Chest CT is emerging as a valuable diagnostic tool for clinical management of COVID-19 associated lung disease. Artificial intelligence (AI) has the potential to aid in rapid evaluation of CT scans for differentiation of COVID-19 findings from other clinical entities. Here we show that a series of deep learning algorithms, trained in a diverse multinational cohort of 1280 patients to localize parietal pleura/lung parenchyma followed by classification of COVID-19 pneumonia, can achieve up to 90.8% accuracy, with 84% sensitivity and 93% specificity, as evaluated in an independent test set (not included in training and validation) of 1337 patients. Normal controls included chest CTs from oncology, emergency, and pneumonia-related indications. The false positive rate in 140 patients with laboratory confirmed other (non COVID-19) pneumonias was 10%. AI-based algorithms can readily identify CT scans with COVID-19 associated pneumonia, as well as distinguish non-COVID related pneumonias with high specificity in diverse patient populations.

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Background: Twenty to 30% of patients with breast cancer have cognitive impairment after surgery and before adjuvant treatment, but very few studies have focused on cognition before any treatment. This study used a subgroup of women with newly diagnosed breast cancer from the French cancer and toxicities (CANTO) cohort to describe cognition before any treatment in comparison with a group of healthy controls (HC).Methods: Cognitive assessment was performed before any breast cancer treatment (surgery or neoadjuvant treatment) on women with newly diagnosed invasive stage I-III breast cancer and HCs. Objective cognitive performance, cognitive complaints, anxiety, depression, and fatigue were assessed. Objective cognitive impairment was defined according to International Cognition and Cancer Task Force recommendations.Results: Of the 264 included patients with breast cancer (54 AE 11 years) and 132 age-matched HCs (53 AE 9 years), overall objective cognitive impairment was observed in 28% of patients with breast cancer and 8% of HCs (P < 0.001). Cognitive complaints were reported by 24% of patients versus 12% of HCs (P < 0.01). Patients reported significantly more anxiety and emotional and cognitive fatigue than HCs (P < 0.01). After adjustment, significantly more patients with breast cancer had overall objective cognitive impairment than HCs [OR ¼ 3.01; 95% confidence interval (CI): 1.31-6.88] without significant difference between groups for cognitive complaints (OR ¼ 1.38; 95% CI: 0.65-2.92). Cognitive complaints were positively associated with fatigue (OR ¼ 1.03; 95% CI: 1.02-1.05).Conclusions: In this prospective study, compared with HCs, patients with localized breast cancer had more objective cognitive impairment before any treatment. Cognitive complaints were mostly related to fatigue.Impact: Baseline assessment before treatment is important to assess the impact of each cancer treatment on cognition.

Objectives The early infection dynamics of patients with SARS-CoV-2 are not well understood. We aimed to investigate and characterize associations between clinical, laboratory, and imaging features of asymptomatic and pre-symptomatic patients with SARS-CoV-2. Methods Seventy-four patients with RT-PCR-proven SARS-CoV-2 infection were asymptomatic at presentation. All were retrospectively identified from 825 patients with chest CT scans and positive RT-PCR following exposure or travel risks in outbreak settings in Japan and China. CTs were obtained for every patient within a day of admission and were reviewed for infiltrate subtypes and percent with assistance from a deep learning tool. Correlations of clinical, laboratory, and imaging features were analyzed and comparisons were performed using univariate and multivariate logistic regression. Results Forty-eight of 74 (65%) initially asymptomatic patients had CT infiltrates that pre-dated symptom onset by 3.8 days. The most common CT infiltrates were ground glass opacities (45/48; 94%) and consolidation (22/48; 46%). Patient body temperature ( p < 0.01), CRP ( p < 0.01), and KL-6 ( p = 0.02) were associated with the presence of CT infiltrates. Infiltrate volume ( p = 0.01), percent lung involvement ( p = 0.01), and consolidation ( p = 0.043) were associated with subsequent development of symptoms. Conclusions COVID-19 CT infiltrates pre-dated symptoms in two-thirds of patients. Body temperature elevation and laboratory evaluations may identify asymptomatic patients with SARS-CoV-2 CT infiltrates at presentation, and the characteristics of CT infiltrates could help identify asymptomatic SARS-CoV-2 patients who subsequently develop symptoms. The role of chest CT in COVID-19 may be illuminated by a better understanding of CT infiltrates in patients with early disease or SARS-CoV-2 exposure. Key Points • Forty-eight of 74 (65%) pre-selected asymptomatic patients with SARS-CoV-2 had abnormal chest CT findings. • CT infiltrates pre-dated symptom onset by 3.8 days (range 1–5). • KL-6, CRP, and elevated body temperature identified patients with CT infiltrates. Higher infiltrate volume, percent lung involvement, and pulmonary consolidation identified patients who developed symptoms.

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A better understanding of temporal relationships between chest CT and labs may provide a reference for disease severity over the disease course. Generalized curves of lung opacity volume and density over time can be used as standardized references from well before symptoms develop to over a month after recovery, when residual lung opacities remain. 739 patients with COVID-19 underwent CT and RT-PCR in an outbreak setting between January 21st and April 12th, 2020. 29 of 739 patients had serial exams (121 CTs and 279 laboratory measurements) over 50 ± 16 days, with an average of 4.2 sequential CTs each. Sequential volumes of total lung, overall opacity and opacity subtypes (ground glass opacity [GGO] and consolidation) were extracted using deep learning and manual segmentation. Generalized temporal curves of CT and laboratory measurements were correlated. Lung opacities appeared 3.4 ± 2.2 days prior to symptom onset. Opacity peaked 1 day after symptom onset. GGO onset was earlier and resolved later than consolidation. Lactate dehydrogenase, and C-reactive protein peaked earlier than procalcitonin and leukopenia. The temporal relationships of quantitative CT features and clinical labs have distinctive patterns and peaks in relation to symptom onset, which may inform early clinical course in patients with mild COVID-19 pneumonia, or may shed light upon chronic lung effects or mechanisms of medical countermeasures in clinical trials.

SWE is a reliable tool for assessing stiffness in the LPM. Reliability of SWE protocols is improved during seated position. Tensioning of the TLF via LD stretching did not influence LPM stiffness. This article is protected by copyright. All rights reserved.

Introduction: 18 F-DCFPyL, 18 F-NaF and 18 F-FDG PET/CT were compared in a prospective cohort of men with metastatic prostate cancer (PCa).Materials and Methods: 67 men (Group 1) with documented metastatic PCa underwent 18 F-DCFPyL and 18 F-NaF PET/CT and a subgroup of 30 men (Group 2) underwent additional imaging with 18 F-FDG PET/CT. The tracers were compared for their detection rates, imaging concordance, associations with Prostate Specific Antigen (PSA), treatment at the time of imaging and castration status.Results: Overall, 61 men had metastatic disease detected on one or more scans, while 6 men were negative. In Group 1, 18 F-NaF detected significantly more metastatic lesions than 18 F-DCFPyL (median of 3 lesions versus 2, p=0.001) even after eliminating benign causes of 18 F-NaF uptake.This difference was particularly clear for men receiving treatment (p=0.005) or who were castrate resistant (p=0.014). The median percentage of bone lesions that were concordant on 18 F-DCFPyL and 18 F-NaF was 50%. In Group 2, 18 F-DCFPyL detected more lesions than 18 F-FDG (median of 5 lesions versus 2, p=0.0003), regardless of PSA level, castration status or treatment. The median percentage of lesions that were concordant on 18 F-DCFPyL and 18 F-FDG was 22.2%. This percentage was slightly higher for castrate-resistant than castrate-sensitive men (p=0.048). Conclusion:18 F-DCFPyL PET/CT is the most versatile of the three PET agents for metastatic PCa however, 18 F-NaF detects more bone metastases. Imaging reveals substantial tumor heterogeneity with only 50% concordance between 18 F-DCFPyL and 18 F-NaF and 22% concordance for 18 F-DCFPyL and 18 F-FDG. This indicates considerable phenotypic differences among metastatic lesions.