ga]Ga-DOTA-TOC PET/CT on a LAFOV system. [68 Ga]Ga-DOTA-TOC uptake and calcifications in the coronary arteries were evaluated visually and semi-quantitatively. Data on patients' cardiac risk factors and coronary artery calcium score were also collected. Patients were followed up for 21.5 ± 3.4 months. RESULTS: A total of 66 patients (61.1%) presented with calcified coronary artery plaques. Of these, 32 patients had increased [68 Ga]Ga-DOTA-TOC uptake in at least one coronary vessel (TBR: 1.65 ± 0.53). Patients with single-vessel calcifications showed statistically significantly lower uptake (SUVmax 1.10 ± 0.28) compared to patients with two- (SUVmax 1.31 ± 0.29, p < 0.01) or three-vessel calcifications (SUVmax 1.24 ± 0.33, p < 0.01). There was a correlation between coronary artery calcium score (CACS) and [68 Ga]Ga-DOTA-TOC uptake, especially in the LAD (p = 0.02). Stroke and all-cause death occurred more frequently in patients with increased [68 Ga]Ga-DOTA-TOC uptake (15.63% vs. 0%; p:0.001 and 21.88% vs. 6.58%; p: 0.04, respectively) during the follow-up period. CONCLUSION: [68 Ga]Ga-DOTA-TOC as a marker for the macrophage activity can reveal unknown cases of inflamed calcified coronary artery plaques using a LAFOV PET system. [68 Ga]Ga-DOTA-TOC uptake increased with the degree of calcification and correlated with higher risk of stroke and all-cause death. [68 Ga]Ga-DOTA-TOC LAFOV PET/CT may be useful to assess patients' cardiovascular risk.

Combined [68 Ga]Ga-PSMA-11 and low-dose 2-[18F]FDG PET/CT using a long-axial field of view scanner for patients referred for [177Lu]-PSMA-radioligand therapy.

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.

New thresholds in semi-quantitative [18F]FDG PET/CT are needed to assess large vessel vasculitis with long-axial field-of-view scanners.

AIM: [18F]FDG PET/CT proved accurate in the diagnostic work-up of large vessel vasculitis (LVV). While a visual interpretation is currently considered adequate, several attempts have been made to integrate it with a semiquantitative evaluation. In this regard, there is the need to validate current or new thresholds for the semiquantitative parameters on long-axial field of view (LAFOV) scanners. METHODS: We retrospectively evaluated 100 patients (50 with LVV and 50 controls) who underwent [18F]FDG LAFOV PET/CT. Semiquantitative parameters (SUVmax and SUVmean) were calculated for large vessels in 3 districts (supra-aortic [SA], thoracic aorta [TA], and infra-aortic [IA]). Values were also normalized to liver activity (SUVmax/L-SUVmax, and SUVmax/L-SUVmean). RESULTS: Of the 50 patients diagnosed with LVV, SA vessels were affected in 38 (76%), TA in 42 (84%) and IA vessels in 26 (52%). To-liver normalized values had higher diagnostic accuracy than non-normalized values (AUC always ≥ 0.90 vs. 0.74-0.89). For the SA vessels, best thresholds were 0.66 for SUVmax/L-SUVmax and 0.88 for SUVmax/L-SUVmean; for the TA, 1.0 for SUVmax/L-SUVmax and 1.30 for SUVmax/L-SUVmean; finally, for IA vessels, the best threshold was 0.83 for SUVmax/L-SUVmax and 1.11 for SUVmax/L-SUVmean. CONCLUSION: LAFOV [18F]FDG-PET/CT is accurate in the diagnostic workup of LVV, but different threshold in semi-quantitative parameters than reported in literature for standard scanners should be considered.

Feasibility of using abbreviated scan protocols with population-based input functions for accurate kinetic modeling of [18F]-FDG datasets from a long axial FOV PET scanner.

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 < 15% precision error in 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.

The diagnostic accuracy of radiolabeled PSMA-ligand PET for tumour staging in newly diagnosed prostate cancer patients compared to histopathology: a systematic review and meta-analysis.

PURPOSE: The current clinical recommendations posit the deployment of specific approved radiolabeled prostate-specific membrane antigen-ligand positron emission tomography (PSMA PET) for detecting metastatic prostate cancer during primary staging. Nevertheless, the precise efficacy of such ligands in localizing intraprostatic tumours (index tumour) and T-staging is not well established. Consequently, the objective of this inquiry is to ascertain the diagnostic accuracy of PSMA-PET in the tumour staging of newly diagnosed prostate cancer by means of a meta-analysis that integrates studies utilizing histological confirmation as the reference standard. METHODS: In this study, we conducted a systematic literature search of the PubMed, Embase, Web of Science, and Cochrane Library databases using a predefined collection of search terms. These terms included 'PSMA PET', 'primary staging', and 'prostate cancer'. Subsequently, two independent reviewers evaluated all the studies based on predetermined inclusion criteria, extracted pertinent data, and assessed the quality of evidence. Any disparities were resolved by a third reviewer. A random effects Sidik-Jonkman model was applied to conduct a meta-analysis and estimate the diagnostic accuracy on a per-patient basis, along with 95% confidence intervals. Moreover, an appraisal regarding the likelihood of publication bias and the impact of small-study effects was performed utilizing both Egger's test and a graphical examination of the funnel plot. RESULTS: The present analysis comprised a total of twenty-three scientific papers encompassing 969 patients and involved their analysis by both qualitative and quantitative approaches. The results of this study demonstrated that the estimated diagnostic accuracy of PSMA PET/CT and PSMA PET/MRI, for the detection of intraprostatic tumours, regardless of the type of PSMA-ligand, was 86% (95% CI: 76-96%) and 97% (95% CI: 94-100%), respectively. Furthermore, the diagnostic accuracy for the detection of extraprostatic extension (EPE) was 73% (95% CI: 64-82%) and 77% (95% CI: 69-85%), while the diagnostic accuracy for the detection of seminal vesicle involvement (SVI) was 87% (95% CI: 80-93) and 90% (95% CI: 82-99%), respectively. CONCLUSION: The present investigation has demonstrated that PSMA PET/MRI surpasses currently recommended multiparametric magnetic resonance imaging (mpMRI) in terms of diagnostic accuracy as inferred from a notable data trajectory, whereas PSMA-PET/CT exhibited comparable diagnostic accuracy for intraprostatic tumour detection and T-staging compared to mpMRI. Nevertheless, the analysis has identified certain potential limitations, such as small-study effects and a potential for publication bias, which may impact the overall conclusions drawn from this study.

Low-dose coronary artery calcium scoring compared to the standard protocol.

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 < .001), with Bland-Altman limits of agreement of - 563.5 to 871.9 and a bias of - 154.2. The proportion of patients assigned to the < 25% percentile class (P = .03) and with CACS = 0 differed between the two protocols (n = 264 vs 437, P < .001). 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.

Diagnostic accuracy of [18F]PSMA-1007 PET/CT in biochemical recurrence of prostate cancer.

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.

Assessment of malignancy and PSMA expression of uncertain bone foci in [18F]PSMA-1007 PET/CT for prostate cancer-a single-centre experience of PET-guided biopsies.

PURPOSE: Uncertain focal bone uptake (UBU) with intensive radiopharmaceutical avidity are frequently observed in patients undergoing [18F]PSMA-1007 PET/CT for the detection of prostate cancer (PC). Such foci can pose diagnostic conundrums and risk incorrect staging. The aim of this short communication is to share the results of PET-guided biopsies of such foci. METHODS: A retrospective analysis revealed 10 patients who were referred to our department for PET-guided biopsy of UBU visible in a previous [18F]PSMA-1007 PET/CT. [18F]-PSMA-1007 PET-guided biopsy was conducted for 11 PSMA-avid bone foci 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 foci. RESULTS: 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. CONCLUSIONS: 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 [18F]PSMA-1007 uptake of which the reason remains unclear. Readers must interpret such foci 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 foci.

Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners.

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.

Image-level trajectory inference of tau pathology using variational autoencoder for Flortaucipir PET.

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.

Comparing the clinical performance and cost efficacy of [68Ga]Ga-PSMA-11 and [18F]PSMA-1007 in the diagnosis of recurrent prostate cancer: a Markov chain decision analysis.

PURPOSE: Amongst others, [68Ga]Ga-PSMA-11 and [18F]PSMA-1007 are available for the detection of recurrent prostate cancer (rPC). There are currently limited data comparing the performance of these two radioligands with respect to clinical outcomes or their cost efficacy, which this study aims to address. METHODS: Two hundred and forty-four patients undergoing PSMA PET/CT for rPC were retrospectively analysed for this study (one hundred and twenty two with each radiopharmaceutical) to generate rates of PET positivity, negativity and unclear findings. Patients underwent follow-up to determine the rate of additional examinations and to confirm PET findings. A Markov chain decision analysis was implemented to model clinical decision-making processes and to analyse clinical performance of the two tracers. We determine their clinical cost efficacies using cost data from several countries where both radiotracers are in routine use. RESULTS: The PET positivity rate was non-significantly higher for [18F]PSMA-1007 compared to [68Ga]Ga-PSMA-11 (91.8% vs. 86.9%, p = 0.68), whereas the rate of uncertain findings was significantly greater (17.2% vs. 8.25%, p = 0.02). The probability of a true positive finding was higher for [68Ga]Ga-PSMA-11 (0.90, 95% CI 0.70-0.98) vs. [18F]PSMA-1007 (0.81, 95% CI 0.66-0.91). A significantly (p < 0.0001) higher PPV for [68Ga]Ga-PSMA-11 (0.99, 95% CI 0.99-1.0 vs. 0.86) was found compared to [18F]PSMA-1007 (0.86, 95% CI 0.82-1.00). Intervention efficacy analysis favoured [68Ga]Ga-PSMA-11, where the number needed to image (to achieve a true positive finding) was 10.58 and the number needed to image to harm (to achieve a false positive finding) was - 8.08. A cost efficacy analysis favours [68Ga]Ga-PSMA-11 in three of the four jurisdictions analysed where health economic data was available (Switzerland, Israel, Australia) and [18F]PSMA-1007 in one jurisdiction (Denmark). CONCLUSION: The analysis reveals a non-significantly higher PET positivity rate for [18F]PSMA-1007, but finds significantly greater rates of uncertain findings and false positive findings when compared to [68Ga]Ga-PSMA-11. We find differences in the two tracers in terms of clinical performance and cost efficacy. The method presented herein is generalisable and can be used with clinical or cost data for other countries or tracers.

Using radiomics-based modelling to predict individual progression from mild cognitive impairment to Alzheimer's disease.

BACKGROUND: 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. METHOD: 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. RESULTS: 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. CONCLUSION: The preliminary results demonstrated that the developed RPM approach has the potential to monitor progression in high-risk populations with AD.

First results on kinetic modelling and parametric imaging of dynamic 18F-FDG datasets from a long axial FOV PET scanner in oncological patients.

PURPOSE: To investigate the kinetics of 18F-fluorodeoxyglucose (18F-FDG) by positron emission tomography (PET) in multiple organs and test the feasibility of total-body parametric imaging using an image-derived input function (IDIF). METHODS: Twenty-four oncological patients underwent dynamic 18F-FDG scans lasting 65 min using a long  axial FOV (LAFOV) PET/CT system. Time activity curves (TAC) were extracted from semi-automated segmentations of multiple organs, cerebral grey and white matter, and from vascular structures. The tissue and tumor lesion TACs were fitted using an irreversible two-tissue compartment (2TC) and a Patlak model. Parametric images were also generated using direct and indirect Patlak methods and their performances were evaluated. RESULTS: We report estimates of kinetic parameters and metabolic rate of glucose consumption (MRFDG) for different organs and tumor lesions. In some organs, there were significant differences between MRFDG values estimated using 2TC and Patlak models. No statistically significant difference was seen between MRFDG values estimated using 2TC and Patlak methods in tumor lesions (paired t-test, P = 0.65). Parametric imaging showed that net influx (Ki) images generated using direct and indirect Patlak methods had superior tumor-to-background ratio (TBR) to standard uptake value (SUV) images (3.1- and 3.0-fold mean increases in TBRmean, respectively). Influx images generated using the direct Patlak method had twofold higher contrast-to-noise ratio in tumor lesions compared to images generated using the indirect Patlak method. CONCLUSION: We performed pharmacokinetic modelling of multiple organs using linear and non-linear models using dynamic total-body 18F-FDG images. Although parametric images did not reveal more tumors than SUV images, the results confirmed that parametric imaging furnishes improved tumor contrast. We thus demonstrate the feasibility of total-body kinetic modelling and parametric imaging in basic research and oncological studies. LAFOV PET can enhance dynamic imaging capabilities by providing high sensitivity parametric images and allowing total-body pharmacokinetic analysis.

Abbreviated scan protocols to capture 18F-FDG kinetics for long axial FOV PET scanners.

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.

A cross-scanner and cross-tracer deep learning method for the recovery of standard-dose imaging quality from low-dose PET.

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.

Further studies on C2'-substituted 1-phenylbenzazepines as dopamine D1 receptor ligands.

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 (Ki = 5.7 nM), was identified in this study; further pharmacological characterization indicates that 10b is an antagonist at D1R (IC50 = 10.7 nM). Docking studies on 10b indicate that a number of interactions with hydrophobic residues (Trp321, Val317, Phe313, Phe289, Phe288, Phe285, Phe203, Tyr194, Leu190, Ser188, His 164, Ile104, Val100 and Trp99) in addition to the typical N-Asp103 salt bridge are important for its D1R affinity.

Feasibility of late acquisition [68Ga]Ga-PSMA-11 PET/CT using a long axial field-of-view PET/CT scanner for the diagnosis of recurrent prostate cancer-first clinical experiences.

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 < 0.001) and SNR was improved with borderline significance (4 h: 33.02 vs 1 h: 24.80, 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.