The uncertain position of lung tumor during radiotherapy compromises the treatment effect. To effectively control respiratory motion during radiotherapy of lung cancer without any side effects, a novel control scheme, hypnosis, has been introduced in lung cancer treatment. In order to verify the suggested method, six volunteers were selected with a wide range of distribution of age, weight, and...

The aim of this study is to investigate the impact of respiratory motion correction and spatial resolution on lesion detectability in PET as a function of lesion size and tracer uptake. Real respiratory signals describing different breathing types are combined with a motion model formed from real dynamic MR data to simulate multiple dynamic PET datasets acquired from a continuously moving subje...

Introduction: A case of pulmonary sarcoidosis is reported because of difficulties in diagnosis and treatment, including the co-existence of ankylosing spondylitis (AS) and severe corticosteroid dependence. Case Presentation: A 48-year-old nonsmoking woman referred to the hospital because of chronic nonproductive cough and dyspnea with a 10-year history of...

Respiratory motion has been considered a clinical challenge for lung tumor treatments due to target motion. In this study, we aimed to perform an experimental evaluation based on dynamic phantoms using MLC-based beam tracking. TrackBeam, a prototype real-time beam tracking system, has been assembled and evaluated in our clinic. TrackBeam includes an orthogonal dual-layer micro multileaf collima...

Cancer treatments by ionising beam need accurate tumour targeting, which is di cult for lung cancer, due to breathing motions. We propose here to provide physicians with 3D + time CT scan of lung from a physically based simulation of respiratory organs motion.

PURPOSE To address practical issues of implementing artificial neural networks (ANN) for lung-tumor motion prediction in MRI-based intrafractional lung-tumor tracking. METHODS A feedforward four-layered ANN structure is used to predict future tumor positions. A back-propagation algorithm is used for ANN learning. Adaptive learning is incorporated by continuously updating weights and learning ...

Purpose: To adapt the non-uniform Self-Gating (nuSG) method and compare it to established self-gating approaches for lung imaging in uniform highly irregular respiratory patterns. Methods: Six healthy volunteers underwent free breathing MRI using a radial tiny golden angle ultrashort echo-time sequence. Acquisitions were performed with volunteer as uniformly possible deliberately pattern. The a...