FDG Positron Emission Tomography Studies Research Articles

Abstract A024: DCE-MRI-based biophysical simulation to forecast NAT response in HER2+ breast cancer patients, with glucose characterization and orthogonal validation using FDG-PET and 64Cu studies

Abstract Background Regions of high metabolic activity within a tumor can increase tumor perfusion. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) and 18Fluorodeoxyglucose (FDG) positron emission tomography (PET) are imaging methods used in cancer diagnosis; the former identifies perfusion of the tumor microenvironment and the latter provides a coarse readout of glucose metabolic activity. Here, we perform a pilot analysis in a unique cohort of patients who underwent DCE-MRI, 18FDG-PET and 64Cu-DOTA-Traztuzumab. We characterize the performance of our perfusion model SimBioSys-Microvasculature (SBS-MV). We use this model in 3D simulations of individual HER2+ breast cancer patients to forecast response to neoadjuvant chemotherapy (NAT). Methods SBS-MV is a modified Tofts model for pharmacokinetic modeling of DCE-MRI data, utilizing a tissue segmentation model developed in-house to inform parameter fits and ensure that the derived parameters fall within acceptable values on a tissue-by-tissue level. We evaluated the stability of the SBS-MV model by analyzing a separate cohort of 10 patients who underwent ultrafast DCE-MRI. By undersampling the original high temporal resolution data, we mimicked possible variation in standard-of-care (SoC) DCE studies and accessed the variability of our fits with respect to different subsets. Next, we analyzed data from a different cohort of 18 patients, each of whom underwent a pre-NAT SoC DCE-MRI study, a mid-treatment FDG PET study, and a mid-treatment 64Cu-DOTA-Trastuzumab study during treatment. Tissue segmentation and SBS-MV fits were performed on the pre-NAT DCE-MRI. Tightly cropped boxes encompassing the tumor in the 3D SBS-MV volumes and the PET volumes were created. Using these identified regions, all summary statistics were calculated and cross-correlated between imaging modalities. Results SBS-MV was stable to SoC-mimicking temporally undersampled ultrafast DCE-MRI series, demonstrating relatively little variability in the output parameters (a voxel wise median deviation of approximately 0.005 min−1). Further, we demonstrate that SBS-MV parameters (Ktrans, ve) are correlated with FDG SUVSA and 64Cu SUVSA. The glucose concentrations used in the biophysical simulations, which are derived from SBS-MV fits, were correlated with FDG SUVSA, indicating that downstream applications of the SBS-MV models still carry this perfusion information. Finally, using SBS-MV, our biophysical simulations of HER2-targeted therapy accurately predict patient response. In this small cohort, our biophysical simulations performed well, yielding predictive accuracy of 0.83 (sensitivity=0.83, specificity=0.83). Conclusion Our MV model extracts biologically meaningful perfusion parameters from standard clinical DCE-MRI time series, providing the same benefits of a comprehensive kinetic analysis without impacting clinical workflow. This approach could be used in research and clinical settings, offering actionable information on what drives individual patient therapeutic response for a more personalized care. Citation Format: John Whitman, Vikram Adhikarla, Russell Rockne, Lusine Tumyan, Joanne Mortimer, Wei Huang, Dorys Lopez Ramos, Joseph R. Peterson, John A. Cole. DCE-MRI-based biophysical simulation to forecast NAT response in HER2+ breast cancer patients, with glucose characterization and orthogonal validation using FDG-PET and 64Cu studies [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A024.

Imaging Correlates between Headache and Breast Cancer: An [18F]FDG PET Study.

This study aimed to examine brain metabolic patterns on [18F]Fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) in breast cancer (BC), comparing patients with tension-type headache (TTH), migraine (MiG), and those without headache. Further association with BC response to neoadjuvant chemotherapy (NAC) was explored. In this prospective study, BC patients eligible for NAC performed total-body [18F]FDG PET/CT with a dedicated brain scan. A voxel-wise analysis (two-sample t-test) and a multiple regression model were used to compare brain metabolic patterns among TTH, MiG, and no-headache patients and to correlate them with clinical covariates. A single-subject analysis compared each patient's brain uptake before and after NAC with a healthy control group. Primary headache was diagnosed in 39/46 of BC patients (39% TTH and 46% MiG). TTH patients exhibited hypometabolism in specific brain regions before NAC. TTH patients with a pathological complete response (pCR) to NAC showed hypermetabolic brain regions in the anterior medial frontal cortex. The correlation between tumor uptake and brain metabolism varied before and after NAC, suggesting an inverse relationship. Additionally, the single-subject analysis revealed that hypometabolic brain regions were not present after NAC. Primary headache, especially MiG, was associated with a better response to NAC. These findings suggest complex interactions between BC, headache, and hormonal status, warranting further investigation in larger prospective cohorts.

Synaptic Density and Glucose Consumption in Patients with Lewy Body Diseases: An [11 C]UCB-J and [18 F]FDG PET Study.

Patients with Lewy body diseases exhibit variable degrees of cortical and subcortical hypometabolism. However, the underlying causes behind this progressive hypometabolism remain unresolved. Generalized synaptic degeneration may be one key contributor. The objective of this study was to investigate whether local cortical synaptic loss is proportionally linked to the magnitude of hypometabolism in Lewy body disease. Using in vivo positron emission tomography (PET) we investigated cerebral glucose metabolism and quantified the density of cerebral synapses, as measured with [18 F]fluorodeoxyglucose ([18 F]FDG) PET and [11 C]UCB-J, respectively. Volumes-of-interest were defined on magnetic resonance T1 scans and regional standard uptake value ratios-1 values were obtained for 14 pre-selected brain regions. Between-group comparisons were conducted at voxel-level. We observed regional differences in both synaptic density and cerebral glucose consumption in our cohorts of non-demented and demented patients with Parkinson's disease or dementia with Lewy bodies compared to healthy subjects. Additionally, voxel-wise comparisons showed a clear difference in cortical regions between demented patients and controls for both tracers. Importantly, our findings strongly suggested that the magnitude of reduced glucose uptake exceeded the magnitude of reduced cortical synaptic density. Here, we investigated the relationship between in vivo glucose uptake and the magnitude of synaptic density as measured using [18 F]FDG PET and [11 C]UCB-J PET in Lewy body patients. The magnitude of reduced [18 F]FDG uptake was greater than the corresponding decline in [11 C]UCB-J binding. Therefore, the progressive hypometabolism seen in Lewy body disorders cannot be fully explained by generalized synaptic degeneration. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Exploring the neuroprotective effects of montelukast on brain inflammation and metabolism in a rat model of quinolinic acid-induced striatal neurotoxicity

BackgroundOne intrastriatal administration of quinolinic acid (QA) in rats induces a lesion with features resembling those observed in Huntington’s disease. Our aim is to evaluate the effects of the cysteinyl leukotriene receptor antagonist montelukast (MLK), which exhibited neuroprotection in different preclinical models of neurodegeneration, on QA-induced neuroinflammation and regional metabolic functions.MethodsThe right and left striatum of Sprague Dawley and athymic nude rats were injected with QA and vehicle (VEH), respectively. Starting from the day before QA injection, animals were treated with 1 or 10 mg/kg of MLK or VEH for 14 days. At 14 and 30 days post-lesion, animals were monitored with magnetic resonance imaging (MRI) and positron emission tomography (PET) using [18F]-VC701, a translocator protein (TSPO)-specific radiotracer. Striatal neuroinflammatory response was measured post-mortem in rats treated with 1 mg/kg of MLK by immunofluorescence. Rats treated with 10 mg/kg of MLK also underwent a [18F]-FDG PET study at baseline and 4 months after lesion. [18F]-FDG PET data were then used to assess metabolic connectivity between brain regions by applying a covariance analysis method.ResultsMLK treatment was not able to reduce the QA-induced increase in striatal TSPO PET signal and MRI lesion volume, where we only detected a trend towards reduction in animals treated with 10 mg/kg of MLK. Post-mortem immunofluorescence analysis revealed that MLK attenuated the increase in striatal markers of astrogliosis and activated microglia in the lesioned hemisphere. We also found a significant increase in a marker of anti-inflammatory activity (MannR) and a trend towards reduction in a marker of pro-inflammatory activity (iNOS) in the lesioned striatum of MLK—compared to VEH-treated rats. [18F]-FDG uptake was significantly reduced in the striatum and ipsilesional cortical regions of VEH-treated rats at 4 months after lesion. MLK administration preserved glucose metabolism in these cortical regions, but not in the striatum. Finally, MLK was able to counteract changes in metabolic connectivity and measures of network topology induced by QA, in both lesioned and non-lesioned hemispheres.ConclusionsOverall, MLK treatment produced a significant neuroprotective effect by reducing neuroinflammation assessed by immunofluorescence and preserving regional brain metabolism and metabolic connectivity from QA-induced neurotoxicity in cortical and subcortical regions.

Chronic fluoxetine enhances extinction therapy for PTSD by evaluating brain glucose metabolism in rats: an [18F]FDG PET study.

Recent studies suggest that selective serotonin reuptake inhibitors (SSRIs) and exposure therapies have been used to reduced footshock-induced posttraumatic stress disorder (PTSD) symptoms. However, the therapeutic effect of the combination of SSRIs treatment with exposure therapy remains a matter of debate. This study aimed to evaluate these therapeutic effect through the behavioural and the neuroimaging changes by positron emission tomography (PET) in model rats. Pavlovian fear conditioning paradigm to establish model rats, and serial PET imaging with 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) was performed during the control, fear-conditioning, and extinction-retrieval phases. The expression of c-Fos was used to identify neural activity. We report that fear conditioning increased glucose metabolism in the right amygdala and left primary visual cortex but decreased glucose metabolism in the left primary somatosensory cortex. After extinction retrieval, there was increased [18F]FDG uptake in the left striatum, left cochlear nucleus and right primary visual cortex but decreased uptake in the anterior cingulate cortex in the extinction group. Fluoxetine increased [18F]FDG uptake in the left hippocampus and right primary visual cortex but decreased uptake in the bilateral primary somatosensory cortex, left primary/secondary motor cortex and cuneiform nucleus. The combined therapy increased [18F]FDG uptake in the left hippocampus, left striatum, right insular cortex, left posterior parietal cortex, and right secondary visual cortex but reduced uptake in the cerebellar lobule. c-Fos expression in the hippocampal dentate gyrus and anterior cingulate cortex in the fluoxetine and combined groups was significantly higher than that in the extinction group, with no significant difference between the two groups. Chronic fluoxetine enhanced the effects of extinction training in a rat model of PTSD. In vivo PET imaging may provide a promising approach for evaluation chronic fluoxetine treatment of PTSD.

Feature-based Quality Assessment of Middle Cerebral Artery Occlusion Using 18F-Fluorodeoxyglucose Positron Emission Tomography.

In animal experiments, ischemic stroke is usually induced through middle cerebral artery occlusion (MCAO), and quality assessment of this procedure is crucial. However, an accurate assessment method based on 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is still lacking. The difficulty lies in the inconsistent preprocessing pipeline, biased intensity normalization, or unclear spatiotemporal uptake of FDG. Here, we propose an image feature-based protocol to assess the quality of the procedure using a 3D scale-invariant feature transform and support vector machine. This feature-based protocol provides a convenient, accurate, and reliable tool to assess the quality of the MCAO procedure in FDG PET studies. Compared with existing approaches, the proposed protocol is fully quantitative, objective, automatic, and bypasses the intensity normalization step. An online interface was constructed to check images and obtain assessment results.

BIMG-06. RESPONSE ASSESSMENT OF BEVACIZUMAB THERAPY FOR GLIOBLASTOMA BY USING MULTIPLE PET TRACERS

OBJECTIVEUse of the positron emission tomography (PET), such as 18F-fluorodeoxyglucose (FDG), 11C-Methionine (MET), 18F- Fluorothymidine (FLT), and 18F-Fluoromisonidazole (FMISO), is expected to lead the way for novel applications aimed at achieving efficient malignancy grading and treatment of gliomas. The aim of this study was to assess FDG, MET, FLT, and FMISO PET studies to evaluate the biological effects induced by bevacizumab (BEV) therapy in glioblastoma patients.METHODSSeventy-one patients with glioblastoma were treated biweekly with BEV from July 2013 to November 2020. FDG, MET, FLT, and FMISO PET scans were obtained at baseline and at follow-up (4 weeks after treatment onset). Measures of FDG, MET, FLT, and FMISO avidity were recorded; the measures were SUVmax, metabolic tumor volume (MTV; volume of tumor with SUV>42% of SUVmax), SUVmean (within the MTV), tumor-to-normal ratio (TNR), tumor-to blood ratio (TBR), and total lesion avidity (TLA; calculated as MTV x SUVmean). The prognostic analysis was performed in relation to the response assessment by multiple PET tracers using progression-free survival (PFS) and overall survival (OS).RESULTSUnder the assessment of the Cox proportional hazard model, increased changes of FDG SUVmax, MET TLA at follow-up, FLT TLA at follow up, increased changes of FLT TLA, increased changes of FMISO TBR and FMISO MTV were significant prognostic factor of PFS. Increase changes of FDG TLA and FLT TLA and increased changes of FMISO TBR were significant prognostic factor of OS.CONCLUSIONIncreased changes in FLT TLA and FMISO-PET after BEV therapy may be a useful biomarker for predicting PFS and OS in glioblastoma.

Differential Diagnosis of Parkinsonism with Deep Metabolic Imaging Biomarker – An Artificial Intelligence-Aided Multi-Cohort FDG PET Study

Background: The clinical presentation of early idiopathic Parkinson’s disease (IPD) substantially overlaps with that of atypical parkinsonian syndromes such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) has proven useful in assisting in the differential diagnosis of these parkinsonian syndromes. The aim of this study was to develop a metabolic imaging biomarker based on deep learning to support the differential diagnosis of parkinsonism. Methods: In addition to 863 non-parkinsonian subjects, a total of 1275 parkinsonian patients were accessed who underwent FDG PET imaging, clinical evaluation, and follow-up, yielding clinically possible, definite, or confirmative diagnoses of IPD, MSA, and PSP. A 3D deep convolutional neural network was developed to extract a deep metabolic imaging (DMI) biomarker. The accuracy of the DMI biomarker was evaluated with a cross-validation and a blind test. The robustness of the DMI biomarker was assessed on patients with longitudinal follow-up. The functional basis of DMI biomarker was further investigated based on the saliency map of the obtained deep neural network. Findings: The proposed DMI biomarker achieved an area under the receiver operating characteristic curve of 0·986 for the differential diagnosis of IPD, 0·997 for MSA, and 0·982 for PSP in the cross-validation. In the blind test, the DMI biomarker resulted in sensitivities of 98·1%, 88·5%, and 84·5%, as well as specificities of 90·0%, 99·2%, and 97·8% for IPD, MSA, and PSP respectively. The integration of demographic information and clinical assessments to DMI biomarker resulted in slight improvements. Saliencies for the DMI biomarker were found in several parkinsonism-related regions such as midbrain, putamen, and cerebellum. Interpretation: The DMI biomarker based on deep learning shows potential to provide accurate differential diagnosis for parkinsonism on FDG PET. The functional regions behind the DMI biomarker are consistent with known parkinsonian pathology. Funding Statement: The work was supported by grants from the National Natural Science Foundation of China (No. 81771483, 81671239, 81361120393, 81401135, 81971641, 81902282, 91949118, 81771372), from the Ministry of Science and Technology of China (2016YFC1306504), Shanghai Municipal Science and Technology Major Project (No. 2017SHZDZX01, 2018SHZDZX03) and ZJ Lab, Shanghai Sailing Program (No. 18YF1403100). It was also supported by Swiss National Science Foundation (No. 188350) and Siemens Healthineers. Declaration of Interests: W.H.O is Hertie Senior Research Professor, supported by the Charitable Hertie Foundation, Frankfurt/Main, Germany. A.R. and K.S. received research support from Siemens Healthineer. Other authors report no financial interests or potential conflicts of interest regarding the subject matter of the manuscript. Ethics Approval Statement: All procedures performed in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All the data were from Parkinson's Disease Database and Samples Bank in Huashan Hospital. Ethics permission was obtained from the Institutional Review Board of Huashan Hospital and written consent was obtained from each subject after detailed explanation of the procedures.

Machine learning derived input-function in a dynamic 18F-FDG PET study of mice

Tracer kinetic modelling, based on dynamic 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is used to quantify glucose metabolism in humans and animals. Knowledge of the arterial input-function (AIF) is required for such measurements. Our aim was to explore two non-invasive machine learning-based models, for AIF prediction in a small-animal dynamic FDG PET study. 7 tissue regions were delineated in images from 68 FDG PET/computed tomography mouse scans. Two machine learning-based models were trained for AIF prediction, based on Gaussian processes (GP) and a long short-term memory (LSTM) recurrent neural network, respectively. Because blood data were unavailable, a reference AIF was formed by fitting an established AIF model to vena cava and left ventricle image data. The predicted and reference AIFs were compared by the area under curve (AUC) and root mean square error (RMSE). Net-influx rate constants, Ki, were calculated with a two-tissue compartment model, using both predicted and reference AIFs for three tissue regions in each mouse scan, and compared by means of error, ratio, correlation coefficient, P value and Bland-Altman analysis. The impact of different tissue regions on AIF prediction was evaluated by training a GP and an LSTM model on subsets of tissue regions, and calculating the RMSE between the reference and the predicted AIF curve. Both models generated AIFs with AUCs similar to reference. The LSTM models resulted in lower AIF RMSE, compared to GP. Ki from both models agreed well with reference values, with no significant differences. Myocardium was highlighted as important for AIF prediction, but AIFs with similar RMSE were obtained also without myocardium in the input data. Machine learning can be used for accurate and non-invasive prediction of an image-derived reference AIF in FDG studies of mice. We recommend the LSTM approach, as this model predicts AIFs with lower errors, compared to GP.

Development of sodium fluoride PET response criteria for solid tumours (NAFCIST) in a clinical trial of radium-223 in osteosarcoma: from RECIST to PERCIST to NAFCIST

PurposeThe development of osteosarcoma therapeutics has been challenging, in part because of the lack of appropriate criteria to evaluate responses. We developed a novel criteria in a clinical trial of radium-223 dichloride (223RaCl2) for response assessment in osteosarcoma, NAFCIST (Na18F PET response Criteria in Solid Tumors).Experimental designPatients received one to six cycles of 223RaCl2, and cumulative doses varied from 6.84 MBq to 57.81 MBq. Molecular imaging with technetium-99m phosphonate scintigraphy, fluorine-18-fluorodeoxyglucose (18FDG) positron emission tomography (PET) or sodium fluoride-18 (Na18F) PET was used to characterise the disease. Correlation of biomarkers and survival was analysed with NAFCIST measure from Na18F PET.ResultsOf the 18 patients, 17 had bone lesions visible in at least one of the imaging studies. In four of seven patients with multiple skeletal lesions (>5), FDG PET and NaF PET studies could be compared. The skeletal tumour locations varied in our patient population: cranium=2, extremities=7, pelvis=10, spine=12 and thorax=9. The 18F-FDG PET and Na18F PET studies could be compared in all four patients who had multiple lung lesions (>5). Overall the Response Evaluation Criteria in Solid Tumors response was seen in one patient, but four patients experienced mixed responses better defined by Na18F PET. Changes in NAFCIST were correlated with changes in bone alkaline phosphatase levels (r=0.54) and negatively with cumulative dose of 223RaCl2 (r=− 0.53). NAFCIST correlated with overall survival (p value of 0.037) while the PERCIST (PET Response Criteria in Solid Tumors) did not (p value of 0.19).ConclusionsOur results indicate that Na18F PET should be further studied in osteosarcoma staging. NAFCIST may be a promising criteria for high-risk osteosarcoma response evaluation and correlates with survival. Further validation studies are needed.

Preliminary Results that Assess Metformin Treatment in a Preclinical Model of Pancreatic Cancer Using Simultaneous [18F]FDG PET and acidoCEST MRI.

We sought to determine if the synergy between evaluations of glucose uptake in tumors and extracellular tumor acidosis measured with simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) can improve longitudinal evaluations of the response to metformin treatment. A standard 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) PET protocol that evaluates glucose uptake in tumors, and a standard acidoCEST MRI protocol that measures extracellular pH (pHe) in tumors, were simultaneously performed to assess eight vehicle-treated (control) mice and eight metformin-treated mice 1day before treatment, 1day after initiating daily treatment with metformin, and 7days after initiating treatment. Longitudinal changes in SUVmax and extracellular pH (pHe) were evaluated for each treatment group, and differences in SUVmax and pHe between metformin-treated and control groups were also evaluated. MRI acquisition protocols had little effect on the PET count rate, and the PET instrumentation had little effect on image contrast during acidoCEST MRI, verifying that [18F]FDG PET and acidoCEST MRI can be performed simultaneously. The average SUVmax of the tumor model had a significant decrease after 7days of treatment with metformin, as expected. The average tumor pHe decreased after 7days of metformin treatment, which reflected the inhibition of the consumption of cytosolic lactic acid caused by metformin. However, the average SUVmax of the tumor model was not significantly different between the metformin-treated and control groups after 7days of treatment, and average pHe was also not significantly different between these groups. For comparison, the combination of average SUVmax and pHe measurements significantly differed between the treatment group and control group on Day 7. [18F]FDG PET and acidoCEST MRI studies can be performed simultaneously. The synergistic combination of assessing glucose uptake and tumor acidosis can improve differentiation of a drug-treated group from a control group during drug treatment of a tumor model.

Quantitative and Visual Assessments toward Potential Sub-mSv or Ultrafast FDG PET Using High-Sensitivity TOF PET in PET/MRI.

Newer high-performance time-of-flight (TOF) positron emission tomography (PET) systems have the capability to preserve diagnostic image quality with low count density, while maintaining a high raw photon detection sensitivity that would allow for a reduction in injected dose or rapid data acquisition. To assess this, we performed quantitative and visual assessments of the PET images acquired using a highly sensitive (23.3cps/kBq) large field of view (25-cm axial) silicon photomultiplier (SiPM)-based TOF PET (400-ps timing resolution) integrated with 3T-MRI in comparison to PET images acquired on non-TOF PET/x-ray computed tomography (CT) systems. Whole-body 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) PET/CT was acquired for 15 patients followed by whole body PET/magnetic resonance imaging (MRI) with an average injected dose of 325±84MBq. The PET list mode data from PET/MRI were reconstructed using full datasets (4min/bed) and reduced datasets (2, 1, 0.5, and 0.25min/bed). Qualitative assessment between PET/CT and PET/MR images were made. A Likert-type scale between 1 and 5, 1 for non-diagnostic, 3 equivalent to PET/CT, and 5 superior quality, was used. Maximum and mean standardized uptake values (SUVmax and SUVmean) of normal tissues and lesions detected were measured and compared. Mean visual assessment scores were 3.54±0.32, 3.62±0.38, and 3.69±0.35 for the brain and 3.05±0.49, 3.71±0.45, and 4.14±0.44 for the whole-body maximum intensity projections (MIPs) for 1, 2, and 4min/bed PET/MR images, respectively. The SUVmean values for normal tissues were lower and statistically significant for images acquired at 4, 2, 1, 0.5, and 0.25min/bed on the PET/MR, with values of -18±28% (p < 0.001), - 16±29% (p = 0.001), - 16±31% (p = 0.002), - 14±35% (p < 0.001), and - 13±34% (p = 0.002), respectively. SUVmax and SUVpeak values of all lesions were higher and statistically significant (p < 0.05) for 4, 2, 1, 0.50, and 0.25min/bed PET/MR datasets. High-sensitivity TOF PET showed comparable but still better visual image quality even at a much reduced activity in comparison to lower-sensitivity non-TOF PET. Our data translates to a seven times reduction in either injection dose for the same time or total scan time for the same injected dose. This "ultra-sensitivity" PET system provides a path to clinically acceptable extremely low-dose FDG PET studies (e.g., sub 1mCi injection or sub-mSv effective dose) or PET studies as short as 1min/bed (e.g., 6min of total scan time) to cover whole body without compromising diagnostic performance.

The effects of nicotine administration and drug cue on impulsivity

Several [18F]-FDG positron emission tomography (PET) studies in alcoholics have consistently reported decreases in overall brain glucose metabolism at rest and following acute alcohol administration. However, changes in cerebral glucose utilization associated with the transition to addiction are not well understood and require longitudinal translational imaging studies in animal models of alcoholism. Here, we studied brain glucose uptake in alcohol drinking rats in order to provide convergent evidence to what has previously been reported in human studies. Brain glucose metabolism was measured by [18F]-FDG microPET imaging in different male Wistar rat groups: short-term drinking (three months), long-term drinking (twelve months) and alcohol-naïve. Global and regional cerebral glucose uptake was measured at rest and following acute alcohol administration. We showed that alcohol significantly reduced the whole-brain glucose metabolism. This effect was most pronounced in the parietal cortex and cerebellum. Alcohol-induced decreases in brain [18F]-FDG uptake was most apparent in alcohol-naïve rats, less intense in short-term drinkers and absent in long-term drinkers. The latter finding indicates the occurrence of tolerance to the intoxicating effects of alcohol in long-term drinking individuals. In contrast, some regions, like the ventral striatum and entorhinal cortex, showed enhanced metabolic activity, an effect that did not undergo tolerance during long-term alcohol consumption. Our findings are comparable to those described in human studies using the same methodology. We conclude that [18F]-FDG PET studies in rat models of alcoholism provide good translation and can be used for future longitudinal studies investigating alterations in brain function during different stages of the addiction cycle.

Generalized Lymphadenopathy due to Chronic Lymphocytic Leukemia (CLL) : 18F-FDG PET Imaging

Lymphadenopaty is a common clinical finding with a broad differential diagnosis, withCarcinoma of Unknown Primary (CUP) as one of it’s most common causes. Flourine-18 fluoro-2 deoxy glucose (18F- FDG) positron emission tomography (PET) is a Nuclear Medicinescintigraphy procedure commonly used to localize suspected a primary lesion by depicting ametabolic status. However, in the expertise of 18F FDG PET study, clinical finding andepidemiologic data must be considered to get a better conclusion. We describe 18F-FDG PETstudy in the presence of generalized lymphadenopathy due to chronic lymphocytic leukemia(CLL), a rare disease which is initially suspected of having CUP.Keywords: 18F-FDG PET, lymphadenopathy, lymphoma, leukemia

Improved Derivation of Input Function in Dynamic Mouse [18F]FDG PET Using Bladder Radioactivity Kinetics

Accurate determination of the plasma input function (IF) is essential for absolute quantification of physiological parameters in positron emission tomography (PET). However, it requires an invasive and tedious procedure of arterial blood sampling that is challenging in mice because of the limited blood volume. In this study, a hybrid modeling approach is proposed to estimate the plasma IF of 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) in mice using accumulated radioactivity in urinary bladder together with a single late-time blood sample measurement. Dynamic PET scans were performed on nine isoflurane-anesthetized male C57BL/6 mice after a bolus injection of [18F]FDG at the lateral caudal vein. During a 60- or 90-min scan, serial blood samples were taken from the femoral artery. Image data were reconstructed using filtered backprojection with computed tomography-based attenuation correction. Total accumulated radioactivity in the urinary bladder at late times was fitted to a renal compartmental model with the last blood sample and a one-exponential function that described the [18F]FDG clearance in blood. Multiple late-time blood sample estimates were calculated by the blood [18F]FDG clearance equation. A sum of four-exponentials was assumed for the plasma IF that served as a forcing function to all tissues. The estimated plasma IF was obtained by simultaneously fitting the [18F]FDG model to the time-activity curves (TACs) of liver and muscle and the forcing function to early (0-1 min) left-ventricle data (corrected for delay, dispersion, partial-volume effects, and erythrocyte uptake) and the late-time blood estimates. Using only the blood sample collected at the end of the study to estimate the IF and the use of liver TAC as an alternative IF were also investigated. The area under the plasma IFs calculated for all studies using the hybrid approach was not significantly different from that using all blood samples. [18F]FDG uptake constants in brain, myocardium, skeletal muscle, and liver computed by the Patlak analysis using estimated and measured plasma IFs were in excellent agreement (slope∼1; R2>0.983). The IF estimated using only the last blood sample drawn at the end of the study and the use of liver TAC as the plasma IF provided less reliable results. The estimated plasma IFs obtained with the hybrid method agreed well with those derived from arterial blood sampling. Importantly, the proposed method obviates the need of arterial catheterization, making it possible to perform repeated dynamic [18F]FDG PET studies on the same animal. Liver TAC is unsuitable as an input function for absolute quantification of [18F]FDG PET data.

Neural correlates of delayed episodic memory in patients with mild cognitive impairment—A FDG PET study

Mild cognitive impairment (MCI) is characterized by cognitive deficits which do not yet reach the threshold of dementia but represent a putative preclinical state of Alzheimer's disease (AD). Little is known about the neural correlates of delayed episodic memory which is among the earliest signs of cognitive decline in patients at risk of developing AD. We performed resting state positron emission tomography (PET) with 18Fluorodeoxyglucose (FDG) in patients with MCI, and hypothesized a correlation between delayed episodic memory performance and frontal glucose metabolism since the latter is relatively spared in the preclinical phase of the disease. 43 patients (age: 69.7 ± 7.9 years; 24 male, 19 female) with MCI were investigated by FDG PET. Significant positive correlations with delayed episodic memory performance were calculated by statistical parametric mapping. To our knowledge the present study is the first to demonstrate by FDG PET the neural correlates of delayed episodic memory in patients with MCI. Our study revealed a pattern of cerebral glucose metabolism including bifrontal regions which may contribute to the delayed episodic memory performance of patients with MCI. Since not all patients with MCI will further deteriorate, AD specific mechanism may not be concluded from the present study but warrant longitudinal investigations.

Individual cerebral metabolic deficits in Alzheimer’s disease and amnestic mild cognitive impairment: an FDG PET study

The purpose of the study was the identification of group and individual subject patterns of cerebral glucose metabolism (CMRGlu) in patients with Alzheimer's disease (AD) and with amnestic mild cognitive impairment (aMCI). [(18)F]fluorodeoxyglucose positron emission tomography (PET) studies and neuropsychological tests were performed in 16 aMCI patients (ten women, age 75+/-8 years) and in 14 AD patients (ten women, age 75+/-9 years). Comparisons between patient subgroups and with a control population were performed using Statistical Parametric Mapping. Clusters of low CMRGlu were observed bilaterally in the posterior cingulate cortex (PCC), in the precuneus, in the inferior parietal lobule and middle temporal gyrus of AD patients. In aMCI patients, reduced CMRGlu was found only in PCC. Areas of low CMRGlu in PCC were wider in AD compared to aMCI and extended to the precuneus, while low CMRGlu was found in the lateral parietal cortex in AD but not in aMCI patients. Individual subject pattern analysis revealed that 86% of AD patients had low CMRGlu in the PCC (including the precuneus in 71%), 71% in the temporal cortex, 64% in the parietal cortex and 35% in the frontal cortex. Among the aMCI patients, 56% had low CMRGlu in the PCC, 44% in the temporal cortex, 18% in the frontal cortex and none in the parietal cortex. This study demonstrates that both AD and aMCI patients have highly heterogeneous metabolic impairment. This potential of individual metabolic PET imaging in patients with AD and aMCI may allow timely identification of brain damage on individual basis and possibly help planning tailored early interventions.

Comparaison entre les modes d’acquisition 2D et 3D en TEP au FDG

Aim Some positron emission tomography (PET) cameras offer the possibility of choosing between the 2D and 3D acquisition modes. Due to the lack of comparative and objective data in the litterature between the two modes in clinical routine conditions, we have performed a comparative study based on the assessment of qualitative and quantitative parameters. Materials and methods A series of 33 FDG PET studies has been prospectively selected in the nuclear medicine department. All studies have been performed with a Discovery ST ® camera (GE healthcare) first in the 2D or 3D mode according to the usual criteria of the department. Then a new single step was acquired on a pathological region using the other mode. The same single slice was chosen and analyzed in the two modes (blindly and in random order) by seven nuclear physicians in terms of qualitative and quantitative parameters. Results The 2D mode is significantly better than 3D concerning the overall image quality for patients with a body mass index (BMI) > 27.5 ( p = 0.006) and concerning the confidence in lesion reporting for patients with a BMI > 25 ( p = 0.01). The mean number of detected lesions is not affected by the acquisition mode but it is significantly correlated with the image quality and the confidence in lesion reporting ( p = 0.07 and p = 0.013, respectively). Conclusion With the Discovery ST PET-CT, the 2D mode gives better results than 3D for overweight and obese patients in terms of image quality and confidence in lesion reporting.

Clustering‐Based Linear Least Square Fitting Method for Generation of Parametric Images in Dynamic FDG PET Studies

Parametric images generated from dynamic positron emission tomography (PET) studies are useful for presenting functional/biological information in the 3-dimensional space, but usually suffer from their high sensitivity to image noise. To improve the quality of these images, we proposed in this study a modified linear least square (LLS) fitting method named cLLS that incorporates a clustering-based spatial constraint for generation of parametric images from dynamic PET data of high noise levels. In this method, the combination of K-means and hierarchical cluster analysis was used to classify dynamic PET data. Compared with conventional LLS, cLLS can achieve high statistical reliability in the generated parametric images without incurring a high computational burden. The effectiveness of the method was demonstrated both with computer simulation and with a human brain dynamic FDG PET study. The cLLS method is expected to be useful for generation of parametric images from dynamic FDG PET study.

18F]fluoro-2-deoxy-d-glucose ([18F]FDG) positron emission tomography imaging of thymic carcinoid tumor presenting with recurrent Cushing’s syndrome

We report a case of a young woman with Cushing's syndrome (CS), in whom although endocrine investigations and negative pituitary imaging were suggestive of ectopic ACTH secretion, the results of inferior petrosal sinus (IPS) sampling after coricotropin-releasing hormone (CRH) stimulation were suggestive of pituitary ACTH hypersecretion. (111)In-labelled octreotide and high-resolution computer tomography (CT) revealed a lesion possibly responsible for the ACTH source in the thymus. Thymectomy confirmed concomitant ectopic CRH and probable ACTH production by a thymic neuroendocrine carcinoma. After an 8-year remission period the patient developed a clinical and biochemical relapse. A high-resolution computed tomography (CT) scan of the thorax showed a 2-cm nodule in the thymic bed, which was positive on a [(18)F]fluoro-2-deoxy-D-glucose ([(18)F]FDG) positron emission tomography (PET) scan. However, a repeated thymectomy did not result in remission. A repeat [(18)F]FDG PET study showed persistent disease in the thymic bed and also uptake in the adrenals. The patient underwent bilateral adrenalectomy, which resulted in clinical remission. A further [(18)F]FDG PET scan 8 months later showed no progression of the thymic tumor and confirmed complete excision of the adrenals. This is a rare case of concomitant CRH and ACTH secretion from a thymic carcinoid tumor; the case illustrates the usefulness of functional imaging with [(18)F]FDG PET in the diagnosis, management and follow-up of neuroendocrine tumors.