Intra-frame Motion Compensation in Multi-frame Brain PET Imaging

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 2 2 2015 06 30 Intra-frame Motion Compensation in Multi-frame Brain PET Imaging 60 72 EN Hassan Mohy-ud-Din Department of Electrical and Computer Engineering, Johns Hopkins University, MD, USA AND Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, MD, USA. Nicolas A-Karakatsanis Division of Nuclear Medicine, University of Geneva, Geneva, Switzerland. William Willis Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, MD, USA. Abdel K-Tahari Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, MD, USA. Dean F-Wong Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, MD, USA. Arman Rahmim Department of Electrical and Computer Engineering, Johns Hopkins University, MD, USA AND Department of Radiology and Radiological Sciences, Johns Hopkins School of Medicine, MD, USA. 2015 11 24 2015 11 24 Purpose: Inter-frame and intra-frame motion can adversely impact the performance of dynamic brain PET imaging. Only correcting the former can still result in degraded qualitative and quantitative performance. Meanwhile, patient motion introduces mismatches between transmission and emission data which may lead to incorrect attenuation and scatter compensation in the reconstruction process. As a result, the reconstructed dynamic images may carry erroneous estimates of radioactivity distribution. We seek a solution to this problem. Methods: We investigated the use of iterative deconvolution coupled with a proposed use of time-weighted averaging of motion-transformed transmission images to correct the transmission-emission mismatch artifacts in dynamic brain PET images. We performed simulations using real-patient motion profile acquired by the infrared Polaris Vicra motion tracking device which estimates 3-D motion transformations during PET acquisition. This was followed by frame-based motion correction employing three different transmission-emission alignment strategies: transmission image transformed by (1) mean motion transformation, (2) median motion transformation, and (3) the proposed time-weighted average of motion-transformed transmission images. Results-: The results demonstrate that the proposed approach of using time-weighted averaging of motion transformed transmission images outperforms conventional methods by substantially reducing the transmission-emission mismatch artifacts in the reconstructed images. Coupled with an alignment of the reconstructed frames for inter-frame motion correction and a subsequent iterative deconvolution approach for intra-frame motion correction, the resulting motion compensated images showed superior quality, considerable reduction in error norm and enhanced noise-bias performance compared to conventional methods of transmission-emission mismatch compensation. The performance was consistent across different levels of intra-frame motion, and the algorithm was amenable to different framing schemes. Conclusion: In frame-based motion correction of dynamic PET images, it is feasible to achieve intra-frame motion compensation using time-weighted averaging of motion transformed transmission images coupled with a post-reconstruction iterative deconvolution procedure to compensate for intra-frame motion. https://fbt.tums.ac.ir/index.php/fbt/article/view/46 https://fbt.tums.ac.ir/index.php/fbt/article/download/46/41

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 2 2 2015 06 30 Introducing the HeliGuide: Urea Breath Tests System for Detecting Helicobacter Pylori 115 117 EN Aram Radnia Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran. Mohammad Hossein Farahani Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran. Hoorvash C.Yousefzadeh Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran. Mohammad Reza Ay Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, IranAND Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran. 2015 11 24 2015 11 24 Purpose: In this report the design concept and experimental evaluation of the performance of HeliGuide have been illustrated. Methods: 14C-UBT system designed for detecting Helicobacter pylori. In order to assess the capability of the system, results of 221 reference cards have been analyzed. Results: Results of the HeliGuide system are matched with the reference. Conclusion: Results of the evaluation indicated that HeliGuide is adequate as a Urea Breath Test system for detecting helicobacter pylori. https://fbt.tums.ac.ir/index.php/fbt/article/view/53 https://fbt.tums.ac.ir/index.php/fbt/article/download/53/48

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 2 2 2015 06 30 Investigation on Performance Accuracy of Different Surrogates in Real Time Tumor Tracking at External Beam Radiotherapy 73 79 EN Saber Nankali Department of Electrical and Computer Engineering, Kerman Graduate University of Advanced Technology, Kerman, Iran. Ahmad Esmaili Torshabi Department of Electrical and Computer Engineering, Kerman Graduate University of Advanced Technology, Kerman, Iran. Payam Samadi-Miandoab Department of Electrical and Computer Engineering, Kerman Graduate University of Advanced Technology, Kerman, Iran. Amin Baghizadeh Department of Biotechnology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran. 2015 11 24 2015 11 24 Purpose: In external beam radiotherapy of dynamic tumors, several errors raise due to inter- and intra-fractional motions. In order to compensate these errors, signals obtained from different surrogates are used to infer with tumor motion as real time. Therefore, a comparative assessment may be worthwhile on the effect of different surrogates in tumor motion tracking. Methods: The performance accuracy of three internal-external surrogates entitled: external markers, diaphragm movement and lung volume was done using 4 Dimensional Extended Cardiac-Torso (4D-XCAT) phantoms. Adaptive Neuro Fuzzy Inference System (ANFIS) model was implemented to correlate the motion of surrogates with several tumors located in liver and lung, separately. Finally, the Root Mean Square Error (RMSE) of ANFIS model outputs in tumor motion prediction of different surrogates was compared as metric tool. Results- The average value of RMSE of lung and liver tumors were 0.4 mm, 0.6 mm and 0.8 mm for external markers, lung volume and diaphragm motion, respectively. Conclusion- Among three investigated surrogates, the best performance belonged to external markers strategy, while optimum location of these markers determined using an input selection algorithm in this method. https://fbt.tums.ac.ir/index.php/fbt/article/view/47 https://fbt.tums.ac.ir/index.php/fbt/article/download/47/42

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 2 2 2015 06 30 A Study of the Effect of Two Meaningful Syllables Stimuli in Auditory Brainstem Responses Using Correlation and Coherence Analyses 80 86 EN Amin Asgharzadeh-Alavr Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences (TUMS), Tehran, Iran AND Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran, Iran. Amir Homayoun Jafari Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences (TUMS), Tehran, Iran. Zahra Shirzhiyan Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences (TUMS), Tehran, Iran AND Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran, Iran. AmirSalar Jafarpisheh Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences (TUMS), Tehran, Iran AND Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran, Iran. Azadeh Ghalyanchi-Langeroudi Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences (TUMS), Tehran, Iran AND Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran, Iran. Akram Pourbakht Department of Audiology, School of Rehabilitation, Iran University of Medical Sciences (IUMS), Tehran, Iran. 2015 11 24 2015 11 24 Purpose: In elementary studies on brainstem evoked potentials a simple stimuli like click and sinusoidal tones is used, but in recent years Auditory Neuroscience oriented to use complex stimuli. These complex stimuli (e.g. speech and music) are more capable in representation of auditory pathway functions. Previous studies in this field, mainly attend to one single vowel or consonant-vowels. Until now no study has been done which considered the encoding of multi structurally meaning full combination of consonant-vowel. In this study, we try to extract information using suitable tools from Auditory Brainstem Responses (ABR) to stimuli ‘baba’. Methods: At the first step we used a test to find an appropriate distance between two consecutive consonant- vowels ‘ba’ which is perceived ‘baba’. For this, a psychophysical test was designed. Subjects were asked to choose a suitable distance between two ‘ba’ that the combination perceived ‘baba’. After recording evoked potentials to ‘ba’ and ‘baba’, we searched distinctive features between the signals related two stimuli. So at first, we began with comparative time-frequency analyses like correlation and coherence. Results: Correlation analyses show that the response to ‘ba’ and the response to first syllable of ‘baba’ in the Onset and also transient parts of responses are different and the response to first and second syllable of /baba/ become similar. The results of coherence analyses show that these differences could not be represented with a linear relation merely. Conclusion: Brainstem neural activity was different in countering with single syllable stimuli in comparison with meaningful disyllabic stimuli. These changes can be consequences of activities in anatomical top-down pathway. https://fbt.tums.ac.ir/index.php/fbt/article/view/48 https://fbt.tums.ac.ir/index.php/fbt/article/download/48/43

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 2 2 2015 06 30 Discrimination of Benign and Malignant Suspicious Breast Tumors Based on Semi-Quantitative DCE-MRI Parameters Employing Support Vector Machine 87 92 EN Saeedeh Navaei-Lavasani Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Tehran University of Medical Sciences, Tehran, Iran AND Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. Anahita Fathi-Kazerooni Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Tehran University of Medical Sciences, Tehran, Iran AND Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. Hamidreza Saligheh-Rad Quantitative MR Imaging and Spectroscopy Group, Research Center for Cellular and Molecular Imaging, Tehran University of Medical Sciences, Tehran, Iran AND Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. Masoumeh Gity Department of Radiology, Medical Imaging Center, Tehran University of Medical Sciences, Tehran, Iran. 2015 11 24 2015 11 24 Purpose: Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is an effective tool for detection and characterization of breast lesions. Qualitative assessment of suspicious breast DCE-MRI is problematic and operator dependent. The purpose of this study is to evaluate diagnostic efficacy of the representative characteristic parameters, extracted from kinetic curves of DCE-MRI, for discrimination between benign from malignant suspicious breast tumors. Methods: Pre-operative DCE-MR images of twenty-six histopathological approved breast lesions were analyzed. The images were reviewed by an expert radiologist and the regions of interests (ROI)s were selected on the most solid part of the lesion.Semi-quantitative kinetic parameters, namely: maximum signal enhancement (SI), max 60 initial area under the curve (IAUC), time to peak (TTP), wash in rate (WIR), wash out rate (WOR) and signal enhancement ratio (SER), were calculated within each ROI. Mean values of the calculated features among benign and malignant groups were compared using student’s t-test. Finally, a classification was performed employing support vector machines (SVM) using each of the parameters and their combinations in order to investigate the efficacy of the parameters in distinguishing between benign from malignant tumors. Results: The performance of the classification procedure employing the combination of semi-quantitative features with (p-value< 0.001) was evaluated by means of several measures, including accuracy, sensitivity, specificity, positive predictive value and negative predictive value which returned amounts of 97.5%, 96.49%,100%, 100% and 95.61% respectively. Conclusion: In conclusion, semi-quantitative analysis of the characteristic kinetic curves of suspicious breast lesions derived from SVM classifier provides an effective lesion classification in breast DCE-MR images. https://fbt.tums.ac.ir/index.php/fbt/article/view/49 https://fbt.tums.ac.ir/index.php/fbt/article/download/49/49

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 2 2 2015 06 30 2D and 3D Optical Flow Based Interpolation of the 4DCT ImageSequences in the External Beam Radiotherapy 93 102 EN Payam Samadi-Miyandoab Department of Electrical and Computer Engineering, Kerman Graduate University of Advanced Technology, Kerman, Iran AhmadEsmaili Torshabi Department of Electrical and Computer Engineering, Kerman Graduate University of Advanced Technology, Kerman, Iran Saber Nankali Department of Electrical and Computer Engineering, Kerman Graduate University of Advanced Technology, Kerman, Iran 2015 11 24 2015 11 24 Purpose: Although in the external beam radiotherapy tumor motionis a crucial and challenging issue due to respiration motion, temporal changes in anatomy during imaging cause considerable problems. Moreover, the Four Dimensional Computed Tomography (4DCT) imaging has been proposed to track these changes at the different breathing phases. Also at real time tumor tracking, the accuracy of motion tracking models that are necessary can be increased by constructing virtual images due to obtaining additional motion data. Methods: In this study, the 4DCT data set of five real patients who have had lung cancer were provided by DIR-lab site in addition to deformable image registration algorithms presented in MATLAB software and DIRART software respectively to calculate 2D and 3D vector felids between two respiratory volumes. Moreover, the 2D and 3D displacement vector were calculated by optical flow based on Horn-Schunck method, these vector fields were used to generate an interpolated image at the desired time by 2D and 3D interpolation methods. Although 2D interpolation methods included nearest, cubic, linear, and B-spline, the 3D interpolation method was based on the 3D spatial interpolation. In this study, the reconstructed image action of cABR signal is a valid approach for generating important features of cABR and a remarkable evidence of these signals can be represented by some spatial rules. https://fbt.tums.ac.ir/index.php/fbt/article/view/10 https://fbt.tums.ac.ir/index.php/fbt/article/download/10/9

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 1 3 2014 09 30 Automatic Segmentation of Three Dimensional Brain Magnetic Resonance Images Using Both Local and Non-Local Neighbors with Considering Inner and Outer Class Data Distances 211 221 EN Omid Jamshidi Medical Intelligence Laboratory, Computer Engineering Department, Bu Ali Sina University, Hamedan, Iran. Abdol Hamid Pilevar Medical Intelligence Laboratory, Computer Engineering Department, Bu Ali Sina University, Hamedan, Iran. 2015 10 13 2015 10 13 In this article a new combined method from genetic and fuzzy c-means algorithm (FCM) for discovering the correct number of segments and automatic segmentation of human normal and abnormal brain MR images is proposed. For reducing the effect of the noise in segmentation process, we use the local and non-local neighbors, and also a new method for finding the appropriate neighbors of the voxels and adjusting their weights. In addition, by decreasing the distance between the data and data cluster centers, the distances between the data from other cluster centers are increased and caused a better and more precise detection of segments boundaries. The proposed method was applied to 10 clinical MRI data set images. Our experimental results shows that the presented method has a significant improvement compare to other similar methods. https://fbt.tums.ac.ir/index.php/fbt/article/view/11 https://fbt.tums.ac.ir/index.php/fbt/article/download/11/10

Tehran University of Medical Sciences Frontiers in Biomedical Technologies 2345-5837 1 3 2014 09 30 Experimental Evaluation of the Performance of HiReSPECT Scanner: a High-Resolution SPECT System for Small Animal Imaging 222 227 EN Ali Mahmoud Pashazadeh Persian Gulf Nuclear Medicine Research Center, Bushehr University of Medical Sciences, Bushehr, Iran. Kaveh Tanha Persian Gulf Nuclear Medicine Research Center, Bushehr University of Medical Sciences, Bushehr, Iran. Forough Jafarian-Dehkordi Persian Gulf Nuclear Medicine Research Center, Bushehr University of Medical Sciences, Bushehr, Iran. Majid Assadi Persian Gulf Nuclear Medicine Research Center, Bushehr University of Medical Sciences, Bushehr, Iran. Vahideh Moji Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran. Navid Zeraatkar Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran. Mohammad Reza Ay Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran AND Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran. 2015 10 13 2015 10 13 Purpose: In this report, the preliminary results of the experimental evaluation of the Performance of HiReSPECT scanner have been illustrated. Methods: In order to assess the capability of the scanner in both planar and tomographic modes, three rats were injected with 99mTc, 99mTc-DMSA, and 99mTc-MDP for thyroid scan, kidney scan and bone scan respectively in order to perform planar imaging. In addition, two rats were injected with 99mTc-MIBI and 99mTc-DMSA to perform cardiac and kidney tomographic imaging, respectively. Results: Tomographic and planar scans of the rat organs showed that radioactive distribution in cardiac, kidney, bone and thyroid images exhibited detailed physiologic information of the imaged organs. Due to high resolution performance of the scanner, thyroid lobes are well depicted and distinguished from each other. Conclusion: Results of the evaluation of the planar and tomographic images indicated that HiReSPECT has appropriate imaging capability as an imaging system in biomedical research. https://fbt.tums.ac.ir/index.php/fbt/article/view/13 https://fbt.tums.ac.ir/index.php/fbt/article/download/13/12