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PurposeThe present study aimed to analyze and compare sonographic features of papillary thyroid carcinoma (PTC) subtypes to determine whether ultrasound (US) may aid in differentiating particular subtypes.MethodsThis retrospective study enrolled 133 patients diagnosed with 142 histopathologically proven PTCs as per the fifth edition of the World Health Organization classification of thyroid neoplasms between January 2013 and May 2023. US features based on the American College of Radiology and European Thyroid Imaging and Reporting Data Systems (TIRADS), and histopathological characteristics of nodules were assessed and compared.ResultsHistopathological analysis yielded 55 (38.7%) classic PTC, 32 (22.5%) invasive encapsulated follicular variant (IEFV) PTC, 20 (14.1%) oncocytic subtype, 14 (9.9%) non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), 11 (7.8%) infiltrative follicular subtype, 7 (4.9%) tall cell subtype, 2 (1.4%) solid subtype, and 1 (0.7%) diffuse sclerosing subtype. The US findings indicating malignancy, such as taller-than-wide shape, irregular margins, echogenic foci, and higher TIRADS categories, were more frequently demonstrated in nodules with classic PTC and the tall cell subtype, in line with their histopathological features. Conversely, IEFV-PTC and NIFTP rarely exhibited these high-risk sonographic features. US appearance of the oncocytic subtype more frequently overlapped with IEFV-PTC, yet hypo/very hypoechoic nodules with larger nodular diameters and higher TIRADS scores may favor the diagnosis of this subtype.ConclusionUS features of certain subtypes may guide the differential diagnosis regarding shape, margin, echogenic foci, and TIRADS category of nodules; however, definitive subtyping is not yet possible using US images alone.

PURPOSEHigh-risk breast lesions (HRLs) are associated with future risk of breast cancer. Considering the pathological subtypes, malignancy upgrade rate differs according to each subtype and depends on various factors such as clinical and radiological features and biopsy method. Using artificial intelligence and machine learning models in breast imaging, evaluations can be made in terms of risk estimation in different research areas. This study aimed to develop a machine learning model to distinguish HRL cases requiring surgical excision from lesions with a low risk of accompanying malignancy.METHODSA total of 94 patients who were diagnosed with HRL by image-guided biopsy between January 2008 and March 2020 were included in the study. A structured database was created with clinical and radiological characteristics and histopathological results. A machine learning prediction model was created to make binary classifications of lesions as malignant or benign. Random forest, decision tree, K-nearest neighbors, logistic regression, support vector machine (SVM), and multilayer perceptron machine learning algorithms were used. Among these algorithms, SVM was the most successful. The estimations of malignancy for each case detected by artificial intelligence were combined and statistical analyses were performed.RESULTSConsidering all cases, the malignancy upgrade rate was 24.5%. A significant association was observed between malignancy upgrade rate and lesion size (P = 0.004), presence of mammography findings (P = 0.022), and breast imaging-reporting and data system category (P = 0.001). A statistically significant association was also found between the artificial intelligence prediction model and malignancy upgrade rate (P < 0.001). With the SVM model, an 84% accuracy and 0.786 area-underthe- curve score were obtained in classifying the data as benign or malignant.CONCLUSIONOur artificial intelligence model (SVM) can predict HRLs that can be followed up with a lower risk of accompanying malignancy. Unnecessary surgeries can be reduced, or second line vacuum excisions can be performed in HRLs, which are mostly benign, by evaluating on a case-by-case basis, in line with radiology–pathology compatibility and by using an artificial intelligence model.

PURPOSEIn this study, we aimed to assess the effectiveness of malignancy stratification algorithms of the American College of Radiology (ACR) and European Thyroid Association (ETA) in the delineation of thyroid nodules using a database of nodules that were unequivocally diagnosed by means of histopathological examination and meticulously matched with the imaged nodules.METHODSA total of 165 patients having 251 thyroid nodules with histopathologically proven definitive diagnoses during a 5-year period were included in this study. All patients had preoperatively undergone ultrasonography (US) examination, and US characteristics of the thyroid nodules were retrospectively analyzed and assigned in compliance with the thyroid imaging reporting and data system categories recommended by the ACR (ACR-TIRADS) and ETA (EU-TIRADS). The diagnostic effectiveness in the delineation of thyroid nodules and unnecessary fine-needle aspiration (FNAB) rates were evaluated.RESULTSOverall, 189 nodules (75.30%) were diagnosed as benign, while 62 nodules (24.70%) were reported to be malignant based on histopathological assessment. Sensitivity and specificity rates were 71% and 75% for ACR-TIRADS and 73% and 80% for EU-TIRADS. The area under the curve values were 0.78 and 0.80 for ACR-TIRADS and EU-TIRADS, respectively. The unnecessary FNAB rates were 61% for ACR-TIRADS and 64% for EU-TIRADS as per the recommended criteria of each algorithm.CONCLUSIONThe diagnostic performance of both malignancy stratification systems was signified to be moderate and sufficient in a cohort of nodules with definite histopathological diagnosis. In light of our results, we demonstrated the strengths and weaknesses of the ACR- and EU-TIRADS for physicians who should be familiar with them for optimal management of thyroid nodules.

Objective: This study aimed to observe the preventive effect of prophylactic treatment on joint health in people with hemophilia (PwH) and to investigate the importance of integration of ultrasonographic examination into clinical and radiological evaluation of the joints. Materials and Methods: This national, multicenter, prospective, observational study included male patients aged ≥6 years with the diagnosis of moderate or severe hemophilia A or B from 8 centers across Turkey between January 2017 and March 2019. Patients were followed for 1 year with 5 visits (baseline and 3rd, 6th, 9th, and 12th month visits). The Hemophilia Joint Health Score (HJHS) was used for physical examination of joints, the Pettersson scoring system was used for radiological assessment, point-of-care (POC) ultrasonography was used for bilateral examinations of joints, and the Hemophilia Early Arthropathy Detection with Ultrasound (HEAD-US) score was used for evaluation of ultrasonography results. Results: Seventy-three PwH, of whom 62 had hemophilia A and 11 had hemophilia B, were included and 24.7% had target joints at baseline. The HJHS and HEAD-US scores were significantly increased at the 12th month in all patients. These scores were also higher in the hemophilia A subgroup than the hemophilia B subgroup. However, in the childhood group, the increment of scores was not significant. The HEAD-US total score was significantly correlated with both the HJHS total score and Pettersson total score at baseline and at the 12th month. Conclusion: The HEAD-US and HJHS scoring systems are valuable tools during follow-up examinations of PwH and they complement each other. We suggest that POC ultrasonographic evaluation and the HEAD-US scoring system may be integrated into differential diagnosis of bleeding and long-term monitoring for joint health as a routine procedure.

Purpose The aim of this study was to evaluate the associations of sonographic and sonoelastographic parameters with clinical cardiac parameters, as well as to assess their value in predicting survival in patients with pulmonary arterial hypertension (PAH). Methods Thirty-six patients with PAH and normal liver function were prospectively enrolled in this prospective study along with 26 healthy controls, all of whom underwent ultrasound and point shear wave elastography examinations. Additionally, the portal vein pulsatility index (PVPI), inferior vena cava collapsibility index, and clinical cardiac variables were obtained in PAH patients. The values of hepatic (LVs) and splenic shear wave velocity (SVs) were compared between PAH patients and controls. The relationships between all sonographic and clinical parameters in the PAH patients were analyzed. Furthermore, their prognostic value in predicting survival was investigated. Results LVs values in PAH patients (median, 1.62 m/s) were significantly higher than in controls (median, 0.99 m/s), while no significant difference was observed in SVs values. Patients with higher grades of tricuspid regurgitation (TR) had significantly different values of PVPI (P=0.010) and sonoelastographic parameters (P

A new coronavirus outbreak called COVID-19 started in December 2019. In Turkey, the first case was reported on 10 March 2020. In this article, information will be given about the patient and staff management and organization that we have implemented in the Radiology Department of our hospital during the COVID-19 pandemic. The rules we followed were: 1- Performing the examinations of COVID-19 patients and suspects with a CT device isolated from other patients; 2- Reducing the unnecessary workload in imaging modalities other than CT, emergency radiography, and emergency ultrasonography; 3- Directing and managing patients and their relatives in accordance with the mask and distancing rules; 4- Disinfecting the device with an appropriate disinfectant after each patient in order to prevent cross-contamination; 5- Protecting the entire technician team from infection by employing one week work, two weeks off shifts of fixed teams; 6- Ensuring adequate ventilation of the gantry room. Adhering to the above rules, no infection spread was reported from the Radiology department and especially the COVID-19 CT unit.

PURPOSEWe aimed to compare the ultrasonographic and laboratory parameters of euthyroid patients who have only positive antithyroid autoantibody test results with those of patients with a hypothyroid status of Hashimoto’s thyroiditis (HT).MATERIALS AND METHODSThirty-five patients with newly diagnosed HT, 35 euthyroid patients who have autoantibodies against thyroid peroxidase (TPOAb) and/or thyroglobulin (TgAb), and 40 controls were enrolled in the study. Plasma free T3, free T4, thyroid stimulating hormone, TPOAb, and TgAb levels were obtained retrospectively. For gray-scale ultrasonography, each thyroid gland of all individuals graded with gray-scale grading (GSG), which was determined according to the gland size, parenchymal structure, echogenicity, micronodulation, contour irregularity, and existence of hyperechoic septa. For Doppler analysis, the peak systolic velocity (S), resistive index (RI), and pulsatility index (PI) values were obtained from the superior thyroid artery (STA) and intrathyroidal artery (ITA). The color pixel ratio (CPR), which was computationally evaluated from a power Doppler image of all individuals, was used for quantification of the intrathyroidal vascularity.RESULTSAlthough the mean GSG values were higher in the HT and antibody-positive groups than they were in the control group, there was no significant difference between the HT and antibody-positive groups. The three study groups demonstrated no statistically significant difference with regard to the S, RI, or PI variables obtained from the STAs and ITAs. Although the CPR values were highest in the HT group, the difference between the HT and antibody-positive group did not reach statistical significance.CONCLUSIONThe euthyroid antibody-positive group revealed gray-scale and Doppler ultrasonographic findings that were similar to those of the HT group.