CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images.

The development of successful artificial intelligence models for chest X-ray analysis relies on large, diverse datasets with high-quality annotations. While several databases of chest X-ray images have been released, most include disease diagnosis labels but lack detailed pixel-level anatomical segmentation labels. To address this gap, we introduce an extensive chest X-ray multi-center segmentation dataset with uniform and fine-grain anatomical annotations for images coming from five well-known publicly available databases: ChestX-ray8, CheXpert, MIMIC-CXR-JPG, Padchest, and VinDr-CXR, resulting in 657,566 segmentation masks.

Artificial Intelligence Assistance for the Measurement of Full Alignment Parameters in Whole-Spine Lateral Radiographs.

Background: Measuring spinal alignment with radiological parameters is essential in patients with spinal conditions likely to be treated surgically. These evaluations are not usually included in the radiological report. As a result, spinal surgeons commonly perform the measurement, which is time-consuming and subject to errors.

Prognostic role of magnetic resonance imaging of the abdomen with intravenous contrast and magnetic resonance cholangiopancreatography in primary sclerosing cholangitis.

Objective: To evaluate the usefulness of Anali scores, determined by magnetic resonance imaging, for predicting the prognosis of primary sclerosing cholangitis (PSC) and to analyze interobserver variability, as well as to assess the impact of periportal edema and heterogeneous signal intensity on diffusion-weighted imaging of the liver.

Materials And Methods: This was a retrospective cohort study of 29 patients with PSC and baseline magnetic resonance imaging. Anali scores, without gadolinium (0-5 points) and with gadolinium (0-2 points), were calculated by two radiologists.

Measuring the Delay in the Referral of Unstable Vertebral Metastasis to the Spine Surgeon: A Retrospective Study in a Latin American Institution.

Background: The delay in the referral of patients with potential surgical vertebral metastasis (VM) to the spine surgeon is strongly associated with a worse outcome. The spinal instability neoplastic score (SINS) allows for determining the risk of instability of a spine segment with VM; however, it is almost exclusively used by specialists or residents in neurosurgery or orthopedics. The objective of this work is to report the delay in surgical consultation of patients with potentially unstable and unstable VM (SINS >6) at our center.

Radiomics and Machine Learning for prediction of two-year disease-specific mortality and KRAS mutation status in metastatic colorectal cancer.

Purpose: Colorectal cancer is usually accompanied by liver metastases. The prediction of patient evolution is essential for the choice of the appropriate therapy. The aim of this study is to develop and evaluate machine learning models to predict KRAS gene mutations and 2-year disease-specific mortality from medical images.

User Satisfaction with an AI System for Chest X-Ray Analysis Implemented in a Hospital's Emergency Setting.

The acceptance of artificial intelligence (AI) systems by health professionals is crucial to obtain a positive impact on the diagnosis pathway. We evaluated user satisfaction with an AI system for the automated detection of findings in chest x-rays, after five months of use at the Emergency Department. We collected quantitative and qualitative data to analyze the main aspects of user satisfaction, following the Technology Acceptance Model.

Hydatid liver disease with portal vein invasion, cavernous transformation and portal biliopathy.

Hydatid disease is a zoonotic parasitic disease, most commonly affecting the liver, lungs and nervous system. Portal vein involvement by hydatid cyst disease is very rare with only few cases published to our knowledge. We describe a case involving a 53-year-old woman with portal vein invasion, cavernous transformation and portal biliopathy.

Follicular Cholecystitis Mimicking Xanthogranulomatous Cholecystitis and Malignancy: A Case Report.

Chronic follicular cholecystitis (CFC) is a rare pathology characterized by prominent lymphoid follicles in the lamina propria distributed throughout the gallbladder wall. It has also been mentioned in the literature as lymphoid hyperplasia and pseudolymphoma. CFC represents less than 2% of cholecystectomies.