Inclusion of geometrical uncertainties in radiotherapy treatment planning by means of coverage probability

Stroom, J.; Boer, Hans C.J. de; Huizenga, H.; Visser, A.G.

doi:10.1016/s0360-3016(98)00468-4

Cited by 491 publications

(364 citation statements)

References 21 publications

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“…Based on standard margin recipes, ( 6 – 7 ) a 5 mm PTV margin should be optimal. Our results demonstrated that this margin was too large and could effectively be reduced to

~ 1.9 mm

for CTV1 and

~ 1.5 mm

for CTV2 and still provide adequate dose coverage.…”

Section: Discussionmentioning

confidence: 99%

“…In the works for margin recipes, prostate cancer treatment was studied and margins were selected to ensure that the minimum dose (

{normalD}_{min}

) or dose to 99% of the CTV volume (

{normalD}_{99}

) was greater than or equal to 95% of the prescription dose. ( 6 – 7 ) This criterion can be reasonably met in the treatment of prostate cancer, which is a deep seated tumor, with a target volume that is generally of convex shape and is surrounded by few critical structures, mainly the bladder and rectum. For HN cancer, this criterion can not be easily met.…”

Section: Discussionmentioning

confidence: 99%

“…Margins based on published recipes ( 6 – 7 ) and the measured patient setup error data were compared to the overall 5 mm CTV‐to‐PTV margins currently used in the planning. It should be emphasized that in this work only margins for rigid setup uncertainties were investigated.…”

Section: Methodsmentioning

confidence: 99%

“…These recipes can be used to calculate planning margin size using systematic (Σ) and random (σ) setup errors measured for a population of patients. Of the margin recipes proposed, two commonly used are those from van Herk et al ( 6 )

(M 1 = 2.5 Σ + 0.7 σ)

and Stroom et al ( 7 )

(M 2 = 2.0 Σ + 0.7 σ)

. Both recipes were derived and validated based on analysis of 3D conformal treatments, and their validity in HN‐IMRT planning is still being investigated.…”

Section: Introductionmentioning

confidence: 99%

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Dosimetric assessment of rigid setup error by CBCT for HN‐IMRT

Worthy

2010

J Applied Clin Med Phys

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Dose distributions in HN‐IMRT are complex and may be sensitive to the treatment uncertainties. The goals of this study were to evaluate: 1) dose differences between plan and actual delivery and implications on margin requirement for HN‐IMRT with rigid setup errors; 2) dose distribution complexity on setup error sensitivity; and 3) agreement between average dose and cumulative dose in fractionated radiotherapy. Rigid setup errors for HN‐IMRT patients were measured using cone‐beam CT (CBCT) for 30 patients and 896 fractions. These were applied to plans for 12 HN patients who underwent simultaneous integrated boost (SIB) IMRT treatment. Dose distributions were recalculated at each fraction and summed into cumulative dose. Measured setup errors were scaled by factors of 2–4 to investigate margin adequacy. Two plans, direct machine parameter optimization (DMPO) and fluence only (FO), were available for each patient to represent plans of different complexity. Normalized dosimetric indices, conformity index (CI) and conformation number (CN) were used in the evaluation. It was found that current 5 mm margins are more than adequate to compensate for rigid setup errors, and that standard margin recipes overestimate margins for rigid setup error in SIB HN‐IMRT because of differences in acceptance criteria used in margin evaluation. The CTV‐to‐PTV margins can be effectively reduced to 1.9 mm and 1.5 mm for CTV1 and CTV2. Plans of higher complexity and sharper dose gradients are more sensitive to setup error and require larger margins. The CI and CN are not recommended for cumulative dose evaluation because of inconsistent definition of target volumes used. For fractionated radiotherapy in HN‐IMRT, the average fractional dose does not represent the true cumulative dose received by the patient through voxel‐by‐voxel summation, primarily due to the setup error characteristics, where the random component is larger than systematic and different target regions get underdosed at each fraction.PACS numbers: 87.53.Kn, 87.53.Tf.

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“…Based on standard margin recipes, ( 6 – 7 ) a 5 mm PTV margin should be optimal. Our results demonstrated that this margin was too large and could effectively be reduced to

~ 1.9 mm

for CTV1 and

~ 1.5 mm

for CTV2 and still provide adequate dose coverage.…”

Section: Discussionmentioning

confidence: 99%

“…In the works for margin recipes, prostate cancer treatment was studied and margins were selected to ensure that the minimum dose (

{normalD}_{min}

) or dose to 99% of the CTV volume (

{normalD}_{99}

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

(M 1 = 2.5 Σ + 0.7 σ)

and Stroom et al ( 7 )

(M 2 = 2.0 Σ + 0.7 σ)

. Both recipes were derived and validated based on analysis of 3D conformal treatments, and their validity in HN‐IMRT planning is still being investigated.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Dosimetric assessment of rigid setup error by CBCT for HN‐IMRT

Worthy

2010

J Applied Clin Med Phys

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“…Therefore, both target positions and the WEL to the target need to be taken into account for accurate target irradiation. Generally, patient positioning is performed based on bony structures that cause large changes in the WEL when their positions change, and a margin is added to the target to ensure that the prescribed dose is delivered to the target despite changes in the WEL 14 , 15 , 16 , 17 …”

Section: Introductionmentioning

confidence: 99%

Development of an automatic evaluation method for patient positioning error

Kubota

Tashiro

Shinohara

et al. 2015

J Applied Clin Med Phys

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Highly accurate radiotherapy needs highly accurate patient positioning. At our facility, patient positioning is manually performed by radiology technicians. After the positioning, positioning error is measured by manually comparing some positions on a digital radiography image (DR) to the corresponding positions on a digitally reconstructed radiography image (DRR). This method is prone to error and can be time‐consuming because of its manual nature. Therefore, we propose an automated measuring method for positioning error to improve patient throughput and achieve higher reliability. The error between a position on the DR and a position on the DRR was calculated to determine the best matched position using the block‐matching method. The zero‐mean normalized cross‐correlation was used as our evaluation function, and the Gaussian weight function was used to increase importance as the pixel position approached the isocenter. The accuracy of the calculation method was evaluated using pelvic phantom images, and the method's effectiveness was evaluated on images of prostate cancer patients before the positioning, comparing them with the results of radiology technicians' measurements. The root mean square error (RMSE) of the calculation method for the pelvic phantom was 0.23±0.05 mm. The coefficients between the calculation method and the measurement results of the technicians were 0.989 for the phantom images and 0.980 for the patient images. The RMSE of the total evaluation results of positioning for prostate cancer patients using the calculation method was 0.32±0.18 mm. Using the proposed method, we successfully measured residual positioning errors. The accuracy and effectiveness of the method was evaluated for pelvic phantom images and images of prostate cancer patients. In the future, positioning for cancer patients at other sites will be evaluated using the calculation method. Consequently, we expect an improvement in treatment throughput for these other sites.PACS number: 87

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Imaging Devices

Rivard¹,

Heuval²

2006

Encyclopedia of Medical Devices and Instrumentation

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Electronic portal imaging detectors (EPIDs) are devices that electronically capture the photon energy fluence transmitted through a patient irradiated during treatment, and allow direct digitization of the image. This image is then immediately available for visualization on a computer screen and electronic storage. A variety of technologies have been explored in the past two decades. These include camera based systems, liquid ionization chambers, linear arrays of silicon diode detectors, and flat‐panel displays composed of thin film technology (TFT) integrated circuits. TFT EPIDs permit high imaging resolution, high signal‐to‐noise ratios, and high photon detection efficiencies at reasonable cost. EPIDs permit digital comparisons of the simulated treatment plan with the resultant radiotherapy implementation. EPIDs are quickly replacing radiographic film as an important tool for providing direct confirm treatment delivery. Due to the electronic nature of the system, on‐ and off‐line image analysis is possible for augmenting patient positioning, artifact removal, imaging processing, and evaluation. While increasing the rate of image acquisition, patient throughput is largely unimpeded and improvements in radiotherapy delivery result. EPIDs can reduce the incidence and extent of errors made during radiation treatment delivery. Due to the electronic nature of EPID measurement of the photon energy fluence exiting a patient, one can perform exit dosimetry and quantitative comparisons with treatment planning intentions. EPID quality assurance is described in the 2001 Task Group No. 58 protocol of the American Association of Physicists in Medicine. Daily, monthly, and annual tests are performed to assure the EPID is reliable for clinical use.

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Inclusion of geometrical uncertainties in radiotherapy treatment planning by means of coverage probability

Cited by 491 publications

References 21 publications

Dosimetric assessment of rigid setup error by CBCT for HN‐IMRT

Dosimetric assessment of rigid setup error by CBCT for HN‐IMRT

Development of an automatic evaluation method for patient positioning error

Imaging Devices

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