Browsing by Author "Ozcan, Alpay"

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A Platform Integrating Acquisition, Reconstruction, Visualization, and Manipulator Control Modules for MRI-Guided Interventions
(SPRINGER, 2019-01-01) Garcia, Jose D. Velazco; Navkar V, Nikhil; Gui, Dawei; Morales, Cristina M.; Christoforou, Eftychios G.; Ozcan, Alpay; Abinahed, Julien; Al-Ansari, Abdulla; Webb, Andrew; Seimenis, Ioannis; Tsekos V, Nikolaos
This work presents a platform that integrates a customized MRI data acquisition scheme with reconstruction and three-dimensional (3D) visualization modules along with a module for controlling an MRI-compatible robotic device to facilitate the performance of robot-assisted, MRI-guided interventional procedures. Using dynamically-acquired MRI data, the computational framework of the platform generates and updates a 3D model representing the area of the procedure (AoP). To image structures of interest in the AoP that do not reside inside the same or parallel slices, the MRI acquisition scheme was modified to collect a multi-slice set of intraoblique to each other slices
On using signal magnitude in diffusion magnetic resonance measurements of restricted motion
(ELSEVIER SCIENCE INC, 2019-01-01) Ozcan, Alpay
Tissue microstructure has significance as a biomarker, however its accurate inference with diffusion magnetic resonance (MR) is still an open problem. With few exceptions, diffusion weighted (DW) MR models either process diffusion MR data using signal magnitude, whereby microstructural information is forcefully confined to symmetry due to Fourier transform properties, or directly use symmetric basis expansions. Herein, information loss from magnitude utilization is demonstrated by numerically simulating particles undergoing diffusion near a fully reflective infinite wall and an orthogonal corner. Simulation results show that the loss of the Hermitian property when using signal magnitude impedes DW MR from accurately inferring microstructural information in both of the geometries.
The effect of tumor shape irregularity on Gamma Knife treatment plan quality and treatment outcome: an analysis of 234 vestibular schwannomas
(NATURE PORTFOLIO, 2022-01-01) Sumer, Esra; Tek, Ece; Ture, O. Artunc; Sengoz, Meric; Dincer, Alp; Ozcan, Alpay; Pamir, M. Necmettin; Ozduman, Koray; Ozturk-Isik, Esin
The primary aim of Gamma Knife (GK) radiosurgery is to deliver high-dose radiation precisely to a target while conforming to the target shape. In this study, the effects of tumor shape irregularity (TSI) on GK dose-plan quality and treatment outcomes were analyzed in 234 vestibular schwannomas. TSI was quantified using seven different metrics including volumetric index of sphericity (VioS). GK treatment plans were created on a single GK-Perfexion/ICON platform. The plan quality was measured using selectivity index (SI), gradient index (GI), Paddick's conformity index (PCI), and efficiency index (EI). Correlation and linear regression analyses were conducted between shape irregularity features and dose plan indices. Machine learning was employed to identify the shape feature that predicted dose plan quality most effectively. The treatment outcome analysis including tumor growth control and serviceable hearing preservation at 2 years, were conducted using Cox regression analyses. All TSI features correlated significantly with the dose plan indices (P < 0.0012). With increasing tumor volume, vestibular schwannomas became more spherical (P < 0.05) and the dose plan indices varied significantly between tumor volume subgroups (P < 0.001 and P < 0.01). VioS was the most effective predictor of GK indices (P < 0.001) and we obtained 89.36\% accuracy (79.17\% sensitivity and 100\% specificity) for predicting PCI. Our results indicated that TSI had significant effects on the plan quality however did not adversely affect treatment outcomes.