Evolution of CT Findings and Lung Residue in Patients with COVID-19 Pneumonia: Quantitative Analysis of the Disease with a Computer Automatic Tool

Purpose: the purpose of this study was to assess the evolution of computed tomography (CT) findings and lung residue in patients with COVID-19 pneumonia, via quantified evaluation of the disease, using a computer aided tool. Materials and methods: we retrospectively evaluated 341 CT examinations of...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of personalized medicine 2021-07, Vol.11 (7), p.641
Hauptverfasser: Grassi, Roberto, Cappabianca, Salvatore, Urraro, Fabrizio, Granata, Vincenza, Giacobbe, Giuliana, Magliocchetti, Simona, Cozzi, Diletta, Fusco, Roberta, Galdiero, Roberta, Picone, Carmine, Belfiore, Maria Paola, Reginelli, Alfonso, Atripaldi, Umberto, Picascia, Ornella, Coppola, Michele, Bignardi, Elio, Grassi, Roberta, Miele, Vittorio
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 7
container_start_page 641
container_title Journal of personalized medicine
container_volume 11
creator Grassi, Roberto
Cappabianca, Salvatore
Urraro, Fabrizio
Granata, Vincenza
Giacobbe, Giuliana
Magliocchetti, Simona
Cozzi, Diletta
Fusco, Roberta
Galdiero, Roberta
Picone, Carmine
Belfiore, Maria Paola
Reginelli, Alfonso
Atripaldi, Umberto
Picascia, Ornella
Coppola, Michele
Bignardi, Elio
Grassi, Roberta
Miele, Vittorio
description Purpose: the purpose of this study was to assess the evolution of computed tomography (CT) findings and lung residue in patients with COVID-19 pneumonia, via quantified evaluation of the disease, using a computer aided tool. Materials and methods: we retrospectively evaluated 341 CT examinations of 140 patients (68 years of median age) infected with COVID-19 (confirmed by real-time reverse transcriptase polymerase chain reaction (RT-PCR)), who were hospitalized, and who received clinical and CT examinations. All CTs were evaluated by two expert radiologists, in consensus, at the same reading session, using a computer-aided tool for quantification of the pulmonary disease. The parameters obtained using the computer tool included the healthy residual parenchyma, ground glass opacity, consolidation, and total lung volume. Results: statistically significant differences (p value ≤ 0.05) were found among quantified volumes of healthy residual parenchyma, ground glass opacity (GGO), consolidation, and total lung volume, considering different clinical conditions (stable, improved, and worsened). Statistically significant differences were found among quantified volumes for healthy residual parenchyma, GGO, and consolidation (p value ≤ 0.05) between dead patients and discharged patients. CT was not performed on cadavers; the death was an outcome, which was retrospectively included to differentiate findings of patients who survived vs. patients who died during hospitalization. Among discharged patients, complete disease resolutions on CT scans were observed in 62/129 patients with lung disease involvement ≤5%; lung disease involvement from 5% to 15% was found in 40/129 patients, while 27/129 patients had lung disease involvement between 16 and 30%. Moreover, 8–21 days (after hospital admission) was an “advanced period” with the most severe lung disease involvement. After the extent of involvement started to decrease—particularly after 21 days—the absorption was more obvious. Conclusions: a complete disease resolution on chest CT scans was observed in 48.1% of discharged patients using a computer-aided tool to quantify the GGO and consolidation volumes; after 16 days of hospital admission, the abnormalities identified by chest CT began to improve; in particular, the absorption was more obvious after 21 days.
doi_str_mv 10.3390/jpm11070641
format Article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8305822</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2554587851</sourcerecordid><originalsourceid>FETCH-LOGICAL-c386t-78414a436529e36baa6b900eb8575c624261917c597f486e7b543ea772b227233</originalsourceid><addsrcrecordid>eNpdkdtqGzEQhkVpaUKaq76AoDeFsq3O0vaiYDaHBgxJi9tboV2PbZldyV1JDnmNPnHWdShp52YG5puf-WcQekvJR85r8mm7GyglmihBX6BTRrSshGDq5bP6BJ2ntCVTGMmYIq_RCRdcakrMKfp9uY99yT4GHFe4WeArH5Y-rBN2YYnnJazxd0h-WQD7gO9c9hBywvc-b3Bz-_PmoqI1vgtQhhi8-4y_FReyzxO3BzwLrn9IPh2k8wbwhU_gEhynHW7isCsZRjwrOQ7TSIcXMfZv0KuV6xOcP-Uz9OPqctF8rea31zfNbF513KhcaSOocIIryWrgqnVOtTUh0BqpZafY5JzWVHey1ithFOhWCg5Oa9YyphnnZ-jLUXdX2gGW3WRsdL3djX5w44ONztt_O8Fv7DrureFEGsYmgfdPAmP8VSBlO_jUQd-7ALEky6SsBWfU0Al99x-6jWWczvOHEtJoIw_UhyPVjTGlEVZ_l6HEHt5tn72bPwLJ1pr3</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2554587851</pqid></control><display><type>article</type><title>Evolution of CT Findings and Lung Residue in Patients with COVID-19 Pneumonia: Quantitative Analysis of the Disease with a Computer Automatic Tool</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central Open Access</source><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>PubMed Central</source><creator>Grassi, Roberto ; Cappabianca, Salvatore ; Urraro, Fabrizio ; Granata, Vincenza ; Giacobbe, Giuliana ; Magliocchetti, Simona ; Cozzi, Diletta ; Fusco, Roberta ; Galdiero, Roberta ; Picone, Carmine ; Belfiore, Maria Paola ; Reginelli, Alfonso ; Atripaldi, Umberto ; Picascia, Ornella ; Coppola, Michele ; Bignardi, Elio ; Grassi, Roberta ; Miele, Vittorio</creator><creatorcontrib>Grassi, Roberto ; Cappabianca, Salvatore ; Urraro, Fabrizio ; Granata, Vincenza ; Giacobbe, Giuliana ; Magliocchetti, Simona ; Cozzi, Diletta ; Fusco, Roberta ; Galdiero, Roberta ; Picone, Carmine ; Belfiore, Maria Paola ; Reginelli, Alfonso ; Atripaldi, Umberto ; Picascia, Ornella ; Coppola, Michele ; Bignardi, Elio ; Grassi, Roberta ; Miele, Vittorio</creatorcontrib><description>Purpose: the purpose of this study was to assess the evolution of computed tomography (CT) findings and lung residue in patients with COVID-19 pneumonia, via quantified evaluation of the disease, using a computer aided tool. Materials and methods: we retrospectively evaluated 341 CT examinations of 140 patients (68 years of median age) infected with COVID-19 (confirmed by real-time reverse transcriptase polymerase chain reaction (RT-PCR)), who were hospitalized, and who received clinical and CT examinations. All CTs were evaluated by two expert radiologists, in consensus, at the same reading session, using a computer-aided tool for quantification of the pulmonary disease. The parameters obtained using the computer tool included the healthy residual parenchyma, ground glass opacity, consolidation, and total lung volume. Results: statistically significant differences (p value ≤ 0.05) were found among quantified volumes of healthy residual parenchyma, ground glass opacity (GGO), consolidation, and total lung volume, considering different clinical conditions (stable, improved, and worsened). Statistically significant differences were found among quantified volumes for healthy residual parenchyma, GGO, and consolidation (p value ≤ 0.05) between dead patients and discharged patients. CT was not performed on cadavers; the death was an outcome, which was retrospectively included to differentiate findings of patients who survived vs. patients who died during hospitalization. Among discharged patients, complete disease resolutions on CT scans were observed in 62/129 patients with lung disease involvement ≤5%; lung disease involvement from 5% to 15% was found in 40/129 patients, while 27/129 patients had lung disease involvement between 16 and 30%. Moreover, 8–21 days (after hospital admission) was an “advanced period” with the most severe lung disease involvement. After the extent of involvement started to decrease—particularly after 21 days—the absorption was more obvious. Conclusions: a complete disease resolution on chest CT scans was observed in 48.1% of discharged patients using a computer-aided tool to quantify the GGO and consolidation volumes; after 16 days of hospital admission, the abnormalities identified by chest CT began to improve; in particular, the absorption was more obvious after 21 days.</description><identifier>ISSN: 2075-4426</identifier><identifier>EISSN: 2075-4426</identifier><identifier>DOI: 10.3390/jpm11070641</identifier><identifier>PMID: 34357108</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Cadavers ; Chest ; Computed tomography ; Coronaviruses ; COVID-19 ; Lung diseases ; Medical equipment ; Parenchyma ; Patients ; Pneumonia ; Polymerase chain reaction ; Precision medicine ; Quantitative analysis ; RNA-directed DNA polymerase ; Software ; Statistical analysis</subject><ispartof>Journal of personalized medicine, 2021-07, Vol.11 (7), p.641</ispartof><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 by the authors. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c386t-78414a436529e36baa6b900eb8575c624261917c597f486e7b543ea772b227233</citedby><cites>FETCH-LOGICAL-c386t-78414a436529e36baa6b900eb8575c624261917c597f486e7b543ea772b227233</cites><orcidid>0000-0002-0469-9969 ; 0000-0001-7028-9047 ; 0000-0002-7848-1567 ; 0000-0003-0566-3199</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305822/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8305822/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27903,27904,53769,53771</link.rule.ids></links><search><creatorcontrib>Grassi, Roberto</creatorcontrib><creatorcontrib>Cappabianca, Salvatore</creatorcontrib><creatorcontrib>Urraro, Fabrizio</creatorcontrib><creatorcontrib>Granata, Vincenza</creatorcontrib><creatorcontrib>Giacobbe, Giuliana</creatorcontrib><creatorcontrib>Magliocchetti, Simona</creatorcontrib><creatorcontrib>Cozzi, Diletta</creatorcontrib><creatorcontrib>Fusco, Roberta</creatorcontrib><creatorcontrib>Galdiero, Roberta</creatorcontrib><creatorcontrib>Picone, Carmine</creatorcontrib><creatorcontrib>Belfiore, Maria Paola</creatorcontrib><creatorcontrib>Reginelli, Alfonso</creatorcontrib><creatorcontrib>Atripaldi, Umberto</creatorcontrib><creatorcontrib>Picascia, Ornella</creatorcontrib><creatorcontrib>Coppola, Michele</creatorcontrib><creatorcontrib>Bignardi, Elio</creatorcontrib><creatorcontrib>Grassi, Roberta</creatorcontrib><creatorcontrib>Miele, Vittorio</creatorcontrib><title>Evolution of CT Findings and Lung Residue in Patients with COVID-19 Pneumonia: Quantitative Analysis of the Disease with a Computer Automatic Tool</title><title>Journal of personalized medicine</title><description>Purpose: the purpose of this study was to assess the evolution of computed tomography (CT) findings and lung residue in patients with COVID-19 pneumonia, via quantified evaluation of the disease, using a computer aided tool. Materials and methods: we retrospectively evaluated 341 CT examinations of 140 patients (68 years of median age) infected with COVID-19 (confirmed by real-time reverse transcriptase polymerase chain reaction (RT-PCR)), who were hospitalized, and who received clinical and CT examinations. All CTs were evaluated by two expert radiologists, in consensus, at the same reading session, using a computer-aided tool for quantification of the pulmonary disease. The parameters obtained using the computer tool included the healthy residual parenchyma, ground glass opacity, consolidation, and total lung volume. Results: statistically significant differences (p value ≤ 0.05) were found among quantified volumes of healthy residual parenchyma, ground glass opacity (GGO), consolidation, and total lung volume, considering different clinical conditions (stable, improved, and worsened). Statistically significant differences were found among quantified volumes for healthy residual parenchyma, GGO, and consolidation (p value ≤ 0.05) between dead patients and discharged patients. CT was not performed on cadavers; the death was an outcome, which was retrospectively included to differentiate findings of patients who survived vs. patients who died during hospitalization. Among discharged patients, complete disease resolutions on CT scans were observed in 62/129 patients with lung disease involvement ≤5%; lung disease involvement from 5% to 15% was found in 40/129 patients, while 27/129 patients had lung disease involvement between 16 and 30%. Moreover, 8–21 days (after hospital admission) was an “advanced period” with the most severe lung disease involvement. After the extent of involvement started to decrease—particularly after 21 days—the absorption was more obvious. Conclusions: a complete disease resolution on chest CT scans was observed in 48.1% of discharged patients using a computer-aided tool to quantify the GGO and consolidation volumes; after 16 days of hospital admission, the abnormalities identified by chest CT began to improve; in particular, the absorption was more obvious after 21 days.</description><subject>Cadavers</subject><subject>Chest</subject><subject>Computed tomography</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Lung diseases</subject><subject>Medical equipment</subject><subject>Parenchyma</subject><subject>Patients</subject><subject>Pneumonia</subject><subject>Polymerase chain reaction</subject><subject>Precision medicine</subject><subject>Quantitative analysis</subject><subject>RNA-directed DNA polymerase</subject><subject>Software</subject><subject>Statistical analysis</subject><issn>2075-4426</issn><issn>2075-4426</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNpdkdtqGzEQhkVpaUKaq76AoDeFsq3O0vaiYDaHBgxJi9tboV2PbZldyV1JDnmNPnHWdShp52YG5puf-WcQekvJR85r8mm7GyglmihBX6BTRrSshGDq5bP6BJ2ntCVTGMmYIq_RCRdcakrMKfp9uY99yT4GHFe4WeArH5Y-rBN2YYnnJazxd0h-WQD7gO9c9hBywvc-b3Bz-_PmoqI1vgtQhhi8-4y_FReyzxO3BzwLrn9IPh2k8wbwhU_gEhynHW7isCsZRjwrOQ7TSIcXMfZv0KuV6xOcP-Uz9OPqctF8rea31zfNbF513KhcaSOocIIryWrgqnVOtTUh0BqpZafY5JzWVHey1ithFOhWCg5Oa9YyphnnZ-jLUXdX2gGW3WRsdL3djX5w44ONztt_O8Fv7DrureFEGsYmgfdPAmP8VSBlO_jUQd-7ALEky6SsBWfU0Al99x-6jWWczvOHEtJoIw_UhyPVjTGlEVZ_l6HEHt5tn72bPwLJ1pr3</recordid><startdate>20210706</startdate><enddate>20210706</enddate><creator>Grassi, Roberto</creator><creator>Cappabianca, Salvatore</creator><creator>Urraro, Fabrizio</creator><creator>Granata, Vincenza</creator><creator>Giacobbe, Giuliana</creator><creator>Magliocchetti, Simona</creator><creator>Cozzi, Diletta</creator><creator>Fusco, Roberta</creator><creator>Galdiero, Roberta</creator><creator>Picone, Carmine</creator><creator>Belfiore, Maria Paola</creator><creator>Reginelli, Alfonso</creator><creator>Atripaldi, Umberto</creator><creator>Picascia, Ornella</creator><creator>Coppola, Michele</creator><creator>Bignardi, Elio</creator><creator>Grassi, Roberta</creator><creator>Miele, Vittorio</creator><general>MDPI AG</general><general>MDPI</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FH</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-0469-9969</orcidid><orcidid>https://orcid.org/0000-0001-7028-9047</orcidid><orcidid>https://orcid.org/0000-0002-7848-1567</orcidid><orcidid>https://orcid.org/0000-0003-0566-3199</orcidid></search><sort><creationdate>20210706</creationdate><title>Evolution of CT Findings and Lung Residue in Patients with COVID-19 Pneumonia: Quantitative Analysis of the Disease with a Computer Automatic Tool</title><author>Grassi, Roberto ; Cappabianca, Salvatore ; Urraro, Fabrizio ; Granata, Vincenza ; Giacobbe, Giuliana ; Magliocchetti, Simona ; Cozzi, Diletta ; Fusco, Roberta ; Galdiero, Roberta ; Picone, Carmine ; Belfiore, Maria Paola ; Reginelli, Alfonso ; Atripaldi, Umberto ; Picascia, Ornella ; Coppola, Michele ; Bignardi, Elio ; Grassi, Roberta ; Miele, Vittorio</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c386t-78414a436529e36baa6b900eb8575c624261917c597f486e7b543ea772b227233</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Cadavers</topic><topic>Chest</topic><topic>Computed tomography</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>Lung diseases</topic><topic>Medical equipment</topic><topic>Parenchyma</topic><topic>Patients</topic><topic>Pneumonia</topic><topic>Polymerase chain reaction</topic><topic>Precision medicine</topic><topic>Quantitative analysis</topic><topic>RNA-directed DNA polymerase</topic><topic>Software</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Grassi, Roberto</creatorcontrib><creatorcontrib>Cappabianca, Salvatore</creatorcontrib><creatorcontrib>Urraro, Fabrizio</creatorcontrib><creatorcontrib>Granata, Vincenza</creatorcontrib><creatorcontrib>Giacobbe, Giuliana</creatorcontrib><creatorcontrib>Magliocchetti, Simona</creatorcontrib><creatorcontrib>Cozzi, Diletta</creatorcontrib><creatorcontrib>Fusco, Roberta</creatorcontrib><creatorcontrib>Galdiero, Roberta</creatorcontrib><creatorcontrib>Picone, Carmine</creatorcontrib><creatorcontrib>Belfiore, Maria Paola</creatorcontrib><creatorcontrib>Reginelli, Alfonso</creatorcontrib><creatorcontrib>Atripaldi, Umberto</creatorcontrib><creatorcontrib>Picascia, Ornella</creatorcontrib><creatorcontrib>Coppola, Michele</creatorcontrib><creatorcontrib>Bignardi, Elio</creatorcontrib><creatorcontrib>Grassi, Roberta</creatorcontrib><creatorcontrib>Miele, Vittorio</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection (ProQuest)</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Biological Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of personalized medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Grassi, Roberto</au><au>Cappabianca, Salvatore</au><au>Urraro, Fabrizio</au><au>Granata, Vincenza</au><au>Giacobbe, Giuliana</au><au>Magliocchetti, Simona</au><au>Cozzi, Diletta</au><au>Fusco, Roberta</au><au>Galdiero, Roberta</au><au>Picone, Carmine</au><au>Belfiore, Maria Paola</au><au>Reginelli, Alfonso</au><au>Atripaldi, Umberto</au><au>Picascia, Ornella</au><au>Coppola, Michele</au><au>Bignardi, Elio</au><au>Grassi, Roberta</au><au>Miele, Vittorio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evolution of CT Findings and Lung Residue in Patients with COVID-19 Pneumonia: Quantitative Analysis of the Disease with a Computer Automatic Tool</atitle><jtitle>Journal of personalized medicine</jtitle><date>2021-07-06</date><risdate>2021</risdate><volume>11</volume><issue>7</issue><spage>641</spage><pages>641-</pages><issn>2075-4426</issn><eissn>2075-4426</eissn><abstract>Purpose: the purpose of this study was to assess the evolution of computed tomography (CT) findings and lung residue in patients with COVID-19 pneumonia, via quantified evaluation of the disease, using a computer aided tool. Materials and methods: we retrospectively evaluated 341 CT examinations of 140 patients (68 years of median age) infected with COVID-19 (confirmed by real-time reverse transcriptase polymerase chain reaction (RT-PCR)), who were hospitalized, and who received clinical and CT examinations. All CTs were evaluated by two expert radiologists, in consensus, at the same reading session, using a computer-aided tool for quantification of the pulmonary disease. The parameters obtained using the computer tool included the healthy residual parenchyma, ground glass opacity, consolidation, and total lung volume. Results: statistically significant differences (p value ≤ 0.05) were found among quantified volumes of healthy residual parenchyma, ground glass opacity (GGO), consolidation, and total lung volume, considering different clinical conditions (stable, improved, and worsened). Statistically significant differences were found among quantified volumes for healthy residual parenchyma, GGO, and consolidation (p value ≤ 0.05) between dead patients and discharged patients. CT was not performed on cadavers; the death was an outcome, which was retrospectively included to differentiate findings of patients who survived vs. patients who died during hospitalization. Among discharged patients, complete disease resolutions on CT scans were observed in 62/129 patients with lung disease involvement ≤5%; lung disease involvement from 5% to 15% was found in 40/129 patients, while 27/129 patients had lung disease involvement between 16 and 30%. Moreover, 8–21 days (after hospital admission) was an “advanced period” with the most severe lung disease involvement. After the extent of involvement started to decrease—particularly after 21 days—the absorption was more obvious. Conclusions: a complete disease resolution on chest CT scans was observed in 48.1% of discharged patients using a computer-aided tool to quantify the GGO and consolidation volumes; after 16 days of hospital admission, the abnormalities identified by chest CT began to improve; in particular, the absorption was more obvious after 21 days.</abstract><cop>Basel</cop><pub>MDPI AG</pub><pmid>34357108</pmid><doi>10.3390/jpm11070641</doi><orcidid>https://orcid.org/0000-0002-0469-9969</orcidid><orcidid>https://orcid.org/0000-0001-7028-9047</orcidid><orcidid>https://orcid.org/0000-0002-7848-1567</orcidid><orcidid>https://orcid.org/0000-0003-0566-3199</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2075-4426
ispartof Journal of personalized medicine, 2021-07, Vol.11 (7), p.641
issn 2075-4426
2075-4426
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8305822
source Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central Open Access; MDPI - Multidisciplinary Digital Publishing Institute; PubMed Central
subjects Cadavers
Chest
Computed tomography
Coronaviruses
COVID-19
Lung diseases
Medical equipment
Parenchyma
Patients
Pneumonia
Polymerase chain reaction
Precision medicine
Quantitative analysis
RNA-directed DNA polymerase
Software
Statistical analysis
title Evolution of CT Findings and Lung Residue in Patients with COVID-19 Pneumonia: Quantitative Analysis of the Disease with a Computer Automatic Tool
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-24T01%3A58%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Evolution%20of%20CT%20Findings%20and%20Lung%20Residue%20in%20Patients%20with%20COVID-19%20Pneumonia:%20Quantitative%20Analysis%20of%20the%20Disease%20with%20a%20Computer%20Automatic%20Tool&rft.jtitle=Journal%20of%20personalized%20medicine&rft.au=Grassi,%20Roberto&rft.date=2021-07-06&rft.volume=11&rft.issue=7&rft.spage=641&rft.pages=641-&rft.issn=2075-4426&rft.eissn=2075-4426&rft_id=info:doi/10.3390/jpm11070641&rft_dat=%3Cproquest_pubme%3E2554587851%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2554587851&rft_id=info:pmid/34357108&rfr_iscdi=true