Stage 1-biomarkers of kidney injury in dogs undergoing constant rate infusion of hydroxyethyl starch 130/0.4

In veterinary medicine, investigations relating the effects of hydroxyethyl starch (HES) on renal function report contrasting results. This study aimed to assess the changes in the selected biomarkers of kidney injury in dogs after the administration of HES 130/0.4 as a constant rate infusion (CRI) for 24 h. Ten adult client-owned dogs with hypoalbuminemia (albumin < 2 g/dL) and ongoing fluid losses were included. Enrolled dogs received intravenous fluid therapy with crystalloids and a CRI of HES 130/0.4 at a dose of 2 mL/kg/h for 24 h. Serum creatinine (sCr), fractional excretion (FE) of electrolytes, urinary protein to creatinine ratio (UPC), urinary albumin to creatinine ratio (UAC), SDS-page, and urinary neutrophil gelatinase-associated lipocalin (uNGAL) were measured at the baseline before HES infusion, and after 24 h (T24) and 48 h (T48) from the baseline. No statistically significant difference was found between the baseline value vs. T24 and the baseline vs. T48 for sCr, UAC, UPC, FE of sodium, chloride and calcium, and uNGAL. A significant increase in FEK (p = 0.04) was noticed between the baseline and T48. In this study sample of hypoalbuminemic dogs, HES 130/0.4 at the dose and rate of infusion applied did not cause any significant changes in the investigated biomarkers of kidney injury

Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study

Brain vascular damage accumulate in aging and often manifest as white matter hyperintensities (WMHs) on MRI. Despite increased interest in automated methods to segment WMHs, a gold standard has not been achieved and their longitudinal reproducibility has been poorly investigated. The aim of present work is to evaluate accuracy and reproducibility of two freely available segmentation algorithms. A harmonized MRI protocol was implemented in 3T-scanners across 13 European sites, each scanning five volunteers twice (test-retest) using 2D-FLAIR. Automated segmentation was performed using Lesion segmentation tool algorithms (LST): the Lesion growth algorithm (LGA) in SPM8 and 12 and the Lesion prediction algorithm (LPA). To assess reproducibility, we applied the LST longitudinal pipeline to the LGA and LPA outputs for both the test and retest scans. We evaluated volumetric and spatial accuracy comparing LGA and LPA with manual tracing, and for reproducibility the test versus retest. Median volume difference between automated WMH and manual segmentations (mL) was −0.22[IQR = 0.50] for LGA-SPM8, −0.12[0.57] for LGA-SPM12, −0.09[0.53] for LPA, while the spatial accuracy (Dice Coefficient) was 0.29[0.31], 0.33[0.26] and 0.41[0.23], respectively. The reproducibility analysis showed a median reproducibility error of 20%[IQR = 41] for LGA-SPM8, 14% [31] for LGA-SPM12 and 10% [27] with the LPA cross-sectional pipeline. Applying the LST longitudinal pipeline, the reproducibility errors were considerably reduced (LGA: 0%[IQR = 0], p < 0.001; LPA: 0% [3], p < 0.001) compared to those derived using the cross-sectional algorithms. The DC using the longitudinal pipeline was excellent (median = 1) for LGA [IQR = 0] and LPA [0.02]. LST algorithms showed moderate accuracy and good reproducibility. Therefore, it can be used as a reliable cross-sectional and longitudinal tool in multi-site studies

White matter hyperintensities are no major confounder for alzheimer's disease cerebrospinal fluid biomarkers

Background: The cerebrospinal fluid (CSF) biomarkers amyloid-β 1–42 (Aβ 42), total and phosphorylated tau (t-tau, p-tau) are increasingly used to assist in the clinical diagnosis of Alzheimer’s disease (AD). However, CSF biomarker levels can be affected by confounding factors. Objective: To investigate the association of white matter hyperintensities (WMHs) present in the brain with AD CSF biomarker levels. Methods: We included CSF biomarker and magnetic resonance imaging (MRI) data of 172 subjects (52 controls, 72 mild cognitive impairment (MCI), and 48 AD patients) from 9 European Memory Clinics. A computer aided detection system for standardized automated segmentation of WMHs was used on MRI scans to determine WMH volumes. Association of WMH volume with AD CSF biomarkers was determined using linear regression analysis. Results: A small, negative association of CSF Aβ 42, but not p-tau and t-tau, levels with WMH volume was observed in the AD (r 2 = 0.084, p = 0.046), but not the MCI and control groups, which was slightly increased when including the distance of WMHs to the ventricles in the analysis (r 2 = 0.105, p = 0.025). Three global patterns of WMH distribution, either with 1) a low, 2) a peak close to the ventricles, or 3) a high, broadly-distributed WMH volume could be observed in brains of subjects in each diagnostic group. Conclusion: Despite an association of WMH volume with CSF Aβ 42 levels in AD patients, the occurrence of WMHs is not accompanied by excess release of cellular proteins in the CSF, suggesting that WMHs are no major confounder for AD CSF biomarker assessment