Deep learning based automated delineation of the intraprostatic gross tumour volume in PSMA-PET for patients with primary prostate cancer.

PURPOSE: With the increased use of focal radiation dose escalation for primary prostate cancer (PCa), accurate delineation of gross tumor volume (GTV) in prostate-specific membrane antigen PET (PSMA-PET) becomes crucial. Manual approaches are time-consuming and observer dependent. The purpose of this study was to create a deep learning model for the accurate delineation of the intraprostatic GTV in PSMA-PET. METHODS: A 3D U-Net was trained on 128 different 18F-PSMA-1007 PET images from three different institutions. Testing was done on 52 patients including one independent internal cohort (Freiburg: n = 19) and three independent external cohorts (Dresden: n = 14 18F-PSMA-1007, Boston: Massachusetts General Hospital (MGH): n = 9 18F-DCFPyL-PSMA and Dana-Farber Cancer Institute (DFCI): n = 10 68Ga-PSMA-11). Expert contours were generated in consensus using a validated technique. CNN predictions were compared to expert contours using Dice similarity coefficient (DSC). Co-registered whole-mount histology was used for the internal testing cohort to assess sensitivity/specificity. RESULTS: Median DSCs were Freiburg: 0.82 (IQR: 0.73-0.88), Dresden: 0.71 (IQR: 0.53-0.75), MGH: 0.80 (IQR: 0.64-0.83) and DFCI: 0.80 (IQR: 0.67-0.84), respectively. Median sensitivity for CNN and expert contours were 0.88 (IQR: 0.68-0.97) and 0.85 (IQR: 0.75-0.88) (p = 0.40), respectively. GTV volumes did not differ significantly (p > 0.1 for all comparisons). Median specificity of 0.83 (IQR: 0.57-0.97) and 0.88 (IQR: 0.69-0.98) were observed for CNN and expert contours (p = 0.014), respectively. CNN prediction took 3.81 seconds on average per patient. CONCLUSION: The CNN was trained and tested on internal and external datasets as well as histopathology reference, achieving a fast GTV segmentation for three PSMA-PET tracers with high diagnostic accuracy comparable to manual experts.

Zn doped CaP coatings used for controlling the degradation rate of MgCa1 alloy: In vitro anticorrosive properties, sterilization and bacteria/cell-material interactions.

The purpose of this study was to investigate the effect of Zn doped CaP coatings prepared by micro-arc oxidation method, as a possible approach to control MgCa1 alloy degradation. All the prepared coatings comprised a calcium deficient CaP phase. The control in this evaluation was performed with undoped CaP coating in SBF solution at body temperature (37 ± 0.5°C). The investigation involved determination of microchemical, mechanical, morphological, properties along with anticorrosive, cytocompatibility and antibacterial efficacy. The effect of sterilization process on the properties of the surfaces was also investigated. The results showed that the addition of Zn into CaP increased the corrosion resistance of MgCa1 alloy. Moreover, the adhesion strength of the coatings to MgCa1 alloy was enhanced by Zn addition. In cytotoxicity testing of the samples, extracts of the samples in MEM were incubated with L929 cells and malformation, degeneration and lysis of the cells were examined microscopically after 72 h. The results showed that all samples were cytocompatible. The degradation of MgCa1 alloy in the simulated body fluids (SBF) or DMEM was decreased by coating with CaP. Moreover, the degradation rate of CaP was further decreased by adding a small amount of Zn into the CaP matrix. The samples having CaP coatings and Zn doped CaP coating demonstrated antibacterial efficacy against E.coli. As a result, coating of magnesium alloy with Zn-doped CaP decreased the degradation rate, increased the corrosion resistance, cytocompatibility and the antibacterial effects of the alloys.

Regression discontinuity threshold optimization.

Treatments often come with thresholds, e.g. we are given statins if our cholesterol is above a certain threshold. But which statin administration threshold maximizes our quality of life adjusted years? More generally, which threshold would optimize the average expected outcome? Regression discontinuity approaches are used to measure the local average treatment effect (LATE) and more recently also the Marginal Threshold Treatment Effect (MTTE), which shows how marginal changes in the threshold can affect the LATE. We extend this idea to define the problem of optimizing a policy threshold, i.e. selecting a threshold that optimizes the cumulative effect of the treatment on the treated. We present an estimator of the optimal threshold based on a constrained optimization framework. We show how to use machine learning (Gaussian process regression) for non-linear estimation. We also extend the estimation to a conservative threshold that is unlikely to produce harm, and we show how to include policy cost constraints. We apply these results to estimate an optimal tip-maximizing threshold for tip suggestions in taxi cabs Haggag (2014).

Ex vivo γH2AX assay for tumor radiosensitivity in primary prostate cancer patients and correlation with clinical parameters.

BACKROUND: Accurate surrogate parameters for radio resistance are warranted for individualized radiotherapy (RT) concepts in prostate cancer (PCa). The purpose of this study was to assess intertumoral heterogeneity in terms of radio resistance using an ex-vivo γH2AX assay after irradiation of prostate biopsy cores and to investigate its correlation with clinical features of respective patients as well as imaging and genomic features of tumor areas. METHODS: Twenty one patients with histologically-proven PCa and pre-therapeutic multiparametric resonance imaging and prostate-specific membrane antigen positron emission tomography were included in the study. Biopsy cores were collected from 26 PCa foci. Residual γH2AX foci were counted 24 h after ex-vivo irradiation (with 0 and 4 Gy) of biopsy specimen and served as a surrogate for radio resistance. Clinical, genomic (next generation sequencing) and imaging features were collected and their association with the radio resistance was studied. RESULTS: In total 18 PCa lesions from 16 patients were included in the final analysis. The median γH2AX foci value per PCa lesion was 3.12. According to this, the patients were divided into two groups (radio sensitive vs. radio resistant) with significant differences in foci number (p < 0.0001). The patients in the radio sensitive group had significantly higher prostate specific antigen serum concentration (p = 0.015), tumor areas in the radio sensitive group had higher SUV (standardized uptake values in PSMA PET)-max and -mean values (p = 0.0037, p = 0.028) and lower ADC (apparent diffusion coefficient-mean values, p = 0.049). All later parameters had significant (p < 0.05) correlations in Pearson's test. One patient in the radio sensitive group displayed a previously not reported loss of function frameshift mutation in the NBN gene (c.654_658delAAAAC) that introduces a premature termination codon and results in a truncated protein. CONCLUSION: In this pilot study, significant differences in intertumoral radio resistance were observed and clinical as well as imaging parameters may be applied for their prediction. After further prospective validation in larger patient cohorts these finding may lead to individual RT dose prescription for PCa patients in the future.

Intraindividual Comparison Between [18F] PSMA-1007 PET/CT and Multiparametric MRI for Radiotherapy Planning in Primary Prostate Cancer Patients.

Introduction: Accurate detection and segmentation of the intraprostatic gross tumor volume (GTV) is pivotal for radiotherapy (RT) in primary prostate cancer (PCa) since it influences focal therapy target volumes and the patients' cT stage. The study aimed to compare the performance of multiparametric resonance imaging (mpMRI) with [18F] PSMA-1007 positron emission tomography (PET) for intraprostatic GTV detection as well as delineation and to evaluate their respective influence on RT concepts. Materials and Methods: In total, 93 patients from two German University Hospitals with [18F] PSMA-1007-PET/CT and MRI (Freiburg) or [18F] PSMA-1007-PET/MRI (Dresden) were retrospectively enrolled. Validated contouring techniques were applied for GTV-PET and -MRI segmentation. Absolute tumor volume and cT status were determined for each imaging method. The PCa distribution from histopathological reports based on biopsy cores and surgery specimen was used as reference in terms of laterality (unilateral vs. bilateral). Results: In the Freiburg cohort (n = 84), mpMRI and PET detected in median 2 (range: 1-5) and 3 (range: 1-8) GTVs, respectively (p < 0.01). The median GTV-MRI was significantly smaller than the GTV-PET, measuring 2.05 vs. 3.65 ml (p = 0.0005). PET had a statistically significant higher concordance in laterality with surgery specimen compared to mpMRI (p = 0.04) and biopsy (p < 0.01), respectively. PSMA PET led to more cT2c and cT3b stages, whereas cT3a stage was more pronounced in mpMRI. Based on the cT stage derived from mpMRI and PET information, 21 and 23 as well as 59 and 60 patients, respectively, were intermediate- and high-risk according to the National Comprehensive Cancer Network (NCCN) v1.2022 criteria. In the Dresden cohort (n = 9), similar results were observed. Conclusion: Intraprostatic GTV segmentation based on [18F] PSMA-1007 PET results in more and larger GTVs compared to mpMRI. This influences focal RT target volumes and cT stage definition, but not the NCCN risk group.

Prevalence of depression in women with low income living in developed countries.

OBJECTIVE: To conduct a systematic review of studies reporting prevalence rates of depression in women living in low-income circumstances in developed countries. METHODS: The published and unpublished literature was searched for studies reporting prevalence of depression in women with low income in developed countries. Searches, data extraction, and methodological appraisal were conducted twice independently. To perform the analysis, the meta and metafor packages in R, a random effect model to account for both between and within studies' variances, and the restricted maximum likelihood method for estimation were used. RESULTS: One-hundred sixty-four studies, involving 218,035 participants, were located through the search process. The point prevalence of depression among women in low-income circumstances using self-report instruments in 134 studies was 37.4% (95% CI, 34.0%-40.7%). Additionally, the point prevalence according to depression diagnosis in 25 studies was 22.9% (95% CI, 17.8%-28.5%). CONCLUSIONS: The high rate of depression among women living in low-income circumstances is of serious public health concern. POLICY IMPLICATIONS: Women living in low-income circumstances should receive screening and referral/treatment in not only medical service settings, but also in social service settings serving women receiving welfare benefits.

Incentives can reduce bias in online employer reviews.

Online reviews are widely used to propagate the reputations of employers. However, existing research suggests that online reviews often suffer from selection bias-people with extreme opinions are more motivated to select into sharing them than people with moderate opinions, resulting in more extreme ratings. We find that providing incentives for reviewing can reduce this selection bias, because incentives can mitigate the motivational deficit of people who hold moderate opinions. Using data from Glassdoor, a leading employer review website, we find that incentivized ratings are less extreme than voluntary (self-selected) ratings. The likely bias in the distribution of voluntary reviews can affect workers' choice of employers. We complement our investigation with a randomized experiment that provides a cleaner test of selection bias. We again find that voluntary reviews of employers lead to more extreme reviews compared to non-voluntary reviews. Moreover, providing relatively high monetary rewards or a pro-social cue as incentives for reviewing also lowers the relative prevalence of extreme reviews. Although voluntary employer reviews often suffer from selection bias, incentives can reduce it and help workers make more informed employment choices. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The impact of the Federal Pandemic Unemployment Compensation on job search and vacancy creation.

During the COVID-19 pandemic, the Federal Pandemic Unemployment Compensation (FPUC) increased US unemployment benefits by $600 a week. Theory predicts that FPUC should decrease job applications, while the effect on vacancy creation is ambiguous. We estimate the effect of FPUC on job applications and vacancy creation week by week, from March to July 2020, using granular data from the online jobs platform Glassdoor. We exploit variation in the proportional increase in benefits across local labor markets. To isolate the effect of FPUC, we flexibly allow for different trends in local labor markets differentially exposed to the COVID-19 crisis. We verify that trends in outcomes prior to the FPUC do not correlate with future increases in benefits, which supports our identification assumption. First, we find that a 10% increase in unemployment benefits caused a 3.6% decline in applications, but did not decrease vacancy creation; hence, FPUC increased labor market tightness (vacancies/applications). Second, we document that tightness was unusually depressed during the FPUC period. Altogether, our results imply that the positive effect of FPUC on tightness was likely welfare improving: FPUC decreased competition among applicants at a time when jobs were unusually scarce. Our results also help explain prior findings that FPUC did not decrease employment.

Probing the Effective Treatment Thresholds for Alteplase in Acute Ischemic Stroke With Regression Discontinuity Designs.

Randomized Controlled Trials (RCTs) are considered the gold standard for measuring the efficacy of medical interventions. However, RCTs are expensive, and use a limited population. Techniques to estimate the effects of stroke interventions from observational data that minimize confounding would be useful. We used regression discontinuity design (RDD), a technique well-established in economics, on the Get With The Guidelines-Stroke (GWTG-Stroke) data set. RDD, based on regression, measures the occurrence of a discontinuity in an outcome (e.g., odds of home discharge) as a function of an intervention (e.g., alteplase) that becomes significantly more likely when crossing the threshold of a continuous variable that determines that intervention (e.g., time from symptom onset, since alteplase is only given if symptom onset is less than e.g., 3 h). The technique assumes that patients near either side of a threshold (e.g., 2.99 and 3.01 h from symptom onset) are indistinguishable other than the use of the treatment. We compared outcomes of patients whose estimated onset to treatment time fell on either side of the treatment threshold for three cohorts of patients in the GWTG-Stroke data set. This data set spanned three different treatment thresholds for alteplase (3 h, 2003-2007, N = 1,869; 3 h, 2009-2016, N = 13,086, and 4.5 h, 2009-2016, N = 6,550). Patient demographic characteristics were overall similar across the treatment thresholds. We did not find evidence of a discontinuity in clinical outcome at any treatment threshold attributable to alteplase. Potential reasons for failing to find an effect include violation of some RDD assumptions in clinical care, large sample sizes required, or already-well-chosen treatment threshold.

Quasi-experimental causality in neuroscience and behavioural research.

In many scientific domains, causality is the key question. For example, in neuroscience, we might ask whether a medication affects perception, cognition or action. Randomized controlled trials are the gold standard to establish causality, but they are not always practical. The field of empirical economics has developed rigorous methods to establish causality even when randomized controlled trials are not available. Here we review these quasi-experimental methods and highlight how neuroscience and behavioural researchers can use them to do research that can credibly demonstrate causal effects.

HIV, wages, and the skill premium.

The HIV epidemic has dramatically decreased labor supply among prime-age adults in Sub-Saharan Africa. Using within-country variation in regional HIV prevalence and a synthetic panel, I find that HIV significantly increases the capital-labor ratio in urban manufacturing firms. The impact of HIV on average wages is positive but imprecisely estimated. In contrast, HIV has a large positive impact on the skill premium. The impact of HIV on the wages of low skilled workers is insignificantly different from 0, and is strongly dampened by competition from rural migrants. The HIV epidemic disproportionately increases the incomes of high-skilled survivors, thus increasing inequality.

Informality and the expansion of social protection programs: evidence from Mexico.

Many countries are moving from employer-based to universal health coverage, which can generate crowd out. In Mexico, Seguro Popular provides public health coverage to the uninsured. Using the gradual roll-out of the system at the municipality level, we estimate that Seguro Popular had no effect on informality in the overall population. Informality did increase by 1.7% for less educated workers, but the wage gains for workers who switch between the formal and the informal sector were not significantly affected. This suggests that marginal workers do not choose between formal and informal jobs on the basis of health insurance coverage.