Towards a better understanding of abdominal wall biomechanics: in vivo relationship between dynamic intra-abdominal pressure and magnetic resonance imaging measurements

TL;DR

This study investigates in vivo abdominal wall biomechanics by simultaneously tracking dynamic MRI-based muscle motion and intra-abdominal pressure (IAP) via an ingestible sensor across breathing, coughing, and Valsalva maneuvers in 18 healthy participants. It reveals strong, yet highly participant-specific, correlations between IAP and visceral area or muscle displacement, with RA coupling strongest during passive breathing and lateral muscles coupling during active maneuvers. Abdominal pseudo-compliance varies considerably between individuals and exercises, underscoring the need for personalized assessment. The findings have implications for mesh design, surgical decision-making, and individualized healthcare in abdominal wall pathologies such as hernias.

Abstract

Background In vivo mechanical behaviour of the abdominal wall has been poorly characterised and important details are missing regarding the occurrence and post-operative recurrence rate of hernias which can be as high as 30 %. This study aimed to assess the correlation between abdominal wall displacement and intra-abdominal pressure, as well as abdominal compliance. Methods Eighteen healthy participants performed audio-guided passive (breathing) and active (coughing, Valsalva maneuver) exercises. Axial dynamic changes of abdominal muscles and visceral area were measured using MRI, and intra-abdominal pressure with ingested pressure sensor. Findings Correlations between abdominal wall displacement and intra-abdominal pressure were specific to participant, exercise, and varying between rectus abdominis and lateral muscles. Strong correlations were found between rectus abdominis displacement and intra-abdominal pressure during breathing (r = 0.92 $\pm$ 0.06), as well as lateral muscles displacement with intra-abdominal pressure during coughing and Valsalva maneuver (r = --0.98 $\pm$ 0.03 and -- 0.94 $\pm$ 0.05 respectively). The abdominal pseudo-compliance varied greatly among participants during muscular contraction, the coefficient of variation reaching up to 70 %. Interpretation The combination of intra-abdominal pressure and dynamic MRI measurements enables the identification of participant-specific behaviour pattern. Intra-abdominal pressure and abdominal wall dynamic undergo consistent and predictable interactions. However, this relationship is subject-specific and may not be extrapolated to other individuals. Therefore, both intra-abdominal pressure and abdominal wall motion must be measured in the same participant in order to accurately characterise the abdominal wall behaviour. These results are of great importance for mesh design, surgical decision-making, and personalised healthcare.

Figures (5)

• Figure 1: Typical 2D axial abdominal MRI slice without annotation a) Segmentation masks are indicated in b) and c)
• Figure 2: Metrics derived from MRI a) Abdominal radial distances at rest b) Radial displacement scheme c) Radial displacement of each pixel of the segmentation masks d) Radial displacement averaged among LM and RA segmentation masks
• Figure 3: Example of selected timepoints and averaging repetitions during breathing a) Repetitions delimitation (left: visceral area, right: intra-abdominal pressure (IAP)) b) Average cycle (left: visceral area, right: IAP) c) Linear correlation between the average cycles of IAP and visceral area during ascending phase, i.e. from the beginning until the IAP reaches its maximum value
• Figure 4: Temporal changes for different exercises of a) Intra-abdominal pressure (IAP, mmHg) b) Visceral area (%) c) Radial displacement of LM and RA (%) Results are presented as mean values $\pm$ one standard deviation $\sigma$
• Figure 5: Intra-abdominal pressure maximum change $\Delta_{max} IAP$ as a function of visceral area maximum change $\Delta_{max} VA$ for all participants and all exercises Each spoke represents one participant (Pn: participant n) Data normalised by the highest value (among all participants) to be scaled from 0 to 1