Multi-Energy Evaluation of Image Quality in Spectral CT Pulmonary Angiography Using Different Strength Deep Learning Spectral Reconstructions.

Rationale And Objectives: To evaluate and compare image quality of different energy levels of virtual monochromatic images (VMIs) using standard versus strong deep learning spectral reconstruction (DLSR) on dual-energy CT pulmonary angiogram (DECT-PA).

Materials And Methods: A retrospective study was performed on 70 patients who underwent DECT-PA (15 PE present; 55 PE absent) scans. VMIs were reconstructed at different energy levels ranging from 35 to 200 keV using standard and strong levels with deep learning spectral reconstruction.

Acute Lung Injury.

Acute lung injury (ALI) is acute pulmonary inflammation with underlying pathology of disruption of the pulmonary vasculature endothelial and alveolar epithelial barriers. ALI is not an uncommon diagnosis and has a myriad of causes including pulmonary infection, (including sepsis), drugs, connective tissue disease, and polytrauma. Patients present clinically with hypoxemia with imaging supportive of bilateral pulmonary findings without pulmonary edema.

Unlocking the clinical potential of paired inspiratory and expiratory CT scans in the differential diagnosis of cystic lung diseases: A systematic review.

Introduction: Currently, high-resolution computed tomography (HRCT) is the imaging of choice for the differential diagnosis of various cystic lung lesions, including true cystic lung diseases (CLD) and lesions that may mimic them. However, the traditionally used inspiratory scan still presents a significant spectrum of overlapping radiological features. Recent studies have demonstrated variation in lesion size between inspiratory and expiratory phases, probably due to cyst-airway communication.

Rethinking how mobile units can catalyze progress on lung cancer screening: a scoping review of what we have learned.

Background: Despite United States Preventive Services Task Force (USPSTF) recommendations, low uptake of lung cancer screening (LCS) highlights the need for measures to promote adoption. This scoping review aims to outline the global landscape of mobile low-dose computed tomography (LDCT) platforms, summarizing research and evaluating efficacy in screening at-risk populations.

Methods: We comprehensively searched Cumulative Index to Nursing and Allied Health Literature (CINAHL), PubMed, Embase, Scopus, and Web of Science for articles published between 2017 and 2023.

Automatic Quantification of Abnormal Lung Parenchymal Attenuation on Chest Computed Tomography Images Using Densitometry and Texture-based Analysis.

Purpose: To compare texture-based analysis using convolutional neural networks (CNNs) against lung densitometry in detecting chest computed tomography (CT) image abnormalities.

Material And Methods: A U-NET was used for lung segmentation, and an ensemble of 7 CNN architectures was trained for the classification of low-attenuation areas (LAAs; emphysema, cysts), normal-attenuation areas (NAAs; normal parenchyma), and high-attenuation areas (HAAs; ground-glass opacities, crazy paving/linear opacity, consolidation). Lung densitometry also computes (LAAs, ≤-950 HU), NAAs (-949 to -700 HU), and HAAs (-699 to -250 HU).

Automated Segmentation of Lymph Nodes on Neck CT Scans Using Deep Learning.

Early and accurate detection of cervical lymph nodes is essential for the optimal management and staging of patients with head and neck malignancies. Pilot studies have demonstrated the potential for radiomic and artificial intelligence (AI) approaches in increasing diagnostic accuracy for the detection and classification of lymph nodes, but implementation of many of these approaches in real-world clinical settings would necessitate an automated lymph node segmentation pipeline as a first step. In this study, we aim to develop a non-invasive deep learning (DL) algorithm for detecting and automatically segmenting cervical lymph nodes in 25,119 CT slices from 221 normal neck contrast-enhanced CT scans from patients without head and neck cancer.

Computed tomography versus ultrasound for the diagnosis of acute cholecystitis: a systematic review and meta-analysis.

Objectives: Some patients undergo both computed tomography (CT) and ultrasound (US) sequentially as part of the same evaluation for acute cholecystitis (AC). Our goal was to perform a systematic review and meta-analysis comparing the diagnostic performance of US and CT in the diagnosis of AC.

Materials And Methods: Databases were searched for relevant published studies through November 2023.

Chronic Chest Computed Tomography Findings Following COVID-19 Pneumonia.

Respiratory symptoms are a frequent manifestation of patients with post-acute sequela of SARS-CoV-2 (PASC), also known as long-COVID. Many cohorts of predominantly hospitalized patients have shown that a significant subset may have persistent chest computed tomography findings for more than 12 months after the acute infection. Proper understanding of the evolving long-term imaging findings and terminology is crucial for accurate imaging interpretation and patient care.

Appropriateness and imaging outcomes of ultrasound, CT, and MR in the emergency department: a retrospective analysis from an urban academic center.

Purpose: To evaluate the appropriateness and outcomes of ultrasound (US), computed tomography (CT), and magnetic resonance (MR) orders in the ED.

Methods: We retrospectively reviewed consecutive US, CT, and MR orders for adult ED patients at a tertiary care urban academic center from January to March 2019. The American College of Radiology Appropriateness Criteria (ACRAC) guidelines were primarily used to classify imaging orders as "appropriate" or "inappropriate".

Diagnostic Performance of MRI for the Detection of Pulmonary Nodules: A Systematic Review and Meta-Analysis.

Purpose To perform a meta-analysis of the diagnostic performance of MRI for the detection of pulmonary nodules, with use of CT as the reference standard. Materials and Methods PubMed, Embase, Scopus, and other databases were systematically searched for studies published from January 2000 to March 2023 evaluating the performance of MRI for diagnosis of lung nodules measuring 4 mm or larger, with CT as reference. Studies including micronodules, nodules without size stratification, or those from which data for contingency tables could not be extracted were excluded.

Lung cancer screening in Brazil: recommendations from the Brazilian Society of Thoracic Surgery, Brazilian Thoracic Association, and Brazilian College of Radiology and Diagnostic Imaging.

Although lung cancer (LC) is one of the most common and lethal tumors, only 15% of patients are diagnosed at an early stage. Smoking is still responsible for more than 85% of cases. Lung cancer screening (LCS) with low-dose CT (LDCT) reduces LC-related mortality by 20%, and that reduction reaches 38% when LCS by LDCT is combined with smoking cessation.

Predicting major adverse cardiovascular events after orthotopic liver transplantation using a supervised machine learning model: A cohort study.

Background: Liver transplant (LT) patients have become older and sicker. The rate of post-LT major adverse cardiovascular events (MACE) has increased, and this in turn raises 30-d post-LT mortality. Noninvasive cardiac stress testing loses accuracy when applied to pre-LT cirrhotic patients.

Evaluating Acute Pulmonary Changes of Coronavirus 2019: Comparative Analysis of the Pertinent Modalities.

This review explores imaging's crucial role in acute Coronavirus Disease 2019 (COVID-19) assessment. High Resolution Computer Tomography is especially effective in detection of lung abnormalities. Chest radiography has limited utility in the initial stages of COVID-19 infection.