Solitary pulmonary nodular lung adenocarcinoma: correlation of histopathologic scoring and patient survival with imaging biomarkers

Survival benefit of adjuvant chemotherapy after resection of Stage I lung adenocarcinoma containing micropapillary components

BACKGROUND

The usefulness of postoperative adjuvant chemotherapy (ACT) for patients with stage I lung adenocarcinoma with micropapillary (MIP) components remains unclear. We analyzed whether postoperative ACT could reduce recurrence in patients with stage I lung adenocarcinoma with MIP components, thereby improving their overall survival (OS) and disease-free survival (DFS).

METHODS

Data for patients with pathologically confirmed stage I lung adenocarcinoma with MIP components from January 2012 to December 2018 were retrospectively analyzed. OS and DFS were analyzed in groups and subgroups.

RESULTS

Overall, 259 patients were enrolled. Patients who received ACT in stage IA showed significantly better survival than did those with no-adjuvant chemotherapy (NACT); (5-year OS 89.4% vs. 73.6%, p < 0.001; 5-year DFS 87.2% vs. 66.0%, p = 0.008). A difference was also observed for in-stage IB patients (5-year OS 82.0% vs. 51.8%, p = 0.001; 5-year DFS 76.0% vs. 41.11 %, p = 0.004). In subgroup analysis based on the proportion of MIP components, patients with 1%-5% MIP components had a significantly better prognosis in the ACT group than in the NACT group (5-year OS 82.4% vs. 66.0%, p = 0.005; 5-year DFS 76.5% vs. 49.1%, p = 0.032). A similar difference was observed for patients with MIP ≥5% (5-year OS 80.7% vs. 47.8%, p = 0.009; 5-year DFS 73.11% vs. 43.5%, p = 0.007).

CONCLUSION

Among patients with stage I lung adenocarcinoma with MIP components, those who received ACT showed significant survival benefits compared to those without ACT. Patients with lung adenocarcinoma with MIP components could benefit from ACT when the MIP was ≥1%.

Qualitative and Semiquantitative Parameters of 18F-FDG-PET/CT as Predictors of Malignancy in Patients with Solitary Pulmonary Nodule

This study aims to evaluate the reliability of qualitative and semiquantitative parameters of ¹⁸F-FDG PET-CT, and eventually a correlation between them, in predicting the risk of malignancy in patients with solitary pulmonary nodules (SPNs) before the diagnosis of lung cancer. A total of 146 patients were retrospectively studied according to their pre-test probability of malignancy (all patients were intermediate risk), based on radiological features and risk factors, and qualitative and semiquantitative parameters, such as SUVmax, SUVmean, TLG, and MTV, which were obtained from the FDG PET-CT scan of such patients before diagnosis. It has been observed that visual analysis correlates well with the risk of malignancy in patients with SPN; indeed, only 20% of SPNs in which FDG uptake was low or absent were found to be malignant at the cytopathological examination, while 45.45% of SPNs in which FDG uptake was moderate and 90.24% in which FDG uptake was intense were found to be malignant. The same trend was observed evaluating semiquantitative parameters, since increasing values of SUVmax, SUVmean, TLG, and MTV were observed in patients whose cytopathological examination of SPN showed the presence of lung cancer. In particular, in patients whose SPN was neoplastic, we observed a median (MAD) SUVmax of 7.89 (±2.24), median (MAD) SUVmean of 3.76 (±2.59), median (MAD) TLG of 16.36 (±15.87), and a median (MAD) MTV of 3.39 (±2.86). In contrast, in patients whose SPN was non-neoplastic, the SUVmax was 2.24 (±1.73), SUVmean 1.67 (±1.15), TLG 1.63 (±2.33), and MTV 1.20 (±1.20). Optimal cut-offs were drawn for semiquantitative parameters considered predictors of malignancy. Nodule size correlated significantly with FDG uptake intensity and with SUVmax. Finally, age and nodule size proved significant predictors of malignancy. In conclusion, considering the pre-test probability of malignancy, qualitative and semiquantitative parameters can be considered reliable tools in patients with SPN, since cut-offs for SUVmax, SUVmean, TLG, and MTV showed good sensitivity and specificity in predicting malignancy.

T1 invasive lung adenocarcinoma: Thin-section CT solid score and histological periostin expression predict tumor recurrence

Adenocarcinoma is the most common histological type of non-small cell lung cancer (NSCLC), and various biomarkers for predicting its prognosis after surgical resection have been suggested, particularly in early-stage lung adenocarcinoma. Periostin (also referred to as POSTN, PN or osteoblast-specific factor) is an extracellular matrix protein, the expression of which is associated with tumor invasiveness in patients with NSCLC. In the present study, the novel approach, in which the thin-section CT findings prior to surgical resection and periostin expression of resected specimens were analyzed in combination, was undertaken to assess whether the findings could be a biomarker for predicting the outcomes following resection of T1 invasive lung adenocarcinoma. A total of 73 patients who underwent surgical resection between January 2000 and December 2009 were enrolled. A total of seven parameters were assessed in the thin-section CT scans: i) Contour; ii) part-solid ground-glass nodule or solid nodule; iii) percentage of solid component (the CT solid score); iv) presence of air-bronchogram and/or bubble-like lucencies; v) number of involved vessels; vi) shape linear strands between the nodule and the visceral pleura; and vii) number of linear strands between the nodule and the visceral pleura. Two chest radiologists independently assessed the parameters. Periostin expression was evaluated on the basis of the strength and extent of staining. Univariate and multivariate analyses were subsequently performed using the Cox proportional hazards model. There was a substantial to almost perfect agreement between the two observers with regard to classification of the seven thin-section CT parameters (κ=0.64-0.85). In the univariate analysis, a CT solid score >80%, pathological lymphatic invasion, tumor and lymph node status and high periostin expression were significantly associated with recurrence (all P<0.05). Multivariate analysis demonstrated that a CT solid score >80% and high periostin expression were risk factors for recurrence (P=0.002 and P=0.011, respectively). The cumulative recurrence rates among the three groups (both negative, CT solid score >80% or high periostin expression, or both positive) were significantly different (log-rank test, P<0.001). Although the solid component is already known to be a major predictor of outcome in lung adenocarcinomas according to previous studies, the combined analysis of CT solid score and periostin expression might predict the likelihood of tumor recurrence more precisely.

Parallel comparison and combining effect of radiomic and emerging genomic data for prognostic stratification of non-small cell lung carcinoma patients

BACKGROUND

A single institution retrospective analysis of 124 non-small cell lung carcinoma (NSCLC) patients was performed to identify whether disease-free survival (DFS) achieves incremental values when radiomic and genomic data are combined with clinical information.

METHODS

Using the least absolute shrinkage and selection operator (LASSO) Cox regression method, radiomic and genetic features were reduced in number for selection of the most useful prognostic feature. We created four models using only baseline clinical data, clinical data with selected genetic features, clinical data with selected radiomic features, and clinical data with selected genetic and radiomic features together. Multivariate Cox proportional hazards analysis was performed to determine predictors of DFS. Receiver operating characteristic (ROC) calculation was made to compare the discriminative performance for DFS prediction by four constructed models at the five-year time point.

RESULTS

On precontrast scan, improved discrimination performance was obtained in a merging of selected radiomics and genetics (AUC = 0.8638), compared with clinical data only (AUC = 0.7990), selected genetic features (AUC = 0.8497), and selected radiomic features (AUC = 0.8355). On post-contrast scan, discrimination performance was improved (AUC = 0.8672) compared with the clinical variables (AUC = 0.7913), and selected genetic features (AUC = 0.8376) and selected radiomic features (AUC = 0.8399) were considered.

CONCLUSIONS

The combination of selected radiomic and genomic features improved stratification of NSCLC patients upon survival. Thus, integrating clinicopathologic model with radiomic and genomic features may lead to improved prognostic accuracy compared to conventional clinicopathological data alone.

KEY POINTS

SIGNIFICANT FINDINGS OF THE STUDY: Receiver operating characteristic (ROC) calculation was made to compare the discriminative performance for disease-free survival (DFS). The discriminative performance for DFS was better when combining radiomic and genetic features compared to clinical data only, selected genetic features, and selected radiomic features.

WHAT THIS STUDY ADDS

The combination of selected radiomic and genomic features improved stratification of NSCLC patients upon survival. Thus, integrating a clinicopathological model with radiomic and genomic features may lead to improved prognostic accuracy compared to conventional clinicopathological data alone.

Low Galectin-3 Expression Level in Primary Tumors Is Associated with Metastasis in T1 Lung Adenocarcinoma

BACKGROUND AND OBJECTIVE

Although nodal and distant metastasis is rare in T1 lung adenocarcinoma, it is related to poor clinical prognosis. Association between galectin-3 (Gal-3) expression level, and clinical outcome of T1 lung adenocarcinoma has not been clarified.

METHODS

From January 2009 to December 2014, 74 patients with surgically resected T1 lung adenocarcinoma were enrolled in this retrospective cohort study. Patient outcomes were followed up until December 2019. Gal-3 expression level in primary tumors was assessed immunohistochemically and evaluated based on the staining intensity and percentage. Patient characteristics and correlation between Gal-3 expression level and clinical outcomes were reviewed.

RESULTS

Low Gal-3 expression was associated with increased metastatic events (p = 0.03), especially distant metastasis (p = 0.007), and mortality rate (p = 0.04). Kaplan-Meier analysis revealed that high Gal-3 expression level was associated with favorable recurrence-free survival in T1 lung adenocarcinoma (log-rank p = 0.048) and T1a (≤ 2 cm, American Joint Committee on Cancer (AJCC) 7th edition) lung adenocarcinoma (log-rank p = 0.043). Gal-3 expression along with tumor size showed a larger area under curve (AUC) than tumor size alone for predicting metastatic events (AUC = 0.747 vs. 0.681) and recurrence (AUC = 0.813 vs. 0.766) in T1a lung adenocarcinoma in the receiver-operating characteristic curve.

CONCLUSION

Low Gal-3 expression level in primary tumors was remarkably associated with increased metastatic events and reduced recurrence-free survival in T1 lung adenocarcinoma. We suggest that Gal-3 expression level in addition to tumor size may potentially be stronger than tumor size alone in predicting metastasis in T1a lung adenocarcinoma patients.

The Natural Growth of Subsolid Nodules Predicted by Quantitative Initial CT Features: A Systematic Review

Background: The detection rate for pulmonary nodules, particularly subsolid nodules (SSNs), has been significantly improved. The purpose of this review is to summarize the relationship between quantitative features of initial CT imaging and the subsequent natural growth of SSNs to explore potential reasons for these findings.

Methods: Relevant studies were collected from a literature search of PubMed, Embase, Web of Science, and Cochrane. Data extraction was performed on the patients' basic information, CT methods, and acquisition methods, including quantitative CT features, and statistical methods.

Results: A total of 10 relevant articles were included in our review, which included 850 patients with 1,026 SSNs. Overall, the results were variable, and the key findings were as follows. Seven studies looked at the relationship between the diameter and growth of SSNs, showing that SSNs with larger diameters were associated with increased growth. An additional three studies which focused on the relationship between CT attenuation and the growth of SSNs showed that SSNs with a high CT attenuation were associated with increased growth.

Conclusion: CT attenuation may be useful in predicting the natural growth of SSNs, and mean CT attenuation may be more useful in predicting the natural growth of pure ground glass nodules (GGNs) than part-solid GGNs. While evaluation by diameter did have some limitations, it demonstrates value in predicting the growth of SSNs.

Marginal radiomics features as imaging biomarkers for pathological invasion in lung adenocarcinoma

OBJECTIVES

Lung adenocarcinomas which manifest as ground-glass nodules (GGNs) have different degrees of pathological invasion and differentiating among them is critical for treatment. Our goal was to evaluate the addition of marginal features to a baseline radiomics model on computed tomography (CT) images to predict the degree of pathologic invasiveness.

METHODS

We identified 236 patients from two cohorts (training, n = 189; validation, n = 47) who underwent surgery for GGNs. All GGNs were pathologically confirmed as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IA). The regions of interest were semi-automatically annotated and 40 radiomics features were computed. We selected features using L1-norm regularization to build the baseline radiomics model. Additional marginal features were developed using the cumulative distribution function (CDF) of intratumoral intensities. An improved model was built combining the baseline model with CDF features. Three classifiers were tested for both models.

RESULTS

The baseline radiomics model included five features and resulted in an average area under the curve (AUC) of 0.8419 (training) and 0.9142 (validation) for the three classifiers. The second model, with the additional marginal features, resulted in AUCs of 0.8560 (training) and 0.9581 (validation). All three classifiers performed better with the added features. The support vector machine showed the most performance improvement (AUC improvement = 0.0790) and the best performance was achieved by the logistic classifier (validation AUC = 0.9825).

CONCLUSION

Our novel marginal features, when combined with a baseline radiomics model, can help differentiate IA from AIS and MIA on preoperative CT scans.

KEY POINTS

• Our novel marginal features could improve the existing radiomics model to predict the degree of pathologic invasiveness in lung adenocarcinoma.

Management of incidental pulmonary nodules: current strategies and future perspectives

Introduction: Detection and characterization of pulmonary nodules is an important issue, because the process is the first step in the management of lung cancers.Areas covered: Literature review was performed on May 15 2019 by using the PubMed, US National Library of Medicine National Institutes of Health, and the National Center for Biotechnology information. CT features helping identify the druggable mutations and predict the prognosis of malignant nodules were presented. Technical advancements in MRI and PET/CT were introduced for providing functional information about malignant nodules. Advances in various tissue biopsy techniques enabling molecular analysis and histologic diagnosis of indeterminate nodules were also presented. New techniques such as radiomics, deep learning (DL) technology, and artificial intelligence showing promise in differentiating between malignant and benign nodules were summarized. Recently, updated management guidelines for solid and subsolid nodules incidentally detected on CT were described. Risk stratification and prediction models for indeterminate nodules under active investigation were briefly summarized.Expert opinion: Advancement in CT knowledge has led to a better correlation between CT features and genomic alterations or tumor histology. Recent advances like PET/CT, MRI, radiomics, and DL-based approach have shown promising results in the characterization and prognostication of pulmonary nodules.

A Novel Algorithm to Differentiate Between Multiple Primary Lung Cancers and Intrapulmonary Metastasis in Multiple Lung Cancers With Multiple Pulmonary Sites of Involvement

INTRODUCTION

Differentiating between multiple primary lung cancer (MPLC) and intrapulmonary metastasis (IPM) is critical for developing a therapeutic strategy to treat multiple lung cancers with multiple pulmonary sites of involvement.

METHODS

We retrospectively included 252 lesions (126 pairs) from 126 patients with surgically resected multiple lung adenocarcinomas. Each pair was classified as MPLC or IPM based on histopathologic findings as the reference standard. A novel algorithm was established with four sequential decision steps based on the combination of computed tomography (CT) lesion types (step 1), CT lesion morphology (step 2), difference of maximal standardized uptake values on positron-emission tomography/CT (step 3), and presence of N2/3 lymph node metastasis or distant metastasis (step 4). The diagnostic accuracy of the algorithm was analyzed. Performances of 11 observers were assessed without and with knowledge of algorithm.

RESULTS

Among 126 pairs, 90 (71.4%) were classified as MPLCs and 36 (28.6%) as IPMs. On applying the diagnostic algorithm, the overall accuracy for diagnosis of IPM among conclusive cases up to step 4 was 88.9%, and 65 and 44 pairs were correctly diagnosed based on step 1 and step 2, respectively. Specificity and positive predictive value for diagnosis of IPM increased significantly in all observers compared with reading rounds without the algorithm.

CONCLUSIONS

Application of the algorithm based on comprehensive information on clinical and imaging variables can allow differentiation between MPLCs and IPMs. When both of two suspected malignant lesions appear as solid predominant lesions without spiculation or air-bronchogram on CT, IPM should be considered.

Evaluating the tumor biology of lung adenocarcinoma: A multimodal analysis

We evaluated the relationships among functional imaging modality such as PET-CT and DW-MRI and lung adenocarcinoma pathologic heterogeneity, extent of invasion depth, and tumor cellularity as a marker of tumor microenvironment.In total, 74 lung adenocarcinomas were prospectively included. All patients underwent 18F-fluorodeoxyglucose (FDG) PET-CT and MRI before curative surgery. Pathology revealed 68 stage I tumors, 3 stage II tumors, and 3 stage IIIA tumors. Comprehensive histologic subtyping was performed for all surgically resected tumors. Maximum standardized uptake value (SUVmax) and ADC values were correlated with pathologic grade, extent of invasion, solid tumor size, and tumor cellularity.Mean solid tumor size (low: 1.7 ± 3.0 mm, indeterminate: 13.9 ± 14.2 mm, and high grade: 30.3 ± 13.5 mm) and SUVmax (low: 1.5 ± 0.2, indeterminate: 3.5 ± 2.5, and high grade: 15.3 ± 0) had a significant relationship with pathologic grade based on 95% confidence intervals (P = .01 and P < .01, respectively). SUVmax showed a strong correlation with tumor cellularity (R = 0.713, P < .001), but was not correlated with extent of invasion (R = 0.387, P = .148). A significant and strong positive correlation was observed among SUVmax values and higher cellularity and pathologic grade. ADC did not exhibit a significant relationship with tumor cellularity.Intratumor heterogeneity quantification using a multimodal-multiparametric approach might be effective when tumor volume consists of a real tumor component as well as a non-tumorous stromal component.

Looking for Lepidic Component inside Invasive Adenocarcinomas Appearing as CT Solid Solitary Pulmonary Nodules (SPNs): CT Morpho-Densitometric Features and 18-FDG PET Findings

Objective

To investigate CT morphologic and densitometric features and 18-FDG PET findings of surgically excised lung adenocarcinomas "mixed subtype" with predominant lepidic component, appearing as solid solitary pulmonary nodules (SPNs) on CT scan.

Materials and Methods

Approval for this study was given from each local institutional review board according to its retrospective nature. Nodules pathologically classified as lung adenocarcinoma mixed subtype with bronchioloalveolar otherwise lepidic predominant component, in three different Italian institutions (Napoli; Varese; Parma), were retrospectively selected.

Results

22 patients were identified. The number of SPNs with smooth margins was significantly lower with respect to the number of SPNs with spiculated margins (p: 0.033), radiating spiculations (p: 0.019), and notch sign (p: 0.011). Mean contrast enhancement (CE) was 53.34 HU (min 5.5 HU, max 112 HU); considering 15 HU as cut-off value, CE was positive in 20/22 cases. No significant correlation was found between size and CE. Mean SUVmax was 2.21, ranging from 0.2 up to 7.5 units; considering 2.5 units as cut-off, SUVmax was positive in 7/22 cases. The number of SPNs with positive CE was significantly higher than the number of SPNs with positive SUVmax (p: 0.0005).

Conclusion

CT generally helps in identifying solid SPN suspicious for malignancy but 18-FDG PET may result in false-negative evaluation; when 18-FDG PET findings of a solid SPN are negative even though CT morphology and CE suggest malignancy, radiologist should consider that lepidic component may be present inside the invasive tumor, despite the absence of ground glass.

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.

Updating the role of FDG PET/CT for evaluation of lung cancer manifesting in nonsolid nodules

PURPOSE

To assess the feasibility of using CT to correct specific uptake values (SUVs) for fluorodeoxyglucose (FDG) in patients with nonsolid nodules.

METHODS

Patients with FDG-PET/CT and thin-section CT were included in this pilot study. Thirty-five adenocarcinomas manifesting as nonsolid nodules were classified into two groups; 90-100% and 1-89% lepidic component. SUVmax was corrected based on the CT determination of the proportion of soft tissue component within the cancer (SUVatt).

RESULTS

Both SUVmax and SUVatt increased as the percentage of the lepidic component decreased. SUVmax and SUVatt were significantly different between the groups.

CONCLUSION

Extent of invasiveness of nonsolid cancers (as a marker of aggressiveness) can potentially be quantified by PET/CT using a correction method that accounts for the proportion of soft tissue within the tumor.

Clustering approach to identify intratumour heterogeneity combining FDG PET and diffusion-weighted MRI in lung adenocarcinoma

OBJECTIVES

Malignant tumours consist of biologically heterogeneous components; identifying and stratifying those various subregions is an important research topic. We aimed to show the effectiveness of an intratumour partitioning method using clustering to identify highly aggressive tumour subregions, determining prognosis based on pre-treatment PET and DWI in stage IV lung adenocarcinoma.

METHODS

Eighteen patients who underwent both baseline PET and DWI were recruited. Pre-treatment imaging of SUV and ADC values were used to form intensity vectors within manually specified ROIs. We applied k-means clustering to intensity vectors to yield distinct subregions, then chose the subregion that best matched the criteria for high SUV and low ADC to identify tumour subregions with high aggressiveness. We stratified patients into high- and low-risk groups based on subregion volume with high aggressiveness and conducted survival analyses. This approach is referred to as the partitioning approach. For comparison, we computed tumour subregions with high aggressiveness without clustering and repeated the described procedure; this is referred to as the voxel-wise approach.

RESULTS

The partitioning approach led to high-risk (median SUVmax = 14.25 and median ADC = 1.26x10^-3 mm²/s) and low-risk (median SUVmax = 14.64 and median ADC = 1.09x10^-3 mm²/s) subgroups. Our partitioning approach identified significant differences in survival between high- and low-risk subgroups (hazard ratio, 4.062, 95% confidence interval, 1.21 - 13.58, p-value: 0.035). The voxel-wise approach did not identify significant differences in survival between high- and low-risk subgroups (p-value: 0.325).

CONCLUSION

Our partitioning approach identified intratumour subregions that were predictors of survival.

KEY POINTS

• Multimodal imaging of PET and DWI is useful for assessing intratumour heterogeneity. • Data-driven clustering identified subregions which might be highly aggressive for lung adenocarcinoma. • The data-driven partitioning results might be predictors of survival.

Prognostic Impact of the Findings on Thin-Section Computed Tomography in stage I lung adenocarcinoma with visceral pleural invasion

Visceral pleural invasion (VPI) in stageI lung adenocarcinoma is an independent negative prognostic factor. However, no studies proved any morphologic pattern could be referred to as a prognostic factor. Thus, we aim to investigate the potential prognostic impact of VPI by extracting high-dimensional radiomics features on thin-section computed tomography (CT). A total of 327 surgically resected pathological-N0M0 lung adenocarcinoma 3 cm or less in size were evaluated. Radiomics signature was generated by calculating the contribution weight of each feature and validated using repeated leaving-one-out ten-fold cross-validation approach. The accuracy of proposed radiomics signature for predicting VPI achieved 90.5% with ROC analysis (AUC, 0.938, sensitivity, 90.6%, specificity, 93.2%, PPV: 91.2, NPV: 92.8). The cut-off value allowed separation of patients in the validation data into high-risk and low-risk groups with an odds ratio 12.01. Radiomics signature showed a concordance index of 0.895 and AIC value of 88.9% with regression analysis. Among these radiomics features, percentile 10%, wavEnLL_S_2, S_0_1_SumAverage represented as independent factors for determining VPI. Results suggested that radiomics signature on CT exhibited as an independent prognostic factor in discriminating VPI in lung adenocarcinoma and could potentially help to discriminate the prognosis difference in stage I lung adenocarcinoma.

Pathologic stratification of operable lung adenocarcinoma using radiomics features extracted from dual energy CT images

PURPOSE

To evaluate the usefulness of surrogate biomarkers as predictors of histopathologic tumor grade and aggressiveness using radiomics data from dual-energy computed tomography (DECT), with the ultimate goal of accomplishing stratification of early-stage lung adenocarcinoma for optimal treatment.

RESULTS

Pathologic grade was divided into grades 1, 2, and 3. Multinomial logistic regression analysis revealed i-uniformity and 97.5th percentile CT attenuation value as independent significant factors to stratify grade 2 or 3 from grade 1. The AUC value calculated from leave-one-out cross-validation procedure for discriminating grades 1, 2, and 3 was 0.9307 (95% CI: 0.8514-1), 0.8610 (95% CI: 0.7547-0.9672), and 0.8394 (95% CI: 0.7045-0.9743), respectively.

MATERIALS AND METHODS

A total of 80 patients with 91 clinically and radiologically suspected stage I or II lung adenocarcinoma were prospectively enrolled. All patients underwent DECT and F-18-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT, followed by surgery. Quantitative CT and PET imaging characteristics were evaluated using a radiomics approach. Significant features for a tumor aggressiveness prediction model were extracted and used to calculate diagnostic performance for predicting all pathologic grades.

CONCLUSIONS

Quantitative radiomics values from DECT imaging metrics can help predict pathologic aggressiveness of lung adenocarcinoma.

Quantitative image variables reflect the intratumoral pathologic heterogeneity of lung adenocarcinoma

We aimed to compare quantitative radiomic parameters from dual-energy computed tomography (DECT) of lung adenocarcinoma and pathologic complexity.

A total 89 tumors with clinical stage I/II lung adenocarcinoma were prospectively included. Fifty one radiomic features were assessed both from iodine images and non-contrast images of DECT datasets. Comprehensive histologic subtyping was evaluated with all surgically resected tumors. The degree of pathologic heterogeneity was assessed using pathologic index and the number of mixture histologic subtypes in a tumor. Radiomic parameters were correlated with pathologic index. Tumors were classified as three groups according to the number of mixture histologic subtypes and radiomic parameters were compared between the three groups.

Tumor density and 50^th through 97.5^th percentile Hounsfield units (HU) of histogram on non-contrast images showed strong correlation with the pathologic heterogeneity. Radiomic parameters including 75^th and 97.5^th percentile HU of histogram, entropy, and inertia on 1-, 2- and 3 voxel distance on non-contrast images showed incremental changes while homogeneity showed detrimental change according to the number of mixture histologic subtypes (all Ps < 0.05).

Radiomic variables from DECT of lung adenocarcinoma reflect pathologic intratumoral heterogeneity, which may help in the prediction of intratumoral heterogeneity of the whole tumor.

CT Radiomics in Thoracic Oncology: Technique and Clinical Applications

Precision medicine offers better treatment options and improved survival for cancer patients based on individual variability. As the success of precision medicine depends on robust biomarkers, the requirement for improved imaging biomarkers that reflect tumor biology has grown exponentially. Radiomics, the field of study in which high-throughput data are generated and large amounts of advanced quantitative features are extracted from medical images, has shown great potential as a source of quantitative biomarkers in the field of oncology. Radiomics provides quantitative information about the morphology, texture, and intratumoral heterogeneity of the tumor itself as well as features related to pulmonary function. Hence, radiomics data can be used to build descriptive and predictive clinical models that relate imaging characteristics to tumor biology phenotypes. In this review, we describe the workflow of CT radiomics, types of CT radiomics, and its clinical application in thoracic oncology.

Dynamic prognostication using conditional survival analysis for patients with operable lung adenocarcinoma

PURPOSE

To evaluate conditional survival among patients with surgically resected stage I-IIIa lung adenocarcinoma and identify changes in prognostic contributions for various prognostic factors over time.

PATIENTS AND METHODS

We performed conditional survival analysis at each t0 (=0, 1, 2, 3, 4, 5 years) for 723 consecutive patients who underwent surgical resection for lung adenocarcinoma, stratified by various clinico-demographic features, as well as pathologic and imaging (tumor-shadow disappearance ratio [TDR] on CT and maximum standardized uptake value [SUVmax] on PET) characteristics. Uni- and multivariableCox regression analyses were performed to evaluate relationships between those variables and conditional survival.

RESULTS

Three-year conditional overall survival (OS) and disease-free survival (DFS) were 92.12% and 75.51% at baseline, but improved steadily up to 98.33% and 95.95% at 5 years after surgery. In contrast to demographic factors, pathologic (stage, subtype, pathologic grade and differentiation) and radiologic factors (TDR and SUVmax) maintained a statistically significant association with subseqeunt 3-year OS until 3 years after surgery. According to the multivariableanalysis, high SUVmax and low TDR value were independent predictors of subsequent 3-year OS and DFS at baseline, 1 and 2 years after surgery, respectively.

CONCLUSION

Our findings based on CS provide theoretical background for clinicians to plan longer period of surveillance following lung adenocarcinoma resection in survivors with preoperatively high SUVmax and low TDR on PET-CT and chest CT, respectively.

Imaging Phenotyping Using Radiomics to Predict Micropapillary Pattern within Lung Adenocarcinoma

INTRODUCTION

Lung adenocarcinomas (ADCs) with a micropapillary pattern have been reported to have a poor prognosis. However, few studies have reported on the imaging-based identification of a micropapillary component, and all of them have been subjective studies dealing with qualitative computed tomography variables. We aimed to explore imaging phenotyping using a radiomics approach for predicting a micropapillary pattern within lung ADC.

METHODS

We enrolled 339 patients who underwent complete resection for lung ADC. Histologic subtypes and grades of the ADC were classified. The amount of micropapillary component was determined. Clinical features and conventional imaging variables such as tumor disappearance rate and maximum standardized uptake value on positron emission tomography were assessed. Quantitative computed tomography analysis was performed on the basis of histogram, size and shape, Gray level co-occurrence matrix-based features, and intensity variance and size zone variance-based features.

RESULTS

Higher tumor stage (OR = 3.270, 95% confidence interval [CI]: 1.483-7.212), intermediate grade (OR = 2.977, 95% CI: 1.066-8.316), lower value of the minimum of the whole pixel value (OR = 0.725, 95% CI: 0.527-0.98800), and lower value of the variance of the positive pixel value (OR = 0.961, 95% CI: 0.927-0.997) were identified as being predictive of a micropapillary component within lung ADC. On the other hand, maximum standardized uptake value and tumor disappearance rate were not significantly different in groups with a micropapillary pattern constituting at least 5% or less than 5% of the entire tumor.

CONCLUSION

A radiomics approach can be used to interrogate an entire tumor in a noninvasive manner. Combining imaging parameters with clinical features can provide added diagnostic value to identify the presence of a micropapillary component and thus, can influence proper treatment planning.

Role of CT and PET Imaging in Predicting Tumor Recurrence and Survival in Patients with Lung Adenocarcinoma: A Comparison with the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society Classification of Lung Adenocarcinoma

INTRODUCTION

Recently, a new lung adenocarcinoma classification scheme was published. The prognostic value of this new classification has not been elaborated together with the value of imaging biomarkers including computed tomography (CT) and positron emission tomography (PET).

METHODS

We reviewed pathologic specimens and imaging characteristics of primary tumors from 723 consecutive patients who underwent surgical resection for lung adenocarcinoma. On pathology, the predominant histologic subtype and pattern group were quantified. Tumor-shadow disappearance ratio (TDR) on CT and maximum standardized uptake value (SUVmax) on PET were assessed. The relationships between those variables and survival (overall survival [OS] and disease-free survival) were analyzed by using Kaplan-Meier curves and Cox regression analyses.

RESULTS

The median follow-up period was 3.8 years. There were 137 patients (19%) with recurrence and 167 patients (23%) with metastasis after surgical resection. Among 723 patients, 35 patients (4.8%) had adenocarcinoma in situ, 34 patients (4.7%) had minimally invasive adenocarcinoma, 125 patients (17.3%) had lepidic predominant, 314 patients (43.4%) had acinar predominant, 65 patients (9.0%) had papillary predominant, 23 patients (3.2%) had micropapillary predominant, 113 patients (15.6%) had solid predominant, and 14 patients (1.9%) had variant adenocarcinomas. OS and disease-free survival rates were significantly different according to TDR on CT and SUVmax on PET, predominant subtypes, and pattern groups. On multivariate analysis, the SUVmax (p < 0.001), TDR (p = 0.038), and pattern group (p = 0.015) were independent predictors of OS.

CONCLUSIONS

TDR on CT, SUVmax on PET, and the new histologic classification schemes appear to be promising parameters for the prognostic stratification of patients with lung adenocarcinomas, allowing for the triage of patients who necessitate further staging workup and adjuvant therapy.

Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art

With the development of functional imaging modalities we now have the ability to study the microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use of automated or semi-automated post-processing and analysis of large amounts of quantitative imaging features that can be derived from medical images. The automated generation of these analytical features helps to quantify a number of variables in the imaging assessment of lung malignancy. These imaging features include: tumor spatial complexity, elucidation of the tumor genomic heterogeneity and composition, subregional identification in terms of tumor viability or aggressiveness, and response to chemotherapy and/or radiation. Therefore, a radiomic approach can help to reveal unique information about tumor behavior. Currently available radiomic features can be divided into four major classes: (a) morphological, (b) statistical, (c) regional, and (d) model-based. Each category yields quantitative parameters that reflect specific aspects of a tumor. The major challenge is to integrate radiomic data with clinical, pathological, and genomic information to decode the different types of tissue biology. There are many currently available radiomic studies on lung cancer for which there is a need to summarize the current state of the art.

Prognosis in Resected Invasive Mucinous Adenocarcinomas of the Lung: Related Factors and Comparison with Resected Nonmucinous Adenocarcinomas

INTRODUCTION

In the 2015 World Health Organization classification, invasive mucinous adenocarcinoma (IMA) is categorized as one of various subtypes of lung invasive adenocarcinoma (ADC). However, no comprehensive analysis regarding the clinicoradiologic and prognostic features of IMA has been reported. We aimed to report prognostic factors in IMA and to compare the prognosis of IMAs with that of nonmucinous ADCs.

METHODS

We included 81 patients with a solitary IMA of the lung and analyzed them from the standpoint of clinicoradiologic presentation. Survival rates were assessed and compared with those of 646 resected solitary invasive nonmucinous ADCs.

RESULTS

Patients with IMA showed longer disease-free survival (DFS) than did those with nonmucinous ADCs, whereas overall survival (OS) did not differ significantly (p = 0.023 and p = 0.824, respectively). The DFS of patients with IMA was between that of patients with lepidic predominant (low-grade) and acinar/papillary predominant (intermediate-grade) ADC. In terms of OS, the survival curve of IMA was similar to that of acinar/papillary predominant ADC. Multivariate analysis revealed that tumor size (hazard ratio [HR] = 1.370, 95% confidence interval [CI]: 1.141-1.645, p = 0.001) and maximum standardized uptake value (HR = 1.338, 95% CI: 1.160-1.544, p < 0.001) were independent poor prognostic predictors for DFS. Regarding OS, tumor size (HR = 1.309, 95% CI: 1.092-1.570; p = 0.004) was the only predictor of poor prognosis.

CONCLUSION

Patients with IMA demonstrate a DFS between that of patients with low-grade nonmucinous ADC and that of patients with intermediate-grade nonmucinous ADC and an OS similar to that of patients with intermediate-grade nonmucinous ADC. In IMA, tumor size and maximum standardized uptake value are the factors related to mitigating DFS and tumor size is the only predictor for reduced OS.

Pulmonary Intravascular Lymphomatosis: Clinical, CT, and PET Findings, Correlation of CT and Pathologic Results, and Survival Outcome

Purpose To describe clinical, computed tomographic (CT), and positron emission tomographic (PET) features, correlation of CT and pathologic results, and survival of patients with pulmonary intravascular lymphomatosis. Materials and Methods The institutional review board approved this retrospective study with waiver of patient consent. Forty-two patients with pulmonary intravascular lymphomatosis were identified, 11 (26%) of whom showed lung involvement. CT features were correlated with histopathologic results. Clinical and survival outcomes were compared between patients with and those without pulmonary involvement by adopting the χ(2), Student t, or Kaplan-Meier analysis with log-rank tests. Results At clinical presentation, all 11 patients showed B symptoms (systemic symptoms of fever, night sweats, and weight loss), 10 had respiratory and four had neurologic symptoms, and two had skin lesions. Patients received cyclophosphamide, doxorubicin, vincristine, and prednisone chemotherapy with (n = 5) or without (n = 6) rituximab, and seven (64%) patients died. Patients with lung involvement showed reduced overall and recurrence-free survival (median; 10.8 and 18.9 months, respectively) compared with those without lung involvement (median, 18.4 and 31.0 months, respectively) (P = .338 and .065, respectively). The most common CT abnormality was bilateral ground-glass opacity (GGO, n = 10), with increased fluorodeoxyglucose uptake at PET/CT (seven of seven patients). GGO correlated histopathologically with the expanded alveolar septal vasculatures and perivascular spaces filled with neoplastic lymphoid cells. Conclusion Pulmonary intravascular lymphomatosis appeared as bilateral GGO on CT images, with increased fluorodeoxyglucose uptake on PET/CT images. GGO on CT images correlated with the area of expanded alveolar septae because of distended vessels filled with neoplastic lymphoid cells. (©) RSNA, 2016 Online supplemental material is available for this article.

Improvement in imaging diagnosis technique and modalities for solitary pulmonary nodules: from ground-glass opacity nodules to part-solid and solid nodules

With advances in CT technology and the popularity of low-dose CT as a device for lung cancer screening, the detection rate of sub-solid pulmonary nodules as well as solid nodules has been increased. Distinguishing solid from sub-solid features is an essential step in the CT evaluation of solitary pulmonary nodules (SPNs) because strategies for nodule characterization and guidelines for management are different for each category. In addition to conventional CT parameters, numerous novel concepts and modalities have been developed. Although there is currently no single effective method for differentiating malignant from benign nodules, growth rate measurement using volumetry, evaluation of tumor vascularity on dynamic helical CT, dual-energy CT and MRI and physiologic evaluation with PET/CT can all be useful for nodule characterization. New techniques such as tomosynthesis can improve detection over radiography alone. The purpose of this article is to enhance our understanding of the evidence-based strategies involved in diagnosing SPNs.

Computer-Aided Nodule Assessment and Risk Yield Risk Management of Adenocarcinoma: The Future of Imaging?

Increased clinical use of chest high-resolution computed tomography results in increased identification of lung adenocarcinomas and persistent subsolid opacities. However, these lesions range from very indolent to extremely aggressive tumors. Clinically relevant diagnostic tools to noninvasively risk stratify and guide individualized management of these lesions are lacking. Research efforts investigating semiquantitative measures to decrease interrater and intrarater variability are emerging, and in some cases steps have been taken to automate this process. However, many such methods currently are still suboptimal, require validation and are not yet clinically applicable. The computer-aided nodule assessment and risk yield software application represents a validated tool for the automated, quantitative, and noninvasive tool for risk stratification of adenocarcinoma lung nodules. Computer-aided nodule assessment and risk yield correlates well with consensus histology and postsurgical patient outcomes, and therefore may help to guide individualized patient management, for example, in identification of nodules amenable to radiological surveillance, or in need of adjunctive therapy.

Quantitative CT Scanning Analysis of Pure Ground-Glass Opacity Nodules Predicts Further CT Scanning Change

BACKGROUND

We sought to determine whether quantitative analysis of lung adenocarcinoma manifesting as a ground-glass opacity (GGO) nodule (GGN) on initial CT scans can predict further CT scanning change or rate of growth.

METHODS

This retrospective study included patients with lung adenocarcinoma manifesting as pure GGN on initial CT scans who were followed up with interval CT scanning until resection. All pure GGNs were classified based on CT scanning interval change in three subgroups as follows: group A (development of solid component), group B (growth of GGO component), and group C (no change in size). Nodule size, volume, density, mass, and CT scanning attenuation values were assessed from initial CT data sets.

RESULTS

Fifty-four pure GGNs were enrolled and classified into group A (n = 9), group B (n = 25), and group C (n = 20). Nodule size, volume, mass, and density of the GGNs in each subgroup were not significantly different. The 97.5th percentile CT scanning attenuation value and slope of CT scanning attenuation values from the 2.5th to the 97.5th percentile were significantly different among the three subgroups (P = .02, P < .00). Three of nine (33%) pure GGNs showing a new solid component developed a solid component within 6 months.

CONCLUSIONS

The 97.5th percentile CT scanning attenuation value and slope of CT scanning attenuation values from the 2.5th to the 97.5th percentile could be helpful in predicting future CT scanning change and growth rate of pure GGNs. Pure GGNs showing higher 97.5th percentile CT scanning attenuation values and steeper slopes of CT scanning attenuation values may require more frequent follow-up than the usual interval of 6 months.

Clinical impacts of a micropapillary pattern in lung adenocarcinoma: a review

Lung adenocarcinoma with a micropapillary pattern (MPPAC) has recently drawn increased attention among researchers. Micropapillary-predominant adenocarcinoma (MPA), which is defined by micropapillary pattern (MPP), is the primary histological pattern observed semiquantitatively in 5% increments on resection specimens, and MPA was formally determined to be a new histological subtype according to the new multidisciplinary classification in 2011. According to published studies, MPPAC is most common in males and nonsmokers and is associated with lymphatic invasion, pleural invasion, and lymph node metastases. MPPAC often presents as part-solid and lobulated nodules in computed tomography scans. MPP tends to have a higher maximum standardized uptake value as determined by fluorodeoxyglucose positron emission tomography combined with computed tomography, indicating a high risk of recurrence. Molecular markers, including vimentin, napsin A, phosphorylated c-Met, cytoplasmic maspin, Notch-1, MUC1, and tumoral CD10, may have higher expression in MPPAC than other subtypes; conversely, markers such as MUC4 and surfactant apoprotein A have lower expression in MPPAC. MPPAC with EGFR mutations can benefit from treatment with EGFR tyrosine kinase inhibitors. Furthermore, a complete lobectomy may be more suitable than limited resection for MPPAC because of the low sensitivity of intraoperative frozen sections and the high risk of lymph node metastasis. MPA benefits more from adjuvant chemotherapy than do other histological subtypes, whereas MPA does not benefit from adjuvant radiotherapy. Of note, MPP is associated with poor prognosis in early-stage lung adenocarcinoma, but the prognostic value of MPP is controversial in advanced-stage lung adenocarcinoma.

Clinical impact of minimal micropapillary pattern in invasive lung adenocarcinoma: prognostic significance and survival outcomes

Micropapillary subtype has recently been established to be a distinct marker for poor prognosis in lung adenocarcinomas. According to the current classification of lung adenocarcinomas, all subtypes are listed semiquantitatively in 5% increments. In other words, a minimal amount of the micropapillary pattern, precisely <5% of the entire tumor is disregarded. Therefore, we sought to assess the prognostic significance and survival outcomes in patients with a micropapillary pattern proportion of <5% of the entire tumor. A total of 525 patients with lung adenocarcinoma were classified into 3 subgroups according to the presence and proportion of micropapillary subtype: (1) ≥5% of the micropapillary pattern (n=114); (2) <5% of the micropapillary pattern (n=115); and (3) absence (<1%) of the micropapillary pattern (n=296). Sex, TNM stage, lymph node status (N status), tumor size, and predominant subtype demonstrated a significant difference among the 3 subgroups. Overall survival (OS) and disease-free survival (DFS) were significantly different among the 3 subgroups (P=0.009 and 0.001 for OS and DFS, respectively). Furthermore, OS was significantly better in patients without the micropapillary pattern (<1%) than in those with <5% (P=0.034). At multivariate analyses, age (P=0.005) and N status (P=0.005) were independent prognostic factors influencing OS. In conclusion, our results demonstrated that even a small proportion of the micropapillary pattern, specifically <5% of the entire tumor has a significant prognostic impact on OS. N status remained an independent prognostic factor that negatively influenced OS.

Prevalence and clinical significance of incidental (18)F-fluoro-2-deoxyglucose uptake in prostate

Purpose

To investigate the prevalence and clinical significance of incidental prostate fluoro-2-deoxyglucose (FDG) uptake and to evaluate its impact on patient management.

Materials and Methods

Of 47,109 men who underwent FDG positron emission tomography between 2004 and 2014, 1,335 (2.83%) demonstrated incidental FDG uptake in the prostate, with 99 of the latter undergoing prostate biopsy. The primary end point was the histological presence of prostate adenocarcinoma in the biopsy specimen. Outcomes, including treatment methods, survival, and causes of death, were also assessed. Factors associated with the diagnosis of prostate cancer were evaluated by using logistic regression analysis.

Results

Patients with prostate cancer were more likely to have higher serum prostate-specific antigen (PSA) (p=0.001) and focal FDG uptake (p=0.036) than were those without. Prostate cancer occurred in 1 of 26 patients (3.8%) with serum PSA<2.5 ng/mL, compared with 40 of 67 patients (59.7%) with serum PSA≥2.5 ng/mL. Multivariable analysis showed that focal lesions (odds ratio [OR], 5.50; p=0.038), age (OR, 1.06; p=0.031), and serum PSA (OR, 1.28; p=0.001) were independent predictors of prostate cancer diagnosis. Most patients with prostate cancer had organ-confined tumors. Of these, 12 (29.3%) underwent radical prostatectomy and 25 (60.9%) received hormone therapy. Of the 11 patients who died, 9 died of primary cancer progression, with only 1 patient dying from prostate cancer.

Conclusions

The prevalence of incidental FDG uptake in the prostate was not high, although patients with elevated serum PSA had a higher incidence of prostate cancer. Patients with FDG uptake in the prostate should be secondarily evaluated by measuring serum PSA, with those having high serum PSA undergoing prostate biopsy.

Predictive factors for survival in stage IIIA N2 NSCLC patients treated with neoadjuvant CCRT followed by surgery

PURPOSE

To assess the impact of imaging, surgical, histopathologic and patient-related factors on the risks of recurrence and overall survival (OS) in stage IIIA-N2 non-small cell lung cancer (NSCLC) patients undergoing definitive resection after neoadjuvant concurrent chemoradiotherapy (CCRT).

METHODS

We retrospectively examined 104 consecutive patients with stage IIIA-N2 NSCLC who received neoadjuvant CCRT followed by surgery between 2008 and 2011. While reviewing the clinical and surgical data, we also assessed histopathologic and imaging (CT and PET/CT) factors. Disease-free survival (DFS) and OS were estimated with predictors for recurrence and survival.

RESULTS

The 3-year OS for patients with and without recurrence was 37.1 and 63.3 %, respectively (p < 0.001). Size decrease of target lesion(s) ≥36 % on post-neoadjuvant CCRT CT (p = 0.048) and viable tumor size on surgical specimen <9.4 mm (p = 0.035) were related to longer OS. Regarding shorter DFS, tumor size on post-neoadjuvant CCRT CT (p = 0.046), SUV(max) of the primary tumor (p = 0.011), male gender (p = 0.023), total tumor size on surgical specimen (p = 0.041) and viable tumor size on surgical specimen (p = 0.043) were the significant predictors.

CONCLUSIONS

OS is prolonged with greater extent of size decrease of target lesion(s) on post-neoadjuvant CCRT CT and smaller viable tumor size on surgical specimen. Larger tumor size on post-neoadjuvant CCRT CT, higher SUV(max), male gender, larger total tumor size and larger viable tumor size on surgical specimen may herald the higher probability of recurrence and the necessity of more attention.

Implementing the new IASLC/ATS/ERS classification of lung adenocarcinomas: results from international and Chinese cohorts

A new histologic classification of lung adenocarcinoma was proposed by the International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society (IASLC/ATS/ERS) in 2011 to provide uniform terminology and diagnostic criteria for multidisciplinary strategic management. This classification proposed a comprehensive histologic subtyping (lepidic, acinar, papillary, micropapillary, and solid pattern) and a semi-quantitative assessment of histologic patterns (in 5% increments) in an effort to choose a single, predominant pattern in invasive adenocarcinomas. The prognostic value of this classification has been validated in large, independent cohorts from multiple countries. In patients who underwent curative-intent surgery, those with either an adenocarcinoma in situ (AIS) or a minimal invasive adenocarcinoma have nearly 100% disease-free survival and are designated "low grade tumors". For invasive adenocarcinomas, the acinar and papillary predominant histologic subtypes were usually designated as "intermediate grade" while the solid and micropapillary predominant histologic subtypes were designated "high grade" tumors; this was based on the statistic difference of overall survival. This classification, coupled with additional prognostic factors [nuclear grade, cribriform pattern, high Ki-67 labeling index, thyroid transcription factor-1 (TTF-1) immunohistochemistry, immune markers, and (18)F-fluorodeoxyglucose uptake on positron emission tomography (PET)] that we have published on, could further stratify patients into prognostic subgroups and may prove helpful for individual patient care. With regard to Chinese oncologists, the implementation of this new classification only requires hematoxylin and eosin (H&E) stained slides and basic pathologic training, both of which require no additional costs. More importantly, this new classification system could provide informative data for better selection and stratification of clinical trials and molecular studies.

Lung cancer imaging

Lung cancer remains the leading cause of cancer-related deaths in the US. Imaging plays an important role in the diagnosis, staging, and follow-up evaluation of patients with lung cancer. With recent advances in technology, it is important to update and standardize the radiological practices in lung cancer evaluation. In this article, the authors review the main clinical applications of different imaging modalities and the most common radiological presentations of lung cancer.

A prospective investigation into the clinical impact of 4D-PET/CT in the characterisation of solitary pulmonary nodules

Background

While the effects of respiratory motion on measuring metabolic signal in PET/CT scanning are well known, it is still standard practice in most centres to scan patients while breathing freely with no correction for the effects of respiratory motion. The aim of this study was to investigate the impact of 4D-PET/CT in classifying lesions in patients with a radiologically-indeterminate solitary pulmonary nodule.

Methods

Twenty consecutive patients with a solitary pulmonary nodule for investigation were prospectively recruited and completed a whole-body (WB)-PET/CT and 4D-PET/CT in the same session. The reporting physician initially classified the nodule using a 5-point scale (Definitely Malignant, Probably Malignant, Indeterminate, Probably benign, Definitely Benign) on the WB-PET/CT. The physician was then shown the 4D-PET/CT and asked if they would re-classify the lesion. Frequency, sensitivity, specificity and accuracy values were calculated for WB-PET/CT alone and then with the addition of the 4D-PET/CT.

Results

There were no changes in the classification for nodules initially classed as either benign or malignant with the addition of a 4D-PET/CT. However changes were observed between WB and 4D-PET/CT scans in lesions initially classified as indeterminate. When indeterminate lesions were defined as malignant there was a minor increase in sensitivity (from 73% to 75%), in specificity (56%-63%) and in accuracy (65%-70%) but these results do not reach statistical significance. When the Indeterminate lesions were defined as benign there was an increase in sensitivity (from 55% to 67%) but there was a reduction in the specificity (100%-75%) and accuracy (75%-70%) with the addition of the 4D-PET/CT but again the results did not reach statistical significance.

Conclusion

The addition of 4D-PET/CT is most likely to have an impact on those nodules initially classified as indeterminate on standard WB-PET/CT. In lesions classified as benign or malignant on standard WB-PET/CT the addition of a 4D-PET/CT is less likely to impact lesion classification. While 4D-PET/CT does improve the measurement of the metabolic signal, it does not overcome inherent limitations of FDG in differentiating a malignant lesion from inflammatory processes, correct for partial volume effects or compensate for the low intrinsic FDG-avidity of some malignancies.

Pure ground-glass opacity neoplastic lung nodules: histopathology, imaging, and management

OBJECTIVE

The purpose of this article is to discuss histologic diagnosis of pure pulmonary ground-glass opacity nodules (GGNs), high-resolution CT (HRCT) findings and pathologic correlation, and management.

CONCLUSION

When pure GGNs are greater than 15 mm in diameter with nodularity or have high pixel attenuation (>-472 HU), the nodules are more likely to be invasive adenocarcinomas. Sublobar resection with a secured safety margin and without nodal dissection is performed for HRCT-suggested pure-GGN invasive adenocarcinomas and has a 100% 5-year survival rate.

Quantitative CT variables enabling response prediction in neoadjuvant therapy with EGFR-TKIs: are they different from those in neoadjuvant concurrent chemoradiotherapy?

Background and Purpose

To correlate changes of various CT parameters after the neoadjuvant treatment in patients with lung adenocarcinoma with pathologic responses, focused on their relationship with different therapeutic options, particularly of EGFR-TKI and concurrent chemoradiation therapy (CCRT) settings.

Materials and Methods

We reviewed pre-operative CT images of primary tumors and surgical specimens obtained after neoadjuvant therapy (TKI, n = 23; CCRT, n = 28) from 51 patients with lung adenocarcinoma. Serial changes in tumor volume, density, mass, skewness/kurtosis, and size-zone variability/intensity variability) were assessed from CT datasets. The changes in CT parameters were correlated with histopathologic responses, and the relationship between CT variables and histopathologic responses was compared between TKI and CCRT groups.

Results

Tumor volume, mass, kurtosis, and skewness were significant predictors of pathologic response in CCRT group in univariate analysis. Using multivariate analysis, kurtosis was found to be independent predictor. In TKI group, intensity variability and size-zone variability were significantly decreased in pathologic responder group. Intensity variability was found to be an independent predictor for pathologic response on multivariate analysis.

Conclusions

Quantitative CT variables including histogram or texture analysis have potential as a predictive tool for response evaluation, and it may better reflect treatment response than standard response criteria based on size changes.

Prevalence and risk of cancer of incidental uptake in prostate identified by fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography

OBJECTIVE

The objective was to investigate the prevalence of incidental fluorine-18 fluorodeoxyglucose (FDG) uptake in positron emission tomography/computed tomography.

METHODS

A total of 11,239 male nonprostate disease patients were included retrospectively.

RESULTS

The prevalence of incidental prostate FDG uptake was approximately 1.8%. Among 198 incidental lesions, 100 patients had further examinations; 20 lesions were confirmed to be malignant, while 80 lesions were benign. After logistic regression analysis, age, site, and the maximum standard uptake value were the potent predictors for differentiation of malignant prostate lesions.

CONCLUSION

When focal FDG uptake in the peripheral zone of prostate is detected, especially in elderly men, further clinical evaluation is recommended.

Persistent pure ground-glass opacity lung nodules ≥ 10 mm in diameter at CT scan: histopathologic comparisons and prognostic implications

BACKGROUND

Little is known about the histopathology and prognosis of persistent pure ground-glass opacity nodules (GGNs) of ≥ 10 mm in diameter. We aimed to compare the morphologic features of persistent pure GGNs of ≥ 10 mm in diameter at thin-section CT (TSCT) scan with histopathology and patient prognosis.

METHODS

A total of 46 resected GGNs that were evaluated with TSCT scan and followed up for ≥ 3 years were included in this study. Correlations between histopathology (adenocarcinoma in situ [AIS], minimally invasive adenocarcinoma [MIA], and invasive adenocarcinoma) and CT scan characteristics were examined. CT scan and clinicodemographic data were investigated by univariate and multivariate analyses to identify features that helped distinguish invasive adenocarcinoma from AIS or MIA. Disease recurrence was also evaluated.

RESULTS

The nodules included 19 AISs (41%), nine MIAs (20%), and 18 invasive adenocarcinomas (39%). On univariate analysis, the presence of air bronchogram (P = .012), size of nodule (P = .032, cutoff = 16.4 mm in diameter), and mass of nodule (P = .040, cutoff = 0.472 g) were significant factors that differentiated invasive adenocarcinoma from AIS or MIA. On multivariate analysis, size (P = .010) and mass of nodule (P = .016) were significant determinants for invasive adenocarcinoma. There were no cases of recurrence during a follow-up period of ≥ 3 years after surgical resection.

CONCLUSIONS

In persistent pure GGNs of ≥ 10 mm in diameter, the size and mass of the nodule are determinants of invasive adenocarcinoma, for which surgical resection leads to excellent prognosis.