Routine clinical on-line portal imaging followed by immediate field adjustment using a tele-controlled patient couch

Neve, Wilfried De; Heuvel, Frank Van den; Beukeleer, M. De; Coghe, M.; Thon, L.; Roover, P. De; Lancker, M. Van; Storme, Guy

doi:10.1016/0167-8140(92)90353-v

Cited by 111 publications

(29 citation statements)

References 7 publications

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“…Since about half the number of fields had to be corrected, the average extra time per fraction per analyzed field is now about 2 minutes. Because it takes two images to determine the 3D patient set-up, a total of 4 minutes per fraction are maximally needed, which is comparable to most other studies [30,31,39,71,116] and to the routinely used off-line protocol in our institute. FUlthermore, elaborate setup equipment such as mattresses and foot and ann supports also require extra time.…”

Section: Extra Treatment Timementioning

confidence: 64%

“…With on-line corrections, the set-up deviation is determined and conected before the (bulk of the) daily treatment dose is given. Other groups have repor1ed superior set-up accuracies at the cost of increased treatment time [7,30,31,35,39,71,116,117]. In this paper, we will discuss whether on-line set-up corrections are beneficial and clinically feasible in our institute.…”

Section: E On-line Set-up Correctionsmentioning

confidence: 99%

“…The obvious way to achieve that is by on-line con'ections, i.e., by correcting the tumor position each day before the full irradiation dose is given. For set-up variations, the use of electronic portal imaging for this purpose has been investigated several times, as is described in Chapter 6 and in previous publications [7,30,31,35,39,71,116,117]. The accuracy that can be obtained by this method is in principle limited by the accuracy of the measurements and the corrections, which depends highly on the mechanical accuracy of the accelerator, treahnent table, and EPID.…”

Section: Vmentioning

confidence: 99%

“…In the last two decades several electronic pOital imaging (EPID) systems have been developed for computerized acquisition and analysis of 1'01 tal images [2,20,123]. Either off-line [12,14] (before the next treahnent session) or on-line [31,105] (while the patient is still on the treatment couch) setup correction protocols can then be used to minimize the sehlp e11'OrS. On-line corrections yield better accuracies than off-line corrections but generally take more time.…”

Section: A Geometrical Uncertailltiesmentioning

confidence: 99%

“…This so-called "off-line protocol" reduces systematic deviations while random deviations remain unchanged. Both systematic and random set-up deviations can be reduced to negligible values if on-line cOlTections are applied [31,105]. In this case, the patient position is verified at each fraction using a small number of monitor units.…”

Section: Introductionmentioning

confidence: 99%

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Safety margins for geometrical uncertainties in radiotherapy

Stroom

2000

Med. Phys.

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In this thesis we deal with the calculation and minimization of safety margins (CTV to PTV) that are required to account for setup errors and internal organ motion in radiotherapy. First of all, an algorithm was developed to automatically expand a three‐dimensional (3‐D) tumor volume, defined in a set of 2‐D CT images, with 3‐D margins of a given size. To do this manually and in three dimensions is impossible. The clinical advantages of the automatically calculated 3‐D margins over the much applied manual 2‐D expansion procedure were assessed. In addition, a model was devised to calculate the margins using measured geometrical deviations from the planned situation in representative patient populations. The calculated margins were such that the expected radiation dose in the tumor was adequate and homogeneous. It appeared that systematic deviations, which are the same each fraction of the treatment, are about three times more important than random deviations, which vary from fraction to fraction. The model was used to investigate whether smaller margins could be used when patients with prostate cancer are treated in the prone instead of the supine position, but there was no significant difference. Finally, the use of portal images for an on‐line correction of geometrical deviations was studied. The registration of bony structures in the images enabled on‐line corrections of the patient setup within a couple of minutes and a significant margin reduction. For prostate cancer treatments, simulations using multiple CT data of 15 patients indicated that gas pockets in the rectum, which are also visible in portal images, may be used for the on‐line determination of rectal wall and tumor motion.

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Section: Extra Treatment Timementioning

confidence: 64%

Section: E On-line Set-up Correctionsmentioning

confidence: 99%

Section: Vmentioning

confidence: 99%

Section: A Geometrical Uncertailltiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Safety margins for geometrical uncertainties in radiotherapy

Stroom

2000

Med. Phys.

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A survey of image‐guided radiation therapy use in the United States

Simpson

Lawson

Nath

et al. 2010

Cancer

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Image and isocentre management in the paperless age: an automated decision making model

et al. 2009

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Purpose: The introduction of sophisticated imaging and image analysis tools into daily radiotherapy has made it feasible to undertake image guided radiation therapy (IGRT) on a daily basis. The aim of this paper is to outline that the introduction of a paperless automated decision making model to assess systematic trends in field placement can enhance the efficiency of a treating radiotherapy team. Methods: Automated custom reports were written using Infomaker (Sybase, Dublin, California, USA) to integrate with the ARIA (Varian, Palo Alto, California, USA) patient information system. This allowed automated systematic trend identification in treatment field set-up. The efficiency and accuracy of an automated approach was then compared to manual field placement analysis and a statistical model (Newcastle model). Results:The automated decision making model has been shown to reduce the amount of time taken to analyse images and systematic trend analysis, when compared to manual methods, significantly (P < 0.001). In addition to the enhanced efficiency there is no trade off in accuracy with the automated decision making model. Discussion: An automated approach to trend analysis allows the treating radiotherapy team to manage field placement in a highly efficient manner, which is paramount in the era of increased image data. A paperless approach to image analysis and field placement trend analysis places the responsibility of accurate field placement on the radiation therapist and represents a vital link in the management of an IGRT protocol. Conclusion: In the era of IGRT with increased imaging data, efficient methods must be found to analyse and manage systematic trends. An automated decision making model represents an increase in efficiency with no trade off in accuracy.

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Routine clinical on-line portal imaging followed by immediate field adjustment using a tele-controlled patient couch

Cited by 111 publications

References 7 publications

Safety margins for geometrical uncertainties in radiotherapy

Safety margins for geometrical uncertainties in radiotherapy

A survey of image‐guided radiation therapy use in the United States

Image and isocentre management in the paperless age: an automated decision making model

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