Screening for brain metastases in patients with stage III non-small-cell lung cancer, magnetic resonance imaging or computed tomography? A prospective study

Real-life clinical management patterns in extensive-stage small cell lung cancer across France: a multi-method study

BACKGROUND

We designed this study based on both a physician practice survey and real-world patient data to: (1) evaluate clinical management practices in extensive-stage small cell lung cancer (ES-SCLC) among medical centers located across France; and (2) describe first-line treatment patterns among patients with ES-SCLC following the introduction of immunotherapy into clinical practice.

METHODS

A 50-item questionnaire was completed by physicians from 45 medical centers specialized in SCLC management. Responses were collected from June 2022 to January 2023. The survey questions addressed diagnostic workup of ES-SCLC, chemoimmunotherapy in first-line and second-line settings, and use of prophylactic cranial irradiation (PCI) and radiotherapy. In parallel, using a chart review approach, we retrospectively analyzed aggregated information from 548 adults with confirmed ES-SCLC receiving first-line treatment in the same centers.

RESULTS

In ES-SCLC, treatment planning is based on chest computed tomography (CT) (as declared by 100% of surveyed centers). Mean time between diagnosis and treatment initiation was 2-7 days, as declared by 82% of centers. For detection of brain metastases, the most common imaging test was brain CT (84%). The main exclusion criteria for first-line immunotherapy in the centers were autoimmune disease (87%), corticosteroid therapy (69%), interstitial lung disease (69%), and performance status ≥ 2 (69%). Overall, 53% and 36% of centers considered that patients are chemotherapy-sensitive if they relapse within ≥ 3 months or ≥ 6 months after first-line chemoimmunotherapy, respectively. Among the 548 analyzed patients, 409 (75%) received chemoimmunotherapy as a first-line treatment, 374 (91%) of whom received carboplatin plus etoposide and 35 (9%) cisplatin plus etoposide. Overall, 340/548 patients (62%) received maintenance immunotherapy. Most patients (68%) did not receive radiotherapy or PCI.

CONCLUSIONS

There is an overall alignment of practices reflecting recent clinical guidelines among medical centers managing ES-SCLC across France, and a high prescription rate of immunotherapy in the first-line setting.

A systematic review of brain metastases from lung cancer using magnetic resonance neuroimaging: Clinical and technical aspects

INTRODUCTION

Brain metastases (BMs) are common in lung cancer (LC) and are associated with poor prognosis. Magnetic resonance imaging (MRI) plays a vital role in the detection, diagnosis and management of BMs. This review summarises recent advances in MRI techniques for BMs from LC.

METHODS

This systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive literature search was conducted in three electronic databases: PubMed, Scopus and the Web of Science. The search was limited to studies published between January 2000 and March 2023. The quality of the included studies was evaluated using appropriate tools for different study designs. A narrative synthesis was carried out to describe the key findings of the included studies.

RESULTS

Sixty-five studies were included. Standard MRI sequences such as T1-weighted (T1w), T2-weighted (T2w) and fluid-attenuated inversion recovery (FLAIR) were commonly used. Advanced techniques included perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and radiomics analysis. DWI and PWI parameters could distinguish tumour recurrence from radiation necrosis. Radiomics models predicted genetic mutations and the risk of BMs. Diagnostic accuracy was improved with deep learning (DL) approaches. Prognostic factors such as performance status and concurrent chemotherapy impacted survival.

CONCLUSION

Advanced MRI techniques and specialised MRI methods have emerging roles in managing BMs from LC. PWI and DWI improve diagnostic accuracy in treated BMs. Radiomics and DL facilitate personalised prognosis and treatment. Magnetic resonance imaging plays a key role in the continuum of care for BMs of patients with LC, from screening to treatment monitoring.

Canadian Consensus Recommendations for the Management of Operable Stage II/III Non-Small-Cell Lung Cancer: Results of a Modified Delphi Process

The treatment paradigm for patients with stage II/III non-small-cell lung cancer (NSCLC) is rapidly evolving. We performed a modified Delphi process culminating at the Early-stage Lung cancer International eXpert Retreat (ELIXR23) meeting held in Montreal, Canada, in June 2023. Participants included medical and radiation oncologists, thoracic surgeons and pathologists from across Quebec. Statements relating to diagnosis and treatment paradigms in the preoperative, operative and postoperative time periods were generated and modified until all held a high level of consensus. These statements are aimed to help guide clinicians involved in the treatment of patients with stage II/III NSCLC.

Clinical management of stage III non-small cell lung cancer in India: An expert consensus statement

Non-small cell lung cancer (NSCLC) is considered the most common type of lung cancer (>80% of all lung cancers); patients are often diagnosed at advanced stages of the disease. The management of NSCLC is considered challenging owing to variations in size, an extension of the tumors, involvement patterns, and classification. Although adequate literature and guidelines are available on the management of NSCLC in several countries, an Indian perspective on stage III NSCLC management is lacking. We used the modified Delphi approach to form consensus statements. A thorough literature search was done. The authors then convened and deliberated over published literature, available guidelines, and clinical judgment. Recommendation statements were formed for different clinical scenarios. These statements were sent as a form of survey to other oncologists, and their responses were recorded and mentioned. Evidence-based statements were formed for diagnosing and managing stage III NSCLC. These recommendation statements cover various aspects-surgical, radiation, and medical treatment in various clinical scenarios including adjuvant, neoadjuvant, and consolidation therapies.

Genomic Alterations and the Incidence of Brain Metastases in Advanced and Metastatic NSCLC: A Systematic Review and Meta-Analysis

INTRODUCTION

Brain metastases (BMs) in patients with advanced and metastatic NSCLC are linked to poor prognosis. Identifying genomic alterations associated with BM development could influence screening and determine targeted treatment. We aimed to establish prevalence and incidence in these groups, stratified by genomic alterations.

METHODS

A systematic review and meta-analysis compliant with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses were conducted (PROSPERO identification CRD42022315915). Articles published in MEDLINE, EMBASE, and Cochrane Library between January 2000 and May 2022 were included. Prevalence at diagnosis and incidence of new BM per year were obtained, including patients with EGFR, ALK, KRAS, and other alterations. Pooled incidence rates were calculated using random effects models.

RESULTS

A total of 64 unique articles were included (24,784 patients with NSCLC with prevalence data from 45 studies and 9058 patients with NSCLC having incidence data from 40 studies). Pooled BM prevalence at diagnosis was 28.6% (45 studies, 95% confidence interval [CI]: 26.1-31.0), and highest in patients that are ALK-positive (34.9%) or with RET-translocations (32.2%). With a median follow-up of 24 months, the per-year incidence of new BM was 0.13 in the wild-type group (14 studies, 95% CI: 0.11-0.16). Incidence was 0.16 in the EGFR group (16 studies, 95% CI: 0.11-0.21), 0.17 in the ALK group (five studies, 95% CI: 0.10-0.27), 0.10 in the KRAS group (four studies, 95% CI: 0.06-0.17), 0.13 in the ROS1 group (three studies, 95% CI: 0.06-0.28), and 0.12 in the RET group (two studies, 95% CI: 0.08-0.17).

CONCLUSIONS

Comprehensive meta-analysis indicates a higher prevalence and incidence of BM in patients with certain targetable genomic alterations. This supports brain imaging at staging and follow-up, and the need for targeted therapies with brain penetrance.

Application of radiomics in diagnosis and treatment of lung cancer

Radiomics has become a research field that involves the process of converting standard nursing images into quantitative image data, which can be combined with other data sources and subsequently analyzed using traditional biostatistics or artificial intelligence (Al) methods. Due to the capture of biological and pathophysiological information by radiomics features, these quantitative radiomics features have been proven to provide fast and accurate non-invasive biomarkers for lung cancer risk prediction, diagnosis, prognosis, treatment response monitoring, and tumor biology. In this review, radiomics has been emphasized and discussed in lung cancer research, including advantages, challenges, and drawbacks.

Trends in the epidemiology of small-cell lung cancer: a Dutch nationwide population-based study over 1989-2020

INTRODUCTION

This study describes the evolving characteristics of patients with small-cell lung cancer (SCLC) from 1989 to 2020 in the Netherlands to analyse how the population of patients with SCLC has changed in the last decades, hypothesising that this might explain the little progress made in SCLC.

METHODS

Patients with SCLC diagnosed from 1989 to 2020 were selected from the Dutch cancer registry. Incidence, patient and disease characteristics, treatments, and overall survival (OS) were analysed. Joinpoint analyses were used to test annual percentage changes for statistical significance.

RESULTS

A total of 52,527 patients were diagnosed with SCLC. The absolute numbers of patients with SCLC remained equal over the years; however, the incidence rates decreased from 15.01 to 8.93 per 100,000 person-years. The proportion of women increased from 22% to 50%, and those aged ≥75 years increased from 20% to 25%. The latter coincided with a higher proportion receiving only the best supportive care (BSC) over the years (18-24%). The use of surgery in stage I increased from 2% to 37%. The proportion of patients diagnosed with stage IV increased from 46% to 70% due to better staging. The OS improved for all stages, with a 2-year OS rate for stage IV doubling from 3% to 6%.

CONCLUSION

The incidence of SCLC has significantly decreased over the last 30 years, with an increasing proportion of elderly and women. The male-female ratio became similar, and the OS improved. As a consequence of more elderly and probably more vulnerable patients, more patients received only the BSC.

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.

Screening for Brain Metastases in Patients With NSCLC: A Qualitative Study on the Psychologic Impact of Being Diagnosed With Asymptomatic Brain Metastases

Introduction

The brain is a frequent site of metastases in NSCLC, and screening for asymptomatic brain metastases (BM) is increasingly advised in NSCLC guidelines. An asymptomatic BM diagnosis may trigger anxiety for future neurologic problems and can negatively affect quality of life of patients and their relatives. Therefore, we performed this qualitative study.

Methods

Three focus group discussions were organized with patients with NSCLC and asymptomatic BM (N = 3–4 per group) and separately with their relatives, to explore this psychosocial impact. Two researchers independently performed an inductive content analysis.

Results

A total of 10 patients and 10 relatives participated in six focus groups. A diagnosis of BM caused feelings of distress and anxiety in both patients and relatives. These feelings diminished over time in case of a tumor responding to systemic therapy. The diagnosis of BM was not perceived as more distressful than other metastases, and scan-related anxiety was not experienced. Although magnetic resonance imaging screening and follow-up were thought of as burdensome, follow-up was valued. The coping strategies of both groups seemed related to personality and to the efficacy of the given systemic therapy. Relatives appreciated peer support of other relatives during the focus groups, and they seemed open for future psychological support.

Conclusions

Asymptomatic BM diagnosis can cause anxiety and distress, but this diminishes over time with effective systemic treatment. Although patients perceive magnetic resonance imaging as burdensome, they value follow-up screening and imaging. Relatives highly appreciated peer support, and psychological distress of relatives should not be overlooked.

Investigation of the added value of CT-based radiomics in predicting the development of brain metastases in patients with radically treated stage III NSCLC

Introduction:

Despite radical intent therapy for patients with stage III non-small-cell lung cancer (NSCLC), cumulative incidence of brain metastases (BM) reaches 30%. Current risk stratification methods fail to accurately identify these patients. As radiomics features have been shown to have predictive value, this study aims to develop a model combining clinical risk factors with radiomics features for BM development in patients with radically treated stage III NSCLC.

Methods:

Retrospective analysis of two prospective multicentre studies. Inclusion criteria: adequately staged [¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (18-FDG-PET-CT), contrast-enhanced chest CT, contrast-enhanced brain magnetic resonance imaging/CT] and radically treated stage III NSCLC, exclusion criteria: second primary within 2 years of NSCLC diagnosis and prior prophylactic cranial irradiation. Primary endpoint was BM development any time during follow-up (FU). CT-based radiomics features (N = 530) were extracted from the primary lung tumour on 18-FDG-PET-CT images, and a list of clinical features (N = 8) was collected. Univariate feature selection based on the area under the curve (AUC) of the receiver operating characteristic was performed to identify relevant features. Generalized linear models were trained using the selected features, and multivariate predictive performance was assessed through the AUC.

Results:

In total, 219 patients were eligible for analysis. Median FU was 59.4 months for the training cohort and 67.3 months for the validation cohort; 21 (15%) and 17 (22%) patients developed BM in the training and validation cohort, respectively. Two relevant clinical features (age and adenocarcinoma histology) and four relevant radiomics features were identified as predictive. The clinical model yielded the highest AUC value of 0.71 (95% CI: 0.58–0.84), better than radiomics or a combination of clinical parameters and radiomics (both an AUC of 0.62, 95% CIs of 0.47–076 and 0.48–0.76, respectively).

Conclusion:

CT-based radiomics features of primary NSCLC in the current setup could not improve on a model based on clinical predictors (age and adenocarcinoma histology) of BM development in radically treated stage III NSCLC patients.

BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients

The aim of the study was to analyze the use of block sequential regularized expectation maximization (BSREM) with different β-values for the detection of brain metastases in digital fluorine-18 labeled 2-deoxy-2-fluoro-D-glucose (18F-FDG) PET/CT in lung cancer patients. We retrospectively analyzed staging/restaging 18F-FDG PET/CT scans of 40 consecutive lung cancer patients with new brain metastases, confirmed by MRI. PET images were reconstructed using BSREM (β-values of 100, 200, 300, 400, 500, 600, 700) and OSEM. Two independent blinded readers (R1 and R2) evaluated each reconstruction using a 4-point scale for general image quality, noise, and lesion detectability. SUVmax of metastases, brain background, target-to-background ratio (TBR), and contrast recovery (CR) ratio were recorded for each reconstruction. Among all reconstruction techniques, differences in qualitative parameters were analyzed using non-parametric Friedman test, while differences in quantitative parameters were compared using analysis of variances for repeated measures. Cohen's kappa (k) was used to measure inter-reader agreement. The overall detectability of brain metastases was highest for BSREM200 (R1: 2.83 ± 1.17; R2: 2.68 ± 1.32) and BSREM300 (R1: 2.78 ± 1.23; R2: 2.68 ± 1.36), followed by BSREM100, which had lower accuracy owing to noise. The highest median TBR was found for BSREM100 (R1: 2.19 ± 1.05; R2: 2.42 ± 1.08), followed by BSREM200 and BSREM300. Image quality ratings were significantly different among reconstructions (p < 0.001). The median quality score was higher for BSREM100-300, and both noise and metastases' SUVmax decreased with increasing β-value. Inter-reader agreement was particularly high for the detectability of photopenic metastases and blurring (all k > 0.65). BSREM200 and BSREM300 yielded the best results for the detection of brain metastases, surpassing both BSREM400 and OSEM, typically used in clinical practice.

Development and validation a radiomics nomogram for diagnosing occult brain metastases in patients with stage IV lung adenocarcinoma

Background

To develop and validate a radiomics model using computed tomography (CT) images acquired from the first diagnosis to estimate the status of occult brain metastases (BM) in patients with stage IV lung adenocarcinoma (LADC).

Methods

One hundred and ninety-three patients who were first diagnosed with stage IV LADC were enrolled and divided into a training cohort (n=135) and a validation cohort (n=58). Then, 725 radiomic features were extracted from contoured primary tumor volumes of LADCs. Intra- and interobserver reliabilities were calculated, and the least absolute shrinkage and selection operator (LASSO) was applied for feature selection. Subsequently, a radiomics signature (Rad-Score) was built. To improve performance, a nomogram incorporating a radiomics signature and an independent clinical predictor was developed. Finally, the established signature and nomogram were assessed using receiver operating characteristic (ROC) curves and precision-recall curves (PRC). Both empirical and α-binomial model-based ROCs and PRCs were plotted, and the area under the curve (AUC) and average precision (AP) of ROCs and PRCs were calculated and compared.

Results

A radiomics signature and Rad-Score were constructed using eight radiomic features, and these had significant correlations with occult BM status. A nomogram was developed by incorporating a Rad-Score and the primary tumor location. The nomogram yielded an optimal AUC of 0.911 [95% confidence interval (CI): 0.903–0.919] and an AP of 0.885 (95% CI: 0.876–0.894) in the training cohort, and an AUC of 0.873 (95% CI: 0.866–0.80) and an AP of 0.827 (95% CI: 0.820–0.834) in the validation cohort using α-binomial model-based method. The calibration curve demonstrated that the nomogram showed high agreement between the actual occult BM probability and predicted by the nomogram (P=0.427).

Conclusions

The nomogram incorporating a radiomics signature and a clinical risk factor achieved optimal performance after holistic assessment using unbiased indexes for diagnosing occult BM of patients who were first diagnosed with stage IV LADC.

The role of the surgeon in the management of oligometastatic non-small cell lung cancer: a literature review

OBJECTIVE

In this review, we aim to summarize the most recent data on the surgical management of oligometastatic non-small cell lung cancer (NSCLC).

BACKGROUND

Approximately 60-70% of all patients with NSCLC initially present with advanced stages of cancer at time of diagnosis. These patients are generally treated with chemotherapy, radiation therapy, or a combination of these modalities. Patients with late-stage disease are usually not considered to be amenable for curative-intent treatments due to poor prognoses. Despite advances in systemic therapies, 5-year overall survival rates in these patients remain poor. However, technological advances in imaging modalities and new imaging strategies have substantially increased tumor detection rates and have resulted in a shift towards earlier diagnosis of NSCLC, possibly in stages in which metastatic disease is limited and still treatable. Studies in recent years have shown that there is a distinct group of patients with metastatic lesions at one or a few sites, often referred to as oligometastatic disease, that may have better survival outcomes compared to patients with more disseminated diseases. Furthermore, it is suggested that these patients may benefit from a combination of systemic treatment and local treatment aimed at the metastatic site(s). However, the role of surgery in this setting remains a controversial subject, with many unanswered questions.

METHODS

The PubMed/MEDLINE database and the Cochrane database were searched to find relevant articles regarding oligometastatic NSCLC. Specifically, articles regarding definitions of oligometastatic disease, oligometastatic tumor biology, diagnosis, and the treatment of oligometastatic disease were identified.

CONCLUSIONS

Oligometastatic NSCLC represents a wide spectrum of diseases and encompasses a heterogeneous patient population. Current data suggests that local ablative treatment of oligometastatic lesions with surgery or stereotactic body radiation therapy may result in improved overall survival and progression-free survival rates. However, more data from multi-center prospective trials are necessary to shed light on which therapeutic modalities are most suitable for the treatment of oligometastatic NSCLC. Integration of clinical and molecular staging data is necessary to allow for more personalized treatment approaches.

The Value of PETRA in Pulmonary Nodules of <3 cm Among Patients With Lung Cancer

Objective

This study aimed to evaluate the visibility of different subgroups of lung nodules of <3 cm using the pointwise encoding time reduction with radial acquisition (PETRA) sequence on 3T magnetic resonance imaging (MRI) in comparison with that obtained using low-dose computed tomography (LDCT).

Methods

The appropriate detection rate was calculated for each of the different subgroups of lung nodules of <3 cm. The mean diameter of each detected nodule was determined. The detection rates and diameters of the lung nodules detected by MRI with the PETRA sequence were compared with those detected by computed tomography (CT). The sensitivity of detection for the different subgroups of pulmonary nodules was determined based on the location, size, type of nodules and morphologic characteristics. Agreement of nodule characteristics between CT and MRI were assessed by intraclass correlation coefficient (ICC) and Kappa test.

Results

The CT scans detected 256 lung nodules, comprising 99 solid nodules (SNs) and 157 subsolid nodules with a mean nodule diameter of 8.3 mm. For the SNs, the MRI detected 30/47 nodules of <6 mm in diameter and 52/52 nodules of ≥6 mm in diameter. For the subsolid nodules, the MRI detected 30/51 nodules of <6 mm in diameter and 102/106 nodules of ≥6 mm in diameter. The PETRA sequence returned a high detection rate (84%). The detection rates of SN, ground glass nodules, and PSN were 82%, 72%, and 94%, respectively. For nodules with a diameter of >6 mm, the sensitivity of the PETRA sequence reached 97%, with a higher rate for nodules located in the upper lung fields than those in the middle and lower lung fields. Strong agreement was found between the CT and PETRA results (correlation coefficients = 0.97).

Conclusion

The PETRA technique had high sensitivity for different type of nodule detection and enabled accurate assessment of their diameter and morphologic characteristics. It may be an effective alternative to CT as a tool for screening and follow up pulmonary nodules.

Concurrent chemoradiotherapy for stage III non-small-cell lung cancer: recent progress and future perspectives (a narrative review)

Concurrent chemoradiotherapy (CHRT) remains the therapeutic standard for locally advanced inoperable non-small-cell lung cancer (NSCLC). The median overall survival (OS) with this approach is in the range of 20–30 months, with five-year survival of approximately 30%. These outcomes have recently been further improved by supplementing CHRT with maintenance durvalumab, a monoclonal anti-PD-L1 agent. The progress in treatment outcomes of locally advanced NSCLC before the era of immunotherapy has been achieved mainly by virtue of developments in diagnostics and radiotherapy techniques. Routine implementation of endoscopic and endobronchial ultrasonography for mediastinal lymph nodes assessment, positron emission tomography/computed tomography and magnetic resonance imaging of the brain allows for more accurate staging of NSCLC and for optimizing treatment strategy. Thorough staging and respiratory motion control allows for higher conformity of radiotherapy and reduction of radiotherapy related toxicity. Dose escalation with prolonged overall treatment time does not improve treatment outcomes of CHRT. In consequence, 60 Gy in 2 Gy fractions or equivalent biological dose remains the standard dose for definitive CHRT in locally advanced NSCLC. However, owing to increased toxicity of CHRT, this option may not be applicable in a proportion of elderly or frail patients. This article summarizes recent developments in curative CHRT for inoperable stage III NSCLC, and presents perspectives for further improvements of this strategy

Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model

BACKGROUND AND PURPOSE

Malignant melanoma is an aggressive skin cancer in which brain metastases are common. Our aim was to establish and evaluate a deep learning model for fully automated detection and segmentation of brain metastases in patients with malignant melanoma using clinical routine MR imaging.

MATERIALS AND METHODS

Sixty-nine patients with melanoma with a total of 135 brain metastases at initial diagnosis and available multiparametric MR imaging datasets (T1-/T2-weighted, T1-weighted gadolinium contrast-enhanced, FLAIR) were included. A previously established deep learning model architecture (3D convolutional neural network; DeepMedic) simultaneously operating on the aforementioned MR images was trained on a cohort of 55 patients with 103 metastases using 5-fold cross-validation. The efficacy of the deep learning model was evaluated using an independent test set consisting of 14 patients with 32 metastases. Manual segmentations of metastases in a voxelwise manner (T1-weighted gadolinium contrast-enhanced imaging) performed by 2 radiologists in consensus served as the ground truth.

RESULTS

After training, the deep learning model detected 28 of 32 brain metastases (mean volume, 1.0 [SD, 2.4] cm³) in the test cohort correctly (sensitivity of 88%), while false-positive findings of 0.71 per scan were observed. Compared with the ground truth, automated segmentations achieved a median Dice similarity coefficient of 0.75.

CONCLUSIONS

Deep learning-based automated detection and segmentation of brain metastases in malignant melanoma yields high detection and segmentation accuracy with false-positive findings of <1 per scan.

Central nervous system metastases and oligoprogression during treatment with tyrosine kinase inhibitors in oncogene-addicted non-small cell lung cancer: how to treat and when?

Up to 70% of non-small cell lung cancer (NSCLC) patients develop central nervous system (CNS) metastases during the course of their disease, especially those with oncogenic drivers treated with a first-generation tyrosine kinase inhibitor (TKI), because of the relatively poor CNS penetration. CNS metastases are associated with a negative impact on quality of life and survival. As, with the introduction of newer generation TKIs, the survival rates are increasing in this particular population, treatment and/or prevention of CNS metastases becomes even more relevant and the TKI with the best CNS efficacy should be selected. Unfortunately, CNS efficacy data in clinical trials are not fully comparable. Furthermore, oligoprogression to the brain without extracranial progression regularly occurs in the oncogenic driver population and both local therapy and switch of systemic therapy are possible treatment options. However, the best order of systemic and local therapy is still not precisely known. In this narrative review, we will summarize incidence and treatment of CNS metastases in oncogene driven NSCLC, including the optimal treatment of CNS oligometastatic disease (synchronous as well as oligoprogressive).