Characterizing supplement use and dietary behaviors in adults with acquired brain injury.

Background: Acquired brain injury (ABI) can result in persistent symptoms and lasting disability. Supplements are becoming more popular in patients with chronic symptoms; however, little is known about supplementation and dietary behaviors after ABI.

Methods: In this cross-sectional observational study, questionnaires were collected from 211 adults with ABI presenting to outpatient brain injury clinics.

Swallowing outcomes after transoral robotic surgery and adjuvant treatment in unknown primary.

Objectives: Robotic transoral mucosectomy of the base of tongue was introduced as a diagnostic procedure in patients treated for head and neck cancer with unknown primary (CUP), increasing the identification rate of the primary tumour. For the treatment of CUP, a considerable percentage of patients require adjuvant (chemo)radiation. The aim of this study was to investigate swallowing outcomes among CUP patients after TORS and adjuvant treatment.

Accuracy of the Apple Watch Series 4 and Fitbit Versa for Assessing Energy Expenditure and Heart Rate of Wheelchair Users During Treadmill Wheelchair Propulsion: Cross-sectional Study.

Background: The Apple Watch (AW) Series 1 provides energy expenditure (EE) for wheelchair users but was found to be inaccurate with an error of approximately 30%, and the corresponding error for heart rate (HR) provided by the Fitbit Charge 2 was approximately 10% to 20%. Improved accuracy of estimated EE and HR is expected with newer editions of these smart watches (SWs).

Objective: This study aims to assess the accuracy of the AW Series 4 (wheelchair-specific setting) and the Fitbit Versa (treadmill running mode) for estimating EE and HR during wheelchair propulsion at different intensities.

Deep Learning for Automated Elective Lymph Node Level Segmentation for Head and Neck Cancer Radiotherapy.

Depending on the clinical situation, different combinations of lymph node (LN) levels define the elective LN target volume in head-and-neck cancer (HNC) radiotherapy. The accurate auto-contouring of individual LN levels could reduce the burden and variability of manual segmentation and be used regardless of the primary tumor location. We evaluated three deep learning approaches for the segmenting individual LN levels I−V, which were manually contoured on CT scans from 70 HNC patients.

Disease outcome and associated factors after definitive platinum based chemoradiotherapy for advanced stage HPV-negative head and neck cancer.

Background: Definitive concomitant cisplatin-based chemoradiotherapy (CRT) is the current gold standard for most patients with advanced stage head and neck squamous cell carcinoma (HNSCC) of the pharynx and larynx. Since previous meta-analysis on CRT outcomes in HNSCC have been reported, advances have been made in radiotherapy techniques and clinical management, while HPV-status has been identified as a strong confounding prognostic factor in oropharyngeal cancer. Here, we present real-world outcome data from a large multicenter cohort of HPV-negative advanced stage HNSCC treated with CRT using contemporary IMRT-based techniques.