Lymphoma

Imaging-based stratification of Claudin 18.2-positive gastric adenocarcinoma using 18F-FDG PET/CT radiomics.

PURPOSE: This study aimed to develop and validate a non-invasive, multimodal radiomics model based on preoperative 1⁸F-FDG PET/CT to predict CLDN18.2 expression in gastric adenocarcinoma (GAC), addressing the limitations of intratumoral heterogeneity and invasiveness associated with endoscopic biopsies. METHODS: This retrospective study enrolled 291 patients with pathologically confirmed GAC who u...

Organ-Aware Cross-Modality Registration Enables Attenuation Correction Without Repeated CT in Multi-Scan Total-Body PET/CT Imaging.

Multi-Scan Total-Body PET/CT imaging, including dual-time-point and multi-tracer protocols, provides valuable metabolic information for enhanced disease diagnosis. However, the necessity for repeated CT scans due to patient repositioning for attenuation correction (AC) increases radiation exposure, raising safety concerns. To address this, we propose a novel organ-aware cross-modality registration...

A fully automated CT-based pelvimetry pipeline for quantifying mid-pelvic surgical workspace in rectal cancer.

PURPOSE: Pelvimetry may aid preoperative planning in rectal cancer surgery, yet manual measurements are time-consuming and MRI-based methods require d...

Mapping intratumoral heterogeneity through PET-derived washout and deep learning after proton therapy.

The distribution of produced isotopes during proton therapy can be imaged with Positron Emission Tomography (PET) to verify dose delivery. However, bi...

Temporal AI-assisted compressed sensing for high-resolution, motion-robust small-bowel MR enterography without antiperistaltic agents: a feasibility study.

OBJECTIVES: To evaluate whether temporal AI-assisted compressed sensing (tACS) enables high-resolution, motion-robust magnetic resonance enterography ...

Predicting CO2 emissions and strength of FA-SF geopolymer mortar: An ANN approach for sustainable construction.

The construction industry is facing increasing pressure to reduce the CO2 emissions from conventional cement manufacturing. Geopolymer concrete, utili...

Evolution of the Diagnostic Paradigm for Giant Cell Arteritis: From Histopathology to Multi-Modal Imaging Integration Running title: GCA: Histology to Imaging.

Giant cell arteritis (GCA) is a systemic vasculitis that predominantly affects mediumand large-sized arteries. Delayed diagnosis may result in irrever...

CT data harmonization via learned virtual monoenergetic imaging for cross-kV scan translation and radiomics reproducibility.

BACKGROUND: Radiomics extracts quantitative imaging features from computed tomography (CT) data for clinical decision-making. However, variations in a...

Interpretable LightGBM model with SHAP analysis predicts non-excellent response to initial radioiodine therapy in differentiated thyroid carcinoma.

PURPOSE: To identify independent determinants influencing therapeutic outcomes of initial radioactive iodine (1 3 1I) therapy in differentiated thyroi...

A metabolite-augmented FIB-4 machine learning panel achieves superior liver fibrosis staging in chronic liver disease.

Accurate, non-invasive liver fibrosis detection is essential for chronic liver disease management, particularly with rising metabolic dysfunction-asso...

Short-chain fatty acid-producing microbes differentiate non-infectious and infectious neutropenic fever in leukemia.

UNLABELLED: Neutropenic fever (NF) is often the first sign of infection in patients with hematologic malignancies, but its cause is frequently unknown...

AI-assessed sarcopenia as an independent predictor of neoadjuvant chemotherapy outcomes in muscle-invasive bladder cancer.

PURPOSE: Sarcopenia has already been widely investigated as a potential indicator of negative outcomes in oncology patients. Our aim was to evaluate t...

Artificial Intelligence in Periodontology: A Systematic Review.

AIM: To provide a comprehensive review of artificial intelligence (AI) applications in periodontology, focusing (1) on deep learning for image-based d...

Automated Echocardiographic Detection of Congenital Heart Disease Using Artificial Intelligence.

BACKGROUND: Delayed or missed diagnosis of congenital heart disease (CHD) contributes to excess pediatric mortality worldwide. Echocardiography (echo)...

A cough sound-based deep learning algorithm for accessible prompt detection of chronic obstructive pulmonary disease with smartphones.

Early COPD diagnosis is vital for effective management, yet conventional tools such as professional spirometers are often inaccessible in resource-lim...

Personalized mapping of body homeostasis using whole-body PET connectomics and routine FDG PET imaging.

BACKGROUND: Immuno-inflammation and systemic alterations are key features of chronic diseases. While PET molecular imaging is widely used in precision...

Impact of an artificial intelligence-driven triage system on workflow and transfer efficiency: stratified analysis of 4548 admissions to four thrombectomy hubs receiving transfers from sixty spokes.

BACKGROUND: We aimed to evaluate the impact of implementing an artificial intelligence (AI)-enabled acute ischaemic stroke triage system on workflow e...

Advanced neuroimaging for central nervous system infections: when, where, how, and why?

PURPOSE OF REVIEW: Central nervous system (CNS) infections remain a major cause of morbidity and mortality worldwide, particularly in children, older ...

Convolutional neural networks detected changes in facial expressions of mice that had conditioned fear stress.

Animal models are essential for studying aversive states such as fear and pain. Facial expressions may provide non-invasive readouts of aversive state...

Identification of Novel Non-coding Genetic Variants of Serum Urate Using Whole Genome Sequencing in 7,339 Chinese.

OBJECTIVE: To investigate the genetic architecture of low-frequency and rare variants of serum urate (SU) in East Asian populations, aiming to clarify...