Evidence map›Paper›PMID 27000558›Full record

ArticleBiomedical engineering online2016

Signal processing in urodynamics: towards high definition urethral pressure profilometry.

Mario Klünder, Oliver Sawodny, Bastian Amend, Michael Ederer, Alexandra Kelp, Karl-Dietrich Sievert, Arnulf Stenzl, Ronny Feuer

Open access · goldAbstract read
In one paragraph

Article in Biomedical engineering online, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 2 countries.

Mario KlünderInstitute for System Dynamics, University of Stuttgart, Waldburgstr. 17/19, 70563, Stuttgart, Germany. mario.kluender@isys.uni-stuttgart.de.
Oliver SawodnyInstitute for System Dynamics, University of Stuttgart, Waldburgstr. 17/19, 70563, Stuttgart, Germany.
Bastian AmendDepartment of Urology, University of Tübingen, Hoppe-Seyler-Straße 3, 72076, Tübingen, Germany.
Michael EdererInstitute for System Dynamics, University of Stuttgart, Waldburgstr. 17/19, 70563, Stuttgart, Germany.
Alexandra KelpDepartment of Urology, University of Tübingen, Hoppe-Seyler-Straße 3, 72076, Tübingen, Germany.
Karl-Dietrich SievertDepartment of Urology, Paracelsus Medical University of Salzburg, Müllner Hauptstr. 48, 5020, Salzburg, Austria.
Arnulf StenzlDepartment of Urology, University of Tübingen, Hoppe-Seyler-Straße 3, 72076, Tübingen, Germany.
Ronny FeuerInstitute for System Dynamics, University of Stuttgart, Waldburgstr. 17/19, 70563, Stuttgart, Germany.
University of Stuttgart · DEUniversity of Tübingen · DEParacelsus Medical University · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUrethral pressure profilometry (UPP) is used in the diagnosis of stress urinary incontinence (SUI) which is a significant medical, social, and economic problem. Low spatial pressure resolution, common occurrence of artifacts, and uncertainties in data location limit the diagnostic value of UPP. To overcome these limitations, high definition urethral pressure profilometry (HD-UPP) combining enhanced UPP hardware and signal processing algorithms has been developed. In this work, we present the different signal processing steps in HD-UPP and show experimental results from female minipigs.

methodsWe use a special microtip catheter with high angular pressure resolution and an integrated inclination sensor. Signals from the catheter are filtered and time-correlated artifacts removed. A signal reconstruction algorithm processes pressure data into a detailed pressure image on the urethra's inside. Finally, the pressure distribution on the urethra's outside is calculated through deconvolution. A mathematical model of the urethra is contained in a point-spread-function (PSF) which is identified depending on geometric and material properties of the urethra. We additionally investigate the PSF's frequency response to determine the relevant frequency band for pressure information on the urinary sphincter.

resultsExperimental pressure data are spatially located and processed into high resolution pressure images. Artifacts are successfully removed from data without blurring other details. The pressure distribution on the urethra's outside is reconstructed and compared to the one on the inside. Finally, the pressure images are mapped onto the urethral geometry calculated from inclination and position data to provide an integrated image of pressure distribution, anatomical shape, and location.

conclusionsWith its advanced sensing capabilities, the novel microtip catheter collects an unprecedented amount of urethral pressure data. Through sequential signal processing steps, physicians are provided with detailed information on the pressure distribution in and around the urethra. Therefore, HD-UPP overcomes many current limitations of conventional UPP and offers the opportunity to evaluate urethral structures, especially the sphincter, in context of the correct anatomical location. This could enable the development of focal therapy approaches in the treatment of SUI.

Indexed as

PressureSignal Processing, Computer-AssistedUrodynamicsAlgorithmsAnimalsCathetersDiagnostic Techniques, UrologicalFemaleSwineSwine, MiniatureUrethraUrinary Incontinence, StressSignal processingUrethral pressureUrodynamics

Identifiers

PMID27000558
PMCPMC4802619
OpenAlexW2303556270

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.