scholarly journals Rapid Spectroscopic Liquid Biopsy for the Universal Detection of Brain Tumours

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3851
Author(s):  
Ashton Theakstone ◽  
Paul Brennan ◽  
Michael Jenkinson ◽  
Samantha Mills ◽  
Khaja Syed ◽  
...  
Keyword(s):  
Early Detection ◽  
Brain Tumour ◽  
Liquid Biopsy ◽  
Brain Tumours ◽  
Genetic Material ◽  
Machine Learning Algorithms ◽  
Great Promise ◽  
Low Grade ◽  
Detection And Diagnosis ◽  
Early Detection And Diagnosis

Background: To support the early detection and diagnosis of brain tumours we have developed a rapid, cost-effective and easy to use spectroscopic liquid biopsy based on the absorbance of infrared radiation. We have previously reported highly sensitive results of our approach which can discriminate patients with a recent brain tumour diagnosis and asymptomatic controls. Other liquid biopsy approaches (e.g., based on tumour genetic material) report a lower classification accuracy for early-stage tumours. In this manuscript we present an investigation into the link between brain tumour volume and liquid biopsy test performance. Methods: In a cohort of 177 patients (90 patients with high-grade glioma (glioblastoma (GBM) or anaplastic astrocytoma), or low-grade glioma (astrocytoma, oligoastrocytoma and oligodendroglioma)) tumour volumes were calculated from magnetic resonance imaging (MRI) investigations and patients were split into two groups depending on MRI parameters (T1 with contrast enhancement or T2/FLAIR (fluid-attenuated inversion recovery)). Using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy coupled with supervised learning methods and machine learning algorithms, 90 tumour patients were stratified against 87 control patients who displayed no symptomatic indications of cancer, and were classified as either glioma or non-glioma. Results: Sensitivities, specificities and balanced accuracies were all greater than 88%, the area under the curve (AUC) was 0.98, and cancer patients with tumour volumes as small as 0.2 cm3 were correctly identified. Conclusions: Our spectroscopic liquid biopsy approach can identify gliomas that are both small and low-grade showing great promise for deployment of this technique for early detection and diagnosis.

A review of predictive, prognostic and diagnostic biomarkers for brain tumours: towards personalised and targeted cancer therapy

2019 ◽  
pp. 1-16 ◽  
Author(s):  
Ernest Osei ◽  
Pascale Walters ◽  
Olivia Masella ◽  
Quinton Tennant ◽  
Amber Fishwick ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Early Detection ◽  
Brain Cancer ◽  
Treatment Efficacy ◽  
Brain Tumours ◽  
Molecular Mechanisms ◽  
Patient Response ◽  
Biomarker Analysis ◽  
Detection And Diagnosis ◽  
Early Detection And Diagnosis

Abstract Background: Brain tumours are relatively rare disease but present a large medical challenge as there is currently no method for early detection of the tumour and are typically not diagnosed until patients have progressed to symptomatic stage which significantly decreases chances of survival and also minimises treatment efficacy. However, if brain cancers can be diagnosed at early stages and also if clinicians have the potential to prospectively identify patients likely to respond to specific treatments, then there is a very high potential to increase patients’ treatment efficacy and survival. In recent years, there have been several investigations to identify biomarkers for brain cancer risk assessment, early detection and diagnosis, the likelihood of identifying which group of patients will benefit from a particular treatment and monitoring patient response to treatment. Materials and methods: This paper reports on a review of 21 current clinical and emerging biomarkers used in risk assessment, screening for early detection and diagnosis, and monitoring the response of treatment of brain cancers. Conclusion: Understanding biomarkers, molecular mechanisms and signalling pathways can potentially lead to personalised and targeted treatment via therapeutic targeting of specific genetic aberrant pathways which play key roles in malignant brain tumour formation. The future holds promising for the use of biomarker analysis as a major factor for personalised and targeted brain cancer treatment, since biomarkers have the potential to measure early disease detection and diagnosis, the risk of disease development and progression, improved patient stratification for various treatment paradigms, provide accurate information of patient response to a specific treatment and inform clinicians about the likely outcome of a brain cancer diagnosis independent of the treatment received.

scholarly journals AN IN-DEPTH ANALYSIS OF THE IDENTIFIED ALGORITHMS AND THEIR COMPARATIVE STUDY IN THE EARLY DETECTION AND DIAGNOSIS OF BREAST CANCER

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mridul Sharma
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Early Detection ◽  
Healthcare Workers ◽  
State Of The Art ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Depth Analysis ◽  
Detection And Diagnosis ◽  
Early Detection And Diagnosis

These days one of the major inevitable ailments for females is bosom malignancy. The appropriate medication and early findings are important stages to take to thwart this ailment. Although, it's not easy to recognize due to its few vulnerabilities and lack of data. Can use artificial intelligence to create devices that can help doctors and healthcare workers to early detection of this cancer. In This research, we investigate three specific machine learning algorithms widely used to detect bosom ailments in the breast region. These algorithms are Support vector machine (SVM), Bayesian Networks (BN) and Random Forest (RF). The output in this research is based on the State-of-the-art technique.

Detection of Leukemia Using Image Processing

2018 ◽  
Vol 8 (4) ◽  
pp. 61
Author(s):  
A. Sivasangari ◽  
G. Sasikumar
Keyword(s):  
Image Processing ◽  
Statistical Analysis ◽  
Early Detection ◽  
Visual Inspection ◽  
Causes Of Death ◽  
Cure Rate ◽  
Blood Disorders ◽  
Detection And Diagnosis ◽  
The Moment ◽  
Early Detection And Diagnosis

Leukemia   disease   is one   of    the   leading   causes   of death   among   human. Its  cure  rate and  prognosis   depends   mainly   on  the  early  detection   and  diagnosis  of   the  disease. At  the  moment, identification  of  blood  disorders  is  through   visual  inspection  of  microscopic  images  by  examining  changes  like  texture, geometry, colour  and   statistical  analysis  of  images . This  project  aims  to  preliminary  of  developing  a  detection  of  leukemia  types  using   microscopic  blood  sample using MATLAB. Images  are  used  as  they  are  cheap  and  do  not  expensive  for testing  and  lab  equipment.

scholarly journals A Selective Ensemble Classification Method Combining Mammography Images with Ultrasound Images for Breast Cancer Diagnosis

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Jinyu Cong ◽  
Benzheng Wei ◽  
Yunlong He ◽  
Yilong Yin ◽  
Yuanjie Zheng
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis ◽  
Ensemble Classification ◽  
Classification Method ◽  
Ultrasound Images ◽  
Selective Ensemble ◽  
Detection And Diagnosis ◽  
Early Detection And Diagnosis

Breast cancer has been one of the main diseases that threatens women’s life. Early detection and diagnosis of breast cancer play an important role in reducing mortality of breast cancer. In this paper, we propose a selective ensemble method integrated with the KNN, SVM, and Naive Bayes to diagnose the breast cancer combining ultrasound images with mammography images. Our experimental results have shown that the selective classification method with an accuracy of 88.73% and sensitivity of 97.06% is efficient for breast cancer diagnosis. And indicator R presents a new way to choose the base classifier for ensemble learning.

scholarly journals Determination of SOX9 Gene Expression In Brain Tumours Among East Coast Malaysia Population

2020 ◽  
Vol 18 (2) ◽  
Author(s):  
Md Dzali NB ◽  
Wan Taib WR ◽  
Zahary MN ◽  
Abu Bakar NH ◽  
Abd Latif AZ ◽  
...  
Keyword(s):  
Brain Tissue ◽  
Brain Tumour ◽  
Brain Tumours ◽  
East Coast ◽  
Rna Extraction ◽  
Slight Modification ◽  
Low Grade ◽  
Normal Brain ◽  
Sox9 Expression ◽  
Sox9 Gene

Introduction: SOX9, a members of SOX family, plays a significant roles in developmental processes during embryogenesis, including brain tissue. Few studies have shown that SOX9 has been involved in tumourigenesis of several types of cancer including brain tumour. However, such studies are still lacking in the Malaysian population. The aim of this study was to determine SOX9 expression level in several types of brain tumours in East Coast Malaysia. Materials and Methods: Five formalin-fixed pariffin-embedded brain tumour samples of Malay descendants were sectioned by using microtome. RNA extraction was performed with slight modification by adding Trizol during tissue lysis. The RNA was converted to cDNA using reverse transcription technique before SOX9 expression was detected using RT q-PCR assay in brain tumours normalized to non-neoplastic brain tissues. Results: Overall results displayed that SOX9 gene in all samples were up-regulated. SOX9 overexpression was found in both high and low grade glioma (anaplastic and pilocytic astrocytoma respectively). This is consistence with both low grade (benign) and atypical meningioma. Secondary brain tumour also showed up-regulation when compared to normal brain tissue. Conclusion: Up-regulation in SOX9 expression in selected brain tumours in Malay patients revealed its significant roles in brain tumourigenesis. Functional studies should be carried out to observe the SOX9 functions and mechanism whether they should reflect their diverse roles in Malaysia population.

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