@article {reiss2012quantile, title = {Smoothness Selection for Penalized Quantile Regression Splines}, journal = {International Journal of Biostatistics} year={2012}, year = {Submitted}, note = {To appear}, keywords = {keyword-test1}, author = {Philip T. Reiss and Lei Huang} } @article {795, title = {A comparison of supervised machine learning algorithms and feature vectors for MS lesion segmentation using multimodal structural MRI.}, journal = {PLoS One}, volume = {9}, year = {2014}, month = {2014}, pages = {e95753}, abstract = {

Machine learning is a popular method for mining and analyzing large collections of medical data. We focus on a particular problem from medical research, supervised multiple sclerosis (MS) lesion segmentation in structural magnetic resonance imaging (MRI). We examine the extent to which the choice of machine learning or classification algorithm and feature extraction function impacts the performance of lesion segmentation methods. As quantitative measures derived from structural MRI are important clinical tools for research into the pathophysiology and natural history of MS, the development of automated lesion segmentation methods is an active research field. Yet, little is known about what drives performance of these methods. We evaluate the performance of automated MS lesion segmentation methods, which consist of a supervised classification algorithm composed with a feature extraction function. These feature extraction functions act on the observed T1-weighted (T1-w), T2-weighted (T2-w) and fluid-attenuated inversion recovery (FLAIR) MRI voxel intensities. Each MRI study has a manual lesion segmentation that we use to train and validate the supervised classification algorithms. Our main finding is that the differences in predictive performance are due more to differences in the feature vectors, rather than the machine learning or classification algorithms. Features that incorporate information from neighboring voxels in the brain were found to increase performance substantially. For lesion segmentation, we conclude that it is better to use simple, interpretable, and fast algorithms, such as logistic regression, linear discriminant analysis, and quadratic discriminant analysis, and to develop the features to improve performance.

}, issn = {1932-6203}, doi = {10.1371/journal.pone.0095753}, author = {Sweeney, Elizabeth M and Vogelstein, Joshua T and Cuzzocreo, Jennifer L and Calabresi, Peter A and Reich, Daniel S and Crainiceanu, Ciprian M and Shinohara, Russell T} } @article {822, title = {An evaluation of independent component analyses with an application to resting-state fMRI.}, journal = {Biometrics}, volume = {70}, year = {2014}, month = {2014 Mar}, pages = {224-36}, abstract = {

We examine differences between independent component analyses (ICAs) arising from different assumptions, measures of dependence, and starting points of the algorithms. ICA is a popular method with diverse applications including artifact removal in electrophysiology data, feature extraction in microarray data, and identifying brain networks in functional magnetic resonance imaging (fMRI). ICA can be viewed as a generalization of principal component analysis (PCA) that takes into account higher-order cross-correlations. Whereas the PCA solution is unique, there are many ICA methods-whose solutions may differ. Infomax, FastICA, and JADE are commonly applied to fMRI studies, with FastICA being arguably the most popular. Hastie and Tibshirani (2003) demonstrated that ProDenICA outperformed FastICA in simulations with two components. We introduce the application of ProDenICA to simulations with more components and to fMRI data. ProDenICA was more accurate in simulations, and we identified differences between biologically meaningful ICs from ProDenICA versus other methods in the fMRI analysis. ICA methods require nonconvex optimization, yet current practices do not recognize the importance of, nor adequately address sensitivity to, initial values. We found that local optima led to dramatically different estimates in both simulations and group ICA of fMRI, and we provide evidence that the global optimum from ProDenICA is the best estimate. We applied a modification of the Hungarian (Kuhn-Munkres) algorithm to match ICs from multiple estimates, thereby gaining novel insights into how brain networks vary in their sensitivity to initial values and ICA method.

}, keywords = {Adolescent, Algorithms, Attention Deficit Disorder with Hyperactivity, brain mapping, Child, Child, Preschool, Computer Simulation, Humans, Magnetic Resonance Imaging, Models, Statistical, Principal Component Analysis}, issn = {1541-0420}, doi = {10.1111/biom.12111}, author = {Risk, Benjamin B and Matteson, David S and Ruppert, David and Eloyan, Ani and Caffo, Brian S} } @article {790, title = {Health effects of lesion localization in multiple sclerosis: spatial registration and confounding adjustment.}, journal = {PLoS One}, volume = {9}, year = {2014}, month = {2014}, pages = {e107263}, abstract = {

Brain lesion localization in multiple sclerosis (MS) is thought to be associated with the type and severity of adverse health effects. However, several factors hinder statistical analyses of such associations using large MRI datasets: 1) spatial registration algorithms developed for healthy individuals may be less effective on diseased brains and lead to different spatial distributions of lesions; 2) interpretation of results requires the careful selection of confounders; and 3) most approaches have focused on voxel-wise regression approaches. In this paper, we evaluated the performance of five registration algorithms and observed that conclusions regarding lesion localization can vary substantially with the choice of registration algorithm. Methods for dealing with confounding factors due to differences in disease duration and local lesion volume are introduced. Voxel-wise regression is then extended by the introduction of a metric that measures the distance between a patient-specific lesion mask and the population prevalence map.

}, issn = {1932-6203}, doi = {10.1371/journal.pone.0107263}, author = {Eloyan, Ani and Shou, Haochang and Shinohara, Russell T and Sweeney, Elizabeth M and Nebel, Mary Beth and Cuzzocreo, Jennifer L and Calabresi, Peter A and Reich, Daniel S and Lindquist, Martin A and Crainiceanu, Ciprian M} } @article {834, title = {Separate neural representations for physical pain and social rejection.}, journal = {Nat Commun}, volume = {5}, year = {2014}, month = {2014}, pages = {5380}, abstract = {

Current theories suggest that physical pain and social rejection share common neural mechanisms, largely by virtue of overlapping functional magnetic resonance imaging (fMRI) activity. Here we challenge this notion by identifying distinct multivariate fMRI patterns unique to pain and rejection. Sixty participants experience painful heat and warmth and view photos of ex-partners and friends on separate trials. FMRI pattern classifiers discriminate pain and rejection from their respective control conditions in out-of-sample individuals with 92\% and 80\% accuracy. The rejection classifier performs at chance on pain, and vice versa. Pain- and rejection-related representations are uncorrelated within regions thought to encode pain affect (for example, dorsal anterior cingulate) and show distinct functional connectivity with other regions in a separate resting-state data set (N=91). These findings demonstrate that separate representations underlie pain and rejection despite common fMRI activity at the gross anatomical level. Rather than co-opting pain circuitry, rejection involves distinct affective representations in humans.

}, issn = {2041-1723}, doi = {10.1038/ncomms6380}, author = {Woo, Choong-Wan and Koban, Leonie and Kross, Ethan and Lindquist, Martin A and Banich, Marie T and Ruzic, Luka and Andrews-Hanna, Jessica R and Wager, Tor D} } @article {786, title = {Statistical normalization techniques for magnetic resonance imaging.}, journal = {Neuroimage Clin}, volume = {6}, year = {2014}, month = {2014}, pages = {9-19}, abstract = {

While computed tomography and other imaging techniques are measured in absolute units with physical meaning, magnetic resonance images are expressed in arbitrary units that are difficult to interpret and differ between study visits and subjects. Much work in the image processing literature on intensity normalization has focused on histogram matching and other histogram mapping techniques, with little emphasis on normalizing images to have biologically interpretable units. Furthermore, there are no formalized principles or goals for the crucial comparability of image intensities within and across subjects. To address this, we propose a set of criteria necessary for the normalization of images. We further propose simple and robust biologically motivated normalization techniques for multisequence brain imaging that have the same interpretation across acquisitions and satisfy the proposed criteria. We compare the performance of different normalization methods in thousands of images of patients with Alzheimer{\textquoteright}s disease, hundreds of patients with multiple sclerosis, and hundreds of healthy subjects obtained in several different studies at dozens of imaging centers.

}, issn = {2213-1582}, doi = {10.1016/j.nicl.2014.08.008}, author = {Shinohara, Russell T and Sweeney, Elizabeth M and Goldsmith, Jeff and Shiee, Navid and Mateen, Farrah J and Calabresi, Peter A and Jarso, Samson and Pham, Dzung L and Reich, Daniel S and Crainiceanu, Ciprian M} } @article {820, title = {Successful implementation of a unit-based quality nurse to reduce central line-associated bloodstream infections.}, journal = {Am J Infect Control}, volume = {42}, year = {2014}, month = {2014 Feb}, pages = {139-43}, abstract = {

BACKGROUND: Central line (CL)-associated bloodstream infections (CLABSI) are an important cause of patient morbidity and mortality. Novel strategies to prevent CLABSI are needed.

METHODS: We described a quasiexperimental study to examine the effect of the presence of a unit-based quality nurse (UQN) dedicated to perform patient safety and infection control activities with a focus on CLABSI prevention in a surgical intensive care unit (SICU).

RESULTS: From July 2008 to March 2012, there were 3,257 SICU admissions; CL utilization ratio was 0.74 (18,193 CL-days/24,576 patient-days). The UQN program began in July 2010; the nurse was present for 30\% (193/518) of the days of the intervention period of July 2010 to March 2012. The average CLABSI rate was 5.0 per 1,000 CL-days before the intervention and 1.5 after the intervention and decreased by 5.1\% (P = .005) for each additional 1\% of days of the month that the UQN was present, even after adjusting for CLABSI rates in other adult intensive care units, time, severity of illness, and Comprehensive Unit-based Safety Program participation (5.1\%, P = .004). Approximately 11.4 CLABSIs were prevented.

CONCLUSION: The presence of a UQN dedicated to perform infection control activities may be an effective strategy for CLABSI reduction.

}, keywords = {Adult, Catheter-Related Infections, Catheterization, Central Venous, Humans, Infection Control, Intensive Care Units, Nurses, Quality Control, Quality of Health Care}, issn = {1527-3296}, doi = {10.1016/j.ajic.2013.08.006}, author = {Thom, Kerri A and Li, Shanshan and Custer, Melissa and Preas, Michael Anne and Rew, Cindy D and Cafeo, Christina and Leekha, Surbhi and Caffo, Brian S and Scalea, Thomas M and Lissauer, Matthew 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 {807, title = {Bayesian scalar-on-image regression with application to association between intracranial DTI and cognitive outcomes.}, journal = {Neuroimage}, volume = {83}, year = {2013}, month = {2013 Dec}, pages = {210-23}, abstract = {

Diffusion tensor imaging (DTI) measures water diffusion within white matter, allowing for in vivo quantification of brain pathways. These pathways often subserve specific functions, and impairment of those functions is often associated with imaging abnormalities. As a method for predicting clinical disability from DTI images, we propose a hierarchical Bayesian "scalar-on-image" regression procedure. Our procedure introduces a latent binary map that estimates the locations of predictive voxels and penalizes the magnitude of effect sizes in these voxels, thereby resolving the ill-posed nature of the problem. By inducing a spatial prior structure, the procedure yields a sparse association map that also maintains spatial continuity of predictive regions. The method is demonstrated on a simulation study and on a study of association between fractional anisotropy and cognitive disability in a cross-sectional sample of 135 multiple sclerosis patients.

}, issn = {1095-9572}, doi = {10.1016/j.neuroimage.2013.06.020}, author = {Huang, Lei and Goldsmith, Jeff and Reiss, Philip T and Reich, Daniel S and Crainiceanu, Ciprian M} } @article {839, title = {An fMRI-based neurologic signature of physical pain.}, journal = {N Engl J Med}, volume = {368}, year = {2013}, month = {2013 Apr 11}, pages = {1388-97}, abstract = {

BACKGROUND: Persistent pain is measured by means of self-report, the sole reliance on which hampers diagnosis and treatment. Functional magnetic resonance imaging (fMRI) holds promise for identifying objective measures of pain, but brain measures that are sensitive and specific to physical pain have not yet been identified.

METHODS: In four studies involving a total of 114 participants, we developed an fMRI-based measure that predicts pain intensity at the level of the individual person. In study 1, we used machine-learning analyses to identify a pattern of fMRI activity across brain regions--a neurologic signature--that was associated with heat-induced pain. The pattern included the thalamus, the posterior and anterior insulae, the secondary somatosensory cortex, the anterior cingulate cortex, the periaqueductal gray matter, and other regions. In study 2, we tested the sensitivity and specificity of the signature to pain versus warmth in a new sample. In study 3, we assessed specificity relative to social pain, which activates many of the same brain regions as physical pain. In study 4, we assessed the responsiveness of the measure to the analgesic agent remifentanil.

RESULTS: In study 1, the neurologic signature showed sensitivity and specificity of 94\% or more (95\% confidence interval [CI], 89 to 98) in discriminating painful heat from nonpainful warmth, pain anticipation, and pain recall. In study 2, the signature discriminated between painful heat and nonpainful warmth with 93\% sensitivity and specificity (95\% CI, 84 to 100). In study 3, it discriminated between physical pain and social pain with 85\% sensitivity (95\% CI, 76 to 94) and 73\% specificity (95\% CI, 61 to 84) and with 95\% sensitivity and specificity in a forced-choice test of which of two conditions was more painful. In study 4, the strength of the signature response was substantially reduced when remifentanil was administered.

CONCLUSIONS: It is possible to use fMRI to assess pain elicited by noxious heat in healthy persons. Future studies are needed to assess whether the signature predicts clinical pain. (Funded by the National Institute on Drug Abuse and others.).

}, keywords = {Adult, Analgesics, Opioid, Artificial Intelligence, Brain, brain mapping, Female, Hot Temperature, Humans, Magnetic Resonance Imaging, Male, Pain, Pain Measurement, Piperidines, ROC Curve, Sensitivity and Specificity, Young Adult}, issn = {1533-4406}, doi = {10.1056/NEJMoa1204471}, author = {Wager, Tor D and Atlas, Lauren Y and Lindquist, Martin A and Roy, Mathieu and Woo, Choong-Wan and Kross, Ethan} } @article {800, title = {Hierarchical Adaptive Regression Kernels for Regression with Functional Predictors.}, journal = {J Comput Graph Stat}, volume = {22}, year = {2013}, month = {2013}, abstract = {

We propose a new method for regression using a parsimonious and scientifically interpretable representation of functional predictors. Our approach is designed for data that exhibit features such as spikes, dips, and plateaus whose frequency, location, size, and shape varies stochastically across subjects. We propose Bayesian inference of the joint functional and exposure models, and give a method for efficient computation. We contrast our approach with existing state-of-the-art methods for regression with functional predictors, and show that our method is more effective and efficient for data that include features occurring at varying locations. We apply our methodology to a large and complex dataset from the Sleep Heart Health Study, to quantify the association between sleep characteristics and health outcomes. Software and technical appendices are provided in online supplemental materials.

}, issn = {1061-8600}, doi = {10.1080/10618600.2012.694765}, author = {Woodard, Dawn B and Crainiceanu, Ciprian and Ruppert, David} } @article {809, title = {In vivo identification of morphologic retinal abnormalities in neuromyelitis optica.}, journal = {Neurology}, volume = {80}, year = {2013}, month = {2013 Apr 9}, pages = {1406-14}, abstract = {

OBJECTIVE: To assess eyes with neuromyelitis optica (NMO) for morphologic retinal abnormalities utilizing high-definition optical coherence tomography (OCT) imaging.

METHODS: In this cross-sectional study, 39 patients with NMO spectrum disorders and 39 age- and sex-matched healthy controls underwent spectral-domain OCT and visual function testing.

RESULTS: Microcystic macular edema (MME) of the inner nuclear layer (INL) was identified in 10 of 39 patients (26\%) and was exclusively found in eyes with a history of optic neuritis (ON). MME eyes had lower high- and low-contrast letter-acuity scores (100\%: p = 0.002; 2.5\%: p = 0.002; 1.25\%: p = 0.004), lower peripapillary retinal nerve fiber layer (RNFL) thickness (p = 0.04), lower macular RNFL thickness (p = 0.004), lower ganglion cell layer + inner plexiform layer (GCIP) thickness (p = 0.007), higher INL thickness (p < 0.001), and a greater number of ON episodes (p = 0.008) relative to non-MME eyes with a history of ON. After adjusting for history of multiple ON episodes, these findings remained significant for macular-RNFL thickness (p = 0.03), INL thickness (p < 0.001), and 100\% and 2.5\% contrast letter-acuity scores (p = 0.008 and p = 0.03, respectively). NMO spectrum eyes without ON history had lower macular RNFL thickness (p = 0.003), GCIP thickness (p = 0.002), outer nuclear layer thickness (p = 0.02), and low-contrast letter-acuity scores (2.5\%: p = 0.03; 1.25\%: p = 0.002) compared to healthy controls.

CONCLUSIONS: We have identified a pattern of retinal morphologic abnormalities in NMO that is associated with severe retinal axonal and neuronal loss and corresponding visual disability. MME may contribute to poor visual outcomes following NMO-associated ON or alternatively represent a marker of ON severity. Additionally, our results support that subclinical involvement of the anterior visual pathway may occur in NMO spectrum disorders.

}, keywords = {Adolescent, Adult, Aged, Aquaporin 4, Autoantibodies, Case-Control Studies, Chi-Square Distribution, Female, Humans, Macular Edema, Male, Middle Aged, Nerve Fibers, Neuromyelitis Optica, Retina, Tomography, Optical Coherence, Vision Tests, Visual Acuity, Young Adult}, issn = {1526-632X}, doi = {10.1212/WNL.0b013e31828c2f7a}, author = {Sotirchos, Elias S and Saidha, Shiv and Byraiah, Gita and Mealy, Maureen A and Ibrahim, Mohamed A and Sepah, Yasir Jamal and Newsome, Scott D and Ratchford, John N and Frohman, Elliot M and Balcer, Laura J and Crainiceanu, Ciprian M and Nguyen, Quan Dong and Levy, Michael and Calabresi, Peter A} } @article {802, title = {OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI.}, journal = {Neuroimage Clin}, volume = {2}, year = {2013}, month = {2013}, pages = {402-13}, abstract = {

Magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients and is essential for diagnosing the disease and monitoring its progression. In practice, lesion load is often quantified by either manual or semi-automated segmentation of MRI, which is time-consuming, costly, and associated with large inter- and intra-observer variability. We propose OASIS is Automated Statistical Inference for Segmentation (OASIS), an automated statistical method for segmenting MS lesions in MRI studies. We use logistic regression models incorporating multiple MRI modalities to estimate voxel-level probabilities of lesion presence. Intensity-normalized T1-weighted, T2-weighted, fluid-attenuated inversion recovery and proton density volumes from 131 MRI studies (98 MS subjects, 33 healthy subjects) with manual lesion segmentations were used to train and validate our model. Within this set, OASIS detected lesions with a partial area under the receiver operating characteristic curve for clinically relevant false positive rates of 1\% and below of 0.59\% (95\% CI; [0.50\%, 0.67\%]) at the voxel level. An experienced MS neuroradiologist compared these segmentations to those produced by LesionTOADS, an image segmentation software that provides segmentation of both lesions and normal brain structures. For lesions, OASIS out-performed LesionTOADS in 74\% (95\% CI: [65\%, 82\%]) of cases for the 98 MS subjects. To further validate the method, we applied OASIS to 169 MRI studies acquired at a separate center. The neuroradiologist again compared the OASIS segmentations to those from LesionTOADS. For lesions, OASIS ranked higher than LesionTOADS in 77\% (95\% CI: [71\%, 83\%]) of cases. For a randomly selected subset of 50 of these studies, one additional radiologist and one neurologist also scored the images. Within this set, the neuroradiologist ranked OASIS higher than LesionTOADS in 76\% (95\% CI: [64\%, 88\%]) of cases, the neurologist 66\% (95\% CI: [52\%, 78\%]) and the radiologist 52\% (95\% CI: [38\%, 66\%]). OASIS obtains the estimated probability for each voxel to be part of a lesion by weighting each imaging modality with coefficient weights. These coefficients are explicit, obtained using standard model fitting techniques, and can be reused in other imaging studies. This fully automated method allows sensitive and specific detection of lesion presence and may be rapidly applied to large collections of images.

}, issn = {2213-1582}, doi = {10.1016/j.nicl.2013.03.002}, author = {Sweeney, Elizabeth M and Shinohara, Russell T and Shiee, Navid and Mateen, Farrah J and Chudgar, Avni A and Cuzzocreo, Jennifer L and Calabresi, Peter A and Pham, Dzung L and Reich, Daniel S and Crainiceanu, Ciprian M} } @article {801, title = {Quantification of multiple-sclerosis-related brain atrophy in two heterogeneous MRI datasets using mixed-effects modeling.}, journal = {Neuroimage Clin}, volume = {3}, year = {2013}, month = {2013}, pages = {171-9}, abstract = {

Brain atrophy, measured by MRI, has been proposed as a useful surrogate marker for disease progression in multiple sclerosis (MS). However, it is conventionally assumed that the accurate quantification of brain atrophy is made difficult, if not impossible, by changes in the parameters of the MRI acquisition, which are almost inevitable over the course of a longitudinal study since MRI technology changes rapidly. This state of affairs can negatively affect clinical trial design and limit the use of historical data. Here, we investigate whether we can coherently estimate brain atrophy rates in a heterogeneous MS sample via linear mixed-effects multivariable regression, incorporating three critical assumptions: (1) using age at time of scanning, rather than time since baseline, as the regressor of interest; (2) scanning individuals with a variety of techniques; and (3) introducing a simple additive correction for major differences in MRI protocol. We fit the model to several measures of brain volume as the outcome in two MS populations: 1123 scans from 195 cases acquired for over approximately 7~years in two natural history protocols (Cohort 1), and 1331 scans from 69 cases seen for over 11~years who were primarily treated with two specific MS disease-modifying therapies (Cohort 2). We compared the mixed-effects model with additive correction for MRI acquisition parameters to a model fit without this correction and performed sample-size calculations to provide an estimate of the number of participants in an MS clinical trial that might be required to see a therapeutic effect of treatment using the approach described here. The results show that without the additive correction for T1-weighted protocol parameters, atrophy was underestimated and subject-specific estimates were more narrowly distributed about the population mean. Ventricular CSF is the most consistently estimated brain volume, with a mean of 2.8\%/year increase in Cohort 1 and 4.4\%/year increase in Cohort 2. An interesting observation was that gray matter volume decreased and white matter volume remained essentially unchanged in both cohorts, suggesting that changes in ventricular CSF volume are a surrogate for changes in gray matter volume. In conclusion, the mixed-effects modeling framework presented here allows effective use of heterogeneously acquired and historical data in the study of brain atrophy in MS, potentially simplifying the design of future single- and multi-site clinical trials and natural history studies.

}, issn = {2213-1582}, doi = {10.1016/j.nicl.2013.08.001}, author = {Jones, Blake C and Nair, Govind and Shea, Colin D and Crainiceanu, Ciprian M and Cortese, Irene C M and Reich, Daniel S} } @article {811, title = {Relationships between retinal axonal and neuronal measures and global central nervous system pathology in multiple sclerosis.}, journal = {JAMA Neurol}, volume = {70}, year = {2013}, month = {2013 Jan}, pages = {34-43}, abstract = {

OBJECTIVE: To determine the relationships between conventional and segmentation-derived optical coherence tomography (OCT) retinal layer thickness measures with intracranial volume (a surrogate of head size) and brain substructure volumes in multiple sclerosis (MS).

DESIGN: Cross-sectional study.

SETTING: Johns Hopkins University, Baltimore, Maryland.

PARTICIPANTS: A total of 84 patients with MS and 24 healthy control subjects.

MAIN OUTCOME MEASURES: High-definition spectral-domain OCT conventional and automated segmentation-derived discrete retinal layer thicknesses and 3-T magnetic resonance imaging brain substructure volumes.

RESULTS: Peripapillary retinal nerve fiber layer as well as composite ganglion cell layer+inner plexiform layer thicknesses in the eyes of patients with MS without a history of optic neuritis were associated with cortical gray matter (P=.01 and P=.04, respectively) and caudate (P=.04 and P=.03, respectively) volumes. Inner nuclear layer thickness, also in eyes without a history of optic neuritis, was associated with fluid-attenuated inversion recovery lesion volume (P=.007) and inversely associated with normal-appearing white matter volume (P=.005) in relapsing-remitting MS. As intracranial volume was found to be related with several of the OCT measures in patients with MS and healthy control subjects and is already known to be associated with brain substructure volumes, all OCT-brain substructure relationships were adjusted for intracranial volume. CONCLUSIONS Retinal measures reflect global central nervous system pathology in multiple sclerosis, with thicknesses of discrete retinal layers each appearing to be associated with distinct central nervous system processes. Moreover, OCT measures appear to correlate with intracranial volume in patients with MS and healthy control subjects, an important unexpected factor unaccounted for in prior studies examining the relationships between peripapillary retinal nerve fiber layer thickness and brain substructure volumes.

}, keywords = {Adult, Axons, Caudate Nucleus, Central Nervous System, Cerebral Cortex, Cross-Sectional Studies, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Multiple Sclerosis, Retina, Retinal Neurons, Tomography, Optical Coherence}, issn = {2168-6157}, doi = {10.1001/jamaneurol.2013.573}, author = {Saidha, Shiv and Sotirchos, Elias S and Oh, Jiwon and Syc, Stephanie B and Seigo, Michaela A and Shiee, Navid and Eckstein, Chistopher and Durbin, Mary K and Oakley, Jonathan D and Meyer, Scott A and Frohman, Teresa C and Newsome, Scott and Ratchford, John N and Balcer, Laura J and Pham, Dzung L and Crainiceanu, Ciprian M and Frohman, Elliot M and Reich, Daniel S and Calabresi, Peter A} } @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 {landmanb, title = {Biological parametric mapping accounting for random regressors with regression calibration and model II regression}, journal = {Accepted in Neuroimage}, year = {2012}, author = {Yang, X and Lauzon, C and Crainiceanu, C and Caffo, B and Resnick, S and Landman, B} } @article {679, title = {Bootstrap-based inference on the difference in the means of two correlated functional processes.}, journal = {Stat Med}, year = {2012}, month = {2012 Aug 1}, abstract = {

We propose nonparametric inference methods on the mean difference between two correlated functional processes. We compare methods that (1) incorporate different levels of smoothing of the mean and covariance; (2) preserve the sampling design; and (3) use parametric and nonparametric estimation of the mean functions. We apply our method to estimating the mean difference between average normalized δ power of sleep electroencephalograms for 51 subjects with severe sleep apnea and 51 matched controls in the first 4\ ;h after sleep onset. We obtain data from the Sleep Heart Health Study, the largest community cohort study of sleep. Although methods are applied to a single case study, they can be applied to a large number of studies that have correlated functional data. Copyright {\textcopyright} 2012 John Wiley \& Sons, Ltd.

}, issn = {1097-0258}, doi = {10.1002/sim.5439}, author = {Crainiceanu, C and Staicu, A. M. and Ray, Shubankar and Punjabi, Naresh} } @article {ellignton, title = {Computerized lung sound analysis to improve the specificity of pediatric pneumonia in resource-poor settings}, journal = {Accepted in the British Medical Journal Open}, year = {2012}, author = {Ellington, L and Gilman, R and Tielsch, J and Steinhoff, M and Figueroa, D and Rodriguez, S and Caffo, B and Tracey, B and West, J and Checkley, W} } @article {mhssr2012, title = {Functional Generalized Additive Models}, journal = {J. of Computational and Graphical Statistics}, year = {2012}, pages = {to appear}, author = {McLean, M. and Hooker, G. and Staicu, A. M. and Scheipl, F. and Ruppert, D.} } @article {goldsmith, title = {Longitudinal penalized functional regression for cognitive outcomes on neuronal tract measurements}, journal = {Journal of the Royal Statistical Society Series C}, number = {61}, year = {2012}, pages = {453{\textendash}469}, author = {Goldsmith, J and Crainiceanu, C and Caffo, B and Reich, D.} } @article {709, title = {Microcystic macular oedema, thickness of the inner nuclear layer of the retina, and disease characteristics in multiple sclerosis: a retrospective study.}, journal = {Lancet Neurol}, volume = {11}, year = {2012}, month = {2012 Nov}, pages = {963-72}, abstract = {

BACKGROUND: Microcystic macular oedema (MMO) of the retinal inner nuclear layer (INL) has been identified in patients with multiple sclerosis (MS) by use of optical coherence tomography (OCT). We aimed to determine whether MMO of the INL, and increased thickness of the INL are associated with disease activity or disability progression.

METHODS: This retrospective study was done at the Johns Hopkins Hospital (Baltimore, MD, USA), between September, 2008, and March, 2012. Patients with MS and healthy controls underwent serial OCT scans and clinical assessments including visual function. OCT scanning, including automated intraretinal layer segmentation, yielded thicknesses of the retinal nerve fibre layer, the ganglion cell layer plus inner plexiform layer, the INL plus outer plexiform layer (the combined thickness of these layers was used as a surrogate measure of INL thickness), and the outer nuclear layer. Patients with MS also underwent annual brain MRI scans. Disability scores were compared with the Wilcoxon rank-sum test. Mixed-effects linear regression was used to compare OCT measures and letter-acuity scores. Logistic regression was used to examine the relations of baseline OCT thicknesses with clinical and radiological parameters.

FINDINGS: 164 patients with MS and 60 healthy controls were assessed. Mean follow-up was 25{\textperiodcentered}8 months (SD 9{\textperiodcentered}1) for patients with MS and 22{\textperiodcentered}4 months (11{\textperiodcentered}4) for healthy controls. Ten (6\%) patients with MS had MMO during at least one study visit; MMO was visible at baseline in four of these patients. Healthy controls did not have MMO. Patients with MS and MMO had higher baseline MS severity scores (median 5{\textperiodcentered}93 [range 2{\textperiodcentered}44-8{\textperiodcentered}91]) than those who did not have MMO at any time during the study (151 patients; 3{\textperiodcentered}81 [0{\textperiodcentered}13-9{\textperiodcentered}47]; p=0{\textperiodcentered}032), although expanded disability status scale (EDSS) scores were not significantly different (5{\textperiodcentered}2 [1{\textperiodcentered}0-6{\textperiodcentered}5] for patients with MS and MMO vs 2{\textperiodcentered}5 [0{\textperiodcentered}0-8{\textperiodcentered}0] for those without MMO; p=0{\textperiodcentered}097). The eyes of patients with MS and MMO (12 eyes) versus those without MMO (302 eyes) had lower letter-acuity scores (100\% contrast, p=0{\textperiodcentered}017; 2{\textperiodcentered}5\% contrast, p=0{\textperiodcentered}031; 1{\textperiodcentered}25\% contrast, p=0{\textperiodcentered}014), and increased INL thicknesses (p=0{\textperiodcentered}003) at baseline. Increased baseline INL thickness in patients with MS was associated with the development of contrast-enhancing lesions (p=0{\textperiodcentered}007), new T2 lesions (p=0{\textperiodcentered}015), EDSS progression (p=0{\textperiodcentered}034), and relapses in patients with relapsing-remitting MS (p=0{\textperiodcentered}008) during the study. MMO was not associated with disease activity during follow-up.

INTERPRETATION: Increased INL thickness on OCT is associated with disease activity in MS. If this finding is confirmed, INL thickness could be a useful predictor of disease progression in patients with MS.

FUNDING: National Multiple Sclerosis Society, National Eye Institute, Braxton Debbie Angela Dillon and Skip Donor Advisor Fund.

}, keywords = {Adult, Cohort Studies, Female, Follow-Up Studies, Humans, Macular Edema, Male, Middle Aged, Multiple Sclerosis, Retina, Retinal Ganglion Cells, Retrospective Studies, Tomography, Optical Coherence}, issn = {1474-4465}, doi = {10.1016/S1474-4422(12)70213-2}, author = {Saidha, Shiv and Sotirchos, Elias S and Ibrahim, Mohamed A and Crainiceanu, Ciprian M and Gelfand, Jeffrey M and Sepah, Yasir J and Ratchford, John N and Oh, Jiwon and Seigo, Michaela A and Newsome, Scott D and Balcer, Laura J and Frohman, Elliot M and Green, Ari J and Nguyen, Quan D and Calabresi, Peter A} } @article {pmid22006982, title = {Optical coherence tomography segmentation reveals ganglion cell layer pathology after optic neuritis}, journal = {Brain}, volume = {135}, number = {Pt 2}, year = {2012}, month = {Feb}, pages = {521{\textendash}533}, author = {Syc, S. B. and Saidha, S. and Newsome, S and Ratchford, J and Levy, M. and Ford, E. and Crainiceanu, C and Durbin, M. K. and Oakley, J. D. and Meyer, S. A. and Frohman, E. M. and Calabresi, P} } @article {goldsmithNI, title = {Penalized functional regression analysis of white-matter tract profiles in multiple sclerosis}, journal = {Accepted in Neuroimage, PMCID: PMC3114268}, year = {2012}, author = {Goldsmith, J and Crainiceanu, C and Caffo, B and Reich, D.} } @article {pmid22442041, title = {Predicting Breakdown of the Blood-Brain Barrier in Multiple Sclerosis without Contrast Agents}, journal = {AJNR Am J Neuroradiol}, year = {2012}, month = {Mar}, author = {Shinohara, R and Goldsmith, J and Mateen, F J and Crainiceanu, C and Reich, D S} } @article {710, title = {Relationships Between Retinal Axonal and Neuronal Measures and Global Central Nervous System Pathology in Multiple Sclerosis.}, journal = {Arch Neurol}, year = {2012}, month = {2012 Oct 1}, pages = {1-10}, abstract = {

OBJECTIVE To determine the relationships between conventional and segmentation-derived optical coherence tomography (OCT) retinal layer thickness measures with intracranial volume (a surrogate of head size) and brain substructure volumes in multiple sclerosis (MS). DESIGN Cross-sectional study. SETTING Johns Hopkins University, Baltimore, Maryland. PARTICIPANTS A total of 84 patients with MS and 24 healthy control subjects. MAIN OUTCOME MEASURES High-definition spectral-domain OCT conventional and automated segmentation-derived discrete retinal layer thicknesses and 3-T magnetic resonance imaging brain substructure volumes. RESULTS Peripapillary retinal nerve fiber layer as well as composite ganglion cell layer\ +\ inner plexiform layer thicknesses in the eyes of patients with MS without a history of optic neuritis were associated with cortical gray matter (P\ =\ .01 and P\ =\ .04, respectively) and caudate (P\ =\ .04 and P\ =\ .03, respectively) volumes. Inner nuclear layer thickness, also in eyes without a history of optic neuritis, was associated with fluid-attenuated inversion recovery lesion volume (P\ =\ .007) and inversely associated with normal-appearing white matter volume (P\ =\ .005) in relapsing-remitting MS. As intracranial volume was found to be related with several of the OCT measures in patients with MS and healthy control subjects and is already known to be associated with brain substructure volumes, all OCT-brain substructure relationships were adjusted for intracranial volume. CONCLUSIONS Retinal measures reflect global central nervous system pathology in multiple sclerosis, with thicknesses of discrete retinal layers each appearing to be associated with distinct central nervous system processes. Moreover, OCT measures appear to correlate with intracranial volume in patients with MS and healthy control subjects, an important unexpected factor unaccounted for in prior studies examining the relationships between peripapillary retinal nerve fiber layer thickness and brain substructure volumes.

}, issn = {1538-3687}, doi = {10.1001/archneurol.2013.573}, author = {Saidha, Shiv and Sotirchos, Elias S and Oh, Jiwon and Syc, Stephanie B and Seigo, Michaela A and Shiee, Navid and Eckstein, Chistopher and Durbin, Mary K and Oakley, Jonathan D and Meyer, Scott A and Frohman, Teresa C and Newsome, Scott and Ratchford, John N and Balcer, Laura J and Pham, Dzung L and Crainiceanu, Ciprian M and Frohman, Elliot M and Reich, Daniel S and Calabresi, Peter A} } @article {shee, title = {Revisiting Brain Atrophy and Its Relationship to Disability in Multiple Sclerosis}, journal = {PLoS ONE}, volume = {7}, number = {5}, year = {2012}, month = {05}, pages = {e37049}, publisher = {Public Library of Science}, doi = {10.1371/journal.pone.0037049}, url = {http://dx.doi.org/10.1371\%2Fjournal.pone.0037049}, author = {Shiee, N and Bazin, P and Zackowski, K and Farrell, S and Harrison, D and Newsome, S and Ratchford, J and Caffo, B and Calabresi, P and Pham, D and Reich, D.} } @article {830, title = {Total white matter hyperintensity volume in bipolar disorder patients and their healthy relatives.}, journal = {Bipolar Disord}, volume = {14}, year = {2012}, month = {2012 Dec}, pages = {888-93}, abstract = {

OBJECTIVES: White matter hyperintensities (WMH) are more common in subjects with bipolar disorder (BP) than in healthy subjects (HS). Few studies have examined the effect of the diagnostic type of bipolar illness on WMH burden, and none have approached this question through a direct measurement of the volume of affected white matter in relationship to familiality. In this pilot study, we utilized a volumetric measurement of WMH to investigate the relationship between the total volume of WMH and the familiality and type of BP.

METHODS: Forty-five individuals with bipolar I disorder (BP-I) with psychotic features, BP-I without psychotic features, or bipolar II disorder (BP-II), seven of their unaffected relatives, and 32 HS were recruited for participation. T-2 weighted magnetic resonance imaging scans were obtained on all subjects, and the total volume of all WMH for each subject was measured in cubic centimeters. The significance of difference between groups was tested using ANOVA with post-hoc adjustment for multiple comparisons. Further, we used logistic regression to test for trends between symptom load and total WMH volume.

RESULTS: The mean total volume of WMH in BP-I patients with psychotic features was significantly higher (p < 0.05) than that of HS. Further, we observed a positive linear trend by familiality and type of affectedness when comparing mean total WMH volume of HS, unaffected family members, subjects with BP-II, and BP-I with and without a history of psychosis (p < 0.05).

CONCLUSIONS: Based on a quantitative technique, WMH burden appears to be associated with familiality and type of BP. The significance of these findings remains to be fully elucidated.

}, keywords = {Adult, Analysis of Variance, Bipolar Disorder, Brain, Female, Humans, Image Processing, Computer-Assisted, Leukoencephalopathies, Magnetic Resonance Imaging, Male, Nerve Fibers, Myelinated}, issn = {1399-5618}, doi = {10.1111/bdi.12019}, author = {Tighe, Sarah K and Reading, Sarah A and Rivkin, Paul and Caffo, Brian and Schweizer, Barbara and Pearlson, Godfrey and Potash, James B and Depaulo, J Raymond and Bassett, Susan S} } @article {reiss2011extracting, title = {Extracting information from functional connectivity maps via function-on-scalar regression}, journal = {NeuroImage}, volume = {56}, number = {1}, year = {2011}, pages = {140{\textendash}148}, author = {Reiss, P.T. and Mennes, M. and Petkova, E. and Huang, L. and Hoptman, M.J. and Biswal, B.B. and Colcombe, S.J. and Zuo, X.N. and Milham, M.P.} } @article {shinohara2011longitudinal, title = {Longitudinal Analysis of Spatiotemporal Processes: A Case Study of Dynamic Contrast-Enhanced Magnetic Resonance in Multiple Sclerosis}, journal = {Johns Hopkins University, Dept. of Biostatistics Working Papers}, year = {2011}, pages = {231}, publisher = {bepress}, author = {Shinohara, R and Crainiceanu, C and Caffo, B and Reich, D S} } @article {harrison, title = {Longitudinal changes in diffusion-tensor-based quantitative MRI in multiple sclerosis}, journal = {Neurology, PMCID: PMC3030233}, volume = {76}, year = {2011}, pages = {179{\textendash}186}, author = {Harrison, D and Caffo, B and Shiee, N and Farrell, J Bazin, P and Farrell, S and Ratchford, J and Calabresi, P and Reich, D.} } @article {pmid22050118, title = {Modeling Functional Data with Spatially Heterogeneous Shape Characteristics}, journal = {Biometrics}, year = {2011}, month = {Nov}, author = {Staicu, A. M. and Crainiceanu, C and Reich, D S and Ruppert, D.} } @article {goldsmithAAS, title = {Nonlinear tube-fitting for the analysis of anatomical and functional structures}, journal = {Annals of Applied Statistics, PMCID: PMC3119905}, volume = {5}, number = {1}, year = {2011}, pages = {337-363}, issn = {1932-6157}, doi = {10.1214/10-AOAS384}, author = {Goldsmith, J and Caffo, B and Crainiceanu, C and Reich, D. and Du, Y and Hendrix, C} } @article {doi:10.1198/jcgs.2010.10007, title = {Penalized Functional Regression}, journal = {Journal of Computational and Graphical Statistics}, volume = {20}, number = {4}, year = {2011}, pages = {830-851}, doi = {10.1198/jcgs.2010.10007}, url = {http://pubs.amstat.org/doi/abs/10.1198/jcgs.2010.10007}, author = {Goldsmith, J and Bobb, J. and Crainiceanu, C and Caffo, B and Reich, D.} } @article {pmid21554962, title = {Penalized functional regression analysis of white-matter tract profiles in multiple sclerosis}, journal = {Neuroimage}, volume = {57}, number = {2}, year = {2011}, month = {Jul}, pages = {431{\textendash}439}, author = {Goldsmith, J and Crainiceanu, C and Caffo, B and Reich, D S} } @article {takiPCA, title = {Population-wide principal component-based quantification of blood-brain-barrier dynamics in multiple sclerosis}, journal = {Neuroimage, PMCID: PMC3138825}, volume = {57}, number = {4}, year = {2011}, pages = {1430 {\textendash} 1446}, author = {Shinohara, R and Crainiceanu, C and Caffo, B and Gaitan, M and Reich, D.} } @article {nazarian2011AI, title = {Prospective study to assess the safety of a protocol for magnetic resonance imaging of patients with implanted cardiac devices}, journal = {Annals of Interal Medicine}, volume = {155}, number = {7}, year = {2011}, pages = {415{\textendash}424}, publisher = {American College of Physicians}, author = {Nazarian, S and Hansford, R and Roguin, A and Goldsher, D and Zviman, M and Lardo, A and Caffo, B and Frick, K and Kraut, M and Kamel, I and Ihab, R and Calkins, H and Berger, R and Bluemke, D and Halperin, H} } @article {reiss2011resampling, title = {Resampling-Based Information Criteria for Best-Subset Regression}, journal = {Annals of the Institute of Statistical Mathematics}, year = {2011}, author = {Reiss, P.T. and Huang, L. and Cavanaugh, J.E. and Krain Roy, A.} } @article {reiss2010fast, title = {Fast function-on-scalar regression with penalized basis expansions}, journal = {International Journal of Biostatistics}, volume = {6}, number = {1}, year = {2010}, pages = {article{\textendash}28}, author = {Reiss, P.T. and Huang, L. and Mennes, M.} } @article {greven, title = {Longitudinal functional principal components analysis}, journal = {Electronic Journal of Statistics, PMCID: PMC3131008}, volume = {4}, year = {2010}, pages = {1022-1054}, author = {Greven, S. and Crainiceanu, C and Caffo, B and Reich, D.} } @article {reich2, title = {MRI of the Corpus Callosum in Multiple Sclerosis: Association with Disability}, journal = {Multiple Sclerosis, PMCID: PMC2820126}, volume = {16}, number = {2}, year = {2010}, pages = {166{\textendash}177}, author = {Ozturk, A and Smith, S and Gordon-Lipkin, E and Harrison, D and Shiee, N and Pham, D and Caffo, B and Calabresi, P and Reich, D.} } @article {Paninski2010, title = {A new look at state-space models for neural data.}, journal = {Journal of computational neuroscience}, volume = {29}, number = {1-2}, year = {2010}, pages = {107{\textendash}26}, abstract = {

State space methods have proven indispensable in neural data analysis. However, common methods for performing inference in state-space models with non-Gaussian observations rely on certain approximations which are not always accurate. Here we review direct optimization methods that avoid these approximations, but that nonetheless retain the computational efficiency of the approximate methods. We discuss a variety of examples, applying these direct optimization techniques to problems in spike train smoothing, stimulus decoding, parameter estimation, and inference of synaptic properties. Along the way, we point out connections to some related standard statistical methods, including spline smoothing and isotonic regression. Finally, we note that the computational methods reviewed here do not in fact depend on the state-space setting at all; instead, the key property we are exploiting involves the bandedness of certain matrices. We close by discussing some applications of this more general point of view, including Markov chain Monte Carlo methods for neural decoding and efficient estimation of spatially-varying firing rates.

}, keywords = {1 introduction, Action Potentials, Action Potentials: physiology, Animals, Computer Simulation, for inference in state-space, forward-backward methods, hidden markov model, models, neural coding, Neurological, Neurons, Neurons: physiology, Retinal Ganglion Cells, Retinal Ganglion Cells: physiology, state-space models, Statistical, Synapses, Synapses: physiology, tridiagonal matrix}, issn = {1573-6873}, doi = {10.1007/s10827-009-0179-x}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19649698}, author = {Paninski, Liam and Ahmadian, Yashar and Gil, Daniel and Shinsuke, Ferreira and Rahnama, Kamiar and Michael, Rad and Vogelstein, Joshua T and Wu, Wei and Ferreira, Daniel Gil and Koyama, Shinsuke and {Rahnama Rad}, Kamiar and Vidne, Michael} } @article {boatman, title = {Quantifying Auditory Event-Related Responses in Multichannel Human Intracranial Recordings}, journal = {Invited submission to Frontiers in Computational Neuroscience, PMCID: PMC2859880}, volume = {4}, number = {4}, year = {2010}, pages = {1{\textendash}17}, author = {Boatman-Reich, D and Franaszczuk, Piotr J. and Korzeniewska, A. and Caffo, B and Ritzl, E and Colwell, S and Crone, N} } @article {vidwan2010relation, title = {Relation of platelet count to bleeding and vascular complications in patients undergoing coronary angiography}, journal = {The American journal of cardiology}, volume = {105}, number = {9}, year = {2010}, pages = {1219{\textendash}1222}, publisher = {Elsevier}, author = {Vidwan, P. and Lee, S. and Rossi, J.S. and Stouffer, G.A.} } @article {reich2009damage, title = {Damage to the Optic Radiation in Multiple Sclerosis Is Associated With Retinal Injury and Visual Disability}, journal = {Archives of Neurology, PMCID: PMC2784485}, volume = {66}, number = {8}, year = {2009}, pages = {998{\textendash}1006}, publisher = {Am Med Assoc}, author = {Reich, D. and Smith, S and Gordon-Lipkin, E and Ozturk, A and Caffo, B and Balcer, L and Calabresi, P} } @article {o2009prospective, title = {Prospective Study of Sleep-disordered Breathing and Hypertension: The Sleep Heart Health Study}, journal = {American Journal of Respiratory and Critical Care Medicine, PMCID: PMC2695498}, volume = {179}, number = {12}, year = {2009}, pages = {1159{\textendash}1164}, publisher = {Am Thoracic Soc}, author = {O{\textquoteright}Connor, G and Caffo, B and Newman, A and Quan, S and Rapoport, D and Redline, S and Resnick, H and Samet, J and Shahar, E} } @article {punjabi, title = {Sleep-disordered Breathing and Mortality: a Prospective Cohort Study}, journal = {PLOS Medicine, PMCID: PMC2722083}, volume = {6}, year = {2009}, author = {Punjabi, N and Caffo, B and Goodwin, J and Gottlieb, D and Newman, A and O{\textquoteright}Connor, G and Rapoport, D and Redline, S and Resnick, H and Robbins, J and Samet, J and Shahar, E and Unruh, M} } @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:Digg:Rowl:biva:2008, title = {Bivariate Binomial Spatial Modeling of Loa Loa Prevalence in Tropical Africa}, journal = {Journal of the American Statistical Association}, volume = {103}, number = {481}, year = {2008}, pages = {21{\textendash}37}, keywords = {Geostatistics, low rank, thin-plate splines}, author = {Crainiceanu, C and Diggle, Peter J. and Rowlingson, Barry} } @article {redgrave2008differential, title = {Differential brain activation in anorexia nervosa to Fat and Thin words during a Stroop task}, journal = {NeuroReport, PMCID: PMC2891098}, volume = {19}, number = {12}, year = {2008}, pages = {1181{\textendash}1185}, author = {Redgrave, G and Bakker, A and Bello, N and Caffo, B and Coughlin, J and Guarda, A and McEntee, J and Pekar, J and Reinblatt, S and Verduzco, G. and Moran, T} } @article {stamatakis2008fasting, title = {Fasting Glycemia in Sleep Disordered Breathing: Lowering the Threshold on Oxyhemoglobin Desaturation}, journal = {Sleep, PMCID: PMC2491502}, volume = {31}, number = {7}, year = {2008}, pages = {1018{\textendash}1024}, publisher = {American Academy of Sleep Medicine}, author = {Stamatakis, K and Sanders, M and Caffo, B and Resnick, H and Gottlieb, D and Mehra, R and Punjabi, N} } @article {choi2008mechanistic, title = {A mechanistic latent variable model for estimating drug concentrations in the male genital tract: A case study in drug kinetics}, journal = {Statistics in Medicine, PMCID: PMC2763330}, volume = {27}, number = {14}, year = {2008}, pages = {2697{\textendash}2714}, publisher = {John Wiley \& Sons, Ltd Chichester, UK}, author = {Choi, L and Caffo, B and Rohde, C and Ndovi, T and Hendrix, C} } @article {cao2008noninvasive, title = {Noninvasive Quantitation of Drug Concentration in Prostate and Seminal Vesicles: Improvement and Validation With Desipramine and Aspirin}, journal = {The Journal of Clinical Pharmacology}, volume = {48}, number = {2}, year = {2008}, pages = {176-183}, publisher = {Am Coll Clin Pharm}, author = {Cao, Y and Caffo, B and Choi, L and Radebaugh, C and Fuchs, E and Hendrix, C} } @article {streid2008, title = {On probability matching priors}, journal = {The Canadian J. of Statistics}, volume = {36}, year = {2008}, pages = {613{\textendash}622}, author = {Staicu, A. M. and Reid, N} } @article {Crai:Digg:Rowl:rejo:2008, title = {Rejoinder}, journal = {Journal of the American Statistical Association}, volume = {103}, number = {481}, year = {2008}, pages = {43{\textendash}43}, author = {Crainiceanu, C and Diggle, Peter J. and Rowlingson, Barry} } @article {choi2008survey, title = {A survey of the likelihood approach to bioequivalence trials}, journal = {Statistics in Medicine, PMCID: PMC2778077}, volume = {27}, number = {24}, year = {2008}, pages = {4874{\textendash}4894}, publisher = {John Wiley \& Sons, Ltd Chichester, UK}, author = {Choi, L and Caffo, B and Rohde, C} } @article {caffo2007flexible, title = {Flexible random intercept models for binary outcomes using mixtures of normals}, journal = {Computational Statistics and Data Analysis, PMCID: PMC2031853}, volume = {51}, number = {11}, year = {2007}, pages = {5220{\textendash}5235}, publisher = {Elsevier}, author = {Caffo, B and An, M and Rohde, C} } @article {ndovi2007new, title = {A new method to estimate quantitatively seminal vesicle and prostate gland contributions to ejaculate}, journal = {British Journal of Clinical Pharmacology, PMCID: PMC2203235}, volume = {63}, number = {4}, year = {2007}, pages = {404-420}, publisher = {Blackwell Publishing}, author = {Ndovi, T and Parsons, T and Choi, L and Caffo, B and Rohde, C and Hendrix, C} } @article {choi2007optimal, title = {Optimal sampling times in bioequivalence studies using a simulated annealing algorithm}, journal = {Statistics and Computing}, volume = {17}, number = {4}, year = {2007}, pages = {337{\textendash}347}, publisher = {Springer}, author = {Choi, L and Caffo, B and Rohde, C} } @article {pmid17344421, title = {Reduced kidney function as a risk factor for incident heart failure: the atherosclerosis risk in communities (ARIC) study}, journal = {J. Am. Soc. Nephrol.}, volume = {18}, number = {4}, year = {2007}, month = {Apr}, pages = {1307{\textendash}1315}, author = {Kottgen, A. and Russell, S. D. and Loehr, L. R. and Crainiceanu, C and Rosamond, W. D. and Chang, P. P. and Chambless, L. E. and Coresh, J.} } @article {Crai:Rupp:Carr:Josh:Good:spat:2007, title = {Spatially Adaptive Bayesian Penalized Splines with Heteroscedastic Errors}, journal = {Journal of Computational and Graphical Statistics}, volume = {16}, number = {2}, year = {2007}, pages = {265{\textendash}288}, keywords = {Heteroscedasticity, MCMC, Multivariate smoothing, Regression splines, spatially adaptive penalty, thin-plate splines, Variance functions}, author = {Crainiceanu, C and Ruppert, D. and Carroll, Raymond J. and Joshi, Adarsh and Goodner, Billy} } @article {ndovi2006quantitative, title = {Quantitative assessment of seminal vesicle and prostate drug concentrations by use of a noninvasive method}, journal = {Clinical Pharmacology \& Therapeutics}, volume = {80}, number = {2}, year = {2006}, pages = {146{\textendash}158}, publisher = {Nature Publishing Group}, author = {Ndovi, T and Choi, L and Caffo, B and Parsons, T and Baker, S and Zhao, M and Rohde, C and Hendrix, C} } @article {Crai:Rupp:Clae:Wand:exac:2005, title = {Exact Likelihood Ratio Tests for Penalised Splines}, journal = {Biometrika}, volume = {92}, number = {1}, year = {2005}, pages = {91{\textendash}103}, keywords = {Linear mixed model, Penalised spline, Smoothing, Zero variance component}, author = {Crainiceanu, C and Ruppert, D. and Claeskens, Gerda and Wand, M. P.} } @article {Crai:Rupp:like:2004, title = {Likelihood Ratio Tests in Linear Mixed Models with One Variance Component}, journal = {Journal of the Royal Statistical Society, Series B: Statistical Methodology}, volume = {66}, number = {1}, year = {2004}, pages = {165{\textendash}185}, keywords = {Degrees of freedom, Non-regular problems, penalized splines}, author = {Crainiceanu, C and Ruppert, D.} } @article {Carr:Rupp:Crai:Tost:Kara:nonl:2004, title = {Nonlinear and Nonparametric Regression and Instrumental Variables}, journal = {Journal of the American Statistical Association}, volume = {99}, number = {467}, year = {2004}, pages = {736{\textendash}750}, keywords = {Bayesian methods, Identifiability, Measurement error, Simulation extrapolation, Splines, structural modeling}, author = {Carroll, Raymond J. and Ruppert, D. and Crainiceanu, C and Tosteson, Tor D. and Karagas, Margaret R.} } @article {Crai:Rupp:rest:2004, title = {Restricted Likelihood Ratio Tests in Nonparametric Longitudinal Models}, journal = {Statistica Sinica}, volume = {14}, number = {3}, year = {2004}, pages = {713{\textendash}729}, keywords = {Bootstrap, linear mixed models, non-standard asymptotics, penalized splines, subject-specific curves, Variance components}, author = {Crainiceanu, C and Ruppert, D.} } @conference {Crai:Rupp:Sted:Behr:impr:2002, title = {Improving MCMC Mixing for a GLMM Describing Pathogen Concentrations in Water Supplies}, booktitle = {Case Studies in Bayesian Statistics, Volume V (Lecture Notes in Statistics Vol. 162)}, year = {2002}, pages = {207{\textendash}221}, publisher = {Springer-Verlag Inc}, organization = {Springer-Verlag Inc}, keywords = {Ecology}, author = {Crainiceanu, C and Ruppert, D. and Stedinger, Jery R. and Behr, Christopher T.} }