Radiology

Imaging and AI in tertiary prevention of lung cancer: Narrative review and clinical perspectives.

OBJECTIVE: To provide a structured narrative review of current evidence and future directions for artificial intelligence (AI) applications in the tertiary prevention of lung cancer, with a focus on radiology-driven recurrence surveillance, treatment response assessment, prognostic stratification, and real-world clinical implementation. METHODS: A narrative review was conducted using PubMed, Embas...

Deep learning model for noninvasive prediction of Ki-67 expression and prognostic stratification in breast cancer: a multicenter retrospective study.

OBJECTIVE: Ki-67 correlates with prognosis for patients with breast cancer. However, the evaluation of Ki-67expression relies on pathological analysis and invasive biopsy, which hinders its wide adoption. This work sought to develop a noninvasive Ki-67 prediction model for breast cancer patients through ultrasound and clinical information and evaluate model performance in risk stratification of ly...

Incremental diagnostic value of multiregional single-slice CT muscle areas over L3 for sarcopenia: a deep learning-based segmentation study.

OBJECTIVE: To compare the diagnostic performance of multiregional CT-based muscle assessment with conventional single-level (L3) evaluation. MATERIALS...

Reconstruction algorithms and arm positioning effects on abdominal CT image quality and radiation dose: a phantom study.

OBJECTIVE: To evaluate the effects of arm positioning and reconstruction algorithms on radiation dose and image quality of abdominal CT. MATERIALS AND...

The MR quality landscape in Europe.

OBJECTIVES: Over the last few years, with the introduction of advanced MR imaging techniques, increasing exam demand and the growth of multi-center cl...

A Segmentation-Guided Feature Alignment and Fusion Network for Glioma IDH Genotyping.

Isocitrate dehydrogenase (IDH) is a pivotal molecular marker for glioma diagnosis, prognosis, and treatment planning. Multi-modal deep learning method...

Autoencoder/RandomForest-TabPFN for Cross-Cancer Metabolomics: Prostate and Breast Cancer Diagnosis Using Paper Spray and Ion Mobility-Mass Spectrometry Techniques.

Accurate and rapid disease diagnosis, particularly in prostate cancer (PC) and breast cancer (BC), is critical for early intervention and improved pat...

The application of Artificial Intelligence in the ultrasound-based diagnosis of liver disease: current status, hurdles, and prospects.

Over the past decade, there has been marked progress in artificial intelligence (AI) and its application in medicine. In the field of hepatology, AI c...

Development and Clinical Validation of an Automated Artificial Intelligence System for Bowel Wall Thickness Assessment in Adult Inflammatory Bowel Diseases.

PURPOSE: Intestinal ultrasound (IUS) is used to assess and monitor inflammatory bowel disease (IBD). Bowel wall thickness (BWT) is its key marker, but...

Enhancing 1p/19q Classification in Brain Gliomas Using IDH Status: A Deep Learning Study.

BACKGROUND AND PURPOSE: IDH mutation & 1p/19q codeletion are critical biomarkers for glioma diagnosis & therapy. 1p/19q codeletion occurs exclusively ...

Adnexal torsion diagnosis framework with CT-based adaptive preprocessing and deep neural networks.

Adnexal cystic torsion is a gynecological emergency that requires prompt and accurate diagnosis followed by immediate surgical intervention to preserv...

A step-by-step guide for implementation of virtual surgical applications and patient data centralization: practical experience and lessons learned.

BACKGROUND: The expansion of digitalization in the pre-, intra- and post-operative surgical phases allow the development and integration of advanced t...

Real-time artificial intelligence-based needle tracking for ultrasound-guided regional anesthesia training: a pilot prospective randomized controlled trial.

BACKGROUND: Proper needle visualization is a major technical challenge for novices learning ultrasound-guided regional anesthesia (UGRA). We developed...

The value of the serum cytokine-to-immune ratio model in predicting the progression-free survival after interventional therapy for hepatocellular carcinoma.

OBJECTIVE: To develop and validate a prognostic nomogram for predicting progression-free survival (PFS) in patients with hepatocellular carcinoma (HCC...

Artificial intelligence in ovarian pathophysiology and management: a systematic review and meta-analysis.

BACKGROUND: The integration of artificial intelligence (AI) into reproductive medicine and gynecologic oncology has driven transformative advances in ...

Classification of marine plastic debris using hyperspectral imaging and band selection: A patch-based and pixel-based fusion approach.

Marine plastic pollution poses significant ecological, economic, and social challenges, requiring innovative monitoring and identification solutions t...

Decreasing Administrative Effort Related to Non-Approval of Image-guidED Procedures Using Large Language Models - The DENIED-AI Pilot Study.

RATIONALE AND OBJECTIVES: To evaluate whether large language models (LLMs) can generate accurate, clinically valid, and usable letters to appeal insur...

The Role of Digital Pathology in Optimizing the Quality and Timeliness of Intraoperative Consultation.

BackgroundIntraoperative consultation using frozen sections has been crucial for guiding surgical decisions, but has often been limited by the time an...

Automatic Extraction of PET RANO Criteria with an Externally Validated Deep Learning Model: Application to [18F]FDOPA PET Imaging.

BACKGROUND: Automatic segmentation of gliomas on amino acid PET is essential for quantitative tumor assessment, a pillar in monitoring gliomas under t...

Artificial Intelligence Sees the Image, Radiologists See the Patient.

Radiology is often portrayed as the medical specialty most vulnerable to replacement by artificial intelligence (AI), potentially impacting medical st...