Evidence map›Paper›PMID 39312493›Full record

ArticleMedical physics2024

Imaging of ventilation and lung injury with low-frequency tomographic ultrasound.

Andre Vieira Pigatto, Sergio Furuie, Diego Cardénas, Marlis L Rezende, Raul Lima, Jennifer L Mueller

Abstract read
In one paragraph

Article in Medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Andre Vieira PigattoSchool of Biomedical Engineering, Colorado State University, Fort Collins, Colorado, USA.
Sergio FuruiePolytechnic School of the University of São Paulo, São Paulo, Sao Paulo, Brazil.
Diego CardénasPolytechnic School of the University of São Paulo, São Paulo, Sao Paulo, Brazil.
Marlis L RezendeDepartment of Clinical Sciences and College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, Colorado, USA.
Raul LimaPolytechnic School of the University of São Paulo, São Paulo, Sao Paulo, Brazil.
Jennifer L MuellerDepartment of Mathematics and School of Biomedical Engineering and the Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, Colorado, USA.

Funding

An integrated electrical impedance/ultrasound tomography system for pulmonary monitoring and diagnosisR21EB024683 · NIBIB · COLORADO STATE UNIVERSITY · PI MUELLER, JENNIFER LYNN · 2017 to 2019
$560k
FAPESP 2021/04814-9NIBIB NIH HHS R21 EB024683NIBIB NIH HHS R21EB024683
6 · The paper itself

Abstract

backgroundMechanical ventilation in the intensive care unit (ICU) is a life-saving technique for patients with acute respiratory failure, but is also associated with a high incidence of complications in the injured lung. Currently, there is no widely used monitoring technique to guide the ventilator setting to facilitate a precision medicine approach or to provide a real-time alert for developing adverse pulmonary conditions. Conventional ultrasound has been used as a thoracic bedside technology, but the lack of signal penetration into lung tissue results in images that often contain more information in their artifacts than in the images themselves. Perhaps the greatest obstacle to using traditional ultrasound in the ICU is the need for highly skilled technicians to perform the data collection. In contrast, low-frequency ultrasound (50-500 kHz) has been shown to penetrate the lung, and can detect air trapping in patients with chronic obstructive pulmonary disease (COPD). PURPOSE: Here, we present a method of collecting low-frequency ultrasound computed tomographic (USCT) data in vivo on a mechanically ventilated porcine model and computing tomographic reconstructions of airflow during tidal breathing and induced lung injuries. We evaluate the ability of the novel low-frequency USCT system to image regional changes in sound speed in the thorax due to changes in airflow during tidal breathing and induced lung injuries. This represents the first study of low-frequency tomographic ultrasound imaging in vivo and the first to produce tomographic images of ventilatory changes in vivo.

methodsUSCT and computed tomography (CT) scan data were collected alternately on a mechanically ventilated Landrace pig weighing approximately 75 kg during tidal breathing, induced pneumothorax, atelectasis, and pleural effusion. The pneumothorax was induced by injecting air through a 5 mm thick intrathoracic tube inserted in the 8th posterior intercostal space. After removing the air, atelectasis was induced by ventilating the animal with a high concentration of oxygen and low tidal volumes. The pleural effusion was induced by injecting a saline solution through the tube. The USCT data were collected at 125 kHz using the USCT low-frequency ultrasound tomography (LUFT) system on a transducer belt placed around the animal's thorax. Tomographic reconstructions were computed from the USCT data using a regularized refraction-corrected Gauss-Newton-based time-of-flight reconstruction algorithm.

resultsCyclic changes in computed lung area during tidal breathing were demonstrated to agree with the respiratory rate on the mechanical ventilator. Reconstructed images computed at time steps during the procedure demonstrate regional changes consistent with what would be expected during the induced lung injury. No ground truth was available for images during the procedures since CT scans could only be taken before and after each established lung injury.

conclusionsIn this work, we have demonstrated in the first in vivo study using a mechanically ventilated porcine animal model that low-frequency ultrasound tomography has the ability to image regional changes in sound speed in the thorax corresponding to changes in airflow during tidal breathing and induced lung injury. The results show promise for using low-frequency USCT as a bedside imaging technique in the future for patients with acute respiratory distress syndrome.

Indexed as

Lung InjuryUltrasonographyAnimalsImage Processing, Computer-AssistedLungPulmonary VentilationRespiration, ArtificialSwineTomography, X-Ray Computedlow‐frequency ultrasoundpulmonary imagingultrasound computed tomography

Identifiers

PMID39312493
PMCPMC11656285

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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.