Prediction of Recurrence by Machine Learning in Salivary Gland Cancer Patients After Adjuvant (Chemo)Radiotherapy.

BACKGROUND/AIM: To investigate survival outcomes and recurrence patterns using machine learning in patients with salivary gland malignant tumor (SGMT) undergoing adjuvant chemoradiotherapy (CRT). PATIENTS AND METHODS: Consecutive SGMT patients were identified, and a data set included nine predictor variables and a dependent variable [disease-free survival (DFS) event] was standardized. The open-source R software was used. Survival outcomes were estimated by the Kaplan-Meier method. The random forest approach was used to select the important explanatory variables. A classification tree that optimally partitioned SGMT patients with different DFS rates was built. RESULTS: In total, 54 SGMT patients were included in the final analysis. Five-year DFS was 62.1%. The top two important variables identified were pathologic node (pN) and pathologic tumor (pT). Based on these explanatory variables, patients were partitioned in three groups, including pN0, pT1-2 pN+ and pT3-4 pN+ with 26%, 38% and 75% probability of recurrence, respectively. Accordingly, 5-year DFS rates were 73.7%, 57.1% and 34.3%, respectively. CONCLUSION: The proposed decision tree algorithm is an appropriate tool to partition SGMT patients. It can guide decision-making and future research in the SGMT field.

Color-Doppler ultrasound in the diagnosis of oral vascular anomalies.

In last few years, thanks to laser technology with minimally invasive approach, there was a growing need for treatment of oral vascular malformations inside the dental offices. Generally, the diagnosis of oral vascular malformations is based on clinical history, clinical examination and imaging exams. In the present paper, we review, researching by PubMed, the technical aspects, clinical indications, potentialities and limitations of color-Doppler ultrasound in the work-up of oral vascular malformations. Different imaging modalities are encountered for the diagnosis and follow-up of these lesions such as computed tomography, magnetic resonance imaging, color-Doppler ultrasound and angiography. To date, color-Doppler ultrasound is considered the first-line imaging approach since it provides a non-invasive, cost effective, real time evaluation of oral vascular anomalies. It provides both morphological and vascular information, which are useful to determine the best therapeutic options. Ultrasonography, for these reasons, could be considered as a valuable diagnostic tool in the preliminary assessment of oral vascular anomalies.