PET Imaging of Mild Traumatic Brain Injury and Whiplash Associated Disorder

Traumatic brain injury is the leading cause of brain injury in our society with 235 per 100,000 inhabitants per year in the European Union and about 500 per 100,000 inhabitants per year in the United States. About 80% of all these events are accounted for as mild cases. At the same time, whiplash-associated disorder is one of the most frequent consequences of motor vehicle related accidents affecting about 300 per 100,000 inhabitants per year in the United States and Western European countries. Both brain injuries are frequently underestimated due to their apparent low severity and because in many cases these symptoms disappear within few weeks. Nevertheless, several patients describe long-lasting discomfort in the absence of detectable alterations with conventional clinical diagnostic tools or imaging studies, such as magnetic resonance imaging (MRI) and computed tomography (CT). Therefore, the mechanism behind the long-lasting manifestations remains unknown. It is within this context that functional imaging techniques, such as positron emission tomography (PET) have the potential to provide insight into the undetected changes related to mild traumatic brain injury and whiplash-associated disorder

Diffeomorphic transforms for data augmentation of highly variable shape and texture objects

[EN] Background and objective: Training a deep convolutional neural network (CNN) for automatic image classification requires a large database with images of labeled samples. However, in some applications such as biology and medicine only a few experts can correctly categorize each sample. Experts are able to identify small changes in shape and texture which go unnoticed by untrained people, as well as distinguish between objects in the same class that present drastically different shapes and textures. This means that currently available databases are too small and not suitable to train deep learning models from scratch. To deal with this problem, data augmentation techniques are commonly used to increase the dataset size. However, typical data augmentation methods introduce artifacts or apply distortions to the original image, which instead of creating new realistic samples, obtain basic spatial variations of the original ones. Methods: We propose a novel data augmentation procedure which generates new realistic samples, by combining two samples that belong to the same class. Although the idea behind the method described in this paper is to mimic the variations that diatoms experience in different stages of their life cycle, it has also been demonstrated in glomeruli and pollen identification problems. This new data augmentation procedure is based on morphing and image registration methods that perform diffeomorphic transformations. Results: The proposed technique achieves an increase in accuracy over existing techniques of 0.47%, 1.47%, and 0.23% for diatom, glomeruli and pollen problems respectively. Conclusions: For the Diatom dataset, the method is able to simulate the shape changes in different diatom life cycle stages, and thus, images generated resemble newly acquired samples with intermediate shapes. In fact, the other methods compared obtained worse results than those which were not using data augmentation. For the Glomeruli dataset, the method is able to add new samples with different shapes and degrees of sclerosis (through different textures). This is the case where our proposed DA method is more beneficial, when objects highly differ in both shape and texture. Finally, for the Pollen dataset, since there are only small variations between samples in a few classes and this dataset has other features such as noise which are likely to benefit other existing DA techniques, the method still shows an improvement of the resultsSIThe authors acknowledge financial support of the Spanish Government and Junta de Comunidades de Castilla-La Mancha under projects AQUALITAS (Ref. CTM2014-51907-C2-R-MINECO), HYPERDEEP (Ref. SBPLY/19/180501/000273), and APRENDAMOS (Ref. SBPLY/17/180501/000543). They would also like to extend the acknowledgment to technicians Enrique Cepeda and Jesus Diaz for their help in running some experiment

Diseño y evaluación de un programa para la mejora de la condición física en Educación Primaria: efecto sobre la autoestima y la intención de ser activo

The objective was to design a program to improve physical fitness and evaluate its effect on the intent to remain active and general self-esteem. An 8-week program of activities was designed to improve physical fitness in Physical Education, in addition to sports physical activity at recess. The quasi-experimental design included 70 schoolchildren (39 experimental group; 31 control group) from 6th grade of Primary Education. The high priority ALPHA-Fitness battery, the intentionality scale of being physically active in Primary Education, and the Multimedia and Multilingual Self-esteem Evaluation Questionnaire were used as measuring instruments. The effectiveness of the program was found in all the variables studied, especially in the improvement of cardiorespiratory capacity, jumping capacity and the socio-affective dimension of self-esteem. The importance of these programs in the improvement of the physical, psychological and social health of the students is highlighted.El objetivo fue diseñar un programa para mejorar la condición física y evaluar su efecto sobre la intencionalidad de seguir siendo activo y autoestima general. Se diseñó un programa de 8 semanas de actividades para mejorar la condición física en Educación Física, además de actividad física deportiva en los recreos. El diseño cuasiexperimental incluyó 70 escolares (39 grupo experimental; 31 grupo control) de 6º de Educación Primaria. Como instrumentos de medida se utilizaron la batería ALPHA-Fitness de alta prioridad, la Escala de intencionalidad de ser físicamente activo en Educación Primaria, y el Cuestionario Multimedia y Multilingüe de Evaluación de la Autoestima. Se encontró efectividad del programa en todas las variables estudiadas, en especial en la mejora de la capacidad cardiorrespiratoria, la capacidad de salto y la dimensión socioafectiva de la autoestima. Se destaca la importancia de estos programas en la mejora de la salud física, psicológica y social del alumnado

Optimization of the k(2)' Parameter Estimation for the Pharmacokinetic Modeling of Dynamic PIB PET Scans Using SRTM2

Background: This study explores different approaches to estimate the clearance rate of the reference tissue (k2 ') parameter used for pharmacokinetic modeling, using the simplified reference tissue model 2 (SRMT2) and further explores the effect on the binding potential (BPND) of C-11-labeled Pittsburgh Compound B (PIB) PET scans. Methods: Thirty subjects underwent a dynamic PIB PET scan and were classified as PIB positive (+) or negative (-). Thirteen regions were defined from where to estimate k2 ': the whole brain, eight anatomical region based on the Hammer's atlas, one region based on a SPM comparison between groups on a voxel level, and three regions using different BPNDSRTM thresholds. Results: The different approaches resulted in distinct k2 ' estimations per subject. The median value of the estimated k2 ' across all subjects in the whole brain was 0.057. In general, PIB+ subjects presented smaller k2 ' estimates than this median, and PIB-, larger. Furthermore, only threshold and white matter methods resulted in non-significant differences between groups. Moreover, threshold approaches yielded the best correlation between BPNDSRTM and BPNDSRTM2 for both groups (R-2 = 0.85 for PIB+, and R-2 = 0.88 for PIB-). Lastly, a sensitivity analysis showed that overestimating k2 ' values resulted in less biased BPNDSRTM2 estimates. Conclusion: Setting a threshold on BPNDSRTM might be the best method to estimate k2 ' in voxel-based modeling approaches, while the use of a white matter region might be a better option for a volume of interest based analysis

Mitigation of noise-induced bias of PET radiomic features

INTRODUCTION: One major challenge in PET radiomics is its sensitivity to noise. Low signal-to-noise ratio (SNR) affects not only the precision but also the accuracy of quantitative metrics extracted from the images resulting in noise-induced bias. This phantom study aims to identify the radiomic features that are robust to noise in terms of precision and accuracy and to explore some methods that might help to correct noise-induced bias. METHODS: A phantom containing three 18F-FDG filled 3D printed inserts, reflecting heterogeneous tracer uptake and realistic tumor shapes, was used in the study. The three different phantom inserts were filled and scanned with three different tumor-to-background ratios, simulating a total of nine different tumors. From the 40-minute list-mode data, ten frames each for 5 s, 10 s, 30 s, and 120 s frame duration were reconstructed to generate images with different noise levels. Under these noise conditions, the precision and accuracy of the radiomic features were analyzed using intraclass correlation coefficient (ICC) and similarity distance metric (SDM) respectively. Based on the ICC and SDM values, the radiomic features were categorized into four groups: poor, moderate, good, and excellent precision and accuracy. A "difference image" created by subtracting two statistically equivalent replicate images was used to develop a model to correct the noise-induced bias. Several regression methods (e.g., linear, exponential, sigmoid, and power-law) were tested. The best fitting model was chosen based on Akaike information criteria. RESULTS: Several radiomic features derived from low SNR images have high repeatability, with 68% of radiomic features having ICC ≥ 0.9 for images with a frame duration of 5 s. However, most features show a systematic bias that correlates with the increase in noise level. Out of 143 features with noise-induced bias, the SDM values were improved based on a regression model (53 features to excellent and 67 to good) indicating that the noise-induced bias of these features can be, at least partially, corrected. CONCLUSION: To have a predictive value, radiomic features should reflect tumor characteristics and be minimally affected by noise. The present study has shown that it is possible to correct for noise-induced bias, at least in a subset of the features, using a regression model based on the local image noise estimates

The association between active tumor volume, total lesion glycolysis and levels of S-100B and LDH in stage IV melanoma patients

Introduction: The Standardized Uptake Value (SUV) in single lesions on F-18-FDG PET/CT scans and serum S-100B concentrations are inversely associated with disease-free survival in stage IV melanoma. The aim of this study was to assess the association between biomarkers (S-100B, LDH) and the PET-derived metrics SUVmean/max, metabolic active tumor volume (MATV), and total lesion glycolysis (TLG) in stage IV melanoma in order to understand what these biomarkers reflect and their possible utility for follow-up. Methods: In 52 stage IV patients the association between PET-derived metrics and the biomarkers S-100B and LDH was assessed and the impact on survival analyzed. Results: S-100B was elevated (>0.15 mu g/l) in 37 patients (71%), LDH in 11 (21%). There was a correlation between S-100B and LDH (R-2 = 0.19). S-100B was correlated to both MATV (R-2 = 0.375) and TLG (R-2 = 0.352), but LDH was not. Higher MATV and TLG levels were found in patients with elevated S-100B (p 250 U/l) (p <0.001). There was no association between the biomarkers and SUVmean/max. Survival analysis indicated that LDH was the only predictor of melanoma-specific survival. Conclusion: In newly diagnosed stage IV melanoma patients S-100B correlates with F-18-FDG PET/CT derived MATV and TLG in contrast to LDH, is more often elevated than LDH (71% vs. 21%) and seems to be a better predictor of disease load and disease progression. However, elevated LDH is the only predictor for survival. The biomarkers, S-100B and LDH appear to describe different aspects of the extent of metastatic disease and of tumornecrosis. (C) 2020 The Authors. Published by Elsevier Ltd

Bone Mineral Density in Transgender Individuals After Gonadectomy and Long-Term Gender-Affirming Hormonal Treatment

Introduction: Establishing the influence of long-term, gender-affirming hormonal treatment (HT) on bone mineral density (BMD) in transgender individuals is important to improve the therapeutic guidelines for these individuals. Aim: To examine the effect of long-term HT and gonadectomy on BMD in transgender individuals. Methods: 68 transwomen and 43 transmen treated with HT who had undergone gonadectomy participated in this study. Dual-energy x-ray absorptiometry (DXA) scans were performed to measure BMD at the lumbar spine and total hip. Laboratory values related to sex hormones were collected within 3 months of performing the DXA scan and analyzed. Main Outcome Measure: BMD and levels of sex hormones in transwomen and transmen. Results: In transwomen, the mean BMD values at the lumbar spine and total hip at the first DXA scan were, respectively, 0.99 ± 0.15 g/cm2 (n = 68) and 0.94 ± 0.28 g/cm2 (n = 65). In transmen, the mean BMD values at the lumbar spine and total hip at the first DXA scan were, respectively, 1.08 ± 0.16 g/cm2 (n = 43) and 1.01 ± 0.18 g/cm2 (n = 43). A significant decrease in total hip BMD was found in both transwomen and transmen after 15 years of HT compared with 10 years of HT (P =.02). Conclusion: In both transwomen and transmen, a decrease was observed in total hip bone mineral density after 15 years of HT compared to the first 10 years of HT. Dobrolińska M, van der Tuuk K, Vink P, et al. Bone Mineral Density in Transgender Individuals After Gonadectomy and Long-Term Gender-Affirming Hormonal Treatment. J Sex Med 2019; 16:1469–1477

No evidence for decreased D2/3 receptor availability and frontal hypoperfusion in subjects with compulsive pornography use

Pornographic addiction refers to an addiction model associated with compulsive and repeated use of pornographic material. Whether the use of pornography may indeed become addictive remains a matter of debate. The current study investigated whether compulsive pornography use (CPU) is accompanied by reduced D2/3 receptor availability in the striatum and frontal hypofunctionality. Male subjects between 18 and 50 years of age with and without CPU were recruited using online and newspaper advertisements. Questionnaires were used to the assess the severity of compulsive pornography use (CIUS) and symptoms of depression, impulsivity and sensation seeking. Dopaminergic imaging was performed using [11C]-raclopride PET. Striatal binding potentials (BPND) and regional frontal cerebral influx values (R1) of [11C]-raclopride were calculated. Arterial Spin Labeling (ASL) MRI was performed to assess regional cerebral blood flow. No group differences between striatal BPND's of [11C]-raclopride in subjects with (n = 15) and without (n = 10) CPU were detected. In CPU subjects, no correlation was found between the CIUS score and striatal BPND's. Cerebral R1 values in frontal brain regions and cerebral blood flow measurements did not differ between groups. The current study fails to provide imaging support for sharing similar neurobiological alterations as previously has been reported in other addictive modalities