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10.1016/j.ejrad.2021.109650 http://scihub22266oqcxt.onion/10.1016/j.ejrad.2021.109650 33743491!7948674!33743491     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Eur+J+Radiol 2021 ; 138 (ä): 109650 Nephropedia Template TP {{tp|p=33743491|t=2021. Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients |pdf=|usr=}}{{33743491}} gab.com Text Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients JO: Eur J Radiol http://www.kidney.de/pget.php?&tw=1&pmid=33743491 #FOAvip PURPOSE: The capability of lung ultrasound (LUS) to distinguish the different pulmonary patterns of COVID-19 and quantify the disease burden compared to chest CT is still unclear. METHODS: PCR-confirmed COVID-19 patients who underwent both LUS and chest CT at the Emergency Department were retrospectively analysed. In both modalities, twelve peripheral lung zones were identified and given a Severity Score basing on main lesion pattern. On CT scans the well-aerated lung volume (%WALV) was visually estimated. Per-patient and per-zone assessments of LUS classification performance taking CT findings as reference were performed, further revisioning the images in case of discordant results. Correlations between number of disease-positive lung zones, Severity Score and %WALV on both LUS and CT were assessed. The area under receiver operating characteristic curve (AUC) was calculated to determine LUS performance in detecting %WALV?</=?70 %. RESULTS: The study included 219 COVID-19 patients with abnormal chest CT. LUS correctly identified as positive 217 (99 %) patients, but per-zone analysis showed sensitivity?=?75 % and specificity?=?66 %. The revision of the 121 (55 %) cases with positive LUS and negative CT revealed COVID-compatible lesions in 42 (38 %) CT scans. Number of disease-positive zones, Severity Score and %WALV between LUS and CT showed moderate correlations. The AUCs for LUS Severity Score and number of LUS-positive zones did not differ in detecting %WALV?</=?70 %. CONCLUSION: LUS in COVID-19 is valuable for case identification but shows only moderate correlation with CT findings as for lesion patterns and severity quantification. The number of disease-positive lung zones in LUS alone was sufficient to discriminate relevant disease burden. Twit Text FOAVip Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients ????Eur J Radiol http://www.kidney.de/pget.php?&tw=1&pmid=33743491 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33743491 #FOAvip English Wikipedia <ref>{{Cite pmid|33743491}}</ref> Correlation between lung ultrasound and chest CT patterns with estimation of pulmonary burden in COVID-19 patients #MMPMID33743491 Rizzetto F; Perillo N; Artioli D; Travaglini F; Cuccia A; Zannoni S; Tombini V; Di Domenico SL; Albertini V; Bergamaschi M; Cazzaniga M; De Mattia C; Torresin A; Vanzulli A Eur J Radiol 2021[May]; 138 (ä): 109650 PMID33743491show ga PURPOSE: The capability of lung ultrasound (LUS) to distinguish the different pulmonary patterns of COVID-19 and quantify the disease burden compared to chest CT is still unclear. METHODS: PCR-confirmed COVID-19 patients who underwent both LUS and chest CT at the Emergency Department were retrospectively analysed. In both modalities, twelve peripheral lung zones were identified and given a Severity Score basing on main lesion pattern. On CT scans the well-aerated lung volume (%WALV) was visually estimated. Per-patient and per-zone assessments of LUS classification performance taking CT findings as reference were performed, further revisioning the images in case of discordant results. Correlations between number of disease-positive lung zones, Severity Score and %WALV on both LUS and CT were assessed. The area under receiver operating characteristic curve (AUC) was calculated to determine LUS performance in detecting %WALV? |*COVID-19[MESH] |Humans[MESH] |Lung/diagnostic imaging[MESH] |Retrospective Studies[MESH] |SARS-CoV-2[MESH] |Tomography, X-Ray Computed[MESH]Correlation between lung ultrasound and chest CT patterns with estimat(epmc).pdf DeepDyve Pubget Overpricing