Ventilation Distribution Studies Comparing Technegas and ""Gallgas"" Using (68)GaCl(3) as the Label

Ventilation distribution can be assessed by SPECT with Technegas. This study was undertaken in piglets with different degrees of ventilation inhomogeneity to compare PET using (68)Ga-labeled pseudogas or ""Gallgas"" with Technegas. Methods: Twelve piglets were studied in 3 groups: control, lobar obstruction, and diffuse airway obstruction. Two more piglets were assessed for lung volume (functional residual capacity). Results: In controls, SPECT and PET images showed an even distribution of radioactivity. With lobar obstruction, the absence of ventilation of the obstructed lobe was visible with both techniques. In diffuse airway obstruction, SPECT images showed an even distribution of radioactivity, and PET images showed more varied radioactivity over the lung. Conclusion: PET provides detailed ventilation distribution images and a better appreciation of ventilation heterogeneity. Gallgas with PET is a promising new diagnostic tool for the assessment of ventilation distribution.

Can the CAMCOG be a good cognitive test for patients with Alzheimer`s disease with low levels of education?

Background: The Cambridge Cognitive Examination (CAMCOG) is a useful test in screening for Alzheimer`s disease (AD). However, the interpretation of CAMCOG cut-off scores is problematic and reference values are needed for different educational strata. Given the importance of earlier diagnoses of mild dementia, new cut-off values are required which take into account patients with low levels of education. This study aims to evaluate whether the CAMCOG can be used as an accurate screening test among AD patients and normal controls with different educational levels. Methods: Cross-sectional assessment was undertaken of 113 AD and 208 elderly controls with heterogeneous educational levels (group 1: 1-4 years; group 2: 5-8 years; and group 3: >= 9 years) from a geriatric clinic. submitted to a thorough diagnostic evaluation for AD including the Cambridge Examination for Mental Disorders of the Elderly (CAMDEX). Controls had no cognitive or mood complaints. Sensitivity (SE) and specificity (SP) for the CAMCOG in each educational group was assessed with receiver-operator-characteristic (ROC) curves. Results: CAMCOG mean values were lower when education was reduced in both diagnostic groups (controls - group 1: 87; group 2: 91; group 3: 96; AD - group 1: 63; group 2: 62; group 3: 77). Cutoff scores for the three education groups were 79, 80 and 90, respectively. SE and SP varied among the groups (group 1: 88.1% and 83.5%; group 2: 84.6% and 96%; group 3: 70.8% and 90%). Conclusion: The CAMCOG can be used as a cognitive test for patients with low educational level with good accuracy. Patients with higher education showed lower scores than previously reported.

Verbal fluency in the detection of mild cognitive impairment and Alzheimer`s disease among Brazilian Portuguese speakers: the influence of education

Background: Verbal fluency (VF) tasks are simple and efficient clinical tools to detect executive dysfunction and lexico-semantic impairment. VF tasks are widely used in patients with suspected dementia, but their accuracy for detection of mild cognitive impairment (MCI) is still under investigation. Schooling in particular may influence the subject`s performance. The aim of this study was to compare the accuracy of two semantic categories (animals and fruits) in discriminating controls, MCI patients and Alzheimer`s disease (AD) patients. Methods: 178 subjects, comprising 70 controls (CG), 70 MCI patients and 38 AD patients, were tested on two semantic VF tasks. The sample was divided into two schooling groups: those with 4-8 years of education and those with 9 or more years. Results: Both VF tasks - animal fluency (VFa) and fruits fluency (VFf) - adequately discriminated CG from AD in the total sample (AUC = 0.88 +/- 0.03, p < 0.0001) and in both education groups, and high educated MCI from AD (VFa: AUC = 0.82 +/- 0.05, p < 0.0001; VFf: AUC = 0.85 +/- 0.05, p < 0.0001). Both tasks were moderately accurate in discriminating CG from MCI (VFa: AUC = 0.68 +/- 0.04, p < 0.0001 - VFf:AUC = 0.73 +/- 0.04, p < 0.0001) regardless of the schooling level, and MCI from AD in the total sample (VFa: AUC = 0.74 +/- 0.05, p < 0.0001; VFf: AUC = 0.76 +/- 0.05, p < 0.0001). Neither of the two tasks differentiated low educated MCI from AD. In the total sample, fruits fluency best discriminated CG from MCI and MCI from AD; a combination of the two improved the discrimination between CG and AD. Conclusions: Both categories were similar in discriminating CG from AD; the combination of both categories improved the accuracy for this distinction. Both tasks were less accurate in discriminating CG from MCI, and MCI from AD.