Deep learning for discrimination of active and inactive lesions in multiple sclerosis using non-contrast FLAIR MRI: A multicenter study.

BACKGROUND: Within the domain of multiple sclerosis (MS), the precise discrimination between active and inactive lesions bears immense significance. Active lesions are enhanced on T1-weighted MRI images after administration of gadolinium-based contrast agents, which brings about associated complexities. This study investigates the potential of deep learning to differentiate between active and inactive lesions in MS using non-contrast FLAIR-type MRI data, presenting a non-invasive alternative to conventional gadolinium-based MRI methods. METHODS: The dataset encompasses 9097 lesion images collected from 130 MS patients across four distinct imaging centers, with post-contrast T1-weighted images as the benchmark reference. We initially identified and labeled the lesions and carefully selected corresponding regions of interest (ROIs). These ROIs were employed as inputs for a convolutional neural network (CNN) to predict lesion status. Also, transfer learning was utilized, incorporating 12 pre-trained CNN models. Subsequently, an ensemble technique was applied to 3 of best models, followed by a systematic comparison of the results. RESULTS: Through a 5-fold cross-validation, our custom designed network exhibited an average accuracy of 85 %, a sensitivity of 95 %, a specificity of 75 %, and an AUC value of 0.90. Among the pre-trained models, ResNet50 emerged as the most effective, achieving a specificity of 58 %, an accuracy of 75 %, a sensitivity of 91 %, and an AUC value of 0.81. Our comprehensive evaluations encompassed the receiver operating characteristic curve, precision-recall curve, and confusion matrix analyses. CONCLUSION: The findings underscore the efficacy of the proposed CNN, trained on FLAIR MRI data ROIs, in accurately discerning active and inactive lesions without reliance on contrast agents. Our multicenter study of 130 patients with diverse imaging devices outperforms the other single-center studies, achieving superior sensitivity and specificity. Unlike studies using multiple modalities, our exclusive use of FLAIR images streamlines the process, and our streamlined approach, excluding conventional pre-processing, demonstrates efficiency. The external validation conducted on diverse datasets, coupled with the analysis of dilated masks, underscores the adaptability and efficacy of our custom CNN model in discerning between active and inactive lesions.

Performance comparison of different medical image fusion algorithms for clinical glioma grade classification with advanced magnetic resonance imaging (MRI).

Non-invasive glioma grade classification is an exciting area in neuroimaging. The primary purpose of this study is to investigate the performance of different medical image fusion algorithms for glioma grading purposes by fusing advanced Magnetic Resonance Imaging (MRI) images. Ninety-six subjects underwent an Apparent diffusion coefficient (ADC) map and Susceptibility-weighted imaging (SWI) MRI scan. After preprocessing, the different medical image fusion methods used to fuse ADC maps and SWI were Principal Component Analysis (PCA), Structure-Aware, Discrete Cosine Harmonic Wavelet Transform (DCHWT), Deep-Convolutional Neural network (DNN), Dual-Discriminator conditional generative adversarial network (DDcGAN), and Laplacian Re-Decomposition (LRD). The Entropy, standard deviation (STD), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and Relative Signal Contrast (RSC) were calculated for qualitative and quantitative analysis. We found high fused image quality with LRD and DDcGAN methods. Further quantitative analysis showed that RSCs in fused images in Low-Grade glioma (LGG) were significantly higher than RSCs in High-Grade glioma (HGG) with PCA, DCHWT, LRD, and DDcGAN. The Receiver Operating Characteristic (ROC) curve test highlighted that LRD and DDcGAN have the highest performance for glioma grade classification. Our work suggests using the DDcGAN and LRD networks for glioma grade classification by fusing ADC maps and SWI images.

Diagnostic Accuracy of Multiple MRI Parameters in Dealing with Incidental Thyroid Nodules.

Background: Different MRI parameters have been studied for evaluating thyroid nodules. Diffusion-weighted imaging (DWI) and T2 imaging sequences with considerable efficacy in evaluating soft tissue tumors merit further assessment for thyroid nodule investigation. Method: We evaluated incidental thyroid nodules (ITNs) reported on head and neck MRI studies. The T2 signal intensity (SI), T2 signal intensity ratio (SIR), Z value, and apparent diffusion coefficient (ADC) values of the thyroid nodule were obtained for every patient. The patients were referred to the radiology department for the thyroid nodule ultrasound study. Finally, 33 participants (37 thyroid nodules) who were scheduled for fine needle aspiration and cytology (FNAC) were enrolled. Regarding the FNAC results, the nodules were divided into malignant and benign groups. The two groups' MRI parameters were compared using a two samples independent t test, and the cutoff values were estimated by analyzing the receiver operating characteristics plot. Results: The T2 signal intensities, SIR, Z values, and ADC values were significantly higher in the benign group than malignant. The cutoff points of 230 (AUC = 0.759), 3.38 (AUC = 0.754), 37 (AUC = 0.759), and 1.73 (AUC = .690) were obtained for T2 values, SIR, Z values, and ADC values, respectively. Conclusion: T2, SIR, Z, and ADC values are reliable for discriminating benign from malignant ITNs. However, further studies with a larger sample size are needed to provide more accurate mean values, identify outliers, and reduce confounding factors and bias.

Severity of Disease and COVID-19 Complications During Hospital Stay: A Prospective Cohort Study.

BACKGROUND: COVID-19, with its high transmission and mortality rates and unknown outcomes, has become a major concern in the world. Among people with COVID-19, severe cases can quickly progress to serious complications, and even death. So, the present study aimed to examine the relationship between the severity of the disease and the outcome in patients afflicted by COVID-19 during hospitalization. METHODS: A total of 653 patients with COVID-19 aged 18 years or older were included from Khorshid hospital in Isfahan, Iran and followed for a mean of 22.72 days (median 23.50; range 1-47). Severe COVID-19 was defined by respiration rate≥30 times/min, oxygen saturation level≤88% in the resting position, and pulse rate≥130/min. The primary outcome was mortality. The secondary outcomes included need for mechanical ventilation and intensive care unit (ICU) admission. RESULTS: During 4233 person-days of follow-up, 49 (7.5%) deaths, 27 (4.1%) invasive ventilation and 89 (13.6%) ICU admissions in hospital were reported. After adjustment for potential confounders, severity of the disease was positively associated with risk of mortality, invasive ventilation and ICU admissions (hazard ratio [HR]: 5.99; 95% CI: 2.85, 12.59; P<0.001, HR: 7.09; 95% CI: 3.24, 15.52; P<0.001 and HR: 4.88; 95% CI: 2.98, 7.98; P<0.001, respectively). In addition, greater age (HR=1.04; 95% CI=1.02-1.07; P=0.002), chronic kidney disease (HR=3.05; 95% CI=1.35, 6.90; P=0.008), blood urea nitrogen (BUN) (HR=1.04; 95% CI=1.03-1.05; P<0.001) and creatinine (HR=1.44; 95% CI=1.26-1.65; P<0.001) were probably significant risk factors for mortality in severe COVID-19 patients. CONCLUSION: More intensive therapy and special monitoring should be implemented for patients with older age, hypertension and kidney disease who are infected with COVID-19 to prevent rapid worsening.

Association of systemic complications with mortality in coronavirus disease of 2019: A cohort study on intensive care unit patients.

Background: Since the beginning of the coronavirus disease of 2019 (COVID-19) pandemic, concerns raised by the growing number of deaths worldwide. Acute respiratory distress syndrome (ARDS) and extrapulmonary complications can correlate with prognosis in COVID-19 patients. This study evaluated the association of systemic complications with mortality in severely affected COVID-19 patients. Materials and Methods: This retrospective study was done on 51 intensive care unit (ICU)-admitted COVID-19 adult patients who were admitted to the ICU ward of Khorshid hospital, affiliated with Isfahan University of Medical Sciences. Only the patients who had a definite hospitalization outcome (dead vs. survivors) were included in the study. Daily clinical and paraclinical records were used to diagnose in-hospital complications in these patients. Results: The sample was comprised of 37 males (72.5%) and 14 females (27.4%). The median age of patients was 63 years (Min: 20, Max: 84), with the mortality rate of 47.1%. In total, 70.6% of patients had at least one coexisting disorder. Chronic kidney disease was associated with the worse outcome (29.16% of dead patients against 3.70 of survived ones). Mechanical ventilation was used in 58.8% of patients. Patients who had received invasive ventilation were more likely to die (87.50% of dead patients against 7.40 of survivors), Complications including sepsis and secondary infections (odds ratio: 8.05, confidence interval: 2.11-30.63) was the strongest predictors of mortality. Conclusion: Complications including sepsis and secondary infections can increase the risk of death in ICU-admitted COVID-19 patients. Therefore, it is substantial that the physicians consider preventing or controlling these complications.

Chest Computed Tomography Severity Score to Predict Adverse Outcomes of Patients with COVID-19.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) continues to wreak havoc worldwide. This study assessed the ability of chest computed tomography (CT) severity score (CSS) to predict intensive care unit (ICU) admission and mortality in patients with COVID-19 pneumonia. MATERIALS AND METHODS: A total of 192 consecutive patients with COVID-19 pneumonia aged more than 20 years and typical CT findings and reverse-transcription polymerase chain reaction positive admitted in a tertiary hospital were included. Clinical symptoms at admission and short-term outcome were obtained. A semi-quantitative scoring system was used to evaluate the parenchymal involvement. The association between CSS, disease severity, and outcomes were evaluated. Prediction of CSS was assessed with the area under the receiver-operating characteristic (ROC) curves. RESULTS: The incidence of admission to ICU was 22.8% in men and 14.1% in women. CSS was related to ICU admission and mortality. Areas under the ROC curves were 0.764 for total CSS. Using a stepwise binary logistic regression model, gender, age, oxygen saturation, and CSS had a significant independent relationship with ICU admission and death. Patients with CSS ≥12.5 had about four-time risk of ICU admission and death (odds ratio 1.66, 95% confidence interval 1.66 - 9.25). The multivariate regression analysis showed the superiority of CSS over other clinical information and co-morbidities. CONCLUSION: CSS was a strong predictor of progression to ICU admission and death and there was a substantial role of non-contrast chest CT imaging in the presence of typical features for COVID-19 pneumonia as a reliable predictor of clinical severity and patient's outcome.

Risk factors associated with intensive care unit (ICU) admission and in-hospital death among adults hospitalized with COVID-19: a two-center retrospective observational study in tertiary care hospitals.

BACKGROUND: The COVID-19 pandemic is straining the health care systems worldwide. Therefore, health systems should make strategic shifts to ensure that limited resources provide the highest benefit for COVID-19 patients. OBJECTIVE: This study aimed to describe the risk factors associated with poor in-hospital outcomes to help clinicians make better patient care decisions. MATERIAL AND METHODS: This retrospective observational study enrolled 176 laboratory-confirmed COVID-19 patients. Demographic characteristics, clinical data, lymphocyte count, CT imaging findings on admission, and clinical outcomes were collected and compared. Two radiologists evaluated the distribution and CT features of the lesions and also scored the extent of lung involvement. The receiver operating characteristic (ROC) curve was used to determine the optimum cutoff point for possible effective variables on patients' outcomes. Multivariable logistic regression models were used to determine the risk factors associated with ICU admission and in-hospital death. RESULT: Thirty-eight (21.5%) patients were either died or admitted to ICU from a total of 176 enrolled ones. The mean age of the patients was 57.5 ± 16.1 years (males: 61%). The best cutoff point for predicting poor outcomes based on age, CT score, and O2 saturation was 60 years (sensitivity: 71%, specificity: 62%), 10.5 (sensitivity: 73%, specificity: 58%), and 90.5% (sensitivity: 73%, specificity: 59%), respectively. CT score cutoff point was rounded to 11 since this score contains only integer numbers. Multivariable-adjusted regression models revealed that ages of ≥ 60 years, CT score of ≥ 11, and O2 saturation of ≤ 90.5% were associated with higher worse outcomes among study population (odds ratio (OR): 3.62, 95%CI: 1.35-9.67, P = 0.019; OR: 4.38, 95%CI: 1.69-11.35, P = 0.002; and OR: 2.78, 95%CI: 1.03-7.47, P = 0.042, respectively). CONCLUSION: The findings indicate that older age, higher CT score, and lower O2 saturation could be categorized as predictors of poor outcome among COVID-19-infected patients. Other studies are required to prove these associations.

Is High Preprocedural Renal Resistive Index Sensitive Enough to Predict Iodine Contrast-Induced Nephropathy in Patients Receiving Intra-Arterial Iodinate Contrast?

PURPOSE: Renal Resistive Index (RRI) is a newly introduced sonographic index in predicting contrast-induced nephropathy (CIN) development. It has been suggested that RRI > 0.69 should be considered as a risk factor for CIN development. The present study aimed to calculate the predictive value of RRI using a cutoff point of 0.69. METHODS: A total of 90 patients who were a candidate for coronary vessels angiography were enrolled in this study. Color Doppler ultrasonography was performed and RRI was measured. Patients were followed up for 48 hours after contrast media exposure for the CIN development. The diagnosis of CIN was based on a 25% relative rise or 0.5 mg/dL absolute rise in creatinine level. The predictive values of RRI were measured using 0.69 as a cutoff point. RESULTS: Out of 90 patients, CIN developed in 3 patients and 17 patients had preprocedural RRI > 0.69. Of 3 patients with CIN, 1 had RRI > 0.69. Using 0.69 as the cutoff point, the measured sensitivity and specificity of RRI were 33.3% and 83.9%, respectively. CONCLUSIONS: RRI > 0.69 is not a sensitive index in predicting the CIN development and cannot be used as an independent factor.

The value of thoracic computed tomography scan comparing to reverse transcription-polymerase chain reaction for the diagnosis of COVID-19.

BACKGROUND: Novel coronavirus disease of 2019 (COVID-19) is the current pandemic causing massive morbidity and mortality worldwide. The gold standard diagnostic method in use is reverse transcription-polymerase chain reaction (RT-PCR) which cannot be solely relied upon. Computed tomography (CT) scan is a method currently used for diagnosis of lung disease and can play a substantial role if proved helpful in COVID-19 diagnosis. We conducted this study to evaluate the diagnostic value of CT scan compared to RT-PCR in the diagnosis of COVID-19. MATERIALS AND METHODS: We recruited 291 hospitalized patients suspicious of COVID-19 according to typical clinical findings during February-March 2020. The patients underwent CT-scan and RT-PCR procedures on the day of hospital admission. CT scans were reported by two radiologists as typical, indeterminate, negative, and atypical. Statistical indices were calculated twice: once considering "typical" and "indeterminate" categories as positive and the other time counting "typical" results as positive. RESULTS: The CT reports were classified as typical (64.95%), indeterminate (10.31%), atypical (11%), and negative (13.75%). Considering "typical" and "intermediate" as positive, sensitivity and specificity were 85.3% and 38.8%, respectively, and using the second assumption, the mentioned indices were 75.9% and 50.4%, respectively. CONCLUSION: According to our study, CT results do not create enough diagnostic benefit and could result in incorrect confidence if negative. Since widely available, CT integration in the clinical process may be helpful in screening of suspected patients in epidemics. Yet, suspected patients should be isolated till confirmed by (multiple) PCRs.

A review of glioblastoma tumors with primitive neuronal component and a case report of a patient with this uncommon tumor at a rare location.

Glioblastoma with primitive neuronal component should be considered as a differential diagnosis of infratentorial tumors.

A one-year hospital-based prospective COVID-19 open-cohort in the Eastern Mediterranean region: The Khorshid COVID Cohort (KCC) study.

The COVID-19 is rapidly scattering worldwide, and the number of cases in the Eastern Mediterranean Region is rising. Thus, there is a need for immediate targeted actions. We designed a longitudinal study in a hot outbreak zone to analyze the serial findings between infected patients for detecting temporal changes from February 2020. In a hospital-based open-cohort study, patients are followed from admission until one year from their discharge (the 1st, 4th, 12th weeks, and the first year). The patient recruitment phase finished at the end of August 2020, and the follow-up continues by the end of August 2021. The measurements included demographic, socio-economics, symptoms, health service diagnosis and treatment, contact history, and psychological variables. The signs improvement, death, length of stay in hospital were considered primary, and impaired pulmonary function and psychotic disorders were considered main secondary outcomes. Moreover, clinical symptoms and respiratory functions are being determined in such follow-ups. Among the first 600 COVID-19 cases, 490 patients with complete information (39% female; the average age of 57±15 years) were analyzed. Seven percent of these patients died. The three main leading causes of admission were: fever (77%), dry cough (73%), and fatigue (69%). The most prevalent comorbidities between COVID-19 patients were hypertension (35%), diabetes (28%), and ischemic heart disease (14%). The percentage of primary composite endpoints (PCEP), defined as death, the use of mechanical ventilation, or admission to an intensive care unit was 18%. The Cox Proportional-Hazards Model for PCEP indicated the following significant risk factors: Oxygen saturation < 80% (HR = 6.3; [CI 95%: 2.5,15.5]), lymphopenia (HR = 3.5; [CI 95%: 2.2,5.5]), Oxygen saturation 80%-90% (HR = 2.5; [CI 95%: 1.1,5.8]), and thrombocytopenia (HR = 1.6; [CI 95%: 1.1,2.5]). This long-term prospective Cohort may support healthcare professionals in the management of resources following this pandemic.

Interobserver and intraobserver variability in magnetic resonance imaging evaluation of patients with suspected disc herniation.

OBJECTIVE: Magnetic resonance imaging (MRI) is usually the modality of choice to assess sciatica and intervertebral disc herniation. Despite remarkable progression in diagnostic imaging and surgical techniques, definite diagnosis based on imaging interpretation is still a great challenge. The aim of this study was to determine interobserver and intraobserver variability in reporting lumbar MRI between two neuroradiologists based on the new 2014 version of disc nomenclature. PATIENTS AND METHODS: The study population was composed of 134 irresponsive to conservative therapy patients with clinical presentations of disc herniation and lumbar radiculopathy. MRI was taken from all the participants using a 1.5 T MRI system. Two neuroradiologists evaluated the images, separately and one of them did it twice and interpreted the scans in sagittal and axial planes. Disc bulge, disc herniation and nerve root compression were evaluated at each level. Interobserver and interaobserver agreements between two neuroradiologists, and one neuroradiologist in two times of reporting were calculated for the evaluation of bulging and herniated discs and nerve root compression by applying the Kappa statistics. RESULTS: Bulging disc, herniated disc, the type of disc, location of the discs, and nerve root compression diagnosis were significantly in excellent agreement (kappa>0.7, p-value<0.001) through intraobserver assessments, while interobserver assessments presented statistically significant with a fair agreement (kappa:0.4-0.7 and p-value<0.05). CONCLUSION: Remarkable intraobserver agreement was found between diagnoses of disc-related pathologies of the lumbar spine while interobserver assessments revealed only fair concordance.

Associations between bone mineral density, trabecular bone score, and body mass index in postmenopausal females.

OBJECTIVES: Bone mineral density (BMD), as a gold standard determinant of osteoporosis, assesses only one of many characteristics contributing to the bone. Trabecular bone score (TBS) is applied to evaluate the microarchitecture of trabecular bone. A high body mass index (BMI) has been reported to have a positive correlation with BMD. However, the relation between BMI and TBS has remained unclear. Therefore, the aim of this study is to shed light on the associations between BMI, T-score, and TBS in postmenopausal women without a diagnosed underlying disease. METHODS: In this cross-sectional study, 1054 postmenopausal women were randomly recruited from the Department of Radiology, Isfahan University of Medical Sciences. Demographic characteristics and medical history of all subjects were collected from documents. TBS measurements for L1-L4 vertebrae were retrospectively performed by the TBS iNsight software using the dual X-ray absorptiometry (DXA) from the same region of spine of the subjects. The analysis was done to detect the correlation between TBS and BMI. RESULTS: A statistically significant negative correlation was found between TBS and BMI in patients with osteoporosis and low bone mass. In patients with normal T-scores, BMI was not significantly correlated to TBS (P > 0.05). Furthermore, there was a significant positive association between T-score and BMI. CONCLUSIONS: Although a higher BMI had a protective effect against osteoporosis, higher BMI was associated with a lower TBS in patients with an abnormal T-score. However, BMI did not have a significant effect on TBS in patients with normal T-scores.

The assessment of acute pulmonary embolism severity using CT angiography features.

BACKGROUND: This study was conducted to detect the association between radiologic features of CT pulmonary angiography (CTPA) and pulmonary embolism severity index (PESI). METHODS: A total of 150 patients with a definite diagnosis of PE entered the study. The CTPA feature including obstruction index, pulmonary trunk size, presence of backwash contrast, septal morphology, right ventricular (RV) and left ventricular (LV) dimensions, and RV/LV ratio were examined. The severity of the PE was estimated using PESI. The association between CTPA indices and PESI was measured. Statistical analysis was conducted using the SPSS software. P value < 0.05 was considered as statistically significant. RESULTS: A positive correlation was detected between the obstruction index and PESI (r = 0.45, P < 0.05). Moreover, PESI was significantly higher in patients with a more dilated pulmonary trunk (r = 0.20, P < 0.05). The backwash contrast and abnormal septal morphology were significantly more common among patients with higher PESI (P < 0.05). However, no significant correlation was detected between RV, LV, RV/LV, and PESI. The most predictor of high-risk PE was dilated pulmonary trunk with an odds ratio of 4.4. CONCLUSION: Higher Obstruction index, dilated pulmonary trunk, presence of backwash contrast, and an abnormal septal morphology can be associated with a higher PESI.

A study on bone mass density using dual energy X-ray absorptiometry: Does high body mass index have protective effect on bone density in obese patients?

BACKGROUND: Osteoporosis is known as reduction of bone density, which is diagnosed using dual-energy X-ray absorptiometry. Although some studies have shown high body mass index (BMI) as a protective factor for osteoporosis and fracture risks, some other studies demonstrated obesity as a risk factor for osteoporosis. The aim of this study is to evaluate the relationship between BMI and bone mineral density (BMD) in premenopausal and postmenopausal females. Furthermore, we determined the correlation between BMI and fracture risk in postmenopausal females. MATERIALS AND METHODS: In this study, we evaluated the relationship between the age and BMI with 10-year probability fracture risk (estimated using fracture risk assessment tool) and BMD in the L1-L4 spine and femoral neck. Data were collected from BMD center, Askariye Hospital, Isfahan, Iran, from May 2016 to July 2017. RESULTS: The study consisted of 1361 individuals, including 305 premenopausal females and 1056 postmenopausal females. The results showed a statistically significant increase of BMD (P < 0.001) and a decrease of fracture risk (ß = -0.158, R 2 = 0.518) with an increase of BMI in postmenopausal females. Moreover, lumbar spine and femoral neck BMD were significantly higher in individuals with BMI ≥30 than in those with BMI <25 in both premenopausal and postmenopausal females (P < 0.001). In addition, older postmenopausal females indicated significantly lower L1-L4 BMD (r = -0.280, P < 0.05) and femoral neck BMD (r = -0.358, P < 0.05). CONCLUSION: The results showed a positive correlation between BMI and BMD of the spine and femoral neck which did not differ by menopausal status. However, there was a correlation between BMI and fracture risk in postmenopausal females.

Prediction of thyroid nodule malignancy using thyroid imaging reporting and data system (TIRADS) and nodule size.

OBJECTIVES: Thyroid imaging reporting and data system (TIRADS) is a combination of ultrasonographic features developed to help physicians in predicting the malignancy risk of thyroid nodules based on sonographic characteristics. Thyroid nodule size is another factor in determining whether a nodule is malignant. The aim of this study was detecting the predictive value of TIRADS and nodule size based on Bethesda classification in prognostication of malignancy. METHODS: This was a cross-sectional study of 239 patients with thyroid nodules. The patients underwent ultrasonography using TIRADS classification and FNA biopsy based on Bethesda categorization. The results were analyzed using SPSS with the cut off points and predictive values measured. RESULTS: TIRADS ≥4 could detect malignant nodules with a sensitivity of 91.67% and specificity of 52.8%. An inverse relationship was observed between nodule size and malignancy risk and cutoff point of 12 mm was found for detecting malignant nodules. CONCLUSIONS: Thyroid nodules with TIRADS 4 and 5 and diameter lower than 12 mm, are highly suspicious for malignancy and should be considered as indications for fine needle aspiration biopsy. ADVANCES IN KNOWLEDGE: The study suggests TIRADS and thyroid nodule size as sensitive predictors of malignancy.

Are cerebral veins hounsfield unit and H: H ratio calculating in unenhanced CT eligible to diagnosis of acute cerebral vein thrombosis?

BACKGROUND: For both the clinician and a radiologist, the diagnosis of cerebral venous sinus thrombosis (CVST), because of the variety of signs and symptoms, remains a challenge. In this study, the role of unenhanced brain computed tomography (CT) in the diagnosis of CVST was assessed. MATERIALS AND METHODS: In this case-control study, unenhanced CT of 35 patients with acute CVST was compared with 70 normal patients. Hematocrit (HCT), creatinine, and blood urea nitrogen were recorded in all patients. CT images were read, and the attenuation was measured by two independent experienced radiologists. The H:H ratio was calculated for all patients in both case and control groups to normalized densities regarding HCT. RESULTS: The mean of attenuation in patients was 66.95 ± 10.63 Hounsfield unit (HU) and in the controls was 52.51 ± 2.92 HU (P < 0.0001). The mean of H:H ratio in patients was 1.78 ± 0.40 and in controls was 1.46 ± 0.28 (P < 0.0001). Attenuation >60.4 HU was the best optimal cutoff with area under the curve of 0.918 (0.848-0.962) and had 71.4% sensitivity and 100% specificity. H:H ratio >1.42 as the optimal cutoff had 94.3% sensitivity and 54.3% specificity for identifying the CVST. CONCLUSION: Attenuation value >60.4 HU and H: H ratio >1.42 calculated based on unenhanced CT can be used as reliable methods to detect CVST in the absence of magnetic resonance imaging and magnetic resonance venography in the emergency setting.

Quantitative diagnosis of osteoporosis using lumbar spine signal intensity in magnetic resonance imaging.

OBJECTIVE: Osteoporosis is the most common metabolic bone disease that is not recognized in many elderly people. To determine the cause of low back pain, lumbosacral MRI is done for a large population who may not have gone under dual energy X-ray absorptiometry (DXA). The aim of this study was to predict bone density using lumbar spine signals in lumbosacral MRI in high risk patients for osteoporosis including post-menopausal females and calculate a threshold for a new quantitative MRI-based score to be used in estimation of lumbar spine bone mass density. METHODS: 82 menopaused females, who had undergone DXA before, were selected and MRI was done within 6 months after DXA. 69 healthy females aged 20-29 years who had undergone lumbar MRI were selected as reference group. Results were analyzed and threshold and diagnostic performance of MRI-based score (M-score) on the method of T-score was calculated. RESULTS: Negative correlation between M-score and T-score was detected. Cut off point of 2.05 was found for M-score with near sensitivity of 90% and specificity of 87% for detecting osteoporotic patients from non-osteoporotic individuals. CONCLUSION: M-score is a MRI-based method which can identify patients at risk of osteoporosis. Early diagnosis of osteoporosis can reduce morbidity and mortality caused by it. ADVANCES IN KNOWLEDGE: The research introduced cut of points for M-score as a new MRI quantitative method to be used as an opportunistic technique for detecting osteoporotic patients.

Radiological Evaluation of the Styloid Process Length Using 64-row Multidetector Computed Tomography Scan.

BACKGROUND: As elongated styloid process is one of the causes of recurrent oropharyngeal pain and carotid nerve plexus compression called Eagle's syndrome and this length is not similar in different communities, the aim of the current study is to determine average length of styloid process by paranasal multidetector computed tomography. MATERIALS AND METHODS: This is a retrospective cross-sectional study about 393 patients who underwent paranasal MDCT scan for trauma in Radiology Department without pathologic finding. Styloid length from temporal bone junction to tip of the process was measured using Workstation software. Demographic data including age, sex, and height were gathered from the patients' records, and patients were questioned about symptoms of Eagle's syndrome before trauma. Data were analyzed using SPSS version 20 with the methods of t-test, Chi-square, and ANOVA. P < 0.05 was considered statistically significant. RESULTS: Two-hundred and sixteen males and 177 females underwent MDCT. The length of right, left, and mean length of both sides were 25.4 ± 7.3, 25.2 ± 7.8, 25.3 ± 7.1, respectively. The mean length of both sides' process was more among male that was statistically significant (P = 0.025 and 0.043, respectively). Right and left side styloid process' higher length was in correlation with patient's height (P = 0.002, r = 0.153, P = 0.029, r = 0.110, respectively) and number of symptoms (P < 0.001, r = 0.300, P < 0.001, r = 0.334, respectively). CONCLUSION: The mean length of styloid process was 25.3 ± 7.1 that was in accordance with some studies and different from others. Styloid process length is higher in males. The length of styloid process is in association with height and number of symptoms as well.