Journal
NEUROGASTROENTEROLOGY AND MOTILITY
Volume 30, Issue 8, Pages -Publisher
WILEY
DOI: 10.1111/nmo.13335
Keywords
Fecal incontinence and continence; functional lumen imaging probe (FLIP); functional morphometry; involuntary and voluntary muscle properties; sphincter muscles
Funding
- Nanotera.ch initiative
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BackgroundA large proportion of age-related fecal incontinence is attributed to weakness or degeneration of the muscles composing the anal continence organ. However, the individual role of these muscles and their functional interplay remain poorly understood. MethodsThis study employs a novel technique based on the combination of MR imaging and FLIP measurements (MR-FLIP) to obtain anatomical and mechanical information simultaneously. Unlike previous methods used to assess the mechanics of the continence organ, MR-FLIP allows inter-individual comparisons and statistical analysis of the sphincter morpho-mechanical parameters. The anatomy as well as voluntary and involuntary mechanical properties of the anal continence organ were characterized in 20 healthy senior volunteers. ResultsResults showed that the external anal sphincter (EAS) forms a funnel-like shape with wall thickness increasing by a factor of 2.5 from distal (60mm) to proximal (15 +/- 3mm). Both voluntary and involuntary mechanical properties in this region correlate strongly with the thickness of the muscle. The positions of least compliance and maximal orifice closing were both located toward the proximal EAS end. In addition, maximal contraction during squeeze maneuvers was reached after 2s, but high muscle fatigue was measured during a 7s holding phase, corresponding to about 60% loss of the energy produced by the muscles during the contraction phase. ConclusionsThis work reports baseline parameters describing the morpho-mechanical condition of the sphincter muscle of healthy elderly volunteers. New parameters were also proposed to quantify the active properties of the muscles based on the mechanical energy associated with muscle contraction and fatigue. This information could be used to assess patients suffering from AI or for the design of novel implants.
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