The clinical diagnostic value of right-to-left shunt in cryptogenic stroke under right heart contrast echocardiography: a retrospective case-control study.

Background: About 30% of ischemic strokes do not have a clear cause, which is called cryptogenic stroke (CS). Increasing evidence suggests a potential link between CS and right-to-left shunt (RLS). RLS may lead to CS via paradoxical embolic mechanism.

Deep learning based analysis of dynamic video ultrasonography for predicting cervical lymph node metastasis in papillary thyroid carcinoma.

Background: Cervical lymph node metastasis (CLNM) is the most common form of thyroid cancer metastasis. Accurate preoperative CLNM diagnosis is of more importance in patients with papillary thyroid cancer (PTC). However, there is currently no unified methods to objectively predict CLNM risk from ultrasonography in PTC patients.

The clinical value of artificial intelligence in assisting junior radiologists in thyroid ultrasound: a multicenter prospective study from real clinical practice.

Background: This study is to propose a clinically applicable 2-echelon (2e) diagnostic criteria for the analysis of thyroid nodules such that low-risk nodules are screened off while only suspicious or indeterminate ones are further examined by histopathology, and to explore whether artificial intelligence (AI) can provide precise assistance for clinical decision-making in the real-world prospective scenario.

Methods: In this prospective study, we enrolled 1036 patients with a total of 2296 thyroid nodules from three medical centers. The diagnostic performance of the AI system, radiologists with different levels of experience, and AI-assisted radiologists with different levels of experience in diagnosing thyroid nodules were evaluated against our proposed 2e diagnostic criteria, with the first being an arbitration committee consisting of 3 senior specialists and the second being cyto- or histopathology.

Tumor and metastatic lymph nodes metabolic activity on F-FDG-PET/CT to predict progression-free survival in locally advanced cervical cancer.

Objective: The present study investigated the predictive diseases progression value of preoperative fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) in patients with local advanced cervical cancer (LACC).

Methods: In total, 267 patients [median age 58 (range: 27-85) years old] with LACC underwent F-FDG PET/CT prior to any treatment. The maximum standardized uptake values (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary lesion and metastatic lymph nodes were measured on PET/CT and correlated with clinicopathological features and progression-free survival (PFS).

Clinical features and imaging examination assessment of cervical lymph nodes for thyroid carcinoma.

Backgrounds: The purpose of this study is to investigate the relationship between clinical characteristics and cervical lymph node metastasis (LNM) in patients with thyroid carcinoma, as well as estimate the preoperative diagnosis values of ultrasound (US) and contrast enhanced computed tomography (CECT) examinations on the neck for detection of cervical LNM in thyroid carcinoma.

Methods: A retrospective analysis of 3 026 patients with surgically proven thyroid carcinoma was conducted. Patients' clinical characteristics, including gender, age, tumor size, bilateral lesions, multifocality, adenomatous nodules, Hashimoto's thyroiditis (HT), and extrathyroidal extension, were collected to explore their association with cervical LNM in thyroid carcinoma.

Deep learning approaches for differentiating thyroid nodules with calcification: a two-center study.

Background: Calcification is a common phenomenon in both benign and malignant thyroid nodules. However, the clinical significance of calcification remains unclear. Therefore, we explored a more objective method for distinguishing between benign and malignant thyroid calcified nodules.

AI diagnosis of Bethesda category IV thyroid nodules.

Thyroid nodules are a common disease, and fine needle aspiration cytology (FNAC) is the primary method to assess their malignancy. For the diagnosis of follicular thyroid nodules, however, FNAC has limitations. FNAC can classify them only as Bethesda IV nodules, leaving their exact malignant status and pathological type undetermined.

Ultrasound and clinicopathological characteristics-based model for prediction of pathologic response to neoadjuvant chemotherapy in HER2-positive breast cancer: a case-control study.

Background: The objective of this study was to develop a model combining ultrasound (US) and clinicopathological characteristics to predict the pathologic response to neoadjuvant chemotherapy (NACT) in human epidermal growth factor receptor 2 (HER2)-positive breast cancer.

Materials And Methods: This is a retrospective study that included 248 patients with HER2-positive breast cancer who underwent NACT from March 2018 to March 2022. US and clinicopathological characteristics were collected from all patients in this study, and characteristics obtained using univariate analysis at p < 0.

Leveraging deep learning to identify calcification and colloid in thyroid nodules.

Background: Both calcification and colloid in thyroid nodules are reflected as echogenic foci in ultrasound images. However, calcification and colloid have significantly different probabilities of malignancy. We explored the performance of a deep learning (DL) model in distinguishing the echogenic foci of thyroid nodules as calcification or colloid.

The auxiliary diagnosis of thyroid echogenic foci based on a deep learning segmentation model: A two-center study.

Objective: The aim of this study is to develop AI-assisted software incorporating a deep learning (DL) model based on static ultrasound images. The software aims to aid physicians in distinguishing between malignant and benign thyroid nodules with echogenic foci and to investigate how the AI-assisted DL model can enhance radiologists' diagnostic performance.

Methods: For this retrospective study, a total of 2724 ultrasound (US) scans were collected from two independent institutions, encompassing 1038 echogenic foci nodules.

Comparison of machine learning models based on multi-parametric magnetic resonance imaging and ultrasound videos for the prediction of prostate cancer.

Objective: To establish machine learning (ML) prediction models for prostate cancer (PCa) using transrectal ultrasound videos and multi-parametric magnetic resonance imaging (mpMRI) and compare their diagnostic performance.

Materials And Methods: We systematically collated the data of 383 patients, including 187 with PCa and 196 with benign lesions. Of them, 307 patients (150 with PCa and 157 with benign lesions) were randomly selected to train and validate the ML models, 76 patients were used as test set.

An artificial intelligence ultrasound system's ability to distinguish benign from malignant follicular-patterned lesions.

Objectives: To evaluate the application value of a generally trained artificial intelligence (AI) automatic diagnosis system in the malignancy diagnosis of follicular-patterned thyroid lesions (FPTL), including follicular thyroid carcinoma (FTC), adenomatoid hyperplasia nodule (AHN) and follicular thyroid adenoma (FTA) and compare the diagnostic performance with radiologists of different experience levels.

Methods: We retrospectively reviewed 607 patients with 699 thyroid nodules that included 168 malignant nodules by using postoperative pathology as the gold standard, and compared the diagnostic performances of three radiologists (one junior, two senior) and that of AI automatic diagnosis system in malignancy diagnosis of FPTL in terms of sensitivity, specificity and accuracy, respectively. Pairwise t-test was used to evaluate the statistically significant difference.

A multi-institutional study of association of sonographic characteristics with cervical lymph node metastasis in unifocal papillary thyroid carcinoma.

Objective: Papillary thyroid carcinoma (PTC) is the most common pathological type of thyroid carcinoma, and is prone to cervical lymph node metastases (CLNM). We aim to evaluate the association between sonographic characteristics of PTC and CLNM before the initial surgery.

Methods: Clinical information as well as ultrasonographic measurements and characteristics for 2376 patients from three hospitals were acquired in this retrospective cohort study.

Machine learning prediction of prostate cancer from transrectal ultrasound video clips.

Objective: To build a machine learning (ML) prediction model for prostate cancer (PCa) from transrectal ultrasound video clips of the whole prostate gland, diagnostic performance was compared with magnetic resonance imaging (MRI).

Methods: We systematically collated data from 501 patients-276 with prostate cancer and 225 with benign lesions. From a final selection of 231 patients (118 with prostate cancer and 113 with benign lesions), we randomly chose 170 for the purpose of training and validating a machine learning model, while using the remaining 61 to test a derived model.

The diagnostic value of a nomogram based on multimodal ultrasonography for thyroid-nodule differentiation: A multicenter study.

Objective: To establish and verify a nomogram based on multimodal ultrasonography (US) for the assessment of the malignancy risk of thyroid nodules and to explore its value in distinguishing benign from malignant thyroid nodules.

Methods: From September 2020 to December 2021, the data of 447 individuals with thyroid nodules were retrieved from the multicenter database of medical images of the National Health Commission's Capacity Building and Continuing Education Center, which includes data from more than 20 hospitals. All patients underwent contrast-enhanced US (CEUS) and elastography before surgery or fine needle aspiration.

Differential diagnosis of non-diffuse primary thyroid lymphoma and papillary thyroid carcinoma by ultrasound combined with computed tomography.

Background: Primary thyroid lymphoma (PTL) and papillary thyroid carcinoma (PTC) are both thyroid malignancies, but their therapeutic methods and prognosis are different. This study aims to explore their sonographic and computed tomography(CT)features, and to improve the early diagnosis rate.

Methods: The clinical and imaging data of 50 patients with non-diffuse PTL and 100 patients with PTC confirmed by pathology were retrospectively analysed.

Combined Conventional Ultrasound and Contrast-Enhanced Computed Tomography for Cervical Lymph Node Metastasis Prediction in Papillary Thyroid Carcinoma.

Objectives: This study aimed to evaluate conventional ultrasound (US) combined with contrast-enhanced computed tomography (CT) of the neck to predict central lymph node metastasis (CLNM) in clinical lymph-negative patients with papillary thyroid carcinoma (PTC), establish a simple preoperative risk-scoring model, and validate its effectiveness in a two-center dataset.

Methods: A total of 423 patients with PTC preoperatively evaluated by US and contrast-enhanced CT were included in the modeling group, and 102 patients from two hospitals were enrolled in the validation group. Independent predictive factors were determined using multivariate logistic regression analysis.

Correlation Analysis of Nodular Sonographic Parameters with Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma.

Background: Papillary thyroid carcinoma (PTC) is the most common thyroid carcinoma and is prone to cervical lymph node metastases (CLNM). We aim to analyze the correlation between clinical information, ultrasonic parameters of PTC, and CLNM.

Methods: 1335 patients who had pathologically confirmed unifocal PTC were enrolled in this retrospective cohort study.

Correlation between preoperative ultrasonic features of medullary thyroid carcinoma and postoperative recurrence.

Background: To investigate the factors that affect postoperative recurrence in medullary thyroid carcinoma (MTC) patients, including preoperative ultrasonic characteristics and other factors.

Method: A retrospective analysis of 7 MTC patients who underwent the first thyroid surgery from 2009 to 2018 and who had complete follow-up data was conducted. According to the follow-up results, these patients were divided into the recurrence group (17 cases) and non-recurrence group (57 cases).

A Control Study on the Value of the Ultrasound Grayscale Ratio for the Differential Diagnosis of Thyroid Micropapillary Carcinoma and Micronodular Goiter in Two Medical Centers.

Objective: To investigate the value of ultrasound gray-scale ratio (UGSR) for the differential diagnosis of papillary thyroid microcarcinoma (PTMC) and micronodular goiter (MNG) in two medical centers.

Methods: Ultrasound images of 881 PTMCs from 785 patients and 744 MNGs from 687 patients in center A were retrospectively analyzed and compared with 243 PTMCs from 203 patients and 251 MNGs from 198 patients in center B. All cases were confirmed by surgery and histology.