Cleft palate is one of the most common maxillofacial congenital malformations, which results in severe speech disorders. Compensatory articulation disorder, also known as non-oral articulation disorder (NOA), is considered as the major pathological change among these patients. However, the outcome of speech therapy, an important treatment method, for NOA is often unsatisfactory. This is attributed to the erroneous articulation patterns and entrenched habits in patients with NOA, which require considerable training intensity and time. According to preliminary results from the investigators' own study, as well as studies by others, structural and functional changes have been clearly identified in some brain regions of patients with NOA, suggesting that abnormal neural networks are involved in the progression of NOA. Thus, the investigators proposed the hypothesis that speech therapy effectively corrects articulation disorders through reconfiguration of pathological neural function and reorganization of the abnormal neural network involved in NOA. In this study, multimodal brain imaging techniques will be applied to investigate differences in brain functional connectivity and structural connectivity networks among groups with oral articulation (OA), varying degrees of NOA in postoperative cleft palate patients, and healthy controls. The relationship between improvement in speech intelligibility and alterations in brain networks before and after intervention will be compared. This study aims to reveal the neural network substrates associated with NOA and speech therapy. Overall, through this comprehensive study, the investigators aim not only to provide new insight into the underlying neural mechanism of NOA but also to accumulate evidence for improving the efficacy of speech therapy and discovering new therapeutic strategies in clinical practice.
Cleft palate often leads to compensatory articulation disorder (Non-oral Articulation, NOA), which is resistant to conventional speech therapy. This study is grounded in the hypothesis that the efficacy of speech training is mediated by the reorganization of pathological neural networks and structures associated with NOA. This non-randomized, longitudinal study employs a parallel-group design involving three cohorts: patients with NOA receiving speech training, postoperative cleft palate patients with normal oral articulation (OA) as a clinical control, and healthy controls. The primary objective is to identify the distinctive neural signatures (in both functional connectivity and brain structure) linked to NOA and its remediation through training. All participants undergo multimodal magnetic resonance imaging (including high-resolution T1-weighted and resting-state functional scans) and standardized speech assessments at baseline. Only the NOA group then receives a structured speech training intervention, followed by post-intervention reevaluation. By comparing changes within and between groups, this study aims to disentangle neural alterations specific to NOA from those related to cleft palate in general. The integrative analysis of brain-wide changes with a focus on speech-related regions is expected to provide a systems-level understanding of the neural mechanisms underlying NOA and treatment-induced recovery. The findings may contribute to the development of more effective, neuroscience-informed therapeutic strategies.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
TREATMENT
Masking
SINGLE
Enrollment
164
This structured, one-on-one speech decompensation therapy targets Non-oral Articulation Disorder (NOA) in postoperative cleft palate patients, using the glottal stop /kʔ/ as a key sound to guide correct articulation placement and correct compensatory habits. It follows a structured paradigm from error recognition to generalization, integrating multisensory cues. Delivered by a therapist 3 times/week for 1 hour over 5-12 weeks with parent participation, it includes daily home practice. Completion requires accurate sound production, with daily parent-supervised maintenance practice for one year thereafter.
School & Hospital of Stomatology Wenzhou Medical University
Wenzhou, Zhejiang, China
Change in Functional Connectivity of the Speech Related Network
Change in resting-state functional connectivity, focusing on connections between pre-defined speech-related regions (Broca's and Wernicke's areas) and additionally assessed through whole-brain network analysis, using resting-state fMRI data.
Time frame: From baseline assessment to post-training assessment (approximately at Week 12)
Change in Percent Correct Consonants (PCC)
Change in the percentage of consonants produced correctly, assessed within both single-word and conversational speech contexts. The measure is derived from standardized speech samples, which are evaluated by blinded, certified speech-language pathologists.
Time frame: From baseline assessment to post-training assessment (approximately at Week 12)
Change in Grey Matter Volume (GMV) of Articulation-Related Regions
Alterations in grey matter volume across the whole brain, with a focus on regions implicated in articulation. Measured by voxel-based morphometry (VBM) analysis of high-resolution T1-weighted magnetic resonance imaging (MRI) scans.
Time frame: From baseline to post-training assessment (at Week 12)
Change in Regional Homogeneity (ReHo) in Speech-Related Cortex
Changes in local brain activity synchronization across the whole brain, with particular emphasis on the speech-related cortex.
Time frame: From baseline to post-training assessment (at Week 12)
Change in Amplitude of Low-Frequency Fluctuations (fALFF)
Changes in the fractional amplitude of low-frequency fluctuations in the blood-oxygen-level-dependent (BOLD) signal across the whole brain, assessed within regions of the speech and auditory processing networks. Derived from resting-state fMRI data.
Time frame: From baseline to post-training assessment (at Week 12)
Change in Proportion of Compensatory Articulation Errors
Change in the proportion of compensatory (non-oral) articulation errors relative to the total number of consonants attempted, analyzed within both single-word and conversational speech samples. This metric is calculated through phonetic transcription of the speech samples to quantify the frequency of error patterns characteristic of non-oral articulation.
Time frame: From baseline to post-training assessment (at Week 12)
Change in White Matter Volume (WMV) of Articulation-Related Regions
Alterations in white matter volume across the whole brain, particularly within tracts associated with speech motor pathways. Analyzed using voxel-based analysis of T1-weighted MRI to quantify white matter volume changes.
Time frame: From baseline to post-training assessment (at Week 12)
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