Focal area of ground-glass opacity and ground-glass opacity predominance on thin-section CT: Discrimination between neoplastic and non-neoplastic lesions

Bubble-like lucency in pulmonary ground glass nodules on computed tomography: a specific pattern of air-containing space for diagnosing neoplastic lesions

PURPOSE

To investigate the computed tomography (CT) characteristics of air-containing space and its specific patterns in neoplastic and non-neoplastic ground glass nodules (GGNs) for clarifying their significance in differential diagnosis.

MATERIALS AND METHODS

From January 2015 to October 2022, 1328 patients with 1,350 neoplastic GGNs and 462 patients with 465 non-neoplastic GGNs were retrospectively enrolled. Their clinical and CT data were analyzed and compared with emphasis on revealing the differences of air-containing space and its specific patterns (air bronchogram and bubble-like lucency [BLL]) between neoplastic and non-neoplastic GGNs and their significance in differentiating them.

RESULTS

Compared with patients with non-neoplastic GGNs, female was more common (P < 0.001) and lesions were larger (P < 0.001) in those with neoplastic ones. Air bronchogram (30.1% vs. 17.2%), and BLL (13.0% vs. 2.6%) were all more frequent in neoplastic GGNs than in non-neoplastic ones (each P < 0.001), and the BLL had the highest specificity (93.6%) in differentiation. Among neoplastic GGNs, the BLL was more frequently detected in the larger (14.9 ± 6.0 mm vs. 11.4 ± 4.9 mm, P < 0.001) and part-solid (15.3% vs. 10.7%, P = 0.011) ones, and its incidence significantly increased along with the invasiveness (9.5-18.0%, P = 0.001), whereas no significant correlation was observed between the occurrence of BLL and lesion size, attenuation, or invasiveness.

CONCLUSION

The air containing space and its specific patterns are of great value in differentiating GGNs, while BLL is a more specific and independent sign of neoplasms.

Construction and validation of a predictive model of invasive adenocarcinoma in pure ground-glass nodules less than 2 cm in diameter

OBJECTIVES

In this study, we aimed to develop a multiparameter prediction model to improve the diagnostic accuracy of invasive adenocarcinoma in pulmonary pure glass nodules.

METHOD

We included patients with pulmonary pure glass nodules who underwent lung resection and had a clear pathology between January 2020 and January 2022 at the Qilu Hospital of Shandong University. We collected data on the clinical characteristics of the patients as well as their preoperative biomarker results and computed tomography features. Thereafter, we performed univariate and multivariate logistic regression analyses to identify independent risk factors, which were then used to develop a prediction model and nomogram. We then evaluated the recognition ability of the model via receiver operating characteristic (ROC) curve analysis and assessed its calibration ability using the Hosmer-Lemeshow test and calibration curves. Further, to assess the clinical utility of the nomogram, we performed decision curve analysis.

RESULT

We included 563 patients, comprising 174 and 389 cases of invasive and non-invasive adenocarcinoma, respectively, and identified seven independent risk factors, namely, maximum tumor diameter, age, serum amyloid level, pleural effusion sign, bronchial sign, tumor location, and lobulation. The area under the ROC curve was 0.839 (95% CI: 0.798-0.879) for the training cohort and 0.782 (95% CI: 0.706-0.858) for the validation cohort, indicating a relatively high predictive accuracy for the nomogram. Calibration curves for the prediction model also showed good calibration for both cohorts, and decision curve analysis showed that the clinical prediction model has clinical utility.

CONCLUSION

The novel nomogram thus constructed for identifying invasive adenocarcinoma in patients with isolated pulmonary pure glass nodules exhibited excellent discriminatory power, calibration capacity, and clinical utility.

Correlations Between Inflammatory Cell Infiltration and Relative Density and the Boundary Manifestation of Pulmonary Non-Neoplastic Ground Glass Nodules

Purpose

To investigate the influence factors for the various boundary manifestations of pulmonary non-neoplastic ground glass nodules (GGNs) on computed tomography (CT).

Materials and Methods

From January 2015 to March 2022, a total of 280 patients with 318 non-neoplastic GGNs were enrolled. The correlations between degree of inflammatory cell infiltration and relative density (ΔCT) and the boundary manifestations of lesions were evaluated, respectively.

Results

Nongranulomatous nodules (283, 89.0%) with fibrous tissue proliferation and/or inflammatory cells as the predominant pathological findings were the most common non-neoplastic GGNs, followed by granulomatous nodules (28, 8.8%). Among nongranulomatous GGNs, cases with more and less/no inflammatory cells were 15 (10.9%) and 122 (89.1%) in 137 well-defined ones with smooth margin, 16 (24.6%) and 49 (75.4%) in 65 well-defined ones with coarse margin, 43 (91.5%) and 4 (8.5%) in 47 ill-defined ones with higher ΔCT (>151HU), and 4 (11.8%) and 30 (88.2%) in 34 ill-defined ones with lower ΔCT (< 151HU). The proportion of cases with more inflammatory cells in well-defined nodules was similar to that in ill-defined ones with lower ΔCT (P = 0.587) but significantly lower than that in ill-defined ones with higher ΔCT (P < 0.001). Among the granulomatous nodules, ill-defined cases with higher ΔCT (16, 57.1%) were the most common, and they (7/8, 87.5%) frequently had changes during short-term follow-up.

Conclusion

Nongranulomatous nodules are the most common non-neoplastic GGNs, their diverse boundary manifestations closely correlate with degree of inflammatory cell infiltration and density difference.

Differential diagnosis of benign and malignant patchy ground-glass opacity by thin-section computed tomography

Background

Previous studies confirmed that ground-glass nodules (GGNs) with certain CT manifestations had a higher probability of malignancy. However, differentiating patchy ground-glass opacities (GGOs) and GGNs has not been discussed solely. This study aimed to investigate the differences between the CT features of benign and malignant patchy GGOs to improve the differential diagnosis.

Methods

From January 2016 to September 2021, 226 patients with 247 patchy GGOs (103 benign and 144 malignant) confirmed by postoperative pathological examination or follow-up were retrospectively enrolled. Their clinical and CT data were reviewed, and their CT features were compared. A binary logistic regression analysis was performed to reveal the predictors of malignancy.

Results

Compared to patients with benign patchy GGOs, malignant cases were older (P <  0.001), had a lower incidence of malignant tumor history (P = 0.003), and more commonly occurred in females (P = 0.012). Based on CT images, there were significant differences in the location, distribution, density pattern, internal bronchial changes, and boundary between malignant and benign GGOs (P <  0.05). The binary logistic regression analysis revealed that the independent predictors of malignant GGOs were the following: patient age ≥ 58 years [odds ratio (OR), 2.175; 95% confidence interval (CI), 1.135–6.496; P = 0.025], locating in the upper lobe (OR, 5.481; 95%CI, 2.027–14.818; P = 0.001), distributing along the bronchovascular bundles (OR, 12.770; 95%CI, 4.062–40.145; P < 0.001), centrally distributed solid component (OR, 3.024; 95%CI, 1.124–8.133; P = 0.028), and well-defined boundary (OR, 5.094; 95%CI, 2.079–12.482; P < 0.001).

Conclusions

In older patients (≥58 years), well-defined patchy GGOs with centric solid component, locating in the upper lobe, and distributing along the bronchovascular bundles should be highly suspected as malignancy.

Adding predictive and diagnostic values of pulmonary ground-glass nodules on lung cancer via novel non-invasive tests

Pulmonary ground-glass nodules (GGNs) are highly associated with lung cancer. Extensive studies using thin-section high-resolution CT images have been conducted to analyze characteristics of different types of GGNs in order to evaluate and determine the predictive and diagnostic values of GGNs on lung cancer. Accurate prediction of their malignancy and invasiveness is critical for developing individualized therapies and follow-up strategies for a better clinical outcome. Through reviewing the recent 5-year research on the association between pulmonary GGNs and lung cancer, we focused on the radiologic and pathological characteristics of different types of GGNs, pointed out the risk factors associated with malignancy, discussed recent genetic analysis and biomarker studies (including autoantibodies, cell-free miRNAs, cell-free DNA, and DNA methylation) for developing novel diagnostic tools. Based on current progress in this research area, we summarized a process from screening, diagnosis to follow-up of GGNs.

Discriminating invasive adenocarcinoma among lung pure ground-glass nodules: a multi-parameter prediction model

Background

Patients with consistent lung pure ground-glass nodules (pGGNs) have a high incidence of lung adenocarcinoma that can be classified as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IAC). Regular follow-up is recommended for AIS and MIA, while surgical resection should be considered for IAC. This study sought to develop a multi-parameter prediction model to increase the diagnostic accuracy in discriminating between IAC and AIS or MIA.

Methods

The training data set comprised consecutive patients with lung pGGNs who underwent resection from January to December 2017 at the Zhongshan Hospital. Of the 370 resected pGGNs, 344 were pathologically confirmed to be AIS, MIA, or IAC and were included in the study. The 26 benign pGGNs were excluded. We compared differences in the clinical features (e.g., age and gender), the content of serum tumor biomarkers, the computed tomography (CT) parameters (e.g., nodule size and the maximal CT value), and the morphologic characteristics of nodules (e.g., lobulation, spiculation, pleura indentation, vacuole sign, and normal vessel penetration or abnormal vessel) between the pathological subtypes of AIS, MIA, and IAC. An abnormal vessel was defined as “vessel curve” or “vessel enlargement”. Statistical analyses were performed using the chi-square test, analysis of variance (ANOVA), and rank test. The IAC prediction model was constructed via a multivariate logistical regression. Our prediction model for lung pGGNs was further validated in a data set comprising consecutive patients from multiple medical centers in China from July to December 2018. In total, 345 resected pGGNs were pathologically diagnosed as lung adenocarcinoma in the validation data set.

Results

In the training data set, patients with pGGNs ≥10 mm in size had a high incidence (74.5%) of IAC. The maximal CT value of IAC [–416.1±121.2 Hounsfield unit (HU)] was much higher than that of MIA (–507.7±138.0 HU) and AIS (–602.6±93.3 HU) (P<0.001). IAC was more common in pGGNs that displayed any of the following CT manifestations: lobulation, spiculation, pleura indentation, vacuole sign, and vessel abnormality. The IAC prediction model was constructed using the parameters that were assessed as risk factors (i.e., the nodule size, maximal CT value, and CT signs). The receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) of this model for diagnosing IAC was 0.910, which was higher than that of the AUC for nodule size alone (0.891) or the AUC for the maximal CT value alone (0.807) (P<0.05, respectively). A multicenter validation data set was used to validate the performance of our prediction model in diagnosing IAC, and our model was found to have an AUC of 0.883, which was higher than that of the AUC of 0.827 for the module size alone model or the AUC of 0.791 for the maximal CT value alone model (P<0.05, respectively).

Conclusions

Our multi-parameter prediction model was more accurate at diagnosing IAC than models that used only nodule size or the maximal CT value alone. Thus, it is an efficient tool for identifying the IAC of malignant pGGNs and deciding if surgery is needed.

Solitary Pulmonary Inflammatory Nodule: CT Features and Pathological Findings

Purpose

Solitary pulmonary inflammatory nodules (SPINs) are frequently misdiagnosed as malignancy. We aimed to investigate CT features and pathological findings of SPINs for improving diagnosis strategies.

Patients and Methods

In this retrospective study, 225 and 310 consecutive patients with confirmed SPINs and lung cancerous nodules were enrolled from January 2013 to December 2020. Nodules were classified into different types based on the key CT features: I, homogeneous and well-defined nodules with smooth (Ia), coarse (Ib), or spiculated margins (Ic); II, nodules with blurred boundaries, peripheral patches, or both; III, nodules exhibiting heterogeneous density; and IV, polygonal nodules. The pathological findings of SPINs were simultaneously studied and summarized.

Results

Among the 225 SPINs, type I (Ia, Ib, and Ic), II, III, and IV were 137 (60.9%) (47 [20.9%], 33 [14.7%], and 57 [25.3%]), 62 (27.6%), 12 (5.3%) and 14 (6.2%), respectively. Correspondingly, those in 310 cancerous nodules were 275 (88.7%) (119 [38.4%], 70 [22.6%], and 86 [27.7%]), 20 (6.5%), 15 (4.8%), and 0, respectively. Compared with lung cancers, type I nodules were less common but type II and IV nodules were more common in SPINs (each P < 0.0001). Though the frequencies of subtype I (P = 0.095) and type III (P = 0.796) nodules were similar between two groups, their specific CT features were significantly different. The main pathological findings of each type of SPINs were most extensively identical (82.2 - 100%).

Conclusion

Between cancerous nodules and SPINs, differences in overall or specific CT features exist. The type II and IV nodules are highly indicative of SPINs, and each type of SPINs have almost similar pathological findings.

Differentiating focal interstitial fibrosis from adenocarcinoma in persistent pulmonary subsolid nodules (> 5 mm and < 20 mm): the role of coronal thin-section CT images

OBJECTIVES

To investigate thin-section computed tomography (CT) features of pulmonary subsolid nodules (SSNs) with sizes between 5 and 20 mm to determine predictive factors for differentiating focal interstitial fibrosis (FIF) from adenocarcinoma.

METHODS

From January 2017 to December 2018, 169 patients who had persistent SSNs 5-20 mm in size and underwent preoperative nodule localization were enrolled. Patient characteristics and thin-section CT features of the SSNs were reviewed and compared between the FIF and adenocarcinoma groups. Univariable and multivariable analyses were used to identify predictive factors of malignancy. Receiver operating characteristic (ROC) curve analysis was used to quantify the performance of these factors.

RESULTS

Among the 169 enrolled SSNs, 103 nodules (60.9%) presented as pure ground-glass opacities (GGOs), and 40 (23.7%) were FIFs. Between the FIF and adenocarcinoma groups, there were significant differences (p< 0.05) in nodule border, shape, thickness, and coronal/axial (C/A) ratio. Multivariable analysis demonstrated that a well-defined border, a nodule thickness >4.2, and a C/A ratio >0.62 were significant independent predictors of malignancy. The performance of a model that incorporated these three predictors in discriminating FIF from adenocarcinoma achieved a high area under the ROC curve (AUC, 0.979) and specificity (97.5%).

CONCLUSIONS

For evaluating persistent SSNs 5-20 mm in size, the combination of a well-defined border, a nodule thickness > 4.2, and a C/A ratio > 0.62 is strongly correlated with malignancy. High accuracy and specificity can be achieved by using this predictive model.

KEY POINTS

• Thin-section coronal images play an important role in differentiating FIF from adenocarcinoma. • The combination of a well-defined border, nodule thickness>4.2 mm, and C/A ratio >0.62 is associated with malignancy. • This predictive model may be helpful for managing persistent SSNs between 5 and 20 mm in size.

Pulmonary Benign Ground-Glass Nodules: CT Features and Pathological Findings

Background

Some pulmonary ground-glass nodules (GGNs) are benign and frequently misdiagnosed due to lack of understanding of their CT characteristics. This study aimed to reveal the CT features and corresponding pathological findings of pulmonary benign GGNs to help improve diagnostic accuracy.

Patients and Methods

From March 2016 to October 2019, patients with benign GGNs confirmed by operation or follow-up were enrolled retrospectively. According to overall CT manifestations, GGNs were classified into three types: I, GGO with internal high-attenuation zone; II, nodules lying on adjacent blood vessels; and other type, lesions without obvious common characteristics. CT features and pathological findings of each nodule type were evaluated.

Results

Among the 40 type I, 25 type II, and 14 other type GGNs, 24 (60.0%), 19 (76.0%), and 10 (71.4%) nodules were resected, respectively. Type I GGNs were usually irregular (25 of 40, 62.5%) with only one high-attenuation zone (38 of 40, 95.0%) (main pathological components: thickened alveolar walls with inflammatory cells, fibrous tissue, and exudation), which was usually centric (24 of 40, 60.0%), having blurred margin (38 of 40, 95.0%), and connecting to blood vessels (32 of 40, 80.0%). The peripheral GGO (main pathological component: a small amount of inflammatory cell infiltration with fibrous tissue proliferation) was usually ill-defined (28 of 40, 70.0%). Type II GGNs (main pathological components: focal interstitial fibrosis with or without inflammatory cell infiltration) lying on adjacent vessel branches were usually irregular (19 of 25, 76.0%) and well defined (16 of 25, 64.0%) but showed coarse margins (15 of 16, 93.8%). Other type GGNs had various CT manifestations but their pathological findings were similar to that of type II.

Conclusion

For subsolid nodules with CT features manifested in type I or II GGNs, follow-up should be firstly considered in further management.

Semi-quantitative CT imaging in improving visualization of faint ground glass opacities seen in early/mild coronavirus (covid-19) cases

Background

Chest CT is an essential and simple diagnostic method for early detection of pulmonary changes in COVID-19 patients. Semi-quantitative technique depending on both visual and color coded images helps to improve the early detection of COVID-19 chest affection and thus help to control spread of infection.

Results

From first of May to July 15, 2020, 30 patients in Cairo, Egypt who have positive RT-PCR tests and positive pulmonary manifestation were included in our study, 26 patients (86.6%) with faint ground glass opacities were detected by both visual and color coded images, while in 4 patients (13.3%) were only visualized by color coded images and confirmed by CT density assessment.

Conclusion

The combined use of visual and color coded images enhance and improve the early detection of faint ground glass opacities seen in early COVID-19 affection.

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

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.

Morphological classification of pre-invasive lesions and early-stage lung adenocarcinoma based on CT images

OBJECTIVE

To retrospectively analyze the computed tomography (CT) features in patients with pre-invasive lesions and early-stage lung adenocarcinoma and to explore the correlation between tumor morphological changes and pathological diagnoses.

MATERIALS AND METHODS

CT morphological characteristics in 2106 patients with pre-invasive (stage 0) and early-stage (stage I) lung adenocarcinoma were analyzed; lesions were confirmed by surgical pathology. Based on the morphological characteristics, the lesions were divided into eight types: I (cotton ball, ground-glass nodules), II (solid fill), III (granular), IV (dendriform), V (bubble-like lucencies), VI (alveolate or honeycomb), VII (scar-like), and VIII (notched or umbilication). The different distributions of eight morphological types in pathological types of the lesions and subtypes of invasive adenocarcinoma were analyzed by chi-squared or Fisher's exact test. Correlation between the percentage of ground-glass opacity in the lesions and pathology types were analyzed by two-tailed Pearson's test.

RESULTS

A negative correlation was observed between the pathological types and proportion of ground-glass component in the lesions (p < 0.001 and r = - 0.583). Significant differences in morphological characteristics among various pathological types of pre-invasive lesions and early lung adenocarcinomas were observed (p < 0.05). Furthermore, among the different pathological subtypes of stage I invasive adenocarcinoma, the differences in their manifestation as morphological types I, II, III, and VI were statistically significant (p < 0.05).

CONCLUSION

The eight types of morphological classification of pre-invasive lesions and early-stage (stage 0 or stage I) lung adenocarcinoma has different pathological bases, and morphological classification may be useful for the diagnosis and differential diagnosis of lung adenocarcinoma.

KEY POINTS

• CT morphological classification of pre-invasive lesions and lung adenocarcinoma is intuitive. • CT morphological classification characterizes morphological changes of the entire lesion. • Different pathological types of lung adenocarcinoma have different morphological features.

Radiomic features from computed tomography to differentiate invasive pulmonary adenocarcinomas from non-invasive pulmonary adenocarcinomas appearing as part-solid ground-glass nodules

Objective

We aim to investigate radiomic imaging features extracted in computed tomography (CT) images to differentiate invasive pulmonary adenocarcinomas (IPAs) from non-IPAs appearing as part-solid ground-glass nodules (GGNs), and to incorporate significant radiomic features with other clinically-assessed features to develop a diagnostic nomogram model for IPAs.

Methods

This retrospective study was performed, with Institutional Review Board approval, on 88 patients with a total of 100 part-solid nodules (56 IPAs and 44 non-IPAs) that were surgically confirmed between February 2014 and November 2016 in the First Affiliated Hospital of China Medical University. Quantitative radiomic features were computed automatically on 3D nodule volume segmented from arterial-phase contrast-enhanced CT images. A set of regular risk factors and visually-assessed qualitative CT imaging features were compared with the radiomic features using logistic regression analysis. Three diagnostic models, i.e., a basis model using the clinical factors and qualitative CT features, a radiomics model using significant radiomic features, and a nomogram model combining all significant features, were built and compared in terms of receiver operating characteristic (ROC) curves. Decision curve analysis was performed for the nomogram model to explore its potential clinical benefit.

Results

In addition to three visually-assessed qualitative imaging features, another three quantitative features selected from hundreds of radiomic features were found to be significantly (all P<0.05) associated with IPAs. The diagnostic nomogram model showed a significantly higher performance [area under the ROC curve (AUC) =0.903] in differentiating IPAs from non-IPAs than either the basis model (AUC=0.853, P=0.0009) or the radiomics model (AUC=0.769, P<0.0001). Decision curve analysis indicates a potential benefit of using such a nomogram model in clinical diagnosis.

Conclusions

Quantitative radiomic features provide additional information over clinically-assessed qualitative features for differentiating IPAs from non-IPAs appearing as GGNs, and a diagnostic nomogram model including all these significant features may be clinically useful in preoperative strategy planning.

Lung nodules: A comprehensive review on current approach and management

In daily clinical practice, radiologists and pulmonologists are faced with incidental radiographic findings of pulmonary nodules. Deciding how to manage these findings is very important as many of them may be benign and require no further action, but others may represent early disease and importantly early-stage lung cancer and require prompt diagnosis and definitive treatment. As the diagnosis of pulmonary nodules includes invasive procedures which can be relatively minimal, such as bronchoscopy or transthoracic aspiration or biopsy, but also more invasive procedures such as thoracic surgical biopsies, and as these procedures are linked to anxiety and to cost, it is important to have clearly defined algorithms for the description, management, and follow-up of these nodules. Clear algorithms for the imaging protocols and the management of positive findings should also exist in lung cancer screening programs, which are already established in the USA and which will hopefully be established worldwide. This article reviews current knowledge on nodule definition, diagnostic evaluation, and management based on literature data and mainly recent guidelines.

Computed tomography and pathology evaluation of lung ground-glass opacity

The aim of this study was to investigate the pathogenesis of lung ground-glass opacity (GGO) and the diagnostic value of computed tomography scan for lung GGO. Computed tomography (CT) images of 106 lung GGO cases were analyzed retrospectively, and the type, location, size, structure, boundaries and surrounding lung fields were evaluated. There were 12 cases of GGO with a diameter <1.0 cm, 36 cases with diameter of 1.0-1.5 cm, 25 cases with diameter of 1.6-2.0 cm, 19 cases with diameter of 2.0-2.5 cm and 14 cases with diameter of 2.5-3.0 cm. There were 20 lesions with a round shape and 68 lesions with an oval shape. There were 56 lesions with spinous processes, 18 lesions with air bronchograms and 37 lesions with surrounding pleural indentation. The diagnosis and differential diagnosis of GGO would be improved with combined CT scan and pathology results.

CT characterization of different pathological types of subcentimeter pulmonary ground-glass nodular lesions

OBJECTIVE

To explore the CT characteristics of small lung nodules and improve the diagnosis of pulmonary ground-glass nodules less than 10  mm in size.

METHODS

We retrospectively analyzed CT images of 161 pulmonary nodules (less than 10  mm in size) with spiculation, lobulation, vacuoles, and pleural indentation and compared these images with pathological results or follow-up CT images. The relationships between the ground-glass nodules (GGNs) and blood vessels were observed. The GGN-vessel relationship was divided into four types, Type I (pass-by), Type II (pass-through), Type III (distorted/dilated), Type IV (complicated). The vessels traveling through a GGN were divided into three categories, category A (arteries), category B (veins), category C (arteries and veins).

RESULTS

161 GGNs were divided into three groups (benign group, pre-invasive group, and adenocarcinoma group) according to their pathological diagnosis. Significant differences in density of nodules were observed among the three different groups (p < 0.05). Significant differences in the shape (round/round-like or not) of the nodules were observed between the benign group and the pre-invasive group and between the pre-invasive group and the adenocarcinoma group (p < 0.05). No significant differences in the presence of vacuoles were observed between the benign group and the pre-invasive group or between the pre-invasive group and the adenocarcinoma group (p ＞0.05), but a significant difference was observed between the benign group and the adenocarcinoma group (p < 0.05). The differences in the vascularization of the lesions among the three groups were statistically significant (p < 0.05). No significant differences or correlations were observed between vascular categories and GGN groups (p > 0.05).

CONCLUSION

For subcentimeter nodules, mixed GGNs with vacuoles, well-defined border, combined with Type III or Type IV GGN-vessel relationship may strongly suggest malignant.

ADVANCES IN KNOWLEDGE

Previous studies mainly focused on CT diagnosis of pulmonary nodules (≤ 3  cm in diameter), but this study focused on ground-glass nodules less than 10  mm in diameter, which had not been fully studied. For subcentimeter nodules, mixed GGNs with vacuoles, well-defined border, especially the GGN-vessel relationship manifest as Type III (distorted/dilated) or Type IV (complicated) may strongly suggest malignant.

Contrast analysis of the relationship between the HRCT sign and new pathologic classification in small ground glass nodule-like lung adenocarcinoma

PURPOSE

To perform contrast analysis of the relationship between high-resolution computed tomography (HRCT) signs and new pathologic classification of small GGNs-like lung adenocarcinoma.

MATERIALS AND METHODS

The HRCT data from 145 pathologically confirmed cases of small GGNs of lung adenocarcinoma were analysed retrospectively. The 145 cases of GGNs were divided into pre-invasive (PI) group (n = 46), micro-invasive adenocarcinoma (MIA) group (n = 48), and invasive adenocarcinoma (IAC) group (n = 51). HRCT imaging sign of GGNs in each group was assessed and compared.

RESULTS

Significant differences in GGN size were found among the three groups (P < 0.05). The presence of a tumour-lung interface in the MIA and IAC groups was significantly higher than that in the PI group (P < 0.05), but no significant difference was found between the MIA and IAC groups. The presence of a pleural indentation sign in the IAC group was significantly higher than that in the other two groups (P < 0.05), but no significant difference was noted between the latter two groups. Significant differences were found in the lobulated and spicule signs among the three groups (P < 0.05). The presence of a microvascular sign in the MIA and IAC groups was significantly higher than that in the PI group (P < 0.05). No significant difference was found in the GGN density, vacuole sign, air bronchus sign and notch sign among the three groups.

CONCLUSIONS

The HRCT signs of GGNs could be used to differentiate among pre-invasive lesions, micro-invasive lesions and invasive lung adenocarcinoma.

[Value of CT Features on Differential Diagnosis of Pulmonary Subsolid Nodules and Degree of invasion Prediction in Pulmonary Adenocarcinoma]

背景与目的

亚实性肺结节为肺原发腺癌的常见计算机体层成像（computed tomography, CT）表现，依据其CT影像特征预测病理分型对确定临床治疗策略具有临床价值。本研究根据病理分类，回顾性分析良性、不典型腺瘤样增生（atypical adenomatous hyperplasia, AAH）/原位腺癌（adenocarcinoma in situ, AIS）/微侵袭性腺癌（minimally invasive adenocarcinoma, MIA）、侵袭性腺癌三组亚实性肺结节的CT征象，评估其在良恶性鉴别及恶性侵袭程度判别中的价值。

方法

回顾性分析106例经手术切除亚实性结节的CT征象。依据手术病理分为良性和恶性组，恶性组根据侵袭程度分为无/微侵袭组（AAH/AIS/MIA）、侵袭性腺癌组，测量结节大小、实性成分比例、瘤肺界面、形状、边缘、胸膜牵拉征、空气支气管征、结节内血管异常等CT征象。根据单因素分析（χ²检验、非参数检验Mann-Whitney U检验）结果筛选有统计学差异的变量，纳入Logistic回归多因素分析。

结果

Logistic回归分析显示清晰的瘤肺界面、空气支气管征以及结节内血管异常是恶性结节的重要预测指标，风险比分别为38.1（95%CI: 5.0-287.7; P < 0.01）、7.9（95%CI: 1.3-49.3; P=0.03）、7.2（95%CI: 1.4-37.0; P=0.02）。更大的实性成分所占比例是侵袭性腺癌与AAH/AIS/MIA组鉴别的重要指标，其风险比分别为1.04（95%CI: 1.01-1.06, P=0.01）。

结论

亚实性结节中出现清晰的瘤肺界面、空气支气管征、结节内血管异常提示其恶性概率增加。恶性结节中实性成分所占比例越大预示着侵袭性更高。

High-resolution Computed Tomography Features Distinguishing Benign and Malignant Lesions Manifesting as Persistent Solitary Subsolid Nodules

INTRODUCTION

We retrospectively investigated the high-resolution computed tomography features that distinguish benign lesions (BLs) from malignant lesions (MLs) appearing as persistent solitary subsolid nodules (SSNs).

MATERIALS AND METHODS

In 2015, the data from patients treated in our department with persistent solitary SSNs 5 to 30 mm in size were analyzed retrospectively. The demographic data and HRCT findings were analyzed and compared between those with BLs and MLs.

RESULTS

Of the 1934 SSNs, 94 were BLs and 1840 were MLs. One half of the MLs (920 SSNs) were randomly selected and analyzed. The BLs were classified into 2 subgroups: 28 pure ground-glass nodules (pGGNs) and 66 part-solid nodules (PSNs). After matching in each group, 56 pGGNs and 132 PSNs in the ML group were selected. In the pGGN subgroup, multivariate analysis found that a well-defined border (odds ratio [OR], 4.320; 95% confidence interval [CI], 1.534-12.168; P = .006; area under the curve, 0.705; 95% CI, 0.583-0.828; P = .002) and a higher average CT value (OR, 1.007; 95% CI, 1.001-1.013; P = .026; area under the curve, 0.715; 95% CI, 0.599-0.831; P = .001) favored the diagnosis of malignancy. In the PSN subgroup, multivariate analysis revealed that a larger size (OR, 1.084; 95% CI, 1.015-1.158; P = .016), a well-defined border (OR, 3.447; 95% CI, 1.675-7.094; P = .001), and a spiculated margin (OR, 2.735; 95% CI, 1.359-5.504; P = .005) favored the diagnosis of malignancy.

CONCLUSION

In pGGNs, a well-defined lesion border and a larger average CT value can be valuable discriminators to distinguish between MLs and BLs. In PSNs, a larger size, well-defined border, and spiculated margin had greater predictive value for malignancy.

Differential Diagnosis of Solitary Pulmonary Inflammatory Lesions and Peripheral Lung Cancers with Contrast-enhanced Computed Tomography

OBJECTIVES:

To clarify differences between solitary pulmonary inflammatory lesions and peripheral lung cancers with contrast-enhanced computed tomography.

METHODS:

In total, 64 and 132 patients with solitary pulmonary inflammatory masses/nodules and peripheral lung cancers, respectively, were enrolled in this study. Their computed tomographic findings were summarized and compared retrospectively.

RESULTS:

Compared with the peripheral lung cancers, the inflammatory lesions were located closer to the pleura (p<0.0001). The majority of the inflammatory lesions were patchy and oval-shaped (82.8%), whereas most of the tumors were lobulated (82.6%). Almost all the inflammatory cases were unclear (93.8%), whereas most of the tumors had spiculated margins (72.7%). Computed tomography values were significantly higher for the inflammatory lesions than for the cancers (p<0.0001). More than half of the inflammatory lesions had defined necrosis (59.3%). Furthermore, 49.2% of the cancers enhanced inhomogeneously, but only 24.6% had ill-defined necrosis or cavities. The peripheral zones of 98.4% of the inflammatory lesions and 72.7% of the tumors were unclear, with peripheral scattered patches (92.2%) and beam-shaped opacity (66.7%) being the most common findings, respectively. Adjacent pleural thickening was more frequent for the inflammatory lesions than the cancers (95.3% vs. 21.1%, p<0.0001), whereas pleural indentation was found in 67.4% of the subjects with cancer. In addition, hilar (p=0.034) and mediastinal (p=0.003) lymphadenopathy were more commonly detected in the cancers than in the inflammatory cases.

CONCLUSIONS:

Contrast-enhanced computed tomography findings for pulmonary inflammatory lesions and peripheral lung cancers were significantly different in many aspects. Developing a comprehensive understanding of these differences is helpful for directing their management.

Thin-section computed tomography-histopathologic comparisons of pulmonary focal interstitial fibrosis, atypical adenomatous hyperplasia, adenocarcinoma in situ, and minimally invasive adenocarcinoma with pure ground-glass opacity

OBJECTIVE

To retrospectively compare focal interstitial fibrosis (FIF), atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), and minimally invasive adenocarcinoma (MIA) with pure ground-glass opacity (GGO) using thin-section computed tomography (CT).

MATERIALS AND METHODS

Sixty pathologically confirmed cases were reviewed including 7 cases of FIF, 17 of AAH, 23of AIS, and 13 of MIA. All nodules kept pure ground glass appearances before surgical resection and their last time of thin-section CT imaging data before operation were collected. Differences of patient demographics and CT features were compared among these four types of lesions.

RESULTS

FIF occurred more frequently in males and smokers while the others occurred more frequently in female nonsmokers. Nodule size was significant larger in MIA (P<0.001, cut-off value=7.5mm). Nodule shape (P=0.045), margin characteristics (P<0.001), the presence of pleural indentation (P=0.032), and vascular ingress (P<0.001) were significant factors that differentiated the 4 groups. A concave margin was only demonstrated in a high proportion of FIF at 85.7% (P=0.002). There were no significant differences (all P>0.05) in age, malignant history, attenuation value, location, and presence of bubble-like lucency.

CONCLUSION

A nodule size >7.5mm increases the possibility of MIA. A concave margin could be useful for differentiation of FIF from the other malignant or pre-malignant GGO nodules. The presence of spiculation or pleural indentation may preclude the diagnosis of AAH.

Modified inflammation-based score as an independent malignant predictor in patients with pulmonary focal ground-glass opacity: a propensity score matching analysis

Pulmonary focal Ground-glass Opacities (fGGOs) would frequently be identified after widely implementation of low-dose computed tomography (LDCT) screening. Because of the high false-positive rate of LDCT, antibiotics should be regarded as advocates in clinical management for detected fGGOs. Retrospectively review consecutive patients with fGGOs between August 2006 and August 2012. Then, relative Glasgow prognostic score (GPS) were constructed in three different systems, traditional GPS system (tGPS), modified GPS system 1 (m1GPS), and modified GPS system 2 (m2GPS). Moreover, propensity score matching (PSM) was employed in balancing baseline covariates. After PSM, patients were matched and included in benign and malignant groups as 1:1 ratio. All reported parameters were balanced in both groups and no statistical differences could be detected. Finally, m1GPS exhibited remarkable different distribution between benign and malignant fGGOs. In detail, m1GPS 1 was more frequently observed in benign fGGOs nodules, while m1GPS 2 in malignant fGGOs nodules. Modified inflammation-based score was identified as an independent predictor of malignancies in patients with pulmonary fGGOs. Patients with m1GPS 1 were more likely to be benign fGGOs, while victims with m1GPS 2 more likely to be malignant.

Multi-slice computed tomography characteristics of solitary pulmonary ground-glass nodules: Differences between malignant and benign

Background

Ground‐glass nodules (GGNs), which are possible precursors of lung cancer, attract increasing attention. Many studies have attempted to identify the characteristic imaging features of GGNs for their qualitative diagnosis; however, the comprehension of GGNs remains controversial. We performed this study to identify imaging characteristics helpful to the differential diagnosis of solitary GGNs.

Methods

We retrospectively evaluated 112 solitary GGNs resected from 112 patients, pathologically examined after surgical resection. Imaging features of the GGNs, such as size, shape, a solid component, lobulation, spiculation, vascular convergence sign, pleural tag, and air cavity density, were assessed. Differences between malignant and benign nodules were analyzed using binary logistic regression analysis.

Results

Of the 112 GGNs, 82 were malignant and 30 were benign. A solid component, vascular convergence sign, and a larger diameter were risk factors for malignancy, with a sensitivity, specificity, and accuracy of 93.9%, 60.0%, and 84.8%, respectively. Lobulation, spiculation, air cavity densities, and pleural tags were also important indicators of malignancy, with positive predictive values of 93.5%, 83.3%, 91.7%, and 87.2%, respectively.

Conclusion

GGNs with a solid component, vascular convergence sign, and a larger diameter are highly suggestive of malignancy. The possibility of a neoplasm should also be considered in the case of GGNs that show lobulation, spiculation, air cavity densities, or pleural tags. To obtain a comprehensive and accurate analysis of the nodules, three‐dimensional reconstruction is highly recommended.

CT features of lung scar cancer

OBJECTIVE

To explore the CT features of lung scar cancer (LSC).

METHODS

CT images of 41 LSCs and 66 non-LSCs were retrospectively compared in terms of location, size, shape, border, speculation, lobulation, pleural indentation, surrounding ground-glass opacification (sGGO), vessel convergence, vacuolation, calcification and satellite opacification.

RESULTS

Thirty-eight LSCs were histopathologically identified as adenocarcinoma. The LSCs and non-LSCs were located 8.73±8.65 and 12.55±10.67 mm from the pleura, respectively. The mean lesion sizes (3-D ratios) in the initial LSC, pre-surgical LSC and non-LSC images were 24.28±6.29 (0.33±0.65), 32.23±8.14 (0.60±0.18) and 23.24±3.73 (0.35±0.61) mm, respectively. The initial and pre-surgical LSC images showed significant differences in speculation and sGGO (P<0.05). Significant differences were also noted in vacuolation, vessel convergence and sGGO between the pre-surgical LSC and the non-LSC images (P<0.05) and in vacuolation between the initial LSC and the non-LSC images (P<0.05).

CONCLUSIONS

Despite similar CT features of LSCs and non-LSCs, the early detection and diagnosis of LSCs is possible by studying scar-tissue changes such as enlargement and sGGO associated with well-defined lesion borders in follow-up CT images.

Morphological factors differentiating between early lung adenocarcinomas appearing as pure ground-glass nodules measuring ≤10 mm on thin-section computed tomography

Background

We aimed to compare the morphological features of pure ground-glass nodules (GGNs; diameter, ≤10 mm) on thin-section computed tomography (TSCT) with their histopathological results in order to identify TSCT features differentiating between atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA).

Methods

Between January and December 2013, 205 pure GGNs with a diameter ≤10 mm on TSCT were pathologically confirmed as AAH (40), AIS (95) or MIA (70) lesions. The patients’ age and sex were recorded. The morphological features were evaluated, and maximum diameter and mean CT value were measured for each nodule. F test, Pearson χ² test, Fisher exact test and multinomial logistic regression analysis were used to identify factors differentiating between AAH, AIS and MIA. Receiver operating characteristic (ROC) curve analysis was performed for maximum diameter and mean CT value.

Results

F test, Pearson χ² test and Fisher exact test revealed that maximum diameter (P <0.00001), mean CT value (P =0.005), type of interface (P =0.005) and presence of air bronchograms (P =0.02, n =44) significantly differed among the AAH, AIS and MIA groups. Multinomial logistic regression analysis showed that maximum diameter ≥6.5 mm, a well-defined and coarse interface indicated AIS or MIA rather than AAH; air bronchograms differentiated MIA from AAH; but these parameters did not differentiate between AIS and MIA. A mean CT value less than −520 HU indicated AAH or AIS rather than MIA, but did not differentiate between AAH and AIS.

Conclusions

In the case of pure GGNs measuring ≤10 mm, a maximum diameter ≥6.5 mm, a well-defined and coarse interface indicate AIS or MIA rather than AAH; an air bronchogram can differentiate MIA from AAH. A mean CT value less than −520 HU indicates AAH or AIS rather than MIA.

Clinical model to estimate the pretest probability of malignancy in patients with pulmonary focal Ground-glass Opacity

BACKGROUND

Effective strategies for managing patients with pulmonary focal Ground-glass Opacity (fGGO) depend on the pretest probability of malignancy. Estimating a clinical probability of malignancy in patients with fGGOs can facilitate the selection and interpretation of subsequent diagnostic tests. METHODS : Data from patients with pulmonary fGGO lesions, who were diagnosed at Sun Yat-sen University Cancer Center, was retrospectively collected. Multiple logistic regression analysis was used to identify independent clinical predictors for malignancy and to develop a clinical predictive model to estimate the pretest probability of malignancy in patients with fGGOs.

RESULTS

 One hundred and sixty-five pulmonary fGGO nodules were detected in 128 patients. Independent predictors for malignant fGGOs included a history of other cancers (odds ratio [OR], 0.264; 95% confidence interval [CI], 0.072 to 0.970), pleural indentation (OR, 8.766; 95% CI, 3.033-25.390), vessel-convergence sign (OR, 23.626; 95% CI, 6.200 to 90.027) and air bronchogram (OR, 7.41; 95% CI, 2.037 to 26.961). Model accuracy was satisfactory (area under the curve of the receiver operating characteristic, 0.934; 95% CI, 0.894 to 0.975), and there was excellent agreement between the predicted probability and the observed frequency of malignant fGGOs.

CONCLUSIONS

We have developed a predictive model, which could be used to generate pretest probabilities of malignant fGGOs, and the equation could be incorporated into a formal decision analysis.

[Multiple focal pure ground-glass opacities on HRCT images: clinical significance in patients with lung cancer]

BACKGROUND AND OBJECTIVE

Some cases of lung cancer in addition to a primary tumor are associated with multiple pure ground-glass opacities (pGGOs). The objective of this study is to evaluate the clinical significance of multiple pGGOs on CT images of patients with lung cancer. The number, size, distribution, and morphological characteristics of the pGGOs were evaluated. Serial changes in pGGOs that were not surgically resected were analyzed at follow-up CT.

METHODS

The cases of 25 patients with proven lung cancer and associated multiple pGGOs on CT images were retrospectively reviewed.

RESULTS

In total, 207 pGGOs were detected. The size of the opacities ranged from 2 mm to 31 mm in largest diameter. Lung cancer and pGGOs were seen in the same lobe and/or in other lobes. Of the lesions, 183 (88.4%) had a round shape or well-defined border. Histological findings were obtained for 17 lesions representing 87 pGGOs that were surgically resected, namely, 13 atypical adenomatous hyperplasias, 3 bronchioloalveolar carcinomas, and 1 focal fibrosis. Of the 120 pGGOs followed up with CT for a median duration of 61.5 months, 113 (94.2%) retained their size, 1 decreased in size, and 6 disappeared.

CONCLUSIONS

The size of most pGGOs associated with lung cancer did not change during the follow-up period. Most of the lesions histologically diagnosed were atypical adenomatous hyperplasias or bronchioloalveolar carcinomas. The results justify the therapeutic strategy of resecting the primary tumor without therapeutic intervention in the remaining pGGOs.

Multidetector CT features of pulmonary focal ground-glass opacity: differences between benign and malignant

OBJECTIVE

To evaluate different features between benign and malignant pulmonary focal ground-glass opacity (fGGO) on multidetector CT (MDCT).

METHODS

82 pathologically or clinically confirmed fGGOs were retrospectively analysed with regard to demographic data, lesion size and location, attenuation value and MDCT features including shape, margin, interface, internal characteristics and adjacent structure. Differences between benign and malignant fGGOs were analysed using a χ(2) test, Fisher's exact test or Mann-Whitney U-test. Morphological characteristics were analysed by binary logistic regression analysis to estimate the likelihood of malignancy.

RESULTS

There were 21 benign and 61 malignant lesions. No statistical differences were found between benign and malignant fGGOs in terms of demographic data, size, location and attenuation value. The frequency of lobulation (p=0.000), spiculation (p=0.008), spine-like process (p=0.004), well-defined but coarse interface (p=0.000), bronchus cut-off (p=0.003), other air-containing space (p=0.000), pleural indentation (p=0.000) and vascular convergence (p=0.006) was significantly higher in malignant fGGOs than that in benign fGGOs. Binary logistic regression analysis showed that lobulation, interface and pleural indentation were important indicators for malignant diagnosis of fGGO, with the corresponding odds ratios of 8.122, 3.139 and 9.076, respectively. In addition, a well-defined but coarse interface was the most important indicator of malignancy among all interface types. With all three important indicators considered, the diagnostic sensitivity, specificity and accuracy were 93.4%, 66.7% and 86.6%, respectively.

CONCLUSION

An fGGO with lobulation, a well-defined but coarse interface and pleural indentation gives a greater than average likelihood of being malignant.

Pulmonary malignant focal ground-glass opacity nodules and solid nodules of 3cm or less: comparison of multi-detector CT features

INTRODUCTION

To evaluate the different multi-detector computed tomography (MDCT) features between pulmonary malignant focal ground-glass opacity (fGGO) nodules and solid nodules of 3cm or less in diameter.

METHODS

One hundred and five malignant solid nodules and 48 malignant fGGOs confirmed by pathology were retrospectively analysed with regard to the patient's demographic data, nodule size and MDCT features (shape, margin, interface, internal characteristics and adjacent structure). Differences were analysed using the Fisher exact test or Mann-Whitney U-test.

RESULTS

The male to female ratio of patients with malignant solid nodules (60:45) was higher than that with malignant fGGOs (18:30) (P<0.05). There was no significant difference in either patient's age (P>0.05) or nodule size (P>0.05). The frequency of irregular shape (4% vs. 21%), spiculation (57% vs. 40%), vacuole sign (11% vs. 52%) and natural air bronchograms (0% vs. 24%) was significantly different between malignant solid nodules and fGGOs. No differences were found in the frequency of lobulation, cusp angle, spine-like process, interface and adjacent structure between the two groups (P>0.05).

CONCLUSION

Malignant fGGOs and solid nodules showed mostly similar MDCT features. For malignant fGGOs, the frequency of irregular shape, vacuole sign and natural air bronchograms was higher than that in solid nodules, but the frequency of spiculation was lower than that in solid nodules.

Dose reduction strategies for thoracic multidetector computed tomography: background, current issues, and recommendations

This review will summarize the current background knowledge about radiation exposure related to thoracic computed tomography (CT). It will also review the historical development in this area. This will be followed by a summary of current efforts to reduce dose with respect to predefined clinical indications. Finally, the review will indicate future strategies for further dose reduction in thoracic CT imaging and give practical recommendations for everyday use.

[Localized pure or mixed ground-glass lung opacities]

Localized ground-glass opacities (GGOs) have been recently individualized and account for between 2.9% and 19% of all pulmonary nodules detected in high-risk patients included in CT screening series for lung cancer. These opacities, nodular, lobular or flat, correspond to benign lesions (localised infectious and inflammatory diseases, focal interstitial fibrosis, and atypical alveolar hyperplasia) or malignant lesions (bronchioloalveolar carcinoma, early-stage adenocarcinoma and sometimes metastases). Localized GGOs are more likely to be malignant than solid nodules and prognosis is related to the percentage of the ground-glass component. However, doubling time of pure localized malignant GGOs is longer than mixed localized malignant GGOs and even longer than the doubling time of solid malignant nodules. Therefore, localized GGOs warrant a dedicated diagnostic workup.

Lung cancer with localized ground-glass attenuation represents early-stage adenocarcinoma in nonsmokers

BACKGROUND

Studies of lung cancer showing localized ground-glass attenuation (GGA) on thin-section computed tomography (TSCT) have been limited to resected stage IA adenocarcinomas. This study aimed to clarify the features of localized GGA cancer as a distinct clinicoradiological entity through a survey of lung cancers of all types.

METHODS

From 2000 through 2002, 492 patients with newly diagnosed stage I-IV lung cancer underwent TSCT at a single institution. The tumors were semiquantitatively classified into four groups on the basis of GGA area as a percentage of the whole tumor shadow (GGA ratio) on TSCT images: 100%, 99-50%, 49-1%, and 0%. The relationship between clinicopathological data and the GGA ratio, predictors of the presence of GGA, survival data, and prognostic factors were evaluated retrospectively.

RESULTS

All localized GGA cancers were adenocarcinomas (p < 0.05). A GGA component was not found in patients with advanced cancer (p < 0.05). GGA cancer was related to nonsmoking status (Odds ratio 6.17, p < 0.05). A threshold tumor size of 30 mm in GGA cancer (hazard ratio, 2.86; p < 0.01) and the GGA ratio (hazard ratio, 4.17; p < 0.01) were independent prognostic factors. Survival rates were higher in patients with a GGA ratio > or = 50% and stage IB lung cancer than in patients with a GGA ratio < 50% and stage IA lung cancer.

CONCLUSION

Localized GGA cancer, with presurgical prognostic factors of tumor size and GGA ratio, represents early-stage lung adenocarcinoma in nonsmokers.

Focal interstitial fibrosis manifesting as nodular ground-glass opacity: thin-section CT findings

The purpose of this study was to describe the thin-section computed tomographic (CT) features of focal interstitial fibrosis manifesting as nodular ground-glass opacity (GGO) and its changes during follow-up. The thin-section CT findings of pathologically proven focal interstitial fibrosis manifesting as nodular GGO were retrospectively evaluated in nine patients (five women and four men; mean age, 59.3 years; age range, 34-81 years). The thin-section CT findings of each lesion were analyzed for multiplicity, location, shape, margin characteristics, pleural retraction or vascular convergence, size and internal attenuation, lesion internal features and lesion changes on follow-up CT scans (mean 90 days, range 5 to 215 days). All lesions manifested as a solitary nodular GGO (100%), and seven of the nine lesions (77.8%) were located in the upper lobe. Focal interstitial fibrosis was round or oval in shape in five cases (55.6%), complex in shape in three cases (33.3%) and polygonal in one case (11.1%). Lesion margins were smooth in five patients (55.6%), irregular in three (33.3%) and spiculated in one (11.1%). Pleural retraction or vascular convergence was present in two patients (22.2%). Lesions measured 4.8 mm to 25.5 mm (mean, 11.5 mm) and had attenuations ranging from -151 to -699 HU (mean, -514.7 HU). Eight (88.9%) manifested as pure nodular GGOs and one as mixed GGO with a spiculated margin. In all patients, no lesion changes were observed in follow-up CT scans. Focal interstitial fibrosis manifesting as nodular GGO usually presents as a solitary nodule with pure GGO on thin-section CT, which does not change significantly during follow-up.

Management of an incidentally discovered pulmonary nodule

The incidental finding of a pulmonary nodule on computed tomography (CT) is becoming an increasingly frequent event. The discovery of such a nodule should evoke the possibility of a small bronchogenic carcinoma, for which excision is indicated without delay. However, invasive diagnostic procedures should be avoided in the case of a benign lesion. The objectives of this review article are: (1) to analyze the CT criteria defining benign nodules, nodules of high suspicion of malignancy and indeterminate nodules, (2) to analyze the diagnostic performances and limitations of complementary investigations requested to characterize indeterminate lung nodules, (3) to review the criteria permitting to assess the probability of malignancy of indeterminate nodules and (4) to report on the new guidelines provided by the Fleischner Society for the management of small indeterminate pulmonary nodules, according to their prior probability of malignancy.