Spin lock and magnetization transfer imaging of head and neck tumors.

Magnetization transfer imaging of the head and neck: normative data.

PURPOSE To determine magnetization transfer ratios for normal head and neck structures so that evaluation of disease will be possible. METHODS Two-dimensional magnetization transfer imaging was performed in 12 healthy volunteers and 20 patients. We used a repetition time of 500, echo time of 12, 20 degrees flip angle, and a magnetization transfer pulse offset from the resonance frequency of w...

A Study on the Improvement of Inherent and Enhanced Tissue Contrast in Mr Imaging Using Magnetization Transfer and Spin Lock Techniques

Head and Neck Nerve Sheath Tumors: A 10-Year Evaluation in Iran

  Background and Objective: Approximately 45% of benign peripheral nerve sheath tumors (PNST) occur in head and neck regions. Malignant peripheral nerve sheath tumors (MPNST) are less common and only 8-15% of these tumors occur in head and neck region. In this study, we aimed at evaluating the demographic characteristics, pathologic findings, locations, main clinical presentations and family h...

Dynamic Contrast Magnetic Resonance Imaging (DCE-MRI) and Diffusion Weighted MR Imaging (DWI) for Differentiation between Benign and Malignant Salivary Gland Tumors

Background: Salivary gland tumors form nearly 3% of head and neck tumors. Due to their large histological variety and vicinity to facial nerves, pre-operative diagnosis and differentiation of benign and malignant parotid tumors are a major challenge for radiologists. Objective: The majority of these tumors are benign; however, sometimes they tend to transform into a malignant form. Functional M...

A Novel Classification Method using Effective Neural Network and Quantitative Magnetization Transfer Imaging of Brain White Matter in Relapsing Remitting Multiple Sclerosis

Background: Quantitative Magnetization Transfer Imaging (QMTI) is often used to quantify the myelin content in multiple sclerosis (MS) lesions and normal appearing brain tissues. Also, automated classifiers such as artificial neural networks (ANNs) can significantly improve the identification and classification processes of MS clinical datasets.Objective: We classified patients with relapsing-r...