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Article ; Online: COVID-19 in CXR: From Detection and Severity Scoring to Patient Disease Monitoring.

Frid-Adar, Maayan / Amer, Rula / Gozes, Ophir / Nassar, Jannette / Greenspan, Hayit

IEEE journal of biomedical and health informatics

2021 Volume 25, Issue 6, Page(s) 1892–1903

Abstract: This work estimates the severity of pneumonia in COVID-19 patients and reports the findings ... The assessment of disease severity serves to build a temporal disease extent profile for hospitalized patients ... of a longitudinal study of disease progression. It presents a deep learning model for simultaneous detection and ...

Abstract	This work estimates the severity of pneumonia in COVID-19 patients and reports the findings of a longitudinal study of disease progression. It presents a deep learning model for simultaneous detection and localization of pneumonia in chest Xray (CXR) images, which is shown to generalize to COVID-19 pneumonia. The localization maps are utilized to calculate a "Pneumonia Ratio" which indicates disease severity. The assessment of disease severity serves to build a temporal disease extent profile for hospitalized patients. To validate the model's applicability to the patient monitoring task, we developed a validation strategy which involves a synthesis of Digital Reconstructed Radiographs (DRRs - synthetic Xray) from serial CT scans; we then compared the disease progression profiles that were generated from the DRRs to those that were generated from CT volumes.
MeSH term(s)	COVID-19/diagnostic imaging ; COVID-19/pathology ; COVID-19/virology ; Case-Control Studies ; Humans ; Monitoring, Physiologic/methods ; Pneumonia, Viral/diagnostic imaging ; Pneumonia, Viral/pathology ; Pneumonia, Viral/virology ; Radiography, Thoracic ; SARS-CoV-2/isolation & purification ; Severity of Illness Index
Language	English
Publishing date	2021-06-03
Publishing country	United States
Document type	Journal Article
ZDB-ID	2695320-1
ISSN	2168-2208 ; 2168-2194
ISSN (online)	2168-2208
ISSN	2168-2194
DOI	10.1109/JBHI.2021.3069169
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Article: COVID-19 in CXR: from Detection and Severity Scoring to Patient Disease Monitoring

Amer, Rula / Frid-Adar, Maayan / Gozes, Ophir / Nassar, Jannette / Greenspan, Hayit

Abstract: In this work, we estimate the severity of pneumonia in COVID-19 patients and conduct ... detection and segmentation of pneumonia in chest Xray (CXR) images and generalized to COVID-19 pneumonia ... of disease severity enables to build a disease extent profile over time for hospitalized patients ...

Abstract	In this work, we estimate the severity of pneumonia in COVID-19 patients and conduct a longitudinal study of disease progression. To achieve this goal, we developed a deep learning model for simultaneous detection and segmentation of pneumonia in chest Xray (CXR) images and generalized to COVID-19 pneumonia. The segmentations were utilized to calculate a"Pneumonia Ratio"which indicates the disease severity. The measurement of disease severity enables to build a disease extent profile over time for hospitalized patients. To validate the model relevance to the patient monitoring task, we developed a validation strategy which involves a synthesis of Digital Reconstructed Radiographs (DRRs - synthetic Xray) from serial CT scans; we then compared the disease progression profiles that were generated from the DRRs to those that were generated from CT volumes.
Keywords	covid19
Publisher	ArXiv
Document type	Article
Database	COVID19

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Book ; Online: COVID-19 in CXR

Amer, Rula / Frid-Adar, Maayan / Gozes, Ophir / Nassar, Jannette / Greenspan, Hayit

from Detection and Severity Scoring to Patient Disease Monitoring

2020

Abstract: In this work, we estimate the severity of pneumonia in COVID-19 patients and conduct ... detection and segmentation of pneumonia in chest Xray (CXR) images and generalized to COVID-19 pneumonia ... The measurement of disease severity enables to build a disease extent profile over time for hospitalized patients ...

Abstract	In this work, we estimate the severity of pneumonia in COVID-19 patients and conduct a longitudinal study of disease progression. To achieve this goal, we developed a deep learning model for simultaneous detection and segmentation of pneumonia in chest Xray (CXR) images and generalized to COVID-19 pneumonia. The segmentations were utilized to calculate a "Pneumonia Ratio" which indicates the disease severity. The measurement of disease severity enables to build a disease extent profile over time for hospitalized patients. To validate the model relevance to the patient monitoring task, we developed a validation strategy which involves a synthesis of Digital Reconstructed Radiographs (DRRs - synthetic Xray) from serial CT scans; we then compared the disease progression profiles that were generated from the DRRs to those that were generated from CT volumes. Comment: paper was accepted to JBHI IEEE journal
Keywords	Electrical Engineering and Systems Science - Image and Video Processing ; Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Machine Learning ; covid19
Subject code	006
Publishing date	2020-08-04
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: COVID-19 outbreak in Italy

Borghesi, A. / Maroldi, R.

experimental chest X-ray scoring system for quantifying and monitoring disease progression

2020

Abstract: ... our experimental CXR scoring system that we are applying to hospitalized patients with COVID-19 pneumonia ... to quantify and monitor the severity and progression of this new infectious disease. We also present ... infection, formally called Coronavirus Disease 2019 (COVID-19), has spread rapidly in China and beyond. On 8 ...

Abstract	Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a new virus recently isolated from humans. SARS-CoV-2 was discovered to be the pathogen responsible for a cluster of pneumonia cases associated with severe respiratory disease that occurred in December 2019 in China. This novel pulmonary infection, formally called Coronavirus Disease 2019 (COVID-19), has spread rapidly in China and beyond. On 8 March 2020, the number of Italians with SARS-CoV-2 infection was 7375 with a 48% hospitalization rate. At present, chest-computed tomography imaging is considered the most effective method for the detection of lung abnormalities in early-stage disease and quantitative assessment of severity and progression of COVID-19 pneumonia. Although chest X-ray (CXR) is considered not sensitive for the detection of pulmonary involvement in the early stage of the disease, we believe that, in the current emergency setting, CXR can be a useful diagnostic tool for monitoring the rapid progression of lung abnormalities in infected patients, particularly in intensive care units. In this short communication, we present our experimental CXR scoring system that we are applying to hospitalized patients with COVID-19 pneumonia to quantify and monitor the severity and progression of this new infectious disease. We also present the results of our preliminary validation study on a sample of 100 hospitalized patients with SARS-CoV-2 infection for whom the final outcome (recovery or death) was available.
Keywords	Chest X-ray ; Computed tomography ; COVID-19 ; SARS-CoV-2 ; Scoring system ; Aged ; Coronavirus Infections ; Disease Outbreaks ; Disease Progression ; Humans ; Italy ; Male ; Pandemics ; Pneumonia ; Viral ; Radiography ; Thoracic ; Betacoronavirus ; covid19
Subject code	610
Language	English
Publishing country	it
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: COVID-19 severity scoring systems in radiological imaging - a review.

Wasilewski, Piotr G / Mruk, Bartosz / Mazur, Samuel / Półtorak-Szymczak, Gabriela / Sklinda, Katarzyna / Walecki, Jerzy

Polish journal of radiology

2020 Volume 85, Page(s) e361–e368

Abstract: ... to assess the severity of lung involvement in COVID-19 patients in everyday work, both for CXR and CT ... in evaluating the course of COVID-19 and in choosing proper management of infected patients. Chest X-ray (CXR ... for monitoring the rapid progression of lung involvement in COVID-19, especially in patients admitted ...

Abstract	The current reference standard to make a definitive diagnosis of SARS-CoV-2 infection is the reverse transcription- polymerase chain reaction assay (rt-PCR). However, radiological imaging plays a crucial role in evaluating the course of COVID-19 and in choosing proper management of infected patients. Chest X-ray (CXR) is generally considered not to be sensitive for the detection of pulmonary abnormalities in the early stage of the disease. However, in the emergency setting CXR can be a useful diagnostic tool for monitoring the rapid progression of lung involvement in COVID-19, especially in patients admitted to intensive care units. The rapid course of SARS-CoV-2 infection and the severity and progression of lung aberrations require a method of radiological evaluation to implement and manage the appropriate treatment for infected patients. Computed tomography (CT) imaging is considered to be the most effective method for the detection of lung abnormalities, especially in the early stage of the disease. Moreover, serial chest CT imaging with different time intervals is also effective in estimating the evolution of the disease from initial diagnosis to discharge from hospital. Despite having low specificity in distinguishing abnormalities in viral infections, the high sensitivity of CT makes this method ideal for assessing the severity of the disease in patients with confirmed COVID-19. In this review, we present and discuss currently available scales that can be used to assess the severity of lung involvement in COVID-19 patients in everyday work, both for CXR and CT imaging.
Keywords	covid19
Language	English
Publishing date	2020-07-17
Publishing country	Poland
Document type	Journal Article ; Review
ZDB-ID	2675143-4
ISSN	1899-0967 ; 1733-134X
ISSN (online)	1899-0967
ISSN	1733-134X
DOI	10.5114/pjr.2020.98009
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Book ; Online: COVID-19 severity scoring systems in radiological imaging

a review

2020

Abstract: ... the course of COVID-19 and in choosing proper management of infected patients. Chest X-ray (CXR) is generally ... of CT makes this method ideal for assessing the severity of the disease in patients with confirmed COVID ... involvement in COVID-19, especially in patients admitted to intensive care units. The rapid course of SARS-CoV ...

Abstract	The current reference standard to make a definitive diagnosis of SARS-CoV-2 infection is the reverse transcriptionpolymerase chain reaction assay (rt-PCR). However, radiological imaging plays a crucial role in evaluating the course of COVID-19 and in choosing proper management of infected patients. Chest X-ray (CXR) is generally considered not to be sensitive for the detection of pulmonary abnormalities in the early stage of the disease. However, in the emergency setting CXR can be a useful diagnostic tool for monitoring the rapid progression of lung involvement in COVID-19, especially in patients admitted to intensive care units. The rapid course of SARS-CoV-2 infection and the severity and progression of lung aberrations require a method of radiological evaluation to implement and manage the appropriate treatment for infected patients. Computed tomography (CT) imaging is considered to be the most effective method for the detection of lung abnormalities, especially in the early stage of the disease. Moreover, serial chest CT imaging with different time intervals is also effective in estimating the evolution of the disease from initial diagnosis to discharge from hospital. Despite having low specificity in distinguishing abnormalities in viral infections, the high sensitivity of CT makes this method ideal for assessing the severity of the disease in patients with confirmed COVID-19.
Keywords	X-ray ; computed tomography ; CT ; COVID-19 ; SARS-CoV-2 ; CXR ; covid19
Subject code	610
Language	English
Publishing country	pl
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Sextus chest radiograph severity score correlates to clinical outcomes in patients with COVID-19: A cross-sectional study.

Sun, Justin / Yu, Daohai / Yoo, Kevin / Choi, Robert / Lu, Xiaoning / Standiford, Taylor / Cohen, Gary / Marchetti, Nathaniel / Agosto, Omar / Kumaran, Maruti / Maresky, Hillel

Medicine

2021 Volume 100, Issue 45, Page(s) e27663

Abstract: ... a standardized CXR scoring system and assess its prognostic value in hospitalized patients found to have COVID-19 ... score may provide insight into identifying and monitoring high-risk patients with COVID-19. ... diagnosis of COVID-19 between March 15, 2020 to April 15, 2020 were included. Each patient's CXR and coronal ...

Abstract	Abstract: The value of chest radiography (CXR) in detection and as an outcome predictor in the management of patients with coronavirus disease-2019 (COVID-19) has not yet been fully understood.To validate a standardized CXR scoring system and assess its prognostic value in hospitalized patients found to have COVID-19 by imaging criteria and to compare it to computed tomography (CT).In this cross-sectional chart review study, patients aged 18-years or older who underwent chest CT at a single institution with an imaging-based diagnosis of COVID-19 between March 15, 2020 to April 15, 2020 were included. Each patient's CXR and coronal CT were analyzed for opacities in a 6-zonal assessment method and aggregated into a "Sextus score." Inter-reader variability and correlation between CXR and coronal CT images were investigated to validate this scoring system. Univariable and multiple logistic regression techniques were used to investigate relationships between CXR scores and clinical parameters in relation to patient outcomes.One hundred twenty-four patients (median [interquartile range] age 58.5 [47.5-69.0] years, 72 [58%] men, 58 [47%] Blacks, and 35 [28%] Hispanics) were included. The CXR Sextus score (range: 0-6) was reliable (inter-rater kappa = 0.76; 95% confidence interval [CI]: 0.69-0.83) and correlated strongly with the CT Sextus score (Spearman correlation coefficient = 0.75, P < .0001). Incremental increases of CXR Sextus scores of 2 points were found to be an independent predictor of intubation (adjusted odds ratio [95% CI]: 4.49 [1.98, 10.20], P = .0003) and prolonged hospitalization (≥10 days) (adjusted odds ratio [95% CI]: 4.06 [1.98, 8.32], P = .0001).The CXR Sextus score was found to be reproducible and CXR-CT severity scores were closely correlated. Increasing Sextus scores were associated with increased risks for intubation and prolonged hospitalization for patients with COVID-19 in a predominantly Black population. The CXR Sextus score may provide insight into identifying and monitoring high-risk patients with COVID-19.
MeSH term(s)	Aged ; COVID-19/diagnosis ; COVID-19/diagnostic imaging ; Cross-Sectional Studies ; Female ; Humans ; Male ; Middle Aged ; Radiography, Thoracic ; Reproducibility of Results ; Retrospective Studies ; SARS-CoV-2 ; X-Rays
Language	English
Publishing date	2021-11-09
Publishing country	United States
Document type	Journal Article
ZDB-ID	80184-7
ISSN	1536-5964 ; 0025-7974
ISSN (online)	1536-5964
ISSN	0025-7974
DOI	10.1097/MD.0000000000027663
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Article ; Online: COVID-19 outbreak in Italy: experimental chest X-ray scoring system for quantifying and monitoring disease progression.

Borghesi, Andrea / Maroldi, Roberto

La Radiologia medica

2020 Volume 125, Issue 5, Page(s) 509–513

Abstract	Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a new virus recently isolated from humans. SARS-CoV-2 was discovered to be the pathogen responsible for a cluster of pneumonia cases associated with severe respiratory disease that occurred in December 2019 in China. This novel pulmonary infection, formally called Coronavirus Disease 2019 (COVID-19), has spread rapidly in China and beyond. On 8 March 2020, the number of Italians with SARS-CoV-2 infection was 7375 with a 48% hospitalization rate. At present, chest-computed tomography imaging is considered the most effective method for the detection of lung abnormalities in early-stage disease and quantitative assessment of severity and progression of COVID-19 pneumonia. Although chest X-ray (CXR) is considered not sensitive for the detection of pulmonary involvement in the early stage of the disease, we believe that, in the current emergency setting, CXR can be a useful diagnostic tool for monitoring the rapid progression of lung abnormalities in infected patients, particularly in intensive care units. In this short communication, we present our experimental CXR scoring system that we are applying to hospitalized patients with COVID-19 pneumonia to quantify and monitor the severity and progression of this new infectious disease. We also present the results of our preliminary validation study on a sample of 100 hospitalized patients with SARS-CoV-2 infection for whom the final outcome (recovery or death) was available.
MeSH term(s)	Aged ; Betacoronavirus ; COVID-19 ; Coronavirus Infections/diagnostic imaging ; Coronavirus Infections/epidemiology ; Disease Outbreaks ; Disease Progression ; Humans ; Italy/epidemiology ; Male ; Pandemics ; Pneumonia, Viral/diagnostic imaging ; Pneumonia, Viral/epidemiology ; Radiography, Thoracic ; SARS-CoV-2
Keywords	covid19
Language	English
Publishing date	2020-05-01
Publishing country	Italy
Document type	Journal Article
ZDB-ID	205751-7
ISSN	1826-6983 ; 0033-8362
ISSN (online)	1826-6983
ISSN	0033-8362
DOI	10.1007/s11547-020-01200-3
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Article: COVID-19 severity scoring systems in radiological imaging - a review

Wasilewski, Piotr G. / Mruk, Bartosz / Mazur, Samuel / Półtorak-Szymczak, Gabriela / Sklinda, Katarzyna / Walecki, Jerzy

Polish journal of radiology

Abstract: ... the severity of lung involvement in COVID-19 patients in everyday work, both for CXR and CT imaging ... in evaluating the course of COVID-19 and in choosing proper management of infected patients Chest X-ray (CXR) is ... of the disease However, in the emergency setting CXR can be a useful diagnostic tool for monitoring the rapid ...

Abstract	The current reference standard to make a definitive diagnosis of SARS-CoV-2 infection is the reverse transcription- polymerase chain reaction assay (rt-PCR) However, radiological imaging plays a crucial role in evaluating the course of COVID-19 and in choosing proper management of infected patients Chest X-ray (CXR) is generally considered not to be sensitive for the detection of pulmonary abnormalities in the early stage of the disease However, in the emergency setting CXR can be a useful diagnostic tool for monitoring the rapid progression of lung involvement in COVID-19, especially in patients admitted to intensive care units The rapid course of SARS-CoV-2 infection and the severity and progression of lung aberrations require a method of radiological evaluation to implement and manage the appropriate treatment for infected patients Computed tomography (CT) imaging is considered to be the most effective method for the detection of lung abnormalities, especially in the early stage of the disease Moreover, serial chest CT imaging with different time intervals is also effective in estimating the evolution of the disease from initial diagnosis to discharge from hospital Despite having low specificity in distinguishing abnormalities in viral infections, the high sensitivity of CT makes this method ideal for assessing the severity of the disease in patients with confirmed COVID-19 In this review, we present and discuss currently available scales that can be used to assess the severity of lung involvement in COVID-19 patients in everyday work, both for CXR and CT imaging
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #725787
Database	COVID19

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Article: COVID-19 outbreak in Italy: experimental chest X-ray scoring system for quantifying and monitoring disease progression

Borghesi, Andrea / Maroldi, Roberto

Radiol Med

Abstract	Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a new virus recently isolated from humans. SARS-CoV-2 was discovered to be the pathogen responsible for a cluster of pneumonia cases associated with severe respiratory disease that occurred in December 2019 in China. This novel pulmonary infection, formally called Coronavirus Disease 2019 (COVID-19), has spread rapidly in China and beyond. On 8 March 2020, the number of Italians with SARS-CoV-2 infection was 7375 with a 48% hospitalization rate. At present, chest-computed tomography imaging is considered the most effective method for the detection of lung abnormalities in early-stage disease and quantitative assessment of severity and progression of COVID-19 pneumonia. Although chest X-ray (CXR) is considered not sensitive for the detection of pulmonary involvement in the early stage of the disease, we believe that, in the current emergency setting, CXR can be a useful diagnostic tool for monitoring the rapid progression of lung abnormalities in infected patients, particularly in intensive care units. In this short communication, we present our experimental CXR scoring system that we are applying to hospitalized patients with COVID-19 pneumonia to quantify and monitor the severity and progression of this new infectious disease. We also present the results of our preliminary validation study on a sample of 100 hospitalized patients with SARS-CoV-2 infection for whom the final outcome (recovery or death) was available.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #154745
Database	COVID19

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