A randomised trial of patient repositioning during radiotherapy using a megavoltage imaging system

Gildersleve, J.; Dearnaley, David P.; Evans, Philip; Law, Mary; Rawlings, C.; Swindell, W.

doi:10.1016/0167-8140(94)90396-4

Cited by 47 publications

(13 citation statements)

References 28 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: 63%

“…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%

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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: 63%

Section: E On-line Set-up Correctionsmentioning

confidence: 99%

Section: Vmentioning

confidence: 99%

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Safety margins for geometrical uncertainties in radiotherapy

Stroom

2000

Med. Phys.

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“…The next step consisted of the CBCT acquisition and the 3D-3D fusion with the CT planning scan. Online correction was applied when any translation was bigger than 3 mm (action level value) [8][9][10][11][12][13]. Rotation corrections were not carried out, but recorded; in addition, they should not exceed 3º, otherwise it is mandatory to review the patient positioning.…”

Section: Igrt Clinical Protocolmentioning

confidence: 99%

Uncertainties and CTV to PTV margins quantitative assessment using cone-beam CT technique in clinical application for prostate, and head and neck irradiation tumours

et al. 2011

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PURPOSE To evaluate the magnitude of systematic and random errors from a subset of 100 prostate and 26 head and neck (H&N) cancer patients treated with conventional conformal radiotherapy and using image-guided radiotherapy (IGRT). After treatment, the uncertainties involved and the CTV to PTV margin were evaluated. MATERIAL AND METHODS An Elekta Synergy® linear accelerator was used, taking advantage of 3D on-board computed tomography. IGRT with no-action level (NAL) protocol was applied, reporting the 3D translation and rotation corrections. A statistical study was performed to analyse systematic, random and interobserver uncertainties, and, finally, to obtain the CTV to PTV margins. RESULTS The H&N patients' uncertainties found were smaller than those of prostate patients. The CTV to PTV margins assessed, following the guidelines found in the literature, in the three dimensions of space (right-left, superior-inferior, anterior-posterior) were (5.3, 3.5, 3.2) mm for H&N and (7.3, 7.0, 9.0) mm for prostate cancer treatments. CONCLUSIONS It was found that assessing all the involved uncertainties within radiation treatments was very revealing; their quality improves using IGRT techniques and performing extensive data analysis.

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“…1,2,3,4,5,6 With appropriate training, equipment and highly sophisticated automated tools, radiation therapy teams can be assured of field placement accuracy on a daily basis, with management of both systematic and random set-up error. 7,8,9,10,11 This level of online verification, however, leads to enormous amounts of image data that must be analysed in both the online and offline environments. Since the clinical inception of Radiation Oncology Queensland (ROQ) in May 2007, over 25,000 MV or kV verification images have been taken.…”

Section: Introductionmentioning

confidence: 99%

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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A randomised trial of patient repositioning during radiotherapy using a megavoltage imaging system

Cited by 47 publications

References 28 publications

Safety margins for geometrical uncertainties in radiotherapy

Safety margins for geometrical uncertainties in radiotherapy

Uncertainties and CTV to PTV margins quantitative assessment using cone-beam CT technique in clinical application for prostate, and head and neck irradiation tumours

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

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