Exploring pleural effusion characterisation with quantitative thoracic ultrasound imaging: a viewpoint on the investigational role of pixel-based echogenicity analysis in transudate and exudate differentiation

Pleural effusion represents a frequent and diagnostically challenging condition across multiple clinical settings. Conventional characterisation relies on invasive thoracentesis and biochemical analysis, with Light's criteria offering high sensitivity but limited specificity. Procedural risks and patient factors may limit fluid sampling, highlighting the need for complementary, noninvasive approaches. Recent advances in thoracic ultrasound (TUS) suggest that quantitative assessment of pleural fluid (PF) echogenicity, particularly pixel density analysis and hypoechogenicity index, may represent an investigational approach for objective and reproducible evaluation. Preliminary studies using standardised image analysis platforms, such as ImageJ, indicate that exudative effusions more frequently exhibit higher pixel density than transudates, in association with markers of cellularity, protein content, and inflammation. Hybrid scoring systems combining quantitative metrics with morphological sonographic features, such as septations, fibrin strands, and debris, have been explored and may enhance diagnostic specificity, although validation remains limited. However, methodological constraints, operator- and device-dependent variability and small sample sizes continue to restrict their applicability in routine clinical practice. Emerging approaches, including artificial intelligence, may be able to mitigate these limitations by standardising measurements, harmonising grayscale output, and integrating clinical, laboratory and imaging data to generate real-time risk scores. In the absence of robustly validated evidence, quantitative TUS should be regarded as an investigational adjunct, with potential to refine PF characterisation, support clinical decision-making, and inform future research on noninvasive diagnostic strategies.

Authors

Institutions

Publication Details

Journal
Breathe
Published
2025-10-01
DOI
https://doi.org/10.1183/20734735.0282-2025
Citations
3
Primary Topic
Ultrasound in Clinical Applications
Type
article
Field-Weighted Citation Impact
4.64
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring pleural effusion characterisation with quantitative thoracic ultrasound imaging: a viewpoint on the investigational role of pixel-based echogenicity analysis in transudate and exudate differentiation

Gianluca Marchi
3 citations
Breathe
Ultrasound in Clinical Applications
4.64
article

Exploring pleural effusion characterisation with quantitative thoracic ultrasound imaging: a viewpoint on the investigational role of pixel-based echogenicity analysis in transudate and exudate differentiation

Gianluca Marchi
article en
3 citations

Abstract

Pleural effusion represents a frequent and diagnostically challenging condition across multiple clinical settings. Conventional characterisation relies on invasive thoracentesis and biochemical analysis, with Light's criteria offering high sensitivity but limited specificity. Procedural risks and patient factors may limit fluid sampling, highlighting the need for complementary, noninvasive approaches. Recent advances in thoracic ultrasound (TUS) suggest that quantitative assessment of pleural fluid (PF) echogenicity, particularly pixel density analysis and hypoechogenicity index, may represent an investigational approach for objective and reproducible evaluation. Preliminary studies using standardised image analysis platforms, such as ImageJ, indicate that exudative effusions more frequently exhibit higher pixel density than transudates, in association with markers of cellularity, protein content, and inflammation. Hybrid scoring systems combining quantitative metrics with morphological sonographic features, such as septations, fibrin strands, and debris, have been explored and may enhance diagnostic specificity, although validation remains limited. However, methodological constraints, operator- and device-dependent variability and small sample sizes continue to restrict their applicability in routine clinical practice. Emerging approaches, including artificial intelligence, may be able to mitigate these limitations by standardising measurements, harmonising grayscale output, and integrating clinical, laboratory and imaging data to generate real-time risk scores. In the absence of robustly validated evidence, quantitative TUS should be regarded as an investigational adjunct, with potential to refine PF characterisation, support clinical decision-making, and inform future research on noninvasive diagnostic strategies.

BreatheVol. 21(4)
University of Pisa (IT), Azienda Ospedaliera Universitaria Pisana (IT)
Openalex Percentile: Top 5%
Ultrasound in Clinical Applications
4.64
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.