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Using of Laplacian Re-decomposition image fusion algorithm for glioma grading with SWI, ADC, and FLAIR images

Khorasani Amir, Tavakoli Mohamad Bagher, Saboori Masih

Polish Journal of Medical Physics and Engineering

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2021

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Vol. 27, Iss. 4

261--269

EN

Introduction: Based on the tumor’s growth potential and aggressiveness, glioma is most often classified into low or high-grade groups. Traditionally, tissue sampling is used to determine the glioma grade. The aim of this study is to evaluate the efficiency of the Laplacian Re-decomposition (LRD) medical image fusion algorithm for glioma grading by advanced magnetic resonance imaging (MRI) images and introduce the best image combination for glioma grading. Material and methods: Sixty-one patients (17 low-grade and 44 high-grade) underwent Susceptibility-weighted image (SWI), apparent diffusion coefficient (ADC) map, and Fluid attenuated inversion recovery (FLAIR) MRI imaging. To fuse different MRI image, LRD medical image fusion algorithm was used. To evaluate the effectiveness of LRD in the classification of glioma grade, we compared the parameters of the receiver operating characteristic curve (ROC). Results: The average Relative Signal Contrast (RSC) of SWI and ADC maps in high-grade glioma are significantly lower than RSCs in low-grade glioma. No significant difference was detected between low and high-grade glioma on FLAIR images. In our study, the area under the curve (AUC) for low and high-grade glioma differentiation on SWI and ADC maps were calculated at 0.871 and 0.833, respectively. Conclusions: By fusing SWI and ADC map with LRD medical image fusion algorithm, we can increase AUC for low and high-grade glioma separation to 0.978. Our work has led us to conclude that, by fusing SWI and ADC map with LRD medical image fusion algorithm, we reach the highest diagnostic accuracy for low and high-grade glioma differentiation and we can use LRD medical fusion algorithm for glioma grading.

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A numerical study on the effect of conductivity change in cell kill distribution in irreversible electroporation

Khorasani Amir

Polish Journal of Medical Physics and Engineering

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2020

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Vol. 26, Iss. 2

69--76

EN

Introduction: irreversible electroporation (IRE) is a tissue ablation technique and physical process used to kill the undesirable cells. In the IRE process by mathematical modelling we can calculate the cell kill probability and distribution inside the tissue. The purpose of the study is to determine the influence of electric conductivity change in the IRE process into the cell kill probability and distribution. Methods: cell death probability and electric conductivity were calculated with COMSOL Multiphysics software package. 8 pulses with a frequency of 1 Hz, pulse width of 100 μs and electric field intensity from 1000 to 3000 V/Cm with steps of 500 V/Cm used as electric pulses. Results: significantly, the electrical conductivity of tissue will increase during the time of pulse delivery. According to our results, electrical conductivity increased with an electric field intensity of pulses. By considering the effect of conductivity change on cell kill probability, the cell kill probability and distribution will change. Conclusion: we believe that considering the impact of electric conductivity change on the cell kill probability will improve the accuracy of treatment outcome in the clinic for treatment with IRE.

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Conductivity change with needle electrode during high frequency irreversible electroporation: a finite element study

Khorasani Amir, Firoozabadi Seyed Mohammad, Shankayi Zeinab

Polish Journal of Medical Physics and Engineering

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2019

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Vol. 25, Iss. 4

237--242

EN

Irreversible electroporation (IRE) is a process in which the cell membrane is damaged and leads to cell death. IRE has been used as a minimally invasive ablation tool. This process is affected by some factors. The most important factor is the electric field distribution inside the tissue. The electric field distribution depends on the electric pulse parameters and tissue properties, such as the electrical conductivity of tissue. The present study focuses on evaluating the tissue conductivity change due to high-frequency and low-voltage (HFLV) as well as low-frequency and high-voltage (LFHV) pulses during irreversible electroporation. We were used finite element analysis software, COMSOL Multiphysics 5.0, to calculate the conductivity change of the liver tissue. The HFLV pulses in this study involved 4000 bipolar and monopolar pulses with a frequency of 5 kHz, pulse width of 100 µs, and electric field intensity from 100 to 300 V/cm. On the other hand, the LFHV pulses, which we were used, included 8 bipolar and monopolar pulses with a frequency of 1 Hz, the pulse width of 2 ms and electric field intensity of 2500 V/cm. The results demonstrate that the conductivity change for LFHV pulses due to the greater electric field intensity was higher than for HFLV pulses. The most significant conclusion is the HFLV pulses can change tissue conductivity only in the vicinity of the tip of electrodes. While LFHV pulses change the electrical conductivity significantly in the tissue of between electrodes.

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A literature review on multimodality molecular imaging nanoprobes for cancer detection

Shahbazi-Gahrouei Daryoush, Moradi Khaniabadi Pegah, Shahbazi-Gahrouei Saghar, Khorasani Amir, Mahmoudi Farshid

Polish Journal of Medical Physics and Engineering

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2019

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Vol. 25, Iss. 2

57--68

EN

Molecular imaging techniques using nanoparticles have significant potential to be widely used for the detection of various types of cancers. Nowadays, there has been an increased focus on developing novel nanoprobes as molecular imaging contrast enhancement agents in nanobiomedicine. The purpose of this review article is to summarize the use of a variety of nanoprobes and their current achievements in accurate cancer imaging and effective treatment. Nanoprobes are rapidly becoming potential tools for cancer diagnosis by using novel molecular imaging modalities such as Ultrasound (US) imaging, Computerized Tomography (CT), Single Photon Emission Tomography (SPECT) and Positron Emission Tomography (PET), Magnetic Resonance Imaging (MRI), and Optical Imaging. These imaging modalities may facilitate earlier and more accurate diagnosis and staging the most of cancers.