William R. Riddle

Implementing Pediatric Growth Charts into an Electronic Health Record System

Electronic health record (EHR) systems are increasingly being adopted in pediatric practices; however, requirements for integrated growth charts are poorly described and are not standardized in current systems. The authors integrated growth chart functionality into an EHR system being developed and installed in a multispecialty pediatric clinic in an academic medical center. During a three-year observation period, rates of electronically documented values for weight, stature, and head circumference increased from fewer than ten total per weekday, up to 488 weight values, 293 stature values, and 74 head circumference values (p<0.001 for each measure). By the end of the observation period, users accessed the growth charts an average 175 times per weekday, compared to 127 patient visits per weekday to the sites that most closely monitored pediatric growth. Because EHR systems and integrated growth charts can manipulate data, perform calculations, and adapt to user preferences and patient characteristics, users may expect greater functionality from electronic growth charts than from paper-based growth charts.

Longitudinal Progression of Cognitive Decline Correlates with Changes in the Spatial Pattern of Brain 18F-FDG PET

Evaluating the symptomatic progression of mild cognitive impairment (MCI) caused by Alzheimer disease (AD) is practically accomplished by tracking performance on cognitive tasks, such as the Alzheimer Disease Assessment Scale’s cognitive subscale (ADAS_cog), the Mini-Mental Status Examination (MMSE), and the Functional Activities Questionnaire (FAQ). The longitudinal relationships between cognitive decline and metabolic function as assessed using 18F-FDG PET are needed to address both the cognitive and the biologic progression of disease state in individual subjects. We conducted an exploratory investigation to evaluate longitudinal changes in brain glucose metabolism of individual subjects and their relationship to the subject’s changes of cognitive status. Methods: We describe a method to determine correlations in 18F-FDG spatial distribution over time. This parameter is termed the regional 18F-FDG time correlation coefficient (rFTC). By using linear mixed-effects models, we determined the difference in the rFTC decline rate between controls and subjects at high risk of developing AD, such as individuals with MCI or the presence of apolipoprotein E (APOE)–ε4 allele. The association between each subject’s rFTC and performance on cognitive tests (ADAS_cog, MMSE, and FAQ) was determined with 2 different correlation methods. All subject data were downloaded from the Alzheimer Disease Neuroimaging Initiative. Results: The rFTC values of controls remained fairly constant over time (−0.003 annual change; 95% confidence interval, −0.010–0.004). In MCI patients, the rFTC declined faster than in controls by an additional annual change of −0.02 (95% confidence interval, −0.030 to −0.010). In MCI patients, the decline in rFTC was associated with cognitive decline (ADAS_cog, P = 0.011; FAQ, P = 0.0016; MMSE, P = 0.004). After a linear effect of time was accounted for, visit-to-visit changes in rFTC correlated with visit-to-visit changes in all 3 cognitive tests. Conclusion: Longitudinal changes in rFTC detect subtle metabolic changes in individuals associated with variations in their cognition. This analytic tool may be useful for a patient-based monitoring of cognitive decline.

Removing effects of eddy currents in proton MR spectroscopy.

The use of pulsed gradients to define a volume of interest for localized magnetic resonance spectroscopy produces magnetic field perturbations which distort both the free induction decay and the spectrum after Fourier transformation. A technique is presented that removes the artifacts from eddy currents from a sampled free induction decay. To linearize the phase, the nonlinear phase of a reference free induction decay is subtracted from the phase of a sample free induction decay. Next, to move the frequency to resonance and perform a zero-order phase correction, the line fit from a linear regression is subtracted from the phase. After reconstructing the free induction decay, the resulting frequency spectra are sorted into absorption mode and dispersion mode components.

Quantifying cerebral changes in adolescence with MRI and deformation based morphometry.

To identify and quantify structural changes in the maturing brain between childhood and adolescence.

Modeling brain tissue volumes over the lifespan: quantitative analysis of postmortem weights and in vivo MR images

Normative measurements of brain gray matter and white matter tissue volumes across the lifespan have not yet been established. The purpose of this article was to use mathematical modeling and analytical functions to demonstrate the growth trajectory of gray matter and white matter from age 0 to age 90. For each gender, brain weight functions were generated by utilizing existing autopsy data from 4400 subjects. Brain gray matter, white matter and lateral ventricular volumes were measured from 39 MR volumes of normal individuals. These were converted to weight by multiplying the tissue volumes by the specific gravity of that tissue. White matter volumes were described by a saturating exponential function, and the gray matter volume function was calculated by subtracting the white matter weight function from the brain weight function. For each gender, equations were generated for white matter and gray matter volumes as a function of age over the lifespan.

Modeling clustered activity increase in amyloid- beta positron emission tomographic images with statistical descriptors

Background Amyloid-beta (Aβ) imaging with positron emission tomography (PET) holds promise for detecting the presence of Aβ plaques in the cortical gray matter. Many image analyses focus on regional average measurements of tracer activity distribution; however, considerable additional information is available in the images. Metrics that describe the statistical properties of images, such as the two-point correlation function (S2), have found wide applications in astronomy and materials science. S2 provides a detailed characterization of spatial patterns in images typically referred to as clustering or flocculence. The objective of this study was to translate the two-point correlation method into Aβ-PET of the human brain using 11C-Pittsburgh compound B (11C-PiB) to characterize longitudinal changes in the tracer distribution that may reflect changes in Aβ plaque accumulation. Methods We modified the conventional S2 metric, which is primarily used for binary images and formulated a weighted two-point correlation function (wS2) to describe nonbinary, real-valued PET images with a single statistical function. Using serial 11C-PiB scans, we calculated wS2 functions from two-dimensional PET images of different cortical regions as well as three-dimensional data from the whole brain. The area under the wS2 functions was calculated and compared with the mean/median of the standardized uptake value ratio (SUVR). For three-dimensional data, we compared the area under the wS2 curves with the subjects’ cerebrospinal fluid measures. Results Overall, the longitudinal changes in wS2 correlated with the increase in mean SUVR but showed lower variance. The whole brain results showed a higher inverse correlation between the cerebrospinal Aβ and wS2 than between the cerebrospinal Aβ and SUVR mean/median. We did not observe any confounding of wS2 by region size or injected dose. Conclusion The wS2 detects subtle changes and provides additional information about the binding characteristics of radiotracers and Aβ accumulation that are difficult to verify with mean SUVR alone.

Automatic Computation of Brain and Cerebellum Volumes in Normal Subjects and Chronic Alcoholics

Automatic volumetric measurements of brain structures and substructures is a prerequisite for longitudinal studies as well as studies aimed at measuring and quantifying differences between populations. This study tests the hypothesis that a fully automatic, atlas-based method can be used for the computation of the volume encompassed by the dura, the volume of the brain, and the volume of the cerebellum from which indices of atrophy are estimated. The method has been tested on normal volunteers and alcoholic patients. It has been validated both by comparing contours obtained manually and automatically and by repeating the measurements on serial acquisitions. Results demonstrate that the method is both robust and accurate, even in the presence of large morphological differences due to severe atrophy caused by chronic alcoholism.

A new data analysis approach for measuring longitudinal changes of metabolism in cognitively normal elderly adults

Introduction Previously, we discussed several critical barriers in including [18F] fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) imaging of preclinical Alzheimer’s disease (AD) subjects. These factors included the reference region selection and intensity normalization of PET images and the within- and across-subject variability of affected brain regions. In this study, we utilized a novel FDG-PET analysis, the regional FDG time correlation coefficient, rFTC, that can address and resolve these barriers and provide a more sensitive way of monitoring longitudinal changes in metabolism of cognitively normal elderly adults. The rFTC analysis captures the within-subject similarities between baseline and follow-up regional radiotracer distributions. Methods The rFTC trajectories of 27 cognitively normal subjects were calculated to identify 1) trajectories of rFTC decline in individual cognitively normal subjects; 2) how these trajectories correlate with the subjects’ cognitive test scores, baseline cerebrospinal fluid (CSF) levels of amyloid beta (Aβ), and apolipoprotein E4 (APOE-E4) status; and 3) whether similar trajectories are observed in regional/composite standardized uptake value ratio (SUVR) values. Results While some of the subjects maintained a stable rFTC trajectory, other subjects had declining and fluctuating rFTC values. We found that the rFTC decline was significantly higher in APOE-E4 carriers compared to noncarriers (p=0.04). We also found a marginally significant association between rFTC decline and cognitive decline measured by Alzheimer’s Disease Assessment Scale – cognitive subscale (ADAS_cog) decline (0.05). In comparison to the rFTC trajectories, the composite region of interest (ROI) SUVR trajectories did not change in any of the subjects. No individual/composite ROI SUVR changes contributed significantly to explaining changes in ADAS_cog, conversion to mild cognitive impairment (MCI), or any general changes in clinical symptoms. Conclusion The rFTC decline may serve as a new biomarker of early metabolic changes before the MCI stage.

Defining the Expected Growth of the Preterm Infant

The infant mortality rate, defined as the number of children who die before 1 year of age per 1000 live births, has long been considered a measure of a population’s health. The subspecialty of pediatrics now known as neonatology and the Neonatal Intensive Care Unit (NICU) arose from efforts to decrease infant mortality. Access to neonatal intensive care has improved the survival rate of those infants with birth trauma, asphyxia, bacterial infections, and congenital anomalies. Additionally, the miniaturization of technology has made it possible to challenge the lower limits of viability by providing cardiopulmonary support to smaller and prematurely born infants. However, the incidence of low birth weight has not decreased and the incidence of preterm birth is continuing to increase. Providing the care to support the development of the extremely premature infant in an extrauterine environment is an ongoing challenge for all perinatal care providers. Pediatricians agree that nutrition and growth of prematurely born infants in the NICU should be similar to growth in utero. However, in utero nutrition requirements and growth are poorly defined. Multiple investigators have reported values for anthropometric measurements for premature infants, but the values are not coincident. This chapter compares the differences in recently defined growth patterns of preterm infants from 22 to 37 weeks gestation and describes differences in early growth patterns according to race and gender. Additional data are presented to describe the necessary caloric intake to support reasonable growth.

Evaluation of Lung Vascular Permeability by External Scanning of Gamma Emitter Activity

A minimally invasive method for measuring and analyzing lung transvascular protein flux would be useful for diagnosing and monitoring patients with lung injury. We have developed a method which detects movement of radiolabeled albumin from plasma to lung interstitium using sodium iodide detectors that are located outside the body, and positioned over the lung. The technique is similar to methods reported by Gorin (1,2), Prichard and Lee (3,4), and Dauber et al. (5).