Diaphragm Ultrasound: State-of-the-Art Review

Diaphragm ultrasound has become a widely adopted bedside tool for assessing respiratory muscle function in both acute and chronic respiratory failure. Initially introduced as a descriptive imaging technique, it is now increasingly used to support physiological interpretation, prognostic evaluation, and monitoring during invasive and noninvasive respiratory support, as well as in chronic respiratory diseases. In clinical practice, diaphragm ultrasound findings are often interpreted using isolated threshold values to classify diaphragm function as normal or abnormal, an approach that may inadequately represent the underlying respiratory muscle physiology. This state-of-the-art review summarizes current evidence across critical illness, noninvasive respiratory support, chronic respiratory failure, and chronic obstructive pulmonary disease (COPD). Conventional parameters-such as diaphragm thickness, thickening fraction, and excursion-are discussed within a physiological framework, highlighting their limitations in assessing intrinsic muscle strength when considered in isolation. Emerging ultrasound-based techniques, including speckle tracking, elastography, echogenicity analysis, contrast-enhanced ultrasound, and area-based motion assessment, are also reviewed. These approaches aim to provide deeper insights into diaphragmatic biomechanics, muscle quality, and perfusion, although they remain largely investigational and lack standardized acquisition and interpretation protocols. Overall, conventional diaphragm ultrasound parameters offer partial, load-dependent information with moderate and variable prognostic value across clinical settings. Integrated approaches combining diaphragm, lung, and peripheral muscle ultrasound appear to enhance physiological interpretation and clinical relevance. Diaphragm ultrasound should therefore be regarded as a dynamic, complementary component of multimodal respiratory assessment rather than a stand-alone diagnostic tool, with its greatest value in longitudinal monitoring and individualized clinical decision making.