Evaluation of Submandibular Infections using 3-Dimensional Reconstruction of Computed Tomography Images

Evaluation of Submandibular Infections using 3-Dimensional Reconstruction of Computed Tomography Images

Bibliographic Details
Main Author: Elmshiti, Hashim
Language:English
Published: The Ohio State University / OhioLINK 2016
Subjects:
Health Sciences
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=osu1452523769
id ndltd-OhioLink-oai-etd.ohiolink.edu-osu1452523769
record_format oai_dc
collection NDLTD
language English
sources NDLTD
topic Health Sciences
spellingShingle Health Sciences
Elmshiti, Hashim
Evaluation of Submandibular Infections using 3-Dimensional Reconstruction of Computed Tomography Images
author Elmshiti, Hashim
author_facet Elmshiti, Hashim
author_sort Elmshiti, Hashim
title Evaluation of Submandibular Infections using 3-Dimensional Reconstruction of Computed Tomography Images
title_short Evaluation of Submandibular Infections using 3-Dimensional Reconstruction of Computed Tomography Images
title_full Evaluation of Submandibular Infections using 3-Dimensional Reconstruction of Computed Tomography Images
title_fullStr Evaluation of Submandibular Infections using 3-Dimensional Reconstruction of Computed Tomography Images
title_full_unstemmed Evaluation of Submandibular Infections using 3-Dimensional Reconstruction of Computed Tomography Images
title_sort evaluation of submandibular infections using 3-dimensional reconstruction of computed tomography images
publisher The Ohio State University / OhioLINK
publishDate 2016
url http://rave.ohiolink.edu/etdc/view?acc_num=osu1452523769
work_keys_str_mv AT elmshitihashim evaluationofsubmandibularinfectionsusing3dimensionalreconstructionofcomputedtomographyimages
_version_ 1719439644254273536
spelling ndltd-OhioLink-oai-etd.ohiolink.edu-osu14525237692021-08-03T06:34:50Z Evaluation of Submandibular Infections using 3-Dimensional Reconstruction of Computed Tomography Images Elmshiti, Hashim Health Sciences AbstractPurposeThis study presents the use of three-dimensional computed tomography (3D-CT) in the evaluation of odontogenic maxillofacial infections. A secondary surgical procedure is common amongst maxillofacial infected patients to establish drainage of an abscess. These secondary procedures lead to an increase in hospital length of stay (LOS), which creates a problem for the surgeons, patients, and insurance companies. In this study, we examined the following variables: second surgery (SS), and increasing hospital LOS as the outcome variables, and the other clinical and three-dimensional (3D) factors as predictive variables. This retrospective study will determine if there is a relationship between the predictive and outcome variables.Study DesignThis imaging project was approved by the Institutional Review Board (IRB) using 103 deidentified patient scans. Patient records were collected from the Wexner Medical Center at The Ohio State University by the Division of Maxillofacial Surgery between November, 2011 and September, 2014. Patient ages included in the study ranged from 18 to 73 years. The proposed analytic method is divided into two basic approaches: clinical data collection and 3D data collection. In addition to the computed tomography images, the clinical variables recorded from the patient`s chart were age, sex, race, ethnicity,iiietiology, number of surgical interventions, past medical history (ie. hypertension, diabetes, cancer, and renal insufficiency) and time of admission, operation and discharge. The 3D image variables examined included the volume of submandibular infection, volume of associated muscles, and spatial relationship of 3D polygonal shape of the infection to adjacent structures. Moreover, we selected the following three clinical variables as outcome variables: Second Surgical Procedures (SS), and Hospital length of stay (LOS). The other remaing clinical variables (demographic, autoimmune suppression diseases, infected facial spaces, time frame variables and etc) and 3D variables are predictive variables.Results:All of the participants included in this study were clinically diagnosed with a submandibular space infection with or without extension to other facial spaces.The predictive variables that were found to be significantly associated with second surgery (SS): retromolar trigon region (p = 0.021), and submental space (p = 0.040). By comparison, the predictive variables that were found to be significantly associated with LOS included age (p = 0.031), submental space (p = 0.022), and air-way narrowing (p = 0.035). 3D-CT reformatted images showed a measurable difference in volume between the masseter (3DIM) (t = 7.300, p = 0.001) and medial pterygoid (3DIMP) (t = 6.390, p = 0.001) muscles on the infected versus uninfected side, while the volume of the lateral pterygoid (3DILP) remained statistically unchanged.ivConclusions:The difference in volume between the muscles on the affected side and the unaffected side appear to represent a good predictive measure for the severity of infection. However, when we used to predict the severity of infections, can not show any significant statistical relationship with the outcome variables.Although most of the health professional who treat patients with the odontogenic infections correlated the size of swelling with the severity of infection, 3D volume of the submandibular space infection can not show any significant relationship with the second operation and Hospital LOS, which inturn could not predict the sverity of the submandibular space infections. Using 3D-CT in evaluating submandibular space infection can provide a better orientation and understanding of the anatomical relationship between the infection and adjacent structures, which can`t be easily shown in 2D-CT. This study illustrates that the computed tomography images and 3D-CT can assist in diagnosing and presurgical planning for the treatment of submandibular space infections and may prove useful in the treatment of other deep neck facial space infections. 2016-06-10 English text The Ohio State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=osu1452523769 http://rave.ohiolink.edu/etdc/view?acc_num=osu1452523769 unrestricted This thesis or dissertation is protected by copyright: some rights reserved. It is licensed for use under a Creative Commons license. Specific terms and permissions are available from this document's record in the OhioLINK ETD Center.

Similar Items