MRI-directed cognitive fusion-guided biopsy of the anterior prostate tumors

PURPOSE:We aimed to evaluate the efficacy of magnetic resonance imaging (MRI)-directed cognitive fusion transrectal ultrasonography (TRUS)-guided anterior prostate biopsy for diagnosis of anterior prostate tumors and to illustrate this technique.METHODS:A total of 39 patients with previous negative TRUS biopsy, but high clinical suspicion of occult prostate cancer, prospectively underwent prostate MRI including diffusion-weighted imaging (DWI). Patients with a suspicious anterior lesion on MRI underwent targeted anterior gland TRUS-guided biopsy with cognitive fusion technique using sagittal probe orientation. PIRADS version 1 scores (T2, DWI, and overall), lesion size, prostate-specific antigen (PSA), PSA density, and prostate gland volume were compared between positive and negative biopsy groups and between clinically significant cancer and remaining cases. Logistic regression analysis of imaging parameters and prostate cancer diagnosis was performed.RESULTS:Anterior gland prostate adenocarcinoma was diagnosed in 18 patients (46.2%) on targeted anterior gland TRUS-guided biopsy. Clinically significant prostate cancer was diagnosed in 13 patients (33.3%). MRI lesion size, T2, DWI, and overall PIRADS scores were significantly higher in patients with positive targeted biopsies and those with clinically significant cancer (P < 0.05). Biopsies were positive in 90%, 33%, and 29% of patients with overall PIRADS scores of 5, 4, and 3 respectively. Overall PIRADS score was an independent predictor of all prostate cancer diagnosis and of clinically significant prostate cancer diagnosis.CONCLUSION:Targeted anterior gland TRUS-guided biopsy with MRI-directed cognitive fusion enables accurate sampling and may improve tumor detection yield of anterior prostate cancer

3D Printing Aids Acetabular Reconstruction in Complex Revision Hip Arthroplasty

Revision hip arthroplasty requires comprehensive appreciation of abnormal bony anatomy. Advances in radiology and manufacturing technology have made three-dimensional (3D) representation of osseous anatomy obtainable, which provide visual and tactile feedback. Such life-size 3D models were manufactured from computed tomography scans of three hip joints in two patients. The first patient had undergone multiple previous hip arthroplasties for bilateral hip infections, resulting in right-sided pelvic discontinuity and a severe left-sided posterosuperior acetabular deficiency. The second patient had a first-stage revision for infection and recurrent dislocations. Specific metal reduction protocols were used to reduce artefact. The images were imported into Materialise MIMICS 14.12®. The models were manufactured using selective laser sintering. Accurate templating was performed preoperatively. Acetabular cup, augment, buttress, and cage sizes were trialled using the models, before being adjusted, and resterilised, enhancing the preoperative decision-making process. Screw trajectory simulation was carried out, reducing the risk of neurovascular injury. With 3D printing technology, complex pelvic deformities were better evaluated and treated with improved precision. Life-size models allowed accurate surgical simulation, thus improving anatomical appreciation and preoperative planning. The accuracy and cost-effectiveness of the technique should prove invaluable as a tool to aid clinical practice

Modifications of poly(o-phenylenediamine) permselective layer on Pt-Ir for biosensor application in neurochemical monitoring

Reports that globular proteins could enhance the interference blocking ability of the PPD (poly(o-phenylenediamine) layer used as a permselective barrier in biosensor design, prompted this study where a variety of modifying agents were incorporated into PPD during its electrosynthesis on Pt-Ir electrodes. Trapped molecules, including fibrous proteins and β-cyclodextrin, altered the polymer/modifier composite selectivity by affecting the sensitivity to both H2O2 (signal molecule in many enzyme-based biosensors) and the archetypal interference species, ascorbic acid. A comparison of electrochemical properties of Pt and a Pt-Ir alloy suggests that the benefits of the latter, more rigid, metal can be exploited in PPD-based biosensor design without significant loss of backward compatibility with studies involving pure Pt

Emerging infectious disease implications of invasive mammalian species : the greater white-toothed shrew (Crocidura russula) is associated with a novel serovar of pathogenic Leptospira in Ireland

The greater white-toothed shrew (Crocidura russula) is an invasive mammalian species that was first recorded in Ireland in 2007. It currently occupies an area of approximately 7,600 km2 on the island. C. russula is normally distributed in Northern Africa and Western Europe, and was previously absent from the British Isles. Whilst invasive species can have dramatic and rapid impacts on faunal and floral communities, they may also be carriers of pathogens facilitating disease transmission in potentially naive populations. Pathogenic leptospires are endemic in Ireland and a significant cause of human and animal disease. From 18 trapped C. russula, 3 isolates of Leptospira were cultured. However, typing of these isolates by standard serological reference methods was negative, and suggested an, as yet, unidentified serovar. Sequence analysis of 16S ribosomal RNA and secY indicated that these novel isolates belong to Leptospira alstonii, a unique pathogenic species of which only 7 isolates have been described to date. Earlier isolations were limited geographically to China, Japan and Malaysia, and this leptospiral species had not previously been cultured from mammals. Restriction enzyme analysis (REA) further confirms the novelty of these strains since no similar patterns were observed with a reference database of leptospires. As with other pathogenic Leptospira species, these isolates contain lipL32 and do not grow in the presence of 8-azagunaine; however no evidence of disease was apparent after experimental infection of hamsters. These isolates are genetically related to L. alstonii but have a novel REA pattern; they represent a new serovar which we designate as serovar Room22. This study demonstrates that invasive mammalian species act as bridge vectors of novel zoonotic pathogens such as Leptospira

Brain-Age Prediction: Systematic Evaluation of Site Effects, and Sample Age Range and Size

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain‐age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain‐age has highlighted the need for robust and publicly available brain‐age models pre‐trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain‐age model. Here we expand this work to develop, empirically validate, and disseminate a pre‐trained brain‐age model to cover most of the human lifespan. To achieve this, we selected the best‐performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain‐age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5–90 years; 53.59% female). The pre‐trained models were tested for cross‐dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8–80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9–25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age‐bins (5–40 and 40–90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain‐age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open‐science, web‐based platform for individualized neuroimaging metrics

Brain-Age Prediction: Systematic Evaluation of Site Effects, and Sample Age Range and Size

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain‐age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain‐age has highlighted the need for robust and publicly available brain‐age models pre‐trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain‐age model. Here we expand this work to develop, empirically validate, and disseminate a pre‐trained brain‐age model to cover most of the human lifespan. To achieve this, we selected the best‐performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain‐age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5–90 years; 53.59% female). The pre‐trained models were tested for cross‐dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8–80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9–25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age‐bins (5–40 and 40–90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain‐age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open‐science, web‐based platform for individualized neuroimaging metrics

Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro Imaging genetics through meta analysis (ENIGMA) Consortium

BACKGROUND: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. METHODS: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide. RESULTS: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. CONCLUSIONS: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five novel loci for intracranial volume and confirmed two known signals. Four of the loci are also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic=0.748), which indicated a similar genetic background and allowed for the identification of four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, Parkinson’s disease, and enriched near genes involved in growth pathways including PI3K–AKT signaling. These findings identify biological underpinnings of intracranial volume and provide genetic support for theories on brain reserve and brain overgrowth

Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders

Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research

Altres ajuts: Max Planck Society (Germany).The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes