Identifying invasive lung adenocarcinomas manifesting as part-solid nodules by measuring the size of multiple solid portions and maximum solid portions

Introduction

A part-solid nodule (PSN), defined as a subclass of pulmonary nodules, is radiologically characterized by the coexistence of ground-glass opacity and a solid component on lung window settings of computed tomography (CT) scans. In recent years, the implementation of lung cancer screening programs around the world has led to a high rate of PSN detection (1). Some studies have shown that PSNs with both ground-glass change and solid components often carry higher risks than solid nodules of comparable size (2), and about 63% of persistent PSNs [i.e., nodules that remain stable or increase in size over a follow-up period of 3 months or longer (3)] found incidentally on CT images are eventually diagnosed as adenocarcinomas or precursors (4). Thus, the early identification of malignant PSNs could advance lung cancer diagnosis and improve patient survival, which are popular issues in current clinical research.

Existing research suggests that solid portions in PSNs correspond well to pathologic invasive components (5,6). The Japanese Clinical Oncology Group used the consolidation/tumor ratio (CTR) on imaging as an important criterion for determining pathological invasiveness, and ultimately reported that the diagnosis of non-invasive adenocarcinoma (IAC) with a CTR ≤0.25 in lung nodules ≤2 cm had a specificity of 98.7% (7). However, it is not uncommon to encounter PSNs containing multifocal solid portions in the clinic, of which is difficult to go for a clear definition of the CTR. In such cases, an alternative approach to radiological assessment is to examine the multiplicity of the solid portions of the PSNs (i.e., the size of each solid portion). However, the approach employed in this process significantly increases the time it takes to obtain the measurements, and its predictive implications have not been evaluated (8). Consequently, further studies need to be conducted to examine the measurement methods and evaluation standards applied to such nodules.

This study retrospectively analyzed the CT images of different PSNs, and explored the correlation between solid portions and histological invasiveness based on different quantitative measurement methods, including the single largest solid portion, the solid proportion, and the sum of multiple solid portions, which have been rarely described in previous studies, to evaluate the differential implications of solid portions for IAC. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-2032/rc).

Methods

This retrospective study was approved by the Institutional Review Board of Zhengzhou University People’s Hospital (No. 201925), and the requirement of individual consent for this retrospective analysis was waived. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Study population

We retrospectively collected the medical data of patients with PSNs who underwent surgery at Zhengzhou University People’s Hospital from December 2018 to December 2022. Patients were included in the study if they met the following criteria: (I) had nodules that appeared as part-solid opacities with a maximum diameter <30 mm on the lung window; (II) had qualified chest CT images available that had been taken 1 month before surgery (slice thickness: ≤1.25 mm); and (III) had undergone nodule resection and had obtained a definitive pathological diagnosis. Patients were excluded from the study if they met any of the following exclusion criteria: (I) had missing image data or poor-quality image data; (II) had received anti-inflammatory treatments or anti-tumor treatments before CT examinations; and/or (III) had nodules that were pathologically confirmed to be derived from the extrapulmonary malignant tumor.

After reviewing the CT images of patients with pulmonary nodules, 281 PSNs were selected for inclusion in the study. However, 25 PSNs were later excluded due to an absence of qualified thin-section chest CT images taken within 1 month before surgery, or because the PSNs were diagnosed as benign after surgery. Further, the pulmonary nodules of 70 patients that were considered either pure ground-glass or solid were excluded after a careful review of the CT scans of the entire study population by two board-certified thoracic radiologist with 5 years of experience in CT imaging research. Thus, ultimately, 186 patients were included in the present study. The selection procedure of the patients is shown in Figure 1.

Figure 1 Flowchart for patient selection in this study. PSN, part-solid nodule; CT, computed tomography; AAH, atypical adenomatous hyperplasia; AIS, adenocarcinoma in situ; MIA, minimally invasive adenocarcinoma; IAC, invasive adenocarcinoma.

CT examinations

The chest CT scans were performed on a 64-slice spiral CT machine (Somatom Definition Flash, Siemens Healthineers, Forchheim, Germany) within 1 month before surgery. All patients were placed in a supine position with both arms raised, and asked to hold their breath after a deep inhalation for better exposure. The scan range ran from the lung tip to below the costophrenic angle. Patients who underwent enhanced CT required an additional contrast injection of iohexol via the elbow vein at an injection flow rate of 3.0 mL/s at a dose of 90–100 mL (1.5 mL/kg) with a scanning delay of 40 s. The following scan parameters were used: tube voltage: 110–120 kV; tube current: 100–500 mAs; scan layer thickness: 5 mm; and reconstruction layer thickness: 0.625–1.25 mm.

Data collection

The CT data of all the patients were independently reviewed on FACT-Digital Lung (DEXIN, Shanxi, China) by two senior physicians with more than 5 years of experience in thoracic imaging diagnosis, who were blinded to the pathological diagnosis. To ensure the consistency of observation, all the images were viewed on the lung window [window level, −500 Hounsfield units (HU); window width, 1,500 HU]. A solid portion was defined as a high-density lesion that completely obscured blood vessels and bronchial passages. A ground-glass portion was defined as a lesion with slightly higher density than normal lung tissue that did not obscure the blood vessels and bronchial passages. The multiplicity (single or multiple) of each solid portion was determined based on a serial review of the axial CT slices. Multiple solid portions were defined as the existence of two or more independent solid portions in a nodule. After determining the multiplicity of a solid component together, the physicians used electronic calipers and least absolute shrinkage and selection operator (Lasso) tool to measure the solid portion of each nodule independently (see Figure 2 for a schematic illustration). The PSNs were then evaluated in terms of the—(I) location (the lung lobe and lung segment); (II) size: the long-axis diameter of the nodule (D_long), and the volume of the nodule (volume); and (III) size of the solid portion: the long-axis diameter of the single largest solid portion (max solid D_long), the volume of the single largest solid portion (max solid volume), the ratio of the long-axis diameter of the single largest solid portion to the long-axis diameter of the nodule (max solid D_long/D_long), the ratio of the volume of the single largest solid portion to the volume of the nodule (max solid volume/volume), the sum of the long-axis diameter of multiple solid portions (total solid D_long), the sum of the volume of multiple solid portions (total solid volume), the ratio of the sum of the long-axis diameter of multiple solid portions to the long-axis diameter of the nodule (total solid D_long/D_long), and the ratio of the sum of the volume of multiple solid portions to the volume of the nodule (total solid volume/volume). The observer transmitted the reconstructed chest CT images to the FACT-Digital Lung^TM workstation, and performed the automatic screening, segmentation, and delineation of region of interest using the computer-aided detection system. The observer modified the contour of the nodules layer by layer to ensure the accuracy of the measurements, and avoided blood vessels, bronchi, and pleural tissues as much as possible. The observer then manually delineated the solid area contour layer by layer along the boundary between the solid portion and the ground-glass portion. After each drawing, quantitative parameters such as the volume and the long-axis diameter were automatically calculated by the system (9). Finally, the mean values of the two doctors’ measurements were taken for the statistical analysis, and if there were significant differences in the results, a third radiologist was consulted to make a final determination.

Figure 2 Schematic diagram of lung nodule image processing. (A) The system recognizes and locates the nodule. (B) The red circle is an outline of the PSN automatically segmented by the system, and the long-axis diameter of the nodule measured on the maximal cross-section is 18.62 mm, and the volume of the nodule is 3,323.45 mm³. The solid portion of the nodule is segmented by the green circle, the long-axis diameter of the solid portion is 10.52 mm, and the volume of the solid portion is 731.91 mm³. (C) Through three-dimensional visualization reconstruction, the three-dimensional anatomical relationship between the nodule and the surrounding tissues is clearly displayed. PSN, part-solid nodule.

Pathologic diagnosis

All 186 nodules were pathologically confirmed after surgery. The pathological diagnoses were jointly reviewed by two pathologists with 5 years of experience or above according to the International Association for the Study of Lung Cancer/the American Thoracic Society/the European Respiratory Society (IASLC/ATS/ERS) lung adenocarcinoma (LUAD) classification (10)—(I) atypical adenomatous hyperplasia (AAH): a localized lesion (usually ≤10 mm) consisting of a single layer of atypical epithelial cells; (II) adenocarcinoma in situ (AIS): localized lesions (≤30 mm), the tumor cells grow along the alveolar wall but without signs of vascular, stromal, or pleural invasion; (III) minimally IAC (MIA): localized lesions (≤30 mm), the adenocarcinoma cells grow along the alveolar wall, accompanied by one or more foci of infiltrates (≤5 mm); and (IV) IAC: the tumor cells have penetrated the basement membrane, and the maximum diameter of the infiltrating foci is >5 mm. The percentage of each histological component (lepidic, acinar, papillary, micropapillary, and mucinous) in each IAC was recorded in 5% increments. The IACs were then further classified as lepidic-predominant adenocarcinoma (LPA), acinar-predominant adenocarcinoma (APA), papillary-predominant adenocarcinoma (PPA), micropapillary-predominant adenocarcinoma (MPA), and mucinous adenocarcinoma (MAC) based on the type of the main tissue component.

Statistical analysis

All the statistical analyses were performed at the two-tailed 5% significance level using SPSS (version 26.0, IBM, Armonk, NY, USA), R (version 4.4.1), and GraphPad Prism (version 9.5.0, GraphPad Software). The qualitative data are expressed as the number of cases (%), and were compared using the Chi-square (χ²) test or Fisher’s exact test between groups. The consistency of the measured values in plain CT and contrast-enhanced CT was assessed using the Bland-Altman plot. The non-normally distributed data are expressed as the median (interquartile range), and the Mann-Whitney U test was used for group comparisons. Multiple comparison analyses were performed using the Kruskal-Wallis test and Bonferroni correction test. Variables between groups were included in the multivariate logistic regression analysis to identify independent risk factors for IAC. The synthetic minority oversampling technique was employed to address the data imbalance problem, and receiver operating characteristic (ROC) curves were then drawn to compare the performance of different assessment methods in predicting IAC. Precision, accuracy, F1 score, and Matthews correlation coefficient (MCC) were selected as the evaluation indicators. These parameters were defined as follows:

Precision=TPTP+FP[1]

Accuracy=TP+TNTP+FP+TN+FN[2]

F1score=2×Precision×RecallPrecision+Recall[3]

MCC=TP×TN−FP×FN(TP+FN)×(TN+FP)×(TP+FP)×(TN+FN)[4]

Recall=TPTP+FN[5]

where TP represents true positive, FP represents false positive, TN represents true negative, FN represents false negative.

Results

Clinical and radiological characteristics

Of the 186 patients included in the study, 65 were male and 121 were female. The frequencies of each pathological subtype were as follows—AAH: 1.61% (3 of 186); AIS: 5.92% (11 of 186); MIA: 20.43% (38 of 186); LPA: 17.74% (33 of 186); APA: 34.95% (65 of 186); PPA: 11.29% (21 of 186); MPA: 6.45% (12 of 186); and MAC: 1.61% (3 of 186). A multiplicity of solid portions was found in 20.4% (38 of 186) of the PSNs. Among them, 52.63% (20 of 38) had two solid portions, while 47.37% (18 of 38) had three solid portions. The clinical and radiological features of the patients are summarized in Table 1. Of the PSNs with two solid portions, 5% (1 of 20) were pathologically diagnosed as AAH, 15% (3 of 20) as MIA, and 80% (16 of 20) as IAC. Of the PSNs with three solid portions, only one was diagnosed as MIA, and the remaining 94.44% (17 of 18) of the nodules were ultimately pathologically diagnosed as IAC.

Solid portion and proportion in different pathological subtypes

Of the 186 patients, 70 underwent both plain and contrast-enhanced chest scans, and 116 patients underwent only one of the two scans. To avoid the influence of the contrast agent on the measurements and ensure the consistency of the included data, we measured the long-axis diameters of the solid portions of the 70 nodules in the same slice of the lung window both on the plain CT and the contrast-enhanced CT, and performed the Bland-Altman analysis and t-test. The results indicated that the measurements of the two types of CT scans were in good agreement. The average difference between the measurements in the plain scan and the contrast-enhanced scan was 0.02 mm, while the 95% limit of agreement was between −1.163 mm and 1.211 mm.

The between-group comparison showed that there were significant differences in the measurement values of the solid portions among the precursor lesions, MIAs, and IACs. A further pairwise comparison found that the D_long, max solid D_long, total solid D_long, max solid D_long/D_long, total solid D_long/D_long, volume, max solid volume, total solid volume, max solid volume/volume, and total solid volume/volume of the PSNs featuring IAC were significantly higher than those in the precursor lesions and MIAs (P<0.001), while the latter two did not show any significant differences in terms of the proportion of the solid portions (P>0.05) (Table 2).

The intergroup comparison of the different histological subtypes in the IAC group revealed a significant difference in the proportion of solid portions (P<0.001), with a gradual increase trend from LPA/APA to PPA/MPA to MAC (see Table 3 and Figure 3).

Figure 3 CT quantitative parameters of different pathological subtypes. The middle horizontal line represents the median, while the upper and lower dotted lines of the violin plot represent the upper and lower quartiles, respectively. Significance: *, P<0.05; **, P<0.01; ***, P<0.001. CT, computed tomography; D, diameter; LPA, lepidic-predominant adenocarcinoma; APA, acinar-predominant adenocarcinoma; PPA, papillary-predominant adenocarcinoma; MPA, micropapillary-predominant adenocarcinoma; MAC, mucinous adenocarcinoma.

Factors associated with IAC in PSNs

A univariate logistic regression analysis was then performed in which IAC was the dependent variable to screen out the factors that could predict histologic invasiveness. The goodness-of-fit test results suggested that the model was well calibrated (Table 4).

After balancing the data classes, a ROC curve analysis was performed to test the efficacy of the different quantitative parameters in predicting IAC, and the precision, accuracy, F1 score and MCC were used to determine the corresponding optimal values. The results showed that all of the quantitative parameters had good performance in predicting the invasiveness of PSN. Taking a max solid D_long/D_long >40.38% as the critical value, the accuracy was 87%; taking a total solid D_long/D_long >51.24% as the critical value, the accuracy was 87%; taking a max solid volume/volume >18.94% as the critical value, the accuracy was 90%; taking a total solid volume/volume >19.04% as the critical value, the accuracy was 90% (Table 5 and Figure 4).

Figure 4 Receiver operating characteristic curves of different CT parameters in distinguishing pre-IAC from IAC in PSNs. CT, computed tomography; D, diameter; IAC, invasive adenocarcinoma; PSNs, part-solid nodules.

Discussion

Traditional theory holds that the evolution of LUAD is a gradual linear multi-step progression process (12). It originates from type II alveolar epithelial cells or Clara cells, and initially grows along the alveolar wall or respiratory bronchioles, without surrounding infiltration or alveolar collapse, and usually appears as a homogeneous ground-glass opacity on CT. With the progression of the disease, the morphological atypia of the tumor cells increases (showing nucleus enlargement and chromatin thickening), and the proliferation of tumor cells results in colonies of tightly packed cells in multi-layers along the alveoli. The further development of these lesions may lead to focal interstitial infiltration, alveolar wall collapse, and fibrous hyperplasia, which eventually evolve into MIA or IAC, and which present as nodules with solid components on CT (10,13). Thus, it is widely believed that the solid components of PSNs correspond to the infiltrating portion in histopathological sections (14), and as the size of the solid components increase, the degree of infiltration of the lesion may be deeper, and the risk of metastasis increases (15).

Based on the tumor evolution described above, under the Eighth Edition of the Tumor-Node-Metastasis (TNM) Staging Classification, the solid portion is considered a crucial basis for the clinical T classification of PSN-like LUAD (10). However, the majority of incidentally detected PSNs have more than two solid components, and research needs to be conducted to determine whether this measurement is equally applicable to PSNs with diverse solid components. In our study, we included 186 PSNs, of which 20.43% had ≥2 solid components. The results showed that both the long-axis diameter, the volume based on the largest solid portion, and the sum of solid components were independent risk factors for identifying IAC, and could be used as imaging markers. Further, a maximum solid D_long/D_long >40.38%, or a total solid D_long/D_long >51.24%, or a max solid volume/volume >18.94%, or a total solid volume/volume >19.04 highly suggested that the tumor cells might have invaded the interstitium and progressed to IAC. For such patients, biopsy and/or surgery should be performed as soon as possible, and the 5-year survival rate of such patients can be as high as 90% if there are no metastases in the intrapulmonary lymph nodes (16,17). A previous study examining the prognostic value of solid measurements of stage IA LUADs reported that the simultaneous measurement of multiple solid portions of PSNs is prone to reader-to-reader differences (8), which may ultimately result in the inaccurate summation of solid part results, thereby reducing the prognostic performance of the staging system.

In this study, the interpretation and measurements of all the images were performed independently by two physicians, and by a third physician for quality control. The ROC curve analysis showed that several measurement methods had good diagnostic value; however, the diagnostic value based on multiple solid portions or the sum of solid portions was not significantly better than that of the traditional clinical assessment based on a single largest solid portion. Moreover, additional measurements and the documentation of multiple solid portions would add to the time consumption and is not necessary.

Notably, in our study, PSNs classified as precursor lesions and MIAs did not differ significantly in terms of the proportion of volume and long-axis diameter of the solid component (Table S1). This could be in part due to the relatively small number of cases, and the fact that there are only slight differences in the pathological diagnostic criteria between AIS and MIA. According to the World Health Organization classification of LUAD (18), AIS is an early stage lesion that grows along the alveolar septum without structural damage. MIA is a lesion with focal interstitial infiltration ≤5 mm, without extensive alveolar destruction and lymph node metastasis, which can be completely resected by surgery, and has a 5-year disease-free survival (DFS) rate of 100% (19,20). Once the lesion progresses to IAC, the tumor cells grow rapidly, the degree of infiltration increases remarkably, the risk of metastasis and recurrence also increases, and the 5-year survival rate drops to 19% (21). Thus, in this study, we classified MIA as part of the pre-IAC group to distinguish it from IAC.

Previous studies have shown that LPA is a common histological subtype of LUAD, and its presence is often associated with a better prognosis (22,23). Some studies have found that a higher proportion of lepidic growth indicates a better prognosis (23,24). PPA and APA are considered malignant tumors with an intermediate prognosis, the 5-year DFS after resection ranges from 54–84%, the 5-year overall survival (OS) rate ranges from 67–81.2%, and the risk of recurrence and progression with other complex components is higher than LPA (25). Additionally, both PPA and APA have a higher proportion of solid components than LPA. The prognosis of MPA is significantly worse than that of other subtypes, the high degree of LUAD invasion under this growth pattern has been reported to be related to the accumulation and aggregation of tumor cells in the alveoli, and the DFS of such patients range from 0–67% at 5 years after resection, and the OS rates range from 38–62% at 5 years (26). However, we found that the proportion of solid components in LPA, APA, PPA, and MPA were significantly higher than those of AIS and MIA, but there was no significant difference among the subtypes in the IAC group (Table S2). Due to the limited sample size of this study, the results may not reflect the actual situation, and the large sample data need to be supplemented and improved in the future to provide more detailed suggestions for the pathological classification of adenocarcinoma.

This was a retrospective study, and due to time constraints, only the data of cases from the previous 5 years in which surgery had been performed were screened, and the number of samples was insufficient for a further stratified subtype analysis in the IAC group. In the future, it is necessary to further explore using prospective, multicenter, large sample-size, and crossover design methods.

Conclusions

For PSNs with multiple solid portions, measurements based on the single largest solid portion and the sum of multiple solid portions are decisive for pathological diagnosis. Given the amount of work involved in obtaining the measurements, it is not mandatory to take additional individual measurements of each solid portion.

Acknowledgments

The authors gratefully acknowledge the participants of the study and the clinical staff of Zhengzhou University People’s Hospital who assisted in the patient recruitment and data collection.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-2032/rc

Funding: This work was supported by grants from the National Natural Science Foundation of China (No. 81970077).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-2032/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (revised in 2013). This retrospective study was approved by the Institutional Review Board of Zhengzhou University People’s Hospital (No. 201925), and the requirement of individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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