فهرست مطالب

  • Volume:6 Issue:1, 2019
  • تاریخ انتشار: 1397/10/11
  • تعداد عناوین: 4
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  • Sakineh Ranji, Burachaloo , Payam Sarraf , Elham Rahimian , Shirin Shakiba , Nina Javadian , Parastoo Faraji , Abbas Tafakhori Page 1
    Background
    Near one-third of epileptic cases never achieve remission, despite optimal medication use. In these patients, various surgical procedures can be helpful. However, surgical success is directly associated with the ability to localize precisely the region of seizure onset.
    Objectives
    The goal of this study was to evaluate the role of susceptibility weighted imaging (SWI) in detecting intracerebral lesions and localizing epileptogenic zones in addition to conventional MRI with routine epilepsy protocol in drug-resistant epileptic patients.
    Methods
    The study was carried out at an academic medical center in a major metropolitan city, and all participants underwent conventional MRI assessment with seizure protocol and SWI evaluation.
    Results
    During the study period, 59 cases met the criteria. Thirty-four were male (57.6%) and twenty-five were female. Mean age of participants was 30 years, and mean age at the time of epilepsy onset was 11. In 50 cases (85%), there was evidence of brain abnormalities in conventional MRI and/or SWI. Brain abnormalities were also evident in conventional MRI evaluation of 47 cases (79%). In three out of twelve cases with normal conventional MRI with routine epilepsy protocol, SWI showed brain abnormalities. In 20 cases (40%), the same lateralization or localized lesions were detected in EEG and MRI. More information from SWI was reported in 13 patients (22%). In two cases, in which EEG showed evidence of partial seizures, conventional MRI showed no abnormality while SWI showed abnormal vascular cluster. In one of these two cases, caput medusa, in agreement with developmental venous anomaly, was reported. In one case, conventional MRI was normal while SWI showed evidence of cavernoma. In another patient, in addition to the lesion detectable in conventional MRI, SWI found two other lesions in agreement with cavernomas.
    Conclusions
    Susceptibility weighted imaging can be helpful in localizing epileptogenic zones, which are not detectable by conventional MRI with routine epilepsy protocol, in patients with drug-resistant epilepsy.
    Keywords: Epilepsy, Susceptibility Weighted Imaging, Drug-Resistant, Iran
  • Asghar Rajabzadeh Page 2
    Dear Editor, Electromagnetic fields (EMFs), physical energy, are non-ionic waves with speed, frequency, wavelength, and amplitude characteristics, emitted by electrical machines and industry equipments. According to frequency, these fields are divided to low, intermediate, high, and static radiations. In previous studies, it has been claimed that EMFs (duration of exposure) have noxious outcomes on biological systems of humans and rodent, based on frequency and other properties (1, 2). Most researches have been done on EMFs and central nervous systems (CNS) with different exposures involved in vital portions (3, 4). Hippocampus formations, as the main compartment of the limbic system, are principal members of CNS at emotional, behaviors, memory, and regulating of endocrine systems, which could be one of the high sensitive portions to EMFs waves. According to previous studies, it is estimated that EMFs have remarkable effects on neurological compartments (5). A previous study by the current authors showed that 30 mT electromagnetic fields has negative impacts on rat's hippocampus (6). Increased free radicals and created oxidative stress via EMFs waves may be one of the most important reasons (7). This condition leads to promotion of cell's apoptosis pathway in the main parts of hippocampus, such as the dentate gyrus (6). The EMFs have a potential role in the starting of intrinsic and extrinsic pathways of apoptotic process. Breaking of DNA in brain's cells, chromosome abnormalities, genetic mutations, intracellular enzymes dysfunction, and altered expression level of neurotransmitters in various parts of the brain are side effects of electromagnetic fields (8, 9). Furthermore, it is assumed that EMFs have a major effect on high metabolic and proliferative organs, such as hippocampus formations. The produced free radicals in the hippocampus and similar structures can be defined as sensitive organs to EMFs (Figure 1). However, in addition to some researches on the relationship between electromagnetic fields and CNS, there is no suitable strategy to remove electrical devices in the society's life style. In this case, general global designs should be made in order to prevent abnormal births and the risk of neurological disorders
    Keywords: Electromagnetic Fields, Hippocampus, Oxidative Stress
  • Hamid A. Jalab *, Ali M. Hasan Page 3
    Context
     Medical imaging technologies are an indispensable tool in medicine today developed to satisfy the significant demand for information on medical imaging by visualizing internal organs for clinical analysis. This enables the radiologists and clinicians to accurately understand the patient’s condition and makes medical practices easier, more effective for patients, and cheaper for the healthcare system.
    Objective
    The current study aimed at presenting a comprehensive review on the recent classification and segmentation techniques of brain tumors in magnetic resonance image (MRI).
    Data Source
     Google Scholar, ScienceDirect, Web of Knowledge, Springer, and manual search of reference lists from 1990 to 2018.
    Inclusion Criteria
     The current study considered brain tumors since they are relatively less common and more important compared with other tumors due to their high morbidity rate.
    Results
    Many automated brain tumors segmentation algorithms of magnetic resonance imaging (MRI) were reviewed and discussed including their advantages and limitations to provide a clear insight into these algorithms. The review concentratedon the state-of-art methods of segmentation of MRI brain tumors since they attracted a significant attention in the recent two decades resulting in many algorithms being developed for automated, semi-automated, and interactive segmentation of brain tumors. While there is a significant development of segmentation algorithms, they are rarely used clinically due to lack of interaction between developers and clinicians.
    Conclusions
    Most studies did not consider grading of brain tumors and did not distinguish to which grade the brain tumor belonged. This enables the developers to understand how the margins of brain tumors appear in medical images.
    Limitations
     The most important limitations that make brain tumors segmentation remaina challenging task are the variety of the shape and intensity of tumors in addition to the probability of inhomogeneity of tumorous tissue.
    Keywords: Classification, Segmentation, Magnetic Resonance Imaging, Brain Tumors
  • Samira Raminfard, Hamidreza Haghighatkhah , Maysam Alimohamadi , Ali Yoonessi , Farshid Arbabi , Seyed Amir Hossein Batouli, Mohammad Oghabian * Page 4
    Background
    Detection of actual residual tumor extent after resection of gliomas is important for further treatment implications. Conventional MRI features such as T1 weighted contrast enhancement or T2 weighted hyperintensity are not strong indicators of the tumor. Therefore, it is needed to use advanced metabolic imaging such as magnetic resonance spectroscopy (MRS).
    Objectives
    This work reports the contrast between MRS defining metabolic alteration and imaging features of residual tumor after glioma resection.
    Methods
    Eighteen patients with glioma after tumor resection were included in the study. Routine MRI sequences and multi-voxel MRS were obtained. Metabolic regions of interest (ROI) were defined for Cho/NAA and Cho/Cr in different thresholds. Imaging ROI for residual tumor (ROI-t) was defined on conventional MR images. Area of each ROI, the distance between ROI centers, and dice coefficient for the evaluation of similarity between imaging and metabolic ROIs were calculated.
    Results
    Maximum similarity and minimum distance of ROI centers were determined between ROI of Cho/NAA > 1.7 and ROI-t. For Cho/Cr, the maximum similarity was determined in > 1.5.
    Conclusions
    Findings of the present study propose that MRS could be a proper detector for residual tumor after surgical treatment of glioma.
    Keywords: Glioma, MRI, Magnetic Resonance Spectroscopy (MRS), Metabolic Regions of Interest (ROI)