scholarly journals Neutrophil-to-Lymphocyte Ratio: Can It Be Used as an Adjunct Tool to Predict Histopathological Grade of Brain Tumor?

2019 ◽  
Vol 10 (04) ◽  
pp. 648-652
Author(s):  
K. G. Ashwath ◽  
Ashish Aggarwal ◽  
Kokkula Praneeth ◽  
Navneet Singla ◽  
Kirti Gupta
Keyword(s):  
Brain Tumor ◽  
Brain Tumors ◽  
Predictive Value ◽  
P Value ◽  
Low Grade ◽  
High Grade ◽  
Histopathological Grade ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
The Mean

Abstract Background Since histopathology is available only after surgery, clinical condition and radiological characters of the tumor are important factors on which a clinician counsels the patient of brain tumor to take a decision regarding the management. Neutrophil lymphocyte ratio (NLR), a marker of inflammation can be used as a prognostic marker to predict the survival in high-grade gliomas and metastases. We evaluated the utility of NLR as an adjunct tool in predicting the histopathological grade of brain tumors. Materials and Methods One hundred sixteen patients with a diagnosis of brain tumors planned for surgical excision or biopsy were enrolled in the study. NLR was estimated in the preoperative blood sample. Patients were grouped into low- and highgrade brain tumors and their mean NLRs were analyzed. Similar evaluation was carried out between the intra- and extra-axial tumors. Results Mean age of the study group was 40.14 years with 61 males. Seventy-eight patients had low-grade tumor and 38 patients had high-grade tumor. Sixty patients had extra-axial tumors and 56 patients had intra-axial tumors. The mean NLR of low-grade tumors was 1.68 ± 0.53 and that of high-grade tumors was 3.12 ± 0.74. NLR > 2.4 can be used to identify high-grade brain tumors with a sensitivity of 80%, specificity of 92%, positive predictive value of 82.1%, negative predictive value of 91%, an excellent impact with likelihood ratio (+) of 10.1, and an odds ratio of 54.1. The mean NLR of extra-axial tumors was 1.68 + 0.62 and that of intra-axial tumors was 2.64 ± 0.91. These observations were statistically significant with p-value < 0.05. Conclusions NLR is an easily available and inexpensive marker of systemic inflammation, which varies across different histopathological grades of brain tumors. Mean NLR is higher in high-grade tumors and also intra-axial tumors with a cutoff value of NLR > 2.4 and > 2.0, respectively.

scholarly journals Assessment of the Neutrophil Lymphocyte Ratio and Mean Platelet Volume in Pregnancy

2020 ◽  
Vol 5 (1) ◽  
pp. 85-93
Author(s):  
Rendy Singgih ◽  
Yohanes Firmansyah
Keyword(s):  
Roc Curve ◽  
Mean Platelet Volume ◽  
Statistical Tests ◽  
P Value ◽  
Platelet Volume ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Hypertension In Pregnancy ◽  
The Mean ◽  
In Pregnancy

Abstract Introduction:  Hypertension in pregnancy is a common complication that affects maternal and fetal morbidity and mortality. Comprehensive handling is needed to overcome the incidence of hypertension in pregnancy so that it does not get worse. The use of inflammatory markers is widely used as a predictor of the incidence of hypertension in pregnancy, especially preeclampsia. Neutrophil-lymphocyte ratio (NLR) and mean platelet volume (MPV) values are believed to predict the incidence of hypertension in pregnancy. Aim of study: The purpose of this study was to determine the ability of both the NLR and MPV values to predict the incidence of hypertension in pregnancy. Methods: This research is an analytic observational study using secondary data from medical records. The data were taken from the Cimacan Regional Hospital from January to December 2019. The variables were then tested statistically to see the difference in the mean. If there are significant results, the predictor's ability will be tested again with the ROC curve test. Results: The results of statistical tests between the normotensive pregnancy group and pregnancy with hypertension showed that the mean difference was significant in the NLR variable with P-value of 0.004 and MPV with a P-value of 0.005. Then the NLR and MPV values were tested again by the ROC Curve method. The AUC results on the NLR variable (AUC: 0.562 / p-value: 0.022) and MPV (AUC: 0.560 / p-value: 0.022). Conclusion: Although NLR and MPV had differences mean between the two groups, their ability to predict pregnancy with hypertension was very low.   Keywords: Pregnancy; Hypertension; Preeclampsia; NLR; MPV.

scholarly journals A Review on Brain Tumor Classification Methodologies

2019 ◽  
pp. 346-359 ◽  
Author(s):  
Bichitra Panda ◽  
Chandra Sekhar Panda
Keyword(s):  
Feature Extraction ◽  
Brain Tumor ◽  
Brain Tumors ◽  
Brain Mri ◽  
Tumor Classification ◽  
Low Grade ◽  
High Grade ◽  
Mr Images ◽  
The Brain

Brain tumor is one of the leading disease in the world. So automated identification and classification of tumors are important for diagnosis. Magnetic resonance imaging (MRI)is widely used modality for imaging brain. Brain tumor classification refers to classify the brain MR images as normal or abnormal, benign or malignant, low grade or high grade or types. This paper reviews various techniques used for the classification of brain tumors from MR images. Brain tumor classification can be divided into three phases as preprocessing, feature extraction and classification. As segmentation is not mandatory for classification, hence resides in the first phase. The feature extraction phase also contains feature reduction. DWT is efficient for both preprocessing and feature extraction. Texture analysis based on GLCM gives better features for classification where PCA reduces the feature vector maintaining the accuracy of classification of brain MRI. Shape features are important where segmentation has already been performed. The use of SVM along with appropriate kernel techniques can help in classifying the brain tumors from MRI. High accuracy has been achieved to classify brain MRI as normal or abnormal, benign or malignant and low grade or high grade. But classifying the tumors into more particular types is more challenging.

scholarly journals The prognostic value of neutrophil-lymphocyte ratio in acute pancreatitis

2016 ◽  
Vol 18 (3) ◽  
pp. 27
Author(s):  
Binit Katuwal ◽  
Sushil Kumar Shilpakar
Keyword(s):  
Acute Pancreatitis ◽  
University Teaching ◽  
Total Leucocyte Count ◽  
P Value ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Surgical Ward ◽  
The Mean ◽  
Marshall Score ◽  
One Year

Introduction and objective: Acute Pancreatitis (AP) is one of the leading causes of morbidity and mortality worldwide. In approximately a third of the patient with acute pancreatitis, severe pancreatitis may develop, producing progressive organ dysfunction caused by a systemic inflammatory response syndrome (SIRS). This study aimed to determine the correlation between Neutrophil Lymphocyte Ratio (NLR) and the severity of AP.Materials and Methods: All patients admitted in the Surgical Ward of Tribhuvan University Teaching Hospital with the diagnosis of AP were studied prospectively over a period of one year from January 2014 to January 2015. Total leucocyte count (TLC), neutrophil count, lymphocyte count and neutrophil lymphocyte ratio (NLR) at admission was recorded for each patient. Modified Marshall Score was determined at admission and at 48 hours. Severity of acute pancreatitis as defined by revised Atlanta Classification 2012 was taken into account.Results: A total of 79 patients of AP were included in the study. Among them, 38 % were categorized as having severe AP according to the revised Atlanta classification. There was a weak positive correlation of NLR to severity of AP which was statistically significant. The mean NLR was high in higher severity grades of AP (p-value < 0.05). The cutoff NLR of 8.02 showed sensitivity of 60 %, specificity of 60.4 %, PPV of 48.6 % and NPV of 70.7 %.Conclusion: NLR may be useful as an easy and reliable prognostic marker for the severity and complications of acute pancreatitis.

scholarly journals P08.03 Separation and divorce after the diagnosis of child’s brain tumor

2019 ◽  
Vol 21 (Supplement_3) ◽  
pp. iii37-iii37
Author(s):  
I Sardi ◽  
M Censullo ◽  
M Rousseau ◽  
M Guidi ◽  
F Giordano ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Data Analysis ◽  
Brain Tumors ◽  
Traumatic Experience ◽  
Low Grade ◽  
High Grade ◽  
Italian Regions ◽  
The Family ◽  
High Grade Gliomas ◽  
Child's Brain

Abstract BACKGROUND The diagnosis of a child’s brain tumor is a terrible situation for every member of the family. Numerous are the case of separations and divorces in Italy after a diagnosis of a child’s cancer. In particular, it happens with parents of children affected with brain tumor, being the most frequent solid tumor and the first cause of a tumor child’s death. The crisis related to the discovery of a tumor consists of four phases: shock, reaction, processing and re-orientation. It can happen that the diagnosis, experienced as a traumatic experience, can unite the family members as well as separate them. If there is already a process of family disintegration, a trauma can be a cause for breakup. The aim of our study was to investigate the possible correlation between brain tumor diagnosis in children and parental separations/divorces. MATERIAL AND METHODS We considered 427 patients afferent from 2012 to 2018 to the Neuro-Oncology Unit of the Meyer Children’s Hospital. Brain tumors are the 55–60% of all the tumors of our hospital, with an extra-regionality greater than 65%. The data analysis was conducted through information obtained directly from the families during follow-up visits or by telephone interviews. RESULTS Consistent with literature data in our series, the most frequent brain tumors were low-grade gliomas medulloblastomas, high-grade gliomas, ependymomas, midline diffuse gliomas, craniopharyngiomas, germ cell tumors and other rare pediatric tumors. The population was divided in 16 females and 18 males from different Italian regions: 65% from Central Italy, 23% from the South and Islands, 12% from the North. Data analysis showed 34 cases of separation and/or divorce, equal to 7% of our whole population, during treatment and more frequently at the end of treatment or after death. The median age of the 34 patients at the diagnosis of brain tumor was 9.5 years (range 1–19 years), with a higher percentage of cases of separations (41%) for parents of patients aged 10 years-14 years; 7 were the cases of separation and/or divorce when the diagnosis of brain tumor was made around 12–48 months after the child birth. CONCLUSION The diagnosis of a child’s brain tumor can generate stress in the family leading to different reactions, such as conflicts between parents or a real family crisis. The results of our study suggest a possible correlation between the diagnosis of a child’s brain tumor and the cases of separation and/or divorce. High risk medulloblastomas and high-grade gliomas that are likely to have a shorter path due to the unfavorable prognosis of the disease, appear to be the pathologies more often related to situations of family disputes. However, further investigations are necessary to verify the trend emerged from our study respect to the normal population.

Apparent diffusion coefficient values and non-homogeneity of diffusion in brain tumors in diffusion-weighted MRI

2019 ◽  
Vol 61 (2) ◽  
pp. 244-252
Author(s):  
Sedigheh Basirjafari ◽  
Masoud Poureisa ◽  
Babak Shahhoseini ◽  
Mohammad Zarei ◽  
Saeideh Aghayari Sheikh Neshin ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Standard Deviation ◽  
Brain Tumors ◽  
Region Of Interest ◽  
Low Grade ◽  
High Grade ◽  
Ki 67 ◽  
Apparent Diffusion ◽  
Adc Values ◽  
The Mean

Background The values that have been received from apparent diffusion coefficient (ADC) maps of diffusion-weighted magnetic resonance imaging (DW-MRI) might play a vital role in evaluating tumors and their grading scale. Purpose To investigate the predictive role of this heterogeneity in brain tumor pathologies and its correlation with Ki-67. Material and Methods A total of 124 patients with brain tumors underwent brain MRI with gadolinium injection. ADC and standard deviation of each lesion have been obtained from manual localization of the region of interest on the ADC map. A receiver operating characteristic analysis was conducted to determine the minimum cut-off values of the mean ADC and mean standard deviation of ADC maps having the highest sensitivity and specificity to differentiate high-grade and low-grade tumors. Results Mean ADC values in the region of interest were significantly lower for malignant tumors (grade IV and metastasis) than grade I brain tumors, while a higher mean standard deviation was observed. In a more detailed comparison of tumor groups, the mean standard deviation of the ADC for glioblastoma multiform was significantly higher than meningioma grade I ( P < 0.001) and metastasis was significantly higher than grade III and IV astrocytic tumors ( P = 0.004). The analysis of Ki-67 proliferation index and mean ADC values in gliomas showed a significant inverse correlation between the parameters (r = –0.0429, P < 0.001) and direct correlation between Ki-67 and mean standard deviation of the ADC (r = 0.551, P < 0.001). As an index for the ADC to differentiate high-grade and low-grade tumors, the cut-off values of 1.40*10−3 mm2/s for mean ADC and 45*10−3 mm2/s for mean standard deviation have the highest combination of sensitivity, specificity, and area under the curve. Conclusion The mean value and standard deviation of the ADC could be considered for differentiating between low-grade and high-grade brain tumors, as two available non-invasive methods.

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.

Prediction of Troponin elevation in Non- ST Acute Coronary Syndrome Patients presenting to The Emergency Department Using Neutrophil-lymphocyte ratio

QJM ◽  
2021 ◽  
Vol 114 (Supplement_1) ◽  
Author(s):  
Sarah Mohamed Mahmoud ◽  
Bassam Sobhy ◽  
Ramy Raymond
Keyword(s):  
Emergency Department ◽  
Acute Coronary Syndrome ◽  
Complete Blood Count ◽  
P Value ◽  
Troponin Elevation ◽  
Positive Group ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Coronary Syndrome

Abstract Background The neutrophil–lymphocyte ratio (NLR) is considered an independent predictor of mortality and myocardial infarction (MI) in stable coronary artery disease (SCAD). Also NLR have prognostic value in patients with acute coronary syndromes (ACSs). However the diagnostic power of NLR in patients suspected of ACS is still under study Objective is to determine the ability of neutrophil-lymphocyte ratio to predict troponin elevation in patients presenting to emergency department with acute coronary syndrome Material and Methods From June 2018 to March 2019, 100 patients were enrolled who presented to the ER with NST-ACS. Patients were divided into 2 groups based upon the troponin positivity in the 12- to 24-hour follow-up. Baseline Complete blood count with calculation of NLR is done Results The study population was divided into 2 groups: troponin- negative group (n = 50) and troponin-positive group (n = 50). Mean age was 55.8 ± 11.3. 77% of the patients were male. No significance difference in the level of hemoglobin, WBCs and platelets between the 2 groups. The neutrophil count was significantly higher in the troponin-positive group (p &lt; 0.001). The median admission. NLR was significantly higher in the troponin-positive group (2 vs. 3.9, P &lt; 0.001). A cutoff point of 3.4 for NLR measured on admission had 84% sensitivity and 84% specificity in predicting follow-up troponin positivity. A highly significant correlation was found between NLR and level of troponin change (p value &lt;0.01) Conclusion NLR can be used as a diagnostic tool in the differentiation of patients with acute coronary syndrome. NLR is a non-expensive, simple and available parameter that can be used in diagnosis of NSTEMI.

The Prognostic Significance of DNA Topoisomerase II-alpha (Ki-S1), p21/Cip-1, and p27/Kip-1 Protein Immunoexpression in Oligodendrogliomas

2001 ◽  
Vol 125 (7) ◽  
pp. 892-898 ◽  
Author(s):  
Andrey Korshunov ◽  
Andrey Golanov
Keyword(s):  
Topoisomerase Ii ◽  
World Health ◽  
Low Grade ◽  
Image Analyzer ◽  
High Grade ◽  
Dna Topoisomerase Ii ◽  
Survival Times ◽  
Topoisomerase Ii Alpha ◽  
Dna Topoisomerase ◽  
The Mean

Abstract Objective.—To evaluate a possible association between clinical outcome of patients with oligodendroglioma and expression of 2 cyclin-dependent kinase inhibitors, p21/Cip-1 (p21) and p27/Kip-1 (p27), and of DNA topoisomerase II-alpha (Ki-S1), which has been recently used as a marker of cellular proliferation. Design.—Ninety-one specially selected patients with cerebral oligodendrogliomas treated with surgery and radiotherapy were studied retrospectively. Tumor specimens were immunohistochemically examined with antibodies to p21, p27, and Ki-S1. A computerized color image analyzer was used to count immunostained nuclei. Results.—The mean Ki-S1 labeling index (LI) was found to be significantly prominent for World Health Organization (WHO) high-grade tumors (9.5% vs 3.2% for WHO low-grade tumors). In contrast, the mean p27 LI was significantly higher for low-grade tumors (43.3% vs 25.7% for high-grade tumors). The number of p21-positive cases and the mean p21 LI were found to be relatively equal for low- and high-grade tumors. For low-grade oligodendrogliomas, the progression-free and overall survival times were found to be significantly shorter for tumors with p27 LIs less than 20%. For high-grade oligodendrogliomas, survival times were significantly reduced for tumors with Ki-S1 LIs greater than 10%. Regression-tree analysis identified 4 groups of oligodendrogliomas with distinctly different outcomes: (1) 32 patients with low-grade tumors and p27 LIs greater than 20%; (2) 14 patients with low-grade tumors and p27 LIs less than 20%; (3) 25 patients with high-grade tumors and Ki-S1 LIs less than 10%; and (4) 20 patients with high-grade tumors and Ki-S1 LIs greater than 10%. Conclusions.—Immunoreactivity for Ki-S1 and p27 was found to be useful for further subdividing oligodendroglioma prognoses among low-grade and high-grade tumors. It seems unlikely that p21 immunohistochemistry will be of value for determining clinical outcomes for patients with oligodendrogliomas.

scholarly journals Genetic Abnormalities, Clonal Evolution, and Cancer Stem Cells of Brain Tumors

2018 ◽  
Vol 6 (4) ◽  
pp. 85 ◽  
Author(s):  
Ugo Testa ◽  
Germana Castelli ◽  
Elvira Pelosi
Keyword(s):  
Brain Tumors ◽  
Clonal Evolution ◽  
Pediatric Brain Tumors ◽  
Genetic Alterations ◽  
World Health ◽  
Driver Mutations ◽  
Low Grade ◽  
High Grade ◽  
Genetic Profiling ◽  
Health Organization

Brain tumors are highly heterogeneous and have been classified by the World Health Organization in various histological and molecular subtypes. Gliomas have been classified as ranging from low-grade astrocytomas and oligodendrogliomas to high-grade astrocytomas or glioblastomas. These tumors are characterized by a peculiar pattern of genetic alterations. Pediatric high-grade gliomas are histologically indistinguishable from adult glioblastomas, but they are considered distinct from adult glioblastomas because they possess a different spectrum of driver mutations (genes encoding histones H3.3 and H3.1). Medulloblastomas, the most frequent pediatric brain tumors, are considered to be of embryonic derivation and are currently subdivided into distinct subgroups depending on histological features and genetic profiling. There is emerging evidence that brain tumors are maintained by a special neural or glial stem cell-like population that self-renews and gives rise to differentiated progeny. In many instances, the prognosis of the majority of brain tumors remains negative and there is hope that the new acquisition of information on the molecular and cellular bases of these tumors will be translated in the development of new, more active treatments.

scholarly journals Cellular Inflammatory Indices in Hospitalized Nigerian COVID-19 Patients

2021 ◽  
pp. 19-26
Author(s):  
Jeremiah Adeyemi Akinwumi ◽  
Fabian Victory Edem ◽  
Ganiyu Olatunbosun Arinola
Keyword(s):  
Blood Cell ◽  
Lymphocyte Count ◽  
White Blood Cells ◽  
Calculated Data ◽  
Inflammatory Cells ◽  
Neutrophil Lymphocyte Ratio ◽  
Lymphocyte Ratio ◽  
Inflammatory Index ◽  
Cell Counts ◽  
The Mean

The pandemicity of coronavirus disease 2019 (COVID-19) necessitated its novel biomarkers in prognosis and monitoring in low resource settings. Changes in total white blood cell counts have been associated with the progression of diseases. This study determined the prognostic value of some cellular inflammatory cells and their indices in relation to duration of hospital admission, gender, and age of COVID-19 patients. This longitudinal and case–control study determined blood cell components (total white blood cells (TWBC), neutrophil, lymphocyte, monocyte, and platelet) and inflammatory indices (neutrophil lymphocyte ratio [NLR], lymphocyte monocyte ratio [LMR], platelet lymphocyte ratio [PLR], derived NLR [DNLR], and systemic immune inflammatory index [SII]) in 95 symptomatic hospitalized COVID-19 patients and 45 COVID-19 free controls. These parameters were related to age, sex, and days of admission of the patients. Blood samples obtained were analyzed using hematological autoanalyzer (Sysmex XN-450) and indices calculated. Data were analyzed using the Statistical Package for the Social Sciences (SPSS Inc., USA) version 20.0. The mean platelet count (P = 0.016) and PLR (P = 0.000) were significantly lower while TWBC counts (P = 0.013) were significantly increased in COVID-19 patients compared with control. The mean TWBC count (P = 0.030) and SII (P = 0.029) were significantly increased while lymphocyte count (P = 0.015) and LMR (P = 0.026) were significantly decreased in COVID-19 patients at discharge compared with COVID-19 patients at admission. The mean neutrophil count (P = 0.048), PLR (P = 0.015), and SII (P = 0.022) were significantly lower while mean lymphocyte count (P = 0.026) was significantly higher in COVID-19 patients aged <40 years compared with patients aged ?40 years. This study concluded that inflammatory response is a phenomenon in COVID-19 patients especially in patients ?40 years of age and that this inflammation persist till discharge, though gender has no influence on cellular inflammatory indices of COVID-19 patients.

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