Predicting radiation pneumonitis in lung cancer: a EUD-based machine learning approach for volumetric modulated arc therapy patients.

Purpose: This study aims to develop an optimal machine learning model that uses lung equivalent uniform dose (lung EUD to predict radiation pneumonitis (RP) occurrence in lung cancer patients treated with volumetric modulated arc therapy (VMAT). Methods: We analyzed a cohort of 77 patients diagnosed with locally advanced squamous cell lung cancer (LASCLC) receiving concurrent chemoradiotherapy with VMAT. Patients were categorized based on the onset of grade II or higher radiation pneumonitis (RP 2+). Dose volume histogram data, extracted from the treatment planning system, were used to compute the lung EUD values for both groups using a specialized numerical analysis code. We identified the parameter α, representing the most significant relative difference in lung EUD between the two groups. The predictive potential of variables for RP2+, including physical dose metrics, lung EUD, normal tissue complication probability (NTCP) from the Lyman-Kutcher-Burman (LKB) model, and lung EUD-calibrated NTCP for affected and whole lung, underwent both univariate and multivariate analyses. Relevant variables were then employed as inputs for machine learning models: multiple logistic regression (MLR), support vector machine (SVM), decision tree (DT), and K-nearest neighbor (KNN). Each model's performance was gauged using the area under the curve (AUC), determining the best-performing model. Results: The optimal α-value for lung EUD was 0.3, maximizing the relative lung EUD difference between the RP 2+ and non-RP 2+ groups. A strong correlation coefficient of 0.929 (P< 0.01) was observed between lung EUD (α = 0.3) and physical dose metrics. When examining predictive capabilities, lung EUD-based NTCP for the affected lung (AUC: 0.862) and whole lung (AUC: 0.815) surpassed LKB-based NTCP for the respective lungs. The decision tree (DT) model using lung EUD-based predictors emerged as the superior model, achieving an AUC of 0.98 in both training and validation datasets. Discussions: The likelihood of developing RP 2+ has shown a significant correlation with the advancements in RT technology. From traditional 3-D conformal RT, lung cancer treatment methodologies have transitioned to sophisticated techniques like static IMRT. Accurately deriving such a dose-effect relationship through NTCP modeling of RP incidence is statistically challenging due to the increased number of degrees-of-freedom. To the best of our knowledge, many studies have not clarified the rationale behind setting the α-value to 0.99 or 1, despite the closely aligned calculated lung EUD and lung mean dose MLD. Perfect independence among variables is rarely achievable in real-world scenarios. Four prominent machine learning algorithms were used to devise our prediction models. The inclusion of lung EUD-based factors substantially enhanced their predictive performance for RP 2+. Our results advocate for the decision tree model with lung EUD-based predictors as the optimal prediction tool for VMAT-treated lung cancer patients. Which could replace conventional dosimetric parameters, potentially simplifying complex neural network structures in prediction models.

Fractionation versus Adaptation for Compensation of Target Volume Changes during Online Adaptive Radiotherapy for Bladder Cancer: Answers from a Prospective Registry.

Online adaptive radiotherapy (ART) allows adaptation of the dose distribution to the anatomy captured by with pre-adaptation imaging. ART is time-consuming, and thus intra-fractional deformations can occur. This prospective registry study analyzed the effects of intra-fraction deformations of clinical target volume (CTV) on the equivalent uniform dose (EUDCTV) of focal bladder cancer radiotherapy. Using margins of 5-10 mm around CTV on pre-adaptation imaging, intra-fraction CTV-deformations found in a second imaging study reduced the 10th percentile of EUDCTV values per fraction from 101.1% to 63.2% of the prescribed dose. Dose accumulation across fractions of a series was determined with deformable-image registration and worst-case dose accumulation that maximizes the correlation of cold spots. A strong fractionation effect was demonstrated-the EUDCTV was above 95% and 92.5% as determined by the two abovementioned accumulation methods, respectively, for all series of dose fractions. A comparison of both methods showed that the fractionation effect caused the EUDCTV of a series to be insensitive to EUDCTV-declines per dose fraction, and this could be explained by the small size and spatial variations of cold spots. Therefore, ART for each dose fraction is unnecessary, and selective ART for fractions with large inter-fractional deformations alone is sufficient for maintaining a high EUDCTV for a radiotherapy series.

Effective optimization strategy for large optimization volume object, remaining volume at risk (RVR):α-value selection and usage from generalized equivalent uniform dose (gEUD) curve deviation perspective.

Objective.A large optimization volume for intensity-modulated radiation therapy (IMRT), such as the remaining volume at risk (RVR), is traditionally unsuitable for dose-volume constraint control and requires planner-specific empirical considerations owing to the patient-specific shape. To enable less empirical optimization, the generalized equivalent uniform dose (gEUD) optimization is effective; however, the utilization of parametera-values remains elusive. Our study clarifies thea-value characteristics for optimization and to enable effectivea-value use.Approach.The gEUD can be obtained as a function of itsa-value, which is the weighted generalized mean; its curve has a continuous, differentiable, and sigmoid shape, deforming in its optimization state with retained curve characteristics. Using differential geometry, the gEUD curve changes in optimization is considered a geodesic deviation intervened by the forces between deforming and retaining the curve. The curvature and gradient of the curve are radically related to optimization. The vertex point (a=ak) was set and thea-value roles were classified into the following three parts of the curve with respect to thea-value: (i) high gradient and middle curvature, (ii) middle gradient and high curvature, and (iii) low gradient and low curvature. Then, a strategy for multiplea-values was then identified using RVR optimization.Main results.Eleven head and neck patients who underwent static seven-field IMRT were used to verify thea-value characteristics and curvature effect for optimization. The lowera-value (i) (a= 1-3) optimization was effective for the whole dose-volume range; in contrast, the effect of highera-value (iii) (a= 12-20) optimization addressed strongly the high-dose range of the dose volume. The middlea-value (ii) (arounda=ak) showed intermediate but effective high-to-low dose reduction. Thesea-value characteristics were observed as superimpositions in the optimization. Thus, multiple gEUD-based optimization was significantly superior to the exponential constraints normally applied to the RVR that surrounds the PTV, normal tissue objective (NTO), resulting in up to 25.9% and 8.1% improvement in dose-volume indices D2% and V10Gy, respectively.Significance.This study revealed an appropriatea-value for gEUD optimization, leading to favorable dose-volume optimization for the RVR region using fixed multiplea-value conditions, despite the very large and patient-specific shape of the region.

Value of generalized equivalent uniform dose optimization in radiotherapy for chest malignant tumors / 中国辐射卫生

Objective To explore the value of generalized equivalent uniform dose (gEUD) optimization in radiotherapy for chest malignant tumors. Methods Sixty patients with chest malignant tumors who were treated in Center for Tumor Radiotherapy, Chizhou Municipal People’s Hospital, Anhui Province, China from October 2021 to June 2022 were enrolled; each patient underwent tumor localization with a conventional fixed computed tomography scan. The patients were divided into two groups using the same field direction and weight in the Varian Eclipse 15.6 planning system. The first group was planned using the conventional physical dose-volume objective function plus the Upper gEUD objective function, with organs at risks (OARs) optimized with the EUD values suggested by the Varian Eclipse 15.6 planning system. The second group only adopted the conventional physical dose-volume objective function for OARs optimization. The two groups were compared for the radiation doses delivered to the OARs. Results Compared with the conventional physical dose-volume objective function alone, the addition of Upper gEUD objective function resulted in no significant difference in lung V5Gy, but resulted in significant reductions in V20Gy and mean dose in the lungs; some reductions in V30Gy, V40Gy, and mean dose in the heart; and significant reductions in the maximum dose in the spinal cord. Conclusion The gEUD objective optimization can effectively protect the normal tissue in the radiotherapy for chest malignant tumors and thus is recommended in radiotherapy planning.

Dose volume histogram prediction method for organ at risk in VMAT planning of nasopharyngeal carcinoma based on equivalent uniform dose / 中华放射肿瘤学杂志

Objective:To evaluate the practicability of dose volume histogram (DVH) prediction model for organ at risk (OAR) of radiotherapy plan by minimizing the cost function based on equivalent uniform dose (EUD).Methods:A total of 66 nasopharyngeal carcinoma (NPC) patients received volume rotational intensity modulated arc therapy (VMAT) at Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences from 2020 to 2021 were retrospectively selected for this study. Among them, 50 patients were used to train the recurrent neutral network (RNN) model and the remaining 16 cases were used to test the model. DVH prediction model was constructed based on RNN. A three-dimensional equal-weighted 9-field conformal plan was designed for each patient. For each OAR, the DVHs of individual fields were acquired as the model input, and the DVH of VMAT plan was regarded as the expected output. The prediction error obtained by minimizing EUD-based cost function was employed to train the model. The prediction accuracy was characterized by the mean and standard deviation between predicted and true values. The plan was re-optimized for the test cases based on the DVH prediction results, and the consistency and variability of the EUD and DVH parameters of interest (e.g., maximum dose for serial organs such as the spinal cord) were compared between the re-optimized plan and the original plan of OAR by the Wilcoxon paired test and box line plots.Results:The neural network obtained by training the cost function based on EUD was able to obtain better DVH prediction results. The new plan guided by the predicted DVH was in good agreement with the original plan: in most cases, the D 98% in the planning target volume (PTV) was greater than 95% of the prescribed dose for both plans, and there was no significant difference in the maximum dose and EUD in the brainstem, spinal cord and lens (all P>0.05). Compared with the original plan, the average reduction of optic chiasm, optic nerves and eyes in the new plans reached more than 1.56 Gy for the maximum doses and more than 1.22 Gy for EUD, and the average increment of temporal lobes reached 0.60 Gy for the maximum dose and 0.30 Gy for EUD. Conclusion:The EUD-based loss function improves the accuracy of DVH prediction, ensuring appropriate dose targets for treatment plan optimization and better consistency in the plan quality.

Biological Evaluation of Grid versus 3D Conformal Radiotherapy in Bulky Head and Neck Cancer.

Grid radiotherapy is one of the treatment techniques applied to treat patients with advanced bulky tumors. Purpose: This study aims to estimate the difference in biological and dosimetric parameters of the grid radiotherapy technique for the treatment of bulky head and neck (H and N) tumors and compare it with conventional conformal radiotherapy. Subjects and Methods: Three-dimensional conformal and grid radiotherapy were designed by the Monaco treatment planning system (TPS). Eight bulky tumors of (H and N) cases were selected, using a single fraction 15-20 Gy. Dose-volume histogram of the tumors and organs at risk (OARs) used to calculate the equivalent uniform dose (EUD) (Gy) by Matlab program. Furthermore, dosimetric parameters of the tumors from the TPS were compared for two techniques (grid radiotherapy and the conventional conformal radiotherapy). Results: Grid attained a lower EUD (Gy) in tumors and OARs as compared to conformal therapy, as Grid principle protects about half of the tumor area from the radiation leads to less coverage of the tumor. Also, where OARs in closed with tumors and the shielding by multi-leaf (1 cm) were more effective than other techniques, lead to a decrease of radiobiological values according to its definition by Niemierko. Radiobiological results showed significant differences between the two methods, and dosimetric data obtained by the TPS for tumours for two plans were P < 0.05. Conclusions: The grid plan achieves lower values of EUDs than the conformal technique for OARs. Hence, it achieves more sparing and fewer complications for these organs.

Dosimetric differences between intensity-modulated radiotherapy based on equivalent uniform dose and dose-volume optimization in stage III non-small cell lung cancer.

OBJECTIVE: To determine the dosimetric differences between biological and physical functions of equivalent uniform dose (EUD) and dose volume (DV) therapy in patients with phase III non-small cell lung cancer. METHODS: Four different radiotherapy plans (DV+DV, DV-EUD+DV, EUD+EUD and EUD-DV+EUD) were developed for 15 patients with stage III NSCLC. To study physical function (DV+DV) the target area was optimized by introducing the conditions of biological function optimization, while the organs at risk were optimized by means of physical function (DV-EUD+DV). Biological function optimization (EUD+EUD) was performed for the target area by applying conditions of physical function optimization while biological function optimization (EUD-DV+DV) was conducted for the organs at risk to compare dosimetric parameters among the four groups of treatment plans. RESULTS: PTV: D2%, D98%, D50%, V105% and Dmax of both the DV-EUD+DV group and EDU-DV+EUD group were the minimum (P<0.05). The minimum and average dose of the EUD+EUD group showed an increasing trend and high-dose area became observable. For homogeneity index (HI), DV-EUD+DV group and EUD-DV+EUD results were compared with the other groups (P<0.05), no significant difference was observed statistically between the DV-EUD+DV group and EUD DV+EUD (P=0.659). With regard to conformability index (CI), the results of the four groups showed no significant difference (P>0.05). For the organs at risk, the mean dose of lung tissue (MLD), V5, V10, V20, V30, heart V30, V40, and Dmean also revealed no significant difference (P>0.05). For the spinal cord, the D1 % of the EUD+EUD group and EUD-DV+EUD groups were significantly different (P<0.05) than the other groups. While no significant difference (P=0.32) was found between the EUD+EUD and EUD-DV+EUD groups. When comparing the number of machine unions (MU) no significant difference was revealed (P>0.05) among the results of the 4 groups. CONCLUSION: The methods featuring optimization of physical and biological functions are effective in improving the uniformity of target area to have better outcome of the treatment. Biological function optimization or the combination of biological and physical function optimization is conducive to significantly reduce the required dose for the spinal cord.

A novel knowledge-based prediction model for estimating an initial equivalent uniform dose in semi-auto-planning for cervical cancer.

BACKGROUND: We developed a novel concept, equivalent uniform length (EUL), to describe the relationship between the generalized equivalent uniform dose (EUD) and the geometric anatomy around a tumor target. By correlating EUL with EUD, we established two EUD-EUL knowledge-based (EEKB) prediction models for the bladder and rectum that predict initial EUD values for generating quality treatment plans. METHODS: EUL metrics for the rectum and bladder were extracted and collected from the intensity-modulated radiotherapy therapy (IMRT) plans of 60 patients with cervical cancer. The two EEKB prediction models were built using linear regression to establish the relationships between EULr and EUDr (EUL and EUD of rectum) and EULb, and EUDb (EUL and EUD of bladder), respectively. The EE plans were optimized by incorporating the predicted initial EUD parameters for the rectum and bladder with the conventional pinnacle auto-planning (PAP) initial dose parameters for other organs. The efficiency of the predicted initial EUD values were then evaluated by comparing the consistency and quality of the EE plans, PAP plans (based on default PAP initial parameters), and manual plans (designed manually by different dosimetrists) for a sample of 20 patients. RESULTS: Linear regression analyses showed a significant correlation between EUL and EUD (R2 = 0.79 and 0.69 for EUDb and EUDr, respectively). In a sample of 20 patients, the average bladder V40 and V50 derived from the EE plans were significantly lower (V40: 30.00 ± 5.76, V50: 14.36 ± 4.00) than the V40 and V50 values derived from manual plans (V40: 36.03 ± 8.02, V50: 19.02 ± 5.42). Compared with the PAP plans, the EE plans produced significantly lower average V30 and Dmean values for the bladder (V30: 50.55 ± 6.33, Dmean: 31.48 ± 1.97 Gy). CONCLUSIONS: Our EEKB prediction models predicted reasonable initial EUD values for the rectum and bladder based on patient-specific geometric EUL values, thereby improving optimization and planning efficiency.

Dosimetric and radiobiological comparison in head-and-neck radiotherapy using JO-IMRT and 3D-CRT.

Introduction: Dosimetric and radiobiological evaluations for the Jaws-only Intensity-modulated radiotherapy (JO-IMRT) technique for head and neck jaws-only intensity-modulated radiation therapy (JO-IMRT) and 3D conformal radiation therapy (3D-CRT). To compare the head-and-neck therapeutic approaches utilizing JO-IMRT and 3D-CRT techniques, different radiation dose indices were calculated, including: conformity index (CI), homogeneity index (HI), and radiobiological variables like Niemierko's equivalent uniform dose based tumor control probability (TCP) of planning target volume (PTV), normal tissue complication probability (NTCP) of organs at risk (OAR) (brainstem, spinal cord, and parotid grand). Materials and methods: Twenty-five nasopharynx patients were studied using the Prowess Panther Treatment Planning System (Prowess Inc). The results were compared with the dose distribution obtained using 3D-CRT. Results: Regarding tumor coverage and CI, JO-IMRT showed better results than 3D-CRT. The average doses received by the PTVs were quite similar: 72.1 ± 0.8 Gy by 3D-CRT and 72.5 ± 0.6 Gy by JO-IMRT plans (p > 0.05). The mean doses received by the parotid gland were 56.7 ± 0.7 Gy by 3D-CRT and 26.8 ± 0.3 Gy by JO-IMRT (p > 0.05). The HI and CI were 0.13 ± 0.01 and 0.14 ± 0.05 and (p > 0.05) by 3D-CRT and 0.83 ± 0.05 and 0.73 ± 0.10 by JO-IMRT (p < 0.05). The average TCP of PTV was 0.82 ± 0.08 by 3D-CRT and 0.92 ± 0.02 by JO-IMRT. Moreover, the NTCP of the parotid glands, brain stem, and spinal cord were lower using the JO-IMRT than 3D-CRT plans. In comparison to the 3D-CRT approach, the JO-IMRT technique was able to boost dose coverage to the PTV, improve the target's CI and HI, and spare the parotid glands. This suggests the power of the JO-IMRT over 3D-CRT in head-and-neck radiotherapy.

Including Volume Effects in Biological Treatment Plan Optimization for Carbon Ion Therapy: Generalized Equivalent Uniform Dose-Based Objective in TRiP98.

We describe a way to include biologically based objectives in plan optimization specific for carbon ion therapy, beyond the standard voxel-dose-based criteria already implemented in TRiP98, research planning software for ion beams. The aim is to account for volume effects-tissue architecture-dependent response to damage-in the optimization procedure, using the concept of generalized equivalent uniform dose (gEUD), which is an expression to convert a heterogeneous dose distribution (e.g., in an organ at risk (OAR)) into a uniform dose associated with the same biological effect. Moreover, gEUD is closely related to normal tissue complication probability (NTCP). The multi-field optimization problem here takes also into account the relative biological effectiveness (RBE), which in the case of ion beams is not factorizable and introduces strong non-linearity. We implemented the gEUD-based optimization in TRiP98, allowing us to control the whole dose-volume histogram (DVH) shape of OAR with a single objective by adjusting the prescribed gEUD 0 and the volume effect parameter a, reducing the volume receiving dose levels close to mean dose when a = 1 (large volume effect) while close to maximum dose for a >> 1 (small volume effect), depending on the organ type considered. We studied the role of gEUD 0 and a in the optimization, and we compared voxel-dose-based and gEUD-based optimization in chordoma cases with different anatomies. In particular, for a plan containing multiple OARs, we obtained the same target coverage and similar DVHs for OARs with a small volume effect while decreasing the mean dose received by the proximal parotid, thus reducing its NTCP by a factor of 2.5. Further investigations are done for this plan, considering also the distal parotid gland, obtaining a NTCP reduction by a factor of 1.9 for the proximal and 2.9 for the distal one. In conclusion, this novel optimization method can be applied to different OARs, but it achieves the largest improvement for organs whose volume effect is larger. This allows TRiP98 to perform a double level of biologically driven optimization for ion beams, including at the same time RBE-weighted dose and volume effects in inverse planning. An outlook is presented on the possible extension of this method to the target.

A Dosimetric Parameter Reference Look-Up Table for GRID Collimator-Based Spatially Fractionated Radiation Therapy.

Computations of heterogeneity dose parameters in GRID therapy remain challenging in many treatment planning systems (TPS). To address this difficulty, we developed reference dose tables for a standard GRID collimator and validate their accuracy. The .decimal Inc. GRID collimator was implemented within the Eclipse TPS. The accuracy of the dose calculation was confirmed in the commissioning process. Representative sets of simulated ellipsoidal tumours ranging from 6-20 cm in diameter at a 3-cm depth; 16-cm ellipsoidal tumours at 3, 6, and 10 cm in depth were studied. All were treated with 6MV photons to a 20 Gy prescription dose at the tumour center. From these, the GRID therapy dosimetric parameters (previously recommended by the Radiosurgery Society white paper) were derived. Differences in D5 through D95 and EUD between different tumour sizes at the same depth were within 5% of the prescription dose. PVDR from profile measurements at the tumour center differed from D10/D90, but D10/D90 variations for the same tumour depths were within 11%. Three approximation equations were developed for calculating EUDs of different prescription doses for three radiosensitivity levels for 3-cm deep tumours. Dosimetric parameters were consistent and predictable across tumour sizes and depths. Our study results support the use of the developed tables as a reference tool for GRID therapy.

Treatment Planning Study for Microbeam Radiotherapy Using Clinical Patient Data.

Microbeam radiotherapy (MRT) is a novel, still preclinical dose delivery technique. MRT has shown reduced normal tissue effects at equal tumor control rates compared to conventional radiotherapy. Treatment planning studies are required to permit clinical application. The aim of this study was to establish a dose comparison between MRT and conventional radiotherapy and to identify suitable clinical scenarios for future applications of MRT. We simulated MRT treatment scenarios for clinical patient data using an inhouse developed planning algorithm based on a hybrid Monte Carlo dose calculation and implemented the concept of equivalent uniform dose (EUD) for MRT dose evaluation. The investigated clinical scenarios comprised fractionated radiotherapy of a glioblastoma resection cavity, a lung stereotactic body radiotherapy (SBRT), palliative bone metastasis irradiation, brain metastasis radiosurgery and hypofractionated breast cancer radiotherapy. Clinically acceptable treatment plans were achieved for most analyzed parameters. Lung SBRT seemed the most challenging treatment scenario. Major limitations comprised treatment plan optimization and dose calculation considering the tissue microstructure. This study presents an important step of the development towards clinical MRT. For clinical treatment scenarios using a sophisticated dose comparison concept based on EUD and EQD2, we demonstrated the capability of MRT to achieve clinically acceptable dose distributions.

Automated robust SBPT planning using EUD-based prediction of SBRT plan for patients with lung cancer.

PURPOSE: To evaluate the quality of robust stereotactic body proton therapy (RSBPT) plans generated by one-clicking scripting method for patients with lung cancer. MATERIALS AND METHODS: Retrospective analysis was performed on fifty lung cancer patients whose plan with robustly stereotactic body radiation therapy (SBRT). Thirty out of fifty patients were used for training to build a regression model, based on robust SBRT reference doses, to predict EUD values of ROIs for robust SBPT planning. Thereafter, robust SBPT plans with both automated EUD-Based mimicking (Automated Robust Proton ARP) and manual (Manual Robust Proton MRP) methods were evaluated in the remaining 20 patients. Plans were compared in terms of dosimetric parameters and planning time. RESULTS: A statistically significantly improvement in target dose fall off was observed for ARP plans compare to MRP plans (Dose fall off: 135 for MRP and 88 for ARP, p < 0.01), while no differences in target coverage and conformity. A statistically significantly reduce in normal lung tissue were observed for ARP plans compare to MRP plans (Lung [Dmean cGy (RBE)]: MRP: 478 vs. ARP: 351, p < 0.01; Lung [V5Gy (RBE) (%)]: MRP: 16.1 vs. ARP: 12.1, p < 0.01; Lung [V20Gy (RBE) (%)]: MRP: 8.5 vs. ARP: 6.8, p < 0.01). Planning time was reduced for ARP plans compare to MRP plans (optimization time: 12 min for MRP vs. 8 min for ARP; total plan time: 23 min for MRP vs. 18 min for ARP). CONCLUSION: The automated robust SBPT plans using EUD-Based mimicking of SBRT reference dose improve target dose fall off, reduced the radiation doses to the lungs, reduce planning time, which might be beneficial for patient with lung cancer in clinical.

Comparison of a Hybrid IMRT/VMAT technique with non-coplanar VMAT and non-coplanar IMRT for unresectable olfactory neuroblastoma using the RayStation treatment planning system-EUD, NTCP and planning study.

The purpose of this study was to compare hybrid intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (Hybrid IMRT/VMAT), with non-coplanar (nc) IMRT and nc-VMAT treatment plans for unresectable olfactory neuroblastoma (ONB). Hybrid IMRT/VMAT, nc-IMRT and nc-VMAT plans were optimized for 12 patients with modified Kadish C stage ONB. Dose prescription was 65 Gy in 26 fractions. Dose-volume histogram parameters, conformation number (CN), homogeneity index (HI), integral dose and monitor units (MUs) delivered per fraction were assessed. Equivalent uniform dose (EUD) and normal tissue complication probability (NTCP) based on the EUD model (NTCPLogit) and the Lyman-Kutcher-Burman model (NTCPLKB) were also evaluated. We found that the Hybrid IMRT/VMAT plan significantly improved the CN for clinical target volume (CTV) and planning treatment volume (PTV) compared with the nc-VMAT plan. In general, sparing of organs at risk (OARs) is similar with the three techniques, although the Hybrid IMRT/VMAT plan resulted in a significantly reduced Dmax to contralateral (C/L) optic nerve compared with the nc-IMRT plan. The Hybrid IMRT/VMAT plan significantly reduce EUD to the ipsilateral (I/L) and C/L optic nerve in comparison with the nc-IMRT plan and nc-VMAT plan, but the difference in NTCP between the three technique was <1%. We concluded that the Hybrid IMRT/VMAT technique can offer improvement in terms of target conformity and EUD for optic nerves, while achieving equal or better OAR sparing compared with nc-IMRT and nc-VMAT, and can be a viable radiation technique for treating unresectable ONB. However, the clinical benefit of these small differences in dosimetric data, EUD and NTCP of optic nerves may be minimal.

Revisiting the formalism of equivalent uniform dose based on the linear-quadratic and universal survival curve models in high-dose stereotactic body radiotherapy.

PURPOSE: To examine the equivalent uniform dose (EUD) formalism using the universal survival curve (USC) applicable to high-dose stereotactic body radiotherapy (SBRT). MATERIALS AND METHODS: For nine non-small-cell carcinoma cell (NSCLC) lines, the linear-quadratic (LQ) and USC models were used to calculate the EUD of a set of hypothetical two-compartment tumor dose-volume histogram (DVH) models. The dose was varied by ±5%, ±10%, and ±20% about the prescription dose (60 Gy/3 fractions) to the first compartment, with fraction volume varying from 1% and 5% to 30%. Clinical DVHs of 21 SBRT treatments of NSCLC prescribed to the 70-83% isodose lines were also considered. The EUD of non-standard SBRT dose fractionation (EUDSBRT) was further converted to standard fractionation of 2 Gy (EUDCFRT) using the LQ and USC models to facilitate comparisons between different SBRT dose fractionations. Tumor control probability (TCP) was then estimated from the LQ- and USC-EUDCFRT. RESULTS: For non-standard SBRT fractionation, the deviation of the USC- from the LQ-EUDSBRT is largely limited to 5% in the presence of dose variation up to ±20% to fractional tumor volume up to 30% in all NSCLC cell lines. Linear regression with zero constant yielded USC-EUDSBRT = 0.96â€¯× LQ-EUDSBRT (r2 = 0.99) for the clinical DVHs. Converting EUDSBRT into standard 2­Gy fractions by the LQ formalism produced significantly larger EUDCFRT than the USC formalism, particularly for low [Formula: see text] ratios and large fraction dose. Simplified two-compartment DVH models illustrated that both the LQ- and USC-EUDCFRT values were sensitive to cold spot below the prescription dose with little volume dependence. Their deviations were almost constant for up to 30% dose increase above the prescription. Linear regression with zero constant yielded USC-EUDCFRT = 1.56â€¯× LQ-EUDCFRT (r2 = 0.99) for the clinical DVHs. The clinical LQ-EUDCFRT resulted in median TCP of almost 100% vs. 93.8% with USC-EUDCFRT. CONCLUSION: A uniform formalism of EUD should be defined among the SBRT community in order to apply it as a single metric for dose reporting and dose-response modeling in high-dose-gradient SBRT because its value depends on the underlying cell survival model and the model parameters. Further investigations of the optimal formalism to derive the EUD through clinical correlations are warranted.

Assessment of robustness of institutional applied clinical target volume (CTV) to planning target volume (PTV) margin in cervical cancer using biological models.

The aim of this study is to investigate the robustness of our institutionally applied clinical target volume (CTV)-to-planning target volume (PTV) margins in cervical cancer patients in terms of an equivalent uniform dose (EUD) based on tumor control probability (TCP). We simulated target motion using 25 IMRT cervical cancer plans to demonstrate the effect of geometrical uncertainties on the EUD and TCP. The different components of the total geometrical uncertainties budget were estimated. The biological effects were compared by calculating the EUDs from the trial DVHs. The impact of geometric uncertainties was calculated as a percentage of the difference between 〖EUD〗_static and 〖EUD〗_motion, where the 〖EUD〗_static is the EUD calculated from the target DVHs and 〖EUD〗_motion is averaged, over a 1000 calculated EUDs for each of the analyzed IMRT treatment plans. The multivariate nonlinear regression was used to find the predicted difference between the static and motion EUD. The estimate of the systematic and random motion errors were Σ_(total(SI,LR,AP)) (mm)=(2.6; 2.5; 1.8) and σ_(total(SI,LR,AP)) (mm)=(3.4; 1.4; 3.4). For average 〈EUD〉_motion=44.3 Gy (over 25 patients) we have found a TCP decrease of about 1%, %(ΔTCP)≈1% for predefined PTV margin. According to the calculated EUD motion-distributions, for particular patients, the CTV does receive the prescribed EUD of 45 Gy. The predicted difference in EUD showed that our isotropic margin of 10 mm is large enough to absorb geometric uncertainties and ensure dose coverage of the moving CTV in the cervical cancer patients.

Potential Defects and Improvements of Equivalent Uniform Dose Prediction Model Based on the Analysis of Radiation-Induced Brain Injury.

PURPOSE: To study the impact of dose distribution on volume-effect parameter and predictive ability of equivalent uniform dose (EUD) model, and to explore the improvements. METHODS AND MATERIALS: The brains of 103 nasopharyngeal carcinoma patients treated with IMRT were segmented according to dose distribution (brain and left/right half-brain for similar distributions but different sizes; V D with different D for different distributions). Predictive ability of EUDV D (EUD of V D ) for radiation-induced brain injury was assessed by receiver operating characteristics curve (ROC) and area under the curve (AUC). The optimal volume-effect parameter a of EUD was selected when AUC was maximal (mAUC). Correlations between mAUC, a and D were analyzed by Pearson correlation analysis. Both mAUC and a in brain and half-brain were compared by using paired samples t-tests. The optimal D V and V D points were selected for a simple comparison. RESULTS: The mAUC of brain/half-brain EUD was 0.819/0.821 and the optimal a value was 21.5/22. When D increased, mAUC of EUDV D increased, while a decreased. The mAUC reached the maximum value when D was 50-55 Gy, and a was always 1 when D ≥55 Gy. The difference of mAUC/a between brain and half-brain was not significant. If a was in range of 1 to 22, AUC of brain/half-brain EUDV55 Gy (0.857-0.830/0.845-0.830) was always larger than that of brain/half-brain EUD (0.681-0.819/0.691-0.821). The AUCs of optimal dose/volume points were 0.801 (brain D2.5 cc), 0.823 (brain V70 Gy), 0.818 (half-brain D1 cc), and 0.827 (half-brain V69 Gy), respectively. Mean dose (equal to EUDV D with a = 1) of high-dose volume (V50 Gy-V60 Gy) was superior to traditional EUD and dose/volume points. CONCLUSION: Volume-effect parameter of EUD is variable and related to dose distribution. EUD with large low-dose volume may not be better than simple dose/volume points. Critical-dose-volume EUD could improve the predictive ability and has an invariant volume-effect parameter. Mean dose may be the case in which critical-dose-volume EUD has the best predictive ability.

Dosimetric differences in intensity modulated radiation therapy based on EUD and DV optimizations in lung cancer / 中国辐射卫生

Objective To compare the dosimetric difference between the biological function based on equivalent uniform dose (EUD) and the physical function based on dose volume (DV) in the intensity modulated radiotherapy for stage Ⅲ non-small cell lung cancer. Methods Four different radiotherapy plans were designed for 15 stage Ⅲ non-small cell lung cancer patients: Group A, physical function optimization (DV + DV) was used for target area and organs at risk; GroupB, in the target region, biological function optimization conditions were added on the basis of physical function optimization, and physical function optimization of organs at risk (DV－EUD + DV) was added. Group C, biological function optimization (EUD + EUD) was used for target area and organs at risk. Group D, in the target area, physical function optimization conditions were added on the basis of biological function optimization, and biological function optimization of organs at risk (EUD－DV + DV) was added. The differences in dosimetric parameters of the four plans were compared. Results Target area: PTV: D2%, D98%, D50%, D105% and Dmax values of group C (P < 0.05) is the highest while group B and group D were relatively small (P > 0.05); The homogeneity index: the results of the group B and the group D were better than those of the other two groups (P < 0.05). conformity index: The results of the four groups were similar (P>0.05). Organ at risk: lung tissue mean dose (MLD), V5, V10, V20, V30 and heart V30, V40, Dmean dose parameters were similar (P > 0.05). Spinalcord: Group C and group D D1% were better than the other two groups (P < 0.05). There was no statistical difference in the number ofmonitor unit (MU) among the four groups (P > 0.05). Conclusion The optimization method combining physical and biological function optimization in the target area can improve the conformity of the target area on the premise of ensuring the treatment. The Spinalcord load would be significantly reduced when using biological function optimization or the combination of biological function and physical function optimization.

Associating dose-volume characteristics with theoretical radiobiological metrics for rapid Gamma Knife stereotactic radiosurgery plan evaluation.

PURPOSE: To examine general dose-volume characteristics in Gamma Knife (GK) plans which may be associated with higher tumor control probability (TCP) and equivalent uniform dose (EUD) using characteristic curve sets. METHODS: Two sets of dose-volume histograms (DVHs) were exported alongside an analytical purpose-generated DVH: (a) single-shot large collimator (8 or 16 mm) emulated with multiple shots of 4 mm collimator. (b) shot-within-shot (SWS) technique with isodose lines (IDLs) of 40-75%. TCP, average dose, EUD in single-fraction (EUDT ) and 2 Gy fractionated regimens (EUDR ) were examined for trends with cumulative DVH (cDVH) shape as calculated using a linear-quadratic cell survival model (α/ß = 10.0 Gy, N0  = 1 × 106 ) with both α = 0.20 Gy-1 and α = 0.23 Gy-1 . RESULTS: Using α = 0.20 Gy-1 (α = 0.23 Gy-1 ), plans in the analytical set with higher shoulder regions had TCP, EUDT , EUDR increased by 180%, 5.9%, 10.7% (11.2%, 6.3%, 10.0%), respectively. With α = 0.20 Gy-1 (α = 0.23 Gy-1 ), plans with higher heels had TCP, EUDT , EUDR increased by 4.0%, <1%, <1% (0.6%, <1%, <1%), respectively. In emulating a 16 (8) mm collimator, 64 (12) shots of the small collimators were used. Plans based on small collimators had higher shoulder regions and, with α = 0.20 Gy-1 (α = 0.23 Gy-1 ), TCP, EUDT , EUDR was increased up to 351.4%, 5.0%, 8.8% (270.4%, 5.0%, 6.8%) compared with the single-shot large collimator. Delivery times ranged from 10.2 to 130.3 min. The SWS technique used 16:8 mm collimator weightings ranging from 1:2 to 9.2:1 for 40-75% IDL. With α = 0.20 Gy-1 (α = 0.23 Gy-1 ), the 40% IDL plan had the highest shoulder with increased TCP, EUDT , EUDR by 130.7%, 9.6%, 17.1% (12.9%, 9.1%, 16.4%) over the 75% IDL plan. Delivery times ranged 6.9-13.8 min. CONCLUSIONS: The magnitude of the shoulder region characteristic to GK cDVHs may be used to rapidly identify superior plan among candidates. Practical issues such as delivery time may require further consideration.

Pro-con of proton: Dosimetric advantages of intensity-modulation over passive scatter for thoracic malignancies.

The use of passively scattered proton therapy (PSPT) or intensity modulated proton therapy (IMPT) opens the potential for dose escalation or critical structure sparing in thoracic malignancies. While the latter offers greater dose conformality, dose distributions are subjected to greater uncertainties, especially due to interplay effects. Exploration in this area is warranted to determine if there is any dosimetric advantages in using IMPT for thoracic malignancies. This review aims to both compare organs-at-risk sparing and plan robustness between PSPT and IMPT and examine the mitigation strategies for the reduction of interplay effects currently available. Early evidence suggests that IMPT is dosimetrically superior to PSPT in thoracic malignancies. Randomised control trials are required before any clinical benefit of IMPT can be confirmed.