Prognostic study of intracranial branch atheromatous disease in the blood-supplying areas of the lenticulostriate and paramedian pontine arteries.

Introduction: Branch atheromatous disease (BAD) is prone to early neurological deterioration (END), leading to a poor prognosis. The most common arteries causing END are the lenticulostriate arteries (LSA) and the paramedian pontine arteries (PPA). To gain insight into the characteristics of symptomatic plaques and their association with poor prognosis in patients with BAD, we conducted a prospective study using high-resolution magnetic resonance imaging (HRMRI).

A comprehensive analysis of imaging features and clinical characteristics to differentiate malignant from non-malignant mammographic architectural distortion.

Background: Mammographic architectural distortion (AD) is usually subtle and has variable presentations and causes, which poses a diagnostic challenge for breast radiologists and consequently a complex decision-making challenge for clinicians and patients. Presently, there is no reliable imaging standard to differentiate between malignant and benign ADs preoperatively. This study aimed to perform a comprehensive analysis of detailed mammographic and ultrasonographic features and clinical characteristics to enhance the diagnostic and differential efficacy for AD lesions.

Construction of ceRNA network mediated by circRNAs screening from microarray and identification of novel biomarkers for myasthenia gravis.

Background: Recent studies have revealed that circRNA can serve as ceRNA to participate in multiple autoimmune diseases. Our study aims to explore the key circRNA as ceRNA and biomarker for MG.

Methods: We used circRNA microarray to explore differentially expressed circRNAs (DECs) from MG and compare with control.

MRI-Based Kinetic Heterogeneity Evaluation in the Accurate Access of Axillary Lymph Node Status in Breast Cancer Using a Hybrid CNN-RNN Model.

Background: Accurate evaluation of the axillary lymph node (ALN) status is needed for determining the treatment protocol for breast cancer (BC). The value of magnetic resonance imaging (MRI)-based tumor heterogeneity in assessing ALN metastasis in BC is unclear.

Purpose: To assess the value of deep learning (DL)-derived kinetic heterogeneity parameters based on BC dynamic contrast-enhanced (DCE)-MRI to infer the ALN status.

Feasibility analysis of magnetic resonance imaging-based radiomics features for preoperative prediction of nuclear grading of ductal carcinoma in situ.

Background: The nuclear grading of ductal carcinoma in situ (DCIS) affects its clinical risk. The aim of this study was to investigate the possibility of predicting the nuclear grading of DCIS, by magnetic resonance imaging (MRI)-based radiomics features. And to develop a nomogram combining radiomics features and MRI semantic features to explore the potential role of MRI radiomic features in the assessment of DCIS nuclear grading.

MR imaging phenotypes and features associated with pathogenic mutation to predict recurrence or metastasis in breast cancer.

Objectives: Distant metastasis remains the main cause of death in breast cancer. Breast cancer risk is strongly influenced by pathogenic mutation.This study was designed to develop a multiple-feature model using clinicopathological and imaging characteristics adding pathogenic mutations associated signs to predict recurrence or metastasis in breast cancers in high familial risk women.

Identification of region-specific amino acid signatures for doxorubicin-induced chemo brain.

Doxorubicin (DOX) is a cornerstone of chemotherapy for solid tumors and leukemias. DOX-induced cognitive impairment, termed chemo brain, has been reported in cancer survivors, whereas its mechanism remains poorly understood. Here we initially evaluated the cognitive impairments of mice treated with clinically relevant, long-term, low-dosage of DOX.

Differences in Molecular Subtype Reference Standards Impact AI-based Breast Cancer Classification with Dynamic Contrast-enhanced MRI.

Background Breast cancer tumors can be identified as different luminal molecular subtypes depending on either immunohistochemical (IHC) staining or St Gallen criteria that includes Ki-67. Purpose To characterize molecular subtypes and understand the impact of disagreement among IHC and St Gallen molecular subtype reference standards on artificial intelligence classification of luminal A and luminal B tumors with use of radiomic features extracted from dynamic contrast-enhanced (DCE) MRI scans. Materials and Methods In this retrospective study, 28 radiomic features previously extracted from DCE-MRI scans of breast tumors imaged between February 2015 and October 2017 were examined in the following groups: tumors classified as luminal A by both reference standards ("agreement"), tumors classified as luminal A by IHC and luminal B by St Gallen ("disagreement"), and tumors classified as luminal B by both ("agreement").

Impact of continuous learning on diagnostic breast MRI AI: evaluation on an independent clinical dataset.

We demonstrate continuous learning and assess its impact on the performance of artificial intelligence of breast dynamic contrast-enhanced magnetic resonance imaging in the task of distinguishing malignant from benign lesions on an independent clinical test dataset. The study included 1979 patients with 1990 lesions who underwent breast MR imaging during 2015, 2016, and 2017, retrospectively collected under an IRB-approved protocol; there were 1494 malignant and 496 benign lesions based on histopathology. AI was conducted in the task of distinguishing malignant and benign lesions, and independent testing was performed to assess the effect of increasing the numbers of training cases.

Night shift work and depression among Chinese workers: the mediating role of sleep disturbances.

Background: Depression is considered as a global problem. Recently, the prevalence of depression among night shift workers has been attracting people's attention. This study aims to explore the associations among night shift work, shift frequency and depression among Chinese workers and to explore whether sleep disturbances are a critical factor.

Abbreviated protocol combining quantitative diffusion-weighted imaging: a new strategy increasing diagnostic accuracy for breast magnetic resonance imaging?

Background: To compare the diagnostic accuracy of an abbreviated protocol (AP) with or without quantitative apparent diffusion coefficient (ADC) values on diffusion-weighted imaging (DWI) and a full diagnostic protocol (FDP) in terms of the Breast Imaging Reporting and Data System (BI-RADS) classification of breast magnetic resonance imaging (MRI).

Methods: Our study sample consisted of 436 patients undergoing breast MRI from January to October 2015 in a clinical setting. The three reviews included a pre-contrast and the first single post-contrast T1-weighted (T1W) sequences (AP1), AP1 combined with quantitative DWI (AP2), and the FDP, the AP1 of which were assessed independently by a junior and senior radiologist.

Multi-Stage Harmonization for Robust AI across Breast MR Databases.

Radiomic features extracted from medical images may demonstrate a batch effect when cases come from different sources. We investigated classification performance using training and independent test sets drawn from two sources using both pre-harmonization and post-harmonization features. In this retrospective study, a database of thirty-two radiomic features, extracted from DCE-MR images of breast lesions after fuzzy c-means segmentation, was collected.

Metabolic network-based identification of plasma markers for non-small cell lung cancer.

Metabolic markers, offering sensitive information on biological dysfunction, play important roles in diagnosing and treating cancers. However, the discovery of effective markers is limited by the lack of well-established metabolite selection approaches. Here, we propose a network-based strategy to uncover the metabolic markers with potential clinical availability for non-small cell lung cancer (NSCLC).

Development and evaluation of the screening performance of a low-cost high-risk screening strategy for breast cancer.

Objective: To develop and evaluate the screening performance of a low-cost high-risk screening strategy for breast cancer in low resource areas.

Methods: Based on the Multi-modality Independent Screening Trial, 6 questionnaire-based risk factors of breast cancer (age at menarche, age at menopause, age at first live birth, oral contraceptive, obesity, family history of breast cancer) were used to determine the women with high risk of breast cancer. The screening performance of clinical breast examination (CBE), breast ultrasonography (BUS), and mammography (MAM) were calculated and compared to determine the optimal screening method for these high risk women.

Interpretation of specification for breast cancer screening, early diagnosis, and treatment management in Chinese women.

Breast cancer has become the most common malignant tumor worldwide. However, the survival rate of breast cancer patients in China is 8% lower compared to that in European and American countries. Insufficient screening coverage and low rate of early detection are key problems.

Improved Classification of Benign and Malignant Breast Lesions Using Deep Feature Maximum Intensity Projection MRI in Breast Cancer Diagnosis Using Dynamic Contrast-enhanced MRI.

Purpose: To develop a deep transfer learning method that incorporates four-dimensional (4D) information in dynamic contrast-enhanced (DCE) MRI to classify benign and malignant breast lesions.

Materials And Methods: The retrospective dataset is composed of 1990 distinct lesions (1494 malignant and 496 benign) from 1979 women (mean age, 47 years ± 10). Lesions were split into a training and validation set of 1455 lesions (acquired in 2015-2016) and an independent test set of 535 lesions (acquired in 2017).

Attenuation of doxorubicin-induced oxidative damage in rat brain by regulating amino acid homeostasis with Astragali Radix.

The nervous system disorders caused by doxorubicin (DOX) are among the severe adverse effects that dramatically reduce the quality of life of cancer survivors. Astragali Radix (AR), a popular herbal drug and dietary supplement, is believed to help treat brain diseases by reducing oxidative stress and maintaining metabolic homeostasis. Here we show the protective effects of AR against DOX-induced oxidative damage in rat brain via regulating amino acid homeostasis.

Nomogram for Early Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Using Dynamic Contrast-enhanced and Diffusion-weighted MRI.

Rationale And Objectives: The study investigated the potential of the combined use of dynamic contrast-enhanced MRI and diffusion-weighted imaging in predicting the pathological complete response (pCR) of neoadjuvant chemotherapy (NAC) after two cycles of NAC.

Materials And Methods: Eighty-seven patients with breast cancer who underwent MR examination before and after two cycles of NAC were enrolled. The patients were randomly assigned to a training cohort and a validation cohort (3:1 ratio).

Distant metastasis prediction via a multi-feature fusion model in breast cancer.

This study aimed to develop a model that fused multiple features (multi-feature fusion model) for predicting metachronous distant metastasis (DM) in breast cancer (BC) based on clinicopathological characteristics and magnetic resonance imaging (MRI). A nomogram based on clinicopathological features (clinicopathological-feature model) and a nomogram based on the multi-feature fusion model were constructed based on BC patients with DM (n=67) and matched patients (n=134) without DM. DM was diagnosed on average (17.

The diagnostic performance of automated versus handheld breast ultrasound and mammography in symptomatic outpatient women: a multicenter, cross-sectional study in China.

Objectives: The purpose of this study was to evaluate the diagnostic performance of automated breast ultrasound (ABUS) for breast cancer by comparing it to handheld ultrasound (HHUS) and mammography (MG).

Methods: A multicenter cross-sectional study was conducted between February 2016 and March 2017 in five tertiary hospitals in China, and 1922 women aged 30-69 years old were recruited. Women aged 30-39 years (group A) underwent ABUS and HHUS, and women aged 40-69 (group B) underwent additional MG.

Treatment-triggered onset and diagnosis of Sheehan syndrome in a multiple myeloma patient.

Background: Sheehan syndrome refers to a series of clinical symptoms resulting from avascular necrosis of anterior pituitary due to various reasons.

Case: We report a case of multiple myeloma patient after one cycle of chemotherapy consisting of bortezomib and dexamethasone diagnosis of Sheehan syndrome with obstinate diarrhea, low blood glucose, and coma symptom, especially, the fluorodeoxyglucose positron emission tomography (FDG-PET) and brain magnetic resonance imaging (MRI) revealed that the manifestations in the saddle area were in accordance with empty sella syndrome. A single administration with lenalidomide was given for both consolidative and maintenance treatment, and satisfactory efficacy was achieved.

Magnetic resonance imaging semantic and quantitative features analyses: an additional diagnostic tool for breast phyllodes tumors.

Objective: This study aimed to differentiate benign and non-benign (borderline/malignant) phyllodes tumors of the breast by the semantic and quantitative features in magnetic resonance imaging (MRI).

Methods: The female patients, diagnosed with phyllodes tumors by MRI and pathological test, were retrospectively selected from December, 2006 to April, 2019. The MRI of benign, borderline and malignant phyllodes tumors was analyzed using 8 semantic features and 20 computed quantitative features from diffuse contrast-enhanced magnetic resonance imaging (DCE-MRI).

Harmine Ameliorates Cognitive Impairment by Inhibiting NLRP3 Inflammasome Activation and Enhancing the BDNF/TrkB Signaling Pathway in STZ-Induced Diabetic Rats.

Diabetes mellitus (DM) is considered a risk factor for cognitive dysfunction. Harmine not only effectively improves the symptoms of DM but also provides neuroprotective effects in central nervous system diseases. However, whether harmine has an effect on diabetes-induced cognitive dysfunction and the underlying mechanisms remain unknown.

Diagnostic performance of automated breast ultrasound and handheld ultrasound in women with dense breasts.

Purpose: As an adjunct to mammography, ultrasound can improve the detection of breast cancer in women with dense breasts. We aimed to evaluate the diagnostic performance of automated breast ultrasound system (ABUS) and handheld ultrasound (HHUS) in Chinese women with dense breasts, both in combination with mammography and separately.

Methods: This is a cross-sectional multicenter clinical research study.

Harmonization of radiomic features of breast lesions across international DCE-MRI datasets.

Radiomic features extracted from medical images acquired in different countries may demonstrate a batch effect. Thus, we investigated the effect of harmonization on a database of radiomic features extracted from dynamic contrast-enhanced magnetic resonance (DCE-MR) breast imaging studies of 3150 benign lesions and cancers collected from international datasets, as well as the potential of harmonization to improve classification of malignancy. Eligible features were harmonized by category using the ComBat method.