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Background: The anatomical complexity of the oropharynx and the difficulty in reaching its distal portion have always conditioned the surgical accessibility. Robotic surgery represents an excellent alternative in the treatment of cervico-facial oncological diseases. Methods: This series comprises all patients managed for head and neck cancer by Trans Oral Robotic Surgery TORS. The staging assessment, including neck ultrasound and total body PET/CT scan, was performed in each patient according to the TNM classification. All charts were recorded with the following data: name and surname, age, gender, date of surgery intra or post-operative hemorragia, tumor site, histology, TNM stage, robot set-up time, tumor resection time, whether or not tracheotomy was performed, whether or not neck dissection was performed, insertion of a nasogastric tube or gastrostomy, time to resumption of oral feeding, surgical margins, mean length of hospital stay, adjuvant treatment and follow-up. Results: From February 2013 to February 2018, TORS was performed in 67 consecutive patients affected by head and neck tumours. We divided, our sample, in 3 subsites: supraglottic larynx, parapharyngeal space and oropharynx. Pathology reports confimed malignancy in 44 cases: 8 cases lymphomas, 36 cases of Squamous cell carcinoma (SCC), 5 cases of benign salivary glands tumors and 18 miscellaneous cases. Neck dissection was performed in 12 cases. Tracheotomy was perfomed in 3/67 cases for respiratory failures. A nasogastric tube was inserted at the end of the surgical procedure in 21 patients. The mean length of hospital stay was 10 days. Major complications included post-operative bleeding in 3 patients, 1 exitus for massive bleeding 20 days post-surgery and 1 respiratory failure treated with tracheotomy and monitoring in the Intensive Care Unit (ICU) for 3 days. Conclusions: Robotic surgery has been considered a valid alternative to traditional open treatment in many specializations with the advantages of an endoscopic procedure, with the same oncological and functional results and with fewer complications. The advantages of this type of surgical technique have been discussed, it is mandatory to focus on the indications and contraindications. [ABSTRACT FROM AUTHOR]

This is a showcase for technical description of a full digital workflow aimed to reconstruct and prosthetically rehabilitate the mandible after surgical resection. The surgery was performed following a computer-aided design and computer-aided manufacturing (CAD-CAM) guided workflow, using 3D reconstruction of the mandible and the fibula. After 2 years, when the ossification of the flap was reached and verified by a computed tomography (CT) scan, surgery was performed using a two-step implant rehabilitation, with successful outcomes. [ABSTRACT FROM AUTHOR]

Simple Summary: The purpose of this study is to predict the risk of metastatic lymph nodes related to oral tongue squamous cell carcinoma (OTSCC) and tumor grading through the combination of clinical data with radiomics metrics extracted from computed tomography (CT) images. We aimed to develop a supportive approach in the management of lymphatic cervical areas, with particular attention given to the early stages (T1−T2). Specifically, we evaluated the effectiveness of the radiomics and clinical features in the study of OTSCC and in the prediction of occult laterocervical metastatic lymph nodes. We concluded that radiomics features and clinical parameters have an important role in identifying tumor grading and metastatic lymph nodes. Machine learning approaches can be used as an easy-to-use tool to stratify patients with early-stage OTSCC, based on the identification of metastatic and non-metastatic lymph nodes Objective: To predict the risk of metastatic lymph nodes and the tumor grading related to oral tongue squamous cell carcinoma (OTSCC) through the combination of clinical data with radiomics metrics by computed tomography, and to develop a supportive approach in the management of the lymphatic cervical areas, with particular attention to the early stages (T1−T2). Between March 2016 and February 2020, patients with histologically confirmed OTSCC, treated by partial glossectomy and ipsilateral laterocervical lymphadenectomy and subjected to computed tomography (CT) before surgery, were identified by two centers: 81 patients (49 female and 32 male) with 58 years as the median age (range 19–86 years). Univariate analysis with non-parametric tests and multivariate analysis with machine learning approaches were used. Clinical, hematological parameters and radiological features extracted by CT were considered individually and in combination. All clinical parameters showed statistically significant differences (p < 0.05) for the Kruskal−Wallis test when discriminating both the tumor grading and the metastatic lymph nodes. DOI, PLR, SII, and SIRI showed an accuracy of 0.70 (ROC analysis) when identifying the tumor grading, while an accuracy ≥ 0.78 was shown by DOI, NLR, PLR, SII, and SIRI when discriminating metastatic lymph nodes. In the context of the analysis of radiomics metrics, the original_glszm_HighGrayLevelZoneEmphasis feature was selected for identifying the tumor grading (accuracy of 0.70), while the wavelet_HHH_glrlm_LowGrayLevelRunEmphasis predictor was selected for determining metastatic lymph nodes (accuracy of 0.96). Remarkable findings were also obtained when classifying patients with a machine learning approach. Radiomics features alone can predict tumor grading with an accuracy of 0.76 using a logistic regression model, while an accuracy of 0.82 can be obtained by running a CART algorithm through a combination of three clinical parameters (SIRI, DOI, and PLR) with a radiomics feature (wavelet_LLL_glszm_SizeZoneNonUniformityNormalized). In the context of predicting metastatic lymph nodes, an accuracy of 0.94 was obtained using 15 radiomics features in a logistic regression model, while both CART and CIDT achieved an asymptotic accuracy value of 1.00 using only one radiomics feature. Radiomics features and clinical parameters have an important role in identifying tumor grading and metastatic lymph nodes. Machine learning approaches can be used as an easy-to-use tool to stratify patients with early-stage OTSCC, based on the identification of metastatic and non-metastatic lymph nodes. [ABSTRACT FROM AUTHOR]

Background: Orbital fracture usually occurs as a result of blunt orbital and facial trauma and may involve ocular injuries. International studies on orbital floor fracture show several differences in epidemiology, diagnostic criteria, surgical treatment modalities, and complication rates; therefore, any comparison should be made with caution. Here we describe an unusual case involving a 19-year-old man with violence-related periorbital trauma, wherein a foreign body (a plastic pen cap) traversed the median wall of the maxillary sinus and penetrated the lower turbinate.Case Presentation: A 19-year-old Caucasian man was referred to our department with localized pain and swelling in the left suborbital region following a physical fight in May 2014. A clinical examination revealed no abnormalities in his eyeballs or eye movement, palpation of the orbital contour revealed no fractures, and ophthalmological evaluation showed no evidence of diplopia. A computed tomography scan revealed fractures in the left orbital floor, periorbital tissue herniation without muscular entrapment and left maxillary hemosinus were observed. A hypodense soft tissue mass was lodged in the left orbital floor, which extended to the median wall of the maxillary sinus and penetrated the left lower turbinate. Surgical exploration of the foreign body was conducted, revealing the foreign body to be a pen cap.Conclusions: History or clinical examination alone may be inadequate to raise the suspicion of a retained periorbital foreign body in a situation of orbital region trauma. Computed tomography is important for the evaluation of periorbital injuries, especially because it could reveal the presence of a foreign body. Periorbital foreign bodies can be observed distinctly on computed tomography, which remains the most sensitive study and should be the first imaging modality in such cases. [ABSTRACT FROM AUTHOR]