Prognosis of Small Adenocarcinoma of the Lung Based on Thin-Section Computed Tomography and Pathological Preparations:

Multi-Window CT Based Radiological Traits for Improving Early Detection in Lung Cancer Screening

Rationale and Objectives

Evaluate ability of radiological semantic traits assessed on multi-window computed tomography (CT) to predict lung cancer risk.

Materials and Methods

A total of 199 participants were investigated, including 60 incident lung cancers and 139 benign positive controls. Twenty lung window features and 2 mediastinal window features were extracted and scored on a point scale in three screening rounds. Multivariate logistic regression analysis was used to explore the association of these radiological traits with the risk of developing lung cancer. The areas under the receiver operating characteristic curve (AUROC), sensitivity, specificity, and positive predictive value (PPV) were computed to evaluate the best predictive model.

Results

Combining mediastinal window-specific features with the lung window features-based model significantly improves performance compared to individual window features. Model performance is consistent both at baseline and the first follow-up scan, with an AUROC increased from 0.822 to 0.871 (p = 0.009) and from 0.877 to 0.917 (p = 0.008), respectively, for single to multi-window feature models. We also find that the multi-window CT based model showed better specificity and PPV, with PPV at the second follow-up scan improved to 0.953.

Conclusion

We find combining window semantic features improves model performance in identifying cancerous nodules. We also find that lung window features are more informative compared to mediastinal features in predicting malignancy.

Effect of 5-Line Signs in the Prediction of Staging, Progression, and Prognosis of Peripheral Lung Carcinoma: Preliminary Observation Report

BACKGROUND

The single line of the normal interlobar fissure shown on a thin section image can be reconstructed as a 5-line sign on axial maximal intensity projection. The line between the lung nodule and the pleura is called the pleural tail sign on thin image. On the axial maximal intensity projection, it can also be reconstructed as the 5-line sign or fewer than 5 lines.

OBJECTIVE

This study aimed to observe the effect of 5-line signs in staging, progression, and prognosis of peripheral lung carcinoma.

MATERIALS AND METHODS

This study included 132 patients with peripheral lung carcinoma. Among these patients, 93 were men and 39 were women, with an age range of 27 to 82 years and a lung nodule range of 0.98 to 8.75 cm. Maximal intensity projection was reconstructed based on 1.0 or 1.25 mm of thin-slice images in multislice spiral computed tomography. Five-line signs on the margin of the nodule (mass) were observed and were classified into grades 1 to 4 according to the sharpness of the 5-line signs.

RESULTS

Multivariate logistic regression analysis showed that the sharpness of the 5-line signs was correlated with N and TNM staging of peripheral lung carcinoma (P = 0.012, P = 0.016). The lower the sharpness of the 5-line signs, the greater the number of cases of progression of the tumor (P < 0.001), and thus the higher the mortality rate and the lower the survival rate (P = 0.001). The sensitivity and specificity of predicting tumor progression were 56.3% and 93.3%, and those of tumor prognosis were 61.1% and 82.4%, respectively.

CONCLUSIONS

The sharpness of the 5-line signs has certain effects on the prediction of invasion, progression, and prognosis of lung carcinoma, particularly of small lung cancer (≤3.0 cm).

Multi-window CT based Radiomic signatures in differentiating indolent versus aggressive lung cancers in the National Lung Screening Trial: a retrospective study

Background

We retrospectively evaluated the capability of radiomic features to predict tumor growth in lung cancer screening and compared the performance of multi-window radiomic features and single window radiomic features.

Methods

One hundred fifty lung nodules among 114 screen-detected, incident lung cancer patients from the National Lung Screening Trial (NLST) were investigated. Volume double time (VDT) was calculated as the difference between continuous two scans and used to define indolent and aggressive lung cancers. Lung nodules were semi-automatically segmented using lung and mediastinal windows separately, and subtracting the mediastinal window region from the lung window region generated the difference region. 364 radiomic features were separately exacted from nodules using the lung window, the mediastinal window and the difference region. Multivariable models were conducted to identify the most predictive features in predicting tumor growth. Clinical information was also obtained from the database.

Results

Based on our definition, 26% of the cases were indolent lung cancer. The tumor growth pattern could be predicted by radiomic models constructed using features obtained in the lung window, the difference region, and by combining features obtained in both the lung window and difference regions with areas under the receiver operator characteristic (AUROCs) of 0.799, 0.819, and 0.846, respectively. The multi-window feature model showed better performance compared to single window features (P < 0.001). Incorporating clinical factors into the multi-window feature models showed improvement, yielding an accuracy of 84.67% and AUROC of 0.855 for distinguishing indolent from aggressive disease.

Conclusions

Multi-window CT based radiomics features are valuable predictors of indolent lung cancers and out performed single CT window setting. Combining clinical information improved predicting performance.

Electronic supplementary material

The online version of this article (10.1186/s40644-019-0232-6) contains supplementary material, which is available to authorized users.

Value of window technique in diagnosis of the ground glass opacities in patients with non-small cell pulmonary cancer

The aim of the present study was to examine the value of window technique in qualitative diagnosis of the ground glass opacities (GGO) in patients with non-small cell pulmonary cancer. A total of 124 clinically suspected pulmonary cancer patients were analyzed retrospectively. The lesions were affirmed by puncture biopsy, and were GGO on pulmonary window while were invisible on mediastinal window. Sixty-four multi-detector spiral computed tomography with the window width and window level of 1,500 Hounsfield units (HU) and −450 HU on pulmonary window, while the window width and window level of 400 and 40 HU on mediastinal window, was used in the study. The window adjustment technique was used to analyze the window width and window level of lesion on pulmonary window and mediastinal window, for searching invisible threshold on 3-megapixel medical displays. The diagnostic accuracy and the cut-off value were compared on receiver operating characteristic (ROC) curve. The results showed that the window width and window level on pulmonary window and mediastinal window of malignant lesions were significantly less than those of benign ones (P<0.05). The cut-off value on pulmonary window was the window width and window level of 1,300 and −220 HU, the area under the ROC was 0.830 [sensitivity was 72.5%, specificity was 84.3%; 95% confidence interval (CI), 0.712–0.945]. The cut-off value on mediastinal window was the window width and window level of 360 and 30 HU, and the area under the ROC was 0.623 (was 62.0%, specificity was 55.7%; 95% CI, 0.541–0.745). In conclusion, the window technique has high sensitivity and accuracy in qualitative diagnosis of the GGO.

Microscopic Invasions, Prognoses, and Recurrence Patterns of Stage I Adenocarcinomas Manifesting as Part-Solid Ground-Glass Nodules: Comparison With Adenocarcinomas Appearing as Solid Nodules After Matching Their Solid Parts' Size

The purpose of the present study was to compare the frequency of microscopic invasions, disease-free-survival (DFS), and the frequency and pattern of disease recurrence between stage I pulmonary adenocarcinomas appearing as solid nodules and those appearing as part-solid ground-glass nodules (GGNs) after matching their solid parts' size (D(solid)) and patients' age. Among 501 patients who underwent curative surgery for stage I pulmonary adenocarcinomas between 2003 and 2011, 172 patients (86 with solid nodules [M: F = 36: 50; mean age, 62.8 years] and 86 with part-solid GGNs [M:F = 30:56; mean age, 63.0 years]) matched for D(solid) and patients' age were included. DFS, frequency of microscopic invasions, recurrence, and recurrence pattern were compared between the two groups. No significant difference was observed in the frequency of microscopic invasions between the two groups (visceral pleural invasion, 30.23% vs. 29.07%, P = 0.867; lymphatic invasion, 5.81% vs. 3.49%, P = 0.720; vascular invasion, 1.16% vs. 0%, P = 1.000; solid nodules vs. part-slid GGNs, respectively) and DFS (estimated 5-year DFS, 83.6% vs. 81.9%, P = 0.744; solid nodules vs. part-slid GGNs, respectively). As for recurrence and recurrence pattern, there were no significant differences between the solid nodule group (14/86), and part-solid GGN group (12/86) (P = 0.670). Lung parenchymal nodules were the most frequent pattern of disease recurrence in both groups, followed by pleural seeding. In conclusion, after matching D(solid) and patients' age, there was no significant difference in the frequency of microscopic invasions, DFS, and the frequency and pattern of recurrence between stage I pulmonary adenocarcinomas appearing as solid nodules and part-solid GGNs.

Development of a nomogram combining clinical staging with (18)F-FDG PET/CT image features in non-small-cell lung cancer stage I-III

PURPOSE

Our goal was to develop a nomogram by exploiting intratumour heterogeneity on CT and PET images from routine (18)F-FDG PET/CT acquisitions to identify patients with the poorest prognosis.

METHODS

This retrospective study included 116 patients with NSCLC stage I, II or III and with staging (18)F-FDG PET/CT imaging. Primary tumour volumes were delineated using the FLAB algorithm and 3D Slicer™ on PET and CT images, respectively. PET and CT heterogeneities were quantified using texture analysis. The reproducibility of the CT features was assessed on a separate test-retest dataset. The stratification power of the PET/CT features was evaluated using the Kaplan-Meier method and the log-rank test. The best standard metric (functional volume) was combined with the least redundant and most prognostic PET/CT heterogeneity features to build the nomogram.

RESULTS

PET entropy and CT zone percentage had the highest complementary values with clinical stage and functional volume. The nomogram improved stratification amongst patients with stage II and III disease, allowing identification of patients with the poorest prognosis (clinical stage III, large tumour volume, high PET heterogeneity and low CT heterogeneity).

CONCLUSION

Intratumour heterogeneity quantified using textural features on both CT and PET images from routine staging (18)F-FDG PET/CT acquisitions can be used to create a nomogram with higher stratification power than staging alone.

Diagnosis of the invasiveness of lung adenocarcinoma manifesting as ground glass opacities on high-resolution computed tomography

BACKGROUND

To explore the diagnostic method in assessing the malignancy of pulmonary adenocarcinoma characterized by ground glass opacities (GGO) on computed tomography (CT).

METHODS

Preoperative CT data for preinvasive and invasive lung adenocarcinomas were analyzed retrospectively. GGO lesions that were detected on lung windows but absent using the mediastinal window were subject to adjustment of the window width, which was reduced with the fixed interval of 100 HU until the lesions were no longer evident, with a fixed mediastinal window level of 40 HU. The shape, smoking habits, size of the lesion on the lung window, and window width at which lesions disappeared were compared and receiver operating characteristic curves were used to determine the optimal cut-off of the lesion size and window width to differentiate between these invasive and preinvasive lesions.

RESULTS

Of the 209 lung adenocarcinomas, 102 were preinvasive (25 atypical adenomatous hyperplasia and 77 adenocarcinoma in situ), while 107 were invasive (78 minimally invasive adenocarcinoma and 29 invasive adenocarcinoma). The shape, lesion size, and window width at which lesions were no longer evident differed significantly between the two groups (P < 0.05). The size of 8.9 mm and a window width of 1250 HU were the optimal cut-off to differentiate between preinvasive and invasive lesions.

CONCLUSION

The shape, size of the lesion, and window width on high-resolution CT may be useful in assessing the invasiveness of lung adenocarcinoma that manifests as GGO. Irregular lesions that disappear at window width <1250 HU, with a diameter of > 8.9 mm are more likely to be invasive.

Radiographic and pathological analysis of small lung adenocarcinoma using the new IASLC classification

AIM

To analyse the correlation between computed tomography (CT) findings of small lung adenocarcinomas and the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society Classification of Lung Adenocarcinoma.

MATERIALS AND METHODS

A retrospective review of 300 lung adenocarcinoma lesions (size ≤20 mm) after surgical resection in 295 consecutive patients was performed. Tumours were defined as air-containing type if the ratio of the maximum dimension of the tumour on mediastinal windows to the maximum dimension of the tumour on lung windows was ≤50%, and as solid-density type if the ratio was >50%. The incidence between CT findings (air bronchogram, vascular involvement, pleural tags, notches, and spiculation) and pathological findings were investigated.

RESULTS

Of the 142 air-containing lesions, 114 were adenocarcinoma in situ (AIS), 28 were minimally invasive adenocarcinoma (MIA), and none of the lesions were invasive adenocarcinoma. Of the 158 solid-density lesions, 30 were AIS, 24 were MIA, and 104 were invasive adenocarcinoma. Notches and pleural tags were commonly observed in cases of invasive adenocarcinoma (p < 0.05).

CONCLUSIONS

In the air-containing type of small lung adenocarcinomas, AIS and MIA were observed but no cases of invasive adenocarcinoma were found. The presence of notches and pleural tags were a significant factor in invasive adenocarcinoma.

Radiologic implications of the 2011 classification of adenocarcinoma of the lung

Now the leading subtype of lung cancer, adenocarcinoma received a new classification in 2011. For tumors categorized previously as bronchioloalveolar carcinoma (BAC), criteria and terminology had not been uniform, so the 2011 classification provided four new terms: (a) adenocarcinoma in situ (AIS), representing histopathologically a small (≤3-cm), noninvasive lepidic growth, which at computed tomography (CT) is usually nonsolid; (b) minimally invasive adenocarcinoma, representing histopathologically a small (≤3-cm) and predominantly lepidic growth that has 5-mm or smaller invasion, which at CT is mainly nonsolid but may have a central solid component of up to approximately 5 mm; (c) lepidic predominant nonmucinous adenocarcinoma, representing histopathologically invasive adenocarcinoma that shows predominantly lepidic nonmucinous growth, which at CT is usually part solid but may be nonsolid or occasionally have cystic components; and (d) invasive mucinous adenocarcinoma, histopathologically showing lepidic growth as its predominant component, which at CT varies widely from solid to mostly solid to part solid to nonsolid and may be single or multiple (when multifocal, it was formerly called multicentric BAC). In addition, new histopathologic subcategories of acinar, papillary, micropapillary, and solid predominant adenocarcinoma are now described, all as nonmucinous, predominantly invasive, may include a small lepidic component, and at CT are usually solid but may include a small nonsolid component. The micropapillary subtype has a poorer prognosis than the other subtypes. In addition, molecular genetic correlations for the subcategories of adenocarcinoma of the lung are now a topic of increasing interest. As the new classification enters common use, further descriptions of related correlations can be anticipated.

Comparison of thin-section CT and pathological findings in small solid-density type pulmonary adenocarcinoma: prognostic factors from CT findings

OBJECTIVE

We divided pulmonary adenocarcinoma of ≤ 20 mm into air-containing and solid-density types based on a percentage reduction of the maximum tumor diameter in the mediastinal window image compared to the area in the lung window image on thin-section (TS) CT of ≥ 50% (air-containing type) and <50% (solid-density type). No relapse occurred in patients with air-containing type. The prognosis of solid-density type may be poor even when the tumor size is 20mm or smaller. We investigated whether CT findings for these tumors could serve as prognostic factors.

METHODS

The subjects were 105 patients with solid-density type pulmonary adenocarcinoma that was identified on TSCT and found to have a diameter of 20mm or smaller after surgical resection during the period from April 1997 to November 2004. Notches, air bronchogram, pleural retraction, spiculation, venous involvement, and ground glass opacity were examined on TSCT, and their associations with pathological findings (i.e., pleural invasion, lymphatic permeation, vascular invasion, lymph node metastasis, and Noguchi's classification) and relapse were investigated using chi-square test and Cox proportional hazards model.

RESULTS

The incidence of relapse was significantly higher in cases with notches. The incidence of notches increased with tumor growth and notches were frequent in Noguchi type D tumors, reflecting poorly differentiated adenocarcinoma. Lymphatic permeation and type D cases were independent factors associated with a poor prognosis using Cox proportional hazards model.

CONCLUSIONS

TSCT findings may be useful for prediction of the prognosis of solid-density type pulmonary adenocarcinoma.