A Novel Definition of Equivalent Uniform Dose Based on Volume Dose Curve

© 2013 IEEE. With the improvement of mobile device performance, the requirement of equivalent dose description in intensity-modulated radiation therapy is increasing in mobile multimedia for healthcare. The emergence of mobile cloud computing will provide cloud servers and storage for intensity-modulated radiotherapy (IMRT) mobile applications, thus realizing visualized radiotherapy in a real sense. Equivalent uniform dose (EUD) is a biomedical indicator based on the dose measure. In this paper, the dose volume histogram is used to describe the dose distribution of different tissues in target and nontarget regions. The traditional definition of EUD, such as the exponential form and the linear form, has only a few parameters in the model for fast calculation. However, there is no close relationship between this traditional definition and the dose volume histogram. In order to establish the consistency between the EUD and the dose volume histogram, this paper proposes a novel definition of EUD based on the volume dose curve, called VD-EUD. By using a unique organic volume weight curve, it is easy to calculate VD-EUD for different dose distributions. In definition, different weight curves are used to represent the biological effects of different organs. For the target area, we should be more careful about those voxels with a low dose (cold point); thus, the weight curve is monotonically decreasing. While for the nontarget area, the curve is monotonically increasing. Furthermore, we present the curves for parallel, serial, and mixed organs of nontarget areas separately, and we define the weight curve form with only two parameters. Medical doctors can adjust the curve interactively according to different patients and organs. We also propose a fluence map optimization model with the VD-EUD constraint, which means that the proposed EUD constraint will lead to a large feasible solution space. We compare the generalized EUD (gEUD) and the proposed VD-EUD by experiments, which show that the VD-EUD has a closer relationship with the dose volume histogram. If the biological survival probability is equivalent to the VD-EUD, the feasible solution space would be large, and the target areas can be covered. By establishing a personalized organic weight curve, medical doctors can have a unique VD-EUD for each patient. By using the flexible and adjustable EUD definition, we can establish the VD-EUD-based fluence map optimization model, which will lead to a larger solution space than the traditional dose volume constraint-based model. The VD-EUD is a new definition; thus, we need more clinical testing and verification

Определение ожидаемой эффективности лучевого лечения злокачественных новообразований области головы и шеи на основе эквивалентной однородной дозы

В данной работе анализируется ожидаемая эффективность лечения для рака области головы и шеи. На основе таких параметров, как TCP (tumor control probability), NTCP (normal tissue complication probability), EUD (equivalent uniform dose) и DVH (dose-volume histogram) было проведено сравнение предсказанных и полученных результатов, а также анализ влияния значений данных величин на исход лечения.In the paper expected effectiveness of treatment head-and-neck cancer is analyzed. Based on such parameters as TCP (tumor control probability), NTCP (normal tissue complication probability), EUD (equivalent uniform dose) and DVH (dose-volume histogram) comparison of predicted and obtained results was provided. Also paper contains analysis of the influence of these values on the outcomes of treatment

Gastrointestinal Toxicity Prediction Not Influenced by Rectal Contour or Dose-Volume Histogram Definition.

PURPOSE: Rectal dose delivered during prostate radiation therapy is associated with gastrointestinal toxicity. Treatment plans are commonly optimized using rectal dose-volume constraints, often whole-rectum relative-volumes (%). We investigated whether improved rectal contouring, use of absolute-volumes (cc), or rectal truncation might improve toxicity prediction. METHODS AND MATERIALS: Patients from the CHHiP trial (receiving 74 Gy/37 fractions [Fr] vs 60 Gy/20 Fr vs 57 Gy/19 Fr) were included if radiation therapy plans were available (2350/3216 patients), plus toxicity data for relevant analyses (2170/3216 patients). Whole solid rectum relative-volumes (%) dose-volume-histogram (DVH), as submitted by treating center (original contour), was assumed standard-of-care. Three investigational rectal DVHs were generated: (1) reviewed contour per CHHiP protocol; (2) original contour absolute volumes (cc); and (3) truncated original contour (2 versions; ±0 and ±2 cm from planning target volume [PTV]). Dose levels of interest (V30, 40, 50, 60, 70, 74 Gy) in 74 Gy arm were converted by equivalent-dose-in-2 Gy-Fr (EQD2α/β= 3 Gy) for 60 Gy/57 Gy arms. Bootstrapped logistic models predicting late toxicities (frequency G1+/G2+, bleeding G1+/G2+, proctitis G1+/G2+, sphincter control G1+, stricture/ulcer G1+) were compared by area-undercurve (AUC) between standard of care and the 3 investigational rectal definitions. RESULTS: The alternative dose/volume parameters were compared with the original relative-volume (%) DVH of the whole rectal contour, itself fitted as a weak predictor of toxicity (AUC range, 0.57-0.65 across the 8 toxicity measures). There were no significant differences in toxicity prediction for: (1) original versus reviewed rectal contours (AUCs, 0.57-0.66; P = .21-.98); (2) relative- versus absolute-volumes (AUCs, 0.56-0.63; P = .07-.91); and (3) whole-rectum versus truncation at PTV ± 2 cm (AUCs, 0.57-0.65; P = .05-.99) or PTV ± 0 cm (AUCs, 0.57-0.66; P = .27-.98). CONCLUSIONS: We used whole-rectum relative-volume DVH, submitted by the treating center, as the standard-of-care dosimetric predictor for rectal toxicity. There were no statistically significant differences in prediction performance when using central rectal contour review, with the use of absolute-volume dosimetry, or with rectal truncation relative to PTV. Whole-rectum relative-volumes were not improved upon for toxicity prediction and should remain standard-of-care

Dose volume histogram‐based optimization of image reconstruction parameters for quantitative 90Y‐PET imaging

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147185/1/mp13269.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147185/2/mp13269_am.pd

Analisis Kurva Dose Volume Histogram (DVH) pada Teknik 3D Konformal dengan Metode Monte Carlo

Pemilihan sudut penyinaran yang tepat dalam terapi 3D konformal beberapa jenis kanker sangat menentukan keberhasilan pengobatan. Oleh karena itu, tujuan penelitian ini adalah untuk menganalisis dose volume histogram (DVH) teknik 3D konformal dengan konfigurasi sudut penyinaran yang berbeda pada fantom inhomogenitas dengan metode Monte Carlo (MC). EGSnrc-DOSXYZnrc MC digunakan untuk menyimulasikan teknik 3D konformal pada fantom inhomogenitas. Fantom inhomogenitas terdiri atas material air dan paru-paru dimana material paru-paru berada di dalam fantom air pada kedalaman 2 cm dari permukaan fantom air. Fantom ini diradiasi dengan sumber radiasi monoenergetik 10 MeV dengan sudut penyinaran 0 – 360o. Data distribusi dosis yang diperoleh diolah untuk memperoleh data DVH. Analisis DVH juga dilakukan dengan mengkombinasikan beberapa sudut penyinaran dan pembobotan. Hasil yang diperoleh menunjukkan bahwa distribusi dosis hasil simulasi beragam terhadap sudut penyinaran. Dari kurva DVH diperoleh bahwa sudut penyinaran pada 0o, 20o, 40o, 320o, dan 340o dengan pembobotan memberikan kurva DVH target yang paling baik dibandingkan dengan set-up sudut penyinaran lainnya. Pembobotan dapat mereduksi dosis pada resiko organ dan meningkatkan dosis pada target

Dosimetric comparison study between intensity modulated radiation therapy and three-dimensional conformal proton therapy for pelvic bone marrow sparing in the treatment of cervical cancer.

The objective was to compare intensity-modulated radiation therapy (IMRT) with 3D conformal proton therapy (3DCPT) in the treatment of cervical cancer. In particular, each technique's ability to spare pelvic bone marrow (PBM) was of primary interest in this study. A total of six cervical cancer patients (3 postoperative and 3 intact) were planned and analyzed. All plans had uniform 1.0 cm CTV-PTV margin and satisfied the 95% PTV with 100% isodose (prescription dose = 45 Gy) coverage. Dose-volume histograms (DVH) were analyzed for comparison. The overall PTV and PBM volumes were 1035.9 ± 192.2 cc and 1151.4 ± 198.3 cc, respectively. In terms of PTV dose conformity index (DCI) and dose homogeneity index (DHI), 3DCPT was slightly superior to IMRT with 1.00 ± 0.001, 1.01 ± 0.02, and 1.10 ± 0.02, 1.13 ± 0.01, respectively. In addition, 3DCPT demonstrated superiority in reducing lower doses (i.e., V30 or less) to PBM, small bowel and bladder. Particularly in PBM, average V10 and V20 reductions of 10.8% and 7.4% (p = 0.001 and 0.04), respectively, were observed. However, in the higher dose range, IMRT provided better sparing (> V30). For example, in small bowel and PBM, average reductions in V45 of 4.9% and 10.0% (p = 0.048 and 0.008), respectively, were observed. Due to its physical characteristics such as low entrance dose, spread-out Bragg peak and finite particle range of protons, 3DCPT illustrated superior target coverage uniformity and sparing of the lower doses in PBM and other organs. Further studies are, however, needed to fully exploit the benefits of protons for general use in cervical cancer

Explicit optimization of plan quality measures in intensity-modulated radiation therapy treatment planning

Conventional planning objectives in optimization of intensity-modulated radiotherapy treatment (IMRT) plans are designed to minimize the violation of dose-volume histogram (DVH) thresholds using penalty functions. Although successful in guiding the DVH curve towards these thresholds, conventional planning objectives offer limited control of the individual points on the DVH curve (doses-at-volume) used to evaluate plan quality. In this study, we abandon the usual penalty-function framework and propose planning objectives that more explicitly relate to DVH statistics. The proposed planning objectives are based on mean-tail-dose, resulting in convex optimization. We also demonstrate how to adapt a standard optimization method to the proposed formulation in order to obtain a substantial reduction in computational cost. We investigate the potential of the proposed planning objectives as tools for optimizing DVH statistics through juxtaposition with the conventional planning objectives on two patient cases. Sets of treatment plans with differently balanced planning objectives are generated using either the proposed or the conventional approach. Dominance in the sense of better distributed doses-at-volume is observed in plans optimized within the proposed framework, indicating that the DVH statistics are better optimized and more efficiently balanced using the proposed planning objectives

RadOnc: An R Package for Analysis of Dose-Volume Histogram and Three-Dimensional Structural Data

Purpose/Objectives: Dose volume histogram (DVH) data are generally analyzed within the context of a treatment planning system (TPS) on a per-patient basis, with evaluation of single-plan or comparative dose distributions. However, TPS software generally cannot perform simultaneous comparative dosimetry among a cohort of patients. The same limitations apply to parallel analyses of three-dimensional structures and other clinical data. Materials/Methods: We developed a suite of tools ("RadOnc" package) using R statistical software to better compare pooled DVH data and empower analysis of structure data and clinical correlates. Representative patient data were identified among previously analyzed adult (n=13) and pediatric (n=1) cohorts and these data were used to demonstrate the performance and functionality of the RadOnc package. Results: The RadOnc package facilitates DVH data import from the TPS and includes automated methods for DVH visualization, dosimetric parameter extraction, statistical comparison among multiple DVHs, basic three-dimensional structural processing, and visualization tools to enable customizable production of publication-quality images. Conclusions: The RadOnc package provides a potent clinical research tool with the ability to integrate robust statistical software and dosimetric data from cohorts of patients. It is made freely available to the community for their current use and remains under active development

A dose-volume histogram based decision-support system for dosimetric comparison of radiotherapy treatment plans

Background: The choice of any radiotherapy treatment plan is usually made after the evaluation of a few preliminary isodose distributions obtained from different beam configurations. Despite considerable advances in planning techniques, such final decision remains a challenging task that would greatly benefit from efficient and reliable assessment tools. Methods: For any dosimetric plan considered, data on dose-volume histograms supplied by treatment planning systems are used to provide estimates on planning target coverage as well as on sparing of organs at risk and the remaining healthy tissue. These partial metrics are then combined into a dose distribution index (DDI), which provides a unified, easy-to-read score for each competing radiotherapy plan. To assess the performance of the proposed scoring system, DDI figures for fifty brain cancer patients were retrospectively evaluated. Patients were divided in three groups depending on tumor location and malignancy. For each patient, three tentative plans were designed and recorded during planning, one of which was eventually selected for treatment. We thus were able to compare the plans with better DDI scores and those actually delivered. Results: When planning target coverage and organs at risk sparing are considered as equally important, the tentative plan with the highest DDI score is shown to coincide with that actually delivered in 32 of the 50 patients considered. In 15 (respectively 3) of the remaining 18 cases, the plan with highest DDI value still coincides with that actually selected, provided that organs at risk sparing is given higher priority (respectively, lower priority) than target coverage. Conclusions: DDI provides a straightforward and non-subjective tool for dosimetric comparison of tentative radiotherapy plans. In particular, DDI readily quantifies differences among competing plans with similar-looking dose-volume histograms and can be easily implemented for any tumor type and localization, irrespective of the planning system and irradiation technique considered. Moreover, DDI permits to estimate the dosimetry impact of different priorities being assigned to sparing of organs at risk or to better target coverag