scholarly journals Development of experimental ground truth and quantification of intracranial aneurysm pulsation in a patient

Author(s):  
Axel Vanrossomme ◽  
Kamil Chodzyński ◽  
Omer Eker ◽  
Karim Zouaoui Boudjeltia

Abstract Aneurysm wall motion has been reported to be associated with rupture. However, its quantification with medical imaging is challenging and should be based on experimental ground-truth to avoid misinterpretation of results. In this work a time-resolved CT angiography (4D-CTA) acquisition protocol is proposed to detect the pulsation of intracranial aneurysms with a low radiation dose. To acquire ground-truth data, the accuracy of pulsation detection and quantification in a silicone phantom was assessed by applying pressure sinusoidal waves of increasing amplitudes. These experiments were carried out using a test bench that could reproduce pulsatile waveforms similar to those inside the internal carotid arteries of human subjects. 4D-CTA acquisition parameters (mAs, kVp) were then selected to achieve reliable pulsation detection and quantification with the lowest radiation dose achievable. The resulting acquisition protocol was then used to image an anterior communicating artery aneurysm in a human subject. Data reveals that in a simplified in vitro setting 4D-CTA allows for an effective and reproducible method to detect and quantify aneurysm pulsation with an inferior limit as low as 3 mm³ and a background noise of 0.5 to 1 mm³. Aneurysm pulsation can be detected in vivo with a radiation dose approximating 1 mSv.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Axel E. Vanrossomme ◽  
Kamil J. Chodzyński ◽  
Omer F. Eker ◽  
Karim Zouaoui Boudjeltia

AbstractAneurysm wall motion has been reported to be associated with rupture. However, its quantification with medical imaging is challenging and should be based on experimental ground-truth to avoid misinterpretation of results. In this work a time-resolved CT angiography (4D-CTA) acquisition protocol is proposed to detect the pulsation of intracranial aneurysms with a low radiation dose. To acquire ground-truth data, the accuracy of volume pulsation detection and quantification in a silicone phantom was assessed by applying pressure sinusoidal waves of increasing amplitudes. These experiments were carried out using a test bench that could reproduce pulsatile waveforms similar to those inside the internal carotid arteries of human subjects. 4D-CTA acquisition parameters (mAs, kVp) were then selected to achieve reliable pulsation detection and quantification with the lowest radiation dose achievable. The resulting acquisition protocol was then used to image an anterior communicating artery aneurysm in a human subject. Data reveals that in a simplified in vitro setting 4D-CTA allows for an effective and reproducible method to detect and quantify aneurysm volume pulsation with an inferior limit as low as 3 mm3 and a background noise of 0.5–1 mm3. Aneurysm pulsation can be detected in vivo with a radiation dose approximating 1 mSv.


eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Pierre Yger ◽  
Giulia LB Spampinato ◽  
Elric Esposito ◽  
Baptiste Lefebvre ◽  
Stéphane Deny ◽  
...  

In recent years, multielectrode arrays and large silicon probes have been developed to record simultaneously between hundreds and thousands of electrodes packed with a high density. However, they require novel methods to extract the spiking activity of large ensembles of neurons. Here, we developed a new toolbox to sort spikes from these large-scale extracellular data. To validate our method, we performed simultaneous extracellular and loose patch recordings in rodents to obtain ‘ground truth’ data, where the solution to this sorting problem is known for one cell. The performance of our algorithm was always close to the best expected performance, over a broad range of signal-to-noise ratios, in vitro and in vivo. The algorithm is entirely parallelized and has been successfully tested on recordings with up to 4225 electrodes. Our toolbox thus offers a generic solution to sort accurately spikes for up to thousands of electrodes.


2016 ◽  
Author(s):  
Pierre Yger ◽  
Giulia L.B. Spampinato ◽  
Elric Esposito ◽  
Baptiste Lefebvre ◽  
Stéphane Deny ◽  
...  

AbstractUnderstanding how assemblies of neurons encode information requires recording large populations of cells in the brain. In recent years, multi-electrode arrays and large silicon probes have been developed to record simultaneously from hundreds or thousands of electrodes packed with a high density. However, these new devices challenge the classical way to do spike sorting. Here we developed a new method to solve these issues, based on a highly automated algorithm to extract spikes from extracellular data, and show that this algorithm reached near optimal performance both in vitro and in vivo. The algorithm is composed of two main steps: 1) a “template-finding” phase to extract the cell templates, i.e. the pattern of activity evoked over many electrodes when one neuron fires an action potential; 2) a “template-matching” phase where the templates were matched to the raw data to find the location of the spikes. The manual intervention by the user was reduced to the minimal, and the time spent on manual curation did not scale with the number of electrodes. We tested our algorithm with large-scale data from in vitro and in vivo recordings, from 32 to 4225 electrodes. We performed simultaneous extracellular and patch recordings to obtain “ground truth” data, i.e. cases where the solution to the sorting problem is at least partially known. The performance of our algorithm was always close to the best expected performance. We thus provide a general solution to sort spikes from large-scale extracellular recordings.


2020 ◽  
Vol 19 (1) ◽  
pp. 185-204 ◽  
Author(s):  
Alessio Paolo Buccino ◽  
Gaute Tomas Einevoll

AbstractWhen recording neural activity from extracellular electrodes, both in vivo and in vitro, spike sorting is a required and very important processing step that allows for identification of single neurons’ activity. Spike sorting is a complex algorithmic procedure, and in recent years many groups have attempted to tackle this problem, resulting in numerous methods and software packages. However, validation of spike sorting techniques is complicated. It is an inherently unsupervised problem and it is hard to find universal metrics to evaluate performance. Simultaneous recordings that combine extracellular and patch-clamp or juxtacellular techniques can provide ground-truth data to evaluate spike sorting methods. However, their utility is limited by the fact that only a few cells can be measured at the same time. Simulated ground-truth recordings can provide a powerful alternative mean to rank the performance of spike sorters. We present here , a Python-based software which permits flexible and fast simulation of extracellular recordings. allows users to generate extracellular signals on various customizable electrode designs and can replicate various problematic aspects for spike sorting, such as bursting, spatio-temporal overlapping events, and drifts. We expect will provide a common testbench for spike sorting development and evaluation, in which spike sorting developers can rapidly generate and evaluate the performance of their algorithms.


2019 ◽  
Author(s):  
Alessio P. Buccino ◽  
Gaute T. Einevoll

AbstractWhen recording neural activity from extracellular electrodes, both in vivo and in vitro, spike sorting is a required and very important processing step that allows for identification of single neurons’ activity. Spike sorting is a complex algorithmic procedure, and in recent years many groups have attempted to tackle this problem, resulting in numerous methods and software packages. However, validation of spike sorting techniques is complicated. It is an inherently unsupervised problem and it is hard to find universal metrics to evaluate performance. Simultaneous recordings that combine extracellular and patch-clamp or juxtacellular techniques can provide ground-truth data to evaluate spike sorting methods. However, their utility is limited by the fact that only a few cells can be measured at the same time. Simulated ground-truth recordings can provide a powerful alternative mean to rank the performance of spike sorters. We present here MEArec, a Python-based software which permits flexible and fast simulation of extracellular recordings. MEArec allows users to generate extracellular signals on various customizable electrode designs and can replicate various problematic aspects for spike sorting, such as bursting, spatio-temporal overlapping events, and drifts. We expect MEArec will provide a common testbench for spike sorting development and evaluation, in which spike sorting developers can rapidly generate and evaluate the performance of their algorithms.


Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4554
Author(s):  
Ralph-Alexandru Erdelyi ◽  
Virgil-Florin Duma ◽  
Cosmin Sinescu ◽  
George Mihai Dobre ◽  
Adrian Bradu ◽  
...  

The most common imaging technique for dental diagnoses and treatment monitoring is X-ray imaging, which evolved from the first intraoral radiographs to high-quality three-dimensional (3D) Cone Beam Computed Tomography (CBCT). Other imaging techniques have shown potential, such as Optical Coherence Tomography (OCT). We have recently reported on the boundaries of these two types of techniques, regarding. the dental fields where each one is more appropriate or where they should be both used. The aim of the present study is to explore the unique capabilities of the OCT technique to optimize X-ray units imaging (i.e., in terms of image resolution, radiation dose, or contrast). Two types of commercially available and widely used X-ray units are considered. To adjust their parameters, a protocol is developed to employ OCT images of dental conditions that are documented on high (i.e., less than 10 μm) resolution OCT images (both B-scans/cross sections and 3D reconstructions) but are hardly identified on the 200 to 75 μm resolution panoramic or CBCT radiographs. The optimized calibration of the X-ray unit includes choosing appropriate values for the anode voltage and current intensity of the X-ray tube, as well as the patient’s positioning, in order to reach the highest possible X-rays resolution at a radiation dose that is safe for the patient. The optimization protocol is developed in vitro on OCT images of extracted teeth and is further applied in vivo for each type of dental investigation. Optimized radiographic results are compared with un-optimized previously performed radiographs. Also, we show that OCT can permit a rigorous comparison between two (types of) X-ray units. In conclusion, high-quality dental images are possible using low radiation doses if an optimized protocol, developed using OCT, is applied for each type of dental investigation. Also, there are situations when the X-ray technology has drawbacks for dental diagnosis or treatment assessment. In such situations, OCT proves capable to provide qualitative images.


2021 ◽  
Vol 49 (1) ◽  
pp. 185-193
Author(s):  
Ateeque Ur Rehman ◽  
Muhammad Hassan ◽  
Sadia Bano ◽  
Khizir Farooq ◽  
Aun Raza ◽  
...  

2019 ◽  
Author(s):  
David D Shteynberg ◽  
Eric W Deutsch ◽  
David S Campbell ◽  
Michael R Hoopmann ◽  
Ulrike Kusebauch ◽  
...  

Spectral matching sequence database search engines commonly used on mass spectrometry-based proteomics experiments excel at identifying peptide sequence ions, and in addition, possible sequence ions carrying post-translational modifications (PTMs), but most do not provide confidence metrics for the exact localization of those PTMs when several possible sites are available. Localization is absolutely required for downstream molecular cell biology analysis of PTM function in vitro and in vivo. Therefore, we developed PTMProphet, a free and open-source software tool integrated into the Trans-Proteomic Pipeline, which reanalyzes identified spectra from any search engine for which pepXML output is available to provide localization confidence to enable appropriate further characterization of biologic events. Localization of any type of mass modification (e.g., phosphorylation) is supported. PTMProphet applies Bayesian mixture models to compute probabilities for each site/peptide spectrum match where a PTM has been identified. These probabilities can be combined to compute a global false localization rate at any threshold to guide downstream analysis. We describe the PTMProphet tool, its underlying algorithms and demonstrate its performance on ground-truth synthetic peptide reference datasets, one previously published small dataset, one new larger dataset, and also on a previously published phospho-enriched dataset where the correct sites of modification are unknown. Data have been deposited to ProteomeXchange with identifier PXD013210.


2016 ◽  
Author(s):  
Roshni Cooper ◽  
Shaul Yogev ◽  
Kang Shen ◽  
Mark Horowitz

AbstractMotivation:Microtubules (MTs) are polarized polymers that are critical for cell structure and axonal transport. They form a bundle in neurons, but beyond that, their organization is relatively unstudied.Results:We present MTQuant, a method for quantifying MT organization using light microscopy, which distills three parameters from MT images: the spacing of MT minus-ends, their average length, and the average number of MTs in a cross-section of the bundle. This method allows for robust and rapid in vivo analysis of MTs, rendering it more practical and more widely applicable than commonly-used electron microscopy reconstructions. MTQuant was successfully validated with three ground truth data sets and applied to over 3000 images of MTs in a C. elegans motor neuron.Availability:MATLAB code is available at http://roscoope.github.io/MTQuantContact:[email protected] informationSupplementary data are available at Bioinformatics online.


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