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author:("uvula, Ramesh")
1.  Age, kidney function, and risk factors associate differently with cortical and medullary volumes of the kidney 
Kidney international  2013;85(3):677-685.
The kidney atrophies in patients with advanced chronic kidney disease (CKD) but factors influencing kidney size in normal adults are less clear. To help define this we measured kidney volumes on contrast-enhanced CT images from 1344 potential kidney donors (ages 18 to 75 years). Cortical volume per body surface area progressively declined in both genders with increased age. Statistically, this was primarily dependent on the age-related decline in glomerular filtration rate (GFR). Independent predictors of increased cortical volume per body surface area were male gender, increased GFR, increased 24-hour urine albumin, current smoker, and decreased high-density lipid cholesterol. Medullary volume per body surface area increased with age in men while it increased with age in women until age 50 followed by a subsequent decline. Independent predictors of increased medullary volume per body surface area were older age, male gender, increased GFR, increased 24-hour urine albumin, increased serum glucose, and decreased serum uric acid. Thus, while cortical volume declines with age along the same biological pathway as the age-related decline in GFR and albuminuria some CKD risk factors are actually associated with increased cortical or medullary volume among relatively healthy adults. Underlying hypertrophy or atrophy of different nephron regions may explain these findings.
doi:10.1038/ki.2013.359
PMCID: PMC3943620  PMID: 24067437
kidney cortical volume; kidney medullary volume; aging; kidney function; CKD risk factors
2.  Disrupted thalamocortical connectivity in PSP: a resting state fMRI, DTI, VBM study 
Parkinsonism & related disorders  2011;17(8):599-605.
Progressive supranuclear palsy (PSP) is associated with pathological changes along the dentatorubrothalamic tract and in premotor cortex. We aimed to assess whether functional neural connectivity is disrupted along this pathway in PSP, and to determine how functional changes relate to changes in structure and diffusion. Eighteen probable PSP subjects and 18 controls had resting-state (task-free) fMRI, diffusion tensor imaging and structural MRI. Functional connectivity was assessed between thalamus and the rest of the brain, and within the basal ganglia, salience and default mode networks (DMN). Patterns of atrophy were assessed using voxel-based morphometry, and patterns of white matter tract degeneration were assessed using tract-based spatial statistics. Reduced in-phase functional connectivity was observed between the thalamus and premotor cortex including supplemental motor area (SMA), striatum, thalamus and cerebellum in PSP. Reduced connectivity in premotor cortex, striatum and thalamus were observed in the basal ganglia network and DMN, with subcortical salience network reductions. Tract degeneration was observed between cerebellum and thalamus and in superior longitudinal fasciculus, with grey matter loss in frontal lobe, premotor cortex, SMA and caudate. SMA functional connectivity correlated with SMA volume and measures of cognitive and motor dysfunction, while thalamic connectivity correlated with degeneration of superior cerebellar peduncles. PSP is therefore associated with disrupted thalamocortical connectivity that is associated with degeneration of the dentatorubrothalamic tract and the presence of cortical atrophy.
doi:10.1016/j.parkreldis.2011.05.013
PMCID: PMC3168952  PMID: 21665514
Resting state fMRI; functional connectivity; white matter tracts; atrophy; dentatorubrothalamic tract
3.  Clinical correlates of white matter tract degeneration in PSP 
Archives of Neurology  2011;68(6):753-760.
Objective
Progressive supranuclear palsy (PSP) is associated with degeneration of white matter tracts that can be detected using diffusion tensor imaging (DTI). However, little is known about whether tract degeneration is associated with the clinical symptoms of PSP. The aim of this study was to use DTI to assess white matter tract degeneration in PSP and to investigate correlates, between tract integrity and clinical measures.
Design
Case-control study
Setting
Tertiary care medical centre
Patients
Twenty subjects with probable PSP and 20 age and gender-matched healthy controls. All PSP subjects underwent standardized clinical testing, including the Frontal Behavioral Inventory and Frontal Assessment Battery to assess behavioral change; the PSP Rating Scale to measure disease severity, the Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (parts I, II and III) to measure motor function, and the PSP Saccadic Impairment Scale to measure eye movement abnormalities.
Main outcome measures
Fractional anisotropy and mean diffusivity measured using both region-of-interest analysis and Track Based Spatial Statistics.
Results
Abnormal diffusivity was observed predominantly in superior cerebellar peduncles, body of the corpus callosum, inferior longitudinal fasciculus and superior longitudinal fasciculus in PSP compared to controls. Fractional anisotropy values in the superior cerebellar peduncles correlated with disease severity; inferior longitudinal fasciculus correlated with motor function, and superior longitudinal fasciculus correlated with severity of saccadic impairments.
Conclusions
These results demonstrate that PSP is associated with degeneration of brainstem, association and commissural fibers and that this degeneration likely plays an important role in clinical dysfunction.
doi:10.1001/archneurol.2011.107
PMCID: PMC3401587  PMID: 21670399
4.  Effect of APOE ε4 Status on Intrinsic Network Connectivity in Cognitively Normal Elderly 
Archives of Neurology  2011;68(9):1131-1136.
Objective
To examine default mode and salience network functional connectivity as a function of APOE ε4 status in a group of cognitively normal age, gender and education-matched older adults.
Design
Case-control study.
Setting
Community-based sample
Subjects
Fifty-six cognitively normal APOE ε4 carriers and 56 age, gender and education-matched cognitively normal APOE ε4 non-carriers.
Main Outcome Measure
Alterations in in-phase default mode and salience network connectivity in APOE ε4 carriers compared to APOE ε4 non-carriers ranging from 63 to 91 years of age.
Results
A posterior cingulate seed revealed decreased in-phase connectivity in regions of the posterior default mode network that included the left inferior parietal lobe, left middle temporal gyrus, and bilateral anterior temporal lobes in the ε4 carriers relative to APOE ε4 non-carriers. An anterior cingulate seed showed greater in-phase connectivity in the salience network, including the cingulate gyrus, medial prefrontal cortex, bilateral insular cortex, striatum, and thalamus in APOE ε4 carriers vs. non-carriers. There were no group-wise differences in brain anatomy.
Conclusions
We found reductions in posterior default mode network connectivity but increased salience network connectivity in elderly cognitively normal APOE ε4 carriers relative to APOE ε4 non-carriers at rest. The observation of functional alterations in connectivity in the absence of structural changes between APOE e4 carriers and non-carriers suggests that alterations in connectivity may have the potential to serve as an early biomarker.
doi:10.1001/archneurol.2011.108
PMCID: PMC3392960  PMID: 21555604
5.  FLAIR Histogram Segmentation for Measurement of Leukoaraiosis Volume 
The purpose of this study was to develop a method to measure brain and white matter hyperintensity (leukoaraiosis) volume that is based on the segmentation of the intensity histogram of fluid attenuated inversion recovery (FLAIR) images, and to assess the accuracy and reproducibility of the method. Whole head synthetic image phantoms with manually introduced leukoaraiosis lesions of varying severity were constructed. These synthetic image phantom sets incorporated image contrast and anatomic features which mimicked leukoaraiosis found in real life. One set of synthetic image phantoms was used to develop the segmentation algorithm (FLAIR-histoseg). A second set was used to measure its accuracy. Test re-test reproducibility was assessed in 10 elderly volunteers who were imaged twice. The mean absolute error of the FLAIR-histoseg method for measurement of leukoaraiosis volume was 6.6% and for brain volume 1.4%. The mean test re-test coefficient of variation for leukoaraiosis volume was 1.4% and for brain volume was 0.3%. We conclude that the FLAIR-histoseg method is an accurate and reproducible method for measuring leukoaraiosis and whole brain volume in elderly subjects.
PMCID: PMC2755497  PMID: 11747022
quantitative MRI; pulse sequences; segmentation; white matter disease; dementia
6.  An algorithm for automatic segmentation and classification of magnetic resonance brain images 
Journal of Digital Imaging  1998;11(2):74-82.
In this article, we describe the development and validation of an automatic algorithm to segment brain from extracranial tissues, and to classify intracranial tissues as cerebrospinal fluid (CSF), gray matter (GM), white matter (WM) or pathology. T1 weighted spin echo, dual echo fast spin echo (T2 weighted and proton density (PD) weighted images) and fast Fluid Attenuated Inversion Recovery (FLAIR) magentic resonance (MR) images were acquired ino 100 normal patients and 9 multiple sclerosis (MS) patients. One of the normal studies had synthesized MS-like lesions superimposed. This allowed precise measurement of the accuracy of the classification. The 9 MS patients were imaged twice in one week. The algorithm was applied to these data sets to measure reproducibility. The accuracy was measured based on the synthetic lesion images, where the true voxel class was known. Ninety-six percent of normal intradural tissue voxels (GM, WM, and CSF) were labeled correctly, and 94% of pathological tissues were labeled correctly. A low coefficient of variation (COV) was found (mean, 4.1%) for measurement of brain tissues and pathology when comparing MRI scans on the 9 patients. A totally automatic segmentation algorithm has been described which accurately and reproducibly segments and classifies intradural tissues based on both synthetic and actual images.
doi:10.1007/BF03168729
PMCID: PMC3452992  PMID: 9608930
automatic multiparametric classification; brain segmentation; multiple sclerosis (MS); magnetic resonance imaging (MRI)

Results 1-6 (6)