The National Cancer Institute estimates that over 42,000 people will be diagnosed with oral cancer and over 8,000 will die from this disease in 2014. Although these rates are low in comparison to many other cancers, unlike most other cancers the incidence of oral cancers-especially the human papillomavirus (HPV)-positive cancers-has been increasing. By some estimates there is as much as a five-fold increase in oral cancers just over the past decade. In the case of tongue cancer treatment through glossectomy (the surgical removal of part of the tongue including the cancer), which we focus on here, there is often significant post-treatment morbidity including difficulties in speech and swallowing and sleep apnea. Research connecting the tumor size and type of glossectomy surgery with tongue movement in speech after surgery has been ongoing for a number of years. These studies, most of which involve acoustic and speech intelligibility outcome measures, are beginning to reveal principles that can inform clinicians in developing optimal treatments. But very little information has been available relating tongue motion itself as an outcome, and when this is reported it almost exclusively reports measures derived from measurement of motion of the tongue surface, not its internal muscles. With advancements in technology we now have the opportunity to study the detailed patterns of tongue muscle motions in both normal controls and patients. By simultaneously analyzing data from cine magnetic resonance images, tagged magnetic resonance images, and diffusion magnetic resonance images, we will be able to observe patterns of activation throughout the tongue-observing and measuring a new type of functional connectivity-in order to better understand how patients compensate for muscle loss due to glossectomy. Specifically, we will: 1) Optimize acquisition of diffusion MRI imaging of in vivo tongue muscles; 2) Establish strain measures in the line of action of tongue muscle fibers using in vivo tagged MRI and diffusion MRI; 3) Develop models of functional connectivity in the tongue during speech; and 4) Assess tongue strategies in post-glossectomy speech. The ability of muscle fibers to create strain is crucial in the function of any muscle, but it is has not been possible to study this relationship in vivo in the past due to imaging constraints. The present research will enable simultaneous in vivo analysis in the complex muscle geometry of the tongue, a muscular hydrostat, possible for the first time. Through optimization of existing methods-both imaging and image analysis-we will enable a novel capability for the assessment of surgical outcomes in tongue cancer surgery. The study to be carried out on a spectrum of tongue cancer survivors will provide key information about the impact of tongue cancer treatment on speech, in order that significant morbidity might be avoided by modifying surgical practice or by engaging in specific speech therapies after surgery.

Public Health Relevance

This project is concerned with tongue cancer and the impact on speech caused by glossectomy surgery, which is the surgical removal of tongue tumors. The research will use new imaging and image processing techniques to learn how glossectomy patients use their tongues differently than normal speakers. These results may help surgeons to plan glossectomy surgeries that will preserve speaking ability and thereby help to improve the quality of life of tongue cancer survivors.

Agency
National Institute of Health (NIH)
Institute
National Institute on Deafness and Other Communication Disorders (NIDCD)
Type
Research Project (R01)
Project #
1R01DC014717-01
Application #
8943325
Study Section
Motor Function, Speech and Rehabilitation Study Section (MFSR)
Program Officer
Shekim, Lana O
Project Start
2015-08-07
Project End
2020-07-31
Budget Start
2015-08-07
Budget End
2016-07-31
Support Year
1
Fiscal Year
2015
Total Cost
$347,257
Indirect Cost
$57,403
Name
Johns Hopkins University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21205
Woo, Jonghye; Xing, Fangxu; Lee, Junghoon et al. (2018) A Spatio-Temporal Atlas and Statistical Model of the Tongue During Speech from Cine-MRI. Comput Methods Biomech Biomed Eng Imaging Vis 6:520-531
Gomez, Arnold D; Elsaid, Nahla; Stone, Maureen L et al. (2018) Laplace-based modeling of fiber orientation in the tongue. Biomech Model Mechanobiol 17:1119-1130
Ye, Chuyang; Prince, Jerry L (2018) Dictionary-based fiber orientation estimation with improved spatial consistency. Med Image Anal 44:41-53
Woo, Jonghye; Prince, Jerry L; Stone, Maureen et al. (2018) A Sparse Non-negative Matrix Factorization Framework for Identifying Functional Units of Tongue Behavior from MRI. IEEE Trans Med Imaging :
Stone, Maureen; Woo, Jonghye; Lee, Junghoon et al. (2018) Structure and variability in human tongue muscle anatomy. Comput Methods Biomech Biomed Eng Imaging Vis 6:499-507
Xing, Fangxu; Prince, Jerry L; Stone, Maureen et al. (2018) Strain Map of the Tongue in Normal and ALS Speech Patterns from Tagged and Diffusion MRI. Proc SPIE Int Soc Opt Eng 10574:
Tolpadi, Aniket A; Stone, Maureen L; Carass, Aaron et al. (2018) Inverse Biomechanical Modeling of the Tongue via Machine Learning and Synthetic Training Data. Proc SPIE Int Soc Opt Eng 10576:
Wang, Xiaokai; Stone, Maureen L; Prince, Jerry L et al. (2018) A Novel Filtering Approach for 3D Harmonic Phase Analysis of Tagged MRI. Proc SPIE Int Soc Opt Eng 10574:
Ramsey, Jordan; Prince, Jerry L; Gomez, Arnold D (2017) Test Suite for Image-Based Motion Estimation of the Brain and Tongue. Proc SPIE Int Soc Opt Eng 10137:
Xing, Fangxu; Prince, Jerry L; Stone, Maureen et al. (2017) A Four-dimensional Motion Field Atlas of the Tongue from Tagged and Cine Magnetic Resonance Imaging. Proc SPIE Int Soc Opt Eng 10133:

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