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Baseline 18F-FDG PET was performed in a 74-year-old patient with relapsing upper mediastinum lymphoma. Left subclavian thrombosis was suspected on prior contrast-enhanced CT. Dynamic PET imaging was achieved during 3 min after IV injection of 18F-FDG to the left arm in order to further assess left subclavian vein permeability. The 20-s dynamic frame at 1 min after injection confirmed the absence of flow in the left subclavian vein and evidenced the derivation of 18F-FDG through left axillary, then superficial, then right internal mammary collaterals to the superior vena cava, hence confirming the subclavian thrombosis.

The pathophysiology of rapid eye movement sleep behavior disorder (RBD) associated with narcolepsy type 1 (NT1) is still poorly understood, potentially distinct from idiopathic RBD (iRBD), but may share affected common pathways. We investigated whether MIBG cardiac uptake differs between iRBD and NT1 comorbid with RBD. Thirty-four patients with NT1-RBD and 15 patients with iRBD underwent MIBG cardiac scintigraphy. MIBG uptake was measured by calculating the early and delayed heart to mediastinum (H/M) ratios. A delayed H/M ratio lower than 1.46 was considered abnormal based on a population of 78 subjects without neurological or cardiac diseases. Patients with iRBD were older, had an older RBD onset age and higher REM sleep phasic and tonic muscular activities than NT1-RBD. Lower delayed and early H/M ratios were associated with iRBD, but not with NT1-RBD, in crude and adjusted associations. The delayed H/M ratio differed between iRBD and controls, after adjustment, but not between patients with NT1-RBD and controls. In conclusion, the MIBG cardiac uptake difference between NT1-RBD and iRBD supports the hypothesis of different processes involved in RBD pathogenesis, providing for the first time a cardiac biomarker to differentiate those disorders.

Influence of CT-based attenuation correction (CT-AC) in assessment of left and right ventricular functions with count-based gated blood-pool SPECT (GBPS) was evaluated in a mixed population. Thirty-two patients (81% male; mean age 56 ± 12) referred for various symptoms or heart diseases were prospectively included. Data from 32 GBPS acquisitions were reconstructed using an iterative algorithm with (IRAC) and without (IRNC) CT-AC and analyzed using previously described segmentation software based on the watershed algorithm. LV and RV EF and volumes were assessed with and without CT-AC and compared. EF and volumes were correlated (P

Classically, the missing portions in the oblique projection data acquired from cylindrical scanners are synthesized by forward projecting an estimation of the activity computed from non-oblique data. Another quick and powerful way to perform the estimation of the truncated portions consists in applying Fourier rebinning methods. This paper intends to compare the performances of 3D geometric re-projection versus two Fourier rebinning techniques (iterative FOREPROJ and extended FORE) designed for re-projection.Both analytical and noisy 3D projection data corresponding to a phantom constituted of warm and cold ellipsoids over a uniform background are simulated numerically for the SIEMENS Hi-Rez scanner. The object is reconstructed using 3D filtered back-projection. A prior estimation of the missing oblique data is performed using the three algorithms.The resolution properties and noise behavior of the three methods are compared and demonstrate a significant signal to noise ratio improvement using rebinning-based algorithms.We show that iterative FOREPROJ provides projection data with high accuracy 60% less time than geometric re-projection.

Purpose: This study sought to determine whether 133Xe-radiospirometry (XRS) successfully selects patients able to undergo lung resection without postoperative respiratory complications and whether perfusion lung scintigraphy (PLS) is likely to provide a similar selection of patients for certain tumour stages. Methods: Two hundred and eighty-four patients with resectable lung cancer underwent preoperative assessment of postoperative forced expiratory volume in 1 s (FEV1) by XRS and PLS. Correlations, Bland and Altman analysis and contingency tables were used to analyse the difference between the two predictive techniques. Results: One hundred and sixty patients underwent lung resection on the basis of XRS preoperative testing only. None of them developed respiratory insufficiency. Despite a close correlation, the limits of agreement between predicted FEV1 by XRS and PLS exceeded ±0.3 l/s. For tumour stages T1Nx and T2N0, PLS underestimated postoperative FEV1 whereas it overestimated this parameter for stage III. Conclusion: XRS accurately selects patients able to undergo lung resection without postoperative pulmonary insufficiency. The agreement between XRS and PLS is unacceptable. When only PLS is available, higher thresholds for patients with stage III cancers and lower thresholds for those with stage I cancers should be used to decide on operability.

OBJECTIVE To compare insulin sensitivity indexes derived from plasma insulin (I) and glucose (G) in the basal state (Sib) and at the second hour (I2h and G2h) of an oral glucose tolerance test (OGTT, Si2h) (i) with measurements of insulin sensitivity using the insulin modified frequently sampled intravenous glucose tolerance test (FSIVGTT) [Si(IVGTT)] and (ii) with modelling of fasting glucose and insulin by the homeostasis model assessment (HOMA). SUBJECTS 47 subjects entered the study. 31 subjects were classified as having normal glucose tolerance (NGT), 10 as having impaired tolerance to glucose (IGT) and six as type 2 diabetes mellitus according to the World Health Organisation (WHO) criteria. MEASUREMENTS Sib and Si2h were calculated as follows. Sib = 10(8)/(I x G x VD), Si2h = 10(8)/(I2hr x G2hr x VD) where VD is an estimate of the apparent glucose distribution volume. A third insulin sensitivity index (SiM) was calculated by averaging Sib and Si2h. HOMA was calculated as follows: I/(22.5 x e(-lnG)) RESULTS: Si(IVGTT), Sib, SI2h and SiM were all significantly higher in subjects with NGT than in those with IGT or type 2 diabetes. Si(IVGTT) was highly correlated (P < or = 0.0001) with the three insulin sensitivity indexes found in the total population, in subjects with NGT and in those with IGT. In type 2 diabetic patients, a significant correlation was only noted when SiM was tested against Si(IVGTT) (P < or = 0.05). In most circumstances, the associations of Si(IVGTT) with Sib, SI2h and SiM were stronger than the corresponding associations with Ib, I2h or HOMA. SiM was the index that correlated best with Si(IVGTT) in the whole group (r = 0.92, P < 0.0001) as well as in NGT (r = 0.86, P < 0.0001), IGT (r = 0.96; P < 0.0001) and type 2 diabetes (r = 0.83, P < or = 0.05) subgroups. CONCLUSIONS Calculations of sensitivity indexes from G and I concentrations in the basal state and during a conventional 2 h OGTT appear to be useful for coupling in the same simple and single test both a determination of glucose tolerance and an estimate of insulin sensitivity.

OBJECTIVE: To study the associations of obesity (as body mass index (BMI)), of body fat distribution (as waist to hip ratio (WHR)) and of β-endorphinaemia (β-EP-aemia) with fasting insulin and glucose concentrations, with insulin secretion (as first phase insulin response (FPIR)) and with insulin sensitivity (SI) in obese women. DESIGN: a cross-sectional study of insulin sensitivity in obese women. SUBJECTS: 45 obese women (age: 20–70 y, BMI: 27–50). MEASUREMENTS: Frequently sampled intravenous glucose tolerance test (FSIGTT), FPIR, fasting glucose, fasting insulin, BMI, body fat topography (WHR), β-EP-aemia, plasma ACTH. RESULTS: In univariate analysis the following positive associations were observed: fasting glucose with age and WHR, fasting insulin with BMI and WHR, β-EP plasma concentration with WHR; SI was negatively associated with BMI, WHR and β-EP plasma concentrations. This pattern of associations remained unaltered in multivariate analysis including age, BMI and WHR as independent variables. The contribution of β-EP plasma concentrations to SI variability was corroborated by a stepwise multiple regression analysis: 53.8% of SI variation could be explained by BMI (30.7%), by β-EP plasma concentrations (17.2%) and by WHR (5.9%). Finally, women were divided into two groups according to whether they had a peripheral (P-BFD, WHR≤0.80, n=24) or an abdominal (A-BFD, WHR≥0.85, n=16) body fat distribution. After adjustment for age and BMI, SI values were lower while β-EP and ACTH plasma concentrations were higher in the A-BFD compared to the P-BFD group. In this latter group, 54.8% of SI variation was explained by the same variables as in the whole group. In the A-BFD group, higher WHR was associated with lower FPIR. CONCLUSIONS: 1) The major finding of this study is that, in non-diabetic obese women (especially those with a P-BFD), higher β-EP plasma concentrations are associated with lower insulin sensitivity. This association is independent of both the magnitude of obesity and the pattern of fat distribution, although these two parameters are strong predictors of SI. 2) The major reduction in SI observed in women with A-BFD probably results from the additive effects of obesity, of elevated β-EP plasma concentrations and of metabolic and endocrine alterations in relation with the central pattern of fat distribution.

The purpose of this study was to define an optimal strategy for the tomographic reconstruction procedure in routine brain single-photon emission tomography (SPET) studies, including the number of projections, filter function and matrix size. A set of projection data with different count densities was obtained from a technetium-99m hexamethylpropylene amine oxime (99mTc-HMPAO) brain SPET acquisition from one volunteer. The projections were reconstructed with different filters and the quality of the reconstructed images was determined using both a subjective observer rating score and the Gilbert index. For each count density, the observers' choice corresponded to images with the lowest Gilbert index. The noise level in brain SPET sections was estimated and correlated with the fractal dimension. The results of this study indicate that although noise represents a fundamental component of brain SPET imaging, image quality also depends on the reconstructed spatial resolution. Image quality is satisfactorily described by fractal dimension. In addition the optimal filter function depends on the available count density. For high count levels, optimal reconstruction may be obtained by using a high-resolution matrix and a slightly smoother reconstruction filter. When count densities are low, best results are obtained by using a low-resolution matrix and a sharper filter. Finally, this study suggests that image quality is not influenced by the number of projections for equivalent count densities. These results were confirmed by 30 HMPAO brain SPET studies acquired in a routine clinical setting.