Non-motile cilia are thought to be important determinants of the progression of many types of can... more Non-motile cilia are thought to be important determinants of the progression of many types of cancers. Our goal was to identify patterns of cilia gene dysregulation in eight cancer types (glioblastoma multiforme, colon adenocarcinoma, breast adenocarcinoma, kidney renal clear cell carcinoma, lung squamous cell carcinoma, lung adenocarcinoma, rectal adenocarcinoma, and ovarian cancer) profiled by The Cancer Genome Atlas. Among these types, 2.5-19.8% of cilia-associated genes were significantly differentially expressed (versus 5.5-32.4% dysregulation across all genes). In four cancer types (breast adenocarcinoma, colon adenocarcinoma, glioblastoma multiforme, and ovarian cancer), cilia genes were on average down-regulated (median fold change from -1.53--0.3), in the other four types, cilia genes were up-regulated (fold change=0.86-3.5). Pairwise comparisons between cancer types revealed varying degrees of similarity in the differentially expressed cilia genes, ranging from 7.1% (ovarian cancer and lung squamous cell carcinoma) to 65.8% (ovarian cancer and rectal adenocarcinoma). Hierarchical clustering and principal components analysis of gene expression identified glioblastoma multiforme, colon adenocarcinoma, breast adenocarcinoma; and kidney renal clear cell carcinoma, lung squamous cell carcinoma, lung adenocarcinoma, rectal adenocarcinoma, and ovarian cancer as sub-classes with similar dysregulation patterns. Our study suggests that genes involved in cilia biosynthesis and function are frequently dysregulated in cancer, and may be useful for identifying and classifying cancer types.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2013
A large number of sophisticated techniques have been proposed over the last few decades for autom... more A large number of sophisticated techniques have been proposed over the last few decades for automatic analysis of brain MR images to help clinicians better diagnose and understand anatomical changes due to neurological disorders. While significant improvements in performance have been achieved, almost all techniques suffer from a common limitation of high computational complexity due to the large number of voxels present in a typical MR volume. Computational complexity is a major hurdle in the clinical application of these sophisticated image analysis techniques. Brain MR volumes consist of approximately piecewise constant tissue regions with high redundancy among voxel intensities, which can be grouped into perceptually meaningful entities (superpixels) to reduce the complexity. In this study, we investigate the utility of superpixels (2D) and supervoxels (3D) in reducing computational complexity of brain MR analysis tasks. We investigate the extent of spatial and intensity distort...
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2012
Retrospective correction of intensity inhomogeneities in magnetic resonance images of the brain i... more Retrospective correction of intensity inhomogeneities in magnetic resonance images of the brain is an essential pre-processing step before any sophisticated image analysis task can be performed. A popular choice when defining the degradation model in MR images is to use multiplicative intensity inhomogeneities that slowly varying across the image domain; this approach has been extensively used for bias field estimation. However, such a multiplicative model is often insufficient given that some of the most dominant physical causes of intensity inhomogeneities in MRI (such as nonuniform excitation strength) have a non-linear relationship with the receptor signal intensity. In this study, we consider a linear image degradation model with multiplicative and additive intensity inhomogeneity components. We propose a variational level sets approach that combines estimation of intensity inhomogeneity components during the image segmentation process. The evaluation of proposed approach on re...
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011
Accurate segmentation of magnetic resonance (MR) images of the brain to differentiate features su... more Accurate segmentation of magnetic resonance (MR) images of the brain to differentiate features such as soft tissue, tumor, edema and necrosis is critical for both diagnosis and treatment purposes. Region-based formulations of geometric active contour models are popular choices for segmentation of MR and other medical images. Most of the traditional region-based formulations model local region intensity by assuming a piecewise constant approximation. However, the piecewise constant approximation rarely holds true for medical images such as MR images due to the presence of noise and bias field, which invariably results in a poor segmentation of the image. To overcome this problem, we have developed a probabilistic region-based active contour model for automatic segmentation of MR images of the brain. In our approach, a mixture of Gaussian distributions is used to accurately model the arbitrarily shaped local region intensity distribution. Prior spatial information derived from probabi...
Brain tissue segmentation on magnetic resonance (MR) imaging is a difficult task because of signi... more Brain tissue segmentation on magnetic resonance (MR) imaging is a difficult task because of significant intensity overlap between the tissue classes. We present a new knowledge-driven decision theory (KDT) approach that incorporates prior information of the relative extents of intensity overlap between tissue class pairs for volumetric MR tissue segmentation. The proposed approach better handles intensity overlap between tissues without explicitly employing methods for removal of MR image corruptions (such as bias field). Adaptive tissue class priors are employed that combine probabilistic atlas maps with spatial contextual information obtained from Markov random fields to guide tissue segmentation. The energy function is minimized using a variational level-set-based framework, which has shown great promise for MR image analysis. We evaluate the proposed method on two well-established real MR datasets with expert ground-truth segmentations and compare our approach against existing segmentation methods. KDT has low-computational complexity and shows better segmentation performance than other segmentation methods evaluated using these MR datasets.
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014
Although many genetic markers are identified as being associated with Alzheimer&a... more Although many genetic markers are identified as being associated with Alzheimer's disease (AD), not much is known about their association with the structural changes that happen as the disease progresses. In this study, we investigate the genetic etiology of neurodegeneration in AD by associating genetic markers with atrophy profiles obtained using patient data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. The atrophy profiles were quantified using a linear least-squares regression model over the span of patient enrollment, and used as imaging features throughout the analysis. A subset of the imaging features were selected for genetic association based on their ability to discriminate between healthy individuals and AD patients in a Support Vector Machines (SVM) classifier. Each imaging feature was associated with single-nucleotide polymorphisms (SNPs) using a linear model that included age and cognitive impairment scores as covariates to correct for normal disease progression. After false discovery rate correction, we observed 53 significant associations between SNPs and our imaging features, including associations of ventricular enlargement with SNPs on estrogen receptor 1 (ESR1) and sortilin-related VPS10 domain containing receptor 1 (SORCS1), hippocampal atrophy with SNPs on ESR1, and cerebral atrophy with SNPs on transferrin (TF) and amyloid beta precursor protein (APP). This study provides important insights into genetic predictors of specific types of neurodegeneration that could potentially be used to improve the efficacy of treatment strategies for the disease and allow the development of personalized treatment plans based on each patient's unique genetic profile.
We show here that, although genes constitute only a small percentage of the maize genome, it is p... more We show here that, although genes constitute only a small percentage of the maize genome, it is possible to identify them phenotypically as Ac receptor sites. Simple and efficient Ac transposition assays based on the well-studied endosperm markers bz and wx were used to generate a collection of >1300 independent Ac transposants. The majority of transposed Ac elements are linked to either the bz or the wx donor loci on chromosome 9. A few of the insertions produce obvious visible phenotypes, but most of them do not, suggesting that these populations will be more useful for reverse genetics than for forward transposon mutagenesis. An inverse polymerase chain reaction method was adapted for the isolation of DNA adjacent to the transposed Ac elements (tac sites). Most Ac insertions were into unique DNA. By sequencing tac sites and comparing the sequences to existing databases, insertions were identified in a number of putative maize genes. The expression of most of these genes was confirmed by RNA gel blot analysis. We report here the isolation and characterization of the first 46 tac sites from the two insertion libraries.
Prospective study of 29 patients who underwent anterior cervical (AC) or posterior lumbar (PL) sp... more Prospective study of 29 patients who underwent anterior cervical (AC) or posterior lumbar (PL) spinal surgery. A validated measure of dysphagia, the Swallowing-Quality of Life (SWAL-QOL) survey, was used to assess the degree of postoperative dysphagia. To determine the degree of dysphagia preoperatively and postoperatively in patients undergoing AC surgery compared with a control group that underwent PL surgery. Dysphagia is a well-known complication of AC spine surgery and has been shown to persist for up to 24 months or longer. A total of 18 AC patients and a control group of 11 PL patients were prospectively enrolled in this study and were assessed preoperatively and at 3 weeks and 1.5 years postoperatively using a 14-item questionnaire from the SWAL-QOL survey to determine degree of dysphagia. Other patient factors and anesthesia records were examined to evaluate their relationship to dysphagia. There were no significant differences between the AC and PL groups with respect to age, sex, body mass index, or length of surgery. The SWAL-QOL scores at 3 weeks were significantly lower for the AC group than for the PL group (76 vs. 96; P = 0.001), but there were no differences between the groups preoperatively or at final follow-up. Smokers, patients with chronic obstructive pulmonary disease, and women had lower SWAL-QOL scores at one or more time point. Patients undergoing AC surgery had a significant increase in the degree of dysphagia 3 weeks after surgery compared with patients undergoing PL surgery. By final follow-up, swallowing in the AC group recovered to a level similar to preoperative and comparable to that in patients undergoing lumbar surgery at 1.5 years. Smoking, chronic obstructive pulmonary disease, and female sex are possible factors in the development of postoperative dysphagia.
As their power and utility increase, genome-wide association (GWA) studies are poised to become a... more As their power and utility increase, genome-wide association (GWA) studies are poised to become an important element of the neurosurgeon's toolkit for diagnosing and treating disease. In this paper, the authors review recent findings and discuss issues associated with gathering and analyzing GWA data for the study of neurological diseases and disorders, including those of neurosurgical importance. Their goal is to provide neurosurgeons and other clinicians with a better understanding of the practical and theoretical issues associated with this line of research. A modern GWA study involves testing hundreds of thousands of genetic markers across an entire genome, often in thousands of individuals, for any significant association with a particular disease. The number of markers assayed in a study presents several practical and theoretical issues that must be considered when planning the study. Genome-wide association studies show great promise in our understanding of the genes underlying common neurological diseases and disorders, as well as in leading to a new generation of genetic tests for clinicians.
A seasonal and meteorological influence on the incidence of spontaneous subarachnoid hemorrhage (... more A seasonal and meteorological influence on the incidence of spontaneous subarachnoid hemorrhage (SAH) has been suggested, but a consensus in the literature has yet to emerge. This study examines the impact of weather patterns on the incidence of SAH using a geographically broad analysis of hospital admissions and represents the largest study of the topic to date. We retrospectively analyzed SAH admissions to 155 US hospitals during the calendar years 2004 to 2008 (N = 7758). Daily weather readings for temperature, pressure, and humidity were obtained for the same period from National Oceanic and Atmospheric Administration weather stations located near each hospital. The daily values of each weather variable were associated with the daily volume of SAH admissions using a combination of correlation and time-series analyses. No seasonal trends were observed in the monthly volume of SAH admissions during the study period. No significant correlation was detected between the daily SAH admission volume and the day's weather, the previous day's weather, or the 24-hour weather change. This study represents the most comprehensive investigation of the association between weather and spontaneous SAH to date. The results suggest that neither season nor weather significantly influences the incidence of SAH.
Differentiating treatment-induced necrosis from tumor recurrence is a central challenge in neuro-... more Differentiating treatment-induced necrosis from tumor recurrence is a central challenge in neuro-oncology. These 2 very different outcomes after brain tumor treatment often appear similarly on routine follow-up imaging studies. They may even manifest with similar clinical symptoms, further confounding an already difficult process for physicians attempting to characterize a new contrast-enhancing lesion appearing on a patient's follow-up imaging. Distinguishing treatment necrosis from tumor recurrence is crucial for diagnosis and treatment planning, and therefore, much effort has been put forth to develop noninvasive methods to differentiate between these disparate outcomes. In this article, we review the latest developments and key findings from research studies exploring the efficacy of structural and functional imaging modalities for differentiating treatment necrosis from tumor recurrence. We discuss the possibility of computational approaches to investigate the usefulness of fine-grained imaging characteristics that are difficult to observe through visual inspection of images. We also propose a flexible treatment-planning algorithm that incorporates advanced functional imaging techniques when indicated by the patient's routine follow-up images and clinical condition.
The authors comprehensively studied the recovery of individual patients undergoing treatment for ... more The authors comprehensively studied the recovery of individual patients undergoing treatment for lumbar disc herniation. The primary goal was to gain insight into the variability of individual patient utility scores within a treatment cohort. The secondary goal was to determine how the rates and variability of patient recovery over time, represented by improvement in utility scores, affected long-term patient outcomes. EuroQol Group-5 Dimension (EQ-5D) scores were obtained at baseline and at 2, 4, 8, 12, 26, 38, and 52 weeks for 93 patients treated under a prolonged conservative care protocol for lumbar disc herniation. Gaussian kernel densities were used to estimate the distribution of utility scores at each time point. Logistic regression and multistate Markov models were used to characterize individual patient improvement over time. Fisher exact tests were used to compare the distribution of EQ-5D domain scores. The distribution of utility scores was bimodal at 1 year and effectively sorted patients into a "higher" utility group (EQ-5D = 1; 43% of cohort) and a "lower" utility group (EQ-5D ≤ 0.86; 57% of cohort). Fisher exact tests revealed that pain/discomfort, mobility, and usual activities significantly differed between the 2 utility groups (p ≪ 0.001). The utility groups emerged at 8 weeks and were stable for the remainder of the treatment period. Using utility scores from 8 weeks, regression models predicted 1-year outcomes with 62% accuracy. This study is the first to comprehensively consider the utility recovery of individual patients within a treatment cohort for lumbar disc herniation. The results suggest that most utility is recovered during the early treatment period. Moreover, the findings suggest that initial improvement is critical to a patient's long-term outcome: patients who do not experience significant initial recovery appear unlikely to do so at a later time under the same treatment protocol.
Non-motile cilia are thought to be important determinants of the progression of many types of can... more Non-motile cilia are thought to be important determinants of the progression of many types of cancers. Our goal was to identify patterns of cilia gene dysregulation in eight cancer types (glioblastoma multiforme, colon adenocarcinoma, breast adenocarcinoma, kidney renal clear cell carcinoma, lung squamous cell carcinoma, lung adenocarcinoma, rectal adenocarcinoma, and ovarian cancer) profiled by The Cancer Genome Atlas. Among these types, 2.5-19.8% of cilia-associated genes were significantly differentially expressed (versus 5.5-32.4% dysregulation across all genes). In four cancer types (breast adenocarcinoma, colon adenocarcinoma, glioblastoma multiforme, and ovarian cancer), cilia genes were on average down-regulated (median fold change from -1.53--0.3), in the other four types, cilia genes were up-regulated (fold change=0.86-3.5). Pairwise comparisons between cancer types revealed varying degrees of similarity in the differentially expressed cilia genes, ranging from 7.1% (ovarian cancer and lung squamous cell carcinoma) to 65.8% (ovarian cancer and rectal adenocarcinoma). Hierarchical clustering and principal components analysis of gene expression identified glioblastoma multiforme, colon adenocarcinoma, breast adenocarcinoma; and kidney renal clear cell carcinoma, lung squamous cell carcinoma, lung adenocarcinoma, rectal adenocarcinoma, and ovarian cancer as sub-classes with similar dysregulation patterns. Our study suggests that genes involved in cilia biosynthesis and function are frequently dysregulated in cancer, and may be useful for identifying and classifying cancer types.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2013
A large number of sophisticated techniques have been proposed over the last few decades for autom... more A large number of sophisticated techniques have been proposed over the last few decades for automatic analysis of brain MR images to help clinicians better diagnose and understand anatomical changes due to neurological disorders. While significant improvements in performance have been achieved, almost all techniques suffer from a common limitation of high computational complexity due to the large number of voxels present in a typical MR volume. Computational complexity is a major hurdle in the clinical application of these sophisticated image analysis techniques. Brain MR volumes consist of approximately piecewise constant tissue regions with high redundancy among voxel intensities, which can be grouped into perceptually meaningful entities (superpixels) to reduce the complexity. In this study, we investigate the utility of superpixels (2D) and supervoxels (3D) in reducing computational complexity of brain MR analysis tasks. We investigate the extent of spatial and intensity distort...
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2012
Retrospective correction of intensity inhomogeneities in magnetic resonance images of the brain i... more Retrospective correction of intensity inhomogeneities in magnetic resonance images of the brain is an essential pre-processing step before any sophisticated image analysis task can be performed. A popular choice when defining the degradation model in MR images is to use multiplicative intensity inhomogeneities that slowly varying across the image domain; this approach has been extensively used for bias field estimation. However, such a multiplicative model is often insufficient given that some of the most dominant physical causes of intensity inhomogeneities in MRI (such as nonuniform excitation strength) have a non-linear relationship with the receptor signal intensity. In this study, we consider a linear image degradation model with multiplicative and additive intensity inhomogeneity components. We propose a variational level sets approach that combines estimation of intensity inhomogeneity components during the image segmentation process. The evaluation of proposed approach on re...
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011
Accurate segmentation of magnetic resonance (MR) images of the brain to differentiate features su... more Accurate segmentation of magnetic resonance (MR) images of the brain to differentiate features such as soft tissue, tumor, edema and necrosis is critical for both diagnosis and treatment purposes. Region-based formulations of geometric active contour models are popular choices for segmentation of MR and other medical images. Most of the traditional region-based formulations model local region intensity by assuming a piecewise constant approximation. However, the piecewise constant approximation rarely holds true for medical images such as MR images due to the presence of noise and bias field, which invariably results in a poor segmentation of the image. To overcome this problem, we have developed a probabilistic region-based active contour model for automatic segmentation of MR images of the brain. In our approach, a mixture of Gaussian distributions is used to accurately model the arbitrarily shaped local region intensity distribution. Prior spatial information derived from probabi...
Brain tissue segmentation on magnetic resonance (MR) imaging is a difficult task because of signi... more Brain tissue segmentation on magnetic resonance (MR) imaging is a difficult task because of significant intensity overlap between the tissue classes. We present a new knowledge-driven decision theory (KDT) approach that incorporates prior information of the relative extents of intensity overlap between tissue class pairs for volumetric MR tissue segmentation. The proposed approach better handles intensity overlap between tissues without explicitly employing methods for removal of MR image corruptions (such as bias field). Adaptive tissue class priors are employed that combine probabilistic atlas maps with spatial contextual information obtained from Markov random fields to guide tissue segmentation. The energy function is minimized using a variational level-set-based framework, which has shown great promise for MR image analysis. We evaluate the proposed method on two well-established real MR datasets with expert ground-truth segmentations and compare our approach against existing segmentation methods. KDT has low-computational complexity and shows better segmentation performance than other segmentation methods evaluated using these MR datasets.
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2014
Although many genetic markers are identified as being associated with Alzheimer&a... more Although many genetic markers are identified as being associated with Alzheimer's disease (AD), not much is known about their association with the structural changes that happen as the disease progresses. In this study, we investigate the genetic etiology of neurodegeneration in AD by associating genetic markers with atrophy profiles obtained using patient data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. The atrophy profiles were quantified using a linear least-squares regression model over the span of patient enrollment, and used as imaging features throughout the analysis. A subset of the imaging features were selected for genetic association based on their ability to discriminate between healthy individuals and AD patients in a Support Vector Machines (SVM) classifier. Each imaging feature was associated with single-nucleotide polymorphisms (SNPs) using a linear model that included age and cognitive impairment scores as covariates to correct for normal disease progression. After false discovery rate correction, we observed 53 significant associations between SNPs and our imaging features, including associations of ventricular enlargement with SNPs on estrogen receptor 1 (ESR1) and sortilin-related VPS10 domain containing receptor 1 (SORCS1), hippocampal atrophy with SNPs on ESR1, and cerebral atrophy with SNPs on transferrin (TF) and amyloid beta precursor protein (APP). This study provides important insights into genetic predictors of specific types of neurodegeneration that could potentially be used to improve the efficacy of treatment strategies for the disease and allow the development of personalized treatment plans based on each patient's unique genetic profile.
We show here that, although genes constitute only a small percentage of the maize genome, it is p... more We show here that, although genes constitute only a small percentage of the maize genome, it is possible to identify them phenotypically as Ac receptor sites. Simple and efficient Ac transposition assays based on the well-studied endosperm markers bz and wx were used to generate a collection of >1300 independent Ac transposants. The majority of transposed Ac elements are linked to either the bz or the wx donor loci on chromosome 9. A few of the insertions produce obvious visible phenotypes, but most of them do not, suggesting that these populations will be more useful for reverse genetics than for forward transposon mutagenesis. An inverse polymerase chain reaction method was adapted for the isolation of DNA adjacent to the transposed Ac elements (tac sites). Most Ac insertions were into unique DNA. By sequencing tac sites and comparing the sequences to existing databases, insertions were identified in a number of putative maize genes. The expression of most of these genes was confirmed by RNA gel blot analysis. We report here the isolation and characterization of the first 46 tac sites from the two insertion libraries.
Prospective study of 29 patients who underwent anterior cervical (AC) or posterior lumbar (PL) sp... more Prospective study of 29 patients who underwent anterior cervical (AC) or posterior lumbar (PL) spinal surgery. A validated measure of dysphagia, the Swallowing-Quality of Life (SWAL-QOL) survey, was used to assess the degree of postoperative dysphagia. To determine the degree of dysphagia preoperatively and postoperatively in patients undergoing AC surgery compared with a control group that underwent PL surgery. Dysphagia is a well-known complication of AC spine surgery and has been shown to persist for up to 24 months or longer. A total of 18 AC patients and a control group of 11 PL patients were prospectively enrolled in this study and were assessed preoperatively and at 3 weeks and 1.5 years postoperatively using a 14-item questionnaire from the SWAL-QOL survey to determine degree of dysphagia. Other patient factors and anesthesia records were examined to evaluate their relationship to dysphagia. There were no significant differences between the AC and PL groups with respect to age, sex, body mass index, or length of surgery. The SWAL-QOL scores at 3 weeks were significantly lower for the AC group than for the PL group (76 vs. 96; P = 0.001), but there were no differences between the groups preoperatively or at final follow-up. Smokers, patients with chronic obstructive pulmonary disease, and women had lower SWAL-QOL scores at one or more time point. Patients undergoing AC surgery had a significant increase in the degree of dysphagia 3 weeks after surgery compared with patients undergoing PL surgery. By final follow-up, swallowing in the AC group recovered to a level similar to preoperative and comparable to that in patients undergoing lumbar surgery at 1.5 years. Smoking, chronic obstructive pulmonary disease, and female sex are possible factors in the development of postoperative dysphagia.
As their power and utility increase, genome-wide association (GWA) studies are poised to become a... more As their power and utility increase, genome-wide association (GWA) studies are poised to become an important element of the neurosurgeon's toolkit for diagnosing and treating disease. In this paper, the authors review recent findings and discuss issues associated with gathering and analyzing GWA data for the study of neurological diseases and disorders, including those of neurosurgical importance. Their goal is to provide neurosurgeons and other clinicians with a better understanding of the practical and theoretical issues associated with this line of research. A modern GWA study involves testing hundreds of thousands of genetic markers across an entire genome, often in thousands of individuals, for any significant association with a particular disease. The number of markers assayed in a study presents several practical and theoretical issues that must be considered when planning the study. Genome-wide association studies show great promise in our understanding of the genes underlying common neurological diseases and disorders, as well as in leading to a new generation of genetic tests for clinicians.
A seasonal and meteorological influence on the incidence of spontaneous subarachnoid hemorrhage (... more A seasonal and meteorological influence on the incidence of spontaneous subarachnoid hemorrhage (SAH) has been suggested, but a consensus in the literature has yet to emerge. This study examines the impact of weather patterns on the incidence of SAH using a geographically broad analysis of hospital admissions and represents the largest study of the topic to date. We retrospectively analyzed SAH admissions to 155 US hospitals during the calendar years 2004 to 2008 (N = 7758). Daily weather readings for temperature, pressure, and humidity were obtained for the same period from National Oceanic and Atmospheric Administration weather stations located near each hospital. The daily values of each weather variable were associated with the daily volume of SAH admissions using a combination of correlation and time-series analyses. No seasonal trends were observed in the monthly volume of SAH admissions during the study period. No significant correlation was detected between the daily SAH admission volume and the day's weather, the previous day's weather, or the 24-hour weather change. This study represents the most comprehensive investigation of the association between weather and spontaneous SAH to date. The results suggest that neither season nor weather significantly influences the incidence of SAH.
Differentiating treatment-induced necrosis from tumor recurrence is a central challenge in neuro-... more Differentiating treatment-induced necrosis from tumor recurrence is a central challenge in neuro-oncology. These 2 very different outcomes after brain tumor treatment often appear similarly on routine follow-up imaging studies. They may even manifest with similar clinical symptoms, further confounding an already difficult process for physicians attempting to characterize a new contrast-enhancing lesion appearing on a patient's follow-up imaging. Distinguishing treatment necrosis from tumor recurrence is crucial for diagnosis and treatment planning, and therefore, much effort has been put forth to develop noninvasive methods to differentiate between these disparate outcomes. In this article, we review the latest developments and key findings from research studies exploring the efficacy of structural and functional imaging modalities for differentiating treatment necrosis from tumor recurrence. We discuss the possibility of computational approaches to investigate the usefulness of fine-grained imaging characteristics that are difficult to observe through visual inspection of images. We also propose a flexible treatment-planning algorithm that incorporates advanced functional imaging techniques when indicated by the patient's routine follow-up images and clinical condition.
The authors comprehensively studied the recovery of individual patients undergoing treatment for ... more The authors comprehensively studied the recovery of individual patients undergoing treatment for lumbar disc herniation. The primary goal was to gain insight into the variability of individual patient utility scores within a treatment cohort. The secondary goal was to determine how the rates and variability of patient recovery over time, represented by improvement in utility scores, affected long-term patient outcomes. EuroQol Group-5 Dimension (EQ-5D) scores were obtained at baseline and at 2, 4, 8, 12, 26, 38, and 52 weeks for 93 patients treated under a prolonged conservative care protocol for lumbar disc herniation. Gaussian kernel densities were used to estimate the distribution of utility scores at each time point. Logistic regression and multistate Markov models were used to characterize individual patient improvement over time. Fisher exact tests were used to compare the distribution of EQ-5D domain scores. The distribution of utility scores was bimodal at 1 year and effectively sorted patients into a "higher" utility group (EQ-5D = 1; 43% of cohort) and a "lower" utility group (EQ-5D ≤ 0.86; 57% of cohort). Fisher exact tests revealed that pain/discomfort, mobility, and usual activities significantly differed between the 2 utility groups (p ≪ 0.001). The utility groups emerged at 8 weeks and were stable for the remainder of the treatment period. Using utility scores from 8 weeks, regression models predicted 1-year outcomes with 62% accuracy. This study is the first to comprehensively consider the utility recovery of individual patients within a treatment cohort for lumbar disc herniation. The results suggest that most utility is recovered during the early treatment period. Moreover, the findings suggest that initial improvement is critical to a patient's long-term outcome: patients who do not experience significant initial recovery appear unlikely to do so at a later time under the same treatment protocol.
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Papers by Matthew Cowperthwaite