Chest CT Computerized Aided Quantification of PNEUMONIA Lesions in COVID-19 Infection: A Comparison among Three Commercial Software

被引：43

作者：

Grassi, Roberto ^{[1
]}

Cappabianca, Salvatore ^{[1
]}

Urraro, Fabrizio ^{[1
]}

Feragalli, Beatrice ^{[2
]}

Montanelli, Alessandro ^{[3
]}

Patelli, Gianluigi ^{[4
]}

Granata, Vincenza ^{[5
]}

Giacobbe, Giuliana ^{[1
]}

Russo, Gaetano Maria ^{[1
]}

Grillo, Assunta ^{[1
]}

De Lisio, Angela ^{[6
]}

Paura, Cesare ^{[6
]}

Clemente, Alfredo ^{[1
]}

Gagliardi, Giuliano ^{[6
]}

Magliocchetti, Simona ^{[1
]}

Cozzi, Diletta ^{[7
]}

Fusco, Roberta ^{[5
]}

Belfiore, Maria Paola ^{[1
]}

Grassi, Roberta ^{[1
]}

Miele, Vittorio ^{[7
]}

机构：

[1] Univ Campania Luigi Vanvitelli, Div Radiodiagnost, I-80138 Naples, Italy

[2] G DAnnunzio Univ Chieti Pescara, Dept Med Oral & Biotechnol Sci, Radiol Unit, I-66100 Chieti, Italy

[3] ASST Bergamo Est, Lab Med Unit, I-24068 Seriate, Italy

[4] ASST Bergamo Est, Dept Radiol, I-24068 Seriate, Italy

[5] Ist Nazl Tumori IRCCS Fdn Pascale IRCCS Napli, Div Radiol, I-80131 Naples, Italy

[6] Azienda Osped Rilievo Nazl Giuseppe Moscati, Diagnost Imaging Unit, I-83100 Avellino, Italy

[7] Azienda Osped Univ Careggi, Div Radiodiagnost, I-50139 Florence, Italy

来源：

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH | 2020年 / 17卷 / 18期

关键词：

COVID-19; computed tomography; computer-aided quantification; DISEASE;

D O I：

10.3390/ijerph17186914

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Purpose: To compare different commercial software in the quantification of Pneumonia Lesions in COVID-19 infection and to stratify the patients based on the disease severity using on chest computed tomography (CT) images. Materials and methods: We retrospectively examined 162 patients with confirmed COVID-19 infection by reverse transcriptase-polymerase chain reaction (RT-PCR) test. All cases were evaluated separately by radiologists (visually) and by using three computer software programs: (1) Thoracic VCAR software, GE Healthcare, United States; (2) Myrian, Intrasense, France; (3) InferRead, InferVision Europe, Wiesbaden, Germany. The degree of lesions was visually scored by the radiologist using a score on 5 levels (none, mild, moderate, severe, and critic). The parameters obtained using the computer tools included healthy residual lung parenchyma, ground-glass opacity area, and consolidation volume. Intraclass coefficient (ICC), Spearman correlation analysis, and non-parametric tests were performed. Results: Thoracic VCAR software was not able to perform volumes segmentation in 26/162 (16.0%) cases, Myrian software in 12/162 (7.4%) patients while InferRead software in 61/162 (37.7%) patients. A great variability (ICC ranged for 0.17 to 0.51) was detected among the quantitative measurements of the residual healthy lung parenchyma volume, GGO, and consolidations volumes calculated by different computer tools. The overall radiological severity score was moderately correlated with the residual healthy lung parenchyma volume obtained by ThoracicVCAR or Myrian software, with the GGO area obtained by the ThoracicVCAR tool and with consolidation volume obtained by Myrian software. Quantified volumes by InferRead software had a low correlation with the overall radiological severity score. Conclusions: Computer-aided pneumonia quantification could be an easy and feasible way to stratify COVID-19 cases according to severity; however, a great variability among quantitative measurements provided by computer tools should be considered.

引用

页码：1 / 15

页数：15

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