Molecular alterations and clinical prognostic factors in resectable non-small cell lung cancer.

Background: EGFR inhibitor and immunotherapy have been approved for adjuvant treatment in resectable non-small cell lung cancer (NSCLC). Limited reports of molecular and clinical characteristics as prognostic factors in NSCLC have been published.

Methods: Medical records of patients with resectable NSCLC stage I-III diagnosed during 2015-2020 were reviewed.

Practical application and validation of the 2018 ATS/ERS/JRS/ALAT and Fleischner Society guidelines for the diagnosis of idiopathic pulmonary fibrosis.

Background: Accurate diagnosis of idiopathic pulmonary fibrosis (IPF) is essential to inform prognosis and treatment. In 2018, the ATS/ERS/JRS/ALAT and Fleischner Society released new diagnostic guidelines for usual interstitial pneumonitis (UIP)/IPF, adding Probable UIP as a CT category based on prior studies demonstrating this category had relatively high positive predictive value (PPV) for histopathologic UIP/Probable UIP. This study applies the 2018 ATS/ERS/JRS/ALAT and Fleischner Society guidelines to determine test characteristics of CT categories in academic clinical practice.

Artificial intelligence-based vessel suppression for detection of sub-solid nodules in lung cancer screening computed tomography.

Background: Lung cancer screening (LCS) with low-dose computed tomography (LDCT) helps early lung cancer detection, commonly presenting as small pulmonary nodules. Artificial intelligence (AI)-based vessel suppression (AI-VS) and automatic detection (AI-AD) algorithm can improve detection of subsolid nodules (SSNs) on LDCT. We assessed the impact of AI-VS and AI-AD in detection and classification of SSNs [ground-glass nodules (GGNs) and part-solid nodules (PSNs)], on LDCT performed for LCS.

Initial diagnosis and successful treatment of pulmonary tumor embolism manifesting as the first clinical sign of prostatic adenocarcinoma.

Although pulmonary tumor embolism (PTE) is a well-recognized end-stage form of pulmonary metastases at postmortem examination, the entity is rarely the first clinical sign of prostate cancer. Diagnosis of this condition in patients who have no previous history of malignancy is a challenge. Herein, we reported a 79-year-old man presented with progressive, unexplained dyspnea on exertion.

Semiautomatic Segmentation and Radiomics for Dual-Energy CT: A Pilot Study to Differentiate Benign and Malignant Hepatic Lesions.

This study assessed a machine learning-based dual-energy CT (DECT) tumor analysis prototype for semiautomatic segmentation and radiomic analysis of benign and malignant liver lesions seen on contrast-enhanced DECT. This institutional review board-approved study included 103 adult patients (mean age, 65 ± 15 [SD] years; 53 men, 50 women) with benign (60/103) or malignant (43/103) hepatic lesions on contrast-enhanced dual-source DECT. Most malignant lesions were histologically proven; benign lesions were either stable on follow-up CT or had characteristic benign features on MRI.

Multiplatform, Non-Breath-Hold Fast Scanning Protocols: Should We Stop Giving Breath-Hold Instructions for Routine Chest CT? [Formula: see text].

Objective: We assessed if non-breath-hold (NBH) fast scanning protocol can provide respiratory motion-free images for interpretation of chest computed tomography (CT).

Materials And Methods: In our 2-phase project, we first collected baseline data on frequency of respiratory motion artifacts on breath-hold chest CT in 826 adult patients. The second phase included 62 patients (mean age 66 ± 15 years; 21 females, 41 males) who underwent an NBH chest CT on either single-source (n = 32) or dual-source (n = 30) multidetector-row CT scanners.

Comparison of Baseline, Bone-Subtracted, and Enhanced Chest Radiographs for Detection of Pneumothorax.

Purpose: To assess and compare detectability of pneumothorax on unprocessed baseline, single-energy, bone-subtracted, and enhanced frontal chest radiographs (chest X-ray, CXR).

Method And Materials: Our retrospective institutional review board-approved study included 202 patients (mean age 53 ± 24 years; 132 men, 70 women) who underwent frontal CXR and had trace, moderate, large, or tension pneumothorax. All patients (except those with tension pneumothorax) had concurrent chest computed tomography (CT).

Deep learning-enabled system for rapid pneumothorax screening on chest CT.

Purpose: Prompt diagnosis and quantitation of pneumothorax impact decisions pertaining to patient management. The purpose of our study was to develop and evaluate the accuracy of a deep learning (DL)-based image classification program for detection of pneumothorax on chest CT.

Method: In an IRB approved study, an eight-layer convolutional neural network (CNN) using constant-size (36*36 pixels) 2D image patches was trained on a set of 80 chest CTs, with (n = 50) and without (n = 30) pneumothorax.

Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction.

Commercial iterative reconstruction techniques help to reduce CT radiation dose but altered image appearance and artifacts limit their adoptability and potential use. Deep learning has been investigated for low-dose CT (LDCT). Here we design a modularized neural network for LDCT and compared it with commercial iterative reconstruction methods from three leading CT vendors.

Extent of Intraprotocol and Intersite Variability of Thoracic Magnetic Resonance Acquisition Times at a Large Quaternary Institution: MR Technologist Insights as to Its Causes.

Purpose: The purpose of this study was to describe Thoracic magnetic resonance (MR) acquisition time (AT) variability, associations, and technologist insights as to its causes at a large quaternary institution, by MR protocol and imaging site.

Materials And Methods: A retrospective review of our 2017 QI database of 1.5 T MR imaging ATs for adults 19 years and above at the main hospital and outpatient (OPT) satellites was performed for all 5 Thoracic MR protocols.

Assessment of proximal and peripheral airway dysfunction by computed tomography and respiratory impedance in asthma and COPD patients with fixed airflow obstruction.

Objective: To ascertain: (i) if elderly patients with fixed airflow obstruction (FAO) due to asthma and chronic obstructive pulmonary disease (COPD) have distinct airway morphologic and physiologic changes; (ii) the correlation between the morphology of proximal/peripheral airways and respiratory impedance.

Methods: Twenty-five asthma cases with FAO and 22 COPD patients were enrolled. High-resolution computed tomography was used to measure the wall area (WA) and lumen area (LA) of the proximal airway at the apical segmental bronchus of the right upper lobe (RB1) adjusted by body surface area (BSA) and bronchial wall thickening (BWT ) of the peripheral airways and extent of expiratory air trapping (AT ).

Deep learning in chest radiography: Detection of findings and presence of change.

Background: Deep learning (DL) based solutions have been proposed for interpretation of several imaging modalities including radiography, CT, and MR. For chest radiographs, DL algorithms have found success in the evaluation of abnormalities such as lung nodules, pulmonary tuberculosis, cystic fibrosis, pneumoconiosis, and location of peripherally inserted central catheters. Chest radiography represents the most commonly performed radiological test for a multitude of non-emergent and emergent clinical indications.

Thin-section CT findings of thoracolithiasis.

Purpose: To review thin-section CT findings of thoracolithiasis.

Materials And Methods: Thirty-three thin-section CT scans of 9 patients with thoracolithiasis diagnosed between 2008 and 2016 were reviewed for the location, shape, longest diameter, and calcification of each freely mobile nodule (thoracolith) and for the presence of coexisting abnormalities.

Results: The mean age of 9 patients (5 women) was 65.