@article {bai2016activity, title = {An activity index for raw accelerometry data and its comparison with other activity metrics}, journal = {PloS ONE}, volume = {11}, number = {8}, year = {2016}, pages = {e0160644}, publisher = {Public Library of Science}, author = {Bai, Jiawei and Di, Chongzhi and Xiao, Luo and Evenson, Kelly R and LaCroix, Andrea Z and Crainiceanu, Ciprian M and Buchner, David M} } @article {819, title = {Analytic programming with FMRI data: a quick-start guide for statisticians using R.}, journal = {PLoS One}, volume = {9}, year = {2014}, month = {2014}, pages = {e89470}, abstract = {

Functional magnetic resonance imaging (fMRI) is a thriving field that plays an important role in medical imaging analysis, biological and neuroscience research and practice. This manuscript gives a didactic introduction to the statistical analysis of fMRI data using the R project, along with the relevant R code. The goal is to give statisticians who would like to pursue research in this area a quick tutorial for programming with fMRI data. References of relevant packages and papers are provided for those interested in more advanced analysis.

}, keywords = {Brain, brain mapping, Humans, Magnetic Resonance Imaging, Programming Languages}, issn = {1932-6203}, doi = {10.1371/journal.pone.0089470}, author = {Eloyan, Ani and Li, Shanshan and Muschelli, John and Pekar, Jim J and Mostofsky, Stewart H and Caffo, Brian S} } @article {798, title = {Assessing the "physical cliff": detailed quantification of age-related differences in daily patterns of physical activity.}, journal = {J Gerontol A Biol Sci Med Sci}, volume = {69}, year = {2014}, month = {2014 Aug}, pages = {973-9}, abstract = {

BACKGROUND: In spite of evidence that physical activity has beneficial effects on health and age-related functional decline, there is a scarcity of detailed and accurate information on objectively measured daily activity and patterns of such activity in older adults.

METHODS: Participants in the Baltimore Longitudinal Study of Aging (n = 611, 50\% male, mean age 67, range 32-93) wore the Actiheart portable activity monitor for 7 days in the free-living environment. The association between activity and age was modeled using a continuous log-linear regression of activity counts on age with sex, body mass index, employment status, functional performance, and comorbid conditions as covariates.

RESULTS: In the fully adjusted model, continuous analyses demonstrated that overall physical activity counts were 1.3\% lower for each year increase in age. Although there were no differences among morning levels of activity, there was significantly lower afternoon and evening activity in older individuals (p < .01). After adjusting for age, poor functional performance, nonworking status, and higher body mass index were independently associated with less physical activity (p < .001).

CONCLUSIONS: The use of accelerometers to characterize minute-by-minute intensity, cumulative physical activity counts, and daily activity patterns provides detailed data not gathered by traditional subjective methods, particularly at low levels of activity. The findings of a 1.3\% decrease per year in activity from mid-to-late life, and the corresponding drop in afternoon and evening activity, provide new information that may be useful when targeting future interventions. Further, this methodology addresses essential gaps in understanding activity patterns and trends in more sedentary sectors of the population.

}, keywords = {Accelerometry, Adult, Age Factors, Aged, Aged, 80 and over, Employment, Female, Health Behavior, Humans, Linear Models, Longitudinal Studies, Male, Middle Aged, Motor Activity, Physical Fitness, Sedentary Lifestyle}, issn = {1758-535X}, doi = {10.1093/gerona/glt199}, author = {Schrack, Jennifer A and Zipunnikov, Vadim and Goldsmith, Jeff and Bai, Jiawei and Simonsick, Eleanor M and Crainiceanu, Ciprian and Ferrucci, Luigi} } @article {806, title = {Acute lesions that impair affective empathy.}, journal = {Brain}, volume = {136}, year = {2013}, month = {2013 Aug}, pages = {2539-49}, abstract = {

Functional imaging studies of healthy participants and previous lesion studies have provided evidence that empathy involves dissociable cognitive functions that rely on at least partially distinct neural networks that can be individually impaired by brain damage. These studies converge in support of the proposal that affective empathy--making inferences about how another person feels--engages at least the following areas: prefrontal cortex, orbitofrontal gyrus, anterior insula, anterior cingulate cortex, temporal pole, amygdala and temporoparietal junction. We hypothesized that right-sided lesions to any one of these structures, except temporoparietal junction, would cause impaired affective empathy (whereas bilateral damage to temporoparietal junction would be required to disrupt empathy). We studied 27 patients with acute right hemisphere ischaemic stroke and 24 neurologically intact inpatients on a test of affective empathy. Acute impairment of affective empathy was associated with infarcts in the hypothesized network, particularly temporal pole and anterior insula. All patients with impaired affective empathy were also impaired in comprehension of affective prosody, but many patients with impairments in prosodic comprehension had spared affective empathy. Patients with impaired affective empathy were older, but showed no difference in performance on tests of hemispatial neglect, volume of infarct or sex distribution compared with patients with intact affective empathy.

}, keywords = {Adult, Aged, Brain, Brain Ischemia, brain mapping, Cognition, Emotions, Empathy, Female, Functional Laterality, Humans, Male, Middle Aged, Nerve Net, Social Perception, Stroke}, issn = {1460-2156}, doi = {10.1093/brain/awt177}, author = {Leigh, Richard and Oishi, Kenichi and Hsu, John and Lindquist, Martin and Gottesman, Rebecca F and Jarso, Samson and Crainiceanu, Ciprian and Mori, Susumu and Hillis, Argye E} } @article {828, title = {Axial 3D gradient-echo imaging for improved multiple sclerosis lesion detection in the cervical spinal cord at 3T.}, journal = {Neuroradiology}, volume = {55}, year = {2013}, month = {2013 Mar}, pages = {431-9}, abstract = {

INTRODUCTION: In multiple sclerosis (MS), spinal cord imaging can help in diagnosis and follow-up evaluation. However, spinal cord magnetic resonance imaging (MRI) is technically challenging, and image quality, particularly in the axial plane, is typically poor compared to brain MRI. Because gradient-recalled echo (GRE) images might offer improved contrast resolution within the spinal cord at high magnetic field strength, both without and with a magnetization transfer prepulse, we compared them to T2-weighted fast-spin-echo (T2-FSE) images for the detection of MS lesions in the cervical cord at 3T.

METHODS: On a clinical 3T MRI scanner, we studied 62 MS cases and 19 healthy volunteers. Axial 3D GRE sequences were performed without and with off-resonance radiofrequency irradiation. To mimic clinical practice, all images were evaluated in conjunction with linked images from a sagittal short tau inversion recovery scan, which is considered the gold standard for lesion detection in MS. Two experienced observers recorded image quality, location and size of focal lesions, atrophy, swelling, and diffuse signal abnormality independently at first and then in consensus.

RESULTS: The number and volume of lesions detected with high confidence was more than three times as high on both GRE sequences compared to T2-FSE (p < 0.0001). Approximately 5 \% of GRE scans were affected by artifacts that interfered with image interpretation, not significantly different from T2W-FSE.

CONCLUSIONS: Axial 3D GRE sequences are useful for MS lesion detection when compared to 2D T2-FSE sequences in the cervical spinal cord at 3T and should be considered when examining intramedullary spinal cord lesions.

}, keywords = {Adult, Aged, Algorithms, Cervical Vertebrae, Echo-Planar Imaging, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Male, Middle Aged, Multiple Sclerosis, Reproducibility of Results, Sensitivity and Specificity, Spinal Cord}, issn = {1432-1920}, doi = {10.1007/s00234-012-1118-5}, author = {Ozturk, Arzu and Aygun, Nafi and Smith, Seth A and Caffo, Brian and Calabresi, Peter A and Reich, Daniel S} } @article {827, title = {Analysis of group ICA-based connectivity measures from fMRI: application to Alzheimer{\textquoteright}s disease.}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e49340}, abstract = {

Functional magnetic resonance imaging (fMRI) is a powerful tool for the in vivo study of the pathophysiology of brain disorders and disease. In this manuscript, we propose an analysis stream for fMRI functional connectivity data and apply it to a novel study of Alzheimer{\textquoteright}s disease. In the first stage, spatial independent component analysis is applied to group fMRI data to obtain common brain networks (spatial maps) and subject-specific mixing matrices (time courses). In the second stage, functional principal component analysis is utilized to decompose the mixing matrices into population-level eigenvectors and subject-specific loadings. Inference is performed using permutation-based exact logistic regression for matched pairs data. The method is applied to a novel fMRI study of Alzheimer{\textquoteright}s disease risk under a verbal paired associates task. We found empirical evidence of alternative ICA-based metrics of connectivity when comparing subjects evidencing mild cognitive impairment relative to carefully matched controls.

}, keywords = {Aged, Algorithms, Alzheimer Disease, Brain, brain mapping, Case-Control Studies, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Mild Cognitive Impairment, Nerve Net, Principal Component Analysis, Task Performance and Analysis, Time Factors}, issn = {1932-6203}, doi = {10.1371/journal.pone.0049340}, author = {Li, Shanshan and Eloyan, Ani and Joel, Suresh and Mostofsky, Stewart and Pekar, James and Bassett, Susan Spear and Caffo, Brian} } @article {685, title = {Analysis of tiling array expression studies with flexible designs in Bioconductor (waveTiling.}, journal = {BMC Bioinformatics}, volume = {13}, year = {2012}, month = {2012 Sep 14}, pages = {234}, abstract = {

ABSTRACT: BACKGROUND: Existing statistical methods for tiling array transcriptome data either focus on transcript discovery in one biological or experimental condition or on the detection of differential expression between two conditions. Increasingly often, however, biologists are interested in time-course studies, studies with more than two conditions or even multiple-factor studies. As these studies are currently analyzed with the traditional microarray analysis techniques, they do not exploit the genome-wide nature of tiling array data to its full potential. RESULTS: We present an R Bioconductor package, waveTiling, which implements a wavelet-based model for analyzing transcriptome data and extends it towards more complex experimental designs. With waveTiling the user is able to discover (1) group-wise expressed regions, (2) differentially expressed regions between any two groups in single-factor studies and in (3) multifactorial designs. Moreover, for time-course experiments it is also possible to detect (4) linear time effects and (5) a circadian rhythm of transcripts. By considering the expression values of the individual tiling probes as a function of genomic position, effect regions can be detected regardless of existing annotation. Three case studies with different experimental set-ups illustrate the use and the flexibility of the model-based transcriptome analysis. CONCLUSIONS: The waveTiling package provides the user with a convenient tool for the analysis of tiling array trancriptome data for a multitude of experimental set-ups. Regardless of the study design, the probe-wise analysis allows for the detection of transcriptional effects in both exonic, intronic and intergenic regions, without prior consultation of existing annotation.

}, issn = {1471-2105}, doi = {10.1186/1471-2105-13-234}, author = {De Beuf, K. and Pipelers, Peter and Andriankaja, Megan and Thas, O. and Inz{\'e}, Dirk and Crainiceanu, C and Clement, Lieven} } @article {708, title = {Arsenic exposure, diabetes prevalence, and diabetes control in the Strong Heart Study.}, journal = {Am J Epidemiol}, volume = {176}, year = {2012}, month = {2012 Nov 15}, pages = {865-74}, abstract = {

This study evaluated the association of arsenic exposure, as measured in urine, with diabetes prevalence, glycated hemoglobin, and insulin resistance in American Indian adults from Arizona, Oklahoma, and North and South Dakota (1989-1991). We studied 3,925 men and women 45-74 years of age with available urine arsenic measures. Diabetes was defined as a fasting glucose level of 126 mg/dL or higher, a 2-hour glucose level of 200 mg/dL or higher, a hemoglobin A1c (HbA1c) of 6.5\% or higher, or diabetes treatment. Median urine arsenic concentration was 14.1 {\textmu}g/L (interquartile range, 7.9-24.2). Diabetes prevalence was 49.4\%. After adjustment for sociodemographic factors, diabetes risk factors, and urine creatinine, the prevalence ratio of diabetes comparing the 75th versus 25th percentiles of total arsenic concentrations was 1.14 (95\% confidence interval: 1.08, 1.21). The association between arsenic and diabetes was restricted to participants with poor diabetes control (HbA1c >=8\%). Arsenic was positively associated with HbA1c levels in participants with diabetes. Arsenic was not associated with HbA1c or with insulin resistance (assessed by homeostatic model assessment to quantify insulin resistance) in participants without diabetes. Urine arsenic was associated with diabetes control in a population from rural communities in the United States with a high burden of diabetes. Prospective studies that evaluate the direction of the relation between poor diabetes control and arsenic exposure are needed.

}, keywords = {Aged, Arizona, Arsenicals, Blood Glucose, Creatinine, Diabetes Mellitus, Environmental Exposure, Female, Hemoglobin A, Glycosylated, Humans, Indians, North American, Male, Middle Aged, North Dakota, Oklahoma, Poisson Distribution, Prevalence, Regression Analysis, Risk Factors, South Dakota}, issn = {1476-6256}, doi = {10.1093/aje/kws153}, author = {Gribble, Matthew O and Howard, Barbara V and Umans, Jason G and Shara, Nawar M and Francesconi, Kevin A and Goessler, Walter and Crainiceanu, Ciprian M and Silbergeld, Ellen K and Guallar, Eliseo and Navas-Acien, Ana} } @article {calSimex, title = {Assessment of bias in experimentally measured diffusion tensor imaging parameters using SIMEX}, journal = {Accepted in Magnetic Resonance in Medicine}, year = {2012}, author = {Lauzon, C and Crainiceanu, C and Caffo, B and Landman, B} } @article {621, title = {Automatic Lesion Incidence Estimation and Detection in Multiple Sclerosis Using Multisequence Longitudinal MRI.}, journal = {AJNR Am J Neuroradiol}, year = {2012}, month = {2012 Jul 5}, abstract = {

BACKGROUND AND PURPOSE:Detecting incidence and enlargement of lesions is essential in monitoring the progression of MS. In clinical trials, lesion load is observed by manually segmenting and comparing serial MR images, which is time consuming, costly, and prone to inter- and intraobserver variability. Subtracting images from consecutive time points nulls stable lesions, leaving only new lesion activity. We propose SuBLIME, an automated method for segmenting incident lesion voxels.MATERIALS AND METHODS:We used logistic regression models incorporating multiple MR imaging sequences and subtraction images from consecutive longitudinal studies to estimate voxel-level probabilities of lesion incidence. We used T1-weighted, T2-weighted, FLAIR, and PD volumes from a total of 110 MR imaging studies from 10 subjects.RESULTS:To assess the performance of the model, we assigned 5 subjects to a training set and the remaining 5 to a validation set. With SuBLIME, lesion incidence is detected and delineated in the validation set with an AUC of 99\% (95\% CI [97\%, 100\%]) at the voxel level.CONCLUSIONS:This fully automated and computationally fast method allows sensitive and specific detection of lesion incidence that can be applied to large collections of images. Using the explicit form of the statistical model, SuBLIME can easily be adapted to cases when more or fewer imaging sequences are available.

}, issn = {1936-959X}, doi = {10.3174/ajnr.A3172}, author = {Sweeney, E M and Shinohara, R and Shea, C D and Reich, D S and Crainiceanu, C} } @article {ANA:ANA22452, title = {Assessing bioequivalence of generic antiepilepsy drugs}, journal = {Annals of Neurology, NIHMSID: 286919}, volume = {70}, number = {2}, year = {2011}, pages = {221{\textendash}228}, publisher = {Wiley Subscription Services, Inc., A Wiley Company}, issn = {1531-8249}, doi = {10.1002/ana.22452}, url = {http://dx.doi.org/10.1002/ana.22452}, author = {Krauss, G and Caffo, B and Chang, Y and Hendrix, C and Chuang, K} } @article {pmid21995019, title = {Assessment of bias for MRI diffusion tensor imaging using SIMEX}, journal = {Med Image Comput Comput Assist Interv}, volume = {14}, number = {Pt 2}, year = {2011}, pages = {107{\textendash}115}, author = {Lauzon, C and Asman, A. J. and Crainiceanu, C and Caffo, B and Landman, B} } @article {chen2009adaptive, title = {Adaptive control of the false discovery rate in voxel-based morphometry}, journal = {Human Brain Mapping, NIHMSID: 316414}, volume = {30}, number = {7}, year = {2009}, pages = {2304{\textendash}2311}, publisher = {Wiley Subscription Services, Inc., A Wiley Company Hoboken}, author = {Chen, S and Wang, C. and Eberly, L and Caffo, B and Schwartz, B} } @article {scharfstein2008accounting, title = {Accounting for within-patient correlation in assessing relative sensitivity of an adjunctive diagnostic test: Application to lung cancer}, journal = {Statistics in Medicine}, volume = {27}, number = {12}, year = {2008}, pages = {2110{\textendash}2126}, publisher = {John Wiley \& Sons, Ltd Chichester, UK}, author = {Scharfstein, D and Ryea, J and Caffo, B} } @article {Crai:Domi:adju:2008, title = {Adjustment Uncertainty in Effect Estimation}, journal = {Biometrika}, volume = {95}, number = {3}, year = {2008}, pages = {635{\textendash}651}, keywords = {Air pollution, Bayesian model averaging}, author = {Crainiceanu, C and Dominici, Francesca and Parmigiani, G.} } @article {Luo:Crai:Loui:Chat:anal:2008, title = {Analysis of Smoking Cessation Patterns Using a Stochastic Mixed-Effects Model With a Latent Cured State}, journal = {Journal of the American Statistical Association}, volume = {103}, number = {483}, year = {2008}, pages = {1002{\textendash}1013}, keywords = {cure model, Mixed-effects model, Recurrent events, Smoking cessation, stochastic transition model}, author = {Luo, Sheng and Crainiceanu, C and Louis, Thomas A. and Chatterjee, Nilanjan} } @article {caffo2007brain, title = {Are Brain Volumes based on Magnetic Resonance Imaging Mediators of the Associations of Cumulative Lead Dose with Cognitive Function?}, journal = {American Journal of Epidemiology}, volume = {167}, number = {4}, year = {2007}, pages = {429{\textendash}437}, publisher = {Oxford Univ Press}, author = {Caffo, B and Chen, S and Stewart, W and Bolla, K and Yousem, D and Davatzikos, C. and Schwartz, B} } @article {caffo2005ascent, title = {Ascent-Based Monte Carlo EM}, journal = {Journal of the Royal Statistical Society, Series B}, volume = {67}, year = {2005}, pages = {235{\textendash}252}, author = {Caffo, B and Jank, W and Jones, G} }