Lung Cancer

Radiomics-based IVIM-DWI for early noninvasive assessment of renal allograft dysfunction.

OBJECTIVE: To develop and rigorously validate radiomics-based predictive models using postoperative intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) MRI for the early, noninvasive assessment of impaired renal allograft function (IRF) in kidney transplant recipients. METHODS: This retrospective study included 97 kidney transplant recipients (mean age, 36.77 ± 10.71 years), categor...

Predictive value of artificial intelligence-based quantitative CT feature analysis for diagnosing the pathological types of pulmonary nodules.

OBJECTIVES: Accurate preoperative classification of pulmonary nodules (PNs) is critical for guiding clinical decision-making and preventing overtreatment. This study aims to evaluate the predictive performance of artificial intelligence (AI)-based quantitative computed tomography (CT) feature analysis in differentiating among four pathological types of PNs: atypical adenomatous hyperplasia and ade...

Automated detection and characterization of small cell lung cancer liver metastasis on computed tomography.

PURPOSE: Small cell lung cancer (SCLC) is an aggressive disease with diverse phenotypes that reflect the heterogeneous expression of tumor-related gen...

Radiation Risk in 2D Mammography Screening: A Scoping Review of Modelling Strategies and Emerging AI Applications.

Breast cancer is the most commonly diagnosed cancer among women worldwide, and concerns regarding radiation exposure from mammography screening remain...

Preferences for Adopting Artificial Intelligence in Radiation Therapy Treatment: A Discrete Choice Experiment.

OBJECTIVES: The integration of artificial intelligence (AI) in radiation therapy offers significant potential to enhance cancer care by improving diag...

Photon-counting detector computed tomography in thoracic oncology: revolutionizing tumor imaging through precision and detail.

Photon-counting detector computed tomography (PCD-CT) is an emerging imaging technology that promises to overcome the limitations of conventional ener...

Refining the Classroom: The Self-Supervised Professor Model for Improved Segmentation of Locally Advanced Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer-related deaths, with accurate staging being critical for treatment planning. Auto...

Performance of a Novel Frameless and Maskless Robotic Head Motion Compensation System for Stereotactic Radiosurgery in a Realistic Clinical Environment with Healthy Volunteers.

PURPOSE: Stereotactic radiosurgery (SRS) is a nonsurgical method for treating brain abnormalities and small tumors. Traditional high-accuracy SRS requ...

Dose Reduction in 4-Dimensional Computed Tomography Imaging: Breathing Signal-Guided Deep Learning-Driven Data Acquisition.

PURPOSE: Four-dimensional computed tomography (4D CT) imaging is essential for radiation therapy planning in thoracic tumors. However, current protoco...

Current State-of-the-Art 3D MRI Sequences for Assessing Bone Morphology with Emphasis on Cranial and Spinal Imaging: A Narrative Review.

Traditionally, CT has been the go-to method for visualizing bone structures, while MRI has been preferred for assessing soft tissues, because structur...

Multimodal deep learning method based on multiple spectra for lung cancer early diagnosis.

Lung cancer remains one of the most lethal malignancies worldwide, and the early and accurate diagnostic is critical. Traditional diagnostic technique...

A Pilot Study on Quantitative Accuracy and Radiomic Feature Stability of Deep Progressive Learning Reconstruction in NSCLC PET.

Deep progressive learning reconstruction (DPR) is a novel deep learning-based algorithm for PET imaging, yet its impact on quantitative metrics and ra...

Optimizing guideline-directed medical therapy in chronic kidney disease and type 2 diabetes mellitus patients in primary care.

BACKGROUND: Despite KDIGO (Kidney Disease: Improving Global Outcomes) recommendations for renin-angiotensin-aldosterone system inhibitors (RAASi's) an...

Novel risk calculator predicting long-term survival in pediatric versus adult patients diagnosed with spinal low-grade glioma: a nationwide analysis.

BACKGROUND CONTEXT: Spinal low-grade gliomas (SLGGs) are rare, slow-growing central nervous system tumors affecting both pediatric and adult populatio...

Screening for Barrett Esophagus and Esophageal Adenocarcinoma: Approaches and Outcomes.

Barrett esophagus (BE) is the only known histological precursor to esophageal adenocarcinoma (EAC). The incidence of EAC has risen significantly over ...

Spatial imaging features derived from SUVmax location in resectable NSCLC are associated with tumor aggressiveness.

PURPOSE: Accurate non-invasive prediction of histopathologic invasiveness and recurrence risk remains a clinical challenge in resectable non-small cel...

Determining the Survival Impact and Cost-Effectiveness of Multi-Gene Panel Sequencing in Metastatic Colorectal Cancer With Super Learning Approaches.

OBJECTIVE: To determine the effectiveness and cost-effectiveness of multi-gene panel sequencing compared to single-gene KRAS testing for metastatic co...

PD-L1 expression scoring using artificial intelligence algorithms in non-small cell lung cancer harbouring ROS1 fusions: potential clinical-biological significance.

BACKGROUND: PD-L1 expression in ROS1-positive non-small cell lung carcinoma (NSCLC) patients remains unclear regarding its possible clinical-biologica...

Development and validation of a transformer-based deep learning model for predicting distant metastasis in non-small cell lung cancer using 18FDG PET/CT images.

BACKGROUND: This study aimed to develop and validate a hybrid deep learning (DL) model that integrates convolutional neural network (CNN) and vision t...

Machine learning modeling and analysis of prognostic hub genes in cervical adenocarcinoma: a multi target therapy for enhancement in immunosurveillance.

Endocervical adenocarcinoma (ECA) the fatal and intrusive subtype of cervical carcinoma is on rise from the last decade. Its improper detection leads ...