Bow Hunter\u27s Syndrome in a Patient with a Right Hypoplastic Vertebral Artery and a Dynamically Compressible Left Vertebral Artery

This is a case report of a 48-year-old man with multiple transient ischemic attacks and a known hypoplastic right vertebral artery (VA) who presented after a syncopal event while turning his head to the left. The objective of this study is to demonstrate the necessity of proper diagnosis and management of cerebrovascular pathology including imaging and surgical intervention in patients with known anatomical anomalies. This study was conducted at Massachusetts, United States of America. Our patient\u27s history was significant for a hypoplastic right VA and a stenotic segment of the right VA at the C3-C4 junction. There was also degeneration of the C3-C4 facet on the left, with osteophyte formation compressing the VA, and a fusion of the C2-C3 segment. Imaging demonstrated obliteration of the left VA flow with head rotation to the left and subsequent reconstitution of flow in the neutral position. After consultation, the patient decided to proceed with surgical management with an anterior cervical discectomy and fusion at the level of C3-C4. Symptoms of vertebrobasilar insufficiency including syncopal episodes resolved after treatment. VA anomalies, although uncommon, are important to understand. Our patient presented with an anomalous right VA, as well as severe degenerative changes to the C2/C3 vertebrae that contributed to the development of Bow Hunter\u27s syndrome. It is essential that proper monitoring and follow-up has to be carried out in patients with abnormal cerebral vasculature to minimize the occurrence of Bow Hunter\u27s syndrome

A dissimilarity representation approach to designing systems for signature verification and bio-cryptography

Automation of legal and financial processes requires enforcing of authenticity, confidentiality, and integrity of the involved transactions. This Thesis focuses on developing offline signature verification (OLSV) systems for enforcing authenticity of transactions. In addition, bio-cryptography systems are developed based on the offline handwritten signature images for enforcing confidentiality and integrity of transactions. Design of OLSV systems is challenging, as signatures are behavioral biometric traits that have intrinsic intra-personal variations and inter-personal similarities. Standard OLSV systems are designed in the feature representation (FR) space, where high-dimensional feature representations are needed to capture the invariance of the signature images. With the numerous users, found in real world applications, e.g., banking systems, decision boundaries in the high-dimensional FR spaces become complex. Accordingly, large number of training samples are required to design of complex classifiers, which is not practical in typical applications. In contrast, design of bio-cryptography systems based on the offline signature images is more challenging. In these systems, signature images lock the cryptographic keys, and a user retrieves his key by applying a query signature sample. For practical bio-cryptographic schemes, the locking feature vector should be concise. In addition, such schemes employ simple error correction decoders, and therefore no complex classification rules can be employed. In this Thesis, the challenging problems of designing OLSV and bio-cryptography systems are addressed by employing the dissimilarity representation (DR) approach. Instead of designing classifiers in the feature space, the DR approach provides a classification space that is defined by some proximity measure. This way, a multi-class classification problem, with few samples per class, is transformed to a more tractable two-class problem with large number of training samples. Since many feature extraction techniques have already been proposed for OLSV applications, a DR approach based on FR is employed. In this case, proximity between two signatures is measured by applying a dissimilarity measure on their feature vectors. The main hypothesis of this Thesis is as follows. The FRs and dissimilarity measures should be properly designed, so that signatures belong to same writer are close, while signatures of different writers are well separated in the resulting DR spaces. In that case, more cost-effecitive classifiers, and therefore simpler OLSV and bio-cryptography systems can be designed. To this end, in Chapter 2, an approach for optimizing FR-based DR spaces is proposed such that concise representations are discriminant, and simple classification thresholds are sufficient. High-dimensional feature representations are translated to an intermediate DR space, where pairwise feature distances are the space constituents. Then, a two-step boosting feature selection (BFS) algorithm is applied. The first step uses samples from a development database, and aims to produce a universal space of reduced dimensionality. The resulting universal space is further reduced and tuned for specific users through a second BFS step using user-specific training set. In the resulting space, feature variations are modeled and an adaptive dissimilarity measure is designed. This measure generates the final DR space, where discriminant prototypes are selected for enhanced representation. The OLSV and bio-cryptographic systems are formulated as simple threshold classifiers that operate in the designed DR space. Proof of concept simulations on the Brazilian signature database indicate the viability of the proposed approach. Concise DRs with few features and a single prototype are produced. Employing a simple threshold classifier, the DRs have shown state-of-the-art accuracy of about 7% AER, comparable to complex systems in the literature. In Chapter 3, the OLSV problem is further studied. Although the aforementioned OLSV implementation has shown acceptable recognition accuracy, the resulting systems are not secure as signature templates must be stored for verification. For enhanced security, we modified the previous implementation as follows. The first BFS step is implemented as aforementioned, producing a writer-independent (WI) system. This enables starting system operation, even if users provide a single signature sample in the enrollment phase. However, the second BFS is modified to run in a FR space instead of a DR space, so that no signature templates are used for verification. To this end, the universal space is translated back to a FR space of reduced dimensionality, so that designing a writer-dependent (WD) system by the few user-specific samples is tractable in the reduced space. Simulation results on two real-world offline signature databases confirm the feasibility of the proposed approach. The initial universal (WI) verification mode showed comparable performance to that of state-of-the-art OLSV systems. The final secure WD verification mode showed enhanced accuracy with decreased computational complexity. Only a single compact classifier produced similar level of accuracy (AER of about 5.38 and 13.96% for the Brazilian and the GPDS signature databases, respectively) as complex WI and WD systems in the literature. Finally, in Chapter 4, a key-binding bio-cryptographic scheme known as the fuzzy vault (FV) is implemented based on the offline signature images. The proposed DR-based two-step BFS technique is employed for selecting a compact and discriminant user-specific FR from a large number of feature extractions. This representation is used to generate the FV locking/unlocking points. Representation variability modeled in the DR space is considered for matching the unlocking and locking points during FV decoding. Proof of concept simulations on the Brazilian signature database have shown FV recognition accuracy of 3% AER and system entropy of about 45-bits. For enhanced security, an adaptive chaff generation method is proposed, where the modeled variability controls the chaff generation process. Similar recognition accuracy is reported, where more enhanced entropy of about 69-bits is achieved

Injection treatment and back pain associated with degenerative lumbar spinal stenosis in older adults

BACKGROUND: Lower back pain is one of the most common health-related complaints in the adult population. Thirty percent of Americans 65 years and older reported symptoms of lower back pain in 2004 (NCHS, 2006). Injection treatment is a commonly used non-surgical procedure to alleviate lower back pain in older adults. However, the effectiveness of injection treatment, particularly in older adults, has not been well documented. OBJECTIVE: This study quantified the effectiveness of injection treatment on pain relief among adults 60 years and over who were diagnosed with degenerative lumbar spinal stenosis, a common cause of lower back pain in older adults. The variations of the effectiveness were examined by selected patient attributes. STUDY DESIGN: Prospective, non-randomized, observational human study. SETTING: Single institution spine clinic. METHODS: Patients scheduled for lumbar injection treatment between January 1 and July 1, 2008 were prospectively selected from the study spine clinic. Selection criteria included patients age 60 and over, diagnosed with degenerative lumbar spinal stenosis and no previous lumbar injection within 6 months or lumbar surgery within 2 years. The pain sub-score of the SF-36 questionnaire was used to measure pain at baseline and at one and 3 months post injection. Variations in longitudinal changes in pain scores by patient characteristics were analyzed in both unadjusted (univariate) analyses using one-way analysis of variance (ANOVA), and adjusted (multiple regression) analyses using linear mixed effects models. LIMITATIONS: This study is limited by its sample size and observational design. RESULTS: Of 62 patients receiving epidural steroid injections, the mean Pain score at baseline was 27.4 (SD =13.6), 41.7 (SD = 22.0) at one month and 35.8 (SD = 19.0) at 3 months. Mean Pain scores improved significantly from baseline to one month (14.1 points), and from baseline to 3 months (8.3 points). Post injection changes in pain scores varied by body mass index (BMI) and baseline emotional health. Based on a linear mixed effects model analysis, higher baseline emotional health, as measured by the SF-36 Mental Component Score (MCS \u3e/= 50), was associated with greater reduction in pain over 3 months when compared to lower emotional health (MCS), was associated with greater reduction in pain over 3 months when compared to lower emotional health (MCS \u3c50). In patients with higher emotional health, pain scores improved by 14.1 (P \u3c .05: 95% CI 6.9, 21.3). Patients who were obese also showed significant improvement in pain scores over 3 months compared to non-obese patients. In obese patients, pain scores increased by 7.9 (P \u3c.05; 95% CI:1.0, 14.8) points. CONCLUSION: Lower back pain in older adults with degenerative lumbar spinal stenosis might be clinically significantly alleviated after injection treatment. Pain relief varies by a patients personal and clinical characteristics. Healthier emotional status and obesity appears to be associated with more pain relief experienced over 3 months following injection

Income diversification and income inequality : household responses to the 2013 floods in Pakistan

In this paper we investigate the economic response of rural households to the 2013 floods in Pakistan. The case study illustrates the important roles of labor supply adjustments and income diversification in coping with climate-related risks. Using detailed household panel data that were collected before and after the 2013 floods, we find that the exposure to flood results in lower participation in farm activities. The overall effects are decreased diversification in the sources of income and ambiguous reduction in inequality which is associated with overall declines in incomes. These changes could be locked in if affected households do not have sufficient assets to resume farming. The results suggest intervention points for public policy, related to labor mobility and access to capital

The association between preoperative spinal cord rotation and postoperative C5 nerve palsy

BACKGROUND: C5 nerve palsy is a known complication of cervical spine surgery. The development and etiology of this complication are not completely understood. The purpose of the present study was to determine whether rotation of the cervical spinal cord predicts the development of a C5 palsy. METHODS: We performed a retrospective review of prospectively collected spine registry data as well as magnetic resonance images. We reviewed the records for 176 patients with degenerative disorders of the cervical spine who underwent anterior cervical decompression or corpectomy within the C4 to C6 levels. Our measurements included area for the spinal cord, space available for the cord, and rotation of the cord with respect to the vertebral body. RESULTS: There was a 6.8% prevalence of postoperative C5 nerve palsy as defined by deltoid motor strength of /= 11 degrees ) and palsy (point-biserial correlation = 0.94; p \u3c 0.001). A diagnostic criterion of 6 degrees of rotation could identify patients who had a C5 palsy (sensitivity = 1.00 [95% confidence interval, 0.70 to 1.00], specificity = 0.97 [95% confidence interval, 0.93 to 0.99], positive predictive value = 0.71 [95% confidence interval, 0.44 to 0.89], negative predictive value = 1.00 [95% confidence interval, 0.97 to 1.00]). CONCLUSIONS: Our evidence suggests that spinal cord rotation is a strong and significant predictor of C5 palsy postoperatively. Patients can be classified into three types, with Type 1 representing mild rotation (0 degrees to 5 degrees ), Type 2 representing moderate rotation (6 degrees to 10 degrees ), and Type 3 representing severe rotation (\u3e/= 11 degrees ). The rate of C5 palsy was zero of 159 in the Type-1 group, eight of thirteen in the Type-2 group, and four of four in the Type-3 group. This information may be valuable for surgeons and patients considering anterior surgery in the C4 to C6 levels