PubMed Health⌕ Search

PubMed · 8293260

A frameless method for stereotactic radiotherapy.

Abstract

A frameless method for stereotactic multiple arc radiotherapy (SMART) is described. Three short gold wires are implanted in the scalp approximately 100 mm apart. These are localized in a computed tomographic or angiographic study along with the target. Subsequently the gold markers are localized on beam films and the target position calculated using a computer program ISOLOC. This program provides the couch movements required to move the target to the isocentre and a micropositioner attached to the couch is used to make the adjustment. Beam films are repeated until the movements required are less than 1 mm in any direction. It is shown that the simple procedures of implanting the markers subcutaneously do not provide a stable reference system in about 25% of patients and the markers are now screwed into the cranium. The precision of the method is evaluated by phantom studies and measurements taken during several hundred treatments.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

D Jones, D A Christopherson, J T Washington, M D Hafermann, J W Rieke, J J Travaglini, S S Vermeulen. 1993. A frameless method for stereotactic radiotherapy.. https://doi.org/10.1259/0007-1285-66-792-1142

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

A penalized likelihood approach to magnetic resonance image reconstruction.

Currently, images acquired via magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI) technology are reconstructed using the discrete inverse Fourier transform. While computationally convenient, this approach is not able to filter out noise. This is a serious limitation because the amount of noise in MRI and fMRI can be substantial. In this paper, we propose an alternative approach to reconstruction, based on penalized likelihood methodology. In particular, we focus on non-linear shrinkage estimators and show that this approach achieves a great reduction in integrated mean squared error (IMSE) of the estimated image with respect to the currently used estimator. This approach is extremely fast and easy to implement computationally. In addition, it can be combined with various alternative approaches to MR image reconstruction and can be easily adapted to other, non-MRI contexts, in which the observed data and the quantities of interest are related via a linear transform.

Brain Diseases↗