Elekta Ab (publ)

Elekta Ab

Marcel Van Herk

Jan-Jakob Sonke

Peter Remeijer

Jeffrey H Siewerdsen

Kevin J Brown

David Anthony Jaffray

Lambert Zijp

Angelo Mencarelli

Simon Van Kranen

Kevin John Brown

Jeffrey Siewerdsen

Jon-Jakob Sonke

An example of sporadic motion that causes difficulty in CT scanning is gas pockets moving around the rectum. The invention allows the automatic detection of such movements, by enhancing low density features around the prostate in the individual X-ray images, projecting these features on the cranio-caudal axis (assuming that the gas predominantly moves in this direction) to form a 1-dimensional image, and combining successive ID projections to form a 2D image. Moving gas will produce tilted lines in this image, identifying an angular range that needs to be discarded. Such a process can be used in an image processing apparatus of a CT scanner.

Motion artefact reduction in CT scanning

Methods and systems are provided for protecting a critical structure during the administration of radiation treatment to a patient. A register receives proposed positions for one or more radiation beams with respect to a critical structure. A processor predicts a cumulative dose volume for the critical structure based on the dose distribution, and determines if the cumulative dose volume exceeds a tolerance value. If the cumulative dose volume exceeds the tolerance value, the dose distribution may be translated at least in part based on a relationship between the cumulative dose volume and the dose distribution position.

Methods and systems for protecting critical structures during radiation treatment

An in-line 4D cone beam CT reconstruction algorithm queues a limited number of projection images such that the phase determination algorithm can look-ahead. At regular intervals, the queue is scanned and those images which have enough look-ahead to obtain phase information are filtered and back-projected. The algorithm thus keeps up with the image acquisition speed and produces a 4D reconstruction within a few seconds of the end of scanning.

On-line cone beam CT reconstruction

The present invention provides a method and an apparatus for reconstructing images from data acquired during radiotherapy. The approach is based on summing the imaging data acquired while both therapeutic and imaging source are active, with that acquired when only the therapeutic source is active. Further correction of the summed data can lead to reconstructed images of excellent quality.

Radiotherapy and imaging methods and apparatus

Artifacts in the reconstructed volume data of cone beam CT systems can be removed by the application of respiration correlation techniques to the acquired projection images. To achieve this, the phase of the patients breathing is monitored while acquiring projection images continuously. On completion of the acquisition, projection images that have comparable breathing phases can be selected from the complete set, and these are used to reconstruct the volume data using similar techniques to those of conventional CT. Any phase can be selected and therefore the effect of breathing can be studied. It is also possible to use a feature in the projection images such as the patient's diaphragm to determine the breathing phase. This feature in the projection images can be used to control delivery of therapeutic radiation dependent on the patient's breathing cycle, to ensure that the tumor is in the correct position when the radiation is delivered.

Computed tomography scanning

An apparatus, method and software module for selecting phase-correlated images from the output of a scanner such as a cone beam CT scanner operates by collapsing the images derived from the series from two dimensions to one dimension by summing the intensities of pixels along a dimension transverse to the one dimension, producing a further image from a composite of the one-dimensional images obtained from images in the series, analysing the further image for periodic patterns, and selecting from the series images having like phase in that periodic pattern. If desired, a plurality of reconstructions can be derived at different phases. The analysis of the further image for periodic patterns can include comparing the one-dimensional images therein, to identify a movement of features in that dimension. This allows (inter alia) the accurate determination of the breathing cycle in a patient and a concomitant improvement in the quality of CT scans by using phase-correlated images.

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Amsterdam, Netherlands

Marcel Van Herk