Clinical and CT characteristics of surgically resected lung adenocarcinomas harboring ALK rearrangements or EGFR mutations

Clinical characteristics and progression of pre-/minimally invasive lung adenocarcinoma harboring ALK or RET rearrangements: a retrospective cohort study

Background

Patients harboring anaplastic lymphoma kinase (ALK) or rearranged during transfection (RET) rearrangements are usually diagnosed at a relatively late stage with nodal and distant metastasis, and rapid progression course of ALK/RET fusion-positive lung cancer were well-known. However, clinical characteristics and course of pre-/minimally invasive lung adenocarcinoma harboring ALK or RET fusions are poorly described. Identifying patients with gene fusions at early stage may offer surgical options that could cure those patients.

Methods

We retrospectively included patients with surgically resected pre-/minimally invasive lung adenocarcinomas harboring epidermal growth factor receptor (EGFR) mutations or ALK/RET rearrangements, and further compared the patient clinical characteristics, nodule natural course, and survival outcomes. Radiological characteristics including ground-glass component, cystic airspace, pleural attachment, etc. were specially assessed for this study. EGFR (exons 18-22) was detected by Sanger sequencing and quantitative real-time polymerase chain reaction (qRT-PCR) was used to analyze the ALK/RET rearrangements. Lung cancer-specific survival (LCSS), relapse-free survival (RFS), and overall survival (OS) were all evaluated.

Results

Of 238 patients with pre-/minimally invasive lung adenocarcinomas, 226 patients had EGFR mutations, 7 patients had ALK fusions, and 5 patients had RET fusions. Average age at surgery was 45.3 years for ALK/RET-positive group and 52.6 years for EGFR-positive group (P=0.049). Radiologically, among the 12 patients with ALK/RET fusions, the majority of lesions (10/12) manifested as mixed ground-glass opacities (mGGOs), which was significantly more prevalent when compared with patients with EGFR mutations (83.4% vs. 24.3%, P<0.001). Moreover, a substantial proportion of cystic airspace was found in ALK/RET-positive group but not in EGFR-positive group (66.7% vs. 14.2%, P<0.001). Among four patients with ALK/RET fusions undergoing surveillance over 1 year before surgery, two of them developed rapid radiologic progression. The 5-year LCSS and RFS were 100%, 100% for ALK/RET-positive group, and 100%, 100% for EGFR-positive group, respectively.

Conclusions

ALK/RET-positive pre-/minimally invasive lung adenocarcinomas were mostly characterized as mGGOs with cystic airspace developing rapid nodule progression, and no recurrence occurred during long-term follow-up after resection. This provides insights into proper curative surgery timing in the management of patients with gene fusions. However, these findings must be treated with caution and validated in future multi-center studies with larger sample size.

Clinicopathological and computed tomography features of patients with early-stage non-small-cell lung cancer harboring ALK rearrangement

BACKGROUND

Although some studies have assessed the correlation between computed tomography (CT) features and anaplastic lymphoma kinase (ALK) rearrangement in patients with non-small-cell lung cancer (NSCLC), few have focused on early-stage patients. The results of some previous studies are inconsistent and contradictory. Therefore, this study aimed to analyze the clinicopathological and CT features of patients with early-stage NSCLC harboring ALK rearrangement.

METHODS

This retrospective analysis included 65 patients with ALK rearrangement and 629 ALK-negative patients. All patients had surgically resected NSCLC and were diagnosed with stage IA or stage IIB NSCLC. Clinicopathological features and CT signs, including tumor size and density, consolidation tumor ratio (CTR), lesion location, round or irregular shape, lobulated or spiculated margins, air bronchograms, bubble-like lucency or cavities, and pleural retraction, were investigated according to different genotypes.

RESULTS

The prevalence of ALK rearrangement in patients with early-stage NSCLC was 9.3% (65/694). Patients with ALK rearrangement were significantly younger than those without ALK rearrangement (P = 0.033). The frequency of moderate cell differentiation was significantly lower in tumors with ALK rearrangement than in those without ALK rearrangement (46.2% vs. 59.8%, P = 0.034). The frequency of the mucinous subtype was significantly higher in the ALK-positive group than in the ALK-negative group (13.8% vs. 5.4%, P = 0.007). No significant differences were found in any CT signs between the ALK-positive and ALK-negative groups.

CONCLUSIONS

Patients with ALK-positive lung cancer may have specific clinicopathological features, including younger age, lower frequency of moderate cell differentiation, and higher frequency of the mucinous type. CT features may not correlate with ALK rearrangement in early-stage lung cancer. Immunohistochemistry or next-generation sequencing is needed to further clarify the genomic mutation status.

Characteristic computed tomography features in mesenchymal-epithelial transition exon14 skipping-positive non-small cell lung cancer

Background

Mesenchymal-epithelial transition exon14 (METex14) skipping is one of the therapeutic driver oncogene mutations in non-small cell lung cancer (NSCLC), and can be treated with tepotinib and capmatinib. There is only one report on computed tomography (CT) findings of METex14 skipping-positive NSCLC, which shows that the primary tumor tends to have a large mass in the upper lobe, and extrathoracic metastases are common. This study examined the CT findings of METex14 skipping-positive NSCLC, focusing on the features of the margins and internal structures.

Methods

We consecutively included patients with METex14 skipping-positive NSCLC who were diagnosed between January 2018 and December 2020 at four independent institutions. We retrospectively reviewed the patient demographics and CT findings for tumor margins (invasion into surrounding tissue, lobulation, pleural indentation, spicula, and ground-glass opacity) and internal structures (air bronchograms, cavitation and internal low-density area).

Results

Fifteen patients with METex14 skipping-positive NSCLC were identified. Almost half of the patients were men (7/15; 46.7%), and their median age was 75.0 years. More than half were either current or former smokers (9/15; 60.0%). A vast majority of histological subtypes were adenocarcinoma (10/15; 66.7%), followed by pleomorphic carcinoma (3/15; 20.0%) and squamous cell carcinoma (2/15; 13.3%). With regard to CT findings, most primary tumors presented as masses larger than 30 mm (12/15; 80.0%) and were located in the upper lobes (12/15; 80.0%). Invasion into surrounding tissue and presence of internal low-density areas were observed in 60.0% (9/15) and 66.7% (10/15) of the primary tumors, respectively. Additionally, their frequencies increased to 72.7% (8/11) and 90.9% (10/11) in stage III/IV cases, respectively. In lymph node metastasis, internal low-density areas were observed in 8/10 cases (80.0%). Although these two CT features were rarely observed in distant metastases at diagnosis, they became apparent with progression of the metastatic tumor size.

Conclusions

METex14 skipping-positive NSCLC tumors tend to invade surrounding tissue and possess internal low-density areas. These CT findings might be characteristic of METex14 skipping-positive NSCLC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-02037-4.

Preoperative prediction of the degree of differentiation of lung adenocarcinoma presenting as sub-solid or solid nodules with a radiomics nomogram

AIM

To develop and validate a radiomics nomogram for prediction of degree of differentiation in lung adenocarcinoma presenting as sub-solid or solid nodules.

MATERIALS AND METHODS

A total of 438 patients with histopathologically confirmed adenocarcinoma (248 non-poorly differentiated and 190 poorly differentiated) were divided into training cohort (n=235) and internal validation cohort (n=203) according to surgery sequence. Sixty patients form public TCIA dataset were selected for external validation. One thousand, two hundred and eighteen radiomics features were extracted from each volumetric region of interest and a least absolute shrinkage and selection operator logistic regression was applied to select meaningful radiomic features for building a radiomics score (Rad-score) model. A nomogram model incorporating the Rad-score and type was established after multivariable logistic regression. The discrimination efficiency, calibration efficacy, and clinical utility value of the nomogram were evaluated.

RESULTS

The Rad-score model could predict the differentiation degree of lung adenocarcinoma with an area under the curve (AUC) of 0.83 (95% confidence interval [CI]: 0.78-0.89) in the internal validation cohort. The AUC of the nomogram and radiographic model was 0.86 (95% CI: 0.80-0.91), 0.78 (95% CI: 0.72-0.84) in the internal validation cohort respectively. The AUC of the nomogram in the external validation cohort was 0.73 (95% CI: 0.58-0.88). Delong's test showed that the nomogram performed better than radiographic features alone (p=0.001).

CONCLUSIONS

The proposed radiomics nomogram has the potential to predict the differentiation degree of lung adenocarcinoma preoperatively.

Radiomics and Radiogenomics in Evaluation of Colorectal Cancer Liver Metastasis

Colorectal cancer is one common digestive malignancy, and the most common approach of blood metastasis of colorectal cancer is through the portal vein system to the liver. Early detection and treatment of liver metastasis is the key to improving the prognosis of the patients. Radiomics and radiogenomics use non-invasive methods to evaluate the biological properties of tumors by deeply mining the texture features of images and quantifying the heterogeneity of metastatic tumors. Radiomics and radiogenomics have been applied widely in the detection, treatment, and prognostic evaluation of colorectal cancer liver metastases. Based on the imaging features of the liver, this paper reviews the current application of radiomics and radiogenomics in the diagnosis, treatment, monitor of disease progression, and prognosis of patients with colorectal cancer liver metastases.

Clinical and CT patterns to predict EGFR mutation in patients with non-small cell lung cancer: A systematic literature review and meta-analysis

Purpose

This study aims to determine if the presence of specific clinical and computed tomography (CT) patterns are associated with epidermal growth factor receptor (EGFR) mutation in patients with non-small cell lung cancer.

Methods

A systematic literature review and meta-analysis was carried out in 6 databases between January 2002 and July 2021. The relationship between clinical and CT patterns to detect EGFR mutation was measured and pooled using odds ratios (OR). These results were used to build several mathematical models to predict EGFR mutation.

Results

34 retrospective diagnostic accuracy studies met the inclusion and exclusion criteria. The results showed that ground-glass opacities (GGO) have an OR of 1.86 (95%CI 1.34 −2.57), air bronchogram OR 1.60 (95%CI 1.38 – 1.85), vascular convergence OR 1.39 (95%CI 1.12 – 1.74), pleural retraction OR 1.99 (95%CI 1.72 – 2.31), spiculation OR 1.42 (95%CI 1.19 – 1.70), cavitation OR 0.70 (95%CI 0.57 – 0.86), early disease stage OR 1.58 (95%CI 1.14 – 2.18), non-smoker status OR 2.79 (95%CI 2.34 – 3.31), female gender OR 2.33 (95%CI 1.97 – 2.75). A mathematical model was built, including all clinical and CT patterns assessed, showing an area under the curve (AUC) of 0.81.

Conclusions

GGO, air bronchogram, vascular convergence, pleural retraction, spiculated margins, early disease stage, female gender, and non-smoking status are significant risk factors for EGFR mutation. At the same time, cavitation is a protective factor for EGFR mutation. The mathematical model built acts as a good predictor for EGFR mutation in patients with lung adenocarcinoma.

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GGO, air bronchogram, vascular convergence, pleural retraction, and spiculated margins, are risk factors for EGFR mutation.

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Early disease stage, female gender and non-smoking status are risk factors for EGFR mutation.

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Cavitation is a protective factor for EGFR mutation.

Development and Validation of a Concise Prediction Scoring System for Asian Lung Cancer Patients with EGFR Mutation Before Treatment

Purpose We aimed to determine the epidermal growth factor receptor (EGFR) genetic profile of lung cancer in Asians, and develop and validate a non-invasive prediction scoring system for EGFR mutation before treatment. Methods This was a single-center retrospective cohort study using data of patients with lung cancer who underwent EGFR detection (n = 1450) from December 2014 to October 2020. Independent predictors were filtered using univariate and multivariate logistic regression analyses. According to the weight of each factor, a prediction scoring system for EGFR mutation was constructed. The model was internally validated using bootstrapping techniques and temporally validated using prospectively collected data (n = 210) between November 2020 and June 2021.Results In 1450 patients with lung cancer, 723 single mutations and 51 compound mutations were observed in EGFR. Thirty-nine cases had two or more synchronous gene mutations. We developed a scoring system according to the independent clinical predictors and stratified patients into risk groups according to their scores: low-risk (score <4), moderate-risk (score 4-8), and high-risk (score >8) groups. The C-statistics of the scoring system model was 0.754 (95% CI 0.729-0.778). The factors in the validation group were introduced into the prediction model to test the predictive power of the model. The results showed that the C-statistics was 0.710 (95% CI 0.638-0.782). The Hosmer–Lemeshow goodness-of-fit showed that χ² = 6.733, P = 0.566. Conclusions The scoring system constructed in our study may be a non-invasive tool to initially predict the EGFR mutation status for those who are not available for gene detection in clinical practice.

Tumor-to-liver standard uptake ratio using fluorine-18 fluorodeoxyglucose positron emission tomography computed tomography effectively predict occult lymph node metastasis of non-small cell lung cancer patients

OBJECTIVES

We aimed to investigate predictive factors of occult lymph node metastasis and to explore the diagnostic value of various standardized uptake value (SUV) parameters using fluorine-18 fluorodeoxyglucose (F-FDG) positron emission tomography computed tomography (PET/CT) in predicting occult lymph node metastasis of clinical N0 non-small cell lung cancer patients.

METHODS

We retrospectively analyzed PET/computed tomography parameters of tumor and clinical data of 124 clinical N0 non-small cell lung cancer patients who underwent both preoperative F-FDG PET/computed tomography and anatomical pulmonary resection with systematic lymph node dissections. The SUVmax, SUVmean, metabolic total volume, and total lesion glycolysis of the primary tumor was automatically measured on the PET/computed tomography workstation. Standardized uptake ratio (SUR) were derived from tumor standardized uptake value divided by blood SUVmean (B-SUR) or liver SUVmean (L-SUR), respectively.

RESULTS

According to postoperative pathology, 19 (15%) were diagnosed as occult lymph node metastasis among 124 clinical N0 non-small cell lung cancer patients. On univariate analysis, carcinoembryonic antigen, cytokeratin 19 fragment, lobulation, and all PET parameters were associated with occult lymph node metastasis. The area under the receiver operating characteristic curve, sensitivity, and negative predictive value of L-SURmax were the highest among all PET parameters (0.778, 94.7%, and 98.4%, respectively). On multivariate analysis, carcinoembryonic antigen, cytokeratin 19 fragment, and L-SURmax were independent risk factors for predicting occult lymph node metastasis. Compared to L-SURmax alone and the combination of carcinoembryonic antigen and cytokeratin 19 fragment, the model consisting of three independent risk factors achieved a greater area under the receiver operating characteristic curve (0.901 vs. 0.778 vs. 0.780, P = 0.021 and 0.0141).

CONCLUSIONS

L-SURmax showed the most powerful predictive performance than the other PET parameters in predicting occult lymph node metastasis. The combination of three independent risk factors (carcinoembryonic antigen, cytokeratin 19 fragment, and L-SURmax) can effectively predict occult lymph node metastasis in clinical N0 non-small cell lung cancer patients.

Individualized nomogram for predicting ALK rearrangement status in lung adenocarcinoma patients

OBJECTIVES

To develop a nomogram to identify anaplastic lymphoma kinase (ALK) mutations in lung adenocarcinoma patients using clinical, CT, PET/CT, and histopathological features.

METHODS

This retrospective study included 399 lung adenocarcinoma patients (129 ALK-rearranged patients and 270 ALK-negative patients) that were randomly divided into a training cohort and an internal validation cohort (4:1 ratio). Clinical factors, radiologist-defined CT features, maximum standard uptake values (SUVmax), and histopathological features were used to construct predictive models with stepwise backward-selection multivariate logistic regression (MLR). The models were then evaluated using the AUC. The integrated model was compared to the clinico-radiological model using the DeLong test to evaluate the role of histopathological features. An associated individualized nomogram was established.

RESULTS

The integrated model reached an AUC of 0.918 (95% CI, 0.886-0.950), sensitivity of 0.774, and specificity of 0.934 in the training cohort and an AUC of 0.857 (95% CI, 0.777-0.937), sensitivity of 0.739, and specificity of 0.810 in the validation cohort. The MLR analysis showed that younger age, never smoker, lymph node enlargement, the presence of cavity, high SUVmax, solid or micropapillary predominant histology subtype, and local invasiveness were strong and independent predictors of ALK rearrangements. The nomogram calculated the risk of harboring ALK mutation for lung adenocarcinoma patients and exhibited a good generalization ability.

CONCLUSION

Our study demonstrates that histopathological features added value to the imaging characteristics-based model. The nomogram with clinical, imaging, and histopathological features can serve as a supplementary non-invasive tool to evaluate the probability of ALK rearrangement in lung adenocarcinoma.

KEY POINTS

• The developed nomogram can accurately predict the probability of lung adenocarcinoma harboring ALK-fused gene. • Pathological analysis is important to predict ALK rearrangement in lung adenocarcinoma. • Lung adenocarcinoma with lepidic predominant growth pattern and TTF-1 negativity is unlikely to have ALK rearrangement.

Clinicoradiopathological features and prognosis according to genomic alterations in patients with resected lung adenocarcinoma

Background

We investigated the clinicoradiopathological features and prognosis according to genomic alterations in patients with surgically resected lung adenocarcinoma.

Methods

Patients who underwent surgical resection for pathologic stage I, II, or IIIA lung adenocarcinoma between 2009 and 2016 and for whom results regarding EGFR mutation, ALK immunohistochemistry (IHC), and KRAS mutation were available were included. Clinicoradiopathological characteristics, genomic alterations, and disease-free survival were analyzed retrospectively.

Results

Of 164 patients, 86 (52.4%) were female and 94 (57.3%) were never-smokers. The most common imaging patterns were part-solid lesion (67.7%) followed by solid (26.2%) and non-solid (6.1%) lesions. EGFR mutation, ALK IHC, and KRAS mutation were positive in 95 (57.9%), 9 (5.5%), and 11 (6.7%) patients, respectively. EGFR mutation positivity was associated with female sex, never-smoker, subsolid pattern on radiological examination, and acinar or papillary predominant histologic subtype. ALK IHC positivity was associated with longer maximal diameter, advanced stage, solid pattern on radiological examination, solid predominant histologic subtype, and distant metastasis during follow-up. KRAS mutation positivity was associated with male sex, smoker, solid pattern on radiological examination, and invasive mucinous adenocarcinoma on histologic analysis. In multivariable analysis, ALK IHC positivity and lymph node involvement were independently associated with recurrence. However, solidity was not an independent risk factor for recurrence.

Conclusions

Genomic alterations are associated with clinicoradiopathologic features in patients with resected lung adenocarcinoma. Identifying genomic alterations could help to predict the prognosis of early-stage lung adenocarcinoma.

Clinical, Conventional CT and Radiomic Feature-Based Machine Learning Models for Predicting ALK Rearrangement Status in Lung Adenocarcinoma Patients

Objectives: To predict the anaplastic lymphoma kinase (ALK) mutations in lung adenocarcinoma patients non-invasively with machine learning models that combine clinical, conventional CT and radiomic features.

Methods: This retrospective study included 335 lung adenocarcinoma patients who were randomly divided into a primary cohort (268 patients; 90 ALK-rearranged; and 178 ALK wild-type) and a test cohort (67 patients; 22 ALK-rearranged; and 45 ALK wild-type). One thousand two hundred and eighteen quantitative radiomic features were extracted from the semi-automatically delineated volume of interest (VOI) of the entire tumor using both the original and the pre-processed non-enhanced CT images. Twelve conventional CT features and seven clinical features were also collected. Normalized features were selected using a sequential of the F-test-based method, the density-based spatial clustering of applications with noise (DBSCAN) method, and the recursive feature elimination (RFE) method. Selected features were then used to build three predictive models (radiomic, radiological, and integrated models) for the ALK-rearranged phenotype by a soft voting classifier. Models were evaluated in the test cohort using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity, and the performances of three models were compared using the DeLong test.

Results: Our results showed that the addition of clinical information and conventional CT features significantly enhanced the validation performance of the radiomic model in the primary cohort (AUC = 0.83–0.88, P = 0.01), but not in the test cohort (AUC = 0.80–0.88, P = 0.29). The majority of radiomic features associated with ALK mutations reflected information around and within the high-intensity voxels of lesions. The presence of the cavity and left lower lobe location were new imaging phenotypic patterns in association with ALK-rearranged tumors. Current smoking was strongly correlated with non-ALK-mutated lung adenocarcinoma.

Conclusions: Our study demonstrates that radiomics-derived machine learning models can potentially serve as a non-invasive tool to identify ALK mutation of lung adenocarcinoma.

Clinicopathologic and Imaging Features of Non-Small-Cell Lung Cancer with MET Exon 14 Skipping Mutations

MET exon 14 (METex14) skipping mutations are an emerging potentially targetable oncogenic driver mutation in non-small-cell lung cancer (NSCLC). The imaging features and patterns of metastasis of NSCLC with primary METex14 skipping mutations (METex14-mutated NSCLC) are not well described. Our goal was to determine the clinicopathologic and imaging features that may suggest the presence of METex14 skipping mutations in NSCLC. This IRB-approved retrospective study included NSCLC patients with primary METex14 skipping mutations and pre-treatment imaging data between January 2013 and December 2018. The clinicopathologic characteristics were extracted from electronic medical records. The imaging features of the primary tumor and metastases were analyzed by two thoracic radiologists. In total, 84 patients with METex14-mutated NSCLC (mean age = 71.4 ± 10 years; F = 52, 61.9%, M = 32, 38.1%; smokers = 47, 56.0%, nonsmokers = 37, 44.0%) were included in the study. Most tumors were adenocarcinoma (72; 85.7%) and presented as masses (53/84; 63.1%) that were peripheral in location (62/84; 73.8%). More than one in five cancers were multifocal (19/84; 22.6%). Most patients with metastatic disease had only extrathoracic metastases (23/34; 67.6%). Fewer patients had both extrathoracic and intrathoracic metastases (10/34; 29.4%), and one patient had only intrathoracic metastases (1/34, 2.9%). The most common metastatic sites were the bones (14/34; 41.2%), the brain (7/34; 20.6%), and the adrenal glands (7/34; 20.6%). Four of the 34 patients (11.8%) had metastases only at a single site. METex14-mutated NSCLC has distinct clinicopathologic and radiologic features.

Computed Tomography Imaging Features and Distribution of Metastases in ROS1-rearranged Non-Small-cell Lung Cancer

BACKGROUND

ROS proto-oncogene 1 (ROS1) rearrangements are a known molecular target in non-small-cell lung cancer (NSCLC). Our goal was to determine whether ROS1-rearranged NSCLC has imaging features and patterns of metastasis, which differ from those of anaplastic lymphoma kinase (ALK)-rearranged or epidermal growth factor receptor (EGFR)-mutant NSCLC.

PATIENTS AND METHODS

We retrospectively identified patients with metastatic ROS1-rearranged, ALK-rearranged, or EGFR-mutant NSCLC from January 2014 to June 2018 and included those with pretreatment imaging studies available. We assessed the imaging features of the primary tumor and the distribution of metastases in these patients. The Wilcoxon rank-sum test and Fisher exact test were used to compare the imaging features.

RESULTS

We identified 257 patients (167 women and 90 men; median age, 56 years; range, 19-90 years) with metastatic NSCLC (ROS1, 53; ALK, 87; EGFR, 117). Compared with ALK-rearranged or EGFR-mutant NSCLC, ROS1-rearranged NSCLC was less likely to present with extrathoracic metastases (ROS1, 49%; ALK, 75%; EGFR, 72%; P < .01), including brain metastases (ROS1, 9%; ALK, 25%; EGFR, 40%; P < .04). Compared with EGFR-mutant NSCLC, ROS1-rearranged tumors were more likely to exhibit imaging features of lymphangitic carcinomatosis (ROS1, 42%; EGFR, 12%; P < .01) and less likely to have air bronchograms in the primary tumor (ROS1, 2%; EGFR, 28%; P < .01). ROS1-rearranged tumors were also more likely to present with distant nodal metastases (ROS1, 15%; EGFR, 2%; P < .01) and sclerotic-type bone metastases (ROS1, 17%; EGFR, 6%; P < .01).

CONCLUSION

Although considerable overlap exists in the imaging features of ROS1-rearranged, ALK-rearranged, and EGFR-mutant NSCLC, we found that ROS1-rearranged NSCLC has certain distinct imaging features and patterns of spread.

CT Characteristics of Non-Small Cell Lung Cancer With Anaplastic Lymphoma Kinase Rearrangement: A Systematic Review and Meta-Analysis

OBJECTIVE. The purpose of this study was to perform a systematic review and meta-analysis regarding CT features of non-small cell lung cancer (NSCLC) with anaplastic lymphoma kinase (ALK) rearrangement. MATERIALS AND METHODS. The PubMed and Embase databases were searched up to February 20, 2019. Studies that evaluated CT features of NSCLC with and without ALK rearrangement was included. Methodologic quality was assessed using Quality Assessment of Diagnostic Accuracy Studies-2. The association between CT features and ALK rearrangement was pooled in the form of the odds ratio (OR) or the mean difference (MD) using the random-effects model. Heterogeneity was examined using the inconsistency index (I²). Publication bias was examined using funnel plots and Egger tests. RESULTS. Sixteen studies were included, consisting of 3113 patients with NSCLC. The overall prevalence of patients with ALK rearrangement was 17% (528/3113). Compared with NSCLC without ALK rearrangement, on CT images those with ALK rearrangement were more frequently solid (OR = 2.86), central in location (OR = 2.72), and 3 cm or smaller (OR = 0.57); had lower contrast-enhanced CT attenuation (MD = -4.79 HU); more frequently had N2 or N3 disease (OR = 5.63), lymphangitic carcinomatosis (OR = 3.46), pleural effusion (OR = 1.91), or pleural metastasis (OR = 1.81); and less frequently had lung metastasis (OR = 0.66). Heterogeneity varied among CT features (I² = 0-80%). No significant publication bias was seen (p = 0.15). CONCLUSION. NSCLC with ALK rearrangement had several distinctive CT features compared with that without ALK rearrangement. These CT biomarkers may help identify patients likely to have ALK rearrangement.

Quantitative features of dual-energy spectral computed tomography for solid lung adenocarcinoma with EGFR and KRAS mutations, and ALK rearrangement: a preliminary study

Background

The present work aimed to evaluate radio-genomic associations of quantitative parameters obtained by dual-energy spectral computed tomography (DESCT) for solid lung adenocarcinoma with epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations, as well as anaplastic lymphoma kinase (ALK) rearrangement.

Methods

Ninety-six cases of solid lung cancer were selected and assessed for EGFR and KRAS mutations, and ALK rearrangement. Then, they underwent chest DESCT, and quantitative parameters, including water concentration (WC), iodine concentration (IC), CT value at 70 keV, effective atomic number (Effective-Z) and spectral Hounsfield unit curve slope (λHU slope) were measured. Finally, the associations of quantitative radiological features with various gene alterations were evaluated.

Results

The positive rates were 51.0% (49/96) for EGFR, 13.5% (13/96) for KRAS and 16.7% (16/96) for ALK. In univariate analysis, EGFR mutation was associated with smoking status, CT value at 70 keV, IC, Effective-Z, and λHU slope; KRAS mutation was associated with CT value at 70 keV, IC, Effective-Z, and λHU slope, and ALK rearrangement was correlated with age and WC. In multivariate analysis, smoking status (OR =2.924, P=0.019) and CT value at 70 keV (OR =1.036, P=0.006) were significantly associated with EGFR mutation; Effective-Z and age were significantly associated with KRAS mutation (OR =0.047, P=0.032) and ALK rearrangement (OR =0.933, P=0.008), respectively.

Conclusions

Quantitative analysis of DESCT could help detect solid lung adenocarcinoma harboring EGFR or KRAS mutation, or ALK rearrangement.

Computed Tomography Imaging Characteristics of Non-Small-Cell Lung Cancer With Anaplastic Lymphoma Kinase Rearrangements: A Systematic Review and Meta-Analysis

INTRODUCTION

Several studies have suggested that non-small-cell lung cancer (NSCLC) patients who harbor anaplastic lymphoma kinase (ALK) rearrangement might have different imaging features compared with those without the rearrangement. The goal of this work was to systematically investigate the computed tomography (CT) imaging features of ALK-rearranged NSCLC.

MATERIALS AND METHODS

We searched published studies that investigated CT imaging features of ALK-rearranged NSCLC compared with ALK-negative, including epidermal growth factor receptor (EGFR)-mutant and ALK/EGFR-negative, NSCLC. We extracted clinicopathologic characteristics and CT imaging features of patients in the included studies. Features were compared and tested in the form of odds ratios (ORs) or weighted mean differences at a 95% confidence interval.

RESULTS

Twelve studies with 2210 patients with NSCLC were included. Compared with ALK-negative NSCLC, ALK-rearranged NSCLC was more likely to be solid (OR, 2.37; P < .001) and less likely to have cavitation (OR, 0.45; P = .002). In advanced stages, patients with ALK-rearranged NSCLC, compared with EGFR-mutant NSCLC, were more likely to have lymphadenopathy (OR, 3.47; P < .001), pericardial metastasis (OR, 2.18; P = .04), pleural metastasis (OR, 2.07; P = .004), and lymphangitic carcinomatosis (OR, 3.41; P = .02), but less likely to have lung metastasis (OR, 0.52; P = .003). Compared with ALK/EGFR-negative NSCLC, ALK-rearranged NSCLC was more likely to have lymphangitic carcinomatosis (OR, 3.88; P = .03), pleural metastasis (OR, 1.89; P = .02), and pleural effusion (OR, 2.94; P = .003).

CONCLUSION

ALK-rearranged NSCLC has imaging features that are different compared with EGFR-mutant and ALK/EGFR-negative NSCLC. These imaging features might provide clues as to the presence of ALK rearrangement and help in the selection of patients who might benefit from expedited molecular testing or repeat testing after a negative assay.

Clinical and computed tomography characteristics of non-small cell lung cancer with ALK gene rearrangement: Comparison with EGFR mutation and ALK/EGFR-negative lung cancer

Background

The study was conducted to evaluate the clinical and computed tomography (CT) findings of non‐small cell lung cancer (NSCLC) patients to distinguish between ALK gene rearrangement, EGFR mutation, and non‐ALK/EGFR (no genetic abnormalities).

Methods

We enrolled 201 patients with primary NSCLC who had undergone molecular testing for both ALK gene rearrangement and EGFR mutation. The clinical features and CT findings of the main lesion and associated pulmonary abnormalities were investigated.

Results

Female gender (P = 0.0043 vs. non‐ALK/EGFR), young age (P = 0.0156 vs. EGFR), and a light or never smoking history (P = 0.0039 vs. non‐ALK/EGFR) were significant clinical characteristics of NSCLC with ALK gene rearrangement. The significant CT characteristics compared to NSCLC with EGFR mutation were a large mass (P = 0.0155), solid mass (P = 0.0048), and no air bronchogram (P = 0.0148). A central location (P = 0.0322) and lymphadenopathy (P = 0.0353) were also more frequently observed. Coexisting emphysema was significantly less frequent in NSCLC patients with ALK gene rearrangement (P = 0.0135) than non‐ALK/EGFR.

Conclusions

NSCLC with ALK gene rearrangement was more likely to develop in younger women with a light or never smoking history. The characteristic CT findings of NSCLC with ALK gene rearrangement were a large solid mass, less air bronchogram, a central location, and lymphadenopathy.

Prediction of EGFR mutations by conventional CT-features in advanced pulmonary adenocarcinoma

OBJECTIVE

This study assessed the ability of conventional computed tomography (CT) features (including primary tumors, metastatic lesions, lymph nodes, and emphysema) to predict epidermal growth factor receptor (EGFR) mutations in advanced pulmonary adenocarcinoma.

METHODS

Patients who were diagnosed with advanced pulmonary adenocarcinoma between January 2017 and August 2017 and had undergone a chest CT and EGFR mutation testing were enrolled in this retrospective study. Qualitative and quantitative CT-features and clinical characteristics evaluated in this study included: primary tumor location, size, and morphology (including degree of lobulation, density, calcification, cavitation, vacuole sign, and air bronchogram), size and distribution of lung and pleural metastatic nodules, size and status of hilar and mediastinal lymph nodes, emphysema, organs with distant metastasis, and patient age, sex, and smoking history.

RESULTS

Of 201 patients, 107 (53.23%) were EGFR-mutation positive. The multivariate logistic regression indicated that EGFR mutations were significantly associated with smaller lymph nodes, a lower percentage of deep lobulation of the primary tumor and partial fusion of lymph nodes, and absence of emphysema. The area under the curve of logistic regression model for predicting EGFR mutations was 0.898.

CONCLUSIONS

Conventional CT-features, including emphysema, degree of primary tumor lobulation, and lymph node size and status, help to predict the presence or absence of EGFR mutations in advanced pulmonary adenocarcinoma. Additionally, these same CT-features demonstrated that the CT manifestations of the EGFR mutant group were of relatively lower malignancy and less invasive as compared to the wild-type EGFR group.

Delta radiomic features improve prediction for lung cancer incidence: A nested case-control analysis of the National Lung Screening Trial

Background

Current guidelines for lung cancer screening increased a positive scan threshold to a 6 mm longest diameter. We extracted radiomic features from baseline and follow‐up screens and performed size‐specific analyses to predict lung cancer incidence using three nodule size classes (<6 mm [small], 6‐16 mm [intermediate], and ≥16 mm [large]).

Methods

We extracted 219 features from baseline (T0) nodules and 219 delta features which are the change from T0 to first follow‐up (T1). Nodules were identified for 160 incidence cases diagnosed with lung cancer at T1 or second follow‐up screen (T2) and for 307 nodule‐positive controls that had three consecutive positive screens not diagnosed as lung cancer. The cases and controls were split into training and test cohorts; classifier models were used to identify the most predictive features.

Results

The final models revealed modest improvements for baseline and delta features when compared to only baseline features. The AUROCs for small‐ and intermediate‐sized nodules were 0.83 (95% CI 0.76‐0.90) and 0.76 (95% CI 0.71‐0.81) for baseline‐only radiomic features, respectively, and 0.84 (95% CI 0.77‐0.90) and 0.84 (95% CI 0.80‐0.88) for baseline and delta features, respectively. When intermediate and large nodules were combined, the AUROC for baseline‐only features was 0.80 (95% CI 0.76‐0.84) compared with 0.86 (95% CI 0.83‐0.89) for baseline and delta features.

Conclusions

We found modest improvements in predicting lung cancer incidence by combining baseline and delta radiomics. Radiomics could be used to improve current size‐based screening guidelines.

Clinicoradiological features associated with epidermal growth factor receptor exon 19 and 21 mutation in lung adenocarcinoma

AIM

To retrospectively identify clinicopathological and radiological characteristics that could be independent predictors of epidermal growth factor receptor (EGFR) exon 19 and 21 mutation in surgically resected lung adenocarcinomas in a cohort of Asian patients.

MATERIALS AND METHODS

Demographics, histopathology data, and preoperative chest computed tomography (CT) images were evaluated retrospectively in 471 surgically resected lung adenocarcinomas. A total of 24 CT descriptors were assessed. Univariate analyses and multivariate logistic regression analyses were performed to identify independent predicted factors of harbouring EGFR mutations.

RESULTS

EGFR mutations were existed in 252 (53.5%) of 471 patients, and associated with 11 clinicoradiological features. For the model with both clinical and radiological features, the independent predictors of harbouring EGFR mutation were small maximum diameter (≤3.9 cm), non-smokers, micropapillary pattern, pleural retraction, vascular convergence, and absence of solid pattern. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.784. Multivariable logistic regression analysis indicated that non-smokers, vascular convergence, and absence of solid pattern were important independent predictors of EGFR exon 19 mutation, while non-smokers and vascular convergence were independent predictors of EGFR exon 21 mutation. The AUCs were 0.807 and 0.794, respectively. A lepidic growth pattern appeared more frequently in exon 21 mutant tumours than in exon 19 mutant group (p<0.001).

CONCLUSION

CT imaging features of lung adenocarcinomas in combination with clinical variables could be used to prognosticate EGFR mutation status. The separate analysis of EGFR exon 19 or 21 mutation could further improve diagnostic performance.

Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis

With targeted treatments playing an increasing role in oncology, the need arises for fast non-invasive genotyping in clinical practice. Radiogenomics is a rapidly evolving field of research aimed at identifying imaging biomarkers useful for non-invasive genotyping. Radiogenomic genotyping has the advantage that it can capture tumor heterogeneity, can be performed repeatedly for treatment monitoring, and can be performed in malignancies for which biopsy is not available. In this systematic review of 187 included articles, we compiled a database of radiogenomic associations and unraveled networks of imaging groups and gene pathways oncology-wide. Results indicated that ill-defined tumor margins and tumor heterogeneity can potentially be used as imaging biomarkers for 1p/19q codeletion in glioma, relevant for prognosis and disease profiling. In non-small cell lung cancer, FDG-PET uptake and CT-ground-glass-opacity features were associated with treatment-informing traits including EGFR-mutations and ALK-rearrangements. Oncology-wide gene pathway analysis revealed an association between contrast enhancement (imaging) and the targetable VEGF-signalling pathway. Although the need of independent validation remains a concern, radiogenomic biomarkers showed potential for prognosis prediction and targeted treatment selection. Quantitative imaging enhanced the potential of multiparametric radiogenomic models. A wealth of data has been compiled for guiding future research towards robust non-invasive genomic profiling.

Radial gradient and radial deviation radiomic features from pre-surgical CT scans are associated with survival among lung adenocarcinoma patients

The goal of this study was to extract features from radial deviation and radial gradient maps which were derived from thoracic CT scans of patients diagnosed with lung adenocarcinoma and assess whether these features are associated with overall survival. We used two independent cohorts from different institutions for training (n= 61) and test (n= 47) and focused our analyses on features that were non-redundant and highly reproducible. To reduce the number of features and covariates into a single parsimonious model, a backward elimination approach was applied. Out of 48 features that were extracted, 31 were eliminated because they were not reproducible or were redundant. We considered 17 features for statistical analysis and identified a final model containing the two most highly informative features that were associated with lung cancer survival. One of the two features, radial deviation outside-border separation standard deviation, was replicated in a test cohort exhibiting a statistically significant association with lung cancer survival (multivariable hazard ratio = 0.40; 95% confidence interval 0.17-0.97). Additionally, we explored the biological underpinnings of these features and found radial gradient and radial deviation image features were significantly associated with semantic radiological features.

Comparison of clinical and radiological characteristics between anaplastic lymphoma kinase rearrangement and epidermal growth factor receptor mutation in treatment naïve advanced lung adenocarcinoma

Background

Gene analysis could not be performed in all patients, especially in advanced non-small cell lung cancer (NSCLC). We aimed to find some clinical futures and CT or FDG-PET characteristics, which could be combined to help distinguish anaplastic lymphoma kinase (ALK) rearrangement form epidermal growth factor receptor (EGFR) mutations in treatment naïve advanced lung adenocarcinoma of Chinese patients.

Methods

We retrospectively reviewed clinical and radiological characteristics of 145 patients with treatment naïve advanced lung adenocarcinoma. The one-way ANOVA, the Mann-Whitney test, chi-square test and logistic regression were used for comparison between patients with ALK rearrangement and those with EGFR mutation.

Results

Among 145 patients with advanced lung adenocarcinoma, only six patients had both ALK rearrangement and EGFR mutation, the sample size was too small to analysis. Univariate analysis revealed that patients with ALK rearrangement were younger (P=0.001) and with lower serum carcinoembryonic antigen (CEA) level (P=0.008) than those with EGFR mutation. More of tumors with ALK rearrangement were well defined (P=0.023) and have bubble lucency (P=0.026) compared with those with EGFR mutation (P=0.026). Lymphadenopathy was seen more frequently in patients with ALK rearrangement (P=0.167). Twenty-six patients received FDG-PET/CT, among this population, lesion standardized uptake values (SUV) >6.95 and lymph nodes SUV_max >6.25 were more often seen in ALK rearrangement group (P=0.011, both). In multivariate analysis, patients younger than 50 years (RR =9.878, 95% CI: 2.318-42.090, P=0.002), with lower CEA level than 4.95 µg/L (RR =8.166, 95% CI: 1.085-31.983, P=0.003) and without brain metastasis (RR =7.304, 95% CI: 1.099-48.558, P=0.040) were more likely to be ALK rearrangement than EGFR mutation. Tumor diameter less than 36 mm were prone to be EGFR mutation (RR =0.078, 95% CI: 0.017-0.356, P=0.001).

Conclusions

Treatment naïve advanced lung adenocarcinomas with ALK rearrangement were more likely to have younger age, lower serum CEA level, larger tumor volume, well defined tumor border, and non-brain metastasis than those with EGFR mutation. Bubble lucency and higher FDG uptake of lesion and lymph nodes may help distinguish ALK rearrangement from EGFR mutation in the absence of genetic analysis.

Prognostic value and molecular correlates of a CT image-based quantitative pleural contact index in early stage NSCLC

PURPOSE

To evaluate the prognostic value and molecular basis of a CT-derived pleural contact index (PCI) in early stage non-small cell lung cancer (NSCLC).

EXPERIMENTAL DESIGN

We retrospectively analysed seven NSCLC cohorts. A quantitative PCI was defined on CT as the length of tumour-pleura interface normalised by tumour diameter. We evaluated the prognostic value of PCI in a discovery cohort (n = 117) and tested in an external cohort (n = 88) of stage I NSCLC. Additionally, we identified the molecular correlates and built a gene expression-based surrogate of PCI using another cohort of 89 patients. To further evaluate the prognostic relevance, we used four datasets totalling 775 stage I patients with publically available gene expression data and linked survival information.

RESULTS

At a cutoff of 0.8, PCI stratified patients for overall survival in both imaging cohorts (log-rank p = 0.0076, 0.0304). Extracellular matrix (ECM) remodelling was enriched among genes associated with PCI (p = 0.0003). The genomic surrogate of PCI remained an independent predictor of overall survival in the gene expression cohorts (hazard ratio: 1.46, p = 0.0007) adjusting for age, gender, and tumour stage.

CONCLUSIONS

CT-derived pleural contact index is associated with ECM remodelling and may serve as a noninvasive prognostic marker in early stage NSCLC.

KEY POINTS

• A quantitative pleural contact index (PCI) predicts survival in early stage NSCLC. • PCI is associated with extracellular matrix organisation and collagen catabolic process. • A multi-gene surrogate of PCI is an independent predictor of survival. • PCI can be used to noninvasively identify patients with poor prognosis.

Associations between radiologist-defined semantic and automatically computed radiomic features in non-small cell lung cancer

Tumor phenotypes captured in computed tomography (CT) images can be described qualitatively and quantitatively using radiologist-defined "semantic" and computer-derived "radiomic" features, respectively. While both types of features have shown to be promising predictors of prognosis, the association between these groups of features remains unclear. We investigated the associations between semantic and radiomic features in CT images of 258 non-small cell lung adenocarcinomas. The tumor imaging phenotypes were described using 9 qualitative semantic features that were scored by radiologists, and 57 quantitative radiomic features that were automatically calculated using mathematical algorithms. Of the 9 semantic features, 3 were rated on a binary scale (cavitation, air bronchogram, and calcification) and 6 were rated on a categorical scale (texture, border definition, contour, lobulation, spiculation, and concavity). 32-41 radiomic features were associated with the binary semantic features (AUC = 0.56-0.76). The relationship between all radiomic features and the categorical semantic features ranged from weak to moderate (|Spearmen's correlation| = 0.002-0.65). There are associations between semantic and radiomic features, however the associations were not strong despite being significant. Our results indicate that radiomic features may capture distinct tumor phenotypes that fail to be perceived by naked eye that semantic features do not describe and vice versa.