Factors Associated with Myocardial Uptake on Oncologic Somatostatin PET Investigations and Differentiation from Myocardial Uptake of Acute Myocarditis.

Myocardial somatostatin PET uptake is observed not only in most patients with acute myocarditis (AM) but also in some oncology patients referred for routine somatostatin PET. This raises concerns about the specificity of somatostatin PET for detecting myocarditis. The current study aims to identify factors associated with the detection of myocardial uptake on somatostatin PET scans recorded for oncology indications and differential PET criteria that characterize myocardial uptake in AM patients. Methods: We analyzed factors associated with the detection of myocardial [68Ga]Ga-DOTATOC uptake in 508 [68Ga]Ga-DOTATOC PET scans from 178 patients, performed for confirmed or suspected oncologic disease (Onc-PET) and PET criteria that could differentiate myocardial [68Ga]Ga-DOTATOC uptake in 31 patients with MRI-ascertained AM (AM-PET) from that in the Onc-PET group. Results: Significant myocardial uptake was detected in 137 (26.9%) Onc-PET scans and was independently associated with somatostatin analog treatment (exp(ß), 0.805; 95% CI, 0.728-0.890; P < 0.001) and age (exp(ß), 1.005; 95% CI, 1.001-1.009; P = 0.012). A comparable model was selected for predicting the myocardial-to-blood SUVmax ratio using somatostatin analog treatment (P < 0.001) and history of coronary artery disease (P = 0.022). Myocardial uptake was detected in 12.9% (25/193) of Onc-PET scans from patients treated with somatostatin analogs but in 43.4% (59/136) of untreated patients over the median age of 64 y. Myocardial uptake was apparent in all 31 AM-PET scans, with volume and intensity of uptake dramatically higher than in the 137 Onc-PET scans showing myocardial uptake. A myocardial-to-blood SUVmax ratio threshold of 2.20 provided a sensitivity of 87% (27/31) and a specificity of 88% (44/50) for differentiating myocardial uptake between the AM-PET group and an Onc-PET group restricted to patients with clinical characteristics comparable to those of patients in the AM-PET group (≤64 y of age, no coronary artery disease history, and no somatostatin agonists). A myocardial uptake volume threshold of 18 cm3 provided comparable diagnostic accuracy (sensitivity, 84% [26/31]; specificity, 94% [47/50]). Conclusion: Myocardial uptake was detected in 26.9% of somatostatin PET scans recorded for oncology indications. This rate was decreased by somatostatin analog treatments and increased in older individuals. However, somatostatin PET scans, analyzed with the quantitative criterion of uptake intensity or volume, are able to identify AM and to differentiate it from myocardial uptake of other origins.

Association between baseline hemodynamic indices, cardiotoxicity risk, and survival in women with breast cancer.

BACKGROUND: The outcome of breast cancer (BrCa) women monitored by low-dose equilibrium radionuclide angiography (ERNA) remains challenging to predict. AIM: This study aims to determine whether heart rate (HR)/blood pressure (BP) ratio-based indexes, previously confirmed to predict outcomes of various diseases, also predict BrCa-therapy-related cardiotoxicity and survival. METHODS: Predictors of cardiotoxicity and survival were determined among pre-therapy variables, including shock index ([SI HR/systolic BP) and age-adjusted SI (ASI), in a female BrCa cohort with normal baseline ERNA-left ventricular ejection fraction (LVEF). RESULTS: We included 274 women with a median age of 54.8 (interquartile range: 45.5-65.4) years, 271 treated with anthracyclines and 96 with trastuzumab. During a median follow-up of 25.9 (18.6-33.5) months, 31 women developed cardiotoxicity (LVEF: <50% and ≥10% drop from baseline), and 25 died. Baseline ASI was a multivariate predictor (p < 0.001) of (i) cardiotoxicity, in association with trastuzumab treatment (p = 0.010), and LV end-diastolic volume (p = 0.001) and (ii) survival, in association with metastasis (p < 0.001) and estimated glomerular filtration rate (p = 0.008). Cardiotoxicity poorly impacted survival (p = 0.064). The 36-month cardiotoxicity and mortality rates were markedly higher for patients in the upper half of baseline ASI values (ASI: >30 years min-1.mmHg-1, 16.5% and 20.7%, respectively) than in the lower half (7.6% and 4.5%, respectively, both p < 0.05). CONCLUSIONS: In BrCa women with normal baseline ERNA-LVEF, HR/BP ratio-based indexes unmask hemodynamic profiles associated with increased cardiotoxicity risk and decreased survival, highlighting the need for a comprehensive assessment of cardiac- and vascular-related risks in BrCa women monitored by ERNA. CONDENSED ABSTRACT: In a cohort of 274 women BrCa women who were monitored by ERNA for potentially cardiotoxic drugs (anthracyclines or trastuzumab) and who had no history of cardiac disease and a normal left ventricular ejection fraction before treatment, baseline indexes based on HR/BP ratios unmask hemodynamic profiles strongly associated with an increased risk of cardiotoxicity and subsequently decreased survival. Although further validations in other cohorts are needed, these findings highlight the need for a more comprehensive assessment of the cardiac- and vascular-related risk in BrCa women monitored by ERNA.

Assessment of a one-week ketogenic diet on brain glycolytic metabolism and on the status epilepticus stage of a lithium-pilocarpine rat model.

The ketogenic diet (KD) has been shown to be effective in refractory epilepsy after long-term administration. However, its interference with short-term brain metabolism and its involvement in the early process leading to epilepsy remain poorly understood. This study aimed to assess the effect of a short-term ketogenic diet on cerebral glucose metabolic changes, before and after status epilepticus (SE) in rats, by using [18F]-FDG PET. Thirty-nine rats were subjected to a one-week KD (KD-rats, n = 24) or to a standard diet (SD-rats, n = 15) before the induction of a status epilepticus (SE) by lithium-pilocarpine administrations. Brain [18F]-FDG PET scans were performed before and 4 h after this induction. Morphological MRIs were acquired and used to spatially normalize the PET images which were then analyzed voxel-wisely using a statistical parametric-based method. Twenty-six rats were analyzed (KD-rats, n = 15; SD-rats, n = 11). The 7 days of the KD were associated with significant increases in the plasma ß-hydroxybutyrate level, but with an unchanged glycemia. The PET images, recorded after the KD and before SE induction, showed an increased metabolism within sites involved in the appetitive behaviors: hypothalamic areas and periaqueductal gray, whereas no area of decreased metabolism was observed. At the 4th hour following the SE induction, large metabolism increases were observed in the KD- and SD-rats in areas known to be involved in the epileptogenesis process late-i.e., the hippocampus, parahippocampic, thalamic and hypothalamic areas, the periaqueductal gray, and the limbic structures (and in the motor cortex for the KD-rats only). However, no statistically significant difference was observed when comparing SD and KD groups at the 4th hour following the SE induction. A one-week ketogenic diet does not prevent the status epilepticus (SE) and associated metabolic brain abnormalities in the lithium-pilocarpine rat model. Further explorations are needed to determine whether a significant prevention could be achieved by more prolonged ketogenic diets and by testing this diet in less severe experimental models, and moreover, to analyze the diet effects on the later and chronic stages leading to epileptogenesis.

Effects of medication on dopamine transporter imaging using [123I]I-FP-CIT SPECT in routine practice.

PURPOSE: Dopamine transporter (DAT) imaging is used to support the diagnosis of neurodegenerative parkinsonian disorders. Specific medications have been reported to confound the interpretation of [123I]I-FP-CIT SPECT scans, but there is limited data. The aim of the current study is to identify potential medication effects on the interpretation of [123I]I-FP-CIT SPECT scans in routine practice. MATERIALS AND METHODS: Consecutive patients undergoing a [123I]I-FP-CIT SPECT/CT scan on a 360° CZT camera between September 2019 and December 2022 were included. An exhaustive review of patient medications (antidepressants, antipsychotics, anti-epileptics, anti-parkinsonians, benzodiazepines, lithium, opioids, and stimulants) was performed. Two experienced nuclear physicians, blinded to the medication reports, interpreted the [123I]I-FP-CIT SPECT scans visually and a semi-quantitative analysis was performed using a local normal database. RESULTS: The study included 305 patients (71.0 ± 10.4, 135 women) and 145 (47.5%) visually interpreted normal scans. In normal scans, the striatum/occiput radioligand uptake ratio was decreased by noradrenergic and specific serotonergic antidepressants (NASSAs) (n = 15, z-score of - 0.93) and opioid medication (tramadol, n = 6, z-score of - 0.85) and was associated with a younger age in the multivariate analysis. In the overall population, the striatum/occiput ratio was influenced by NASSAs and associated with consensual visual analysis, age, sex, and anti-parkinsonian medications related to the status of the disease. CONCLUSION: Our study confirms the potential impact of antidepressant (NASSA) and opioid (tramadol) medications on the semi-quantitative analysis of [123I]I-FP-CIT SPECT scans. However, when performing a visual analysis, only NASSAs significantly impacted the interpretation of [123I]I-FP-CIT SPECT scans.

Early exposure to mercury and cardiovascular function of seven-year old children in Guadeloupe (French West Indies).

BACKGROUND: The cardiotoxicity of prenatal exposure to mercury has been suggested in populations having regular contaminated seafood intake, though replications in the literature are inconsistent. METHODS: The Timoun Mother-Child Cohort Study was set up in Guadeloupe, an island in the Caribbean Sea where seafood consumption is regular. At seven years of age, 592 children underwent a medical examination, including cardiac function assessment. Blood pressure (BP) was taken using an automated blood pressure monitor, heart rate variability (HRV, 9 parameters) and electrocardiogram (ECG) characteristics (QT, T-wave parameters) were measured using Holter cardiac monitoring during the examination. Total mercury concentrations were measured in cord blood at birth (median = 6.6 µg/L, N = 399) and in the children's blood at age 7 (median = 1.7 µg/L, N = 310). Adjusted linear and non-linear modelling was used to study the association of each cardiac parameter with prenatal and childhood exposures. Sensitivity analyses included co-exposures to lead and cadmium, adjustment for maternal seafood consumption, selenium and polyunsaturated fatty acids (n3-PUFAs), and for sporting activity. RESULTS: Higher prenatal mercury was associated with higher systolic BP at 7 years of age (ßlog2 = 1.02; 95% Confidence Interval (CI) = 0.10, 1.19). In boys, intermediate prenatal exposure was associated with reduced overall HRV and parasympathetic activity, and longer QT was observed with increasing prenatal mercury (ßlog2 = 4.02; CI = 0.48, 7.56). In girls, HRV tended to increase linearly with prenatal exposure, and no association was observed with QT-wave related parameters. Mercury exposure at 7 years was associated with decreased BP in girls (ßlog2 = -1.13; CI = -2.22, -0.004 for diastolic BP). In boys, the low/high-frequency (LF/HF) ratio increased for intermediate levels of exposure. CONCLUSION: Our study suggests sex-specific and non-monotonic modifications in some cardiac health parameters following prenatal exposure to mercury in pre-pubertal children from an insular fish-consuming population.

Body Surface Gastrointestinal Potential Mapping: A Simulation Framework to Evaluate Source Separation Algorithms.

Gastrointestinal (GI) potential mapping could be useful for evaluating GI motility disorders. Such disorders are found in inflammatory bowel diseases, such as Crohn's disease, or GI functional disorders. GI potential mapping data originate from a mixture of several GI electrophysiological sources (termed ExG) and other noise sources, including the electrocardiogram (ECG) and respiration. Denoising and/or source separation techniques are required, however, with real measurements, no ground truth is available. In this paper we propose a framework for the simulation of body surface GI potential mapping data. The framework is an electrostatic model, based on fecgsyn toolbox, using dipoles as electrical sources for the heart, stomach, small bowel and colon, and an array of surface electrodes. It is shown to generate realistic ExG waveforms, which are then used to compare several ECG and respiration cancellation techniques, based on, fast independent component analysis (FastICA) and pseudo-periodic component analysis (PiCA). The best performance was obtained with PiCA with a median root mean squared error of 0.005.

Identification of resting-state networks using dynamic brain perfusion SPECT imaging: A fSPECT case report.

Connectivity studies with nuclear medicine systems are scarce in literature. They mainly employ PET imaging and group level analyses due to the low temporal resolution of PET and especially SPECT imaging. Our current study analyses connectivity at an individual level using dynamic SPECT imaging, which has been enabled by the improved temporal resolution performances provided by the 360°CZT cameras. We present the case of an 80-year-old man referred for brain perfusion SPECT imaging for cognitive disorders for whom a dynamic SPECT acquisition was performed utilizing a 360°CZT camera (temporal sampling of 15 frames × 3 s, 10 frames × 15 s, 14 frames × 30 s), followed by a conventional static acquisition of 15 m. Functional SPECT connectivity (fSPECT) was assessed through a seed correlation analysis and 5 well-known resting-state networks were identified: the executive, the default mode, the sensory motor, the salience, and the visual networks. This case report supports the feasibility of fSPECT imaging to identify well known resting-state networks, thanks to the novel properties of a 360°CZT camera, and opens the way to the development of more dedicated functional connectivity studies using brain perfusion SPECT imaging.

Brain 18F-FDG PET imaging in outpatients with post-COVID-19 conditions: findings and associations with clinical characteristics.

BACKGROUND: Brain 18F-FDG PET imaging has the potential to provide an objective assessment of brain involvement in post-COVID-19 conditions but previous studies of heterogeneous patient series yield inconsistent results. The current study aimed to investigate brain 18F-FDG PET findings in a homogeneous series of outpatients with post-COVID-19 conditions and to identify associations with clinical patient characteristics. METHODS: We retrospectively included 28 consecutive outpatients who presented with post-COVID-19 conditions between September 2020 and May 2022 and who satisfied the WHO definition, and had a brain 18F-FDG PET for suspected brain involvement but had not been hospitalized for COVID-19. A voxel-based group comparison with 28 age- and sex-matched healthy controls was performed (p-voxel at 0.005 uncorrected, p-cluster at 0.05 FWE corrected) and identified clusters were correlated with clinical characteristics. RESULTS: Outpatients with post-COVID-19 conditions exhibited diffuse hypometabolism predominantly involving right frontal and temporal lobes including the orbito-frontal cortex and internal temporal areas. Metabolism in these clusters was inversely correlated with the number of symptoms during the initial infection (r = - 0.44, p = 0.02) and with the duration of symptoms (r = - 0.39, p = 0.04). Asthenia and cardiovascular, digestive, and neurological disorders during the acute phase and asthenia and language disorders during the chronic phase (p ≤ 0.04) were associated with these hypometabolic clusters. CONCLUSION: Outpatients with post-COVID-19 conditions exhibited extensive hypometabolic right fronto-temporal clusters. Patients with more numerous symptoms during the initial phase and with a longer duration of symptoms were at higher risk of persistent brain involvement.

Metabolic connectivity is associated with seizure outcome in surgically treated temporal lobe epilepsies: A 18F-FDG PET seed correlation analysis.

18F-FDG PET provides high sensitivity for the pre-surgical assessment of drug-resistant temporal lobe epilepsy (TLE). However, little is known about the metabolic connectivity of epileptogenic networks involved. This study therefore aimed to evaluate the association between metabolic connectivity and seizure outcome in surgically treated TLE. METHODS: The study included 107 right-handed patients that had undergone a presurgical interictal 18F-FDG PET assessment followed by an anterior temporal lobectomy and were classified according to seizure outcome 2 years after surgery. Metabolic connectivity was evaluated by seed correlation analysis in left and right epilepsy patients with a Class Engel IA or > IA outcome and compared to age-, sex- and handedness-matched healthy controls. RESULTS: Increased metabolic connectivity was observed in the >IA compared to the IA group within the operated temporal lobe (respective clusters of 7.5 vs 3.3 cm3 and 2.6 cm3 vs 2.2 cm3 in left and right TLE), and to a lower extent with the contralateral temporal lobe (1.2 vs 0.7 cm3 and 1.7 cm3 vs 0.7 cm3 in left and right TLE). Seed correlations provided added value for the estimated individual performance of seizure outcome over the group comparisons in left TLE (AUC of 0.74 vs 0.67). CONCLUSION: Metabolic connectivity is associated with outcome in surgically treated TLE with a strengthened epileptogenic connectome in patients with non-free-seizure outcomes. The added value of seed correlation analysis in left TLE underlines the importance of evaluating metabolic connectivity in network related diseases.

A comparative study of the performance of methods for f-wave extraction.

Objective.This study proposes a novel technique for atrial fibrillatory waves (f-waves) extraction and investigates the performance of the proposed method comparing with different f-wave extraction methods.Approach.We propose a novel technique combining a periodic component analysis (PiCA) and echo state network (ESN) for f-waves extraction, denoted PiCA-ESN. PiCA-ESN benefits from the advantages of using both source separation and nonlinear adaptive filtering. PiCA-ESN is evaluated by comparing with other state-of-the-art approaches, which include template subtraction technique based on principal component analysis, spatiotemporal cancellation, nonlinear adaptive filtering using an echo state neural network, and a source separation technique based on PiCA. Quality assessment is performed on a recently published reference database including a large number of simulated ECG signals in atrial fibrillation (AF). The performance of the f-wave extraction methods is evaluated in terms of signal quality metrics (SNR, ΔSNR) and robustness of f-wave features.Main results.The proposed method offers the best signal quality performance, with a ΔSNR of approximately 22 dB across all 8 sets of the reference database, as well as the most robust extraction of f-wave features, with 75% of all estimates of dominant atrial frequency well below 1 Hz.

Interactions Between Brain 18F-FDG PET Metabolism and Hemodynamic Parameters at Different Ages of Life: Results From a Prospective Cross-Sectional Study.

Brain 18F-FDG PET imaging is useful to characterize accelerated brain aging at a pre-symptomatic stage. This study aims to examine the interactions between brain glycolytic metabolism and hemodynamic parameters in different age groups. Methods: A total of 72 patients (from 23 to 88 years of age, 38 women) without any cerebral diseases but with available cardiac, arterial peripheral, and central blood pressure measurements as well as arterial stiffness parameters obtained from brachial pressure and applanation tonometry and a brain 18F-FDG PET scan were prospectively included into this study. Quantitative voxel-to-voxel analyses were carried out to test for negative associations between brain glycolytic metabolism and individual hemodynamic parameters (p-voxel of <0.001 for the whole population and <0.005 for age groups). Results: The heart rate parameter of the whole population showed the most extensive associations with brain metabolism (15,857 mm3, T-score: 5.1), predominantly affecting the frontal and temporal regions (69% of the volume). Heart rate for the younger age group, systolic and pulse pressure for the 41-60-year-old group, and diastolic pressure for the older group were most extensively associated with brain metabolism and mainly involved the fronto-temporal lobes (respective involvement of 52.8%, 60.9%, and 65.5%) which are also the regions implicated in accelerated brain aging. Conclusion: This cross-sectional prospective study identified extensive associations between cerebral metabolism and hemodynamic parameters, indicating common aging mechanisms. Heart rate throughout adult life, systolic and pulse pressure parameters around middle age, and diastolic pressure parameters in older patients, suggest the existence of potentially therapeutic targets to prevent accelerated brain aging.

Multi-tracer and multiparametric PET imaging to detect the IDH mutation in glioma: a preclinical translational in vitro, in vivo, and ex vivo study.

BACKGROUND: This translational study explores multi-tracer PET imaging for the non-invasive detection of the IDH1 mutation which is a positive prognostic factor in glioma. METHODS: U87 human high-grade glioma (HGG) isogenic cell lines with or without the IDH1 mutation (CRISP/Cas9 method) were stereotactically grafted into rat brains, and examined, in vitro, in vivo and ex vivo. PET imaging sessions, with radiotracers specific for glycolytic metabolism ([18F]FDG), amino acid metabolism ([18F]FDopa), and inflammation ([18F]DPA-714), were performed sequentially during 3-4 days. The in vitro radiotracer uptake was expressed as percent per million cells. For each radiotracer examined in vivo, static analyses included the maximal and mean tumor-to-background ratio (TBRmax and TBRmean) and metabolic tumor volume (MTV). Dynamic analyses included the distribution volume ratio (DVR) and the relative residence time (RRT) extracted from a reference Logan model. Ex vivo analyses consisted of immunological analyses. RESULTS: In vitro, IDH1+ cells (i.e. cells expressing the IDH1 mutation) showed lower levels of [18F]DPA-714 uptake compared to IDH1- cells (p < 0.01). These results were confirmed in vivo with lower [18F]DPA-714 uptake in IDH+ tumors (3.90 versus 5.52 for TBRmax, p = 0.03). Different values of [18F]DPA-714 and [18F] FDopa RRT (respectively 11.07 versus 22.33 and 2.69 versus - 1.81 for IDH+ and IDH- tumors, p < 0.02) were also observed between the two types of tumors. RRT [18F]DPA-714 provided the best diagnostic performance to discriminate between the two cell lines (AUC of 100%, p < 0.01). Immuno-histological analyses revealed lower expression of Iba-1 and TSPO antibodies in IDH1+ tumors. CONCLUSIONS: [18F]DPA-714 and [18F] FDopa both correlate with the presence of the IDH1 mutation in HGG. These radiotracers are therefore good candidates for translational studies investigating their clinical applications in patients.

Preliminary Study of New Gallium-68 Radiolabeled Peptide Targeting NRP-1 to Detect Brain Metastases by Positron Emission Tomography.

Due to their very poor prognosis and a fatal outcome, secondary brain tumors are one of the biggest challenges in oncology today. From the point of view of the early diagnosis of these brain micro- and macro-tumors, the sensitivity and specificity of the diagnostic tools constitute an obstacle. Molecular imaging, such as Positron Emission Tomography (PET), is a promising technique but remains limited in the search for cerebral localizations, given the commercially available radiotracers. Indeed, the [18F]FDG PET remains constrained by the physiological fixation of the cerebral cortex, which hinders the visualization of cerebral metastases. Tumor angiogenesis is recognized as a crucial phenomenon in the progression of malignant tumors and is correlated with overexpression of the neuropilin-1 (NRP-1) receptor. Here, we describe the synthesis and the photophysical properties of the new gallium-68 radiolabeled peptide to target NRP-1. The KDKPPR peptide was coupled with gallium-68 anchored into a bifunctional NODAGA chelating agent, as well as Cy5 for fluorescence detection. The Cy5 absorbance spectra did not change, whereas the molar extinction coefficient (ε) decreased drastically. An enhancement of the fluorescence quantum yield (φF) could be observed due to the better water solubility of Cy5. [68Ga]Ga-NODAGA-K(Cy5)DKPPR was radiosynthesized efficiently, presented hydrophilic properties (log D = -1.86), and had high in vitro stability (>120 min). The molecular affinity and the cytotoxicity of this new chelated radiotracer were evaluated in vitro on endothelial cells (HUVEC) and MDA-MB-231 cancer cells (hormone-independent and triple-negative line) and in vivo on a brain model of metastasis in a nude rat using the MDA-MB-231 cell line. No in vitro toxicity has been observed. The in vivo preliminary experiments showed promising results, with a high contrast between the healthy brain and metastatic foci for [68Ga]Ga-NODAGA-K(Cy5)DKPPR.

Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient?

PURPOSE: Dynamic amino acid positron emission tomography (PET) has become essential in neuro-oncology, most notably for its prognostic value in the noninvasive prediction of isocitrate dehydrogenase (IDH) mutations in newly diagnosed gliomas. The 6-[18F]fluoro-l-DOPA (18F-FDOPA) kinetic model has an underlying complexity, while previous studies have predominantly used a semiquantitative dynamic analysis. Our study addresses whether a semiquantitative analysis can capture all the relevant information contained in time-activity curves for predicting the presence of IDH mutations compared to the more sophisticated graphical and compartmental models. METHODS: Thirty-seven tumour time-activity curves from 18F-FDOPA PET dynamic acquisitions of newly diagnosed gliomas (median age = 58.3 years, range = 20.3-79.9 years, 16 women, 16 IDH-wild type) were analyzed with a semiquantitative model based on classical parameters, with (SQ) or without (Ref SQ) a reference region, or on parameters of a fit function (SQ Fit), a graphical Logan model with input function (Logan) or reference region (Ref Logan), and a two-tissue compartmental model previously reported for 18F-FDOPA PET imaging of gliomas (2TCM). The overall predictive performance of each model was assessed with an area under the curve (AUC) comparison using multivariate analysis of all the parameters included in the model. Moreover, each extracted parameter was assessed in a univariate analysis by a receiver operating characteristic curve analysis. RESULTS: The SQ model with an AUC of 0.733 for predicting IDH mutations showed comparable performance to the other models with AUCs of 0.752, 0.814, 0.693, 0.786, and 0.863, respectively corresponding to SQ Fit, Ref SQ, Logan, Ref Logan, and 2TCM (p ≥ 0.10 for the pairwise comparisons with other models). In the univariate analysis, the SQ time-to-peak parameter had the best diagnostic performance (75.7% accuracy) compared to all other individual parameters considered. CONCLUSIONS: The SQ model circumvents the complexities of the 18F-FDOPA kinetic model and yields similar performance in predicting IDH mutations when compared to the other models, most notably the compartmental model. Our study provides supportive evidence for the routine clinical application of the SQ model for the dynamic analysis of 18F-FDOPA PET images in newly diagnosed gliomas.

Effect of Point Spread Function Deconvolution in Reconstruction of Brain 18F-FDG PET Images on the Diagnostic Thinking Efficacy in Alzheimer's Disease.

Purpose: This study aims to determine the effect of applying Point Spread Function (PSF) deconvolution, which is known to improve contrast and spatial resolution in brain 18F-FDG PET images, to the diagnostic thinking efficacy in Alzheimer's disease (AD). Methods: We compared Hoffman 3-D brain phantom images reconstructed with or without PSF. The effect of PSF deconvolution on AD diagnostic clinical performance was determined from digital brain 18F-FDG PET images of AD (n = 38) and healthy (n = 35) subjects compared to controls (n = 36). Performances were assessed with SPM at the group level (p < 0.001 for the voxel) and at the individual level by visual interpretation of SPM T-maps (p < 0.005 for the voxel) by the consensual analysis of three experienced raters. Results: A mix of large hypometabolic (1,483cm3, mean value of -867 ± 492 Bq/ml) and intense hypermetabolic (902 cm3, mean value of 1,623 ± 1,242 Bq/ml) areas was observed in the PSF compared to the no PSF phantom images. Significant hypometabolic areas were observed in the AD group compared to the controls, for reconstructions with and without PSF (respectively 23.7 and 26.2 cm3), whereas no significant hypometabolic areas were observed when comparing the group of healthy subjects to the control group. At the individual level, no significant differences in diagnostic performances for discriminating AD were observed visually (sensitivity of 89 and 92% for reconstructions with and without PSF respectively, similar specificity of 74%). Conclusion: Diagnostic thinking efficacy performances for diagnosing AD are similar for 18F-FDG PET images reconstructed with or without PSF.

Early bradycardia detection and therapeutic interventions in preterm infant monitoring.

In very preterm infants, cardio-respiratory events and associated hypoxemia occurring during early postnatal life have been associated with risks of retinopathy, growth alteration and neurodevelopment impairment. These events are commonly detected by continuous cardio-respiratory monitoring in neonatal intensive care units (NICU), through the associated bradycardia. NICU nurse interventions are mainly triggered by these alarms. In this work, we acquired data from 52 preterm infants during NICU monitoring, in order to propose an early bradycardia detector which is based on a decentralized fusion of three detectors. The main objective is to improve automatic detection under real-life conditions without altering performance with respect to that of a monitor commonly used in NICU. We used heart rate lower than 80 bpm during at least 10 sec to define bradycardia. With this definition we observed a high rate of false alarms (64%) in real-life and that 29% of the relevant alarms were not followed by manual interventions. Concerning the proposed detection method, when compared to current monitors, it provided a significant decrease of the detection delay of 2.9 seconds, without alteration of the sensitivity (97.6% vs 95.2%) and false alarm rate (63.7% vs 64.1%). We expect that such an early detection will improve the response of the newborn to the intervention and allow for the development of new automatic therapeutic strategies which could complement manual intervention and decrease the sepsis risk.

Brain 18F-FDG PET for the diagnosis of autoimmune encephalitis: a systematic review and a meta-analysis.

OBJECTIVE: To consolidate current understanding of detection sensitivity of brain 18F-FDG PET scans in the diagnosis of autoimmune encephalitis and to define specific metabolic imaging patterns for the most frequently occurring autoantibodies. METHODS: A systematic and exhaustive search of data available in the literature was performed by querying the PubMed/MEDLINE and Cochrane databases for the search terms: ((PET) OR (positron emission tomography)) AND ((FDG) OR (fluorodeoxyglucose)) AND ((encephalitis) OR (brain inflammation)). Studies had to satisfy the following criteria: (i) include at least ten pediatric or adult patients suspected or diagnosed with autoimmune encephalitis according to the current recommendations, (ii) specifically present 18F-FDG PET and/or morphologic imaging findings. The diagnostic 18F-FDG PET detection sensitivity in autoimmune encephalitis was determined for all cases reported in this systematic review, according to a meta-analysis following the PRISMA method, and selected publication quality was assessed with the QUADAS-2 tool. RESULTS: The search strategy identified 626 articles including references from publications. The detection sensitivity of 18F-FDG PET was 87% (80-92%) based on 21 publications and 444 patients included in the meta-analysis. We also report specific brain 18F-FDG PET imaging patterns for the main encephalitis autoantibody subtypes. CONCLUSION AND RELEVANCE: Brain 18F-FDG PET has a high detection sensitivity and should be included in future diagnostic autoimmune encephalitis recommendations. Specific metabolic 18F-FDG PET patterns corresponding to the main autoimmune encephalitis autoantibody subtypes further enhance the value of this diagnostic.

In vivo characterization of physiological and metabolic changes related to isocitrate dehydrogenase 1 mutation expcression by multiparametric MRI and MRS in a rat model with orthotopically grafted human-derived glioblastoma cell lines.

The physiological mechanism induced by the isocitrate dehydrogenase 1 (IDH1) mutation, associated with better treatment response in gliomas, remains unknown. The aim of this preclinical study was to characterize the IDH1 mutation through in vivo multiparametric MRI and MRS. Multiparametric MRI, including the measurement of blood flow, vascularity, oxygenation, permeability, and in vivo MRS, was performed on a 4.7 T animal MRI system in rat brains grafted with human-derived glioblastoma U87 cell lines expressing or not the IDH1 mutation by the CRISPR/Cas9 method, and secondarily characterized with additional ex vivo HR-MAS and histological analyses. In univariate analyses, compared with IDH1-, IDH1+ tumors exhibited higher vascular density (p < 0.01) and better perfusion (p = 0.02 for cerebral blood flow), but lower vessel permeability (p < 0.01 for time to peak (TTP), p = 0.04 for contrast enhancement) and decreased T1 map values (p = 0.02). Using linear discriminant analysis, vascular density and TTP values were found to be independent MRI parameters for characterizing the IDH1 mutation (p < 0.01). In vivo MRS and ex vivo HR-MAS analysis showed lower metabolites of tumor aggressiveness for IDH1+ tumors (p < 0.01). Overall, the IDH1 mutation exhibited a higher vascularity on MRI, a lower permeability, and a less aggressive metabolic profile. These MRI features may prove helpful to better pinpoint the physiological mechanisms induced by this mutation.

Clinical impact of digital and conventional PET control databases for semi-quantitative analysis of brain 18F-FDG digital PET scans.

PURPOSE: Digital PET cameras markedly improve sensitivity and spatial resolution of brain 18F-FDG PET images compared to conventional cameras. Our study aimed to assess whether specific control databases are required to improve the diagnostic performance of these recent advances. METHODS: We retrospectively selected two groups of subjects, twenty-seven Alzheimer's Disease (AD) patients and twenty-two healthy control (HC) subjects. All subjects underwent a brain 18F-FDG PET on a digital camera (Vereos, Philips®). These two group (AD and HC) are compared, using a Semi-Quantitative Analysis (SQA), to two age and sex matched controls acquired with a digital PET/CT (Vereos, Philips®) or a conventional PET/CT (Biograph 6, Siemens®) camera, at group and individual levels. Moreover, individual visual interpretation of SPM T-maps was provided for the positive diagnosis of AD by 3 experienced raters. RESULTS: At group level, SQA using digital controls detected more marked hypometabolic areas in AD (+ 116 cm3 at p < 0.001 uncorrected for the voxel, corrected for the cluster) than SQA using conventional controls. At the individual level, the accuracy of SQA for discriminating AD using digital controls was higher than SQA using conventional controls (86% vs. 80%, p < 0.01, at p < 0.005 uncorrected for the voxel, corrected for the cluster), with higher sensitivity (89% vs. 78%) and similar specificity (82% vs. 82%). These results were confirmed by visual analysis (accuracies of 84% and 82% for digital and conventional controls respectively, p = 0.01). CONCLUSION: There is an urgent need to establish specific digital PET control databases for SQA of brain 18F-FDG PET images as such databases improve the accuracy of AD diagnosis.

Robust, real-time generic detector based on a multi-feature probabilistic method.

Robust, real-time event detection from physiological signals acquired during long-term ambulatory monitoring still represents a major challenge for highly-artifacted signals. In this paper, we propose an original and generic multi-feature probabilistic detector (MFPD) and apply it to real-time QRS complex detection under noisy conditions. The MFPD method calculates a binary Bayesian probability for each derived feature and makes a centralized fusion, using the Kullback-Leibler divergence. The method is evaluated on two ECG databases: 1) the MIT-BIH arrhythmia database from Physionet containing clean ECG signals, 2) a benchmark noisy database created by adding noise recordings of the MIT-BIH noise stress test database, also from Physionet, to the MIT-BIH arrhythmia database. Results are compared with a well-known wavelet-based detector, and two recently published detectors: one based on spatiotemporal characteristic of the QRS complex and the second, as the MFDP, based on feature calculations from the University of New South Wales detector (UNSW). For both benchmark Physionet databases, the proposed MFPD method achieves the lowest standard deviation in sensitivity and positive predictivity (+P) despite its online algorithm architecture. While the statistics are comparable for low-to mildly artifactual ECG signals, the MFPD outperforms reference methods for artifacted ECG with low SNR levels reaching 87.48 ± 14.21% in sensitivity and 89.39 ± 14.67% in +P as compared to 88.30 ± 17.66% and 86.06 ± 19.67% respectively from UNSW, the best performing reference method. With demonstrations on the extensively studied QRS detection problem, we consider that the proposed generic structure of the multi-feature probabilistic detector should offer promising perspectives for long-term monitoring applications for highly-artifacted signals.