scholarly journals An expandable informatics framework for enhancing central cancer registries with digital pathology specimens, computational imaging tools, and advanced mining capabilities

2022 ◽  
Vol 13 (1) ◽  
pp. 5
Author(s):  
DavidJ Foran ◽  
EricB Durbin ◽  
Wenjin Chen ◽  
Evita Sadimin ◽  
Ashish Sharma ◽  
...  
Keyword(s):  
Digital Pathology ◽  
Cancer Registries ◽  
Computational Imaging

Trends in the incidence and mortality of oral cancer in Nevada (Preprint)

2020 ◽  
Author(s):  
Kevin Foote ◽  
Karl Kingsley
Keyword(s):  
Public Health ◽  
Oral Cancer ◽  
Cancer Incidence ◽  
Cancer Control ◽  
Cancer Registries ◽  
Public Health Research ◽  
Chi Square ◽  
Incidence And Mortality ◽  
The Us ◽  
Chi Square Analysis

BACKGROUND Reviews of national and state-specific cancer registries have revealed differences in rates of oral cancer incidence and mortality that have implications for public health research and policy. Many significant associations between head and neck (oral) cancers and major risk factors, such as cigarette usage, may be influenced by public health policy such as smoking restrictions and bans – including the Nevada Clean Indoor Act of 2006 (and subsequent modification in 2011). OBJECTIVE Although evaluation of general and regional advances in public policy have been previously evaluated, no recent studies have focused specifically on the changes to the epidemiology of oral cancer incidence and mortality in Nevada. METHODS Cancer incidence and mortality rate data were obtained from the National Cancer Institute (NCI) Division of Cancer Control and Population Sciences (DCCPS) Surveillance, Epidemiology and End Results (SEER) program. Most recently available rate changes in cancer incidence and mortality for Nevada included the years 2012 – 2016 and are age-adjusted to the year 2000 standard US population. Comparisons of any differences between Nevada and the overall US population were evaluated using Chi square analysis. RESULTS This analysis revealed that the overall rates of incidence and mortality from oral cancer in Nevada differs from that observed in the overall US population. For example, although the incidence of oral cancer among Caucasians is increasing in Nevada and the US overall, it is increasing at nearly twice that rate in Nevada, P=0.0002. In addition, although oral cancer incidence among Minorities in the US is declining, it is increasing in Nevada , P=0.0001. Analysis of reported mortality causes revealed that mortality from oral cancer increased in the US overall but declined in Nevada during the same period (2012-2016). More specifically, mortality among both Males and Females in the US is increasing, but is declining in Nevada, P=0.0027. CONCLUSIONS Analysis of the epidemiologic data from Nevada compared with the overall US revealed significant differences in rates of oral cancer incidence and mortality. More specifically, oral cancer incidence increased in Nevada between 2012-2016 among all groups analyzed (Males, Females, White, Minority), while decreases were observed nationally among Females and Minorities. Although mortality in Nevada decreased over this same time period (in contrast to the national trends), the lag time between diagnosis (incidence) and mortality suggests that these trends will change in the near future. CLINICALTRIAL Not applicable

scholarly journals A Digital Pathology Solution to Resolve the Tissue Floater Conundrum

2020 ◽  
Author(s):  
Liron Pantanowitz ◽  
Pamela Michelow ◽  
Scott Hazelhurst ◽  
Shivam Kalra ◽  
Charles Choi ◽  
...  
Keyword(s):  
Digital Pathology ◽  
Primary Diagnosis ◽  
Image Search ◽  
Molecular Tests ◽  
Tissue Identification ◽  
Digital Database ◽  
Glass Slides ◽  
Search Tool ◽  
Hematoxylin And Eosin ◽  
Whole Slide Images

Context.— Pathologists may encounter extraneous pieces of tissue (tissue floaters) on glass slides because of specimen cross-contamination. Troubleshooting this problem, including performing molecular tests for tissue identification if available, is time consuming and often does not satisfactorily resolve the problem. Objective.— To demonstrate the feasibility of using an image search tool to resolve the tissue floater conundrum. Design.— A glass slide was produced containing 2 separate hematoxylin and eosin (H&E)-stained tissue floaters. This fabricated slide was digitized along with the 2 slides containing the original tumors used to create these floaters. These slides were then embedded into a dataset of 2325 whole slide images comprising a wide variety of H&E stained diagnostic entities. Digital slides were broken up into patches and the patch features converted into barcodes for indexing and easy retrieval. A deep learning-based image search tool was employed to extract features from patches via barcodes, hence enabling image matching to each tissue floater. Results.— There was a very high likelihood of finding a correct tumor match for the queried tissue floater when searching the digital database. Search results repeatedly yielded a correct match within the top 3 retrieved images. The retrieval accuracy improved when greater proportions of the floater were selected. The time to run a search was completed within several milliseconds. Conclusions.— Using an image search tool offers pathologists an additional method to rapidly resolve the tissue floater conundrum, especially for those laboratories that have transitioned to going fully digital for primary diagnosis.

scholarly journals COVID-19 and cancer registries: learning from the first peak of the SARS-CoV-2 pandemic

2021 ◽  
Author(s):  
Alvin J. X. Lee ◽  
Karin Purshouse
Keyword(s):  
Risk Factors ◽  
Performance Status ◽  
Poor Performance ◽  
Cancer Registries ◽  
Adverse Outcomes ◽  
Smoking History ◽  
Poor Performance Status ◽  
International Studies ◽  
Patients With Cancer ◽  
Increased Risk

AbstractThe SARS-Cov-2 pandemic in 2020 has caused oncology teams around the world to adapt their practice in the aim of protecting patients. Early evidence from China indicated that patients with cancer, and particularly those who had recently received chemotherapy or surgery, were at increased risk of adverse outcomes following SARS-Cov-2 infection. Many registries of cancer patients infected with SARS-Cov-2 emerged during the first wave. We collate the evidence from these national and international studies and focus on the risk factors for patients with solid cancers and the contribution of systemic anti-cancer treatments (SACT—chemotherapy, immunotherapy, targeted and hormone therapy) to outcomes following SARS-Cov-2 infection. Patients with cancer infected with SARS-Cov-2 have a higher probability of death compared with patients without cancer. Common risk factors for mortality following COVID-19 include age, male sex, smoking history, number of comorbidities and poor performance status. Oncological features that may predict for worse outcomes include tumour stage, disease trajectory and lung cancer. Most studies did not identify an association between SACT and adverse outcomes. Recent data suggest that the timing of receipt of SACT may be associated with risk of mortality. Ongoing recruitment to these registries will enable us to provide evidence-based care.

scholarly journals Incidence of Benign Meningiomas in the United States: Current and Future Trends

2021 ◽  
Author(s):  
Sonia Bhala ◽  
Douglas R Stewart ◽  
Victoria Kennerley ◽  
Valentina I Petkov ◽  
Philip S Rosenberg ◽  
...  
Keyword(s):  
United States ◽  
Age Groups ◽  
Cancer Registries ◽  
Health Impact ◽  
The United States ◽  
Birth Cohorts ◽  
Benign Meningioma ◽  
Case Count ◽  
Future Burden ◽  
Rate Ratios

Abstract Background Benign meningiomas are the most frequently reported central nervous system tumors in the United States (US), with increasing incidence in past decades. However, the future trajectory of this neoplasm remains unclear. Methods We analyzed benign meningioma incidence of cases identified by any means (eg, radiographically with or without microscopic confirmation) in US Surveillance Epidemiology and End Results (SEER) cancer registries among 35–84-year-olds during 2004–2017 by sex and race/ethnicity using age-period-cohort (APC) models. We employed APC forecasting models to glean insights regarding the etiology, distribution, and anticipated future (2018–2027) public health impact of this neoplasm. Results In all groups, meningioma incidence overall increased through 2010, then stabilized. Temporal declines were statistically significant overall and in most groups. JoinPoint analysis of cohort rate-ratios identified substantial acceleration in White men born after 1963 (from 1.1% to 3.2% per birth year); cohort rate-ratios were stable or increasing in all groups and all birth cohorts. We forecast that meningioma incidence through 2027 will remain stable or decrease among 55–84-year-olds but remain similar to current levels among 35–54-year-olds. Total meningioma burden in 2027 is expected to be approximately 30,470 cases, similar to the expected case count of 27,830 in 2018. Conclusions Between 2004–2017, overall incidence of benign meningioma increased and then stabilized or declined. For 2018–2027, our forecast is incidence will remain generally stable in younger age groups but decrease in older age groups. Nonetheless, the total future burden will remain similar to current levels because the population is aging.

scholarly journals Global Burden, Risk Factors, and Trends of Esophageal Cancer: An Analysis of Cancer Registries from 48 Countries

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 141
Author(s):  
Junjie Huang ◽  
Anastasios Koulaouzidis ◽  
Wojciech Marlicz ◽  
Veeleah Lok ◽  
Cedric Chu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Esophageal Cancer ◽  
The Netherlands ◽  
Cancer Registries ◽  
Global Burden ◽  
Annual Percent Change ◽  
The United Kingdom ◽  
Incidence And Mortality ◽  
Elevated Cholesterol ◽  
Prevalence Of Obesity

This study aimed to examine the global burden, risk factors, and trends of esophageal cancer based on age, sex, and histological subtype. The data were retrieved from cancer registries database from 48 countries in the period 1980–2017. Temporal patterns of incidence and mortality were evaluated by average annual percent change (AAPC) using joinpoint regression. Associations with risk factors were examined by linear regression. The highest incidence of esophageal cancer was observed in Eastern Asia. The highest incidence of adenocarcinoma (AC) was found in the Netherlands, the United Kingdom, and Ireland. A higher AC/squamous cell carcinoma (SCC) incidence ratio was associated with a higher prevalence of obesity and elevated cholesterol. We observed an incidence increase (including AC and SCC) in some countries, with the Czech Republic (female: AAPC 4.66), Spain (female: 3.41), Norway (male: 3.10), Japan (female: 2.18), Thailand (male: 2.17), the Netherlands (male: 2.11; female: 1.88), and Canada (male: 1.51) showing the most significant increase. Countries with increasing mortality included Thailand (male: 5.24), Austria (female: 3.67), Latvia (male: 2.33), and Portugal (male: 1.12). Although the incidence of esophageal cancer showed an overall decreasing trend, an increasing trend was observed in some countries with high AC/SCC incidence ratios. More preventive measures are needed for these countries.

scholarly journals Food Environments and Hepatocellular Carcinoma Incidence

2021 ◽  
Vol 18 (11) ◽  
pp. 5740
Author(s):  
Mimi Ton ◽  
Michael J. Widener ◽  
Peter James ◽  
Trang VoPham
Keyword(s):  
Hepatocellular Carcinoma ◽  
Food Environment ◽  
Variance Estimation ◽  
Cancer Registries ◽  
County Level ◽  
Individual Level ◽  
Retail Food Environment ◽  
Food Retailers ◽  
Environment Index ◽  
Rate Ratios

Research into the potential impact of the food environment on liver cancer incidence has been limited, though there is evidence showing that specific foods and nutrients may be potential risk or preventive factors. Data on hepatocellular carcinoma (HCC) cases were obtained from the Surveillance, Epidemiology, and End Results (SEER) cancer registries. The county-level food environment was assessed using the Modified Retail Food Environment Index (mRFEI), a continuous score that measures the number of healthy and less healthy food retailers within counties. Poisson regression with robust variance estimation was used to calculate incidence rate ratios (IRRs) and 95% confidence intervals (CIs) for the association between mRFEI scores and HCC risk, adjusting for individual- and county-level factors. The county-level food environment was not associated with HCC risk after adjustment for individual-level age at diagnosis, sex, race/ethnicity, year, and SEER registry and county-level measures for health conditions, lifestyle factors, and socioeconomic status (adjusted IRR: 0.99, 95% CI: 0.96, 1.01). The county-level food environment, measured using mRFEI scores, was not associated with HCC risk.

scholarly journals Spectroscopic and deep learning-based approaches to identify and quantify cerebral microhemorrhages

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Christian Crouzet ◽  
Gwangjin Jeong ◽  
Rachel H. Chae ◽  
Krystal T. LoPresti ◽  
Cody E. Dunn ◽  
...  
Keyword(s):  
Deep Learning ◽  
Prussian Blue ◽  
Processing Speed ◽  
Digital Pathology ◽  
Ground Truth ◽  
Individual Variability ◽  
Rgb Images ◽  
Cerebral Microhemorrhages ◽  
Phasor Analysis ◽  
Better Than

AbstractCerebral microhemorrhages (CMHs) are associated with cerebrovascular disease, cognitive impairment, and normal aging. One method to study CMHs is to analyze histological sections (5–40 μm) stained with Prussian blue. Currently, users manually and subjectively identify and quantify Prussian blue-stained regions of interest, which is prone to inter-individual variability and can lead to significant delays in data analysis. To improve this labor-intensive process, we developed and compared three digital pathology approaches to identify and quantify CMHs from Prussian blue-stained brain sections: (1) ratiometric analysis of RGB pixel values, (2) phasor analysis of RGB images, and (3) deep learning using a mask region-based convolutional neural network. We applied these approaches to a preclinical mouse model of inflammation-induced CMHs. One-hundred CMHs were imaged using a 20 × objective and RGB color camera. To determine the ground truth, four users independently annotated Prussian blue-labeled CMHs. The deep learning and ratiometric approaches performed better than the phasor analysis approach compared to the ground truth. The deep learning approach had the most precision of the three methods. The ratiometric approach has the most versatility and maintained accuracy, albeit with less precision. Our data suggest that implementing these methods to analyze CMH images can drastically increase the processing speed while maintaining precision and accuracy.

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