Acellular cadaveric dermal matrix grafts for orbital wall reconstruction in patients with sinonasal malignancies
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DOI: 10.1080/01676830.2021.2020850
Abstract: ABSTRACT Purpose To describe the utilization of acellular cadaveric dermal matrix (ACDM) in patients undergoing orbital wall reconstruction after orbital preservation surgery for sinonasal malignancy. Methods Retrospective case series of seven patients with sinonasal malignancy… read more here.
Keywords: patients sinonasal; acellular cadaveric; wall reconstruction; reconstruction ... See more keywords
Orbital and periocular complications in patients with sinonasal tumours with orbital invasion
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DOI: 10.1136/bjo-2022-322855
Abstract: Aims The purpose of this study was to determine the frequency and associated risk factors of orbital/periocular complications in patients with sinonasal tumour with orbital invasion managed with eye-sparing treatments. Methods A retrospective case series… read more here.
Keywords: periocular complications; patients sinonasal; orbital invasion; eye ... See more keywords
The Role of Salvage in the Management of Patients with Sinonasal Squamous Cell Carcinoma
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DOI: 10.3390/biomedicines10061266
Abstract: Objectives: This paper presents and discusses the rate and outcome of salvage according to various factors for patients with sinonasal squamous cell carcinoma (SNSCC). Methods: Data of 79 patients treated radically due to SNSCC between… read more here.
Keywords: salvage; cell carcinoma; patients sinonasal; squamous cell ... See more keywords
Machine-Learning-Based Prediction of Treatment Outcomes Using MR Imaging-Derived Quantitative Tumor Information in Patients with Sinonasal Squamous Cell Carcinomas: A Preliminary Study
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DOI: 10.3390/cancers11060800
Abstract: The purpose of this study was to determine the predictive power for treatment outcome of a machine-learning algorithm combining magnetic resonance imaging (MRI)-derived data in patients with sinonasal squamous cell carcinomas (SCCs). Thirty-six primary lesions… read more here.
Keywords: machine; machine learning; treatment; patients sinonasal ... See more keywords