Video tracking-based mandibular movement kinematic analysis in patients with nasopharyngeal carcinoma

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 to examine relationship with mastication efficiency.

Method: Thirty-three patients with early-stage NPC after radiotherapy and thirty-seven 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 13.500 (11.600, 16.400); HC 10.533 (9.716, 12.250) & Chewing Sequence Duration (NPC 0.614 (0.582, 0.701); HC 0.544 (0.480, 0.586)], speed of mandibular motion [Maximum Chewing Speed (NPC 23.740 (17.775, 25.906); HC 28.467 (24.009, 38.600) & Average Chewing Speed (NPC 11.844 (10.395,13.285); HC 18.169 (16.586, 19.632)], and Mandibular Motion Amplitude [NPC 7.159 (5.887, 7.869); HC 9.184 (7.541;11.141)] 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, and 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. The Average Chewing Speed of chewing is a highly sensitive kinematic indicator for evaluating mastication efficiency. Furthermore, the Average Chewing Speed could serve as a screening test for patients with mastication disorder of nasopharyngeal cancer and provide dietary guidance for such individuals.

Keywords: Dysphagia; Kinematics; Mastication; Mastication efficiency; Nasopharyngeal carcinoma.

Fig. 1

A Environment used for recording the video. B Face model used in this work

Fig. 2

Image from masticatory efficiency analysis using software program (ViewGum)

Fig. 3

A. 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 Mandibular Motion Amplitude, Total Masticatory Time, Chewing Sequence Duration and Average Chewing Speed, with odds ratios of 0.005, 0.009, 0.007, 0.008. B. Receiver operating characteristic curves (ROC) to assess Masticatory Efficiency by kinematic parameters. C. Results of linear regression analysis of Average Chewing Speed-Mastication Efficiency (VOH [SDHue])