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Pneumonic-type invasive mucinous adenocarcinoma and infectious pneumonia: clinical and CT imaging analysis from multiple centers

BMC Pulmonary Medicine volume 22, Article number: 460 (2022) Cite this article

Abstract

Background

Pneumonic-type invasive mucinous adenocarcinoma (IMA) was often misdiagnosed as pneumonia in clinic. However, the treatment of these two diseases is different.

Methods

A total of 341 patients with pneumonic-type IMA (n = 134) and infectious pneumonia (n = 207) were retrospectively enrolled from January 2017 to January 2022 at six centers. Detailed clinical and CT imaging characteristics of two groups were analyzed and the characteristics between the two groups were compared by χ2 test and Student’s t test. The multivariate logistic regression analysis was performed to identify independent predictors. Receiver operating characteristic curve analysis was used to determine the diagnostic performance of different variables.

Results

A significant difference was found in age, fever, no symptoms, elevation of white blood cell count and C-reactive protein level, family history of cancer, air bronchogram, interlobular fissure bulging, satellite lesions, and CT attenuation value (all p < 0.05). Age (odds ratio [OR], 1.034; 95% confidence interval [CI] 1.008–1.061, p = 0.010), elevation of C-reactive protein level (OR, 0.439; 95% CI 0.217–0.890, p = 0.022), fever (OR, 0.104; 95% CI 0.048–0.229, p < 0.001), family history of cancer (OR, 5.123; 95% CI 1.981–13.245, p = 0.001), air space (OR, 6.587; 95% CI 3.319–13.073, p < 0.001), and CT attenuation value (OR, 0.840; 95% CI 0.796–0.886, p < 0.001) were the independent predictors of pneumonic-type IMA, with an area under the curve of 0.893 (95% CI 0.856–0.924, p < 0.001).

Conclusion

Detailed evaluation of clinical and CT imaging characteristics is useful for differentiating pneumonic-type IMA and infectious pneumonia.

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Introduction

Lung cancer is currently the leading cause of cancer incidence and mortality worldwide, and lung adenocarcinoma is the main subtype of lung cancer [1, 2]. Compared with other lung adenocarcinoma subtypes, invasive mucinous adenocarcinoma (IMA), a rare and distinct subtype of lung adenocarcinoma, has significantly worse prognosis and is more prone to lung metastasis [3, 4]. IMA characterized by consolidations opacities on CT imaging mimicking pneumonia was recognized as pneumonic-type IMA [5]. In view of the overlapping clinical symptoms and radiological features, this type of pulmonary IMA is often misdiagnosed as infectious pneumonia, resulting in a delay in definitive management and an increased risk of death in the affected patients [6].

Several studies have assessed the clinical, imaging, and pathological features of pneumonic-type lung IMA [5, 7], however, they didn’t investigate to distinguish it from infectious pneumonia. Jung et al. [8] and Kim et al. [9] previously distinguished between mucinous bronchioloalveolar carcinoma, redefined as IMA nowadays, and infectious pneumonia by CT characteristics. Given the low incidence of IMA, accounting for 2% to 5% of all adenocarcinomas [10], most studies about pneumonic-type IMA were with small samples and without sufficient clinical information. Therefore, comprehensive clinical and imaging studies with larger samples to differentiate pneumonic-type IMA and infectious pneumonia are imminent.

The purpose of this study was to evaluate the clinical and CT imaging features between pneumonic-type IMA and infectious pneumonia.

Materials and methods

Patients

Institutional review board approval was obtained, and patient informed consent was waived due to the retrospective nature of this study.

We searched the radiology reports using the terms “lung adenocarcinoma”, “mucinous adenocarcinoma” “infectious lesions” and “pneumonia” on non-enhanced lung CT scans from January 2017 to January 2022 at six institutions (Affiliated Shandong Provincial Hospital of Shandong First Medical University; Shandong Province Yuhuangding Hospital; Shandong Tumor Hospital; Affiliated Hospital of Jining Medical University; Affiliated Hospital of Qingdao University; Qilu Hospital of Shandong University). Inclusion criteria for pneumonic-type IMA were: (1) pathologically proven IMA, (2) no radiotherapy or chemotherapy, and (3) presenting as consolidation on CT. Inclusion criteria for infectious pneumonia were: (1) pathologically proven pneumonia, or (2) clinically proven pneumonia and at least two CT examinations, the lesions completely disappearing on follow-up CT examination after anti-inflammatory treatment, (3) presenting as consolidation on CT, and (4) no treatment before the first CT examination. Common exclusion criteria for both diseases were as follows: (1) poor images, and (2) incomplete clinical data. If a patient had multiple lesions, then a single largest lesion was analyzed each patient. And if a patient had at least two CT examinations, the first CT examination was used for analysis. Two radiologists (S.Z. and X.X.Y., with 7 and 10 years of experience in lung radiology, respectively) made consensus decisions on correlation. To avoid recall bias, these two radiologists were not involved in CT image analysis evaluation. Flowchart for selecting the study population is shown in Fig. 1.

Fig. 1
figure 1

Patient flow chart and patient selection

Full size image

Demographic and clinical information including age, sex, smoking, cough, sputum, fever, no symptoms, laboratory results (elevation of white blood cell count [> 10 × 109/L] and C-reactive protein level [> 10 mg/L]), family history of cancer was collected from medical record.

CT protocols

All non-enhanced CT images were obtained on the multidetector CT scanners (Ingenuity CT, Philips; Brilliance iCT, Philips; Somatom Force, Siemens Healthcare; Somatom Definition Flash, Siemens Healthcare; Somatom Definition AS, Siemens; Optima CT660, GE Healthcare; Discovery 750, GE Healthcare). The chest CT scanning parameters were the following: tube voltage of 120 kVp, pitch of 0.8–1.0, 250–400 mA (using automatic tube current modulation technique) tube current, a matrix of 512 × 512, reconstructed slice thickness of 1 mm, reconstructed slice interval of 1 mm, rotation time of 500–600 ms. Non-enhanced CT scanning was performed with coverage from the thoracic inlet to the lung base in the supine position.

Image analysis

All images were independently evaluated by two radiologists (S.L. and X.M.W.) with more than 10-year’ experience in chest imaging, both of whom were blinded to patient clinical information with any disagreement in assessment resolved by consensus.

The pneumonia type IMA is defined as consolidation along the lung lobe or segment without definite shape on CT [5]. The assessments of CT features of lesions including location (unilateral or bilateral), margin (well-defined or ill-defined), air bronchogram (absence, regular, or irregular), interlobular fissure bulging (absent or present), air space (absent or present), satellite lesions (absent or present), pleural effusion (absent or present), lymphadenopathy (absent or present), and CT attenuation value were obtained by using post-processing workstation (Syngo.via, Siemens Force, Germany). Among them, air bronchogram was defined as air-filled bronchi within lesions, and irregular air bronchogram appeared as dilatation, stiffness, or narrowing of bronchi. Lymphadenopathy was defined as hilar or mediastinal lymph nodes > 1 cm in short axis diameter. On non-enhanced CT images, three circular regions of interests (ROIs) were selected at the maximum cross-sectional area of the lesions, avoiding vessels, bronchi, and air space. Then, we measured the non-enhanced CT values of the ROIs and calculated the mean value. All CT attenuation measurements are reported in HU. Inter-observer agreement in evaluation of CT image was calculated using the intraclass correlation coefficient and kappa statistics.

Statistical analysis

Statistical analysis was performed using SPSS (version 22.0, IBM) and R statistical software (version 3.3.3, https://www.r-project.org). Continuous variables were described as mean ± standard deviation, whereas categorical variables were expressed as percentage. Clinical information and CT image characteristics were compared between pneumonic-type IMA and infectious pneumonia by using Student’s t test and χ2 test. Moreover, multivariate logistic regression analysis with generalized estimating equation correction was performed to calculate odds ratio (OR) and the corresponding 95% confidence interval (CI) of the independent predictors. Receiver operating characteristic (ROC) curve analysis was performed to analyze statistically significant variables in differentiating pneumonic-type IMA and infectious pneumonia. The diagnostic performance was assessed by the area under the curve (AUC), sensitivity, specificity, and accuracy. Differences in the AUC values were estimated using the Delong test. A p < 0.05 was considered statistically significant. The logistic regression prediction formula was defined as: P(z) = 1/(1 + e−z), z = θX + b, where X is the characteristics variable, θ is the weight variable, and b is the intercept.

Results

Study population

Five hundred and twenty patients with poor images were excluded, and seven hundred and twenty-one patients without complete clinical data were excluded. A total of 341 patients (mean age ± standard deviation, 66 ± 42 years; 12 men) with pneumonic-type IMA (n = 134) and infectious pneumonia (n = 207) from six institutions were enrolled in this study. In the pathological proven infectious pneumonia (n = 76) and pneumonia-type IMA (n = 134), 42 patients with infectious pneumonia and 107 patients with pneumonia-type IMA were determined by surgery, and the remainders were determined by biopsy. The clinical data are summarized in Table 1.

Table 1 The clinical characteristics between pneumonic-type IMA and infectious pneumonia
Full size table

Comparison of clinical data between pneumonic-type IMA and infectious pneumonia

As shown in Table 1, compared with patients with infectious pneumonia, those with pneumonic-type IMA tended to be older (63.8 ± 10.2 years vs. 59.9 ± 15.0 years; p < 0.001). The patients with pneumonic-type IMA showed a higher prevalence of no symptoms (17.9% vs. 8.7%, p = 0.011) and family history of cancer (17.9% vs. 9.7%, p = 0.026) than those with infectious pneumonia. Fever (55.1% vs. 14.2%, p < 0.001), elevation of white blood cell count (34.8% vs. 20.1%, p = 0.004), and elevation of C-reactive protein level (69.1% vs. 41.8%, p < 0.001) were more commonly observed in patients with infectious pneumonia than those with pneumonic-type IMA. No significant difference was founded in other clinical information between two groups (p > 0.05).

Comparison of CT imaging features between pneumonic-type IMA and infectious pneumonia

The detailed CT characteristics of two groups are presented in Table 2. Irregular Air bronchogram (50.7% vs. 37.7%, p = 0.016), interlobular fissure bulging (18.7% vs. 9.7%, p = 0.017), air space (65.7% vs. 30.0%, p < 0.001), and satellite lesions (19.4% vs. 11.6%, p = 0.046) were frequently present in pneumonic-type IMA than infectious pneumonia (Fig. 2). The pneumonic-type IMA had lower CT attenuation value (25.9 ± 7.1 HU vs. 32.3 ± 5.1 HU, p < 0.001) than infectious pneumonia. However, no significant differences were observed in other CT features between two groups (p > 0.05).

Table 2 Comparison of CT imaging features between pneumonic-type IMA and infectious pneumonia
Full size table
Fig. 2
figure 2

Representative images of CT imaging characteristics. Non-enhanced CT images (a, b) of lung window from a 69-year-old-male patient indicate the consolidation with irregular air bronchogram (red arrow), air space (white arrowhead), and interlobular fissure bulging (white arrow) in the left upper lobe. Pathology (c) confirmed invasive mucinous adenocarcinoma (hematoxylin and eosin staining, × 200). Non-enhanced CT images (d, e) of lung window from a 62-year-old-male patient indicate the consolidation with regular air bronchogram (red arrow) and no interlobular fissure bulging (white arrow) in the right middle lobe. Pathology (f) confirmed infectious pneumonia (hematoxylin and eosin staining, × 200)

Full size image

Multivariate logistic regression analysis

By multivariate logistic regression analysis, age (OR, 1.034; 95% CI 1.008–1.061, p = 0.010), elevation of C-reactive protein level (OR, 0.439; 95% CI 0.217–0.890, p = 0.022), fever (OR, 0.104; 95% CI 0.048–0.229, p < 0.001), family history of cancer (OR, 5.123; 95% CI 1.981–13.245, p = 0.001), air space (OR, 6.587; 95% CI 3.319–13.073, p < 0.001), CT attenuation value (OR, 0.840; 95% CI 0.796–0.886, p < 0.001) were the independent predictors of pneumonic-type IMA (Fig. 3).

Fig. 3
figure 3

ROC analysis in differentiating between pneumonic-type invasive mucinous adenocarcinoma and infectious pneumonia. Model 1: age, elevation of C-reactive protein level, fever and family history of cancer; Model 2: air space; Model 3: CT attenuation value; Model 4: model 2 + model 3; Model 5: model 1 + model 4

Full size image

Assessment of diagnostic performance of models

For differentiating between pneumonic-type IMA and infectious pneumonia using ROC analysis, we analyzed the combined clinical variables of age, elevation of C-reactive protein level, fever and family history of cancer (model 1), air space (model 2), CT attenuation value (model 3), combination of air space and CT attenuation value (model 4), and combination of clinical variables of age, elevation of C-reactive protein level, fever, family history of cancer, air space and CT attenuation value (model 5). The diagnostic performances of different models and their corresponding AUCs are shown in Table 3, and the ROC curves for different models are shown in Fig. 4. For model 3, the best cut-off of CT attenuation value was 27.0 HU. Model 5 had better diagnostic performance with an AUC of 0.893 (95% CI 0.856–0.924) and an accuracy of 84.16% than the other 4 models (all p < 0.05). The predicted probability formula of model 5 was as follows: P(z) = 1/(1 + e−z), z = 0.033 × age—0.686 × elevation of C-reactive protein level—1.995 × fever + 0.797 × family history of cancer + 1.459 × air space—0.212 × CT attenuation value. The differences in AUC values among all models are demonstrated in Table 4.

Table 3 The diagnostic performances of different models in differentiating pneumonic-type IMA and infectious pneumonia
Full size table
Fig. 4
figure 4

The independent predictors of pneumonic-type invasive mucinous adenocarcinoma

Full size image
Table 4 Comparison of the AUC values between different models in differentiating pneumonic-type IMA and infectious pneumonia
Full size table

Inter-observer agreement

The Cohens kappa coefficient of lesion margin, air bronchogram, interlobular fissure bulging, air space, satellite lesions, pleural effusion, and lymphadenopathy were 0.848 (95CI% 0.767–0.918), 0.921 (95CI% 0.880–0.958), 0.951 (95CI% 0.897–0.989), 0.947 (95CI% 0.911–0.977), 0.966 (95CI% 0.919–0.999), 0.970 (95CI% 0.941–0.994), 0.953 (95CI% 0.918–0.986), respectively, and the intraclass correlation coefficient of CT attenuation value was 0.937 (95CI% 0.923–0.949) for inter-observer agreement.

Discussion

The treatment of pneumonic-type IMA and infectious pneumonia is totally different [5, 11]. Therefore, it is necessary to distinguish between pneumonic-type IMA and infectious pneumonia. In addition, clinical and radiologic data are considered as valuable tools to differentiate them [7, 12]. In our study we compared the clinical and CT imaging characteristics between the pneumonic-type IMA and infectious pneumonia groups and presented several significant features that can assist to differentiate these lesions.

In view of the overlapping clinical symptoms such as cough and sputum, this pneumonic-type IMA is often misdiagnosed as infectious pneumonia, resulting in a delay in diagnosis and treatment [6]. Consistent with Zong et al. [13], we found that no significant difference was observed in cough and sputum between pneumonic-type IMA and infectious pneumonia (p > 0.05). In line with previous studies [14], our study indicated that fever and laboratory results (elevation of white blood cell count and C-reactive protein level) were more commonly associated with infectious pneumonia. In addition, our findings suggested that pneumonic-type IMA was more likely to occur in older people and in families with a history of tumors, which was similar to the results in several studies [15].

Previous studies have assessed the CT imaging features of pneumonic-type lung IMA and proposed the several useful imaging characteristics in identifying the pneumonic-type lung IMA [5, 16]. Consistent with several studies [9, 16], our study confirmed irregular air bronchogram as a key feature in differentiating pneumonic-type IMA from infectious pneumonia. The dilatation, stiffness, or narrowing of bronchi in IMA may be as a result of tumor invasion [17]. However, Jung et al. [8] found that air bronchogram was not helpful in differentiating two groups. We presume that sample size may account for this discrepancy. Our results also indicated that interlobular fissure bulging was more frequently detected in pneumonic-type IMA, which conforms to the findings of several investigators [16]. The interlobular fissure bulging may be caused by increased lung parenchymal volume as a result of mucus secretion by IMA tumor cells [18]. Contrary to the findings of Jung et al. [8], we found the air space was helpful in distinguish two lesions. This is because tumor cells are more likely to invade the bronchus to form a one-way back valve, leading to cavity formation [19]. In our study, we reported that the satellite lesions were more common in pneumonic-type IMA. Not only this, satellite lesions in infectious pneumonia showed frequently ill-defined fibrotic lesions on CT. In addition, we showed that pneumonic-type IMA had lower CT attenuation value than infectious pneumonia, which is consistent with several studies [8, 9]. The lower CT attenuation value was primarily the result of mucus secretion by the IMA tumor.

In this study, we developed the clinical model (model 1) with independent clinical predictors of age, elevation of C-reactive protein level, fever and family history of cancer, with an AUC of 0.786 and an accuracy of 69.79%. And we built the CT imaging model (model 4) with two independent imaging predictors of air space and CT attenuation value, with an AUC of 0.817 and an accuracy of 77.13%. Both models had good diagnostic efficacy and no significant difference in the AUC values between two models (p > 0.05). In addition, we developed the combined model (model 5) by incorporating all independent clinical and radiologic predictors, with an AUC of 0.893 and an accuracy of 84.16%. And the AUC value of the combined model was significantly higher than that of the clinical factor model (p < 0.001) and CT imaging model (p < 0.001). Therefore, we demonstrated that the evaluation of clinical and CT imaging features can assist in differentiating between pneumonic-type IMA and infectious pneumonia.

Given the low incidence of IMA, most studies about pneumonic-type IMA were with small samples and without sufficient clinical information [8, 9, 17]. Therefore, we collected detailed clinical and radiologic data from 6 situations for research. Beck et al. [20] proposed that IMA can show spontaneous regression of airspace opacities on CT without anticancer drugs and explained that it was due to mucus flow or combined inflammation. In our study, all lung IMA were pathologically confirmed. In addition, the evidence of pneumonia is either pathological confirmation due to misdiagnosis as lung cancer or disappearance of lesions on follow-up CT after anti-inflammatory therapy. And the complete disappearance of pneumonia lesions on follow-up CT after anti-inflammatory treatment suggested no cases with combined tumors.

There are several limitations in our study. First, this is a retrospective study and is subject to inherent limitations associated with retrospective analyses. Second, CT imaging was acquired from different scanners at six centers. However, their CT protocol was similar. In particular, tube voltage, a major parameter affecting CT values, was consistent. Third, given the difficulty of collecting cases, other pathological types of lung cancer with consolidation mimicking pneumonia on CT were not studied, future work should further investigate other lung cancers. Forth, we selected to evaluate the imaging features on non-enhanced CT rather than on contrast-enhanced CT. Although the contrast-enhanced CT imaging can provide more information to differentiate pneumonia-type IMA from pneumonia, plain scan has no contraindications to contrast administration in the clinical practice [21, 22]. And we have obtained relatively good diagnostic efficacy by image features on non-enhanced CT in this study.

In conclusion, our findings showed that pneumonic-type IMA and infectious pneumonia have different clinical and imaging characteristics. Detailed evaluation of clinical and CT imaging characteristics is useful for differentiating pneumonic-type IMA and infectious pneumonia.

Availability of data and materials

The data used and analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

AUC:

Area under the curve

CI:

Confidence interval

IMA:

Invasive mucinous adenocarcinoma

OR:

Odds ratio

ROC:

Receiver operating characteristic

ROI:

Regions of interest

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Acknowledgements

None.

Funding

The present study was supported by the National Natural Science Foundation of China (grant no. 81871354, 81571672), and Academic promotion programme of Shandong First Medical University (grant no. 2019QL023).

Author information

Author notes

  1. Shuai Zhang and Xinxin Yu contributed equally to this work

Authors and Affiliations

  1. School of Medicine, Shandong First Medical University, No. 6699, Qingdao Road, Jinan, 250024, Shandong, China

    Shuai Zhang

  2. Shandong Provincial Hospital, Shandong University, No. 324, Jingwu Road, Jinan, 250021, Shandong, China

    Xinxin Yu, Sha Li & Baosen Zhu

  3. Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No. 440, Jiyan Road, Jinan, 250117, Shandong, China

    Yong Huang

  4. Department of Radiology, The Affiliated Hospital of Qingdao University, No. 16, Jiangsu Road, Qingdao, 266000, Shandong, China

    Pei Nie

  5. Department of Radiology, Qilu Hospital, Shandong University, No. 107, Wenhua West Road, Jinan, 250012, Shandong, China

    Yan Deng

  6. Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, No. 20, Yuhuangding East Road, Yantai, 164000, Shandong, China

    Ning Mao

  7. Physical Examination Center, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No. 324, Jingwu Road, Jinan, 250021, Shandong, China

    Li Wang

  8. Department of Anesthesiology, Shandong Provincial Hospital, Shandong University, No. 324, Jingwu Road, Jinan, 250021, Shandong, China

    Bo Wang

  9. Department of Anesthesiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, No. 324, Jingwu Road, Jinan, 250021, Shandong, China

    Bo Wang

  10. Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Shandong University, No. 324, Jingwu Road, Jinan, 250021, Shandong, China

    Ximing Wang

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  1. Shuai Zhang
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Contributions

SZ and XXY involved in conceptualization, writing-original Draft, writing-review and editing; YH and PN involved in methodology, data Curation, and formal analysis; YD, NM, and SL involved in formal analysis and funding acquisition; BSZ involved in investigation, data curation and project administration; LW involved in conceptualization, and investigation, data curation and project administration; BW involved in methodology and software and validation; XMW involved in resources, visualization, supervision and funding acquisition. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Li Wang, Bo Wang or Ximing Wang.

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Ethics approval and consent to participate

Ethical approval was obtained from the Ethics Committee of Shandong Provincial Hospital Affiliated to Shandong First Medical University, China. In addition, patient informed consent was waived due to the retrospective nature of this study, which was under the permission of the Ethics Committee of Shandong Provincial Hospital Affiliated to Shandong First Medical University. All methods were carried out in accordance with relevant guidelines and regulations.

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Zhang, S., Yu, X., Huang, Y. et al. Pneumonic-type invasive mucinous adenocarcinoma and infectious pneumonia: clinical and CT imaging analysis from multiple centers. BMC Pulm Med 22, 460 (2022). https://doi.org/10.1186/s12890-022-02268-5

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  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12890-022-02268-5

Keywords

  • Invasive mucinous adenocarcinoma
  • Infectious pneumonia
  • Computed tomography
  • Lung disease

BMC Pulmonary Medicine

ISSN: 1471-2466

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