EFSUMB Recommendations and Guidelines for Gastrointestinal Ultrasound - Part 1: Examination Techniques and Normal Findings (Short version)

Abstract ▼ In October 2014 the European Federation of Societies for Ultrasound in Medicine and Biology formed a Gastrointestinal Ultrasound (GIUS) task force group to promote the use of GIUS in a clinical setting. One of the main objectives of the task force group was to develop clinical recommendations and guidelines for the use of GIUS under the auspices of EFSUMB. The first part, gives an overview of the examination techniques for GIUS recommended by experts in the field. It also presents the current evidence for the interpretation of normal sonoanatomical and physiological features as examined with different ultrasound modalities

EFSUMB Recommendations and Guidelines for Gastrointestinal Ultrasound - Part 1: Examination Techniques and Normal Findings (Long version).

Abstract ▼ In October 2014 the European Federation of Societies for Ultrasound in Medicine and Biology formed a Gastrointestinal Ultrasound (GIUS) task force group to promote the use of GIUS in a clinical setting. One of the main objectives of the task force group was to develop clinical recommendations and guidelines for the use of GIUS under the auspices of EFSUMB. The first part, gives an overview of the examination techniques for GIUS recommended by experts in the field. It also presents the current evidence for the interpretation of normal sonoanatomical and physiological features as examined with different ultrasound modalities

Local field potentials in a pre-motor region predict learned vocal sequences

Neuronal activity within the premotor region HVC is tightly synchronized to, and crucial for, the articulate production of learned song in birds. Characterizations of this neural activity detail patterns of sequential bursting in small, carefully identified subsets of neurons in the HVC population. The dynamics of HVC are well described by these characterizations, but have not been verified beyond this scale of measurement. There is a rich history of using local field potentials (LFP) to extract information about behavior that extends beyond the contribution of individual cells. These signals have the advantage of being stable over longer periods of time, and they have been used to study and decode human speech and other complex motor behaviors. Here we characterize LFP signals presumptively from the HVC of freely behaving male zebra finches during song production to determine if population activity may yield similar insights into the mechanisms underlying complex motor-vocal behavior. Following an initial observation that structured changes in the LFP were distinct to all vocalizations during song, we show that it is possible to extract time-varying features from multiple frequency bands to decode the identity of specific vocalization elements (syllables) and to predict their temporal onsets within the motif. This demonstrates the utility of LFP for studying vocal behavior in songbirds. Surprisingly, the time frequency structure of HVC LFP is qualitatively similar to well-established oscillations found in both human and non-human mammalian motor areas. This physiological similarity, despite distinct anatomical structures, may give insight into common computational principles for learning and/or generating complex motor-vocal behaviors.Fil: Brown, Daril E.. University of California at San Diego; Estados UnidosFil: Chavez, Jairo I.. University of California at San Diego; Estados UnidosFil: Nguyen, Derek H.. University of California at San Diego; Estados UnidosFil: Kadwory, Adam. University of California at San Diego; Estados UnidosFil: Voytek, Bradley. University of California at San Diego; Estados UnidosFil: Arneodo, Ezequiel Matías. University of California at San Diego; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; ArgentinaFil: Gentner, Timothy Q.. University of California at San Diego; Estados UnidosFil: Gilja, Vikash. University of California at San Diego; Estados Unido

EFSUMB Guidelines on Interventional Ultrasound (INVUS), Part II : Diagnostic ultrasound-guided interventional procedures (Long Version)

Publisher Copyright: © Georg Thieme Verlag KG Stuttgart New York.This is the second part of the series on interventional ultrasound guidelines of the Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB). It deals with the diagnostic interventional procedure. General points are discussed which are pertinent to all patients, followed by organ-specific imaging that will allow the correct pathway and planning for the interventional procedure. This will allow for the appropriate imaging workup for each individual interventional procedure (Long version).publishersversionPeer reviewe

The EFSUMB Guidelines and Recommendations for the Clinical Practice of Elastography in Non-Hepatic Applications: Update 2018

This manuscript describes the use of ultrasound elastography, with the exception of liver applications, and represents an update of the 2013 EFSUMB (European Federation of Societies for Ultrasound in Medicine and Biology) Guidelines and Recommendations on the clinical use of elastography

EFSUMB Recommendations and Guidelines for Gastrointestinal Ultrasound

In October 2014 the European Federation of Societies for Ultrasound in Medicine and Biology formed a Gastrointestinal Ultrasound (GIUS) task force group to promote the use of GIUS in a clinical setting. One of the main objectives of the task force group was to develop clinical recommendations and guidelines for the use of GIUS under the auspices of EFSUMB. The first part, gives an overview of the examination techniques for GIUS recommended by experts in the field. It also presents the current evidence for the interpretation of normal sonoanatomical and physiological features as examined with different ultrasound modalities

EFSUMB Recommendations for Gastrointestinal Ultrasound Part 3: Endorectal, Endoanal and Perineal Ultrasound

This article represents part 3 of the EFSUMB Recommendations and Guidelines for Gastrointestinal Ultrasound (GIUS). It provides an overview of the examination techniques recommended by experts in the field of endorectal/endoanal ultrasound (ERUS/EAUS), as well as perineal ultrasound (PNUS). The most important indications are rectal tumors and inflammatory diseases like fistula and abscesses in patients with or without inflammatory bowel disease (IBD). PNUS sometimes is more flexible and convenient compared to ERUS. However, the technique of ERUS is quite well established, especially for the staging of rectal cancer. EAUS also gained ground in the evaluation of perianal diseases like fistulas, abscesses and incontinence. For the staging of perirectal tumors, the use of PNUS in addition to conventional ERUS could be recommended. For the staging of anal carcinomas, PNUS can be a good option because of the higher resolution. Both ERUS and PNUS are considered excellent guidance methods for invasive interventions, such as the drainage of fluids or targeted biopsy of tissue lesions. For abscess detection and evaluation, contrast-enhanced ultrasound (CEUS) also helps in therapy planning

Inferring single-trial neural population dynamics using sequential auto-encoders

Neuroscience is experiencing a revolution in which simultaneous recording of thousands of neurons is revealing population dynamics that are not apparent from single-neuron responses. This structure is typically extracted from data averaged across many trials, but deeper understanding requires studying phenomena detected in single trials, which is challenging due to incomplete sampling of the neural population, trial-to-trial variability, and fluctuations in action potential timing. We introduce latent factor analysis via dynamical systems, a deep learning method to infer latent dynamics from single-trial neural spiking data. When applied to a variety of macaque and human motor cortical datasets, latent factor analysis via dynamical systems accurately predicts observed behavioral variables, extracts precise firing rate estimates of neural dynamics on single trials, infers perturbations to those dynamics that correlate with behavioral choices, and combines data from non-overlapping recording sessions spanning months to improve inference of underlying dynamics