Poster No:
1382
Submission Type:
Abstract Submission
Authors:
Kimberly Weldon1, Robert Hermosillo2, Rahel Nardos2, Damien Fair1
Institutions:
1University of Minnesota, Minneapolis, MN, 2Oregon Health & Science University, Portland, OR
First Author:
Co-Author(s):
Rahel Nardos
Oregon Health & Science University
Portland, OR
Introduction:
Urge urinary incontinence (UUI) is a condition defined by sudden sensations of the need to urinate accompanied with or followed by immediate leakage of urine (Griffiths et al., 2010). Prior work found functional connectivity differences between patients with UUI and control participants without UUI depending on whether their bladder was full or empty (Nardos et al., 2016). This previous work relied on averaging brain responses of each group, which could obscure individual-specific responses to each condition. In this study we leveraged precision functional mapping (PFM; Gordon et al., 2017), to resolve individual-specific brain networks without averaging across patients. We used this method to investigate the effect of empty and full bladders on network connectivity in women with and without UUI.
Methods:
Female participants were recruited from gynecology clinics at Oregon Health & Science University (OHSU), partner health centers, and the OHSU community at large. The participants (n = 45, age = 57.57 ± 7.65 years, 17 control participants) completed up to two scanning sessions.
Data was acquired with a 3.0-T Siemens Tim Trio Scanner using a 12-channel head coil at OHSU between 2010 and 2014. High-resolution T1w images were obtained for all participants. For ten of those participants, high-resolution T2 images were also acquired. T2*-weighted echo planar images (TR: 2,500 ms, TE: 30 ms, slice thickness: 3.75mm, flip angle: 90°) were acquired in 5 min 2 s resting state functional MRI (rsfMRI) runs and in 5 min 14 s task fMRI runs.
In each scanning session, participants first completed two rsfMRI runs with an empty bladder, followed by two task fMRI runs wherein saline was infused and withdrawn from the participant's bladder via transurethral bladder catheter during the run. These four runs made up a "non-Urge" condition. Following these runs, the participant's bladder was infused with saline until the participant expressed the first desire to void their bladder. The participant then repeated two rsfMRI runs and two task fMRI runs in an "Urge condition". These acquisitions resulted in a maximum of 20 min 10 s of BOLD data in each of the two conditions.
All of the data for each participant were minimally preprocessed with fmriPrep 24.0.1 (Esteban et al., 2019). Denoised BOLD images and functional derivatives were generated with XCP-D 9.0.0 (Mehta et al., 2024). Precision functional maps were constructed for each participant in the study. Network templates were produced from all 45 participants using the template matching procedure (Hermosillo et al., 2024). In brief, the spatial similarity (eta²) at each grayordinate was calculated to each of the network templates and, in each individual participant, each grayordinate was assigned to the network template that had the highest eta² value. Group connectivity matrices were generated by assigning each grayordinate to a network if it occurred in that network in at least 36 individuals.
Results:
Functional connectivity as it relates to the urge to urinate were resolved for every participant. Participants without UUI showed more differences in overall functional connectivity between the Urge and non-Urge conditions than UUI patients.
Conclusions:
PFM is a feasible method for investigating how functional connectivity changes in patients with UUI and control participants without UUI as a result of experiencing the urge to urinate. The method produces individual maps that allow detection of network topography with increased confidence. In this study, control participants showed more changes in functional connectivity as a result of having the urge to urinate compared to patients with a history of UUI.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 1
Perception, Attention and Motor Behavior:
Perception: Pain and Visceral
Keywords:
FUNCTIONAL MRI
Other - precision imaging, overactive bladder
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Resting state
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Patients
Was this research conducted in the United States?
Yes
Are you Internal Review Board (IRB) certified?
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Yes, I have IRB or AUCC approval
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
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Not applicable
Please indicate which methods were used in your research:
Functional MRI
Structural MRI
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
AFNI
FSL
Free Surfer
Provide references using APA citation style.
Esteban, O. (2019). fMRIPrep: a robust preprocessing pipeline for functional MRI. Nature methods, 16(1), 111-116.
Gordon, E. M. (2017). Precision functional mapping of individual human brains. Neuron, 95(4), 791-807.
Griffiths, D. J. (2009). Cerebral control of the lower urinary tract: how age-related changes might predispose to urge incontinence. Neuroimage, 47(3), 981-986.
Hermosillo, R. J., (2024). A precision functional atlas of personalized network topography and probabilities. Nature neuroscience, 27(5), 1000-1013.
Mehta, K. (2024). XCP-D: A Robust Pipeline for the post-processing of fMRI data. Imaging Neuroscience, 2, 1-26.
Nardos, R. (2016). Abnormal functional connectivity in women with urgency urinary incontinence: can we predict disease presence and severity in individual women using Rs‐fcMRI. Neurourology and urodynamics, 35(5), 564-573.
No