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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]

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: 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.