Fully automated deep learning based auto-contouring of liver segments and spleen on contrast-enhanced CT images.

Manual delineation of liver segments on computed tomography (CT) images for primary/secondary liver cancer (LC) patients is time-intensive and prone to inter/intra-observer variability. Therefore, we developed a deep-learning-based model to auto-contour liver segments and spleen on contrast-enhanced CT (CECT) images. We trained two models using 3d patch-based attention U-Net ([Formula: see text] and 3d full resolution of nnU-Net ([Formula: see text] to determine the best architecture ([Formula: see text]. BA was used with vessels ([Formula: see text] and spleen ([Formula: see text] to assess the impact on segment contouring. Models were trained, validated, and tested on 160 ([Formula: see text]), 40 ([Formula: see text]), 33 ([Formula: see text]), 25 (CCH) and 20 (CPVE) CECT of LC patients. [Formula: see text] outperformed [Formula: see text] across all segments with median differences in Dice similarity coefficients (DSC) ranging 0.03-0.05 (p < 0.05). [Formula: see text], and [Formula: see text] were not statistically different (p > 0.05), however, both were slightly better than [Formula: see text] by DSC up to 0.02. The final model, [Formula: see text], showed a mean DSC of 0.89, 0.82, 0.88, 0.87, 0.96, and 0.95 for segments 1, 2, 3, 4, 5-8, and spleen, respectively on entire test sets. Qualitatively, more than 85% of cases showed a Likert score [Formula: see text] 3 on test sets. Our final model provides clinically acceptable contours of liver segments and spleen which are usable in treatment planning.

A Novel Technique for Performing Transfemoral Transcatheter Self-Expanding Aortic Valve Replacement With No Contrast Which Minimizes Acute Kidney Injury.

Transcatheter aortic valve replacement (TAVR) treats severe aortic stenosis. However, patients with limited renal function may be ineligible for contrast use during valve deployment. We evaluate TAVR via transfemoral approach using 2-wire technique and no contrast injection. Primary endpoints are acute kidney injury and procedural success. Safety analysis includes mortality, stroke, myocardial infarction, coronary obstruction, and more. Forty-six patients were included; most with preserved ejection fraction. Baseline creatinine was 1.63 ± 0.68 and post-TAVR was significantly better (1.47 ± 0.64, P < 0.01). No statistical difference existed between creatinine at baseline and 30 days. After TAVR, 91% had no paravalvular leak (PVL). Peak-velocity post-TAVR was 1.32 ± 0.33 and mean-gradient was 7 ± 4. No valve repositioning during deployment was required. No mortality at 30 days without incidence of stroke, myocardial infarction or coronary obstruction. One patient had retroperitoneal bleeding requiring transfusion. The noncontrast technique for self-expanding valve deployment is feasible and safe in patients who cannot tolerate contrast.

Analysis and prediction of liver volume change maps derived from computational tomography scans acquired pre- and post-radiation therapy.

External beam radiation therapy (EBRT) of liver cancers can cause local liver atrophy as a result of tissue damage or hypertrophy as a result of liver regeneration. Predicting those volumetric changes would enable new strategies for liver function preservation during treatment planning. However, understanding of the spatial dose/volume relationship is still limited. This study leverages the use of deep learning-based segmentation and biomechanical deformable image registration (DIR) to analyze and predict this relationship. Pre- and Post-EBRT imaging data were collected for 100 patients treated for hepatocellular carcinomas, cholangiocarcinoma or CRC with intensity-modulated radiotherapy (IMRT) with prescription doses ranging from 50 to 100 Gy delivered in 10-28 fractions. For each patient, DIR between the portal and venous (PV) phase of a diagnostic computed tomography (CT) scan acquired before radiation therapy (RT) planning, and a PV phase of a diagnostic CT scan acquired after the end of RT (on average 147 ± 36 d) was performed to calculate Jacobian maps representing volume changes in the liver. These volume change maps were used: (i): to analyze the dose/volume relationship in the whole liver and individual Couinaud's segments; and (ii): to investigate the use of deep-learning to predict a Jacobian map solely based on the pre-RT diagnostic CT and planned dose distribution. Moderate correlations between mean equivalent dose in 2 Gy fractions (EQD2) and volume change was observed for all liver sub-regions analyzed individually with Pearson correlationrranging from -0.36 to -067. The predicted volume change maps showed a significantly stronger voxel-wise correlation with the DIR-based volume change maps than when considering the original EQD2 distribution (0.63 ± 0.24 versus 0.55 ± 23, respectively), demonstrating the ability of the proposed approach to establish complex relationships between planned dose and liver volume response months after treatment, which represents a promising prediction tool for the development of future adaptive and personalized liver radiation therapy strategies.

Changing socioeconomic and geographic gradients in cardiovascular disease risk factors among Indians aged 15-49 years - evidence from nationally representative household surveys.

Background: Cardiovascular diseases (CVDs) are the leading cause of death in most low- and middle-income countries (LMICs). CVDs and their metabolic risk factors have historically been concentrated among urban residents with higher socioeconomic status (SES) in LMICs such as India. However, as India develops, it is unclear whether these socioeconomic and geographic gradients will persist or change. Understanding these social dynamics in CVD risk is essential for mitigating the rising burden of CVDs and to reach those with the greatest needs. Methods: Using nationally representative data with biomarker measurements from the fourth (2015-16) and fifth (2019-21) Indian National Family and Health Surveys, we investigated trends in the prevalence of four CVD risk factors: smoking (self-reported), unhealthy weight (BMI ≥25 kgm2), diabetes (random plasma glucose concentration ≥200 mg/dL or self-reported diabetes), and hypertension (one of: average systolic blood pressure ≥140 mmHg, average diastolic blood pressure ≥90 mmHg, self-reported past diagnosis, or self-reported current antihypertensive medication use) among adults aged 15-49 years. We first described changes at the national level and then trends stratified by place of residence (urban versus rural), geographic region (northern, northeastern, central, eastern, western, southern), regional level of development (Empowered Action Group member state or not), and two measures of socioeconomic status: level of education (no education, primary incomplete, primary complete, secondary incomplete, secondary complete, higher) and wealth (quintiles). Findings: Unhealthy weight increased among all social and geographic groups but both the absolute and the relative changes were substantially higher among people with low SES (as measured by education or wealth) and in rural areas. For diabetes and hypertension, the prevalence increased for those from disadvantaged groups while staying constant or even decreasing among the wealthier and more educated. In contrast, smoking consumption declined for all social and geographic groups. Interpretation: In 2015-16, CVD risk factors were higher among more advantaged subpopulations in India. However, between 2015-16 and 2019-21, the prevalence of these risk factors grew more rapidly for less wealthy and less educated subpopulations and those living in rural areas. These trends have resulted in CVD risk becoming far more widespread throughout the population; CVD can no longer be characterized as a wealthy urban phenomenon. Funding: This work was supported by the Alexander von Humboldt Foundation (grant received by NS); the Stanford Diabetes Research Center [grant received by PG] and the Chan Zuckerberg Biohub [grant received by PG].

Automated Contouring and Planning in Radiation Therapy: What Is 'Clinically Acceptable'?

Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is 'clinical acceptability'? Quantitative and qualitative approaches have been used to assess this ill-defined concept, all of which have advantages and disadvantages or limitations. The approach chosen may depend on the goal of the study as well as on available resources. In this paper, we discuss various aspects of 'clinical acceptability' and how they can move us toward a standard for defining clinical acceptability of new autocontouring and planning tools.

To Anticoagulate or Not to Anticoagulate in COVID-19: Lessons after 2 Years.

A hypercoagulable state associated with coronavirus disease 2019 (COVID-19) has been well documented and is believed to be strongly supported by a proinflammatory state. The hypercoagulable state in turn results in increased incidence of arterial and venous thromboembolism (VTE) seen in hospitalized COVID-19 when compared with hospitalized non-COVID-19 patient cohorts. Moreover, patients with arterial or VTE and COVID-19 have higher mortality compared with COVID-19 patients without arterial or VTE. Prevention of arterial or VTE thus remains an essential question in the management of COVID-19 patients, especially because of high rates of reported microvascular and macrovascular thrombosis. This has prompted multiple randomized control trials (RCTs) evaluating different anticoagulation strategies in COVID-19 patients at various stages of the disease. Herein, we review findings from RCTs in the past 2 years of antithrombotic therapy in critically ill hospitalized patients, noncritically ill hospitalized patients, patients postdischarge from the hospital, and outpatients. RCTs in critically ill patients demonstrated therapeutic dose anticoagulation does not improve outcomes and has more bleeding than prophylaxis dose anticoagulant in these patients. Trials in noncritically ill hospitalized patients showed a therapeutic dose anticoagulation with a heparin formulation might improve clinical outcomes. Anticoagulation with a direct oral anticoagulant posthospital discharge may improve outcomes, although there is a large RCT in progress. Nonhospitalized COVID-19 patients have an insufficient burden of events to be candidates for antithrombotic therapy. Anticoagulation in pregnant and lactating patients with COVID-19, as well as antiplatelet therapy for COVID-19, is also reviewed.

Changes in Child Undernutrition and Overweight in India From 2006 to 2021: An Ecological Analysis of 36 States.

OBJECTIVES: We evaluated changes in priority indicators of child growth from 2006 to 2021 and examined the role of human development measures in these changes. METHODS: We estimated cumulative and annualized changes in state- and district-level child growth indicators using 3 rounds of National Family Health Surveys (2005-2006, 2015-2016, 2019-2021) in 36 states. Outcomes included stunting, underweight, wasting, and overweight. Human development was measured using a principal components analysis of 9 ecological indicators. We contrasted expected versus observed changes in district-level growth outcomes between 2016 and 2021 based on changes in development indicators using 2-way Blinder Oaxaca decomposition. RESULTS: From 2006 to 2021, the prevalence of stunting, underweight, and wasting decreased by 12.3, 10.3, and 0.7 percentage points, respectively, while the prevalence of overweight increased by 1.9 percentage points. The annualized rate of within-state change for stunting was lower from 2016 to 2021 compared with the 2006 to 2016 period, while the rate of change in overweight was higher. Simultaneously, all 9 human development indicators improved between 2006 and 2021. A unit increase between 2016 and 2021 in the human development score predicted a -5.1 percentage point (95% confidence interval=-5.8, -4.4) change in stunting, yet observed stunting declined by just -2.5 percentage points. CONCLUSIONS: From 2016 to 2021, population-level reduction in child stunting has slowed and the rise in child overweight has accelerated, relative to the 10 years preceding this period.

Development and validation of a population-based anatomical colorectal model for radiation dosimetry in late effects studies of survivors of childhood cancer.

PURPOSE: The purposes of this study were to develop and integrate a colorectal model that incorporates anatomical variations of pediatric patients into the age-scalable MD Anderson Late Effects (MDA-LE) computational phantom, and validate the model for pediatric radiation therapy (RT) dose reconstructions. METHODS: Colorectal contours were manually derived from whole-body non-contrast computed tomography (CT) scans of 114 pediatric patients (age range: 2.1-21.6 years, 74 males, 40 females). One contour was used for an anatomical template, 103 for training and 10 for testing. Training contours were used to create a colorectal principal component analysis (PCA)-based statistical shape model (SSM) to extract the population's dominant deformations. The SSM was integrated into the MDA-LE phantom. Geometric accuracy was assessed between patient-specific and SSM contours using several overlap metrics. Two alternative colorectal shapes were generated using the first 17 dominant modes of the PCA-based SSM. Dosimetric accuracy was assessed by comparing colorectal doses from test patients' CT-based RT plans (ground truth) with reconstructed doses for the mean and two alternative models in age-matched MDA-LE phantoms. RESULTS: When using all 103 PCA modes, the mean (min-max) Dice similarity coefficient, distance-to-agreement and Hausdorff distance between the patient-specific and reconstructed contours for the test patients were 0.89 (0.85-0.91), 2.1 mm (1.7-3.0), and 8.6 mm (5.7-14.3), respectively. The average percent difference between reconstructed and ground truth mean and maximum colorectal doses for the mean (alternative 1, 2) model were 6.3% (8.1%, 6.1%) and 4.4% (4.3%, 4.7%), respectively. CONCLUSIONS: We developed, validated and integrated a colorectal PCA-based SSM into the MDA-LE phantom and demonstrated its dosimetric performance for accurate pediatric RT dose reconstruction.

Seasonal variation in infant mortality in India.

Investigating seasonal variation in health helps us understand interactions between population, environment, and disease. Using information on birth month and year, survival status within the first year of life, and age at death (if applicable) of more than 330,000 children observed in four rounds of India's Demographic and Health Surveys, I estimate period mortality rates between birth and age one (1m0) by calendar month. Relative to spring months, infant mortality is higher in the summer, monsoon, and winter months. If spring mortality conditions had been prevalent throughout the year, mortality below age one would have been lower by 11.4 deaths per 1,000 in the early 1990s and 3.7 deaths per 1,000 in the mid-2010s. Seasonal variation in infant mortality has declined overall but remains higher among disadvantaged children. The results highlight the multiple environmental health threats that Indian infants face and the short time of year when these threats are less salient.

Can administrative health data be used to estimate population level birth and child mortality estimates? A comparison of India's Health Information Management System data with nationally representative survey data.

•HMIS covers a large proportion of births, but a smaller fraction of child deaths compared to estimates from surveys.•Birth and death coverage in HMIS, while incomplete, has been improving nationally and for many states.•States that have improved HMIS reporting, should be studied for replicating best practices.•HMIS can provide signals for real time policy decisions, if used with due consideration of its limitations.•Including patient socioeconomic and demographic traits in HMIS, could further bolster its utility in population health.

Peripheral arterial disease and hypertension.

PURPOSE OF REVIEW: Hypertension (HTN) is a well known risk factor for atherosclerosis and peripheral arterial disease (PAD). PAD affects more than 250 million people globally and is associated with worse clinical outcomes. Although multiple studies have been performed to evaluate treatment of HTN in patients with PAD, blood pressure management in this high-risk cohort remains poor. RECENT FINDINGS: There has been conflicting evidence regarding blood pressure goals in PAD with some recent studies showing adverse outcomes with low blood pressure in this patient population. Current guidelines, however, continue to recommend treatment goals in PAD patients similar to patients without PAD. To date, no single antihypertensive drug class has shown a clear benefit in PAD population over other antihypertensive drug classes. SUMMARY: Prospective randomized trials enrolling PAD patients are required that can shed light on optimum blood pressure target and also distinguish between different antihypertensive drugs in terms of reducing adverse outcomes.

Social disadvantage, economic inequality, and life expectancy in nine Indian states.

SignificanceIndia is one of the most hierarchical societies in the world. Because vital statistics are incomplete, mortality disparities are not quantified. Using survey data on more than 20 million individuals from nine Indian states representing about half of India's population, we estimate and decompose life expectancy differences between higher-caste Hindus, comprising other backward classes and high castes, and three marginalized social groups: Adivasis (indigenous peoples), Dalits (oppressed castes), and Muslims. The three marginalized groups experience large disadvantages in life expectancy at birth relative to higher-caste Hindus. Economic status explains less than half of these gaps. These large disparities underscore parallels between diverse systems of discrimination akin to racism. They highlight the global significance of addressing social inequality in India.

Endovascular Management of Chronic Mesenteric Ischemia in a Patient With Left Ventricular Assist Device.

Classical symptoms of chronic mesenteric ischemia include postprandial pain referred to as "intestinal angina", food fear and weight loss. Here we present a case of chronic mesenteric ischemia treated by endovascular stenting in a patient with chronic heart failure and left ventricular assist device.

Assessing mortality registration in Kerala: the MARANAM study.

Complete or improving civil registration systems in sub-national areas in low- and middle-income countries provide several opportunities to better understand population health and its determinants. In this article, we provide an assessment of vital statistics in Kerala, India. Kerala is home to more than 33 million people and is a comparatively low-mortality context. We use individual-level vital registration data on more than 2.8 million deaths between 2006 and 2017 from the Kerala MARANAM (Mortality and Registration Assessment and Monitoring) Study. Comparing age-specific mortality rates from the Civil Registration System (CRS) to those from the Sample Registration System (SRS), we do not find evidence that the CRS underestimates mortality. Instead, CRS rates are smoother across ages and less variable across periods. In particular, the CRS records higher death rates than the SRS for ages, where mortality is usually low and for women. Using these data, we provide the first set of annual sex-specific life tables for any state in India. We find that life expectancy at birth was 77.9 years for women in 2017 and 71.4 years for men. Although Kerala is unique in many ways, our findings strengthen the case for more careful attention to mortality records within low- and middle-income countries, and for their better dissemination by government agencies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41118-021-00149-z.

Estimates of pandemic excess mortality in India based on civil registration data.

The population health impacts of the COVID-19 pandemic are less well understood in low and middle-income countries, where mortality surveillance before the pandemic was patchy. Interpreting the limited all-cause mortality data available in India is challenging. We use existing data on all-cause mortality from civil registration systems of twelve Indian states comprising around 60% of the national population to understand the scale and timing of excess deaths in India during the COVID-19 pandemic. We carefully characterize the reasons why registration is incomplete and estimate the extent of coverage in the data. Comparing the pandemic period to 2019, we estimate excess mortality in twelve Indian states, and extrapolate our estimates to the rest of India. We explore sensitivity of the estimates to various assumptions. For the 12 states with available all-cause mortality data, we document an increase of 28% in deaths during April 2020-May 2021 relative to expectations from 2019. This level of increase in mortality, if it applies nationally, would imply 2.8-2.9 million excess deaths. More limited data from June 2021 increases national estimates of excess deaths during April 2020-June 2021 to 3.8 million. With more optimistic or pessimistic assumptions, excess deaths during this period could credibly lie between 2.8 million and 5.2 million. The scale of estimated excess deaths is broadly consistent with expectations based on seroprevalence and COVID-19 fatality rates observed internationally. Moreover, the timing of excess deaths and recorded COVID-19 deaths is similar-they rise and fall at the same time. The surveillance of pandemic mortality in India has been extremely poor, with 8-10 times as many excess deaths as officially recorded COVID-19 deaths. India is among the countries most severely impacted by the pandemic. Our approach highlights the utility of all-cause mortality data, as well as the significant challenges in interpreting it.

Body region-specific 3D age-scaling functions for scaling whole-body computed tomography anatomy for pediatric late effects studies.

Purpose.Radiation epidemiology studies of childhood cancer survivors treated in the pre-computed tomography (CT) era reconstruct the patients' treatment fields on computational phantoms. For such studies, the phantoms are commonly scaled to age at the time of radiotherapy treatment because age is the generally available anthropometric parameter. Several reference size phantoms are used in such studies, but reference size phantoms are only available at discrete ages (e.g.: newborn, 1, 5, 10, 15, and Adult). When such phantoms are used for RT dose reconstructions, the nearest discrete-aged phantom is selected to represent a survivor of a specific age. In this work, we (1) conducted a feasibility study to scale reference size phantoms at discrete ages to various other ages, and (2) evaluated the dosimetric impact of using exact age-scaled phantoms as opposed to nearest age-matched phantoms at discrete ages.Methods.We have adopted the University of Florida/National Cancer Institute (UF/NCI) computational phantom library for our studies. For the feasibility study, eight male and female reference size UF/NCI phantoms (5, 10, 15, and 35 years) were downscaled to fourteen different ages which included next nearest available lower discrete ages (1, 5, 10 and 15 years) and the median ages at the time of RT for Wilms' tumor (3.9 years), craniospinal (8.0 years), and all survivors (9.1 years old) in the Childhood Cancer Survivor Study (CCSS) expansion cohort treated with RT. The downscaling was performed using our in-house age scaling functions (ASFs). To geometrically validate the scaling, Dice similarity coefficient (DSC), mean distance to agreement (MDA), and Euclidean distance (ED) were calculated between the scaled and ground-truth discrete-aged phantom (unscaled UF/NCI) for whole-body, brain, heart, liver, pancreas, and kidneys. Additionally, heights of the scaled phantoms were compared with ground-truth phantoms' height, and the Centers for Disease Control and Prevention (CDC) reported 50th percentile height. Scaled organ masses were compared with ground-truth organ masses. For the dosimetric assessment, one reference size phantom and seventeen body-size dependent 5-year-old phantoms (9 male and 8 female) of varying body mass indices (BMI) were downscaled to 3.9-year-old dimensions for two different radiation dose studies. For the first study, we simulated a 6 MV photon right-sided flank field RT plan on a reference size 5-year-old and 3.9-year-old (both of healthy BMI), keeping the field size the same in both cases. Percent of volume receiving dose ≥15 Gy (V15) and the mean dose were calculated for the pancreas, liver, and stomach. For the second study, the same treatment plan, but with patient anatomy-dependent field sizes, was simulated on seventeen body-size dependent 5- and 3.9-year-old phantoms with varying BMIs. V15, mean dose, and minimum dose received by 1% of the volume (D1), and by 95% of the volume (D95) were calculated for pancreas, liver, stomach, left kidney (contralateral), right kidney, right and left colons, gallbladder, thoracic vertebrae, and lumbar vertebrae. A non-parametric Wilcoxon rank-sum test was performed to determine if the dose to organs of exact age-scaled and nearest age-matched phantoms were significantly different (p < 0.05).Results.In the feasibility study, the best DSCs were obtained for the brain (median: 0.86) and whole-body (median: 0.91) while kidneys (median: 0.58) and pancreas (median: 0.32) showed poorer agreement. In the case of MDA and ED, whole-body, brain, and kidneys showed tighter distribution and lower median values as compared to other organs. For height comparison, the overall agreement was within 2.8% (3.9 cm) and 3.0% (3.2 cm) of ground-truth UF/NCI and CDC reported 50th percentile heights, respectively. For mass comparison, the maximum percent and absolute differences between the scaled and ground-truth organ masses were within 31.3% (29.8 g) and 211.8 g (16.4%), respectively (across all ages). In the first dosimetric study, absolute difference up to 6% and 1.3 Gy was found for V15and mean dose, respectively. In the second dosimetric study, V15and mean dose were significantly different (p < 0.05) for all studied organs except the fully in-beam organs. D1and D95were not significantly different for most organs (p > 0.05).Conclusion.We have successfully evaluated our ASFs by scaling UF/NCI computational phantoms from one age to another age, which demonstrates the feasibility of scaling any CT-based anatomy. We have found that dose to organs of exact age-scaled and nearest aged-matched phantoms are significantly different (p < 0.05) which indicates that using the exact age-scaled phantoms for retrospective dosimetric studies is a better approach.

Development and Validation of a Multivariable Risk Prediction Model for COVID-19 Mortality in the Southern United States.

OBJECTIVE: To evaluate clinical characteristics of patients admitted to the hospital with coronavirus disease 2019 (COVID-19) in Southern United States and development as well as validation of a mortality risk prediction model. PATIENTS AND METHODS: Southern Louisiana was an early hotspot during the pandemic, which provided a large collection of clinical data on inpatients with COVID-19. We designed a risk stratification model to assess the mortality risk for patients admitted to the hospital with COVID-19. Data from 1673 consecutive patients diagnosed with COVID-19 infection and hospitalized between March 1, 2020, and April 30, 2020, was used to create an 11-factor mortality risk model based on baseline comorbidity, organ injury, and laboratory results. The risk model was validated using a subsequent cohort of 2067 consecutive hospitalized patients admitted between June 1, 2020, and December 31, 2020. RESULTS: The resultant model has an area under the curve of 0.783 (95% CI, 0.76 to 0.81), with an optimal sensitivity of 0.74 and specificity of 0.69 for predicting mortality. Validation of this model in a subsequent cohort of 2067 consecutively hospitalized patients yielded comparable prognostic performance. CONCLUSION: We have developed an easy-to-use, robust model for systematically evaluating patients presenting to acute care settings with COVID-19 infection.

Gender and LPG use after government intervention in rural north India.

Exposure to air pollution from cooking with solid fuels has important consequences for public health. This paper focuses on rural north India, where despite robust economic growth and government subsidies, the vast majority of households mainly use solid fuels. We draw on new qualitative and quantitative data collected in the context of a policy environment that dramatically expanded ownership of liquid petroleum gas (LPG) to examine why households are slow to adopt clean fuels in rural north India. We find that patriarchal gender norms and attitudes encourage the use of solid fuels in this region. North Indian society confers low status to women, promotes women's seclusion, and constrains women's engagement in economic activities outside of the home. These beliefs encourage women to preserve gas, promote women's work that facilitates the use of solid fuels, and hinder communication between the cook and the decision-maker regarding LPG refills. When rural north Indian households use gas, it is frequently to facilitate the adherence to norms of seclusion that prevent women from leaving the home to collect solid fuels. In addition to expanding access and improving economic conditions, future research and policy interventions should pay careful attention to the gender norms and attitudes that discourage the use of gas. Addressing these beliefs and norms is essential to sustained LPG use and health improvements.

Radiation therapy related cardiac disease risk in childhood cancer survivors: Updated dosimetry analysis from the Childhood Cancer Survivor Study.

BACKGROUND AND PURPOSE: We previously evaluated late cardiac disease in long-term survivors in the Childhood Cancer Survivor Study (CCSS) based on heart radiation therapy (RT) doses estimated from an age-scaled phantom with a simple atlas-based heart model (HAtlas). We enhanced our phantom with a high-resolution CT-based anatomically realistic and validated age-scalable cardiac model (HHybrid). We aimed to evaluate how this update would impact our prior estimates of RT-related late cardiac disease risk in the CCSS cohort. METHODS: We evaluated 24,214 survivors from the CCSS diagnosed from 1970 to 1999. RT fields were reconstructed on an age-scaled phantom with HHybrid and mean heart dose (Dm), percent volume receiving ≥ 20 Gy (V20) and ≥ 5 Gy with V20 = 0 ( [Formula: see text] ) were calculated. We reevaluated cumulative incidences and adjusted relative rates of grade 3-5 Common Terminology Criteria for Adverse Events outcomes for any cardiac disease, coronary artery disease (CAD), and heart failure (HF) in association with Dm, V20, and [Formula: see text] (as categorical variables). Dose-response relationships were evaluated using piecewise-exponential models, adjusting for attained age, sex, cancer diagnosis age, race/ethnicity, time-dependent smoking history, diagnosis year, and chemotherapy exposure and doses. For relative rates, Dm was also considered as a continuous variable. RESULTS: Consistent with previous findings with HAtlas, reevaluation using HHybrid dosimetry found that, Dm ≥ 10 Gy, V20 ≥ 0.1%, and [Formula: see text]  ≥ 50% were all associated with increased cumulative incidences and relative rates for any cardiac disease, CAD, and HF. While updated risk estimates were consistent with previous estimates overall without statistically significant changes, there were some important and significant (P < 0.05) increases in risk with updated dosimetry for Dm in the category of 20 to 29.9 Gy and V20 in the category of 30% to 79.9%. When changes in the linear dose-response relationship for Dm were assessed, the slopes of the dose response were steeper (P < 0.001) with updated dosimetry. Changes were primarily observed among individuals with chest-directed RT with prescribed doses ≥ 20 Gy. CONCLUSION: These findings present a methodological advancement in heart RT dosimetry with improved estimates of RT-related late cardiac disease risk. While results are broadly consistent with our prior study, we report that, with updated cardiac dosimetry, risks of cardiac disease are significantly higher in two dose and volume categories and slopes of the Dm-specific RT-response relationships are steeper. These data support the use of contemporary RT to achieve lower heart doses for pediatric patients, particularly those requiring chest-directed RT.