RADIFUSION: A multi-radiomics deep learning based breast cancer risk prediction model using sequential mammographic images with image attention and bilateral asymmetry refinement

Breast cancer is a significant public health concern and early detection is critical for triaging high risk patients. Sequential screening mammograms can provide important spatiotemporal information about changes in breast tissue over time. In this study, we propose a deep learning architecture called RADIFUSION that utilizes sequential mammograms and incorporates a linear image attention mechanism, radiomic features, a new gating mechanism to combine different mammographic views, and bilateral asymmetry-based finetuning for breast cancer risk assessment. We evaluate our model on a screening dataset called Cohort of Screen-Aged Women (CSAW) dataset. Based on results obtained on the independent testing set consisting of 1,749 women, our approach achieved superior performance compared to other state-of-the-art models with area under the receiver operating characteristic curves (AUCs) of 0.905, 0.872 and 0.866 in the three respective metrics of 1-year AUC, 2-year AUC and > 2-year AUC. Our study highlights the importance of incorporating various deep learning mechanisms, such as image attention, radiomic features, gating mechanism, and bilateral asymmetry-based fine-tuning, to improve the accuracy of breast cancer risk assessment. We also demonstrate that our model's performance was enhanced by leveraging spatiotemporal information from sequential mammograms. Our findings suggest that RADIFUSION can provide clinicians with a powerful tool for breast cancer risk assessment.Comment: v

DNA methylation-based biological age, genome-wide average DNA methylation, and conventional breast cancer risk factors.

DNA methylation-based biological age (DNAm age), as well as genome-wide average DNA methylation, have been reported to predict breast cancer risk. We aimed to investigate the associations between these DNA methylation-based risk factors and 18 conventional breast cancer risk factors for disease-free women. A sample of 479 individuals from the Australian Mammographic Density Twins and Sisters was used for discovery, a sample of 3354 individuals from the Melbourne Collaborative Cohort Study was used for replication, and meta-analyses pooling results from the two studies were conducted. DNAm age based on three epigenetic clocks (Hannum, Horvath and Levine) and genome-wide average DNA methylation were calculated using the HumanMethylation 450 K BeadChip assay data. The DNAm age measures were positively associated with body mass index (BMI), smoking, alcohol drinking and age at menarche (all nominal P < 0.05). Genome-wide average DNA methylation was negatively associated with smoking and number of live births, and positively associated with age at first live birth (all nominal P < 0.05). The association of DNAm age with BMI was also evident in within-twin-pair analyses that control for familial factors. This study suggests that some lifestyle and hormonal risk factors are associated with these DNA methylation-based breast cancer risk factors, and the observed associations are unlikely to be due to familial confounding but are likely causal. DNA methylation-based risk factors could interplay with conventional risk factors in modifying breast cancer risk

Mapping for engagement: setting up a community based participatory research project to reach underserved communities at risk for Hepatitis C in Ho Chi Minh City, Vietnam

Background: Approximately 1. 07 million people in Vietnam are infected with hepatitis C virus (HCV). To address this epidemic, the South East Asian Research Collaborative in Hepatitis (SEARCH) launched a 600-patient cohort study and two clinical trials, both investigating shortened treatment strategies for chronic HCV infection with direct-acting antiviral drugs. We conducted ethnographic research with a subset of trial participants and found that the majority were aware of HCV infection and its implications and were motivated to seek treatment. However, people who inject drugs (PWID), and other groups at risk for HCV were under-represented, although injecting drug use is associated with high rates of HCV. Material and Methods: We designed a community-based participatory research (CBPR) study to engage in dialogues surrounding HCV and other community-prioritized health issues with underserved groups at risk for HCV in Ho Chi Minh City. The project consists of three phases: situation analysis, CBPR implementation, and dissemination. In this paper, we describe the results of the first phase (i.e., the situation analysis) in which we conducted desk research and organized stakeholder mapping meetings with representatives from local non-government and community-based organizations where we used participatory research methods to identify and analyze key stakeholders working with underserved populations. Results: Twenty six institutions or groups working with the key underserved populations were identified. Insights about the challenges and dynamics of underserved communities were also gathered. Two working groups made up of representatives from the NGO and CBO level were formed. Discussion: Using the information provided by local key stakeholders to shape the project has helped us to build solid relationships, give the groups a sense of ownership from the early stages, and made the project more context specific. These steps are not only important preliminary steps for participatory studies but also for other research that takes place within the communities

Elevated Levels of Cell-Free Circulating DNA in Patients with Acute Dengue Virus Infection

BACKGROUND: Apoptosis is thought to play a role in the pathogenesis of severe dengue and the release of cell-free DNA into the circulatory system in several medical conditions. Therefore, we investigated circulating DNA as a potential biomarker for severe dengue. METHODS AND FINDINGS: A direct fluorometric degradation assay using PicoGreen was performed to quantify cell-free DNA from patient plasma. Circulating DNA levels were significantly higher in patients with dengue virus infection than with other febrile illnesses and healthy controls. Remarkably, the increase of DNA levels correlated with the severity of dengue. Additionally, multivariate logistic regression analysis showed that circulating DNA levels independently correlated with dengue shock syndrome. CONCLUSIONS: Circulating DNA levels were increased in dengue patients and correlated with dengue severity. Additional studies are required to show the benefits of this biomarker in early dengue diagnosis and for the prognosis of shock complication

Characteristics of attempted suicides seen in emergency-care settings of general hospitals in eight low- and middle-income countries

Background. The objective was to describe patients presenting themselves at emergency-care settings following a suicide attempt in eight culturally different sites Campinas (Brazil), Chennai (India), Colombo (Sri Lanka), Durban (South Africa), Hanoi (Viet Nam), Karaj (Iran), Tallinn (Estonia), and Yuncheng, (China). Method. Subjects seen for su icide attempts, as identified by the medical staff in the emergency units of 18 collaborating hospitals were asked to participate in a 45-minute structured interview administered by trained health personnel after the patient was medically stable. Result s. Self-poisoning was the main method of attempting suicide in all eight sites. Self-poisoning by pesticides played a particularly important role in Yuncheng (71·6% females, 61·5% males), in Colombo (43·2% males, 19·6% females), and in Chennai (33·8% males, 23·8% females). The suicide attempt resulted in danger to life in the majority of patients in Yuncheng and in Chennai (over 65%). In four of the eight sites less than one-third of subjects received any type of referral for follow-up evaluation or care. Conclus ions. Action for the prevention of suicide attempts can be started immediately in the sites investigated by addressing the one most important method of attempted suicide, namely self-poisoning. Regulations for the access to drugs, medicaments, pesticides, and other toxic substances need to be improved and revised regulations must be implemented by integrating the efforts of different sectors, such as health, agriculture, education, and justice. The care of patients who attempt suicide needs to include routine psychiatric and psychosocial assessment and systematic referral to professional services after discharge. © 2005 Cambridge University Press

Measurement challenge : protocol for international case–control comparison of mammographic measures that predict breast cancer risk

Introduction: For women of the same age and body mass index, increased mammographic density is one of the strongest predictors of breast cancer risk. There are multiple methods of measuring mammographic density and other features in a mammogram that could potentially be used in a screening setting to identify and target women at high risk of developing breast cancer. However, it is unclear which measurement method provides the strongest predictor of breast cancer risk. Methods and analysis: The measurement challenge has been established as an international resource to offer a common set of anonymised mammogram images for measurement and analysis. To date, full field digital mammogram images and core data from 1650 cases and 1929 controls from five countries have been collated. The measurement challenge is an ongoing collaboration and we are continuing to expand the resource to include additional image sets across different populations (from contributors) and to compare additional measurement methods (by challengers). The intended use of the measurement challenge resource is for refinement and validation of new and existing mammographic measurement methods. The measurement challenge resource provides a standardised dataset of mammographic images and core data that enables investigators to directly compare methods of measuring mammographic density or other mammographic features in case/control sets of both raw and processed images, for the purposes of the comparing their predictions of breast cancer risk. Ethics and dissemination: Challengers and contributors are required to enter a Research Collaboration Agreement with the University of Melbourne prior to participation in the measurement challenge. The Challenge database of collated data and images are stored in a secure data repository at the University of Melbourne. Ethics approval for the measurement challenge is held at University of Melbourne (HREC ID 0931343.3)

Genetic and environmental causes of variation in epigenetic aging across the lifespan

Abstract: Background: DNA methylation-based biological age (DNAm age) is an important biomarker for adult health. Studies in specific age ranges have found widely varying results about its genetic and environmental causes of variation. However, these studies are not able to provide a comprehensive view of the causes of variation over the lifespan. Results: In order to investigate the genetic and environmental causes of DNAm age variation across the lifespan, we pooled genome-wide DNA methylation data for 4217 people aged 0–92 years from 1871 families. DNAm age was calculated using the Horvath epigenetic clock. We estimated familial correlations in DNAm age for monozygotic (MZ) twin, dizygotic (DZ) twin, sibling, parent–offspring, and spouse pairs by cohabitation status. Genetic and environmental variance components models were fitted and compared. We found that twin pair correlations were − 0.12 to 0.18 around birth, not different from zero (all P > 0.29). For all pairs of relatives, their correlations increased with time spent living together (all P DZ and siblings > parent–offspring; P < 0.001) and decreased with time spent living apart (P = 0.02) at similar rates. These correlation patterns were best explained by cohabitation-dependent shared environmental factors, the effects of which were 1.41 (95% confidence interval [CI] 1.16 to 1.66) times greater for MZ pairs than for DZ and sibling pairs, and the latter were 2.03 (95% CI 1.13 to 9.47) times greater than for parent–offspring pairs. Genetic factors explained 13% (95% CI − 10 to 35%) of variation (P = 0.27). Similar results were found for another two epigenetic clocks, suggesting that our observations are robust to how DNAm age is measured. In addition, results for the other clocks were consistent with there also being a role for prenatal environmental factors in determining their variation. Conclusions: Variation in DNAm age is mostly caused by environmental factors, including those shared to different extents by relatives while living together and whose effects persist into old age. The equal environment assumption of the classic twin study might not hold for epigenetic aging

Predicting interval and screen-detected breast cancers from mammographic density defined by different brightness thresholds.

BACKGROUND: Case-control studies show that mammographic density is a better risk factor when defined at higher than conventional pixel-brightness thresholds. We asked if this applied to interval and/or screen-detected cancers. METHOD: We conducted a nested case-control study within the prospective Melbourne Collaborative Cohort Study including 168 women with interval and 422 with screen-detected breast cancers, and 498 and 1197 matched controls, respectively. We measured absolute and percent mammographic density using the Cumulus software at the conventional threshold (Cumulus) and two increasingly higher thresholds (Altocumulus and Cirrocumulus, respectively). Measures were transformed and adjusted for age and body mass index (BMI). Using conditional logistic regression and adjusting for BMI by age at mammogram, we estimated risk discrimination by the odds ratio per adjusted standard deviation (OPERA), calculated the area under the receiver operating characteristic curve (AUC) and compared nested models using the likelihood ratio criterion and models with the same number of parameters using the difference in Bayesian information criterion (ΔBIC). RESULTS: For interval cancer, there was very strong evidence that the association was best predicted by Cumulus as a percentage (OPERA = 2.33 (95% confidence interval (CI) 1.85-2.92); all ΔBIC > 14), and the association with BMI was independent of age at mammogram. After adjusting for percent Cumulus, no other measure was associated with risk (all P > 0.1). For screen-detected cancer, however, the associations were strongest for the absolute and percent Cirrocumulus measures (all ΔBIC > 6), and after adjusting for Cirrocumulus, no other measure was associated with risk (all P > 0.07). CONCLUSION: The amount of brighter areas is the best mammogram-based measure of screen-detected breast cancer risk, while the percentage of the breast covered by white or bright areas is the best mammogram-based measure of interval breast cancer risk, irrespective of BMI. Therefore, there are different features of mammographic images that give clinically important information about different outcomes

Genetic and environmental causes of variation in epigenetic aging across the lifespan.

BACKGROUND: DNA methylation-based biological age (DNAm age) is an important biomarker for adult health. Studies in specific age ranges have found widely varying results about its genetic and environmental causes of variation. However, these studies are not able to provide a comprehensive view of the causes of variation over the lifespan. RESULTS: In order to investigate the genetic and environmental causes of DNAm age variation across the lifespan, we pooled genome-wide DNA methylation data for 4217 people aged 0-92 years from 1871 families. DNAm age was calculated using the Horvath epigenetic clock. We estimated familial correlations in DNAm age for monozygotic (MZ) twin, dizygotic (DZ) twin, sibling, parent-offspring, and spouse pairs by cohabitation status. Genetic and environmental variance components models were fitted and compared. We found that twin pair correlations were - 0.12 to 0.18 around birth, not different from zero (all P > 0.29). For all pairs of relatives, their correlations increased with time spent living together (all P  DZ and siblings > parent-offspring; P < 0.001) and decreased with time spent living apart (P = 0.02) at similar rates. These correlation patterns were best explained by cohabitation-dependent shared environmental factors, the effects of which were 1.41 (95% confidence interval [CI] 1.16 to 1.66) times greater for MZ pairs than for DZ and sibling pairs, and the latter were 2.03 (95% CI 1.13 to 9.47) times greater than for parent-offspring pairs. Genetic factors explained 13% (95% CI - 10 to 35%) of variation (P = 0.27). Similar results were found for another two epigenetic clocks, suggesting that our observations are robust to how DNAm age is measured. In addition, results for the other clocks were consistent with there also being a role for prenatal environmental factors in determining their variation. CONCLUSIONS: Variation in DNAm age is mostly caused by environmental factors, including those shared to different extents by relatives while living together and whose effects persist into old age. The equal environment assumption of the classic twin study might not hold for epigenetic aging