Primary solid lung cancerous nodules with different sizes: computed tomography features and their variations

doi:10.21203/rs.2.11173/v2

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Primary solid lung cancerous nodules with different sizes: computed tomography features and their variations

https://doi.org/10.21203/rs.2.11173/v2

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published 07 Nov, 2019

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Background: The computed tomography (CT) features of small solid lung cancers and their changing regularity as they grow have not been well studied. The purpose of this study was to analyze the CT features of solid lung cancerous nodules (SLCNs) with different sizes and their variations. Methods: Between February 2013 and April 2018, a consecutive cohort of 224 patients (225 nodules) with confirmed primary SLCNs was enrolled. The nodules were divided into four groups based on tumor diameter (A: diameter ≤ 1.0 cm, 35 lesions; B: 1.0 cm < diameter ≤ 1.5 cm, 60 lesions; C: 1.5 cm < diameter ≤ 2.0 cm, 63 lesions; and D: 2.0 cm < diameter ≤ 3.0 cm, 67 lesions). CT features of nodules within each group were summarized and compared. Results: Most nodules in different groups were located in upper lobes (groups A−D：50.8%−73.1%) and had a gap from the pleura (groups A−D：89.6%−100%). The main CT features of smaller (diameter ≤ 1 cm) and larger (diameter > 1 cm) nodules were significantly different. As nodule diameter increased, more lesions showed a regular shape, homogeneous density, clear but coarse tumor–lung interface, lobulation, spiculation, spinous protuberance, vascular convergence, pleural retraction, bronchial truncation, and beam-shaped opacity (p < 0.05 for all). The presence of halo sign in all groups was similar (17.5%−22.5%; p > 0.05). Conclusions: The CT features vary among SLCNs with different sizes. Understanding their changing regularity is helpful for identifying smaller suspicious malignant nodules and early determining their nature in follow-up.

Nuclear Medicine & Medical Imaging

Oncology

Cancer Biology

solid pulmonary nodule

lung cancer

computed tomography

Lung cancer is the most common tumor type and leading cause of cancer-related mortality worldwide [1, 2]. Pulmonary nodules as one of the main performances of lung cancer, they have always been the key point of research. Based on their density features in computed tomography (CT) images, cancerous nodules can be generally divided into solid and subsolid nodules, each with significantly different morphological and pathological features [3]. Several studies have been conducted on the differential diagnosis of benign and malignant subsolid nodules [4-8] and solid ones [9-13]. Compared with subsolid lung cancerous nodules, solid ones have a worse prognosis because of their rapid growth [14-16] and earlier development of metastases [16-19]. Therefore, early identification of malignant solid nodules, particularly smaller ones, based on CT features, is of great value for their prognosis.

Among various CT features, spiculation, lobulation, vascular convergence, and pleural retraction have been associated with malignancy in lung cancer [6, 20-25]; therefore, they are helpful in differentiating benign from malignant nodules. However, these features are usually absent from smaller nodules, making their diagnosis challenging. Management of smaller nodules has mainly relied on clinical follow-up, using changes in nodule size to determine benignity or malignancy [26-28]. However, there is no systematic report on changes other than size, including shape, density, margins, interface, and internal characteristics; their clinical significance also remains unclear. Therefore, further investigating CT features associated with the changing regularity of solid lung cancerous nodules (SLCNs) with different sizes has a potential to greatly improve early detection of malignant nodules.

To date, no study has reported imaging features associated with the development of primary SLCNs. Therefore, the purpose of this study is to investigate and summarize CT manifestations and their differences based on the nodules size and to provide a reference for early and accurate identification of potentially malignant small nodules.

Patients

The present study enrolled patients with pathologically confirmed peripheral lung cancer between February 2013 and April 2018. All patients underwent chest CT examination before surgery. Inclusion criteria was met by patients with (1) lesions comprising nodules with ≤ 3 cm diameter; (2) chest CT scan and surgery interval of one month, and (3) lesions not treated with antitumor therapy before CT examination. Patients were excluded if their CT images had poor quality (5 cases) or lesions were metastatic lung cancers (14 cases). A total of 224 patients (225 lesions) were included in the study.

CT examinations

All patients were examined with a 64-slice spiral CT scanner (SOMATOM Definition Flash, Siemens, Germany) with the following settings: tube voltage, 140kVp; tube current calculated according to individuals’ weight, height, and body mass index; rotation time, 0.5 s; pitch, 1.0; collimation, 0.6 mm; slice thickness and interval for axial images, 5 mm and 5 mm; reorganization interval, 1 mm. Upon CT examination, patients were put in the supine position with both hands near the head. Image acquisition was performed from the level of the thoracic inlet to inferior to the costophrenic angle. Images were obtained with mediastinal window (width, 400 HU; level, 30 HU) and lung window (width, 1500 HU; level, −600 HU) settings.

Image analysis

All patients’ CT data were reviewed on a workstation (Advantage Workstation 4.6; GE Healthcare) by two senior chest radiologists who were blinded to the pathological results of lesions. Interpretation discrepancy, if any, was resolved by consensus.

The followings features were evaluated on CT images: lesion size (average of the maximal long-axis and perpendicular maximal short-axis dimension); distribution in different lobes (left superior and inferior lobes and right superior, middle, and inferior lobes); location (clinging to pleura or not); shape (regular: oval, round, and polygonal or irregular); internal features (calcification, air bronchogram, vacuole, cavity); density (homogenous or heterogeneous); margins (lobulation, spiculation, spinous protuberance); and tumor–lung interface (coarse, unclear, or smooth). In addition, peripheral lesion areas were also evaluated, including vascular convergence, pleural retraction, bronchial truncation, and beam-shaped opacity. Pleural effusions and lymph nodes in the hilum and mediastinum were further evaluated. Enlarged mediastinal and hilar lymph nodes were generally defined as diameter >1 cm in short axis on chest CT scans.

For investigating the differences in CT features of SLCNs with different sizes, especially for the smaller ones, nodules were divided into four groups according to tumor size: Group A: diameter ≤ 1.0 cm; Group B: 1.0 cm < diameter ≤ 1.5 cm; Group C: 1.5 cm < diameter ≤ 2.0 cm; and Group D: 2.0 cm < diameter ≤ 3.0 cm.

Statistical analysis

Clinical data and CT features of nodules were statistically analyzed for each group. Continuous variables were expressed as mean ± standard deviation, whereas categorical variables were expressed as absolute number and percentage. Independent sample t-tests were used to compare age among different groups. A chi-square test was used to compare differences in patients’ clinical and pathological data, distribution and location of nodules, and various CT features among groups. Tukey-Kramer test was used for multiple comparisons between the groups. A p-value less than 0.05 was considered statistically significant. All statistical analyzes were performed through the statistical software SPSS (version 22.0 for Windows, SPSS Inc., Chicago, Illinois, USA).

Patient Characteristics

Among the 224 patients, 129 (57.6%) were male and 95 (42.4%) were female. Patients were aged 38–83 years, with an average age of 61.7 ± 9.5 years. A total of 127 (56.7%) cases had cough, expectoration, hemoptysis, chest pain, or chest tightness. The number of SLCNs in groups A, B, C, and D was 35, 60, 63, and 67, respectively. Table 1 summarizes clinical and pathological data of patients included in each group. No significant differences were found in gender, age, clinical symptoms, smoking history, and histopathological types of lung cancer among the four groups (p > 0.05).

Table 1. Patients’ clinical and pathological data

	Group A (n=35)	Group B (n=60)	Group C (n=63)	Group D (n=67)	*p-value*
Age (years)	59.3 ± 9.2	63.0 ±10.6	60.9 ± 8.3	64.0 ± 9.0	0.841
Male	18 (51.4)	35 (58.3)	36 (57.1)	41 (61.2)	0.821
Smokers	12 (34.3)	20 (33.3)	29 (46.0)	34 (50.8)	0.157
Clinical symptoms	16 (45.7)	32 (53.3)	42 (66.7)	37 (55.2)	0.204
Pathological types
Adenocarcinoma	32 (91.4)	55 (91.7)	51 (81.0)	56 (83.6)	0.245
Squamous cell carcinoma	1 (2.9)	5 (14.3)	10 (15.9)	6 (9.0)	0.191
Others	2 (5.7)	0 (0)	2 (3.2)	5 (7.5)	0.174
The data are expressed as n (%).

Lesion distribution and location

Nodules distribution and location are summarized in Table 2. In the four groups, nodules were mainly distributed in the upper lobes (50.8%−73.1%) and most did not cling to pleura (89.6%−100%).

Table 2. Distribution and location of nodules

	Group A (n=35)	Group B (n=60)	Group C (n=63)	Group D (n=67)	*p-value*
Right lung	28 (80.0)	33 (55.0)	31 (49.2)	42 (62.7)	0.022
SL	15 (42.9)	20 (33.3)	16 (25.4)	29 (43.3)	0.137
ML	5 (14.3)	2 (3.3)	4 (6.4)	5 (7.5)	0.252
IL	8 (22.9)	11 (18.3)	11 (17.5)	8 (11.9)	0.540
Left lung	7 (20)	27 (45)	32 (50.8)	25 (37.4)	0.022
SL	6 (17.1)	17 (28.3)	16 (25.4)	20 (29.9)	0.550
IL	1 (2.9)	10 (16.7)	16 (25.4)	5 (7.5)	0.005
SLs of both lungs	21 (60.0)	37 (61.7)	32 (50.8)	49 (73.1)	0.074
ILs of both lungs	9 (25.8)	21 (35)	27 (42.9)	13 (19.4)	0.026
Relationship with pleura
Not clinging to pleura	35 (100.0)	58 (96.7)	58 (92.1)	60 (90)	0.114
Clinging to pleura	0 (-)	2 (3.33)	3 (4.76)	6 (8.96)	0.114
SL= Superior lobe, ML= Middle lobe, IL = Inferior lobe. The data are expressed as n (%).

CT characteristics of lesions and their surroundings

Nodule CT features are summarized in Table 3. As nodule diameter increased, more lesions had regular shapes, homogeneous density, clear but coarse tumor-lung interface, lobulation, spiculation, spinous protuberance, vascular convergence, pleural retraction, bronchial truncation, and beam-shaped opacity (p < 0.05 for each) (Figure 1-4). However, the significant differences in various CT features were mainly detected between nodules in group A (diameter ≤ 1cm) and those in groups B, C and D (diameter > 1cm). Additionally, presence of halo sign in groups A and B was

Table 3. CT features of nodules in different size

CT features	Group A (n=35)	Group B (n=60)	Group C (n=63)	Group D (n=67)	*p-value*	Sig.
Shape
Round	9 (25.7)	14 (23.3)	15 (23.8)	15 (22.4)	0.986	−
Oval	16 (45.7)	41 (68.3)	42 (66.7)	48 (71.6)	0.060	−
Polyonal	5 (14.3)	3 (5)	4 (6.3)	2 (3.0)	0.154	−
Irregular	5 (14.3)	2 (3.3)	2 (3.2)	2 (3.0)	0.049	A/BCD
Size (mm)	8.2±1.4	12.8±1.3	17.7±1.4	24.1±2.7	/
Heterogeneous density	18 (51.4)	15 (25)	8 (12.7)	3 (4.5)	0.000	A/BCD
Internal feature
Calcification	0 (-)	0 (-)	1 (1.6)	1 (1.5)	0.687	−
Vacuole	5 (14.3)	5 (14.3)	4 (6.4)	11 (16.4)	0.242	−
Air bronchogram	1 (2.9)	1 (1.7)	5 (7.9)	12 (17.9)	0.005	A/BCD
Cavity	0	1 (1.7)	7 (11.1)	4 (6.0)	0.051	−
Margin
Lobulation	10 (28.6)	22 (36.7)	36 (57.1)	47 (70.1)	0.000	AB/CD
Spiculation or spinous protuberance	7 (20)	27 (45)	36 (57.1)	47 (70.1)	0.000	A/BCD
Halo sign	7 (20)	15 (25)	11 (17.5)	12 (17.9)	0.712	−
Tumor-lung interface
Coarse	26 (74.3)	48 (80)	55 (87.3)	64 (95.5)	0.013	A/D
Unclear	6 (17.1)	7 (11.7)	3 (4.8)	1 (1.5)	0.016	A/D
Smooth	3 (8.6)	5 (14.3)	5 (7.9)	2 (3.0)	0.553	−
Bronchial truncation	0 (-)	8 (13.3)	10 (15.9)	18 (26.9)	0.005	A/BCD
Vascular convergence	6 (17.1)	32 (53.3)	43 (68.3)	50 (74.6)	0.000	A/BCD
Beam-shaped opacity	3 (8.6)	15 (25)	15 (23.8)	26 (38.8)	0.010	A/BCD
Pleural retraction	3 (8.6)	22 (36.7)	28 (44.4)	34 (50.8)	0.000	A/BCD
Obstructive pneumonia	0 (-)	1 (1.67)	4 (6.4)	5 (7.5)	/	/
The data are expressed as n (%). Heterogeneous density indicates the density of nodules in addition to calcification, vacuole, air bronchogram, and cavity. A/BCD indicates there is significant difference between group A and B but no significant difference among groups of B, C and D. AB/CD indicates there is significant difference between group B and C but no significant difference between group A and B or group C and D. A/D indicates there is significant difference only between group A and D.

CT characteristics of suspicious malignancy for group A nodules

Combining with lesion distribution, location, and morphological features, the main CT characteristics indicating suspicious malignancy for group A nodules were summarized in table 4.

Table 4. CT characteristics indicating suspicious malignancy for group A nodules

CT features	Numbers	Percentage (%)
SLs of both lungs^†	21	60.0
Not clinging to pleura^†	35	100.0
Irregular shape^*	5	14.3
Heterogeneous density^*	18	51.4
Lobulation^‡	10	28.6
Spiculation or spinous protuberance^‡	7	20
Coarse tumor-lung interface^†	26	74.3
Unclear tumor-lung interface^*	6	17.1
Halo sign^†	7	20
SL= Superior lobe; ^†indicates the common features for group A-D nodules; ^* indicates these features are relatively common in group A nodules. ^‡indicates these features are relatively rare in group A nodules.

Lymph nodes in the hilum and mediastinum and pleural effusion

As nodule size increased, the incidence of enlarged lymph nodes in the hilum or mediastinum also gradually increased (8.6%, 18.3%, 27.0%, and 46.3% for each group; p < 0.001). Incidence of pleural effusion was extremely low for four groups.

This study showed that the distribution of SLCNs in different size groups was similar. It was generally believed that the lung cancers were mainly distributed in the upper lobes [29-31]. Concerning nodule location, most nodules, particularly the smaller ones, were not connected with the adjacent pleura. It appeared that the space between the tumor and pleura will subsist until the nodules grow large enough to involve it [32]. It is possible that a SLCN is typically derived from the distal bronchus, and a distance exists between the lesion and pleura. These findings suggested that smaller nodules clinging to the pleura, which are usually detected on chest CT scan, were less likely to indicate lung cancer.

In this study, the smaller lesions (≤ 1cm) usually had different CT features with the bigger one (> 1cm). As nodule size increased, they acquired a more regular shape, and the margins and surrounding features also gradually increased. It may be because a nodule becomes more regular with an increase in size, and the limitation of the surrounding structure becomes more obvious. Lobulation, spiculation, pleural retraction, and vascular convergence are considered common signs of malignancy in lung cancer [6, 20-25]. However, for smaller nodules, traction and invasion of surrounding blood vessels and tissues, as well as tumor and peritumoral fibrosis were not obvious. As nodules increased, the invasiveness of the surrounding tissue also increased, and more signs were evident.

Siegelman et al. [33] reported that the incidence of coarse tumor–lung interface in lung cancer was significantly higher than that in benign lesions. In this study, tumor–lung interface in each group was mainly coarse. Additionally, the incidence of coarse interface increased with the increasing size of the nodule. This may be because tumor cells locally infiltrate the peripheral tissue, particularly the bigger nodules. However, the smaller the nodules, the higher the incidence of unclear interface, which may be related to the relatively sparse tumor cells in the peripheral areas of nodules. Therefore, for smaller solid nodules with unclear interface, the possibility of lung cancer cannot be completely excluded; follow-up is recommended to avoid an erroneous diagnosis.

The growth of solid lung cancer is a gradual process. The tumor cells gradually accumulate, and the lesion size continuously increases. Theoretically, tumor density will be more homogeneous on plain CT scan with an increase in the lesion size. In the present study, smaller nodules had a higher incidence of heterogeneous density, particularly those less than 1 cm in diameter. However, incidence of internal calcification, vacuole sign, or cavity was low in each group, like the previous reports [34, 35]. Therefore, small solid nodules with heterogeneous density can be selectively observed, and lung cancer should be highly suspected once their density increases and becomes homogeneous.

Beam-shaped opacity is a banded ground glass opacity, which is located at the side of the tumor close to the pleura in different directions. It is common in adenocarcinoma and highly significant in the diagnosis of lung cancer [36]. This sign may be related to the traction of the surrounding lung tissue. In this study, the incidence of beam-shaped opacity was higher in the group D, but it was significantly lower in the group A. This implicates that small nodules are usually not able to cause significant changes in surrounding structures.

Halo sign was a nonspecific sign around solid pulmonary nodules, and its border was usually clear for lung cancer [37]. In this study, a well-defined halo sign was mainly located on one side of the nodule, and its incidence was slightly higher in smaller lesions. Therefore, the smaller solid nodules without other features but halo sign should be suspicious for lung cancer.

Overall, regarding the smaller pulmonary nodules, follow-up looks like a good way to discriminate their nature based on CT feature changes. Recent study confirmed that quantitative image features (“radiomics”) could also discriminate benign from malignant pulmonary nodules [38]. Additionally, quantitative radiomic signatures showed the potential to reveal and predict the tumor growth speed, and could identify the indolent from aggressive lung cancer [39]. Thus, radiomics may provide a new way for evaluating and managing indeterminate pulmonary nodules in the future.

This study had several limitations. Evaluation of CT feature changing regularity for SLCNs was performed by comparing grouped nodules with different sizes rather than only following one group of lesions. Thus, results obtained here should be confirmed in clinical practice. Additionally, pathological types of SLCNs varied but showed no significant differences among different groups. Therefore, present results seem to represent a general, rather than a specific tumor type. It should be noted that some types within smaller samples may not conform to the general morphological development.

SLCNs morphological changes presented some degree of regularity in their growth process. With diameter increasing, more nodules had regular shapes, homogeneous density, clear but coarse tumor-lung interface, and margin or peripheral signs. Thus, larger nodules could be easily diagnosed due to presence of more features. However, for smaller nodules located in the upper lobe, not clinging to the pleura, showing irregular shape, heterogeneous density, unclear tumor–lung interface, or well-defined halo sign, malignancy should be suspected. Understanding the changing regularity of SLCNs is helpful for identifying smaller suspicious malignant nodules and early determining its nature in follow-up.

CT: computed tomography

SLCN: solid lung cancerous nodule

Acknowledgments

No.

Funding

This study was supported by the National Natural Science Foundation of China (81601545) and Chongqing Health and Family Planning Commission Foundation (2016MSXM018) of China. The funding was used to conduct all data analyses and cover publication fees. The funding bodies did not have any influence on the design of the study, collection, analysis, interpretation of data or in writing the manuscript.

Authors’ contributions

Z.-G. C. and Y. Z. contributed to the data analysis and manuscript writing. W.-J. L., Q. L. and Y.-N. Z. were involved in performing data collection. F.-J. L. was responsible for the study coordination. All authors have read and approved the manuscript, and ensure that this is the case.

Ethics Approval and Consent to Participate

The Research Ethics Committee of The First Affiliated Hospital of Chongqing Medical University (IRB No. 2019-062) approved this study. All the participants provided written informed consent.

Consent for Publication

Not applicable.

Availability of Data and Material

Please contact author for data requests.

Competing Interests

The authors have declared that no competing interest exists.

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17 Sep, 2019

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Primary solid lung cancerous nodules with different sizes: computed tomography features and their variations

Status:

Journal Publication

Version 2

Abstract

Figures

Background

Methods

Results

Discussion

Conclusions

Abbreviations

Declarations

References

Status:

Journal Publication

Version 2