A new metric for assessing IMRT modulation complexity and plan deliverability

This study investigated the impact of beam complexities on planar quality assurance and plan quality robustness by introducing MLC errors in intensity‐modulate radiation therapy. Forty patients' planar quality assurance (QA) plans were enrolled in this study, including 20 dynamic MLC (DMLC) IMRT plans and 20 static MLC (SMLC) IMRT plans. The total beam numbers were 150 and 160 for DMLC and SMLC, respectively. Six different magnitudes of MLC errors were introduced to these beams. Gamma pass rates were calculated by comparing error‐free fluence and error‐induced fluence. The plan quality variation was acquired by comparing PTV coverage. Eight complexity scores were calculated based on the beam fluence and the MLC sequence. The complexity scores include fractal dimension, monitor unit, modulation index, fluence map complexity, weighted average of field area, weighted average of field perimeter, and small aperture ratio false(<5cm2 and<50 cm2false). The Spearman's rank correlation coefficient was calculated to analyze the correlation between these scores and gamma pass rate and plan quality variation. For planar QA, the most significant complexity index was fractal dimension for DMLC false(p=−0.40false) and weighted segment area for SMLC false(p=0.27false) at low magnitude MLC error. For plan quality, the most significant complexity index was weighted segment perimeter for DMLC false(p=0.56false) and weighted segment area for SMLC false(p=0.497false) at low magnitude MLC error. The sensitivity of planar QA was weakly associated with the field complexity with low magnitude MLC error, but the plan quality robustness was associated with beam complexity. Plans with simple beams were more robust to MLC error.PACS number(s): 87.55

Section: Discussionmentioning

confidence: 99%

“…In the inverse optimization, the complexity metric was used to get a smoother fluence (12) . Some aperture‐based metrics were also developed 13 , 14 , 15 , 16 …”

Section: Introductionmentioning

confidence: 99%

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Are simple IMRT beams more robust against MLC error? Exploring the impact of MLC errors on planar quality assurance and plan quality for different complexity beams

Wang

Jin

Peng

et al. 2016

“…The calculation method was based on the equation described by McNiven 14. Analysis was performed between the MCS and the detectability to see the correlation between complexity of the MLC motion and the fiducial marker detection.…”

Section: Methodsmentioning

confidence: 99%

Recommendation of fiducial marker implantation for better target tracking using MV imager in prostate radiotherapy

Kilian-Meneghin

Kumaraswamy

2018

PurposeThe aim of this study was to develop a model that optimizes the fiducial marker locations in the prostate to increase detectability of the markers in the projected EPID images during VMAT treatments.Methods and MaterialsThe fiducial marker tracking capability for each arc was evaluated through a proposed formula. The output of the formula, a detectability score, was calculated with the in‐house developed software written in MATLAB (The Mathworks, Inc., Natick, MA, USA). Three unique weighting factors were added to penalize the detectability score. The detectability scores of four different patterns containing 40 combinations of simulated fiducial marker locations were evaluated with 101 previously treated prostate treatment plans (containing 202 individual arcs). The results were analyzed for each pattern group and each marker separation distance on the transverse plane.ResultsThe maximum detectability of the markers occurred when they were placed between 10 and 15 mm from the center of the prostate in the transverse plane and 6–13 mm in the superior–inferior direction. The detectability decreased when the markers were placed beyond 20 mm in both directions.ConclusionsThe fiducial marker‐based detectability score can be used to predict the real‐time tracking capability. Suggestions for optimal insertion locations were given to improve prostate motion management using MV imaging.

“…The modulation complexity, described by the Modulation Complexity Score (MCS), 23 , 24 for IMRT and VMAT:

M C S_{b e a m} = \sum_{i = 1}^{Z - 1} (\frac{L S V_{C P_{i} +} L S V_{C P_{i + 1}}}{2}, \frac{A A V_{C P_{i} +} A A V_{C P_{i + 1}}}{2}, \frac{M U_{i, i + 1}}{M U_{b e a m}})

with the Leaf Sequence Variability (LSV) per control point

C P_{i}

, for a total number Z of control points:

L S V_{C P} = {[\frac{\sum_{n}^{Z - 1} (p o s_{max} - | p o s_{n} - p o s_{n + 1} |)}{(N - 1) \times p o s_{max}}]}_{l e f t} \cdot {[\frac{\sum_{n}^{Z - 1} (p o s_{max} - | p o s_{n} - p o s_{n + 1} |)}{(N - 1) \times p o s_{max}}]}_{r i g h t}

where

p o s_{n}

is the position of the left/right leaf n and

p o s_{m a x}

is the maximal position variability of the left/right leaf bank at control point

C P_{i}

, for a total number N of open leaves.The Aperture Area Variability (AAV) per control point is given by:

A A V_{C P} = true \sum_{n = 1}

…”

Section: Methodsmentioning

confidence: 99%

EPID based in vivo dosimetry system: clinical experience and results

Celi

Costa

Wessels

et al. 2016

Mandatory in several countries, in vivo dosimetry has been recognized as one of the next milestones in radiation oncology. Our department has implemented clinically an EPID based in vivo dosimetry system, EPIgray, by DOSISOFT S.A., since 2006. An analysis of the measurements per linac and energy over a two‐year period was performed, which included a more detailed examination per technique and treatment site over a six‐month period. A comparison of the treatment planning system doses and the doses estimated by EPIgray shows a mean of the differences of 1.9% (±5.2%) for the two‐year period. The 3D conformal treatment plans had a mean dose difference of 2.0% (±4.9%), while for intensity‐modulated radiotherapy and volumetric‐modulated arc therapy treatments the mean dose difference was −3.0 (±5.3%) and −2.5 (±5.2%), respectively. In addition, root cause analyses were conducted on the in vivo dosimetry measurements of two breast cancer treatment techniques, as well as prostate treatments with intensity‐modulated radiotherapy and volumetric‐modulated arc therapy. During the breast study, the dose differences of breast treatments in supine position were correlated to patient setup and EPID positioning errors. Based on these observations, an automatic image shift correction algorithm is developed by DOSIsoft S.A. The prostate study revealed that beams and arcs with out‐of‐tolerance in vivo dosimetry results tend to have more complex modulation and a lower exposure of the points of interest. The statistical studies indicate that in vivo dosimetry with EPIgray has been successfully implemented for classical and complex techniques in clinical routine at our institution. The additional breast and prostate studies exhibit the prospects of EPIgray as an easy supplementary quality assurance tool. The validation, the automatization, and the reduction of false‐positive results represent an important step toward adaptive radiotherapy with EPIgray.PACS number(s): 87.53.Bn, 87.55.Qr, 87.56.Fc, 87.57.uq