Brain metastasis of unknown primary: A diagnostic and therapeutic dilemma

Differentiation of lung and breast cancer brain metastases: Comparison of texture analysis and deep convolutional neural networks

PURPOSE

Metastases are the most common neoplasm in the adult brain. In order to initiate the treatment, an extensive diagnostic workup is usually required. Radiomics is a discipline aimed at transforming visual data in radiological images into reliable diagnostic information. We aimed to examine the capability of deep learning methods to classify the origin of metastatic lesions in brain MRIs and compare the deep Convolutional Neural Network (CNN) methods with image texture based features.

METHODS

One hundred forty three patients with 157 metastatic brain tumors were included in the study. The statistical and texture based image features were extracted from metastatic tumors after manual segmentation process. Three powerful pre-trained CNN architectures and the texture-based features on both 2D and 3D tumor images were used to differentiate lung and breast metastases. Ten-fold cross-validation was used for evaluation. Accuracy, precision, recall, and area under curve (AUC) metrics were calculated to analyze the diagnostic performance.

RESULTS

The texture-based image features on 3D volumes achieved better discrimination results than 2D image features. The overall performance of CNN architectures with 3D inputs was higher than the texture-based features. Xception architecture, with 3D volumes as input, yielded the highest accuracy (0.85) while the AUC value was 0.84. The AUC values of VGG19 and the InceptionV3 architectures were 0.82 and 0.81, respectively.

CONCLUSION

CNNs achieved superior diagnostic performance in differentiating brain metastases from lung and breast malignancies than texture-based image features. Differentiation using 3D volumes as input exhibited a higher success rate than 2D sagittal images.

Stereotactic biopsy for multiple intra-axial brain lesions: impact on consequent treatment Regimen

Background and objectives

Multiple brain lesions represent a serious challenge in which biopsy is commonly the first step to help overcome patients' mental anxiety and decide the following treatment step. This study presents an effective decisional algorithm that could guide in dealing with such a challenge. We evaluate the feasibility and safety of frame-based stereotactic biopsy to obtain the histopathologic diagnosis of the multiple intra-axial brain lesions and to decide the further treatment.

Patients and methods

Thirty-two patients with multiple intracerebral lesions underwent stereotactic serial biopsies for brain lesions at the Neurosurgery Department, Tanta University Hospital. All the stereotactic biopsies were obtained under local anesthesia using Riechert–Mundinger (RM) system or Cosman–Roberts–Wells (CRW) system.

Results

The histopathological diagnosis revealed multifocal malignant gliomas in 43.75% of patients (18.75% anaplastic astrocytoma and 25% multiform glioblastoma) and metastatic tumor in 37.5% of patients (all were adenocarcinoma). In addition, 12.5% had multiple brain abscesses, and 6.25% had malignant lymphoma. We reported no mortality secondary to the surgical procedure.

Conclusions

Stereotactic biopsy is considered the best choice to allow histopathologic diagnosis of multiple brain lesions with minimal morbidity and no mortality. Histopathologic findings gained with stereotactic procedures guided the choice of proper treatment thus eliminating the hazards associated with blind treatments.

Revisiting the Role of Surgical Resection for Brain Metastasis

Brain metastasis (BM) is the most common type of brain tumor in adults. The contemporary management of BM remains challenging. Advancements in systemic cancer treatment have increased the survival of patients with cancer. Although the treatment of BM is still complicated, advances in radiotherapy, including stereotactic radiosurgery and chemotherapy, have improved treatment outcomes. Surgical resection is the traditional treatment for BM and its role in the surgical resection of BM has been well established. However, refinement of the surgical resection technique and strategy for BM is needed. Herein, we discuss the evolving role of surgery in patients with BM and the future of BM treatment.

Radiomic-Based MRI for Classification of Solitary Brain Metastases Subtypes From Primary Lymphoma of the Central Nervous System

BACKGROUND

Differential diagnosis of brain metastases subtype and primary central nervous system lymphoma (PCNSL) is necessary for treatment decisions. The application of machine learning facilitates the classification of brain tumors, but prior investigations into primary lymphoma and brain metastases subtype classification have been limited.

PURPOSE

To develop a machine-learning model to classify PCNSL, brain metastases with primary lung and non-lung origin.

STUDY TYPE

Retrospective.

POPULATION

A total of 211 subjects with pathologically confirmed PCNSL or brain metastases (training cohort 168 and testing cohort 43).

FIELD STRENGTH/SEQUENCE

A 3.0 T axial contrast-enhanced T1-weighted spin-echo inversion recovery sequence (T1WI-CE), axial T2-weighted fluid-attenuation inversion recovery sequence (T2FLAIR) ASSESSMENT: Several machine-learning models (support vector machine, random forest, and K-nearest neighbors) were built with least absolute shrinkage and selection operator (LASSO) using features from T1WI-CE, T2FLAIR, and clinical. The model with the highest performance in the training cohort was selected to differentiate lesions in the testing cohort. Then, three radiologists conducted a two-round classification (with and without model reference) using images and clinical information from testing cohorts.

STATISTICAL TESTS

Five-fold cross-validation was used for model evaluation and calibration. Model performance was assessed based on sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC).

RESULTS

Twenty-five image features were selected by LASSO analysis. Random forest classifier was selected for its highest performance on the training set with an AUC of 0.73. After calibration, this model achieved an accuracy of 0.70 on the testing set. Accuracies of all three radiologists improved under model reference (0.49 vs. 0.70, 0.60 vs. 0.77, 0.58 vs. 0.72, respectively).

DATA CONCLUSION

The random forest model based on conventional MRI and clinical data can diagnose PCNSL and brain metastases subtypes (lung and non-lung origin). Model classification can help foster the diagnostic accuracy of specialists and streamline prognostication workflow.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

A transformer-based deep-learning approach for classifying brain metastases into primary organ sites using clinical whole-brain MRI images

Treatment decisions for brain metastatic disease rely on knowledge of the primary organ site and are currently made with biopsy and histology. Here, we develop a deep-learning approach for accurate non-invasive digital histology with whole-brain magnetic resonance imaging (MRI) data. Contrast-enhanced T1-weighted and fast spoiled gradient echo brain MRI exams (n = 1,582) were preprocessed and input to the proposed deep-learning workflow for tumor segmentation, modality transfer, and primary site classification into one of five classes. Tenfold cross-validation generated an overall area under the receiver operating characteristic curve (AUC) of 0.878 (95% confidence interval [CI]: 0.873,0.883). These data establish that whole-brain imaging features are discriminative enough to allow accurate diagnosis of the primary organ site of malignancy. Our end-to-end deep radiomic approach has great potential for classifying metastatic tumor types from whole-brain MRI images. Further refinement may offer an invaluable clinical tool to expedite primary cancer site identification for precision treatment and improved outcomes.

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.

Survival outcomes following craniotomy for intracranial metastases from an unknown primary

Introduction

Management of patients with intracranial metastases from an unknown primary tumor (CUP) varies compared to those with metastases of known primary tumor origin (CKP). The National Institute for Health and Care Excellence (NICE) recognizes the current lack of research to support the management of CUP patients with brain metastases. The primary aim was to compare survival outcomes of CKP and CUP patients undergoing early resection of intracranial metastases to understand the efficacy of surgery for patients with CUP.

Methods

A retrospective study was performed, wherein patients were identified using a pathology database. Data was collected from patient notes and trust information services. Surgically managed patients during a 10-year period aged over 18 years, with a histological diagnosis of intracranial metastasis, were included.

Results

298 patients were identified, including 243 (82.0%) CKP patients and 55 (18.0%) CUP patients. Median survival for CKP patients was 9 months (95%CI 7.475–10.525); and 6 months for CUP patients (95%CI 4.263–7.737, p = 0.113). Cox regression analyses suggest absence of other metastases (p = 0.016), age (p = 0.005), and performance status (p = 0.001) were positive prognostic factors for improved survival in cases of CUP. The eventual determination of the primary malignancy did not affect overall survival for CUP patients.

Conclusions

There was no significant difference in overall survival between the two groups. Surgical management of patients with CUP brain metastases is an appropriate treatment option. Current diagnostic pathways specifying a thorough search for the primary tumor pre-operatively may not improve patient outcomes.

The spectrum of malignancies presenting with neurological manifestations: A prospective observational study

Introduction

A neurological consultation is needed in nearly 45% of patients suffering from cancer. The present study was planned to evaluate the clinical, radiological and histopathological spectrum of patients with an underlying malignancy and presenting with a neurological complaint.

Materials and Methods

We prospectively evaluated all patients provisionally diagnosed either with a primary or secondary malignancy of the brain on the basis of clinical, radiological and/or histopathological features.

Results

A total of 155 patients were enrolled from a total of 4893 admissions done from January 2015 to July 2016. The common presenting symptoms were headache, back pain and paraparesis. Around 26% of patients presented with an altered sensorium, 19.4% with seizures and 21% had at least one cranial nerve involvement. The most common site of involvement was the brain noted in 49.7% of patients. Primary malignancies constituted 78 cases (50.7%) while secondary malignancies included 77 cases (49.3%). Magnetic resonance imaging (MRI) revealed 92 (59.4%) intra-axial lesions and 59 (38.1%) extra-axial lesions, with five cases having both. The most common diagnoses were intra-cerebral metastases and glioblastoma (intra-axial), and vertebral metastases and meningioma (extra-axial). Histopathological confirmation was obtained in 59 patients (38.1%) with 12 primary and 47 secondary lesions. Ten (6.45%) patients had an unknown primary with secondary metastases. The three most common histopathologically confirmed diagnoses were adenocarcinoma lung, plasma cell dyscrasia and adenocarcinoma prostate.

Conclusion

Primary neurological consultations with an unknown primary are common hence a high index of suspicion can prevent an inadvertent delay in the diagnosis and appropriate treatment of a malignant lesion. Developing a neuro-oncology register may help us in gaining more insight into such situations.

Advances in the management of brain metastases from cancer of unknown primary

Cancer of unknown primary accounts for 3-5% of all cancers for which an adequate investigation does not identify the primary tumor. The particular subset of brain metastasis in cancer of unknown primary (BMCUP) is a clinical challenge that lacks standardized diagnostic and therapeutic options. It is diagnosed predominantly in male patients in the sixth decade of age with complaints of headache, neurological dysfunction, cognitive and behavioral disturbances and seizures. The therapeutic approach to patients with BMCUP relies on local control and systemic treatment. Surgery or stereotactic radiosurgery and/or whole brain radiation therapy seems to be the cornerstone of the treatment approach to BMCUP. Systemic therapy remains essential as cancers of unknown primary are conceptually metastatic tumors. The benefits of chemotherapy were disappointing whereas those of targeted therapies and immune checkpoint inhibitors remain to be evaluated. In this Review, we address the advances in the diagnosis and treatment of BMCUP.

Radiomics of Brain MRI: Utility in Prediction of Metastatic Tumor Type

Purpose To investigate the feasibility of tumor type prediction with MRI radiomic image features of different brain metastases in a multiclass machine learning approach for patients with unknown primary lesion at the time of diagnosis. Materials and methods This single-center retrospective analysis included radiomic features of 658 brain metastases from T1-weighted contrast material-enhanced, T1-weighted nonenhanced, and fluid-attenuated inversion recovery (FLAIR) images in 189 patients (101 women, 88 men; mean age, 61 years; age range, 32-85 years). Images were acquired over a 9-year period (from September 2007 through December 2016) with different MRI units, reflecting heterogeneous image data. Included metastases originated from breast cancer (n = 143), small cell lung cancer (n = 151), non-small cell lung cancer (n = 225), gastrointestinal cancer (n = 50), and melanoma (n = 89). A total of 1423 quantitative image features and basic clinical data were evaluated by using random forest machine learning algorithms. Validation was performed with model-external fivefold cross validation. Comparative analysis of 10 randomly drawn cross-validation sets verified the stability of the results. The classifier performance was compared with predictions from a respective conventional reading by two radiologists. Results Areas under the receiver operating characteristic curve of the five-class problem ranged between 0.64 (for non-small cell lung cancer) and 0.82 (for melanoma); all P values were less than .01. Prediction performance of the classifier was superior to the radiologists' readings. Highest differences were observed for melanoma, with a 17-percentage-point gain in sensitivity compared with the sensitivity of both readers; P values were less than .02. Conclusion Quantitative features of routine brain MR images used in a machine learning classifier provided high discriminatory accuracy in predicting the tumor type of brain metastases. © RSNA, 2018 Online supplemental material is available for this article.

Double cystic brain metastasis in a patient with stable pancreatic intraductal papillary mucinous neoplasm

BACKGROUND

Brain metastases in pancreatic cancer are a rare condition and are usually seen in case of pancreatic adenocarcinoma. Only few cases of brain metastasis in patients affected by Intraductal papillary mucinous neoplasm (IPMN) are actually reported.

CASE DESCRIPTION

We report a patient diagnosed with double cystic brain lesions that the histological examination reveal to be consistent, with pancreatic metastasis. Our patient had an history shown of stable pancreatic IPMN which has never made the oncologist suspicious about neoplastic progression or degeneration into pancreatic carcinoma. Considering the rarity of these metastasis we did a literature review on the topic.

CONCLUSIONS

Despite rare, pancreatic origin of a cystic brain metastasis should considered in differential diagnosis in both patient with IPMN or patient with unknown primitive tumor.

Brain metastases: neuroimaging

Magnetic resonance imaging (MRI) is the cornerstone for evaluating patients with brain masses such as primary and metastatic tumors. Important challenges in effectively detecting and diagnosing brain metastases and in accurately characterizing their subsequent response to treatment remain. These difficulties include discriminating metastases from potential mimics such as primary brain tumors and infection, detecting small metastases, and differentiating treatment response from tumor recurrence and progression. Optimal patient management could be benefited by improved and well-validated prognostic and predictive imaging markers, as well as early response markers to identify successful treatment prior to changes in tumor size. To address these fundamental needs, newer MRI techniques including diffusion and perfusion imaging, MR spectroscopy, and positron emission tomography (PET) tracers beyond traditionally used 18-fluorodeoxyglucose are the subject of extensive ongoing investigations, with several promising avenues of added value already identified. These newer techniques provide a wealth of physiologic and metabolic information that may supplement standard MR evaluation, by providing the ability to monitor and characterize cellularity, angiogenesis, perfusion, pH, hypoxia, metabolite concentrations, and other critical features of malignancy. This chapter reviews standard and advanced imaging of brain metastases provided by computed tomography, MRI, and amino acid PET, focusing on potential biomarkers that can serve as problem-solving tools in the clinical management of patients with brain metastases.

The evolving clinical management of cerebral metastases

Concepts in the management of brain metastases are evolving. Until recently, brain metastases have been considered as a homogenous condition, managed with whole brain radiotherapy, surgical resection for large lesions and stereotactic radiosurgery for smaller lesions. Increasingly, specific systemic medical therapies are being used to treat brain metastases based on the primary site of disease. This disease specific management is causing a change in perspective about brain metastases and has led to improved survival for patients with primary disease subtypes amenable to tailored medical therapies. We review the recent literature to present evidence for the use of subtype specific medical therapies, advances in surgical resection techniques and stereotactic radiosurgery as the primary treatment modalities. The decline in use of whole brain radiotherapy as first line treatment is also discussed. Based on the recent literature, we propose a new management algorithm to reflect the progress in available options for tailoring disease specific treatments and support the change in paradigm to consider brain metastases as separate disease states based on the primary site of cancer rather than as a homogenous entity.

TIMP-1 overexpression in lung carcinoma enhances tumor kinetics and angiogenesis in brain metastasis

Tissue inhibitors of matrix metalloproteinase (TIMP) orchestrate many biologic activities, including inhibition of matrix metalloproteinase activity, activation of pro-matrix metalloproteinases, and regulation of cell proliferation, angiogenesis, and apoptosis induction. Tissue inhibitors of matrix metalloproteinase can play a protective role during tumor invasion and metastasis, but elevated TIMP messenger RNA levels have also been associated with aggressive cancers and poor clinical outcome. We examined the potential roles of TIMP-1 in H2009 lung adenocarcinoma cells and in cells transfected with a human TIMP-1-overexpressing vector (HB-6 and HB-1). Tumors resulting from the implantation of parental cell lines and transfected HB-1 cells into the brains of nude mice had a typical carcinoma profile, but human TIMP-1-overexpressing tumors showed enhanced tumor kinetics and focally more infiltrative features; vessel density assessed with anti-CD31 immunohistochemistry was also greater within HB-1 tumor implants. Similar effects on HB-6 and HB-1 cells versus parental cell lines and empty vector clones were observed in endothelial cell assays. Anchorage-independent growth and invasion through Matrigel were also increased in TIMP-1-overexpressing cells. Together, these results indicate tumor-promoting functions of TIMP-1 through alterations in angiogenesis, increased tumorigenicity, and invasive behavior. Although matrix metalloproteinase inhibition has been the traditionally identified function of TIMP-1, matrix metalloproteinase-independent interactions may contribute to the growth of metastatic carcinomas in the brain.

Molecular pathology via IR and Raman spectral imaging

During the last 15 years, vibrational spectroscopic methods have been developed that can be viewed as molecular pathology methods that depend on sampling the entire genome, proteome and metabolome of cells and tissues, rather than probing for the presence of selected markers. First, this review introduces the background and fundamentals of the spectroscopies underlying the new methodologies, namely infrared and Raman spectroscopy. Then, results are presented in the context of spectral histopathology of tissues for detection of metastases in lymph nodes, squamous cell carcinoma, adenocarcinomas, brain tumors and brain metastases. Results from spectral cytopathology of cells are discussed for screening of oral and cervical mucosa, and circulating tumor cells. It is concluded that infrared and Raman spectroscopy can complement histopathology and reveal information that is available in classical methods only by costly and time-consuming steps such as immunohistochemistry, polymerase chain reaction or gene arrays. Due to the inherent sensitivity toward changes in the bio-molecular composition of different cell and tissue types, vibrational spectroscopy can even provide information that is in some cases superior to that of any one of the conventional techniques.

Diagnostic immunohistochemistry of canine and feline intracalvarial tumors in the age of brain biopsies

The focus of immunohistochemistry as applied to nervous system tumors is in identifying the neoplasm present and evaluating margins between normal and neoplastic tissue. Although not always utilized by specialists in neuropathology, immunohistochemistry remains useful to resolve concerns about the differentiation and rate of tumor growth. The aims of this review are to discuss the utility of immunohistochemical reagents currently used in diagnosis of canine and feline intracalvarial tumors, to indicate the applicability of some tests currently used in human nervous system tumors for domestic species, and to evaluate a few less commonly used reagents. A panel of biomarkers is usually needed to confirm a diagnosis, with groups of reagents for leptomeningeal, intraparenchymal, and ventricular neoplasms. In the future, signature genetic alterations found among feline and canine brain tumors--as correlated prospectively with diagnosis, rate of enlargement, or response to treatment--may result in new immunohistochemical reagents to simplify the task of diagnosis. Prospective studies determining the type and proportion of stem cell marker expression on patient longevity are likely to be fruitful and suggest new therapies. Due to increased frequency of biopsy or partial resection of tumors from the living patient, biomarkers are needed to serve as accurate prognostic indicators and assist in determining the efficacy of developing therapeutic options in nervous system tumors of dogs and cats.

The role of CT body scans in the investigation of patients with newly diagnosed brain tumours

OBJECTIVE

In the UK approximately 4000 patients are diagnosed with brain tumours each year. Many patients undergo CT scans of the chest, abdomen and pelvis as part of the investigation of such tumours. We aimed to determine the value of CT body scans in patients with newly diagnosed brain tumours.

METHODS

We retrospectively reviewed the minutes of our neuro-oncology multidisciplinary team (MDT) meetings over a 12-month period to identify patients with a new radiological diagnosis of a brain tumour. Patients were divided into groups based on radiological diagnosis. Histology results were obtained for patients who underwent surgery. Results of CT body scans were obtained.

RESULTS

A total of 261 patients were identified. Sixty percent had radiological primary brain tumours and 40% had secondary brain tumours. Concordance between radiological and histological diagnoses was high (97% for radiological primary brain tumours, and 83% for radiological secondary brain tumours). CT body scans demonstrated primary lesions in 90% of radiological secondary brain tumours. Thirty-four percent of patients with a radiological diagnosis of primary brain tumour underwent CT body scans. The majority of these scans were normal (78%).

CONCLUSION

The ability of a specialist neuro-oncology MDT to correctly identify primary and secondary brain tumours on initial imaging is high. If the radiological diagnosis is of a secondary brain tumour, then CT body scans are essential. If the radiological diagnosis is of a primary brain tumour, then CT scans of the body are likely to add little to patient management.

Tumor margin identification and prediction of the primary tumor from brain metastases using FTIR imaging and support vector machines

Infrared spectroscopy enables the identification of tissue types based on their inherent vibrational fingerprint without staining in a nondestructive way. Here, Fourier transform infrared microscopic images were collected from 22 brain metastasis tissue sections of bladder carcinoma, lung carcinoma, mamma carcinoma, colon carcinoma, prostate carcinoma and renal cell carcinoma. The scope of this study was to distinguish the infrared spectra of carcinoma from normal tissue and necrosis and to use the infrared spectra of carcinoma to determine the primary tumor of brain metastasis. Data processing follows procedures that have previously been developed for the analysis of Raman images of these samples and includes the unmixing algorithm N-FINDR, segmentation by k-means clustering, and classification by support vector machines (SVMs). Upon comparison with the subsequent hematoxylin and eosin stained tissue sections of training specimens, correct classification rates of the first level SVM were 98.8% for brain tissue, 98.4% for necrosis and 94.4% for carcinoma. The primary tumors were correctly predicted with an overall rate of 98.7% for FTIR images of the training dataset by a second level SVM. Finally, the two level discrimination models were applied to four independent specimens for validation. Although the classification rates are slightly reduced compared to the training specimens, the majority of the infrared spectra of the independent specimens were assigned to the correct primary tumor. The results demonstrate the capability of FTIR imaging to complement histopathological tools for brain tissue diagnosis.

Time trends in survival from cancer of unknown primary: small steps forward

BACKGROUND

Cancer of unknown primary (CUP) is a fatal cancer for which incidence trends have changed but detailed survival trends remain unexplored. These could point out successful diagnostic and therapeutic approaches. We investigate survival trends in CUP according to histology, locations of metastases and site-specific causes of death.

PATIENTS AND METHODS

A total of 20,523 CUP patients with nodal and extranodal metastases were identified from the Swedish Cancer Registry. Hazard ratios (HRs) were estimated, comparing three different time periods (1987-1993, 1994-2000 and 2001-2008) with respect to histological subtype, CUP location and the cause of death.

RESULTS

Survival for patients with CUP increased over the study period (HR=0.91 [95% confidence interval (CI): 0.78-0.84], p<0.001 for trend). Adenocarcinoma was the only histology associated with increased survival (0.78 [0.74-0.82], p<0.001 for trend). Survival was improved most clearly for CUP of the pelvis (0.55 [0.36-0.83]), peritoneum (0.58 [0.53-0.65]) and nervous system (0.46 [0.29-0.72]). Survival improved substantially in patients with ovarian (0.57 [0.46-0.70]), peritoneal (0.39 [0.24-0.65]) and biliary system cancers (0.67 [0.52-0.87]). Kaplan-Meier curves showed significant survival gains for all CUP and adenocarcinoma patients (p<0.001).

CONCLUSIONS

Over time, survival for patients with CUP increased for adenocarcinoma and for CUP of the pelvis, peritoneum and nervous system. Survival trends in CUP may be related to (1) similar trends in other common metastatic tumours, particularly pancreatic and hepatobiliary cancers, which are common 'hidden' primaries for CUP, (2) earlier detection and (3) advances in the management of metastatic cancers. The improvement in survival at specific locations suggests true therapeutic gains.

Diagnostic segregation of human brain tumours using Fourier-transform infrared and/or Raman spectroscopy coupled with discriminant analysis

The most common initial treatment received by patients with a brain tumour is surgical removal of the growth. Precise histopathological diagnosis of brain tumours is to some extent subjective. Furthermore, currently available diagnostic imaging techniques to delineate the excision border during cytoreductive surgery lack the required spatial precision to aid surgeons. We set out to determine whether infrared (IR) and/or Raman spectroscopy combined with multivariate analysis could be applied to discriminate between normal brain tissue and different tumour types (meningioma, glioma and brain metastasis) based on the unique spectral "fingerprints" of their biochemical composition. Formalin-fixed paraffin-embedded tissue blocks of normal brain and different brain tumours were de-waxed, mounted on low-E slides and desiccated before being analyzed using attenuated total reflection Fourier-transform IR (ATR-FTIR) and Raman spectroscopy. ATR-FTIR spectroscopy showed a clear segregation between normal and different tumour subtypes. Discrimination of tumour classes was also apparent with Raman spectroscopy. Further analysis of spectral data revealed changes in brain biochemical structure associated with different tumours. Decreased tentatively-assigned lipid-to-protein ratio was associated with increased tumour progression. Alteration in cholesterol esters-to-phenylalanine ratio was evident in grade IV glioma and metastatic tumours. The current study indicates that IR and/or Raman spectroscopy have the potential to provide a novel diagnostic approach in the accurate diagnosis of brain tumours and have potential for application in intra-operative diagnosis.

Cancer of unknown primary site

Cancer of unknown primary site (CUP) is a well recognised clinical disorder, accounting for 3-5% of all malignant epithelial tumours. CUP is clinically characterised as an aggressive disease with early dissemination. Diagnostic approaches to identify the primary site include detailed histopathological examination with specific immunohistochemistry and radiological assessment. Gene-profiling microarray diagnosis has high sensitivity, but further prospective study is necessary to establish whether patients' outcomes are improved by its clinical use. Metastatic adenocarcinoma is the most common CUP histopathology (80%). CUP patients are divided into subsets of favourable (20%) and unfavourable (80%) prognosis. Favourable subsets are mostly given locoregional treatment or systemic platinum-based chemotherapy. Responses and survival are similar to those of patients with relevant known primary tumours. Patients in unfavourable subsets are treated with empirical chemotherapy based on combination regimens of platinum or taxane, but responses and survival are generally poor.

A study of patients with brain metastases as the initial manifestation of their systemic cancer in a Chinese population

To investigate the clinical characteristics of patients with brain metastases as the initial manifestation of their systemic cancer in a Chinese population, a retrospective study of 254 such patients admitted to Huashan Hospital, Fudan University, Shanghai, China between January 1, 2003 and December 30, 2008 was performed. Data were collected to determine the features of this group (i.e., manifesting signs and symptoms, imaging studies, extracerebral metastases, primary tumor sites, initial diagnosis, and survival data). Common symptoms included headache and motor impairment. The distribution of brain metastases paralleled blood flow, and the majority of brain metastases were located in the cerebral hemispheres. Magnetic resonance imaging (MRI) was more sensitive than computed tomography (CT) for confirming presence of brain lesions. This distinct clinical entity exhibited high rates of misdiagnosis at initial presentation. Pathology varied, and adenocarcinomas were most commonly observed. Underlying primary tumors were identified in 84.2% of patients, most often located in lung (71.7%), followed by digestive tract. Chest CT had high yield. Sixty-two patients presented with silent extracerebral metastases at initial presentation. Median survival time was 15 months (95% confidence interval, 12.2-17.8 months). Survival rates for 1, 2, and 5 years were 59.2%, 23.2%, and 15.1%, respectively. Contrast-enhanced MRI had high yield for detection of brain metastases. Adenocarcinoma was the most common histologic type. Given the high frequency of primary lung tumors and the sensitivity of chest CT, chest CT should be a part of the initial screen of primary site with brain metastases as the initial manifestation. Metastatic dissemination of malignancy to the brain as the initial manifestation is generally associated with dismal prognosis, with the exception of a minority who experience long survival.

Gene expression profiles help identify the tissue of origin for metastatic brain cancers

BACKGROUND

Metastatic brain cancers are the most common intracranial tumor and occur in about 15% of all cancer patients. In up to 10% of these patients, the primary tumor tissue remains unknown, even after a time consuming and costly workup. The Pathwork Tissue of Origin Test (Pathwork Diagnostics, Redwood City, CA, USA) is a gene expression test to aid in the diagnosis of metastatic, poorly differentiated and undifferentiated tumors. It measures the expression pattern of 1,550 genes in these tumors and compares it to the expression pattern of a panel of 15 known tumor types. The purpose of this study was to evaluate the performance of the Tissue of Origin Test in the diagnosis of primary sites for metastatic brain cancer patients.

METHODS

Fifteen fresh-frozen metastatic brain tumor specimens of known origins met specimen requirements. These specimens were entered into the study and processed using the Tissue of Origin Test. Results were compared to the known primary site and the agreement between the two results was assessed.

RESULTS

Fourteen of the fifteen specimens produced microarray data files that passed all quality metrics. One originated from a tissue type that was off-panel. Among the remaining 13 cases, the Tissue of Origin Test accurately predicted the available diagnosis in 12/13 (92.3%) cases.

DISCUSSION

This study demonstrates the accuracy of the Tissue of Origin Test when applied to predict the tissue of origin of metastatic brain tumors. This test could be a very useful tool for pathologists as they classify metastatic brain cancers.

Comparison of 1H-MRS-detected metabolic characteristics in single metastatic brain tumors of different origin

Various types of intracranial metastases exhibit different growth patterns, which can be reflected in their metabolic characteristics and investigated noninvasively by proton magnetic resonance spectroscopy (1H-MRS). The objective of the present study was comparison of the 1H-MRS-detected metabolic parameters in brain metastases of different origin. Twenty-five patients (15 men and 10 women; mean age, 62.0 years) with single, previously nontreated metastatic brain tumors were investigated by long-echo single-voxel volume-selected 1H-MRS. The primary cancer was located in the lungs (10 cases), colon and rectum (8 cases), breast (3 cases), kidney (2 cases), prostate (1 case), and cardiac muscle (1 case). Comparison of clinical and radiological variables, including type of tumor contrast enhancement and extension of peritumoral edema, did not disclose statistically significant differences in metastatic brain tumors of different origin. At the same time, comparison of 1H-MRS-detected metabolic characteristics revealed that metastases of colorectal carcinoma have greater content of mobile lipids (Lip) compared to other neoplasms. In conclusion, high Lip content in the viable brain metastases of colorectal carcinoma can be used as an additional diagnostic clue for noninvasive identification of these tumors and should be taken into consideration in cases of 1H-MRS-based differentiation of their recurrence and radiation-induced necrosis after radiosurgical or radiotherapeutic treatment.

Brain metastasis of non-small cell lung cancer presenting as sensorineural hearing loss and vertigo

We report a case of lung cancer with multiple metastases to the brain and internal auditory canal. A 59-year-old man complained about persistent and progressive vertigo for 3 weeks with rapidly developing left-sided hearing loss and tinnitus. Bilateral intact eardrums and unsteady gait were noted on physical examination. There was no nystagmus. Pure tone audiometry showed left-sided sensorineural hearing loss. Magnetic resonance imaging of the brain revealed multiple intracranial tumors, including of the left-side internal auditory canal, which were interpreted as seeding of metastatic malignancy. Computed tomographic and bronchoscopic biopsy identified an asymptomatic primary pulmonary adenocarcinoma in the right upper lobe of the lungs. This was a rare case of asymptomatic primary pulmonary adenocarcinoma with brain metastases presenting with sudden hearing loss and vertigo.

Supraclavicular lymph node metastases of unknown origin: HPV-typing identifies the primary tumour

Cancers of unknown primary origin (CUP) account for 0.5-10% of all malignancies. CUP patients with metastases have a median survival of approximately 6 months, despite therapy. Identification of the primary tumour site may offer the opportunity of a specific and more efficient treatment. The case of a 45-year-old woman with supraclavicular lymph node metastases of a squamous cell CUP is reported. A staging laparoscopy with multiple biopsies and a loop diathermy excision of the cervix were performed. Human papillomavirus (HPV)-testing in the tissues revealed the tumour cells as metastases of an occult cervical cancer. Primary platin-based chemotherapy combined with paclitaxel leads to a complete apparative remission. Twelve months later, staging positron emission tomography with 2-[18F]fluoro-2-deoxy-D-glucose in combination with computed tomography identified an isolated left renal lymph node metastasis. The patient received targeted radiation therapy, combined with cisplatin. To date, 19 months after diagnosis, she is doing well without any evidence of disease. The presented case report addresses the difficulties involving the identification of CUP. HPV-DNA is found in over 95% of cervical cancers. As the presented case illustrates, testing for this virus DNA in human tissues can be a useful diagnostic tool in patients with CUP where cervical cancer is the possible primary tumour.

Surgical Therapies in Brain Metastasis

Brain metastases are the most common intracranial tumors in adults and source of the most common neurological complications of systemic cancer. The treatment approach to brain metastases differs essentially from treatment of systemic metastases due to the unique anatomical and physiological characteristics of the brain. Surgery and radiosurgery are important components in the complex treatment of brain metastases and can prolong survival and improve the quality of life (QOL). Aggressive intervention may be indicated for selected patients with well-controlled systemic cancer and good performance status in whom central nervous system (CNS) disease poses the greatest threat to functionality and survival. In this review the respective roles of surgery and radiosurgery, patient selection, general prognostic factors and tailoring of optimal surgical management strategies for cerebral metastases are discussed.

Prognosis in patients presenting with brain metastasis from an undiagnosed primary tumor

OBJECT

The aim of this study was to test the validity of the hypothesis that patients in whom brain metastasis is the first indication of an undiagnosed primary tumor have a better chance of survival than similar patients with a known primary lesion.

METHODS

Between January 1983 and December 1998, 342 patients with computed tomography-diagnosed brain metastases were treated at a single institution. Information on potential prognostic factors, including primary diagnosis status, was collected retrospectively. Univariate and multivariate analyses were performed to identify prognostic factors related to survival. Survival was not statistically different between patients with an undiagnosed primary (UDP) lesion and those with a diagnosed primary (DP) tumor (6 and 4.5 months, respectively; p = 0.097). In the UDP group (122 patients [36%]), survival was not affected by the eventual identification of the primary disease (p = 0.905). The median survival for the entire population was 5.2 months, with 1-, 2-, and 3-year survival rates of 25, 11, and 4%, respectively. Prognostic factors for the overall population included treatment (p < 0.0001), an age less than 65 years (p = 0.004), discharge status (p < 0.001), absence of systemic metastasis (p = 0.036), and asymptomatic cerebral metastasis (p = 0.05).

CONCLUSIONS

Treatment modality was the most significant independent variable affecting survival in patients with brain metastases. Eventual identification of a primary tumor does not affect overall survival; therefore, delaying therapeutic intervention in pursuit of a primary diagnosis may not be appropriate. Data in this study failed to demonstrate a statistically significant difference in survival between patients with UDP and those with DP lesions, on first presenting with brain metastases.

Immunohistochemical Analysis of Metastatic Neoplasms of the Central Nervous System

Metastatic neoplasms to the central nervous system are often encountered in the practice of surgical neuropathology. It is not uncommon for patients with systemic malignancies to present to medical attention because of symptoms from a brain metastasis and for the tissue samples procured from these lesions to represent the first tissue available to study a malignancy from an unknown primary. In general surgical pathology, the evaluation of a metastatic neoplasm of unknown primary is a very complicated process, requiring knowledge of numerous different tumor types, reagents, and staining patterns. The past few years, however, have seen a remarkable refinement in the immunohistochemical tools at our disposal that now empower neuropathologists to take an active role in defining the relatively limited subset of neoplasms that commonly metastasize to the central nervous system. This information can direct imaging studies to find the primary tumor in a patient with an unknown primary, clarify the likely primary site of origin in patients who have small tumors in multiple sites without an obvious primary lesion, or establish lesions as late metastases of remote malignancies. Furthermore, specific treatments can begin and additional invasive procedures may be prevented if the neuropathologic evaluation of metastatic neoplasms provides information beyond the traditional diagnosis of "metastatic neoplasm." In this review, differential cytokeratins, adjuvant markers, and organ-specific antibodies are described and the immunohistochemical signatures of metastatic neoplasms that are commonly seen by neuropathologists are discussed.

Oncologic emergencies: diagnosis and treatment

Patients with malignancies are subject to developing a unique set of complications that require emergent evaluation and treatment. With the increasing incidence of cancer in the general population and improved survival, these emergencies will be more frequently encountered. Physicians must be able to recognize these conditions and institute appropriate therapy after a focused initial evaluation. The approach to definitive therapy is commonly multidisciplinary, involving surgeons, radiation oncologists, medical oncologists, and other medical specialists. Prompt interventions can be lifesaving and may spare patients considerable morbidity and pain. In this review, we discuss the diagnosis of and initial therapy for common emergencies in hematology and oncology.

Identification of primary tumors of brain metastases by SIMCA classification of IR spectroscopic images

Brain metastases are secondary intracranial lesions which occur more frequently than primary brain tumors. The four most abundant types of brain metastasis originate from primary tumors of lung cancer, colorectal cancer, breast cancer and renal cell carcinoma. As metastatic cells contain the molecular information of the primary tissue cells and IR spectroscopy probes the molecular fingerprint of cells, IR spectroscopy based methods constitute a new approach to determine the origin of brain metastases. IR spectroscopic images of 4 by 4 mm2 tissue areas were recorded in transmission mode by a FTIR imaging spectrometer coupled to a focal plane array detector. Unsupervised cluster analysis revealed variances within each cryosection. Selected clusters of five IR images with known diagnoses trained a supervised classification model based on the algorithm soft independent modeling of class analogies (SIMCA). This model was applied to distinguish normal brain tissue from brain metastases and to identify the primary tumor of brain metastases in 15 independent IR images. All specimens were assigned to the correct tissue class. This proof-of-concept study demonstrates that IR spectroscopy can complement established methods such as histopathology or immunohistochemistry for diagnosis.