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10.1007/s00259-021-05435-8 http://scihub22266oqcxt.onion/10.1007/s00259-021-05435-8 34137946!8210511!34137946     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Eur+J+Nucl+Med+Mol+Imaging 2021 ; 48 (13): 4339-4349 Nephropedia Template TP {{tp|p=34137946|t=2021. Early prediction of lung lesion progression in COVID-19 patients with extended CT ventilation imaging |pdf=|usr=}}{{34137946}} gab.com Text Early prediction of lung lesion progression in COVID-19 patients with extended CT ventilation imaging JO: Eur J Nucl Med Mol Imaging http://www.kidney.de/pget.php?&tw=1&pmid=34137946 #FOAvip PURPOSE: In the prediction of COVID-19 disease progression, a clear illustration and early determination of an area that will be affected by pneumonia remain great challenges. In this study, we aimed to predict and visualize the progression of lung lesions in COVID-19 patients in the early stage of illness by using chest CT. METHODS: COVID-19 patients who underwent three chest CT scans in the progressive phase were retrospectively enrolled. An extended CT ventilation imaging (CTVI) method was proposed in this work that was adapted to use two chest CT scans acquired on different days, and then lung ventilation maps were generated. The prediction maps were obtained according to the fractional ventilation values, which were related to pulmonary regional function and tissue property changes. The third CT scan was used to validate whether the prediction maps could be used to distinguish healthy regions and potential lesions. RESULTS: A total of 30 patients (mean age +/- SD, 43 +/- 10 years, 19 females, and 2-12 days between the second and third CT scans) were included in this study. The predicted lesion locations and sizes were almost the same as the true ones visualized in third CT scan. Quantitatively, the predicted lesion volumes and true lesion volumes showed both a good Pearson correlation (R(2) = 0.80; P < 0.001) and good consistency in the Bland-Altman plot (mean bias = 0.04 cm(3)). Regarding the enlargements of the existing lesions, prediction results also exhibited a good Pearson correlation (R(2) = 0.76; P < 0.001) with true lesion enlargements. CONCLUSION: The present findings demonstrated that the extended CTVI method could accurately predict and visualize the progression of lung lesions in COVID-19 patients in the early stage of illness, which is helpful for physicians to predetermine the severity of COVID-19 pneumonia and make effective treatment plans in advance. Twit Text FOAVip Early prediction of lung lesion progression in COVID-19 patients with extended CT ventilation imaging ????Eur J Nucl Med Mol Imaging http://www.kidney.de/pget.php?&tw=1&pmid=34137946 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34137946 #FOAvip English Wikipedia <ref>{{Cite pmid|34137946}}</ref> Early prediction of lung lesion progression in COVID-19 patients with extended CT ventilation imaging #MMPMID34137946 Wang C; Huang L; Xiao S; Li Z; Ye C; Xia L; Zhou X Eur J Nucl Med Mol Imaging 2021[Dec]; 48 (13): 4339-4349 PMID34137946show ga PURPOSE: In the prediction of COVID-19 disease progression, a clear illustration and early determination of an area that will be affected by pneumonia remain great challenges. In this study, we aimed to predict and visualize the progression of lung lesions in COVID-19 patients in the early stage of illness by using chest CT. METHODS: COVID-19 patients who underwent three chest CT scans in the progressive phase were retrospectively enrolled. An extended CT ventilation imaging (CTVI) method was proposed in this work that was adapted to use two chest CT scans acquired on different days, and then lung ventilation maps were generated. The prediction maps were obtained according to the fractional ventilation values, which were related to pulmonary regional function and tissue property changes. The third CT scan was used to validate whether the prediction maps could be used to distinguish healthy regions and potential lesions. RESULTS: A total of 30 patients (mean age +/- SD, 43 +/- 10 years, 19 females, and 2-12 days between the second and third CT scans) were included in this study. The predicted lesion locations and sizes were almost the same as the true ones visualized in third CT scan. Quantitatively, the predicted lesion volumes and true lesion volumes showed both a good Pearson correlation (R(2) = 0.80; P < 0.001) and good consistency in the Bland-Altman plot (mean bias = 0.04 cm(3)). Regarding the enlargements of the existing lesions, prediction results also exhibited a good Pearson correlation (R(2) = 0.76; P < 0.001) with true lesion enlargements. CONCLUSION: The present findings demonstrated that the extended CTVI method could accurately predict and visualize the progression of lung lesions in COVID-19 patients in the early stage of illness, which is helpful for physicians to predetermine the severity of COVID-19 pneumonia and make effective treatment plans in advance. |*COVID-19[MESH] |Adult[MESH] |Female[MESH] |Humans[MESH] |Lung/diagnostic imaging[MESH] |Middle Aged[MESH] |Retrospective Studies[MESH] |SARS-CoV-2[MESH]Early prediction of lung lesion progression in COVID-19 patients with (epmc).pdf DeepDyve Pubget Overpricing