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Mohammadi MR, Badrfam R, Zandifar A, Ahmadi N, Khaleghi A, Hooshyari Z, Alavi SS, Ahmadi A, Yousefi F, Jaberghaderi N, Nader-Mohammadi Moghadam M, Mohamadian F, Nazaribadie M, Sajedi Z, Farshidfar Z, Kaviani N, Davasazirani R, Jamshidzehi Shahbakhsh A, Roshandel Rad M, Shahbazi K, Rostami Khodaverdiloo R, Noohi Tehrani L, Nasiri M, Naderi F, Kiani A, Chegeni M, Hashemi Nasab SM, Ghaneian M, Parsamehr H, Nilforoshan N, Salmanian M, Zarafshan H. Social Capital of Parents of Children and Adolescents and Its Relation to Psychiatric Disorders; A Population-Based Study. Community Ment Health J 2022; 58:1157-1167. [PMID: 35031903 DOI: 10.1007/s10597-021-00926-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 11/27/2021] [Indexed: 11/29/2022]
Abstract
Social capital is a complex concept that is considered an effective factor in the development of societies. Considering the importance of burdens of psychiatric disorders in Iran, we studied the relationship between various dimensions of social capital of parents of children and adolescents and psychiatric disorders among them. In this cross-sectional study, 18,940 parents of children and adolescents aged 6 to 18 years old were randomly selected from all provinces of Iran and were evaluated by the Millon clinical multiaxial inventory-III (MCMI-III) and a modified version of Nahapiet and Ghoshal questionnaire. MCMI-III was designed as a self-report tool for investigating psychiatric clinical disorders and personality traits in the general population. Modified Nahapiet and ghoshal questionnaire has 20 items and measures four components of social capital included trust, values, communication, and collaboration. Validity and reliability of both questionnaires have been approved in Iran. In the regression model, the relationship between social capital components and clinical and sever clinical syndromes, in the form of regression weight and standard weight for trust was - 0.558 and - 0.062 with p value less than 0.0001, and for values was - 0.466 and - 0.057, respectively, with p value less than 0.0001. There was a reverse correlation between social capital components of parents of children and adolescents and psychiatric disorders in Iran. In regression statistical models, the two components of values and trust were negative predictors of psychiatric disorders. Considering the high prevalence of psychiatric disorders in Iran, it seems that the strengthening of cognitive and structural aspects of social capital of parents of children and adolescents is one of the effective factors in reducing the prevalence of these disorders among them.
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Affiliation(s)
- Mohammad Reza Mohammadi
- Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Rahim Badrfam
- Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran.
| | - Atefeh Zandifar
- Social Determinants of Health Research Center, Alborz University of Medical Sciences, Karaj, Iran
| | - Nastaran Ahmadi
- Yazd Cardiovascular Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Ali Khaleghi
- Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Zahra Hooshyari
- Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyyed Salman Alavi
- Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Ameneh Ahmadi
- Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Fayegh Yousefi
- Department of Psychiatry, Medical Faculty, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Nasrin Jaberghaderi
- Department of Clinical Psychology, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | | | - Fathola Mohamadian
- Department of Psychology, Psychosocial Injuries Research Center, Ilam University of Medical Sciences, Ilam, Iran
| | - Marzieh Nazaribadie
- Research Center for Behavioral Disorders and Substance Abuse, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Zahra Sajedi
- Faculty of Psychology and Educational Sciences, University of Semnan, Semnan, Iran
| | - Zahra Farshidfar
- Graduate Student in Health Psychology, Gorgan Islamic Azad University, Gorgan, Iran
| | - Nahid Kaviani
- Health Deputy, Kerman University of Medical Sciences, Kerman, Iran
| | - Reza Davasazirani
- Community Mental Health and Addiction Health Department of Khuzestan Province, Ahvaz Jundishapur University of Medical Sciences (AJUMS), Ahvaz, Iran
| | | | | | | | | | | | - Mahdie Nasiri
- Clinical Psychology, University of Alzahra, Tehran, Iran
| | - Fateme Naderi
- Medical Sciences, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Arezou Kiani
- Urmia University of Medical Sciences, Urmia, Iran
| | - Mahboobeh Chegeni
- Department of Psychology, Arak University of Medical Sciences, Arak, Iran
| | | | - Mahnaz Ghaneian
- Department of Psychology, Najaf Abad Branch, Islamic Azad University, Najaf Abad, Iran
| | - Hosien Parsamehr
- Imam Reza Psychiatric Hospital, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Neda Nilforoshan
- Department of Psychology, Islamic Azad University, Yazd Branch, Yazd, Iran
| | - Maryam Salmanian
- Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Hadi Zarafshan
- Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
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Momeni F, Abedi-Firouzjah R, Farshidfar Z, Taleinezhad N, Ansari L, Razmkon A, Banaei A, Mehdizadeh A. Differentiating Between Low- and High-grade Glioma Tumors Measuring Apparent Diffusion Coefficient Values in Various Regions of the Brain. Oman Med J 2021; 36:e251. [PMID: 33936779 PMCID: PMC8077446 DOI: 10.5001/omj.2021.59] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 08/31/2020] [Indexed: 11/03/2022] Open
Abstract
Objectives Our study aimed to apply the apparent diffusion coefficient (ADC) values to quantify the differences between low- and high-grade glioma tumors. Methods We conducted a multicenter, retrospective study between September to December 2019. Magnetic resonance imaging (MRI) diffusion-weighted images (DWIs), and the pathologic findings of 56 patients with glioma tumors (low grade = 28 and high grade = 28) were assessed to measure the ADC values in the tumor center, tumor edema, boundary area between tumor with normal tissue, and inside the healthy hemisphere. These values were compared between the two groups, and cut-off values were calculated using the receiver operating characteristic curve. Results We saw significant differences between the mean ADC values measured in the tumor center and edema between high- and low-grade tumors (p< 0.005). The ADC values in the boundary area between tumors with normal tissue and inside healthy hemisphere did not significantly differ in the groups. The ADC values at tumor center and edema were higher than 1.12 × 10-3 mm2/s (sensitivity = 100% and specificity = 96.0%) and 1.15 × 10-3 mm2/s (sensitivity = 75.0% and specificity = 64.0%), respectively, could be classified as low-grade tumors. Conclusions The ADC values from the MRI DWIs in the tumor center and edema could be used as an appropriate method for investigating the differences between low- and high-grade glioma tumors. The ADC values in the boundary area and healthy tissues had no diagnostic values in grading the glioma tumors.
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Affiliation(s)
- Farideh Momeni
- Medical Physics and Biomedical Engineering Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.,Research Center for Neuromodulation and Pain, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Razzagh Abedi-Firouzjah
- Department of Medical Physics, Radiobiology and Radiation Protection, Babol University of Medical Sciences, Babol, Iran
| | - Zahra Farshidfar
- Radiology Technology Department, School of Paramedicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Nastaran Taleinezhad
- Medical Physics and Biomedical Engineering Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Leila Ansari
- Medical Physics and Biomedical Engineering Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Ali Razmkon
- Research Center for Neuromodulation and Pain, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Amin Banaei
- Department of Medical Physics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.,Department of Radiology, Faculty of Paramedical Sciences, AJA University of Medical Sciences, Tehran, Iran
| | - Alireza Mehdizadeh
- Medical Physics and Biomedical Engineering Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.,Research Center for Neuromodulation and Pain, Shiraz University of Medical Sciences, Shiraz, Iran
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Hazeri M, Farshidfar Z, Faramarzi M, Sadrizadeh S, Abouali O. Details of the physiology of the aerodynamic and heat and moisture transfer in the normal nasal cavity. Respir Physiol Neurobiol 2020; 280:103480. [PMID: 32553890 DOI: 10.1016/j.resp.2020.103480] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 06/11/2020] [Accepted: 06/11/2020] [Indexed: 12/13/2022]
Abstract
Anatomically accurate 3D models of 10 healthy nasal cavities are developed from computerized tomography (CT) scan images. Considering anatomical and physiological importance of different parts of the nasal cavity, the surface of each nasal passage is divided to eleven anatomical surfaces. Also the coronal cross sections in the nasal passage are divided to six sub-sections that share the total nasal passage airflow. The details of the flow field, heat transfer and water-vapor transport are numerically investigated for resting and low activity conditions. The mean and standard deviation of the different anatomical and air conditioning parameters such as: surface area, wall shear stress, heat and moisture transfer on different parts of the nasal passage surfaces and volume flow rates through different sections are presented. Results show that the percentages of airflow for inferior, middle and superior meatuses are 11.3 ± 6.4, 36.5 ± 9.5, 1.9 ± 0.81 % respectively and 4.1 ± 2.1 % of air passes through olfactory area. The inhaled air passing from the remaining surface (main passage) is 46.2 ± 10 %. Heat and moisture fluxes are highest in the anterior part of the nasal cavity, turbinates and lower part of the septum respectively. The percentage of the heat transfer from turbinates is 25.7 ± 3.9 % of total nasal heat transfer.
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Affiliation(s)
- Mohammad Hazeri
- School of Mechanical Engineering, Shiraz University, Shiraz, Iran
| | | | - Mohammad Faramarzi
- Department of Otolaryngology Head & Neck Surgery, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Sasan Sadrizadeh
- Department of Civil and Architectural Engineering, KTH University, Stockholm, Sweden
| | - Omid Abouali
- School of Mechanical Engineering, Shiraz University, Shiraz, Iran.
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Mohammadi MR, Khaleghi A, Mostafavi SA, Ahmadi N, Kamali K, Hooshyari Z, Ahmadi A, Fadaei Fooladi M, Mohammadzadeh S, Hojjat SK, Sarraf N, Nazaribadie M, Farshidfar Z, Mohamadian F, Sajedi Z, Shahbakhsh R, Nasiri M, Chegeni M, Rostami R, Riasati A, Shahbazi K, Roshandel Rad M, Ghaneian M, Parsamehr H, Nilforoshan N, Naderi F, Noohi Tehrani L, Kaviani N, Davasazirani R, Hashemi Nasab SM, Kiani A, Amiri S, Ahmadipour A, Alavi SS, Salmanian M. Gender Determines the Pattern of Correlation between Body Mass Index and Major Depressive Disorder among Children and Adolescents: Results from Iranian Children and Adolescents' Psychiatric Disorders Study. Child Obes 2019; 15:331-337. [PMID: 31070473 DOI: 10.1089/chi.2018.0323] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Background: We aimed to determine the correlation of BMI with depression and to determine the role of gender in this association, in a large study sample. Methods: We used the data of participants in the Iranian Children and Adolescents' Psychiatric Disorders (IRCAP) Study, conducted in 2017. This study was a national community-based, cross-sectional study in which the urban and rural areas of all provinces of Iran were covered. Overall 30,532 children and adolescents, ages 6-18, were randomly selected with the stratified cluster sampling method. Results: Of a total of 30,532 participants, 25,321, whose BMI had been measured and who had been interviewed with Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS), entered the study (12,455 boys and 12,866 girls). We categorized the participants according to the national cutoff points for BMI classification. After controlling for age, father's and mother's job and education, and place of residence, the odds ratio (OR) of depression in underweight, healthy weight, and overweight boys compared with obese boys was 2.19 [95% confidence interval (95% CI): 1.00-4.81], 1.06 (95% CI: 0.73-1.55), and 0.80 (95% CI: 0.49-1.32), respectively. In the girls' subgroup, after controlling for the aforementioned covariates, the OR of depression in healthy weight, overweight, and obese participants compared with underweight subjects was 1.29 (95% CI: 0.52-3.19), 1.54 (95% CI: 0.59-3.98), and 1.79 (95% CI: 0.68-4.69), respectively. Conclusions: Underweight boys were more likely diagnosed with depression than normal weight and overweight boys. While in girls, the probability of depression increased by increased BMI.
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Affiliation(s)
- Mohammad Reza Mohammadi
- 1 Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Ali Khaleghi
- 1 Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed-Ali Mostafavi
- 1 Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Nastaran Ahmadi
- 2 Yazd Cardiovascular Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Koorosh Kamali
- 3 Department of Public Health, School of Public Health, Zanjan University of Medical Sciences, Zanjan, Iran
| | - Zahra Hooshyari
- 1 Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Ameneh Ahmadi
- 1 Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahbod Fadaei Fooladi
- 4 Department of Psychology and Educational Sciences, Allameh Tabatabai University, Tehran, Iran
| | - Soleiman Mohammadzadeh
- 5 Department of Psychiatry, Neuroscience Research Center, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Seyed Kaveh Hojjat
- 6 Addiction and Behavioral Sciences Research Center, North Khorasan University of Medical Sciences, Bojnurd, Iran
| | - Nasrin Sarraf
- 7 Department of Child and Adolescents Psychiatry, School of Medicine, Qazvin University of Medical Sciences, Qazvin, Iran
| | - Marzieh Nazaribadie
- 8 Research Center for Behavioral Disorders and Substance Abuse, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Zahra Farshidfar
- 9 Department of Health Psychology, Gorgan Islamic Azad University, Gorgan, Iran
| | - Fathola Mohamadian
- 10 Department of Psychology, Psychosocial Injuries Research Center, Ilam University of Medical Science, Ilam, Iran
| | - Zahra Sajedi
- 11 Department of Psychology and Educational Sciences, University of Semnan, Semnan, Iran
| | - Rahim Shahbakhsh
- 12 Department of Clinical Psychology, University of Science and Culture, Tehran, Iran
| | - Mahdie Nasiri
- 13 Department of Clinical Psychology, University of Alzahra, Tehran, Iran
| | - Mahboobeh Chegeni
- 14 Department of Psychology, Arak University of Medical Sciences, Arak, Iran
| | - Rohollah Rostami
- 15 Department of Psychiatry, Hafez Hospital, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Atieh Riasati
- 16 Department of Psychology, Payam Noor University, Pardis Branch, Pardis, Iran
| | - Koroush Shahbazi
- 17 Department of Psychology, Islamic Azad University, Karaj, Iran
| | - Mahboubeh Roshandel Rad
- 18 Department of Psychiatry, Shafa Hospital, Guilan University of Medical Sciences, Rasht, Iran
| | - Mahnaz Ghaneian
- 19 Department of Psychology, Islamic Azad University, Najaf Abad Branch, Najaf Abad, Iran
| | - Hosien Parsamehr
- 20 Department of Psychology, Imam Reza Psychiatric Hospital, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Neda Nilforoshan
- 21 Department of Psychology, Islamic Azad University, Yazd Branch, Yazd, Iran
| | - Fateme Naderi
- 22 Department of Psychology, Hormozgan University of Medical Sciences, Hormozgan, Iran
| | - Leyla Noohi Tehrani
- 23 Department of Psychology, Islamic Azad University, Shahrood Branch, Shahrood, Iran
| | - Nahid Kaviani
- 24 Health Deputy, Kerman University of Medical Sciences, Kerman, Iran
| | - Reza Davasazirani
- 25 Community Mental Health and Addiction Department, Ahvaz University of Medical Sciences, Ahvaz, Iran
| | | | - Arezou Kiani
- 27 Department of Psychiatry, Urmia Medical University, Urmia, Iran
| | - Shahrokh Amiri
- 28 Research Center of Psychiatry and Behavioral Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Ahmad Ahmadipour
- 29 Department of Psychiatry, Khalij-E Fars Hospital, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Seyyed Salman Alavi
- 1 Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Maryam Salmanian
- 1 Psychiatry and Psychology Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
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Mohammadi MR, Alavi SS, Ahmadi N, Khaleghi A, Kamali K, Ahmadi A, Hooshyari Z, Mohamadian F, Jaberghaderi N, Nazaribadie M, Sajedi Z, Farshidfar Z, Kaviani N, Davasazirani R, Shahbakhsh AJ, Rad MR, Shahbazi K, Khodaverdloo RR, Tehrani LN, Nasiri M, Naderi F, Kiani A, Chegeni M, Hashemi Nasab SM, Ghaneian M, Parsamehr H, Nilforoushan N, Amiri S, Fooladi MF, Mohammadzadeh S, Ahmadipour A, Sarraf N, Hojjat SK, Nadermohammadi M, Mostafavi SA, Zarafshan H, Salmanian M, Shakiba A, Ashoori S. The prevalence, comorbidity and socio-demographic factors of depressive disorder among Iranian children and adolescents: To identify the main predictors of depression. J Affect Disord 2019; 247:1-10. [PMID: 30640024 DOI: 10.1016/j.jad.2019.01.005] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2018] [Revised: 12/23/2018] [Accepted: 01/04/2019] [Indexed: 01/04/2023]
Abstract
BACKGROUND Depressive disorders are a major public health problem in developed and developing countries. Recently, several risk factors have been described for depressive disorders in children and adolescents. The aim of the present study was to identify the main risk factors that can affect the incidence of depression in Iranian children and adolescents. METHODS A total of 30,546 children and adolescents (between 6 and 18 years of age) participated in a cross-sectional study to identify the predictors of depressive disorders. Depressive disorders were assessed using the Persian version of the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS-PL). In addition, a demographic characteristics questionnaire was completed by parents of the participants. The data was analyzed using the SPSS22 software via performing the descriptive analysis and the multiple logistic regression analysis methods. P-values less than 0.05 were considered statistically significant. RESULTS Results showed that a higher age (15-18), being female, and the father's unemployment were associated with an increased odds ratio for depressive disorders. The age of 10-14 (OR = 2.1; 95% CI, 1.57-2.81), the age of 15-18 (OR = 4.44; 95% CI, 3.38-5.83), female gender (OR = 1.44; 95% CI, 1.2-1.73) and the father's unemployment (OR = 1.59; 95% CI, 1.01-2.5) were significant positive predictors, whereas, the mother's job (as a housewife) (OR = 0.66; 95% CI, 0.45-0.96) and a history of psychiatric hospitalization of the father and mother (OR = 0.34; 95% CI, 0.15-0.78 and OR = 0.34; 95% CI, 0.14-0.84) were negative predictors for depressive symptoms. CONCLUSION Depressive symptoms are common in children and adolescents and are correlated with age and gender. The assessment of the prevalence of psychiatric disorders, especially the depressive disorders and their comorbidities, may help to prevent mood disorders in children and adolescents.
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Affiliation(s)
- Mohammad Reza Mohammadi
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
| | - Seyyed Salman Alavi
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
| | - Nastran Ahmadi
- Yazd Cardiovascular Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
| | - Ali Khaleghi
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
| | - Koorosh Kamali
- Department of Public Health, School of Public Health, Zanjan University of Medical Sciences, Zanjan, Iran.
| | - Ameneh Ahmadi
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
| | - Zahra Hooshyari
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
| | - Fathola Mohamadian
- Department of Psychology, Psychosocial Injuries Research Center, Ilam University of Medical Science, Ilam, Iran.
| | - Nasrin Jaberghaderi
- Department of Clinical Psychology, School of Medicine, Kermanshah University of Medical Sciences, Kermanshah, Iran.
| | - Marzieh Nazaribadie
- Research Center for Behavioral Disorders and Substance Abuse, Hamadan University of Medical Sciences, Hamadan, Iran.
| | - Zahra Sajedi
- Faculty of Psychology and Educational Sciences, University of Semnan, Semnan, Iran.
| | | | - Nahid Kaviani
- Health Deputy, Kerman University of Medical Sciences, Kerman, Iran.
| | - Reza Davasazirani
- Community Mental Health and Addiction Health Department of Khuzestan Province, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
| | | | | | | | | | | | | | - Fatemeh Naderi
- Hormozgan University of Medical Sciences, Hormozgan, Iran.
| | - Arezou Kiani
- Urmia University of Medical Sciences, Urmia, Iran.
| | | | | | - Mahnaz Ghaneian
- Department of Psychology, Islamic Azad University, Najafabad Branch, Najafabad, Iran.
| | - Hosein Parsamehr
- Lorestan University of Medical Sciences, Imam Reza Psychiatric Hospital, Khorramabad, Iran.
| | | | - Shahrokh Amiri
- Research Center of Psychiatry and Behavioral Sciences, Tabriz University of Medical Sciences, Tabriz, Iran.
| | - Mahbod Fadaei Fooladi
- Department of Psychology and Educational Sciences, Allameh Tabatabai University, Tehran, Iran.
| | - Soleiman Mohammadzadeh
- Department of Psychiatry, Neuroscience Research Center, Kurdistan University of Medical Sciences, Sanandaj, Iran.
| | - Ahmad Ahmadipour
- Department of Psychiatry, Booshehr University of Medical Sciences, Khalij-E Fars Hospital. Booshehr, Iran.
| | - Nasrin Sarraf
- Department of Child and Adolescents Psychiatry, School of Medicine, Qazvin University of Medical Sciences, Qazvin, Iran.
| | - Seyed Kaveh Hojjat
- Addiction and Behavioral Sciences Research Center, North Khorasan University of Medical Sciences, Bojnurd, Iran.
| | | | - Seyed-Ali Mostafavi
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
| | - Hadi Zarafshan
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
| | - Maryam Salmanian
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
| | - Alia Shakiba
- Psychiatry and Psychology Research Center, Tehran University of Medical Sciences, Tehran, Iran.
| | - Simin Ashoori
- Mashhad University of Medical Sciences, Mashhad, Iran.
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Khorram FS, Faeghi F, Jafarisepehr A, Farshidfar Z. Evaluation of Respiratory Triggered Diffusion-Weighted MRI with Three b-Values Compared to ADC Map and Fast Spin Echo Heavily T2W in Differential Diagnosis of Hemangioma from Malignant Liver Lesions. J Med Imaging Radiat Sci 2018; 49:251-256. [DOI: 10.1016/j.jmir.2018.04.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Revised: 02/22/2018] [Accepted: 04/11/2018] [Indexed: 10/14/2022]
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Farshidfar Z, Faeghi F, Haghighatkhah H, Abdolmohammadi J. The Optimization of Magnetic Resonance Imaging Pulse Sequences in Order to Better Detection of Multiple Sclerosis Plaques. J Biomed Phys Eng 2017; 7:265-270. [PMID: 29082217 PMCID: PMC5654132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2016] [Accepted: 07/12/2016] [Indexed: 11/10/2022]
Abstract
BACKGROUND AND OBJECTIVE Magnetic resonance imaging (MRI) is the most sensitive technique to detect multiple sclerosis (MS) plaques in central nervous system. In some cases, the patients who were suspected to MS, Whereas MRI images are normal, but whether patients don't have MS plaques or MRI images are not enough optimized enough in order to show MS plaques? The aim of the current study is evaluating the efficiency of different MRI sequences in order to better detection of MS plaques. MATERIALS AND METHODS In this cross-sectional study which was performed at Shohada-E Tajrish in Tehran - Iran hospital between October, 2011 to April, 2012, included 20 patients who suspected to MS disease were selected by the method of random sampling and underwent routine brain Pulse sequences (Axial T2w, Axial T1w, Coronal T2w, Sagittal T1w, Axial FLAIR) by Siemens, Avanto, 1.5 Tesla system. If any lesion which is suspected to the MS disease was observed, additional sequences such as: Sagittal FLAIR Fat Sat, Sagittal PDw-fat Sat, Sagittal PDw-water sat was also performed. RESULTS This study was performed in about 52 lesions and the results in more than 19 lesions showed that, for the Subcortical and Infratentorial areas, PDWw sequence with fat suppression is the best choice, And in nearly 33 plaques located in Periventricular area, FLAIR Fat Sat was the most effective sequence than both PDw fat and water suppression pulse sequences. CONCLUSION Although large plaques may visible in all images, but important problem in patients with suspected MS is screening the tiny MS plaques. This study showed that for revealing the MS plaques located in the Subcortical and Infratentorial areas, PDw-fat sat is the most effective sequence, and for MS plaques in the periventricular area, FLAIR fat Sat is the best choice.
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Affiliation(s)
- Z. Farshidfar
- MSc of Medical Imaging Technology (MRI), Radiology Department of Paramedical School, Shiraz University of Medical Sciences, Shiraz, Iran
| | - F. Faeghi
- Ph.D. in Medical Physics, Radiology Technology Department, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - H.R. Haghighatkhah
- MD, Department of Radiology, Shohada Tajrish Hospital, Shahid Beheshti University of medical sciences, Tehran, Iran
| | - J. Abdolmohammadi
- MSc. of Medical Imaging Technology (MRI), Department of Radiology, Faculty of Paramedical Sciences, Kurdistan University of Medical Sciences, Sanandaj, Iran
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Abdolmohammadi J, Shafiee M, Faeghi F, Arefan D, Zali A, Motiei-Langroudi R, Farshidfar Z, Nazarlou AK, Tavakkoli A, Yarham M. Determination of intra-axial brain tumors cellularity through the analysis of T2 Relaxation time of brain tumors before surgery using MATLAB software. Electron Physician 2016; 8:2726-2732. [PMID: 27757181 PMCID: PMC5053452 DOI: 10.19082/2726] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2016] [Accepted: 04/09/2016] [Indexed: 12/04/2022] Open
Abstract
Introduction Timely diagnosis of brain tumors could considerably affect the process of patient treatment. To do so, para-clinical methods, particularly MRI, cannot be ignored. MRI has so far answered significant questions regarding tumor characteristics, as well as helping neurosurgeons. In order to detect the tumor cellularity, neuro-surgeons currently have to sample specimens by biopsy and then send them to the pathology unit. The aim of this study is to determine the tumor cellularity in the brain. Methods In this cross-sectional study, 32 patients (18 males and 14 females from 18–77 y/o) were admitted to the neurosurgery department of Shohada-E Tajrish Hospital in Tehran, Iran from April 2012 to February 2014. In addition to routine pulse sequences, T2W Multi echo pulse sequences were taken and the images were analyzed using the MATLAB software to determine the brain tumor cellularity, compared with the biopsy Results These findings illustrate the need for more T2 relaxation time decreases, the higher classes of tumors will stand out in the designed table. In this study, the results show T2 relaxation time with a 85% diagnostic weight, compared with the biopsy, to determine the brain tumor cellularity (p<0.05). Conclusion Our results indicate that the T2 relaxation time feature is the best method to distinguish and present the degree of intra-axial brain tumors cellularity (85% accuracy compared to biopsy). The use of more data is recommended in order to increase the percent accuracy of this techniques.
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Affiliation(s)
- Jamil Abdolmohammadi
- M.Sc. of Medical Imaging Technology (MRI), Department of Radiology, Faculty of Paramedical Sciences, Kurdistan University of Medical Sciences, Sanandaj, Iran
| | - Mohsen Shafiee
- M.Sc. of Medical Physics, Cellular and Molecular Research Center, Yasuj University of Medical sciences, Yasuj, Iran
| | - Fariborz Faeghi
- Ph.D. in Medical Physics, Radiology Technology Department, School of Allied Medical Sciences, Shahid Beheshti University of Medical Science, Tehran, Iran
| | - Douman Arefan
- Department of Radiation Medicine Engineering, Shahid Beheshti University, Evin, Tehran, Iran
| | - Alireza Zali
- Neurosurgeon, Head of Neurosurgery Department of Shohada-E Tajrish Hospital, Chairman of the Medical Council of Iran, Tehran, Iran
| | - Rouzbeh Motiei-Langroudi
- Department of Neurosurgery, Shohada Tajrish Hospital, Shahid Beheshti University of Medical Science, Tehran, Iran
| | - Zahra Farshidfar
- M.Sc. of Medical Imaging Technology (MRI), Radiology Department of Paramedical School, Shiraz University of Medical Science, Shiraz, Iran
| | - Ali Kiani Nazarlou
- M.Sc. of Medical Imaging Technology, Department of Radiology, Imam Reza Medical Research and Training Hospital, Golgasht Ave., Tabriz, Iran
| | - Ali Tavakkoli
- M.Sc. of Medical Imaging Technology (MRI), Bahonar Medical Research and Training Hospital, Alborz University of Medical Science, Karaj, Iran
| | - Mohammad Yarham
- M.Sc. of Medical Imaging Technology (MRI), Radiology Department of Paramedical School, Shiraz University of Medical Science, Shiraz, Iran
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Farshidfar Z, Faeghi F, Mohseni M, Seddighi A, Kharrazi HH, Abdolmohammadi J. Diffusion tensor tractography in the presurgical assessment of cerebral gliomas. Neuroradiol J 2014; 27:75-84. [PMID: 24571836 DOI: 10.15274/nrj-2014-10008] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2013] [Accepted: 11/26/2013] [Indexed: 11/12/2022] Open
Abstract
Glioma is the most common intra-axial brain tumor characterized by invasion into the surrounding white matter (WM) tracts. These tumors are usually diagnosed by conventional MRI, but this method is unable to describe the relationship between tumor and neighboring WM tracts. Diffusion tensor tractography (DTT) is a new imaging modality which can solve this problem. The current study evaluated the application of DTT imaging in the presurgical assessment of gliomas, and introduces this new modality and its importance to physicians and imaging centers in Iran. Ten patients with intra-axial brain tumor and suspicion of glioma underwent conventional brain MRI pulse sequences and DTT imaging between December 2011 and February 2013 with a 1.5 Tesla system using 64 independent diffusion encoding directions. Acquired images were assessed by the neuroradiologist and neurosurgeon. The treatment strategies were recognized and compared using data before and after the tractography. On the basis of DTT data, the treatment strategy changed from radiotherapy to the craniotomy in seven patients, and in one patient, the neurosurgeon preferred to avoid surgery. In one patient, the treatment technique did not change, and in the last one radiosurgery was replaced by craniotomy. As we can infer from this study, based on the tractography results, the treatment strategy may be changed, and the treatment technique could be devised more accurately and may lead to fewer postoperative neurological deficits and better outcomes.
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Affiliation(s)
- Zahra Farshidfar
- Radiology Technology Department, School of Paramedicine, Shahid Beheshti University of Medical Sciences; Tehran, Iran -
| | - Fariborz Faeghi
- Radiology Technology Department, School of Paramedicine, Shahid Beheshti University of Medical Sciences; Tehran, Iran
| | - Mostafa Mohseni
- Neurosurgery Department, Shohada Tajrish Hospital, Shahid Beheshti University of Medical Sciences; Tehran, Iran
| | - Afsoun Seddighi
- Functional Neurosurgery Research Center of Shohada Tajrish Hospital; Tehran, Iran
| | | | - Jamil Abdolmohammadi
- Radiology Technology Department, School of Paramedicine, Shahid Beheshti University of Medical Sciences; Tehran, Iran
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