Early prediction of lung lesion progression in COVID-19 patients with extended CT ventilation imaging.
Early prediction of lung lesion progression in COVID-19 patients with extended CT ventilation imaging.
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DOI：
10.1007/s00259-021-05435-8
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发表时间：
2021-12
影响因子：
9.1
通讯作者：
Zhou X
中科院分区：
文献类型：
--
作者：
Wang C;Huang L;Xiao S;Li Z;Ye C;Xia L;Zhou X
在预测COVID-19疾病进展时，明确说明和早期确定将受肺炎影响的区域仍然是巨大的挑战。在这项研究中，我们的目的是通过使用胸部CT来预测和可视化COVID-19患者在疾病早期的肺部病变进展。回顾性入组了在进行期接受三次胸部CT扫描的COVID-19患者。提出了一种扩展的CT通气成像（CTVI）方法，该方法适用于使用不同日期采集的两次胸部CT扫描，然后生成肺通气图。根据肺通气分数值得到预测图，预测图与肺局部功能和组织性质变化相关。第三次CT扫描用于验证预测图是否可用于区分健康区域和潜在病变。本研究共纳入30例患者（平均年龄± SD，43 ± 10岁，19例女性，第二次和第三次CT扫描之间间隔2-12天）。预测的病变位置和大小与第三次CT扫描中显示的真实病变几乎相同。定量分析显示，预测的病变体积和真实病变体积具有良好的Pearson相关性（R2 = 0.80; P < 0.001），并且在Bland-Altman图中具有良好的一致性（平均偏差= 0.04 cm 3）。关于现有病变的扩大，预测结果也显示出与真实病变扩大的良好Pearson相关性（R2 = 0.76; P < 0.001）。目前的研究结果表明，扩展CTVI方法可以在疾病早期准确预测和可视化COVID-19患者肺部病变的进展，这有助于医生预先确定COVID-19肺炎的严重程度并提前制定有效的治疗计划。在线版本包含补充材料，可通过10.1007/s 00259 -021-05435-8获得。
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. 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. 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 (R2 = 0.80; P < 0.001) and good consistency in the Bland–Altman plot (mean bias = 0.04 cm3). Regarding the enlargements of the existing lesions, prediction results also exhibited a good Pearson correlation (R2 = 0.76; P < 0.001) with true lesion enlargements. 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. The online version contains supplementary material available at 10.1007/s00259-021-05435-8.
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影响因子：
5.9
作者：
Pu J;Leader JK;Bandos A;Ke S;Wang J;Shi J;Du P;Guo Y;Wenzel SE;Fuhrman CR;Wilson DO;Sciurba FC;Jin C
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影响因子：
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DOI：
10.1007/s00259-002-1055-3
发表时间：
2003-05-01
影响因子：
9.1
作者：
Cohade, C;Osman, M;Wahl, RL
通讯作者：
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影响因子：
16.6
作者：
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