Cancer differentiation analysis technology as a novel technology for cerebral cancer screening.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 2040-2040
Author(s):  
Hongmei Tao ◽  
Xing Tang ◽  
Yue Lin ◽  
Chris Chang Yu ◽  
Xuedong Du
Keyword(s):  
Cancer Screening ◽  
Sensitivity And Specificity ◽  
Physical Property ◽  
Screening Methods ◽  
Potential Candidate ◽  
Healthy Individuals ◽  
Level Information ◽  
Area Under Roc Curve ◽  
Multi Level ◽  
Initial Results

2040 Background: While the current cancer screening methods mostly failed to detect cerebral cancer, a novel, promising technology named cancer differentiation analysis (CDA) technology has been developed to measure novel bio-physical properties to obtain valuable multi-level and multi-parameter information including protein, cellular and molecular level information. Initial results showed that CDA technology is capable of detecting cerebral cancer with a high degree of sensitivity and specificity. Methods: In this study, samples from 78 cerebral cancer patients and 321 healthy individuals were measured. Peripheral blood of each individual was drawn in EDTA tubes. One class of bio-physical property in blood samples was utilized for CDA tests. CDA data were conducted using SPSS, and the results were shown in table. Results: The average CDA values of cerebral cancer and control groups were 52.30 and 33.38 (rel. units) respectively. The results indicated that cerebral cancer could be significantly distinguished from the control (p < 0.001). Area under ROC curve (AUC) was 0.980, and sensitivity and specificity was 92.3% and 96.6% respectively. Conclusions: Initial results showed that CDA technology could effectively distinguish cerebral cancer from healthy individuals. As a novel bio-physical based cancer detection approach with multi-level and multi-parameter expressions, CDA could be a potential candidate for cerebral cancer screening. Results from Statistical Analysis of CDA. [Table: see text]

A novel biophysical based marker with multilevel, multiparameter expression for early stage cancer detection.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e20673-e20673
Author(s):  
Junjie Wu ◽  
Gengxi Jiang ◽  
Jiansong Ji ◽  
Xuedong Du ◽  
Yue Lin ◽  
...  
Keyword(s):  
Sensitivity And Specificity ◽  
Cancer Detection ◽  
Early Stage ◽  
Physical Property ◽  
Stage I ◽  
Potential Candidate ◽  
Healthy Individuals ◽  
Blind Test ◽  
Early Stage Cancer ◽  
Multi Level

e20673 Background: Early stage cancer detection remains to be elusive despite of many years of efforts. In this work, a bio-physical based marker (named Cancer Differentiation Analysis (CDA)) with multi-level and multi-parameter expression features has been developed which has shown a number of clear advantages over the traditional approaches such as bio-chemistry based marker, circulating tumor cell (CTC) and circuiting DNA (ct-DNA). In stage I non-small cell lung cancer (NSCLC), sensitivity and specificity reached a record high of 85.2% and 93.0%, respectively. Methods: In this study, 832 NSCLC cancer samples with pathological information and 642 samples from healthy individuals were measured in a single blind test. Peripheral blood of each individual was drawn in EDTA tubes. One class of bio-physical property in blood samples was utilized for CDA tests. The CDA data were first processed using an algorithm built from data base and subsequently analyzed using SPSS. The results were shown in the table. Results: The results indicated that CDA technology has a very good sensitivity and specificity even at stage I (85% and 93%, respectively), which is much better than those previously reported results by other methods. Conclusions: Initial results showed that CDA technology could effectively screen NSCLC patients from healthy individuals. As a novel bio-physical based cancer detection approach with multi-level and multi-parameter expressions, CDA technology could be a potential candidate for early stage cancer screening. [Table: see text]

Age-related variations: A retrospective analysis of 851 prospectively collected patient samples to determine the benefit of combining combinatorial protein biomarker assay for risk assessment in women with dense breast.

2015 ◽  
Vol 33 (28_suppl) ◽  
pp. 27-27
Author(s):  
David Emery Reese ◽  
Michael Silver ◽  
Meredith C. Henderson ◽  
Sherri Borman ◽  
Christa Corn ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Sensitivity And Specificity ◽  
Dense Breast ◽  
Patient Specific ◽  
Screening Methods ◽  
Breast Lesions ◽  
Breast Cancers ◽  
Age Related

27 Background: Clinicians often experience difficulty in differentiating benign lesions from invasive breast cancers in patients designated as dense breast. A major limitation of radiological breast cancer screening methods involves a decrease in sensitivity and specificity in women with dense breast. Thus, we sought to test whether Klarify Breast, a combinatorial protein-based biomarker panel could improve early detection of significant breast lesions in a controlled fashion. Clearly, a diagnostic assay that would provide biochemical evidence in the patient’s clinical course is greatly needed. Methods: We have conducted two independent, multi-center, prospective clinical trials to establish the clinical validity of Klarify Breast – an assay that uses multiple Serum Protein Biomarkers (SPBs), Tumor-Associated Autoantibodies (TAAbs), patient specific clinical data and develop a score to differentiate patients with benign breast disease from those with invasive breast cancer. Independent panels of biomarkers and associated algorithms were developed using prospectively collected samples from women under age 50 (n = 351) and from women ages 25-75 (n = 500). Here, we present the benefit of integrating the results of Klarify Breast test with patient imaging to best assess risk in women with dense breast. Results: While performance of the assay was somewhat age dependent (women under the age of 50 demonstrated a higher sensitivity and specificity than women over the age of 50). Here we present data that both groups of women clearly benefit from the addition of a biomarker assay combined with standard of care imaging in identifying invasive breast lesions. Conclusions: Clearly, in women with dense breast, where radiologic studies alone do not permit full assessment in women with a dense breast finding. The biomarker test here, comprised of TAAbs and SPBs, offers a clear advantage in terms of NPV, PPV, Sensitivity and specificity. The results argue strongly for the use of appropriate biomarkers to augment imaging based breast cancer screening in women with dense breast or those who are at high risk. Clinical trial information: NCT01839045, NCT02078570.

Investigations of breast cancer screening using a novel in vitro diagnostics technology.

2015 ◽  
Vol 33 (28_suppl) ◽  
pp. 13-13
Author(s):  
Hongmei Tao ◽  
Xuedong Du ◽  
Xing Tang ◽  
Yue Lin ◽  
Da Lou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Youden Index ◽  
Potential Candidate ◽  
Cancer Group ◽  
Area Under Roc Curve ◽  
Breast Cancer Group ◽  
And Control

13 Background: A newly developed in-vitro diagnostic technology named Cancer Differentiation Analysis Technology (CDA) was investigated for breast cancer screening. The CDA technology is a blood-sample based, multi-level, multi-parameter diagnostic method which detects signals from both proteins and cells, in which multiple aspects and parameters of information were collected to improve diagnostic accuracy. Methods: Blood samples from breast cancer group (n = 222), and control subjects (n = 204) were collected in EDTA tubes. CDA values were measured using a CDA medical device. The results were shown in Table 1 and Figure 1 below. Results: The average CDA values of breast cancer and control groups were 50.43 and 34.03 (rel. units) respectively. The results indicated that breast cancer could be significantly distinguished from the control (p < 0.001). Area under ROC curve was 0.914. When Youden Index reached the maximum, sensitivity and specificity was 82.0% and 89.2% respectively. Conclusions: Initial results showed that CDA technology could be a potential candidate for breast cancer screening. [Table: see text]

Multi-level 3D Densenets for False-positive Reduction in Lung Nodule Detection Based on Chest Computed Tomography

2020 ◽  
Vol 16 (8) ◽  
pp. 1004-1021
Author(s):  
Xiaoqi Lu ◽  
Yu Gu ◽  
Lidong Yang ◽  
Baohua Zhang ◽  
Ying Zhao ◽  
...  
Keyword(s):  
False Positive ◽  
Contextual Information ◽  
Lung Nodule ◽  
Positive Sample ◽  
Lung Nodules ◽  
Lung Nodule Detection ◽  
Nodule Detection ◽  
Level Information ◽  
Multi Level ◽  
Cade System

Objective: False-positive nodule reduction is a crucial part of a computer-aided detection (CADe) system, which assists radiologists in accurate lung nodule detection. In this research, a novel scheme using multi-level 3D DenseNet framework is proposed to implement false-positive nodule reduction task. Methods: Multi-level 3D DenseNet models were extended to differentiate lung nodules from falsepositive nodules. First, different models were fed with 3D cubes with different sizes for encoding multi-level contextual information to meet the challenges of the large variations of lung nodules. In addition, image rotation and flipping were utilized to upsample positive samples which consisted of a positive sample set. Furthermore, the 3D DenseNets were designed to keep low-level information of nodules, as densely connected structures in DenseNet can reuse features of lung nodules and then boost feature propagation. Finally, the optimal weighted linear combination of all model scores obtained the best classification result in this research. Results: The proposed method was evaluated with LUNA16 dataset which contained 888 thin-slice CT scans. The performance was validated via 10-fold cross-validation. Both the Free-response Receiver Operating Characteristic (FROC) curve and the Competition Performance Metric (CPM) score show that the proposed scheme can achieve a satisfactory detection performance in the falsepositive reduction track of the LUNA16 challenge. Conclusion: The result shows that the proposed scheme can be significant for false-positive nodule reduction task.

scholarly journals Scope of Artificial Intelligence in Screening and Diagnosis of Colorectal Cancer

2020 ◽  
Vol 9 (10) ◽  
pp. 3313 ◽  
Author(s):  
Hemant Goyal ◽  
Rupinder Mann ◽  
Zainab Gandhi ◽  
Abhilash Perisetti ◽  
Aman Ali ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Colorectal Cancer ◽  
Cancer Screening ◽  
Colorectal Cancer Screening ◽  
Narrow Band Imaging ◽  
Screening Methods ◽  
Polyp Detection ◽  
Mortality And Morbidity ◽  
Magnifying Chromoendoscopy

Globally, colorectal cancer is the third most diagnosed malignancy. It causes significant mortality and morbidity, which can be reduced by early diagnosis with an effective screening test. Integrating artificial intelligence (AI) and computer-aided detection (CAD) with screening methods has shown promising colorectal cancer screening results. AI could provide a “second look” for endoscopists to decrease the rate of missed polyps during a colonoscopy. It can also improve detection and characterization of polyps by integration with colonoscopy and various advanced endoscopic modalities such as magnifying narrow-band imaging, endocytoscopy, confocal endomicroscopy, laser-induced fluorescence spectroscopy, and magnifying chromoendoscopy. This descriptive review discusses various AI and CAD applications in colorectal cancer screening, polyp detection, and characterization.

A prospective study of an AI-based breast cancer screening solution for resource-constrained settings.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13586-e13586
Author(s):  
Richa Bansal ◽  
Bharat Aggarwal ◽  
Lakshmi Krishnan
Keyword(s):  
Breast Cancer ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Sensitivity And Specificity ◽  
Breast Tissue ◽  
Dense Breast ◽  
Resource Constrained ◽  
Dense Breast Tissue ◽  
Dense Breasts ◽  
Low Sensitivity

e13586 Background: Screening mammography is often found to have low sensitivity in women with high density breast tissues. Alternate modalities of breast USG and MRI require high-quality expensive equipment making the regular screening with these modalities less affordable and accessible, particularly in resource-constrained settings This study evaluates the clinical performance of an AI-based test (Thermalytix) that uses machine learning on breast thermal images which could potentially be a low-cost solution for breast screening in low- and middle-income countries (LMICs). Methods: The prospective comparative study conducted from December 2018 to January 2020 evaluated the performance of Thermalytix in women with dense and non-dense breast tissue who presented for a health check-up at a hospital. All women underwent Thermalytix and mammography. Further investigations were recommended for participants who were reported as positive on either test. Sensitivity and specificity of Thermalytix were evaluated across age-groups, menopausal status, and breast densities. Results: Among the 687 women recruited for the study, 459 women who satisfied the inclusion criteria were included in the analysis. 168 women had ACR categories ‘c’ or ‘d’ dense breasts, of which 37 women had an inconclusive mammography report (BI-RADS 0). Overall, 21 women were detected with breast cancer in the study. Thermalytix demonstrated an overall sensitivity of 95.2% (95% CI, 76.1-99·9) and a specificity of 88.6% (95% CI, 85.2-91.4). Among women with dense breast tissue (n=168), Thermalytix showed a sensitivity of 100% (95% CI, 69.2-100) and a specificity of 81.7% (95% CI, 74.7-87.4). In women with ACR categories ‘c’ and ‘d’ dense breasts, mammography reported 22% of them as inconclusive (BI-RAD 0), while in the same sub-set of the population Thermalytix demonstrated a sensitivity of 100%. Conclusions: The AI-based Thermalytix demonstrated high sensitivity and specificity in the study cohort. It also fared well in women younger than 50 years and pre-menopausal women where routine mammography screening yields low sensitivity. Overall, this study introduces Thermalytix, a promising radiation-free, automated, and privacy-aware test that can supplement mammography for routine screening of women, especially in women with dense breast tissue, and has the potential to influence the clinical practice in LMICs by making breast cancer screening portable and affordable. Performance of Thermalytix and mammography in women with high breast densities (ACR categories ‘c’ and ‘d’ breasts). Clinical trial information: NCT04688086. [Table: see text]

scholarly journals Circulating Natural IgM Antibodies against Angiogenin in the Peripheral Blood Sera of Patients with Osteosarcoma as Candidate Biomarkers and Reporters of Tumorigenesis

2010 ◽  
Vol 2 ◽  
pp. BIC.S6040 ◽  
Author(s):  
Yulia A. Savitskaya ◽  
Genaro Rico ◽  
Luis Linares ◽  
Roberto González ◽  
René Téllez ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
Sensitivity And Specificity ◽  
Peripheral Blood ◽  
Enzyme Linked Immunosorbent Assay ◽  
Control Group ◽  
Healthy Individuals ◽  
Igm Antibodies ◽  
Potential Biomarker ◽  
Increased Risk ◽  
Natural Igm

Background Tumor immunology research has led to the identification of a number of tumor-associated self antigens, suggesting that most tumors trigger an immunogenic response, as is the case in osteosarcoma, where the detection of natural serum IgM antibodies might achieve the diagnosis of osteosarcoma. Natural IgM antibodies to tumor-associated proteins may expand the number of available tumor biomarkers for osteosarcoma and may be used together in a serum profile to enhance test sensitivity and specificity. Natural IgM antibodies can be consistently detected in the peripheral blood sera months to years before the tumor is diagnosed clinically. The study of the level of a potential biomarker many months (or years) prior to diagnosis is fundamentally important. Integrated circulating and imaging markers in clinical practice treating osteosarcoma have potential applications for controlling tumor angiogenesis. Objectives To study the expression of natural IgM antibodies to the tumor antigens of angiogenesis in the peripheral blood sera of osteosarcoma patients and healthy individuals, and to develop serum-based predictive biomarkers. Methods Peripheral venous blood samples were collected from 117 osteosarcoma patients and 117 patients with other tumors. All diagnosis was histologically confirmed. Staging of patients was performed according to the Enneking Surgical Staging System. The control group consisted of 117 age- and sex- matched healthy individuals. In this study, novel immunoconjugates were designed, synthesized and then used to develop a rapid, specific and sensitive enzyme-linked immunosorbent assay (ELISA) method to detect angiogenin (ANG)–IgM directly in the peripheral blood sera of humans. Results Serum ANG–IgM levels are significantly higher in osteosarcoma patients than in healthy individuals ( P < 0.005). Serum ANG–IgM levels varied widely, but were highly dependent on the concentration of IgM (r = 0.85; P < 0.0005). We found ANG–IgM in the sera of 85% of newly diagnosed osteosarcoma patients and ANG–IgM levels were significantly higher in osteosarcoma patients compared to any other tumors ( P < 0.001). Conclusions These results demonstrated that the combined biomarker ANG–IgM has greater sensitivity and specificity in early diagnosis of osteosarcoma patients than the traditional biomarkers (ANG and vascular endothelial growth factor). Circulating ANG–IgM immune complexes can potentially serve as a biomarker for increased risk of osteosarcoma, because relatively high serum levels were also detected in otherwise healthy individuals with a first degree family history of osteosarcoma and in patients with a diagnosis of benign conditions. Immunological aspects of angiogenesis for managing osteosarcoma will have a practical value in early diagnosis, prognosis and monitoring response to antiangiogenic therapy.

scholarly journals Can Serum Glypican-3 Be a Biomarker for Effective Diagnosis of Hepatocellular Carcinoma? A Meta-Analysis of the Literature

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Sheng-Li Yang ◽  
Xiefan Fang ◽  
Zao-Zao Huang ◽  
Xiang-Jie Liu ◽  
Zhi-Fan Xiong ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cirrhosis ◽  
Sensitivity And Specificity ◽  
Meta Analysis ◽  
Diagnostic Value ◽  
Healthy Individuals ◽  
Subgroup Analyses ◽  
Effective Diagnosis ◽  
Diagnostic Index

Objective. This review is to evaluate the diagnostic value of serum GPC3 for hepatocellular carcinoma (HCC) due to conflicting results reported.Methods. NCBI PubMed and Embase were comprehensively searched for studies that have used serum GPC3 level as a diagnostic index for HCC. The quality of the included studies was assessed. Subgroup analyses were conducted to evaluate the sensitivity and specificity of GPC3 as a HCC marker. Statistical analysis was performed with the software STATA version 12.0.Results. A total of 22 studies were included. The qualities of included studies were relatively poor. Among them, 18 studies have shown that serum GPC3 is a specific biomarker for HCC, and the pooled sensitivity and specificity of these studies were 69 and 93%, respectively. The other 4 studies have reported conflicting results, which were not caused by races, infection status of HBV and HCV, or assay reagents but due to one common experimental design of enrolling liver cirrhosis patients as control subjects.Conclusions. This meta-analysis indicates that serum GPC3 is elevated in HCC patients compared with healthy individuals, but more studies are needed to evaluate its effectiveness to differentially diagnose HCC and liver cirrhosis.

scholarly journals Differential diagnosis of Alzheimer’s disease using spectrochemical analysis of blood

2017 ◽  
Vol 114 (38) ◽  
pp. E7929-E7938 ◽  
Author(s):  
Maria Paraskevaidi ◽  
Camilo L. M. Morais ◽  
Kássio M. G. Lima ◽  
Julie S. Snowden ◽  
Jennifer A. Saxon ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Diseases ◽  
Sensitivity And Specificity ◽  
Lewy Bodies ◽  
Total Reflection ◽  
Attenuated Total Reflection ◽  
Repeated Measurements ◽  
Healthy Individuals ◽  
Different Types

The progressive aging of the world’s population makes a higher prevalence of neurodegenerative diseases inevitable. The necessity for an accurate, but at the same time, inexpensive and minimally invasive, diagnostic test is urgently required, not only to confirm the presence of the disease but also to discriminate between different types of dementia to provide the appropriate management and treatment. In this study, attenuated total reflection FTIR (ATR-FTIR) spectroscopy combined with chemometric techniques were used to analyze blood plasma samples from our cohort. Blood samples are easily collected by conventional venepuncture, permitting repeated measurements from the same individuals to monitor their progression throughout the years or evaluate any tested drugs. We included 549 individuals: 347 with various neurodegenerative diseases and 202 age-matched healthy individuals. Alzheimer’s disease (AD;n= 164) was identified with 70% sensitivity and specificity, which after the incorporation of apolipoprotein ε4 genotype (APOEε4) information, increased to 86% when individuals carried one or two alleles of ε4, and to 72% sensitivity and 77% specificity when individuals did not carry ε4 alleles. Early AD cases (n= 14) were identified with 80% sensitivity and 74% specificity. Segregation of AD from dementia with Lewy bodies (DLB;n= 34) was achieved with 90% sensitivity and specificity. Other neurodegenerative diseases, such as frontotemporal dementia (FTD;n= 30), Parkinson’s disease (PD;n= 32), and progressive supranuclear palsy (PSP;n= 31), were included in our cohort for diagnostic purposes. Our method allows for both rapid and robust diagnosis of neurodegeneration and segregation between different dementias.

scholarly journals Evaluation of serum amyloid A, soluble E-selectin and soluble E-cadherin as lung cancer biomarkers

2017 ◽  
Vol 4 (3) ◽  
pp. 650
Author(s):  
Varinder Saini ◽  
Chikkahonnaiah Prashanth ◽  
Jasbinder Kaur ◽  
Ashok Kumar Janmeja ◽  
Seema Gupta ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Sensitivity And Specificity ◽  
Respiratory Diseases ◽  
Serum Levels ◽  
Screening Methods ◽  
Healthy Controls ◽  
Amyloid A ◽  
Significant Difference ◽  
Soluble E Selectin ◽  
E Cadherin

Background: Lung cancer screening is a challenge. Sputum cytology, chest X-ray, low dose computed tomography and other screening methods have not proved to be very effective. Serum biomarkers are a new hope in screening of lung cancer. The present study was planned to evaluate sensitivity and specificity of serum levels of amyloid A (SAA), soluble E- selectin (sE-selectin) and soluble E-cadherin (sE-cadherin) as lung cancer biomarkers.Methods: An observational and cross-sectional study comprised of three groups with 20 subjects each of proven lung cancer cases, patients with non-malignant respiratory diseases and healthy controls. Levels of SAA, sE-selectin and sE-cadherin were measured by solid phase sandwich ELISA. Individual and collective sensitivity and specificity of these biomarkers was analysed and cut off values calculated by receiver operating curves.Results: A statistically significant difference was found in the median levels (ng/ml) of SAA in patients of lung cancer, other non-malignant respiratory diseases, and healthy controls, the levels (Mean±SD) being 24980.50±6564.14,9961.10±2000.24 and 580.95±334.94 respectively in the three groups. A sensitivity of 80% and specificity of 55% was found when SAA levels of 1068 ng/ml were taken as cut off for screening of lung cancer. However, no significant difference was found in the serum levels of sE selectin and sE cadherin between the three groups. Moreover, significant association of biomarkers could also not be established with lung cancer when they were used in combination.Conclusions: In this preliminary report from India, SAA has been found to be a promising biomarker in screening for lung cancer.

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