Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 3 3-4 2016 12 30 41 48 EN Elham Shamsi Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. AND Research Center for Biomedical Technologies and Robotics, Tehran University of Medical Sciences, Tehran, Iran. Zahra Shirzhiyan Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. AND Research Center for Biomedical Technologies and Robotics, Tehran University of Medical Sciences, Tehran, Iran. Ahmadreza Keihani Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. AND Research Center for Biomedical Technologies and Robotics, Tehran University of Medical Sciences, Tehran, Iran. Morteza Farahi Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. AND Research Center for Biomedical Technologies and Robotics, Tehran University of Medical Sciences, Tehran, Iran. Amin Mahnam Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran Mohsen Reza Heydari Department of Neurology, Faculty of Medicine, Baqiyatallah University of Medical Sciences, Tehran, Iran Amir Homayoun Jafari Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. AND Research Center for Biomedical Technologies and Robotics, Tehran University of Medical Sciences, Tehran, Iran. 2017 09 04 2017 11 05 Purpose: Many of the current brain-computer interface systems rely on the patient`s ability to control voluntary eye movements. Some diseases can lead to defects in the visual system. Due to the intactness of these patients` auditory system, researchers moved towards the auditory paradigms. Attention can modulate the power of auditory steady-state response. As a result, this response is useful in an auditory brain-computer interface. As humans intrinsically enjoy listening to rhythmic sounds, this project was carried out with the aim of extraction and classification of the EEG signal patterns in response to simple and rhythmic auditory stimuli to investigate the possibility of using the rhythmic stimuli in brain-computer interface systems. Methods: Two three-membered simple and rhythmic groups of auditory sinusoidally amplitude-modulated tones were generated as the stimuli. Corresponding EEG signals were recorded and classified by means of five-fold cross-validated naïve Bayes classifier on the basis of power spectral density at message frequencies. Results: There was no significant difference between the classification performances of the responses to each group of the stimuli. All the classification accuracies, even without any noise reduction and artifact rejection, was greater than the acceptable value for being used in brain-computer interface systems (70%). Conclusion: Like the common sinusoidally amplitude-modulated tones, the novel proposed rhythmic stimuli in this project have a promising discrimination for being used in brain-computer interface systems. In addition, Power spectral density has provided an appropriate discrimination for within- and between-subject EEG classification.   https://fbt.tums.ac.ir/index.php/fbt/article/view/139 https://fbt.tums.ac.ir/index.php/fbt/article/download/139/91

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 3 3-4 2016 12 30 49 59 EN Fatemeh Sadat Fatemi Nasrollahi Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran. AND Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran Pardis Ghafarian Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran. AND PET/CT and Cyclotron Center, Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran Parham Grramifar Research Center for Nuclear Medicine, Tehran University of Medical Sciences, Tehran, Iran Mohammad Reza Ay Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran. AND Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran 2017 09 01 2017 11 18 Purpose: Respiratory-induced artifacts are dominant in Positron Emission Tomography/Computed Tomography (PET/CT) images. We investigated the impact of using the ACT data (respiration-averaged CT) in attenuation correction process. We evaluated the improvement in parameters such as maximum standardized uptake value ( ) and size in different respiratory traces for multiple lesion sizes in various locations of the thorax and abdomen. Procedures: The attenuation in PET sinograms were corrected using end inhalation CT (EICT), end exhalation CT (EECT), and average CT (ACT) respectively. It should be noted that stationary PET images (without the respiratory motion) were reconstructed, and evaluated as the stationary truth. For the phantom study, a moving phantom was built mimicking the respiratory movement. The attenuation in uncorrected PET data was corrected using the three CT images mentioned above. Results: Using EICT for attenuation correction, the respiration pattern with 35-millimeter diaphragm motion results in a %53 error in  estimation in comparison with the stationary truth for a 9-milimeter lesion in the liver. The use of ACT in attenuation correction can reduce such amount of error in  estimation up to %10 for this lesion. For the phantom study, using ACT for attenuation correction results in significant improvement in Signal to Noise Ratio (SNR) and contrast (p-value<0.05). Besides, better  was acquired for all the lesions. Conclusion: The amount of respiratory induced errors in the quantified values of both  and the volume of the tumor depends on the location of the tumor, its diameter, the amplitude of the diaphragm motion, and the CT image we use for attenuation correction. Overall, ACT shows better results in comparison with the aforementioned techniques for attenuation correction of PET data in thorax region. https://fbt.tums.ac.ir/index.php/fbt/article/view/138 https://fbt.tums.ac.ir/index.php/fbt/article/download/138/92

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 3 3-4 2016 12 30 60 69 EN Arash Zare Sadeghi Skull Base Research Center, Iran University of Medical Sciences, Tehran, Iran. AND Neuroimaging and Analysis Group (NIAG), Imaging center, Imam Khomeini hospital complex, Tehran University of Medical Sciences, Tehran, Iran Amir homayoun Jafari Medical Physics and Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran Iran Seyed AmirHosein Batouli Neuroimaging and Analysis Group, Imam Khomeini Hospital Complex, Tehran University of Medical sciences, Tehran, Iran Mohammad Ali Oghabian Neuroimaging and Analysis Group, Imam Khomeini Hospital Complex, Tehran University of Medical sciences, Tehran, Iran. AND Medical Physics and Biomedical Engineering Department, School of Medicine, Tehran University of Medical Sciences, Tehran Iran 2017 01 31 2017 11 14 Purpose: Effective connectivity is an active time-variable type of association between brain regions. The change of links’ strength in effective connectivity networks has been studied before but as far as we know, the change in the structure of the network has not yet been tested. Procedures: We simulated a time-variable data including three regions and one input to validate our method. In addition, we used a real fMRI data in order to evaluate the time-variability of brain effective connectivity between four brain regions using Dynamic Causal Modeling. The model space contained 38 models, all including the four regions of ventromedial prefrontal cortex, dor-solateral prefrontal cortex, amygdala, and ventral striatum. In both data, a proper moving window algorithm was used to find the changes over time. Results: The results of simulated data matched the simulated pattern change over time. The results of real data initially showed time-dependent changes in the strength of some of the connections between brain regions. The most valid changes happened in the input and non-linear modulatory links. The input links’ strength increased and the nonlinear links’ strength decreased exponentially. These results show that the pattern of effective connectivity network changes and so reporting a single network for the whole data acquisition period is not meaningful. Conclusion: In this study, we have used a method to find the time-dependent pattern changes during an fMRI task. We have shown the links’ strength change over time and accordingly the structure of the network changes. https://fbt.tums.ac.ir/index.php/fbt/article/view/81 https://fbt.tums.ac.ir/index.php/fbt/article/download/81/93

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 3 3-4 2016 12 30 70 79 EN Anahita Fathi Kazerooni Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Institute for Advanced Medical Technologies, Tehran, Iran Mahnaz Nabil Department of Statistics, Faculty of Mathematical Science, University of Guilan, Rasht, Iran. Elaheh Kia Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Institute for Advanced Medical Technologies, Tehran, Iran Mahrooz Malek Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran Hamidreza Saligheh Rad Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Institute for Advanced Medical Technologies, Tehran University of Medical Sciences Tehran, Iran 2017 02 27 2017 12 02 Purpose: Quantification of dynamic contrast enhanced (DCE-) MRI of ovarian masses is susceptible to errors caused by motion artifacts and intensity inhomogeneity induced by bias fields. Motion artifacts and bias fields introduce signal intensity variations in the images that must be resolved from intensity changes caused by the passage of contrast agent. Thus, registration of DCE-MRI image sequence is a challenging issue. In this work, we proposed a solution to the misregistration problem of DCE-MR images. Methods: We acquired pre-operative DCE-MR images of 16 patients diagnosed with solid or solid/cystic complex ovarian masses on ultrasound examination (with post-operative histopathological assessment showing 8 benign and 8 malignant cases). Residual complexity (RC) similarity measure was exploited in a non-rigid registration framework, to account for complex intensity variations. The performance of the proposed method was evaluated by computed semi-quantitative parameters, determined in the regions of interest (ROIs) selected on the solid portion of the tumor and the psoas muscle. The results were compared with unregistered data and registered images using mutual information (MI) similarity measure. Results: The registered data using RC similarity measure indicated lower variations in the signal intensity over the time course of contrast agent passage. The derived quantitative parameters showed enhanced separation of benign and malignant tumors using RC registration in comparison with unregistered and MI-registered data. Conclusion: RC registration is a useful tool for correcting the misalignment of DCE-MR image series in the presence of bias field artifact, while it conserves the quantitative information of the contrast enhancement. https://fbt.tums.ac.ir/index.php/fbt/article/view/94 https://fbt.tums.ac.ir/index.php/fbt/article/download/94/94

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 3 3-4 2016 12 30 80 85 EN Golsa Tabatabaei PhD in Medical Physics, Medical Physics Department, University Sains Malaysia, Malaysia Mohamad Suhaimi Jaafar PhD in Medical Physics, Medical Physics Department, University Sains Malaysia, Malaysia Wan Zaidah Abdullah - MD in Hematology, Transfusion, Thrombosis and Hemostasis and MPath in Hematology, Hematology Department, University Sains Malaysia, Malaysia 2017 05 24 2017 12 04 Background: Ultraviolet irradiation has been shown to be effective for Transfusion Associated Graft Versus Host Disease (TAGVHD) prevention. However, ionizing irradiation has not yet been replaced by ultraviolet irradiation for blood irradiation at some blood banks, since there are still questions about the safety of this technique. Materials and Methods: In this research the hematological, morphological characteristics and potassium level of the irradiated blood, irradiated with an equivalent dose of 4 J/cm2 of UVC (254nm) for 3 min, which is the minimum dose shown to be effective for TAGVHD prevention according to literature available, has been studied. The data was analyzed with SPSS software. Results: The results showed that UV irradiation does not change the blood potassium level and hence does not damage the RBC membrane. Furthermore, the hematological tests showed no significant hematological change after ultraviolet exposure. Moreover, the morphology of RBCs and PLTs after ultraviolet irradiation was normal. Conclusion: According to the results, the ultraviolet irradiation is a safe and suitable way for blood and blood component irradiation for TAGVHD prevention and other applications with an equivalent dose of up to this UV irradiation dose. https://fbt.tums.ac.ir/index.php/fbt/article/view/133 https://fbt.tums.ac.ir/index.php/fbt/article/download/133/95