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Medicine and Health Sciences

The Texas Medical Center Library

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Diagnosis

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Osteoarthritis Disease Severity In The Temporomandibular Joint And The Knee Joint: A Comparative Cadaveric Study, Jessica A Immonen, Jason Ciccotelli, Linh M Nguyen, Lesley Gilmer, Landen Broadhead, Mackenzie Kitchen, Conner Paul, Jeremy James Dec 2023

Osteoarthritis Disease Severity In The Temporomandibular Joint And The Knee Joint: A Comparative Cadaveric Study, Jessica A Immonen, Jason Ciccotelli, Linh M Nguyen, Lesley Gilmer, Landen Broadhead, Mackenzie Kitchen, Conner Paul, Jeremy James

Journal Articles

OBJECTIVE: The objective of this study was to determine the level of disease severity in a pilot cohort of temporomandibular joints (TMJs) and compare them to the pathology findings previously characterized in cadaveric knee joints.

DESIGN: Thirty-one intact TMJs from 17 cadaveric donors were harvested and arthritic lesioning seen in the knee joint was investigated on the condyle and the fossa of the TMJ. Prevalence of gross alterations was equated and disease severity was determined for sex- and age-based donor pools using a validated, osteoarthritis (OA) disease severity scale (DSS). Knee joint DSS scores were also compared to the TMJ …


Papillary Fibroelastoma In Differential Diagnosis Of Left Atrial Appendage Masses, Anthony Alozie, Annette Zimpfer, Andreas Erbersdobler, Felix G Meinel, Pascal M Dohmen, Alper Öner Jan 2021

Papillary Fibroelastoma In Differential Diagnosis Of Left Atrial Appendage Masses, Anthony Alozie, Annette Zimpfer, Andreas Erbersdobler, Felix G Meinel, Pascal M Dohmen, Alper Öner

The Texas Heart Institute Journal

Papillary fibroelastomas are benign tumors that usually originate from cardiac valves but may have other endocardial origins. We report the cases of 2 patients in whom left atrial appendage masses were initially diagnosed as thrombus. They were treated for embolic stroke and their symptoms resolved; however, their left atrial appendage masses did not regress. After surgery, histologic analysis of the resected masses revealed papillary fibroelastoma in both cases. We discuss the diagnostic and therapeutic dilemmas encountered in patients with papillary fibroelastomas and cardiac masses other than thrombus.


Incidental Detection Of An Occult Oral Malignancy With Autofluorescence Imaging: A Case Report, Nadarajah Vigneswaran, Sheila Koh, Ann Gillenwater Jan 2009

Incidental Detection Of An Occult Oral Malignancy With Autofluorescence Imaging: A Case Report, Nadarajah Vigneswaran, Sheila Koh, Ann Gillenwater

Journal Articles

BACKGROUND: Autofluorescence imaging is used widely for diagnostic evaluation of various epithelial malignancies. Cancerous lesions display loss of autofluorescence due to malignant changes in epithelium and subepithelial stroma. Carcinoma of unknown primary site presents with lymph node or distant metastasis, for which the site of primary tumour is not detectable. We describe here the use of autofluorescence imaging for detecting a clinically innocuous appearing occult malignancy of the palate which upon pathological examination was consistent with a metastatic squamous cell carcinoma.

CASE DESCRIPTION: A submucosal nodule was noted on the right posterior hard palate of a 59-year-old white female during …


Comparison Of Accuracy Captured By Different Controlled Languages In Oral Pathology Diagnoses, Jung-Wei Chen, Catherine Flaitz, Todd Johnson Jan 2005

Comparison Of Accuracy Captured By Different Controlled Languages In Oral Pathology Diagnoses, Jung-Wei Chen, Catherine Flaitz, Todd Johnson

Journal Articles

This project was comparing the accuracy of capturing the oral pathology diagnoses among different coding systems. 55 diagnoses were selected for comparison among 5 coding systems. The results of accuracy in capturing oral diagnoses are: AFIP (96.4%), followed by Read 99 (85.5%), SNOMED 98 (74.5%), ICD-9 (43.6%), and CDT-3 (14.5%). It shows that the currently used coding systems, ICD-9 and CDT-3, were inadequate, whereas the AFIP coding system captured the majority of oral diagnoses. In conclusion, the most commonly used medical and dental coding systems lack terms for the diagnosis of oral and dental conditions.