High-resolution CT analysis of small peripheral lung adenocarcinomas revealed on screening helical CT

Morphologic Features of Invasion in Lung Adenocarcinoma: Diagnostic Pitfalls

Reproducibility of pulmonary invasive adenocarcinoma diagnosis is poor when applying the World Health Organization (WHO) classification. In this article, we aimed first to explain by 3-dimensional morphology why simple pattern recognition induces pitfalls for the assessment of invasion as applied in the current WHO classification of pulmonary adenocarcinomas. The underlying iatrogenic-induced morphologic alterations in collapsed adenocarcinoma in situ overlap with criteria for invasive adenocarcinoma. Pitfalls in seemingly acinar and papillary carcinoma are addressed with additional cytokeratin 7 and elastin stains. In addition, we provide more stringent criteria for a better reproducible and likely generalizable classification.

Quantitative analysis of lung lesions using unenhanced chest computed tomography images

INTRODUCTION

Chest radiograph and computed tomography (CT) scans can accidentally reveal pulmonary nodules. Malignant and benign pulmonary nodules can be difficult to distinguish without specific imaging features, such as calcification, necrosis, and contrast enhancement. However, these lesions may exhibit different image texture characteristics which cannot be assessed visually. Thus, a computer-assisted quantitative method like histogram analysis (HA) of Hounsfield unit (HU) values can improve diagnostic accuracy, reducing the need for invasive biopsy.

METHODS

In this exploratory control study, nonenhanced chest CT images of 20 patients with benign (10) and cancerous (10) lesion were selected retrospectively. The appearances of benign and malignant lesions were very similar in chest CT images, and only pathology report was used to discriminate them. Free hand region of interest (ROI) was inserted inside the lesion for all slices of each lesion. Mean, minimum, maximum, and standard deviations of HU values were recorded and used to make HA.

RESULTS

HA showed that the most malignant lesions have a mean HU value between 30 and 50, a maximum HU less than 150, and a minimum HU between -30 and 20. Lesions outside these ranges were mostly benign.

CONCLUSION

Quantitative CT analysis may differentiate malignant from benign lesions without specific malignancy patterns on unenhanced chest CT image.

Association between quantitative spectral CT parameters, Ki-67 expression, and invasiveness in lung adenocarcinoma manifesting as ground-glass nodules

BACKGROUND

Few studies about lung ground-glass nodules (GGNs) have been done using non-enhancement spectral computed tomography (CT) imaging.

PURPOSE

To examine the association between spectral CT parameters, Ki-67 expression, and invasiveness in lung adenocarcinoma manifesting as GGNs.

MATERIAL AND METHODS

Spectral CT parameters were analyzed in 106 patients with lung GGNs. The Ki-67 labeling index (Ki-67 LI) was measured, and patients were divided into low expression and high expression groups according to the number of positive-stained cells (low expression ≤10%; high expression >10%). Spectral CT parameters were compared between low and high expression groups. The correlation between spectral CT parameters and Ki-67 LI was estimated by Spearman correlation analysis. Cases were divided into a preinvasive and minimally invasive adenocarcinoma (MIA) group (atypical adenomatous hyperplasia, adenocarcinoma in situ, and MIA) and invasive adenocarcinoma (IA) group. Spectral CT parameters were compared between the two groups. The diagnostic performance was evaluated using receiver operating characteristic analysis.

RESULTS

There were significant differences in water concentration of lesions (WCL) and monochromatic CT values between the low and high expression groups. CT 40 keV had the highest correlation coefficient with Ki-67 LI. WCL and monochromatic CT values were significantly higher in the IA group than in the pre/MIA group. The value of area under the curve of CT 40 keV was 0.946 (95% confidence interval=0.905-0.988) for differentiating the two groups; the cutoff was -280.66 Hu.

CONCLUSION

Spectral CT is an effective non-invasive method for the prediction of proliferation and invasiveness in lung adenocarcinoma manifesting as GGNs.

A predictive model based on ground glass nodule features via high-resolution CT for identifying invasiveness of lung adenocarcinoma

Objective

The morphology of ground-glass nodule (GGN) under high-resolution computed tomography (HRCT) has been suggested to indicate different histological subtypes of lung adenocarcinoma (LUAD); however, existing studies only include the limited number of GGN characteristics, which lacks a systematic model for predicting invasive LUAD. This study aimed to construct a predictive model based on GGN features under HRCT for LUAD.

Methods

A total of 301 surgical LUAD patients with HRCT-confirmed GGN were enrolled, and their GGN-related features were assessed by 2 individual radiologists. The pathological diagnosis of the invasive LUAD was established by pathologic examination following surgery (including 171 invasive and 130 non-invasive LUAD patients).

Results

GGN features including shorter distance from pleura, larger diameter, area and mean CT attenuation, more heterogeneous uniformity of density, irregular shape, coarse margin, not defined nodule-lung interface, spiculation, pleural indentation, air bronchogram, vacuole sign, vessel changes, lobulation were observed in invasive LUAD patients compared with non-invasive LUAD patients. After adjustment by multivariate logistic regression model, GGN diameter (OR = 1.490, 95% CI, 1.326-1.674), mean CT attenuation (OR = 1.007, 95% CI, 1.004-1.011) and heterogeneous uniformity of density (OR = 3.009, 95% CI, 1.485-6.094) were independent risk factors for invasive LUAD. In addition, a predictive model integrating these three independent GGN features was established (named as invasion of lung adenocarcinoma by GGN features (ILAG)), and receiver-operating characteristic curve illustrated that the ILAG model presented good predictive value for invasive LUAD (AUC: 0.919, 95% CI, 0.889-0.949).

Conclusions

ILAG predictive model integrating GGN diameter, mean CT attenuation and heterogeneous uniformity of density via HRCT shows great potential for early estimation of LUAD invasiveness.

Are Incidental Minute Pulmonary Nodules Ultimately Determined to Be Metastatic Nodules in Esophageal Cancer Patients?

PURPOSE

Esophageal cancer patients may simultaneously have resectable esophageal cancer and undiagnosable incidental minute solid pulmonary nodules. While the latter is rarely metastatic, only a few studies have reported on the outcomes of such nodules after surgery. In this retrospective study, we assessed the incidence of such nodules, the probability that they are ultimately metastatic nodules, and the prognosis of patients after esophagectomy according to the metastatic status of the nodules.

METHODS

Data of 398 patients who underwent esophagectomy for resectable esophageal cancer between January 2012 and December 2016 were collected. We reviewed computed tomography (CT) images from the first visit and searched for incidental minute pulmonary nodules <10 mm in size. We followed the outcomes of these nodules and compared the characteristics of metastatic and nonmetastatic nodules. We also assessed the prognosis of patients whose minute pulmonary nodules were metastatic.

RESULTS

Among the patients who underwent esophagectomy, 149 (37.4%) had one or more minute pulmonary nodules, with a total of 285 nodules. Thirteen (4.6%) of these nodules in 12 (8.1%) patients were ultimately diagnosed as being metastatic. Thirteen (8.7%) patients experienced recurrence at a different location from where the nodules were originally identified. Characteristics of the metastatic nodules were not unique in terms of size, SUVmax, or location in the lungs. Two-year and 5-year overall survival rates of patients whose nodules were metastatic were 64.2 and 32.1%, respectively.

CONCLUSION

The rate of minute pulmonary nodules which were ultimately metastatic was 4.6%. Our findings suggest that esophagectomy followed by the identification of minute pulmonary nodules is an acceptable strategy even if the nodules cannot be diagnosed as being metastatic on the first visit CT due to their small size.

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.

A clinicopathological study of lung adenocarcinomas with pure ground-glass opacity > 3 cm on high-resolution computed tomography

OBJECTIVES

This study aimed to discuss whether a diameter of 3 cm is a threshold for diagnosing lung adenocarcinomas presenting with radiological pure ground-glass mass (PGGM, pure ground-glass opacity > 3 cm) as adenocarcinomas in situ or minimally invasive adenocarcinomas (AIS-MIAs). Another aim was to identify CT features and patient prognosis that differentiate AIS-MIAs from invasive adenocarcinomas (IACs) in patients with PGGMs.

METHODS

From June 2007 to October 2015, 69 resected PGGMs with HRCT and followed up for ≥ 5 years were included in this study and divided into AIS-MIA (n = 13) and IAC (n = 56) groups. Firth's logistic regression model was performed to determine CT characteristics that helped distinguish IACs from AIS-MIAs. The discriminatory power of the significant predictors was tested with the area under the receiver operating characteristics curve (AUC). Disease recurrence was also evaluated.

RESULTS

Univariable and multivariable analyses identified that the mean CT attenuation (odds ratio: 1.054, p = 0.0087) was the sole significant predictor for preoperatively discriminating IACs from AIS-MIAs in patients with PGGMs. The CT attenuation had an excellent differentiating accuracy (AUC: 0.981), with the optimal cut-off value at -600 HU (sensitivity: 87.5%; specificity: 100%). Additionally, no recurrence was observed in patients manifesting with PGGMs > 3 cm, and the 5-year recurrence-free survival and overall survival rates were both 100%, even in cases of IAC.

CONCLUSIONS

This study demonstrated that PGGMs > 3 cm could still be AIS-MIAs. When PGGMs are encountered in clinical practice, the CT value may be the only valuable parameter to preoperatively distinguish IACs from AIS-MIAs.

KEY POINTS

• Patients with pure ground-glass opacity > 3 cm in diameter are rare but can be diagnosed as adenocarcinomas in situ or minimally invasive adenocarcinomas. • The mean CT attenuation is the sole significant CT parameter that differentiates invasive adenocarcinoma from adenocarcinoma in situ or minimally invasive adenocarcinoma in patients with pure ground-glass opacity > 3 cm. • Lung adenocarcinoma with pure ground-glass opacity > 3 cm has an excellent prognosis, even in cases of invasive adenocarcinoma.

Association of postoperative recurrence with radiological and clinicopathological features in patients with stage IA-IIA lung adenocarcinoma

OBJECTIVES

To retrospectively investigate whether radiological and clinicopathological characteristics were associated with the presence of stage IA-IIA lung adenocarcinoma in patients at high risk for a postoperative recurrence.

MATERIALS AND METHODS

Three hundred twelve patients with biopsy-proven node-negative early-stage (IA-IIA) lung adenocarcinoma met the inclusion criteria for this study. Demographics data and histopathological findings were collected from medical records. Computed tomography (CT) performed approximately 1 month before surgery was manually scored using 23 CT descriptors. Univariate analyses were applied to demonstrate an association between clinicopathological and radiological features and 2-/5-year recurrences. Multivariate logistic regression was performed to assess the ability of radiological and clinicopathological features to discriminate low and high-risk factors for recurrence. A ROC curve was used to evaluate prediction performance.

RESULTS

Univariate analysis revealed that the 2-year recurrence was associated with six radiological features and two clinicopathological features, while 5-year recurrence was associated with five radiological features and two clinicopathological features. A multivariate logistic regression model of combined clinicopathological and radiological features showed that stage IIA (OR = 2.87), solid texture (solid part > 50 %: OR = 4.81; solid part = 100 %: OR = 3.61), pleural attachment (OR = 3.97) and bronchovascular bundle thickening (OR = 2.16) were associated with the independent predictors of 2-year recurrence, and stage IIA (OR = 3.52), solid texture (solid part > 50 %: OR = 3.56; solid part = 100 %: OR = 2.44) and pleural attachment (OR = 4.57) were associated with 5-year recurrence. Combined radiological and clinicopathological features could be significant indicators of 2- and 5-year recurrences (AUC = 0.784 and AUC = 0.815, respectively).

CONCLUSIONS

The combination of radiological and clinicopathological features has the potential to help predict postoperative recurrence in patients with stage IA-IIA lung adenocarcinomas and guide oncologists and patients whether to undergo additional treatment after surgery.

Predicting recurrence of non-small cell lung cancer based on mean computed tomography value

Background

The aim of this study was to assess the ability of using mean computed tomography (mCT) values to predict non-small cell lung cancer (NSCLC) tumor recurrence.

Methods

A retrospective study was conducted on 494 patients with stage IA NSCLC. Receiver operating characteristics analysis was used to assess the ability to use mCT value, C/T ratio, tumor size, and SUV to predict tumor recurrence. Multiple logistic regression analyses were performed to determine the independent variables for the prediction of tumor recurrence.

Results

The m-CT values were − 213.7 ± 10.2 Hounsfield Units (HU) for the recurrence group and − 594.1 ± 11.6 HU for the non-recurrence group (p < 0.0001). Recurrence occurred in 45 patients (9.1%). The tumor recurrence group was strongly associated with a high CT attenuation value, high C/T ratio, large solid tumor size, and SUV. The diagnostic value of mCT value was more accurate than the C/T ratio, excluding the pure ground-glass opacity and pure solid (0 < C/T ratio < 100) groups. The SUV and mCT are independent predictive factors of tumor recurrence.

Conclusions

The evaluation of mCT values was useful for predicting recurrence after the limited resection of small-sized NSCLC, and may potentially contribute to the selection of suitable treatment strategies.

Use of relative CT values to evaluate the invasiveness of pulmonary subsolid nodules in patients with emphysema

Background

Lung cancer is a major cause of death, and adenocarcinoma is the most common histologic subtype. Precise diagnosis and treatment of invasive adenocarcinoma (IAC) can substantially improve the survival of patients. However, early-stage adenocarcinomas frequently appear as subsolid nodules (SSN) on computed tomography (CT), and the optimal cut-off CT value for differentiating the invasiveness of SSNs in emphysematous patients is unclear.

Methods

High-resolution CT targeted scans of 187 pulmonary SSNs in 175 patients with emphysema as confirmed by surgery and histology were retrospectively reviewed. The mean CT value, the relative CT (rCT) values of 1 (nodule CT value - lung CT value), and 2 (nodule CT value/lung CT value), and the size of the SSNs were measured and calculated. The differentiating performance of the CT values between pre-invasive and invasive tumors was evaluated using a receiver operating characteristic (ROC) curve.

Results

Significant differences were found in the rCT values of 1 and 2 among pure ground-glass nodules (GGNs) with different levels of invasiveness, in the rCT values of 1 and 2 for the ground-glass component (GGC) and the mean CT value of the solid component (SC) of part-solid nodules (PSNs) between minimally invasive adenocarcinoma (MIA) and IAC (all P<<0.05). The size was significantly different among pure GGNs with different invasiveness (P<0.05). The cut-off rCT values of 1, 2 and nodule size for differentiating between pre-invasive and invasive pure GGNs were 293.82 [sensitivity 58.0%, specificity 94.7%; area under the curve (AUC) 0.783], 0.68 (sensitivity 89.5%, specificity 58.0%, AUC 0.742) and 1.10 cm (sensitivity 74.0%, specificity 79.0%, AUC 0.796), respectively. The AUCs of combining rCT values 1 and 2 with the size of nodule were 0.795 (sensitivity 62.5%, specificity 89.5%) and 0.845 (sensitivity 71.6%, specificity 89.5%) respectively. There were no significant differences in the mean CT values between pure GGNs with different levels of invasiveness and between the GGC of PSNs of MIA and IAC.

Conclusions

In patients with emphysema, the rCT values are more useful than the mean CT values for differentiating between SSNs with different invasiveness and can be valuable for patient management.

A case of lymphocytic interstitial pneumonia presenting with a ground glass nodule as an initial finding

A 65-year-old woman had a ground glass nodule, which was suspicious for lung cancer, in her right lung S⁶ by chest computed tomography. For diagnosis, video-assisted thoracoscopic surgery was performed, and the specimen showed a pathological pattern of lymphocytic interstitial pneumonia (LIP). Four years after surgery, new localized ground glass shadows gradually increased on the base of the lung. However, because she had no respiratory symptoms and had normal respiratory function, she was observed with no medication. Subsequently, no other underlying diseases associated with LIP developed. The ground glass nodule was the initial lesion of LIP.

HRCT imaging features in representative imported cases of 2019 novel coronavirus pneumonia

With the spread of novel coronavirus (2019-nCoV) pneumonia, chest high-resolution computed tomography (HRCT) has been one of the key diagnostic tools. To achieve early and accurate diagnostics, determining the radiological characteristics of the disease is of great importance. In this small scale research we retrospectively reviewed and selected six cases confirmed with 2019-nCoV infection in West China Hospital and investigated their initial and follow-up HRCT features, along with the clinical characteristics. The 2019-nCoV pneumonia basically showed a multifocal or unifocal involvement of ground-glass opacity (GGO), sometimes with consolidation and fibrosis. No pleural effusion or lymphadenopathy was identified in our presented cases. The follow-up CT generally demonstrated mild to moderate progression of the lesion, with only one case showing remission by the reducing extent and density of the airspace opacification.

A Novel Computer-Aided Diagnosis Scheme on Small Annotated Set: G2C-CAD

Purpose

Computer-aided diagnosis (CAD) can aid in improving diagnostic level; however, the main problem currently faced by CAD is that it cannot obtain sufficient labeled samples. To solve this problem, in this study, we adopt a generative adversarial network (GAN) approach and design a semisupervised learning algorithm, named G2C-CAD.

Methods

From the National Cancer Institute (NCI) Lung Image Database Consortium (LIDC) dataset, we extracted four types of pulmonary nodule sign images closely related to lung cancer: noncentral calcification, lobulation, spiculation, and nonsolid/ground-glass opacity (GGO) texture, obtaining a total of 3,196 samples. In addition, we randomly selected 2,000 non-lesion image blocks as negative samples. We split the data 90% for training and 10% for testing. We designed a DCGAN generative adversarial framework and trained it on the small sample set. We also trained our designed CNN-based fuzzy Co-forest on the labeled small sample set and obtained a preliminary classifier. Then, coupled with the simulated unlabeled samples generated by the trained DCGAN, we conducted iterative semisupervised learning, which continually improved the classification performance of the fuzzy Co-forest until the termination condition was reached. Finally, we tested the fuzzy Co-forest and compared its performance with that of a C4.5 random decision forest and the G2C-CAD system without the fuzzy scheme, using ROC and confusion matrix for evaluation.

Results

Four different types of lung cancer-related signs were used in the classification experiment: noncentral calcification, lobulation, spiculation, and nonsolid/ground-glass opacity (GGO) texture, along with negative image samples. For these five classes, the G2C-CAD system obtained AUCs of 0.946, 0.912, 0.908, 0.887, and 0.939, respectively. The average accuracy of G2C-CAD exceeded that of the C4.5 random decision tree by 14%. G2C-CAD also obtained promising test results on the LISS signs dataset; its AUCs for GGO, lobulation, spiculation, pleural indentation, and negative image samples were 0.972, 0.964, 0.941, 0.967, and 0.953, respectively.

Conclusion

The experimental results show that G2C-CAD is an appropriate method for addressing the problem of insufficient labeled samples in the medical image analysis field. Moreover, our system can be used to establish a training sample library for CAD classification diagnosis, which is important for future medical image analysis.

Peripheral blood telomere alterations in ground glass opacity (GGO) lesions may suggest malignancy

A ground glass opacity (GGO) lung lesion may represent early stage adenocarcinoma, which has an excellent prognosis upon prompt surgical resection. However, GGO lesions have broad differential diagnoses, including both benign and malignant lesions. Our objective was to study telomere length and telomerase activity in patients with suspected lung cancer in which GGO was the predominant radiographic feature. Knowledge of telomere biology may help distinguish malignant from benign radiographic lesions and guide risk assessment of these lesions. Peripheral blood samples were taken from 22 patients with suspected adenocarcinoma with the GGO radiographic presentation. Multidisciplinary discussion confirmed the need for surgery in all cases. We used an age and gender‐matched group without known lung disease as a control. Telomere length and aggregates were assessed by quantitative fluorescence in situ hybridization (QFISH) and quantitative PCR. Cell senescence was evaluated by senescence‐associated heterochromatin foci. Subjects with GGO lesions had a higher percentage of lymphocytes with shorter telomeres (Q‐FISH, P = 0.003). Furthermore, relative telomere length was also reduced among the GGO cases (qPCR, P < 0.05). Increased senescence was observed in the GGO group compared to controls (P < 0.001), with significant correlation between the senescence‐associated heterochromatin foci and aggregate formation (r = −0.7 and r = −0.44 for cases and controls, respectively). In conclusion, patients with resectable early adenocarcinoma demonstrate abnormal telomere length and cell senescence in peripheral blood leukocytes compared to control subjects. Abnormal telomere biology in the peripheral blood may increase suspicion of early adenocarcinoma among patients with GGO lesions.

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.

Impact of the 8th Edition of the UICC-TNM Classification on Clinical Stage 0-IA Lung Adenocarcinoma: Does the New Classification Predict Postoperative Prognosis More Precisely than the Previous One?

PURPOSE

Early lung adenocarcinoma has been more frequently found recently. The 8th edition of the Union for International Cancer Control (UICC)-Tumor Node Metastasis (TNM) classification for lung cancer has been effective since January 2017. This study aims to elucidate advantages of the current classification for patients with clinical stage 0-IA lung adenocarcinoma, in comparison with the older one.

METHODS

We retrospectively reviewed the data of clinical stage IA (7th edition) lung adenocarcinoma patients who underwent surgery at our institute from 2001 to 2012, and reclassified them by the 8th edition. Survival analysis was used to evaluate the impact of the two classifications.

RESULTS

In all, 281 cases were eligible. Clinical T-factors (8th) were significant prognostic factors for overall survival (P = 0.001), recurrence-free survival (P <0.001), and cancer-specific survival (P = 0.001). However, those in the previous edition were not (P = 0.894, P = 0.144, and P = 0.822, respectively).

CONCLUSION

The 8th edition of the UICC-TNM classification predicts postoperative prognosis more precisely than the 7th one in clinical stage 0-IA lung adenocarcinoma. It is probably because the stage distribution of the population, which included in the research project the 8th edition based on, has been changed, and the new edition develops more accurate staging criteria for ground-glass nodule (GGN).

Tumor Growth Assessment by Computed Tomography Perfusion Imaging (CTPI), Perfusion-Weighted Imaging (PWI), and Diffusion-Weighted Imaging (DWI) in a Rabbit Pleural Squamous Cell Carcinoma VX2-Implanted Model

Background

Computed tomography perfusion imaging (CTPI) and perfusion-weighted imaging (PWI) are non-invasive technologies that can quantify tumor vascularity and blood flow. This study explored the blood flow information, tumor cell viability, and hydrothoraces in a rabbit pleural VX2-implanted model through use of CTPI, PWI, and DWI.

Material/Methods

A pleural VX2-implanted model was established in 58 New Zealand white rabbits. CTPI, PWI, and DWI were applied with a 16-slice spiral CT and an Archival 1.5 T dual-gradient MRI.

Results

Compared with muscle tissue, PV, PEI, and BV of parietal and visceral pleural tumor implantation rabbits showed significant differences. The t values of PV, PEI, and BV between parietal and visceral pleura were 2.08, 2.29, and 2.88, respectively. Compared with muscle tissue, WIR, WOR, and MAXR of parietal and visceral pleural tumor implantation rabbits showed significant differences. In parietal pleural tumor implantation rabbits, the section surface of lesion tissues was 5.2±2.7 cm². Hydrothorax appeared 6.0±2.0 days after tumor implantation. The mean value of ADC was 1.5±0.6. In visceral pleural tumor implantation rabbits, the section surface of lesion tissues was 1.6±0.8 cm². Hydrothorax appeared 7.0±3.0 days after tumor implantation. The mean value of ADC was 1.4±0.5. The t values of the above 3 indices for the parietal and visceral pleura were 1.85, 1.83, and 1.76, respectively (P<0.05).

Conclusions

The combined application of CTPI, PWI, and DWI accurately and visually reflects the blood perfusion of tumor tissues and quantitatively analyzes blood flow information and the mechanism underlying hydrothorax generation in tumor tissues.

Computed tomography-guided hook wire localization facilitates video-assisted thoracoscopic surgery of pulmonary ground-glass nodules

BACKGROUND

This retrospectively study was conducted to assess the efficiency and safety of computed tomography (CT)-guided hook wire localization of pulmonary ground-glass nodules (GGNs) prior to video-assisted thoracoscopic surgery (VATS).

METHODS

From 2015 to 2018, a total of 86 patients with 86 pulmonary GGNs underwent preoperative CT-guided hook wire localization before VATS. The technical details and clinicopathological findings were analyzed.

RESULTS

All 86 pulmonary GGNs (25 pure GGNs and 61 part-solid GGNs) were successfully located and resected. The mean diameter of the GGNs was 1.4 ± 0.4 cm (range 0.6-2.2) and the mean lesion distance to the pleural surface was 7.3 ± 4.3 mm (range 2-19). Complications of hook wire marking included asymptomatic minor pneumothorax in 21 patients (24%) and focal pulmonary hemorrhage in 18 (21%). The median hook wire localization time was 19.1 minutes (range 10-30) and the median VATS time was 49 minutes (range 28-89). Pathology revealed 72 precancerous lesions or primary lung adenocarcinomas, 5 metastatic tumors, and 9 benign lesions.

CONCLUSIONS

Preoperative localization of small pulmonary GGNs using CT-guided hook wire was efficient and safe prior to VATS resection.

Assessing the Blood Supply Status of the Focal Ground-Glass Opacity in Lungs Using Spectral Computed Tomography

Objective

To exploit material decomposition analysis in dual-energy spectral computed tomography (CT) to assess the blood supply status of the ground-glass opacity (GGO) in lungs.

Materials and Methods

This retrospective study included 48 patients with lung adenocarcinoma, who underwent a contrast-enhanced dual-energy spectral CT scan before treatment (53 GGOs in total). The iodine concentration (IC) and water content (WC) of the GGO, the contralateral and ipsilateral normal lung tissues were measured in the arterial phase (AP) and their differences were analyzed. IC, normalized IC (NIC), and WC values were compared between the pure ground-glass opacity (pGGO) and the mixed ground-glass opacity (mGGO), and between the group of preinvasive lesions and the minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IA) groups.

Results

The values of pGGO (IC = 20.9 ± 6.2 mg/mL and WC = 345.1 ± 87.1 mg/mL) and mGGO (IC = 23.8 ± 8.3 mg/mL and WC = 606.8 ± 124.5 mg/mL) in the AP were significantly higher than those of the contralateral normal lung tissues (IC = 15.0 ± 4.9 mg/mL and WC = 156.4 ± 36.8 mg/mL; IC = 16.2 ± 5.7 mg/mL and WC = 169.4 ± 41.0 mg/mL) and ipsilateral normal lung tissues (IC = 15.1 ± 6.2 mg/mL and WC = 156.3 ± 38.8 mg/mL; IC = 15.9 ± 6.0 mg/mL and WC = 174.7 ± 39.2 mg/mL; all p < 0.001). After normalizing the data according to the values of the artery, pGGO (NIC = 0.1 and WC = 345.1 ± 87.1 mg/mL) and mGGO (NIC = 0.2 and WC = 606.8 ± 124.5 mg/mL) were statistically different (p = 0.049 and p < 0.001, respectively), but not for the IC value (p = 0.161). The WC values of the group with preinvasive lesions and MIA (345.4 ± 96.1 mg/mL) and IA (550.1 ± 158.2 mg/mL) were statistically different (p < 0.001).

Conclusion

Using dual-energy spectral CT and material decomposition analysis, the IC in GGO can be quantitatively measured which can be an indicator of the blood supply status in the GGO.

Radiomic analysis of pulmonary ground-glass opacity nodules for distinction of preinvasive lesions, invasive pulmonary adenocarcinoma and minimally invasive adenocarcinoma based on quantitative texture analysis of CT

Objective

To identify the differences among preinvasive lesions, minimally invasive adenocarcinomas (MIAs) and invasive pulmonary adenocarcinomas (IPAs) based on radiomic feature analysis with computed tomography (CT).

Methods

A total of 109 patients with ground-glass opacity lesions (GGOs) in the lungs determined by CT examinations were enrolled, all of whom had received a pathologic diagnosis. After the manual delineation and segmentation of the GGOs as regions of interest (ROIs), the patients were subdivided into three groups based on pathologic analyses: the preinvasive lesions (including atypical adenomatous hyperplasia and adenocarcinoma in situ) subgroup, the MIA subgroup and the IPA subgroup. Next, we obtained the texture features of the GGOs. The data analysis was aimed at finding both the differences between each pair of the groups and predictors to distinguish any two pathologic subtypes using logistic regression. Finally, a receiver operating characteristic (ROC) curve was applied to accurately evaluate the performances of the regression models.

Results

We found that the voxel count feature (P<0.001) could be used as a predictor for distinguishing IPAs from preinvasive lesions. However, the surface area feature (P=0.040) and the extruded surface area feature (P=0.013) could be predictors of IPAs compared with MIAs. In addition, the correlation feature (P=0.046) could distinguish preinvasive lesions from MIAs better.

Conclusions

Preinvasive lesions, MIAs and IPAs can be discriminated based on texture features within CT images, although the three diseases could all appear as GGOs on CT images. The diagnoses of these three diseases are very important for clinical surgery.

Development and Validation of a Predictive Radiomics Model for Clinical Outcomes in Stage I Non-small Cell Lung Cancer

PURPOSE

To develop and validate a radiomics signature that can predict the clinical outcomes for patients with stage I non-small cell lung cancer (NSCLC).

METHODS AND MATERIALS

We retrospectively analyzed contrast-enhanced computed tomography images of patients from a training cohort (n = 147) treated with surgery and an independent validation cohort (n = 295) treated with stereotactic ablative radiation therapy. Twelve radiomics features with established strategies for filtering and preprocessing were extracted. The random survival forests (RSF) method was used to build models from subsets of the 12 candidate features based on their survival relevance and generate a mortality risk index for each observation in the training set. An optimal model was selected, and its ability to predict clinical outcomes was evaluated in the validation set using predicted mortality risk indexes.

RESULTS

The optimal RSF model, consisting of 2 predictive features, kurtosis and the gray level co-occurrence matrix feature homogeneity2, allowed for significant risk stratification (log-rank P < .0001) and remained an independent predictor of overall survival after adjusting for age, tumor volume and histologic type, and Karnofsky performance status (hazard ratio [HR] 1.27; P < 2e-16) in the training set. The resultant mortality risk indexes were significantly associated with overall survival in the validation set (log-rank P = .0173; HR 1.02, P = .0438). They were also significant for distant metastasis (log-rank P < .05; HR 1.04, P = .0407) and were borderline significant for regional recurrence on univariate analysis (log-rank P < .05; HR 1.04, P = .0617).

CONCLUSIONS

Our radiomics model accurately predicted several clinical outcomes and allowed pretreatment risk stratification in stage I NSCLC, allowing the choice of treatment to be tailored to each patient's individual risk profile.

Evaluation of the solitary pulmonary nodule: size matters, but do not ignore the power of morphology

Abstract

Subsequent to the widespread use of multidetector computed tomography and growing interest in lung cancer screening, small pulmonary nodules are more frequently detected. The differential diagnosis for a solitary pulmonary nodule is extremely broad and includes both benign and malignant causes. Recognition of early lung cancers is vital, since stage at diagnosis is crucial for prognosis. Estimation of the probability of malignancy is a challenging task, but crucial for follow-up and further work-up. In addition to the clinical setting and metabolic assessment, morphological assessment on thin-section computed tomography is essential. Size and growth are key factors in assessment of the malignant potential of a nodule. The likelihood of malignancy positively correlates with nodule diameter: as the diameter increases, so does the likelihood of malignancy. Although there is a considerable overlap in the features of benign and malignant nodules, the importance of morphology however should not be underestimated. Features that are associated with benignity include a perifissural location and triangular morphology, internal fat and benign calcifications. Malignancy is suspected in nodules presenting with spiculation, lobulation, pleural indentation, vascular convergence sign, associated cystic airspace, bubble-like lucencies, irregular air bronchogram, and subsolid morphology. Nodules often show different features and combination of findings is certainly more powerful.

Teaching points

• Size of a pulmonary nodule is important, but morphological assessment should not be underestimated.

• Lung nodules should be evaluated on thin section CT, in both lung and mediastinal window setting.

• Features associated with benignity include a triangular morphology, internal fat and calcifications.

• Spiculation, pleural retraction and notch sign are highly suggestive of a malignant nature.

• Complex features (e.g. bubble-like lucencies) are highly indicative of a malignant nature.

[Growth Evaluation of Pulmonary Nodules on Chest CT]

对肺结节行计算机断层扫描（computed tomography, CT）随访并确定结节生长特性是临床针对不定性肺结节常采用的策略。依据肿瘤生长指数模型，常采用体积或质量倍增时间量化结节的生长速率。本文拟对肺癌的指数生长模型、肺结节生长量化评价的方法学、不同类型肺结节的生长特性进行综述。

Can we differentiate minimally invasive adenocarcinoma and non-invasive neoplasms based on high-resolution computed tomography features of pure ground glass nodules?

Objective

The purpose of our study was to assess the differentially diagnostic value of radiographic characteristics of pure ground glass nodules (GGNs) between minimally invasive adenocarcinoma and non-invasive neoplasm.

Methods

Sixty-seven pure GGNs (28 minimally invasive adenocarcinomas (MIA) and 39 pre-invasive lesions) were analyzed from June 2012 to June 2015. Pre-invasive lesions consisted of 15 atypical adenomatous hyperplasia (AAH) and 24 adenocarcinomas in situ (AIS). High-resolution computed tomography (HRCT) features and volume of MIA and pre-invasive lesions were assessed. Fisher exact test, independent sample t test, Mann-Whitney U test and receiver operating characteristic (ROC) curve analysis were performed.

Results

Inter-observer agreement indexes for the diameter, mean HRCT attenuations and volume of pure GGNs were all high (ICC>0.75). Univariate analyses showed that lesion diameter, mean HRCT attenuation, and volume value differed significantly between two groups. Among HRCT findings, GGN shape as round or oval (F = 13.456, P = 0.002) and lesion borders as smooth or notched (F = 15.742, P = 0.001) frequently appeared in pre-invasive lesions in comparison with MIA. Type II and type III of the relationship between blood vessels and pure GGNs suggested higher possibility of malignancy than type I.

Conclusions

HRCT features of pure GGNs can help to differentiate MIA from non-invasive neoplasms.

Mean Computed Tomography Value to Predict the Tumor Invasiveness in Clinical Stage IA Lung Cancer

BACKGROUND

The purpose of this study was to validate the ability of the mean computed tomography (m-CT) value to predict tumor invasiveness and recurrence, and further, to compare with other measurements such as consolidation/tumor ratio and solid tumor size.

METHODS

A retrospective study was conducted of 494 patients with clinical stage IA lung cancer who had peripherally located lung adenocarcinoma. Receiver operating characteristic curve analysis was used to compare the ability to predict tumor invasiveness and recurrence between m-CT value, consolidation/tumor ratio, and tumor size. Multiple logistic regression analyses were performed to determine the independent variables for the prediction of pathologic, less invasive lung cancer. Disease-free survival was measured from the date of the operation until any recurrence.

RESULTS

The m-CT values were 643.6 ± 9.4 Hounsfield units in the noninvasive cancer group and 365.9 ± 11.4 Hounsfield units in the invasive cancer group (p < 0.0001). The invasive cancer group was strongly associated with a high CT attenuation value, high consolidation/tumor ratio, large solid tumor size, large tumor size, and high standardized uptake value. Multiple logistic analyses, including the preoperatively determined variables, revealed that standardized uptake value and m-CT are independent predictive factors of less invasive lung cancer. In addition, the hazard ratio of the m-CT value was higher than that of the standardized uptake value value.

CONCLUSIONS

The evaluation of m-CT value is useful in predicting less invasive lung cancer. The m-CT value can potentially determine operative procedure, particularly limited resection for peripheral lung adenocarcinoma.

Radiological Image Traits Predictive of Cancer Status in Pulmonary Nodules

Purpose: We propose a systematic methodology to quantify incidentally identified pulmonary nodules based on observed radiological traits (semantics) quantified on a point scale and a machine-learning method using these data to predict cancer status.Experimental Design: We investigated 172 patients who had low-dose CT images, with 102 and 70 patients grouped into training and validation cohorts, respectively. On the images, 24 radiological traits were systematically scored and a linear classifier was built to relate the traits to malignant status. The model was formed both with and without size descriptors to remove bias due to nodule size. The multivariate pairs formed on the training set were tested on an independent validation data set to evaluate their performance.Results: The best 4-feature set that included a size measurement (set 1), was short axis, contour, concavity, and texture, which had an area under the receiver operator characteristic curve (AUROC) of 0.88 (accuracy = 81%, sensitivity = 76.2%, specificity = 91.7%). If size measures were excluded, the four best features (set 2) were location, fissure attachment, lobulation, and spiculation, which had an AUROC of 0.83 (accuracy = 73.2%, sensitivity = 73.8%, specificity = 81.7%) in predicting malignancy in primary nodules. The validation test AUROC was 0.8 (accuracy = 74.3%, sensitivity = 66.7%, specificity = 75.6%) and 0.74 (accuracy = 71.4%, sensitivity = 61.9%, specificity = 75.5%) for sets 1 and 2, respectively.Conclusions: Radiological image traits are useful in predicting malignancy in lung nodules. These semantic traits can be used in combination with size-based measures to enhance prediction accuracy and reduce false-positives. Clin Cancer Res; 23(6); 1442-9. ©2016 AACR.

Lung adenocarcinomas: correlation of computed tomography and pathology findings

Adenocarcinoma is the most common histologic type of lung cancer. Recent lung adenocarcinoma classifications from the International Association for the Study of Lung cancer, the American Thoracic Society and the European Respiratory Society (IASLC/ETS/ERS, 2011) and World Health Organization (WHO, 2015) define a wide range of adenocarcinoma types and subtypes featuring different prognosis and management. This spectrum of lesions translates into various CT presentations and features, which generally show good correlation with histopathology, stressing the key role of the radiologist in the diagnosis and management of those patients. This review aims at helping radiologists to understand the basics of the up-to-date adenocarcinoma pathological classifications, radio-pathological correlations and how to use them in the clinical setting, as well as other imaging-related correlations (radiogenomics, quantitative analysis, PET-CT).

Comparisons of clinical outcomes in patients with and without a preoperative tissue diagnosis in the persistent malignant-looking, ground-glass-opacity nodules

To evaluate the clinical usefulness of surgical resection of persistent malignant-looking ground-glass-opacity nodules (GGN) without a preoperative tissue diagnosis.From September 1998 to November 2011, we retrospectively enrolled 288 patients (126 men, 162 women; mean age, 59.3 years) with lung adenocarcinoma proven by surgery and which appeared as GGN on chest computed tomography (CT, ground-glass-opacity [GGO] proportion >20%). We divided the study subjects into 2 groups: patients with a preoperative tissue diagnosis (PTD group, n = 207) and patients without a preoperative tissue diagnosis (No-PTD group, n = 81). In patients with GGN having GGO ≥ 90% (n = 140), we divided them into 2 groups: PTD group (n = 83) and No-PTD group (n = 57). The clinical and surgical outcomes were compared between the 2 groups.In 204 patients who underwent lobectomy for stage Ia lung cancer, there was no significantly different recurrence-free survival between the 2 groups (P = 0.721). A significantly lower percentage of No-PTD group waited >14 days for surgery (77.8% vs 87.9%, P = 0.030) and were hospitalized for >7 days (56.8% vs 89.9%, P < 0.001). They showed a shorter mean surgery time (136.9 vs 155.0 minutes, P = 0.019). In patients with GGN having GGO ≥ 90%, the results were the same as those of all of the study subjects.No-PTD group can gain benefits perioperatively, showing no different recurrence-free survival with PTD group in stage Ia lung cancer.

The IASLC Lung Cancer Staging Project: Background Data and Proposals for the Application of TNM Staging Rules to Lung Cancer Presenting as Multiple Nodules with Ground Glass or Lepidic Features or a Pneumonic Type of Involvement in the Forthcoming Eighth Edition of the TNM Classification

INTRODUCTION

Application of tumor, node, and metastasis (TNM) classification is difficult in patients with lung cancer presenting as multiple ground glass nodules or with diffuse pneumonic-type involvement. Clarification of how to do this is needed for the forthcoming eighth edition of TNM classification.

METHODS

A subcommittee of the International Association for the Study of Lung Cancer Staging and Prognostic Factors Committee conducted a systematic literature review to build an evidence base regarding such tumors. An iterative process that included an extended workgroup was used to develop proposals for TNM classification.

RESULTS

Patients with multiple tumors with a prominent ground glass component on imaging or lepidic component on microscopy are being seen with increasing frequency. These tumors are associated with good survival after resection and a decreased propensity for nodal and extrathoracic metastases. Diffuse pneumonic-type involvement in the lung is associated with a worse prognosis, but also with a decreased propensity for nodal and distant metastases.

CONCLUSION

For multifocal ground glass/lepidic tumors, we propose that the T category be determined by the highest T lesion, with either the number of tumors or m in parentheses to denote the multifocal nature, and that a single N and M category be used for all the lesions collectively-for example, T1a(3)N0M0 or T1b(m)N0M0. For diffuse pneumonic-type lung cancer we propose that the T category be designated by size (or T3) if in one lobe, as T4 if involving an ipsilateral different lobe, or as M1a if contralateral and that a single N and M category be used for all pulmonary areas of involvement.

[Overview of Clinical Progress in Pulmonary Ground-glass Nodules]

磨玻璃结节（ground-glass nodules, GGNs）是肺结节中的特殊类型，随着高分辨薄层计算机断层扫描（high resolution computed tomography, HRCT）的应用，GGNs检出率逐年升高并受到日益广泛的关注。由于缺乏特征性临床症状，肺癌的早期诊断难度较大，而既往研究证实GGNs的出现常常提示与肺癌相关，因此加强筛查及管理有助于早期诊断及治疗肺癌。本文回顾既往相关研究，就GGNs的定义、分类、影像学特征、自然生长史、分子病理特征及诊治流程作一小结。

Ultra-High-Resolution Computed Tomography of the Lung: Image Quality of a Prototype Scanner

Purpose

The image noise and image quality of a prototype ultra-high-resolution computed tomography (U-HRCT) scanner was evaluated and compared with those of conventional high-resolution CT (C-HRCT) scanners.

Materials and Methods

This study was approved by the institutional review board. A U-HRCT scanner prototype with 0.25 mm x 4 rows and operating at 120 mAs was used. The C-HRCT images were obtained using a 0.5 mm x 16 or 0.5 mm x 64 detector-row CT scanner operating at 150 mAs. Images from both scanners were reconstructed at 0.1-mm intervals; the slice thickness was 0.25 mm for the U-HRCT scanner and 0.5 mm for the C-HRCT scanners. For both scanners, the display field of view was 80 mm. The image noise of each scanner was evaluated using a phantom. U-HRCT and C-HRCT images of 53 images selected from 37 lung nodules were then observed and graded using a 5-point score by 10 board-certified thoracic radiologists. The images were presented to the observers randomly and in a blinded manner.

Results

The image noise for U-HRCT (100.87 ± 0.51 Hounsfield units [HU]) was greater than that for C-HRCT (40.41 ± 0.52 HU; P < .0001). The image quality of U-HRCT was graded as superior to that of C-HRCT (P < .0001) for all of the following parameters that were examined: margins of subsolid and solid nodules, edges of solid components and pulmonary vessels in subsolid nodules, air bronchograms, pleural indentations, margins of pulmonary vessels, edges of bronchi, and interlobar fissures.

Conclusion

Despite a larger image noise, the prototype U-HRCT scanner had a significantly better image quality than the C-HRCT scanners.

Correlation between histological invasiveness and the computed tomography value in pure ground-glass nodules

Purpose

The purpose of this study was to evaluate the correlation between histological invasiveness and the computed tomography (CT) value and size in pure ground-glass nodules (GGNs) to determine optimal “follow-up or resection” strategies.

Methods

Between 2001 and 2014, 78 resected, pure GGNs were retrospectively evaluated. The maximum diameter and CT value of pure GGNs were measured using a computer graphics support system.

Results

All GGNs with a maximum diameter ≤10 mm and CT value ≤−600 Hounsfield units (HU) were considered to be noninvasive lesions, while 21 of 26 (81 %) with a maximum diameter >10 mm and CT value >−600 HU were considered to be invasive lesions. With respect to the correlation between each histological type and pure GGN with a maximum diameter ≤10 mm and CT value ≤−600 HU, the specificity was 90 % and the sensitivity and negative predictive value were both 100 % in atypical adenomatous hyperplasia (AAH), while the specificity was 58 % and the sensitivity and positive predictive value were 0 % in minimally invasive and invasive adenocarcinoma.

Conclusion

Pure GGNs with a maximum diameter of ≤10 mm and CT value of ≤−600 HU are nearly always pre-invasive lesions; therefore, surgery should be carefully selected in such patients.

Management of ground-glass opacities: should all pulmonary lesions with ground-glass opacity be surgically resected?

Pulmonary nodules with ground-glass opacity (GGO) are frequently observed and will be increasingly detected. GGO can be observed in both benign and malignant conditions, including lung cancer and its preinvasive lesions. Atypical adenomatous hyperplasia and adenocarcinoma in situ are typically manifested as pure GGOs, whereas more advanced adenocarcinomas may include a larger solid component within the GGO region. The natural history of GGOs has been gradually clarified. Approximately 20% of pure GGOs and 40% of part-solid GGOs gradually grow or increase their solid component, whereas others remain unchanged for years. Therefore, it remains unclear whether all pulmonary lesions with GGO should be surgically resected or whether lesions without changes may not require resection. To distinguish GGOs with growth from those without growth, a 3-year follow-up observation period is a reasonable benchmark based on the data that the volume-doubling time (VDT) of pure GGOs ranges from approximately 600 to 900 days and that of part-solid GGOs ranges from 300 to 450 days. Future studies on the genetic differences between GGOs with growth and those without growth will help establish an appropriate management algorithm.

EGFR L858R mutation is associated with lung adenocarcinoma patients with dominant ground-glass opacity

OBJECTIVES

To retrospectively identify quantitative computed tomographic (CT) features that correlate with the three major driver gene mutations in surgically resected lung adenocarcinomas with dominant ground-glass opacity (GGO) stratified by the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS), and European Respiratory Society (ERS) classification in a Chinese cohort of patients.

MATERIALS AND METHODS

Surgically resected lung adenocarcinomas from Shanghai Pulmonary Hospital were enrolled. EGFR, KRAS and EML4-ALK mutations were detected by qPCR. Clinical and pathological characteristics including gender, age, TNM stage, smoking status and CT pattern were analyzed. Histologic subtype was classified according to IASLC/ATS/ERS classification. At preoperative chest CT, the percentage of GGO volume, diameter, solid volume and total tumor volume of each tumor were measured by using a semiautomated algorithm. Distribution of driver gene mutations was evaluated by using the Fisher exact test, the Student's t test, and Pearson correlation analysis.

RESULTS AND CONCLUSION

788 in total and 158 GGO tumors were taken in this cohort. GGO pattern occurred at a significantly higher frequency in younger, female and non-smoking patients. EGFR/KRAS mutations and EML4-ALK fusions were similar between GGO and solid adenocarcinomas. GGO volume and diameter showed correlation with EGFR mutation. With regard to association between lung adenocarcinoma histological subtypes and GGO features, GGO proportion was significantly higher in lepidic predominant adenocarcinomas, including adenocarcinoma in situ, minimally invasive adenocarcinoma, and lepidic predominant invasive adenocarcinoma. No significant differences of driver gene mutations were found between subtypes of lung adenocarcinoma. It is important that we understand GGO lesions of lung adenocarcinoma to identify molecular biomarkers including EGFR, KRAS and EML4-ALK. These markers would offer useful information for determining the appropriate strategy to treat lung adenocarcinoma with GGO lesions detected by helical CT.

Analysis of pre-invasive lung adenocarcinoma lesions on thin-section computerized tomography

INTRODUCTION

Recent studies have revealed a potential relationship between the presence of ground glass opacity (GGO) on regular computerized tomography (CT) and adenocarcinomas.

OBJECTIVES

To investigate features of pre-invasive lung adenocarcinoma lesions on thin-section CT.

METHODS

We evaluated 59 cases of atypical adenomatous hyperplasia (AAH) and 35 cases of adenoma in situ (AIS) confirmed by histopathology. Comparison of thin-section CT features, such as size, shape, margin, internal characteristics, and adjacent structures of pre-invasive lesions were analyzed. Lesions were further classified to pure ground glass opacity (pGGO) and mixed ground glass opacity (mGGO). Differences were analyzed using Chi-square or Fisher tests.

RESULTS

There were significant differences in lobulation, spiculation, and bubble lucency between pGGO and mGGO (P < 0.05), while no differences in air bronchogram, pleural indentation, or vascular morphological changes were identified (P > 0.05). In the group of pGGO, AAH and AIS lesions did not differ significantly in size (P > 0.05), while significant differences were found with respect to lobulation, spiculation, pleural indentation, and vascular morphological changes (P < 0.05). In the group of mGGO, AAH and AIS lesions were significantly different with respect to size (P < 0.05), while no differences were found in lobulation, spiculation, bubble lucency, air bronchogram, or pleural indentation (P > 0.05). Only vascular morphological changes were significantly different between AAH and AIS lesions (P < 0.05).

CONCLUSION

The features of thin-slice CT of AAH and AIS reflected the corresponding morphological changes from AAH progressing to AIS or adenocarcinoma.

Tumor size and computed tomography attenuation of pulmonary pure ground-glass nodules are useful for predicting pathological invasiveness

Objectives

Pulmonary ground-glass nodules (GGNs) are occasionally diagnosed as invasive adenocarcinomas. This study aimed to evaluate the clinicopathological features of patients with pulmonary GGNs to identify factors predictive of pathological invasion.

Methods

We retrospectively evaluated 101 pulmonary GGNs resected between July 2006 and November 2013 and pathologically classified them as adenocarcinoma in situ (AIS; n = 47), minimally invasive adenocarcinoma (MIA; n = 30), or invasive adenocarcinoma (I-ADC; n = 24). The age, sex, smoking history, tumor size, and computed tomography (CT) attenuation of the 3 groups were compared. Receiver operating characteristic (ROC) curve analyses were performed to identify factors that could predict the presence of pathologically invasive adenocarcinomas.

Results

Tumor size was significantly larger in the MIA and I-ADC groups than in the AIS group. CT attenuation was significantly greater in the I-ADC group than in the AIS and MIA groups. In ROC curve analyses, the sensitivity and specificity of tumor size (cutoff, 11 mm) were 95.8% and 46.8%, respectively, and those for CT attenuation (cutoff, −680 HU) were 95.8% and 35.1%, respectively; the areas under the curve (AUC) were 0.75 and 0.77, respectively. A combination of tumor size and CT attenuation (cutoffs of 11 mm and −680 HU for tumor size and CT attenuation, respectively) yielded in a sensitivity and specificity of 91.7% and 71.4%, respectively, with an AUC of 0.82.

Conclusions

Tumor size and CT attenuation were predictive factors of pathological invasiveness for pulmonary GGNs. Use of a combination of tumor size and CT attenuation facilitated more accurate prediction of invasive adenocarcinoma than the use of these factors independently.

Preliminary application of high-definition computed tomographic Gemstone Spectral Imaging in lung cancer

RATIONALE AND OBJECTIVES

To evaluate the feasibility of multiparameter quantitative measurement lung cancer by Gemstone Spectral Imaging (GSI) high-definition computed tomography.

MATERIALS AND METHODS

Seventy-seven patients who were found to have a lung mass or a nodule by CT plain scan for the first time received chest contrast CT scan with GSI mode on high-definition computed tomography. The GSI viewer was used to display the spectral curve, iodine-based images, water-based images, and 101 sets of monochromatic images of a selected region of interest from the relative homogeneous area of the mass or nodule. Iodine concentration, water concentration, spectral curve slope, and CT values at 40 keV of the region of interest were measured. Finally, 68 eligible patients were divided into a pneumonia group (n = 24) and a malignant tumor group (n = 44, including squamous carcinoma, n = 29, and adenocarcinoma, n = 15).

RESULTS

Significant differences existed in iodine concentration (t = 6.459), spectral curve slope (t = 6.276), and CT values at 40 keV (t = 6.698) between the pneumonia group and the malignant tumor group (P < 0.05), as well as between squamous carcinoma and adenocarcinoma (t = 6.494, 5.634, 6.091, respectively, P < 0.05), whereas water concentrations were found to have no difference between the 2 groups (t = 0.082, P > 0.05) and between the 2 types of malignant tumors (t = 1.234, P > 0.05).

CONCLUSIONS

High-definition computed tomographic GSI technique might be helpful to differentiate lung cancer from lung benign lesions by providing qualitative and quantitative information.

Impact of the IASLC/ATS/ERS classification in pN0 pulmonary adenocarcinomas: a study with radiological-pathological comparisons and survival analyses

The aim of this study was: (1) to compare the new pathological findings as detected by the IASLC/ATS/ERS classification with the traditional radiological features in pulmonary pN0 adenocarcinomas, (2) to evaluate their prognostic significance on overall survival (OS). A total of 42 surgically resected pN0 pulmonary adenocarcinomas were analyzed. On CT scans, the following radiological data were recorded: sphericity, predominant margins, cavitation and bronchogram, attenuation and percentage of ground glass opacity (GGO). On pathological examination, tumors were categorized according to the IASLC/ATS/ERS classification; Sica score and grade, pathological stage, tumor major axis, pleural invasion, vascular and lymphatic invasion, peritumoral lymphoid infiltration, and cytological features were also determined. Clinical follow up was available in 37 cases (range 1-117 months). Radiologically, 31 solid and 11 semisolid tumors were found. Morphologically, 2 minimally invasive and 40 invasive adenocarcinomas were diagnosed. In radiological-pathological comparisons, (1) the acinar pattern was higher in tumors with solid attenuation and low GGO (p=0.018); (2) the lepidic pattern was more elevated in tumors with high GGO (p=0.012). In multivariate survival analyses with stage, predominant margins on CT scans (p=0.036) and Sica score (p=0.028) significantly affected OS. This study confirms the validity of the new classification of pulmonary adenocarcinomas in radiological-pathological comparisons and underlines the importance of both radiological and pathological findings in correctly identifying their prognostic features.