This proposal describes a pathway to independence program for Emi Murano, M.D., Ph.D. The research component of the program is focused on the use of MRI and physiological modeling to help improve the management of glossectomy surgery for the treatment of oral tongue cancer. Oral cancers have the 7th highest incidence in the country;among them, oral tongue cancer has shown a recent 5 to 6-fold increase in incidence in younger adults ages 20 to 44 years and a twofold increase in older adults (Shiboski, 2005). Although the mortality rate of oral tongue cancer is not considered high, its morbidity is significant - causing speech, mastication and swallowing problems, which affect quality of life.
The aims of this application are threefold.
The first aim i s to examine the effects of glossectomy surgery on tongue deformation strategies. These effects will be studied using a unique combination of detailed data on internal tongue deformation from tagged-cine-MRI and anatomy from high-resolution MRI and diffusion tensor imaging. The clinical goal of this work is to provide objective measurements of tongue function following surgical treatment.
The second aim i s to use the MRI data from glossectomy patients and normal controls to explore the occurrence of areas of internal rigidity and deformation in the tongue and how they interact with speech motor control. This investigation will be guided by a view of the tongue as a muscular hydrostat and hypotheses about the use of rigidities as a novel way of reducing the complexity of control strategies.
The third aim i s to simulate glossectomy tongue motion using a physiological/biomechanical model. These simulations, with subject-specific versions of the model, will be used to test our hypotheses, with the ultimate goal of providing a tool for exploring options for surgical management by surgeons, therapists and patients. This work will provide the following new knowledge: (1) Relations between surgical variables and outcomes such as tongue motion and speech quality, (2) Information about patterns of tongue rigidity and how they may constitute a mechanism for reducing the complexity of the motor control, (3) Model-based predictions of the effects of muscle resection and tongue motion during speech post-surgery.

Public Health Relevance

This project will lead to increased understanding of the causes of deficits in speech, mastication and swallowing in glossectomy patients. It will also produce unique new data about glossectomy tongue motion as well as insight into normal and compensatory speech motor control. The model will enable surgeons to explore the effects of alternative of surgical strategies optimizing functional outcomes and rehabilitation.

Agency
National Institute of Health (NIH)
Institute
National Institute on Deafness and Other Communication Disorders (NIDCD)
Type
Research Transition Award (R00)
Project #
5R00DC009279-05
Application #
8129467
Study Section
Special Emphasis Panel (NSS)
Project Start
2009-09-21
Project End
2013-08-31
Budget Start
2011-09-01
Budget End
2013-08-31
Support Year
5
Fiscal Year
2011
Total Cost
$234,166
Indirect Cost
Name
Johns Hopkins University
Department
Otolaryngology
Type
Schools of Medicine
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218
Xing, Fangxu; Woo, Jonghye; Lee, Junghoon et al. (2016) Analysis of 3-D Tongue Motion From Tagged and Cine Magnetic Resonance Images. J Speech Lang Hear Res 59:468-79
Woo, Jonghye; Lee, Junghoon; Murano, Emi Z et al. (2015) A High-resolution Atlas and Statistical Model of the Vocal Tract from Structural MRI. Comput Methods Biomech Biomed Eng Imaging Vis 3:47-60
Lee, Junghoon; Woo, Jonghye; Xing, Fangxu et al. (2014) Semi-automatic segmentation for 3D motion analysis of the tongue with dynamic MRI. Comput Med Imaging Graph 38:714-24
Xing, Fangxu; Woo, Jonghye; Murano, Emi Z et al. (2013) 3D tongue motion from tagged and cine MR images. Med Image Comput Comput Assist Interv 16:41-8
Woo, Jonghye; Murano, Emi Z; Stone, Maureen et al. (2012) Reconstruction of high-resolution tongue volumes from MRI. IEEE Trans Biomed Eng 59:3511-24
Liu, Xiaofeng; Abd-Elmoniem, Khaled Z; Stone, Maureen et al. (2012) Incompressible deformation estimation algorithm (IDEA) from tagged MR images. IEEE Trans Med Imaging 31:326-40
Murano, Emi Z; Shinagawa, Hideo; Zhuo, Jiachen et al. (2010) Application of diffusion tensor imaging after glossectomy. Otolaryngol Head Neck Surg 143:304-6