EP-4543300-B1 - ACCURATE DIAPHRAGM THICKNESS AND FUNCTION EVALUATION USING ULTRASOUND AND MECHANICAL VENTILATOR SIGNALS

Inventors

• HENDRIKS, Cornelis, Petrus
• BUIZZA, Roberto
• POLKEY, Michael
• HAARTSEN, JAAP, ROGER
• SABCZYNSKI, JOERG
• WIEMKER, RAFAEL
• KOEHLER, THOMAS

Dates

Publication Date

20260513

Application Date

20230623

Claims (11)

1. A diaphragm measurement device, comprising: at least one electronic processor programmed to perform a diaphragm measurement method (100) including: receiving ultrasound imaging data (101) of a dimension of a diaphragm of a patient during inspiration and expiration while the patient undergoes mechanical ventilation therapy with a mechanical ventilator; receiving respiratory data of the patient (102) during inspiration and expiration while the patient undergoes the mechanical ventilation therapy, wherein the respiratory data comprises an airway flow in an airway of the patient; calculating a diaphragm thickness metric (103) based on the received ultrasound imaging data of the diaphragm of the patient and the received respiratory data as a ratio of a diaphragmatic thickness of the diaphragm and the airway flow in an airway of the patient; and displaying, on a display device, a representation of the calculated diaphragm thickness metric (104).
2. The device of claim 1, wherein the diaphragm thickness metric includes a diaphragm thickening ratio indicative of a diaphragm thickness during inspiration relative to a diaphragm thickness during expiration.
3. The device of claim 1, wherein the diaphragm thickness metric includes a mean diaphragm thickness over multiple respiratory cycles.
4. The device of claim 1, further comprising: an ultrasound imaging device including an ultrasound patch attached to a portion of the patient, wherein the at least one electronic processor controls the ultrasound imaging device to receive the ultrasound imaging data of the diaphragm of the patient from the ultrasound patch.
5. The device of claim 1, wherein the respiratory data comprises a mean airway flow value at an end of inspiration and at an end of expiration.
6. The device of claim 1, wherein the respiratory data comprises a maximum airway flow value and a minimum airway flow value at an end of inspiration and at an end of expiration.
7. The device of claim 1, wherein the at least one electronic processor is further programmed to: calculate a responsiveness index of a patient as a ratio of a change in a compliance of the airway of the patient to a change in one or more mechanical ventilation settings of an associated mechanical ventilator.
8. The device of claim 7, wherein the at least one electronic processor is further programmed to: control an associated mechanical ventilator to adjust one or more parameters of the mechanical ventilation therapy delivered to the patient based on the calculated responsiveness index.
9. The device of claim 8, wherein the at least one electronic processor is further programmed to: display, on the display device, a representation of the calculated responsiveness index.
10. The device of claim 1, wherein the at least one electronic controller is configured to: control an associated mechanical ventilator to adjust one or more parameters of the mechanical ventilation therapy delivered to the patient based on the calculated diaphragm thickness metric.
11. The device of claim 1, further comprising: a mechanical ventilator configured to deliver mechanical ventilation therapy to the patient.

Description

The following relates generally to the respiratory therapy arts, mechanical ventilation arts, ventilator induced lung injury (VILI) arts, mechanical ventilation weaning arts, and related arts. BACKGROUND Diaphragmatic ultrasonography (US) allows for quantification of diaphragm thickness, strain (rate) and excursion, and with this also the respiratory rate and duration of each contraction. Diaphragm thickness (expressed as thickening fraction) and strain reflect contractile activity and correlate well with diaphragmatic electrical activity and diaphragmatic pressure. Consequently, thickness and strain may be used as a surrogate for respiratory effort. Applications of diaphragmatic ultrasound include assessment of diaphragm function, atrophy detection, weaning prediction, and mechanical ventilation (MV) setting management. Other applications could be asynchrony detection and proportional ventilation (non-invasive neurally adjusted ventilatory assist (NAVA)). The use of diaphragmatic ultrasound in mechanical ventilation is gaining attention and therefore, technical problems and use cases are currently being investigated. A diaphragm thickening fraction (TFdi or TFDI) as measured by ultrasound (US) are carried out by an operator who looks at the patient and takes an ultrasound image at end inhalation and end exhalation. The diaphragm thickness fraction is determined by subtracting the end inhalation thickness from the end exhalation thickness and dividing the difference by the exhale thickness according to Equation 1: TFdi=Tei−TeeTee∗100% with Tei as the end-inspiratory thickness. Some studies have evaluated the correlation between TFdi and respiratory effort. In one study (see, e.g., E. Oppersma et al. Functional assessment of the diaphragm by speckle tracking ultrasound during inspiratory loading. J Appl Phys. 2017), at the zone of apposition the diaphragm strain can similarly be measured in real-time. For example, in this study, the functional assessment of the diaphragm by speckle tracking ultrasound during inspiratory loading was analyzed. The technique of speckle tracking ultrasound allows for the detection and tracking of diaphragmatic strain over time by analyzing acoustic markers called speckles. These speckles are formed by interference of ultrasound waves that are scattered from physical structures of a size comparable to the wavelength of the ultrasound waves. Both diaphragm strain and diaphragm strain rate were highly correlated to transdiaphragmatic pressure Pdi (strain r2 = 0.72; strain rate r2 = 0.80) and diaphragm electrical activity EAdi (strain r2 = 0.60; strain rate r2 = 0.66). A problem is the reliability of the diaphragmatic thickness measurements. The accuracy, repeatability, and reproducibility are limited due to the thin form factor of the diaphragm, the motion and macro-deformation of the diaphragm and the surrounding structures and tissues, the device handling (angle, position, motion), poor image quality, and operator skills. The variation and uncertainty in TFDI can be very high (see, e.g., Goligher EC, et al. 2015, "Measuring diaphragm thickness with ultrasound in mechanically ventilated patients: feasibility, reproducibility and validity". Intensive Care Med. 2015 Apr;41(4):642-9. doi: 10.1007/s00134-015-3687-3. Epub 2015 Feb 19. Erratum in: Intensive Care Med. 2015 Apr;41(4):734. Sebastien-Bolz, Steffen [corrected to Bolz, Steffen-Sebastien]. PMID: 25693448; Tuinman PR, et al., 2020, "Respiratory muscle ultrasonography: methodology, basic and advanced principles and clinical applications in ICU and ED patients-a narrative review". Intensive Care Med. 2020 Apr;46(4):594-605. doi: 10.1007/s00134-019-05892-8. Epub 2020 Jan 14. PMID: 31938825; PMCID: PMC7103016). For example, Goligher reports a thickness change 0.3 mm ± 0.3 mm. In this example the error margin (0.6 mm) is twice the nominal thickness change (0.3 mm). This uncertainty undermines the confidence in clinical decisions which are based on the TFDI, for example decisions on pressure support, weaning, and extubation (see, e.g., Tuinman,). Besides the above-mentioned measurement errors, another source of variability in TFDI is the variation in respiratory effort / work of breathing (WOB) between breaths. This is reflected in the ventilator waveforms which vary over time. If the TFDI is measured and averaged over different breaths, without considering the variability in WOB, this obviously contributes to the error margin in TFDI. A further source of anticipated variation in practice is disease induced diaphragm atrophy which is likely to make the 'noise to signal' ratio higher. Another study (see, e.g., O'Hara DN, et al., 2020, "Ultrasonographic modeling of diaphragm function: A novel approach to respiratory assessment". PLoS ONE 15(3): e0229972. https://doi.org/10.1371/journal.pone.0229972) measured the diaphragm thickness Tdi at different levels of negative inspiratory force (NIF) using a handheld NIF meter. A NIF meter deter