Video tracking-based Mandibular Movement Kinematic Analysis in patients with nasopharyngeal carcinoma

Video tracking-based Mandibular Movement Kinematic Analysis in patients with nasopharyngeal carcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Video tracking-based Mandibular Movement Kinematic Analysis in patients with nasopharyngeal carcinoma Chen Yang, Zhenhai Wei, Fei Zhao, Yangshiyu Zhou, Linfei Wu, Xiaomei Wei, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3894122/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective Patients with dysphagia due to nasopharyngeal carcinoma (NPC) after radiotherapy often have chewing difficulty. Kinematic analysis of mandibular movements may provide clinically useful information for the chewing function. However, current kinematic device costs limited clinical application, and specialized software is required for control and data processing. This study aimed to mandibular kinematics parameter recognition using a self-developed Nswallow 2D motion capture software. To investigate whether differences in kinematic data of mandibular movements during mastication can be used as an indicator of masticatory dysfunction in NPC patients, and the relationship with mastication efficiency. Method Thirty-three patients with early-stage NPC after radiotherapy and thirty-five healthy controls were recruited. The self-developed Nswallow 2D motion capture software was used to automatically mark and capture the facial parts of the participants. We tracked jaw kinematic during chewing, and analyzed the characteristics of kinematic data of mandibular movements during chewing tasks. Meanwhile, the masticatory efficiency using two-color chewing gum was analyzed by the Viewgum software. Result Significant differences were observed in the mastication time (Total Masticatory Time (NPC:12.349 ± 2.428; HC:8.742 ± 1.349) & Chewing Sequence Duration (NPC:636.573 ± 85.432; HC:543.646 ± 65.9388)), speed of mandibular motion (Maximum Speed (NPC:23.740(17.775,25.906); HC:28.800(24.643,38.800) & Average Speed (NPC:11.844(10.395,13.285); HC:18.169(15.790,21.435)), and Mandibular Motion Amplitude (NPC:7.159(5.887,7.869); HC:8.478(7.291;11.020)) between two groups (P < 0.000). Logistic regression analysis and receiver operating characteristic curve analyses were performed based on the above data as explanatory variables. Among them, the average chewing speed exhibited the highest area under the ROC curve, the odds ratio was 3.629, the cutoff value was 14.28, with a sensitivity of 90.91%, a specificity of 80.00%, and an area under the curve of 0.9255. The masticatory efficiency in the NPC group significantly decreased compared to the healthy control group (P < 0.000). Linear regression analysis showed that average chewing speed negatively affects masticatory efficiency. Conclusion The Nswallow 2D motion capture software represents an easy-to-use and affordable system that can be utilized to assess masticatory function in patients with NPC. In addition, the average speed of chewing is a highly sensitive kinematic indicator for evaluating mastication efficiency. nasopharyngeal carcinoma dysphagia mastication kinematics mastication efficiency Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Nasopharyngeal carcinoma (NPC) is a malignant tumor that occurs in the nasopharynx and nasopharyngeal epithelia [ 1 ] . Radiation therapy has been demonstrated to be effective [ 2 ] . However, many complications might be associated with radiation therapy, including dysphagia and trismus [ 3 ] , as well as muscle fibrosis which impaired mastication capabilitie [ 4 ] . These complications can potentially result in gradually worse of swallowing, speech production, chewing ability, and other orofacial motor functions. Early and accurate assessment of motor function impairment can facilitate the comprehension of patients' current functional status, enabling early intervention and enhancing the quality of life [ 5 ] . Oral movement assessments through clinical observation usually was the main sceening test, which may be easy overlook for patients with minor impairment during early stage. The face to face assesssment also could pose the risk of droplet transmission of respiratory infections. Computer vision technology has the potential to fully or partially automate the clinical examination of oral and maxillofacial dysfunction, thus providing an accurate and objective assessment. Researchers have introduced various approaches for precisely measuring the kinematic characteristics of the tongue, jaw, and lips (such as position and speed during speech production) [ 6 ] . These advancements facilitate effective monitoring in the early-stage of orofacial dyskinesia in patients [ 7 ] . A deep learning-based model combined with a 3D camera can accurately localize facial landmarks in videos of patients performing various speech tasks [ 5 – 8 ] . However, the clinical applicability of these techniques is constrained due to their reliance on costly and user-unfriendly systems [ 9 ] . The 2D Markerless Systems are a relatively convenient and cost-effective technique. Research has demonstrated that 2D features, extracted from color cameras only, are as informative as 3D features, extracted from color and depth cameras [ 9 ] , implying that 2D video analysis may serve as a superior evaluation method. Therefore, this study developed an accessible face tracking software system to assess orofacial motor function. The recorded videos of participants were obtained during chewing movement and facial markers was determined before collection through the software. The aim was to investigate the differences of mandibular kinematics data during chewing between NPC patients and healthy participants, and further to clarify the potential indicators for evaluating masticatory dysfunction that influence mastication efficiency. 2. Materials and Methods 2.1 Participants Consecutive patients admitted to a hospital underwent rehabilitation at a hospital outpatient clinic in Guangzhou, China, between February 2020 and November 2020, participated in this cross-sectional study. In this study, thirty-three patients with NPC after radiotherapy (20 males and 13 females, age 54.18 ± 9.70). The duration of radiotherapy for NPC varied from 2 to 24 years, while the number of radiotherapy sessions ranged from 21 to 45. All participants included in the study met the following criteria: (1) diagnosed with NPC and treated with radiotherapy or chemoradiotherapy; complicated with dysphagia which was identified with videofluoroscopic swallowing study (VFSS); (2) FOIS (Functional Oral Intake Scale) ≥ 4; (3) has no history of orofacial trauma or surgery. Patients were excluded if they fulfilled the following criteria: (1) presence of tumor recurrence or metastasis; (2) presence of other neurological diseases affecting oral movements; (3) unstable vital signs; (4) no consent from patients or family members; and (5) a history of oral cancer, dental disorders causing painful chewing, or ill-fitting dentures. Meanwhile, thirty-five age-matched healthy participants (13 males and 22 females, aged 51.80 ± 6.84) were recruited for this study. The research protocol was approved by the Research Ethics Committee of the Third Affiliated Hospital of Sun Yat-sen University (2021-02-321-01). 2.2 Experimental Procedure Kinematics Using a 2-Dimensional Motion Capture System During each session, movements of lips and jaw were recorded by the 2D motion capture system. The 2D motion capture system consisting of analytical software (Nswollow) and a camera (Exilim EX-F1, Casio, Tokyo, Japan, resolution 640×480 pixels at 50 frames per second (fps)), which can automatically mark 67 facial sites for motion capture and quantitative analysis. which can automatically mark facial sites for motion capture and quantitative analysis. Nswallow software was developed to achieve face tracking : ① CMU model: In this study, a Nswallow software was developed that utilizes a CMU model incorporating a face detector to accurately locate and track facial feature points, achieving video-based jaw tracking. The software utilizes the data detected in the preceding frame as input for subsequent frames and performs re-detection only when there are no faces present in the previous frame. ② Extraction points: The recognition of keypoints in the Openpose framework primarily relies on regression algorithms. We utilized the facial marker points obtained from a previously validated deep learning-based facial alignment model. These markers are acquired from the model and are not distributed on the face [ 5 ] . The distribution of these markers is as follows: 10 for eyebrows, 14 for eyes, 9 for noses, and 20 for lips (12 for external contours and 8 for internal contours), 17 for facial contour, as shown in Fig. 1 A. The markers were concealed during recording. The target site investigated in this study was referred to as site 8 and site 33. That is, the point position of jaw central (8th Marker points = JC) and nose tip (33rd Marker points = NT) is extracted as the key point detection. After collecting the subject's chewing video, Openpose is utilized to identify and extract facial and jaw movements from each pre-processed frame. The extracted jaw movement features are then quantified using Opencv. ③ Filtering processing: The extracted point coordinates undergo Savitzky-Golay filtering for noise reduction pre-processing. The result is obtained by reading the json file of the target keypoints. The set of kinematic features extracted for each task is presented in Table 1 . All participants were filmed at a face-camera distance ranging from 30 to 50 cm and at a height close to that of the participant’s eyes [ 10 ] A continuous light source was positioned adjacent to the camera for providing consistent illumination (Fig. 1 B). Throughout the task, participants were required to maintain their gaze towards the camera and minimize excessive head movements. After obtaining preliminary data, researchers had to manually correct the videos in order to eliminate redundant actions. Finally, there were 68 videos included in the analysis: 35 recordings from healthy participants and 33 recordings from patients with NPC. Table 1. Description of the kinematic features extracted for each task. Task Variable (unit) Description Chewing task Mastication Time Total Masticatory Time Duration of all chewing cycles Chewing Sequence Duration Average duration of a single chewing Mandibular Motion Amplitude Average displacement of JC of a single chewing: module of the vector from JC to NT . Speed of Mandibular Motion Maximum speed Maximum velocity of JC during chewing cycles Average speed Average velocity of JC during a single chewing. Right Corner (RC), Left Corner (LC), Jaw Central (JC), and Nose Tip (NT). Calculate the physical data of the target point Two of markers including jaw central (8th Marker points = JC), and nose tip (33rd Marker points = NT) were extracted for kinematic analysis. The key frames depicting the resting position of the jaw and its maximum displacement during the chewing sequence were identified. Subsequently, a demarcation line was established to define the duration period of chewing, followed by computation of relevant temporal parameters. The number of key frames can be obtained, and the duration of entire chewing cycle can be calculated based on the camera's FPS. Spatial parameters for mandibular motion amplitude are computed using each two-dimensional pixel coordinate. By combining these, speed parameters as well as stability and rhythm characteristics of mastication can be calculated. Procedures for assessing masticatory efficiency Masticatory efficiency was evaluated with a previously validated colour-mixing ability test. Specimens of 30 mm length were prepared from Wrigley's Doublemint-F5® gums (Wrigley's Doublemint-F5®; Azure and Pink; The Wrigley Company; Guangzhou, China) in the flavours ‘Sour Berry’ (azure colour) and ‘Watermelon’ (pink colour). We cut strips from both colors and manually stuck them together, resulting in a test strip that measures 30×18×3 mm. Prior to each chewing cycle, participants were instructed to thoroughly remove any food debris from their mouth and clean any soft dirt from the tooth surface. They were then asked to naturally chew two-coloured gums for a total of 20 cycles. The resulting bolus was then retrieved from the oral cavity, and flattened into a 1 mm thick wafer by pressing it with a custom-made polyvinyl chloride plate that had a milled depression of 1mm×50mm×50mm [ 11 ] . The digitized images were arranged side by side to form a single 1000-pixel image for analysis of masticatory efficiency using specialized software program (ViewGum®; dHAL Software) [ 12 ] . The software converts the compound image of both sides of the specimen into the HIS color space and calculates the standard deviation of Hue = sqrt (Variance of Hue, VOH) of the image. VOH can be used as a measure of masticatory efficiency. The greater the hue difference of each pixel in the mixed image, the more insufficient chewing leads to uneven color mixing, resulting in higher VOH, and vice versa, lower VOH is observed when chewing is sufficient. As shown in Fig. 2 . 2.3 Outcome Measures In the images of participants chewing gum, we exclusively considered movements along the longitudinal axis as they constituted the most significant motions during chewing repetition. A cycle was defined as the time period from the initiation of mandible descent to its return to the original position. The measurements included: Total masticatory time, Chewing sequence duration, Mandibular motion amplitude, Maximum speed, Average speed. (Measurement points, Fig. 3 ). 2.4 Statistical Analysis IBM SPSS 22.0 software was used to analyze the data. The measurements data were presented as frequencies or mean (standard deviations). Age and BMI were tested by t test, χ 2 tests were used to compare gender. In the analysis of kinematic data, independent sample t-tests were conducted on Total masticatory time and Chewing sequence duration, non-parametric analyses by Wilcoxon Signed Ranks test were performed to examine Maximum speed, Average speed, and Mandibular motion amplitude. Logistic regression analysis was performed to identify sensitive parameters that could effectively distinguish patients with early-stage NPC using kinematic parameters exhibited significant differences between the two groups as explanatory variables. The significance level was set at p < 0.05. Receiver operating characteristic (ROC) curves were employed to calculate the area under the curve (AUC) and assess test accuracy. Additionally, simple linear regression analysis was performed to examine the relationship between kinematic parameters with significant differences and masticatory efficiency. 3. Results 3.1. Characteristics of the Participants In this study, a total of 200 participants were recruited from the rehabilitation outpatient department, out of which 100 participants met the inclusion criteria. Twenty-two participants were solely assessed and excluded due to a lack of recorded video footage. Additionally, seven individuals could not fully capture their facial chewing movements due to significant body shaking during recording, while three individuals spoke during the chewing process. Participants characteristics are shown in Table 2 . Table 2 Characteristics of study participants. Healthy Control Group (n = 35) NPC Group (n = 33) P Value Age (years) 51.80 (6.84) 54.18 (9.70) 0.244 Sex:male/female (n) 13/22 20/13 0.053 BMI (kg/m 2 ) 20.69 (19.23,23.88) 19.88 (17.30,21.58) 0.035 Radiotherapy sessions (n) — 38 (33,40) — Years from irradition (years) — 10.91 ± 6.26 — 3.2 Kinematic Analysis of mandibular movement The values obtained from analyzing mastication movement were compared between the two groups, it was found that the NPC group had significantly longer masticatory time (Total Masticatory Time & Chewing Sequence Duration (Table 3 )) than those of the healthy control group (P < 0.000). Furthermore, both Mandibular Motion Amplitude (Fig. 4 A) and speed of mandibular motion (Maximum Speed (Fig. 4 B) & Average Speed (Fig. 4 C)) were found to be significantly lower in the NPC group compared to those in the healthy control group (P < 0.000). It is worth mentioning that the Mandibular Motion Amplitude in individual NPC paitents is larger than that of normal individuals. Table 3 Comparison of kinematic analysis results. Mastication Time Healthy Control Group (n = 35) NPC Group (n = 33) P Value Total Masticatory Time 12.349 ± 2.428 12.349 ± 2.428 < 0.000 Chewing Sequence Duration 543.646 ± 65.9388 636.573 ± 85.432 < 0.000 Presented as the mean (standard deviation). 3.3 Masticatory Efficiency Compared to the healthy control group, the NPC group exhibited a significant increase in VOH [SDHue] (P < 0.000), as depicted in Fig. 4 D, indicating a pronounced decrease in masticatory efficiency. 3.4 Logistic Regression Analysis and Linear Regression Analysis Based on these findings, a logistic regression analysis was conducted using the aforementioned variables that exhibited significant disparities as explanatory factors. The study found significant variations in both the Mandibular Motion Amplitude, the average chewing speed and mastication time (Total Masticatory Time & Chewing Sequence Duration). The odds ratios for these variables were determined to be 4.483、 0.363、0.976、and 3.629 respectively, as depicted in Fig. 5 A. Among them, the average chewing speed exhibited the highest area under the ROC curve, the cutoff value was 14.28, with a sensitivity of 90.91%, a specificity of 80%, and an area under the curve of 0.9255 (Fig. 5 B). Linear regression analysis showed that average chewing speed negatively affects masticatory efficiency (Fig. 5 C). 4. Discussion In this study, we developed a straightforward and non-invasive video-based method to investigate the relevant kinematic characteristics of mastication in patients with NPC and explore the relationship between mastication-related kinematic parameters and masticatory efficiency. 4.1 The Kinematic differences in mastication movement This study revealed that individuals with NPC exhibited a prolonged total masticatory time and chewing sequence duration. Additionally, a significant decrease was observed in speed of mandibular motion (Maximum speed & Average speed), Mandibular Motion Amplitude, and masticatory efficiency. These kinematic data are considered characteristic features of masticatory movements in the analysis of masticatory disorders. Nasopharyngeal tumors mainly originate from the cervical fascia and then spread laterally to invade the medial/lateral pterygoid muscles and/or other masticatory muscles [ 13 , 14 ] . After undergoing radiation therapy, patients may develop fibrosis in the masticatory muscles, which can result in reduced muscle elasticity and strength, this affects the masticatory movement, leading to decreased chewing endurance and potential muscle damage or fatigue. Consequently, this can lead to a decrease in chewing speed and require an extended chewing time to compensate for completing the same task. Another study demonstrated a significant association between masticatory muscle activity and both chewing power and occlusal force, with the former showing a positive correlation with masticatory efficiency. When the motor function of chewing is well-preserved, it enables the accomplishment of rapid and forceful chewing, thereby enhancing masticatory efficiency [ 15 ] . After undergoing radiation treatment, the mastication-related muscles strength significantly reduced, resulting in insufficient force generation for food chewing. This can affect the fluency and coordination of the chewing movement. Therefore, it might require a longer duration and slower speed to compensate for the adaptation of chewing movement to changes in muscle function, ensuring optimal food mastication [ 16 ] . Other studies have also demonstrated a strong positive correlation between stable masticatory movement patterns and masticatory efficiency. In other words, unnecessary and irregular mandibular movements may diminish overall mastication efficiency [ 15 ] . Furthermore, saliva performs the crucial function of lubricating and moistening food during chewing. Patients diagnosed with NPC often encounter xerostomia and reduced salivary secretion [ 17 ] . Consequently, the decrease in saliva production can also render the act of chewing challenging. Patients with NPC may have impaired oral mucosa and restricted tongue mobility, further affecting their ability to chew normally. However, we occasionally observed instances of greater mandibular motion during chewing in NPC patients even than that in healthy participants. This might be a compensatory strategy for NPC patients who had obvious tongue atrophy. During chewing, tongue movement aids in thoroughly mixing food and saliva. Patients with NPC after radiotherapy may lose tongue flexibility to some extent. They were prone to adjust a greater range of jaw movement for mixing. 4.2 Temporspacial data and mastication efficacy Furthermore, both multivariate analysis and AUC results demonstrated that mastication time (Total Masticatory Time & Chewing Sequence Duration), mandibular motion amplitude, and average chewing speed could serve as reliable indicators for identifying patients with masticatory dysfunction. The exceptional predictive performance of average chewing speed is particularly noteworthy, which emerged as the most sensitive parameter for evaluating masticatory efficiency. And the results of multivariate analysis and the area under the ROC curve indicate a strong association between average chewing speed and masticatory efficiency. Studies have reported that an increase in the average chewing speed can enhance food refinement and promote uniform mixing [ 18 , 19 ] , thereby improving mastication efficiency. The increase in chewing speed decreases the dwell time of food in the oral cavity, leading to a more rapid and uninterrupted chewing motion. This results in more comprehensive exposure of the food to saliva, enhancing the blending of enzymes in the saliva with the food. Maintaining a consistent chewing speed also enhances the activation of the masticatory muscles, improves chewing force, and facilitates better food processing and fragmentation. Therefore, the average chewing speed of NPC patients could be an indicator of their overall chewing ability. 4.3 Evaluation methods of masticatory movement and masticatory efficiency This study is based on facial recognition and tracking the movement of the target points to obtain accurate and detailed information about jaw movement displacement, speed, and time during chewing [ 20 ] . The application of this technique has been instrumental in assessing the temporal characteristics of jaw movement and detecting impairments in mandibular control in neurodegenerative diseases [ 9 , 21 , 22 ] . Studies have observed a decrease in jaw movement speed preceding changes in speech rate and speech articulation among ALS patients [ 23 , 24 ] . The jaw movement was evaluated through the motion analysis of mandibular landmarks. It is worth to note that, the unmarked facial recognition and tracking system software used in this study is superior to previous research methods. Firstly, as it does not require placing markers on the face that interfere with lip movement. Secondly, using headgear to track the marker makes it difficult to chew normally. Furthermore, motion capture enables the detection of small, subtle movements that are typically not easily discerned, which is more sensitive to alterations compared to observation-based assessments. Through our results, the recorded chewing data were stable and discernible. Masticatory efficiency was used as a metric to objectively assess the participants' ability to chew and quantify the actual chewing function [ 25 ] . The two-color chewing gum, which had been utilized in previous studies [ 25 ] , was employed for evaluation to compare the degree of color mixing in chewing products. This measure is widely utilized as a simple yet effective indicator of masticatory efficiency when screening patients with masticatory disorders [ 26 ] . Compared to traditional chewing, chewing gum is more widely accepted by people and may lead to increased unconscious chewing behavior [ 27 ] . Additionally, chewing gum is less likely to be accidentally swallowed, preventing the risk of choking and aspiration. Previous studies used rice crackers as the testing material; however, this can present challenges in gathering crushed samples post-chewing, especially when dealing with tiny particles and less mobile or sensitive oral structures. The advantage of this measure is that it allows for checking whether the bolus has been sufficiently formed. Limitations This study presents some limitations. Firstly, the recruited patients showed variable chewing function, and suffered different method of radiotharapy. Secondly, the video collected in this study was shot in a controlled and standardized environment; however, we did not assess the predictive performance under different environmental conditions or lighting sources. Thus, potential measurement biases might compromise the integrity of our findings and limit their generalizability. Third, the current study confined its analysis to a single food item, and it remains inconclusive whether other foods might exhibit similar outcomes. Additionally, the experiment was only conducted once, resulting in limited verification. Further validation is required for the these findings due to the excessively cautious nature of this approach. 5. Conclusions The quantitative information on mandibular movement in NPC presented in this study may contribute to the identification and measurement of masticatory disorders. NPC patients were compared with healthy participants to elucidate the lower speed and longer duration of mandibular movement. Furthermore, the average chewing speed could serve as an indicator for early mastication deterioration. Abbreviations NPC nasopharyngeal carcinoma VFSS Videofluoroscopic Swallowing Study FOIS Functional Oral Intake Scale AUC Area under the curve ROC Receiver operating characteristic Declarations Acknowledgements The authors would like to thank the medical staff of the Rehabilitation Department of the Third Affiliated Hospital of Sun Yat-sen University for their support and assistance to this research. Author contributions All authors contributed to the study conception and design. Conceptualization: [WXM], [XCQ]. Methodology: [WXM], [YC], [WZH]. Software design: [ZYSY], [WLF]. Assessment: [XCQ], [ZF]. Data acquisition and analysis: [YC], [ZF]. Writing-original draft preparation: [YC], [WZH]. Writing-review and editing: [YC], [WZH], [WZH]. Funding acquisition: [WXM]. Supervision: [WXM]. Funding This study was funded by Youth Fund of the National Natural Science Foundation of China (Grant No: 81802236). Ethics approval and consent to participate The study was approved by the Third Affiliated Hospital of Sun Yat-sen University (2021-02-321-01) and was conducted according to the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants. Subjects image use declaration All subjects and/or their legal guardian(s) have given informed consent for their identifying information/images to be published in online open-access publications. Availability of Data and Materials The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. References Wang YH, Cheng HZ, Liu K, Cai BL, Luo Y, Kan D, et al. Clinical therapeutic effects of acupuncture in treating patients with dysphagia after radiotherapy in nasopharyngeal carcinoma: A protocol for systematic review and meta-analysis. 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Impact of rehabilitation with removable complete or partial dentures on masticatory efficiency and quality of life: A cross-sectional mapping study. J Prosthet Dent. 2022;128(6):1295–302. Schimmel M, Leemann B, Herrmann FR, Kiliaridis S, Schnider A, Müller F. Masticatory Function and Bite Force in Stroke Patients. J Dent Res. 2010;90(2):230–4. Schimmel M, Christou P, Miyazaki H, Halazonetis D, Herrmann FR, Muller F. A novel colourimetric technique to assess chewing function using two-coloured specimens: Validation and application. J Dent. 2015;43(8):955–64. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3894122","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":269799203,"identity":"c7517ee6-81d1-4158-b8fa-b13fa8424238","order_by":0,"name":"Chen Yang","email":"","orcid":"","institution":"The Third Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Yang","suffix":""},{"id":269799204,"identity":"2ed39b6d-279b-4733-9b9d-f9a9f82e120a","order_by":1,"name":"Zhenhai Wei","email":"","orcid":"","institution":"The Third Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Zhenhai","middleName":"","lastName":"Wei","suffix":""},{"id":269799205,"identity":"ce5cd7d9-7197-438d-87a1-e296ae36f4e2","order_by":2,"name":"Fei Zhao","email":"","orcid":"","institution":"The Third Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"Zhao","suffix":""},{"id":269799206,"identity":"43cab7ce-2b45-4e42-b85d-c19141bce404","order_by":3,"name":"Yangshiyu Zhou","email":"","orcid":"","institution":"Wuhan Estrip Tech Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Yangshiyu","middleName":"","lastName":"Zhou","suffix":""},{"id":269799207,"identity":"f02c3c9b-176e-4bb7-bced-efae944c6fa2","order_by":4,"name":"Linfei Wu","email":"","orcid":"","institution":"Wuhan Estrip Tech Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Linfei","middleName":"","lastName":"Wu","suffix":""},{"id":269799208,"identity":"738bb218-cd3b-4c4c-8431-0e0907378e66","order_by":5,"name":"Xiaomei Wei","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYFACxgYgISEHZDQegIlJEKPFGMQgVgsEJII0EqfF4Hhzm9SNCov0te2Hgbb8OWxvcID54G0eBrs8nFrOHGw2zjkjkbvtTGLDAca2w4kbDrAlW/MwJBfj0mJ2I7HxcW4bUMsBkJaGwwkGB3jMpHkYDoCdilXL/YcNh3P/SaSbnX8Icxj/N/xabjACbWmQSABaB9TCdphxwwEeNrxa7M8kAv1yTMJw2w2gLYlt6YkzD7MZW84xSMapRbL9+DPpnJo6ebPz6Q8ffPhjbc93vPnhjTcVdji1oIIEhmYGBmYQy4Ao9WBQR7zSUTAKRsEoGDEAAOS3YIlMrRRXAAAAAElFTkSuQmCC","orcid":"","institution":"The Third Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":true,"prefix":"","firstName":"Xiaomei","middleName":"","lastName":"Wei","suffix":""},{"id":269799209,"identity":"33dc6763-c6fc-4ff4-8686-942002acb965","order_by":6,"name":"Chunqing Xie","email":"","orcid":"","institution":"The Third Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Chunqing","middleName":"","lastName":"Xie","suffix":""}],"badges":[],"createdAt":"2024-01-24 13:03:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3894122/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3894122/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50383269,"identity":"086db1fc-05ff-42f6-8ddb-a4f3ed15fc08","added_by":"auto","created_at":"2024-01-30 17:25:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":549168,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA. Face model used in this work.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB. Environment used for recording the video.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3894122/v1/6c2e3a16a1333ba407c8ce98.png"},{"id":50383271,"identity":"87381914-e140-4f1d-a769-f8af6f2ec325","added_by":"auto","created_at":"2024-01-30 17:25:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":531506,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImage from masticatory efficiency analysis using software program (ViewGum).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3894122/v1/eadf8ab1ffebeb649e63e35e.png"},{"id":50383272,"identity":"975baa13-69fd-47b3-8661-9412c2665ddf","added_by":"auto","created_at":"2024-01-30 17:25:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":189790,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe software collects the target points datas in the test sequence and process.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3894122/v1/2c3b6c4f1d8ee88570418431.png"},{"id":50383270,"identity":"4b76a396-d8a9-4eb3-998f-d06c77785b0e","added_by":"auto","created_at":"2024-01-30 17:25:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":60071,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of s Kinematic Analysis and masticatory assessment.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNPC (nasopharyngeal carcinoma); Normol (Healthy Control Group).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3894122/v1/c2c18c8a6bc03b17131312b8.png"},{"id":50385360,"identity":"8fa83483-fdf4-470c-a47c-d432b58dd14f","added_by":"auto","created_at":"2024-01-30 17:33:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":79778,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA. Multivariate regression analysis results of forest plot. Forest plot uses the estimated effect size of 1 as the invalid line (horizontal scale is 1). Horizontal bars depicts the effect size of each variable and its 95% confdence interval (95% CI). The odds ratio (OR) depicts the effect size of the study factor. Logistic regression analysis revealed significant differences in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eMandibular Motion Amplitude\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e, \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eTotal Masticatory Time\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e, \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eChewing Sequence Duration\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e Average Speed\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e, with odds ratios of 0.005、0.009、0.007、0.008.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eB. Receiver operating characteristic curves (ROC) to assess Masticatory Efficiency by kinematic parameters.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC. Results of linear regression analysis of Average Chewing Speed-Mastication Efficiency (VOH [SDHue]).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3894122/v1/3131ea92e6419466bf079fb3.png"},{"id":53137593,"identity":"ea515a44-37fd-4894-8cac-ce56b2166e8e","added_by":"auto","created_at":"2024-03-21 05:09:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2019536,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3894122/v1/050ce93f-d9d6-4f9a-967b-5eb88074c5e1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Video tracking-based Mandibular Movement Kinematic Analysis in patients with nasopharyngeal carcinoma","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNasopharyngeal carcinoma (NPC) is a malignant tumor that occurs in the nasopharynx and nasopharyngeal epithelia\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Radiation therapy has been demonstrated to be effective\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. However, many complications might be associated with radiation therapy, including dysphagia and trismus\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e, as well as muscle fibrosis which impaired mastication capabilitie\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. These complications can potentially result in gradually worse of swallowing, speech production, chewing ability, and other orofacial motor functions. Early and accurate assessment of motor function impairment can facilitate the comprehension of patients' current functional status, enabling early intervention and enhancing the quality of life\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Oral movement assessments through clinical observation usually was the main sceening test, which may be easy overlook for patients with minor impairment during early stage. The face to face assesssment also could pose the risk of droplet transmission of respiratory infections.\u003c/p\u003e \u003cp\u003eComputer vision technology has the potential to fully or partially automate the clinical examination of oral and maxillofacial dysfunction, thus providing an accurate and objective assessment. Researchers have introduced various approaches for precisely measuring the kinematic characteristics of the tongue, jaw, and lips (such as position and speed during speech production)\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. These advancements facilitate effective monitoring in the early-stage of orofacial dyskinesia in patients\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA deep learning-based model combined with a 3D camera can accurately localize facial landmarks in videos of patients performing various speech tasks\u003csup\u003e[\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. However, the clinical applicability of these techniques is constrained due to their reliance on costly and user-unfriendly systems\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. The 2D Markerless Systems are a relatively convenient and cost-effective technique. Research has demonstrated that 2D features, extracted from color cameras only, are as informative as 3D features, extracted from color and depth cameras\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e, implying that 2D video analysis may serve as a superior evaluation method. Therefore, this study developed an accessible face tracking software system to assess orofacial motor function. The recorded videos of participants were obtained during chewing movement and facial markers was determined before collection through the software. The aim was to investigate the differences of mandibular kinematics data during chewing between NPC patients and healthy participants, and further to clarify the potential indicators for evaluating masticatory dysfunction that influence mastication efficiency.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Participants\u003c/h2\u003e\n \u003cp\u003eConsecutive patients admitted to a hospital underwent rehabilitation at a hospital outpatient clinic in Guangzhou, China, between February 2020 and November 2020, participated in this cross-sectional study. In this study, thirty-three patients with NPC after radiotherapy (20 males and 13 females, age 54.18\u0026thinsp;\u0026plusmn;\u0026thinsp;9.70). The duration of radiotherapy for NPC varied from 2 to 24 years, while the number of radiotherapy sessions ranged from 21 to 45.\u003c/p\u003e\n \u003cp\u003eAll participants included in the study met the following criteria: (1) diagnosed with NPC and treated with radiotherapy or chemoradiotherapy; complicated with dysphagia which was identified with videofluoroscopic swallowing study (VFSS); (2) FOIS (Functional Oral Intake Scale)\u0026thinsp;\u0026ge;\u0026thinsp;4; (3) has no history of orofacial trauma or surgery. Patients were excluded if they fulfilled the following criteria: (1) presence of tumor recurrence or metastasis; (2) presence of other neurological diseases affecting oral movements; (3) unstable vital signs; (4) no consent from patients or family members; and (5) a history of oral cancer, dental disorders causing painful chewing, or ill-fitting dentures.\u003c/p\u003e\n \u003cp\u003eMeanwhile, thirty-five age-matched healthy participants (13 males and 22 females, aged 51.80\u0026thinsp;\u0026plusmn;\u0026thinsp;6.84) were recruited for this study. The research protocol was approved by the Research Ethics Committee of the Third Affiliated Hospital of Sun Yat-sen University (2021-02-321-01).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Experimental Procedure\u003c/h2\u003e\n \u003cp\u003e\u003cstrong\u003eKinematics Using a 2-Dimensional Motion Capture System\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eDuring each session, movements of lips and jaw were recorded by the 2D motion capture system. The 2D motion capture system consisting of analytical software (Nswollow) and a camera (Exilim EX-F1, Casio, Tokyo, Japan, resolution 640\u0026times;480 pixels at 50 frames per second (fps)), which can automatically mark 67 facial sites for motion capture and quantitative analysis. which can automatically mark facial sites for motion capture and quantitative analysis.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eNswallow software was developed to achieve face tracking\u003c/strong\u003e: ① CMU model: In this study, a Nswallow software was developed that utilizes a CMU model incorporating a face detector to accurately locate and track facial feature points, achieving video-based jaw tracking. The software utilizes the data detected in the preceding frame as input for subsequent frames and performs re-detection only when there are no faces present in the previous frame. ② Extraction points: The recognition of keypoints in the Openpose framework primarily relies on regression algorithms. We utilized the facial marker points obtained from a previously validated deep learning-based facial alignment model. These markers are acquired from the model and are not distributed on the face\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. The distribution of these markers is as follows: 10 for eyebrows, 14 for eyes, 9 for noses, and 20 for lips (12 for external contours and 8 for internal contours), 17 for facial contour, as shown in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA. The markers were concealed during recording. The target site investigated in this study was referred to as site 8 and site 33. That is, the point position of jaw central (8th Marker points\u0026thinsp;=\u0026thinsp;JC) and nose tip (33rd Marker points\u0026thinsp;=\u0026thinsp;NT) is extracted as the key point detection. After collecting the subject\u0026apos;s chewing video, Openpose is utilized to identify and extract facial and jaw movements from each pre-processed frame. The extracted jaw movement features are then quantified using Opencv. ③ Filtering processing: The extracted point coordinates undergo Savitzky-Golay filtering for noise reduction pre-processing. The result is obtained by reading the json file of the target keypoints.\u003c/p\u003e\n \u003cp\u003eThe set of kinematic features extracted for each task is presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. All participants were filmed at a face-camera distance ranging from 30 to 50 cm and at a height close to that of the participant\u0026rsquo;s eyes\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e A continuous light source was positioned adjacent to the camera for providing consistent illumination (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB). Throughout the task, participants were required to maintain their gaze towards the camera and minimize excessive head movements. After obtaining preliminary data, researchers had to manually correct the videos in order to eliminate redundant actions. Finally, there were 68 videos included in the analysis: 35 recordings from healthy participants and 33 recordings from patients with NPC.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1. Description of the kinematic features extracted for each task.\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.511041009463723%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTask\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.01577287066246%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable (unit)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.473186119873816%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.511041009463723%\" rowspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003eChewing task\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.01577287066246%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMastication Time\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.473186119873816%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.95940959409594%\"\u003e\n \u003cp\u003eTotal Masticatory Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.04059040590406%\"\u003e\n \u003cp\u003eDuration of all chewing cycles\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.95940959409594%\"\u003e\n \u003cp\u003eChewing Sequence Duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.04059040590406%\"\u003e\n \u003cp\u003eAverage duration of a single chewing\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.95940959409594%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMandibular Motion Amplitude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.04059040590406%\"\u003e\n \u003cp\u003eAverage displacement of JC of a single chewing: module of the vector from JC to NT .\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.95940959409594%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpeed of Mandibular Motion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.04059040590406%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.95940959409594%\"\u003e\n \u003cp\u003eMaximum speed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.04059040590406%\"\u003e\n \u003cp\u003eMaximum velocity of JC during chewing cycles\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.95940959409594%\"\u003e\n \u003cp\u003eAverage speed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.04059040590406%\"\u003e\n \u003cp\u003eAverage velocity of JC during a single chewing.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cstrong\u003eRight Corner (RC), Left Corner (LC), Jaw Central (JC), and Nose Tip (NT).\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCalculate the physical data of the target point\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTwo of markers including jaw central (8th Marker points\u0026thinsp;=\u0026thinsp;JC), and nose tip (33rd Marker points\u0026thinsp;=\u0026thinsp;NT) were extracted for kinematic analysis. The key frames depicting the resting position of the jaw and its maximum displacement during the chewing sequence were identified. Subsequently, a demarcation line was established to define the duration period of chewing, followed by computation of relevant temporal parameters. The number of key frames can be obtained, and the duration of entire chewing cycle can be calculated based on the camera\u0026apos;s FPS. Spatial parameters for mandibular motion amplitude are computed using each two-dimensional pixel coordinate. By combining these, speed parameters as well as stability and rhythm characteristics of mastication can be calculated.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eProcedures for assessing masticatory efficiency\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eMasticatory efficiency was evaluated with a previously validated colour-mixing ability test. Specimens of 30 mm length were prepared from Wrigley\u0026apos;s Doublemint-F5\u0026reg; gums (Wrigley\u0026apos;s Doublemint-F5\u0026reg;; Azure and Pink; The Wrigley Company; Guangzhou, China) in the flavours \u0026lsquo;Sour Berry\u0026rsquo; (azure colour) and \u0026lsquo;Watermelon\u0026rsquo; (pink colour). We cut strips from both colors and manually stuck them together, resulting in a test strip that measures 30\u0026times;18\u0026times;3 mm. Prior to each chewing cycle, participants were instructed to thoroughly remove any food debris from their mouth and clean any soft dirt from the tooth surface. They were then asked to naturally chew two-coloured gums for a total of 20 cycles. The resulting bolus was then retrieved from the oral cavity, and flattened into a 1 mm thick wafer by pressing it with a custom-made polyvinyl chloride plate that had a milled depression of 1mm\u0026times;50mm\u0026times;50mm\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. The digitized images were arranged side by side to form a single 1000-pixel image for analysis of masticatory efficiency using specialized software program (ViewGum\u0026reg;; dHAL Software)\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. The software converts the compound image of both sides of the specimen into the HIS color space and calculates the standard deviation of Hue\u0026thinsp;=\u0026thinsp;sqrt (Variance of Hue, VOH) of the image. VOH can be used as a measure of masticatory efficiency. The greater the hue difference of each pixel in the mixed image, the more insufficient chewing leads to uneven color mixing, resulting in higher VOH, and vice versa, lower VOH is observed when chewing is sufficient. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Outcome Measures\u003c/h2\u003e\n \u003cp\u003eIn the images of participants chewing gum, we exclusively considered movements along the longitudinal axis as they constituted the most significant motions during chewing repetition. A cycle was defined as the time period from the initiation of mandible descent to its return to the original position. The measurements included: Total masticatory time, Chewing sequence duration, Mandibular motion amplitude, Maximum speed, Average speed. (Measurement points, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e\n \u003cp\u003eIBM SPSS 22.0 software was used to analyze the data. The measurements data were presented as frequencies or mean (standard deviations). Age and BMI were tested by t test, \u0026chi;\u003csup\u003e2\u003c/sup\u003e tests were used to compare gender. In the analysis of kinematic data, independent sample t-tests were conducted on Total masticatory time and Chewing sequence duration, non-parametric analyses by Wilcoxon Signed Ranks test were performed to examine Maximum speed, Average speed, and Mandibular motion amplitude. Logistic regression analysis was performed to identify sensitive parameters that could effectively distinguish patients with early-stage NPC using kinematic parameters exhibited significant differences between the two groups as explanatory variables. The significance level was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Receiver operating characteristic (ROC) curves were employed to calculate the area under the curve (AUC) and assess test accuracy. Additionally, simple linear regression analysis was performed to examine the relationship between kinematic parameters with significant differences and masticatory efficiency.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Characteristics of the Participants\u003c/h2\u003e \u003cp\u003eIn this study, a total of 200 participants were recruited from the rehabilitation outpatient department, out of which 100 participants met the inclusion criteria. Twenty-two participants were solely assessed and excluded due to a lack of recorded video footage. Additionally, seven individuals could not fully capture their facial chewing movements due to significant body shaking during recording, while three individuals spoke during the chewing process. Participants characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of study participants.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy Control Group (n\u0026thinsp;=\u0026thinsp;35)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNPC Group (n\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51.80 (6.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.18 (9.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.244\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex:male/female (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13/22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20/13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.69 (19.23,23.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.88 (17.30,21.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRadiotherapy sessions (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (33,40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears from irradition (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.91\u0026thinsp;\u0026plusmn;\u0026thinsp;6.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Kinematic Analysis of mandibular movement\u003c/h2\u003e \u003cp\u003eThe values obtained from analyzing mastication movement were compared between the two groups, it was found that the NPC group had significantly longer masticatory time (Total Masticatory Time \u0026amp; Chewing Sequence Duration (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)) than those of the healthy control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.000). Furthermore, both Mandibular Motion Amplitude (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eA) and speed of mandibular motion (Maximum Speed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eB) \u0026amp; Average Speed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eC)) were found to be significantly lower in the NPC group compared to those in the healthy control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.000). It is worth mentioning that the Mandibular Motion Amplitude in individual NPC paitents is larger than that of normal individuals.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of kinematic analysis results.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMastication Time\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy Control Group (n\u0026thinsp;=\u0026thinsp;35)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNPC Group (n\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Masticatory Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e12.349\u0026thinsp;\u0026plusmn;\u0026thinsp;2.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e12.349\u0026thinsp;\u0026plusmn;\u0026thinsp;2.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChewing Sequence Duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e543.646\u0026thinsp;\u0026plusmn;\u0026thinsp;65.9388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e636.573\u0026thinsp;\u0026plusmn;\u0026thinsp;85.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003ePresented as the mean (standard deviation).\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Masticatory Efficiency\u003c/h2\u003e \u003cp\u003eCompared to the healthy control group, the NPC group exhibited a significant increase in VOH [SDHue] (P\u0026thinsp;\u0026lt;\u0026thinsp;0.000), as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eD, indicating a pronounced decrease in masticatory efficiency.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Logistic Regression Analysis and Linear Regression Analysis\u003c/h2\u003e \u003cp\u003eBased on these findings, a logistic regression analysis was conducted using the aforementioned variables that exhibited significant disparities as explanatory factors. The study found significant variations in both the Mandibular Motion Amplitude, the average chewing speed and mastication time (Total Masticatory Time \u0026amp; Chewing Sequence Duration). The odds ratios for these variables were determined to be 4.483、 0.363、0.976、and 3.629 respectively, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eA. Among them, the average chewing speed exhibited the highest area under the ROC curve, the cutoff value was 14.28, with a sensitivity of 90.91%, a specificity of 80%, and an area under the curve of 0.9255 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Linear regression analysis showed that average chewing speed negatively affects masticatory efficiency (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this study, we developed a straightforward and non-invasive video-based method to investigate the relevant kinematic characteristics of mastication in patients with NPC and explore the relationship between mastication-related kinematic parameters and masticatory efficiency.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.1 The Kinematic differences in mastication movement\u003c/h2\u003e \u003cp\u003eThis study revealed that individuals with NPC exhibited a prolonged total masticatory time and chewing sequence duration. Additionally, a significant decrease was observed in speed of mandibular motion (Maximum speed \u0026amp; Average speed), Mandibular Motion Amplitude, and masticatory efficiency. These kinematic data are considered characteristic features of masticatory movements in the analysis of masticatory disorders.\u003c/p\u003e \u003cp\u003eNasopharyngeal tumors mainly originate from the cervical fascia and then spread laterally to invade the medial/lateral pterygoid muscles and/or other masticatory muscles\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. After undergoing radiation therapy, patients may develop fibrosis in the masticatory muscles, which can result in reduced muscle elasticity and strength, this affects the masticatory movement, leading to decreased chewing endurance and potential muscle damage or fatigue. Consequently, this can lead to a decrease in chewing speed and require an extended chewing time to compensate for completing the same task. Another study demonstrated a significant association between masticatory muscle activity and both chewing power and occlusal force, with the former showing a positive correlation with masticatory efficiency. When the motor function of chewing is well-preserved, it enables the accomplishment of rapid and forceful chewing, thereby enhancing masticatory efficiency\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. After undergoing radiation treatment, the mastication-related muscles strength significantly reduced, resulting in insufficient force generation for food chewing. This can affect the fluency and coordination of the chewing movement. Therefore, it might require a longer duration and slower speed to compensate for the adaptation of chewing movement to changes in muscle function, ensuring optimal food mastication\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Other studies have also demonstrated a strong positive correlation between stable masticatory movement patterns and masticatory efficiency. In other words, unnecessary and irregular mandibular movements may diminish overall mastication efficiency\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Furthermore, saliva performs the crucial function of lubricating and moistening food during chewing. Patients diagnosed with NPC often encounter xerostomia and reduced salivary secretion\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Consequently, the decrease in saliva production can also render the act of chewing challenging. Patients with NPC may have impaired oral mucosa and restricted tongue mobility, further affecting their ability to chew normally.\u003c/p\u003e \u003cp\u003e However, we occasionally observed instances of greater mandibular motion during chewing in NPC patients even than that in healthy participants. This might be a compensatory strategy for NPC patients who had obvious tongue atrophy. During chewing, tongue movement aids in thoroughly mixing food and saliva. Patients with NPC after radiotherapy may lose tongue flexibility to some extent. They were prone to adjust a greater range of jaw movement for mixing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Temporspacial data and mastication efficacy\u003c/h2\u003e \u003cp\u003eFurthermore, both multivariate analysis and AUC results demonstrated that mastication time (Total Masticatory Time \u0026amp; Chewing Sequence Duration), mandibular motion amplitude, and average chewing speed could serve as reliable indicators for identifying patients with masticatory dysfunction. The exceptional predictive performance of average chewing speed is particularly noteworthy, which emerged as the most sensitive parameter for evaluating masticatory efficiency. And the results of multivariate analysis and the area under the ROC curve indicate a strong association between average chewing speed and masticatory efficiency.\u003c/p\u003e \u003cp\u003eStudies have reported that an increase in the average chewing speed can enhance food refinement and promote uniform mixing\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e, thereby improving mastication efficiency. The increase in chewing speed decreases the dwell time of food in the oral cavity, leading to a more rapid and uninterrupted chewing motion. This results in more comprehensive exposure of the food to saliva, enhancing the blending of enzymes in the saliva with the food. Maintaining a consistent chewing speed also enhances the activation of the masticatory muscles, improves chewing force, and facilitates better food processing and fragmentation. Therefore, the average chewing speed of NPC patients could be an indicator of their overall chewing ability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Evaluation methods of masticatory movement and masticatory efficiency\u003c/h2\u003e \u003cp\u003eThis study is based on facial recognition and tracking the movement of the target points to obtain accurate and detailed information about jaw movement displacement, speed, and time during chewing\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. The application of this technique has been instrumental in assessing the temporal characteristics of jaw movement and detecting impairments in mandibular control in neurodegenerative diseases\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Studies have observed a decrease in jaw movement speed preceding changes in speech rate and speech articulation among ALS patients\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. The jaw movement was evaluated through the motion analysis of mandibular landmarks. It is worth to note that, the unmarked facial recognition and tracking system software used in this study is superior to previous research methods. Firstly, as it does not require placing markers on the face that interfere with lip movement. Secondly, using headgear to track the marker makes it difficult to chew normally. Furthermore, motion capture enables the detection of small, subtle movements that are typically not easily discerned, which is more sensitive to alterations compared to observation-based assessments. Through our results, the recorded chewing data were stable and discernible.\u003c/p\u003e \u003cp\u003eMasticatory efficiency was used as a metric to objectively assess the participants' ability to chew and quantify the actual chewing function\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. The two-color chewing gum, which had been utilized in previous studies\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e, was employed for evaluation to compare the degree of color mixing in chewing products. This measure is widely utilized as a simple yet effective indicator of masticatory efficiency when screening patients with masticatory disorders\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Compared to traditional chewing, chewing gum is more widely accepted by people and may lead to increased unconscious chewing behavior\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Additionally, chewing gum is less likely to be accidentally swallowed, preventing the risk of choking and aspiration. Previous studies used rice crackers as the testing material; however, this can present challenges in gathering crushed samples post-chewing, especially when dealing with tiny particles and less mobile or sensitive oral structures. The advantage of this measure is that it allows for checking whether the bolus has been sufficiently formed.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study presents some limitations. Firstly, the recruited patients showed variable chewing function, and suffered different method of radiotharapy. Secondly, the video collected in this study was shot in a controlled and standardized environment; however, we did not assess the predictive performance under different environmental conditions or lighting sources. Thus, potential measurement biases might compromise the integrity of our findings and limit their generalizability. Third, the current study confined its analysis to a single food item, and it remains inconclusive whether other foods might exhibit similar outcomes. Additionally, the experiment was only conducted once, resulting in limited verification. Further validation is required for the these findings due to the excessively cautious nature of this approach.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe quantitative information on mandibular movement in NPC presented in this study may contribute to the identification and measurement of masticatory disorders. NPC patients were compared with healthy participants to elucidate the lower speed and longer duration of mandibular movement. Furthermore, the average chewing speed could serve as an indicator for early mastication deterioration.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNPC nasopharyngeal carcinoma\u003c/p\u003e \u003cp\u003eVFSS Videofluoroscopic Swallowing Study\u003c/p\u003e \u003cp\u003eFOIS Functional Oral Intake Scale\u003c/p\u003e \u003cp\u003eAUC Area under the curve\u003c/p\u003e \u003cp\u003eROC Receiver operating characteristic\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the medical staff of the Rehabilitation Department of the Third Affiliated Hospital of Sun Yat-sen University for their support and assistance to this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Conceptualization: [WXM], [XCQ]. Methodology: [WXM], [YC], [WZH]. Software design: [ZYSY], [WLF]. Assessment: [XCQ], [ZF]. Data acquisition and analysis: [YC], [ZF]. Writing-original draft preparation: [YC], [WZH]. Writing-review and editing: [YC], [WZH], [WZH]. Funding acquisition: [WXM]. Supervision: [WXM].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Youth Fund of the National Natural Science Foundation of China (Grant No: 81802236).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Third Affiliated Hospital of Sun Yat-sen University (2021-02-321-01) and was conducted according to the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSubjects image use declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll subjects and/or their legal guardian(s) have given informed consent for their identifying information/images to be published in online open-access publications.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWang YH, Cheng HZ, Liu K, Cai BL, Luo Y, Kan D, et al. 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Video-Based Tracking of Jaw Movements During Speech: Preliminary Results and Future Directions. Interspeech 20172017. p. 689\u0026thinsp;\u0026ndash;\u0026thinsp;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuarin DL, Dempster A, Bandini A, Yunusova Y, Taati B. Estimation of Orofacial Kinematics in Parkinson\u0026rsquo;s Disease: Comparison of 2D and 3D Markerless Systems for Motion Tracking. 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020)2020. p. 540-3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBandini A, Orlandi S, Giovannelli F, Felici A, Cincotta M, Clemente D, et al. Markerless Analysis of Articulatory Movements in Patients With Parkinson's Disease. J Voice. 2016;30(6):766. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e.e1-.e11\u003c/span\u003e\u003cspan address=\"http://.e1-.e11\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHalazonetis DJ, Schimmel M, Antonarakis GS, Christou P. Novel software for quantitative evaluation and graphical representation of masticatory efficiency. J Oral Rehabil. 2013;40(5):329\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampos Sugio CY, Mosquim V, Jacomine JC, Zabeu GS, de Esp\u0026iacute;ndola GG, Bonjardim LR, et al. Impact of rehabilitation with removable complete or partial dentures on masticatory efficiency and quality of life: A cross-sectional mapping study. J Prosthet Dent. 2022;128(6):1295\u0026ndash;302.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiao Y, Pan J, Chen Y, Lin S, Zong J, Chen Y, et al. 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JDR Clin Trans Res. 2018;3(4):405\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKam MK, Leung SF, Zee B, Chau RM, Suen JJ, Mo F, et al. Prospective randomized study of intensity-modulated radiotherapy on salivary gland function in early-stage nasopharyngeal carcinoma patients. J Clin Oncol. 2007;25(31):4873\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWoda A, Foster K, Mishellany A, Peyron MA. Adaptation of healthy mastication to factors pertaining to the individual or to the food. Physiol Behav. 2006;89(1):28\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiquel-Kergoat S, Azais-Braesco V, Burton-Freeman B, Hetherington MM. Effects of chewing on appetite, food intake and gut hormones: A systematic review and meta-analysis. Physiol Behav. 2015;151:88\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreen JR, Wilson EM, Wang YT, Moore CA. 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J Dent Res. 2010;90(2):230\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchimmel M, Christou P, Miyazaki H, Halazonetis D, Herrmann FR, Muller F. A novel colourimetric technique to assess chewing function using two-coloured specimens: Validation and application. J Dent. 2015;43(8):955\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"nasopharyngeal carcinoma, dysphagia, mastication, kinematics, mastication efficiency","lastPublishedDoi":"10.21203/rs.3.rs-3894122/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3894122/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003ePatients with dysphagia due to nasopharyngeal carcinoma (NPC) after radiotherapy often have chewing difficulty. Kinematic analysis of mandibular movements may provide clinically useful information for the chewing function. However, current kinematic device costs limited clinical application, and specialized software is required for control and data processing. This study aimed to mandibular kinematics parameter recognition using a self-developed Nswallow 2D motion capture software. To investigate whether differences in kinematic data of mandibular movements during mastication can be used as an indicator of masticatory dysfunction in NPC patients, and the relationship with mastication efficiency.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eThirty-three patients with early-stage NPC after radiotherapy and thirty-five healthy controls were recruited. The self-developed Nswallow 2D motion capture software was used to automatically mark and capture the facial parts of the participants. We tracked jaw kinematic during chewing, and analyzed the characteristics of kinematic data of mandibular movements during chewing tasks. Meanwhile, the masticatory efficiency using two-color chewing gum was analyzed by the Viewgum software.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eSignificant differences were observed in the mastication time (Total Masticatory Time (NPC:12.349\u0026thinsp;\u0026plusmn;\u0026thinsp;2.428; HC:8.742\u0026thinsp;\u0026plusmn;\u0026thinsp;1.349) \u0026amp; Chewing Sequence Duration (NPC:636.573\u0026thinsp;\u0026plusmn;\u0026thinsp;85.432; HC:543.646\u0026thinsp;\u0026plusmn;\u0026thinsp;65.9388)), speed of mandibular motion (Maximum Speed (NPC:23.740(17.775,25.906); HC:28.800(24.643,38.800) \u0026amp; Average Speed (NPC:11.844(10.395,13.285); HC:18.169(15.790,21.435)), and Mandibular Motion Amplitude (NPC:7.159(5.887,7.869); HC:8.478(7.291;11.020)) between two groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.000). Logistic regression analysis and receiver operating characteristic curve analyses were performed based on the above data as explanatory variables. Among them, the average chewing speed exhibited the highest area under the ROC curve, the odds ratio was 3.629, the cutoff value was 14.28, with a sensitivity of 90.91%, a specificity of 80.00%, and an area under the curve of 0.9255. The masticatory efficiency in the NPC group significantly decreased compared to the healthy control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.000). Linear regression analysis showed that average chewing speed negatively affects masticatory efficiency.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe Nswallow 2D motion capture software represents an easy-to-use and affordable system that can be utilized to assess masticatory function in patients with NPC. In addition, the average speed of chewing is a highly sensitive kinematic indicator for evaluating mastication efficiency.\u003c/p\u003e","manuscriptTitle":"Video tracking-based Mandibular Movement Kinematic Analysis in patients with nasopharyngeal carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-30 17:25:07","doi":"10.21203/rs.3.rs-3894122/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ed1954e5-0055-43c6-8a15-98f432f8b552","owner":[],"postedDate":"January 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-21T05:01:28+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-30 17:25:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3894122","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3894122","identity":"rs-3894122","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}