A comprehensive diagnostic approach combining phylogenetic disease bracketing and CT imaging reveals osteomyelitis in a Tyrannosaurus rex

C. A. Hamm, O. Hampe, D. Schwarz, F. Witzmann, P. J. Makovicky, C. A. Brochu, R. Reiter, P. Asbach

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Traditional palaeontological techniques of disease characterisation are limited to the analysis of osseous fossils, requiring several lines of evidence to support diagnoses. This study presents a novel stepwise concept for comprehensive diagnosis of pathologies in fossils by computed tomography imaging for morphological assessment combined with likelihood estimation based on systematic phylogenetic disease bracketing. This approach was applied to characterise pathologies of the left fibula and fused caudal vertebrae of the non-avian dinosaur Tyrannosaurus rex. Initial morphological assessment narrowed the differential diagnosis to neoplasia or infection. Subsequent data review from phylogenetically closely related species at the clade level revealed neoplasia rates as low as 3.1% and 1.8%, while infectious-disease rates were 32.0% and 53.9% in extant dinosaurs (birds) and non-avian reptiles, respectively. Furthermore, the survey of literature revealed that within the phylogenetic disease bracket the oldest case of bone infection (osteomyelitis) was identified in the mandible of a 275-million-year-old captorhinid eureptile Labidosaurus. These findings demonstrate low probability of a neoplastic aetiology of the examined pathologies in the Tyrannosaurus rex and in turn, suggest that they correspond to multiple foci of osteomyelitis.

Original languageEnglish (US)
Article number18897
JournalScientific reports
Volume10
Issue number1
DOIs
StatePublished - Dec 1 2020
Externally publishedYes

Bibliographical note

Funding Information:
Open Access funding enabled and organized by Projekt DEAL. The research did not receive any project-specific grant from funding agencies in the public, commercial, or non-profit sectors. R.R. received funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation): RE 4161/1-1, RE 4161/1-2.

Publisher Copyright:
© 2020, The Author(s).

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