Characterizing search, recognition, and decision in the detection of lung nodules on CT scans: elucidation with eye tracking.

PURPOSE: To determine the effectiveness of radiologists' search, recognition, and acceptance of lung nodules on computed tomographic (CT) images by using eye tracking. MATERIALS AND METHODS: This study was performed with a protocol approved by the institutional review board. All study subjects provided informed consent, and all private health information was protected in accordance with HIPAA. A remote eye tracker was used to record time-varying gaze paths while 13 radiologists interpreted 40 lung CT images with an average of 3.9 synthetic nodules (5-mm diameter) embedded randomly in the lung parenchyma. The radiologists' gaze volumes ( GV gaze volume s) were defined as the portion of the lung parenchyma within 50 pixels (approximately 3 cm) of all gaze points. The fraction of the total lung volume encompassed within the GV gaze volume s, the fraction of lung nodules encompassed within each GV gaze volume (search effectiveness), the fraction of lung nodules within the GV gaze volume detected by the reader (recognition-acceptance effectiveness), and overall sensitivity of lung nodule detection were measured. RESULTS: Detected nodules were within 50 pixels of the nearest gaze point for 990 of 992 correct detections. On average, radiologists searched 26.7% of the lung parenchyma in 3 minutes and 16 seconds and encompassed between 86 and 143 of 157 nodules within their GV gaze volume s. Once encompassed within their GV gaze volume , the average sensitivity of nodule recognition and acceptance ranged from 47 of 100 nodules to 103 of 124 nodules (sensitivity, 0.47-0.82). Overall sensitivity ranged from 47 to 114 of 157 nodules (sensitivity, 0.30-0.73) and showed moderate correlation (r = 0.62, P = .02) with the fraction of lung volume searched. CONCLUSION: Relationships between reader search, recognition and acceptance, and overall lung nodule detection rate can be studied with eye tracking. Radiologists appear to actively search less than half of the lung parenchyma, with substantial interreader variation in volume searched, fraction of nodules included within the search volume, sensitivity for nodules within the search volume, and overall detection rate.

Hyperosmotic stress regulates the distribution and stability of myocardin-related transcription factor, a key modulator of the cytoskeleton.

Hyperosmotic stress initiates several adaptive responses, including the remodeling of the cytoskeleton. Besides maintaining structural integrity, the cytoskeleton has emerged as an important regulator of gene transcription. Myocardin-related transcription factor (MRTF), an actin-regulated coactivator of serum response factor, is a major link between the actin skeleton and transcriptional control. We therefore investigated whether MRTF is regulated by hyperosmotic stress. Here we show that hypertonicity induces robust, rapid, and transient translocation of MRTF from the cytosol to the nucleus in kidney tubular cells. We found that the hyperosmolarity-triggered MRTF translocation is mediated by the RhoA/Rho kinase (ROK) pathway. Moreover, the Rho guanine nucleotide exchange factor GEF-H1 is activated by hyperosmotic stress, and it is a key contributor to the ensuing RhoA activation and MRTF translocation, since siRNA-mediated GEF-H1 downregulation suppresses these responses. While the osmotically induced RhoA activation promotes nuclear MRTF accumulation, the concomitant activation of p38 MAP kinase mitigates this effect. Moderate hyperosmotic stress (600 mosM) drives MRTF-dependent transcription through the cis-element CArG box. Silencing or pharmacological inhibition of MRTF prevents the osmotic stimulation of CArG-dependent transcription and renders the cells susceptible to osmotic shock-induced structural damage. Interestingly, strong hyperosmolarity promotes proteasomal degradation of MRTF, concomitant with apoptosis. Thus, MRTF is an osmosensitive and osmoprotective transcription factor, whose intracellular distribution is regulated by the GEF-H1/RhoA/ROK and p38 pathways. However, strong osmotic stress destabilizes MRTF, concomitant with apoptosis, implying that hyperosmotically induced cell death takes precedence over epithelial-myofibroblast transition, a potential consequence of MRTF-mediated phenotypic reprogramming.

Effect of COVID-19 on computed tomography usage and critical test results in the emergency department: an observational study.

BACKGROUND: The effect of the coronavirus disease 2019 (COVID-19) pandemic on new or unexpected radiologic findings in the emergency department (ED) is unclear. The aim of this study was to determine the effect of the COVID-19 pandemic on the number of computed tomography (CT) critical test results in the ED. METHODS: We performed a retrospective observational study of ED CT usage at 4 Ontario hospitals (1 urban academic, 1 northern academic, 1 urban community and 1 rural community) over 1 month during the COVID-19 pandemic (April 2020) and over the same month 1 year earlier (April 2019; before the pandemic). The CT findings from 1 of the 4 hospitals, Hamilton Health Sciences, were reviewed to determine the number of critical test results by body region. Total CT numbers were compared using Poisson regression and CT yields were compared using the χ2 test. RESULTS: The median number of ED CT examinations per day was markedly lower during the COVID-19 pandemic than before the pandemic (82 v. 133, p < 0.01), with variation across hospitals (p = 0.001). On review of 1717 CT reports from Hamilton Health Sciences, fewer critical test results were demonstrated on CT pulmonary angiograms (43 v. 88, p < 0.001) and CT examinations of the head (82 v. 112, p < 0.03) during the pandemic than before the pandemic; however, the yield of these examinations did not change. Although the absolute number of all CT examinations with critical test results decreased, the number of CT examinations without critical results decreased more, resulting in a higher yield of CT for critical test results during the pandemic (46% [322/696] v. 37% [379/1021], p < 0.01). INTERPRETATION: Emergency department CT volumes markedly decreased during the COVID-19 pandemic, predominantly because there were fewer examinations with new or unexpected findings. This suggests that COVID-19 public information campaigns influenced the behaviours of patients presenting to the ED.

Pictorial review of vascular involvement and complex vascular reconstructions in borderline to minimally advanced pancreatic malignancies.

PURPOSE: To review borderline resectability criteria for pancreatic malignancies, show examples of few surgically treated minimally advanced pancreatic malignancies, discuss various complex vascular reconstructions, and highlight the imaging appearances. BACKGROUND: Often aggressive surgical approaches are used to treat borderline to minimally advanced pancreatic malignancies in specialist centers. As abdominal radiologists it is essential to have up-to-date knowledge to distinguish such tumors with accuracy and also be well versed with the various vascular reconstructions used in such surgeries. IMAGING FINDINGS: We will show various examples of resected borderline resectable and minimally advanced pancreatic malignancies, highlight crucial vascular involvements, describe various types of advanced vascular reconstructions, and review their standard imaging appearances. We will also briefly describe the vascular complications and highlight the importance of imaging surveillance in early post-operative period. CONCLUSIONS: It is essential for abdominal radiologists in specialist centers where aggressive surgical approaches are used to have accurate knowledge to assess vascular involvement in pancreatic malignancies and equally to recognize and assess vascular reconstructions on imaging after complex surgeries.

Variations in the functional visual field for detection of lung nodules on chest computed tomography: Impact of nodule size, distance, and local lung complexity.

PURPOSE: To explore the characteristics that impact lung nodule detection by peripheral vision when searching for lung nodules on chest CT-scans. METHODS: This study was approved by the local IRB and is HIPAA compliant. A simulated primary (1°) target mass (2 × 2 × 5 cm) was embedded into 5 cm thick subvolumes (SV) extracted from three unenhanced lung MDCT scans (64 row, 1.25 mm thickness, 0.7 mm increment). One of 30 solid, secondary nodules with either 3-4 mm and 5-8 mm diameters were embedded into 192 of 207 SVs. The secondary nodule was placed at a random depth within each SV, a transverse distance of 2.5, 5, 7.5, or 10 mm, and along one of eight rays cast every 45° from the center of the 1° mass. Video recordings of transverse paging in cranio-caudal direction were created for each SV (frame rate three sections/sec). Six radiologists observed each cine-loop once while gaze-tracking hardware assured that gaze was centered on the 1° mass. Each radiologist assigned a confidence rating (0-5) to the detection of a secondary nodule and indicated its location. Detection sensitivity was analyzed relative to secondary nodule size, transverse distance, radial orientation, and lung complexity. Lung complexity was characterized by the number of particles (connected pixels) and the sum of the area of all particles above a -500 HU threshold within regions of interest around the 1° mass and secondary nodule. RESULTS: Using a proportional odds logistic regression model and eliminating redundant predictors, models fit individually to each reader resulted in the following decreasing order of association based on greatest reduction in Akaike Information Criterion: secondary nodule diameter (6/6 readers, P < 0.001), distance from central mass (6/6 readers, P < 0.001), lung complexity particle count (5/6 readers, P = 0.05), and lung complexity particle area (3/6 readers, P = 0.03). Substantial inter-reader differences in sensitivity to decreasing nodule diameter, distance, and complexity characteristics were observed. CONCLUSIONS: Of the investigated parameters, secondary nodule size, distance from the gaze center and lung complexity (particle number and area) significantly impact nodule detection with peripheral vision.