Neurology Commons^™

Prediction Of Rapid Early Progression And Survival Risk With Pre-Radiation Mri In Who Grade 4 Glioma Patients, Walia Farzana, Mustafa M. Basree, Norou Diawara, Zeina Shboul, Sagel Dubey, Marie M. Lockheart, Mohamed Hamza, Joshua D. Palmer, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Rapid early progression (REP) has been defined as increased nodular enhancement at the border of the resection cavity, the appearance of new lesions outside the resection cavity, or increased enhancement of the residual disease after surgery and before radiation. Patients with REP have worse survival compared to patients without REP (non-REP). Therefore, a reliable method for differentiating REP from non-REP is hypothesized to assist in personlized treatment planning. A potential approach is to use the radiomics and fractal texture features extracted from brain tumors to characterize morphological and physiological properties. We propose a random sampling-based ensemble classification model. The proposed …

Awake Craniotomy For Resection Of Intracranial Meningioma: First Case Series From A Low- And Middle-Income Country, Saqib Kamran Bakhshi, Noyan Jawed, Faraz Shafiq, Ather Enam

Section of Neurosurgery

Introduction: Awake craniotomy (AC) has emerged as a better modality for resection of intra-axial brain tumors. The advantages are not just related to the preservation of neurological function, but also include early recovery, short hospital stay and possibly lower costs. However, data on AC for meningioma resection is deficient, likely because of concerns related to intra-operative pain and blood loss.
Methods: All patients who underwent AC, using awake through-out technique for resection of meningioma, during the last five years, were included in the study. Non-probability consecutive sampling technique was employed. Variables for demographics, and details of diagnosis and surgical procedure …

A Comparative Study Of Two Prediction Models For Brain Tumor Progression, Deqi Zhou, Loc Tran, Jihong Wang, Jiang Li, Karen O. Egiazarian (Ed.), Sos S. Agaian (Ed.), Atanas P. Gotchev (Ed.)

Electrical & Computer Engineering Faculty Publications

MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images.

We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. …

Histogram Analysis Of Adc In Brain Tumor Patients, Debrup Banerjee, Jihong Wang, Jiang Li, Norbert J. Pelc (Ed.), Ehsan Samei (Ed.), Robert M. Nishikawa (Ed.)

Electrical & Computer Engineering Faculty Publications

At various stage of progression, most brain tumors are not homogenous. In this presentation, we retrospectively studied the distribution of ADC values inside tumor volume during the course of tumor treatment and progression for a selective group of patients who underwent an anti-VEGF trial. Complete MRI studies were obtained for this selected group of patients including pre- and multiple follow-up, post-treatment imaging studies. In each MRI imaging study, multiple scan series were obtained as a standard protocol which includes T1, T2, T1-post contrast, FLAIR and DTI derived images (ADC, FA etc.) for each visit. All scan series (T1, T2, FLAIR, …

Prediction Of Brain Tumor Progression Using Multiple Histogram Matched Mri Scans, Debrup Banerjee, Loc Tran, Jiang Li, Yuzhong Shen, Frederic Mckenzie, Jihong Wang, Ronald M. Summers (Ed.), Bram Van Ginneken (Ed.)

Electrical & Computer Engineering Faculty Publications

In a recent study [1], we investigated the feasibility of predicting brain tumor progression based on multiple MRI series and we tested our methods on seven patients' MRI images scanned at three consecutive visits A, B and C. Experimental results showed that it is feasible to predict tumor progression from visit A to visit C using a model trained by the information from visit A to visit B. However, the trained model failed when we tried to predict tumor progression from visit B to visit C, though it is clinically more important. Upon a closer look at the MRI scans …

Spectrum Of Intracranial Pathology: Tumors Versus Infections At A Tertiary Care Hospital, Muhib Alam Khan, Sukaina Aijazali Panju, Ather Enam

Section of Neurosurgery

Introduction: Aga Khan University Hospital Neurosurgery Department has evolved into a high-volume centre for treatment of neurosurgical diseases. We aimed to compare the relative outcomes of intracranial tumors and CNS infections seen at our facility.
Methods: Hospital records of patients admitted under the neurosurgery service between 1994-2003 were evaluated. Cases with a principal diagnosis of an intracranial lesion were identified for further study. Demographic, clinical,and surgical variables were extracted from the medical record. Length of hospital stay, ICU utilization, and in-hospital mortality were the primary outcome indicators. Data were analyzed through descriptive statistics and comparisons of meansand proportions. …