Pixel-level transformer GAN for enhanced parametric mapping of DCE MRI analysis.

Background: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays a crucial role in the diagnosis and monitoring of cancers, as it reveals physiological and vascular characteristics of tumors. Traditional pharmacokinetic modeling necessitates high temporal resolution, resulting in relatively low signal-to-noise ratio (SNR) and spatial resolution with limited allocated time for each phase.

Purpose: To explore the feasibility of using deep learning with sparse DCE MRI phases to generate dense temporal resolution DCE-MRI-derived parametric map.

The value of dual-energy spectral CT in differentiating the pathological grades of T1-size lung adenocarcinoma.

Background: Accurate preoperative diagnosis of pathological grades in T1-sized lung adenocarcinoma (LUAD) is crucial for clinical decision-making. The study aimed to investigate the value of dual-energy computed tomography (DECT) in distinguishing pathological grades in newly diagnosed LUAD lesions ≤3 cm in size.

Methods: From October 2018 to January 2022, 137 patients with 161 pathologically confirmed LUAD lesions (≤3 cm) having received DECT were retrospectively enrolled with clinical information collected (low-grade: high-grade =41:120).

Ophthalmic changes are associated with visual cortex functional network reorganization after 90-day head-down tilt bed rest.

Background: The microgravity-induced cephalad fluid shift is thought to contribute to neuro-ophthalmological changes such as optic disc edema, globe flattening, and hyperopic shift. However, the effects of prolonged simulated microgravity on ophthalmic alterations and their potential relationship with functional reorganization in the visual cortex remain unclear. This study aimed to address these knowledge gaps.

The role of guardians in preventing unintentional injuries among rural children: a mixed-methods study.

Background: Unintentional injuries are a leading public health concern for children, particularly in rural areas of low- and middle-income countries. Guardians are important in injury prevention, yet few studies have systematically examined guardian-related factors in rural areas of China. This study investigates the association between guardian-related factors and unintentional injuries among children in Hunan Province and proposes a three-stage prevention strategy.

Silencing PPA1 promotes the survival of non-small cell lung cancer A549 cells under glucose-starved conditions.

Background: Non-small cell lung cancer (NSCLC) is a malignant tumor with extremely high morbidity and mortality. The large demand for energy during its progression is highly dependent on glucose. The energy metabolism enzyme inorganic pyrophosphatase 1 (PPA1) can mediate the progression of NSCLC through various pathways.

Predictive value of CT-based imaging model for gene mutation in patients with colorectal cancer: a retrospective study.

Background: In colorectal cancer, the gene mutations are associated with adverse clinical outcomes and therapeutic resistance. Radiomics, a quantitative imaging analysis approach, enables high-throughput extraction of tumor features from computed tomography (CT) scans to develop predictive models. This study aimed to explore the predictive value of CT imaging model for gene mutation in patients with colorectal cancer and provide a reference for clinical practice.

FE-DIC-Based Motion and Intensity Correction for Enhanced CEST-MRI Registration.

Physiological and external motion cause inter-frame misalignment in chemical exchange saturation transfer magnetic resonance imaging (CEST-MRI), thereby compromising quantitative accuracy. In CEST-MRI, saturation effects induce intensity variations, resulting in motion-intensity coupling that makes registration particularly challenging. To address this issue, we extend the finite element digital image correlation (FE-DIC) framework by introducing an alternating correction strategy that iteratively refines both motion and intensity estimation.

Spatial-Temporal Information Fusion for Thyroid Nodule Segmentation in Dynamic Contrast-Enhanced MRI: A Novel Approach.

This study aims to develop a novel segmentation method that utilizes spatio-temporal information for segmenting two-dimensional thyroid nodules on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Leveraging medical morphology knowledge of the thyroid gland, we designed a semi-supervised segmentation model that first segments the thyroid gland, guiding the model to focus exclusively on the thyroid region. This approach reduces the complexity of nodule segmentation by filtering out irrelevant regions and artifacts.

Intercellular Adhesion Molecule 3: Structure, Cellular Functions, and Emerging Role in Human Diseases.

The intercellular adhesion molecule 3 (ICAM3), also known as CD50, is a member of the intercellular adhesion molecule (ICAM) family. All ICAM proteins are type I transmembrane glycoproteins containing 2-9 immunoglobulin-like C2-type structural domains and bind to the lymphocyte function-associated antigen-1 (LFA-1) protein. ICAM3 is abundantly and constitutively expressed in all leukocytes and is probably the most important ligand for LFA-1 in initiating immune responses.

Radiomic features add incremental benefit to conventional radiological feature-based differential diagnosis of lung nodules.

Purpose: To investigate the incremental benefit of adding radiomic features to conventional semantic radiological feature-based differential diagnosis between benign and malignant lung nodules.

Methods: From May 2017 to March 2021, 393 patients with 465 pathologically confirmed lung nodules were enrolled with 54 patients with 54 lung nodules as external testing. Based on manually segmented lung nodules, 1409 radiomics features were extracted.

Baseline computed tomography imaging findings could assist in early diagnosis of visceral pleural invasion for newly discovered early subpleural non-small cell lung cancer: T1 or T2.

Background: Preoperative accurate visceral pleural infiltration (VPI) diagnosis for T1-size non-small cell lung cancer (NSCLC) is significant for clinical decision-making. The study aimed to explore the diagnostic efficacy of computed tomography (CT) imaging features and serum biomarkers in diagnosing VPI in newly discovered subpleural NSCLC ≤3 cm.

Methods: There were 447 patients with NSCLC ≤3 cm retrospectively enrolled and assigned to the VPI group (n=81) and the non-VPI group (n=366) based on elastic fiber staining results.

Research Trends and Evolution in Radiogenomics (2005-2023): Bibliometric Analysis.

Background: Radiogenomics is an emerging technology that integrates genomics and medical image-based radiomics, which is considered a promising approach toward achieving precision medicine.

Objective: The aim of this study was to quantitatively analyze the research status, dynamic trends, and evolutionary trajectory in the radiogenomics field using bibliometric methods.

Methods: The relevant literature published up to 2023 was retrieved from the Web of Science Core Collection.

Deregulation of immune response contributing to fulminant hepatitis in HEV infected pregnant women.

Hepatitis E virus (HEV) infection in pregnant women is associated with a wide spectrum of adverse consequences for both mother and fetus. The high mortality in this population appears to be associated with hormonal changes and consequent immunological changes. This study conducted an analysis of immune responses in pregnant women infected with HEV manifesting varying severity.

A two-stage deep-learning framework for CT denoising based on a clinically structure-unaligned paired data set.

Background: In low-dose computed tomography (LDCT) lung cancer screening, soft tissue is hardly appreciable due to high noise levels. While deep learning-based LDCT denoising methods have shown promise, they typically rely on structurally aligned synthesized paired data, which lack consideration of the clinical reality that there are no aligned LDCT and normal-dose CT (NDCT) images available. This study introduces an LDCT denoising method using clinically structure-unaligned but paired data sets (LDCT and NDCT scans from the same patients) to improve lesion detection during LDCT lung cancer screening.

Analysis of preoperative computed tomography radiomics and clinical factors for predicting postsurgical recurrence of papillary thyroid carcinoma.

Background: Postsurgical recurrence is of great concern for papillary thyroid carcinoma (PTC). We aim to investigate the value of computed tomography (CT)-based radiomics features and conventional clinical factors in predicting the recurrence of PTC.

Methods: Two-hundred and eighty patients with PTC were retrospectively enrolled and divided into training and validation cohorts at a 6:4 ratio.

An interactive nuclei segmentation framework with Voronoi diagrams and weighted convex difference for cervical cancer pathology images.

Nuclei segmentation is crucial for pathologists to accurately classify and grade cancer. However, this process faces significant challenges, such as the complex background structures in pathological images, the high-density distribution of nuclei, and cell adhesion.In this paper, we present an interactive nuclei segmentation framework that increases the precision of nuclei segmentation.

Voxel-wise mapping of DCE-MRI time-intensity-curve profiles enables visualizing and quantifying hemodynamic heterogeneity in breast lesions.

Objectives: To propose a novel model-free data-driven approach based on the voxel-wise mapping of DCE-MRI time-intensity-curve (TIC) profiles for quantifying and visualizing hemodynamic heterogeneity and to validate its potential clinical applications.

Materials And Methods: From December 2018 to July 2022, 259 patients with 325 pathologically confirmed breast lesions who underwent breast DCE-MRI were retrospectively enrolled. Based on the manually segmented breast lesions, the TIC of each voxel within the 3D whole lesion was classified into 19 subtypes based on wash-in rate (nonenhanced, slow, medium, and fast), wash-out enhancement (persistent, plateau, and decline), and wash-out stability (steady and unsteady), and the composition ratio of these 19 subtypes for each lesion was calculated as a new feature set (type-19).

Spectral CT assists differentiation of osteoblastic bone metastasis from bone island in newly diagnosed cancer patients.

Objectives: To investigate measurements derived from plain and enhanced spectral CT in differentiating osteoblastic bone metastasis (OBM) from bone island (BI).

Materials And Methods: From January to November 2020, 73 newly diagnosed cancer patients with 201 bone lesions (OBM = 92, BI = 109) having received spectral CT were retrospectively enrolled. Measurements including CT values of 40-140 keV, slope of the spectral curve, effective atomic number (Z), water (calcium) density, calcium (water) density, and Iodine (calcium) density were derived from manually segmented lesions on plain and enhanced spectral CT, and then analyzed using Student t-test and Pearson's correlation.

A deep learning model based on the attention mechanism for automatic segmentation of abdominal muscle and fat for body composition assessment.

Background: Quantitative muscle and fat data obtained through body composition analysis are expected to be a new stable biomarker for the early and accurate prediction of treatment-related toxicity, treatment response, and prognosis in patients with lung cancer. The use of these biomarkers can enable the adjustment of individualized treatment regimens in a timely manner, which is critical to further improving patient prognosis and quality of life. We aimed to develop a deep learning model based on attention for fully automated segmentation of the abdomen from computed tomography (CT) to quantify body composition.

Utility of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) to predict prognosis and survival risk in laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy.

Purpose: To investigate the predictive power of mono-exponential, bi-exponential, and stretched exponential signal models of intravoxel incoherent motion (IVIM) in prognosis and survival risk of laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC) patients after chemoradiotherapy.

Materials And Methods: Forty-five patients with laryngeal or hypopharyngeal squamous cell carcinoma were retrospectively enrolled. All patients had undergone pretreatment IVIM examination, subsequently, mean apparent diffusion coefficient (ADCmean), maximum ADC (ADCmax), minimum ADC (ADCmin) and ADCrange (ADCmax - ADCmean) by mono-exponential model, true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f) by bi-exponential model, distributed diffusion coefficient (DDC), and diffusion heterogeneity index (α) by stretched exponential model were measured.

Added value of histogram analysis of ADC in predicting radiation-induced temporal lobe injury of patients with nasopharyngeal carcinoma treated by intensity-modulated radiotherapy.

Background: This study evaluated the predictive potential of histogram analysis derived from apparent diffusion coefficient (ADC) maps in radiation-induced temporal lobe injury (RTLI) of nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT).

Results: Pretreatment diffusion-weighted imaging (DWI) of the temporal lobes of 214 patients with NPC was retrospectively analyzed to obtain ADC histogram parameters. Of the 18 histogram parameters derived from ADC maps, 7 statistically significant variables in the univariate analysis were included in the multivariate logistic regression analysis.

PPA1, an energy metabolism initiator, plays an important role in the progression of malignant tumors.

Inorganic pyrophosphatase (PPA1) encoded by PPA1 gene belongs to Soluble Pyrophosphatases (PPase) family and is expressed widely in various tissues of Homo sapiens, as well as significantly in a variety of malignancies. The hydrolysis of inorganic pyrophosphate (PPi) to produce orthophosphate (Pi) not only dissipates the negative effects of PPi accumulation, but the energy released by this process also serves as a substitute for ATP. PPA1 is highly expressed in a variety of tumors and is involved in proliferation, invasion, and metastasis during tumor development, through the JNK/p53, Wnt/β-catenin, and PI3K/AKT/GSK-3β signaling pathways.

Induction TPF followed by concurrent chemoradiotherapy versus concurrent chemoradiotherapy alone in locally advanced hypopharyngeal cancer: a preliminary analysis of a randomized phase 2 trial.

Purpose: Concurrent chemoradiotherapy (CCRT) is a standard treatment choice for locally advanced hypopharyngeal carcinoma. The aim of this study was to investigate whether induction chemotherapy (IC) followed by CCRT is superior to CCRT alone to treat locally advanced hypopharyngeal carcinoma.

Methods And Materials: Patients (n = 142) were randomized to receive two cycles of paclitaxel/cisplatin/5-fluorouracil (TPF) IC followed by CCRT or CCRT alone.