Volumetric analysis of the hypothalamic subunits in obstructive sleep apnea.

BACKGROUND: Obstructive sleep apnea (OSA) is a prevalent sleep disorder that is associated with structural brain damage and cognitive impairment. The hypothalamus plays a crucial role in regulating sleep and wakefulness. We aimed to evaluate hypothalamic subunit volumes in patients with OSA. METHODS: We enrolled 30 participants (15 patients with OSA and 15 healthy controls (HC)). Patients with OSA underwent complete overnight polysomnography (PSG) examination. All the participants underwent MRI. The hypothalamic subunit volumes were calculated using a segmentation technique that trained a 3D convolutional neural network. RESULTS: Although hypothalamus subunit volumes were comparable between the HC and OSA groups (lowest p = .395), significant negative correlations were found in OSA patients between BMI and whole left hypothalamus volume (R = -0.654, p = .008), as well as between BMI and left posterior volume (R = -0.556, p = .032). Furthermore, significant positive correlations were found between ESS and right anterior inferior volume (R = 0.548, p = .042), minimum SpO2 and the whole left hypothalamus (R = 0.551, p = .033), left tubular inferior volumes (R = 0.596, p = .019), and between the percentage of REM stage and left anterior inferior volume (R = 0.584, p = .022). CONCLUSIONS: While there were no notable differences in the hypothalamic subunit volumes between the OSA and HC groups, several important correlations were identified in the OSA group. These relationships suggest that factors related to sleep apnea severity could affect hypothalamic structure in patients.

Low arousal threshold is associated with altered functional connectivity of the ascending reticular activating system in patients with obstructive sleep apnea.

A low arousal threshold (LAT) is a pathophysiological trait of obstructive sleep apnea (OSA) that may be associated with brainstem ascending reticular activating system-cortical functional connectivity changes. We evaluated resting-state connectivity between the brainstem nuclei and 105 cortical/subcortical regions in OSA patients with or without a LAT and healthy controls. Twenty-five patients with moderate to severe OSA with an apnea-hypopnea index between 20 and 40/hr (15 with and 10 without a LAT) and 15 age- and sex-matched controls were evaluated. Participants underwent functional magnetic resonance imaging after overnight polysomnography. Three brainstem nuclei-the locus coeruleus (LC), laterodorsal tegmental nucleus (LDTg), and ventral tegmental area (VTA)-associated with OSA in our previous study were used as seeds. Functional connectivity values of the two brainstem nuclei (LC and LDTg) significantly differed among the three groups. The connectivity of the LC with the precuneus was stronger in OSA patients than in controls regardless of the concomitant LAT. The connectivity between the LDTg and the posterior cingulate cortex was also stronger in OSA patients regardless of the LAT. Moreover, OSA patients without a LAT showed stronger LDTg-posterior cingulate cortex connectivity than those with a LAT (post hoc p = 0.013), and this connectivity strength was negatively correlated with the minimum oxygen saturation in OSA patients (r = - 0.463, p = 0.023). The LAT in OSA patients was associated with altered LDTg-posterior cingulate cortex connectivity. This result may suggested that cholinergic activity may play a role in the LAT in OSA patients.

A Survey Study of the 3D Facial Landmark Detection Techniques Used as a Screening Tool for Diagnosis of the Obstructive Sleep Apnea Syndrome.

Obstructive Sleep Apnea (OSA) is a common disorder affecting both adults and children. It is characterized by repeated episodes of apnea (stopped breathing) and hypopnea (reduced breathing), which result in intermittent hypoxia. We recognize pediatric and adult OSA, and this paper focuses on pediatric OSA. While adults often suffer from daytime sleepiness, children are more likely to develop behavioral abnormalities. Early diagnosis and treatment are important to prevent negative effects on children's development. Without the treatment, children may be at increased risk of developing high blood pressure or other heart problems. The gold standard for OSA diagnosis is the polysomnography (sleep study) PSG performed at a sleep center. Not only is it an expensive procedure, but it can also be very stressful, especially for children. Patients have to stay at the sleep center during the night. Therefore, screening tools are very important. Multiple studies have shown that OSA screening tools can be based on facial anatomical landmarks. Anatomical landmarks are landmarks located at specific anatomical locations. For the purpose of the screening tool, a specific list of anatomical locations needs to be identified. We are presenting a survey study of the automatic identification of these landmarks on 3D scans of the patient's head. We are considering and comparing both knowledge-based and AI-based identification techniques, with a focus on the development of the automatic OSA screening tool.

The effect of including dynamic imaging derived airway wall motion in CFD simulations of respiratory airflow in patients with OSA.

Obstructive sleep apnea (OSA) is an airway disease caused by periodic collapse of the airway during sleep. Imaging-based subject-specific computational fluid dynamics (CFD) simulations allow non-invasive assessment of clinically relevant metrics such as total pressure loss (TPL) in patients with OSA. However, most of such studies use static airway geometries, which neglect physiological airway motion. This study aims to quantify how much the airway moves during the respiratory cycle, and to determine how much this motion affects CFD pressure loss predictions. Motion of the airway wall was quantified using cine MRI data captured over a single respiratory cycle in three subjects with OSA. Synchronously-measured respiratory airflow was used as the flow boundary condition for all simulations. Simulations were performed for full respiratory cycles with 5 different wall boundary conditions: (1) a moving airway wall, and static airway walls at (2) peak inhalation, (3) end inhalation, (4) peak exhalation, and (5) end exhalation. Geometric analysis exposed significant local airway cross-sectional area (CSA) variability, with local CSA varying as much as 300%. The comparative CFD simulations revealed the discrepancies between dynamic and static wall simulations are subject-specific, with TPL differing by up to 400% between static and dynamic simulations. There is no consistent pattern to which static wall CFD simulations overestimate or underestimate the airway TPL. This variability underscores the complexity of accurately modeling airway physiology and the importance of considering dynamic anatomical factors to predict realistic respiratory airflow dynamics in patients with OSA.

Association of MRI Indexes of the Perivascular Space Network and Cognitive Impairment in Patients with Obstructive Sleep Apnea.

Background The role of perivascular space (PVS) dysfunction in obstructive sleep apnea (OSA) requires further study. Purpose To compare MRI indexes of PVS across patients with differing severities of OSA and relate them with disease characteristics and treatment. Materials and Methods This single-center prospective study included healthy controls (HCs) and patients with complaints of snoring who underwent MRI and cognitive evaluation between June 2021 and December 2022. Participants with complaints of snoring were classified into four groups (snoring, mild OSA, moderate OSA, and severe OSA). PVS networks were assessed at MRI using PVS volume fraction, extracellular free water (FW), and diffusion tensor imaging analysis along the PVS (DTI-ALPS). One-way analysis of variance and Pearson correlation were used for analysis. Alterations in PVS indexes and cognitive performance after treatment were assessed in 15 participants with moderate OSA. Results A total of 105 participants (mean age, 33.4 years ± 8.9 [SD]; 80 males) and 50 HCs (mean age, 37.0 years ± 8.6; 33 males) were included. Higher mean PVS volume fraction was observed in participants with severe OSA (n = 23) than in patients with mild OSA (n = 36) (0.11 vs 0.10; P = .03). Participants with severe OSA exhibited higher mean FW index (0.11) than both HCs (0.10; P < .001) and patients with mild OSA (0.10; P = .003). All patient groups had lower DTI-ALPS than HCs (range, 1.5-1.9 vs 2.1; all P < .001). DTI-ALPS correlated with cognitive performance on the Stroop Color and Word Test (r range, -0.23 to -0.24; P value range, .003-.005). After treatment, PVS indexes changed (P value range, <.001 to .01) and cognitive performance improved (P value range, <.001 to .03). Conclusion Differences in PVS indexes were observed among participants with differing severities of OSA and HCs. Indexes correlated with measures of cognitive function, and changes in indexes and improvement in cognitive performance were observed after treatment in participants with moderate OSA. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Port in this issue.

Using standardized ultrasound imaging to correlate OSA severity with tongue morphology.

BACKGROUND: Ultrasound imaging has been explored as a potential diagnostic tool for obstructive sleep apnea (OSA); we reported backscatter ultrasound imaging (BUI) of the tongue correlates with OSA severity in adults. We focus on anatomical features of the tongue using standardized ultrasonography and hypothesize that differences in morphology correlate with OSA severity. METHODS: This prospective study was IRB approved (53,172) and conducted at Stanford University Sleep Surgery Clinic. Patients ≥18 years with polysomnography (PSG) underwent a standardized submental ultrasound scan using a laser alignment tool to observe the upper airway in supine position during tidal respiration. Images acquired from this scan were divided into 4 equiangular regions (A-D). RESULTS: A total of 144 patients (30 women) July 2020-December 2022 were included with mean age 41.6 years (±12.9 SD), BMI 27.2 kg/m2(±4.7 SD), and AHI 19.7 (±20.0 SD). Moderate-to-severe OSA patients had significantly narrower airspace at regions A, B and C with p-values ranging from <0.0001 to 0.0003. These patients had a significantly wider (p = 0.0021-0.0045 for regions A, B and C) tongue and thicker (p = 0.0403 for region B) deep tissue. The predictive model to assess the risk of moderate-to-severe OSA achieved an area under the receiver operating characteristic curve of 0.839 (95 % CI: 0.769 to 0.895). CONCLUSIONS: With standardized, computerized ultrasound imaging of the shape and configuration of the tongue, we identified regions that correlated well with OSA severity. Further research is needed to determine the clinical implications of such pathophysiological findings.

Abnormal dynamic functional connectivity and topological properties of cerebellar network in male obstructive sleep apnea.

PURPOSE: To investigate dynamic functional connectivity (dFC) within the cerebellar-whole brain network and dynamic topological properties of the cerebellar network in obstructive sleep apnea (OSA) patients. METHODS: Sixty male patients and 60 male healthy controls were included. The sliding window method examined the fluctuations in cerebellum-whole brain dFC and connection strength in OSA. Furthermore, graph theory metrics evaluated the dynamic topological properties of the cerebellar network. Additionally, hidden Markov modeling validated the robustness of the dFC. The correlations between the abovementioned measures and clinical assessments were assessed. RESULTS: Two dynamic network states were characterized. State 2 exhibited a heightened frequency, longer fractional occupancy, and greater mean dwell time in OSA. The cerebellar networks and cerebrocerebellar dFC alterations were mainly located in the default mode network, frontoparietal network, somatomotor network, right cerebellar CrusI/II, and other networks. Global properties indicated aberrant cerebellar topology in OSA. Dynamic properties were correlated with clinical indicators primarily on emotion, cognition, and sleep. CONCLUSION: Abnormal dFC in male OSA may indicate an imbalance between the integration and segregation of brain networks, concurrent with global topological alterations. Abnormal default mode network interactions with high-order and low-level cognitive networks, disrupting their coordination, may impair the regulation of cognitive, emotional, and sleep functions in OSA.

Correlation of diffusion tensor tractography with obstructive sleep apnea severity.

INTRODUCTION: Using correlation tractography, this study aimed to find statistically significant correlations between white matter (WM) tracts in participants with obstructive sleep apnea (OSA) and OSA severity. We hypothesized that changes in certain WM tracts could be related to OSA severity. METHODS: We enrolled 40 participants with OSA who underwent diffusion tensor imaging (DTI) using a 3.0 Tesla MRI scanner. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and quantitative anisotropy (QA)-values were used in the connectometry analysis. The apnea-hypopnea index (AHI) is a representative measure of the severity of OSA. Diffusion MRI connectometry that was used to derive correlational tractography revealed changes in the values of FA, MD, AD, RD, and QA when correlated with the AHI. A false-discovery rate threshold of 0.05 was used to select tracts to conduct multiple corrections. RESULTS: Connectometry analysis revealed that the AHI in participants with OSA was negatively correlated with FA values in WM tracts that included the cingulum, corpus callosum, cerebellum, inferior longitudinal fasciculus, fornices, thalamic radiations, inferior fronto-occipital fasciculus, superior and posterior corticostriatal tracts, medial lemnisci, and arcuate fasciculus. However, there were no statistically significant results in the WM tracts, in which FA values were positively correlated with the AHI. In addition, connectometry analysis did not reveal statistically significant results in WM tracts, in which MD, AD, RD, and QA values were positively or negatively correlated with the AHI. CONCLUSION: Several WM tract changes were correlated with OSA severity. However, WM changes in OSA likely involve tissue edema and not neuronal changes, such as axonal loss. Connectometry analyses are valuable tools for detecting WM changes in sleep disorders.

[Correlation study between brain damage and anxiety, depression, and cognitive impairment in patients with moderate to severe obstructive sleep apnea hypopnea syndrome using diffusional kurtosis imaging].

Objective: To explore the brain white matter damage in patients with moderate to severe obstructive sleep apnea hypopnea syndrome(OSAHS) using diffusional kurtosis imaging(DKI), and to analyze its relationship with anxiety, depression and cognitive impairment in patients. Methods: This was a retrospective case-control study. Fifty confirmed cases (47 males and 3 females) of moderate to severe OSAHS diagnosed by polysomnography(PSG) from November 2017 to December 2022 were selected as OSAHS group(age range from 22 to 65 years old, with median age of 40 years old), and 32 healthy controls(27 males and 5 females) of non-OSAHS diagnosed by PSG were selected as control group(age range from 19 to 56 years old, with median age of 34 years old). DKI scanning, Beck Anxiety Inventory(BAI), Beck Depression Inventory-Ⅱ(BDI-Ⅱ), and Montreal cognitive assessment(MoCA) scores were performed in all subjects. Differences in kurtosis fractional anisotropy(KFA) of various brain regions were compared between the two groups to identify differential brain regions. Correlations were analyzed between KFA reduction and anxiety, depression, and cognitive impairment in OSAHS patients. To study the correlation between brain injury and anxiety, depressive mood, and cognitive dysfunction, statistical methods such as non-parametric tests for two independent samples, chi-square tests, and partial correlation analysis, were used to analyze the evaluation indicators of the two groups. Results: The KFA values in right external capsule, left anterior corona radiata, right anterior corona radiata, left posterior corona radiata, right posterior corona radiata, left superior corona radiata, right superior corona radiata, left superior longitudinal fasciculus, right superior longitudinal fasciculus, genu of corpus callosum, splenium of corpus callosum, body of corpus callosum, posterior cingulate gyrus of moderate to severe OSAHS group were all lower than those in the control group(t=-2.247, -3.028, -3.955, -4.871, -2.632, -2.594, -2.121, -2.167, -3.129, -2.015, -2.317, -2.313, -2.152,P<0.05). For the moderate to severe OSAHS group, the correlation between AHI and KFA values of right posterior corona radiata, right superior corona radiata, left anterior corona radiata, left posterior corona radiata, left superior corona radiata, left superior longitudinal fasciculus, genu of corpus callosum, body of corpus callosum, splenium of corpus callosum were all negative(r=-0.378, -0.307, -0.337, -0.343, -0.341, -0.613, -0.390, -0.384, -0.396, P<0.05). The correlation between LSO2 and KFA values of right anterior corona radiata, right posterior corona radiata, right superior corona radiata, right superior longitudinal fasciculus, left anterior corona radiata, left posterior corona radiata, left superior corona radiata, left superior longitudinal fasciculus, genu of corpus callosum, body of corpus callosum, splenium of corpus callosum, posterior cingulate gyrus were all positive(r=0.330, 0.338, 0.425, 0.312, 0.433, 0.358, 0.410, 0.459, 0.473, 0.659, 0.489, 0.356, P<0.05). The correlation between BAI scores and KFA values of right external capsule, right anterior corona radiata, left posterior corona radiata, left superior corona radiata, body of corpus callosum, splenium of corpus callosum were all negative(r=-0.306, -0.372, -0.296, -0.346, -0.318, -0.386, P<0.05). The correlation between BDI-Ⅱ scores and KFA values of right superior corona radiata, right superior longitudinal fasciculus, left anterior corona radiata, genu of corpus callosum, body of corpus callosum, splenium of corpus callosum were all negative(r=-0.334, -0.289, -0.309, -0.310, -0.503, -0.469, P<0.05). The correlation between MoCA scores and KFA values of right posterior corona radiata, right superior longitudinal fasciculus, left anterior corona radiata, left superior corona radiata, left superior longitudinal fasciculus, genu of corpus callosum, body of corpus callosum, splenium of corpus callosum were all positive(r=0.368, 0.431, 0.324, 0.410, 0.469, 0.384, 0.369, 0.309, P<0.05). Conclusions: With the aggravation of OSAHS, the damage to some brain regions becomes more pronounced in moderate to severe OSAHS patients. These damage brain functional areas are closely related to the anxiety, depression, and cognitive impairment of patients.

Association Between Soft Tissue Measures From Computed Tomography and Upper Airway Collapsibility on Drug-Induced Sleep Endoscopy.

OBJECTIVE: Positive airway pressure (PAP) titration during drug-induced sleep endoscopy (DISE) provides objective measures of upper airway collapsibility. While skeletal measurements relate to collapsibility measures on DISE, the influence of soft tissue dimensions on upper airway collapsibility is not known. We analyzed the relationship of measures of upper airway soft tissue volumes, specifically soft palate, pharyngeal lateral walls, and tongue, with metrics of collapsibility. STUDY DESIGN: Cross-sectional analysis from a prospective cohort. SETTING: Academic medical center. METHODS: Patients seeking PAP alternative therapies for obstructive sleep apnea (OSA) underwent standardized supine computed tomography (CT) acquisition and DISE protocols. The CT analysis primarily focused on soft tissue volumes and, secondarily, on airway and skeletal volumetric measures. DISE with PAP administration (DISE-PAP) enabled the determination of the pressure at which inspiratory airflow first commenced (pharyngeal critical pressure, PcritA) and the pressure at which inspiratory flow limitation was abolished (pharyngeal opening pressure, PhOP). Both unadjusted and adjusted correlation analyses were performed to understand the relationship between upper airway anatomy and either PcritA or PhOP. RESULTS: One hundred thirty-nine subjects completed both CT and DISE-PAP. On average, patients were male (70.5%), white (84.2%), middle-aged (56.6 ± 13.5 years), and overweight (29.6 ± 4.7 kg/m2), with moderate-severe apnea-hypopnea index (29.7 ± 21.3 events/h). Adjusted for age, sex, body mass index, and skeletal volumes, soft palate, and lateral pharyngeal wall volumes were not associated with PhOP or PcritA, but a larger tongue was associated with more positive PhOP (⍴ = 0.20, P = .02), and more positive PcritA (⍴ = 0.16, P = .07). Exploratory analyses revealed smaller minimum cross-sectional retropalatal area and intramandibular volume were also associated with increased collapsibility measures. CONCLUSION: After controlling for clinical factors and skeletal volume, greater tongue volume was associated with more severe collapsibility during DISE. These results, in concert with previous work, suggest that greater tongue volume in a smaller skeletal dimensions contribute to the severity of airway collapsibility, a key driver of OSA pathogenesis.

3D analysis of upper airway morphology related to obstructive sleep apnea severity.

BACKGROUND: Obstructive sleep apnea (OSA) is the most common sleep-related breathing disorder characterized by repetitive collapse of the upper airway during sleep. However, little evidence is available on the differences between the sub-regions of the upper airway morphology and OSA severity. Since orthodontists frequently perform cone beam computed tomography (CBCT) in the neck area, we aimed to investigate the relationship and the differences between upper airway morphology and OSA severity using CBCT. MATERIALS AND METHODS: The medical records, CBCT imaging of 21 OSA patients diagnosed by polysomnography, and the apnea-hypopnea index (AHI) results were included to classify OSA severity as mild, moderate, or severe. The minimum cross-sectional areas (MCA) and volumes of the upper pharyngeal airway boundaries in four sub-regions: nasopharynx, retropalatal, retroglossal, and hypopharynx were measured. Dolphin Imaging software was used for upper airway segmentation. The correlation coefficient (r), one-way ANOVA, and the least significant difference post hoc multiple comparison test were applied to fulfill the objectives. RESULTS: A statistically significant relationship was found between the MCA of the nasopharynx and the AHI (r = -0.473, P < 0.05). Furthermore, a difference was found between mild and moderate and moderate and severe OSA severity in the MCA results of the retroglossal region (P < 0.05). However, no relationship was found between the upper airway volume and OSA severity. CONCLUSIONS: MCA was moderately negatively correlated to AHI only in the nasopharynx subregion. Moderate OSA presented significantly less MCA than mild and severe OSA only in the oropharynx and retroglossal subregions.

Altered functional connectivity of cerebellar subregions in male patients with obstructive sleep apnea: A resting-state fMRI study.

PURPOSE: Previous studies have demonstrated impaired cerebellar function in patients with obstructive sleep apnea (OSA), which is associated with impaired cognition. However, the effects of OSA on resting-state functional connectivity (FC) in the cerebellum has not been determined. The purpose of this study was to investigate resting-state FC of the cerebellar subregions and its relevance to clinical symptoms in patients with OSA. METHODS: Sixty-eight patients with OSA and seventy-two healthy controls (HCs) were included in the study. Eight subregions of the cerebellum were selected as regions of interest, and the FC values were calculated for each subregion with other voxels. A correlation analysis was performed to examine the relationship between clinical and cognitive data. RESULTS: Patients with OSA showed higher FC in specific regions, including the right lobule VI with the right posterior middle temporal gyrus and right angular gyrus, the right Crus I with the bilateral precuneus/left superior parietal lobule, and the right Crus II with the precuneus/right posterior cingulate cortex. Furthermore, the oxygen depletion index was negatively correlated with aberrant FC between the right Crus II and the bilateral precuneus / right posterior cingulate cortex in OSA patients (p = 0.004). CONCLUSION: The cerebellum is functionally lateralized and closely linked to the posterior default mode network. Higher FC is related to cognition, emotion, language, and sleep in OSA. Abnormal FC may offer new neuroimaging evidence and insights for a deeper comprehension of OSA-related alterations.

A gated recurrent unit model based on ultrasound images of dynamic tongue movement for determining the severity of obstructive sleep apnea.

Obstructive sleep apnea (OSA) presents as a respiratory disorder characterized by recurrent upper pharyngeal airway collapse during sleep. Dynamic tongue movement (DTM) analysis emerges as a promising avenue for elucidating the pathophysiological underpinnings of OSA, thereby facilitating its diagnosis. Recent endeavors have utilized artificial intelligence techniques to categorize OSA severity leveraging electrocardiography and blood oxygen saturation data. Nonetheless, the integration of ultrasound (US) imaging of the tongue remains largely untapped in the development of machine learning models aimed at determining the severity of OSA. This study endeavors to bridge this gap by capturing US images of DTM dynamics during wakefulness, encompassing transitions from normal breathing (NB) to the performance of the Müller maneuver (MM) in a cohort of 53 patients. Leveraging the modified optical flow method (MOFM), the trajectories of patients' DTM were tracked, facililtating the extraction of 27 parameters vital for model training. These parameters encompassed nine-point lateral movement, nine-point axial movement, and nine-point total displacement of the tongue, resulting in a dataset of 186,030 samples. The gated recurrent unit (GRU) method, renowned for its efficacy in motion tracking, was employed for model development in this study. Validation of the developed model was conducted via stratified k-fold cross-validation (SCV). The systems' overall performance in classifying OSA severity, as quantified by mean accuracy (MA), yielded a value of 43.49%. This pilot investigation marks an exploratory endeavor into the utilization of artificial intelligence for the classification of OSA severity based on US images and dynamic movement patterns. This novel model holds potential to assist clinicians in categorizing OSA severity and guiding the selection of pertinent treatment modalities tailored to the individual needs of patients afflicted with OSA.

Predicting Obstructive Sleep Apnea Based on Computed Tomography Scans Using Deep Learning Models.

Rationale: The incidence of clinically undiagnosed obstructive sleep apnea (OSA) is high among the general population because of limited access to polysomnography. Computed tomography (CT) of craniofacial regions obtained for other purposes can be beneficial in predicting OSA and its severity. Objectives: To predict OSA and its severity based on paranasal CT using a three-dimensional deep learning algorithm. Methods: One internal dataset (N = 798) and two external datasets (N = 135 and N = 85) were used in this study. In the internal dataset, 92 normal participants and 159 with mild, 201 with moderate, and 346 with severe OSA were enrolled to derive the deep learning model. A multimodal deep learning model was elicited from the connection between a three-dimensional convolutional neural network-based part treating unstructured data (CT images) and a multilayer perceptron-based part treating structured data (age, sex, and body mass index) to predict OSA and its severity. Measurements and Main Results: In a four-class classification for predicting the severity of OSA, the AirwayNet-MM-H model (multimodal model with airway-highlighting preprocessing algorithm) showed an average accuracy of 87.6% (95% confidence interval [CI], 86.8-88.6%) in the internal dataset and 84.0% (95% CI, 83.0-85.1%) and 86.3% (95% CI, 85.3-87.3%) in the two external datasets, respectively. In the two-class classification for predicting significant OSA (moderate to severe OSA), the area under the receiver operating characteristic curve, accuracy, sensitivity, specificity, and F1 score were 0.910 (95% CI, 0.899-0.922), 91.0% (95% CI, 90.1-91.9%), 89.9% (95% CI, 88.8-90.9%), 93.5% (95% CI, 92.7-94.3%), and 93.2% (95% CI, 92.5-93.9%), respectively, in the internal dataset. Furthermore, the diagnostic performance of the Airway Net-MM-H model outperformed that of the other six state-of-the-art deep learning models in terms of accuracy for both four- and two-class classifications and area under the receiver operating characteristic curve for two-class classification (P < 0.001). Conclusions: A novel deep learning model, including a multimodal deep learning model and an airway-highlighting preprocessing algorithm from CT images obtained for other purposes, can provide significantly precise outcomes for OSA diagnosis.

Decreased structural pathways mediating functional connectivity in obstructive sleep apnea.

BACKGROUND: Obstructive sleep apnea (OSA) is a common sleep breathing disorder that is often accompanied by changes in structural connectivity (SC) and functional connectivity (FC). However, the current understanding of the interaction between SC and FC in OSA is still limited. METHODS: The aim of this study is to integrate complementary neuroimaging modalities into a unified framework using multi-layer network analysis methods and to reveal their complex interrelationships. We introduce a new graph metric called SC-FC bandwidth, which measures the throughput of SC mediating FC in a multi-layer network. The bandwidth differences between two groups are evaluated using the network-based statistics (NBS) method. Additionally, we traced and analyzed the SC pathways corresponding to the abnormal bandwidth. RESULTS: In both the healthy control and patients with OSA, the majority offunctionally synchronized nodes were connected via SC paths of length 2. With the NBS method, we observed significantly lower bandwidth between the right Posterior cingulate gyrus and right Cuneus, bilateral Middle frontal gyrus, bilateral Gyrus rectus in OSA patients. By tracing the high-proportion SC pathways, it was found that OSA patients typically exhibit a decrease in direct SC-FC, SC-FC triangles, and SC-FC quads intra- and inter-networks. CONCLUSION: Complex interrelationship changes have been observed between the SC and FC in patients with OSA, which might leads to abnormal information transmission and communication in the brain network.

Clinical and radiographic periodontal status in hypertensive patients with or without obstructive sleep apnea 10 years after diagnosis and CPAP initiation.

OBJECTIVES: Through inflammation and hyposalivation, obstructive sleep apnea (OSA) is suggested to affect periodontal status over time. Our aim was to compare the clinical and radiographic periodontal status of hypertensive patients with or without long-term presence of OSA, treated or untreated with continuous positive airway pressure treatment (CPAP). MATERIALS AND METHODS: In 2007-2009, a screening for OSA was conducted among 394 hypertensive primary care patients. Polygraphy was used to create three groups: no OSA, non-CPAP, or adherent CPAP based on the apnea hypopnea index (AHI). After 10 years, a cross-sectional sleep and periodontal examination including a clinical and radiographic examination, a questionnaire, and a matrix metalloproteinase-8 (MMP-8) chair-side test was conducted. Based on levels of alveolar bone, bleeding on probing (BoP), and probing pocket depth (PPD), patients were categorized into four periodontal stages: periodontal health/gingivitis and three periodontal disease stages. Periodontal status and periodontal stages were compared between the OSA (n = 49), non-CPAP (n = 38), or adherent CPAP (n = 34) groups. RESULTS: The 121 patients (53% women) had a median age of 71 years. No differences were seen between the OSA groups regarding median number of teeth (p = .061), teeth/implants, (p = .107), plaque index (p = .245), BoP (p = .848), PPD ≥ 4 mm (p = .561), PPD ≥ 6 mm (p = .630), presence of MMP-8 (p = .693) except for bone loss (p = .011). Among patients with stage periodontal health/gingivitis a significant difference was seen, as 70% of those were categorized as no OSA, 20% as non-CPAP, and 10% as adherent CPAP (p = .029). Differences were not seen in periodontal disease stages. CONCLUSIONS: Hypertensive patients with obstructive sleep apnea (OSA) did not have an adverse clinical periodontal status compared to patients without OSA. However, when combining radiographic and clinical status into periodontal stages, patients without OSA more frequently exhibited periodontal health or gingivitis compared to patients without OSA, regardless of CPAP treatment.

Ultrasonographic changes and impact factors of diaphragmatic function in patients with obstructive sleep apnea-hypopnea syndrome.

PURPOSE: Diaphragmatic impairment has been reported in obstructive sleep apnea-hypopnea syndrome (OSAHS) patients. However, the risk factors of diaphragmatic dysfunction are unclear. This study was conducted to evaluate the diaphragmatic function and to investigate impact factors of ultrasonographic changes of the diaphragm in OSAHS patients. METHODS: This cross-sectional study recruited 150 snoring patients. All patients were divided into the control group (AHI < 5/h, n = 20), the mild-to-moderate OSAHS group (5/h ≤ AHI ≤ 30/h, n = 61), and the severe OSAHS group (AHI > 30/h, n = 69). Diaphragmatic thickness at function residual capacity (TFRC) and total lung capacity (TTLC) were measured by two-dimensional ultrasound, and the diaphragmatic excursion during tidal and deep breath was measured by M-mode ultrasound. The diaphragmatic thickening fraction (TF) was calculated. Spearman analysis and multiple linear stepwise regression analysis were conducted to analyze the impact factors of diaphragmatic function. RESULTS: TFRC in the control group, mild-to-moderate OSAHS group, and severe OSAHS group was 1.23 (1.10, 1.39) mm, 1.60 (1.43, 1.85) mm, and 1.90 (1.70, 2.25) mm; TTLC was 2.75 (2.53, 2.93) mm, 3.25 (2.90, 3.55) mm, and 3.60 (3.33, 3.90) mm, and TF was 119.23% (102.94, 155.97), 96.55% (74.34, 119.11), and 85.29% (60.68,101.22). There were across-group significant differences in TFRC, TTLC, and TF (P < 0.05). The oxygen desaturation index was the influencing factor of TFRC, TTLC, and TF (P < 0.05). CONCLUSION: The diaphragm is thickened and diaphragmatic contractility is decreased in OSAHS patients. Nocturnal intermittent hypoxia is a risk factor for diaphragmatic hypertrophy and impaired diaphragmatic contractility.

The Epworth sleepiness scale may have more advantages than the multiple sleep latency test in assessing sleepiness in patients with obstructive sleep apnea.

This study aimed to analyze the brain function of severe obstructive sleep apnea patients with various sleepiness assessment methods and explore the brain imaging basis for the differences between these methods. This study included 30 severe obstructive sleep apnea patients and 19 healthy controls. Obstructive sleep apnea patients were divided into a subjective excessive daytime sleepiness group and a subjective non-excessive daytime sleepiness group according to the Epworth sleepiness scale. Moreover, they were divided into an objective excessive daytime sleepiness group and an objective non-excessive daytime sleepiness group according to the multiple sleep latency test. The fractional amplitude of low-frequency fluctuation was used to assess the features of brain function. Compared with healthy controls, participants in the subjective excessive daytime sleepiness group exhibited higher fractional amplitude of low-frequency fluctuation signals in the right thalamus, left cerebellar lobe 6, left putamen, and pallidum. Participants in the objective excessive daytime sleepiness group showed higher fractional amplitude of low-frequency fluctuation signals in the right thalamus and lower fractional amplitude of low-frequency fluctuation signals in the right superior frontal gyrus, the dorsolateral and superior frontal gyrus, and the medial orbital. We concluded that the thalamus may be involved in subjective and objective sleepiness regulation. Functional abnormalities in the putamen and pallidum may be involved in subjective sleepiness, whereas the frontal lobe may be involved in objective sleepiness.

Evaluation of condylar and mandibular movements on the upper airway during the use of mandibular advancement device for obstructive sleep apnea treatment.

OBJECTIVES: To evaluate the temporomandibular joint (TMJ), condylar and mandibular movements in obstructive sleep apnea (OSA) patients treated with mandibular advancement device (MAD) and to identify the influence of these anatomic factors on upper airway (UA) volume and polysomnographic outcomes after treatment. MATERIALS AND METHODS: Twenty OSA patients were prospectively treated with MAD. Clinical examinations, cone-beam computed tomography, and polysomnography were performed before MAD treatment and after achieving therapeutic protrusion. Polysomnographic variables and three-dimensional measurements of the TMJ, mandible, and upper airway were statistically analyzed. RESULTS: Condylar rotation, anterior translation, and anterior mandibular displacement were directly correlated with total UA volume, while vertical mandibular translation was inversely correlated with the volume of the inferior oropharynx. MAD treatment resulted in an increase in the volume and area of the superior oropharynx. There was no statistically significant correlation between condylar rotation and translation and polysomnographic variables. With MAD, there was a significant increase in vertical dimension, changes in condylar position (rotation and translation), and mandibular displacement. The central and medial lengths of the articular eminence were inversely correlated with condylar rotation and translation, respectively. The lateral length of the eminence was directly correlated with condylar translation, and the lateral height was directly correlated with condylar rotation and translation. CONCLUSION: Condylar and mandibular movements influenced UA volume. The articular eminence played a role in the amount of condylar rotation and translation. CLINICAL RELEVANCE: Individualized anatomical evaluation of the TMJ proves to be important in the therapy of OSA with MAD.

The role of the tongue in post-stroke dysphagia and obstructive sleep apnea: Correlation with sonography measurement.

OBJECTIVE: Obstructive sleep apnea (OSA) is a common risk factor for stroke, and dysphagia and pneumonia are both well-known complications of stroke. The development of these conditions is related to the oropharyngeal structures. We investigated whether specific structural features of the tongue may lead to the development of these complications. METHODS: Patients with ischemic stroke who required admission and community-dwelling elderly controls were enrolled. The participants underwent tongue measurements by received hand-held ultrasound, and received questionnaires to evaluate sleep quality and daytime sleepiness. The patient group also underwent objective sleep measurement by actigraphy and the 3-Step Swallowing Test (3-SSS). Sleep parameters and outcomes were analyzed. RESULTS: Patient with ischemic stroke had significantly thicker tongue than controls (6.53 cm v. 6.05 cm, p = 0.002). Multiple logistic regression analysis revealed that the anatomical parameters of the tongue in patients with stroke were significantly correlated with parameters of OSA, and the thickness of the tongue was positively correlated with the development of OSA (p = 0.024) and pneumonia (p = 0.048). CONCLUSIONS: A thicker-than average tongue may be a risk factor for OSA and pneumonia in patient with stroke. Hand-held ultrasound can be used to identify these anatomical features. Further studies are warranted to clarify the role of the tongue in these post-stroke complications.