Open Access4D Dynamic‐MRI as Glossectomy Speech Assessment Tool
Author(s) -
Murano Emi Z.,
Xing Fangxu,
Zhuo Jiachen,
Woo Jonghye,
Gullapalli Rao,
Stone Maureen,
Prince Jerry L.
Publication year - 2012
Publication title -
otolaryngology–head and neck surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.232
H-Index - 121
eISSN - 1097-6817
pISSN - 0194-5998
DOI - 10.1177/0194599812451426a60
Subject(s) - tongue , glossectomy , medicine , speech production , macroglossia , computer science , radiology , speech recognition , pathology
Objective Quantitative tools assessing functional outcomes after tongue cancer treatment are crucial for evaluation and comparison of surgical reconstruction techniques or chemoradiation protocols. Furthermore, tools measuring physiologic outcomes directly and specifically may lead to a better understanding of tongue adaptation control. We developed a 4D dynamic MRI to address these issues. Method This MRI tool included 2 components: 1) A static 3D high‐resolution MRI to identify structures spared from the surgery. 2) Dynamic cine‐ and tagged‐MRI scans at 26 frames/second to determine the tongue surface and measure point displacement during speech. Data were collected from 3 patients and 3 controls. Results The 3D segmentation of the residual muscles were compared to the controls. Twenty‐six 3D tongue volumes with surface deformation during the utterance of the word /asouk/ showed that patients adapt their tongue shape for /S/. The medial grooving seen in controls is deviated to the surgical side and the lateral sides of the anterior tongue make palatal and dental contact in patients. The 3D tagged MRI in patients showed asymmetrical displacement in several distinct parts of the tongue not seen in controls. The local distinct pattern suggests local adaptation for utmost speech performance. All patients had above 98% intelligibility scores. Conclusion This is the first study of 4D‐MRI relating residual tongue anatomy to 3D surface and internal kinematics during speech. This technique may provide a future predictive model for treatment options.