Tongue dorsum activity in children with velopharyngeal insufficiency vs. typically developing children.

To investigate whether children with velopharyngeal insufficiency (VPI) exhibit increased elevation and retraction of the tongue dorsum. Two quantitative metrics of tongue dorsum activity: Dorsum excursion Index (DEI) and Tongue Constraint Position Index (TCPI) were captured using mid-sagittal images of the tongue obtained from Ultrasound Tongue Imaging. Participants: Six children with velopharyngeal insufficiency (VPI), six children with palate (w/wo cleft lip) without velopharyngeal insufficiency (wo VPI) and ten typically developing children aged 6-15 repeated six different consonants in aCa and iCi contexts five times.

A retrospective analysis of factors affecting speech production in school-aged children with cleft palate (+- cleft lip).

Objective: The present investigation examined how factors such as cleft type, age of primary palatal surgery, diagnosed syndromes, hearing problems, and malocclusions could predict persistent speech difficulties and the need for speech services in school-aged children with cleft palate.

Methods: Participants included 100 school-aged children with cleft palate. Americleft speech protocol was used to assess the perceptual aspects of speech production.

Feasibility of using ultrasound visual biofeedback to treat persistent speech sound disorders in children with cleft palate- a case series.

The current study aimed to assess the effectiveness of incorporating ultrasound visual biofeedback (UVB) into a treatment programme addressing persistent speech sound disorders linked to cleft palate in children who have been unresponsive to traditional therapy approaches. Materials and Methods. A single-subject multiple baseline experiment was conducted with five children aged 6:5-13:5 over a period of 16 therapy sessions.

Improving Proton Dose Calculation Accuracy by Using Deep Learning.

Introduction: Pencil beam (PB) dose calculation is fast but inaccurate due to the approximations when dealing with inhomogeneities. Monte Carlo (MC) dose calculation is the most accurate method but it is time consuming. The aim of this study was to develop a deep learning model that can boost the accuracy of PB dose calculation to the level of MC dose by converting PB dose to MC dose for different tumor sites.

Boosting radiotherapy dose calculation accuracy with deep learning.

In radiotherapy, a trade-off exists between computational workload/speed and dose calculation accuracy. Calculation methods like pencil-beam convolution can be much faster than Monte-Carlo methods, but less accurate. The dose difference, mostly caused by inhomogeneities and electronic disequilibrium, is highly correlated with the dose distribution and the underlying anatomical tissue density.

Technical Note: A feasibility study on deep learning-based radiotherapy dose calculation.

Purpose: Various dose calculation algorithms are available for radiation therapy for cancer patients. However, these algorithms are faced with the tradeoff between efficiency and accuracy. The fast algorithms are generally less accurate, while the accurate dose engines are often time consuming.

The Relationship between NMR Chemical Shifts of Thermally Polarized and Hyperpolarized Y Complexes and Their Solution Structures.

Recently developed dynamic nuclear polarization (DNP) technology offers the potential of increasing the NMR sensitivity of even rare nuclei for biological imaging applications. Hyperpolarized Y is an ideal candidate because of its narrow NMR linewidth, favorable spin quantum number (I=1/2 ), and long longitudinal relaxation times (T ). Strong NMR signals were detected in hyperpolarized Y samples of a variety of yttrium complexes.