Relationship between computed tomography morphology and prognosis of patients with stage I non-small cell lung cancer

Predictive value of spectral computed tomography parameters for EGFR gene mutation in non-small-cell lung cancer

AIM

To explore the predictive value of morphological signs and quantitative parameters from spectral CT for EGFR gene mutations in intermediate and advanced non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

This retrospective observational study included patients with intermediate or advanced NSCLC at Xinjiang Medical University Affiliated Tumor Hospital between January 2017 and December 2019. The patients were divided into the EGFR gene mutation-positive and -negative groups.

RESULTS

Seventy-nine patients aged 60.75 ± 9.66 years old were included: 32 were EGFR mutation-positive, and 47 were negative. There were significant differences in pathological stage (P<0.001), tumor diameter (P=0.019), lobulation sign, intrapulmonary metastasis, mediastinal lymph node metastasis, distant metastasis (P<0.001), bone metastasis (P<0.001), arterial phase normalized iodine concentration (NIC) (P=0.001), venous phase NIC (P=0.001), slope of the energy spectrum curve (λ) (P<0.001), and CT value at 70 keV in arterial phase (P=0.004) and venous phase (P=0.003) between the EGFR mutation-positive and -negative patients. The multivariable logistic regression analysis showed that intrapulmonary metastasis, distant metastasis, venous phase NIC, venous phase λ, and pathological stage were independent factors predicting EGFR gene mutations, with high diagnostic power (AUC = 0.975, 91.5% sensitivity, and 90.6% specificity).

CONCLUSION

The pathological stage and the spectral CT parameters of intrapulmonary metastasis, distant metastasis, venous phase NIC, and venous phase λ might pre-operatively predict EGFR gene mutations in intermediate and advanced NSCLC.

A nomogram combining CT-based radiomic features with clinical features for the differentiation of benign and malignant cystic pulmonary nodules

BACKGROUND

Currently, the differentiation between benign and malignant cystic pulmonary nodules poses a significant challenge for clinicians. The objective of this retrospective study was to construct a predictive model for determining the likelihood of malignancy in patients with cystic pulmonary nodules.

METHODS

The current study involved 129 patients diagnosed with cystic pulmonary nodules between January 2017 and June 2023 at the Neijiang First People's Hospital. The study gathered the clinical data, preoperative imaging features of chest CT, and postoperative histopathological results for both cohorts. Univariate and multivariate logistic regression analyses were employed to identify independent risk factors, from which a prediction model and nomogram were developed. In addition, The model's performance was assessed through receiver operating characteristic (ROC) curve analysis, calibration curve analysis, and decision curve analysis (DCA).

RESULTS

A cohort of 129 patients presenting with cystic pulmonary nodules, consisting of 92 malignant and 37 benign lesions, was examined. Logistic data analysis identified a cystic airspace with a mural nodule, spiculation, mural morphology, and the number of cystic cavities as significant independent predictors for discriminating between benign and malignant cystic lung nodules. The nomogram prediction model demonstrated a high level of predictive accuracy, as evidenced by an area under the ROC curve (AUC) of 0.874 (95% CI: 0.804-0.944). Furthermore, the calibration curve of the model displayed satisfactory calibration. DCA proved that the prediction model was useful for clinical application.

CONCLUSION

In summary, the risk prediction model for benign and malignant cystic pulmonary nodules has the potential to assist clinicians in the diagnosis of such nodules and enhance clinical decision-making processes.

Construction of a predictive model of 2-3 cm ground-glass nodules developing into invasive lung adenocarcinoma using high-resolution CT

Background

The purpose of this study was to analyze the imaging risk factors for the development of 2-3 cm ground-glass nodules (GGN) for invasive lung adenocarcinoma and to establish a nomogram prediction model to provide a reference for the pathological prediction of 2-3 cm GGN and the selection of surgical procedures.

Methods

We reviewed the demographic, imaging, and pathological information of 596 adult patients who underwent 2-3 cm GGN resection, between 2018 and 2022, in the Department of Thoracic Surgery, Second Affiliated Hospital of the Air Force Medical University. Based on single factor analysis, the regression method was used to analyze multiple factors, and a nomogram prediction model for 2-3 cm GGN was established.

Results

(1) The risk factors for the development of 2-3 cm GGN during the invasion stage of the lung adenocarcinoma were pleural depression sign (OR = 1.687, 95%CI: 1.010-2.820), vacuole (OR = 2.334, 95%CI: 1.222-4.460), burr sign (OR = 2.617, 95%CI: 1.008-6.795), lobulated sign (OR = 3.006, 95%CI: 1.098-8.227), bronchial sign (OR = 3.134, 95%CI: 1.556-6.310), diameter of GGN (OR = 3.118, 95%CI: 1.151-8.445), and CTR (OR = 172.517, 95%CI: 48.023-619.745). (2) The 2-3 cm GGN risk prediction model was developed based on the risk factors with an AUC of 0.839; the calibration curve Y was close to the X-line, and the decision curve was drawn in the range of 0.0-1.0.

Conclusion

We analyzed the risk factors for the development of 2-3  cm GGN during the invasion stage of the lung adenocarcinoma. The predictive model developed based on the above factors had some clinical significance.

[Clinical Multi-features Analysis of Cystic Lung Adenocarcinoma and Construction of Invasive Risk Prediction Model]

BACKGROUND

Cystic lung cancer, a special type of lung cancer, has been paid more and more attention. The most common pathological type of cystic lung cancer is adenocarcinoma. The invasiveness of cystic lung adenocarcinoma is vital for the selection of clinical treatment and prognosis. The aim of this study is to analyze the multiple clinical features of cystic lung adenocarcinoma, explore the independent risk factors of its invasiveness, and establish a risk prediction model.

METHODS

A total of 129 cases of cystic lung adenocarcinoma admitted to the Department of Thoracic Surgery of the First Affiliated Hospital of Nanjing Medical University from January 2021 to July 2022 were retrospectively analyzed and divided into pre-invasive group [atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA)] and invasive group [invasive adenocarcinoma (IAC)] according to pathological findings. There were 47 cases in the pre-invasive group, including 19 males and 28 females, with an average age of (51.23±14.96) years. There were 82 cases in the invasive group, including 60 males and 22 females, with an average age of (61.27±11.74) years. Multiple clinical features of the two groups were collected, including baseline data, imaging data and tumor markers. Univariate analysis, LASSO regression and multivariate Logistic regression analysis were used to screen out the independent risk factors of the invasiveness of cystic lung adenocarcinoma, and the risk prediction model was established.

RESULTS

In univariate analysis, age, gender, smoking history, history of emphysema, neuron-specific enolase (NSE), number of cystic airspaces, lesion diameter, cystic cavity diameter, nodule diameter, solid components diameter, cyst wall nodule, smoothness of cyst wall, shape of cystic airspace, lobulation, short burr sign, pleural retraction, vascular penetration and bronchial penetration were statistically different between the pre-invasive group and invasive groups (P<0.05). The above variables were processed by LASSO regression dimensionality reduction and screened as follows: age, gender, smoking history, NSE, number of cystic airspaces, lesion diameter, cystic cavity diameter, cyst wall nodule, smoothness of cyst wall and lobulation. Then the above variables were included in multivariate Logistic regression analysis. Cyst wall nodule (P=0.035) and lobulation (P=0.001) were found to be independent risk factors for the invasiveness of cystic lung adenocarcinoma (P<0.05). The prediction model was established as follows: P=e^x/(1+e^x), x=-7.927+1.476* cyst wall nodule+2.407* lobulation, and area under the curve (AUC) was 0.950.

CONCLUSIONS

Cyst wall nodule and lobulation are independent risk factors for the invasiveness of cystic lung adenocarcinoma, which have certain guiding significance for the prediction of the invasiveness of cystic lung adenocarcinoma.

Clinicopathological and computed tomography features associated with recurrence-free survival of patients with small-sized peripheral invasive lung adenocarcinoma after sublobectomy

Background

Sublobar resection is gradually becoming a standard treatment for small-sized (≤2 cm) peripheral non-small cell lung cancer (NSCLC), with lung adenocarcinoma (LADC) being the most frequent histologic subtype. However, the prognostic predictors for preoperatively determining whether sublobectomy is feasible for patients with early LADC have not yet been well identified. Therefore, this study aimed to investigate the clinicopathological and computed tomography (CT) features associated with the recurrence-free survival (RFS) of patients with small-sized invasive LADC (SILADC) after sublobar resection.

Methods

This retrospective cohort study analyzed 107 patients with SILADC who underwent preoperative chest CT scan and sublobar resection from December 2012 to March 2019. The Kaplan-Meier survival was used to analyze the relationship between clinicopathological characteristics, preoperative chest CT findings, and RFS. The Cox proportional hazards regression was used to identify independent prognostic factors of poor RFS.

Results

For clinicopathological characteristics, RFS was shorter in patients aged ≥70 years, smokers, and those with micropapillary/solid-predominant adenocarcinomas (all P values <0.05). For preoperative CT features, RFS was shorter in patients with tumor size ≥1.4 cm, solid component size ≥1.1 cm, proportion of solid component ≥72%, solid density, spiculation, vascular convergence sign, peripheral fibrosis, and type II pleural tag (all P values <0.05). Multivariate analysis showed proportion of solid component ≥72% [hazard ratio (HR): 5.920; P=0.006; 95% confidence interval (CI): 1.686-20.794], spiculation (HR: 5.026; P=0.001; 95% CI: 2.008-12.581), and type II pleural tag (HR: 4.638; P=0.002; 95% CI: 1.773-12.136) were independent risk factors for poor prognosis in patients with SILADC after sub-lobectomy.

Conclusions

Clinicopathological and CT characteristics are helpful for predicting the RFS of patients with SILADC after sublobar resection and can be used as an auxiliary tool for thoracic surgeons to choose the best surgical mode.

Growth characteristics of early-stage (IA) lung adenocarcinoma and its value in predicting lymph node metastasis

BACKGROUND

We aim to compare the differences in growth characteristics between part-solid and solid lung adenocarcinoma, and to investigate the value of volume doubling time (VDT) or mass doubling time (MDT) in predicting lymph node (LN) metastasis and preoperative evaluation in patients of early-stage (IA) non-small cell lung cancer (NSCLC).

METHOD

We reviewed 8,653 cases of surgically resected stage IA lung adenocarcinoma between 2018 and 2022, with two follow-up visits at least 3 months apart, comparing diameter, volume, and mass growth of pSN and SN. VDT and MDT calculations for nodules with a volume change of at least 25%. Univariable or multivariable analysis was used to identify the risk factors. The area under the curve (AUC) for the receiver operating characteristic (ROC) curves was used to evaluate the diagnostic value.

RESULTS

A total of 144 patients were included 114 with solid nodules (SN) and 25 with part-solid nodules (pSN). During the follow-up period, the mean VDTt and MDTt of SN were shorter than those of pSN, 337 vs. 541 days (p = 0.005), 298 vs. 458 days (p = 0.018), respectively. Without considering the ground-glass component, the mean VDTc and MDTc of SN were shorter than the solid component of pSN, 337 vs. 498 days (p = 0.004) and 298 vs. 453 days (p = 0.003), respectively. 27 nodules were clinically and pathologically diagnosed as N1/N2. Logistic regression identified initial diameter (p < 0.001), consolidation increase (p = 0.019), volume increase (p = 0.020), mass increase (p = 0.021), VDTt (p = 0.002), and MDTt (p = 0.004) were independent factors for LN metastasis. The ROC curves showed that the AUC for VDTt was 0.860 (95% CI, 0.778-0.943; p < 0.001) and for MDTt was 0.848 (95% CI, 0.759-0.936; p < 0.001).

CONCLUSIONS

Our study showed significant differences in the growth characteristics of pSN and SN, and the application of VDT and MDT could be a valid predictor LN metastasis in patients with early-stage NSCLC.

Correlations between iodine uptake, invasive CT features and pleural invasion in adenocarcinomas with pleural contact

Pleural contact in lung cancers does not always imply pleural invasion (PI). This study was designed to determine whether specific invasive CT characteristics or iodine uptake can aid in the prediction of PI. The sample population comprised patients with resected solid lung adenocarcinomas between April 2019 and May 2022. All participants underwent a contrast enhanced spectral CT scan. Two proficient radiologists independently evaluated the CT features and iodine uptake. Logistic regression analyses were employed to identify predictors for PI, via CT features and iodine uptake. To validate the improved diagnostic efficiency, accuracy analysis and ROC curves were subsequently used. A two-tailed P value of less than 0.05 was considered statistically significant. We enrolled 97 consecutive patients (mean age, 61.8 years ± 10; 48 females) in our study. The binomial logistic regression model revealed that a contact length > 10 mm (OR 4.80, 95% CI 1.92, 11.99, p = 0.001), and spiculation sign (OR 2.71, 95% CI 1.08, 6.79, p = 0.033) were independent predictors of PI, while iodine uptake was not. Enhanced sensitivity (90%) and a greater area under the curve (0.73) were achieved by integrating the two aforementioned CT features in predicting PI. We concluded that the combination of contact length > 10 mm and spiculation sign can enhance the diagnostic performance of PI.

Radiomics nomogram integrating intratumoural and peritumoural features to predict lymph node metastasis and prognosis in clinical stage IA non-small cell lung cancer: a two-centre study

AIM

To investigate the value of a radiomics nomogram integrating intratumoural and peritumoural features in predicting lymph node metastasis and overall survival (OS) in patients with clinical stage IA non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

This study retrospectively enrolled 199 patients (training cohort: 71 patients from Affiliated Tumour Hospital of Nantong University; internal validation cohort: 46 patients from Affiliated Tumour Hospital of Nantong University; external validation cohort: 82 patients from the public database). CT radiomics models were constructed based on four volumes of interest: gross tumour volume (GTV), gross and 3 mm peritumoural volume (GPTV₃), gross and 6 mm peritumoural volume (GPTV₆), and gross and 9 mm peritumoural volume (GPTV₉). The optimal radiomics signature was further combined with independent clinical predictors to develop a nomogram. Univariable and multivariable Cox regression analysis were applied to determine the relationship between factors and OS.

RESULTS

GPTV₆ radiomics yielded better performance than GTV, GPTV₃, and, GPTV₉ radiomics in the training (area under the curve [AUC], 0.81), internal validation (AUC, 0.79), and external validation cohorts (AUC, 0.71), respectively. The nomogram integrating GPTV₆ radiomics and spiculation improved predictive ability, with AUCs of 0.85, 0.80, and 0.74 in three cohorts, respectively. Pathological lymph node metastasis, nomogram-predicted lymph node metastasis, and pleural indentation were independent risk predictors of OS (p<0.05).

CONCLUSIONS

The nomogram integrating GPTV₆ radiomics features and independent clinical predictors performed well in predicting lymph node metastasis and prognosis in patients with clinical stage IA NSCLC.

The pattern of lymph node metastasis in peripheral pulmonary nodules patients and risk prediction models

Background

For peripheral pulmonary nodules, the regularity of lymph node (LN) metastasis has not been studied. This study aimed to evaluate the metastasis pattern of intrapulmonary and relevant mediastinal lymph nodes in early-stage lung cancer, and further selected patients who were of low risk of LN metastasis as potential population to receive sub-lobectomy.

Methods

This study prospectively included consecutive patients with peripheral clinical T1N0M0 disease who underwent complete resection with LN dissection or sampling from August 2014 to July 2015. The patients were followed up to 15, May 2021. Univariable or multivariable Logistic analysis was used to identify the risk factors. Models predicting LN metastasis risk were conducted. The area under the curve for the receiver operating characteristic curves was used to evaluate the diagnostic value. Disease-free survival and overall survival were compared between groups.

Results

Finally, 201 patients were included in this study. For patients with negative tumor-bearing (TB) 13 and 14 station LNs, the positive rate of other lymph node stations was extremely low. Maximum CT value, pleural indentation and CEA level were risk factors for N1 station LNs metastasis. Besides, the factors above and lobulation sign were risk factors for skip metastasis beyond TB 13 and 14 station LNs. We constructed two scoring tables to predict N1 station metastasis and skip metastasis beyond TB 13 and 14 station. The AUC were 0·837 and 0·823, respectively. Based on the first table, 40·9% of patients suffered N1 station LNs metastasis and 27·3% had N2 disease in “high risk group” while the proportion was only 5·7% and 4·5% in “low risk group”. For patients with negative TB13 and TB14 station LNs, based on the latter table, 11·1% of patients had N1 stations LNs metastasis and 16·7% had pN2 disease in “high risk group” while only 2·3% patients in “low risk group” suffered this kind of metastasis.

Conclusion

For peripheral pulmonary nodules patients, stations 13 and 14 LNs may be the sentinel nodes. For patients with low risk of N1 metastasis and skip metastasis, sub-lobar resection might be sufficient for those who were of negative TB 13 and 14 station LNs.

Intrapulmonic Cavity or Necrosis on Baseline CT Scan Serves as an Efficacy Predictor of Anti-PD-(L)1 Inhibitor in Advanced Lung Squamous Cell Carcinoma

Background

Predictive markers for guidance and monitoring of immunotherapy in lung squamous cell carcinoma (LSCC) are an interesting topic but have yet to be fully explored. A primary characteristic of LSCC is tumor necrosis that results in extensive immune suppression in patients. We sought to assess whether tumor necrosis or cavity on baseline CT could effectively predict the efficacy of immune checkpoint inhibitors (ICIs) in advanced LSCC.

Methods

Advanced LSCC cases undergoing pre-treatment chest CT imaging and receiving ICIs were retrospectively collected. All CT images were reviewed by an independent chest radiologist blinded to any previous diagnosis to confirm morphological alterations in necrosis or cavity. We performed Logistic regression and developed Cox proportional hazards models to assess the predictive performance of baseline necrosis or cavity characteristics in advanced LSCC. Survival estimates were observed using Kaplan–Meier curves.

Results

Ninety-three patients were eligible for analysis, predominantly consisting of patients with ECOG performance status of 0 or 1 (97.8%), male patients (95.7%), and heavy smokers (92.5%). Intrapulmonic necrosis or cavity on CT scan was present in 52.7% of all patients. Generally, the objective response rate (ORR) in patients with necrosis or cavity to ICI treatment was significantly worse versus those without (30.6% vs 54.5%, p = 0.020), with the subgroup ORRs as follows: ICI monotherapy (necrosis vs non-necrosis: 10.0% vs 36.8%, p =0.047) and ICI combination therapy (44.8% vs 68.0%, p =0.088). Multivariable analysis identified intrapulmonic necrosis or cavity at baseline as a major risk factor for advanced LSCC (HR 4.042, 95% CI1.149–10.908, p = 0.006). Multivariate Cox analysis showed that baseline necrosis or cavity and ICI monotherapy were unfavorable factors for progression-free survival (HR 1.729; 95% CI1.203–2.484, p =0.003).

Conclusion

LSCC patients with intrapulmonic cavity or necrosis on baseline CT scan may respond poorly to anti-PD-(L)1-treatment, monotherapy and combination therapy alike.

Discriminating Small-Sized (2 cm or Less), Noncalcified, Solitary Pulmonary Tuberculoma and Solid Lung Adenocarcinoma in Tuberculosis-Endemic Areas

Background. Pulmonary tuberculoma can mimic lung malignancy and thereby pose a diagnostic dilemma to clinicians. The purpose of this study was to establish an accurate, convenient, and clinically practical model for distinguishing small-sized, noncalcified, solitary pulmonary tuberculoma from solid lung adenocarcinoma. Methods. Thirty-one patients with noncalcified, solitary tuberculoma and 30 patients with solid adenocarcinoma were enrolled. Clinical characteristics and CT morphological features of lesions were compared between the two groups. Multivariate logistic regression analyses were applied to identify independent predictors of pulmonary tuberculoma and lung adenocarcinoma. Receiver operating characteristic (ROC) analysis was performed to investigate the discriminating efficacy. Results. The mean age of patients with tuberculoma and adenocarcinoma was 46.8 ± 12.3 years (range, 28–64) and 61.1 ± 9.9 years (range, 41–77), respectively. No significant differences were observed concerning smoking history and smoking index, underlying disease, or tumor markers between the two groups. Univariate and multivariate analyses showed age and lobulation combined with pleural indentation demonstrated excellent discrimination. The sensitivity, specificity, accuracy, and the area under the ROC curve were 87.1%, 93.3%, 90.2%, and 0.956 (95% confidence interval (CI), 0.901–1.000), respectively. Conclusion. The combination of clinical characteristics and CT morphological features can be used to distinguish noncalcified, solitary tuberculoma from solid adenocarcinoma with high diagnostic performance and has a clinical application value.

Radiologic Features of Resected Lung Adenocarcinoma With Epithelial-Mesenchymal Transition

BACKGROUND

Epithelial-mesenchymal transition plays a crucial role in cancer progression and is a significant prognosticator for postoperative survival in patients with lung cancer. Predicting epithelial-mesenchymal transition preoperatively using computed tomography may help to determine the optimal surgical strategy.

METHODS

We performed an immunohistochemical analysis of E-cadherin and vimentin expressions using tumor specimens from resected primary lung adenocarcinoma and classified the results into 3 subgroups according to the expressions: epithelial, intermediate, and mesenchymal. The intermediate and mesenchymal groups were classified as the epithelial-mesenchymal transition conversion group. We analyzed the association between epithelial-mesenchymal transition and radiologic characteristics, especially computed tomographic features.

RESULTS

The epithelial-mesenchymal transition conversion group comprised 162 patients (49.1%). Computed tomography revealed that tumors with epithelial-mesenchymal transition conversion showed a high consolidation/tumor ratio compared with those without conversion. Univariate analysis demonstrated that tumors with epithelial-mesenchymal transition were significantly associated with bronchial and/or vascular convergence (P < .001) and notching (P = .028). When the cutoff value for the consolidation/tumor ratio was set by the receiver operating characteristic curve, independent predictive factors for epithelial-mesenchymal transition by multivariate analysis were high ratio (>0.7946; P < .001) and the presence of convergence (P = .05). Tumors with a high consolidation/tumor ratio and convergence had a 4-fold higher odds ratio for epithelial-mesenchymal transition, and patients had significantly poorer survival.

CONCLUSIONS

Convergence and a high consolidation/tumor ratio were independently associated with epithelial-mesenchymal transition conversion. These preoperative radiologic results will help to predict epithelial-mesenchymal transition conversion in lung adenocarcinoma.

Prognostic value of morphological characteristics assessed by CT scan in patients with non-small cell lung cancer treated with nivolumab

Background

Nivolumab is known to demonstrate superior overall survival compared with docetaxel in pretreated non‐small cell lung cancer (NSCLC) patients. Programmed death‐ligand 1 (PD‐L1) expression is reported to predict the outcome of treatment by nivolumab in lung cancer patients. However, the significance of the morphological characteristics of chest computed tomography (CT) as predictors of nivolumab efficacy for advanced NSCLC patients remains unknown.

Methods

We performed a multicenter retrospective trial from April 2013 to March 2017, to assess the significance of CT morphological characteristics as predictors of nivolumab efficacy for advanced NSCLC patients. A total of 78 NSCLC patients pretreated with nivolumab were enrolled. A chest radiologist used chest CT to assess the following morphological characteristics of each patient's main tumor and intrathoracic status prior to nivolumab treatment; interstitial septal thickening, peritumoral ground‐glass opacity, spiculated margin, air bronchogram, cavity or necrosis, adjacent organ invasion, bulky lymph node, and accumulation of small lymph nodes. Logistic regression and Cox proportional hazards regression models were used to analyze outcomes.

Results

A total of 60 (77%) patients were male and 72 (92%) had a performance status (PS) of 0 or 1. The objective response rates of male patients and heavy smokers were significantly higher than those of female patients and light or never smokers, respectively. Multivariate analysis identified light or never smoking, poor PS, histological type of squamous cell carcinoma, and interstitial septal thickening as independent negative predictors of progression free survival (PFS).

Conclusions

Interstitial septal thickening was a significant and independent predictor of PFS in NSCLC patients treated with nivolumab.

Key points

Significant findings of the study

Interstitial septal thickening is an independent predictor of progression free survival in non‐small lung cancer patients treated with nivolumab.

What this study adds

The current study reveals the significance of morphological characteristics obtained via chest computed tomography as a predictor of nivolumab efficacy for advanced non‐small cell lung cancer patients.

Blood Supply of Early Lung Adenocarcinomas in Mice and the Tumor-supplying Vessel Relationship: A Micro-CT Angiography Study

This study aimed to investigate the blood supply of early lung adenocarcinomas in mice and the relationship between tumors and their supplying vessels by using micro-CT. An early lung adenocarcinoma model was established in 10 female mice with subcutaneous injections of a 1-methyl-3-nitro-1-nitrosoguanidine solution. Micro-CT pulmonary and bronchial arteriography were performed to demonstrate the blood supply of early lung adenocarcinomas, especially the tumor-vessel relationships, and the findings were correlated with the pathology results. The quantitative and texture changes in the tumor-supplying vessels were analyzed. Micro-CT showed that the pulmonary artery was densely distributed in and around tumors in 141 (84%) of 167 early lung adenocarcinomas, the bronchial artery was not related to tumors, and there were four patterns of tumor-pulmonary artery relationships that correlated well with pathologic findings. Quantitative and texture analyses showed that the tumor size had positive correlations with vessel volume (VV), VV fraction (VVF), vessel thickness (VT), vessel number (VN), inverse difference moment, long run emphasis, gray level nonuniformity (GLN), and run length nonuniformity (RLN) and negative correlations with vessel separation (VS), inertia, and short run emphasis (SRE); the size of the solid component had positive correlations with VV, VVF, VT, VN, GLN, and RLN and negative correlations with VS, cluster shade, and SRE. This study concluded that early lung adenocarcinomas are mainly supplied by the pulmonary arteries in mice, and micro-CT angiography can clearly demonstrate the morphologic changes of pulmonary arteries and their relationships with tumors.

CT Halo sign: A systematic review

PURPOSE

The CT Halo sign or Halo sign (HS) refers to ground-glass opacity surrounding a nodule or mass in the lung parenchyma. We conducted a systematic review to find the etiological associations of HS. We also evaluated the diagnostic performances of HS for invasive fungal infections (IFI) in immunosuppressed patients.

METHOD

The systematic review was conducted as per PRISMA guidelines. We searched the PubMed and EMBASE database till June 2018 without any restrictions. Only case reports, case series and original articles published in English language were included. A database created from the electronic searches was compiled and subsequent analysis was done. [PROSPERO registration: CRD42018094739] RESULTS: 168 studies were eligible, which included 51 case reports, 15 prospective studies, 102 retrospective studies. A total of 1977 patients (out of 6371) with HS were identified with age range between <1year-94years. The most common diagnosis in the immunosuppressed, mixed, immunocompetent and not specified groups were IFI (86.9 %, n = 1194), Cryptococcosis (51.6 %, n = 124), Cryptococcosis (40 %, n = 20) and lung neoplasms (81.8 %, n = 36) respectively. 14 studies (11 retrospective, 3 prospective) were included in quantitative analysis. The pooled sensitivity(sn), specificity(sp) and odd's ratio (OR) of HS for diagnosing IFI were 50.4 %, 91 % and 6.61 respectively. Also, HS could not reliably differentiate IPA from mucormycosis in the pooled analysis.

CONCLUSIONS

HS can be seen in a large number of diverse conditions both in immunosuppressed and immunocompetent population. In immunosuppressed patients HS is specific for IFI but cannot rule it out. Additionally, it cannot reliably distinguish between IPA and mucormycosis.

Homological radiomics analysis for prognostic prediction in lung cancer patients

PURPOSE

This study explored a novel homological analysis method for prognostic prediction in lung cancer patients.

MATERIALS AND METHODS

The potential of homology-based radiomic features (HFs) was investigated by comparing HFs to conventional wavelet-based radiomic features (WFs) and combined radiomic features consisting of HFs and WFs (HWFs), using training (n = 135) and validation (n = 70) datasets, and Kaplan-Meier analysis. A total of 13,824 HFs were derived through homology-based texture analysis using Betti numbers, which represent the topologically invariant morphological characteristics of lung cancer. The prognostic potential of HFs was evaluated using statistically significant differences (p-values, log-rank test) to compare the survival curves of high- and low-risk patients. Those patients were stratified into high- and low-risk groups using the medians of the radiomic scores of signatures constructed with an elastic-net-regularized Cox proportional hazard model. Furthermore, deep learning (DL) based on AlexNet was utilized to compare HFs by stratifying patients into the two groups using a network that was pre-trained with over one million natural images from an ImageNet database.

RESULTS

For the training dataset, the p-values between the two survival curves were 6.7 × 10^-6 (HF), 5.9 × 10^-3 (WF), 7.4 × 10^-6 (HWF), and 1.1 × 10^-3 (DL). The p-values for the validation dataset were 3.4 × 10^-5 (HF), 6.7 × 10^-1 (WF), 1.7 × 10^-7 (HWF), and 1.2 × 10^-1 (DL).

CONCLUSION

This study demonstrates the excellent potential of HFs for prognostic prediction in lung cancer patients.

Clinical and radiological characteristics of central pulmonary adenocarcinoma: a comparison with central squamous cell carcinoma and small cell lung cancer and the impact on treatment response

Purpose

The proportion of central pulmonary adenocarcinoma (ADC) in central-type lung cancer has been gradually increasing due to the overall increasing incidence of pulmonary ADC. But the clinical and radiological characteristics of central ADCs remain unclear. In this study, we compared the clinical and radiological characteristics of central ADCs with those of small cell lung cancers (SCLCs) and squamous cell carcinomas (SQCCs) and investigated the impact of these characteristics on patients’ treatment response.

Patients and methods

The medical records of 302 consecutive patients with central lung cancer from July 2014 to September 2016 were retrospectively reviewed. There were 99 patients with ADC, 95 with SQCC and 108 with SCLC. Computed tomography images were interpreted by two radiologists. Treatment response was determined by Response Evaluation Criteria In Solid Tumors 1.1.

Results

Univariate analyses found that younger age, female sex, no history of smoking, higher levels of carcinoembryonic antigen (CEA), contralateral hilum lymphadenopathy, contralateral lung metastasis, pleural nodules and pleural metastasis to the interlobular fissure were significantly correlated with central ADC. Multivariate logistic regression analyses revealed that compared with central SQCC, female sex, younger age, no history of smoking, higher levels of CEA and contralateral hilum lymphadenopathy were the significantly independent indicators of central pulmonary ADC. Furthermore, compared with central SCLC, younger age, higher levels of CEA and cytokeratin 19 fragment (Cyfra21-1), lower levels of neuron-specific enolase, pleural nodules and lack of vascular involvement were significantly associated with central ADC. In 85 central ADC patients who received first-line platinum-based chemotherapy, both univariate and multivariate logistic regression analyses revealed that pulmonary emphysema had a negative correlation with treatment response (odds ratio=8.04, p=0.02).

Conclusion

Our study revealed that central pulmonary ADCs exhibited more aggressive clinical and radiological characteristics. Pulmonary emphysema was an independent and negative indicator for treatment response of central ADC.

Novel biologic factors correlated to visceral pleural invasion in early-stage non-small cell lung cancer less than 3 cm

Background

Visceral pleural invasion (VPI) in early-stage non-small cell lung cancer (NSCLC) is traditionally believed as the result of too much close distance between cancerous lesion and the visceral pleura, but whether there are any other biologic factors correlated to VPI beyond our instinctive thoughts remains unclear. Therefore, we conducted this study to investigate potential factors correlated to VPI comprehensively.

Methods

Both clinical and pathological characteristics of patients undergoing surgery for NSCLC with a size of ≤3 cm were retrospectively analysed.

Results

A total of 403 patients were included for analysis. Patients with VPI had older age than those without (61.1 vs. 56.1 years; P<0.001). The mean size of NSCLCs with VPI was larger than those without (2.1 vs. 1.6 cm; P<0.001). Moreover, NSCLCs with VPI were located closer to visceral pleura (0.8 vs. 1.3 cm; P<0.001) and showed larger rates of pleural indentation (86.8% vs. 45.6%; P<0.001) and spiculation (59.7% vs. 34.7%; P<0.001) than those without. Pathologically, NSCLCs with VPI tended more likely to be adenocarcinomas (96.9% vs. 92.7%; P=0.097), and was more likely to be poorly differentiated (38.0% vs. 15.3%; P<0.001), to have cancer embolus (6.2% vs. 0.7%; P=0.001) and lymph node metastasis (29.5% vs. 10.2%; P<0.001) than those without. Besides shorter distance to visceral pleura [odds ratio (OR)=2.169, 95% CI: 1.221-3.855; P=0.008], older age [OR =2.119, 95% confidence interval (CI): 1.255-3.503; P=0.005], pleural indentation (OR =3.679, 95% CI: 1.888-7.169; P<0.001), adenocarcinoma (OR =4.741, 95% CI: 1.383-16.255; P=0.013), and poor tumor differentiation (OR =11.816, 95% CI: 4.470-31.234; P<0.001) were also found to be closely correlated to VPI in early-stage NSCLC.

Conclusions

Besides shorter distance to visceral pleura and pleural indentation, elderly, adenocarcinoma, and poor tumor differentiation were novel biologic factors correlated to VPI in early-stage NSCLC, which may explain why VPI was an unfavorable prognostic factor for early-stage NSCLC.