Cardiovascular Disease in Testicular Cancer Survivors:Identification of Risk Factors and Impact on Quality of Life

PURPOSE: Testicular cancer (TC) treatment is clearly associated with cardiovascular morbidity and mortality. To enable development of preventive strategies for cardiovascular disease (CVD), we assessed cardiometabolic risk factors and quality of life (QoL) in TC survivors.METHODS: Incidence of coronary artery disease, myocardial infarction, and heart failure after TC treatment was assessed in a multicenter cohort comprising 4,748 patients treated at the age of 12-50 years between 1976 and 2007. Patients who had developed CVD and a random sample from the cohort (subcohort) received a questionnaire on cardiometabolic risk factors and QoL. A subgroup of responders in the subcohort additionally underwent clinical evaluation of cardiovascular risk factors.RESULTS: After a median follow-up of 16 years, 272 patients had developed CVD. Compared with orchidectomy only, cisplatin combination chemotherapy was associated with an increased CVD risk (hazard ratio [HR], 1.9; 95% CI, 1.1 to 3.1). Patients who were obese or a smoker at diagnosis (HR, 4.6; 95% CI, 2.0 to 10.0 and HR, 1.7; 95% CI, 1.1 to 2.4, respectively), developed Raynaud's phenomenon (HR, 1.9; 95% CI, 1.1 to 3.6) or dyslipidemia (HR, 2.8; 95% CI, 1.6 to 4.7) or had a positive family history for CVD (HR, 2.9; 95% CI, 1.7 to 4.9) had higher CVD risk. More TC survivors with CVD reported inferior QoL on physical domains than survivors who did not develop CVD. Of 304 TC survivors who underwent clinical evaluation for cardiovascular risk factors (median age at assessment: 51 years), 86% had dyslipidemia, 50% had hypertension, and 35% had metabolic syndrome, irrespective of treatment.CONCLUSION: Cardiovascular events in TC survivors impair QoL. Many TC survivors have undetected cardiovascular risk factors. We advocate early lifestyle adjustments and lifelong follow-up with low-threshold treatment of cardiovascular risk factors, especially in obese and smoking patients treated with platinum-based chemotherapy.</p

A spatiotemporal ensemble machine learning framework for generating land use/land cover time-series maps for Europe (2000–2019) based on LUCAS, CORINE and GLAD Landsat

A spatiotemporal machine learning framework for automated prediction and analysis of long-term Land Use/Land Cover dynamics is presented. The framework includes: (1) harmonization and preprocessing of spatial and spatiotemporal input datasets (GLAD Landsat, NPP/VIIRS) including five million harmonized LUCAS and CORINE Land Cover-derived training samples, (2) model building based on spatial k-fold cross-validation and hyper-parameter optimization, (3) prediction of the most probable class, class probabilities and model variance of predicted probabilities per pixel, (4) LULC change analysis on time-series of produced maps. The spatiotemporal ensemble model consists of a random forest, gradient boosted tree classifier, and an artificial neural network, with a logistic regressor as meta-learner. The results show that the most important variables for mapping LULC in Europe are: seasonal aggregates of Landsat green and near-infrared bands, multiple Landsat-derived spectral indices, long-term surface water probability, and elevation. Spatial cross-validation of the model indicates consistent performance across multiple years with overall accuracy (a weighted F1-score) of 0.49, 0.63, and 0.83 when predicting 43 (level-3), 14 (level-2), and five classes (level-1). Additional experiments show that spatiotemporal models generalize better to unknown years, outperforming single-year models on known-year classification by 2.7% and unknown-year classification by 3.5%. Results of the accuracy assessment using 48,365 independent test samples shows 87% match with the validation points. Results of time-series analysis (time-series of LULC probabilities and NDVI images) suggest forest loss in large parts of Sweden, the Alps, and Scotland. Positive and negative trends in NDVI in general match the land degradation and land restoration classes, with “urbanization” showing the most negative NDVI trend. An advantage of using spatiotemporal ML is that the fitted model can be used to predict LULC in years that were not included in its training dataset, allowing generalization to past and future periods, e.g. to predict LULC for years prior to 2000 and beyond 2020. The generated LULC time-series data stack (ODSE-LULC), including the training points, is publicly available via the ODSE Viewer. Functions used to prepare data and run modeling are available via the eumap library for Python

A custom-made guide-wire positioning device for Hip Surface Replacement Arthroplasty: description and first results

<p>Abstract</p> <p>Background</p> <p>Hip surface replacement arthroplasty (SRA) can be an alternative for total hip arthroplasty. The short and long-term outcome of hip surface replacement arthroplasty mainly relies on the optimal size and position of the femoral component. This can be defined before surgery with pre-operative templating. Reproducing the optimal, templated femoral implant position during surgery relies on guide wire positioning devices in combination with visual inspection and experience of the surgeon. Another method of transferring the templated position into surgery is by navigation or Computer Assisted Surgery (CAS). Though CAS is documented to increase accurate placement particularly in case of normal hip anatomy, it requires bulky equipment that is not readily available in each centre.</p> <p>Methods</p> <p>A custom made neck jig device is presented as well as the results of a pilot study.</p> <p>The device is produced based on data pre-operatively acquired with CT-scan. The position of the guide wire is chosen as the anatomical axis of the femoral neck. Adjustments to the design of the jig are made based on the orthopedic surgeon's recommendations for the drill direction. The SRA jig is designed as a slightly more-than-hemispherical cage to fit the anterior part of the femoral head. The cage is connected to an anterior neck support. Four knifes are attached on the central arch of the cage. A drill guide cylinder is attached to the cage, thus allowing guide wire positioning as pre-operatively planned.</p> <p>Custom made devices were tested in 5 patients scheduled for total hip arthroplasty. The orthopedic surgeons reported the practical aspects of the use of the neck-jig device. The retrieved femoral heads were analyzed to assess the achieved drill place in mm deviation from the predefined location and orientation compared to the predefined orientation.</p> <p>Results</p> <p>The orthopedic surgeons rated the passive stability, full contact with neck portion of the jig and knife contact with femoral head, positive. There were no guide failures. The jig unique position and the number of steps required to put the guide in place were rated 1, while the complexity to put the guide into place was rated 1-2. In all five cases the guide wire was accurately positioned. Maximum angular deviation was 2.9° and maximum distance between insertion points was 2.1 mm.</p> <p>Conclusions</p> <p>Pilot testing of a custom made jig for use during SRA indicated that the device was (1) successfully applied and user friendly and (2) allowed for accurate guide wire placement according to the preoperative plan.</p

Risk of diabetes after para-aortic radiation for testicular cancer

Background: While the risk of diabetes is increased following radiation exposure to the pancreas among childhood cancer survivors, its association among testicular cancer (TC) survivors has not been investigated. Methods: Diabetes risk was studied in 2998 1-year TC survivors treated before 50 years of age with orchidectomy with/without radiotherapy between 1976 and 2007. Diabetes incidence was compared with general population rates. Treatment-specific risk of diabetes was assessed using a case–cohort design. Results: With a median follow-up of 13.4 years, 161 TC survivors were diagnosed with diabetes. Diabetes risk was not increased compared to general population rates (standardised incidence ratios (SIR): 0.9; 95% confidence interval (95% CI): 0.7–1.1). Adjusted for age, para-aortic radiotherapy was associated with a 1.66-fold (95% CI: 1.05–2.62) increased diabetes risk compared to no radiotherapy. The excess hazard increased with 0.31 with every 10 Gy increase in the prescribed radiation dose (95% CI: 0.11–0.51, P = 0.003, adjusted for age and BMI); restricted to irradiated patients the excess hazard increased with 0.33 (95% CI: −0.14 to 0.81, P = 0.169) with every 10 Gy increase in radiation dose. Conclusion: Compared to surgery only, para-aortic irradiation is associated with increased diabetes risk among TC survivors

Risk of diabetes after para-aortic radiation for testicular cancer

Background: While the risk of diabetes is increased following radiation exposure to the pancreas among childhood cancer survivors, its association among testicular cancer (TC) survivors has not been investigated. Methods: Diabetes risk was studied in 2998 1-year TC survivors treated before 50 years of age with orchidectomy with/without radiotherapy between 1976 and 2007. Diabetes incidence was compared with general population rates. Treatment-specific risk of diabetes was assessed using a case–cohort design. Results: With a median follow-up of 13.4 years, 161 TC survivors were diagnosed with diabetes. Diabetes risk was not increased compared to general population rates (standardised incidence ratios (SIR): 0.9; 95% confidence interval (95% CI): 0.7–1.1). Adjusted for age, para-aortic radiotherapy was associated with a 1.66-fold (95% CI: 1.05–2.62) increased diabetes risk compared to no radiotherapy. The excess hazard increased with 0.31 with every 10 Gy increase in the prescribed radiation dose (95% CI: 0.11–0.51, P = 0.003, adjusted for age and BMI); restricted to irradiated patients the excess hazard increased with 0.33 (95% CI: −0.14 to 0.81, P = 0.169) with every 10 Gy increase in radiation dose. Conclusion: Compared to surgery only, para-aortic irradiation is associated with increased diabetes risk among TC survivors

Ecodatacube.eu: analysis-ready open environmental data cube for Europe

The article describes the production steps and accuracy assessment of an analysis-ready, open-access European data cube consisting of 2000–2020+ Landsat data, 2017–2021+ Sentinel-2 data and a 30 m resolution digital terrain model (DTM). The main purpose of the data cube is to make annual continental-scale spatiotemporal machine learning tasks accessible to a wider user base by providing a spatially and temporally consistent multidimensional feature space. This has required systematic spatiotemporal harmonization, efficient compression, and imputation of missing values. Sentinel-2 and Landsat reflectance values were aggregated into four quarterly averages approximating the four seasons common in Europe (winter, spring, summer and autumn), as well as the 25th and 75th percentile, in order to retain intra-seasonal variance. Remaining missing data in the Landsat time-series was imputed with a temporal moving window median (TMWM) approach. An accuracy assessment shows TMWM performs relatively better in Southern Europe and lower in mountainous regions such as the Scandinavian Mountains, the Alps, and the Pyrenees. We quantify the usability of the different component data sets for spatiotemporal machine learning tasks with a series of land cover classification experiments, which show that models utilizing the full feature space (30 m DTM, 30 m Landsat, 30 m and 10 m Sentinel-2) yield the highest land cover classification accuracy, with different data sets improving the results for different land cover classes. The data sets presented in the article are part of the EcoDataCube platform, which also hosts open vegetation, soil, and land use/land cover (LULC) maps created. All data sets are available under CC-BY license as Cloud-Optimized GeoTIFFs (ca. 12 TB in size) through SpatioTemporal Asset Catalog (STAC) and the EcoDataCube data portal

Quantifying Changes in Articulatory Working Space in Individuals Surgically Treated for Oral Cancer with Electromagnetic Articulography

Purpose: The purpose of this study was to quantify sentence-level articulatory kinematics in individuals treated for oral squamous cell carcinoma (ITOC) compared to control speakers while also assessing the effect of treatment site (jaw vs. tongue). Furthermore, this study aimed to assess the relation between articulatory–kinematic measures and self-reported speech problems. Method: Articulatory–kinematic data from the tongue tip, tongue back, and jaw were collected using electromagnetic articulography in nine Dutch ITOC and eight control speakers. To quantify articulatory kinematics, the two-dimensional articulatory working space (AWS; in mm2 ), one-dimensional anteroposterior range of motion (AP-ROM; in mm), and superior–inferior range of motion (SI-ROM in mm) were calculated and examined. Self-reported speech problems were assessed with the Speech Handicap Index (SHI). Results: Compared to a sex-matched control group, ITOC showed significantly smaller AWS, AP-ROM, and SI-ROM for both the tongue tip and tongue back sensor, but no significant differences were observed for the jaw sensor. This pattern was found for both individuals treated for tongue and jaw tumors. Moderate nonsignificant correlations were found between the SHI and the AWS of the tongue back and jaw sensors. Conclusions: Despite large individual variation, ITOC showed reduced one- and two-dimensional tongue, but not jaw, movements compared to control speakers and treatment for tongue and jaw tumors resulted in smaller tongue movements. A larger sample size is needed to establish a more generalizable connection between the AWS and the SHI. Further research should explore how these kinematic changes in ITOC are related to acoustic and perceptual measures of speech

Quantifying changes in articulatory working space following oral cancer treatment

Introduction. Surgical treatment of oral cancer may limit the mobility of the affected articulator as shown by non-speech tasks, which may hinder communication. However, even though patients consistently rank speech as one of their top-priorities during and following treatment, articulatory consequences of oral cancer treatment have not been clearly characterised. The purpose of this study was to evaluate the range of movement of the tongue and jaw during speech by measuring the articulatory working space (AWS) of individuals who were surgically treated for oral cancer. We investigated whether the size of the AWS was (1) smaller in individuals treated for oral cancer compared to controls; (2) related to the type of treatment received; and (3) related to self-reported speech symptoms following treatment.Method. Nine native speakers of Dutch who were surgically treated for a stage 3 or 4 squamous cell carcinoma of the oral cavity (5 male, 4 female; mean age = 61.6 years) and seven age-matched controls (4 male, 3 female; mean age = 61.3 years) participated. Individuals received treatment for a tumour located in the jaw (n=5) or on the tongue (n=4). Participants read the North Wind and the Sun passage while kinematic trajectories were recorded using electromagnetic articulography. The AWS (convex hull in mm2) was calculated using the anteroposterior and superior-inferior trajectories of the tongue-tip, tongue-back, and jaw sensor. Self-reported speech symptoms were quantified using the Speech Handicap Index (SHI).Results. Descriptively, large individual variation in AWS was noted within both the clinical and control group. Compared to a sex-matched control group, the individuals who underwent treatment for oral cancer showed smaller AWS for the tongue-tip and tongue-back. In the clinical group, the AWS for the jaw showed more variability across individuals compared to AWS of the tongue-tip and tongue-back. On average, lower SHI scores (i.e., better speech outcomes) were associated with a larger AWS.Conclusion. Despite large individual variation, most individuals treated for oral cancer show descriptively reduced tongue and jaw AWS when compared to controls. Whereas both treatment for jaw and tongue tumours reduced tongue AWS compared to controls, more variable results for jaw AWS were found across treatment sites. This suggests that there may be no one-to-one mapping between articulator mobility and primary treatment site. Overall, these findings specify specific kinematic changes in individuals who underwent oral cancer treatment that should be further explored in future studies. Kinematic data may be especially informative in designing new therapeutic approaches for this population as they directly measure articulatory changes