Lung Cancer

Synthesizing [F]PSMA-1007 PET bone images from CT images with GAN for early detection of prostate cancer bone metastases: a pilot validation study.

BACKGROUND: [F]FDG PET/CT scan combined with [F]PSMA-1007 PET/CT scan is commonly conducted for detecting bone metastases in prostate cancer (PCa). However, it is expensive and may expose patients to more radiation hazards. This study explores deep learning (DL) techniques to synthesize [F]PSMA-1007 PET bone images from CT bone images for the early detection of bone metastases in PCa, which may re...

Towards automating risk stratification of intraductal papillary mucinous Neoplasms: Artificial intelligence advances beyond human expertise with confocal laser endomicroscopy.

BACKGROUND AND AIMS: Endoscopic Ultrasound (EUS)-guided needle-based confocal laser endomicroscopy (nCLE) enables real-time microscopic visualization of pancreatic cyst epithelium and can identify high-grade dysplasia/invasive adenocarcinoma (HGD/IC) in branch-duct (BD) intraductal papillary mucinous neoplasms (IPMNs). We aimed to compare the performance of experts (humans) with artificial intelli...

Prognostic effect of CD74 and development of a radiomic model for predicting CD74 expression in non-small cell lung cancer.

BACKGROUND: The classical prognostic indicators of lung cancer are no longer sufficient for prognostic stratification and individualized treatment of ...

Exploring Hidden Dangers: Predicting Mycotoxin-like Toxicity and Mapping Toxicological Networks in Hepatocellular Carcinoma.

Mycotoxins are potent triggers of hepatocellular carcinoma (HCC) due to their intricate interplay with cellular macromolecules and signaling pathways....

Future of image enhanced endoscopy of esophageal adenocarcinoma.

Barrett's esophagus is a premalignant precursor lesion of esophageal adenocarcinoma that affects approximately 1% of the population worldwide. Esophag...

Trading off Iodine and Radiation Dose in Coronary Computed Tomography.

Coronary CT angiography (CCTA) has seen steady progress since its inception, becoming a key player in the non-invasive assessment of coronary artery d...

Exploring the Role of Peritumoral Edema in Predicting Lung Cancer Subtypes Through T2-FLAIR Digital Subtraction Imaging of Metastatic Brain Tumors.

: This study aimed to investigate whether small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) can be distinguished based on radiomics...

Real-time respiratory motion forecasting with online learning of recurrent neural networks for accurate targeting in externally guided radiotherapy.

BACKGROUND AND OBJECTIVE: In lung radiotherapy, infrared cameras can track reflective objects on the chest to estimate tumor motion due to breathing. ...

Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.

INTRODUCTION: Prostate adenocarcinoma (PRAD) is an extremely widespread site of urological malignancy and is the second most common male cancer in the...

Classification of non-small cell lung cancer by histologic subtype using deep learning in public and private data sets of computed tomography images.

OBJECTIVE: To develop a deep learning system to classify non-small cell lung cancer (NSCLC) by histologic subtype-adenocarcinoma or squamous cell carc...

Non-invasive CT based multiregional radiomics for predicting pathologic complete response to preoperative neoadjuvant chemoimmunotherapy in non-small cell lung cancer.

PURPOSE: This study aims to develop and validate a multiregional radiomics model to predict pathological complete response (pCR) to neoadjuvant chemoi...

Non-orthogonal kV imaging guided patient position verification in non-coplanar radiation therapy with dataset-free implicit neural representation.

BACKGROUND: Cone-beam CT (CBCT) is crucial for patient alignment and target verification in radiation therapy (RT). However, for non-coplanar beams, p...

Study on the relationship between vaginal dose and radiation-induced vaginal injury following cervical cancer radiotherapy, and model development.

OBJECTIVE: This study investigates the relationship between vaginal radiation dose and radiation-induced vaginal injury in cervical cancer patients, w...

Radiomics of Dynamic Contrast-Enhanced MRI for Predicting Radiation-Induced Hepatic Toxicity After Intensity Modulated Radiotherapy for Hepatocellular Carcinoma: A Machine Learning Predictive Model Based on the SHAP Methodology.

OBJECTIVE: To develop an interpretable machine learning (ML) model using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomic data,...

Emerging research themes in ferroptosis research for non-small cell lung cancer: a bibliometric and visualized analysis.

BACKGROUND: Ferroptosis, an iron-dependent form of regulated cell death, has garnered significant attention as a potential therapeutic target in oncol...

2.5D Multi-view Averaging Diffusion Model for 3D Medical Image Translation: Application to Low-count PET Reconstruction with CT-less Attenuation Correction.

Positron Emission Tomography (PET) is an important clinical imaging tool but inevitably introduces radiation exposure to patients and healthcare provi...

A novel model for predicting immunotherapy response and prognosis in NSCLC patients.

BACKGROUND: How to screen beneficiary populations has always been a clinical challenge in the treatment of non-small-cell lung cancer (NSCLC) with imm...

External Validation of a CT-Based Radiogenomics Model for the Detection of EGFR Mutation in NSCLC and the Impact of Prevalence in Model Building by Using Synthetic Minority Over Sampling (SMOTE): Lessons Learned.

RATIONALE AND OBJECTIVES: Radiogenomics holds promise in identifying molecular alterations in nonsmall cell lung cancer (NSCLC) using imaging features...

Assembling ″Balloon-String″ Colorimetric Probes through Click Chemistry and Hybridization Chain Reaction for Dual-Signal Amplification in Aptamer-Based Lateral Flow Assays.

As a simple and visually assessable point-of-care testing method, lateral flow assays (LFAs) are widely used for detecting procymidone in vegetable sa...

An integrated machine learning-based prognostic model in head and neck cancer using the systemic inflammatory response index and correlations with patient reported financial toxicity.

OBJECTIVE: To investigate the prognostic utility of systemic inflammatory response index (SIRI) as a biological readout of stress associated immune mo...