Diagnostic of Patients with COVID-19 Pneumonia Using Passive Medical Microwave Radiometry (MWR).

2019-nCoV COVID-19 RT-PCR SARS-CoV-2 chest CT community-acquired pneumonia microwave radiometry temperature measurement

Journal

Diagnostics (Basel, Switzerland)
ISSN: 2075-4418
Titre abrégé: Diagnostics (Basel)
Pays: Switzerland
ID NLM: 101658402

Informations de publication

Date de publication:
03 Aug 2023
Historique:
received: 21 04 2023
revised: 14 07 2023
accepted: 26 07 2023
medline: 12 8 2023
pubmed: 12 8 2023
entrez: 12 8 2023
Statut: epublish

Résumé

Chest CT is widely regarded as a dependable imaging technique for detecting pneumonia in COVID-19 patients, but there is growing interest in microwave radiometry (MWR) of the lungs as a possible substitute for diagnosing lung involvement. The aim of this study is to examine the utility of the MWR approach as a screening tool for diagnosing pneumonia with complications in patients with COVID-19. Our study involved two groups of participants. The control group consisted of 50 individuals (24 male and 26 female) between the ages of 20 and 70 years who underwent clinical evaluations and had no known medical conditions. The main group included 142 participants (67 men and 75 women) between the ages of 20 and 87 years who were diagnosed with COVID-19 complicated by pneumonia and were admitted to the emergency department between June 2020 to June 2021. Skin and lung temperatures were measured at 14 points, including 2 additional reference points, using a previously established method. Lung temperature data were obtained with the MWR2020 (MMWR LTD, Edinburgh, UK). All participants underwent clinical evaluations, laboratory tests, chest CT scans, MWR of the lungs, and reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2. The MWR exhibits a high predictive capacity as demonstrated by its sensitivity of 97.6% and specificity of 92.7%. MWR of the lungs can be a valuable substitute for chest CT in diagnosing pneumonia in patients with COVID-19, especially in situations where chest CT is unavailable or impractical.

Sections du résumé

BACKGROUND BACKGROUND
Chest CT is widely regarded as a dependable imaging technique for detecting pneumonia in COVID-19 patients, but there is growing interest in microwave radiometry (MWR) of the lungs as a possible substitute for diagnosing lung involvement.
AIM OBJECTIVE
The aim of this study is to examine the utility of the MWR approach as a screening tool for diagnosing pneumonia with complications in patients with COVID-19.
METHODS METHODS
Our study involved two groups of participants. The control group consisted of 50 individuals (24 male and 26 female) between the ages of 20 and 70 years who underwent clinical evaluations and had no known medical conditions. The main group included 142 participants (67 men and 75 women) between the ages of 20 and 87 years who were diagnosed with COVID-19 complicated by pneumonia and were admitted to the emergency department between June 2020 to June 2021. Skin and lung temperatures were measured at 14 points, including 2 additional reference points, using a previously established method. Lung temperature data were obtained with the MWR2020 (MMWR LTD, Edinburgh, UK). All participants underwent clinical evaluations, laboratory tests, chest CT scans, MWR of the lungs, and reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2.
RESULTS RESULTS
The MWR exhibits a high predictive capacity as demonstrated by its sensitivity of 97.6% and specificity of 92.7%.
CONCLUSIONS CONCLUSIONS
MWR of the lungs can be a valuable substitute for chest CT in diagnosing pneumonia in patients with COVID-19, especially in situations where chest CT is unavailable or impractical.

Identifiants

pubmed: 37568948
pii: diagnostics13152585
doi: 10.3390/diagnostics13152585
pmc: PMC10417460
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Berik Emilov (B)

Educational-Scientific Medical Center, Kyrgyz State Medical Academy Named after Isa Akhunbaev, Bishkek 720040, Kyrgyzstan.

Aleksander Sorokin (A)

Department of Physics, Medical Informatics and Biology, Kyrgyz-Russian Slavic University Named after Boris Yeltsin, Bishkek 720000, Kyrgyzstan.

Meder Seiitov (M)

Educational-Scientific Medical Center, Kyrgyz State Medical Academy Named after Isa Akhunbaev, Bishkek 720040, Kyrgyzstan.

Binsei Toshi Kobayashi (BT)

Well Being Ginza, Tokyo 104-0061, Japan.

Tulegen Chubakov (T)

Kyrgyz State Medical Institute of Post-Graduate Training and Continuous Education Named after S.B. Daniyarov, Bishkek 720040, Kyrgyzstan.

Sergey Vesnin (S)

Medical Microwave Radiometry Ltd., Edinburgh EH10 5LZ, UK.

Illarion Popov (I)

Faculty of Mathematics and Information Technology, Volgograd State University, 400062 Volgograd, Russia.

Aleksandra Krylova (A)

Faculty of Mathematics and Information Technology, Volgograd State University, 400062 Volgograd, Russia.

Igor Goryanin (I)

School of Informatics, University of Edinburgh, Edinburgh EH8 9AZ, UK.
Biological Systems Unit, Okinawa Institute Science and Technology, Kunigami District, Okinawa 904-0495, Japan.

Classifications MeSH