scholarly journals Initial symptoms and diagnostic delay in children with brain tumors at a single institution in Japan

2020 ◽  
Author(s):  
Yuji Yamada ◽  
Daiki Kobayashi ◽  
Keita Terashima ◽  
Chikako Kiyotani ◽  
Ryuji Sasaki ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Diagnostic Delay ◽  
Visual Outcome ◽  
Neurological Impairment ◽  
Tumor Location ◽  
Medical Consultation ◽  
Low Grade ◽  
Initial Symptoms ◽  
Diagnostic Interval

Abstract Background A prolonged interval between onset of symptoms and diagnosis of childhood brain tumor is associated with worse neurological outcomes. The objectives of this study are to determine factors contributing to diagnostic delay and to find an interventional focus for further reduction in the interval between symptom onset and diagnosis in Japan. Methods We retrospectively analyzed 154 patients younger than 18 years with newly diagnosed brain tumors who visited our institution from January 2002 to March 2013. Results The median age at diagnosis was 6.2 years and the median total diagnostic interval (TDI) was 30 days. Patients with low-grade tumors and cerebral midline tumor location had significantly long TDI. Durations between the first medical consultation and diagnosis (diagnostic interval, DI) were exceedingly longer for patients with visual, hearing, or smelling abnormalities as the first symptom (median, 303 days). TDI and DI of patients who visited ophthalmologists or otolaryngologist for the first medical consultation were significantly longer. Among these patients, longer DI was associated with worse visual outcome. Conclusion Raising awareness of brain tumor diagnosis among ophthalmologists and otolaryngologists may reduce diagnostic delay and may improve the neurological impairment of children with brain tumors in Japan.

scholarly journals NCOG-42. INITIAL PRESENTATION AND OUTPATIENT VISIT COMPLIANCE OF INMATES WITH BRAIN TUMORS

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii138-ii138
Author(s):  
Iyad Alnahhas ◽  
Appaji Rayi ◽  
Yasmeen Rauf ◽  
Shirley Ong ◽  
Pierre Giglio ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Civil Liberties ◽  
Delayed Diagnosis ◽  
Low Grade ◽  
Small Series ◽  
Initial Symptoms ◽  
The Ohio State University ◽  
American Civil Liberties Union ◽  
Lost To Follow Up

Abstract INTRODUCTION While advocacy for inmates with cancer has recently gained momentum, little is known about management of brain tumors in inmates. Delays in acknowledging or recognizing nonspecific initial symptoms can lead to delayed diagnosis and treatment. Inmates with cancer are reported to either be ignored or receive substandard care due in part to cost or logistics (American Civil Liberties Union; ASCO Post 2018). METHODS In this retrospective study, we identified inmates with gliomas seen in the Ohio State University Neuro-oncology Center between 1/1/2010-4/20/2019. RESULTS Twelve patients were identified. Median age at presentation was 39.5 years (range 28-62). Eleven patients were Caucasian and one was African American. Diagnoses included glioblastoma (GBM) (n=6), anaplastic astrocytoma (n=1), anaplastic oligodendroglioma (n=1), low-grade astrocytoma (n=3) and anaplastic pleomorphic xanthroastrocytoma (n=1). Patients were more likely to present early after seizures or focal neurologic deficits (9/12) than after headaches alone. Patients with GBM started RT 12-71 days after surgery (median 34.5). One patient’s post-RT MRI was delayed by a month and another with GBM had treatment held after 4 cycles of adjuvant temozolomide (TMZ) due to “incarceration issues”. For one patient who received adjuvant TMZ, the facility failed to communicate with the primary team throughout treatment. Two patients suffered significant nausea while on chemotherapy due to inability to obtain ondansetron in prison, or due to wrong timing. 7/12 (58%) patients were lost to follow-up for periods of 3-15 months during treatment. Three patients refused adjuvant treatment. CONCLUSIONS Although this is a small series, our results highlight the inequities and challenges faced by inmates with gliomas who are more likely to forego treatments or whose incarceration prevents them from keeping appropriate treatment and follow-up schedules. Additional studies are needed to define and address these deficiencies in the care of inmates with brain tumors and other cancers.

IBRDM: An Intelligent Framework for Brain Tumor Classification Using Radiomics- and DWT-based Fusion of MRI Sequences

2022 ◽  
Vol 22 (1) ◽  
pp. 1-30
Author(s):  
Rahul Kumar ◽  
Ankur Gupta ◽  
Harkirat Singh Arora ◽  
Balasubramanian Raman
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Performance Metrics ◽  
Tumor Classification ◽  
Training Dataset ◽  
Tumor Segmentation ◽  
Discrete Wavelet ◽  
Low Grade ◽  
Brain Tumor Segmentation ◽  
Mri Sequences

Brain tumors are one of the critical malignant neurological cancers with the highest number of deaths and injuries worldwide. They are categorized into two major classes, high-grade glioma (HGG) and low-grade glioma (LGG), with HGG being more aggressive and malignant, whereas LGG tumors are less aggressive, but if left untreated, they get converted to HGG. Thus, the classification of brain tumors into the corresponding grade is a crucial task, especially for making decisions related to treatment. Motivated by the importance of such critical threats to humans, we propose a novel framework for brain tumor classification using discrete wavelet transform-based fusion of MRI sequences and Radiomics feature extraction. We utilized the Brain Tumor Segmentation 2018 challenge training dataset for the performance evaluation of our approach, and we extract features from three regions of interest derived using a combination of several tumor regions. We used wrapper method-based feature selection techniques for selecting a significant set of features and utilize various machine learning classifiers, Random Forest, Decision Tree, and Extra Randomized Tree for training the model. For proper validation of our approach, we adopt the five-fold cross-validation technique. We achieved state-of-the-art performance considering several performance metrics, 〈 Acc , Sens , Spec , F1-score , MCC , AUC 〉 ≡ 〈 98.60%, 99.05%, 97.33%, 99.05%, 96.42%, 98.19% 〉, where Acc , Sens , Spec , F1-score , MCC , and AUC represents the accuracy, sensitivity, specificity, F1-score, Matthews correlation coefficient, and area-under-the-curve, respectively. We believe our proposed approach will play a crucial role in the planning of clinical treatment and guidelines before surgery.

scholarly journals Macroscopic fluorescence-lifetime imaging of NADH and protoporphyrin IX improves the detection and grading of 5-aminolevulinic acid-stained brain tumors

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mikael T. Erkkilä ◽  
David Reichert ◽  
Johanna Gesperger ◽  
Barbara Kiesel ◽  
Thomas Roetzer ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Fluorescence Lifetime ◽  
Tumor Tissue ◽  
Aminolevulinic Acid ◽  
Protoporphyrin Ix ◽  
Low Grade ◽  
Wide Field ◽  
Fluorescence Lifetime Imaging ◽  
Lifetime Imaging

AbstractMaximal safe tumor resection remains the key prognostic factor for improved prognosis in brain tumor patients. Despite 5-aminolevulinic acid-based fluorescence guidance the neurosurgeon is, however, not able to visualize most low-grade gliomas (LGG) and infiltration zone of high-grade gliomas (HGG). To overcome the need for a more sensitive visualization, we investigated the potential of macroscopic, wide-field fluorescence lifetime imaging of nicotinamide adenine dinucleotide (NADH) and protoporphyrin IX (PPIX) in selected human brain tumors. For future intraoperative use, the imaging system offered a square field of view of 11 mm at 250 mm free working distance. We performed imaging of tumor tissue ex vivo, including LGG and HGG as well as brain metastases obtained from 21 patients undergoing fluorescence-guided surgery. Half of all samples showed visible fluorescence during surgery, which was associated with significant increase in PPIX fluorescence lifetime. While the PPIX lifetime was significantly different between specific tumor tissue types, the NADH lifetimes did not differ significantly among them. However, mainly necrotic areas exhibited significantly lower NADH lifetimes compared to compact tumor in HGG. Our pilot study indicates that combined fluorescence lifetime imaging of NADH/PPIX represents a sensitive tool to visualize brain tumor tissue not detectable with conventional 5-ALA fluorescence.

scholarly journals Cerebrospinal Fluid MicroRNA Signatures as Diagnostic Biomarkers in Brain Tumors

Cancers ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1546 ◽  
Author(s):  
Alena Kopkova ◽  
Jiri Sana ◽  
Tana Machackova ◽  
Marek Vecera ◽  
Lenka Radova ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Low Grade ◽  
Tumor Type ◽  
Tumor Patients ◽  
Primary Tumors ◽  
Mirna Profiling ◽  
Tumor Types ◽  
Cns Malignancies

Central nervous system (CNS) malignancies include primary tumors that originate within the CNS as well as secondary tumors that develop as a result of metastatic spread. Circulating microRNAs (miRNAs) were found in almost all human body fluids including cerebrospinal fluid (CSF), and they seem to be highly stable and resistant to even extreme conditions. The overall aim of our study was to identify specific CSF miRNA patterns that could differentiate among brain tumors. These new biomarkers could potentially aid borderline or uncertain imaging results onto diagnosis of CNS malignancies, avoiding most invasive procedures such as stereotactic biopsy or biopsy. In total, 175 brain tumor patients (glioblastomas, low-grade gliomas, meningiomas and brain metastases), and 40 non-tumor patients with hydrocephalus as controls were included in this prospective monocentric study. Firstly, we performed high-throughput miRNA profiling (Illumina small RNA sequencing) on a discovery cohort of 70 patients and 19 controls and identified specific miRNA signatures of all brain tumor types tested. Secondly, validation of 9 candidate miRNAs was carried out on an independent cohort of 105 brain tumor patients and 21 controls using qRT-PCR. Based on the successful results of validation and various combination patterns of only 5 miRNA levels (miR-30e, miR-140, let-7b, mR-10a and miR-21-3p) we proposed CSF-diagnostic scores for each tumor type which enabled to distinguish them from healthy donors and other tumor types tested. In addition to this primary diagnostic tool, we described the prognostic potential of the combination of miR-10b and miR-196b levels in CSF of glioblastoma patients. In conclusion, we performed the largest study so far focused on CSF miRNA profiling in patients with brain tumors, and we believe that this new class of biomarkers have a strong potential as a diagnostic and prognostic tool in these patients.

scholarly journals GENE-03. SPECIFIC SIGNATURES OF microRNA IN CEREBROSPINAL FLUID OF PATIENTS WITH PRIMARY BRAIN TUMORS AND METASTASES

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi98-vi98
Author(s):  
Radim Jancalek ◽  
Martin Smrcka ◽  
Alena Kopkova ◽  
Jiri Sana ◽  
Marek Vecera ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Czech Republic ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Brain Metastases ◽  
Independent Set ◽  
Low Grade ◽  
Primary Brain Tumors ◽  
Csf Analysis ◽  
Different Levels

Abstract Cerebrospinal fluid (CSF) baths extracellular environment of the central nervous system, and thus, it is ideal source of tumor diagnostic biomarkers like microRNAs (miRNAs), short non-coding RNAs involved in the pathogenesis of many cancers. As dysregulated levels of brain tumor specific miRNAs have been already observed in CSF, analysis of CSF miRNAs in brain tumor patients might help to develop new diagnostic platform. Next-Generation sequencing (NGS) was performed for analysis of small RNAs in 89 CSF samples taken from 32 glioblastomas (GBM), 14 low-grade gliomas (LGG), 11 meningiomas, 13 brain metastases and 19 non-tumor donors. Subsequently, according to NGS results levels of 10 miRNAs were measured in independent set of CSF samples (41 GBM, 44 meningiomas, 12 brain metastases and 20 non-tumor donors) using TaqMan Advanced miRNA Assays. NGS analysis revealed 22, 12 and 35 CSF miRNAs with significantly different levels in GBM, meningiomas, and brain metastases (adj.p < 0.0005, adj.p < 0.01, and adj.p < 0.005) respectively, in comparison with non-tumor CSF samples. Subsequent validation of selected CSF miRNAs has confirmed different levels of 7 miRNAs in GBM, 2 in meningiomas, and 2 in brain metastases compared to non-tumors. Panel of miR-30e-5p and miR-140-5p was able to distinguish brain metastases with 65% sensitivity and 100% specificity compared to non-tumor samples (AUC = 0.8167); panel of miR-21-3p and miR-196-5p classified metastatic patients with 78% sensitivity and 92 % specificity in comparison to GBM (AUC = 0.90854) and with 75% sensitivity and 83% specificity compared to meningiomas (AUC = 0.84848). We have observed that CSFs from patients with various primary brain tumors and metastases are characterized by specific miRNA signatures. This work was supported by the Ministry of Health, Czech Republic grant nr. NV18-03-00398 and the Ministry of Education, Youth and Sports, Czech Republic under the project CEITEC 2020 (LQ1601).

The distribution of nuclear DNA from human brain-tumor cells

1978 ◽  
Vol 49 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Takao Hoshino ◽  
Kazuhiro Nomura ◽  
Charles B. Wilson ◽  
Kathy D. Knebel ◽  
Joe W. Gray
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Human Brain ◽  
Dna Synthesis ◽  
Tumor Cells ◽  
Malignant Gliomas ◽  
Benign Tumors ◽  
Low Grade ◽  
Human Brain Tumor ◽  
Large Variability

✓ Flow cytometry (FCM) is a technique that measures the quantity of DNA contained in individual nuclei and records a frequency distribution of the DNA content per nucleus in the sampled cell population. Nuclei from a variety of human brain-tumor types were isolated by means of tissue grinding, purified by centrifugation through 40% sucrose (15 minutes at 4000 rpm), fixed with 10% formalin, stained with acriflavin-Feulgen, and analyzed by FCM. Profiles of DNA distribution in histologically benign tumors, such as meningiomas, pituitary adenomas, neuroblastomas, and low-grade astrocytomas, revealed a large diploid population (2C) with a few nuclei in DNA synthesis, as well as a small premitotic population (G2 cells) that contains a 4C DNA complement. In contrast, malignant gliomas, including glioblastomas, consist of more cells in DNA synthesis; these tumor cells show a highly variable distribution of ploidy consisting not only of diploid, and/or aneuploid, but also of triploid, tetraploid, and possibly octaploid populations. Also, a large variability between different regions of each tumor was always observed. In contrast, metastatic brain tumors, despite the fact that they contain a considerable number of cells undergoing DNA synthesis, demonstrate little variability within each individual tumor. The ability to rapidly characterize the cell populations of human brain tumors with FCM may enhance the effectiveness of their clinical management.

The economic impact of glioma survivorship

Neurology ◽  
2020 ◽  
Vol 95 (11) ◽  
pp. e1575-e1581
Author(s):  
Sameah A. Haider ◽  
Karam Asmaro ◽  
Steven N. Kalkanis ◽  
Ian Y. Lee ◽  
Michael Bazydlo ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Household Income ◽  
Medical Expenditure Panel Survey ◽  
Financial Burden ◽  
Tumor Location ◽  
Medical Expenditure ◽  
Fisher Exact Test ◽  
Low Grade ◽  
Annual Household Income ◽  
Initial Surgery

ObjectiveWe aimed to characterize the socioeconomic impact of glioma for patients with clinical and radiographic evidence of disease stability, using the standardized Medical Expenditure Panel Survey–Household Component (MEPS-HC).MethodsThe MEPS-HC questionnaire was used to investigate the degree of economic hardship referable to the patient's brain tumor and treatment. The questionnaire included demographic variables such as age at diagnosis, ethnicity, highest level of education, and annual household income. Descriptive statistics were used to characterize variables and between-group comparisons were evaluated using Fisher exact test.ResultsOf 127 prescreened patients, 89 of 107 eligible patients completed the survey. Pathology at diagnosis was predominantly low grade (60%). Most patients were insured at time of diagnosis (91%), married (76%), and employed (79%), with annual household incomes slightly higher than the national average. Despite this, nearly a quarter incurred debt referable to brain tumor care (24%), 53% required extended unpaid time off, and 46% retired or were no longer working. Financial burden and workforce morbidity were insensitive to tumor location, laterality, and annual household income. Patients with gross total resection at initial surgery were less likely to report ongoing limitations in daily activities (45% vs 83%, p = 0.004).ConclusionsEven in a population of stable, high-functioning glioma survivors, financial burden and workforce morbidity was ubiquitous across all tumor subtypes, treatment paradigms, and income levels.

scholarly journals Potential biomarkers of childhood brain tumor identified by proteomics of cerebrospinal fluid from extraventricular drainage (EVD)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Maurizio Bruschi ◽  
Andrea Petretto ◽  
Armando Cama ◽  
Marco Pavanello ◽  
Martina Bartolucci ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Residual Disease ◽  
S100 Protein ◽  
Therapy Response ◽  
Bioinformatic Analysis ◽  
Low Grade ◽  
Protein Biomarkers ◽  
Bodily Fluids

AbstractBrain tumors are the most common solid tumors in childhood. There is the need for biomarkers of residual disease, therapy response and recurrence. Cerebrospinal fluid (CSF) is a source of brain tumor biomarkers. We analyzed the proteome of waste CSF from extraventricular drainage (EVD) from 29 children bearing different brain tumors and 17 controls needing EVD insertion for unrelated causes. 1598 and 1526 proteins were identified by liquid chromatography-coupled tandem mass spectrometry proteomics in CSF control and brain tumor patients, respectively, 263 and 191 proteins being exclusive of either condition. Bioinformatic analysis revealed promising protein biomarkers for the discrimination between control and tumor (TATA-binding protein-associated factor 15 and S100 protein B). Moreover, Thymosin beta-4 (TMSB4X) and CD109, and 14.3.3 and HSP90 alpha could discriminate among other brain tumors and low-grade gliomas plus glyoneuronal tumors/pilocytic astrocytoma, or embryonal tumors/medulloblastoma. Biomarkers were validated by ELISA assay. Our method was able to distinguish among brain tumor vs non-tumor/hemorrhagic conditions (controls) and to differentiate two large classes of brain tumors. Further prospective studies may assess whether the biomarkers proposed by our discovery approach can be identified in other bodily fluids, therefore less invasively, and are useful to guide therapy and predict recurrences.

scholarly journals Prevalence of asymptomatic glioma and implications for survival

2020 ◽  
Author(s):  
Paula Province Warren ◽  
Mina Lobbous ◽  
Noah C. Peeri ◽  
Zachary J. Thompson ◽  
Reid C. Thompson ◽  
...  
Keyword(s):  
Brain Tumors ◽  
Brain Imaging ◽  
Medical Condition ◽  
Epidemiologic Study ◽  
Tumor Location ◽  
Low Grade ◽  
Who Grade ◽  
Low Grade Gliomas ◽  
Improve Patient Survival ◽  
Asymptomatic Patients

AbstractBackgroundBrain tumors can present as focal neurologic deficits (reflecting the tumor location) or generalized symptoms due to increased intracranial pressure. Occasionally, brain tumors can be found incidentally in asymptomatic patients or in patients with unrelated symptoms who undergo brain imaging. The term incidentaloma is used to refer to these imaging abnormalities.ObjectiveThe object of this study was to examine the prevalence and correlates of asymptomatic glioma in a large epidemiological study of brain tumors.MethodsThe analysis was based on a large series of patients with glioma (N = 1989) enrolled in a multicenter clinic-based epidemiologic study between 2005 and 2017. Patients were considered asymptomatic from the tumor, and thus as having an incidentally detected glioma (IDG), if the tumor was diagnosed during workup of injury or unrelated medical condition.ResultsA total of 32 of 1989 (1.6%) patients were asymptomatic at diagnosis. The leading indication for brain imaging in IDG was non-workplace injuries followed by medical workup for unrelated conditions. IDG was more prevalent in patients younger than 50 years of age (2.6% vs 1.0%). IDG was also more common in patients with low grade gliomas (4.7% for WHO grade II and 1.5% for WHO grade III) vs glioblastomas (0.6% in WHO grade IV).ConclusionThe present data suggest that gliomas may be found incidentally, especially among low grade gliomas. Studies of IDG may be useful as a proxy for early detection of tumor as a means to improve patient survival.

scholarly journals Brain tumor detection and classification using machine learning: a comprehensive survey

2021 ◽  
Author(s):  
Javaria Amin ◽  
Muhammad Sharif ◽  
Anandakumar Haldorai ◽  
Mussarat Yasmin ◽  
Ramesh Sundar Nayak
Keyword(s):  
Machine Learning ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Initial Phase ◽  
Tumor Detection ◽  
Tumor Location ◽  
Future Trends ◽  
Resonance Imaging ◽  
Quantum Machine Learning ◽  
Comprehensive Survey

AbstractBrain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial phase, it may lead to death. Despite many significant efforts and promising outcomes in this domain, accurate segmentation and classification remain a challenging task. A major challenge for brain tumor detection arises from the variations in tumor location, shape, and size. The objective of this survey is to deliver a comprehensive literature on brain tumor detection through magnetic resonance imaging to help the researchers. This survey covered the anatomy of brain tumors, publicly available datasets, enhancement techniques, segmentation, feature extraction, classification, and deep learning, transfer learning and quantum machine learning for brain tumors analysis. Finally, this survey provides all important literature for the detection of brain tumors with their advantages, limitations, developments, and future trends.

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