A new approach in the study of dynamic connectivity changes in the periaqueductal gray related to subjective sensations during a bladder filling protocol using ultra high-field 7T fMRI

de Rijk M1, van den Hurk J2, Rahnama'i M1, van Koeveringe G3

Research Type

Pure and Applied Science / Translational

Abstract Category

Research Methods / Techniques

Abstract 28
Novel Techniques and Approaches in Basic Science
Scientific Podium Short Oral Session 3
Wednesday 4th September 2019
10:07 - 10:15
Hall G3
Anatomy Imaging Outcomes Research Methods Urodynamics Techniques
1.Department of Urology, Maastricht University, The Netherlands, 2.Scannexus ultra high-field MRI center, Maastricht, The Netherlands, 3.Department of Urology, Maastricht University Medical Center (MUMC+), The Netherlands
Presenter
Links

Abstract

Hypothesis / aims of study
The periaqueductal gray (PAG) has been an area of great interest in the study of brain activity related to bladder function. The PAG is a brainstem area that is implicated to be involved in both storage and voiding of urine. The PAG is assumed to serve as a relay station projecting afferent information from the bladder to cortical and subcortical brain areas and as a gatekeeper projecting efferent information from cortical and subcortical areas to the pons and spinal cord [1, 2]. Studies using animal models have shown that the PAG is organized in a columnar fashion. Technological advances during recent years have made ultra high-field magnetic resonance imaging (MRI) scanners more readily available, and the use of such imaging methods will allow for the investigation of PAG activity in sub-millimeter detail in human participants. This, in turn, allows us to study the PAG at a columnar level in humans. The current study aims to develop a protocol that enables the investigation of PAG activity related to bladder sensations using 7 Tesla fMRI during a bladder filling protocol. We hypothesize that connectivity between PAG subclusters will show significant changes related to participants’ reported bladder sensations during filling of the bladder with saline.
Study design, materials and methods
The current study was approved by the local ethical committee, and informed consent was obtained from of our participants. For the development of this novel methodological approach, we evaluated data of 1 healthy female participant. We acquired 3 fMRI datasets. The first with an empty bladder, the second during filling of the bladder, and the third after participant indicated she experienced a strong desire to void. During the filling of the bladder we recorded our participant’s bladder sensations using a custom made matlab script that she could control from within the scanner using a joystick. The participant’s sensation of bladder fullness was measured using a visual analogue scale and her desire to void was measured using the 4-point perception of intensity of urgency scale. The script recorded the participants sensations once every second. The fMRI data acquired during the filling of the bladder was subdivided into three categories using markers obtained from the responses on the bladder sensations script. Combined with the empty and full bladder runs, we had five states of interest: 1) empty bladder, 2) partially filled bladder without sensation of bladder filling, 3) first sensation of bladder filling, 4) first desire to void, 5) strong desire to void.
Functional data were preprocessed using BrainVoyager. We selected all voxels within PAG for each individual subject, on which we computed a voxel-by-voxel correlation matrix based on the functional time course of each voxel during the full bladder scan. We then parcellated this matrix using the Louvain module detection algorithm (Fig. 1.A), which outputs clusters with stronger within-cluster connectivity than between-cluster connectivity [3]. Next, the correlations between the different clusters at the five different states of bladder sensation were calculated, after which we fitted a second degree polynomial to the data points. The actual amplitude of the polynomial was statistally tested using a non-parametric permutation test.
Results
The modularity Q value resulting from our parcellation of the full bladder scan using the Louvain module detection algorithm was above 0.4, which is an indicator of a modular underlying data structure. The parcellation procedure subdivided the PAG into three distinct clusters. The change in functional connectivity as a function of bladder state between PAG clusters 2 and 3 was significant (p = 0.016) after correcting for multiple comparisons using a false discovery rate (q = 0.05). The patterns of connectivity between clusters 1 & 2, and 1 & 3 did not reach statistical significance (Fig. 1.B).
Interpretation of results
Our results indicate that PAG activity in a full bladder state can be subdivided in clusters, and correlations between these clusters change significantly as a function of experienced sensations during bladder filling. This opens new possibilities  to investigate the effects of treatments of lower urinary tract symptoms on signal proccesing in the PAG, as well as, the investigation of disease-specific bladder filling related dynamic signal processing in this small brain structure.
Concluding message
Ultra-high-field 7T fMRI indicates a clustered organization within the PAG and implies differences in connectivity between these clusters related to reported bladder sensations.
Figure 1
References
  1. Fowler, C.J., D. Griffiths, and W.C. de Groat, The neural control of micturition. Nat Rev Neurosci, 2008. 9(6): p. 453-66.
  2. Zare, A., Jahanshahi, A., Rahnama’i, M. S., Schipper, S., & van Koeveringe, G. A. (2018). The Role of the Periaqueductal Gray Matter in Lower Urinary Tract Function. Molecular neurobiology, 1-15.
  3. Fortunato, S. (2010). Community detection in graphs. Physics reports, 486(3), 75-174.
Disclosures
Funding Funding for this study was provided by the Astellas Europe Fund 2015 and the Faculty of Health, Medicine and Life Sciences of Maastricht University in the Netherlands. Clinical Trial No Subjects Human Ethics Committee METC azM/UM Helsinki Yes Informed Consent Yes
13/11/2024 09:26:03