Three-dimensional reconstruction of soft palate modeling from subject-specific magnetic resonance imaging data

Chen, Hui; Fels, Sidney; Pang, T; Tsou, Ling; Almeida, Fernanda R.; Lowe, Alan A.

doi:10.1007/s11325-011-0610-1

Cited by 6 publications

(13 citation statements)

References 21 publications

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“…Previous studies have reported FEM-based models of the soft palate (e.g., Berry et al 1999; Chen et al 2012) and the jaw–tongue–hyoid complex (e.g., Gerard et al 2006; Stavness et al 2011, 2012). The present work extends this work by extensively modifying the soft palate model of Chen et al (2012), and fitting it to the jaw–tongue–hyoid model of Stavness et al (2011, 2012), with the particular goal of observing interactions between the soft palate and tongue in the region of the OPI. The resulting combined model, built using Artisynth (www.artisynth.org), an open-source FEM simulation toolkit, is shown in Figure 2.…”

Section: Methodsmentioning

confidence: 99%

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Speech function of the oropharyngeal isthmus: a modelling study

Gick

Anderson

Chen

et al. 2014

Computer Methods in Biomechanics and Biomedical Engineering: Im

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A finite element method (FEM) based numerical model of upper airway structures (jaw, tongue, maxilla, soft palate) was implemented to observe interactions between the soft palate and tongue, and in particular to distinguish the contributions of individual muscles in producing speech-relevant constrictions of the oropharyngeal isthmus (OPI), or “uvular” region of the oral tract. Simulations revealed a sphincter-like general operation for the OPI, particularly with regard to the function of the palatoglossus muscle. Further, as has been observed with the lips, the OPI can be controlled by multiple distinct muscular mechanisms, each reliably producing a different sized opening and robust to activation noise, suggestive of a modular view of speech motor control. As off-midline structures of the OPI are difficult to observe during speech production, biomechanical simulation offers a promising approach to studying these structures.

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Section: Methodsmentioning

confidence: 99%

“…The initial soft palate geometry of Chen et al (2012) was morphed with reference to the geometries of the skull, tongue, and surrounding structures. The initial morph was done algorithmically, but additional modifications were made by hand (such as enforcing symmetry to the midsagittal plane).…”

Section: Methodsmentioning

confidence: 99%

Speech function of the oropharyngeal isthmus: a modelling study

Gick

Anderson

Chen

et al. 2014

Computer Methods in Biomechanics and Biomedical Engineering: Im

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“…Soft palate region was analyzed in several works. Chen et al [6] extracted a computational three-dimensional (3D) soft palate model from a set of MRI data to generate a patientspecific model. The segmentation was performed manually.…”

Section: Related Workmentioning

confidence: 99%

A deep cascaded segmentation of obstructive sleep apnea-relevant organs from sagittal spine MRI

et al. 2021

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Purpose The main purpose of this work was to develop an efficient approach for segmentation of structures that are relevant for diagnosis and treatment of obstructive sleep apnea syndrome (OSAS), namely pharynx, tongue, and soft palate, from mid-sagittal magnetic resonance imaging (MR) data. This framework will be applied to big data acquired within an on-going epidemiological study from a general population. Methods A deep cascaded framework for subsequent segmentation of pharynx, tongue, and soft palate is presented. The pharyngeal structure was segmented first, since the airway was clearly visible in the T1-weighted sequence. Thereafter, it was used as an anatomical landmark for tongue location. Finally, the soft palate region was extracted using segmented tongue and pharynx structures and used as input for a deep network. In each segmentation step, a UNet-like architecture was applied. Results The result assessment was performed qualitatively by comparing the region boundaries obtained from the expert to the framework results and quantitatively using the standard Dice coefficient metric. Additionally, cross-validation was applied to ensure that the framework performance did not depend on the specific selection of the validation set. The average Dice coefficients on the test set were $$0.89\pm 0.03$$ 0.89 ± 0.03 , $$0.87\pm 0.02$$ 0.87 ± 0.02 , and $$0.79\pm 0.08$$ 0.79 ± 0.08 for tongue, pharynx, and soft palate tissues, respectively. The results were similar to other approaches and consistent with expert readings. Conclusion Due to high speed and efficiency, the framework will be applied for big epidemiological data with thousands of participants acquired within the Study of Health in Pomerania as well as other epidemiological studies to provide information on the anatomical structures and aspects that constitute important risk factors to the OSAS development.

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“…3,9,12,13,[27][28][29][30] Further, volumetric analysis is recommended in people with OSA to localize areas of airway obstruction and to characterize complex tissues with higher accuracy and reproducibility than linear or 2D measurements. [21][22][23] Volumetric studies using CT or MRI and automated imageprocessing algorithms for fat and complex tissue quantification permit collection of highly quantitative data of pharyngeal structures, allowing more accurate and individualized diagnosis and treatment. [21][22][23][24][25][26] The purpose of this study was to describe and compare the volumetric dimensions of the tongue and tongue fat in BC and mesaticephalic (MC) dogs using multiplanar CT images and specialized volumetric software.…”

mentioning

confidence: 99%

“…[21][22][23] Volumetric studies using CT or MRI and automated imageprocessing algorithms for fat and complex tissue quantification permit collection of highly quantitative data of pharyngeal structures, allowing more accurate and individualized diagnosis and treatment. [21][22][23][24][25][26] The purpose of this study was to describe and compare the volumetric dimensions of the tongue and tongue fat in BC and mesaticephalic (MC) dogs using multiplanar CT images and specialized volumetric software. We hypothesized the tongues of BC dogs would be of greater volume with greater fat deposition compared to MC dogs.…”

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confidence: 99%

CT volumetric analysis permits comparison of tongue size and tongue fat in different canine brachycephalic and mesaticephalic breeds

Song

Phillips

Oliveira

et al. 2023

Vet Radiology Ultrasound

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While macroglossia is a newly accepted component of brachycephalic obstructive airway syndrome (BOAS) in dogs, macroglossia with increased tongue fat is a well-known cause for obstructive sleep apnea (OSA) in people, and targeted reduction procedures such as midline glossectomy are used to treat people with OSA. While midline glossectomy has been described in dogs, tissue contributions to macroglossia have not been characterized. The purpose of this retrospective, descriptive, case-control study was to describe and compare volumetric dimensions of the tongue and tongue fat in brachycephalic (BC) and mesaticephalic (MC) dogs using CT images. Data collected included head and neck CT images from 17 BC and 18 control MC dogs. Multiplanar reformatted and 3D reconstructed images were created using image segmentation and specialized visualization software to calculate volumetric dimensions of the total tongue, tongue fat, and tongue muscle. Rostral and caudal topographical distributions of fat were compared. Total tongue and tongue muscle volume (P < 0.0001) and tongue fat volume (P = 0.01) normalized to body weight (BW) were greater in BC dogs. More fat was localized in the caudal tongue in both groups (P < 0.04). In regression analysis, BC conformation and increased weight were significant predictors of increased tongue fat volume. As in people, increased tongue fat may contribute to macroglossia and sleepdisordered breathing in BC dogs. Use of CT volumetry to identify tongue fat deposits may permit targeted surgical reduction of tongue volume in BC dogs and contribute substantially to treatment of BOAS.

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Three-dimensional reconstruction of soft palate modeling from subject-specific magnetic resonance imaging data

Cited by 6 publications

References 21 publications

Speech function of the oropharyngeal isthmus: a modelling study

Speech function of the oropharyngeal isthmus: a modelling study

A deep cascaded segmentation of obstructive sleep apnea-relevant organs from sagittal spine MRI

CT volumetric analysis permits comparison of tongue size and tongue fat in different canine brachycephalic and mesaticephalic breeds

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