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5. Evaluation of Thermal Properties of Ferromagnetic Core for Treatment of Solid Tumors by Electromagnetic Induction Hyperthermia.

Author

Mohagheghpour, Elham, Sheibani, Shahab, Saber, Reza, Soliemanpoor, Mohammad, Sarkar, Saeed, and Nezamdust, Amirhossein

Subjects
ELECTROMAGNETIC induction, VACUUM arcs, THERMAL properties, ENERGY dispersive X-ray spectroscopy, FEVER, TUMOR treatment
Abstract

Background: Electromagnetic induction hyperthermia is a promising method to treat the deep-seated tumors such as brain and prostatic tumors. This technique is performed using the induction of electromagnetic waves in the ferromagnetic cores implanted at the solid tumor. Objective: This study aims at determining the conditions of the optimal thermal distribution in the different frequencies before performing the in vitro cellular study. Material and Methods: In this experimental study, the i-Cu alloy (70.4-29.6; wt%) was prepared and characterized and then the parameters, affecting the amount of induction heating in the ferromagnetic core, were investigated. Self-regulating cores in 1, 3, 6, and 9 arrangements in the water phantom with a volume of 2 cm3 were used as a replacement for solid tumor. Results: Inductively Coupled Plasma (ICP) analysis and Energy Dispersive X-ray Spectroscopy (EDS) show the uniformity of the alloy after 4 times remeling by vacuum arc remelting furnace. The Vibrating Sample Magnetometer (VSM) shows that the Curie temperature (TC) of the ferromagnetic core is less than 50 °C. Temperature profile with a frequency of 100-400 kHz for 30 min, was extracted by infrared imaging camera, indicating the increase temperature in the range of 42 °C to 46 °C. Conclusion: The optimum conditions with used hyperthermia system are supplied in the frequency of 100 kHz, 200 kHz and 400 kHz with 6, 3 and 1 seeds, respectively. It is also possible to induce a temperature up to 50 °C by increasing the number of seeds at a constant frequency and power, or by increasing the applied frequency at a constant number of seeds. [ABSTRACT FROM AUTHOR]

Published
2023
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6. The Sina Robotic Telesurgery System

Author

Mirbagheri, Alireza, primary, Farahmand, Farzam, additional, Sarkar, Saeed, additional, Alamdar, Alireza, additional, Moradi, Mehdi, additional, and Afshari, Elnaz, additional

Published
2020
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7. List of Contributors

Author

Abbott, Jake J., primary, Abedin-Nasab, Mohammad H., additional, Abiri, Ahmad, additional, Afshari, Elnaz, additional, Alamdar, Alireza, additional, Alazmani, Ali, additional, Anderson, Oliver, additional, Andres, Axel, additional, Antico, Maria, additional, Arulampalam, Tan, additional, Azizian, Mahdi, additional, Bergeles, Christos, additional, Bergman, Per, additional, Bisley, James, additional, Blacker, Steven J., additional, Boni, Andrea, additional, Buchs, Nicolas Christian, additional, Cengiz, Turgut Bora, additional, Chan, Danny Tat-Ming, additional, Chiu, Philip Wai Yan, additional, Choi, Hyouk Ryeol, additional, Chudy, Darko, additional, Cochetti, Giovanni, additional, Crawford, Ross, additional, Cross, William, additional, Culmer, Peter, additional, Daimios, Simon, additional, De Mathelin, Michel, additional, De Momi, Elena, additional, De Vermandois, Jacopo Adolfo Rossi, additional, Dlaka, Domagoj, additional, Dooley, John R., additional, Drobilo, Luka, additional, Dutson, Erik, additional, Erchinger, Thomas, additional, Fan, Zhencheng, additional, Fanson, Richard, additional, Farahmand, Farzam, additional, Faraji-Dana, Zahra, additional, Faridpooya, Koorosh, additional, Fernando, Anthony, additional, Fontanarosa, Davide, additional, Gan, Chee Wee, additional, Garayt, Mathieu, additional, Gaudio, Gianluca, additional, Gorgun, Emre, additional, Gould, Jon C., additional, Groenhuis, Vincent, additional, Grundfest, Warren, additional, Guo, Ziyan, additional, Gupta, Anjuli M., additional, Hagen, Monika, additional, Higgins, Rana M., additional, Hladio, Andre, additional, Hobeika, Joe, additional, Iordachita, Iulian, additional, Jaiprakash, Anjali, additional, Jaramaz, Branislav, additional, Jayne, David, additional, Jerbić, Bojan, additional, Jinnah, Alexander H., additional, Jinnah, Riyaz H., additional, Johnson, Kelly R., additional, Jonmohamadi, Yaqub, additional, Juo, Yen-Yi, additional, Kajtazi, Marin, additional, Kang, Jin U., additional, Keggi, John M., additional, Khalaji, Iman, additional, Kilby, Warren, additional, Kim, Uikyum, additional, Kim, Yong Bum, additional, Konan, Sujith, additional, Kottenstette, Nicholas, additional, Kwok, Ka-Wai, additional, Lau, Ka Chun, additional, Lawrence, Jeffrey M., additional, Leong, Martin Chun-Wing, additional, Leung, Michael K.K., additional, Leung, Yun Yee, additional, Li, Changsheng, additional, Liang, Wenyu, additional, Liao, Hongen, additional, Liao, Zhuxiu, additional, Lim, Chwee Ming, additional, Lim, Hsueh Yee, additional, Liu, May, additional, Ma, Longfei, additional, Maden, Carla, additional, Maggitti, Michael J., additional, Mariampillai, Adrian L.D., additional, Mattos, Leonardo S., additional, Maurer, Calvin R., additional, Mearini, Ettore, additional, Milas, Jamie, additional, Mirbagheri, Alireza, additional, Mitra, Riddhit, additional, Moccia, Sara, additional, Moradi, Mehdi, additional, Morel, Philippe, additional, Moustris, George, additional, Muir, Jeffrey, additional, Mushtaq, Faisal, additional, Nageotte, Florent, additional, Nasseri, M. Ali, additional, Nathan, Mohan, additional, Naylor, Michael, additional, Ndubizu, Gordian U., additional, Ng, Cailin, additional, Oh, Daniel, additional, Ohmura, Yasushi, additional, Oriot, Elena, additional, Pandey, Ajay K., additional, Pappas, Theodore, additional, Peloso, Andrea, additional, Pensa, Jake, additional, Penza, Veronica, additional, Plaskos, Christopher, additional, Poon, Wai-Sang, additional, Protyniak, Bogdan, additional, Qiu, Liang, additional, Razjigaev, Andrew, additional, Ren, Hongliang, additional, Riviere, Cameron N., additional, Roberts, Jonathan, additional, Russo, Sheila, additional, Saber, Omid, additional, Saeedi-Hosseiny, Marzieh S., additional, Saragaglia, Dominique, additional, Sarkar, Saeed, additional, Sasazawa, Fumio, additional, Sayeh, Sohail, additional, Šekoranja, Bojan, additional, Sellers, William J., additional, Seok, Dong-Yeop, additional, Shalhoub, Sami, additional, Siepel, Françoise J., additional, Sokhanvar, Saeed, additional, Sorger, Jonathan, additional, Standish, Beau A., additional, Steele, Scott R., additional, Stiperski, Ivan, additional, Stramigioli, Stefano, additional, Strydom, Mario, additional, Su, Hao, additional, Šuligoj, Filip, additional, Sun, Songping, additional, Švaco, Marko, additional, Sznitman, Raphael, additional, Takahashi, Masahiro, additional, Tan, Kok Kiong, additional, Tao, Anna, additional, Todorov, Alex, additional, Toso, Christian, additional, Turco, Morena, additional, Turković, Marija, additional, Tzafestas, Costas, additional, Vander Poorten, Emmanuel, additional, Vidaković, Josip, additional, Vitez, Nikola, additional, Volpin, Andrea, additional, Wu, Liao, additional, Yam, Yeung, additional, Yang, Victor X.D., additional, Zanne, Philippe, additional, Žgaljić, Adrian, additional, Zhang, Xinran, additional, Zorn, Lucile, additional, and Župančić, Ivan, additional

Published
2020
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13. A study of interdetector scattering and enhancement of detector performance in a positron emission tomography system

Author

Sarkar, Saeed

Subjects
539.7, Atomic physics & molecular physics
Abstract

The mini-PET system employed in this study incorporates two blocks of BOO detector crystals. Each detector module contains a 25 x 54 mm block of BOO which is segmented into a 6 x 8 array of crystal elements, 3.5 mm ( transaxially ) by 6.25 mm ( axially ) and 30 mm ( deep ). The crystals are coupled to two Hamamatsu R1548 dual photomultiplier tubes ( PMTs ). The segmented BOO detector block is currently being employed in a number of the commercially available positron tomographs. While the above mentioned block detector has significant advantages over discrete detectors, better energy resolution, sensitivity and axial resolution, it also has disadvantages such as: inter-detector scattering, and variations in sensitivity and energy and spatial resolution across the face of the detector block. In this study the variation in the efficiency, energy resolution, position of the full energy photopeaks, spatial resolution and the amount of inter-crystal scatter fraction for the individual detector crystals across the face of the detector block were investigated. The factors contributing to these variations were identified and suggestions for reducing their effects were made. For example, the inter-detector scattering and the light sharing scheme, employed in the detector block for the identification of the crystal of interaction, were found to be the cause of mispositioning the events. Two novel techniques which showed several advantages over the techniques, employed by other groups, for evaluating the amount and distribution of inter-crystal scattered events were also established. The amount of inter-crystal scatter fraction for one of the central detector crystals, utilising both of the above mentioned techniques, was obtained and found to be almost 36%. The spatial distribution of such scattered events had a FWHM of 1.4 mm which its convolution with the so called ideal LSF of the crystal deteriorated its FWHM by 0.5 mm. It was shown that the energy distribution of the majority of the inter-detector scattering events was around the 511 ke V peak and these scattering events were detected within the full energy photopeak of the true events. Hence it is not possible to reject or discard these events by means of setting a higher energy threshold. This fact, in conjunction with the contribution of these events in worsening the spatial resolution of the PET systems utilizing crystals of small dimensions, demands special consideration to be given to the problem of inter-crystal scattering when further reducing the size of the crystals. Therefore, it is recommended that prior to incorporating detector blocks, which are cut into crystals of small dimensions, in PET systems, the amount and the distribution of the scattered events and their contribution in deteriorating the spatial resolution should be investigated by employing the techniques established in this work.

Published
1994

29. A linogram/sinogram cross-correlation method for motion correction in planar and SPECT imaging

Author

Sarkar, Saeed, Oghabian, Mohammad A., Mohammadi, Iraj, Mohammadpour, Alireza, and Rahmim, Arman

Subjects
Motion detectors -- Research, SPECT imaging -- Research, Correlation (Statistics) -- Research, Business, Electronics, Electronics and electrical industries
Abstract

In this work, a correlation function based on linograms and sinograms of the projection data was introduced, implemented and evaluated in order to estimate and compensate for the patient motion. Parabolic fitting of the peak of the correlation function was utilized to improve in the motion-estimation task. In dynamic planar imaging, the method checked for motion via its separate frames similar to the SPECT work; on the other hand, in static planar imaging, the data acquisition protocol was first exchanged from static to the dynamic modality, followed by application of the motion-correction scheme, and a final combination via summation of the motion-compensated frames. The method was successfully evaluated in many cases. Our tests showed that in SPECT imaging, the time of motion starting in a specific projection and the duration of motion are very important in the motion detection process. Measuring relative error showed that the error in the images with presence of motion along the axis of patient bed was 21.1%, being reduced to 1.4% while the 24.4% error along the perpendicular axis to the patient bed was reduced to 1.5 % with the inclusion of our motion correction scheme. Experimental results in planar imaging also demonstrated the ability of this method to reduce error in the maximum count from 40.7% to 9.7%, wherein intended sudden motion was introduced in static planar acquisition. Similarly, the error produced by gradual simulated motion was reduced from 37% to 1.6%. This method was clinically examined in the bone scan (static planar data) of an old man for an Osteomyefitis study, as well as in a kidney washout study (dynamic planar data) for a child. As a result, the motion artifacts shown in the images were reduced considerably. Index Terms--Cross correlation, linogram, motion correction, planar, sinogram, SPECT.

Published
2007

36. Development and Evaluation of Image Reconstruction Algorithms for a Novel Desktop SPECT System

Author

Zeraatkar, Navid, Rahmim, Arman, Sarkar, Saeed, and Ay, Mohammad Reza

Subjects
lcsh:Medical physics. Medical radiology. Nuclear medicine, OSEM, lcsh:Biology (General), PERSPECT, lcsh:R895-920, Image reconstruction, MLEM, Original Article, lcsh:QH301-705.5, ART
Abstract

Objective (s): Various iterative reconstruction algorithms in nuclear medicine have been introduced in the last three decades. For each new imaging system, it is wise to select appropriate image reconstruction algorithms and evaluate their performance. In this study, three approaches of image reconstruction were developed for a novel desktop open-gantry SPECT system, PERSPECT, to assess their performance in terms of the quality of the resultant reconstructed images. Methods: In the present work, a proposed image reconstruction algorithm for the PERSPECT, referred to as quasi-simultaneous multiplicative algebraic reconstruction technique (qSMART), together with two popular image reconstruction methods, maximum-likelihood expectation-maximization (MLEM) and ordered-subsets EM (OSEM), were implemented and compared. Analytic and Monte Carlo simulations were applied for data acquisition of various phantoms including a micro-Derenzo phantom. All acquired data were reconstructed by the three algorithms using different number of iterations (1-40 ). A thorough set of figures-of-merit was utilized to quantitatively compare the generated images. Results: OSEM depicted reconstructed images of higher (or matching) quality in comparison to qSMART. MLEM also reached nearly similar quality as OSEM but at higher number of iterations. The graph of data discrepancy revealed that the ranking of the three approaches in terms of convergence speed is as qSMART, OSEM, and MLEM. Furthermore, bias-versus-noise curves indicated that optimal bias-noise results were achieved using OSEM. Conclusion: The results showed that although qSMART can be applied for image reconstruction if being halted in the early iterations (up to 5), the best achievable quality of images is obtained using the OSEM.

Published
2017

47. PEGylated superparamagnetic iron oxide nanoparticles labeled with 68Ga as a PET/MRI contrast agent: a biodistribution study

Author

Lahooti, Afsaneh, primary, Sarkar, Saeed, additional, Saligheh Rad, Hamidreza, additional, Gholami, Amir, additional, Nosrati, Sahar, additional, Muller, Robert N., additional, Laurent, Sophie, additional, Grüttner, Cordula, additional, Geramifar, Parham, additional, Yousefnia, Hassan, additional, Mazidi, Mohammad, additional, and Shanehsazzadeh, Saeed, additional

Published
2016
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48. A novel approach to automatic position calibration for pixelated crystals in gamma imaging.

Author

Sajedi, Salar, Zeraatkar, Navid, Kaviani, Sanaz, Khanmohammadi, Hadi, Sarkar, Saeed, Sabet, Hamid, and Ay, Mohammad Reza

Subjects
CRYSTALS, SINGLE crystals, CALIBRATION
Abstract

Introduction: The position estimation in gamma detection system will have constant misplacements which can be corrected in the calibration procedure. In the pixelated crystal uniformly irradiation of detector will produce irregular shape due to position estimation errors. This image is called flood field image and is used to calibrate the position estimation. In this work we present a novel approach to automatically calibrate pixelated crystal array position estimation. Methods: In the flood image of a pixelated crystal array the local peaks represent the estimation of position for the gamma photons that interacted in a single crystal pixel. First, the method detects 2-D peak locations automatically in the case of blurred pixel responses in the presence of noise and disturbance of the image. The algorithm consists of a filtering step for smoothing the image followed by two rounds of local peak detection. After localizing image peaks, the correction routine will map the image locations to the crystal pixels using the thin-plate spline interpolation method. Results: The algorithm is tested for two flood images obtained from developed detector with different irregularity levels. By configuring constant parameters according to the detector configuration the method detected all crystal pixels in the image and map them correctly. The method further has been tested for10 identical blocks and the result showed automatic peak detection routine for all the blocks. Conclusion: An automatic peak detection is presented to work instead of time consuming manual calibration routines. The method shows robust performance in the presence of image noise. [ABSTRACT FROM AUTHOR]

Published
2019

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