Browsing by Author "Aygün, Elif"

Now showing 1 - 4 of 4

Restricted
1959 Türk Hava Yolları Londra Seferi Kazası
(Bilkent University, 2017) Tekdaş, Arsen Berk; Çoban, Çağan Selim; Aygün, Elif; Pehlivan, Mertcan; Binici, Zümrüt Selen
Open Access
Assessment of glymphatic function in narcolepsy using DTI-ALPS index
(Elsevier BV, 2022-12-09) Gümeler, E.; Aygün, Elif; İrsel Tezer, F.; Sarıtaş, Emine Ülkü; Karlı Oğuz, K.
Introduction Sleep is a modulator of glymphatic activity which is altered in various sleep disorders. Narcolepsy is a sleep disorder characterized by excessive daytime sleepiness (EDS), rapid onset of rapid eye movement (REM) sleep, cataplexy, disturbed night sleep with fragmentation. It is categorized into two types, type 1 (NT1) and type 2 (NT2) depending on the presence of cataplexy and/or absence of orexin. We sought for alterations in glymphatic activity in narcoleptic patients using diffusion tensor imaging (DTI) along perivascular space (ALPS) index on magnetic resonance imaging (MRI). Material and methods Adult patients diagnosed with NT1 or NT2 who had polysomnography (PSG) and MRI with DTI were included in the study. Sleep recording included Epworth Sleepiness Scale (ESS) score, sleep latency during multiple sleep latency test (MSLT), sleep efficiency during night PSG, wake after sleep onset (WASO), REM sleep latency during PSG, percentage of non-REM (NREM), REM sleep and wakefulness during night PSG. DTI-ALPS index was calculated for each patient and age-sex matched healthy control(HC)s. Results The study group was composed of 25 patients [F/M = 15/10, median age = 34 (29.5–44.5)], 14 with NT1 and 11 with NT2 disease. ESS, WASO and percentage of wakefulness were significantly higher in NT1 patients (p < 0.05). Mean DTI-ALPS was not significantly different neither between narcoleptic patients and HCs, nor between NT1 and NT2 patients (all, p > 0.05). However, DTI-ALPS was negatively correlated with WASO (r = −0.745, p = 0.013) and percentage of wakefulness (r = −0.837, p = 0.005) in NT1 patients. DTI-ALPS correlated negatively with percentage of N1 sleep (r = −0.781, p = 0.005) but positively with REM percentage (r = 0.618, p = 0.043) in NT2 patients. Conclusion In this study, DTI-ALPS was not significantly different in narcoleptic patients than the HCs. However, the glymphatic index as assessed by DTI-ALPS correlated with PSG parameters; negatively with WASO, percentage of wakefulness in NT1, percentage of N1 sleep in NT2, and positively with REM sleep in NT2. A tendency for a reduction in DTI-ALPS in NT1 patients compared to both NT2 patients and HCs was also found. These findings might show the first evidence of an alteration of glymphatic activity, especially in NT1 patients, thus warrant further prospective studies in larger size of narcoleptic patient cohorts.
Open Access
Assessment of undersampling strategies for accelerated multi-shell diffusion MRI
(2022-08) Aygün, Elif
Diffusion Magnetic Resonance Imaging (dMRI) is a non-invasive imaging technique that can probe the Brownian motion of water molecules within the neurite tissue. Measuring diffusion in the brain by densely sampling the q-space allows quantification of neural microstructure characteristics on a much smaller scale than the regular imaging resolution. Diffusion Tensor Imaging (DTI), which can resolve diffusion anisotropy and primary fiber orientation, is one of the most clinically adopted dMRI techniques. However, white matter (WM) voxels in the brain often contain crossing fibers and complex neurite structures, requiring more sophisticated dMRI techniques. With the goal of resolving multiple diffusion orientations and increasing angular resolution, multi-shell High Angular Resolution Diffusion Imaging (HARDI) samples the q-space densely on multiple spherical surfaces with radii determined by the b-values. This technique allows inferring neurite characteristics of complex fiber bundles, enabling the diagnosis of many neurodegenerative diseases. This thesis focuses on two multi-shell dMRI methods: Multi-Shell Multi-Tissue Constrained Spherical Deconvolution (MSMT-CSD), a model-free method, and Neurite Orientation Dispersion and Density Imaging (NODDI), a model-based method. These methods are used to resolve the Orientation Distribution Function (ODF) and Orientation Dispersion (OD) in the brain. However, the requirement of high number of q-space measurements, combined with the need to acquire images with reversed phase encoding (PE) directions for susceptibility artifact correction, causes prolonged acquisition times and reduces the clinical utility of multi-shell dMRI. This thesis proposes several different undersampling strategies to accelerate multi-shell dMRI, and compares their performances based on the quality of estimated dMRI metrics and ODFs. The first undersampling approach is directly applied to the q-space using Electrostatic Energy Minimization (EEM) to produce 2- or 3-shell schemes with different combinations of gradient directions per shell. The second approach uses acquisitions with reversed PE directions for a single b0 volume only. These strategies are applied to achieve acceleration rates of R=2 and R=3 on dMRI data from 20 subjects. The results suggest that each diffusion metric prefers a different undersampling strategy. For R=2 case, 3-shell strategies perform better in terms of metric fidelity and ODF accuracy. Specifically, gradient tables with a lower variance in the number of q-space points between consecutive shells are preferable. For R=3 case, 2-shell strategies perform better and the strategies containing more gradient points on the outer shell are preferable. The metric maps produced from the undersampled data contain all the necessary microstructural information and preserve diagnostic properties. These analyses will be useful in designing disease and metric-specific multi-shell dMRI gradient tables to ease clinical applications and shorten the acquisition time with minimum loss of information.
Open Access
ThermoCam: smart baby monitoring assistant
(Institute of Electrical and Electronics Engineers, 2020) Akbıyık, M. E.; Çoban, Ç. S.; Aygün, Elif; İmamoğlu, H. Z.; Gürgünoğlu, Doğa; İder, D.
Fever is one of the main symptoms of various illnesses during infancy and it requires continuous supervision especially above 38 degree Celsius as fatal complications may develop. With the emerging IoT and e-Health technologies, a variety of different consumer products are being developed to facilitate the fever monitoring for parents. In this study, our aim is to develop a prototype that will continuously track the body temperature of an infant using an RGB and a thermal camera, and provide different notification capabilities for the users. The product is expected to work effectively from 1-2 meters of distance with approximately 0.4 degree Celsius accuracy. The real-time video display is included to the system with one second of latency for video, audio and alarm features. The user interface also provides room temperature and humidity data, along with measured statistics of baby body temperature. The system is also able to alarm the user upon the detection of loud noise in the environment, which can indicate interruptions in baby's sleep. The prototype is expected to provide an affordable, all-in-one solution for the parents as a baby monitoring device.