ABSTRACT
Purpose@#Assessing brainstem function in humans through typical neuroimaging modalities has been challenging. Our objective was to evaluate brain and brainstem activation patterns during initiation of voiding in healthy males and females utilizing a 7 Tesla magnetic resonance imaging (MRI) scanner and a noninvasive brain-bladder functional MRI (fMRI) protocol. @*Methods@#Twenty healthy adult volunteers (10 males and 10 females) with no history of urinary symptoms were recruited. Each volunteer underwent a clinic uroflow and postvoid residual assessment and was asked to consume water prior to entering the scanner. Anatomical and diffusion tensor images were obtained first, followed by a blood oxygenation level dependent (BOLD) resting-state fMRI (rs-fMRI) during the empty bladder. Subjects indicated when they felt the urge to void, and a full bladder rs-fMRI was obtained. Once completed, the subjects began 5 voiding cycles, where the first 7.5 seconds of each voiding cycle was identified as “initiation of voiding.” BOLD activation maps were generated, and regions of interests with a t-value greater than 2.1 were deemed statistically significant. @*Results@#We present 5 distinct regions within the periaqueductal gray (PAG) and pontine micturition center (PMC) with statistically significant activation associated with an initiation of voiding in both men and women, 3 within the PAG and 2 within the PMC. Several additional areas in the brain also demonstrated activation as well. When comparing males to females, there was an overall lower BOLD activation seen in females throughout all regions, with the exception of the caudate lobe. @*Conclusions@#Our study effectively defines regions within the PAG and PMC involved in initiation of voiding in healthy volunteers. To our knowledge, this is the first study investigating differences between male and female brainstem activation utilizing an ultra-high definition 7T MRI.
ABSTRACT
Purpose@#This study evaluates the grey and white brain matter characteristics in women with multiple sclerosis (MS) and detrusor sphincter dyssynergia (DSD). Grey matter is assessed via the functional connectivity (FC) of brain regions activated during voiding, using functional magnetic resonance imaging (fMRI). Two white matter tracts involved in bladder function, the anterior thalamic radiation (ATR) and superior longitudinal fasciculus (SLF), were evaluated using diffusion tensor imaging. @*Methods@#Twenty-seven women with MS (2 groups: no-DSD [n=23] or DSD [n=4]), and 8 healthy controls (HCs) underwent concurrent urodynamic-fMRI evaluation with 4 cycles of bladder filling and emptying. A FC similarity measure (FC_sim) was calculated for each subject to express the similarity of individual FC at voiding initiation compared to all FC patterns. ATR and SLF tracts were traced and their fractional anisotropy (FA) and mean diffusivity (MD) were recorded. @*Results@#Mean FC_sim values were significantly different among the 3 groups indicating distinct FC patterns; however, no significant difference was found between DSD and no-DSD groups. DSD group showed trends of lower FA and higher MD— indicating loss of coherence—in all tracts compared to HCs, and in the left and right ATR when compared to MS women with neither DSD nor voiding dysfunction (VD), suggesting more damage in these tracts for MS women with DSD. @*Conclusions@#Women with MS show distinctly different FC patterns compared to HCs. There are trends showing more damage in the ATR in women with MS and DSD compared to those with neither DSD nor VD.
ABSTRACT
PURPOSE: To quantify the relative importance of brain regions responsible for reduced functional connectivity (FC) in their Voiding Initiation Network in female multiple sclerosis (MS) patients with neurogenic lower urinary tract dysfunction (NLUTD) and voiding dysfunction (VD). A data-driven machine-learning approach is utilized for quantification. METHODS: Twenty-seven ambulatory female patients with MS and NLUTD (group 1: voiders, n=15 and group 2: VD, n=12) participated in a functional magnetic resonance imaging (fMRI) voiding study. Brain activity was recorded by fMRI with simultaneous urodynamic testing. The Voiding Initiation Network was identified from averaged fMRI activation maps. Four machine-learning algorithms were employed to optimize the area under curve (AUC) of the receiver-operating characteristic curve. The optimal model was used to identify the relative importance of relevant brain regions. RESULTS: The Voiding Initiation Network exhibited stronger FC for voiders in frontal regions and stronger disassociation in cerebellar regions. Highest AUC values were obtained with ‘random forests’ (0.86) and ‘partial least squares’ algorithms (0.89). While brain regions with highest relative importance (>75%) included superior, middle, inferior frontal and cingulate regions, relative importance was larger than 60% for 186 of the 227 brain regions of the Voiding Initiation Network, indicating a global effect. CONCLUSIONS: Voiders and VD patients showed distinctly different FC in their Voiding Initiation Network. Machine-learning is able to identify brain centers contributing to these observed differences. Knowledge of these centers and their connectivity may allow phenotyping patients to centrally focused treatments such as cortical modulation.