Semi-supervised Long-tail Endoscopic Image Classification.

Objective To explore the semi-supervised learning (SSL) algorithm for long-tail endoscopic image classification with limited annotations. Method We explored semi-supervised long-tail endoscopic image classification in HyperKvasir, the largest gastrointestinal public dataset with 23 diverse classes. Semi-supervised learning algorithm FixMatch was applied based on consistency regularization and pseudo-labeling.

Identifying neuroimaging biomarkers for psychogenic erectile dysfunction by fusing multi-level brain information: A resting-state functional magnetic resonance imaging study.

Background: Psychogenic erectile dysfunction (pED) patients who are under their 40s in China consist of a major component of erectile dysfunction. Existing neuroimaging studies have demonstrated that pED is a functional disorder with aberrant neural representations on the local level, the regional level, and the global level, respectively. Therefore, it is reasonable to incorporate brain information from all these levels simultaneously into consideration when identifying neuroimaging biomarkers for pED.

A deep learning-based system for survival benefit prediction of tyrosine kinase inhibitors and immune checkpoint inhibitors in stage IV non-small cell lung cancer patients: A multicenter, prognostic study.

Background: For clinical decision making, it is crucial to identify patients with stage IV non-small cell lung cancer (NSCLC) who may benefit from tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs). In this study, a deep learning-based system was designed and validated using pre-therapy computed tomography (CT) images to predict the survival benefits of EGFR-TKIs and ICIs in stage IV NSCLC patients.

Methods: This retrospective study collected data from 570 patients with stage IV EGFR-mutant NSCLC treated with EGFR-TKIs at five institutions between 2010 and 2021 (data of 314 patients were from a previously registered study), and 129 patients with stage IV NSCLC treated with ICIs at three institutions between 2017 and 2021 to build the ICI test dataset.

Radiomics-Based Preoperative Prediction of Lymph Node Metastasis in Intrahepatic Cholangiocarcinoma Using Contrast-Enhanced Computed Tomography.

Background: Lymph node (LN) metastasis is significantly associated with worse prognosis for patients with intrahepatic cholangiocarcinoma (ICC). Improvement in preoperative assessment on LN metastasis helps in treatment decision-making. We aimed to investigate the role of radiomics-based method in predicting LN metastasis for patients with ICC.

Real-World Visual Experience Alters Baseline Brain Activity in the Resting State: A Longitudinal Study Using Expertise Model of Radiologists.

Visual experience modulates the intensity of evoked brain activity in response to training-related stimuli. Spontaneous fluctuations in the restful brain actively encode previous learning experience. However, few studies have considered how real-world visual experience alters the level of baseline brain activity in the resting state.

Texture analysis of SPECT myocardial perfusion provides prognostic value for dilated cardiomyopathy.

Background: Texture analysis (TA) has demonstrated clinical values in extracting information, quantifying inhomogeneity, evaluating treatment outcomes, and predicting long-term prognosis for cardiac diseases. The aim of this study was to explore whether TA of SPECT myocardial perfusion could contribute to improving the prognosis of dilated cardiomyopathy (DCM) patients.

Methods: Eighty-eight patients were recruited in our study between 2009 and 2020 who were diagnosed with DCM and underwent single-photon emission tomography myocardial perfusion imaging (SPECT MPI).

Knowledge-guided multi-task attention network for survival risk prediction using multi-center computed tomography images.

Accurate preoperative prediction of overall survival (OS) risk of human cancers based on CT images is greatly significant for personalized treatment. Deep learning methods have been widely explored to improve automated prediction of OS risk. However, the accuracy of OS risk prediction has been limited by prior existing methods.

Optimization of ODAP-Urea-based dual-modality PSMA targeting probes for sequential PET-CT and optical imaging.

Prostate-specific membrane antigen (PSMA) is emerging as a promising target to specifically image prostate cancer. Dual-modality probe combining radionuclide imaging and near-infrared fluorescence navigation targeting PSMA would enable both the preoperative staging and intraoperative detection of the tumor lesions. To overcome one of the key barriers for achieving high contrast imaging at both early and late time points, we optimized the pharmacokinetics of dual-modality probes based on oxalyldiaminopropionic acid-urea (ODAP-Urea) PSMA inhibitors recently developed.

Novel fluorescent GLUT1 inhibitor for precision detection and fluorescence image-guided surgery in oral squamous cell carcinoma.

Early detection and complete resection of oral squamous cell carcinoma (OSCC) are crucial to improving patient survival and prognosis. However, specifically targeted imaging probes for OSCC detection are limited. Our study aimed to synthesize a novel near-infrared fluorescence (NIRF) probe for precision detection and fluorescence image-guided surgery in OSCC.

Functional dyspepsia symptom diary is correlated with other questionnaires and associated with severity in patients with functional dyspepsia: a multicenter, prospective observational study.

Background And Aim: Functional dyspepsia symptom diary (FDSD) is a newly designed questionnaire of functional dyspepsia (FD). The relationships between FDSD and other FD-related questionnaires and patient-reported severity remain unclear. This study aims to investigate the correlations between FDSD and other questionnaires and to determine the relationships between FDSD and FD severity.

Defect self-assembly of metal-organic framework triggers ferroptosis to overcome resistance.

The emergence of multidrug treatment resistance presents a hurdle for the successful chemotherapy of tumours. Ferroptosis, resulting from the iron-dependent accumulation of lipid peroxides, has the potential to reverse multidrug resistance. However, simultaneous delivery of the iron sources, ferroptosis inducers, drugs, and enhanced circulation carriers within matrices remains a significant challenge.

Visual expertise modulates baseline brain activity: a preliminary resting-state fMRI study using expertise model of radiologists.

Background: visual expertise and experience modulate evoked brain activity in response to training-related stimuli. However, few studies have considered how the visual experience is represented in the resting state brain activity. This study tried to investigate the way visual experience, i.

Liposomal Glucose Oxidase for Enhanced Photothermal Therapy and Photodynamic Therapy against Breast Tumors.

Organic near-infrared fluorescent dye mediated photothermal therapy (PTT) and photodynamic therapy (PDT) suffer from heat shock response, since, heat shock proteins (HSPs) are overexpressed and can repair the proteins damaged by PTT and PDT. Starvation therapy by glucose oxide (GOx) can inhibit the heat shock response by limiting the energy supply. However, the delivery of sufficient and active GOx remains a challenge.

Reassessment of the Effect of Transcutaneous Auricular Vagus Nerve Stimulation Using a Novel Burst Paradigm on Cardiac Autonomic Function in Healthy Young Adults.

Background: Transcutaneous auricular vagus nerve stimulation (taVNS) may modulate cardiac autonomic function. However, the response rate of the traditional tonic paradigm is low, and the results remain inconsistent. A recent pilot study presented a novel burst paradigm to activate the cardiac parasympathetic system, which might offer a new approach to treat cardiac autonomic function.

Two-stage deep learning network-based few-view image reconstruction for parallel-beam projection tomography.

Background: Projection tomography (PT) is a very important and valuable method for fast volumetric imaging with isotropic spatial resolution. Sparse-view or limited-angle reconstruction-based PT can greatly reduce data acquisition time, lower radiation doses, and simplify sample fixation modes. However, few techniques can currently achieve image reconstruction based on few-view projection data, which is especially important for PT in living organisms.

Mining whole-lung information by artificial intelligence for predicting EGFR genotype and targeted therapy response in lung cancer: a multicohort study.

Background: Epidermal growth factor receptor (EGFR) genotype is crucial for treatment decision making in lung cancer, but it can be affected by tumour heterogeneity and invasive biopsy during gene sequencing. Importantly, not all patients with an EGFR mutation have good prognosis with EGFR-tyrosine kinase inhibitors (TKIs), indicating the necessity of stratifying for EGFR-mutant genotype. In this study, we proposed a fully automated artificial intelligence system (FAIS) that mines whole-lung information from CT images to predict EGFR genotype and prognosis with EGFR-TKI treatment.

Quantitative hypoxia mapping using a self-calibrated activatable nanoprobe.

Hypoxia is a distinguished hallmark of the tumor microenvironment. Hypoxic signaling affects multiple gene expressions, resulting in tumor invasion and metastasis. Quantification of hypoxic status although challenging, can be useful for monitoring tumor development and aggressiveness.

Predicting microvascular invasion in hepatocellular carcinoma: A dual-institution study on gadoxetate disodium-enhanced MRI.

Background & Aims: Microvascular invasion (MVI) is an important risk factor in hepatocellular carcinoma (HCC), but its diagnosis mandates postoperative histopathologic analysis. We aimed to develop and externally validate a predictive scoring system for MVI.

Methods: From July 2015 to November 2020, consecutive patients underwent surgery for HCC with preoperative gadoxetate disodium (EOB)-enhanced MRI was retrospectively enrolled.

A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions.

Background: For patients with meningioma, surgical procedures are different because of the status of sinus invasion. However, there is still no suitable technique to identify the status of sinus invasion in patients with meningiomas. We aimed to build a deep learning radiomics model to identify sinus invasion before surgery.

Biomimetic manganese-eumelanin nanocomposites for combined hyperthermia-immunotherapy against prostate cancer.

Pro-tumoral and immunosuppressive M2-like tumor-associated macrophages (TAMs) contribute to tumor progression, recurrence and distal metastasis. However, current TAMs-modulating therapeutic strategies often encounter challenges including insufficient immune activation, weak antigen presentation ability and unsatisfactory antitumor immune performance. Herein, cyclic RGD peptide functionalized and manganese doped eumelanin-like nanocomposites (RMnMels) are reported for combined hyperthermia-immunotherapy against PC3 prostate cancer.

Deep learning-based AI model for signet-ring cell carcinoma diagnosis and chemotherapy response prediction in gastric cancer.

Purpose: We aimed to develop a noninvasive artificial intelligence (AI) model to diagnose signet-ring cell carcinoma (SRCC) of gastric cancer (GC) and identify patients with SRCC who could benefit from postoperative chemotherapy based on preoperative contrast-enhanced computed tomography (CT).

Methods: A total of 855 GC patients with 855 single GCs were included, of which 249 patients were diagnosed as SRCC by histopathologic examinations. The AI model was generated with clinical, handcrafted radiomic, and deep learning features.

A Data Self-Calibration Method Based on High-Density Parallel Plate Diffuse Optical Tomography for Breast Cancer Imaging.

When performing the diffuse optical tomography (DOT) of the breast, the mismatch between the forward model and the experimental conditions will significantly hinder the reconstruction accuracy. Therefore, the reference measurement is commonly used to calibrate the measured data before the reconstruction. However, it is complicated to customize corresponding reference phantoms based on the breast shape and background optical parameters of different subjects in clinical trials.

A two-center radiomic analysis for differentiating major depressive disorder using multi-modality MRI data under different parcellation methods.

Background: The present study aimed to explore the difference in the brain function and structure between patients with major depressive disorder (MDD) and healthy controls (HCs) using two-center and multi-modal MRI data, which would be helpful to investigate the pathogenesis of MDD.

Methods: The subjects were collected from two hospitals. One including 140 patients with MDD and 138 HCs was used as primary cohort.

A Potent Strategy of Combinational Blow Toward Enhanced Cancer Chemo-Photodynamic Therapy via Sustainable GSH Elimination.

Excessive glutathione (GSH), which is produced owing to abnormal metabolism of tumor cells, scavenges photo-induced reactive oxygen species (ROS) and consumes chemotherapeutic drugs, thereby attenuating the efficacy of photodynamic therapy and chemotherapy, respectively. Predominant strategies for GSH inhibition involve its chemical depletion, which only leads to a temporary therapeutic effect because GSH is replenished via various compensatory routes in tumor cells. Here, a versatile GSH-inhibiting nanosystem (termed PCNPs) for persistent synergistic therapy of cancer is reported.