The relationship of fat and muscle measurements with emphysema and bronchial wall thickening in smokers.

Introduction: Differences in body composition in patients with COPD may have important prognostic value and may provide opportunities for patient-specific management. We investigated the relation of thoracic fat and muscle with computed tomography (CT)-measured emphysema and bronchial wall thickening.

Methods: Low-dose baseline chest CT scans from 1031 male lung cancer screening participants from one site were quantified for emphysema, bronchial wall thickening, subcutaneous fat, visceral fat and skeletal muscle.

Design, Implementation, and Validation of a Pulsatile Heart Phantom Pump.

The developments in Computed Tomography (CT) and Magnetic Resonance allow visualization of blood flow in vivo using these techniques. However, validation tests are needed to determine a gold standard. For the validation tests, controllable systems that can generate pulsatile flow are needed.

Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network With Long Short-term Memory for the Automated Detection of Calcified Plaques From Coronary Computed Tomography Angiography.

Purpose: The purpose of this study was to evaluate the accuracy of a novel fully automated deep learning (DL) algorithm implementing a recurrent neural network (RNN) with long short-term memory (LSTM) for the detection of coronary artery calcium (CAC) from coronary computed tomography angiography (CCTA) data.

Materials And Methods: Under an IRB waiver and in HIPAA compliance, a total of 194 patients who had undergone CCTA were retrospectively included. Two observers independently evaluated the image quality and recorded the presence of CAC in the right (RCA), the combination of left main and left anterior descending (LM-LAD), and left circumflex (LCx) coronary arteries.

Impact of Coronary Computerized Tomography Angiography-Derived Plaque Quantification and Machine-Learning Computerized Tomography Fractional Flow Reserve on Adverse Cardiac Outcome.

This study investigated the impact of coronary CT angiography (cCTA)-derived plaque markers and machine-learning-based CT-derived fractional flow reserve (CT-FFR) to identify adverse cardiac outcome. Data of 82 patients (60 ± 11 years, 62% men) who underwent cCTA and invasive coronary angiography (ICA) were analyzed in this single-center retrospective, institutional review board-approved, HIPAA-compliant study. Follow-up was performed to record major adverse cardiac events (MACE).

Methods of computed tomography screening and management of lung cancer in Tianjin: design of a population-based cohort study.

Objective: European lung cancer screening studies using computed tomography (CT) have shown that a management protocol based on measuring lung nodule volume and volume doubling time (VDT) is more specific for early lung cancer detection than a diameter-based protocol. However, whether this also applies to a Chinese population is unclear. The aim of this study is to compare the diagnostic performance of a volume-based protocol with a diameter-based protocol for lung cancer detection and optimize the nodule management criteria for a Chinese population.

Convolutional neural network to predict the local recurrence of giant cell tumor of bone after curettage based on pre-surgery magnetic resonance images.

Objective: To predict the local recurrence of giant cell bone tumors (GCTB) on MR features and the clinical characteristics after curettage using a deep convolutional neural network (CNN).

Methods: MR images were collected from 56 patients with histopathologically confirmed GCTB after curettage who were followed up for 5.8 years (range, 2.

Prognostic value of CT myocardial perfusion imaging and CT-derived fractional flow reserve for major adverse cardiac events in patients with coronary artery disease.

Objectives: The purpose of this study was to analyze the prognostic value of dynamic CT perfusion imaging (CTP) and CT derived fractional flow reserve (CT-FFR) for major adverse cardiac events (MACE).

Methods: 81 patients from 4 institutions underwent coronary computed tomography angiography (CCTA) with dynamic CTP imaging and CT-FFR analysis. Patients were followed-up at 6, 12, and 18 months after imaging.

Robotic versus Freehand Needle Positioning in CT-guided Ablation of Liver Tumors: A Randomized Controlled Trial.

Purpose To compare the accuracy of freehand versus robotic antenna placement in CT-guided microwave ablation (MWA) of liver tumors. Materials and Methods This study was conducted as a prospective single-center nonblinded randomized controlled trial (Netherlands Trial Registry, NTR6023). Eligible study participants had undergone clinically indicated CT-guided MWA of liver tumors and were able to receive a CT contrast agent.

Hybrid control algorithm for flexible needle steering: Demonstration in phantom and human cadaver.

Needles are commonly used in the clinic for percutaneous procedures. The outcome of such procedures heavily depends on accurate placement of the needle. There are two main challenges to achieve high accuracy: First, aligning the needle with the targeted lesion, and second, compensating for the deflection of the needle in the tissue.

Screening for Early Lung Cancer, Chronic Obstructive Pulmonary Disease, and Cardiovascular Disease (the Big-3) Using Low-dose Chest Computed Tomography: Current Evidence and Technical Considerations.

Lung cancer, chronic obstructive pulmonary disease, and cardiovascular disease are highly prevalent in the general population and expected to cause most deaths by 2050. For these "Big-3," treatment might cure, delay, or stop the progression of disease at a very early stage. Lung nodule growth rate (a biomarker for lung cancer), emphysema/air trapping (a biomarker for chronic obstructive pulmonary disease), and coronary artery calcification (a biomarker for cardiovascular disease) are imaging biomarkers of early stages of the Big-3 that can be acquired with low-dose computed tomography (CT).

Coronary CT angiography-derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia.

Objectives: We sought to investigate the diagnostic performance of coronary CT angiography (cCTA)-derived plaque markers combined with deep machine learning-based fractional flow reserve (CT-FFR) to identify lesion-specific ischemia using invasive FFR as the reference standard.

Methods: Eighty-four patients (61 ± 10 years, 65% male) who had undergone cCTA followed by invasive FFR were included in this single-center retrospective, IRB-approved, HIPAA-compliant study. Various plaque markers were derived from cCTA using a semi-automatic software prototype and deep machine learning-based CT-FFR.

Relationship between the number of new nodules and lung cancer probability in incidence screening rounds of CT lung cancer screening: The NELSON study.

Background: New nodules are regularly found after the baseline round of low-dose computed tomography (LDCT) lung cancer screening. The relationship between a participant's number of new nodules and lung cancer probability is unknown.

Methods: Participants of the ongoing Dutch-Belgian Randomized Lung Cancer Screening (NELSON) Trial with (sub)solid nodules detected after baseline and registered as new by the NELSON radiologists were included.

Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFR): Impact of iterative and filtered back projection reconstruction techniques.

Background: The influence of computed tomography (CT) reconstruction algorithms on the performance of machine-learning-based CT-derived fractional flow reserve (CT-FFR) has not been investigated. CT-FFR values and processing time of two reconstruction algorithms were compared using an on-site workstation.

Methods: CT-FFR was computed on 40 coronary CT angiography (CCTA) datasets that were reconstructed with both iterative reconstruction in image space (IRIS) and filtered back-projection (FBP) algorithms.

Feasibility of extracellular volume quantification using dual-energy CT.

ObjectiveTo assess the feasibility of dual energy CT (DECT) to derive myocardial extracellular volume (ECV) and detect myocardial ECV differences without a non-contrast acquisition, compared to single energy CT (SECT). MethodsSubjects (n = 35) with focal fibrosis (n = 17), diffuse fibrosis (n = 10), and controls (n = 9) underwent non-contrast and delayed acquisitions to calculate SECT-ECV. DECT-ECV was calculated using the delayed acquisition and the derived virtual non-contrast images.

An Update on the European Lung Cancer Screening Trials and Comparison of Lung Cancer Screening Recommendations in Europe.

While lung cancer screening has been implemented in the United States, it is still under consideration in Europe. So far, lung cancer screening trials in Europe were not able to replicate the results of the National Lung Screening Trial, but they do show a stage shift in the lung cancers that were detected. While eagerly awaiting the final result of the only lung cancer screening trial with sufficient statistical power, the NELSON trial, a number of European countries and medical societies have published recommendations for lung cancer screening using computed tomography.

Low CT temporal sampling rates result in a substantial underestimation of myocardial blood flow measurements.

The purpose of this study was to evaluate the effect of temporal sampling rate in dynamic CT myocardial perfusion imaging (CTMPI) on myocardial blood flow (MBF). Dynamic perfusion CT underestimates myocardial blood flow compared to PET and SPECT values. For accurate quantitative analysis of myocardial perfusion with dynamic perfusion CT a stable calibrated HU measurement of MBF is essential.

Appropriate screening intervals in low-dose CT lung cancer screening.

Lung cancer screening by low-dose chest CT (LDCT) is now being implemented in the United States, and in Europe it was recently recommended to start planning for implementation. Current lung cancer screening programmes include up to 25 annual LDCTs, plus shorter-term follow-up LDCTs when indicated. However, the choice of a yearly CT scan has not been based on biological mechanisms, and it is questionable whether all persons eligible for lung cancer screening require annual screening.

The impact of dose reduction on the quantification of coronary artery calcifications and risk categorization: A systematic review.

Multiple dose reduction techniques have been introduced for coronary artery calcium (CAC) computed tomography (CT), but few have emerged into clinical practice while an increasing number of patients undergo CAC scanning. We sought to determine to what extend the radiation dose in CAC CT can be safely reduced without a significant impact on cardiovascular disease (CVD) risk stratification. A systematic database-review of articles published from 2002 until February 2018 was performed in Pubmed, WebOfScience, and Embase.

Extracellular volume quantitation using dual-energy CT in patients with heart failure: Comparison with 3T cardiac MR.

Backgrounds: Cardiac magnetic resonance (CMR) T1 mapping and the extracellular volume (ECV) have been developed to quantitative analysis of diffusely abnormal myocardial fibrosis (MF). However, dual-energy CT (DECT) has a potential for calculation of ECV. The aim of this study is to evaluate the feasibility and accuracy of DECT technique in determining the ECV in patients with heart failure, with 3T CMR as the reference.

New Subsolid Pulmonary Nodules in Lung Cancer Screening: The NELSON Trial.

Introduction: Low-dose computed tomography (LDCT) lung cancer screening is recommended in the United States. While new solid nodules after baseline screening have a high lung cancer probability at small size and require lower size cutoff values than baseline nodules, there only is limited evidence on management of new subsolid nodules.

Methods: Within the Dutch-Belgian randomized controlled LDCT lung cancer screening trial (NELSON), 7557 participants underwent baseline screening between April 2004 and December 2006.

Machine learning in cardiac CT: Basic concepts and contemporary data.

Propelled by the synergy of the groundbreaking advancements in the ability to analyze high-dimensional datasets and the increasing availability of imaging and clinical data, machine learning (ML) is poised to transform the practice of cardiovascular medicine. Owing to the growing body of literature validating both the diagnostic performance as well as the prognostic implications of anatomic and physiologic findings, coronary computed tomography angiography (CCTA) is now a well-established non-invasive modality for the assessment of cardiovascular disease. ML has been increasingly utilized to optimize performance as well as extract data from CCTA as well as non-contrast enhanced cardiac CT scans.

Diagnostic reliability of low dose multidetector CT and cone beam CT in maxillofacial trauma-an experimental blinded and randomized study.

Objectives: To assess the diagnostic reliability of low dose multidetector CT (MDCT) and cone beam CT (CBCT) for zygomaticomaxillary fracture diagnosis.

Methods: Unilateral zygomaticomaxillary fractures were inflicted on four out of six fresh frozen human cadaver head specimens. All specimens were scanned using four MDCT and two CBCT imaging protocols of which the radiation exposure was systematically reduced.