Assessment of Knowledge Levels of Elementary and High School Teachers on Childhood Asthma

Conclusion: Our study will contribute to the national asthma control program. We believe that informing teachers about asthma is important in asthma control and will contribute to the guidelines for training programs

Evaluation of Radiomics to Predict the Accuracy of Markerless Motion Tracking of Lung Tumors: A Preliminary Study

Template-based matching algorithms are currently being considered for markerless motion tracking of lung tumors. These algorithms use tumor templates derived from the planning CT scan, and track the motion of the tumor on single energy fluoroscopic images obtained at the time of treatment. In cases where bone may obstruct the view of the tumor, dual energy fluoroscopy may be used to enhance soft tissue contrast. The goal of this study is to predict which tumors will have a high degree of accuracy for markerless motion tracking based on radiomic features obtained from the planning CT scan, using peak-to-sidelobe ratio (PSR) as a surrogate of tracking accuracy. In this study, CT imaging data of 8 lung cancer patients were obtained and analyzed through the open source IBEX program to generate 2,287 radiomic features. Agglomerative hierarchical clustering was used to narrow down these features into 145 clusters comprised of the highest correlation to PSR. The features among the clusters with the least inter-correlation were then chosen to limit redundancy in the data. The results of this study demonstrated a number of radiomic features that are positively correlated to PSR. The features with the highest degree of correlation included complexity, orientation and range. This approach may be used to determine patients for whom markerless motion tracking would be beneficial

Visual line tracking with vector field guidance for UAV

22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEYWOS: 000356351400141In this study, it is aimed to follow a visual route by an Unmanned Aerial Vehicle (UAV). The recognition of the predetermined line by using image processing algorithms and the process of following the route by using the method of Tangent Vector Field Guidance (TVFG) have been performed in indoor and outdoor experiments. UAV's following the correct route has been ensured by calculating the deflection caused by some factors such as wind and light which adversely affect the flight of UAV. In Vector Field Guidance method, the direction angles calculated by using the vector fields that will follow the line-shaped guide path are used. When the path to be followed has more than one direction instead of a single straight line, it is divided into sections which consist of straight lines, and by prioritizing these lines, the most dominant line is followed. In this study, it is aimed to provide a dynamic model by considering the tracking errors. As a result of the process adopted, UAV's autonomous flight is achieved by using the visual inputs and TVFG method, and the external disturbing factors are investigated.IEEE, Karadeniz Tech Univ, Dept Comp Engn & Elect & Elect Eng

İnsansız hava araçlarında görsel takip ve denetim

2015 23rd Signal Processing and Communications Applications Conference, SIU 2015 -- 16 May 2015 through 19 May 2015 -- -- 113052In this study, we perform target detection and tracking with Unmanned Aerial Vehicle (UAV) as well as the visual command of UAV. Our goal is to develop an autopilot system to reduce the human factor in UAV's. We create a system that follows different objects, stays locked to a graphical object which is glyph that has an encryption that only we describe, and executes the mission encoded on glyph in both indoor and outdoor tests. We obtain the targeting by the angle and the dimensions of the glyph. We've obtained successful results in applied presentations. © 2015 IEEE

Diagnosis of paroxysmal atrial fibrillation from thirty-minute heart rate variability data using convolutional neural networks

Paroxysmal atrial fibrillation (PAF) is the initial stage of atrial fibrillation, one of the most common arrhythmia types. PAF worsens with time and affects the patient's life quality negatively. In this study, we aimed to diagnose PAF early, so patients can start taking precautions before this disease gets worse. We used the atrial fibrillation prediction database, an open data from Physionet and constructed our approach using convolutional neural networks. Heart rate variability (HRV) features are calculated from time-domain measures, frequency-domain measures using power spectral density estimations (fast Fourier transform, Lomb-Scargle, and Welch periodogram), time-frequency-domain measures using wavelet transform, and nonlinear Poincare plot measures. We also normalized these features using min-max normalization and z-score normalization methods. In addition, we also applied alternatively the heart rate normalization (HRN), which gave promising results in a few HRV-based research, before calculating these features. Thus, HRV data, HRN data, and HRV features extracted from six different combinations of these normalizations, in addition to no normalization cases, were applied to the convolutional neural networks classifier. We tuned the classifiers using 90% of samples and tested the classifiers' performances using 10% of data. The proposed approach resulted in 95.92% accuracy, 100% precision, 91.84% recall, and 95.74% f1-score in HRV with z-score feature normalization. When the heart rate normalization was also applied, the proposed approach reached 100% accuracy, 100% precision, 100% recall, and 100% f1-score in HRV with z-score feature normalization. The proposed method with heart rate normalization and z-score normalization methods resulted in better classification performance than similar studies in the literature. In addition, although deep learning models offer no use of separate feature extraction processes, this study reveals that using HRV-specific feature extraction techniques may improve the performance of deep learning algorithms in HRV-based studies. Comparing the existing studies, we concluded that our approach provides a much better tool to diagnose PAF patients.WOS:0007097128000082-s2.0-8511711859

Impact of respiratory motion on lung dose during total marrow irradiation

We evaluated the impact of respiratory motion on the lung dose during linac-based intensity-modulated total marrow irradiation (IMTMI) using two different approaches: (1) measurement of doses within the lungs of an anthropomorphic phantom using thermoluminescent detectors (TLDs) and (2) treatment delivery measurements using ArcCHECK where gamma passing rates (GPRs) and the mean lung doses were calculated and compared with and without motion. In the first approach, respiratory motions were simulated using a programmable motion platform by using typical published peak-to-peak motion amplitudes of 5, 8, and 12 mm in the craniocaudal (CC) direction, denoted here as M1, M2, and M3, respectively, with 2 mm in both anteroposterior (AP) and lateral (LAT) directions. TLDs were placed in five selected locations in the lungs of a RANDO phantom. Average TLD measurements obtained with motion were normalized to those obtained with static phantom delivery. The mean dose ratios were 1.01 (0.98–1.03), 1.04 (1.01–1.09), and 1.08 (1.04–1.12) for respiratory motions M1, M2, and M3, respectively. To determine the impact of directional respiratory motion, we repeated the experiment with 5-, 8-, and 12-mm motion in the CC direction only. The differences in average TLD doses were less than 1% when compared with the M1, M2, and M3 motions indicating a minimal impact from CC motion on lung dose during IMTMI. In the second experimental approach, we evaluated extreme respiratory motion 15 mm excursion in only the CC direction. We placed an ArcCHECK device on a commercial motion platform and delivered the clinical IMTMI plans of five patients. We compared, with and without motion, the dose volume histograms (DVHs) and mean lung dose calculated with the ArcCHECK-3DVH tool as well as GPR with 3%, 5%, and 10% dose agreements and a 3-mm constant distance to agreement (DTA). GPR differed by 11.1 ± 2.1%, 3.8 ± 1.5%, and 0.1 ± 0.2% with dose agreement criteria of 3%, 5%, and 10%, respectively. This indicates that respiratory motion impacts dose distribution in small and isolated parts of the lungs. More importantly, the impact of respiratory motion on the mean lung dose, a critical indicator for toxicity in IMTMI, was not statistically significant (p > 0.05) based on the Student’s t-test. We conclude that most patients treated with IMTMI will have negligible dose uncertainty due to respiratory motion. This is particularly reassuring as lung toxicity is the main concern for future IMTMI dose escalation studies

Beam commissioning of the first clinical biology-guided radiotherapy system.

This study reports the beam commissioning results for the first clinical RefleXion Linac.MethodsThe X1 produces a 6 MV photon beam and the maximum clinical field size is 40 × 2 cm2 at source-to-axis distance of 85 cm. Treatment fields are collimated by a binary multileaf collimator (MLC) system with 64 leaves with width of 0.625 cm and y-jaw pairs to provide either a 1 or 2 cm opening. The mechanical alignment of the radiation source, the y-jaw, and MLC were checked with film and ion chambers. The beam parameters were characterized using a diode detector in a compact water tank. In-air lateral profiles and in-water percentage depth dose (PDD) were measured for beam modeling of the treatment planning system (TPS). The lateral profiles, PDDs, and output factors were acquired for field sizes from 1.25 × 1 to 40 × 2 cm2 field to verify the beam modeling. The rotational output variation and synchronicity were tested to check the gantry angle, couch motion, and gantry rotation.ResultsThe source misalignments were 0.049 mm in y-direction, 0.66% out-of-focus in x-direction. The divergence of the beam axis was 0.36 mm with a y-jaw twist of 0.03°. Clinical off-axis treatment fields shared a common center in y-direction were within 0.03 mm. The MLC misalignment and twist were 0.57 mm and 0.15°. For all measured fields ranging from the size from 1.25 × 1 to 40 × 2 cm2 , the mean difference between measured and TPS modeled PDD at 10 cm depth was -0.3%. The mean transverse profile difference in the field core was -0.3% ± 1.1%. The full-width half maximum (FWHM) modeling was within 0.5 mm. The measured output factors agreed with TPS within 0.8%.ConclusionsThis study summarizes our specific experience commissioning the first novel RefleXion linac, which may assist future users of this technology when implementing it into their own clinics

Treatment planning system commissioning of the first clinical biology-guided radiotherapy machine.

PurposeThe RefleXion X1 is a novel radiotherapy machine designed for image-guided radiotherapy (IGRT) and biology-guided radiotherapy (BgRT). Its treatment planning system (TPS) generates IMRT and SBRT plans for a 6MV-FFF beam delivered axially via 50 firing positions with the couch advancing every 2.1 mm. The purpose of this work is to report the TPS commissioning results for the first clinical installation of RefleXion™ X1.MethodsCT images of multiple phantoms were imported into the RefleXion TPS to evaluate the accuracy of data transfer, anatomical modeling, plan evaluation, and dose calculation. Comparisons were made between the X1, Eclipse™, and MIM™. Dosimetric parameters for open static fields were evaluated in water and heterogeneous slab phantoms. Representative clinical IMRT and SBRT cases were planned and verified with ion chamber, film, and ArcCHECK@ measurements. The agreement between TPS and measurements for various clinical plans was evaluated using Gamma analysis with a criterion of 3%/2 mm for ArcCHECK@ and film. End-to-end (E2E) testing was performed using anthropomorphic head and lung phantoms.ResultsThe average difference between the TPS-reported and known HU values was -1.4 ± 6.0 HU. For static fields, the agreements between the TPS-calculated and measured PDD10 , crossline profiles, and inline profiles (FWHM) were within 1.5%, 1.3%, and 0.5 mm, respectively. Measured output factors agreed with the TPS within 1.3%. Measured and calculated dose for static fields in heterogeneous phantoms agreed within 2.5%. The ArcCHECK@ mean absolute Gamma passing rate was 96.4% ± 3.4% for TG 119 and TG 244 plans and 97.8% ± 3.6% for the 21 clinical plans. E2E film analysis showed 0.8 mm total targeting error for isocentric and 1.1 mm for off-axis treatments.ConclusionsThe TPS commissioning results of the RefleXion X1 TPS were within the tolerances specified by AAPM TG 53, MPPG 5.a, TG 119, and TG 148. A subset of the commissioning tests has been identified as baseline data for an ongoing QA program