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Abstract Background Whole-body magnetic resonance imaging (WB-MRI) has emerged as a valuable tool for cancer detection. This study evaluated the prevalence rates of cancer in asymptomatic individuals undergoing WB-MRI according to the Oncologically Relevant Findings Reporting and Data System (ONCO-RADS) classifications in order to assess the reliability of the classification method. Methods We retrospectively enrolled 2064 asymptomatic individuals who participated in a WB-MRI cancer screening program between 2017 and 2022. WB-MRI was acquired on a 3-T system with a standard protocol, including regional multisequence and gadolinium-based contrast agent-enhanced oncologic MRI. Results of further examinations, including additional imaging and histopathology examinations, performed at our institute were used to validate the WB-MRI findings. Two radiologists blinded to the clinical outcome classified the WB-MRI findings according to the ONCO–RADS categories as follows: 1 (normal), 2 (benign finding highly likely), 3 (benign finding likely), 4 (malignant finding likely), and 5 (malignant finding highly likely). Firth logistic regression analysis was performed to determine the associations between participant characteristics and findings of ONCO-RADS category ≥ 4. Results Of the 2064 participants with median age of 55 years, 1120 (54.3%) were men, 43 (2.1%) had findings of ONCO-RADS category ≥ 4, and 24 (1.2%) had confirmed cancer. The cancer prevalence rates were 0.1%, 5.4%, 42.9%, and 75% for ONCO-RADS categories 2, 3, 4, and 5, respectively. In the multivariable model, older age (OR: 1.035, p = 0.029) and history of hypertension (OR: 2.051, p = 0.026), hepatitis B carrier (OR: 2.584, p = 0.013), or prior surgery (OR: 3.787, p

Abstract Background To develop an artificial intelligence (AI) model with radiomics and deep learning (DL) features extracted from CT images to distinguish benign from malignant ovarian tumors. Methods We enrolled 149 patients with pathologically confirmed ovarian tumors. A total of 185 tumors were included and divided into training and testing sets in a 7:3 ratio. All tumors were manually segmented from preoperative contrast-enhanced CT images. CT image features were extracted using radiomics and DL. Five models with different combinations of feature sets were built. Benign and malignant tumors were classified using machine learning (ML) classifiers. The model performance was compared with five radiologists on the testing set. Results Among the five models, the best performing model is the ensemble model with a combination of radiomics, DL, and clinical feature sets. The model achieved an accuracy of 82%, specificity of 89% and sensitivity of 68%. Compared with junior radiologists averaged results, the model had a higher accuracy (82% vs 66%) and specificity (89% vs 65%) with comparable sensitivity (68% vs 67%). With the assistance of the model, the junior radiologists achieved a higher average accuracy (81% vs 66%), specificity (80% vs 65%), and sensitivity (82% vs 67%), approaching to the performance of senior radiologists. Conclusions We developed a CT-based AI model that can differentiate benign and malignant ovarian tumors with high accuracy and specificity. This model significantly improved the performance of less-experienced radiologists in ovarian tumor assessment, and may potentially guide gynecologists to provide better therapeutic strategies for these patients.

Objective To investigate different parameters derived from the quantity and quality of perinephric fat, and to compare their effectiveness in predicting the malignant pathology of renal tumours. Methods Data from patients diagnosed with renal tumour between April 2014 and December 2020 were retrospectively reviewed, and patients were categorized into malignant or benign tumour groups. Fat parameters, including perinephric fat volume (PFV), perinephric fat area (PFA), perinephric fat thickness (PFT), and Mayo adhesive probability (MAP) score were measured using abdominal computed tomography scans. Between-group differences were assessed by analysis of variance and χ 2 -test. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the performance of perinephric fat parameters in diagnosing malignancy. Results A total of 109 patients were included. MAP score, PFV, PFA, and PFT were significantly increased in the malignant versus benign tumour group, and after correction for body mass index (BMI), the indexed PFV/BMI, PFA/BMI, and PFT/BMI values remained significantly higher in the malignant tumour group. All parameters showed fair predictivity of malignancy, with comparable area under the curve values in the ROC curve. Conclusion An increased amount of perinephric fat is predictive of malignant pathology for renal tumours. The predictive accuracy for each perinephric fat parameter remained fair after correcting for BMI.

Abdominal lymphatic malformations (LM) are rare congenital malformations of the lymphatic system, representing only 2% of all LM in newborns. They may arise from intra-abdominal solid organs (such as the liver, pancreas, kidneys, spleen, adrenal glands, and gastrointestinal tract), mesentery, omentum, and retroperitoneum. Mesenteric LM are the most commonly seen, with retroperitoneal LM being the second most common. Fetal abdominal LM could be associated with karyotypic or other abnormalities, including skin edema, hydrops fetalis, and polyhydramnios, and prenatal diagnosis and perinatal counseling for these LM are important. Prenatal ultrasound (US) and magnetic resonance imaging (MRI) have led to an increased diagnosis of abdominal LM and improved monitoring and intervention postnatally. This article provides an overview of fetal abdominal LM, including the prenatal diagnoses, differential diagnoses, comprehensive illustrations of the imaging findings, treatments, and fetal outcomes.

The recently revised 2017 American College of Cardiology/American Heart Association (ACC/AHA) hypertension (HTN) guidelines employ a lower blood pressure threshold to define HTN, aiming for earlier prevention of HTN-related cardiovascular diseases (CVD). Thoracic aortic calcification (TAC), a new surrogate marker of aging and aortic medial layer degeneration, and different stages of HTN, according to the 2017 ACC/AHA HTN guidelines, remain unknown. We classified 3022 consecutive asymptomatic individuals enrolled into four HTN categories using the revised 2017 ACC/AHA guidelines: normal blood pressure (NBP), elevated blood pressure (EBP), and stage 1 (S1) and stage 2 (S2) HTN. The coronary artery calcification score and TAC metrics (total Agaston TAC score, total plaque volume (mm3), and mean density (Hounsfield units, HU)) were measured using multi-detector computed tomography. Compared to NBP, a graded and significant increase in the TAC metrics was observed starting from EBP and S1 and S2 HTN, using the new 2017 ACC/AHA guidelines (NBP as reference; all trends: p < 0.001). These differences remained consistent after being fully adjusted. Older age (>50 years), S1 and S2 HTN, prevalent diabetes, and chronic kidney disease (2) are all independently contributing factors to higher TAC risk using multivariate stepwise logistic regressions (all p ≤ 0.001). The optimal cutoff values of systolic blood pressure, diastolic blood pressure, and pulse pressure were 121, 74, and 45 mmHg, respectively, for the presence of TAC after excluding subjects with known CVD and ongoing HTN medication treatment. Our data showed that the presence of TAC starts at a stage of elevated blood pressure not categorized as HTN from the updated 2017 ACC/AHA hypertension guidelines.

Prenatal congenital lobar fluid overload (CLFO), which was first described by Ramsay and Byron, is identical to postnatal congenital lobar overinflation. It is characterized by progressive lobar overexpansion that compresses the other adjacent lung lobes. The underlying cause can be an intrinsic cartilaginous abnormality or an extrinsic airway compression. It may be associated with cardiovascular anomalies in 12%–14% of cases and affects males more frequently than females. Most cases are diagnosed postnatally, but early antenatal diagnosis and sequential follow-up are attempted for early treatment, if clinically indicated. This article provided a thorough review of CLFO, including prenatal diagnosis and differential diagnoses, as well as comprehensive illustrations of the perinatal imaging findings of CLFO. Prenatal diagnosis of fetal lung lesions should include CLFO in the differential diagnosis and prompt investigation for associated anomalies.

Introduction: Cushing's syndrome is defined as chronic excess free cortisol in circulation. According to recent studies, midnight salivary cortisol is an accurate and non-stress method for screening and diagnosing Cushing's syndrome. However, there is limited data on midnight salivary cortisol for diagnosing Cushing's syndrome in the Chinese population.Methods: Among 61 suspected Chinese patients, 48 patients were confirmed to have Cushing's syndrome. We evaluated the midnight salivary cortisol, midnight serum cortisol and 24-hour urine free cortisol excretion for diagnosis. Midnight salivary cortisol was collected from 21 healthy volunteers for control purposes.Results: In the patient group, mean urine free cortisol excretion and midnight salivary cortisol levels were 296.50 ± 47.99 µg/day and 10.18 ± 1.29 ng/mL, respectively. Among the control group and normal participants, mean midnight salivary cortisol level was 0.53 ± 0.13 ng/mL and 0.50 ± 0.12 ng/mL, respectively. The cut-off value for midnight salivary cortisol was 1.7 ng/mL for diagnosing Cushing's syndrome, with a sensitivity of 98% and specificity of 100%. The diagnostic performance of midnight salivary cortisol (area under the curve [AUC] = 0.99) was superior to that of urine free cortisol (AUC = 0.89).Conclusion: Our study confirmed the good diagnostic performance of midnight salivary cortisol for diagnosing Cushing's syndrome in a Chinese population. Correlation between midnight salivary cortisol and either urine free cortisol or midnight serum cortisol was good. Midnight salivary cortisol is a convenient and precise tool for diagnosing Cushing's syndrome and can be the screening test of choice for Chinese populations. [ABSTRACT FROM AUTHOR]

Abstract Background Langerhans cell histiocytosis affecting the thyroid commonly presents with nonspecific clinical and radiological manifestations. Thyroid Langerhans cell histiocytosis is typically characterized by non-enhancing hypodense lesions with an enlarged thyroid on computed tomography medical images. Thyroid involvement in LCH is uncommon and typically encountered in adults, as is salivary gland involvement. Therefore, we present a unique pediatric case featuring simultaneous salivary and thyroid involvement in LCH. Case presentation A 3-year-old boy with complaints of an anterior neck mass persisting for 1 to 2 months, accompanied by mild pain, dysphagia, and hoarseness. A physical examination revealed a 2.5 cm firm and tender mass in the left anterior neck. Laboratory examinations revealed normal thyroid function test levels. Ultrasonography revealed multiple heterogeneous hypoechoic nodules with unclear and irregular margins in both lobes of the thyroid. Contrast-enhanced neck computed tomography revealed an enlarged thyroid gland and bilateral submandibular glands with non-enhancing hypointense nodular lesions, and multiple confluent thin-walled small (