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Dive into the research topics where Mehmet Akif Gulsun is active.

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Featured researches published by Mehmet Akif Gulsun.


Radiology | 2011

Hepatocellular Carcinoma: Response to TACE Assessed with Semiautomated Volumetric and Functional Analysis of Diffusion-weighted and Contrast-enhanced MR Imaging Data

Susanne Bonekamp; Prashant Jolepalem; Mariana Lazo; Mehmet Akif Gulsun; Atilla Peter Kiraly; Ihab R. Kamel

PURPOSE To determine the association of early changes in posttreatment apparent diffusion coefficient (ADC) and venous enhancement (VE) with tumor size change after transarterial chemoembolization (TACE) by using an investigational semiautomated software. MATERIALS AND METHODS This retrospective HIPAA-compliant study was approved by the institutional review board, with waiver of informed consent. Patients underwent magnetic resonance (MR) imaging at 1.5 T before TACE, as well as 1 and 6 months after TACE. Volumetric analysis of change in ADC and VE 1 month after TACE compared with pretreatment values was performed in 48 patients with 71 hepatocellular carcinoma (HCC) lesions. Diagnostic accuracy was evaluated with receiver operating characteristic (ROC) analysis, using tumor response at 6 months according to Response Evaluation Criteria in Solid Tumors (RECIST) and modified RECIST as end points. RESULTS According to RECIST criteria, 6 months after TACE, 30 HCC lesions showed partial response (PR), 35 showed stable disease (SD), and six showed progressive disease (PD). Increase in ADC and decrease in VE 1 month after TACE were significantly different between PR, SD, and PD. At area under the ROC curve (AUC) analysis of the ADC increase, there was an AUC of 0.78 for distinguishing PR from SD and PD and an AUC of 0.89 for distinguishing PR and SD from PD. The AUC for decrease in VE was 0.73 for discrimination of PR from SD and PD and 0.90 for discrimination of PR and SD from PD. CONCLUSION Volumetric analysis of increase in ADC and decrease in VE 1 month after TACE can provide an early assessment of response to treatment. Volumetric analysis of multiparametric MR imaging data may have potential as a prognostic biomarker for patients undergoing local-regional treatment of liver cancer.


PLOS ONE | 2013

Evaluation of elevated mean pulmonary arterial pressure based on magnetic resonance 4D velocity mapping: comparison of visualization techniques.

Ursula Reiter; Gert Reiter; Gabor Kovacs; Aurélien Stalder; Mehmet Akif Gulsun; Andreas Greiser; Horst Olschewski; Michael Fuchsjäger

Purpose Three-dimensional (3D) magnetic resonance phase contrast imaging (PC-MRI) allows non-invasive diagnosis of pulmonary hypertension (PH) and estimation of elevated mean pulmonary arterial pressure (mPAP) based on vortical motion of blood in the main pulmonary artery. The purpose of the present study was to compare the presence and duration of PH-associated vortices derived from different flow visualization techniques with special respect to their performance for non-invasive assessment of elevated mPAP and diagnosis of PH. Methods Fifty patients with suspected PH (23 patients with and 27 without PH) were investigated by right heart catheterization and time-resolved PC-MRI of the main pulmonary artery. PC-MRI data were visualized with dedicated prototype software, providing 3D vector, multi-planar reformatted (MPR) 2D vector, streamline, and particle trace representation of flow patterns. Persistence of PH-associated vortical blood flow (tvortex) was evaluated with all visualization techniques. Dependencies of tvortex on visualization techniques were analyzed by means of correlation and receiver operating characteristic (ROC) curve analysis. Results tvortex values from 3D vector visualization correlated strongly with those from other visualization techniques (r = 0.98, 0.98 and 0.97 for MPR, streamline and particle trace visualization, respectively). Areas under ROC curves for diagnosis of PH based on tvortex did not differ significantly and were 0.998 for 3D vector, MPR vector and particle trace visualization and 0.999 for streamline visualization. Correlations between elevated mPAP and tvortex in patients with PH were r = 0.96, 0.93, 0.95 and 0.92 for 3D vector, MPR vector, streamline and particle trace visualization, respectively. Corresponding standard deviations from the linear regression lines ranged between 3 and 4 mmHg. Conclusion 3D vector, MPR vector, streamline as well as particle trace visualization of time-resolved 3D PC-MRI data of the main pulmonary artery can be employed for accurate vortex-based diagnosis of PH and estimation of elevated mPAP.


Proceedings of SPIE | 2010

Segmentation of carotid arteries by graph-cuts using centerline models

Mehmet Akif Gulsun; Hüseyin Tek

This document presents a semi-automatic method for segmenting carotid arteries in contrast enhanced (CE)- CT angiography (CTA) scans. The segmentation algorithm extracts the lumen of carotid arteries between user specified locations. Specifically, the algorithm first detects the centerline representations between the user placed seed points. This centerline extraction algorithm is based on a minimal path detection method which operates on a medialness map. The lumen of carotid arteries is then extracted by graph-cuts optimization technique using the detected centerlines as input. The distance from the centerline representation is used to normalize the gradient based edge weights of the graph. It is shown that this algorithm can successfully segment the carotid arteries without including calcified and non-calcified plaques in the segmentation results.


medical image computing and computer assisted intervention | 2016

Coronary Centerline Extraction via Optimal Flow Paths and CNN Path Pruning

Mehmet Akif Gulsun; Gareth Funka-Lea; Puneet Sharma; Saikiran Rapaka; Yefeng Zheng

We present a novel method for the automated extraction of blood vessel centerlines. There are two major contributions. First, in order to avoid the shortcuts to which minimal path methods are prone, we find optimal paths in a computed flow field. We solve for a steady state porous media flow inside a region of interest and trace centerlines as maximum flow paths. We explain how to estimate anisotropic orientation tensors which are used as permeability tensors in our flow field computation. Second, we introduce a convolutional neural network (CNN) classifier for removing extraneous paths in the detected centerlines. We apply our method to the extraction of coronary artery centerlines found in Computed Tomography Angiography (CTA). The robustness and stability of our method are enhanced by using a model-based detection of coronary specific territories and main branches to constrain the search space [15]. Validation against 20 comprehensively annotated datasets had a sensitivity and specificity at or above 90 %. Validation against 106 clinically annotated coronary arteries showed a sensitivity above 97 %.


medical image computing and computer assisted intervention | 2014

CTA Coronary Labeling through Efficient Geodesics between Trees Using Anatomy Priors

Mehmet Akif Gulsun; Gareth Funka-Lea; Yefeng Zheng; Matthias Eckert

We present an efficient realization of recent work on unique geodesic paths between tree shapes for the application of matching coronary arteries to a standard model of coronary anatomy in order to label the coronary arteries. Automatically labeled coronary arteries would speed reporting for physicians. The efficiency of the approach and the quality of the results are enhanced using the relative position of detected cardiac structures. We explain how to efficiently compute the geodesic paths between tree shapes using Dijkstras algorithm and we present a methodology to account for missing side branches during matching. For nearly all labels our approach shows promise compared with recent work and we results for 8 additional labels.


Journal of Computer Assisted Tomography | 2014

Magnetic resonance 4D flow reveals unusual hemodynamics associated with aneurysm formation and a possible cause of cryptogenic stroke in a patient with aortic dissection.

Phillip M. Young; Kiaran P. McGee; Bradley D. Bolster; Lyle D. Joyce; Andreas Greiser; Jens Guehring; Mehmet Akif Gulsun

Abstract Four-dimensional flow is a magnetic resonance technology that has undergone significant technical improvements in recent years. With increasingly rapid acquisition times and new postprocessing tools, it can provide a tool for demonstrating and visualizing cardiovascular flow phenomena, which may offer new insights into disease. We present an interesting clinical case in which 4-dimensional flow demonstrates potential etiologies for 2 interesting phenomena in the same patient: (1) development of an unusual aneurysm and (2) cryptogenic stroke.


Interface Focus | 2018

Non-invasive assessment of patient-specific aortic haemodynamics from four-dimensional flow MRI data

Lucian Mihai Itu; Dominik Neumann; Viorel Mihalef; Felix Meister; Martin Kramer; Mehmet Akif Gulsun; Marcus Kelm; Titus Kühne; Cardioproof; Puneet Sharma

We introduce a parameter estimation framework for automatically and robustly personalizing aortic haemodynamic computations from four-dimensional magnetic resonance imaging data. The framework is based on a reduced-order multiscale fluid–structure interaction blood flow model, and on two calibration procedures. First, Windkessel parameters of the outlet boundary conditions are personalized by solving a system of nonlinear equations. Second, the regional mechanical wall properties of the aorta are personalized by employing a nonlinear least-squares minimization method. The two calibration procedures are run sequentially and iteratively until both procedures have converged. The parameter estimation framework was successfully evaluated on 15 datasets from patients with aortic valve disease. On average, only 1.27 ± 0.96 and 7.07 ± 1.44 iterations were required to personalize the outlet boundary conditions and the regional mechanical wall properties, respectively. Overall, the computational model was in close agreement with the clinical measurements used as objectives (pressures, flow rates, cross-sectional areas), with a maximum error of less than 1%. Given its level of automation, robustness and the short execution time (6.2 ± 1.2 min on a standard hardware configuration), the framework is potentially well suited for a clinical setting.


Journal of Computer Assisted Tomography | 2016

Evaluation of Left Ventricular Outflow Tract Obstruction With Four-Dimensional Phase Contrast Magnetic Resonance Imaging in Patients with Hypertrophic Cardiomyopathy-A Pilot Study.

Linda C. Chu; Kristin Kelly Porter; Celia P. Corona-Villalobos; Mehmet Akif Gulsun; Steven M. Shea; Michael Markl; Theodore P. Abraham; David A. Bluemke; Ihab R. Kamel; Stefan L. Zimmerman

Objective This study aimed to validate 4-dimensional phase contrast (4D PC) cine magnetic resonance imaging (MRI) as a means of evaluating left ventricular outflow tract (LVOT) obstruction in patients with hypertrophic cardiomyopathy (HCM). Methods In this institutional review board-approved prospective study, 23 patients with suspected HCM from October 2012 to September 2013 underwent 4D PC MRI. Postprocessed 4D PC pathline cine data were reviewed by 2 blinded reviewers to determine presence or absence of LVOT obstruction. Sensitivity, specificity, and accuracy in 4D PC qualitative and quantitative assessment of LVOT obstruction were calculated using echo as reference standard. Results Consensus interpretation of 4D PC showed 100.0% (7/7) sensitivity, 75.0% specificity (12/16), and 82.6% (19/23) accuracy in assessment of LVOT obstruction. The 4D PC quantitative estimates of LVOT gradient have 71.4% (5/7) sensitivity, 93.8% (15/16) specificity, and 87.0% (20/23) accuracy in evaluation of LVOT obstruction compared with echo. Conclusions The 4D PC MRI can assess for LVOT obstruction in HCM patients.


Journal of Cardiovascular Magnetic Resonance | 2013

Fast semi-automated analysis of pulse wave velocity in the thoracic aorta using high temporal resolution 4D flow MRI

Bruce S Spottiswoode; Aurélien Stalder; Mehmet Akif Gulsun; Karissa F Campione; Maria Carr; Marie Wasielewski; Michael Markl

Background Pulse wave velocity (PWV) gives an indication of vessel stiffness, which can be used as a marker of age related changes in compliance, as well as to assess changes in vessel elasticity as a measure of atherosclerosis [1,2]. A recent meta-analysis showed PWV to be a robust predictor for cardiovascular events and all-cause mortality [3]. Recently, 4D flow MRI has been applied to assess PWV with full volumetric coverage of the aorta, but the analysis was limited by its low temporal resolution and the labor intensive segmentation of multiple analysis planes along the aorta. In this study, we propose a fast and semi-automated method for reliably extracting PWV from 4D flow data.


Journal of Cardiovascular Magnetic Resonance | 2014

Evaluation of left ventricular outflow tract obstruction with 4D phase contrast in patients with hypertrophic cardiomyopathy

Linda Chu; Celia P. Corona-Villalobos; Mehmet Akif Gulsun; Steven M. Shea; Michael Markl; Theodore P. Abraham; David A. Bluemke; Ihab R. Kamel; Stefan L. Zimmerman

Background Patients with hypertrophic cardiomyopathy (HCM) develop left ventricular outflow tract (LVOT) obstruction due to combination of asymmetric septal hypertrophy and systolic anterior motion of the mitral leaflet. Degree of LVOT obstruction is an important predictor in patient symptoms and clinical outcome. LVOT obstruction is currently assessed by Doppler echocardiography (echo) using peak velocity to calculate pressure gradient in the LVOT. 4D phase contrast (4D PC) MRI is an emerging technique for quantification of regional flow and velocity. 4D PC MRI is a 3 dimensional, 3 directionally encoded, time resolved (cine) velocity acquisition. It has the advantage of providing full 3D volume coverage and flexibility of retrospective analysis of flow at any location and in any imaging plane. In this preliminary study, we

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Ihab R. Kamel

Johns Hopkins University School of Medicine

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