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Abstract This study evaluated a method for prostate intensity-modulated radiation therapy (IMRT) based on edge-enhanced (EE) intensity in the presence of intrafraction organ deformation using the data of 37 patients treated with step-and-shoot IMRT. On the assumption that the patient setup error was already accounted for by image guidance, only organ deformation over the treatment course was considered. Once the clinical target volume (CTV), rectum, and bladder were delineated and assigned dose constraints for dose optimization, each voxel in the CTV derived from the DICOM RT-dose grid could have a stochastic dose from the different voxel location according to the probability density function as an organ deformation. The stochastic dose for the CTV was calculated as the mean dose at the location through changing the voxel location randomly 1000 times. In the EE approach, the underdose region in the CTV was delineated and optimized with higher dose constraints that resulted in an edge-enhanced intensity beam to the CTV. This was compared to a planning target volume (PTV) margin (PM) approach in which a CTV to PTV margin equivalent to the magnitude of organ deformation was added to obtain an optimized dose distribution. The total monitor units, number of segments, and conformity index were compared between the two approaches, and the dose based on the organ deformation of the CTV, rectum, and bladder was evaluated.
The total monitor units, number of segments, and conformity index were significantly lower with the EE approach than with the PM approach, while maintaining the dose coverage to the CTV with organ deformation. The dose to the rectum and bladder were significantly reduced in the EE approach compared with the PM approach. We conclude that the EE approach is superior to the PM with regard to intrafraction organ deformation. Citation: Sumida I, Yamaguchi H, Das IJ, Anetai Y, Kizaki H, Aboshi K, et al. (2017) Robust plan optimization using edge-enhanced intensity for intrafraction organ deformation in prostate intensity-modulated radiation therapy.
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PLoS ONE 12(3): e0173643. Editor: Qinghui Zhang, North Shore Long Island Jewish Health System, UNITED STATES Received: December 10, 2016; Accepted: February 23, 2017; Published: March 10, 2017 Copyright: © 2017 Sumida et al. This is an open access article distributed under the terms of the, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: All relevant data are within the paper. Funding: The authors received no specific funding for this work. Competing interests: The authors have declared that no competing interests exist.
Introduction Intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy are commonly used for the treatment of prostate cancer due to their superior dose conformality to the target and sparing of normal tissues such as the rectum and bladder when compared to three-dimensional (3D) conformal radiotherapy. To create the planning target volume (PTV), the clinical target volume (CTV) delineated by a physician is expanded to incorporate a setup margin based on the setup error and an internal margin for intrafraction organ motion. Treatment planners take account of the dose constraints in both the target and normal tissues to ensure a satisfactory dose distribution and clinically relevant dose–volume indices. However, even when this is achieved successfully, it may not always be optimal, as described by Roy et al. Even when the required indices can be satisfied within the predefined constraints, it is preferable to keep the dose to normal tissues as low as possible. Several approaches have been proposed for minimizing the dose to normal tissues while ensuring the prescribed dose coverage for the target; these include the individualized margin , anisotropic margin , , and zero-PTV-margin. These margin approaches take into consideration the interfraction motion at setup as well as intrafraction organ motion during the irradiation.
Organ motion can blur the dose distribution at the beam edge , resulting in an underdose in peripheral regions of the target, and so another technique has been proposed using edge-enhanced (EE) intensity maps with a combination of margins. Either the margin or the EE technique can be used to address the underdose and compensate the dose distribution. For dose evaluation regions with relatively homogeneous density, such as the pelvic region, the static dose cloud approximation described by Craig et al.
may be useful for estimating the dose distribution, including interfraction and intrafraction organ motion. This approximation makes it possible to estimate the dose under organ motion and deformation by considering the organ elements (voxels) to be moving within a static dose cloud distribution –. The organ motion is represented by a probability density function (PDF) applied to the voxel elements in each organ. Trofimov et al.
have presented a stochastic “motion kernel” approach for 4D IMRT optimization for lung and liver cancer to compensate for the dose-blurring effect due to organ motion. The target trajectory in the superior–inferior (SI) direction is obtained using 4D computed tomography (CT) datasets and used to create the PDF, which is applied to all parts of the patient’s anatomy. The authors concluded that this approach did not provide a dosimetric advantage compared to tracking or gating approaches, but that it could result in more efficient delivery. In prostate cancer treatment, random variations of the rectum and bladder during radiotherapy have been reported, with variable motion pattern and size. Intrafraction organ motion has been investigated for the evaluation of dose distribution to the prostate, and there have been a few reports about intrafraction tumor deformation in which a tumor deformation tracking system was achieved via a dynamic multileaf collimator approach. In the present study, we applied a different approach using an EE technique in the treatment planning process to account for intrafraction tumor deformation.
This study was based on a simulation of the dose distribution calculated by the treatment planning system (TPS), focusing on the dosimetric effect in the presence of random organ deformation without the patient setup error. Using this approach, the PDF could be applied to each voxel in each organ. The purpose of this study was to create a treatment plan for prostate IMRT using an EE intensity map to address the dose-blurring effect caused by organ deformation, and to compare this approach with the commonly used PTV-margin (PM) approach. Materials and methods The analysis included the data for 37 prostate cancer patients who were treated with fixed-gantry step-and-shoot IMRT using a 10-mm multileaf collimator leaf width. This retrospective study was approved by the local ethics committee at NTT West Osaka hospital. All participants provide their written informed consent to participate in this study, and their analyzed data are anonymized. A beam energy of 10 MV was generated by an X-ray machine equipped with a linear accelerator (ONCOR Impression Plus; Siemens Medical Systems, Concord, CA).
CT images with a slice thickness of 2.5 mm were acquired under free breathing with a VacLok fixation cushion (CIVCO Medical Solutions, Orange City, IA) using a GE BrightSpeed CT scanner (GE Medical Systems, Milwaukee, WI). A CTV including the prostate gland and proximal seminal vesicle was delineated by a radiation oncologist. After the rectum and bladder were delineated as normal tissue, a medical physicist optimized the dose distribution using a XiO treatment planning system (Elekta Instrument AB, Stockholm, Sweden). The prescription dose was 78 Gy in 39 fractions to the CTV D 95% (the dose received by 95% of the volume of the CTV). The dose constraints for the rectum and bladder were adapted from reference , in which the percentage volumes receiving 65 Gy and 40 Gy (V 65Gy and V 40Gy) in the rectum should be less than 17% and 35%, respectively, and in the bladder less than 25% and 50%, respectively. Creation of the de-blurring dose distribution It was assumed in this study that the patient setup error would be perfectly corrected in each treatment fraction by image guidance in both EE and PM approaches, which resulted in the translation errors of zero, and thus, no setup margin was used; we, therefore, considered only the intrafraction organ deformation for the treatment plan over the treatment fractions. The treatment planning processes following the EE and PM approaches are presented in.
First, for the EE approach, the optimized dose distribution to the CTV with no internal margin and to the rectum and bladder without intrafraction organ deformation was necessary before creation of edge-enhanced intensity. The dose constraints were in accordance with the dose constraints specified in the previous section. The optimized dose distribution is shown in. Next, the DICOM RT files including the plan, structure set, and dose were then exported. The resolution of the dose grid was 2 mm. The dose distribution at this time point is referred to as the static dose distribution (D stat).
These files were imported into our in-house software developed using Delphi2007 (Borland Software Corporation, Austin, TX), which can create a probability dose distribution to each voxel in each organ based on the motion PDF. It was assumed that the motion PDF has three components, including axes of motion in the left–right (LR), anterior–posterior (AP), and superior–inferior (SI) directions, and the motion probability was based on the normal distribution with a standard deviation. The magnitudes of intrafraction motion for the CTV , rectum , and bladder in the three axes (SI, LR, and AP) were used in the reports in the respective references and are summarized in. The values given for the CTV and rectum are two standard deviations, and those for the bladder are maximums. Because of the central limit theorem , even when motion probability presents a non-uniform distribution, after many fractions the ultimate probability distribution will converge towards a Gaussian shape. Although the presented deviations are derived from the intrafraction organ motion for the organs, in this study these values were referred to as, and assumed to be, the magnitude of the organ deformation.
The treatment planning process for dose evaluation as applied in the edge-enhanced and planning target volume (PTV)-margin approaches. For the edge-enhanced approach, dose optimization to the clinical target volume (CTV) with no spatial margin was applied, followed by the creation of blurred dose distribution. The underdose region within the CTV was calculated, and the manual delineation was performed on the TPS according to the region. Re-optimization was performed to create the edge-enhanced dose distribution. In contrast, for the PTV-margin approach, dose optimization to the PTV with margin was applied.
Finally, the two planned dose distributions derived from the edge-enhanced and PTV-margin approaches were blurred and compared for evaluation. The dose distributions: a) optimized for the clinical target volume (CTV) with no internal margin before applying the edge-enhanced approach; b) blurred only to CTV derived from a); c) the subtraction image derived from a) and b); d) the edge-enhanced approach created by re-optimization with 5% scaled up the lower dose constraint to the CTV via simultaneous integrated boost technique; and e) the planning target volume (PTV)-margin approach created by optimization to the PTV with margin. In c), the color bar represents the range of 5% dose difference. Magnitudes of intrafraction organ deformation in the three directions for the clinical target volume (CTV), rectum, and bladder. In order to calculate the stochastic dose for the CTV (D stoc) in the presence of intrafraction organ deformation, the location of the dose grid in D stat was changed 1000 times to fulfill the normal distribution criterion as expressed in Eq.
(1) where D stoc( x, y, z) is the mean value of the stochastic dose at location ( x, y, z), which is the same as the DICOM RT-dose grid, and, and are the probable i-th shifts in location in the LR, AP, and SI directions, respectively, with the locations changed 1000 times randomly (based on the normal distribution). The coordinates x, y, and z refer to the LR, AP, and SI directions, respectively. Because the probable shift location is not identical to the dose grid location, 3D linear interpolation was applied to calculate the stochastic dose that resulted in the blurred dose for the CTV shown in. Based on the blurred dose distribution D stoc for the CTV, the underdose region (shown in ) calculated by the subtraction of two dose distributions (D stoc–D stat) that received a dose 5% lower than the prescribed dose was delineated manually in the TPS. The dose was then re-optimized to create the EE dose distribution shown in for that region in the CTV accompanied the 5% scaled up of the lower dose constraint, which is the same as that by the simultaneous integrated boost technique , indicating that the dosimetric margin of 5% scaled up of the lower dose constraint was applied to the CTV instead of the spatial margin, i.e., internal margins. The dose constraints were not changed for the rectum and bladder.
The optimized EE dose shown in is referred to as D edge. Dose under intrafraction organ deformation Under the EE dose delivery approach, we evaluated the dosimetric effect for the CTV, rectum, and bladder that resulted from the intrafraction organ deformation. The motion PDF based on the magnitudes of motion presented in was applied to each dose grid in the organ using Eq. To allow a comparison with the PM technique , the PTV was created in the TPS by adding margins of 6, 8, and 6 mm in the LR, AP, and SI directions, respectively.
Again, the size of these margins was 2 SD of the random prostate motion, with no setup error. The same target dose constraint was used for the PTV but not for the CTV; again, the dose constraints were not changed for the rectum and bladder. The prescription dose was consistent with the specified 78 Gy in 39 fractions to the CTV D 95%. Finally, the dose distribution (D PM) was optimized. We investigated the following two questions, which focused on the CTV and the normal tissues. With the EE dose delivered under intrafraction organ deformation to the CTV, would the dosimetric parameters described earlier be comparable with those for the PM approach? Sonic rivals 2 free play.
With the EE dose delivered under intrafraction organ deformation to the normal tissues, how would the high-dose region derived from the EE approach deliver to the rectum and bladder, and would the doses be increased or decreased compared with those of the PM approach? The anterior side of the rectum and the inferior side of the bladder are close to the CTV. Initially, the total monitor units and the number of segments were compared between the planned doses D edge and D PM. The blurred doses D edge blur and D PM blur that accompanied the intrafraction organ deformation were then simulated using the following Eqs and. The probable shift amount was the same as in Eq and referred to in.
(2) (3) The following dose–volume indices were calculated for the comparisons of D edge blur and D PM blur: the generalized equivalent uniform dose (gEUD) in Gy, the homogeneity index (HI), and the conformity index (CI) for the CTV. HI is defined as (D 2% − D 98%)/D 50%, as discussed in ICRU Report 83. The CI is defined in ICRU Report 50 as the ratio of the volume receiving the prescribed dose to the volume of the PTV.
In this study, we evaluated the CI for the CTV instead of the PTV because of no PTV in the evaluated dose for D edge. Thus, the CI was calculated for the planned doses D edge and D PM. The gEUD, V 65Gy, and V 40Gy were calculated for the rectum and bladder. The gEUD was calculated for each organ using Niemierko’s phenomenological formula given by the following equation: (4) where N is the number of voxels in each organ and a is the tumor- or normal tissue-specific dose–volume effect parameter.
For radiobiological evaluation, the tumor control probability (TCP) was calculated using Niemierko’s EUD-based model given by the following equation: (5) where EUD is the gEUD for the CTV, TCD 50 is the dose required to achieve 50% TCP, and γ50 is the normalized tumor dose–response slope at TCD 50. The individual voxel NTCP (P) was calculated using the relative seriality model given by the following equation: (6) where D i is the dose delivered to the i-th voxel, D 50 is the dose required to achieve 50% NTCP, and γ50 is the normalized normal tissue dose–response slope at D 50. The following equation was used to calculate NTCP for the organ, incorporating the functional architecture of relative seriality: (7) where n is the number of sub-volumes in the organ, s is the relative seriality factor, which ranges between 1 for serial organs and 0 for parallel organs, and Δ v i is defined as v i/ V, where v i denotes the sub-volume in the differential dose–volume histogram and V denotes the total volume of the organ.
These parameters were used to calculate TCP and NTCP with the endpoints in each structure summarized in. Comparison of total monitor units, the number of segments, and the conformity index in the plans created using the edge-enhanced approach and PTV-margin approach for 37 prostate cancer patients. The dose–volume parameters and radiobiological indices in the CTV, rectum, and bladder for the EE and PM approaches are summarized in.
These were calculated for D edge blur and D PM blur. For the CTV, gEUD with the EE approach was 79.26 Gy, which was significantly smaller than that with the PM approach ( p. Dose–volume parameters and radiobiological indices for the edge-enhanced approach and PTV-margin approach under intrafraction organ deformation. For the normal tissues, V 65Gy and V 40Gy for both approaches achieved the predefined dose constraints. For the rectum, V 65Gy and V 40Gy with the EE approach were significantly smaller than those with the PM approach ( p. Conclusions Intrafraction organ deformation can be taken into account by incorporating the probability density function into the treatment planning process to ensure a robust dose distribution. In this study, the edge-enhanced technique was compared with the PTV-margin technique with regard to dosimetric and radiobiological parameters.
The edge-enhanced technique resulted in superior dose reduction for the normal tissue while maintaining the dose coverage for the CTV, as well as reducing monitor units and the number of segments. The spatial margin with respect to the internal organ motion might be replaced with the dosimetric margin used in the edge-enhanced technique. A view of the dosimetric margin will support the robust treatment plan.
Abstract There has been increasing interest in the research on flavonoids from plant sources because of their versatile health benefits reported in various epidemiological studies. Since flavonoids are directly associated with human dietary ingredients and health, there is need to evaluate structure and function relationship. The bioavailability, metabolism, and biological activity of flavonoids depend upon the configuration, total number of hydroxyl groups, and substitution of functional groups about their nuclear structure. Fruits and vegetables are the main dietary sources of flavonoids for humans, along with tea and wine. Most recent researches have focused on the health aspects of flavonoids for humans. Many flavonoids are shown to have antioxidative activity, free radical scavenging capacity, coronary heart disease prevention, hepatoprotective, anti-inflammatory, and anticancer activities, while some flavonoids exhibit potential antiviral activities.
In plant systems, flavonoids help in combating oxidative stress and act as growth regulators. For pharmaceutical purposes cost-effective bulk production of different types of flavonoids has been made possible with the help of microbial biotechnology. This review highlights the structural features of flavonoids, their beneficial roles in human health, and significance in plants as well as their microbial production.