Background: Cervical lymph node metastasis (LNM) is a well-established poor prognosticator of oral squamous cell carcinoma (OSCC), in which occult metastasis is a subtype that makes prediction challenging. Here, we developed and validated a deep learning (DL) model using magnetic resonance imaging (MRI) for the identification of LNM in OSCC patients.
Methods: This retrospective diagnostic study developed a three-stage DL model by 45,664 preoperative MRI images from 723 patients in 10 Chinese hospitals between January 2015 and October 2020.
Objectives: Development of a prediction model using machine learning (ML) method for tumor progression in oral squamous cell carcinoma (OSCC) patients would provide risk estimation for individual patient outcomes.
Patients And Methods: This predictive modeling study was conducted of 1163 patients with OSCC from Hospital of Stomatology, SYSU and SYSU Cancer Center from March 2009 to October 2021. Clinical, pathological, and hematological features of the patients were collected.
Background: A variety of solid tumours, including oral squamous cell carcinoma (OSCC), can cause coagulation abnormalities, and this phenomenon is known as tumour-associated hypercoagulation. We aimed to explore the preoperative thromboelastography (TEG) parameter profiles of OSCC patients, and to investigate their trends in relation to tumour stage progression, and to evaluate their value for predicting cervical lymph node metastasis.
Methods: Data on thromboelastographic parameters and conventional coagulation indices were retrospectively collected, and comparisons were performed among preoperative primary OSCC patients (n = 311), recurrent/metastatic OSCC patients (n = 44) and a control group (n = 71).
Objective: A hypercoagulable state exists in patients with oral squamous cell carcinoma (OSCC), but the role of platelets in the tumour microenvironment has not been explored. This study revealed the status of intratumoral plateletmicrothrombi (PLT-MT) and their clinicopathological relevance and predictive value in OSCC.
Study Design: This study retrospectively evaluated 106 OSCC patients.
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