Grading Of Tumors Research Articles

Association of CT findings with invasive subtypes and the new grading system of lung adenocarcinoma

To predict the differentiation between invasive growth patterns and new grades of lung adenocarcinoma (LAC) using computed tomography (CT). The CT features of 180 surgically treated LAC patients were compared retrospectively to pathological invasive subtypes and tumour grades as defined by the new grading system published in 2021 by the World Health Organization. Two radiologists reviewed the images semi-quantitatively and independently. Univariable and multivariable regression models were built from the statistical means of their assessments to predict invasive subtypes and grades. The area under the curve (AUC) calculation was used to select the best models. The Youden index was applied to determine the cut-off values for radiological parameters. The acinar/papillary patterns were associated with ill-defined margins, lower consolidation/tumour ratio and air bronchogram. The solid growth pattern was associated with a well-defined margin and hypodensity, and the micropapillary (MP) subtype with spiculation. From Grades 1 to 3, the amount of air bronchogram decreased and the consolidation/tumour ratio increased. In the sub-analyses, the best model for differentiating Grade 2 from Grade 1 had the following CT features: solid/subsolid type, consolidation/tumour ratio, well-defined margin, and air bronchogram (AUC=0.783) and Grade 3 from Grade 2: size of the consolidation part/whole tumour ratio, size of the consolidation part, and well-defined margin (AUC=0.759). The interobserver agreements between the two radiologists varied between 0.67 and 0.98. Air bronchogram, consolidation/tumour ratio, and well-defined margin are among the best imaging findings to discriminate between both invasive subtypes and the new grades in LAC.

Detection of Isocitrate Dehydrogenase (IDH-1), Epidermal Growth Factor Receptor (EGFR), P53 and C-erbB2/HER2 Mutation in Glial Tumour

Introduction: In the last decade, several molecular pathways in gliomagenesis have been discovered, with each involving a unique set of molecular alterations. IDH1 has become a diagnostic tool in the latest 2016 WHO Classification. The tumour protein, p53, is involved in the IDH-mutant arm, observed in astrocytoma and oligodendroglioma (grades II and III), and secondary glioblastoma. Meanwhile, EGFR and c-erbB2/HER2 were postulated to be expressed in higher-grade glioma as the disease progresses. Methods: A retrospective cross-sectional study was conducted to evaluate the association of IDH1, EGFR, p53 and c-erbB2/HER2 protein expression in astrocytic and oligodendroglial tumours with clinicopathological data in HUSM, Kota Bharu, Kelantan, Malaysia. This study examined 61 archived formalin-fixed paraffin-embedded (FFPE) tissue blocks of patients diagnosed with glioma. The immunohistochemistry (IHC) test was performed using antibodies, IDH1, EGFR, p53 and c-erbB2/HER2, and the protein expressions were evaluated microscopically. Finally, the association between IDH1, p53, EGFR and c-erbB2/HER with the clinicopathology variables were statistically analysed. Results: A total of 61 glioma cases consisting of 36 (59%) males and 25 (41%) females were included in this study. The IDH1 protein was positively expressed in 14 cases (23%), P53 was highly expressed in 26 cases (42.6%), and EGFR was substantially observed in 34 cases (55.7%). For glioblastoma cases, IDH1 was expressed in two cases (11.1%), EGFR in 14 cases (77.7%), p53 in 12 cases (66.7%) and c-erbB2 in 1 case (5.6%). Significant associations exist between IDH1, p53 and EGFR expressions in astrocytoma and oligodendroglial tumours with the histological types and WHO tumour grades. Conclusion: Recently, our knowledge regarding the genetics of central nervous system (CNS) tumors has expanded; hence, newer antibodies or molecular markers, which can be used in IHC, are continuously being developed. These antibodies, IDH1, p53 and EGFR markers are useful for diagnostic, prognostication and therapeutic. In addition, help to clarify the nature of cellular maturation, tissue differentiation, and tumor progression to be considered as an integral part of WHO classification of CNS tumours.

Automated classification of breast cancer histologic grade using multiphoton microscopy and generative adversarial networks

Histological grade is one of the most powerful prognostic factors for breast cancer and impacts treatment decisions. However, a label-free and automated classification system for histological grading of breast tumors has not yet been developed. In this study, we employed label-free multiphoton microscopy (MPM) to acquire subcellular-resolution images of unstained breast cancer tissues. Subsequently, a deep-learning algorithm based on the generative adversarial network (GAN) was introduced to learn a representation using only MPM images without the histological grade information. Furthermore, to obtain abundant image information and determine the detailed differences between MPM images of different grades, a multiple-feature discriminator network based on the GAN was leveraged to learn the multi-scale spatial features of MPM images through unlabeled data. The experimental results showed that the classification accuracies for tumors of grades 1, 2, and 3 were 92.4%, 88.6%, and 89.0%, respectively. Our results suggest that the fusion of multiphoton microscopy and the GAN-based deep learning algorithm can be used as a fast and powerful clinical tool for the computer-aided intelligent pathological diagnosis of breast cancer.

EMT Molecular Signatures of Pancreatic Neuroendocrine Neoplasms.

Neuroendocrine neoplasms (NENs) are relatively rare neoplasms occurring predominantly in the gastrointestinal tract and pancreas. Their heterogeneity poses challenges for diagnosis and treatment. There is a paucity of markers for characterisation of NEN tumours. For routine diagnosis, immunohistochemistry of the NEN-specific markers CgA and synaptophysin and the proliferation marker Ki-67 are used. These parameters, however, are qualitative and lack the capacity to fully define the tumour phenotype. Molecules of epithelial-mesenchymal transition (EMT) are potential candidates for improved tumour characterisation. Using qRT-PCR, we measured mRNA levels of 27 tumour markers, including 25 EMT-associated markers, in tumour tissue and matched non-tumour tissues for 13 patients with pancreatic NENs. Tissue from patients with three different grades of tumour had distinctly different mRNA profiles. Of the 25 EMT-associated markers analysed, 17 were higher in G3 tissue relative to matched non-tumour tissue, including CD14, CD24, CD31, CD44, CD45, CD56, CK6, CK7, CK13, CK20, NSE, CDX2, CgA, DAXX, PCNA, laminin and Ki-67. The differences in levels of seven EMT-associated markers, Ki-67, DAXX, CD24, CD44, vimentin, laminin and PDX1 plus CgA and NSE (neuroendocrine markers) enabled a distinct molecular signature for each tumour grade to be generated. EMT molecules differentially expressed in three tumour grades have potential for use in tumour stratification and prognostication and as therapeutic targets for treatment of neuroendocrine cancers, following validation with additional samples.

Grading of gliomas using transfer learning on MRI images.

Despite the critical role of Magnetic Resonance Imaging (MRI) in the diagnosis of brain tumours, there are still many pitfalls in the exact grading of them, in particular, gliomas. In this regard, it was aimed to examine the potential of Transfer Learning (TL) and Machine Learning (ML) algorithms in the accurate grading of gliomas on MRI images. Dataset has included four types of axial MRI images of glioma brain tumours with grades I-IV: T1-weighted, T2-weighted, FLAIR, and T1-weighted Contrast-Enhanced (T1-CE). Images were resized, normalized, and randomly split into training, validation, and test sets. ImageNet pre-trained Convolutional Neural Networks (CNNs) were utilized for feature extraction and classification, using Adam and SGD optimizers. Logistic Regression (LR) and Support Vector Machine (SVM) methods were also implemented for classification instead of Fully Connected (FC) layers taking advantage of features extracted by each CNN. Evaluation metrics were computed to find the model with the best performance, and the highest overall accuracy of 99.38% was achieved for the model containing an SVM classifier and features extracted by pre-trained VGG-16. It was demonstrated that developing Computer-aided Diagnosis (CAD) systems using pre-trained CNNs and classification algorithms is a functional approach to automatically specify the grade of glioma brain tumours in MRI images. Using these models is an excellent alternative to invasive methods and helps doctors diagnose more accurately before treatment.

Molecular phenotyping of malignant canine mammary tumours: Detection of high-risk group and its relationship with clinicomolecular characteristics.

Canine mammary gland tumours (CMTs) constitute the most common cancer in female dogs and comprise approximately 50% of all canine cancers. With the advent of high-throughput technologies such as microarray and next-generation sequencing, the molecular phenotyping (classification) of various cancers has been extensively developed. The present study used a canine RNA-sequencing dataset, namely GSE119810, to classify 113 malignant CMTs and 64 matched normal samples via an unsupervised hierarchical algorithm with a view to evaluating the association between the resulting subtypes (clusters) (n= 4) and clinical and molecular characteristics. Finally, a molecular classifier was developed, and it detected 1 high-risk molecular subtype in the training dataset (GSE119810) and 2 independent validation datasets (GSE20718 and GSE22516). Our results revealed four molecular subtypes (C2-C5) in malignant CMTs. Furthermore, the normal samples constituted a distinct group in the clustering analysis. Marked significant associations were observed between the molecular subtypes (especially C5) and clinical/molecular features, including positive lymphatic invasion, high tumour grades, histopathology diagnoses, short survival and high TP53 mutation rates (ps<.05). The high-risk subtype (C5) was further characterized through the development of a cell cycle-based gene signature, which comprised 37 proliferation-related genes according to the support vector machine algorithm. This signature identified the high-risk group in both training and validation datasets (ps<.001). In the validation analysis, our potential classifier robustly predicted patients with positive lymphatic invasion, metastases and short survival.

Histomorphological pattern of lesions of cystoscopic bladder biopsies in a tertiary center in Nepal- A retrospective descriptive study

Background: Bladder cancer accounts for 3% of all cancer diagnoses and is one of the most common cancers worldwide. Bladder tumors have different subtypes and behavioral patterns. This study is performed in the pathology department of Shree Birendra Hospital. It is a data review done on cystoscopic bladder biopsy results for the past 5 years to study the histomorphological patterns of various bladder lesions. Materials and Methods: This is a descriptive cross-sectional study done on cystoscopic bladder biopsy results. A hospital register-based retrospective study was conducted on the data of five years duration. The epidemiological parameters were calculated using Microsoft Excel. Results: A total of 56 cystoscopic biopsies were performed during the study period of 5 years. Among them, 45(80.36%) were male and 11(19.64%) were female. The peak incidence was seen in the age group 70-79 years (26.78%). The majority of the patients had neoplastic lesions (83.92%). The peak incidence of neoplastic lesions also belonged to the age group 70-79 years (31.19%). The most common malignant lesion was papillary urothelial carcinoma i.e. 45 cases (95.74 % among the neoplastic lesions and 80.36% among all the total bladder lesions) Conclusions: Among the bladder lesions that have undergone cystoscopic biopsies, urothelial carcinoma is the most common with male predominance. The early and definitive diagnosis with accurate grading and staging of bladder tumors can be done by histopathology. Early identification of bladder tumors has an impact on the therapeutic approach as well.

The Prediction of Survival Outcome and Prognosis Factor in Association with Comorbidity Status in Patients with Colorectal Cancer: A Research-Based Study.

Colorectal carcinoma (CRC) is rising exponentially in Asia, representing 11% of cancer worldwide. This study analysed the influence of CRC on patients’ life expectancy (survival and prognosis factors) via clinicopathology data and comorbidity status of CRC patients. Methodology: A retrospective study performed in HUSM using clinical data from the Surgery unit from 2015 to 2020. The demographic and pertinent clinical data were retrieved for preliminary analyses (data cleansing and exploration). Demographics and pathological characteristics were illustrated using descriptive analysis; 5-year survival rates were calculated using Kaplan–Meier methods; potential prognostic variables were analysed using simple and multivariate logistic regression analysis conducted via the Cox proportional hazards model, while the Charlson Comorbidity Scale was used to categorize patients’ disease status. Results: Of a total of 114 CRC patients, two-thirds (89.5%) were from Malay tribes, while Indian and Chinese had 5.3% each. The 50–69.9 years were the most affected group (45.6%). Overall, 40.4% were smokers (majorly male (95.7%)), 14.0% ex-smokers, and 45.6% non-smokers (p-value = 0.001). The Kaplan–Meier overall 5-year median survival time was 62.5%. From the outcomes, patients who were male and >70 years had metastasis present, who presented with per rectal bleeding and were classified as Duke C; and who has tumour in the rectum had the lowest survival rate. Regarding the prognosis factors investigated, “Gender” (adjusted hazard ratio (HR): 2.62; 95% CI: 1.56–7.81, p-value = 0.040), “Presence of metastases” (HR: 3.76; 95% CI: 1.89–7.32, p-value = 0.010), “Metastasis site: Liver” (HR: 5.04; 95% CI: 1.71–19.05, p-value = 0.039), “Lymphovascular permeation” (HR: 2.94; 95% CI: 1.99–5.92, p-value = 0.021), and “CEA-level” (HR: 2.43; 95% CI: 1.49–5.80, p-value = 0.001) remained significant in the final model for multiple Cox proportional hazard regression analyses. There was a significant mean association between tumour grades and the patient’s comorbidity status. Conclusions: Histopathological factors (gender, metastases presence, site of metastases, CEA level, and lymphovascular permeation) showed the best prognosis-predicting factors in CRC.

Highly specific selenium nanosystems for fluorescent image-guided rapid diagnosis and pathological grading of ovarian malignant tumors

Comprehensive surgical staging or optimal tumor cytoreductive surgery of malignant ovarian cancer directly affects disease prognosis. Therefore, a fluorescent selenium nanoparticle (Se@RGD/S2.2) decorated with cancer-targeting Arg-Gly-Asp (RGD) peptides and GCAGTTGATCCTTTGGATACCCTGG aptamer (S2.2) was developed for use as a diagnostic agent to achieve rapid, noninvasive diagnosis and visualization of microinvasive lesions during surgery for malignant ovarian cancer.

533 Readmission Rates After Elective Colorectal Cancer Surgery and Its Comparison to National Bowel Cancer Audit in 2019 (NBOCA 2019)

Abstract Background The NBOCA 2019 showed an overall 10.8% of patients had an unplanned readmission within 30 days of surgery (for both elective and emergency colonic resection (NBOCA, 2019). Aim To identify readmissions rates after elective colorectal cancer surgery in our hospital and comparing it to NBOCA 2019. Identifying reasons for readmissions. Method A single centre, retrospective, observational study was performed between January 2018 – January 2019. We included patients that required readmission to hospital following elective colorectal resections for cancer. Data was collected on patient demographics, primary operation, histopathology, stage, neo-adjuvant chemo/radiotherapy, date, and reason of readmission. Results Total of 123 patients had elective resection for colorectal cancer.13.8% (17/123) of these patients required readmissions. 70.6% (12/17) readmitted with 30 days of discharge, 29.4% (5/17) beyond 90 days of discharge. 58.8% (10/17) Of the operations that needed readmission were performed laparoscopically, with the most common primary operation resulting in readmission was LAR (52.9%, 9/17). Tumour grades using Dukes classification were A 41.1% (7/17), B 11.8% (2/17), C 35.2% (6/17), D 5.9% (1/17). Neo-adjuvant chemo/radiotherapy was given in 29.4% (5/17) of patients. Overall, the most common reason for admission was small bowel obstruction (SBO) and abdominal/pelvic collection, each by 23.5% (4/17), followed by wound dehiscence (11.8%, 2/17) and SSI (both deep and organ related) (11.8%, 2/17). Conclusions 13.8% of patients who underwent elective colorectal surgery for cancer were readmitted within 30 days of discharge. Further study is required to investigate more contributing factors to readmission, in order to formulate strategies to help prevent them.

1041 Impact of Spectral Contamination and Anatomical Location on Diagnostic Accuracy of Single-Voxel Spectroscopy in Pre-Operative Glioma Characterisation

Abstract Aim Single-voxel spectroscopy (SVS) discriminates amongst brain tumours by measuring metabolite variations reflective of malignant transformation. However, spectral contamination may affect diagnostic accuracy, impacting radiological opinion of regions of interest (ROI) required to determine extent of surgical resection. Method A single-centre, retrospective, observational study, including 93 SVS meaningfully interpretable examinations between 2012 and 2018. Accuracy of lesion classification was assessed by comparison of histological diagnosis as reference standards against discrimination between entities and tumour grades by SVS, with consideration for voxel location, volume, and proximity to the calvaria or ventricular system. Quantification of metabolites was recorded as ratios, and visual inspection, qualitative and descriptive analysis were undertaken. Results SVS demonstrated high entity accuracy (100%) but lower grade accuracy (87%), ranging from periventricular (73%) vs non-periventricular (90%), and subcalvarial (86%) vs subcortical (88%) voxels. CSF contamination caused metabolite dilution and/or enhanced lactate signals from sub-arachnoid or ventricular CSF, especially in areas of increased brain-skull distance; lipid contamination from peri-calvarial fat and subcutaneous tissue resulted in enhanced lipid signals neighbouring areas of increased brain-scalp distance. Misclassified lesions were located regions of increased cranial concavity, reduced cerebral cortical thickness and inappropriate outer volume suppression (OVS). Voxel volume variation had no impact across cerebral coordinates (p=0.605), calvaria proximity (p=0.127) or ventricular proximity (p=0.367). Conclusion Spectral contamination significantly impacted grade accuracy, with metabolite dilution and enhance lactate and lipids signals leading to radiological under- and overestimation of glioma grade, respectively, thus indicating that avoidance of contaminating tissues and OVS are pivotal to adequate spectral quality for diagnostic accuracy.

B0 Correction for 3T Amide Proton Transfer (APT) MRI Using a Simplified Two-Pool Lorentzian Model of Symmetric Water and Asymmetric Solutes.

Amide proton transfer (APT)-weighted MRI is a promising molecular imaging technique that has been employed in clinic for detection and grading of brain tumors. MTRasym, the quantification method of APT, is easily influenced by B0 inhomogeneity and causes artifacts. Current model-free interpolation methods have enabled moderate B0 correction for middle offsets, but have performed poorly at limbic offsets. To address this shortcoming, we proposed a practical B0 correction approach that is suitable under time-limited sparse acquisition scenarios and for B1 ≥ 1 μT under 3T. In this study, this approach employed a simplified Lorentzian model containing only two pools of symmetric water and asymmetric solutes, to describe the Z-spectral shape with wide and ‘invisible’ CEST peaks. The B0 correction was then performed on the basis of the fitted two-pool Lorentzian lines, instead of using conventional model-free interpolation. The approach was firstly evaluated on densely sampled Z-spectra data by using the spline interpolation of all acquired 16 offsets as the gold standard. When only six offsets were available for B0 correction, our method outperformed conventional methods. In particular, the errors at limbic offsets were significantly reduced (n = 8, p < 0.01). Secondly, our method was assessed on the six-offset APT data of nine brain tumor patients. Our MTRasym (3.5 ppm), using the two-pool model, displayed a similar contrast to the vendor-provided B0-orrected MTRasym (3.5 ppm). While the vendor failed in correcting B0 at 4.3 and 2.7 ppm for a large portion of voxels, our method enabled well differentiation of B0 artifacts from tumors. In conclusion, the proposed approach could alleviate analysis errors caused by B0 inhomogeneity, which is useful for facilitating the comprehensive metabolic analysis of brain tumors.

GEP-NET radiomics: a systematic review and radiomics quality score assessment.

The number of radiomics studies in gastroenteropancreatic neuroendocrine tumours (GEP-NETs) is rapidly increasing. This systematic review aims to provide an overview of the available evidence of radiomics for clinical outcome measures in GEP-NETs, to understand which applications hold the most promise and which areas lack evidence. PubMed, Embase, and Wiley/Cochrane Library databases were searched and a forward and backward reference check of the identified studies was executed. Inclusion criteria were (1) patients with GEP-NETs and (2) radiomics analysis on CT, MRI or PET. Two reviewers independently agreed on eligibility and assessed methodological quality with the radiomics quality score (RQS) and extracted outcome data. In total, 1364 unique studies were identified and 45 were included for analysis. Most studies focused on GEP-NET grade and differential diagnosis of GEP-NETs from other neoplasms, while only a minority analysed treatment response or long-term outcomes. Several studies were able to predict tumour grade or to differentiate GEP-NETs from other lesions with a good performance (AUCs 0.74-0.96 and AUCs 0.80-0.99, respectively). Only one study developed a model to predict recurrence in pancreas NETs (AUC 0.77). The included studies reached a mean RQS of 18%. Although radiomics for GEP-NETs is still a relatively new area, some promising models have been developed. Future research should focus on developing robust models for clinically relevant aims such as prediction of response or long-term outcome in GEP-NET, since evidence for these aims is still scarce. • The majority of radiomics studies in gastroenteropancreatic neuroendocrine tumours is of low quality. • Most evidence for radiomics is available for the identification of tumour grade or differentiation of gastroenteropancreatic neuroendocrine tumours from other neoplasms. • Radiomics for the prediction of response or long-term outcome in gastroenteropancreatic neuroendocrine tumours warrants further research.

Multiparametric Classification of Non-Muscle Invasive Papillary Urothelial Neoplasms: Combining Morphological, Phenotypical, and Molecular Features for Improved Risk Stratification.

Diagnosis and grading of non-invasive papillary urothelial tumors according to the current WHO classification poses some challenges for pathologists. The diagnostic reproducibility of separating low-grade and high-grade lesions is low, which impacts their clinical management. Whereas papillary urothelial neoplasms with low malignant potential (PUN-LMP) and low-grade papillary non-invasive carcinoma (LG-PUC) are comparable and show frequent local recurrence but rarely metastasize, high-grade papillary non-invasive carcinoma (HG-PUC) has a poor prognosis. The main objective of this work is to develop a multiparametric classification to unambiguously distinguish low-grade and high-grade tumors, considering immunohistochemical stains for p53, FGFR3, CK20, MIB-1, p16, p21 and p-HH3, and pathogenic mutations in TP53, FGFR3, TP53, ERCC2, PIK3CA, PTEN and STAG2. We reviewed and analyzed the clinical and histological data of 45 patients with a consensus diagnosis of PUN-LMP (n = 8), non-invasive LG-PUC (n = 23), and HG-PUC (n = 14). The proliferation index and mitotic count assessed with MIB-1 and P-HH3 staining, respectively correlated with grading and clinical behavior. Targeted sequencing confirmed frequent FGFR3 mutations in non-invasive papillary tumors and identified mutations in TP53 as high-risk. Cluster analysis of the different immunohistochemical and molecular parameters allowed a clear separation in two different clusters: cluster 1 corresponding to PUN-LMP and LG-PUC (low MIB-1 and mitotic count/FGFR3 and STAG2 mutations) and cluster 2, HG-PUC (high MIB-1 and mitosis count/CK20 +++ expression, FGFR3 WT and TP53 mutation). Further analysis is required to validate and analyze the reproducibility of these clusters and their biological and clinical implication.

Concordance and Discordance of Mitotic Count, Ki-67 Proliferative Index and Phosphohistone H3 Count in Grading Neuroendocrine Tumors of Gastrointenstinal Tract

Objective: To determine the grades of gastrointestinal neuroendocrine tumours using World Health Organization criteria and Phosphohistone H3 mitotic index and to determine the concordance between the two methods.&#x0D; Study Design: Cross-sectional study.&#x0D; Place and Duration of Study: Department of Histopathology, Armed Forces Institute of Pathology, Rawalpindi Pakistan, from Mar to Oct 2019.&#x0D; Methodology: Forty-two (n=42) patients of either gender between the ages of 18-70 years were enrolled. All the enrolled patients were diagnosed with primary gastrointestinal neuroendocrine tumours and underwent either surgical or endoscopic resection. Tumour grades were determined using World Health Organization criteria and Phosphohistone H3mitotic index. The results obtained with both methods were compared, and the concordance rate was calculated.&#x0D; Results: When mitotic counts were determined through PHH3, MI resulted in a change of grade of 12 (28.6%) tumours, which were graded by the current WHO system. 11 (26.2%) were changed from grade II to grade I and 1 (2.4%) from grade I to grade I1. The agreement (concordance rate) between the two systems was moderate and statistically significant (71.4%, n=30/42, κ= 0.51, p= 0.001).&#x0D; Conclusion: In the present study, we observed a moderate agreement between the Ki-67 labelling index and the PPH3 mitotic index, and both correlate well with the mitotic counts. The PPH3 mitotic index demonstrated a better correlation with mitotic counts when compared with Ki-67 LI. Hence, the inference can be drawn that the mitotic index with Phosphohistone H3is associated more closely with mitosis in gastrointestinal neuroendocrine tumours.

Association of Clinicopathological Factors with Radiation Induced Oral Mucositis in Patients with Head and Neck Carcinoma

Objective:&#x0D; To evaluate the association of clinicopathological factors with radiation induced oral mucositis in patients with head and neck carcinoma .&#x0D; Methodology&#x0D; This cross sectional study was conducted at Department of Neurospine and Cancer Institute, Inclusion criteria were patients with confirmed non-metastatic carcinoma histologically, age range of &gt; 20 and 70 years, patients requiring radical radiotherapy showing visible oral and oropharyngeal mucosa in the field of radiation (55 to 66 Gray). The exclusion criteria were: history of more than one tumour recurrence; prior history of radiation to the head and neck region; atypical liver and renal function; unusual haematological status; other deliberated medical conditions. Non-probability convenience sampling was used for assesment of oral mucositis. Data was analysed by using SPSS version 23.&#x0D; Results: &#x0D; A total of 30 patients were included. The mean age was 43 years (25-70 years) and 76.7% were males. Right sided buccul mucosa was most common primary tumor site, 70% cases belongs to middle-class families with 90% has no previous family history. Histological grade 2 and grade 2 and grade 3 mucositis was mostly reported. Tobacco chewing and betel nut chewing is the most common habit. The most common site affected is buccul mucosa, followed by the cheek and tongue. It has been observed that TNM staging and histological grading have shown significance in cases of oral mucositis.&#x0D; Conclusion:&#x0D; This study concludes that the oral mucositis is significantly associated with TNM staging and histological grading of tumors. Male gender, elderly age, middle to low socioeconomic status, tobacco and betal nut chewing , right sided buccal mucosa and stage II TNM staging. Grade 2 and grade 3 oral mucositis was the most frequent clinicopathological factors associated with the development of head and neck cancer. Although previous family is not very frequent in our study population.&#x0D;

Evaluation of total oxidative stress and antioxidant capacity of brain tumour patients attending referral hospitals in Addis Ababa, 2020: a comparative cross-sectional study.

BackgroundThe exact cause of brain tumours is still unknown, but disruptions of redox balance are thought to play a significant role in all stages of brain tumour development. However, the roles of free radical imbalance at different grades of brain tumour and degree of oxidative stress before and after surgery have not been addressed in prior studies.AimA comparative cross-sectional study was conducted to assess the redox imbalance among confirmed brain tumour patients.Methods and resultsAn institution-based comparative cross-sectional study was conducted on a total of 100 participants (50 brain tumour patients and 50 controls) at referral hospitals in Addis Ababa, Ethiopia. Descriptive statistics, t-test and analysis of variance (ANOVA) (post-hoc) analysis were used and statistical significance was declared at p ≤ 0.05. The serum oxidised glutathione and total oxidative stress were significantly higher in the serum of brain tumour patients (0.72 ± 0.03 μM/μg and 9.66 ± 1.76 μmol H2O2 Eq/L, respectively) compared to the control group (0.21 ± 0.07 μM/μg and 6.59 ± 0.81 μmol H2O2 Eq/L, respectively) (p ≤ 0.05). The serum total oxidant status gradually increased as the tumour grade increased, being higher in grade four (11.96 ± 0.72) and lower in grade one (8.43 ± 1.56), and the mean differences were statistically significant (p ≤ 0 05). A statistically significantly higher total antioxidant capacity (116.78 ± 5.03 Trolox Eq/L) was obtained in the post-surgery than pre-surgery level (79.65 ± 17.914 Trolox Eq/L) (p ≤ 0 05).ConclusionHigher oxidant and lower antioxidant levels were found in the serum of brain tumour patients than in the control group. The post-surgery oxidant level was lower than the pre-surgery state. The findings of this study could suggest that redox imbalance may have a role in the pathophysiology of brain tumours, but further experimental studies are needed.

World Health Organization Classification of Tumors of the Central Nervous System 5th Edition (WHO CNS5): What's new?

The latest fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5) has been built on the prior WHO 2016 classification as well as recommendations put forward by seven updates of the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy (cIMPACT). Various new tumor types and subtypes have been recognized which are of clinical significance. Tumor groups have been restructured and the nomenclature of some tumor types has also been revised. The use of terms 'entity' and 'variant' have been replaced by 'type' and 'subtype'. Significant changes have been introduced in the grading of tumors viz. use of Arabic numerals, grading within individual tumor types and combined histological and molecular grading. The terms 'Not otherwise specified' and 'Not elsewhere classified' can now be used for all tumor types. WHO CNS5 also for the first time endorses the use of DNA methylation profiling for the diagnosis of some tumor types/subtypes. Finally, the importance of combining histology with molecular parameters is emphasized for the "layered reporting" and "integrated diagnosis", which will provide valuable diagnostic, prognostic, and predictive information, as well as for some entities, suggest targeted therapies.

Evaluating neurosurgical biopsies for CNS tumor diagnoses: An algorithmic and pattern based approach.

The 2016 and 2021 World Health Organization (WHO) Classifications of Tumors of the Central Nervous System (CNS) reflect the importance of integrating molecular analysis into CNS tumor diagnosis and classification, adding to the complexity of any surgical neuropathology practice. On the other hand, our evolving understanding of genomic alterations across the spectrum of CNS tumors highlights the importance of utilizing traditional histological and immunohistochemical approaches to first establish as accurate a diagnosis as possible. Such an approach is also essential to recognizing the most appropriate ancillary test(s) needed for accurate classification and grading of CNS tumors. Here, we present an algorithmic approach to be considered while evaluating surgical neuropathology biopsies, which includes a recognition of main histological patterns, and incorporates clinical and radiologic features, to assist with accurate diagnosis and optimal selection of subsequent ancillary testing.

Inclusion of fibroblasts and collagen fibrils in the cytologic grading of canine cutaneous mast cell tumors.

Fibroblasts and/or collagen fibrils have not been included in previous cytologic grading schemes of canine mast cell tumors (MCTs), and their association with biological behavior is broadly debated. This study aimed to evaluate the cytologic findings of canine MCT, with emphasis on the microenvironment, and propose a novel cytologic grading system correlated with mortality and histologic grade. Cytology smears of canine cutaneous MCTs were retrospectively reviewed and compared with their histopathologic counterparts using Cohen´s Kappa test. One-year survival rates were also compared with the cytologic and histopathologic variables using Pearson´s correlation test. From 92 first-occurrence canine cutaneous MCTs, the five features most associated with mortality were selected for a new grading system. The five features were cytoplasmic granulation, fibroblast and/or collagen fibril concentrations, and the presence of mitotic figures, multinucleation, and karyomegaly. Among concordant histopathologic and cytologic cases (ie, the same grades using both systems), mortality rates were 2.6% (1/38) for low-grade and 71.4% (10/14) for high-grade cases (P<0.001, chi-square). For false-negative and false-positive results, mortality rates were 33% (1/3) and 45% (5/11), respectively (P=0.707). Unlike the Camus cytologic grading system, the present amendment excluded binucleation and included fibroblasts and/ or collagen fibrils, which in higher concentrations were associated with increased survival and a low histopathologic grade. Cytologic grading with the inclusion of fibroblast and collagen fibril concentrations correlated with survival, as did the Camus cytologic and Kiupel histopathologic grades; however, further studies are needed to confirm the prognostic value of this novel cytologic grading scheme.