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Covid-19 disease: CT chest volume assessment using nonspecific software “Lung Density” present on “Extended Brilliance Workspace”

Research Article
Authors: Spanò Ferdinando,Arminio Matteo,Carucci Alessandro,Di Luzio Dario,Grimaldi Iolanda,Pittalis Angelo,Caprasecca Stefano,Tortora Alessandra,Lanciotti Silvia,Filannino Floriana,Ricci Paolo
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Submission Date: 2020-10-06
Review Date: 2020-10-21
Pubblication Date: 2020-11-05



The current global COVID-19 pandemic is related to an acute respiratory disease caused by a new coronavirus (SARS-CoV-2), highly contagious and whose evolution is still poorly understood.
The high-resolution Computed Tomography (HRCT) is the most accurate technique for identifying pathogenetic finding of interstitial pneumonia. Standardized HRCT examination in COVID patients binds quantitative evaluation of healthy lung tissue performed in post-processing. In this study we present a valid tool for the Radiologist the diagnosis of Covid-19 diagnosis, an essential support in the evaluation of emergency symptomatic patients with negative NAAT, or asymptomatic patients with negative NAAT who have come into contact with positive one, in fact asymptomatic patients can also have lung lesions on CT imaging.


Covid-19 can be diagnosed on both chest X-Ray and on Computed Tomography (CT). HRCT is the most accurate technique in identifying pathognomonic findings of interstitial pneumonia of ground glass areas, crazy paving, nodules and consolidations, mono or bilateral, irregular or multifocal, central and/or peripheral distribution, declivous or non-declivous (Chung M, 2020).

The extent of lung lesions in coronavirus disease 2019 is closely related to clinical symptoms and has different imaging manifestations at different stages. In the early stage COVID-19 lesions are relatively localized and manifest mainly as inflammatory infiltration limited to the subpleural or peribronchovascular regions of one lung or both lungs, exhibiting patchy or segmental pure GGOs (Ground Glass Opacities) with vascular dilation. Very few cases have CT negative early stage.

In the progressive phase, CT mainly shows an increase in the range of pure GGOs, the involvement of more lobes, consolidations of some lesions, and GGOs surrounding consolidated lesions. Interlobular septal thickening and an obvious crazy-paving pattern are often present and aerial bronchograms are common.

In the advanced stage, CT manifestations of patients are similar to those of other types of pneumonia and include mainly diffuse lesions in both lungs, which are mostly consolidated lesions, and GGOs surrounding consolidated lesions, which are mostly accompanied by parenchymal bands and occasionally a small amount of pleural effusion (Dai W, 2020).

Different imaging manifestations in different stages may be associated with the pathological mechanism of viral pneumonia, which first tends to affect the terminal bronchioles and their surrounding pulmonary parenchyma and then develops into infiltration of pulmonary lobules and finally, diffuse alveolar damage (Bassetti M, 2020).

The main symptoms in COVID-19 patients are fever and cough, which appears to be more frequent in adults than children, as well as dyspnea, and myalgia a lower rate of patients presenting headache, confusion, chest pain, and diarrhea. Furthermore, about half patients infected with 2019-nCoV had underlying chronic diseases, mainly cardiovascular and cerebrovascular diseases and diabetes (Chen N, 2020).

Our study, carried out DAE – Department Accident and Emergency (Radiology -Emergency Unit of “Umberto I” – “ Sapienza” University of Rome) in a cohort of 20 COVID-19 patients, analyzed the incoming and control CT and highlights the progression of lung lesions.

This study aims to demonstrate how the radiographer can help the Radiologist to formulate a correct diagnosis of covid-19 disease in  an emergency using in a new and innovative way a no specific software to deal with the Covid emergency, which has proven to be an excellent support in subsequent comparison with data precise numerical.


The Philips “Lung Density” software on our workstation “Extended Brilliance Workspace” performs quantitative volumetric measurements of pulmonary emphysema. Our idea was to use the properties of this program to calculate the lung damage caused by Covid. This information allows the Radiologist to make a more precise diagnosis of the stage of the disease and allows an adequate therapy.


The study included a cohort of 20 adult patients (10 male and 10 female; median age 59.4, age range 28-86), hospitalized for COVID-19 symptom, none of them had NAAT result. The patients were collected between March 12, 2020, and May 14, 2020, in a designated hospital (Azienda Ospedaliero-Universitaria Policlinico “Umberto I” – Rome, Italy) in Emergency conditions.

The clinical data analyzed were as follows: age, sex, exposure history, comorbid conditions, symptoms, and laboratory results. All this shows that the 20% had previous respiratory disease, the 5% had previous heart disease, the 15% had diabetes and the 55% had hypertension, the 20% had a previous contact with a positive patient. Later, all patients tested positive for NAAT, in fact, according to the results 65% of the patients had at least one of the potential risk factors of contracting Covid-19 that could help clinicians to identify patients with poor prognosis at an early stage (Fei Zhou, 2020) (Paul Weiss, 2020)

Considering the clinical symptoms of Covid-19 the 80% had fever, the 45% had contracted, the 30% suffered from dyspnea, none of patients tested had diarrhea. The 80% had a COVID-19 symptomatology. (Alfonso J. Rodriguez-Moralesa, 2020) (Chaolin Huang, 2020)

Tab. 1

All patients underwent non-contrast enhanced chest computed tomography (CT). CT is widely used, has rapid acquisition speed and high sensitivity, which has led to confirmed Covid-19 infection of a large number of patients whose evolution needs to be followed (Zhu N, 2020).

The equipment used was a Somatom Sensation 16 and a Somatom Sensation 64 (Siemens Healthcare Erlangen, Germany), detectors 16×0.75 or 64×0.6, with a standardized protocol, mA 100, caredose 4D, kV 140, rotation time 0.37 s, pitch 1.2. The dataset used for the volumetric quantification was the same analyzed by the Radiologist for the diagnose, with the following settings: slice thickness of 1 mm contiguous, Kernel b75 very sharp.

Tab. 2

After several tests to validate the reliability of the calculation, we were finally able to obtain quantitative volumetric measurements of healthy lung with a visual representation. The choice of the threshold value was based on the fact the density of the healthy lung is less than or equal to -800 HU, therefore the lesions caused by interstitial pneumonia from Covid-19 have a higher density, it is possible to exclude them from the calculation of the healthy lung. Quantitative volumetric measurements of lung were made by entering a threshold value, -800 HU, so that the values below the threshold are taken into account in the calculation. The software provides a percentage, representative of a healthy lung, from which it’s possible to indirectly estimate lung damage.

For each patient the calculation was made for the first and for the control CT images.

Fig. 1 – Lung parenchyma lesion density measurement with a mixed pixel/ROI system (Radiology Department Emergency and Accident (D.E.A.) of Policlinico Umberto I Roma)
Fig. 2 – Volume Evaluation of parenchyma density (red), the trachea volume (blue).
Radiology Department Emergency and Accident (D.E.A.) of Policlinico Umberto I Roma)
Fig. 3

Two experienced radiologists analyzed the clinical characteristics of the patients, as well as the distribution characteristics, pattern, morphology, and accompanying manifestations of lung lesions. In addition, follow-up CT chest images were evaluated to assess radiological evolution. Radiologists have indicated the stage of interstitial pneumonia for each patient by (initial, progressive and advanced) cataloging them in a table.


The patterns found by CT chest led to a diagnosis of Covid positivity for all patients analyzed, confirmed by the results of the swab obtained at a later time. The profile of the reports made by Radiologists and of the quantitative evaluation of two CT (incoming and control) the numerical results obtained from the calculation of lung capacity (percentage of healthy lung) are comparable to those obtained by radiologists.

Volumetric assessment of lung capacity in Covid patients has proved to be a valid tool as an indicator of the severity of lung injury.

Tab. 3


In conclusion, CT chest is irreplaceable in the preliminary Covid-19 screening, unlined to NAAT of SARS-CoV-2, which is limited by false-negative results and limitations detection of HRCT is simple to perform and readily available, can quickly detect lung lesions and make early on stage imaging diagnoses. Therefore, it has great value in early screening, differential diagnosis, and disease severity assessment of COVID-19. For patients with fever as the first symptom and with a history of exposure to COVID-19, CT chest should be performed as soon as possible. If imaging shows the presence of typical manifestations of 2019-nCoV, even if the NAAT result for the detection of SARS-CoV-2 is not available or negative, it is still necessary to take isolation measures to avoid the spread of the epidemic. (Dai W, 2020)

The availability of a program able to perform a quantification of lung damage in this emergency situation has proved to be of great help for the work of radiologists. In fact, the rapid diagnosis of the disease and the identification of its severity, allows the patient rapid access to treatment. In addition, the possibility of making a comparison between the various control CT allows to see the evolution of the disease and the appropriate therapy, in the vision of a total healing of the patient and the possibility of freeing places in departments of short or long stay.


  1. Alfonso J. Rodriguez-Moralesa, J. A.-O.-O. (2020, March 13). Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis. PMC.
  2. Bassetti M, V. A. (2020, January 31). The novel Chinese coronavirus (2019-nCoV) infections: challenges for fighting the storm.). European Journal of Clinical Investigation.
  3. Chaolin Huang, Y. W. (2020, January 24). Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet.
  4. Chen N, Z. M. (2020, January 30). Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study).
  5. Chung M, B. A. (2020, April). Features of 2019 Novel Coronavirus (2019-nCoV). Radiology, p. 202-207.
  6. Dai W, Z. H. (2020, March 4). CT Imaging and Differential Diagnosis of COVID-19. Canadian Association of Radiologists Journal, p. 195-200.
  7. Fei Zhou, T. Y. (2020, March 11). Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study . ScienceDirect.
  8. Kamel Boulos, M. G. (2020, March 11). Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic and associated events around the world: how 21st century GIS technologies are supporting the global fight against outbr. International Journal of Health Geographics 19, 8.
  9. Paul Weiss, D. R. (2020, April 3). Clinical course and mortality risk of severe COVID-19. Lancet.
  10. Zhu N, Z. D. (2020, January 24). A novel coronavirus from patients with pneumonia in China, 2019.). NEJM.