THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.

Statistics for Spatial Data.

Biomedical imaging is a driver of scientific discovery and a core component of medical care and is being stimulated by the field of deep learning. While semantic segmentation algorithms enable image analysis and quantification in many applications, the design of respective specialized solutions is non-trivial and highly dependent on dataset properties and hardware conditions. We developed nnU-Net, a deep learning-based segmentation method that automatically configures itself, including preprocessing, network architecture, training and post-processing for any new task. The key design choices in this process are modeled as a set of fixed parameters, interdependent rules and empirical decisions. Without manual intervention, nnU-Net surpasses most existing approaches, including highly specialized solutions on 23 public datasets used in international biomedical segmentation competitions. We make nnU-Net publicly available as an out-of-the-box tool, rendering state-of-the-art segmentation accessible to a broad audience by requiring neither expert knowledge nor computing resources beyond standard network training.

nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

Type 2 diabetes (T2D) is responsible for high incidence of cardiovascular (CV) complications leading to heart failure. Coronary artery region-specific metabolic and structural assessment could provide deeper insight into the extent of the disease and help prevent adverse cardiac events. Therefore, in this study, we aimed at investigating such myocardial dynamics for the first time in insulin-sensitive (mIS) and insulin-resistant (mIR) T2D patients. We targeted global and region-specific variations using insulin sensitivity (IS) and coronary artery calcifications (CACs) as CV risk factor in T2D patients. IS was computed using myocardial segmentation approaches at both baseline and after an hyperglycemic–insulinemic clamp (HEC) on [18F]FDG-PET images using the standardized uptake value (SUV) (ΔSUV = SUVHEC − SUVBASELINE) and calcifications using CT Calcium Scoring. Results suggest that some communicating pathways between response to insulin and calcification are present in the myocardium, whilst differences between coronary arteries were only observed in the mIS cohort. Risk indicators were mostly observed for mIR and highly calcified subjects, which supports previously stated findings that exhibit a distinguished exposure depending on the impairment of response to insulin, while projecting added potential complications due to arterial obstruction. Moreover, a pattern relating calcification and T2D phenotypes was observed suggesting the avoidance of insulin treatment in mIS but its endorsement in mIR subjects. The right coronary artery displayed more ΔSUV, whilst plaque was more present in the circumflex. However, differences between phenotypes, and therefore CV risk, were associated to left descending artery (LAD) translating into higher CACs regarding IR, which could explain why insulin treatment was effective for LAD at the expense of higher likelihood of plaque accumulation. Personalized approaches to assess T2D may lead to more efficient treatments and risk-prevention strategies.

https://www.mdpi.com/1422-0067/24/4/3250/pdf?version=1675753954

Insights into Insulin Resistance and Calcification in the Myocardium in Type 2 Diabetes: A Coronary Artery Analysis


 
 
 Being born small-for-gestational age (SGA, 10 percent of all births) is associated with increased risk of cardiovascular mortality (1,2) in adulthood together with lower exercise tolerance (3), but mechanistic pathways are unclear. Central obesity is known to worsen cardiovascular outcomes, but it is uncertain how it affects the heart in adults born SGA.
 
 
 
 We aimed to assess whether central obesity makes young adults born SGA more susceptible to cardiac remodelling and dysfunction.
 
 
 
 A perinatal cohort study including 80 young adults born SGA (birth weight below 10th centile) and 75 adults with normal birth weight (controls). Current waist-to-hip ratio was used as a surrogate of central obesity. Cardiac structure and function were assessed by cardiac magnetic resonance. Statistical shape analysis was used to study the regional geometric variability of the biventricular surfaces produced by central obesity and SGA, and synthetic surfaces representative of obese and non obese were generated for both SGA and controls.
 
 
 
 Figure 1 shows the superimposed representative surfaces of obese and non-obese according to our model, for controls (right column) and SGA (left column). Both SGA and waist-to-hip were highly associated to cardiac shape (F=3.94 p<0.001; F=5.18 p<0.001 respectively) with a statistically significant interaction (F=2.29, p=0.02), indicating a different cardiac remodelling due to obesity in SGA. While controls tend to increase left ventricular end-diastolic volumes, mass and stroke volume with increasing waist-to-hip ratio, young adults born SGA showed unique response with inability to increase cardiac dimensions or mass resulting in reduced stroke volume (both in absolute values and indexed by body surface area) and increased heart rate.
 
 
 
 SGA young adults show unique cardiac adaptation to central obesity, which is associated with a decrease in stroke volume. Preventive strategies aiming to reduce cardiometabolic risk in SGA population may be warranted.
 
 
 
 Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union Horizon 2020 Programme


/pdf/unique-cardiac-remodeling-in-young-adults-born-small-for-1re51gy2.pdf

Unique cardiac remodeling in young adults born Small for Gestational Age with subsequent central obesity

/pdf/digital-health-europe-dhe-twinning-on-severe-asthma-kick-off-5366bbr11u.pdf

Miguel Ángel González Ballester

Papers

Insights into Insulin Resistance and Calcification in the Myocardium in Type 2 Diabetes: A Coronary Artery Analysis

Unique cardiac remodeling in young adults born Small for Gestational Age with subsequent central obesity

Digital Health Europe (DHE) Twinning on severe asthma-kick-off meeting report