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 Table of Contents  
REVIEW ARTICLE
Year : 2021  |  Volume : 8  |  Issue : 4  |  Page : 158-167

Manual severity evaluation methods for novel coronavirus pneumonia based on computed tomography imaging


Department of Medical Imaging, The First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou City, Inner Mongolia Autonomous Region, China

Date of Submission11-Jun-2021
Date of Acceptance07-Oct-2021
Date of Web Publication17-Aug-2022

Correspondence Address:
Lin Luo
Department of Medical Imaging, The First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou City 014010, Inner Mongolia Autonomous Region
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/RID.RID_20_22

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  Abstract 


Computed tomography (CT) examination plays an indispensable role in the diagnosis of coronavirus disease-2019 (COVID-19). Many studies have evaluated the severity of COVID-19 based on CT images, with the severity of COVID-19 being evaluated either manually or by using artificial intelligence. In this review, the recently reported methods for manually evaluating COVID-19 severity based on CT images are summarized and divided into three categories: evaluation based on the extent of abnormalities; evaluation based on the characteristics of abnormalities; and evaluation based on both the extent and characteristics of abnormalities.

Keywords: Computed tomography imaging, coronavirus disease-2019, methodology


How to cite this article:
Chen Q, Luo L. Manual severity evaluation methods for novel coronavirus pneumonia based on computed tomography imaging. Radiol Infect Dis 2021;8:158-67

How to cite this URL:
Chen Q, Luo L. Manual severity evaluation methods for novel coronavirus pneumonia based on computed tomography imaging. Radiol Infect Dis [serial online] 2021 [cited 2022 Oct 6];8:158-67. Available from: http://www.ridiseases.org/text.asp?2021/8/4/158/353894




  Introduction Top


Coronavirus disease-2019 (COVID-19) has spread throughout the world since late 2019.[1] Imaging examination, especially chest computed tomography (CT) examination, plays an indispensable role in the diagnosis of novel coronavirus pneumonia (NCP).[2],[3] Recent studies have shown that the primary imaging manifestations of NCP on chest CT images are ground-glass opacity (GGO), consolidation, and a combination of the two (GGO + consolidation).[4],[5] NCP often involves thickening of the interlobular septa or reticulation. When GGO is combined with interlobular septal thickening, it presents as “crazy paving.” CT imaging not only helps diagnose NCP but it is also used to evaluate NCP severity. However, the methods used for severity evaluation have varied among studies. NCP severity is typically evaluated either manually or by using artificial intelligence. The manual evaluation methods used in studies have usually been those that were previously used for evaluating the severity of pneumonia associated with severe acute respiratory syndrome (SARS) or influenza A (H1N1) virus. Occasionally, these were optimized or improved to some extent. In this review, we summarize the currently reported methods for manual NCP evaluation based on CT imaging. These methods can be grouped into three categories: evaluation based on the extent of abnormalities; evaluation based on the characteristics of abnormalities; and evaluation based on both the extent and characteristics of abnormalities.
  Evaluation Based on the Extent of Abnormalities Top


Assessment of the involvement of abnormalities is the most widely used manual method to evaluate NCP severity based on CT imaging. In this method, the lesion area is used as the main index for evaluating NCP severity, regardless of the characteristics of the lesion. This evaluation method can be divided into the following five categories according to the evaluation unit.

Whole lung used as the evaluation unit

Deng et al.[6] defined the involvement of abnormalities as ≤25%, 26%–50%, 51%–75%, and >75% of the whole lung as mild, moderate, severe, and extremely severe NCP, respectively [Table 1], 4-range scale]. Some studies[7],[8],[9] have defined involvement as ≤10%, 11%–25%, 26%–50%, 51%–75%, and >75% of the whole lung, assigning 1–5 points, respectively. Changhua et al.[10] defined the involvement of abnormalities as <5%, 5%–15%, 16%–30%, 31%–45%, 46%–60%, and >60% of the whole lung, assigning 1–6 points, respectively. Details for these evaluation methods that used the whole lung as the evaluation unit are presented in [Table 1]. Although the whole lung is used as the evaluation unit, the results only roughly approximate the percentage of lesions within the lung. Therefore, these methods were seldom adopted in other relevant studies.
Table 1: Score definition of evaluation methods those use the whole lung as the evaluation unit

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Lung lobes used as the evaluation unit

The majority of studies used the lung lobes as the evaluation units to manually evaluate NCP severity based on CT imaging. The scores are defined according to the extent of lesions involved in each lobe, with no lesions present receiving zero points. The total score of the five lobes is then used as an index to evaluate the extent of abnormality [Table 2]. Chung et al.[11] defined the involvement of abnormalities in each lobe as <26%, 26%–50%, 51%–75%, and >75%, assigning 1–4 points, respectively. The cumulative score range was 0–20. This definition has been applied in many other studies[12],[13],[14],[15],[16],[17],[18],[19],[20],[21],[22],[23],[24],[25],[26],[27],[28],[29],[30],[31],[32],[33],[34],[35],[36],[37],[38],[39] [Table 2], 20-point scale]. Some studies[40],[41],[42],[43],[44],[45],[46],[47],[48],[49],[50],[51],[52],[53],[54],[55],[56],[57],[58],[59],[60],[61],[62],[63],[64],[65],[66],[67],[68],[69],[70],[71],[72],[73],[74],[75],[76] refer to the method reported by Chang et al.,[77] which was used to evaluate the severity of SARS based on chest CT imaging. They defined the extent of lesion involvement in each lobe as <5%, 5%–25%, 26%–50%, 51%–75%, and >75% as 1–5 points, respectively, generating a severity score of 0–25 [Table 2], 25-point scale].
Table 2: Score definition of evaluation methods those use the lung lobe as the evaluation unit

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The two above-mentioned evaluation methods were the most commonly used in studies that evaluated the severity of COVID-19. Some studies[37],[38],[39],[62],[58],[72],[73],[74],[75],[76] found that the scores of these two methods were positively correlated with laboratory findings and markers of disease severity (such as the length of hospital stay and the oxygen requirement), and both methods were useful in the prediction of critical illness, intensive care unit (ICU) admission, and mortality. Zhou et al. reported that a total CT severity score >15 (25-point scale) was an independent risk factor for poor prognosis in patients with COVID-19. Temporal changes in chest CT features and severity scores have been closely associated with COVID-19 mortality.

According to Xiong et al.,[78] a lesion diameter <1 cm was assigned 1 point, 1–3 cm was 2 points, >3 cm and <50% of the lobe area was 3 points, and the involvement of abnormalities ≥50% of the lobe area was 4 points, with a final score of 0–20. Shen et al.[79] and Liu et al.[80] defined lesion involvement in each lobe <1/3, 1/3–2/3, and >2/3 as 1–3 points, respectively, with a cumulative score of 0–15. Zhaoping et al.[81] distinguished the right middle lobe from the upper and lower lobes of both lungs. They assigned 1 point for a lesion extent of <1/2 of the right lung middle lobe, otherwise 2 points were assigned. The scores of the upper and lower lobes of both lungs were assigned, as in Shen et al.[79] and Liu et al.,[80] and the final score range was 0–14. However, compared with the 20-point scale and 25-point scale mentioned above, these three evaluation methods have rarely been used in relevant studies.

Lung segment used as the evaluation unit

Several studies[82],[83],[84] reported by Shanghai Ruijin Hospital (China) refer to the method used by Wong et al.[85] to evaluate the severity of SARS based on chest CT imaging. In this method, a lesion diameter <1 cm in each segment is 1 point, a lesion diameter of 1–3 cm is 2 points, a lesion diameter >3 cm and <50% of the lung segment area is 3 points, and involvement of abnormalities ≥50% of the lung segment area is 4 points. The combined score of the 18 lung segments gives a severity score ranging from 0 to 72 [Table 3], 72-point scale].
Table 3: Score definition of evaluation methods those use the lung segment as the evaluation unit

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In some studies, the whole lung was divided into 20 lung segments (the apicoposterior segment of the upper lobe and the anteromedial basal segment of the lower lobe of the left lung were each regarded as two segments), and the extent of lesion involvement in each lung segment was scored. The cumulative score of the 20 lung segments was used as an index to evaluate NCP severity. Several studies[86],[87],[88],[89],[90],[91],[92] have defined noninvolvement as 0, <50% involvement as 1, and >50% of lung segment involvement as 2, for a total score of 40 [Table 3], 40-point scale]. Palwa et al.[92] reported that the threshold for recognizing severe COVID-19 was 18.5 using this method, with 84.3% sensitivity and 92.5% specificity. Yang et al.[88] reported that a score of <19.5 could rule out severe and critical disease with a high negative predictive value of 96.3%. Several studies[93],[94],[95],[96],[97] referred to the method reported by Juan et al.[98] to evaluate the severity of influenza A (H1N1) virus-associated pneumonia based on chest CT imaging. They defined lesion involvement in any lung segment as 5% of the whole lung; a cumulative score of 0%–100% is obtained to evaluate the involvement of pulmonary lesions in NCP patients. Some studies reported in Chongqing[99],[100],[101] used the pulmonary inflammation index (PII) to evaluate NCP severity based on CT imaging. This index was developed by the Chongqing Radiologist Association of China. The PII consists of a lesion distribution score and a lesion extent score. In the lesion distribution score, the presence of a lesion in a lung segment is 1 point, and the absence of lesions is 0 points. In the lesion extent score, lesions that cover >50% of the lung segment area are 1 point, otherwise 0 points are assigned. A pneumonia index of 0%–100% is obtained using the formula PII = (lesion distribution score + lesion extent score)/40 × 100%.

Most of the studies that used the lung segment as the evaluation unit were conducted in China, primarily in Shanghai and Chongqing City. Therefore, this research method has not been widely recognised.

Intrapulmonary zone used as the evaluation unit

In studies using the intrapulmonary zone as the evaluation unit, the two lungs arefirst divided into multiple zones according to the coronal and/or sagittal markers on the chest CT imaging. The involvement of abnormalities in each zone is then scored, finally obtaining an evaluation index. The zone divisions and index ranges varied among studies. Parry et al.[102] and Tabatabaei et al.[103] divided each lung into three zones, namely the upper, middle, and lower zones on the chest coronal CT imaging, using the carina of trachea and the inferior pulmonary vein as the boundary. The percentage of COVID-19 involvement in each zone was then estimated, and the average percentage of the zones in both lungs was used as the index to evaluate the extent of lesion involvement. Other studies[104],[105],[106],[107],[108],[109],[110],[111],[112],[113],[114],[115],[116] divided each lung into six zones as mentioned above and referred to the previously reported SARS severity evaluation method based on chest CT imaging,[117] with <26%, 26%–50%, 51%–75%, and >75% lesion involvement in each zone assigned 1–4 points, respectively. After scoring the six regions, a severity score ranging from 0 to 24 is generated [Table 4], 24-point scale]. Hajiahmadi et al.[114] reported that this method predicted ICU admission and mortality in patients with COVID-19 pneumonia. Abbasi et al.[116] found that 10 was the optimal CT severity score threshold for identifying deceased patients, with 84% (confidence interval, 71.7%–92.4%) sensitivity and 66% (59.1%–72.5%) specificity. On the basis of the above-mentioned dividing method, Zhou et al.[118],[119] further divided the six zones into 12 zones using the vertical line of the midpoint of the diaphragm on the sagittal imaging as a boundary. The scoring system was the 24-point scale mentioned above, and the cumulative score of the 12 zones ranged from 0 to 48.
Table 4: Score definition of evaluation methods those use the intrapulmonary region as the evaluation unit

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Locations on axial computed tomography imaging used as the evaluation unit

Peiqi et al.[120] and Zhang et al.[121] referred to the previously reported evaluation method of influenza A (H1N1) virus-associated pneumonia[68] based on chest CT imaging. They evaluated the involvement of abnormalities in four locations on axial CT imaging: the aortic arch, carina of trachea, inferior pulmonary vein, and supradiaphragmatic. Lesion involvement <5%, 5%–25%, 26%–50%, 51%–75%, and >75% of the area of each location was assigned 1–5 points, respectively, and the four location scores were summed to obtain a severity score ranging from 0 to 20.


  Evaluation Based on Abnormality Characteristics Top


In a study reported by Zhang et al.,[122] 5 points were assigned to patchy shadow or GGO in a single lung, 7 points were assigned to patchy shadow or GGO in both lungs, and an additional 2 points were added if the distribution of patchy shadow or GGO was diffuse. Consolidation or striped shadow in one lung was assigned 2 points, consolidation or striped shadow in both lungs was assigned 4 points, unilateral pleural effusion was assigned 2 points, bilateral pleural effusion was assigned 4 points, and enlargement of the mediastinal lymph node was assigned 1 point. The final score range was 0–18. Burian et al.[123] classified COVID-19 intrapulmonary manifestations into five grades. Grade 1 was defined as no lesions with typical NCP manifestations in either lung, grade 2 was defined as solitary GGO in one lung, grade 3 was defined as multiple GGOs in both lungs, grade 4 was defined as diffuse GGO with lung consolidation, and grade 5 was defined as the involvement of grade 4 lesions in more than 50% of the lung parenchyma. The severity evaluation methods mentioned above focus on the characteristics of the abnormalities, regardless of the extent of lesion involvement. However, these methods have been rarely adopted.


  Evaluation Based on Abnormality Extent and Characteristics Top


For COVID-19, qualitative evaluation systems can differentiate between severe and less severe cases, but they are typically unable to differentiate between severe and critical cases.[124] The combined use of qualitative and quantitative evaluation systems was shown to distinguish cases at different clinical stages. Such information might help to facilitate the rapid identification and management of critical cases. A comprehensive assessment of lesion extent and lesion characteristics has been applied in several studies of COVID-19. These evaluation methods primarily replace, optimize, or supplement the methods that evaluate the extent of abnormalities.

Lesion extent and characteristics evaluated separately

Wu et al.[125] used both lesion extent and density scores to evaluate NCP severity. The extent scoring system was similar to the 20-point scale mentioned above. In their density scoring system, an absence of abnormal findings was assigned 0 points, and pure GGO was assigned 1 point. GGO combined with consolidation and/or other abnormalities, such as reticulation and interlobular septal thickening, was assigned 2 or 3 points –– if the range of consolidation and/or other abnormalities was <50% of lesions, 2 points were assigned, otherwise 3 points were assigned. Consolidations and/or other abnormalities without GGO were assigned 4 points. In this way, the lesion extent and the lesion characteristics were evaluated separately.

Evaluation based on the extent of abnormalities with different characteristics

Jiang et al.[126] used the 20-point scale to evaluate the extent of abnormalities in the lung and to score patchy consolidation in the lung, providing two evaluation indexes, each with a score range of 0–20. On the basis of the method by Jiang et al., Lyu et al.[124] further used the 20-point scale to score the lesions presenting as crazy paving, thus providing three evaluation indexes, each ranging from 0 to 20. Shang et al.[127] used the 25-point scale to score lesions presenting with consolidation, crazy paving, and fibrosis, providing four evaluation indexes, each ranging from 0 to 25. Zhang et al.[128] defined lesion extents of < 25%, 26%–50%, 51%–75%, and 76%–100% of the whole lung as slight, mild, moderate, and severe NCP, respectively. They scored consolidation using the same method. Fangjun et al.[129] scored only GGO and consolidation lesions in the lung. They assigned 1–4 points to a GGO extent of <25%, 25%–49%, 50%–74%, and ≥75% of the whole lung and 1–3 points to a consolidation extent of <1/3, 1/3–2/3, and >2/3 of the whole lung, respectively. If there were no lesions, the score was 0; therefore, the score range of this method was 0–7 [Table 5].
Table 5: Protocols of range evaluation of abnormalities with different characteristics

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Evaluation combining extent and weight of abnormality characteristics

On the basis of the 24-point scale, Liu et al.[130] and Yuan et al.[131] defined the weight of abnormalities with normal density (density of lung), ground-glass density, and consolidation density as 1–3 points, respectively. The severity in each zone was estimated as the product of the extent score and its weight; the severity ranged from 0 to 72. Salaffi et al.[132] reported a 3-level chest severity score. They defined the characteristic weight of abnormalities as follows: 1 for normal lung parenchyma; 2 for at least 75% GGO/crazy paving; 3 for a combination of GGO, crazy paving, and consolidation, provided that each showed <75% involvement; and 4 for at least 75% consolidation. The extent of abnormality was defined using a 24-point scale; the maximal score in each zone was 16, giving a total score of 0–96 [Table 6]. The method used by Li et al.[133] was similar to that of Salaffi et al. except that they used a 20-point scale rather than a 24-point scale for the lesion extent evaluation; thus, the final score range was 0–60. Zhefeng et al.[134] computed a density score for six zones using a 24-point scale. The density score consisted of the average density of abnormalities (ADA) and the average density of lung tissue in the disease-free area (ADL). The density score of each zone was calculated as (ADA − ADL)/100. The comprehensive score of each zone was calculated as the extent score × density score. The final cumulative score of six zones was used as an index for evaluating NCP severity based on CT imaging. The severity evaluation method used by Yang et al.[135] included two factors: lesion characteristics and lesion size. In this study, the maximum diameter of lesions in axial CT images was used as a proxy for the lesion size. The lesions were divided into simple GGO, GGO + consolidation, GGO + thickening of interlobular septa, and simple consolidation according to lesion density, weighted as 1–4, respectively. The cumulative product of lesion size × lesion density weight for each lesion was used as the parameter to evaluate NCP severity based on CT imaging. Owing to uncertainty in the lesion size, this method has no defined scoring range [Table 6].
Table 6: Protocols of range evaluation combined with characteristics weight of abnormalities

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Abnormality characteristics integrated with the extent evaluation method

Huang et al.[136] adopted a 25-point scale for evaluating NCP severity based on CT imaging. In addition, they gave an additional point for the presence of crazy paving in the lung lobes and an additional 2 points for the presence of consolidation in the lung lobes (regardless of whether there was crazy paving in the lung lobes). Thus, each lobe was scored on a scale of 0–7 and the cumulative score was 0–35. Zhou et al.[137] and Meiling et al.[138] combined a consolidation score with the PII. They assigned 1 point if there was consolidation in the lung segment, otherwise 0 points were assigned. Therefore, the PII calculation was adjusted as lesion distribution score + lesion extent score + consolidation score/40 × 100%. In this method, when the summed score exceeded 40, the result was taken as 40; therefore, the final scoring range was still 0%–100%.


  Comparison of Coronavirus Disease-2019 Severity Scoring Systems Top


Several recent studies have compared the repeatability, accuracy, and time required for the various severity evaluation methods. Holguín-Andrade et al.[139] reported that the 24-point scale method showed the best interobserver agreement, with a coefficient of 0.964 (P = 0.001) when compared with the 20-, 25-, 40-, and 72-point scales. Another study[140] found that 40-, 25-, 20-, and 96-point scale methods all had excellent or very good diagnostic accuracy when the cutoff values for detecting severe cases were >22, >17, >12, and >26, respectively. The authors also found that the 25-point scale had the highest specificity (95.2%) for discriminating severe cases and the shortest time required. In a similar study,[141] the 20- and 25-point scale methods showed less time was required than for the 40-point scale method, but the correlation between the scoring system and QDAR (the ratio of lung involvement to lung parenchyma) was highest for the 40-point scale method. Mruk et al.[142] reported that the 40-point scale method had the strongest positive correlation with the patient clinical condition as expressed by the Modified Early Warning Score.


  Summary and Perspectives Top


There are various methods for evaluating NCP severity based on CT imaging, but there is no unified evaluation standard. Among the various evaluation methods, lesion extent evaluation is the most widely used. Owing to clear boundaries and simple definitions, methods that use the lung lobe as the evaluation unit have been adopted by the majority of studies. However, this type of method does not consider the characteristics of abnormalities in the NCP severity evaluation, and methods based on both the extent and the characteristics of abnormalities have been increasingly adopted. With the application of artificial intelligence and computer-aided diagnosis of COVID-19 based on CT imaging,[79],[115] it is possible that the lesion volume measurement will replace the traditional lesion extent estimation.[38],[62],[69],[79] Yin et al.[62] reported that the classification accuracy of quantitative CT parameters was significantly better than that of semiquantitative visual scoring in terms of evaluating COVID-19 severity, and the clinical classification of COVID-19 severity was significantly correlated with the quantitative volume-dependent parameters. Furthermore, the accuracy of the quantitative CT parameters was significantly better than that of the semiquantitative visual score. Therefore, some scholars[143] have proposed that quantitative diagnosis of COVID-19 will be primarily used in the future. With the development and deepening of the research on the risk factors for severe NCP, it is expected that a unified, quantitative severity evaluation system with multiple severity-related risk factors will be established.

Acknowledgments

This study was supported by grants from the Science and Technology Research Project of Inner Mongolia Autonomous Region (NJZZ21048) and the Scientific Research Foundation of Baotou Medical College (BYJJ-XG 202005). We thank Katherine Thieltges from Liwen Bianji (Edanz) (www. liwenbianji. cn/) for editing the English text of a draft of this manuscript.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]



 

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Abstract
Introduction
Evaluation Based...
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