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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.
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Enfermedad de Alzheimer , Disfunción Cognitiva , Humanos , Enfermedad de Alzheimer/diagnóstico por imagen , Enfermedad de Alzheimer/patología , Proteínas tau/metabolismo , Encéfalo/metabolismo , Disfunción Cognitiva/patología , Tomografía de Emisión de Positrones/métodosRESUMEN
Tau pathology and its spatial propagation in Alzheimer's disease (AD) play crucial roles in the neurodegenerative cascade leading to dementia. However, the underlying mechanisms linking tau spreading to glucose metabolism remain elusive. To address this, we aimed to examine the association between pathologic tau aggregation, functional connectivity, and cascading glucose metabolism and further explore the underlying interplay mechanisms. In this prospective cohort study, we enrolled 79 participants with 18F-Florzolotau positron emission tomography (PET), 18F-fluorodeoxyglucose PET, resting-state functional, and anatomical magnetic resonance imaging (MRI) images in the hospital-based Shanghai Memory Study. We employed generalized linear regression and correlation analyses to assess the associations between Florzolotau accumulation, functional connectivity, and glucose metabolism in whole-brain and network-specific manners. Causal mediation analysis was used to evaluate whether functional connectivity mediates the association between pathologic tau and cascading glucose metabolism. We examined 22 normal controls and 57 patients with AD. In the AD group, functional connectivity was associated with Florzolotau covariance (ß = .837, r = 0.472, p < .001) and glucose covariance (ß = 1.01, r = 0.499, p < .001). Brain regions with higher tau accumulation tend to be connected to other regions with high tau accumulation through functional connectivity or metabolic connectivity. Mediation analyses further suggest that functional connectivity partially modulates the influence of tau accumulation on downstream glucose metabolism (mediation proportion: 49.9%). Pathologic tau may affect functionally connected neurons directly, triggering downstream glucose metabolism changes. This study sheds light on the intricate relationship between tau pathology, functional connectivity, and downstream glucose metabolism, providing critical insights into AD pathophysiology and potential therapeutic targets.
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Enfermedad de Alzheimer , Fluorodesoxiglucosa F18 , Imagen por Resonancia Magnética , Red Nerviosa , Tomografía de Emisión de Positrones , Proteínas tau , Humanos , Enfermedad de Alzheimer/diagnóstico por imagen , Enfermedad de Alzheimer/metabolismo , Enfermedad de Alzheimer/fisiopatología , Masculino , Femenino , Anciano , Proteínas tau/metabolismo , Persona de Mediana Edad , Red Nerviosa/diagnóstico por imagen , Red Nerviosa/metabolismo , Red Nerviosa/fisiopatología , Glucosa/metabolismo , Conectoma , Estudios Prospectivos , Encéfalo/diagnóstico por imagen , Encéfalo/metabolismo , Encéfalo/fisiopatología , Anciano de 80 o más AñosRESUMEN
PURPOSE: Technological advances in instruments have greatly promoted the development of positron emission tomography (PET) scanners. State-of-the-art PET scanners such as uEXPLORER can collect PET images of significantly higher quality. However, these scanners are not currently available in most local hospitals due to the high cost of manufacturing and maintenance. Our study aims to convert low-quality PET images acquired by common PET scanners into images of comparable quality to those obtained by state-of-the-art scanners without the need for paired low- and high-quality PET images. METHODS: In this paper, we proposed an improved CycleGAN (IE-CycleGAN) model for unpaired PET image enhancement. The proposed method is based on CycleGAN, and the correlation coefficient loss and patient-specific prior loss were added to constrain the structure of the generated images. Furthermore, we defined a normalX-to-advanced training strategy to enhance the generalization ability of the network. The proposed method was validated on unpaired uEXPLORER datasets and Biograph Vision local hospital datasets. RESULTS: For the uEXPLORER dataset, the proposed method achieved better results than non-local mean filtering (NLM), block-matching and 3D filtering (BM3D), and deep image prior (DIP), which are comparable to Unet (supervised) and CycleGAN (supervised). For the Biograph Vision local hospital datasets, the proposed method achieved higher contrast-to-noise ratios (CNR) and tumor-to-background SUVmax ratios (TBR) than NLM, BM3D, and DIP. In addition, the proposed method showed higher contrast, SUVmax, and TBR than Unet (supervised) and CycleGAN (supervised) when applied to images from different scanners. CONCLUSION: The proposed unpaired PET image enhancement method outperforms NLM, BM3D, and DIP. Moreover, it performs better than the Unet (supervised) and CycleGAN (supervised) when implemented on local hospital datasets, which demonstrates its excellent generalization ability.
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PURPOSE: Alzheimer's disease (AD) is a heterogeneous disease that presents a broad spectrum of clinicopathologic profiles. To date, objective subtyping of AD independent of disease progression using brain imaging has been required. Our study aimed to extract representations of unique brain metabolism patterns different from disease progression to identify objective subtypes of AD. METHODS: A total of 3620 FDG brain PET images with AD, mild cognitive impairment (MCI), and cognitively normal (CN) were obtained from the ADNI database from 1607 participants at enrollment and follow-up visits. A conditional variational autoencoder model was trained on FDG brain PET images of AD patients with the corresponding condition of AD severity score. The k-means algorithm was applied to generate clusters from the encoded representations. The trained deep learning-based cluster model was also transferred to FDG PET of MCI patients and predicted the prognosis of subtypes for conversion from MCI to AD. Spatial metabolism patterns, clinical and biological characteristics, and conversion rate from MCI to AD were compared across the subtypes. RESULTS: Four distinct subtypes of spatial metabolism patterns in AD with different brain pathologies and clinical profiles were identified: (i) angular, (ii) occipital, (iii) orbitofrontal, and (iv) minimal hypometabolic patterns. The deep learning model was also successfully transferred for subtyping MCI, and significant differences in frequency (P < 0.001) and risk of conversion (log-rank P < 0.0001) from MCI to AD were observed across the subtypes, highest in S2 (35.7%) followed by S1 (23.4%). CONCLUSION: We identified distinct subtypes of AD with different clinicopathologic features. The deep learning-based approach to distinguish AD subtypes on FDG PET could have implications for predicting individual outcomes and provide a clue to understanding the heterogeneous pathophysiology of AD.
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Enfermedad de Alzheimer , Disfunción Cognitiva , Aprendizaje Profundo , Humanos , Enfermedad de Alzheimer/diagnóstico por imagen , Enfermedad de Alzheimer/metabolismo , Fluorodesoxiglucosa F18/metabolismo , Tomografía de Emisión de Positrones/métodos , Progresión de la Enfermedad , Encéfalo/diagnóstico por imagen , Encéfalo/metabolismo , Disfunción Cognitiva/diagnóstico por imagen , Disfunción Cognitiva/metabolismoRESUMEN
PURPOSE: This study aims to develop deep learning techniques on total-body PET to bolster the feasibility of sedation-free pediatric PET imaging. METHODS: A deformable 3D U-Net was developed based on 245 adult subjects with standard total-body PET imaging for the quality enhancement of simulated rapid imaging. The developed method was first tested on 16 children receiving total-body [18F]FDG PET scans with standard 300-s acquisition time with sedation. Sixteen rapid scans (acquisition time about 3 s, 6 s, 15 s, 30 s, and 75 s) were retrospectively simulated by selecting the reconstruction time window. In the end, the developed methodology was prospectively tested on five children without sedation to prove the routine feasibility. RESULTS: The approach significantly improved the subjective image quality and lesion conspicuity in abdominal and pelvic regions of the generated 6-s data. In the first test set, the proposed method enhanced the objective image quality metrics of 6-s data, such as PSNR (from 29.13 to 37.09, p < 0.01) and SSIM (from 0.906 to 0.921, p < 0.01). Furthermore, the errors of mean standardized uptake values (SUVmean) for lesions between 300-s data and 6-s data were reduced from 12.9 to 4.1% (p < 0.01), and the errors of max SUV (SUVmax) were reduced from 17.4 to 6.2% (p < 0.01). In the prospective test, radiologists reached a high degree of consistency on the clinical feasibility of the enhanced PET images. CONCLUSION: The proposed method can effectively enhance the image quality of total-body PET scanning with ultrafast acquisition time, leading to meeting clinical diagnostic requirements of lesion detectability and quantification in abdominal and pelvic regions. It has much potential to solve the dilemma of the use of sedation and long acquisition time that influence the health of pediatric patients.
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Fluorodesoxiglucosa F18 , Tomografía de Emisión de Positrones , Imagen de Cuerpo Entero , Humanos , Niño , Imagen de Cuerpo Entero/métodos , Femenino , Tomografía de Emisión de Positrones/métodos , Masculino , Procesamiento de Imagen Asistido por Computador/métodos , Adolescente , Adulto , Factores de Tiempo , Estudios de Factibilidad , Preescolar , Aprendizaje ProfundoRESUMEN
PURPOSE: Despite the revealed role of immunological dysfunctions in the development and progression of Alzheimer's disease (AD) through animal and postmortem investigations, direct evidence regarding the impact of genetic factors on microglia response and amyloid-ß (Aß) deposition in AD individuals is lacking. This study aims to elucidate this mechanism by integrating transcriptomics and TSPO, Aß PET imaging in clinical AD cohort. METHODS: We analyzed 85 patients with PET/MR imaging for microglial activation (TSPO, [18F]DPA-714) and Aß ([18F]AV-45) within the prospective Alzheimer's Disease Immunization and Microbiota Initiative Study Cohort (ADIMIC). Immune-related differentially expressed genes (IREDGs), identified based on AlzData, were screened and verified using blood samples from ADIMIC. Correlation and mediation analyses were applied to investigate the relationships between immune-related genes expression, TSPO and Aß PET imaging. RESULTS: TSPO uptake increased significantly both in aMCI (P < 0.05) and AD participants (P < 0.01) and showed a positive correlation with Aß deposition (r = 0.42, P < 0.001). Decreased expression of TGFBR3, FABP3, CXCR4 and CD200 was observed in AD group. CD200 expression was significantly negatively associated with TSPO PET uptake (r =-0.33, P = 0.013). Mediation analysis indicated that CD200 acted as a significant mediator between TSPO uptake and Aß deposition (total effect B = 1.92, P = 0.004) and MMSE score (total effect B =-54.01, P = 0.003). CONCLUSION: By integrating transcriptomics and TSPO PET imaging in the same clinical AD cohort, this study revealed CD200 played an important role in regulating neuroinflammation, Aß deposition and cognitive dysfunction.
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Enfermedad de Alzheimer , Humanos , Enfermedad de Alzheimer/diagnóstico por imagen , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/metabolismo , Péptidos beta-Amiloides/metabolismo , Perfilación de la Expresión Génica , Enfermedades Neuroinflamatorias , Tomografía de Emisión de Positrones/métodos , Estudios Prospectivos , Receptores de GABA/genética , Receptores de GABA/metabolismoRESUMEN
PURPOSE: While sedation is routinely used in pediatric PET examinations to preserve diagnostic quality, it may result in side effects and may affect the radiotracer's biodistribution. This study aims to investigate the feasibility of sedation-free pediatric PET imaging using ultra-fast total-body (TB) PET scanners and deep learning (DL)-based attenuation and scatter correction (ASC). METHODS: This retrospective study included TB PET (uExplorer) imaging of 35 sedated pediatric patients under four years old to determine the minimum effective scanning time. A DL-based ASC method was applied to enhance PET quantification. Both quantitative and qualitative assessments were conducted to evaluate the image quality of ultra-fast DL-ASC PET. Five non-sedated pediatric patients were subsequently used to validate the proposed approach. RESULTS: Comparisons between standard 300-second and ultra-fast 15-second imaging, CT-ASC and DL-ASC ultra-fast 15-second images, as well as DL-ASC ultra-fast 15-second images in non-sedated and sedated patients, showed no significant differences in qualitative scoring, lesion detectability, and quantitative Standard Uptake Value (SUV) (P = ns). CONCLUSIONS: This study demonstrates that pediatric PET imaging can be effectively performed without sedation by combining ultra-fast imaging techniques with a DL-based ASC. This advancement in sedation-free ultra-fast PET imaging holds potential for broader clinical adoption.
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Radioguidance that makes use of ß-emitting radionuclides is gaining in popularity and could have potential to strengthen the range of existing radioguidance techniques. While there is a strong tendency to develop new PET radiotracers, due to favorable imaging characteristics and the success of theranostics research, there are practical challenges that need to be overcome when considering use of ß-emitters for surgical radioguidance. In this position paper, the EANM identifies the possibilities and challenges that relate to the successful implementation of ß-emitters in surgical guidance, covering aspects related to instrumentation, radiation protection, and modes of implementation.
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Partículas beta , Partículas beta/uso terapéutico , Humanos , Radioisótopos/química , Medicina Nuclear , Radiofármacos , Cirugía Asistida por Computador/métodos , Protección Radiológica/métodosRESUMEN
PURPOSE: This study aimed to comprehensively explore the different metabolic connectivity topological changes in MTLE and NTLE, as well as their association with surgical outcomes. METHODS: This study enrolled a cohort of patients with intractable MTLE and NTLE. Each individual's metabolic connectome, as determined by Kullback-Leibler divergence similarity estimation for the [18F]FDG PET image, was employed to conduct a comprehensive analysis of the cerebral metabolic network. Alterations in network connectivity were assessed by extracting and evaluating the strength of edge and weighted connectivity. By utilizing these two connectivity strength metrics with the cerebellum, we explored the network properties of connectivity and its association with prognosis in surgical patients. RESULTS: Both MTLE and NTLE patients exhibited substantial alterations in the connectivity of the metabolic network at the edge and nodal levels (p < 0.01, FDR corrected). The key disparity between MTLE and NTLE was observed in the cerebellum. In MTLE, there was a predominance of increased connectivity strength in the cerebellum. Whereas, a decrease in cerebellar connectivity was identified in NTLE. It was found that in MTLE, higher edge connectivity and weighted connectivity strength in the contralateral cerebellar hemisphere correlated with improved surgical outcomes. Conversely, in NTLE, a higher edge metabolic connectivity strength in the ipsilateral cerebellar hemisphere suggested a worse surgical prognosis. CONCLUSION: The cerebellum exhibits distinct topological characteristics in the metabolic networks between MTLE and NTLE. The hyper- or hypo-metabolic connectivity in the cerebellum may be a prognostic biomarker of surgical prognosis, which might aid in therapeutic decision-making for TLE individuals.
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PURPOSE: There is an unmet need for compounds to detect fibrillar forms of alpha-synuclein (αSyn) and 4-repeat tau, which are critical in many neurodegenerative diseases. Here, we aim to develop an efficient surface plasmon resonance (SPR)-based assay to facilitate the characterization of small molecules that can bind these fibrils. METHODS: SPR measurements were conducted to characterize the binding properties of fluorescent ligands/compounds toward recombinant amyloid-beta (Aß)42, K18-tau, full-length 2N4R-tau and αSyn fibrils. In silico modeling was performed to examine the binding pockets of ligands on αSyn fibrils. Immunofluorescence staining of postmortem brain tissue slices from Parkinson's disease patients and mouse models was performed with fluorescence ligands and specific antibodies. RESULTS: We optimized the protocol for the immobilization of Aß42, K18-tau, full-length 2N4R-tau and αSyn fibrils in a controlled aggregation state on SPR-sensor chips and for assessing their binding to ligands. The SPR results from the analysis of binding kinetics suggested the presence of at least two binding sites for all fibrils, including luminescent conjugated oligothiophenes, benzothiazole derivatives, nonfluorescent methylene blue and lansoprazole. In silico modeling studies for αSyn (6H6B) revealed four binding sites with a preference for one site on the surface. Immunofluorescence staining validated the detection of pS129-αSyn positivity in the brains of Parkinson's disease patients and αSyn preformed-fibril injected mice, 6E10-positive Aß in arcAß mice, and AT-8/AT-100-positivity in pR5 mice. CONCLUSION: SPR measurements of small molecules binding to Aß42, K18/full-length 2N4R-tau and αSyn fibrils suggested the existence of multiple binding sites. This approach may provide efficient characterization of compounds for neurodegenerative disease-relevant proteinopathies.
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BACKGROUND AND OBJECTIVE: Treatment planning through the diagnostic dimension of theranostics provides insights into predicting the absorbed dose of RPT, with the potential to individualize radiation doses for enhancing treatment efficacy. However, existing studies focusing on dose prediction from diagnostic data often rely on organ-level estimations, overlooking intra-organ variations. This study aims to characterize the intra-organ theranostic heterogeneity and utilize artificial intelligence techniques to localize them, i.e. to predict voxel-wise absorbed dose map based on pre-therapy PET. METHODS: 23 patients with metastatic castration-resistant prostate cancer treated with [177Lu]Lu-PSMA I&T RPT were retrospectively included. 48 treatment cycles with pre-treatment PET imaging and at least 3 post-therapeutic SPECT/CT imaging were selected. The distribution of PET tracer and RPT dose was compared for kidney, liver and spleen, characterizing intra-organ heterogeneity differences. Pharmacokinetic simulations were performed to enhance the understanding of the correlation. Two strategies were explored for pre-therapy voxel-wise dosimetry prediction: (1) organ-dose guided direct projection; (2) deep learning (DL)-based distribution prediction. Physical metrics, dose volume histogram (DVH) analysis, and identity plots were applied to investigate the predicted absorbed dose map. RESULTS: Inconsistent intra-organ patterns emerged between PET imaging and dose map, with moderate correlations existing in the kidney (r = 0.77), liver (r = 0.5), and spleen (r = 0.58) (P < 0.025). Simulation results indicated the intra-organ pharmacokinetic heterogeneity might explain this inconsistency. The DL-based method achieved a lower average voxel-wise normalized root mean squared error of 0.79 ± 0.27%, regarding to ground-truth dose map, outperforming the organ-dose guided projection (1.11 ± 0.57%) (P < 0.05). DVH analysis demonstrated good prediction accuracy (R2 = 0.92 for kidney). The DL model improved the mean slope of fitting lines in identity plots (199% for liver), when compared to the theoretical optimal results of the organ-dose approach. CONCLUSION: Our results demonstrated the intra-organ heterogeneity of pharmacokinetics may complicate pre-therapy dosimetry prediction. DL has the potential to bridge this gap for pre-therapy prediction of voxel-wise heterogeneous dose map.
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PURPOSE: Accurately and early detection of intestinal fibrosis in Crohn's disease (CD) is crucial for clinical management yet remains an unmet need. Fibroblast activation protein inhibitor (FAPI) PET/CT has emerged as a promising tool to assess fibrosis. We aimed to investigate the diagnostic capability of [18F]F-FAPI PET/CT in detecting intestinal fibrosis and compared it with[18F]F-FDG PET/CT and magnetization transfer MR imaging (MTI). METHODS: Twenty-two rats underwent TNBS treatment to simulate fibrosis development, followed by three quantitative imaging sessions within one week. Mean and maximum standardized uptake values (SUVmean and SUVmax) were calculated on[18F]F-FAPI and [18F]F-FDG PET/CT, along with normalized magnetization transfer ratio on MTI. Intestinal fibrosis was assessed pathologically, with MTI serving as imaging standard for fibrosis. The diagnostic efficacy of imaging parameters in fibrosis was compared using pathological and imaging standards. Ten patients with 34 bowel strictures were prospectively recruited to validate their diagnostic performance, using the identical imaging protocol. RESULTS: In CD patients, the accuracy of FAPI uptake (both AUCs = 0.87, both P ≤ 0.01) in distinguishing non-to-mild from moderate-to-severe fibrosis was higher than FDG uptake (both AUCs = 0.82, P ≤ 0.01) and comparable to MTI (AUCs = 0.90, P ≤ 0.001). In rats, FAPI uptake responded earlier to fibrosis development than FDG and MTI; consistently, during early phase, FAPI uptake showed a stronger correlation (SUVmean: R = 0.69) with pathological fibrosis than FDG (SUVmean: R = 0.17) and MTI (R = 0.52). CONCLUSION: The diagnostic efficacy of [18F]F-FAPI PET/CT in detecting CD fibrosis is superior to [18F]F-FDG PET/CT and comparable to MTI, exhibiting great potential for early detection of intestinal fibrosis.
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Enfermedad de Crohn , Modelos Animales de Enfermedad , Fibrosis , Fluorodesoxiglucosa F18 , Intestinos , Imagen por Resonancia Magnética , Tomografía Computarizada por Tomografía de Emisión de Positrones , Enfermedad de Crohn/diagnóstico por imagen , Enfermedad de Crohn/complicaciones , Animales , Tomografía Computarizada por Tomografía de Emisión de Positrones/métodos , Ratas , Fibrosis/diagnóstico por imagen , Humanos , Masculino , Femenino , Adulto , Intestinos/diagnóstico por imagen , Intestinos/patología , Estudios Prospectivos , Persona de Mediana EdadRESUMEN
Abnormal glucose metabolism and hemodynamic changes in the brain are closely related to cognitive function, providing complementary information from distinct biochemical and physiological processes. However, it remains unclear how to effectively integrate these two modalities across distinct brain regions. In this study, we developed a connectome-based sparse coupling method for hybrid PET/MRI imaging, which could effectively extract imaging markers of Alzheimer's disease (AD) in the early stage. The FDG-PET and resting-state fMRI data of 56 healthy controls (HC), 54 subjective cognitive decline (SCD), and 27 cognitive impairment (CI) participants due to AD were obtained from SILCODE project (NCT03370744). For each participant, the metabolic connectome (MC) was constructed by Kullback-Leibler divergence similarity estimation, and the functional connectome (FC) was constructed by Pearson correlation. Subsequently, we measured the coupling strength between MC and FC at various sparse levels, assessed its stability, and explored the abnormal coupling strength along the AD continuum. Results showed that the sparse MC-FC coupling index was stable in each brain network and consistent across subjects. It was more normally distributed than other traditional indexes and captured more SCD-related brain areas, especially in the limbic and default mode networks. Compared to other traditional indices, this index demonstrated best classification performance. The AUC values reached 0.748 (SCD/HC) and 0.992 (CI/HC). Notably, we found a significant correlation between abnormal coupling strength and neuropsychological scales (p < .05). This study provides a clinically relevant tool for hybrid PET/MRI imaging, allowing for exploring imaging markers in early stage of AD and better understanding the pathophysiology along the AD continuum.
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Enfermedad de Alzheimer , Disfunción Cognitiva , Conectoma , Humanos , Enfermedad de Alzheimer/diagnóstico por imagen , Conectoma/métodos , Imagen por Resonancia Magnética/métodos , Tomografía de Emisión de Positrones/métodos , Disfunción Cognitiva/diagnóstico por imagen , Encéfalo/diagnóstico por imagenRESUMEN
PURPOSE: The image quality characteristics of two NEMA phantoms with yttrium-90 (90Y) were evaluated on a long axial field-of-view (AFOV) PET/CT. The purpose was to identify the optimized reconstruction setup for the imaging of patients with hepatocellular carcinoma after 90Y radioembolization. METHODS: Two NEMA phantoms were used, where one had a 1:10 sphere to background activity concentration ratio and the second had cold background. Reconstruction parameters used are as follows: iterations 2 to 8, Gaussian filter 2- to 6-mm full-width-at-half-maximum, reconstruction matrices 440 × 440 and 220 × 220, high sensitivity (HS), and ultra-high sensitivity (UHS) modes. 50-, 40-, 30-, 20-, 10-, and 5-min acquisitions were reconstructed. The measurements included recovery coefficients (RC), signal-to-noise ratio (SNR), background variability, and lung error which measures the residual error in the corrections. Patient data were reconstructed with 20-, 10-, 5-, and 1-min time frames and evaluated in terms of SNR. RESULTS: The RC for the hot phantom was 0.36, 0.45, 0.53, 0.63, 0.68, and 0.84 for the spheres with diameters of 10, 13, 17, 22, 28, and 37 mm, respectively, for UHS 2 iterations, a 220 × 220 matrix, and 50-min acquisition. The RC values did not differ with acquisition times down to 20 min. The SNR was the highest for 2 iterations, measured 11.7, 16.6, 17.6, 19.4, 21.9, and 27.7 while the background variability was the lowest (27.59, 27.08, 27.36, 26.44, 30.11, and 33.51%). The lung error was 18%. For the patient dataset, the SNR was 19%, 20%, 24%, and 31% higher for 2 iterations compared to 4 iterations for 20-, 10-, 5-, and 1-min time frames, respectively. CONCLUSIONS: This study evaluates the NEMA image quality of a long AFOV PET/CT scanner with 90Y. It provides high RC for the smallest sphere compared to other standard AFOV scanners at shorter scan times. The maximum patient SNR was for 2 iterations, 20 min, while 5 min delivers images with acceptable SNR.
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Neoplasias Hepáticas , Tomografía Computarizada por Tomografía de Emisión de Positrones , Humanos , Tomografía de Emisión de Positrones/métodos , Radioisótopos de Itrio/uso terapéutico , Fantasmas de Imagen , Neoplasias Hepáticas/diagnóstico por imagen , Neoplasias Hepáticas/radioterapiaRESUMEN
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.
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Fluorodesoxiglucosa F18 , Neoplasias , Humanos , Estudios de Factibilidad , Tomografía de Emisión de Positrones/métodos , Arterias , Neoplasias/diagnóstico por imagenRESUMEN
PURPOSE: To assess predictive value of 68Ga-labeled fibroblast activation protein inhibitor-04 ([68Ga]Ga-DOTA-FAPI-04) PET/MR for late left ventricular (LV) remodeling in patients with ST-segment elevated myocardial infarction (STEMI). METHODS: Twenty-six patients with STEMI were included in the study. [68Ga]Ga-DOTA-FAPI-04 PET/MR was performed at baseline and at average 12 months after STEMI. LV remodeling was defined as >10% increase in LV end-systolic volume (LVESV) from baseline to 12 months. RESULTS: The LV remodeling group demonstrated higher [68Ga]Ga-DOTA-FAPI-04 uptake volume (UV) at baseline than the non-LV remodeling group (p < 0.001). [68Ga]Ga-DOTA-FAPI-04 UV at baseline was a significant predictor (OR = 1.048, p = 0.011) for LV remodeling at 12 months after STEMI. Compared to clinical information, MR imaging and cardiac function parameters at baseline, [68Ga]Ga-DOTA-FAPI-04 UV demonstrated better predictive ability (AUC = 0.938, p < 0.001) for late LV remodeling, with sensitivity of 100.0% and specificity of 81.3%. CONCLUSIONS: [68Ga]Ga-DOTA-FAPI-04 PET/MR is an effective tool to non-invasively quantify myocardial fibroblasts activation, and baseline [68Ga]Ga-DOTA-FAPI-04 UV may have potential predictive value for late LV remodeling.
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Infarto del Miocardio , Infarto del Miocardio con Elevación del ST , Humanos , Radioisótopos de Galio , Remodelación Ventricular , Función Ventricular Izquierda , Infarto del Miocardio/diagnóstico por imagen , Imagen por Resonancia Magnética , Tomografía de Emisión de Positrones , Tomografía Computarizada por Tomografía de Emisión de PositronesRESUMEN
BACKGROUND: Despite the demonstrated adverse outcome, it is difficult to early identify the risks for patients with ischemia and no obstructive coronary artery disease (INOCA). We aimed to explore the prognostic potential of CZT SPECT in INOCA patients. METHODS: The study population consisted of a retrospective cohort of 118 INOCA patients, all of whom underwent CZT SPECT imaging and invasive coronary angiography (ICA). Dynamic data were reconstructed, and MBF was quantified using net retention model. Major adverse cardiovascular events (MACEs) were defined as cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, heart failure, late coronary revascularization, or hospitalization for unstable angina. RESULTS: During a median follow-up of 15 months (interquartile range (IQR) 11-20), 19 (16.1%) MACEs occurred; both stress myocardial blood flow (sMBF) ([Formula: see text]) and coronary flow reserve (CFR) ([Formula: see text]) were significantly lower in the MACE group. Optimal thresholds of sMBF<3.16 and CFR<2.52 were extracted from the ROC curves, and both impaired sMBF (HR: 15.08; 95% CI 2.95-77.07; [Formula: see text]) and CFR (HR: 6.51; 95% CI 1.43-29.65; [Formula: see text]) were identified as prognostic factors for MACEs. Only sMBF<3.16 (HR: 11.20; 95% CI 2.04-61.41; [Formula: see text]) remained a robust predictor when sMBF and CFR were integrated considered. Compared with CFR, sMBF provides better prognostic model discrimination and reclassification ability (C-index improvement = 0.06, [Formula: see text]; net reclassification improvement (NRI) = 0.19; integrated discrimination improvement (IDI) = 0.10). CONCLUSION: The preliminary results demonstrated that quantitative analysis on CZT SPECT provides prognostic value for INOCA patients, which may allow the stratification for early prevention and intervention.
Asunto(s)
Enfermedad de la Arteria Coronaria , Infarto del Miocardio , Imagen de Perfusión Miocárdica , Humanos , Enfermedad de la Arteria Coronaria/diagnóstico por imagen , Proyectos Piloto , Pronóstico , Estudios Retrospectivos , Angiografía Coronaria/métodos , Tomografía Computarizada de Emisión de Fotón Único , Imagen de Perfusión Miocárdica/métodosRESUMEN
PURPOSE: Long axial field-of-view (LAFOV) systems have a much higher sensitivity than standard axial field-of-view (SAFOV) PET systems for imaging the torso or full body, which allows faster and/or lower dose imaging. Despite its very high sensitivity, current total-body PET (TB-PET) throughput is limited by patient handling (positioning on the bed) and often a shortage of available personnel. This factor, combined with high system costs, makes it hard to justify the implementation of these systems for many academic and nearly all routine nuclear medicine departments. We, therefore, propose a novel, cost-effective, dual flat panel TB-PET system for patients in upright standing positions to avoid the time-consuming positioning on a PET-CT table; the walk-through (WT) TB-PET. We describe a patient-centered, flat panel PET design that offers very efficient patient throughput and uses monolithic detectors (with BGO or LYSO) with depth-of-interaction (DOI) capabilities and high intrinsic spatial resolution. We compare system sensitivity, component costs, and patient throughput of the proposed WT-TB-PET to a SAFOV (= 26 cm) and a LAFOV (= 106 cm) LSO PET systems. METHODS: Patient width, height (= top head to start of thighs) and depth (= distance from the bed to front of patient) were derived from 40 randomly selected PET-CT scans to define the design dimensions of the WT-TB-PET. We compare this new PET system to the commercially available Siemens Biograph Vision 600 (SAFOV) and Siemens Quadra (LAFOV) PET-CT in terms of component costs, system sensitivity, and patient throughput. System cost comparison was based on estimating the cost of the two main components in the PET system (Silicon Photomultipliers (SiPMs) and scintillators). Sensitivity values were determined using Gate Monte Carlo simulations. Patient throughput times (including CT and scout scan, patient positioning on bed and transfer) were recorded for 1 day on a Siemens Vision 600 PET. These timing values were then used to estimate the expected patient throughput (assuming an equal patient radiotracer injected activity to patients and considering differences in system sensitivity and time-of-flight information) for WT-TB-PET, SAFOV and LAFOV PET. RESULTS: The WT-TB-PET is composed of two flat panels; each is 70 cm wide and 106 cm high, with a 50-cm gap between both panels. These design dimensions were justified by the patient sizes measured from the 40 random PET-CT scans. Each panel consists of 14 × 20 monolithic BGO detector blocks that are 50 × 50 × 16 mm in size and are coupled to a readout with 6 × 6 mm SiPMs arrays. For the WT-TB-PET, the detector surface is reduced by a factor of 1.9 and the scintillator volume by a factor of 2.2 compared to LAFOV PET systems, while demonstrating comparable sensitivity and much better uniform spatial resolution (< 2 mm in all directions over the FOV). The estimated component cost for the WT-TB-PET is 3.3 × lower than that of a 106 cm LAFOV system and only 20% higher than the PET component costs of a SAFOV. The estimated maximum number of patients scanned on a standard 8-h working day increases from 28 (for SAFOV) to 53-60 (for LAFOV in limited/full acceptance) to 87 (for the WT-TB-PET). By scanning faster (more patients), the amount of ordered activity per patient can be reduced drastically: the WT-TB-PET requires 66% less ordered activity per patient than a SAFOV. CONCLUSIONS: We propose a monolithic BGO or LYSO-based WT-TB-PET system with DOI measurements that departs from the classical patient positioning on a table and allows patients to stand upright between two flat panels. The WT-TB-PET system provides a solution to achieve a much lower cost TB-PET approaching the cost of a SAFOV system. High patient throughput is increased by fast patient positioning between two vertical flat panel detectors of high sensitivity. High spatial resolution (< 2 mm) uniform over the FOV is obtained by using DOI-capable monolithic scintillators.
Asunto(s)
Tomografía Computarizada por Tomografía de Emisión de Positrones , Tomografía de Emisión de Positrones , Humanos , Tomografía de Emisión de Positrones/métodos , Método de Montecarlo , Atención Dirigida al PacienteRESUMEN
PURPOSE: The exact phenoconversion time from isolated rapid eye movement (REM) sleep behavior disorder (iRBD) to synucleinopathies remains unpredictable. This study investigated whole-brain dopaminergic damage pattern (DDP) with disease progression and predicted phenoconversion time in individual patients. METHODS: Age-matched 33 iRBD patients and 20 healthy controls with 11C-CFT-PET scans were enrolled. The patients were followed up 2-10 (6.7 ± 2.0) years. The phenoconversion year was defined as the base year, and every 2 years before conversion was defined as a stage. Support vector machine with leave-one-out cross-validation strategy was used to perform prediction. RESULTS: Dopaminergic degeneration of iRBD was found to occur about 6 years before conversion and then abnormal brain regions gradually expanded. Using DDP, area under curve (AUC) was 0.879 (90% sensitivity and 88.3% specificity) for predicting conversion in 0-2 years, 0.807 (72.7% sensitivity and 83.3% specificity) in 2-4 years, 0.940 (100% sensitivity and 84.6% specificity) in 4-6 years, and 0.879 (100% sensitivity and 80.7% specificity) over 6 years. In individual patients, predicted stages correlated with whole-brain dopaminergic levels (r = - 0.740, p < 0.001). CONCLUSION: Our findings suggest that DDP could accurately predict phenoconversion time of individual iRBD patients, which may help to screen patients for early intervention.
Asunto(s)
Trastorno de la Conducta del Sueño REM , Humanos , Trastorno de la Conducta del Sueño REM/diagnóstico por imagen , Encéfalo/diagnóstico por imagen , Dopamina , Progresión de la EnfermedadRESUMEN
PURPOSE: Characteristic features of amyloid-PET (A), tau-PET (T), and FDG-PET (N) can serve for the A/T/N classification of neurodegenerative diseases. Recent studies showed that the early, perfusion-weighted phases of amyloid- or tau-PET recordings serve to detect cerebrometabolic deficits equally to FDG-PET, therefore providing a surrogate of neuronal injury. As such, two channels of diagnostic information can be obtained in the setting of a single PET scan. However, there has hitherto been no comparison of early-phase amyloid- and tau-PET as surrogates for deficits in perfusion/metabolism. Therefore, we undertook to compare [18F]flutemetamol-amyloid-PET and [18F]PI-2620 tau-PET as "one-stop shop" dual purpose tracers for the detection of neurodegenerative disease. METHODS: We obtained early-phase PET recordings with [18F]PI-2620 (0.5-2.5 min p.i.) and [18F]flutemetamol (0-10 min p.i.) in 64 patients with suspected neurodegenerative disease. We contrasted global mean normalized images (SUVr) in the patients with a normal cohort of 15 volunteers without evidence of increased pathology to ß-amyloid- and tau-PET examinations. Regional group differences of tracer uptake (z-scores) of 246 Brainnetome volumes of interest were calculated for both tracers, and the correlations of the z-scores were evaluated using Pearson's correlation coefficient. Lobar compartments, regions with significant neuronal injury (z-scores < - 3), and patients with different neurodegenerative disease entities (e.g., Alzheimer's disease or 4R-tauopathies) served for subgroup analysis. Additionally, we used partial regression to correlate regional perfusion alterations with clinical scores in cognition tests. RESULTS: The z-scores of perfusion-weighted images of both tracers showed high correlations across the brain, especially in the frontal and parietal lobes, which were the brain regions with pronounced perfusion deficit in the patient group (R = 0.83 ± 0.08; range, 0.61-0.95). Z-scores of individual patients correlated well by region (R = 0.57 ± 0.15; range, 0.16-0.90), notably when significant perfusion deficits were present (R = 0.66 ± 0.15; range, 0.28-0.90). CONCLUSION: The early perfusion phases of [18F]PI-2620 tau- and [18F]flutemetamol-amyloid-PET are roughly equivalent indices of perfusion defect indicative of regional and lobar neuronal injury in patients with various neurodegenerative diseases. As such, either tracer may serve for two diagnostic channels by assessment of amyloid/tau status and neuronal activity.