Clinical Manifestations and Diagnostic Imaging of Brain Tumors

Histological types of brain tumors diagnosed at the Kenyatta National Hospital between 2016 and 2019: a retrospective study

PURPOSE

To determine the histological types of brain tumors diagnosed at the Kenyatta National Hospital, Nairobi, Kenya.

METHODS

This retrospective study retrieved patient-archived records at the Kenyatta National Hospital for the period 2016-2019. The histological types of brain tumors were assessed according to age, sex, and the WHO classification for CNS tumors using the GNU PSPP version 1.6.2-g78a33 software. Results were presented in tables and figures.

RESULTS

During the study period, brain tumors appeared to increase gradually; however, there was a decline in 2018. During the study period, 345 brain tumor records were retrieved. Data on age were missing 33 records; hence, 312 records were included for age analyses. The mean age for the pediatrics and adults was 9 (± 5 SD) and 45 (± 14 SD) years, respectively. 88 (28.2%) and 224 (71.8%) tumors were diagnosed among pediatrics and adults, respectively. Most tumors, 60 (19.2%) were reported in patients aged ≤ 10 years, followed by 55 (17.6%), 48 (15.4%), and 47 (15.1%) in patients aged 31-40, 51-60, and 41-50, years, respectively. In both pediatrics and adults, most tumors were diagnosed in females aged ≤ 10 years and 31-40 years, respectively. Overall, two peaks were observed in patients aged 5-15 years and 40-45 years. Gliomas, 43 (48.9%) and medulloblastomas, 21 (23.9%) were the most common tumors in pediatrics, whereas meningiomas, 107 (47.8%) and gliomas, 70 (31.3%) were the most common tumors in adults. Most pediatric and adult tumors were benign with 50 (56.8%) and 157 (70.1%) cases, respectively. Low-grade gliomas and medulloblastomas were the commonest benign and malignant tumors among pediatrics, with 31 (62%) and 21 (55.3%) cases, respectively. Conversely, meningiomas and high-grade gliomas were the most common benign and malignant tumors in adults, with 106 (67.5%) and 44 (65.7%) cases, respectively.

CONCLUSION

This study highlights the existing burden of brain tumors in Kenya and data from KNH may be representative of the national burden of BTs. This study lays a foundation for subsequent clinical and epidemiological studies and emphasizes the need to adopt existing reporting standards to help realize a complete picture of the burden of brain tumors in Kenya.

Expression of Anaplastic Lymphoma Kinase in Astrocytic Tumors (Histopathological and Immunohistochemical Study)

BACKGROUND: Astrocytic tumors are the most common primary brain tumors. Glioblastoma is the most common astrocytic tumor representing the highest World Health Organization (WHO) grade (WHO grade IV) with poor prognosis and short survival time. Anaplastic lymphoma kinase (ALK) has a role in embryonic central nervous system development. ALK receptor is thought to contribute to nervous system function, repair, and metabolic homeostasis and is expressed in high-grade tumors like anaplastic large cell lymphoma that makes it a potential target for therapeutic intervention. AIM: This work aimed to examine the immunohistochemical expression of ALK in astrocytic tumors and its correlation with age, sex, clinical presentation, location, laterality, recurrence, and WHO grade to implicate possible therapeutic potential. METHODS: This retrospective study was conducted on sixty cases of archived, formalin-fixed, paraffin-embedded tissue blocks that included different subtypes and grades of astrocytic tumors. Immunohistochemistry using ALK monoclonal antibody was performed using a standard avidin-biotin-peroxidase system. RESULTS: Of the sixty cases, 57 (95%) cases were negative for ALK, while three (5%) cases are positive for ALK; all showed the strong intensity of expression. No statistically significant association was found between ALK expression and astrocytic tumors in addition to other clinical variables of the studied tumors. CONCLUSIONS: Most cases of astrocytic tumors showed negative ALK expression apart from three positive cases seen in higher WHO grades, especially gliosarcoma. The high number of negative cases for ALK in our study group suggests that ALK expression is not associated with a prognostic significance toward astrocytic tumors whatever its grade.

Epidemiologic and histologic characteristics of CNS lesions: a 20-year experience of a tertiary center in Lebanon

Aim:

Report the epidemiologic and histologic characteristics of CNS lesions in the Lebanese population.

Methods:

We conducted a retrospective study evaluating 2025 CNS lesions diagnosed between 1998 and 2017 in the pathology laboratory of a Lebanese tertiary center.

Results:

52.2% of patients were men with a median age of 50 years. The most frequent symptoms were epilepsy (22.5%), headache (20.6%) and motor impairment (19.9%). 90.7% of tumors were primary. Lung (35.6%) and breast (16.5%) were the most frequent primaries of metastases. 46.2% of primary CNS tumors were glial, predominantly astrocytic (56.4%), and (42.5%) were nonglial, predominantly meningeal tumors (58%).

Conclusion:

Compared with Western literature, the Lebanese population is characterized by a younger age of onset of brain tumors, a lower rate of meningiomas and a higher rate of gliomas.

Comparisons of the accuracy of radiation diagnostic modalities in brain tumor: A nonrandomized, nonexperimental, cross-sectional trial

Tumor morphology improved sensitivity, accuracy, and specificity of the diagnosis, but all diagnostic techniques have attenuation correction issues.To compare computed tomographic (CT), positron emission tomographic (PET), and magnetic resonance imaging (MRI) characteristics of patients with brain tumor in a Chinese setting.A nonrandomized, nonexperimental, cross-sectional trial.Jining No. 1 People's Hospital, China.In total, 127 patients who had clinically confirmed a brain tumor were included in the cross-sectional study. Patients were subjected to brain CT, MRI, and PET. The tumors resected after brain surgery were subjected to morphological diagnosis. Statistical analysis of data of surgically removed tumor and that of different methods of diagnosis was performed using Wilcoxon test following Tukey-Kramer test. Spearmen correlation was performed between diagnostic modalities and in vivo morphology. Results were considered significant at 99% of confidence level.The data of diameter and volume of tumor derived from CT (Spearman r = 0.9845 and 0.9706), and MRI (Spearman r = 0.955 and 0.2378) were failed to correlate with that of that of the surgically removed tumor. However, prediction of diameter and volume of the tumor by PET (Spearman r = 0.9922 and 0.9921) were correlated with that of the surgically removed tumor. CT and MRI were failed to quantified pituitary adenomas.The study was recommended PET for assessment of brain tumor.

Overview of PET Tracers for Brain Tumor Imaging

This article provides an overview of the key considerations for the development and application of molecular imaging agents for brain tumors and the major classes of PET tracers that have been used for imaging brain tumors in humans. The mechanisms of uptake, biological implications, primary applications, and limitations of PET tracers in neuro-oncology are reviewed. The available data indicate that several of these classes of tracers, including radiolabeled amino acids, have imaging properties superior to those of (18)F-fluorodeoxyglucose, and can complement contrast-enhanced magnetic resonance imaging in the evaluation of brain tumors.

(18)F-Flourodeoxy-Glucose PET/Computed Tomography in Brain Tumors: Value to Patient Management and Survival Outcomes

(18)F-flourodeoxy-glucose (FDG) PET/computed tomography (CT) is most useful in the evaluation of primary central nervous system (CNS) lymphoma, important in diagnosis, pretherapy prognosis, and therapy response evaluation. Utility in working up gliomas is less effective, and FDG PET/CT is most helpful when MR imaging is unclear. FDG avidity correlates with the grade of gliomas. FDG PET/CT can be used to noninvasively identify malignant transformation. Establishing this change in the disease process has significant effects on patient management and survival outcome.

Appearance of Meningioma on 99mTc-HMPAO SPECT: Correlation with MRI

On brain perfusion SPECT, a primary brain lesion presents as a localized defect that corresponds to the mass lesion. (99m)Tc-HMPAO images generally show a focal defect in the region of abnormality, whether containing necrotic tissue, recurrent tumor, or both. Further characterization with MR imaging is needed to confirm the diagnosis, as demonstrated in this case report.

The comprehensive neuro-oncology data repository (CONDR): a research infrastructure to develop and validate imaging biomarkers

BACKGROUND

Advanced imaging methods have the potential to serve as quantitative biomarkers in neuro-oncology research. However, a lack of standardization of image acquisition, processing, and analysis limits their application in clinical research. Standardization of these methods and an organized archival platform are required to better validate and apply these markers in research settings and, ultimately, in clinical practice.

OBJECTIVE

The primary objective of the Comprehensive Neuro-oncology Data Repository (CONDR) is to develop a data set for assessing and validating advanced imaging methods in patients diagnosed with brain tumors. As a secondary objective, informatics resources will be developed to facilitate the integrated collection, processing, and analysis of imaging, tissue, and clinical data in multicenter clinical trials. Finally, CONDR data and informatics resources will be shared with the research community for further analysis.

METHODS

CONDR will enroll 200 patients diagnosed with primary brain tumors. Clinical, imaging, and tissue-based data are obtained from patients serially, beginning with diagnosis and continuing over the course of their treatment. The CONDR imaging protocol includes structural and functional sequences, including diffusion- and perfusion-weighted imaging. All data are managed within an XNAT-based informatics platform. Imaging markers are assessed by correlating image and spatially aligned pathological markers and a variety of clinical markers.

EXPECTED OUTCOMES

CONDR will generate data for developing and validating imaging markers of primary brain tumors, including multispectral and probabilistic maps.

DISCUSSION

CONDR implements a novel, open-research model that will provide the research community with both open-access data and open-source informatics resources.

(1) H 2D MRSI tissue type analysis of gliomas

PURPOSE

To decompose 1H MR spectra of glioma patients into normal and abnormal tissue proportions for tumor classification and delineation.

METHODS

Anatomical imaging and 1H magnetic resonance spectroscopic imaging data have been acquired from 11 grade II and 13 grade IV glioma patients. LCModel was used to decompose the magnetic resonance spectroscopic imaging data into normal brain, grade II, and grade IV tissue proportions using a tissue type basis set. Simulations were conducted to evaluate the accuracy of the methodology. Results were visualized using colormaps and abnormality contours showing tumor grade and extent.

RESULTS

Simulations suggest that infiltrative tumor proportions as low as 20% can be identified at the typical 1H magnetic resonance spectroscopy signal-to-noise found in vivo. Tumor grading according to the highest estimated tumor grade within a lesion gave a classification accuracy of 86% discriminating between grade II and grade IV glioma. Voxels with significant proportions of tumor type spectra were found beyond the margins of contrast enhancement for most grade IV cases consistent with infiltration whereas the abnormality contours show that some tumors are confined within the hyperintensities shown by both post contrast T1 weighted and T2 weighted imaging.

CONCLUSION

LCModel can be used to decompose 1H MR spectra into proportions of normal and abnormal tissue to identify tumor extent, infiltration, and overall grade.