Neuropathology of brain metastases

Habitat-based MRI radiomics to predict the origin of brain metastasis

BACKGROUND

This study aims to explore the value of habitat-based magnetic resonance imaging (MRI) radiomics for predicting the origin of brain metastasis (BM).

PURPOSE

To investigate whether habitat-based radiomics can identify the metastatic tumor type of BM and whether an imaging-based model that integrates the volume of peritumoral edema (VPE) can enhance predictive performance.

METHODS

A primary cohort was developed with 384 patients from two centers, which comprises 734 BM lesions. An independent cohort was developed with 28 patients from a third center, which comprises 70 BM lesions. All patients underwent T1-weighted contrast-enhanced (T1CE) and T2-weighted (T2W) MRI scans before treatment. Radiomics features were extracted from tumor active area (TAA) and peritumoral edema area (PEA) selected using the least absolute shrinkage and selection operator (LASSO) to construct radiomics signatures (Rads). The Rads were further integrated with VPE to build combined models for predicting the metastatic type of BM. Performance of the models were assessed through receiver operating characteristic (ROC) curve analysis.

RESULTS

Rads derived from TAA and PEA both showed predictive power for identifying the origin of BM. The developed combined models generated the best performance in the training (AUCs, lung cancer [LC]/non-lung cancer [NLC] vs. small cell lung cancer [SCLC]/non-small cell lung cancer [NSCLC] vs. breast cancer [BC]/gastrointestinal cancer [GIC], 0.870 vs. 0.946 vs. 0.886), internal validation (area under the receiver operating characteristic curves [AUCs], LC/NLC vs. SCLC/NSCLC vs. BC/GIC, 0.786 vs. 0.863 vs. 0.836) and external validation (AUCs, LC /NLC vs. SCLC/NSCLC vs. BC/GIC, 0.805 vs. 0.877 vs. 0.774) cohort.

CONCLUSIONS

The developed habitat-based radiomics models can effectively identify the metastatic tumor type of BM and may be considered as a potential preoperative basis for timely treatment planning.

A Rare Case of Large-Cell Neuroendocrine Carcinoma Metastasizing to the Brain: A Case Report

Neuroendocrine tumors (NETs) encompass a diverse spectrum of neoplasms that can originate from various sites, including the gastrointestinal tract. Brain metastases from neuroendocrine tumors, while rare, present significant clinical challenges. In this case report, we present the unique instance of a 50-year-old female with a history of gastrointestinal neuroendocrine tumor who manifested left-sided weakness, tremors, and recurrent focal convulsions. Initial imaging scans revealed a lesion in the right parietal lobe, which was surgically excised and diagnosed as a metastatic large-cell neuroendocrine carcinoma. Post-surgery, the patient's condition stabilized, but she was subsequently advised to chemotherapy. This case underscores the infrequency of brain metastases in the context of gastrointestinal neuroendocrine tumors, underscoring the need for comprehensive screening in such scenarios. Given the aggressive nature of neuroendocrine carcinomas and their propensity to disseminate to the brain, early detection and intervention are crucial. Our rare case also underscores the importance of distinguishing high-grade neuroendocrine carcinomas, which necessitate intensive management, from less aggressive NETs and other metastatic neoplasms that have different treatment approaches.

Survival and complications following supra- and infratentorial brain metastasis resection

OBJECTIVE

15-30% of primary cancers metastasise to the brain. Of these, 10-25% involve the posterior fossa. It remains unclear whether patients undergoing resection for infratentorial brain metastases experience poorer prognosis than those with supratentorial lesions. We compare the post-operative outcomes of these two groups.

METHODS

We searched the electronic health records of all patients undergoing brain metastases resection at our regional neurosurgical centre between February 2014 and August 2019. Clinical data was collected on 85 consecutive patients (61 supratentorial, 24 infratentorial metastases). Outcome measures included overall survival, post-operative complications, and performance status. Patients were followed up until 21/04/2020.

RESULTS

Median post-operative survival of patients with supratentorial metastases was 323 days (95% CI 235-411), compared to 277 days (95% CI 195-359) for those with infratentorial metastases. These two groups experienced comparable survival (log rank = 0.276, p = 0.60) on univariate analysis. Infratentorial metastasis location was not associated with a change in survival using a Cox proportional hazards model incorporating age, sex and extracranial disease activity (HR = 1.39, 95% CI 0.777-2.486) (p = 0.27). However, neurological and non-neurological post-operative complications were more frequent in patients with infratentorial metastases (neurological = 21% vs 13%, non-neurological = 25% vs 2%, p = 0.002).

CONCLUSION

Patients with supra- and infratentorial metastases experienced comparable post-operative survival but posterior fossa metastasis location was associated with a 2.5 times higher risk of neurological and/or non-neurological post-operative complications. A better understanding of the precise indications for safe and effective surgical intervention for posterior fossa metastases is required.

Metastatic Lesions of the Brain and Spine

Brain and spinal metastases are common in cancer patients and are associated with significant morbidity and mortality. Continued advancement in the systemic care of cancer has increased the life expectancy of patients, and consequently, the incidence of brain and spine metastasis has increased. There has been an increase in the understanding of oncogenic mutations, and research has also demonstrated spatial and temporal mutations in patients that may drive overall treatment resistance and failure. Combinatory treatments with radiation, surgery, and newer systemic therapies have continued to increase the life expectancy of patients with brain and spine metastases. Given the overall complexity of brain and spine metastases, this chapter aims to give a comprehensive overview and cover important topics concerning brain and spine metastases. This will include the molecular, genetic, radiographic, surgical, and non-surgical treatments of brain and spinal metastases.

Differentiation of Perilesional Edema in Glioblastomas and Brain Metastases: Comparison of Diffusion Tensor Imaging, Neurite Orientation Dispersion and Density Imaging and Diffusion Microstructure Imaging

Although the free water content within the perilesional T2 hyperintense region should differ between glioblastomas (GBM) and brain metastases based on histological differences, the application of classical MR diffusion models has led to inconsistent results regarding the differentiation between these two entities. Whereas diffusion tensor imaging (DTI) considers the voxel as a single compartment, multicompartment approaches such as neurite orientation dispersion and density imaging (NODDI) or the recently introduced diffusion microstructure imaging (DMI) allow for the calculation of the relative proportions of intra- and extra-axonal and also free water compartments in brain tissue. We investigate the potential of water-sensitive DTI, NODDI and DMI metrics to detect differences in free water content of the perilesional T2 hyperintense area between histopathologically confirmed GBM and brain metastases. Respective diffusion metrics most susceptible to alterations in the free water content (MD, V-ISO, V-CSF) were extracted from T2 hyperintense perilesional areas, normalized and compared in 24 patients with GBM and 25 with brain metastases. DTI MD was significantly increased in metastases (p = 0.006) compared to GBM, which was corroborated by an increased DMI V-CSF (p = 0.001), while the NODDI-derived ISO-VF showed only trend level increase in metastases not reaching significance (p = 0.060). In conclusion, diffusion MRI metrics are able to detect subtle differences in the free water content of perilesional T2 hyperintense areas in GBM and metastases, whereas DMI seems to be superior to DTI and NODDI.

Connexins orchestrate progression of breast cancer metastasis to the brain by promoting FAK activation

Brain metastasis is a complication of increasing incidence in patients with breast cancer at advanced disease stage. It is a severe condition characterized by a rapid decline in quality of life and poor prognosis. There is a critical clinical need to develop effective therapies to prevent and treat brain metastases. Here, we describe a unique and robust spontaneous preclinical model of breast cancer metastasis to the brain (4T1-BM₂) in mice that has been instrumental in uncovering molecular mechanisms guiding metastatic dissemination and colonization of the brain. Key experimental findings were validated in the additional murine D2A1-BM₂ model and in human MDA231-BrM₂ model. Gene expression analyses and functional studies, coupled with clinical transcriptomic and histopathological investigations, identified connexins (Cxs) and focal adhesion kinase (FAK) as master molecules orchestrating breast cancer colonization of the brain. Cx31 promoted homotypic tumor cell adhesion, heterotypic tumor-astrocyte interaction, and FAK phosphorylation. FAK signaling prompted NF-κB activation inducing Lamc2 expression and laminin 332 (laminin 5) deposition, α6 integrin-mediated adhesion, and sustained survival and growth within brain parenchyma. In the MDA231-BrM₂ model, the human homologous molecules CX43, LAMA4, and α3 integrin were involved. Systemic treatment with FAK inhibitors reduced brain metastasis progression. In conclusion, we report a spontaneous model of breast cancer metastasis to the brain and identified Cx-mediated FAK-NF-κB signaling as a mechanism promoting cell-autonomous and microenvironmentally controlled cell survival for brain colonization. Considering the limited therapeutic options for brain metastatic disease in cancer patients, we propose FAK as a therapeutic candidate to further pursue in the clinic.

Incidence and risk factors for the development of cerebral metastasis in cervical cancer patients

OBJECTIVE

Cerebral metastasis (CM) in cervical cancer (CC) cases, although rare, results in high lethality rates. The present study aimed to assess CM incidence in a Brazilian reference CC center and evaluate the risk factors for CM development. Retrospective observational study of patients diagnosed with CC between 2010 and 2017.

METHODS

Cumulative CM incidence and incidence density were evaluated. Characteristics associated to CM development risks were identified using crude (cOR) or adjusted (aOR) odds ratios.

RESULTS

A total of 3,397 patients were included in this study. Patient age ranged from 18 to 101 years, with a mean age of 48.8±14.0. After a mean follow-up time of 3.2±2.1 years, 51 CM cases were identified, resulting in a cumulative incidence of 1.5% (95% confidence intervals [CI]=1.12-1.97) and an incidence density at the end of the 6th year of 27.4 per 1,000 women/year. Advanced clinical stage (aOR=3.15; 95% CI=1.16-8.58; p=0.025), the presence of previous lung metastasis (aOR=4.04; 95% CI=1.82-8.94; p=0.001) and the adenocarcinoma (aOR=2.90; 95% CI=1.46-5.76; p=0.002), adenosquamous carcinoma (aOR=7.33; 95% CI=2.87-18.73; p<0.001), undifferentiated carcinoma (aOR=14.37; 95% CI=3.77-54.76; p<0.001) and neuroendocrine carcinoma (aOR=21.31; 95% CI=6.65-68.37, p<0.001) histological types were associated with a higher risk for CM development. CM risk was higher in the first years of follow-up, with no cases observed after the 6th year.

CONCLUSION

CC patients in advanced clinical stages, displaying previous lung metastasis and non-squamous histological types are at high risk of developing CM.

Diffusion Microstructure Imaging to Analyze Perilesional T2 Signal Changes in Brain Metastases and Glioblastomas

Purpose: Glioblastomas (GBM) and brain metastases are often difficult to differentiate in conventional MRI. Diffusion microstructure imaging (DMI) is a novel MR technique that allows the approximation of the distribution of the intra-axonal compartment, the extra-axonal cellular, and the compartment of interstitial/free water within the white matter. We hypothesize that alterations in the T2 hyperintense areas surrounding contrast-enhancing tumor components may be used to differentiate GBM from metastases. Methods: DMI was performed in 19 patients with glioblastomas and 17 with metastatic lesions. DMI metrics were obtained from the T2 hyperintense areas surrounding contrast-enhancing tumor components. Resected brain tissue was assessed in six patients in each group for features of an edema pattern and tumor infiltration in the perilesional interstitium. Results: Within the perimetastatic T2 hyperintensities, we observed a significant increase in free water (p < 0.001) and a decrease in both the intra-axonal (p = 0.006) and extra-axonal compartments (p = 0.024) compared to GBM. Perilesional free water fraction was discriminative regarding the presence of GBM vs. metastasis with a ROC AUC of 0.824. Histologically, features of perilesional edema were present in all assessed metastases and absent or marginal in GBM. Conclusion: Perilesional T2 hyperintensities in brain metastases and GBM differ significantly in DMI-values. The increased free water fraction in brain metastases suits the histopathologically based hypothesis of perimetastatic vasogenic edema, whereas in glioblastomas there is additional tumor infiltration.

Histopathological Analysis of Central Nervous System Metastases: Six Years of Data From a Tertiary Center

Introduction: The most common cause of neurological symptoms in patients with systemic malignant tumors is central nervous system (CNS) metastases, and CNS metastases are one of the important causes of morbidity and mortality in these patients. The most common metastatic tumors to the CNS are lung, breast, malignant melanoma, genitourinary, and gastrointestinal tumors. We aimed to analyze our data on patients with CNS metastases in our department, which belongs to a large archive in the field of neuropathology.

Methods: The data of patients who had CNS metastases between January 2015 and August 2021 in our department were reviewed retrospectively. The patients were grouped in terms of demographic data, location, histopathological diagnosis, and primary origin characteristics, and their frequency and immunohistochemical staining characteristics were investigated.

Results: There were 256 patients with CNS metastases in our study. The mean age was found to be 56.12. Of the patients, 30.5% were female and 69.5% were male. Astrocytic and oligodendral tumors (25.3%), followed by meningiomas (24.1%), and then CNS metastases (21.3%) were the most common CNS tumors. Among the CNS metastases, the most common primary sites were the lung (58%), breast (16%), tumors of unknown primary origin (TUP) (5%), colon (4%), and gynecologic tract (3.1%). Localization was found as cerebral (69.5%), cerebellar (28.1%), and spinal (2.3%).

Conclusion: In CNS system metastases, an accurate histological diagnosis should be made by histomorphological evaluation supported by compatible immunohistochemical results in the presence of clinical history and radiological findings. Despite performing a larger immunohistochemical panel, it should be kept in mind that a primary site of origin cannot be found in a significant number of cases.

Emerging Biomarkers for Diagnosis, Prevention and Treatment of Brain Metastases-From Biology to Clinical Utility

Primary malignancies of the lung, skin (melanoma), and breast have higher propensity for metastatic spread to the brain. Advances in molecular tumour profiling have aided the development of targeted therapies, stereotactic radiotherapy, and immunotherapy, which have led to some improvement in patient outcomes; however, the overall prognosis remains poor. Continued research to identify new prognostic and predictive biomarkers is necessary to further impact patient outcomes, as this will enable better risk stratification at the point of primary cancer diagnosis, earlier detection of metastatic deposits (for example, through surveillance), and more effective systemic treatments. Brain metastases exhibit considerable inter- and intratumoural heterogeneity-apart from distinct histology, treatment history and other clinical factors, the metastatic brain tumour microenvironment is incredibly variable both in terms of subclonal diversity and cellular composition. This review discusses emerging biomarkers; specifically, the biological context and potential clinical utility of tumour tissue biomarkers, circulating tumour cells, extracellular vesicles, and circulating tumour DNA.

Voxel-level analysis of normalized DSC-PWI time-intensity curves: a potential generalizable approach and its proof of concept in discriminating glioblastoma and metastasis

OBJECTIVE

Standard DSC-PWI analyses are based on concrete parameters and values, but an approach that contemplates all points in the time-intensity curves and all voxels in the region-of-interest may provide improved information, and more generalizable models. Therefore, a method of DSC-PWI analysis by means of normalized time-intensity curves point-by-point and voxel-by-voxel is constructed, and its feasibility and performance are tested in presurgical discrimination of glioblastoma and metastasis.

METHODS

In this retrospective study, patients with histologically confirmed glioblastoma or solitary-brain-metastases and presurgical-MR with DSC-PWI (August 2007-March 2020) were retrieved. The enhancing tumor and immediate peritumoral region were segmented on CE-T1wi and coregistered to DSC-PWI. Time-intensity curves of the segmentations were normalized to normal-appearing white matter. For each participant, average and all-voxel-matrix of normalized-curves were obtained. The 10 best discriminatory time-points between each type of tumor were selected. Then, an intensity-histogram analysis on each of these 10 time-points allowed the selection of the best discriminatory voxel-percentile for each. Separate classifier models were trained for enhancing tumor and peritumoral region using binary logistic regressions.

RESULTS

A total of 428 patients (321 glioblastomas, 107 metastases) fulfilled the inclusion criteria (256 men; mean age, 60 years; range, 20-86 years). Satisfactory results were obtained to segregate glioblastoma and metastases in training and test sets with AUCs 0.71-0.83, independent accuracies 65-79%, and combined accuracies up to 81-88%.

CONCLUSION

This proof-of-concept study presents a different perspective on brain MR DSC-PWI evaluation by the inclusion of all time-points of the curves and all voxels of segmentations to generate robust diagnostic models of special interest in heterogeneous diseases and populations. The method allows satisfactory presurgical segregation of glioblastoma and metastases.

KEY POINTS

• An original approach to brain MR DSC-PWI analysis, based on a point-by-point and voxel-by-voxel assessment of normalized time-intensity curves, is presented. • The method intends to extract optimized information from MR DSC-PWI sequences by impeding the potential loss of information that may represent the standard evaluation of single concrete perfusion parameters (cerebral blood volume, percentage of signal recovery, or peak height) and values (mean, maximum, or minimum). • The presented approach may be of special interest in technically heterogeneous samples, and intrinsically heterogeneous diseases. Its application enables satisfactory presurgical differentiation of GB and metastases, a usual but difficult diagnostic challenge for neuroradiologist with vital implications in patient management.

Diffusion tensor imaging derived metrics in high grade glioma and brain metastasis differentiation

Background: Pretreatment differentiation between glioblastoma and metastasis is a frequently encountered dilemma in neurosurgical practice. Distinction is required for precise planning of resection or radiotherapy, and also for defining further diagnostic procedures. Morphology and spectroscopy imaging features are not specific and frequently overlap. This limitation of magnetic resonance imaging and magnetic resonance spectroscopy was the reason to initiate this study. The aim of the present study was to determine whether the dataset of diffusion tensor imaging metrics contains information which may be used for the distinction between primary and secondary intra-axial neoplasms. Methods: Two diffusion tensor imaging parameters were measured in 81 patients with an expansive, ring-enhancing, intra-axial lesion on standard magnetic resonance imaging (1.5 T system). All tumors were histologically verified glioblastoma or secondary deposit. For qualitative analysis, two regions of interest were defined: intratumoral and immediate peritumoral region (locations 1 and 2, respectively). Fractional anisotropy and mean difusivity values of both groups were compared. Additional test was performed to determine if there was a significant difference in mean values between two locations. Results: A statistically significant difference was found in fractional anisotropy values among two locations, with decreasing values in the direction of neoplastic infiltration, although such difference was not observed in fractional anisotropy values in the group with secondary tumors. Mean difusivity values did not appear helpful in differentiation between these two entities. In both groups there was no significant difference in mean difusivity values, neither in intratumoral nor in peritumoral location. Conclusion: The results of our study justify associating the diffusion tensor imaging technique to conventional morphologic magnetic resonance imaging as an additional diagnostic tool for the distinction between primary and secondary intra-axial lesions. Quantitative analysis of diffusion tensor imaging metric, in particular measurement of fractional anisotropy in peritumoral edema facilitates accurate diagnosis.

The pattern of peritoneal colorectal metastasis predicts survival after cytoreductive surgery and hyperthermic intra-peritoneal chemotherapy

BACKGROUND

Peritoneal cancer index (PCI) has been used reliably to prognosticate patients with peritoneal metastasis, however, it fails to describe the patterns of peritoneal spread and to correlate these patterns to survival outcomes. We aim to define the scattered peritoneal spread (SPS) as a pattern associated with worse survival in colorectal peritoneal metastasis.

METHODS

A retrospective analysis of metastatic colorectal cancer patients from a prospectively maintained database of peritoneal surface malignances (n = 280) between 2015 and 2020. SPS was defined by the presence of at least two distant and non-contiguous PCI regions. We compared patients with SPS (n = 73) and clustered peritoneal spread (CPS) (n = 88) for demographics, perioperative and survival outcomes.

RESULTS

No difference in demographics or post-operative course was noted between the groups. The median follow-up was 15.4 months (0.4-70.8 months). Worse disease-free survival (DFS) in the SPS group with an estimated median of 8.2 months compared to 22.5 months in the CPS spread group, (p = 0.001). The estimated median overall survival (OS) for SPS group was 35.7 months whereas in the CPS group the median was not reached (p = 0.025). The same effect of SPS was preserved even after stratification of PCI.

CONCLUSIONS

We defined and described the association of the peritoneal spread pattern to survival outcomes. SPS patients exhibit worse DFS and OS independent of the PCI level. Integration of malignant spread pattern into prognostication models along with PCI may aid in predicting oncological outcomes.

Clinical, histopathological and immunohistochemical features of brain metastases originating in colorectal cancer: a series of 27 consecutive cases

Introduction: Brain metastases (BMs) originating in colorectal cancer (CRC) have a significant importance for patients’ survival. Because in literature there are only isolated case reports and only few series published on this issue, we aimed to assess the incidence of BMs from CRC, to identify patient’s characteristics and BMs clinical, histopathological (HP) and immunohistochemical (IHC) features, and to compare the data we obtained with those from literature. Patients, Materials and Methods: We present a retrospective study of 27 histologically confirmed cases of BMs from CRC among all 1040 patients who received metastasectomy in the Department of Neurosurgery, Prof. Dr. Nicolae Oblu Emergency Clinical Hospital, Iaşi, Romania, in an eight-year period (January 2011 to December 2018). Patients’ characteristics (gender, age), primary tumor location, time from primary tumor surgery to BMs surgery and BMs features (number, location and HP characteristics) were investigated. Histochemical [Alcian Blue (AB) and Periodic Acid–Schiff (PAS)] staining and IHC stainings for cytokeratin (CK) 7, CK20, caudal-type homeobox 2 (CDX2) and human epidermal growth factor receptor 2 (HER2)/neu were performed on all available BMs specimens. Results: There were 27 consecutive patients with BMs from CRC, corresponding to 2.59% of all patients with BMs during the eight-year period we have studied, most of them being diagnosed and treated in 2016. Male:female ratio was 1.45. The mean age for all patients at diagnosis of the BMs was 62.25 years (range: 40–79 years). The origin of the primary cancer was mainly the colon (62.96% of all cases). Of all 27 patients, only two (7.4%) presented neurological symptoms without a diagnosis of CRC. BMs were identified in a period ranging from six months to 70 months after the initial diagnosis. The average time between diagnosis of the primary tumor and of the BMs was 25.92 months. At the moment of the diagnosis of BMs, 17 (62.96%) patients also had other systemic metastases. Most of the cases (55.55%) were situated in the supratentorial compartment. IHC stainings were negative for CK7 and positive for CK20 and CDX2 in all BMs from colonic adenocarcinomas (ADCs), a profile consistent with a non-neuronal and gastric origin. AB and PAS stainings revealed pools of extracellular mucin, especially in cases of mucinous ADC. Ki67 labeling index ranged between 90% and 100%. IHC staining with anti-HER2/neu antibody showed in 25 (96.15%) cases a strong and diffuse aberrant nuclear staining. Conclusions: BMs originating in CRC represent a rare pathology and have particular clinical and IHC features that could vary from one series to another series. In a few cases, BMs may be diagnosed in the absence of a known CRC diagnosis and in these situations, the correct diagnosis is of interest. However, a panel of antibodies can help in establishing a correct diagnosis. Our study was among the first to analyze the HER2/neu expression pattern in BMs from CRC and we found a strong aberrant nuclear expression of this molecular marker on IHC investigation. Related to the data published so far in the literature, it is possible that HER2/neu aberrant expression in the tumor nuclei of the BMs from our series may express the metastatic tumor cell phenotype that was previously subjected to cytostatics and radiation therapies. As such, we suggest that HER2/neu aberrant expression in BMs originating in CRC could represent a proof for the worst prognosis of these patients.

The Potential Role of Peritumoral Apparent Diffusion Coefficient Evaluation in Differentiating Glioblastoma and Solitary Metastatic Lesions of the Brain

OBJECTIVE

Differentiating glioblastoma (GBM) and solitary metastasis is not always possible using conventional magnetic resonance imaging (MRI) techniques. In conventional brain MRI, GBM and brain metastases are lesions with mostly similar imaging findings. In this study, we investigated whether apparent diffusion coefficient (ADC) ratios, ADC gradients, and minimum ADC values in the peritumoral edema tissue can be used to discriminate between these two tumors.

METHODS

This retrospective study was approved by the local institutional review board with a waiver of written informed consent. Prior to surgical and medical treatment, conventional brain MRI and diffusion-weighted MRI (b = 0 and b = 1000) images were taken from 43 patients (12 GBM and 31 solitary metastasis cases). Quantitative ADC measurements were performed on the peritumoral tissue from the nearest segment to the tumor (ADC1), the middle segment (ADC2), and the most distant segment (ADC3). The ratios of these three values were determined proportionally to calculate the peritumoral ADC ratios. In addition, these three values were subtracted from each other to obtain the peritumoral ADC gradients. Lastly, the minimum peritumoral and tumoral ADC values, and the quantitative ADC values from the normal appearing ipsilateral white matter, contralateral white matter and ADC values from cerebrospinal fluid (CSF) were recorded.

RESULTS

For the differentiation of GBM and solitary metastasis, ADC3 / ADC1 was the most powerful parameter with a sensitivity of 91.7% and specificity of 87.1% at the cut-off value of 1.105 (p < 0.001), followed by ADC3 / ADC2 with a cut-off value of 1.025 (p = 0.001), sensitivity of 91.7%, and specificity of 74.2%. The cut-off, sensitivity and specificity of ADC2 / ADC1 were 1.055 (p = 0.002), 83.3%, and 67.7%, respectively. For ADC3 - ADC1, the cut-off value, sensitivity and specificity were calculated as 150 (p < 0.001), 91.7% and 83.9%, respectively. ADC3 - ADC2 had a cut-off value of 55 (p = 0.001), sensitivity of 91.7%, and specificity of 77.4 whereas ADC2 - ADC1 had a cut-off value of 75 (p = 0.003), sensitivity of 91.7%, and specificity of 61.3%. Among the remaining parameters, only the ADC3 value successfully differentiated between GBM and metastasis (GBM 1802.50 ± 189.74 vs. metastasis 1634.52 ± 212.65, p = 0.022).

CONCLUSION

The integration of the evaluation of peritumoral ADC ratio and ADC gradient into conventional MR imaging may provide valuable information for differentiating GBM from solitary metastatic lesions.

Urothelial cell carcinoma presenting with rapid visual deterioration, a case of rare brain metastases with unique clinical presentation

BACKGROUND

Urothelial cell carcinoma (UCC), the most common cancer of the urinary system, rarely metastasizes to the brain. 1-3 More rare still is the subset of patients with urothelial carcinoma brain metastases whose UCC primary is first diagnosed at the same time as their CNS metastatic disease, with oncologic workup prompted by CNS clinical manifestations.4 Paraneoplastic optic neuropathy (PON) is likewise a rare clinical entity, which has not yet been described in association with UCC brain metastases.

CASE DESCRIPTION

Herein, we present the sentinel case of UCC believed to be of endometrial origin in an 81 year old woman initially presenting with symptoms of fatigue, nausea, vertigo, and rapidly deteriorating vision over the course of 1 month. Visual deterioration prompted neuro imaging remarkable for multiple supratentorial and infratentorial metastases as well as likely neoplastic inflammatory involvement of the bilateral optic nerves. The patient underwent a right temporal open brain biopsy, with pathology findings consistent with UCC. Subsequent PET scanning demonstrated a heavy burden of disease including an FDG-avid uterine mass with local and distal extension of disease including bilateral hydroureteronephrosis with obstruction of the distal ureters. The patient and her family elected to pursue home hospice without further workup or intervention.

CONCLUSIONS

While this is the first such case presented, it is possible that UCC of the uterine wall represents a particularly aggressive form of the disease more prone to presenting with CNS metastases and PON.

Comparison of Intraoperative Ultrasound B-Mode and Strain Elastography for the Differentiation of Glioblastomas From Solitary Brain Metastases. An Automated Deep Learning Approach for Image Analysis

Background

The differential diagnosis of glioblastomas (GBM) from solitary brain metastases (SBM) is essential because the surgical strategy varies according to the histopathological diagnosis. Intraoperative ultrasound elastography (IOUS-E) is a relatively novel technique implemented in the surgical management of brain tumors that provides additional information about the elasticity of tissues. This study compares the discriminative capacity of intraoperative ultrasound B-mode and strain elastography to differentiate GBM from SBM.

Methods

We performed a retrospective analysis of patients who underwent craniotomy between March 2018 to June 2020 with glioblastoma (GBM) and solitary brain metastases (SBM) diagnoses. Cases with an intraoperative ultrasound study were included. Images were acquired before dural opening, first in B-mode, and then using the strain elastography module. After image pre-processing, an analysis based on deep learning was conducted using the open-source software Orange. We have trained an existing neural network to classify tumors into GBM and SBM via the transfer learning method using Inception V3. Then, logistic regression (LR) with LASSO (least absolute shrinkage and selection operator) regularization, support vector machine (SVM), random forest (RF), neural network (NN), and k-nearest neighbor (kNN) were used as classification algorithms. After the models’ training, ten-fold stratified cross-validation was performed. The models were evaluated using the area under the curve (AUC), classification accuracy, and precision.

Results

A total of 36 patients were included in the analysis, 26 GBM and 10 SBM. Models were built using a total of 812 ultrasound images, 435 of B-mode, 265 (60.92%) corresponded to GBM and 170 (39.8%) to metastases. In addition, 377 elastograms, 232 (61.54%) GBM and 145 (38.46%) metastases were analyzed. For B-mode, AUC and accuracy values of the classification algorithms ranged from 0.790 to 0.943 and from 72 to 89%, respectively. For elastography, AUC and accuracy values ranged from 0.847 to 0.985 and from 79% to 95%, respectively.

Conclusion

Automated processing of ultrasound images through deep learning can generate high-precision classification algorithms that differentiate glioblastomas from metastases using intraoperative ultrasound. The best performance regarding AUC was achieved by the elastography-based model supporting the additional diagnostic value that this technique provides.

The impact of hospital safety-net status on inpatient outcomes for brain tumor craniotomy: a 10-year nationwide analysis

Background

Outcome disparities have been documented at safety-net hospitals (SNHs), which disproportionately serve vulnerable patient populations. Using a nationwide retrospective cohort, we assessed inpatient outcomes following brain tumor craniotomy at SNHs in the United States.

Methods

We identified all craniotomy procedures in the National Inpatient Sample from 2002–2011 for brain tumors: glioma, metastasis, meningioma, and vestibular schwannoma. Safety-net burden was calculated as the number of Medicaid plus uninsured admissions divided by total admissions. Hospitals in the top quartile of burden were defined as SNHs. The association between SNH status and in-hospital mortality, discharge disposition, complications, hospital-acquired conditions (HACs), length of stay (LOS), and costs were assessed. Multivariate regression adjusted for patient, hospital, and severity characteristics.

Results

304,719 admissions were analyzed. The most common subtype was glioma (43.8%). Of 1,206 unique hospitals, 242 were SNHs. SNH admissions were more likely to be non-white (P < .001), low income (P < .001), and have higher severity scores (P = .034). Mortality rates were higher at SNHs for metastasis admissions (odds ratio [OR] = 1.48, P = .025), and SNHs had higher complication rates for meningioma (OR = 1.34, P = .003) and all tumor types combined (OR = 1.17, P = .034). However, there were no differences at SNHs for discharge disposition or HACs. LOS and hospital costs were elevated at SNHs for all subtypes, culminating in a 10% and 9% increase in LOS and costs for the overall population, respectively (all P < .001).

Conclusions

SNHs demonstrated poorer inpatient outcomes for brain tumor craniotomy. Further analyses of the differences observed and potential interventions to ameliorate interhospital disparities are warranted.

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.

Exploratory Analysis of Qualitative MR Imaging Features for the Differentiation of Glioblastoma and Brain Metastases

OBJECTIVES

To identify qualitative VASARI (Visually AcceSIble Rembrandt Images) Magnetic Resonance (MR) Imaging features for differentiation of glioblastoma (GBM) and brain metastasis (BM) of different primary tumors.

MATERIALS AND METHODS

T1-weighted pre- and post-contrast, T2-weighted, and T2-weighted, fluid attenuated inversion recovery (FLAIR) MR images of a total of 239 lesions from 109 patients with either GBM or BM (breast cancer, non-small cell (NSCLC) adenocarcinoma, NSCLC squamous cell carcinoma, small-cell lung cancer (SCLC)) were included. A set of adapted, qualitative VASARI MR features describing tumor appearance and location was scored (binary; 1 = presence of feature, 0 = absence of feature). Exploratory data analysis was performed on binary scores using a combination of descriptive statistics (proportions with 95% binomial confidence intervals), unsupervised methods and supervised methods including multivariate feature ranking using either repeated fitting or recursive feature elimination with Support Vector Machines (SVMs).

RESULTS

GBMs were found to involve all lobes of the cerebrum with a fronto-occipital gradient, often affected the corpus callosum (32.4%, 95% CI 19.1-49.2), and showed a strong preference for the right hemisphere (79.4%, 95% CI 63.2-89.7). BMs occurred most frequently in the frontal lobe (35.1%, 95% CI 28.9-41.9) and cerebellum (28.3%, 95% CI 22.6-34.8). The appearance of GBMs was characterized by preference for well-defined non-enhancing tumor margin (100%, 89.8-100), ependymal extension (52.9%, 36.7-68.5) and substantially less enhancing foci than BMs (44.1%, 28.9-60.6 vs. 75.1%, 68.8-80.5). Unsupervised and supervised analyses showed that GBMs are distinctively different from BMs and that this difference is driven by definition of non-enhancing tumor margin, ependymal extension and features describing laterality. Differentiation of histological subtypes of BMs was driven by the presence of well-defined enhancing and non-enhancing tumor margins and localization in the vision center. SVM models with optimal hyperparameters led to weighted F1-score of 0.865 for differentiation of GBMs from BMs and weighted F1-score of 0.326 for differentiation of BM subtypes.

CONCLUSION

VASARI MR imaging features related to definition of non-enhancing margin, ependymal extension, and tumor localization may serve as potential imaging biomarkers to differentiate GBMs from BMs.

HIF1A signaling selectively supports proliferation of breast cancer in the brain

Blood-borne metastasis to the brain is a major complication of breast cancer, but cellular pathways that enable cancer cells to selectively grow in the brain microenvironment are poorly understood. We find that cultured circulating tumor cells (CTCs), derived from blood samples of women with advanced breast cancer and directly inoculated into the mouse frontal lobe, exhibit striking differences in proliferative potential in the brain. Derivative cell lines generated by serial intracranial injections acquire selectively increased proliferative competency in the brain, with reduced orthotopic tumor growth. Increased Hypoxia Inducible Factor 1A (HIF1A)-associated signaling correlates with enhanced proliferation in the brain, and shRNA-mediated suppression of HIF1A or drug inhibition of HIF-associated glycolytic pathways selectively impairs brain tumor growth while minimally impacting mammary tumor growth. In clinical specimens, brain metastases have elevated HIF1A protein expression, compared with matched primary breast tumors, and in patients with brain metastases, hypoxic signaling within CTCs predicts decreased overall survival. The selective activation of hypoxic signaling by metastatic breast cancer in the brain may have therapeutic implications.

A Rare Case of Diffuse Subependymal Periventricular Metastases from Small Cell Lung Carcinoma

Small cell lung cancer, whose essence is neuroendocrine tumors, makes up proximately 14-20% of all lung cancer circumstances. Compared to non-small cell lung cancer, its clinical manifestation seems more positive and has a tendency to disseminate earlier in the process of its natural past. About 10% of patients present with brain metastases at the time of provisional diagnosis and sometimes all along the course of their disease, there will be 40-50% of developed brain metastases in addition. Although metastases in the brain parenchyma are often found in patients with advanced lung cancer, periventricular metastases are rare. We report one case of diffuse subependymal periventricular metastases from small cell carcinoma of the lung.

Multiple cutaneous and haemorrhagic brain metastases as the sentinel presentation of lung adenocarcinoma

Skin is a relatively uncommon site of metastasis in lung cancer and is associated with a poor prognosis. Although, lung cancer does not uncommonly metastasise to the brain, haemorrhagic brain metastases are rarely reported. In this report, we present a dramatic presentation of a female smoker with a 3-week history of numerous cutaneous lesions over her body and two episodes of transient memory loss. Work-up demonstrated widely metastatic, poorly differentiated lung adenocarcinoma with haemorrhagic brain metastases. She proceeded with whole brain radiotherapy, but her performance status quickly declined afterwards; she succumbed to her malignancy within 6 weeks of presentation. This case presentation demonstrates that, for patients who present with cutaneous masses, especially those aged more than 60 years, and who have extensive smoking history, metastatic lung cancer should remain on the differential diagnosis. Also, the very poor prognosis of multiple metastases may influence medical and social decisions in the patient's treatment plan.

Identification of the origin of brain metastases based on the relative methylation orderings of CpG sites

Accurate diagnosis of the origin of brain metastases (BMs) is crucial for tailoring an effective therapy to improve patients' prognosis. BMs of unknown origin account for approximately 2-14% of patients with BMs. Hence, the aim of this study was to identify the original cancer type of BMs based on their DNA methylation profiles. The DNA methylation profiles of glioma (GM), BM, and seven other types of primary cancers were collected. In comparison with GM, the reversal CpG site pairs were identified for each of the seven other types of primary cancers based on the within-sample relative methylation orderings (RMOs) of the CpG sites. Then, using the reversal CpG site pairs, GMs were distinguished from BMs and the seven other types of primary cancers. All 61 of the GM samples were correctly identified as GM. The cancer type was also identified for the non-GM samples. For the seven other types of primary cancers, greater than 93% of samples of each cancer type were correctly identified as their corresponding cancer type, except for breast cancer, which had an 88% accuracy. For 133 BM samples, 132 BM samples were identified as non-GM, and 95% of the 133 BM samples were correctly classified into their corresponding original cancer types. The RMO-based method can accurately identify the origin of BMs, which is important for precision treatment.

Evaluation of Perienhancing Area in Differentiation between Glioblastoma and Solitary Brain Metastasis

Purpose:

Accurate differential diagnosis between glioblastoma and brain metastasis is important. We aimed to differentiate these tumors by evaluation of the perienhancing area.

Materials and Methods:

Thirty patients with glioblastoma and solitary brain metastasis were included. The diameters of perienhancing and enhancing areas were measured, and the percentage of enhancing area was calculated. We measured Apparent diffusion coefficient (ADC) of perienhancing and enhancing areas. Intratumoral necrotic areas were measured.

Results:

The enhancing area of glioblastoma was 56.61% and metastasis was 42.55% (p = 0.08). The ADC values of the perienhancing part of GBM was 0.7 and metastasis was 0.79 (p = 0.052). The ADC value of the enhancing part of the GBM was 0.82 and metastasis was 0.8 (p-value = 0.72). The intratumoral necrotic area of glioblastoma (152.25 mm³) was higher than in metastasis (0 mm³) (p-value = 0.003) with a cutoff area of 11.8 mm².

Conclusion:

The ADC values of the perienhancing area were lower in glioblastoma with a near-significant p-value. Other perienhancing parameters demonstrated no significant difference between both tumors. The intratumoral necrotic area of glioblastoma is larger than metastasis.

Validation of combined use of DWI and percentage signal recovery-optimized protocol of DSC-MRI in differentiation of high-grade glioma, metastasis, and lymphoma

PURPOSE

With conventional MRI, it is often difficult to effectively differentiate between contrast-enhancing brain tumors, including primary central nervous system lymphoma (PCNSL), high-grade glioma (HGG), and metastasis. This study aimed to assess the discrimination ability of the parameters obtained from DWI and the percentage signal recovery- (PSR-) optimized protocol of DSC-MRI between these three tumor types at an initial step.

METHODS

DSC-MRI using a PSR-optimized protocol (TR/TE = 1500/30 ms, flip angle = 90°, no preload) and DWI of 99 solitary enhancing tumors (60 HGGs, 24 metastases, 15 PCNSLs) were retrospectively assessed before treatment. rCBV, PSR, ADC in the tumor core and rCBV, and ADC in peritumoral edema were measured. The differences were evaluated using one-way ANOVA, and the diagnostic performance was evaluated using ROC curve analysis.

RESULTS

PSR in the tumor core showed the best discriminating performance in differentiating these three tumor types with AUC values of 0.979 for PCNSL vs. others and 0.947 for HGG vs. metastasis. The ADC was only helpful in the tumor core and distinguishing PCNSLs from others (AUC = 0.897).

CONCLUSION

Different from CBV-optimized protocols (preload, intermediate FA), PSR derived from the PSR-optimized protocol seems to be the most important parameter in the differentiation of HGGs, metastases, and PCNSLs at initial diagnosis. This property makes PSR remarkable and carries the need for comprehensive DSC-MRI protocols, which provides PSR sensitivity and CBV accuracy together, such as the preload use of the PSR-optimized protocol before the CBV-optimized protocol.

Melanoma brain metastases: review of histopathological features and immune-molecular aspects

Patients with melanoma brain metastases (MBM) have a dismal prognosis, but the unprecedented advances in systemic therapy alone or in combination with local therapy have now extended the 1-year overall survival rate from 20–25% to nearing 80–85%, mainly in asymptomatic patients. The histopathological and molecular characterization of MBM and the understanding of the microenvironment are critical to more effectively manage patients with advanced melanoma and to design biologically driven clinical trials. This review aims to give an overview of the main histopathological features and the immune-molecular aspects of MBM.

Intravascular carcinomatosis of the brain: a report of two cases

Although central nervous system (CNS) metastases are common in advanced cancer, CNS involvement solely by intravascular tumor cells, known as intravascular carcinomatosis, is extremely rare. We report two cases of brain metastasis in which tumor cells were restricted to the vascular lumina without parenchymal involvement, resulting in ischemic lesions. The first patient is a previously healthy young woman who presented with symptoms of community-acquired pneumonia and progressed to respiratory failure. Computed tomography of the brain showed infarcts of differing ages. At autopsy, she was found to have widely metastatic cervical squamous cell carcinoma and cerebral tumor emboli with multifocal infarcts, mainly microinfarcts. The second patient is an elderly man with cognitive impairment and mild Parkinsonism who presented with symptoms of a urinary tract infection. Magnetic resonance imaging of the brain showed atrophy and changes suggestive of chronic microvascular ischemic disease. Postmortem examination demonstrated prostatic adenocarcinoma and cerebral tumor emboli with multifocal infarcts. These cases illustrate that this pattern of intracranial metastasis may rarely be a cause of cerebral ischemic lesions and emphasize the importance of thorough pathologic examination of the brain.

Contrast-enhanced T1-weighted image radiomics of brain metastases may predict EGFR mutation status in primary lung cancer

Identification of EGFR mutations is critical to the treatment of primary lung cancer and brain metastases (BMs). Here, we explored whether radiomic features of contrast-enhanced T1-weighted images (T1WIs) of BMs predict EGFR mutation status in primary lung cancer cases. In total, 1209 features were extracted from the contrast-enhanced T1WIs of 61 patients with 210 measurable BMs. Feature selection and classification were optimized using several machine learning algorithms. Ten-fold cross-validation was applied to the T1WI BM dataset (189 BMs for training and 21 BMs for the test set). Area under receiver operating characteristic curves (AUC), accuracy, sensitivity, and specificity were calculated. Subgroup analyses were also performed according to metastasis size. For all measurable BMs, random forest (RF) classification with RF selection demonstrated the highest diagnostic performance for identifying EGFR mutation (AUC: 86.81). Support vector machine and AdaBoost were comparable to RF classification. Subgroup analyses revealed that small BMs had the highest AUC (89.09). The diagnostic performance for large BMs was lower than that for small BMs (the highest AUC: 78.22). Contrast-enhanced T1-weighted image radiomics of brain metastases predicted the EGFR mutation status of lung cancer BMs with good diagnostic performance. However, further study is necessary to apply this algorithm more widely and to larger BMs.

Metastases to the central nervous system: Molecular basis and clinical considerations

BACKGROUND

Metastatic tumors are the most common malignancies of the central nervous system (CNS) in adults. CNS metastases are associated with unfavorable prognosis, high morbidity and mortality. Lung cancer is the most common source of brain metastases, followed by breast cancer and melanoma. Rising incidence is primarily due to improvements in systemic control of primary malignancies, prolonged survival and advances in cancer detection.

PURPOSE

To provide an overview of the metastatic cascade and the role of angiogenesis, neuroinflammation, metabolic adaptations, and clinical details about brain metastases from different primary tumors.

METHODS

A review of the literature on brain metastases was conducted, focusing on the pathophysiology and clinical aspects of the disease. PubMed was used to search for relevant articles published from January 1975 through December 2019 using the keywords brain metabolism, brain metastasis, metastatic cascade, molecular mechanisms, incidence, risk factors, and prognosis. 146 articles met the criteria and were included in this review.

DISCUSSION

Some primary tumors have a higher tendency to metastasize to the CNS. Establishing a suitable metastatic microenvironment is important in maintaining tumor cell growth and survival. Magnetic resonance imaging (MRI) is a widely used tool for diagnosis and treatment monitoring. Available treatments include surgery, radiotherapy, stereotactic radiosurgery, chemotherapy, immunotherapy, and systemic targeted therapies.

CONCLUSIONS

Prevention of metastases to the CNS remains a difficult challenge. Advances in screening of high-risk patients and future development of novel treatments may improve patient outcomes.

Companion animal models of neurological disease

Clinical translation of novel therapeutics that improve the survival and quality of life of patients with neurological disease remains a challenge, with many investigational drug and device candidates failing in advanced stage clinical trials. Naturally occurring inherited and acquired neurological diseases, such as epilepsy, inborn errors of metabolism, brain tumors, spinal cord injury, and stroke occur frequently in companion animals, and many of these share epidemiologic, pathophysiologic and clinical features with their human counterparts. As companion animals have a relatively abbreviated lifespan and genetic background, are immunocompetent, share their environment with human caregivers, and can be clinically managed using techniques and tools similar to those used in humans, they have tremendous potential for increasing the predictive value of preclinical drug and device studies. Here, we review comparative features of spontaneous neurological diseases in companion animals with an emphasis on neuroimaging methods and features, illustrate their historical use in translational studies, and discuss inherent limitations associated with each disease model. Integration of companion animals with naturally occurring disease into preclinical studies can complement and expand the knowledge gained from studies in other animal models, accelerate or improve the manner in which research is translated to the human clinic, and ultimately generate discoveries that will benefit the health of humans and animals.

The role of contextual signal TGF-β1 inducer of epithelial mesenchymal transition in metastatic lung adenocarcinoma patients with brain metastases: an update on its pathological significance and therapeutic potential

Lung adenocarcinoma (LA) is the most common cause of cancer-related death worldwide. Despite the advances over last decade in new targeted therapies, cancer genetics, diagnostics, staging, and surgical techniques as well as new chemotherapy and radiotherapy protocols, the death rate from LA remains high. The tumour microenvironment is composed of several cytokines, one of which is transforming growth factor β1 (TGF-β1), which modulates and mediates the expression of epithelial-mesenchymal transition (EMT), correlated with invasive growth in LAs, and exhibits its pleiotropic effects through binding to transmembrane receptors TβR-1 (also termed activin receptor-like kinases – ALKs) and TβR-2. Accordingly, there is an urgent need to elucidate the molecular mechanisms associated with the tumoural spreading process and therapeutic resistance of this serious pathology. In this review, we briefly discuss the current role of contextual signal TGF-β1 inducer of epithelial mesenchymal transition in metastatic lung adenocarcinoma patients with brain metastases, and give an overview of our current mechanistic understanding of the TGF-β1-related pathways in brain metastases progression, TGF-β1 pathway inhibitors that could be used for clinical treatment, and examination of models used to study these processes. Finally, we summarise the current progress in the therapeutic approaches targeting TGF-β1.

Identification of distinctive features in human intracranial tumors by label-free nonlinear multimodal microscopy

Nonlinear multimodal microscopy offers a series of label-free techniques with potential for intraoperative identification of tumor borders in situ using novel endoscopic devices. Here, we combined coherent anti-Stokes Raman scattering, two-photon excited fluorescence (TPEF) and second harmonic generation imaging to analyze biopsies of different human brain tumors, with the aim to understand whether the morphological information carried by single field of view images, similar to what delivered by present endoscopic systems, is sufficient for tumor recognition. We imaged 40 human biopsies of high and low grade glioma, meningioma, as well as brain metastases of melanoma, breast, lung and renal carcinoma, in comparison with normal brain parenchyma. Furthermore, five biopsies of schwannoma were analyzed and compared with nonpathological nerve tissue. Besides the high cellularity, the typical features of tumor, which were identified and quantified, are intracellular and extracellular lipid droplets, aberrant vessels, extracellular matrix collagen and diffuse TPEF. Each tumor type displayed a particular morphochemistry characterized by specific patterns of the above-mentioned features. Nonlinear multimodal microscopy performed on fresh unprocessed biopsies confirmed that the technique has the ability to visualize tumor structures and discern normal from neoplastic tissue likewise in conditions close to in situ.

90-gene signature assay for tissue origin diagnosis of brain metastases

Background

Brain metastases (BM) are the most common intracranial tumors. 2–14% of BM patients present with unknown primary site despite intensive evaluations. This study aims to evaluate the performance of a 90-gene expression signature in determining the primary sites for BM samples.

Methods

The sequence-based gene expression profiles of 708 primary brain tumors (PBT) collected from The Cancer Genome Atlas (TCGA) database were analyzed by the 90-gene expression signature, with a similarity score for each of 21 common tumor types. We then used Optimal Binning algorithm to generate a threshold for separating PBT from BM. Eighteen PBT samples were analyzed to substantiate the reliability of the threshold. In addition, the performance of the 90-gene expression signature for molecular classification of metastatic brain tumors was validated in a cohort of 48 BM samples with the known origin. For each BM sample, the tumor type with the highest similarity score was considered tissue of origin. When a sample was diagnosed as PBT, but the similarity score below the threshold, the second prediction was considered as the primary site.

Results

A threshold of the similarity score, 70, was identified to discriminate PBT from BM (PBT: > 70, BM: ≤ 70) with an accuracy of 99% (703/708, 95% CI 98–100%). The 90-gene expression signature was further validated with 18 PBT and 44 BM samples. The results of 18 PBT samples matched reference diagnosis with a concordance rate of 100%, and all similarity scores were above the threshold. Of 44 BM samples, the 90-gene expression signature accurately predicted primary sites in 89% (39/44, 95% CI 75–96%) of the cases.

Conclusions

Our findings demonstrated the potential that the 90-gene expression signature could serve as a powerful tool for accurately identifying the primary sites of metastatic brain tumors.

Angiosarcoma-related cerebral metastases: a systematic review of the literature

Angiosarcoma-related cerebral metastases have only been recorded in a few case reports and case series and have not been systematically reviewed to date. Our objective was therefore to perform a systematic literature review on cases of angiosarcomas metastasizing to the brain to inform current practice. All three major libraries-PubMed/MEDLINE, Embase, and Cochrane-were systematically searched, until January 2019. Articles in English reporting angiosarcoma-related cerebral metastases via hematogenous route were included. Our search yielded 45 articles (38 case reports, 5 retrospective studies, 1 case series and 1 letter to the editor), totaling 48 patients (mean age 47.9 years). The main primary site was the heart. The mean time of diagnosis of cerebral metastases following primary tumor identification was 4.9 months. In 15 cases, the brain was the only metastatic site. In cases of multiple extracerebral metastases, the most common sites were the lung and bone. Acute intracerebral supratentorial hemorrhage was the most common presenting radiological feature. Treatment strategies were almost equally divided between the surgical (with or without adjuvant treatment) and the medical arm. Mean overall survival was 7.2 months while progression-free survival was 1.5 months. To our knowledge, this is the first systematic literature review on angiosarcoma-related cerebral metastases. This pathology proves to be an extremely rare clinical entity and carries a poor prognosis, and no consensus has been reached regarding treatment.

Innovative Therapeutic Strategies for Effective Treatment of Brain Metastases

Brain metastases are the most prevalent of intracranial malignancies. They are associated with a very poor prognosis and near 100% mortality. This has been the case for decades, largely because we lack effective therapeutics to augment surgery and radiotherapy. Notwithstanding improvements in the precision and efficacy of these life-prolonging treatments, with no reliable options for adjunct systemic therapy, brain recurrences are virtually inevitable. The factors limiting intracranial efficacy of existing agents are both physiological and molecular in nature. For example, heterogeneous permeability, abnormal perfusion and high interstitial pressure oppose the conventional convective delivery of circulating drugs, thus new delivery strategies are needed to achieve uniform drug uptake at therapeutic concentrations. Brain metastases are also highly adapted to their microenvironment, with complex cross-talk between the tumor, the stroma and the neural compartments driving speciation and drug resistance. New strategies must account for resistance mechanisms that are frequently engaged in this milieu, such as HER3 and other receptor tyrosine kinases that become induced and activated in the brain microenvironment. Here, we discuss molecular and physiological factors that contribute to the recalcitrance of these tumors, and review emerging therapeutic strategies, including agents targeting the PI3K axis, immunotherapies, nanomedicines and MRI-guided focused ultrasound for externally controlling drug delivery.

Epigenetic profiling for the molecular classification of metastatic brain tumors

Optimal treatment of brain metastases is often hindered by limitations in diagnostic capabilities. To meet this challenge, here we profile DNA methylomes of the three most frequent types of brain metastases: melanoma, breast, and lung cancers (n = 96). Using supervised machine learning and integration of DNA methylomes from normal, primary, and metastatic tumor specimens (n = 1860), we unravel epigenetic signatures specific to each type of metastatic brain tumor and constructed a three-step DNA methylation-based classifier (BrainMETH) that categorizes brain metastases according to the tissue of origin and therapeutically relevant subtypes. BrainMETH predictions are supported by routine histopathologic evaluation. We further characterize and validate the most predictive genomic regions in a large cohort of brain tumors (n = 165) using quantitative-methylation-specific PCR. Our study highlights the importance of brain tumor-defining epigenetic alterations, which can be utilized to further develop DNA methylation profiling as a critical tool in the histomolecular stratification of patients with brain metastases.

Adjuvant radiotherapy and outcomes of presumed hemorrhagic melanoma brain metastases without malignant cells

Background

Patients with melanoma can present with a hemorrhagic intracranial lesion. Upon resection, pathology reports may not detect any malignant cells. However, the hemorrhage may obscure their presence and so physicians may still decide whether adjuvant radiotherapy should be applied. Here, we report on the outcomes of a series of patients with melanoma with hemorrhagic brain lesions that returned with no tumor cells.

Methods

All melanoma patients who had craniotomies from 2008 to 2017 at a single institution for hemorrhagic brain lesions were identified through retrospective chart review. Those who had pathology reports with no malignant cells were analyzed. Recurrence at the former site of hemorrhage and resection was the primary outcome.

Results

Ten patients met inclusion criteria, and the median follow-up time was 8.5 (1.8-27.3) months. At the time of craniotomy, the median number of brain lesions was 3 (1-25). Two patients had prior craniotomies, eight had prior radiation, and six had prior immunotherapy to the lesion of interest. After surgery, one patient received stereotactic radiosurgery (SRS) to the resection bed. Only one patient developed subsequent melanoma at the resection site; this patient developed the lesion recurrence once and had not received postoperative SRS.

Conclusion

Although small foci of metastatic disease as a source of bleeding for some patients cannot be excluded, melanoma patients with a suspected hemorrhagic brain metastasis that shows no tumor cells on pathology may benefit from close observation. The local recurrence risk in such cases appears to be low, even without adjuvant radiation.

Mechanisms and Therapy for Cancer Metastasis to the Brain

Advances in chemotherapy and targeted therapies have improved survival in cancer patients with an increase of the incidence of newly diagnosed brain metastases (BMs). Intracranial metastases are symptomatic in 60–70% of patients. Magnetic resonance imaging (MRI) with gadolinium is more sensitive than computed tomography and advanced neuroimaging techniques have been increasingly used in the detection, treatment planning, and follow-up of BM. Apart from the morphological analysis, the most effective tool for characterizing BM is immunohistochemistry. Molecular alterations not always reflect those of the primary tumor. More sophisticated methods of tumor analysis detecting circulating biomarkers in fluids (liquid biopsy), including circulating DNA, circulating tumor cells, and extracellular vesicles, containing tumor DNA and macromolecules (microRNA), have shown promise regarding tumor treatment response and progression. The choice of therapeutic approaches is guided by prognostic scores (Recursive Partitioning Analysis and diagnostic-specific Graded Prognostic Assessment-DS-GPA). The survival benefit of surgical resection seems limited to the subgroup of patients with controlled systemic disease and good performance status. Leptomeningeal disease (LMD) can be a complication, especially in posterior fossa metastases undergoing a “piecemeal” resection. Radiosurgery of the resection cavity may offer comparable survival and local control as postoperative whole-brain radiotherapy (WBRT). WBRT alone is now the treatment of choice only for patients with single or multiple BMs not amenable to surgery or radiosurgery, or with poor prognostic factors. To reduce the neurocognitive sequelae of WBRT intensity modulated radiotherapy with hippocampal sparing, and pharmacological approaches (memantine and donepezil) have been investigated. In the last decade, a multitude of molecular abnormalities have been discovered. Approximately 33% of patients with non-small cell lung cancer (NSCLC) tumors and epidermal growth factor receptor mutations develop BMs, which are targetable with different generations of tyrosine kinase inhibitors (TKIs: gefitinib, erlotinib, afatinib, icotinib, and osimertinib). Other “druggable” alterations seen in up to 5% of NSCLC patients are the rearrangements of the “anaplastic lymphoma kinase” gene TKI (crizotinib, ceritinib, alectinib, brigatinib, and lorlatinib). In human epidermal growth factor receptor 2-positive, breast cancer targeted therapies have been widely used (trastuzumab, trastuzumab-emtansine, lapatinib-capecitabine, and neratinib). Novel targeted and immunotherapeutic agents have also revolutionized the systemic management of melanoma (ipilimumab, nivolumab, pembrolizumab, and BRAF inhibitors dabrafenib and vemurafenib).

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study

OBJECTIVE

To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach.

METHODS

Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one.

RESULTS

In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180).

CONCLUSION

Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels.

KEY POINTS

• Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

Covalent nano delivery systems for selective imaging and treatment of brain tumors

Nanomedicine is a rapidly evolving form of therapy that holds a great promise for superior drug delivery efficiency and therapeutic efficacy than conventional cancer treatment. In this review, we attempt to cover the benefits and the limitations of current nanomedicines with special attention to covalent nano conjugates for imaging and drug delivery in the brain. The improvement in brain tumor treatment remains dismal despite decades of efforts in drug development and patient care. One of the major obstacles in brain cancer treatment is the poor drug delivery efficiency owing to the unique blood-brain barrier (BBB) in the CNS. Although various anti-cancer agents are available to treat tumors outside of the CNS, the majority fails to cross the BBB. In this regard, nanomedicines have increasingly drawn attention due to their multi-functionality and versatility. Nano drugs can penetrate BBB and other biological barriers, and selectively accumulate in tumor cells, while concurrently decreasing systemic toxicity.

The Role of MRgLITT in Overcoming the Challenges in Managing Infield Recurrence After Radiation for Brain Metastasis

Radiation necrosis and tumor recurrence are common sequelae after radiation therapy for brain metastasis. The differentiation of radiation necrosis and recurrent brain metastases continues to remain a difficult task despite a number of diagnostic methods. Techniques including magnetic resonance imaging, diffusion-weighted imaging, nuclear studies, and the gold standard of biopsy have all been studied for their effectiveness in accurately diagnosing the postradiation condition. Various specific treatment options of the distinct pathologies are available with the general theory that recurrences require more immediate treatment whereas radiation necrosis can be observed until symptomatic before intervention. This further emphasizes the necessity to accurately diagnose the condition to start appropriate and effective treatment. Despite both pathologies being pathophysiologically distinct, controversies exist as to whether there should be a distinction made at all or if the two can be perceived as a single condition if treatment and presentation are similar enough. Furthermore, a single treatment option such as magnetic resonance–guided, laser-induced thermal therapy (MRgLITT) can be used, potentially eliminating the need to differentiate the 2 entities because it successfully treats both conditions while being minimally invasive.

A differentially expressed set of microRNAs in cerebro-spinal fluid (CSF) can diagnose CNS malignancies

Central Nervous System malignancies often require stereotactic biopsy or biopsy for differential diagnosis, and for tumor staging and grading. Furthermore, stereotactic biopsy can be non-diagnostic or underestimate grading. Hence, there is a compelling need of new diagnostic biomarkers to avoid such invasive procedures. Several biological markers have been proposed, but they can only identify specific prognostic subtype of Central Nervous System tumors, and none of them has found a standardized clinical application.The aim of the study was to identify a Cerebro-Spinal Fluid microRNA signature that could differentiate among Central Nervous System malignancies.CSF total RNA of 34 neoplastic and of 14 non-diseased patients was processed by NanoString. Comparison among groups (Normal, Benign, Glioblastoma, Medulloblastoma, Metastasis and Lymphoma) lead to the identification of a microRNA profile that was further confirmed by RT-PCR and in situ hybridization.Hsa-miR-451, -711, 935, -223 and -125b were significantly differentially expressed among the above mentioned groups, allowing us to draw an hypothetical diagnostic chart for Central Nervous System malignancies.This is the first study to employ the NanoString technique for Cerebro-Spinal Fluid microRNA profiling. In this article, we demonstrated that Cerebro-Spinal Fluid microRNA profiling mirrors Central Nervous System physiologic or pathologic conditions. Although more cases need to be tested, we identified a diagnostic Cerebro-Spinal Fluid microRNA signature with good perspectives for future diagnostic clinical applications.

Demeclocycline as a contrast agent for detecting brain neoplasms using confocal microscopy

Complete resection of brain tumors improves life expectancy and quality. Thus, there is a strong need for high-resolution detection and microscopically controlled removal of brain neoplasms. The goal of this study was to test demeclocycline as a contrast enhancer for the intraoperative detection of brain tumors. We have imaged benign and cancerous brain tumors using multimodal confocal microscopy. The tumors investigated included pituitary adenoma, meningiomas, glioblastomas, and metastatic brain cancers. Freshly excised brain tissues were stained in 0.75 mg ml(-1) aqueous solution of demeclocyline. Reflectance images were acquired at 402 nm. Fluorescence signals were excited at 402 nm and registered between 500 and 540 nm. After imaging, histological sections were processed from the imaged specimens and compared to the optical images. Fluorescence images highlighted normal and cancerous brain cells, while reflectance images emphasized the morphology of connective tissue. The optical and histological images were in accordance with each other for all types of tumors investigated. Demeclocyline shows promise as a contrast agent for intraoperative detection of brain tumors.

Metastatic ovarian carcinoma to the brain: an approach to identification and classification for neuropathologists

Brain metastasis is an uncommon but increasing manifestation of ovarian epithelial carcinoma and neuropathologists' collective experience with these tumors is limited. We present clinicopathological characteristics of 13 cases of brain metastases from ovarian epithelial carcinoma diagnosed at two academic institutions. The mean ages at diagnosis of the ovarian carcinoma and their subsequent brain metastases were 58.7 and 62.8 years, respectively. At the time of initial diagnosis of ovarian carcinoma the majority of patients had an advanced stage and none had brain metastases as their first manifestation of malignancy. Brain metastases tended to be multiple with ring-enhancing features on neuroimaging. Primary tumors and their brain metastases were all high-grade histologically and the histologic subtypes were: nine high-grade serous carcinoma (HGSC) cases, two clear cell carcinoma (CCC) cases and a single case each of carcinosarcoma and high-grade adenocarcinoma. A recommended histo- and immunopathological approach to these tumours are provided to aid neuropathologists in the recognition and classification of metastatic ovarian carcinoma to the brain.

Changes in BAI1 and nestin expression are prognostic indicators for survival and metastases in breast cancer and provide opportunities for dual targeted therapies

The 2-year survival rate of patients with breast cancer brain metastases is less than 2%. Treatment options for breast cancer brain metastases are limited, and there is an unmet need to identify novel therapies for this disease. Brain angiogenesis inhibitor 1 (BAI1) is a GPCR involved in tumor angiogenesis, invasion, phagocytosis, and synaptogenesis. For the first time, we identify that BAI1 expression is significantly reduced in breast cancer and higher expression is associated with better patient survival. Nestin is an intermediate filament whose expression is upregulated in several cancers. We found that higher Nestin expression significantly correlated with breast cancer lung and brain metastases, suggesting both BAI1 and Nestin can be therapeutic targets for this disease. Here, we demonstrate the ability of an oncolytic virus, 34.5ENVE, to target and kill high Nestin-expressing cells and deliver Vstat120 (extracellular fragment of BAI1). Finally, we created two orthotopic immune-competent murine models of breast cancer brain metastases and demonstrated 34.5ENVE extended the survival of immune-competent mice bearing intracranial breast cancer tumors.

An unusual cause of a fall: an unusual presentation of lung carcinoma

An 80-year-old gentleman presented with a fall and subtle symptoms suggestive of a cerebellar lesion, on a background of hemiparesis due to a previous cerebral vascular accident. On admission it was thought that changes on a chest radiograph were consistent with a community-acquired pneumonia. A CT of the head showed a space-occupying lesion in the right cerebellum with surrounding oedema. A previous MRI of the brain performed 8 months earlier for investigation of dementia showed evidence of this lesion although it was significantly smaller and without midline shift; however, this had not been discussed on the MRI report. A subsequent CT of the thorax confirmed a thick-walled cavitating mass in the left upper lobe, with biopsy of this lesion and bronchial washings showing metaplastic and atypical cells suggestive of adenocarcinoma. This report highlights both the importance of accurate imaging reporting, even of incidental findings, and the insidious nature of lung malignancy and its broad clinical presentation.