Resection of symptomatic non-small cell lung cancer brain metastasis in the setting of multiple brain metastases

Surgical treatment of multiple breast cancer brain metastases: clinical characteristics and factors impacting postoperative survival

PURPOSE

Breast cancer (BC) is one of the most common primary tumor entities that develop brain metastases (BM) during disease progression. Multiple BM are associated with poorer prognosis, but various surgical, radiotherapeutic and systemic treatment approaches improve survival. We aimed to identify prognostic factors and evaluate the overall survival following BM surgery in patients with multiple BCBM.

METHODS

All metachronous metastasized female patients with resected BCBM at our institution between 2008 and 2019 were included. Data on clinical, radiologic, and histopathologic parameters were recorded and analyzed using univariate and multivariate regression models.

RESULTS

Among the 93 patients included in the final analysis, 30 individuals presented with multiple BM. Compared to patients with single BM, those with multiple BM were more likely to have infratentorial BM (adjusted odds ratio [aOR] 3.35, 95% confidence interval [CI] 1.03-10.83, p = 0.044), HER2(human epidermal growth factor receptor 2)-positive BC (aOR 3.93, 95% CI 1.23-12.53, p = 0.021) and hepatic metastases (aOR 5.86, 95% CI 1.34-25.61, p = 0.019). There was no significant difference in postoperative survival between individuals with multiple (median: 12.5 months) and single BM (17.0 months, p = 0.186). In the multivariate Cox regression analysis, adjuvant radiotherapy (adjusted hazard ratio [aHR] 5.93, 95% CI 1.06-33.26, p = 0.043) and trastuzumab treatment (aHR 4.95, 95% CI 1.72-14.25, p = 0.003) were associated with longer postoperative survival multiple BCBM patients.

CONCLUSION

BC patients with multiple BM show remarkable postoperative survival, particularly if combined with adjuvant radiotherapy. Our data justify the surgery of multiple BCBM in patients with appropriate clinical condition and feasible location of BM.

A magnetic resonance imaging (MRI)-based deep learning radiomics model predicts recurrence-free survival in lung cancer patients after surgical resection of brain metastases

AIM

To develop and validate a magnetic resonance imaging (MRI)-based deep learning radiomics model (DLRM) to predict recurrence-free survival (RFS) in lung cancer patients after surgical resection of brain metastases (BrMs).

MATERIALS AND METHODS

A total of 215 lung cancer patients with BrMs confirmed by surgical pathology were retrospectively included in five centres, 167 patients were assigned to the training cohort, and 48 to the external test cohort. All patients underwent regular follow-up brain MRIs. Clinical and morphological MRI models for predicting RFS were built using univariate and multivariate Cox regressions, respectively. Handcrafted and deep learning (DL) signatures were constructed from BrMs pretreatment MR images using the least absolute shrinkage and selection operator (LASSO) method, respectively. A DLRM was established by integrating the clinical and morphological MRI predictors, handcrafted and DL signatures based on the multivariate Cox regression coefficients. The Harrell C-index, area under the receiver operating characteristic curve (AUC), and Kaplan-Meier's survival analysis were used to evaluate model performance.

RESULTS

The DLRM showed satisfactory performance in predicting RFS and 6- to 18-month intracranial recurrence in lung cancer patients after BrMs resection, achieving a C-index of 0.79 and AUCs of 0.84-0.90 in the training set and a C-index of 0.74 and AUCs of 0.71-0.85 in the external test set. The DLRM outperformed the clinical model, morphological MRI model, handcrafted signature, DL signature, and clinical-morphological MRI model in predicting RFS (P < 0.05). The DLRM successfully classified patients into high-risk and low-risk intracranial recurrence groups (P < 0.001).

CONCLUSION

This MRI-based DLRM could predict RFS in lung cancer patients after surgical resection of BrMs.

Defining the role of surgery for patients with multiple brain metastases

PURPOSE

To better define the role of surgery, we investigated survival and functional outcomes in patients with multiple brain metastases.

METHODS

Pertinent clinical and radiological data of 131 consecutive patients (156 surgeries) were analyzed retrospectively.

RESULTS

Surgical indications included mass effect (84.6%) and need for tissue acquisition (44.9%, for molecularly informed treatment: 10 patients). Major (i.e. CTCAE grade 3-5) neurological, surgical and medical complication were observed in 6 (3.8%), 12 (7.7%), and 12 (7.7%) surgical cases. Median preoperative and discharge KPS were 80% (IQF: 60-90%). Median overall survival (mOS) was 7.4 months. However, estimated 1 and 2 year overall survival rates were 35.6% and 25.1%, respectively. Survival was dismal (i.e. mOS ≤ 2.5 months) in patients who had no postoperative radio- and systemic therapy, or who incurred major complications. Multivariate analysis with all parameters significantly correlated with survival as univariate parameters revealed female sex, oligometastases, no major new/worsened neurological deficits, and postoperative radio- and systemic therapy as independent positive prognostic parameters. Univariate positive prognostic parameters also included histology (best survival in breast cancer patients) and less than median (0.28 cm3) residual tumor load.

CONCLUSIONS

Surgery is a reasonable therapeutic option in many patients with multiple brain metastases. Operations should primarily aim at reducing mass effect thereby preserving the patients' functional health status which will allow for further local (radiation) and systemic therapy. Surgery for the acquisition of metastatic tissue (more recently for molecularly informed treatment) is another important surgical indication. Cytoreductive surgery may also carry a survival benefit by itself.

Animal models of brain and spinal cord metastases of NSCLC established using a brain stereotactic instrument

Objective

Animal models of brain and spinal cord metastases of non-small cell lung cancer were established through the intracranial injection of PC-9 Luc cells with a brain stereotaxic device. This method provides a reliable modeling method for studying brain and spinal cord metastases of non-small cell lung cancer.

Methods

PC-9 Luc cells at logarithmic growth stage were injected into the skulls of 5-week-old BALB/c nude mice at different cell volumes (30 × 104, 80 × 104) and different locations (using anterior fontanel as a location point, 1 mm from the coronal suture, and 1.5 mm from the sagittal suture on the right upper and right lower side of the skull). After 1 week of cell inoculation, fluorescence signals of tumor cells in the brain and spinal were detected using the IVIS Xenogen Imaging system. After 4 weeks, brain and spinal tissues from the nude mice were harvested. Following paraffin-embedded sectioning, HE staining was performed on the tissues.

Results

The fluorescence signals revealed that both brain and spinal cord metastasis occurred in the mice where the cells were injected at the lower right side of the skull. There was only brain metastasis in the nude mice injected with 30 × 104 cells at the upper right side of the skull. Both brain and spinal cord metastasis occurred in the nude mice injected with 80 × 104 cells. The HE staining revealed that both brain and spinal cord metastasis occurred in the mice injected with different amounts of PC-9 Luc cells, consistent with the results detected using the IVIS Xenogen Imaging system, thereby demonstrating the reliability of detecting fluorescent signals in vivo to determine tumor growth.

Conclusion

It is a reliable method to establish the animal model of brain and spinal cord metastases of non-small cell lung cancer by injecting different quantities of cells from different positions with a brain stereotaxic device. The IVIS Xenogen Imaging system has high reliability in detecting the fluorescence signals of brain and spinal cord metastatic tumors.

Establishment of a prognostic risk prediction modelfor non-small cell lung cancer patients with brainmetastases: a retrospective study

Background

Patients with non-small cell lung cancer (NSCLC) who develop brain metastases (BM) have a poor prognosis. This study aimed to construct a clinical prediction model to determine the overall survival (OS) of NSCLC patients with BM.

Methods

A total of 300 NSCLC patients with BM at the Yunnan Cancer Centre were retrospectively analysed. The prediction model was constructed using the least absolute shrinkage and selection operator-Cox regression. The bootstrap sampling method was employed for internal validation. The performance of our prediction model was compared using recursive partitioning analysis (RPA), graded prognostic assessment (GPA), the update of the graded prognostic assessment for lung cancer using molecular markers (Lung-molGPA), the basic score for BM (BSBM), and tumour-lymph node-metastasis (TNM) staging.

Results

The prediction models comprising 15 predictors were constructed. The area under the curve (AUC) values for the 1-year, 3-year, and 5-year time-dependent receiver operating characteristic (curves) were 0.746 (0.678-0.814), 0.819 (0.761-0.877), and 0.865 (0.774-0.957), respectively. The bootstrap-corrected AUC values and Brier scores for the prediction model were 0.811 (0.638-0.950) and 0.123 (0.066-0.188), respectively. The time-dependent C-index indicated that our model exhibited significantly greater discrimination compared with RPA, GPA, Lung-molGPA, BSBM, and TNM staging. Similarly, the decision curve analysis demonstrated that our model displayed the widest range of thresholds and yielded the highest net benefit. Furthermore, the net reclassification improvement and integrated discrimination improvement analyses confirmed the enhanced predictive power of our prediction model. Finally, the risk subgroups identified by our prognostic model exhibited superior differentiation of patients' OS.

Conclusion

The clinical prediction model constructed by us shows promise in predicting OS for NSCLC patients with BM. Its predictability is superior compared with RPA, GPA, Lung-molGPA, BSBM, and TNM staging.

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.

Mind the gap-the use of sodium fluoresceine for resection of brain metastases to improve the resection rate

INTRODUCTION AND PURPOSE

Brain metastases appear to be well resectable due to dissectable tumor margins, but postoperative MRI quite often depicts residual tumor with potential influence on tumor control and overall survival. Therefore, we introduced sodium fluoresceine into the routine workflow for brain metastasis resection. The aim of this study was to evaluate whether the use of fluorescence-guided surgery has an impact on postoperative tumor volume and local recurrence.

MATERIAL AND METHODS

We retrospectively included patients who underwent surgical resection for intracranial metastases of systemic cancer between 11/2017 and 05/2021 at our institution. Tumor volumes were assessed pre- and postoperatively on T1-CE MRI. Clinical and epidemiological data as well as follow-up were gathered from our prospective database.

RESULTS

Seventy-nine patients (33 male, 46 female) were included in this study. Median preoperative tumor volume amounted to 11.7cm3 and fluoresceine was used in 53 patients (67%). Surgeons reported an estimated gross total resection (GTR) in 95% of the cases, while early postoperative MRI could confirm GTR in 72%. Patients resected using fluoresceine demonstrated significantly lower postoperative residual tumor volumes with a difference of 0.7cm3 (p = 0.044) and lower risk of local tumor recurrence (p = 0.033). The use of fluorescence did not influence the overall survival (OS). Postoperative radiotherapy resulted in a significantly longer OS (p = 0.001).

DISCUSSION

While GTR rates may be overrated, the use of intraoperative fluorescence may help neurosurgeons to achieve a more radical resection. Fluoresceine seems to facilitate surgical resection and increase the extent of resection thus reducing the risk for local recurrence.

The Clinical Frailty Scale as useful tool in patients with brain metastases

PURPOSE

The Clinical Frailty Scale (CFS) evaluates patients' level of frailty on a scale from 1 to 9 and is commonly used in geriatric medicine, intensive care and orthopedics. The aim of our study was to reveal whether the CFS allows a reliable prediction of overall survival (OS) in patients after surgical treatment of brain metastases (BM) compared to the Karnofsky Performance Score (KPS).

METHODS

Patients operated for BM were included. CFS and KPS were retrospectively assessed pre- and postoperatively and at follow-up 3-6 months after resection.

RESULTS

205 patients with a follow-up of 22.8 months (95% CI 18.4-27.1) were evaluated. CFS showed a median of 3 ("managing well"; IqR 2-4) at all 3 assessment-points. Median KPS was 80 preoperatively (IqR 80-90) and 90 postoperatively (IqR 80-100) as well as at follow-up after 3-6 months. CFS correlated with KPS both preoperatively (r = - 0.92; p < 0.001), postoperatively (r = - 0.85; p < 0.001) and at follow-up (r = - 0.93; p < 0.001). The CFS predicted the expected reduction of OS more reliably than the KPS at all 3 assessments. A one-point increase (worsening) of the preoperative CFS translated into a 30% additional hazard to decease (HR 1.30, 95% CI 1.15-1.46; p < 0.001). A one-point increase in postoperative and at follow-up CFS represents a 39% (HR 1.39, 95% CI 1.25-1.54; p < 0.001) and of 42% risk (HR 1.42, 95% CI 1.27-1.59; p < 0.001).

CONCLUSION

The CFS is a feasible, simple and reliable scoring system in patients undergoing resection of brain metastasis. The CFS 3-6 months after surgery specifies the expected OS more accurately than the KPS.