Evidence map›Paper›PMID 41572364›Full record

ArticleCritical care (London, England)2026

Tracking pleural sliding motion to assess lung overdistention using an open source algorithm: a proof-of-concept study on lung ultrasound scans.

Andrea Costamagna, Marry R Smit, Emanuele Pivetta, Paolo Persona, Paolo Navalesi, Luigi Pisani, Marcus J Schultz, Luca Brazzi, Vito Fanelli, Pieter R Tuinman and 1 more

Abstract read
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Article in Critical care (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Andrea CostamagnaDepartment of Surgical Sciences, University of Turin, C.so Dogliotti 14, Turin, 10126, Italy. andrea.costamagna@unito.it.
Marry R SmitDepartment of Intensive Care, Amsterdam University Medical Centers, Amsterdam, the Netherlands.
Emanuele PivettaDepartment of Medical Sciences, University of Turin, Turin, Italy.
Paolo PersonaNeuro and Trauma Critical Care Unit, Verona University Hospital, Verona, Italy.
Paolo NavalesiMedicine Department (DIMED), University of Padua, Padua, Italy.
Luigi PisaniUniversity of Bari 'Aldo Moro', Bari, Italy.
Marcus J SchultzDepartment of Intensive Care, Amsterdam University Medical Centers, Amsterdam, the Netherlands.
Luca BrazziDepartment of Surgical Sciences, University of Turin, C.so Dogliotti 14, Turin, 10126, Italy.
Vito FanelliDepartment of Surgical Sciences, University of Turin, C.so Dogliotti 14, Turin, 10126, Italy.
Pieter R TuinmanDepartment of Intensive Care, Amsterdam University Medical Centers, Amsterdam, the Netherlands.
Lieuwe D J BosDepartment of Intensive Care, Amsterdam University Medical Centers, Amsterdam, the Netherlands.

Funding

Università degli Studi di Torino Ricerca locale 2024
6 · The paper itself

Abstract

backgroundPleural line (PL) movement, assessed by lung ultrasound, is crucial for the detection of pneumothorax and might also indicate overdistention, but research is limited by the lack of a quantitative tool. We set out to answer two research questions: can PL movement be quantified using open-source motion tracking software, and can PL movement be used to identify overdistention? We hypothesize that motion tracking of the PL is feasible and represents an accurate estimation of lung sliding.

methodsLung ultrasound video clips from three patient groups were used: (1) healthy volunteers during expiratory hold maneuvers (functional residual capacity) and quiet breathing, (2) ICU patients, blindly assessed for lung sliding (absent, doubtful, evident but limited or evident and extensive) and (3) Severe COVID-19 viral pneumonia patients undergoing PEEP titration and electrical-impedance tomography. Open-source software that implements the "Channel and Spatial Reliability Tracking" tracker algorithm was used for motion tracking, identifying the PL at three points and a soft tissue reference. Each motion-time curve was subsequently smoothed and normalized to account for soft tissue displacement. The maximum lateral movement on the transversal plane among the three normalized PL landmarks defined PL movement.

resultsIn 143 video clips from 7 healthy individuals, PL movement increased from functional residual capacity (1.2 ± 0.6 mm) to quiet breathing (5.4 ± 2.5 mm; p < 0.01). In 336 video clips from 40 ICU patients, PL movement increased from absent (2.7 ± 1.2 mm) to extensive lung sliding (14.7 ± 5.8 mm; p < 0.01). Ordered logistic regression predicted Absent sliding with 71% balanced accuracy, with motion tracking correctly identifying all cases and no patients without lung sliding misclassified as extensive, based on visual inspection of the pleural line. In 358 video clips from 30 patients undergoing PEEP titration, there was an association between overdistention quantified by electrical-impedance tomography and PL movement (Spearman-rho=-0.6). PL movement decreased from low to high PEEP levels (p < 0.01).

conclusionsPleural line motion tracking is feasible and provides quantitative insight into pleural movement based on data from healthy volunteers and visual inspection of images from ICU patients. Moreover, pleural line movement allows accurate assessment of overdistention during mechanical ventilation when compared with electrical-impedance tomography.

Indexed as

LungPneumothoraxAdultAgedAlgorithmsCOVID-19FemaleHumansMaleMiddle AgedMotion CaptureMovementPositive-Pressure RespirationProof of Concept StudyUltrasonographyAcute respiratory distress syndromeDetection algorithmsLung slidingLung ultrasoundMotion trackingOverdistentionPleural lineQuantitative lung ultrasound

Identifiers

PMID41572364
PMCPMC12829235

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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.