Publications by authors named "Shue Zeng"

Rationale And Objectives: This study aimed to create a radiomics nomogram using grayscale ultrasound (US) to predict human epidermal growth factor receptor 2 (HER-2) expression status preoperatively in invasive breast cancer (IBC) patients.

Materials And Methods: The study population was randomly divided into a training dataset (360 patients, 99 HER-2-positive) and a validation dataset (155 patients, 42 HER-2-positive). Clinical data, including US features, were collected.

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Objectives: Shear-wave elastography (SWE) provides valuable stiffness within breast masses, making it a useful supplement to conventional ultrasound imaging. Super-resolution ultrasound (SRUS) imaging enhances microvascular visualization, aiding in the differential diagnosis of breast masses. Current clinical ultrasound diagnosis of breast cancer primarily relies on gray-scale ultrasound.

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Proliferation and differentiation of intestinal stem cell (ISC) to replace damaged gut mucosal epithelial cells in inflammatory states is a critical step in ameliorating gut inflammation. However, when this disordered proliferation continues, it induces the ISC to enter a cancerous state. The gut microbiota on the free surface of the gut mucosal barrier is able to interact with ISC on a sustained basis.

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Schizophrenia (SCZ) is a complex neuropsychiatric disorder widely recognized for its impaired bioenergy utilization. The astrocyte-neuron lactate shuttle (ANLS) plays a critical role in brain energy supply. Recent studies have revealed abnormal lactate metabolism in SCZ, which is associated with mitochondrial dysfunction, tissue hypoxia, gastric acid retention, oxidative stress, neuroinflammation, abnormal brain iron metabolism, cerebral white matter hypermetabolic activity, and genetic susceptibility.

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Objectives: Precise determination of cervical lymph node metastasis (CLNM) involvement in patients with early-stage thyroid cancer is fairly significant for identifying appropriate cervical treatment options. However, it is almost impossible to directly judge lymph node metastasis based on the imaging information of early-stage thyroid cancer patients with clinically negative lymph nodes.

Methods: Preoperative US images (BMUS and CDFI) of 1031 clinically node negative PTC patients definitively diagnosed on pathology from two independent hospitals were divided into training set, validation set, internal test set, and external test set.

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Purpose: This study aimed to develop a radiomics nomogram based on grayscale ultrasound (US) to distinguish triple-negative breast cancer (TNBC) from non-triple-negative breast cancer (NTNBC) prior to surgery.

Methods: A retrospective analysis of 454 breast carcinoma patients confirmed by pathology was conducted, with 317 patients in the training dataset (59 with TNBC) and 137 patients in the validation dataset (27 with TNBC). Clinical information, conventional US features, and radiomics features were collected, and the Radscore model was constructed after feature selection.

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Article Synopsis
  • The study assessed a deep learning model's ability to distinguish between malignant and benign breast tumors using ultrasound images from multiple hospitals.
  • It involved 45,909 images and included interpretations from both novice and experienced radiologists to evaluate the model's impact on diagnosis accuracy.
  • The findings showed high diagnostic performance with AUC scores around 0.94 and suggested that the model can enhance the accuracy and consistency of radiologists, particularly those with less experience.
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Purpose: The aim of this study was to develop a radiomics nomogram based on grayscale ultrasound (US) for preoperatively predicting Lymphovascular invasion (LVI) in patients with pathologically confirmed T1 (pT1) breast invasive ductal carcinoma (IDC).

Methods: One hundred and ninety-two patients with pT1 IDC between September 2020 and August 2022 were analyzed retrospectively. Study population was randomly divided in a 7: 3 ratio into a training dataset of 134 patients (37 patients with LVI-positive) and a validation dataset of 58 patients (19 patients with LVI-positive).

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Objective: Ultrasound imaging has been widely used in breast cancer screening. Recently, ultrasound super-resolution imaging (SRI) has shown the capability to break the diffraction limit to display microvasculature. However, the application of SRI on differential diagnosis of breast masses remains unknown.

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Human beings develop a highly coordinated and flexible system of social behavior and threat evaluation. In this review we focus on the unique role of early life adversity (ELA) in programming deficits in social behavior and threat processing, and provides guidance on future investigations in the areas of stress reactivity and mental health. We propose that neuroendocrine perturbations of hypothalamus-pituitary-adrenal (HPA) axis and gene activity by epigenetic mechanisms may explain how early adverse circumstances may lead to post traumatic stress disorder (PTSD).

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Objective: To investigate the value of gray-scale ultrasound (US) image histogram in the differential diagnosis between small (≤2.00 cm), oval, or round triple negative breast invasive ductal carcinoma (TN-IDC) and fibroadenoma (FA).

Methods: Fifty-five cases of triple negative breast invasive ductal carcinoma (TN-IDC group) and 57 cases of breast fibroadenoma (FA group) confirmed by pathology in Hubei cancer hospital from September 2017 to September 2021 were analyzed retrospectively.

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Article Synopsis
  • * Researchers collected pelvic ultrasound images from multiple hospitals in China over nearly 16 years, using a large dataset for training and validation to ensure comprehensive evaluation.
  • * The DCNN demonstrated a higher accuracy in detecting ovarian cancer compared to radiologists, achieving an AUC (Area Under the Curve) score of 0.911 in internal testing, indicating its potential to enhance diagnostic practices in clinical settings.
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Computer-aided diagnosis (CAD) systems have attracted extensive attention owing to their performance in the field of image diagnosis and are rapidly becoming a promising auxiliary tool in medical imaging tasks. These systems can quantitatively evaluate complex medical imaging features and achieve efficient and high-diagnostic accuracy. Deep learning is a representation learning method.

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Objectives: To evaluate the value of the computer-aided diagnosis system, S-Detect (based on deep learning algorithm), in distinguishing benign and malignant breast masses and reducing unnecessary biopsy based on the experience of radiologists.

Methods: From February 2018 to March 2019, 266 breast masses in 192 women were included in our study. Ultrasound (US) examination, including S-Detect technique, was performed by the radiologist with about 10 years of clinical experience in breast US imaging.

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Artificial intelligence (AI) has invaded our daily lives, and in the last decade, there have been very promising applications of AI in the field of medicine, including medical imaging, diagnosis, intelligent rehabilitation, and prognosis. Breast cancer is one of the common malignant tumors in women and seriously threatens women's physical and mental health. Early screening for breast cancer mammography, ultrasound and magnetic resonance imaging (MRI) can significantly improve the prognosis of patients.

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Cystic renal masses are often encountered during abdominal imaging. Although most of them are benign simple cysts, some cystic masses have malignant characteristics. The Bosniak classification system provides a useful way to classify cystic masses.

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Aims: To compare the diagnostic value of S-Detect (a computer aided diagnosis system using deep learning) in differentiating thyroid nodules in radiologists with different experience and to assess if S-Detect can improve the diagnostic performance of radiologists.

Materials And Methods: Between February 2018 and October 2019, 204 thyroid nodules in 181 patients were included. An experienced radiologist performed ultrasound for thyroid nodules and obtained the result of S-Detect.

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Rationale: Extra osseous Ewing sarcoma (ES), an uncommon malignant neoplasm, accounts for about 15% of Ewing sarcoma, which mainly affects paravertebral region, lower extremity, chest wall, retroperitoneum, pelvis, and hip. Here is a 54-year-old woman of primary vaginal Ewing sarcoma with uterine fibroid, which has been fewly known or reported.

Patient Concerns: The patient was admitted to our hospital because of vaginal pain.

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