Imaging of Chronic Thromboembolic Pulmonary Hypertension.

Chronic thromboembolic pulmonary hypertension (CTEPH) is pulmonary hypertension secondary to chronic obstruction of pulmonary arteries by organized thromboemboli. Echocardiography and Echocardiography and ventilation/perfusion (V/Q) scan are the initial screening examinations for CTEPH; the diagnosis is often missed on computed tomography (CT). Imaging findings of chronic thromboembolic pulmonary disease overlap with those of acute pulmonary embolism, and radiologists should evaluate for the presence of concurrent chronic disease in all cases of acute pulmonary embolism detected on CT pulmonary angiography.

Deep Learning Synthetic Strain: Quantitative Assessment of Regional Myocardial Wall Motion at MRI.

Purpose: To assess the feasibility of a newly developed algorithm, called (DLSS), to infer myocardial velocity from cine steady-state free precession (SSFP) images and detect wall motion abnormalities in patients with ischemic heart disease.

Materials And Methods: In this retrospective study, DLSS was developed by using a data set of 223 cardiac MRI examinations including cine SSFP images and four-dimensional flow velocity data (November 2017 to May 2021). To establish normal ranges, segmental strain was measured in 40 individuals (mean age, 41 years ± 17 [SD]; 30 men) without cardiac disease.

Multidisciplinary Approach to Chronic Thromboembolic Pulmonary Hypertension: Role of Radiologists.

Management of chronic thromboembolic pulmonary hypertension (CTEPH) should be determined by a multidisciplinary team, ideally at a specialized CTEPH referral center. Radiologists contribute to this multidisciplinary process by helping to confirm the diagnosis of CTEPH and delineating the extent of disease, both of which help determine a treatment decision. Preoperative assessment of CTEPH usually employs multiple imaging modalities, including ventilation-perfusion (V/Q) scanning, echocardiography, CT pulmonary angiography (CTPA), and right heart catheterization with pulmonary angiography.

Early-stage COVID-19 pandemic observations on pulmonary embolism using nationwide multi-institutional data harvesting.

We introduce a multi-institutional data harvesting (MIDH) method for longitudinal observation of medical imaging utilization and reporting. By tracking both large-scale utilization and clinical imaging results data, the MIDH approach is targeted at measuring surrogates for important disease-related observational quantities over time. To quantitatively investigate its clinical applicability, we performed a retrospective multi-institutional study encompassing 13 healthcare systems throughout the United States before and after the 2020 COVID-19 pandemic.

Automated Deep Learning Analysis for Quality Improvement of CT Pulmonary Angiography.

CT pulmonary angiography (CTPA) is the first-line imaging test for evaluation of acute pulmonary emboli. However, diagnostic quality is heterogeneous across institutions and is frequently limited by suboptimal pulmonary artery (PA) contrast enhancement. In this retrospective study, a deep learning algorithm for measuring enhancement of the central PAs was developed and assessed for feasibility of its use in quality improvement of CTPA.

Reader Perceptions and Impact of AI on CT Assessment of Air Trapping.

Quantitative imaging measurements can be facilitated by artificial intelligence (AI) algorithms, but how they might impact decision-making and be perceived by radiologists remains uncertain. After creation of a dedicated inspiratory-expiratory CT examination and concurrent deployment of a quantitative AI algorithm for assessing air trapping, five cardiothoracic radiologists retrospectively evaluated severity of air trapping on 17 examination studies. Air trapping severity of each lobe was evaluated in three stages: qualitatively (visually); semiquantitatively, allowing manual region-of-interest measurements; and quantitatively, using results from an AI algorithm.

Deep Learning-Based 3D Segmentation of True Lumen, False Lumen, and False Lumen Thrombosis in Type-B Aortic Dissection.

Patients with initially uncomplicated typeB aortic dissection (uTBAD) remain at high risk for developing late complications. Identification of morphologic features for improving risk stratification of these patients requires automated segmentation of computed tomography angiography (CTA) images. We developed three segmentation models utilizing a 3D residual U-Net for segmentation of the true lumen (TL), false lumen (FL), and false lumen thrombosis (FLT).

Artificial intelligence and machine learning in aortic disease.

Purpose Of Review: Discuss foundational concepts for artificial intelligence (AI) and review recent literature on its application to aortic disease.

Recent Findings: Machine learning (ML) techniques are rapidly evolving for the evaluation of aortic disease - broadly categorized as algorithms for aortic segmentation, detection of pathology, and risk stratification. Advances in deep learning, particularly U-Net architectures, have revolutionized segmentation of the aorta and show potential for monitoring the size of aortic aneurysm and characterizing aortic dissection.

CT-based True- and False-Lumen Segmentation in Type B Aortic Dissection Using Machine Learning.

Purpose: To develop a segmentation pipeline for segmentation of aortic dissection CT angiograms into true and false lumina on multiplanar reformations (MPRs) perpendicular to the aortic centerline and derive quantitative morphologic features, specifically aortic diameter and true- or false-lumen cross-sectional area.

Materials And Methods: An automated segmentation pipeline including two convolutional neural network (CNN) segmentation algorithms was developed. The algorithm derives the aortic centerline, generates MPRs orthogonal to the centerline, and segments the true and false lumina.

Left Atrial Volume as a Biomarker of Atrial Fibrillation at Routine Chest CT: Deep Learning Approach.

Purpose: To test the performance of a deep learning (DL) model in predicting atrial fibrillation (AF) at routine nongated chest CT.

Materials And Methods: A retrospective derivation cohort (mean age, 64 years; 51% female) consisting of 500 consecutive patients who underwent routine chest CT served as the training set for a DL model that was used to measure left atrial volume. The model was then used to measure atrial size for a separate 500-patient validation cohort (mean age, 61 years; 46% female), in which the AF status was determined by performing a chart review.

Aortic growth and development of partial false lumen thrombosis are associated with late adverse events in type B aortic dissection.

Background: Patients with medically treated type B aortic dissection (TBAD) remain at significant risk for late adverse events (LAEs). We hypothesize that not only initial morphological features, but also their change over time at follow-up are associated with LAEs.

Materials And Methods: Baseline and 188 follow-up computed tomography (CT) scans with a median follow-up time of 4 years (range, 10 days to 12.

What is the added sensitivity of non-lateral cervical spine radiographs in the evaluation of acute cervical spine trauma?

Purpose: Plain radiography of the cervical spine is used as a screening test for trauma patients. We evaluated the diagnostic yield of performing anteroposterior (AP), odontoid, and oblique views in addition to the lateral view in the current era when radiographs are performed only on low-risk patients.

Methods: All imaging reports from cervical spine radiography studies on patients aged 18 years and older in the emergency room of a major academic medical center between November 22, 2003, and January 17, 2012, were retrospectively reviewed.

Cross-sectional imaging of thoracic traumatic aortic injury.

Aortic injury remains a major contributor to morbidity and mortality from acute thoracic trauma. While such injuries were once nearly uniformly fatal, the advent of cross-sectional imaging in recent years has facilitated rapid diagnosis and triage, greatly improving outcomes. In fact, cross-sectional imaging is now the diagnostic test of choice for traumatic aortic injury (TAI), specifically computed tomography angiography (CTA) in the acute setting and CTA or magnetic resonance angiography (MRA) in follow-up.

Improving Quality of Dynamic Airway Computed Tomography Using an Expiratory Airflow Indicator Device.

Purpose: Dynamic computed tomography (CT) of the airways is increasingly used to evaluate patients with suspected expiratory central airway collapse, but current protocols are susceptible to inadequate exhalation caused by variable patient compliance with breathing instructions during the expiratory phase. We developed and tested a low-cost single-use expiratory airflow indicator device that was designed to improve study quality by providing a visual indicator to both patient and operator when adequate expiratory flow was attained.

Materials And Methods: A total of 56 patients undergoing dynamic airway CT were evaluated, 35 of whom were scanned before introduction of the indicator device (control group), with the rest comprising the intervention group.

Indolent thyroid cancer: knowns and unknowns.

Thyroid cancer incidence is rapidly increasing due to increased detection and diagnosis of indolent thyroid cancer, i.e. cancer that is likely to be clinically insignificant.

Hypertrophic pachymeningitis.

Hypertrophic Pachymeningitis (HP) denotes inflammation and thickening of the dura mater that can be idiopathic or secondary to a wide variety of conditions. Clinically, HP can present as debilitating headaches and cranial nerve defects but in other cases may be completely asymptomatic. We aimed to determine the relative incidence of different etiologies of HP and compare their associated imaging findings.

Radiographic features of potential donor livers that precluded donation.

Objective: The objective of our study was to catalog the anatomic features shown on preoperative CT that precluded living-donor liver donation.

Materials And Methods: We retrospectively reviewed the records of 159 consecutive candidates who were evaluated for potential right or left lobe liver donation from November 2007 to January 2012 using MDCT angiography and cholangiography. For the potential donors who were excluded secondary to findings depicted on preoperative imaging, we determined which findings precluded donation.

Spatial spectral imaging as an adjunct to the Bethesda classification of thyroid fine-needle aspiration specimens.

Background: Thyroid fine-needle aspiration (FNA) biopsy, the preoperative diagnostic standard of care for patients with thyroid nodules, has limitations. Spectral imaging captures visible light information that is beyond the capability of the human eye, potentially increasing the accuracy of FNA biopsy. In the current study, the authors demonstrated the feasibility of using spectral imaging in combination with automated spatial analysis based on trainable pattern recognition as an adjunct test for thyroid FNA classification by developing an algorithm that distinguishes between images of papillary thyroid carcinoma (PTC) and benign goiter (BG).

Polycation structure mediates expression of lyophilized polycation/pDNA complexes.

Lyophilization of polycation/pDNA complexes provides stable, long-term storage of complexes prior to clinical use but also reduces gene delivery efficiency. We examined whether polycation structure mediates effects of lyophilization on gene expression. Linear and branched PEI of the same molecular weight were used as a model system.