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Showing 21 results for Magnetic Resonance Imaging
Ghanaati H, Aghaee S, Salehianzandi N, Shakiba M, Jalali S.a.h,
Volume 65, Issue 2 (3-2008)
Volume 65, Issue 2 (3-2008)
Abstract
Background: Imaging abnormalities in the paranasal sinuses are regularly noted as incidental findings on MRI, however, little is known about their prevalence in the Iranian population. The purpose of this study was to classify these findings in the paranasal sinuses as seen on MRI and to investigate the prevalence, according to site and type of paranasal abnormality.
Methods: In this cross-sectional study, the T2-weighted axial MRI of 256 patients with diseases unrelated to their paranasal sinuses were reviewed between May 2002 and June 2003. The findings were categorized according to the anatomic location and the imaging characteristics of the abnormality. The abnormalities recorded included total sinus opacification, mucoperiosteal thickening >5mm, air fluid levels and retention cysts or polyps. Unilateral or bilateral involvement and septal deviation were also noted. A sinus was considered normal if it was fully aerated and no soft-tissue density was apparent within the cavity.
Results: Among our cases, 111 (43.5%) were male and 145 (56.5%) were female. Of these patients, abnormalities in one or more of the sinus groups were found in 110 subjects (42.9%), 55.5% of which were male and 44.5% were female (P=0.001). Maxillary sinus abnormalities were observed in 66.4% of the patients, while ethmoid sinus abnormalities were found in 63.6%. Of the ethmoid abnormalities, 21% were found in the anterior section, 9% in the middle ethmoid, and 8% in the posterior ethmoid. The most common abnormality found was mucosal thickening. Among our cases, 23.4% had septal deviation, which was significantly higher among those with sinusitis (29% versus 19.1% P<0.01). Of those patients with sinus involvement, 16% were involved in the sphenoid sinus and 5% in the frontal sinus. The results obtained from the patients with sinus abnormality revealed that 85% suffered from cough, nasal obstruction, runny nose, facial pain and post nasal discharge and 24% had been diagnosed with chronic sinusitis by physician.
Conclusion: Our results showed that there was a high rate of incidental abnormalities in the paranasal sinuses that are unrelated to the patient's presenting problems.
Koushan A, Sadat Mm, Golbakhsh Mr, Siavashi B, Mehran S, Tajik A,
Volume 68, Issue 5 (8-2010)
Volume 68, Issue 5 (8-2010)
Abstract
Background: There are multiple diagnostic methods for evaluation of patients with low back pain with a radicular pattern, each one has it's own accuracy and diagnostic ability and so comparing them with each other would help the clinicians to find the best diagnostic method. The main objective of our study was to compare the diagnostic accommodation of electromyography (EMG) and Magnetic Resonance Imaging (MRI) findings in patients with low back pain and radiculopathy.
Methods: In this descriptive cross-sectional study, 101 patients with low back pain and radiculopathy attending to Sina Hospital in Tehran, Iran from 2007 to 2009 that had indication for both EMG and MRI were evaluated for their demographic characteristics and disease-related factors.Results: Totally, 90 out of 101 patients (89%) had abnormal EMG findings and 94 out of 101 subjects (93%) had abnormal MRI results. The concordance rate was 88% (89 patients) with no significant difference (p> 0.05). The sensitivity and specificity of MRI were 95.6% and 27.3%, respectively, and the sensitivity and specificity of EMG were 91.5% and 60%, respectively.
Conclusion: According to the results of this study and in comparison with other studies it may be concluded that MRI and EMG are both accurate and use of them in a concomitant manner would result in increased diagnostic ability in patients with low back pain and radiculopathy.
Mahyar Ghafoori , Maryam Alizadeh , Jalil Kuhpayehzade ,
Volume 71, Issue 6 (9-2013)
Volume 71, Issue 6 (9-2013)
Abstract
Background: Prostate cancer is the third leading cause of death and is the most common cause of cancer in elderly men. Regarding to the low accuracy of screening methods such as prostate-specific antigen (PSA), Digital Rectal Examination (DRE) and trans rectal ultrasound (TRUS) in detection and localization of tumor, Magnetic Resonance Imaging (MRI) and Diffusion Weighted Imaging (DWI) attracted many attentions in the past years. DWI reveals micro-molecular diffusion, which is the Brownian motion of the spins in biologic tissues. This technique can delineate pathologic lesions with high tissue contrast against generally suppressed background signal. In this paper, the value of DWI in detection of prostate cancer is studied.
Methods: In this cross-sectional study, the studied population are suspicious patients to prostate cancer based on high Prostatic Specific Antigen level or abnormal Digital Rectal Examination who refered for prostate biopsy to radiology department of Hazrat-e- Rasoul Hospital during the year 2011. The results of DWI are compared to biopsy results for all patients.
Results: Eighty five patients are selected. The DWI sensitivity in detecting of prostate cancer is 100%, specificity 97.1% and positive and negative predictive values are 89.5% and 100%, respectively. The results showed that if DWI reports the prostate cancer as negative, the result was highly reliable and if it reports as positive, although the report was not 100% reliable, but it still had high reliability, more than 90%.
Conclusion: DWI had high accuracy in detecting prostate cancer for patients with cancer. Also the accuracy of this method for patients without prostate cancer was acceptable compared to the other common methods.
Mojtaba Sedaghat , Arash Rashidian , Seyed Davood Hosseini ,
Volume 71, Issue 6 (9-2013)
Volume 71, Issue 6 (9-2013)
Abstract
Background: The request for lumbosacral MRI in Iran based on previous studies is high (almost half of all MRI cases), so, our study is concerned with investigating the necessity of lumbosacral MRI request in patients with low back pain that is covered by complementary health insurance in Tehran through comparing MRI practice with valid guidelines.
Methods: Information of 274 complementary insured patients at Dana Insurance Company in Tehran, who had undergone low back MRI was studied. A portion of information in the questionnaire including age, sex, the physician’s field of specialty, and MRI report, was derived from the medical records. Other information based on guidelines indications, including duration of the prolonged back pain, record of associated infection, malignancy or trauma, saddle anesthesia, lower limb motor deficit and incontinence of urine or feces, was elicited from patients orally.
Results: Males represented 35% and females 65% of patients. Also, males were on average 10 years younger than females. Over 90% of MRI scans were requested by three fields of specialty (orthopedic, neurosurgery and neurology). Considering the indications of lumbar spine MRI request (prolonged back pain of more than one month duration, incontinence of urine or feces, lower limb motor deficit, saddle anesthesia, recent related trauma, infection and malignancy), approximately 20% of lumbar spine MRI scans were prescribed in accordance with guidelines.
Conclusion: Out of every five cases of lumbar spine MRI, four cases were not requested based on guidelines, suggesting needs for local guideline design and revising the manner in which MRI scans are prescribed for low back pain in complementary health insured patients in Tehran.
Bahman Mansori , Abdol Hamid Pilevar , Babak Azadnia ,
Volume 73, Issue 7 (10-2015)
Volume 73, Issue 7 (10-2015)
Abstract
Background: Magnetic resonance imaging (MRI) is widely applied for examination and diagnosis of brain tumors based on its advantages of high resolution in detecting the soft tissues and especially of its harmless radiation damages to human bodies. The goal of the processing of images is automatic segmentation of brain edema and tumors, in different dimensions of the magnetic resonance images. Methods: The proposed method is based on the unsupervised method which discovers the tumor region, if there is any, by analyzing the similarities between two hemispheres and computes the image size of the goal function based on Bhattacharyya coefficient which is used in the next stage to detect the tumor region or some part of it. In this stage, for reducing the color variation, the gray brain image is segmented, then it is turned to gray again. The self-organizing map (SOM) neural network is used the segmented brain image is colored and finally the tumor is detected by matching the detected region and the colored image. This method is proposed to analyze MRI images for discovering brain tumors, and done in Bu Ali Sina University, Hamedan, Iran, in 2014. Results: The results for 30 randomly selected images from data bank of MRI center in Hamedan was compared with manually segmentation of experts. The results showed that, our proposed method had the accuracy of more than 94% at Jaccard similarity index (JSI), 97% at Dice similarity score (DSS), and 98% and 99% at two measures of specificity and sensitivity. Conclusion: The experimental results showed that it was satisfactory and can be used in automatic separation of tumor from normal brain tissues and therefore it can be used in practical applications. The results showed that the use of SOM neural network to classify useful magnetic resonance imaging of the brain and demonstrated a good performance.
Afsaneh Alikhasi , Monir Sadat Mirai Ashtiani , Farshid Farhan , Mehdi Aghili , Mohammad Sadegh Fazeli , Mohammad Babaei, Afsaneh Maddah-Safai, Peiman Haddad,
Volume 73, Issue 10 (1-2016)
Volume 73, Issue 10 (1-2016)
Abstract
Background: This study investigated compatibility between post chemoradiation magnetic resonance images and histologic findings after operation and chemoradiation in patients with locally advanced rectal cancer.
Methods: In this prospective study, 63 patients referred to Cancer Institute of Emam Khomeini Hospital, Tehran, Iran, from October 2011 to October 2013 with locally advanced rectal cancer receiving neoadjuvant chemoradiation (50.4 Gy external beam radiation with concomitant capecitabine 825 mg/m2 PO twice a day with or without 60 mg/m2 oxaliplatin weekly). Patients had an MRI before chemoradiation and MRI assessment were used to identify Tumor (T) and lymph node (N) staging by an experienced radiologist. Patients were recommended to repeat MRI after surgery but it was not obligatory. Findings of post chemoradiation MRI and histopathologic reports were compared. Downstaging was defined as at least one stage decrease in T or N in histopathologic report comparing to their first MRI, on condition of no sign of disease progression.
Results: 32 patients (50.79%) had T downstaging and 36 of them (57.14%) showed N downstaging: none had disease progression. In this study MRI had an accuracy of 55.5% for rectal tumor (T) restaging after chemoradiation comparing to pathology. MRI sensitivity for T restaging was 33.3% to 83.3%. There was a higher possibility to have errors in restaging of T1-2 stages. Specificity of MRI for T restaging was higher than its sensitivity, 66.6%. In this study lymph node involvement (N) was determined according to morphology and size. MRI has an accuracy of 42.8% for detecting lymph node involvement. Its sensitivity and specificity for N restaging were 50% and 66.6% respectively. All patients had MRI before chemoradiation, although 21 of them repeated MRI after chemoradiation since it was not mandatory. 19 of these 21 patients underwent surgery.
Conclusion: Although MRI is a suitable imaging for staging locally advanced rectal cancer its use for restaging after chemoradiation is under question. According to this study, MRI accuracy rates for both T and N restaging were below the rates of previous studies.
Seyed Reza Saadat Mostafavi , Kaveh Samimi , Fatemeh Parvin Ashtiani , Soheil Fateh ,
Volume 73, Issue 10 (1-2016)
Volume 73, Issue 10 (1-2016)
Abstract
Background: Recent studies have indicated the relation of vertebral endplate lesions (Modic changes) to low back pain (LBP). The aim of this study was to investigate the Modic changes in magnetic resonance imaging (MRI) of patients with low back pain, and its correlation with age, sex, type of changes, number of involved segments and location of changes. Additionally, association of degenerative disc changes and disc herniation was assessed.
Methods: In this retrospective study, MRI records of 229 patients with LBP referring to Medical Center of Hazrat-e-Rasoul Hospital, Tehran, Iran, from August to February 2014, were assessed and Modic changes and degenerative and herniated disc changes were recorded.
Results: Based on our observations, a significant association between Modic type and age (P= 0.003) existed in patients with LBP. The highest prevalence in Modic location were observed in anterior part of vertebral endplate (48.8%, P= 0.001). Although, observation of the Modic changes in superior vertebral endplate was higher than inferior parts, but this differences was not statistically significant. The highest prevalence in degenerative disc disease was disc dehydration which was observed in 18.1% of patients (P= 0.04). The relationship between the degenerative changes and Modic type was significant (P= 0.04), while the most prevalent change of disc contour was disc bulging which occurred in 23.7% of patients (P= 0.01). The highest frequency of abnormal disc contour were observed in Modic type 2 which was statistically significant (P= 0.01). Modic surface involvement above 25% was significantly associated with disc herniation (P= 0.04). There was no significant association between Modic height involvement above 25% and disc herniation.
Conclusion: Considering significant association between Modic changes and degenerative and herniated disc changes, reporting of Modic changes is necessary.
Soheila Aminimoghaddam, Sara Norouzi, Elham Nasrolahi, Narmin Karisani,
Volume 74, Issue 6 (9-2016)
Volume 74, Issue 6 (9-2016)
Abstract
Background: Cervical cancer is the third most common gynecologic cancer in women worldwide. Cervical cancer has lower incidence and mortality rates than uterine corpus and ovarian cancer, as well as many other cancer sites. Unfortunately, in countries that do not have access to cervical cancer screening and prevention programs, cervical cancer remains the second most common type of cancer. Staging of the disease is made clinically. The aim of this study was to evaluate the role of magnetic resonance imaging (MRI) for diagnosing the invasion of cancer to organs and staging of cervical cancer and the relationship between clinical and pathological findings and the sensitivity and specificity of the assay in cervical cancer.
Methods: The study included records of 40 patients with cervical cancer that undergo surgery or Chemoradiation in Firoozgar University Hospital. In this study that made retrospectively, non-randomized, the MRI reports and clinical findings records and pathology results was discussed. The sensitivity and specificity of MRI for diagnosing the invasion to parameters, bladder, rectum, vagina, pelvic wall and it’s accuracy to determine tumor stage has been set.
Results: A total of 40 patients with pathology information of cervical cancer was retrospectively reviewed in the study. The patients were 28-83 years old by mean age of 49.3 Pathology of cervical cancer in 80% of cases was SCC, 15% adenocarcinoma and 5% melanoma. The sensitivity and specificity of MRI for diagnosing invasion of parameter was 76% and 88%. The sensitivity of MRI in the detection of bladder invasion was 100% and specificity of 100%. The sensitivity of MRI in the diagnosis of rectal invasion was 50% and specificity of 100%. The sensitivity of MRI in the diagnosis of pelvic wall invasion was 100% and specificity of 86%. Sensitivity in detecting invasion into the upper third of the vagina was 100%.
Conclusion: Overall, this study showed a good sensitivity and specificity for detecting invasion into the bladder, vagina, pelvic wall and parameters and good specificity for the diagnosis of rectal invasion and acceptable accuracy at 67.5% for detection of tumor stage by MRI show.
Hamidreza Saligheh Rad , Anahita Fathi Kazerooni , Mahnaz Nabil , Mohammadreza Alviri , Mehrdad Hadavand, Meysam Mohseni ,
Volume 76, Issue 3 (6-2018)
Volume 76, Issue 3 (6-2018)
Abstract
Background: Due to intrinsic heterogeneity of cellular distribution and density within diffusion weighted images (DWI) of glioblastoma multiform (GBM) tumors, differentiation of active tumor and peri-tumoral edema regions within these tumors is challenging. The aim of this paper was to take advantage of the differences among heterogeneity of active tumor and edematous regions within the glioblastoma multiform tumors in order to discriminate these regions from each other.
Methods: The dataset of this retrospective study was selected from a database which was collected at the medical imaging center, Imam Khomeini Hospital, Tehran University of Medical Sciences, Iran. The quantification was performed as a part of a research study being supported by the Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Iran, between May and September 2017. Twenty patients with histopathologically-confirmed GBM tumors who had been imaged on a 3T MRI scanner prior to their surgery, were included. Conventional and diffusion weighted MR images had been carried out on the patients. The regions of interest including the regions of active tumor and edema were identified on MR images by an expert and overlaid on ADC-maps of the same patients. Histogram analysis was performed on each of these regions and 14 characteristic features were calculated and the best feature combination for discrimination of active tumor from edema was obtained.
Results: It was shown that by combining 8 out of 14 histogram features, including median, normalized mean, standard deviation, skewness, energy, 25th, 75th, and 95th percentiles, differentiation with accuracy of 96.4% and diagnostic performance of 100% can be achieved. Furthermore, by combining mean, energy, and 75th percentile features of histograms, the active tumor region can be discriminated from the edematous region by 92.7% of accuracy and 98.9% of diagnostic performance.
Conclusion: The present study confirms that the heterogeneity of cellular distribution can be a predictive biomarker for differentiation of edematous regions from active tumor part of GBM tumors.
Methods: The dataset of this retrospective study was selected from a database which was collected at the medical imaging center, Imam Khomeini Hospital, Tehran University of Medical Sciences, Iran. The quantification was performed as a part of a research study being supported by the Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Iran, between May and September 2017. Twenty patients with histopathologically-confirmed GBM tumors who had been imaged on a 3T MRI scanner prior to their surgery, were included. Conventional and diffusion weighted MR images had been carried out on the patients. The regions of interest including the regions of active tumor and edema were identified on MR images by an expert and overlaid on ADC-maps of the same patients. Histogram analysis was performed on each of these regions and 14 characteristic features were calculated and the best feature combination for discrimination of active tumor from edema was obtained.
Results: It was shown that by combining 8 out of 14 histogram features, including median, normalized mean, standard deviation, skewness, energy, 25th, 75th, and 95th percentiles, differentiation with accuracy of 96.4% and diagnostic performance of 100% can be achieved. Furthermore, by combining mean, energy, and 75th percentile features of histograms, the active tumor region can be discriminated from the edematous region by 92.7% of accuracy and 98.9% of diagnostic performance.
Conclusion: The present study confirms that the heterogeneity of cellular distribution can be a predictive biomarker for differentiation of edematous regions from active tumor part of GBM tumors.
Mansour Rezaei , Ehsan Zereshki , Hamid Sharini , Mohamad Gharib Salehi , Farhad Naleini ,
Volume 76, Issue 6 (9-2018)
Volume 76, Issue 6 (9-2018)
Abstract
Background: Alzheimer's disease (AD) is the most common disorder of dementia, which has not been cured after its occurrence. AD progresses indiscernible, first destroy the structure of the brain and subsequently becomes clinically evident. Therefore, the timely and correct diagnosis of these structural changes in the brain is very important and it can prevent the disease or stop its progress. Nowadays, remark to this fact that magnetic resonance imaging (MRI) provides very useful and detailed information, and due to non-invasiveness, this method has been great interest to the researchers. The aim of this study was diagnosis of AD with MRI by support vector machine model (SVM).
Methods: This is an analytical and modeling research which done in School of Public Health, Kermanshah University of Medical Science, Iran, from February 2017 to November 2017. The data used in this study was a database named Miriad containing brain MRI of 69 individuals (46 Alzheimer's disease and 23 healthy subjects) that was collected at the central hospital in London. Individuals were categorized into two groups of healthy and Alzheimer's disease with two criteria: NINCDS-ADRAD and MMSE (as the golden standard). In this paper SVM model with three linear, binomial and Gaussian kernels was used to distinguish Alzheimer`s disease from healthy individuals.
Results: Finally, SVM model with Gaussian kernel, separated AD and healthy subjects with 88.34% accuracy. The most important Areas for Alzheimer were three Area: Right para hippocampal gyrus, Left para hippocampal gyrus and Right hippocampus. The clinical result of this study is to identify the most important ROI for the diagnosis of Alzheimer's by a clinical specialist. Experts should focus on atrophy in the three Areas.
Conclusion: This study showed that the SVM model with Gaussian RBF kernel can separated AD from healthy subjects by high accuracy. Based on results of this study, can make a software to use in MRI centers for screening AD test by people over the age of 50 years.
Methods: This is an analytical and modeling research which done in School of Public Health, Kermanshah University of Medical Science, Iran, from February 2017 to November 2017. The data used in this study was a database named Miriad containing brain MRI of 69 individuals (46 Alzheimer's disease and 23 healthy subjects) that was collected at the central hospital in London. Individuals were categorized into two groups of healthy and Alzheimer's disease with two criteria: NINCDS-ADRAD and MMSE (as the golden standard). In this paper SVM model with three linear, binomial and Gaussian kernels was used to distinguish Alzheimer`s disease from healthy individuals.
Results: Finally, SVM model with Gaussian kernel, separated AD and healthy subjects with 88.34% accuracy. The most important Areas for Alzheimer were three Area: Right para hippocampal gyrus, Left para hippocampal gyrus and Right hippocampus. The clinical result of this study is to identify the most important ROI for the diagnosis of Alzheimer's by a clinical specialist. Experts should focus on atrophy in the three Areas.
Conclusion: This study showed that the SVM model with Gaussian RBF kernel can separated AD from healthy subjects by high accuracy. Based on results of this study, can make a software to use in MRI centers for screening AD test by people over the age of 50 years.
Mohadese Zademir, Narjes Sargolzaie, Amirhossein Nourolah ,
Volume 78, Issue 4 (7-2020)
Volume 78, Issue 4 (7-2020)
Abstract
Background: The empty sella syndrome (ESS) is a neurological or pathologic finding in which sella turcica is devoid of pituitary tissue and the subarachnoid space extends into sella turcica, which is either primary or secondary as well as partial and complete. The widespread use of CT scans and MRIs today has made the ESS a common finding in imaging. The aim of this study was to evaluate the prevalence of the empty sella syndrome.
Methods: This is a retrospective descriptive-analytic study in which all patients referred to Imam Ali Hospital (Zahedan) for electromagnetic brain imaging (n=1856) were recruited by cross-sectional sampling during the first 6 months from 21 March 2018 to 23 September 2018. Inclusion criteria included the absence of another known problem in the central nervous system and the absence of concurrent underlying disease. The data gathering tool was a questionnaire consisting of demographic and related variable to empty sella disorder.
Methods: This is a retrospective descriptive-analytic study in which all patients referred to Imam Ali Hospital (Zahedan) for electromagnetic brain imaging (n=1856) were recruited by cross-sectional sampling during the first 6 months from 21 March 2018 to 23 September 2018. Inclusion criteria included the absence of another known problem in the central nervous system and the absence of concurrent underlying disease. The data gathering tool was a questionnaire consisting of demographic and related variable to empty sella disorder.
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Results: The results of this study showed that the prevalence of empty sella was 8.2% with a mean age of 37.02±12.51 years. 66.4% of the patients were female. The prevalence of primary empty sella was 78.9% with a mean age of 34.51±11.26 years. 71.7% of the patients had partial empty sella. There was a significant difference between the mean age and sex of patients with empty sella and non-empty sella subjects (P=0.008) and (P<0.0001). There was a statistically significant difference between the mean age of affected patients with type of empty sella (P<0.0001). There was no statistically significant difference between mean age of patients with empty sella and severity of empty sella (P=0.056). There was no significant difference between the frequency of empty sella type and the severity with gender (P=0.224) and (P=0.091).
Conclusion: The findings of this study indicated that the overall prevalence of empty sella in the referring patients was relatively low. Most of them were females with primary type and minor severity. |
Amir Hossein Jalalzadeh, Ahmad Shalbaf , Arash Maghsoudi,
Volume 78, Issue 10 (1-2021)
Volume 78, Issue 10 (1-2021)
Abstract
Background: Surgery and accurate removal of the brain tumor in the operating room and after opening the scalp is one of the major challenges for neurosurgeons due to the removal of skull pressure and displacement and deformation of the brain tissue. This displacement of the brain changes the location of the tumor relative to the MR image taken preoperatively.
Methods: This study, which is done from March to December 2019 in Tehran, is evaluated on the available database of RetroSpective Evaluation of Cerebral Tumors (RESECT) including pre-operative MR images, and intra-operative ultrasound from 22 patients with low-grade gliomas who underwent surgeries at St. Olavs University Hospital. This study is used for image registration of preoperative MR imaging and ultrasound imaging after resection of the skull to compensate for brain changes. By this method, we obtained a third image that resembles preoperative MR imaging but has the geometry of the brain shape changes. We used a combination of the two transformations named Affine and non-rigid Free Form Deformation (FFD) for hierarchically moving the pixels to compensate for global variations, and also nonlinear local and small variations. Also, by applying the mutual information function, we consider the entropy value as the criterion of similarity due to the non-similarity of the nature of the images. Also, Limited Broyden-Fletcher-Goldfarb-Shannon method is used for optimization.
| Results: The results of the proposed method were presented on the available database of RetroSpective Evaluation of Cerebral Tumors (RESECT) including images of 22 patients with glioma type 2 tumors and evaluated based on 15 landmarks per patient and also mutual information criteria. The mean target registration error for affine, FFD and the proposed method are 46.19, 42.85 and 38.01, respectively. It was shown that the proposed method achieved high accuracy by combining the two transformations of affine and FFD compared to the separate use of each of the two models. Conclusion: In image registration of preoperative MR and ultrasound images for compensation of brain shift, the combination of affine and FFD transformations had better results than the individual use of each of the transformations. |
Hasan Mohammadi Kiani , Ahmad Shalbaf, Arash Maghsoudi,
Volume 79, Issue 2 (5-2021)
Volume 79, Issue 2 (5-2021)
Abstract
Background: Early diagnosis of patients in the early stages of Alzheimer's, known as mild cognitive impairment, is of great importance in the treatment of this disease. If a patient can be diagnosed at this stage, it is possible to treat or delay Alzheimer's disease. Resting-state functional magnetic resonance imaging (fMRI) is very common in the process of diagnosing Alzheimer's disease. In this study, we intend to separate subjects with mild cognitive impairment from healthy control based on fMRI data using brain functional connectivity and graph theory.
Methods: In this article, which was done from April to November 2020 in Tehran, after pre-processing the fMRI data, 116 brain regions were extracted using an Automated Anatomical Labeling atlas. Then, the functional connectivity matrix between the time signals of 116 brain regions was calculated using Pearson correlation and mutual information methods. Using functional connectivity calculations, the brain graph network was formed, followed by thresholding of the brain connectivity network to keep significant and strong edges while eliminating weaker edges that were likely noise. Finally, 11 global features were extracted from the graph network and after performing statistical analyses and selecting optimal features; the classification of 14 healthy individuals and 11 patients with mild cognitive impairment was performed using a support vector machine classifier.
Methods: In this article, which was done from April to November 2020 in Tehran, after pre-processing the fMRI data, 116 brain regions were extracted using an Automated Anatomical Labeling atlas. Then, the functional connectivity matrix between the time signals of 116 brain regions was calculated using Pearson correlation and mutual information methods. Using functional connectivity calculations, the brain graph network was formed, followed by thresholding of the brain connectivity network to keep significant and strong edges while eliminating weaker edges that were likely noise. Finally, 11 global features were extracted from the graph network and after performing statistical analyses and selecting optimal features; the classification of 14 healthy individuals and 11 patients with mild cognitive impairment was performed using a support vector machine classifier.
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Results: Calculations were showed that the mutual information algorithm as a functional connectivity method and five global features of the graph network, including average strength, eccentricity, local efficiency, coefficient clustering and transitivity, using the support vector machine classifier achieved the best performance with the accuracy, sensitivity and specificity of 84, 86 and 93 percent, respectively.
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Conclusion: Combining the features of brain graph and functional connectivity by the mutual information method with a machine learning approach, based on fMRI imaging analysis, is very effective in diagnosing mild cognitive impairment in the early stages of Alzheimer’s which consequently allows treating or delaying this disease.
Negar Abdi, Iraj Abedi, Mozafar Naserpour , Masoud Rabbani,
Volume 79, Issue 6 (9-2021)
Volume 79, Issue 6 (9-2021)
Abstract
Background: Prostate cancer is the most common malignancy in men and the second leading cause of death in all countries of the world. The exact mechanism of prostate cancer is not known. On the other hand, early detection of prostate cancer can lead to a complete cure. Several clinical experiments including Digital Rectum Examination (DRE), biochemistry such as Prostate Specific Antigen (PSA), and pathology such as Trans Rectal Ultra Sonography (TRUS) are used to assess the size and spread of prostate cancer. In this study, the relationship between mean serum PSA and Gleason score as a standard method in patients with prostate cancer was compared using the parameters extracted from DCE MRI.
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Methods: This applied-fundamental study was performed on 90 patients with prostate cancer, according to McDonald's criteria who were referred to Shafa Imaging Center in Isfahan, from March 2020 to October 2020. Quantitative analysis is based on modeling the change of concentration of the contrast agent using pharmacokinetic modeling techniques. The pathologist then determined the Gleason score using anatomical landmarks (such as prostate urethra) in the same areas suspected of being cancerous. Existing commercial software captures DCE-MRI data and creates parametric maps such as Ktrans and Kep maps that can be used for diagnostic purposes.
Results: Kep and Ktrans maps showed a significant difference between healthy and cancerous tissue. Kep and Ktrans in prostate cancer were significantly higher than in healthy tissue (P<0.05). Pearson correlation coefficient was used to investigate the relationship between DCE-MRI parameters and histopathological findings. No significant relationship was observed between Gleason score and DCE MRI parameters. Conclusion: DCE MRI parameters significantly improve the accurate diagnosis of prostate cancer and are useful and effective for diagnosis, management, and evaluation of men with prostate cancer, but should not be considered as a substitute for tissue biopsy. |
Fatemeh Yarmahmoodi , Fatemeh Jaafarzadeh Sarvestani , Seyed Mostajab Razavinejad , Banafsheh Zeinali Rafsanjani ,
Volume 80, Issue 1 (4-2022)
Volume 80, Issue 1 (4-2022)
Abstract
Background: Neonatal seizures can have many causes. Determining the underlying cause of neonatal seizures is very important in determining the prognosis, outcome, and treatment strategies. In this study, we have evaluated the frequency of Magnetic resonance imaging (MRI) findings in neonates younger than 6 months who had been referred to Shiraz Namazi hospital with seizures to determine the prevalence of various causes of seizures.
Methods: This was a retrospective study, that was performed on 199 neonates younger than 6 months of age who were hospitalized due to seizures in hospitals affiliated with Shiraz medical sciences from 21st March 2018 to 20 March 2019. Patient data were extracted by statistics and health information system and imaging data and its reports were extracted from picture archiving and communication system. The data were statistically analyzed by SPSS V26.
Results: In this study, 199 infants under the age of 6 months were examined, of which 124 (62.3%) were boys and 75 (37.7%) were girls. 97 infants (48.7%) were less than one month old and 102 ones (81.3%) were in the age group of 1-6 months. It should be noted that in terms of gender, 57.3% (71) of male infants and 49.3% (37) of female infants had abnormal MRI findings. 54.3% of patients had abnormal MRI findings and 45.7% had normal MRI. The most common abnormal finding was hypoxic-ischemic encephalopathy (HIE), which was the most common cause of seizures in 21.1% of neonates, followed by infection with 12.5% and cerebral hemorrhage with 11% of prevalence. Other important abnormal findings included hydrocephalus, structural abnormalities, venous sinus thrombosis, brain atrophy, developmental abnormality, etc. There was a combination of radiological findings in 18.56% of neonates.
Methods: This was a retrospective study, that was performed on 199 neonates younger than 6 months of age who were hospitalized due to seizures in hospitals affiliated with Shiraz medical sciences from 21st March 2018 to 20 March 2019. Patient data were extracted by statistics and health information system and imaging data and its reports were extracted from picture archiving and communication system. The data were statistically analyzed by SPSS V26.
Results: In this study, 199 infants under the age of 6 months were examined, of which 124 (62.3%) were boys and 75 (37.7%) were girls. 97 infants (48.7%) were less than one month old and 102 ones (81.3%) were in the age group of 1-6 months. It should be noted that in terms of gender, 57.3% (71) of male infants and 49.3% (37) of female infants had abnormal MRI findings. 54.3% of patients had abnormal MRI findings and 45.7% had normal MRI. The most common abnormal finding was hypoxic-ischemic encephalopathy (HIE), which was the most common cause of seizures in 21.1% of neonates, followed by infection with 12.5% and cerebral hemorrhage with 11% of prevalence. Other important abnormal findings included hydrocephalus, structural abnormalities, venous sinus thrombosis, brain atrophy, developmental abnormality, etc. There was a combination of radiological findings in 18.56% of neonates.
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Conclusion: This study showed that hypoxic-ischemic encephalopathy is the most common cause of neonatal seizures. Considering that in this study, a significant percentage (54.3%) of the neonates had abnormal brain MRI, this finding indicates the importance of performing this radiological procedure in the diagnosis, prognosis, and duration of treatment in neonatal seizures.
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Milad Jalilian, Iraj Abedi, Mohammadreza Sharifi,
Volume 80, Issue 2 (5-2022)
Volume 80, Issue 2 (5-2022)
Abstract
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Background: Magnetic resonance imaging (MRI) is a non-invasive imaging technology that shows detailed anatomical and pathological images. It is often used for disease detection, diagnosis, and treatment monitoring, in particular with neurodegenerative diseases, such as Multiple sclerosis (MS), Alzheimer's and amyotrophic lateral sclerosis. However, conventional MRI provides only qualitative information and cannot distinguish between myelin and axon destruction. One of the new methods in early detection for axonal injury is the DTI sequence, which can be used to observe and quantify the various dimensions of these plaques, including the direction of diffusion and average diffusion. In other words, in DTI, quantitative data from the image helps to estimate the physiological and pathophysiological information of plaques in the brain. This study aimed to investigate the relationship between DTI parameters including FA, MD, RD, AD, axon injury and severity of clinical symptoms in patients with MS.
Conclusion: Indicators obtained from the DTI sequence can be used in the prognosis of the disease and the estimation of the severity of clinical symptoms during the patients' involvement. |
Zahra Papi , Iraj Abedi, Fatemeh Dalvand, Alireza Amouheidari,
Volume 80, Issue 4 (7-2022)
Volume 80, Issue 4 (7-2022)
Abstract
Background: Glioma is the most common primary brain tumor, and early detection of tumors is important in the treatment planning for the patient. The precise segmentation of the tumor and intratumoral areas on the MRI by a radiologist is the first step in the diagnosis, which, in addition to the consuming time, can also receive different diagnoses from different physicians. The aim of this study was to provide an automated method for segmenting the tumor and intratumoral areas.
Methods: This is a fundamental-applied study that was conducted from May 2020 to September 2021 using multimodal MRI images of 285 patients with glioma tumors from the BraTS 2018 Database. This database was collected from 19 different MRI imaging centers, including multimodal MRI images of 210 HGG patients, and 75 LGG patients. In this study, a 2D U-Net architecture was designed with a patch-based method for training, which comprises an encoding path for feature extraction and a symmetrical decoding path. The training of this network was performed in three separate stages, using data from high-grade gliomas (HGG), and low-grade gliomas (LGG), and combining two groups of 210, 75, and 220 patients, respectively.
Methods: This is a fundamental-applied study that was conducted from May 2020 to September 2021 using multimodal MRI images of 285 patients with glioma tumors from the BraTS 2018 Database. This database was collected from 19 different MRI imaging centers, including multimodal MRI images of 210 HGG patients, and 75 LGG patients. In this study, a 2D U-Net architecture was designed with a patch-based method for training, which comprises an encoding path for feature extraction and a symmetrical decoding path. The training of this network was performed in three separate stages, using data from high-grade gliomas (HGG), and low-grade gliomas (LGG), and combining two groups of 210, 75, and 220 patients, respectively.
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Results: The proposed model estimated the Dice Similarity Coefficient (DSC) results in HGG datasets 0.85, 0.85, 0.77, LGG datasets 0.80, 0.66, 0.51, and the combination of the two groups 0.88, 0.79, 0.77 for regions the whole tumor, tumor core, and enhancing region in the training dataset, respectively. The results related to Hussdorf Distance (HD) for HGG datasets were 8.24, 9.92, 4.43, LGG datasets 11.5, 11.31, 2.23, and the combination of the two groups 7.20, 8.82, 4.43 for regions the whole tumor, tumor core, and enhancing region in the training dataset, respectively.
Conclusion: Using the U-Net network can help physicians in the accurate segmentation of the tumor and its various areas, as well as increase the survival rate of these patients and improve their quality of life through accurate diagnosis and early treatment. |
Ghazaleh Jamshidi , Farshid Babapour Mofrad , Mahyar Ghafoori, Hamidreza Saligheh Rad ,
Volume 80, Issue 6 (9-2022)
Volume 80, Issue 6 (9-2022)
Abstract
Background: Prostate cancer (PCa) has been one of the most prevalent cancers in men in recent years. Multi-parametric magnetic resonance imaging (mp-MRI) has been increasingly applied in the diagnosis, localization and staging of prostate cancer. This approach uses a combination of morphology information obtained from T2-weighted image along with at least two functional imaging modalities, such as diffusion-weighted (DWI), dynamic-contrast-enhancement (DCE), and magnetic-resonance-spectroscopy (MRS). This review gives a comprehensive overview of the theories and methodologies of the mp-MRI for diagnosing prostate cancer. The search was fulfilled using a list of search engines.
Methods: In this study, with a systematic review of studies conducted during February 2015 to October 2021, the role and potential of integrating the results of morphological and functional imaging in a multi-parameter approach were evaluated and the optimal combination was introduced. This article collected studies that have employed mp-MRI in prostate cancer including: peer-reviews, research articles, academic reports and conferences. This review has been studied from September 2016 to January 2022.
Methods: In this study, with a systematic review of studies conducted during February 2015 to October 2021, the role and potential of integrating the results of morphological and functional imaging in a multi-parameter approach were evaluated and the optimal combination was introduced. This article collected studies that have employed mp-MRI in prostate cancer including: peer-reviews, research articles, academic reports and conferences. This review has been studied from September 2016 to January 2022.
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Results: According to the reported results, the optimum combination of T2-w, DWI and DCE in the mp-MRI approach provides the highest sensitivity and specificity in the diagnosis, localization and staging of prostate cancer. Applying the field strength of 3T versus 1.5T improves detection accuracy including improving sensitivity and specificity as well, and also the application of endorectal coils does not provide much advantage compared to pelvic phased-array coil in term of prostate cancer detection accuracy.
Conclusion: MP-MRI as a precision instrument plays a valuable role in the diagnosis of prostate cancer. The most suitable combination of the pulse sequences to achieve the goals of this approach is T2-w, DWI and DCE. This review is comprehensive overview covered previous articles of mp-MRI in prostate cancer for all the researchers in this field and expresses the positive and negative points of each modality. Moreover, this article reports the sensitivity and the Specificity of the recent researches. |
Somayeh Zamani, Mohammad Reza Sasani , Mahdi Saeedi-Moghadam ,
Volume 81, Issue 4 (7-2023)
Volume 81, Issue 4 (7-2023)
Abstract
Background: MRI is the imaging modality of choice for the detection of diabetic pedal osteomyelitis. The aim of this study is to compare the STIR sequence, as the most important fluid-sensitive sequence, with contrast-enhanced images for diagnosing diabetic pedal osteomyelitis.
Methods: Medical images were compared. Moreover, the effect of adding T1W image findings to the STIR sequence was evaluated. This cross sectional study was collected and analyzed at Namazi Hospital, Shiraz University of Medical Sciences, from 20 March 2016 to 22 September 2017.
Results: The final diagnosis of osteomyelitis was confirmed for 47 bones (78%). 13 bones (22%) didn't have osteomyelitis. The specificity of contrast-enhanced and STIR sequences was 92.3% and 53.8%, respectively; whereas the sensitivity of the two sequences was similar (100%). Records of 48 diabetic patients suspected of having pedal osteomyelitis referred to one of the university hospitals, who underwent foot MRI with and without contrast injection, were assessed. Overall, 48 Patient MRIs and 60 separate bony parts were evaluated. Diagnoses were confirmed by clinical correlation. Finally, sensitivity, specificity and diagnostic accuracy of STIR sequence and contrast-enhanced images were compared. Moreover, the effect of addition of T1W image findings to STIR sequence was evaluated.
Conclusion: This study was performed to suggest a pulse sequence that doesn’t need contrast media injection for diagnosing diabetic pedal osteomyelitis since the previous studies showed that gadolinium-based contrast media shouldn’t be applied in patients with renal failure (glomerular filtration rate<30 ml/min/1.73m2. According to the results STIR images had the same sensitivity as T1 post-contrast images; therefore, it can be concluded that contrast media injection can be avoided using this pulse sequence. The specificity of the STIR pulse sequence was lower than that of post-contrast images which was due to the lower ability of this pulse sequence to detect secondary symptoms of osteomyelitis such as cortex disruption, sinus path, and abscess. Using the T1 pre-contrast images, specificity and diagnostic accuracy increased. Finally, it can be concluded that MRI without contrast including STIR and pre-contrast T1W images is a reliable modality for the detection of osteomyelitis in suspected diabetic patients who are more prone to renal disorders.
Methods: Medical images were compared. Moreover, the effect of adding T1W image findings to the STIR sequence was evaluated. This cross sectional study was collected and analyzed at Namazi Hospital, Shiraz University of Medical Sciences, from 20 March 2016 to 22 September 2017.
Results: The final diagnosis of osteomyelitis was confirmed for 47 bones (78%). 13 bones (22%) didn't have osteomyelitis. The specificity of contrast-enhanced and STIR sequences was 92.3% and 53.8%, respectively; whereas the sensitivity of the two sequences was similar (100%). Records of 48 diabetic patients suspected of having pedal osteomyelitis referred to one of the university hospitals, who underwent foot MRI with and without contrast injection, were assessed. Overall, 48 Patient MRIs and 60 separate bony parts were evaluated. Diagnoses were confirmed by clinical correlation. Finally, sensitivity, specificity and diagnostic accuracy of STIR sequence and contrast-enhanced images were compared. Moreover, the effect of addition of T1W image findings to STIR sequence was evaluated.
Conclusion: This study was performed to suggest a pulse sequence that doesn’t need contrast media injection for diagnosing diabetic pedal osteomyelitis since the previous studies showed that gadolinium-based contrast media shouldn’t be applied in patients with renal failure (glomerular filtration rate<30 ml/min/1.73m2. According to the results STIR images had the same sensitivity as T1 post-contrast images; therefore, it can be concluded that contrast media injection can be avoided using this pulse sequence. The specificity of the STIR pulse sequence was lower than that of post-contrast images which was due to the lower ability of this pulse sequence to detect secondary symptoms of osteomyelitis such as cortex disruption, sinus path, and abscess. Using the T1 pre-contrast images, specificity and diagnostic accuracy increased. Finally, it can be concluded that MRI without contrast including STIR and pre-contrast T1W images is a reliable modality for the detection of osteomyelitis in suspected diabetic patients who are more prone to renal disorders.
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Mahdi Yadollahzadeh, Nader Rezaei , Mohsen Farrokhpour , Mehdi Azimi, Maedeh Barahman, Mohammad Bahadoram , Amirhossein Forouzanmehr , Seyed Ali Javad Mousavi ,
Volume 81, Issue 6 (9-2023)
Volume 81, Issue 6 (9-2023)
Abstract
Background: The realm of diagnosing intrathoracic lesions involves a spectrum of imaging methodologies, among which computed tomography (CT)-scan and magnetic resonance imaging (MRI) stand prominent. In the context of Iran, where there is no study comparing the efficacy of CT-scan and MRI for evaluating intrathoracic lesions, our study endeavors to bridge this gap. Mindful of the nuanced advantages and drawbacks inherent in each method, we aim to conduct a comprehensive comparative analysis of CT-scan and MRI in diagnosing intrathoracic lesions, focusing on patients seeking care at Firoozgar Hospital's pulmonary clinic.
Methods: Embarking on a cross-sectional exploration at Firoozgar Hospital Pulmonary Clinic in Tehran, Iran, our investigative journey unfolded between April 2020 and March 2021. Thirty patients, spanning ages 21 to 69, presenting with intra-thoracic lesions encompassing mediastinal and chest wall anomalies, underwent simultaneous CT scan and MRI examinations. In pursuit of diagnostic certainty, histopathology was ordained as the gold standard, and the ensuing results underwent meticulous scrutiny and analysis utilizing SPSS 23 statistical software.
Methods: Embarking on a cross-sectional exploration at Firoozgar Hospital Pulmonary Clinic in Tehran, Iran, our investigative journey unfolded between April 2020 and March 2021. Thirty patients, spanning ages 21 to 69, presenting with intra-thoracic lesions encompassing mediastinal and chest wall anomalies, underwent simultaneous CT scan and MRI examinations. In pursuit of diagnostic certainty, histopathology was ordained as the gold standard, and the ensuing results underwent meticulous scrutiny and analysis utilizing SPSS 23 statistical software.
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Results: Our study cohort comprised 30 patients, averaging 44.83 years (SD=12.71), with males constituting 60% of the population. Delving into the histological reports, CT-scan and MRI accurately diagnosed 25 (83.3%) and 28 (93.3%) cases, respectively, in retrospective analysis. The Kappa matching coefficient for CT-scan stood at 0.783, while for MRI, it soared to 0.912. A notable revelation surfaced as the Kappa matching coefficient for both CT-scan and MRI maintained a robust 0.783 (P<0.001 in all three cases).
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Conclusion: MRI might wield a superior diagnostic prowess compared to CT-scan in evaluating intrathoracic lesions. The robust Kappa matching coefficients endorse a substantial concordance between the two imaging modalities. The implications further beckon contemplation that, in select scenarios, the acquisition of biopsy and histopathology may prove redundant when scrutinizing intrathoracic lesions using the tandem approach of CT-scan and MRI. However, to etch these findings into the annals of medical certainty, a multicenter study endowed with a judicious sample size emerges as an imperative next step.
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