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Background. The effects of oligopin as an antioxidant on polycystic ovarian morphology (PCOM) have not yet been examined. Therefore, the objective of this study was to evaluate the oligopin supplementation on PCOM among patients with polycystic ovarian syndrome (PCOS). Methods. This randomized, placebo‐controlled trial was carried out at Shariati Hospital, Arash Hospital, and Yas Hospital, Tehran, Iran, to determine the effect of oligopin (50 mg/d) or placebo in PCOS patients. The ultrasonographic ovarian morphology was assessed in women aged 18–40 years, before and after 3 months of intervention. Results. Among 45 randomized participants, 32 participants, of whom 17 were in the oligopin group and 15 were in the placebo group completed the trial. There was only one adverse event in the oligopin group. The mean (standard deviation) age of the patients was 30.47 (6.30) years and the median (interquartile range) BMI was 27.50 (23.42–33.55). Three months of oligopin therapy significantly decreased ovarian stromal area (p = 0.01) and stromal/total area (p = 0.003). However, no significant differences were observed in the ovarian volume, ovarian area, 2–9 mm antral follicle counts, or peripheral follicle distribution pattern at 3 months. Conclusion. Among participants with PCOS, the use of oligopin (50 mg) daily, as compared with a placebo, resulted in improvement of the stromal area and stromal/total area at the end of the 3 months of treatment. Further studies are, however, needed to evaluate the longer‐term efficacy and safety. This trial is registered with IRCT20140406017139N3. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence (AI)-aided analysis of chest CT expedites the quantification of abnormalities and may facilitate the diagnosis and assessment of the prognosis of subjects with COVID-19. Objectives: This study investigates the performance of an AI-aided quantification model in predicting the clinical outcomes of hospitalized subjects with COVID-19 and compares it with radiologists' performance. Subjects and methods: A total of 90 subjects with COVID-19 (men, n = 59 [65.6%]; age, 52.9±16.7 years) were recruited in this cross-sectional study. Quantification of the total and compromised lung parenchyma was performed by two expert radiologists using a volumetric image analysis software and compared against an AI-assisted package consisting of a modified U-Net model for segmenting COVID-19 lesions and an off-the-shelf U-Net model augmented with COVID-19 data for segmenting lung volume. The fraction of compromised lung parenchyma (%CL) was calculated. Based on clinical results, the subjects were divided into two categories: critical (n = 45) and noncritical (n = 45). All admission data were compared between the two groups. Results: There was an excellent agreement between the radiologist-obtained and AI-assisted measurements (intraclass correlation coefficient = 0.88, P < 0.001). Both the AI-assisted and radiologist-obtained %CLs were significantly higher in the critical subjects (P = 0.009 and 0.02, respectively) than in the noncritical subjects. In the multivariate logistic regression analysis to distinguish the critical subjects, an AI-assisted %CL ≥35% (odds ratio [OR] = 17.0), oxygen saturation level of <88% (OR = 33.6), immunocompromised condition (OR = 8.1), and other comorbidities (OR = 15.2) independently remained as significant variables in the models. Our proposed model obtained an accuracy of 83.9%, a sensitivity of 79.1%, and a specificity of 88.6% in predicting critical outcomes. Conclusions: AI-assisted measurements are similar to quantitative radiologist-obtained measurements in determining lung involvement in COVID-19 subjects. [ABSTRACT FROM AUTHOR]

Context: Idiopathic granulomatous mastitis (IGM) is a benign inflammatory condition of the breasts with an unknown etiology, which can mimic breast cancer on conventional ultrasound. Other imaging modalities, such as mammography and magnetic resonance imaging, cannot efficiently differentiate this condition from malignancies. Elastography is a novel imaging technique used to evaluate tissue elasticity. Objectives: This systematic reviewaimed to investigate the imaging features of IGMonelastography and also to determinewhether thismodality is useful for distinguishing IGMfromother breastmalignancies. Materials and Methods: A comprehensive literature search was conducted across several databases, including Medline, Embase, Cochrane Library, Scopus, andWeb of Science, in October 2022. The Joanna Briggs Institute (JBI) critical appraisal tool was used for the quality assessment of the studies. Results: After screening 851 articles, seven studies investigating ultrasound elastographywere found tomeet the inclusion criteria. Regarding the quantitative findings, both the strain ratio and shear wave velocity were observed to be higher inmalignantmasses as compared to IGM. Additionally, qualitative scoring systems, such as the Tsukuba and Tozaki classifications, assigned higher scores to malignant lesions. Five of the included studies in this review proposed a specific cut-off point for differentiating IGM frommalignancies, using either shear wave velocity, strain ratio, or elasticity scores. In four of the studies, these criteria exhibited sensitivity and specificity of approximately 90%. Conclusion: The current findings suggest that ultrasound elastography can serve as a valuable tool for distinguishing IGM from breastmalignancies. By potentially reducing the number of unnecessary tissue biopsies, thismodalitymay lead to amore efficient patient evaluation process. [ABSTRACT FROM AUTHOR]

Purpose To compare lung volume, lung apparent diffusion coefficient (ADC) and signal intensity ratio (SIR) on different magnetic resonance imaging (MRI) sequences between intrauterine growth restriction (IUGR) fetuses and the control group. Materials and methods 49 IUGR and 58 non-IUGR fetuses were imaged using 3 Tesla MRI units. Total lung volume (TLV), lung/liver SIR (LLSIR) and lung/muscle SIR (LMSIR) in T1 and T2-weighted sequences and lung/liver ADC ratio (LLADCR) and lung/muscle ADC ratio (LMADCR) were assessed. Results LLSIR and LMSIR were significantly higher in the T1-weighted sequence (p-value: .03) and LLADCR and LMADCR were significantly lower on diffusion-weighted imaging (DWI) in IUGR fetuses compared to the control group (p-value: .01). There was no significant difference in SIRs in the T2-weighted sequence between the two groups. Although TLV was increased with gestational age in both groups, it was significantly lower in the IUGR group (mean: 82 ± 22.7 ml vs. 110.8 ± 18 ml, p-value: <.001). Conclusion The T1-weighted sequence and DWI seem to be better than the T2-weighted sequence for assessing the faint difference of lung maturity between groups. However, SIR differences were not as meaningful as TLV differences and this could be related to the complex maturation process in IUGR fetuses as the effect of higher endogenous corticosteroids. [ABSTRACT FROM AUTHOR]

Purpose: To compare lung volume, lung apparent diffusion coefficient (ADC) and signal intensity ratio (SIR) on different magnetic resonance imaging (MRI) sequences between intrauterine growth restriction (IUGR) fetuses and the control group.Materials and Methods: 49 IUGR and 58 non-IUGR fetuses were imaged using 3 Tesla MRI units. Total lung volume (TLV), lung/liver SIR (LLSIR) and lung/muscle SIR (LMSIR) in T1 and T2-weighted sequences and lung/liver ADC ratio (LLADCR) and lung/muscle ADC ratio (LMADCR) were assessed.Results: LLSIR and LMSIR were significantly higher in the T1-weighted sequence (p-value: .03) and LLADCR and LMADCR were significantly lower on diffusion-weighted imaging (DWI) in IUGR fetuses compared to the control group (p-value: .01). There was no significant difference in SIRs in the T2-weighted sequence between the two groups. Although TLV was increased with gestational age in both groups, it was significantly lower in the IUGR group (mean: 82 ± 22.7 ml vs. 110.8 ± 18 ml, p-value: <.001).Conclusion: The T1-weighted sequence and DWI seem to be better than the T2-weighted sequence for assessing the faint difference of lung maturity between groups. However, SIR differences were not as meaningful as TLV differences and this could be related to the complex maturation process in IUGR fetuses as the effect of higher endogenous corticosteroids. [ABSTRACT FROM AUTHOR]

Ultrasound (US) and magnetic resonance imaging (MRI) are two modalities for diagnosing fetal gastrointestinal (GI) anomalies. Ultrasound (US) is the modality of choice. MRI can be used as a complementary method. Despite its expanding utilization in central nervous system (CNS) fetal malformation, MRI has not yet been established for evaluation of fetal GI abnormalities. Therefore, more attention should be paid to the clinical implications of MRI investigations following screening by US. [ABSTRACT FROM AUTHOR]

Ultrasound (US) and magnetic resonance imaging (MRI) are two modalities for diagnosing fetal gastrointestinal (GI) anomalies. Ultrasound (US) is the modality of choice. MRI can be used as a complementary method. Despite its expanding utilization in central nervous system (CNS) fetal malformation, MRI has not yet been established for evaluation of fetal GI abnormalities. Therefore, more attention should be paid to the clinical implications of MRI investigations following screening by US. [ABSTRACT FROM AUTHOR]

Background: Chest computed tomography (CT) scan is one of the most common tools used for the diagnosis of patients with coronavirus disease 2019 (COVID-19). While segmentation of COVID-19 lung lesions by radiologists can be time-consuming, the application of advanced deep learning techniques for automated segmentation can be a promising step toward the management of this infection and similar diseases in the future. Objectives: This study aimed to evaluate the performance and generalizability of deep learning-based models for the automated segmentation of COVID-19 lung lesions. Patients and Methods: Four datasets (2 private and 2 public) were used in this study. The first and second private datasets included 297 (147 healthy and 150 COVID-19 cases) and 82 COVID-19 subjects. The public datasets included the COVID19-P20 (20 COVID-19 cases from 2 centers) and the MosMedData datasets (50 COVID-19 patients from a single center). Model comparisons were made based on the Dice similarity coefficient (DSC), receiver operating characteristic (ROC) curve, and area under the curve (AUC). The predicted CT severity scores by the model were compared with those of radiologists by measuring the Pearson's correlation coefficients (PCC). Also, DSC was used to compare the inter-rater agreement of the model and expert against that of 2 experts on an unseen dataset. Finally, the generalizability of the model was evaluated, and a simple calibration strategy was proposed. Results: The VGG16-UNet model showed the best performance across both private datasets, with a DSC of 84.23% ± 1.73% on the first private dataset and 56.61% ± 1.48% on the second private dataset. Similar results were obtained on public datasets, with a DSC of 60.10% ± 2.34% on the COVID19-P20 dataset and 66.28% ± 2.80% on a combined dataset of COVID19-P20 and MosMedData. The predicted CT severity scores of the model were compared against those of radiologists and were found to be 0.89 and 0.85 on the first private dataset and 0.77 and 0.74 on the second private dataset for the right and left lungs, respectively. Moreover, the model trained on the first private dataset was examined on the second private dataset and compared against the radiologist, which revealed a performance gap of 5.74% based on DSCs. A calibration strategy was employed to reduce this gap to 0.53%. Conclusion: The results demonstrated the potential of the proposed model in localizing COVID-19 lesions on CT scans across multiple datasets; its accuracy competed with the radiologists and could assist them in diagnostic and treatment procedures. The effect of model calibration on the performance of an unseen dataset was also reported, increasing the DSC by more than 5%. [ABSTRACT FROM AUTHOR]

Background: The Radiologic Society of North America (RSNA) divides patients into four sections: negative, atypical, indeterminate, and typical coronavirus disease 2019 (COVID-19) pneumonia based on their computed tomography (CT) scan findings. Herein, we evaluate the frequency of the chest CT-scan appearances of COVID-19 according to each RSNA categorical group. Methods: A total of 90 patients with real-time reverse transcriptase-polymerase chain reaction (RT-PCR)-confirmed COVID-19 were enrolled in this study and differences in age, sex, cardiac characteristics, and imaging features of lung parenchyma were evaluated in different categories of RSNA classification. Results: According to the RSNA classification 87.8, 5.56, 4.44, and 2.22% of the patients were assigned as typical, indeterminate, atypical, and negative, respectively. The proportion of "atypical" patients was higher in the patients who had mediastinal lymphadenopathy and pleural effusion. Moreover, ground-glass opacity (GGO) and consolidation were more pronounced in the lower lobes and left lung compared to the upper lobes and right lung, respectively. While small nodules were mostly seen in the atypical group, small GGO was associated with the typical group, especially when it is present in the right lung and indeterminate group. Conclusion: Regardless of its location, non-round GGO is the most prevalent finding in the typical group of the RSNA classification systems. Mediastinal lymphadenopathy, pleural effusion, and small nodules are mostly observed in the atypical group and small GGO in the right lung is mostly seen in the typical group. [ABSTRACT FROM AUTHOR]

Thalamus is an important neuro-anatomic structure in the brain. In this paper, an automated method is presented to segment thalamus from magnetic resonance images (MRI). The method is based on a discrete dynamic contour model that consists of vertices and edges connecting adjacent vertices. The model starts from an initial contour and deforms by external and internal forces. Internal forces are calculated from local geometry of the model and external forces are estimated from desired image features such as edges. However, thalamus has low contrast and discontinues edges on MRI, making external force estimation a challenge. The problem is solved using a new algorithm based on fuzzy C-means (FCM) unsupervised clustering, Prewitt edge-finding filter, and morphological operators. In addition, manual definition of the initial contour for the model makes the final segmentation operator-dependent. To eliminate this dependency, new methods are developed for generating the initial contour automatically. The proposed approaches are evaluated and validated by comparing automatic and radiologist's segmentation results and illustrating their agreement. Index Terms--Clustering, dynamic contours, image processing, magnetic resonance imaging (MRI), segmentation, thalamus.

Objectives: This study aimed to find the difference in the values of the cranial base angles among Iranian adults and investigate the relationship between the Basal and Sphenobasion angles. Methods: 100 individuals (50 males and 50 females) aged between 18 to 60 participated in this cross-sectional study which was carried out from September 2018 to September 2019 in the imaging centers affiliated with the Faculty of Medicine, Tehran University of Medical Sciences and Basal and Sphenobasion angles were measured in all of the participants. Results: A significant correlation was observed between age and Sphenobasion angle in the male group (P = 0.0001, r = 0.439), but no positive relation was observed between Sphenobasion angle and age in the female group (P = 0.309). The results of this study exhibited the significant relations between the Basal and Sphenobasion angles in the females and males (P = 0.001, r = 0.396 and P = 0.0001, r = 0.534 respectively). Conclusion: This study showed positive correlations between the Basal angle and age in the females and males and significant relations between the Basal and Sphenobasion angles in the two genders. [ABSTRACT FROM AUTHOR]

Background: Breast microcalcifications are a category of lesions that can lead to malignancies. They remain a major concern in imaging of suspected cases. Vacuum-assisted biopsy (VAB) has been proposed as a safe and effective measure to evaluate microcalcifications. Objectives: The present study aimed to assess the results of VAB for breast microcalcifications. Patients and Methods: This cross-sectional study was conducted on patients with microcalcifications detected on mammograms. Patients were recruited through simple random sampling during 2019 - 2020, based on the inclusion criteria. The inclusion criteria were microcalcifications on mammography, classified as the breast imaging-reporting and data system (BI-RADS) categories 3, 4B, 4C, and 5, and undergoing mammography-guided VAB for the microcalcifications. Patients with missing data and those who could not be followed-up for at least six months were excluded from the study. They were assessed regarding different imaging characteristics of lesions, including the breast density, BI-RADS classification, microcalcification distribution and morphology, and other demographic and clinical features before biopsy. Additionally, the results of stereotactic-guided VAB were assessed for various benign and malignant pathologies of microcalcifications. The results of descriptive and analytical tests for various radiological and pathological features of lesions were reported. Results: A total of 257 patients, with a mean age of 50.3 ± 8.3 yars, were included in this study. Almost half of the patients (n = 125, 48.6%) had a C-grade breast composition. Regarding the BI-RADS classification, 206 (80.2%) patients were diagnosed with 4B lesions, followed by 44 (17.1%) patients with 4C lesions. The assessment of the pattern of microcalcification distribution in imaging showed that more than half of the patients (n = 148, 57.6%) had lesions in multiple groups. The most prevalent morphology of microcalcifications was punctate amorphous (n = 109, 42.4%). The majority of patients (n = 180, 70%) had benign findings in the pathological assessment, and only 69 (26.8%) had malignant features in pathology. The distribution of malignancies differedamong various BI-RADS categories. In the 4B category of lesions, there were 166 benign lesions versus 32 malignant lesions, while in the 4C category, there were 10 benign lesions versus 34 malignant lesions (P < 0.001). Conclusion: This study described the findings of successful stereotactic-guided VAB for breast microcalcifications. VAB can be implemented as a promising assessment tool to evaluate suspected breast microcalcifications effectively. [ABSTRACT FROM AUTHOR]

Background. Providing efficient care for infectious coronavirus disease 2019 (COVID-19) patients requires an accurate and accessible tool to medically optimize medical resource allocation to high-risk patients. Purpose. To assess the predictive value of on-admission chest CT characteristics to estimate COVID-19 patients' outcome and survival time. Materials and Methods. Using a case-control design, we included all laboratory-confirmed COVID-19 patients who were deceased, from June to September 2020, in a tertiary-referral-collegiate hospital and had on-admission chest CT as the case group. The patients who did not die and were equivalent in terms of demographics and other clinical features to cases were considered as the control (survivors) group. The equivalency evaluation was performed by a fellowship-trained radiologist and an expert radiologist. Pulmonary involvement (PI) was scored (0–25) using a semiquantitative scoring tool. The PI density index was calculated by dividing the total PI score by the number of involved lung lobes. All imaging parameters were compared between case and control group members. Survival time was recorded for the case group. All demographic, clinical, and imaging variables were included in the survival analyses. Results. After evaluating 384 cases, a total of 186 patients (93 in each group) were admitted to the studied setting, consisting of 126 (67.7%) male patients with a mean age of 60.4 ± 13.6 years. The PI score and PI density index in the case vs. the control group were on average 8.9 ± 4.5 vs. 10.7 ± 4.4 (p value: 0.001) and 2.0 ± 0.7 vs. 2.6 ± 0.8 (p value: 0.01), respectively. Axial distribution (p value: 0.01), cardiomegaly (p value: 0.005), pleural effusion (p value: 0.001), and pericardial effusion (p value: 0.04) were mostly observed in deceased patients. Our survival analyses demonstrated that PI score ≥ 10 (p value: 0.02) and PI density index ≥ 2.2 (p value: 0.03) were significantly associated with a lower survival rate. Conclusion. On-admission chest CT features, particularly PI score and PI density index, are potential great tools to predict the patient's clinical outcome. [ABSTRACT FROM AUTHOR]

Objectives The aim of this study was to assess whether is a reliable correlation between the cranial and gnathic angulations in the Iranian population. Methods In a cross-sectional study, 140 patients of Tehran University of Medical Sciences hospitals (70 males and 70 females with an age range of 18-60 years) were selected. Sphenoclivus (cranial base) and gnathic angles were calculated for each case. Then, the data were analyzed using SPSS version 22. Results Statistical analysis showed a relationship between gnathic angle and female (P < 0.05), but no positive relationship was seen between sphenoclivus angle and gender. There was a significant relationship between sphenoclivus angle and age among men. No significant relationship was found between the gnathic and sphenoclivus angles. Conclusion Sphenoclivus angle has the closest link with age in males. The gnathic angle has also a positive relationship with females. Our findings suggest an independent growth pattern between the sphenoclivus angle and the gnathic angle. [ABSTRACT FROM AUTHOR]

Objective: Breast cancer is responsible for most of the cancer-induced deaths in women around the world. The current review will discuss different approaches of targeting HER2, an epidermal growth factor overexpressed in 30% of breast cancer cases. Data sources: We conducted a search on Pubmed and Scopus databases to find studies relevant to HER2+ breast cancers and targeting HER2 as means of immunotherapy. Out of 1043 articles, 105 studies were included in this review. Data summary: As well as the introduction of HER2 and breast cancer subtypes, we discussed various aspects of HER2-targeting immunotherapy including monoclonal antibodies, Antibody-drug conjugates (ADCs), Chimeric Antigen Receptor (CAR) T-cells and vaccines. Conclusions: Despite several ways of controlling breast cancer, the need to investigate new drugs and approaches seems to be much significant as this cancer still has a heavy burden on people's health and survival. [ABSTRACT FROM AUTHOR]

Abstract Background Pre-operative imaging devices generate high-resolution images but intra-operative imaging devices generate low-resolution images. To use high-resolution pre-operative images during surgery, they must be deformed to reflect intra-operative geometry of brain. Methods We employ biomechanical models, guided by low resolution intra-operative images, to determine location of normal and abnormal regions of brain after craniotomy. We also employ finite element methods to discretize and solve the related differential equations. In the process, pre- and intra-operative images are utilized and corresponding points are determined and used to optimize parameters of the models. This paper develops a nonlinear model and compares it with linear models while our previous work developed and compared linear models (mechanical and elastic). Results Nonlinear model is evaluated and compared with linear models using simulated and real data. Partial validation using intra-operative images indicates that the proposed models reduce the localization error caused by brain deformation after craniotomy. Conclusions The proposed nonlinear model generates more accurate results than the linear models. When guided by limited intra-operative surface data, it predicts deformation of entire brain. Its execution time is however considerably more than those of linear models.

Objective: Breast ultrasound (BUS) is often performed as an adjunct to mammography in breast cancer screening or for evaluating breast lesions. Our aim was to design a practical and user-friendly format for BUS that could include the details of the Breast Imaging Reporting and Data System. Materials and Methods: As a team of radiologists and surgeons trained in the management of breast diseases, we gathered and carried out the project in four phases-literature search and collection of present report formats, summarizing key points and preparing the first draft, seeking expert opinion and preparing the final format, and pilot testing-followed by a survey was answered by the research team's radiologists and surgeons. Results: It produced a list of items to be stated in the BUS report, the final BUS report format, and the pilot format guide. Then, the radiologists used the format in three active ultrasound units in university-affiliated centers, and reports were referred to the surgeons. At the end of the project, the survey showed a high degree of ease of use, clarity, conciseness, comprehensiveness, and well-classified structure of the report format; but radiologists believed that the new organization took more time. Conclusion: We propose our design as a user-friendly and practical format for BUS reports. It should be used for a longer time and by various ultrasound centers in order to ascertain its benefits. [ABSTRACT FROM AUTHOR]

Background: Intrauterine growth restriction (IUGR) is a major factor in long-term perinatal morbidity and is associated with abnormal fetal brain development; however, its pattern of brain involvement remains unknown. Objectives: This study aimed to investigate the effect of IUGR on the brain parenchyma. Methods: Forty-two women with IUGR pregnancy and 28 women with normally grown fetuses at 28 - 38 weeks of pregnancy underwent 3-tesla magnetic resonance imaging (MRI). Cortical thickness was assessed in four regions and corrected by the biparietal diameter/2. Also, the whole brain surface area (WBA) was measured, and the areas of six brain regions were calculated and corrected by WBA. Results: In the IUGR group, the cortical thickness in the insula and temporal lobe was significantly thinner than the control group (0.034 vs. 0.043 and 0.036 vs. 0.047, respectively; P < 0.05); these fetuses also showed significantly reduced WBA (P = 0.028). The corrected brain areas were not significantly different between the groups, except for the corrected areas of the cerebellum and the hippocampus, which increased in the IUGRgroupas compared to the control group (0.147 vs. 0.130 and 0.017 vs. 0.0125, respectively; P< 0.05). Conclusions: In the IUGR fetuses, significantly thinner insular cortex and temporal lobe cortex and smaller WBA were found compared to the control group. Among different brain regions, the cerebellum and the hippocampus were less affected by growth restriction in the antenatal period. [ABSTRACT FROM AUTHOR]

Rationale and Objectives: Propagation-based phase-contrast CT (PB-CT) is an advanced X-ray imaging technology that exploits both refraction and absorption of the transmitted X-ray beam. This study was aimed at optimizing the experimental conditions of PB-CT for breast cancer imaging and examined its performance relative to conventional absorption-based CT (AB-CT) in terms of image quality and radiation dose.Materials and Methods: Surgically excised breast mastectomy specimens (n = 12) were scanned using both PB-CT and AB-CT techniques under varying imaging conditions. To evaluate the radiological image quality, visual grading characteristics (VGC) analysis was used in which 11 breast specialist radiologists compared the overall image quality of PB-CT images with respect to the corresponding AB-CT images. The area under the VGC curve was calculated to measure the differences between PB-CT and AB-CT images.Results: The highest radiological quality was obtained for PB-CT images using a 32 keV energy X-ray beam and by applying the Homogeneous Transport of Intensity Equation phase retrieval with the value of its parameter γ set to one-half of the theoretically optimal value for the given materials. Using these optimized conditions, the image quality of PB-CT images obtained at 4 mGy and 2 mGy mean glandular dose was significantly higher than AB-CT images at 4 mGy (AUCVGC = 0.901, p = 0.001 and AUCVGC = 0.819, p = 0.011, respectively).Conclusion: PB-CT achieves a higher radiological image quality compared to AB-CT even at a considerably lower mean glandular dose. Successful translation of the PB-CT technique for breast cancer imaging can potentially result in improved breast cancer diagnosis. [ABSTRACT FROM AUTHOR]

Background: Pseudoaneurysm of the breast is a very uncommon disease mostly occurring following traumatic injuries including biopsy. Increasing the use of core needle biopsy in breast pathologies could lead to more cases of the iatrogenic pseudoaneurysm. Case presentation: Here we described a breast pseudoaneurysm case that occurred after core needle biopsy. The diagnosis was made by color doppler ultrasonography and MRI with contrast. Ultrasound-guided compression was used to treat the lesion. The lesion was followed up with ultrasonography and finally it was resolved. Conclusion: Although hematoma is a more common complication of breast biopsy, other complications including pseudoaneurysm should be kept in mind. Ultrasound is a useful technique for both the diagnosis and non-surgical treatment of the disease. Ultrasound-guided compression and follow up exams could be helpful to prevent invasive procedures. [ABSTRACT FROM AUTHOR]

Purpose: To propose a computer-assisted method for distinguishing uterine sarcoma from leiomyomas based on perfusion weighted magnetic resonance imaging (PWI).Materials and Methods: Forty-two women confirmed to have a total of 60 masses (10 uterine sarcomas and 50 benign leiomyomas) were included. The reference diagnosis was based on postoperative histopathological examination. All women underwent the standard MRI protocol with 3-Tesla MR imager (Magnetom Trio, Siemens, Erlangen, Germany) for assessment of myometrial masses, followed by PWI. For each mass, two regions of interest (ROI) were outlined manually by an experienced radiologist; one (ROIL) represented the entire tumor while the other (ROIs) was placed on the area of the lesion with the most marked contrast enhancement. Two additional ROIs with diameters similar to ROIs (3.0 to 3.1 mm) were placed on psoas muscle (ROIP) and myometrium (ROIM) in order to provide baselines for comparisons. The obtained ROIs of PWI images were then analyzed using the DCE Tool plug-in (version 2.0SP1) within ClearCanvas (Toronto, Ontario, Canada) framework. The DCE Tool provides seven parameters (Ktrans, kep, Vb, IAUC, initial slope, peak, the mean squared error) for modelling contrast uptake within an ROI using the modified Tofts model. Parameters extracted from the ROIs were fed into a decision tree ensemble, which classified the corresponding lesions either as malignant or benign. The leave-one-out cross validation (LOOCV) was utilized to evaluate the performance of the classifier.Results: None of the parameters extracted from ROIL or ROIs differed significantly between uterine sarcoma and benign leiomyomas (all p > 0.05). The overall accuracy of 66.7% was obtained by feeding seven parameters extracted from ROIL to the classifier. When 21 features extracted from ROIL, ROIM, and ROIP were fed into the classifier an accuracy of 91.7%, sensitivity of 100%, and specificity of 90% were achieved in the optimal operating point of classifier.Conclusion: Although none of the PWI parameters differed significantly between benign and malignant lesions, when the information provided by the extracted features was aggregated using a machine learning method, a promising discriminative power was obtained. This suggests that the proposed model for combining the PWI parameters is potentially useful for differentiating uterine sarcoma from leiomyomas. [ABSTRACT FROM AUTHOR]

The purpose of this study was to retrospectively review sonographic imaging features of estrogen-negative breast cancers and compare tumors with and without human epidermal growth factor type II (HER2) overexpression. Breast sonography findings from a sample of 54 patients with estrogen-negative breast cancer as well as pathological data and HER2 status were reviewed. Sonographic features including size, depth shapes, margin, location, patterns of internal echoes, posterior echoes, orientation, and presence of halo and clinicopathologic data and imaging features were correlated with tumor HER2 status. Based on these 54 patients with estrogen-negative breast cancers, 21 patients were positive for HER2 receptor, and 33 patients were negative for HER2 receptor. Among HER2 positive cancers, irregular shape, microlobulation, indistinct margins, posterior shadowing, a thin halo, heterogeneous internal echoes, and parallel orientation were the most frequent sonographic features. No associations were found between HER-2 status and tumor size, shape, margins, posterior feature, halo, internal echoes, or orientation on sonography. [ABSTRACT FROM AUTHOR]

Introduction: Breast magnetic resonance imaging (BMRI) has been identified as a valuable modality in the diagnosis of breast cancer and monitoring the response to chemotherapy. The aim of this study was to evaluate the relative importance of different descriptors of breast masses in contrast-enhanced breast MRI.Material and Methods: In a database of pathologically proven breast lesions, in total 433 masses in 312 patients detected by contrast-enhanced breast MRI were selected. All images were assessed according to the MRI BI-RADS lexicon and those with significant positive MRI findings (BI-RADS categories 3, 4, 5) were enrolled in the study.Results: Mean age of patients was 45.09 ±10.5 years. The most frequent BI-RADS score was 4 (60.7%), followed by 3 (27%). Among the morphologic descriptors of the enhancing masses, the findings most strongly associated with malignancy included spiculated margin (60.6%) and irregular shape (38%). Considering the dynamic descriptors, a wash-out pattern in the time-intensity curve was the most powerful finding associated with malignancy (27.9%). Among all breast MRI descriptors, the best odds ratio (OR) in association with malignancy was noted for speculated margin (OR = 10.2) followed by wash-out or plateau curves (OR = 6.1), size greater than 1 cm (OR = 4.3) and irregular shape (OR = 3.1).Conclusions: It seems that morphologic descriptors of MRI BI-RADS for enhancing masses are quite specific, while dynamic descriptors of the masses are highly sensitive. Appropriate consideration and combination of different BI-RADS findings could help in better characterization of enhancing masses on breast MRI, lowering the rate of false positive reports and avoiding unnecessary biopsies. [ABSTRACT FROM AUTHOR]

Context: The most common cancer and cause of cancer-related death in pregnant and breastfeeding patients is breast cancer. In the world, the incidence of pregnancy-associated breast cancer (P.A.B.C) is increasing, which is due to the fact that women delay their pregnancy up to the middle ages. According to the definition of P.A.B.C, a pregnancy-associated breast cancer is a case of breast cancer that occurs during pregnancy or up to 1 year after delivery. The aim of this paper is to review the clinical findings and novel imaging methods and findings, which help to diagnose pregnancy-associated breast cancer early. Evidence Acquisition: We reviewed the papers with subjects of PABC and imaging modalities in PABC by searching the medical and health databases such as PubMed, Google Scholar, as well as clinical trials. Results: The most frequent manifestation is a painless mass sensation. The most prevalent pathology of PABC is high-grade ductal carcinoma. The first diagnostic tool and most sensitive modality of imaging in this disease is ultrasound. Mammography during pregnancy and lactation is a safe method, which performs in symptomatic patients or in patients with positive ultrasound findings. MRI is not recommended during pregnancy, but it is completely harmless in breastfeeding patients and it is usually used as the complementary modality. Conclusions: Timely diagnosis of PABC requires complete knowledge of clinical symptoms and accurate interpreting of the images in different diagnostic modalities includingmammography, ultrasound, and MRI. It should be noted that delay in diagnosis of PABC is the most common cause of low survival rate and bad prognosis. [ABSTRACT FROM AUTHOR]

Background: The role of quantitative apparent diffusion coefficient (ADC) maps in differentiating adnexal masses is unresolved.Purpose/hypothesis: To propose an objective diagnostic method devised based on spatial features for predicting benignity/malignancy of adnexal masses in ADC maps.Study Type: Prospective.Population: In all, 70 women with sonographically indeterminate and histopathologically confirmed adnexal masses (38 benign, 3 borderline, and 29 malignant) were considered for this study.Field Strength/sequence: Conventional and diffusion-weighted magnetic resonance (MR) images (b-values = 50, 400, 1000 s/mm2 ) were acquired on a 3T scanner.Assessment: For each patient, two radiologists in consensus manually delineated lesion borders in whole ADC map volumes, which were consequently analyzed using spatial models (first-order histogram [FOH], gray-level co-occurrence matrix [GLCM], run-length matrix [RLM], and Gabor filters). Two independent radiologists were asked to identify the attributed (benign/malignant) classes of adnexal masses based on morphological features on conventional MRI.Statistical Tests: Leave-one-out cross-validated feature selection followed by cross-validated classification were applied to the feature space to choose the spatial models that best discriminate benign from malignant adnexal lesions. Two schemes of feature selection/classification were evaluated: 1) including all benign and malignant masses, and 2) scheme 1 after excluding endometrioma, hemorrhagic cysts, and teratoma (14 benign, 29 malignant masses). The constructed feature subspaces for benign/malignant lesion differentiation were tested for classification of benign/borderline/malignant and also borderline/malignant adnexal lesions.Results: The selected feature subspace consisting of RLM features differentiated benign from malignant adnexal masses with a classification accuracy of ∼92%. The same model discriminated benign, borderline, and malignant lesions with 87% and borderline from malignant with 100% accuracy. Qualitative assessment of the radiologists based on conventional MRI features reached an accuracy of 80%.Data Conclusion: The spatial quantification methodology proposed in this study, which works based on cellular distributions within ADC maps of adnexal masses, may provide a helpful computer-aided strategy for objective characterization of adnexal masses.Level Of Evidence: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1061-1071. [ABSTRACT FROM AUTHOR]

Purpose To develop a one-step quantification approach that accounts for joint preprocessing and quantification of whole-range kinetics (early and late-phase washout) of dynamic contrast-enhanced (DCE) MRI of indeterminate adnexal masses. Methods Preoperative DCE-MRI of 43 (24 benign, 19 malignant) sonographically indeterminate adnexal masses were analyzed prospectively. A five-parameter sigmoid function was implemented to model the enhancement curves calculated within regions of interest. Diagnostic performance of five-parameter sigmoid model parameters ( P1 through P5) was compared with pharmacokinetic (PK) modeling, semiquantitative analysis, and three-parameter sigmoid. Statistical analysis was performed using two-tailed student's t-test. Results The results revealed that P2, representing the enhancement amplitude, is significantly higher, and P5, indicating the terminal phase, is generally negative in malignant lesions ( P < 0.001). P2 (sensitivity = 79%, specificity = 87.5%, accuracy = 84%, area under the receiver operating characteristic curve = 91%) outperforms classification performances of PK and semiquantitative parameters. A combination of P2 and P5 shows comparable performance (sensitivity = 79%, specificity = 87.5%, accuracy = 84%, area under the receiver operating characteristic curve = 92%) to that of the combination of PK parameters, whereas the five-parameter sigmoid function maintains fewer assumptions than PK. Conclusions The presented one-step quantification approach is helpful for accurate discrimination of benign from malignant indeterminate adnexal masses. Accordingly, P2 has considerably high diagnostic performance and terminal slope ( P5), as a previously overlooked feature, contributes more than widely accepted early-enhancement kinetic features. Magn Reson Med 79:1165-1171, 2018. © 2017 International Society for Magnetic Resonance in Medicine. [ABSTRACT FROM AUTHOR]

Detecting the micrometastasis is a major challenge in patients' survival. The small volume of the biopsied tissue results in limited number of histopathological samples and might reduce the rate of accurate diagnosis even by molecular technologies. We introduce a microelectronic biochip (named Metas-Chip) to detect the micrometastasis in unprocessed liquid or solid samples. It works based on the tendency of malignant cells to track single human umbilical vein endothelial cell (HUVEC)-sensing traps. Such cells detach themselves from the biopsied sample and invade the sensing traps by inducing membrane retraction and blebbing, which result in sharp changes in electrical response of the sensing elements. Metas-Chip identified the metastasis in more than 70 breast cancer patients, in less than 5 h. Moreover it detected the metastasis in lymph nodes of nine patients whom were missed by conventional pathological procedure. Multilevel IHC and real-time polymerase chain reaction (RT-PCR) tests confirmed the diagnosis. [ABSTRACT FROM AUTHOR]

Background: Pelvic floor dysfunction (PFD) refers to a wide range of issues that occur when muscles of the pelvic floor are weak, tight, or there is an impairment of the sacroiliac joint, lower back, coccyx, or hip joints. PFD and pelvic organ prolapse (POP) affect about 50% of women past middle age. Symptoms include pelvic pain, pressure, dyspareunia, incontinence, incomplete emptying, and gross organ protrusion. Nowadays, there are novel diagnostic tools and therapies proposed for pelvic floor weakness and organ prolapse. Pelvic organ prolapse quantification system (POP-Q) examination and complementary magnetic resonance imaging (MRI) are two methods of diagnosis. Objectives: The goal of our study was to assess the agreement between POP-Q examination and MRI in detecting anterior pelvic prolapses. In addition, we evaluated the additive role of MRI adjunct to POP-Q examination in detecting anterior pelvic organ prolapse. Patients and Methods: An experimental study was carried out on 61 patients having clinical manifestations suggesting pelvic floor weakness. The medical history and physical examination were obtained from all patients. POP-Q examination and dynamic MR imaging was performed. POP-Q results were compared with dynamic MRI findings thereafter. Results: Considering pubococcygeal line (PCL) and H line as reference lines, comparison of MRI and POP-Q findings for detecting bladder neck and urethra prolapses revealed a moderate to good agreement (49% - 80%) rate between MRI and POP-Q examination. This corresponds to a weak to moderate agreement between these two methods. Conclusion: Agreement of MRI and POP-Q is moderate to good for detecting anterior pelvic organs prolapses. MRI could be regarded as a complementary method to POP-Q examination. A combination diagnostic approach, including MRI and POP-Q, for high stage pelvic prolapse is highly recommended. [ABSTRACT FROM AUTHOR]

Neonatal MR templates are appropriate for brain structural analysis and spatial normalization. However, they do not provide the essential accurate details of cranial bones and fontanels-sutures. Distinctly, CT images provide the best contrast for bone definition and fontanels-sutures. In this paper, we present, for the first time, an approach to create a fully registered bimodal MR-CT head template for neonates with a gestational age of 39 to 42 weeks. Such a template is essential for structural and functional brain studies, which require precise geometry of the head including cranial bones and fontanels-sutures. Due to the special characteristics of the problem (which requires inter-subject inter-modality registration), a two-step intensity-based registration method is proposed to globally and locally align CT images with an available MR template. By applying groupwise registration, the new neonatal CT template is then created in full alignment with the MR template to build a bimodal MR-CT template. The mutual information value between the CT and the MR template is 1.17 which shows their perfect correspondence in the bimodal template. Moreover, the average mutual information value between normalized images and the CT template proposed in this study is 1.24±0.07. Comparing this value with the one reported in a previously published approach (0.63±0.07) demonstrates the better generalization properties of the new created template and the superiority of the proposed method for the creation of CT template in the standard space provided by MR neonatal head template. The neonatal bimodal MR-CT head template is freely downloadable from . [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) have a large number of various target genes in different cancer types, which may result in many biological functions. Thus, identifying the molecular mechanisms of miRNAs may effect on the complexity of cancer progression via regulation of gene. In the current study, we utilized real-time PCR to quantify the diction of miR-148b in trail hepatocellular carcinoma (HCC) specimen and normal tissues. Furthermore, we evaluated the relationship of miR-148b and clinicopathological features with survival of HCC patients. Therefore, we evaluated the level of miR-148b expression in 101 HCC patients and also in 40 normal control cases. The result suggested lower expression in tumor tissues than normal control tissues (0.96 ± 0.14; 1.84 ± 0.20, P < 0.05). Our findings suggest that the declined expression of miR-148b can considerably be linked to tumor node metastasis (TNM) stage (stages III and IV; P = 0.021) and vein invasion ( P = 0.029). Nevertheless, miR-148b expression was not related to sex ( P = 0.674), age ( P = 0. 523), size of tumor ( P = 0.507), liver cirrhosis, and histologic grade ( P = 0.734). Survival analysis showed that low expression was remarkably related to overall survival ( P = 0.012). Furthermore, multivariate survival test suggested that decline of miR-148b diction was linked to poor survival in HCC patients. Our results suggested that miR-148b is decreased in HCC. Therefore, we concluded that miR-148b may play its role in the prognosis of HCC. [ABSTRACT FROM AUTHOR]

Background: MicroRNAs (miRNAs) have been documented as playing important roles in cancer development. In this study, we investigated to clarify the clinicopathological significance and prognostic value of miR-124 in breast cancer. Methods: Quantitative Real-time PCR method was used to assess the expression levels of miR-124 in breast cancer patients and the association of miR-124 expression levels with the clinicopathological characteristics in breast cancer patients. Survival and Multivariate Cox proportional hazards model analysis was used to evaluate whether the miR-124 expression level and various clinicopathological characteristics were independent prognostic marker for breast cancer patients. Results: We found that the lower expression of miR-124 in breast cancer specimens compared with corresponding adjacent normal breast tissues P < 0.05. Results showed that decreased expression of miR-124 was significantly related to advanced clinical stage (stage III and IV) (P = 0.021) and positive lymph node-metastasis (P = 0.011). Patients with low expression of miR-124 had significantly shorter overall survival (70.2 %) than patients who had cancers with high miR-124 expression (29.8), (logrank test P = 0.021). Moreover, Multivariate Cox proportional hazards model analysis indicated that lowr miR-124 expression was found to be independently linked to poor survival of patients with breast cancer and other factors were not significantly associated with survival of patients. Conclusion: Our data suggested that decreased expression of miR-124 has prognostic value in breast cancer and may serve as a prognostic marker for breast cancer, and also downregulation of miR-124 was inversely associated with the lymph node metastasis in breast cancer. [ABSTRACT FROM AUTHOR]

Background: Transvaginal Ultrasonography is a noninvasive and inexpensive medical imaging tool used for the diagnosis of various diseases. Objectives: To identify an effective method to identify high-risk patients for developing malignancy after molar evacuation. Patients and Methods: A prospective serial assessment of 19 patients with gestational trophoblastic disease was performed. Clinical and laboratory data, transvaginal ultrasound and Doppler findings were evaluated the day before evacuation. They were followed-up in the first week after evacuation and every two weeks during the next two months, then every month until the sixth month. Results: Ovarian theca lutein cysts (P = 0.018) (among pre-evacuation factors) and first week ultrasound (P =0.02) can help in detecting high-risk patients. Even though, when β-hCG titer is not available in a high-risk patient, post evacuation myometrial involvement (P = 0.005) is a useful sign for detecting persistency. Conclusions: Some ultrasonographic features of molar pregnancy have capability to predict malignancy in the course of disease. [ABSTRACT FROM AUTHOR]

Background: Pre-operative imaging devices generate high-resolution images but intra-operative imaging devices generate low-resolution images. To use highresolution pre-operative images during surgery, they must be deformed to reflect intra-operative geometry of brain. Methods: We employ biomechanical models, guided by low resolution intraoperative images, to determine location of normal and abnormal regions of brain after craniotomy. We also employ finite element methods to discretize and solve the related differential equations. In the process, pre- and intra-operative images are utilized and corresponding points are determined and used to optimize parameters of the models. This paper develops a nonlinear model and compares it with linear models while our previous work developed and compared linear models (mechanical and elastic). Results: Nonlinear model is evaluated and compared with linear models using simulated and real data. Partial validation using intra-operative images indicates that the proposed models reduce the localization error caused by brain deformation after craniotomy. Conclusions: The proposed nonlinear model generates more accurate results than the linear models. When guided by limited intra-operative surface data, it predicts deformation of entire brain. Its execution time is however considerably more than those of linear models. [ABSTRACT FROM AUTHOR]