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Molecular findings in maxillofacial bone tumours and its diagnostic value.

ABSTRACT: According to the WHO, mesenchymal tumours of the maxillofacial bones are subdivided in benign and malignant maxillofacial bone and cartilage tumours, fibro-osseous and osteochondromatous lesions as well as giant cell lesions and bone cysts. The histology always needs to be evaluated considering also the clinical and radiological context which remains an important cornerstone in the classification of these lesions. Nevertheless, the diagnosis of maxillofacial bone tumours is often challenging for radiologists as well as pathologists, while an accurate diagnosis is essential for adequate clinical decision-making. The integration of new molecular markers in a multidisciplinary diagnostic approach may not only increase the diagnostic accuracy but potentially also identify new druggable targets for precision medicine. The current review provides an overview of the clinicopathological and molecular findings in maxillofacial bone tumours and discusses the diagnostic value of these genetic aberrations.

SUBMITTER: Cleven AHG

PROVIDER: S-EPMC6968989 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Molecular findings in maxillofacial bone tumours and its diagnostic value.

Cleven Arjen H G AHG Schreuder Willem H WH Groen Eline E Kroon Herman M HM Baumhoer Daniel D

Virchows Archiv : an international journal of pathology 20191214 1

According to the WHO, mesenchymal tumours of the maxillofacial bones are subdivided in benign and malignant maxillofacial bone and cartilage tumours, fibro-osseous and osteochondromatous lesions as well as giant cell lesions and bone cysts. The histology always needs to be evaluated considering also the clinical and radiological context which remains an important cornerstone in the classification of these lesions. Nevertheless, the diagnosis of maxillofacial bone tumours is often challenging for ...[more]

PMID: 31838586

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Project description:Suspicion of malignant change within a lipoma is a common and increasing workload within the UK Sarcoma multidisciplinary team (MDT) network, and a source of considerable patient anxiety. Currently, there is no lipoma-specific data, with regard to which clinical or radiographic features predict non-benign histology, or calculate an odds-ratio specific to a lipomatous lesion being non-benign. We performed a 9-year, double-blind, unmatched cohort study, comparing post-operative histology outcomes (benign versus non-benign) versus 15 signs across three domains: Clinical (size of tumour, depth, growth noticed by patient, previous lipoma, patient felt pain), Ultrasonographic (size, depth, vascularity, heterogenous features, septae) and MRI (size, depth, vascularity, heterogenous features, septae, complete fat signal suppression). Receiver operating characteristic (ROC) analysis, odds ratios and binary logistic regression analysis was performed double-blind. When each sign is considered independently, (ROC analysis, followed by binary logistic regression) only Ultrasound depth is a significant predictor (p = 0.044) of a histologically non-benign lipoma. Ultrasonographically determined vascularity and septation were not statistically significant predictors. None of the clinical signs were statistically significant (p > 0.05). Of the MRI signs none was statistically significant (p > 0.05). However, heterogeneous MRI features fared better than MRI depth. Ultrasound signs (Pseudo R-Square = 0.105) are more predictive of the post-operation histology outcome than Clinical signs (Pseudo R-Square = 0.082) or MRI tests (Pseudo R-Square = 0.052) Ultrasound and Clinical tests combined (Pseudo R-Square = 0.147) are more predictive of the post-operation histology outcome than MRI tests (Pseudo R-Square = 0.052). This work challenges the traditional perception of "red-flag" signs when applied to lipomatous tumours. We provide accurate data upon which an informed choice can be made, and provides a robust bases for expedited risk/benefit. The importance of an experienced and cohesive MDT network is emphasised.

Dataset Information

Molecular findings in maxillofacial bone tumours and its diagnostic value.

Publications

Molecular findings in maxillofacial bone tumours and its diagnostic value.

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