Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia?
<i>Background and Objectives</i>: This study aimed to investigate whether predictive indicators for the deterioration of respiratory status can be derived from the deep learning data analysis of initial chest computed tomography (CT) scans of patients with coronavirus disease 2019 (COVID...
Guardado en:
| Autores principales: | , , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
MDPI AG
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/8b2884b6076343c2995406c06af04faf |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:8b2884b6076343c2995406c06af04faf |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:8b2884b6076343c2995406c06af04faf2021-11-25T18:18:05ZCan Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia?10.3390/medicina571111481648-91441010-660Xhttps://doaj.org/article/8b2884b6076343c2995406c06af04faf2021-10-01T00:00:00Zhttps://www.mdpi.com/1648-9144/57/11/1148https://doaj.org/toc/1010-660Xhttps://doaj.org/toc/1648-9144<i>Background and Objectives</i>: This study aimed to investigate whether predictive indicators for the deterioration of respiratory status can be derived from the deep learning data analysis of initial chest computed tomography (CT) scans of patients with coronavirus disease 2019 (COVID-19). <i>Materials and Methods</i>: Out of 117 CT scans of 75 patients with COVID-19 admitted to our hospital between April and June 2020, we retrospectively analyzed 79 CT scans that had a definite time of onset and were performed prior to any medication intervention. Patients were grouped according to the presence or absence of increased oxygen demand after CT scan. Quantitative volume data of lung opacity were measured automatically using a deep learning-based image analysis system. The sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of the opacity volume data were calculated to evaluate the accuracy of the system in predicting the deterioration of respiratory status. <i>Results</i>: All 79 CT scans were included (median age, 62 years (interquartile range, 46–77 years); 56 (70.9%) were male. The volume of opacity was significantly higher for the increased oxygen demand group than for the nonincreased oxygen demand group (585.3 vs. 132.8 mL, <i>p</i> < 0.001). The sensitivity, specificity, and AUC were 76.5%, 68.2%, and 0.737, respectively, in the prediction of increased oxygen demand. <i>Conclusion:</i> Deep learning-based quantitative analysis of the affected lung volume in the initial CT scans of patients with COVID-19 can predict the deterioration of respiratory status to improve treatment and resource management.Marie TakahashiTomoyuki FujiokaToshihiro HoriiKoichiro KimuraMizuki KimuraYurika HashimotoYoshio KitazumeMitsuhiro KishinoUkihide TateishiMDPI AGarticlechest imagingCOVID-19deep learningradiologychest CToxygen demandMedicine (General)R5-920ENMedicina, Vol 57, Iss 1148, p 1148 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
chest imaging COVID-19 deep learning radiology chest CT oxygen demand Medicine (General) R5-920 |
| spellingShingle |
chest imaging COVID-19 deep learning radiology chest CT oxygen demand Medicine (General) R5-920 Marie Takahashi Tomoyuki Fujioka Toshihiro Horii Koichiro Kimura Mizuki Kimura Yurika Hashimoto Yoshio Kitazume Mitsuhiro Kishino Ukihide Tateishi Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia? |
| description |
<i>Background and Objectives</i>: This study aimed to investigate whether predictive indicators for the deterioration of respiratory status can be derived from the deep learning data analysis of initial chest computed tomography (CT) scans of patients with coronavirus disease 2019 (COVID-19). <i>Materials and Methods</i>: Out of 117 CT scans of 75 patients with COVID-19 admitted to our hospital between April and June 2020, we retrospectively analyzed 79 CT scans that had a definite time of onset and were performed prior to any medication intervention. Patients were grouped according to the presence or absence of increased oxygen demand after CT scan. Quantitative volume data of lung opacity were measured automatically using a deep learning-based image analysis system. The sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) of the opacity volume data were calculated to evaluate the accuracy of the system in predicting the deterioration of respiratory status. <i>Results</i>: All 79 CT scans were included (median age, 62 years (interquartile range, 46–77 years); 56 (70.9%) were male. The volume of opacity was significantly higher for the increased oxygen demand group than for the nonincreased oxygen demand group (585.3 vs. 132.8 mL, <i>p</i> < 0.001). The sensitivity, specificity, and AUC were 76.5%, 68.2%, and 0.737, respectively, in the prediction of increased oxygen demand. <i>Conclusion:</i> Deep learning-based quantitative analysis of the affected lung volume in the initial CT scans of patients with COVID-19 can predict the deterioration of respiratory status to improve treatment and resource management. |
| format |
article |
| author |
Marie Takahashi Tomoyuki Fujioka Toshihiro Horii Koichiro Kimura Mizuki Kimura Yurika Hashimoto Yoshio Kitazume Mitsuhiro Kishino Ukihide Tateishi |
| author_facet |
Marie Takahashi Tomoyuki Fujioka Toshihiro Horii Koichiro Kimura Mizuki Kimura Yurika Hashimoto Yoshio Kitazume Mitsuhiro Kishino Ukihide Tateishi |
| author_sort |
Marie Takahashi |
| title |
Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia? |
| title_short |
Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia? |
| title_full |
Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia? |
| title_fullStr |
Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia? |
| title_full_unstemmed |
Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia? |
| title_sort |
can deep learning-based volumetric analysis predict oxygen demand increase in patients with covid-19 pneumonia? |
| publisher |
MDPI AG |
| publishDate |
2021 |
| url |
https://doaj.org/article/8b2884b6076343c2995406c06af04faf |
| work_keys_str_mv |
AT marietakahashi candeeplearningbasedvolumetricanalysispredictoxygendemandincreaseinpatientswithcovid19pneumonia AT tomoyukifujioka candeeplearningbasedvolumetricanalysispredictoxygendemandincreaseinpatientswithcovid19pneumonia AT toshihirohorii candeeplearningbasedvolumetricanalysispredictoxygendemandincreaseinpatientswithcovid19pneumonia AT koichirokimura candeeplearningbasedvolumetricanalysispredictoxygendemandincreaseinpatientswithcovid19pneumonia AT mizukikimura candeeplearningbasedvolumetricanalysispredictoxygendemandincreaseinpatientswithcovid19pneumonia AT yurikahashimoto candeeplearningbasedvolumetricanalysispredictoxygendemandincreaseinpatientswithcovid19pneumonia AT yoshiokitazume candeeplearningbasedvolumetricanalysispredictoxygendemandincreaseinpatientswithcovid19pneumonia AT mitsuhirokishino candeeplearningbasedvolumetricanalysispredictoxygendemandincreaseinpatientswithcovid19pneumonia AT ukihidetateishi candeeplearningbasedvolumetricanalysispredictoxygendemandincreaseinpatientswithcovid19pneumonia |
| _version_ |
1718411394377842688 |