Euclidean and hyperbolic lenghs of images of arcs

Let $f$ be a function that is analytic in the unit disc. We give new estimates, and new proofs of existing estimates, of the Euclidean length of the image under $f$ of a radial segment in the unit disc. Our methods are based on the hyperbolic geometry of plane domains, and we address some new questions that follow naturally from this approach.Comment: 26 page

Quantitative Analysis of the Cervical Texture by Ultrasound and Correlation with Gestational Age

Objectives: Quantitative texture analysis has been proposed to extract robust features from the ultrasound image to detect subtle changes in the textures of the images. The aim of this study was to evaluate the feasibility of quantitative cervical texture analysis to assess cervical tissue changes throughout pregnancy. Methods: This was a cross-sectional study including singleton pregnancies between 20.0 and 41.6 weeks of gestation from women who delivered at term. Cervical length was measured, and a selected region of interest in the cervix was delineated. A model to predict gestational age based on features extracted from cervical images was developed following three steps: data splitting, feature transformation, and regression model computation. Results: Seven hundred images, 30 per gestational week, were included for analysis. There was a strong correlation between the gestational age at which the images were obtained and the estimated gestational age by quantitative analysis of the cervical texture (R = 0.88). Discussion: This study provides evidence that quantitative analysis of cervical texture can extract features from cervical ultrasound images which correlate with gestational age. Further research is needed to evaluate its applicability as a biomarker of the risk of spontaneous preterm birth, as well as its role in cervical assessment in other clinical situations in which cervical evaluation might be relevant

Caregiver distress in parkinsonism

This study examined the frequency and degree of caregiver burden in persons with parkinsonism, a group of disorders with four primary symptoms that include tremor, rigidity, postural instability, and bradykinesia. We assessed associations between perceived caregiver burden and physical, cognitive, and functional impairments using well-established tools for persons with parkinsonism. The 49 individuals with parkinsonism ranged in age from 61 to 87 (mean = 75), while their caregivers (N = 49) ranged in age from 48 to 83 (mean = 70). The caregivers were predominantly either wives (82%) or daughters (6%), with other family members, friends, and/or neighbors (12%) making up the rest. The caregivers reported a relatively high ability for coping (mean scores = 4.6/6). Caregiver burden was significantly negatively associated with activities of daily living and motoric difficulties as measured on the Unified Parkinson\u27s Disease Rating Scale (UPDRS). Likewise, caregiver burden was negatively associated with caregiver self-reported sleep and coping ability. Results did not demonstrate an association on the UPDRS among mentation, behavior, and mood. We found a significant negative correlation for mentation between the Folstein Mini-Mental Status Examination and caregiver burden measures; however, we did not find this association with the Dementia Rating Scale-2. Patient\u27s self-reported pain and caregiver burden were not associated

Quantitative ultrasound texture analysis of fetal lungs to predict neonatal respiratory morbidity

Objective To develop and evaluate the performance of a novel method for predicting neonatal respiratory morbidity based on quantitative analysis of the fetal lung by ultrasound. Methods More than 13¿000 non-clinical images and 900 fetal lung images were used to develop a computerized method based on texture analysis and machine learning algorithms, trained to predict neonatal respiratory morbidity risk on fetal lung ultrasound images. The method, termed ‘quantitative ultrasound fetal lung maturity analysis’ (quantusFLM™), was then validated blindly in 144 neonates, delivered at 28¿+¿0 to 39¿+¿0¿weeks' gestation. Lung ultrasound images in DICOM format were obtained within 48¿h of delivery and the ability of the software to predict neonatal respiratory morbidity, defined as either respiratory distress syndrome or transient tachypnea of the newborn, was determined. Results Mean (SD) gestational age at delivery was 36¿+¿1 (3¿+¿3) weeks. Among the 144 neonates, there were 29 (20.1%) cases of neonatal respiratory morbidity. Quantitative texture analysis predicted neonatal respiratory morbidity with a sensitivity, specificity, positive predictive value and negative predictive value of 86.2%, 87.0%, 62.5% and 96.2%, respectively. Conclusions Quantitative ultrasound fetal lung maturity analysis predicted neonatal respiratory morbidity with an accuracy comparable to that of current tests using amniotic fluid.Peer ReviewedPostprint (published version

MRI data quality assessment for the RIN - Neuroimaging Network using the ACR phantoms

PURPOSE: Generating big-data is becoming imperative with the advent of machine learning. RIN-Neuroimaging Network addresses this need by developing harmonized protocols for multisite studies to identify quantitative MRI (qMRI) biomarkers for neurological diseases. In this context, image quality control (QC) is essential. Here, we present methods and results of how the RIN performs intra- and inter-site reproducibility of geometrical and image contrast parameters, demonstrating the relevance of such QC practice. METHODS: American College of Radiology (ACR) large and small phantoms were selected. Eighteen sites were equipped with a 3T scanner that differed by vendor, hardware/software versions, and receiver coils. The standard ACR protocol was optimized (in-plane voxel, post-processing filters, receiver bandwidth) and repeated monthly. Uniformity, ghosting, geometric accuracy, ellipse’s ratio, slice thickness, and high-contrast detectability tests were performed using an automatic QC script. RESULTS: Measures were mostly within the ACR tolerance ranges for both T1- and T2-weighted acquisitions, for all scanners, regardless of vendor, coil, and signal transmission chain type. All measurements showed good reproducibility over time. Uniformity and slice thickness failed at some sites. Scanners that upgraded the signal transmission chain showed a decrease in geometric distortion along the slice encoding direction. Inter-vendor differences were observed in uniformity and geometric measurements along the slice encoding direction (i.e. ellipse’s ratio). CONCLUSIONS: Use of the ACR phantoms highlighted issues that triggered interventions to correct performance at some sites and to improve the longitudinal stability of the scanners. This is relevant for establishing precision levels for future multisite studies of qMRI biomarkers

Quality assessment, variability and reproducibility of anatomical measurements derived from T1-weighted brain imaging: The RIN–Neuroimaging Network case study

Initiatives for the collection of harmonized MRI datasets are growing continuously, opening questions on the reliability of results obtained in multi-site contexts. Here we present the assessment of the brain anatomical variability of MRI-derived measurements obtained from T1-weighted images, acquired according to the Standard Operating Procedures, promoted by the RIN-Neuroimaging Network. A multicentric dataset composed of 77 brain T1w acquisitions of young healthy volunteers (mean age = 29.7 ± 5.0 years), collected in 15 sites with MRI scanners of three different vendors, was considered. Parallelly, a dataset of 7 “traveling” subjects, each undergoing three acquisitions with scanners from different vendors, was also used. Intra-site, intra-vendor, and inter-site variabilities were evaluated in terms of the percentage standard deviation of volumetric and cortical thickness measures. Image quality metrics such as contrast-to-noise and signal-to-noise ratio in gray and white matter were also assessed for all sites and vendors. The results showed a measured global variability that ranges from 11% to 19% for subcortical volumes and from 3% to 10% for cortical thicknesses. Univariate distributions of the normalized volumes of subcortical regions, as well as the distributions of the thickness of cortical parcels appeared to be significantly different among sites in 8 subcortical (out of 17) and 21 cortical (out of 68) regions of i nterest in the multicentric study. The Bland-Altman analysis on “traveling” brain measurements did not detect systematic scanner biases even though a multivariate classification approach was able to classify the scanner vendor from brain measures with an accuracy of 0.60 ± 0.14 (chance level 0.33)

Multi-centre and multi-vendor reproducibility of a standardized protocol for quantitative susceptibility Mapping of the human brain at 3T

Quantitative Susceptibility Mapping (QSM) is an MRI-based technique allowing the non-invasive quantification of iron content and myelination in the brain. The RIN – Neuroimaging Network established an optimized and harmonized protocol for QSM across ten sites with 3T MRI systems from three different vendors to enable multicentric studies. The assessment of the reproducibility of this protocol is crucial to establish susceptibility as a quantitative biomarker. In this work, we evaluated cross-vendor reproducibility in a group of six traveling brains. Then, we recruited fifty-one volunteers and measured the variability of QSM values in a cohort of healthy subjects scanned at different sites, simulating a multicentric study. Both voxelwise and Region of Interest (ROI)-based analysis on cortical and subcortical gray matter were performed. The traveling brain study yielded high structural similarity (∼0.8) and excellent reproducibility comparing maps acquired on scanners from two different vendors. Depending on the ROI, we reported a quantification error ranging from 0.001 to 0.017 ppm for the traveling brains. In the cohort of fifty-one healthy subjects scanned at nine different sites, the ROI-dependent variability of susceptibility values, of the order of 0.005–0.025 ppm, was comparable to the result of the traveling brain experiment. The harmonized QSM protocol of the RIN – Neuroimaging Network provides a reliable quantification of susceptibility in both cortical and subcortical gray matter regions and it is ready for multicentric and longitudinal clinical studies in neurological and pychiatric diseases

Unbounded violation of tripartite Bell inequalities

We prove that there are tripartite quantum states (constructed from random unitaries) that can lead to arbitrarily large violations of Bell inequalities for dichotomic observables. As a consequence these states can withstand an arbitrary amount of white noise before they admit a description within a local hidden variable model. This is in sharp contrast with the bipartite case, where all violations are bounded by Grothendieck's constant. We will discuss the possibility of determining the Hilbert space dimension from the obtained violation and comment on implications for communication complexity theory. Moreover, we show that the violation obtained from generalized GHZ states is always bounded so that, in contrast to many other contexts, GHZ states do in this case not lead to extremal quantum correlations. The results are based on tools from the theories of operator spaces and tensor norms which we exploit to prove the existence of bounded but not completely bounded trilinear forms from commutative C*-algebras.Comment: Substantial changes in the presentation to make the paper more accessible for a non-specialized reade