Brain imaging in early stage non-small cell lung cancer: still a controversial topic?

Differential Distribution of Brain Metastases from Non-Small Cell Lung Cancer Based on Mutation Status

Non-small cell lung cancer (NSCLC) has a high rate of brain metastasis. The purpose of this study was to assess the differential distribution of brain metastases from primary NSCLC based on mutation status. Brain MRI scans of patients with brain metastases from primary NSCLC were retrospectively analyzed. Brain metastatic tumors were grouped according to mutation status of their primary NSCLC and the neuroimaging features of these brain metastases were analyzed. A total of 110 patients with 1386 brain metastases from primary NSCLC were included in this study. Gray matter density at the tumor center peaked at ~0.6 for all mutations. The median depths of tumors were 7.9 mm, 8.7 mm and 9.1 mm for EGFR, ALK and KRAS mutation groups, respectively (p = 0.044). Brain metastases for the EGFR mutation-positive group were more frequently located in the left cerebellum, left cuneus, left precuneus and right precentral gyrus. In the ALK mutation-positive group, brain metastases were more frequently located in the right middle occipital gyrus, right posterior cingulate, right precuneus, right precentral gyrus and right parietal lobe. In the KRAS mutation-positive patient group, brain metastases were more frequently located in the posterior left cerebellum. Our study showed differential spatial distribution of brain metastases in patients with NSCLC according to their mutation status. Information regarding distribution of brain metastases is clinically relevant as it could be helpful to guide treatment planning for targeted therapy, and for predicting prognosis.

Advances in the Molecular Landscape of Lung Cancer Brain Metastasis

Lung cancer is one of the most frequent tumors that metastasize to the brain. Brain metastasis (BM) is common in advanced cases, being the major cause of patient morbidity and mortality. BMs are thought to arise via the seeding of circulating tumor cells into the brain microvasculature. In brain tissue, the interaction with immune cells promotes a microenvironment favorable to the growth of cancer cells. Despite multimodal treatments and advances in systemic therapies, lung cancer patients still have poor prognoses. Therefore, there is an urgent need to identify the molecular drivers of BM and clinically applicable biomarkers in order to improve disease outcomes and patient survival. The goal of this review is to summarize the current state of knowledge on the mechanisms of the metastatic spread of lung cancer to the brain and how the metastatic spread is influenced by the brain microenvironment, and to elucidate the molecular determinants of brain metastasis regarding the role of genomic and transcriptomic changes, including coding and non-coding RNAs. We also present an overview of the current therapeutics and novel treatment strategies for patients diagnosed with BM from NSCLC.

Role of Pre-Operative Brain Imaging in Patients with NSCLC Stage I: A Retrospective, Multicenter Analysis

Simple Summary

Lung cancer is the worldwide leading cause of cancer-related death among both genders, with about 230,000 patients/year being diagnosed in the US alone. It accounts for about 40% of all brain metastases, which already occur in around 3% of early-stage patients. Nonetheless, current international guidelines do not unanimously recommend brain imaging for use in the early stages of cancer. Some studies have suggested that surgical or radiosurgical treatment of brain metastases may provide better survival, especially in asymptomatic patients. Additionally, advances in genome analysis have identified molecular targets for pharmaceutical agents. These recent advancements in treatment stress the importance of studying incidence as well as patient and tumor characteristics in order to potentially adapt future guidelines and provide the best possible treatment for early-stage lung cancer. This multicentric study analyzed the data of 577 patients diagnosed with early-stage lung cancer who had been submitted for brain imaging at initial tumor staging.

Abstract

Background: Lung cancer is the worldwide leading oncological cause of death in both genders combined and accounts for around 40–50% of brain metastases in general. In early-stage lung cancer, the incidence of brain metastases is around 3%. Since the early detection of asymptomatic cerebral metastases is of prognostic value, the aim of this study was to analyze the incidence of brain metastases in early-stage lung cancer and identify possible risk factors. Methods: We conducted a retrospective multicentric analysis of patients with Stage I (based on T and N stage only) Non-Small Cell Lung Cancer (NSCLC) who had received preoperative cerebral imaging in the form of contrast-enhanced CT or MRI. Patients with a history of NSCLC, synchronous malignancy, or neurological symptoms were excluded from the study. Analyzed variables were gender, age, tumor histology, cerebral imaging findings, smoking history, and tumor size. Results were expressed as mean with standard deviation or median with range. Results: In total, 577 patients were included in our study. Eight (1.4%) patients were found to have brain metastases in preoperative brain imaging. Tumor histology was adenocarcinoma in all eight cases. Patients were treated with radiotherapy (five), surgical resection (two), or both (one) prior to thoracic surgical treatment. Other than tumor histology, no statistically significant characteristics were found to be predictive of brain metastases. Conclusion: Given the low incidence of brain metastases in patients with clinical Stage I NSCLC, brain imaging in this cohort could be avoided.

Machine Learning for the Prediction of Synchronous Organ-Specific Metastasis in Patients With Lung Cancer

Background

This study aimed to develop an artificial neural network (ANN) model for predicting synchronous organ-specific metastasis in lung cancer (LC) patients.

Methods

A total of 62,151 patients who diagnosed as LC without data missing between 2010 and 2015 were identified from Surveillance, Epidemiology, and End Results (SEER) program. The ANN model was trained and tested on an 75/25 split of the dataset. The receiver operating characteristic (ROC) curves, area under the curve (AUC) and sensitivity were used to evaluate and compare the ANN model with the random forest model.

Results

For distant metastasis in the whole cohort, the ANN model had metrics AUC = 0.759, accuracy = 0.669, sensitivity = 0.906, and specificity = 0.613, which was better than the random forest model. For organ-specific metastasis in the cohort with distant metastasis, the sensitivity in bone metastasis, brain metastasis and liver metastasis were 0.913, 0.906 and 0.925, respectively. The most important variable was separate tumor nodules with 100% importance. The second important variable was visceral pleural invasion for distant metastasis, while histology for organ-specific metastasis.

Conclusions

Our study developed a “two-step” ANN model for predicting synchronous organ-specific metastasis in LC patients. This ANN model may provide clinicians with more personalized clinical decisions, contribute to rationalize metastasis screening, and reduce the burden on patients and the health care system.

No Prognostic Impact of Staging Brain MRI in Patients with Stage IA Non-Small Cell Lung Cancer

Background Although various guidelines discourage performing brain MRI for staging purposes in asymptomatic patients with clinical stage IA non-small cell lung cancer (NSCLC), evidence regarding their postoperative survival is lacking. Purpose To investigate the survival benefit of performing brain MRI in asymptomatic patients with early-stage NSCLC. Materials and Methods Patients who underwent curative resection between February 2009 and March 2016 for clinical TNM stage T1N0M0 NSCLC were retrospectively included. Patient survival and development of brain metastasis during postoperative surveillance were documented. The cumulative survival rate and incidence of brain metastasis were compared between patients who underwent surgery with or without staging brain MRI by using Cox regression and a Fine-Gray subdistribution hazard model, respectively, for multivariable adjustment. Propensity score matching and inverse probability of treatment weighting were applied for confounder adjustment. Results A total of 628 patients (mean age, 64 years ± 10 [SD]; 319 men) were included, of whom 53% (331 of 628) underwent staging brain MRI. In the multivariable analyses, brain MRI did not show prognostic benefits for brain metastasis-free survival (hazard ratio [HR], 1.06; 95% CI: 0.69, 1.63; P = .79), time to brain metastasis (HR, 1.60; 95% CI: 0.70, 3.94; P = .29), and overall survival (HR, 0.86; 95% CI, 0.54, 1.37; P = .54). Consistent results were obtained after propensity score matching (brain metastasis-free survival [HR, 0.97; 95% CI: 0.60, 1.57; P = .91], time to brain metastasis [HR, 1.29; 95% CI: 0.50, 3.33; P = .60], and overall survival [HR, 0.89; 95% CI: 0.53, 1.51; P = .67]) and inverse probability of treatment weighting. Conclusion No difference was observed between asymptomatic patients with clinical stage IA non-small cell lung cancer who underwent staging brain MRI and those who did not in terms of brain metastasis-free survival, time to brain metastasis, and overall survival. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Bizzi and Pascuzzo in this issue.

Assessment of Brain Metastasis at Diagnosis in Non-Small-Cell Lung Cancer: A Prospective Observational Study From North India

PURPOSE

The incidence of symptomatic brain metastasis at diagnosis in non–small-cell lung cancer (NSCLC) is 5%-10%, and up to 40% develop during the disease course. There is a paucity of data supporting the role of brain imaging at diagnosis in asymptomatic cases particularly from resource-constraint settings. Here, we present our experience of mandatory baseline brain imaging with contrast-enhanced computed tomography (CECT) scans of all patients with NSCLC.

MATERIALS AND METHODS

This was a prospective observation study of patients with NSCLC with mandatory baseline brain CECT and a CNS examination. All histology proven patients with NSCLC diagnosed between January 2018 and October 2019 were included irrespective of stage.

RESULTS

A total of 496 patients were enrolled. The median age was 57 years (range, 23-84) with majority being males (75%) and smokers (66%). The prevalence of epidermal growth factor receptor mutations and anaplastic lymphoma kinase fusions was 33.4% and 12%, respectively. Brain imaging leads to upstaging in 7% cases. The prevalence of brain metastases was 21% (n = 104), with half being asymptomatic (51%). Factors associated with higher proportion of brain metastasis were young age (≤ 40 years), adenocarcinoma histology, poor Eastern Cooperative Oncology Group performance status (3 and 4), and high neutrophil-lymphocyte ratio (NLR) (> 2.5). After a median follow-up of 10.8 months (95% CI, 7.33 to 12.73), the median overall survival was 7.46 versus 12.76 months (hazard ratio 0.67; 95% CI, 0.46 to 0.96; P = .03) in patients with and without brain metastases, respectively. On multivariate analyses, high NLR and molecular graded prognostic assessment affected the overall survival significantly.

CONCLUSION

In our study, 21% of patients had brain metastasis at diagnosis detected with a mandatory baseline brain imaging with CECT. NLR and molecular graded prognostic assessment are significant predictors of survival in patients with brain metastasis.

The effect of diagnostic assessment programs on the diagnosis and treatment of patients with lung cancer in Ontario, Canada

INTRODUCTION

Diagnostic assessment programs (DAPs) were implemented in Ontario, Canada, to improve the efficiency of the lung cancer care continuum. We compared the efficiency and effectiveness of care provided to patients in DAPs relative to usual care (non-DAPs).

METHODS

Lung cancer patients diagnosed between 2014 and 2016 were identified from the Ontario Cancer Registry. Using administrative databases, we identified various health-care encounters 6 months before diagnosis until the start of treatment and compared utilization patterns, timing, and overall survival between DAP and non-DAP patients.

RESULTS

DAP patients were younger (P < 0.0001), had fewer comorbidities (P = 0.0006), and were more likely to have early-stage disease (36% vs. 25%) than non-DAP patients. Although DAP patients had a similar time until diagnosis as non-DAP patients, the time until treatment was 8.5 days shorter for DAP patients. DAP patients were more likely to receive diagnostic tests and specialist consultations and less likely to have duplicate chest imaging. DAP patients were more likely to receive brain imaging. Among early-stage lung cancers, brain imaging was high (74% for DAP and 67% for non-DAP), exceeding guideline recommendations. After adjustment for clinical and demographic factors, DAP patients had better overall survival than non-DAP patients (hazard ratio [HR]: 0.79 [0.76-0.82]), but this benefit was lost after adjusting for emergency presentation (HR: 0.96 [0.92-1.00]). A longer time until treatment was associated with better overall survival.

CONCLUSION

DAPs provided earlier treatment and better access to care, potentially improving survival. Quality improvement opportunities include reducing unnecessary or duplicate testing and characterizing patients who are diagnosed emergently.

Incidence and real-world burden of brain metastases from solid tumors and hematologic malignancies in Ontario: a population-based study

BACKGROUND

Although intracranial metastatic disease (IMD) is a frequent complication of cancer, most cancer registries do not capture these cases. Consequently, a data-gap exists, which thwarts system-level quality improvement efforts. The purpose of this investigation was to determine the real-world burden of IMD.

METHODS

Patients diagnosed with a non-CNS cancer between 2010 and 2018 were identified from the Ontario Cancer Registry. IMD was identified by scanning hospital administrative databases for cranial irradiation or coding for a secondary brain malignancy (ICD-10 code C793).

RESULTS

25,478 of 601,678 (4.2%) patients with a diagnosis of primary cancer were found to have IMD. The median time from primary cancer diagnosis to IMD was 5.2 (0.7, 15.4) months and varied across disease sites, for example, 2.1 months for lung, 7.3 months for kidney, and 22.8 months for breast. Median survival following diagnosis with IMD was 3.7 months. Lung cancer accounted for 60% of all brain metastases, followed by breast cancer (11%) and melanoma (6%). More advanced stage at diagnosis and younger age were associated with a higher likelihood of developing IMD (P < .0001). IMD was also associated with triple-negative breast cancers and ductal histology (P < .001), and with small-cell histology in patients with lung cancer (P < .0001). The annual incidence of IMD was 3,520, translating to 24.2 per 100,000 persons.

CONCLUSION

IMD represents a significant burden in patients with systemic cancers and is a significant cause of cancer mortality. Our findings support measures to actively capture incidents of brain metastasis in cancer registries.

Delayed surgery after histologic or radiologic-diagnosed clinical stage I lung adenocarcinoma

Background

The impact of delayed surgery on clinical outcomes after histologic or radiologic diagnosis of clinical stage I adenocarcinoma remains controversial. We evaluated the effects of delayed surgery on outcomes of patients with early-stage lung cancer.

Methods

Associations between time intervals of “histologic diagnosis-to-surgery” (HDS), “radiologic diagnosis-to-surgery” (RDS), and overall survival in clinical stage I adenocarcinoma were assessed using multivariable Cox proportional hazard analysis.

Results

A total of 561 consecutive patients with preoperative histologic confirmation of stage I lung cancer between 2006 and 2016 were included. Median time to HDS and RDS were 20 (2–267) and 58 (38–2,983) days. Higher Charlson comorbidity score, receiving brain magnetic resonance imaging screening, and video-assisted thoracoscopic surgery approach were significantly associated with increased risk of late HDS (>21 days). Smaller tumor size and non-radiologic solid-dominant pattern were significantly associated with increased risk of late RDS (>60 days). In the overall cohort, worse 5-year overall survival was associated with late HDS compared to early HDS (75.9% vs. 85.5%, P=0.003). No significant differences were found in later late vs. early RDS (83.7% vs. 83.3%, P=0.570). In 286 propensity-score matched patients, late HDS [adjusted hazard ratio (aHR) =2.031, P=0.038], higher Charlson comorbidity score (aHR=1.610, P=0.023), larger tumor size (aHR=2.164, P=0.031), without brain magnetic resonance imaging screening (aHR=2.051, P=0.045), and tumor with angiolymphatic invasion (aHR=4.638, P=0.001) were significantly associated with lower overall survival.

Conclusions

In patients with stage I lung adenocarcinoma, delayed surgery after a histologic diagnosis is an independent predictor of overall survival after adjusting for clinical risk factors, suggesting meaningful differences in clinical outcomes between timely vs. delayed surgeries.