Statistical Methods for Analysis of Structural Magnetic Resonance Imaging in Patients with Multiple Sclerosis

Multiple sclerosis (MS) is an inflammatory disease of the brain and spinal cord characterized by demyelinating lesions. Structural magnetic resonance imaging (sMRI) is a medical imaging technique that is sensitive to these lesions. Quantitive analyses of MRI, such as the number and volume of MS lesions, are essential for diagnosing the disease and monitoring its progression. In addition, the formation of these lesions, a complex process involving inflammation, tissue damage, and repair, is also important for diagnosing and monitoring the disease. While sMRI is sensitive to lesion activity, there is surprisingly poor association between clinical findings and the radiological extent of involvement on MRI using traditional volumetric measures. This phenomenon is referred to as the clinico-radiological paradox. The work in this thesis is an effort to bridge this clinico-radiological paradox and link the longitudinal findings on structural MRI in patients with MS to disease-modifying treatment and other clinical information. Chapter 2 of the thesis is an introduction to sMRI data. Chapter 3 and 4 of the thesis deal with MS lesion segmentation using multi-sequence structural MRI. Chapter 5 is a culmination of this work. The lesion segmentation technique explored in Chapter 3 and 4 is extended to build a pipeline to extract longitudinal intensity information, or lesion profiles, from lesions in multi-sequence sMRI. A PCA regression model is then introduced to relate the longitudinal lesion profiles to disease-modifying treatment and other clinical information in an attempt to link the information from sMRI to clinical information. In addressing these clinical issue, this thesis also contains a number of biostatistical contributions: the design and analysis of expert rater trials, data reduction techniques for high dimensional and longitudinal data through principal component analysis (PCA) regression models, and the comparison of supervised learning algorithms

Relating multi-sequence longitudinal intensity profiles and clinical covariates in new multiple sclerosis lesions

Structural magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients. The formation of these lesions is a complex process involving inflammation, tissue damage, and tissue repair, all of which are visible on MRI. Here we characterize the lesion formation process on longitudinal, multi-sequence structural MRI from 34 MS patients and relate the longitudinal changes we observe within lesions to therapeutic interventions. In this article, we first outline a pipeline to extract voxel level, multi-sequence longitudinal profiles from four MRI sequences within lesion tissue. We then propose two models to relate clinical covariates to the longitudinal profiles. The first model is a principal component analysis (PCA) regression model, which collapses the information from all four profiles into a scalar value. We find that the score on the first PC identifies areas of slow, long-term intensity changes within the lesion at a voxel level, as validated by two experienced clinicians, a neuroradiologist and a neurologist. On a quality scale of 1 to 4 (4 being the highest) the neuroradiologist gave the score on the first PC a median rating of 4 (95% CI: [4,4]), and the neurologist gave it a median rating of 3 (95% CI: [3,3]). In the PCA regression model, we find that treatment with disease modifying therapies (p-value < 0.01), steroids (p-value < 0.01), and being closer to the boundary of abnormal signal intensity (p-value < 0.01) are associated with a return of a voxel to intensity values closer to that of normal-appearing tissue. The second model is a function-on-scalar regression, which allows for assessment of the individual time points at which the covariates are associated with the profiles. In the function-on-scalar regression both age and distance to the boundary were found to have a statistically significant association with the profiles

Nurses\u27 Alumnae Association Bulletin, December 1968

President\u27s Message Officers and Committee Chairman Financial Report Report to Alumnae Association Annual Report to Alumnae Association School of Practical Nursing Report Student Activities Nursing Service Staff Association Letter from Vietnam Resume of Alumnae Meetings Ways and Means Report Social Committee Building Fund Report Bulletin Committee Report Class News Notice

Congenic Mice Confirm That Collagen X Is Required for Proper Hematopoietic Development

The link between endochondral skeletal development and hematopoiesis in the marrow was established in the collagen X transgenic (Tg) and null (KO) mice. Disrupted function of collagen X, a major hypertrophic cartilage matrix protein, resulted in skeletal and hematopoietic defects in endochondrally derived tissues. Manifestation of the disease phenotype was variable, ranging from perinatal lethality in a subset of mice, to altered lymphopoiesis and impaired immunity in the surviving mice. To exclude contribution of strain specific modifiers to this variable manifestation of the skeleto-hematopoietic phenotype, C57Bl/6 and DBA/2J collagen X congenic lines were established. Comparable disease manifestations confirmed that the skeleto-hematopoietic alterations are an inherent outcome of disrupted collagen X function. Further, colony forming cell assays, complete blood count analysis, serum antibody ELISA, and organ outgrowth studies established altered lymphopoiesis in all collagen X Tg and KO mice and implicated opportunistic infection as a contributor to the severe disease phenotype. These data support a model where endochondral ossification-specific collagen X contributes to the establishment of a hematopoietic niche at the chondro-osseous junction

Purposeful Pedaling: Analyzing MS 150 Participant Behavior

Purpose – The purpose of this paper is to explore factors affecting participant awareness, attraction, and attachment to the National Multiple Sclerosis Society’s (NMSS) MS 150 PGA Tour Cycle to the Shore charitable bike ride utilizing the Psychological Continuum Model (PCM) developed by Funk and James. In addition, the authors sought to outline variables sport organizations can use to predict donor behavior. Design/methodology/approach – Data for this project were derived from an electronic survey distributed to race participants and was analyzed in SPSS® software. Regression analysis was employed. Findings – The findings support previous research employing the PCM; wherein social situational variables have the greatest influence on the relational significance of hedonic and dispositional needs in attraction and attachment to sporting events. The work supports the inclusion of communities as an additional attachment outcome. Practical implications – In all, 92 percent of riders were informed about the event through word of mouth (WOM) marketing, highlighting the importance this promotional technique in the awareness stage of the PCM. NMSS would be well served by capitalizing on the power of WOM. Originality/value – The research provides insight into predictors of fundraising efficacy. In terms of fundraising effectiveness, participants with four or more years of participation were six times more likely than first-year riders to raise $1,000 or more

Removing inter-subject technical variability in magnetic resonance imaging studies

Magnetic resonance imaging (MRI) intensities are acquired in arbitrary units, making scans non-comparable across sites and between subjects. Intensity normalization is a first step for the improvement of comparability of the images across subjects. However, we show that unwanted inter-scan variability associated with imaging site, scanner effect and other technical artifacts is still present after standard intensity normalization in large multi-site neuroimaging studies. We propose RAVEL (Removal of Artificial Voxel Effect by Linear regression), a tool to remove residual technical variability after intensity normalization. As proposed by SVA and RUV [Leek and Storey, 2007, 2008, Gagnon-Bartsch and Speed, 2012], two batch effect correction tools largely used in genomics, we decompose the voxel intensities of images registered to a template into a biological component and an unwanted variation component. The unwanted variation component is estimated from a control region obtained from the cerebrospinal fluid (CSF), where intensities are known to be unassociated with disease status and other clinical covariates. We perform a singular value decomposition (SVD) of the control voxels to estimate factors of unwanted variation. We then estimate the unwanted factors using linear regression for every voxel of the brain and take the residuals as the RAVEL-corrected intensities. We assess the performance of RAVEL using T1-weighted (T1-w) images from more than 900 subjects with Alzheimer’s disease (AD) and mild cognitive impairment (MCI), as well as healthy controls from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. We compare RAVEL to intensity-normalization-only methods, histogram matching, and White Stripe. We show that RAVEL performs best at improving the replicability of the brain regions that are empirically found to be most associated with AD, and that these regions are significantly more present in structures impacted by AD (hippocampus, amygdala, parahippocampal gyrus, enthorinal area and fornix stria terminals). In addition, we show that the RAVEL-corrected intensities have the best performance in distinguishing between MCI subjects and healthy subjects by using the mean hippocampal intensity (AUC=67%), a marked improvement compared to results from intensity normalization alone (AUC=63% and 59% for histogram matching and White Stripe, respectively). RAVEL is generalizable to many imaging modalities, and shows promise for longitudinal studies. Additionally, because the choice of the control region is left to the user, RAVEL can be applied in studies of many brain disorders

Nurses\u27 Alumnae Association Bulletin, June 1969

Alumnae President\u27s Message Officers and Chairmen Financial Report Progressive Changes at Jefferson School of Nursing Report Student Activities School of Practical Nursing Report Jefferson Expansion Report Clerk-Typist Report Committee Reports Resume of Alumnae Meetings Class News 1969 CLINIC Correspondence Notice

Nurses\u27 Alumnae Association Bulletin, June 1967

President\u27s Message Officers and Committee Chairman Financial Report Report to Alumnae Association Nursing Service Report Operating Room Report School of Practical Nursing Report School of Nursing Report President Herbert\u27s Address (abstracted) Report from Africa Student Activities Nursing Service Staff Association Resume of Alumnae Meetings Way and Means Report Social Committee Building Fund Report Class News Notice

Comparing treatment fidelity between study arms of a randomized controlled clinical trial for stroke family caregivers

OBJECTIVE: To compare treatment fidelity among treatment arms in the Telephone Assessment and Skill-Building Kit study for stroke caregivers (TASK II) with respect to: 1) protocol adherence; 2) intervention dosage and 3) nurse intervener perspectives. DESIGN: A randomized controlled clinical trial design. SETTING: Urban, community, midwestern United States. SUBJECTS: A total of 254 stroke caregivers (mean ±SD age, 54.4 ±11.8 years), 55 (22.0%) males and 199 (78.4%) females) randomized to the TASK II intervention (n=123) or an Information, Support, and Referral comparison group (n=131). INTERVENTIONS: TASK II participants received the TASK II Resource Guide; Information, Support, and Referral participants received a standard caregiver brochure. At approximately 8 weeks after discharge, both groups received 8 weekly calls from a nurse, with a booster call 4 weeks later. MEASURES: Protocol adherence was evaluated with the TASK II Checklist for Monitoring Adherence. Intervention dosage was measured by the number of minutes caregivers spent reading materials and talking with the nurse. Nurse intervener perspectives were obtained through focus groups. RESULTS: Protocol adherence was 80% for the TASK II and 92% for the Information, Support, and Referral. As expected, intervention dosage differed between TASK II and Information, Support, and Referral with respect to caregiver time spent reading materials (t=-6.49; P<.001) and talking with the nurse (t=-7.38; P<.001). Focus groups with nurses yielded further evidence for treatment fidelity and recommendations for future trials. CONCLUSIONS: These findings substantiate treatment fidelity in both study arms of the TASK II stroke caregiver intervention trial (NIH R01NR010388; ClinicalTrials.govNCT01275495)

Normalization Techniques for Statistical Inference from Magnetic Resonance Imaging

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\u27s Disease, hundreds of patients with multiple sclerosis, and hundreds of healthy subjects obtained in several different studies at dozens of imaging centers