Standard Dose-volume Histograms Research Articles

Benchmarking Automated Machine Learning-Enhanced Planning With Ethos Against Manual and Knowledge-Based Planning for Locally Advanced Lung Cancer

Currently, there is insufficient guidance for standard fractionation lung planning using the Varian Ethos adaptive treatment planning system and its unique intelligent optimization engine. Here, we address this gap in knowledge by developing a methodology to automatically generate high-quality Ethos treatment plans for locally advanced lung cancer. Fifty patients previously treated with manually generated Eclipse plans for inoperable stage IIIA-IIIC non-small cell lung cancer were included in this institutional review board-approved retrospective study. Fifteen patient plans were used to iteratively optimize a planning template for the Daily Adaptive vs Non-Adaptive External Beam Radiation Therapy With Concurrent Chemotherapy for Locally Advanced Non-Small Cell Lung Cancer: A Prospective Randomized Trial of an Individualized Approach for Toxicity Reduction (ARTIA-Lung); the remaining 35 patients were automatically replanned without intervention. Ethos plan quality was benchmarked against clinical plans and reoptimized knowledge-based RapidPlan (RP) plans, then judged using standard dose-volume histogram metrics, adherence to clinical trial objectives, and qualitative review. Given equal prescription target coverage, Ethos-generated plans showed improved primary and nodal planning target volume V95% coverage (P < .001) and reduced lung gross tumor volume V5 Gy and esophagus D0.03 cc metrics (P ≤ .003) but increased mean esophagus and brachial plexus D0.03 cc metrics (P < .001) compared with RP plans. Eighty percent, 49%, and 51% of Ethos, clinical, and RP plans, respectively, were "per protocol" or met "variation acceptable" ARTIA-Lung planning metrics. Three radiation oncologists qualitatively scored Ethos plans, and 78% of plans were clinically acceptable to all reviewing physicians, with no plans receiving scores requiring major changes. A standard Ethos template produced lung radiation therapy plans with similar quality to RP plans, elucidating a viable approach for automated plan generation in the Ethos adaptive workspace.

A mathematical and dosimetric approach to validate auto‐contouring by Varian Smart segmentation for prostate cancer patients

AbstractPurposeThe aim of this study was to quantify the discrepancies in geometrical and dosimetric impacts (in volumetric modulated arc therapy) between manually segmented (MS) contours and smart segmentation (SS) auto‐contours (by Varian Eclipse Treatment Planning System SS v13.5) for prostate cancer patients.MethodsThe automated segmentation was carried out by Eclipse Treatment Planning System (Varian, version 13.5) Smart Segmentation (SS) workspace of 10 prostate cancer patients for four regions of interest; such as, bladder, rectum, femoral head left, and femoral head right. The geometric and dosimetric deviation between SS and MS contours have been quantified in the form of different parameters. The organ‐wise correlation between different validation parameters was addressed.ResultsThe organ‐wise correlation analysis showed the good and consistent correlation between different geometric validation parameters for the bladder. The hypothesis test for checking compliance of different parameters with AAPM 132 tolerance was addressed and validated between MS and SS bladder with p‐value = 0.01 and 0.05. There was no significant dosimetric difference between the dose–volume histogram (DVH) estimated for the SS bladder and standard DVH constraints protocol (as per the TMH PRIME trial) with p‐value = 0.01 and 0.05. The difference between DVH estimated for MS and SS bladder was also not significant, with p‐value = 0.05.ConclusionThis study shows that “well correlated validation parameters infer correctly about the matching or coincidence between auto and manually segmented contours,” and the bladder contouring by Smart Segmentation and plan optimization can achieve acceptable DVH constraints.

The influence of Acuros XB on dose volume histogram metrics and tumour control probability modelling in locally advanced non-small cell lung cancer.

Radiation therapy plans are assessed using dose volume metrics derived from clinical toxicity and outcome data. In this study, plans for patients with locally advanced non-small cell lung cancer (LA-NSCLC) are examined in the context of the implementation of the Acuros XB (AXB) dose calculation algorithm focussing on the impact on common metrics. Volumetric modulated arc therapy (VMAT) plans were generated for twenty patients, using the Analytical Anisotropic Algorithm (AAA) and recalculated with AXB for both dose to water (Dw) and dose to medium (Dm). Standard dose volume histogram (DVH) metrics for both targets and organs-at-risk (OARs) were extracted, in addition to tumour control probability (TCP) for targets. Mean dose to the planning target volume (PTV) was not clinically different between the algorithms (within ±1.1Gy) but differences were seen in the minimum dose, D99% and D98% as well as for conformity and homogeneity metrics. A difference in TCP was seen for AXBDm plans versus both AXBDw and AAA plans. No clinically relevant differences were seen in the lung metrics. For point doses to spinal cord and oesophagus, the AXBDm values were lower than AXBDw, by up to 1.0Gy. Normalisation of plans to the mean/median dose to the target does not need to be adjusted when moving from AAA to AXB. OAR point doses may decrease by up to 1Gy with AXBDm, which can be accounted for in clinical planning. Other OAR metrics do not need to be adjusted.

Comprehensive Comparison of Progressive Optimization Algorithm Based Automatic Plan and Manually Planned Treatment Technique for Cervical-Thoracic Esophageal Cancers.

Purpose:The purpose of the present study was first to apply the progressive optimization algorithm based automatic volumetric modulated arc therapy (POA-VMAT) technology to accelerate and improve the radiotherapy of cervicothoracic esophageal cancer (CTEC). We comprehensive analyze the feasibility, normal tissue complication probability (NTCP) and dosimetric results of POA-VMAT, manual based VMAT and step-shoot intensity-modulated radiation therapy (IMRT) plans in the treatment of CTEC.Methods:Sixty patients with CTEC with or without concomitant chemotherapy at our institution between 2017 and 2019 were retrospectively identified. The manual 7field-IMRT (7f-IMRT), Single-arc-VMAT and Double-arc-VMAT (Single-Arc/Double-Arc) plans were generated in all cases. The POA-VMAT was designed using the automatic dual-arc VMAT technology of Pinnacle3 9.10 planning system based on progressive optimization algorithm. Specially, it includes the selection of treatment techniques, the running of automated planning scripts, and the evaluation of the final radiotherapy regimen. Subsequently, quantitative evaluation of plans was performed by means of standard dose–volume histograms, homogeneity index (HI) and conformity index (CI).Results:Target dose conformity of the 7f-IMRT plan was inferior to all plans, whereas the Double-Arc plan was slightly inferior to the POA-VMAT but superior to the Single-Arc and 7f-IMRT plan. The HI for 7f-IMRT, Single-Arc, Double-Arc and POA-VMAT were 0.17 ± 0.08, 0.28 ± 0.06, 0.29 ± 0.06 and 0.28 ± 0.03, respectively. For the NTCP results, there was significant statistical difference among POA-VMAT, IMRT and VMAT plans. The total MU was reduced by 48.3% and 42.1% in Single-Arc and POA-VMAT plans compare to IMRT plans.Conclusions:By comprehensive consideration, POA-VMAT efficiently generate acceptable treatment plans for CTEC without dose escalation to OARs and overall superior to manual planning which is a good option for treating CTEC.

Analysis of dose heterogeneity using a subvolume-DVH

The dose-volume histogram (DVH) is universally used in radiation therapy for its highly efficient way of summarizing three-dimensional dose distributions. An apparent limitation that is inherent to standard histograms is the loss of spatial information, e.g. it is no longer possible to tell where low- and high-dose regions are, and whether they are connected or disjoint. Two methods for overcoming the spatial fragmentation of low- and high-dose regions are presented, both based on the gray-level size zone matrix, which is a two-dimensional histogram describing the frequencies of connected regions of similar intensities.The first approach is a quantitative metric which can be likened to a homogeneity index. The large cold spot metric (LCS) is here defined to emphasize large contiguous regions receiving too low a dose; emphasis is put on both size, and deviation from the prescribed dose. In contrast, the subvolume-DVH (sDVH) is an extension to the standard DVH and allows for a qualitative evaluation of the degree of dose heterogeneity. The information retained from the two-dimensional histogram is overlaid on top of the DVH and the two are presented simultaneously. Both methods gauge the underlying heterogeneity in ways that the DVH alone cannot, and both have their own merits—the sDVH being more intuitive and the LCS being quantitative.

Can advanced new radiation therapy technologies improve outcome of high grade glioma (HGG) patients? analysis of 3D-conformal radiotherapy (3DCRT) versus volumetric-modulated arc therapy (VMAT) in patients treated with surgery, concomitant and adjuvant chemo-radiotherapy

BackgroundTo assess the impact of volumetric-modulated arc therapy (VMAT) compared with 3D-conformal radiotherapy (3DCRT) in patients with newly diagnosed high grade glioma in terms of toxicity, progression free survival (PFS) and overall survival (OS).MethodsFrom March 2004 to October 2014, 341 patients underwent surgery followed by concomitant and adjuvant chemo-radiotherapy. From 2003 to 2010, 167 patients were treated using 3DCRT; starting from 2011, 174 patients underwent VMAT. The quantitative evaluation of the treatment plans was performed by means of standard dose volume histogram analysis. Response was recorded using the Response Assessment in Neuro-Oncology (RANO) criteria and toxicities graded according to Common Terminology Criteria for Adverse Event version 4.0.ResultsBoth techniques achieved an adequate dose conformity to the target. The median follow up time was 1.3 years; at the last observation 76 patients (23.4 %) were alive and 249 (76.6 %) dead (16 patients were lot to follow-up). For patients who underwent 3DCRT, the median PFS was 0.99 ± 0.07 years (CI95: 0.9–1.1 years); the 1 and 3 years PFS were, 49.6 ± 4 and 19.1 ± 3.1 %. This shall be compared, respectively, to 1.29 ± 0.13 years (CI95: 1.01–1.5 years), 60.8 ± 3.8, and 29.7 ± 4.6 % for patients who underwent VMAT (p = 0.02). The median OS for 3DCRT patients was 1.21 ± 0.09 years (CI95:1.03–1.3 years); 1 and 5 year OS was, 63.3 ± 3.8 and 21.5 ± 3.3 %. The corresponding results for 3DRCT patients were 1.56 ± 0.09 years (CI95:1.37–1.74 years), 73.4 ± 3.5, 30 ± 4.6 % respectively (p < 0.01). In both groups, prognostic factors conditioning PFS and OS were age, gender, KPS, histology and extent of resection (EOR).ConclusionsVMAT resulted superior to 3DCRT in terms of dosimetric findings and clinical results.

SU‐E‐T‐482: Development and Systematic Testing of Dose Analysis Engine for Research and Clinical Applications Using API Interface of Varian Eclipse Treatment Planning System

Purpose:To validate standalone software that provides dose analysis capabilities of a treatment planning system. The intended use of this software is in research and in clinical applications where commercial solutions are not yet available.Methods:We used Application Programmer Interface (API) of the Eclipse Treatment Planning System (Varian,Inc), to extract dosimetric information from treatment plans. We used dose volume histogram (DVH) object to extract standard dose volume histogram data. We used two API functions to construct 3D representation of anatomy (a bitmap) and compute dose values at all voxels that belong to a structure. We wrote a C++ package which achieves the same reconstruction based on stored contour data and a dose volume. For this work we compared structure volumes and simple dose statistics on dose buffers (minimum, mean, maximum and standard deviation). We used data from 6 Head and Neck patients and examined a total of 102 structures.Results:The API based reconstruction of 3D anatomy systematically overestimates structure volumes when compared to volumes reported by the API DVH module. The discrepancy is largest for small structures, and can exceed 20%. Volume estimates obtained by the C++ package show better agreement with the DVH module if partial volume corrections are applied to surface voxels. Among four dosimetric variables, largest discrepancies are observed for the minimum dose. While we observe better than 2% agreement in most cases, we find outliers with discrepancies reaching over 20%, even when we compare the two API based methods.Conclusion:We find that good validation of a standalone dose analysis package requires testing on a large series of structures obtained from multiple patients. Disagreements between two API based methods show that vendor algorithms have hidden features which may affect dosimetric analysis.

SPECT‐based functional lung imaging for the prediction of radiation pneumonitis: A clinical and dosimetric correlation

When we irradiate lung cancer, the radiation dose that can be delivered safely is limited by the risk of radiation pneumonitis (RP) in the surrounding normal lung. This risk is dose-dependent and is commonly predicted using metrics such as the V20, which are usually formulated assuming homogeneous pulmonary function. Because in vivo pulmonary function is not homogeneous, if highly functioning lung can be identified beforehand and preferentially avoided during treatment, it might be possible to reduce the risk of RP, suggesting the utility of function-based prediction metrics. We retrospectively identified 26 patients who received ventilation and perfusion single photon emission computed tomography (SPECT-CT) immediately prior to curative-intent radiation therapy. Patients were separated into non-RP and RP groups. As-treated dose-volume histogram (DVH), perfusion-SPECT-based and ventilation-SPECT-based dose-function histogram (DFH) parameters were defined for each group and were tested for differences. The relative utilities of ventilation-based and perfusion-based DFH metrics were assessed using receiver operating characteristic (ROC) analysis. The standard mean lung dose (MLD) was significantly higher in the RP group; the standard V20 and V30 were higher in the RP group but not significantly. Perfusion-weighted and ventilation-weighted values of the MLD, V20 and V30 were all significantly higher in the RP group. ROC analysis suggested that SPECT-based DFH parameters outperformed standard DVH parameters as predictors of RP. SPECT-based DFH parameters appear to be useful as predictors of RP.

Functional and biologic metrics for predicting radiation pneumonitis in locally advanced non-small cell lung cancer patients treated with chemoradiotherapy

To study the predictive value of functional and biologic metrics for predicting radiation pneumonitis (RP) in locally advanced non-small cell lung cancer (LANSCLC) patients treated with chemoradiotherapy. Between March 2006 and April 2010, 57 LANSCLC patients were enrolled in a prospective study. Fusion of SPECT and computed tomography scans provides perfusion-weighted functional dose-volume histogram (DVH) and associated functional dosimetric parameters. Blood for serum biomarkers-interleukin-6 (IL-6), transforming growth factor-beta1, and superoxide dismutase (SOD)-was drawn pre-RT and then 40Gy/4weeks during the treatment. The incidence of RP was related to the functional and biologic metrics. The predictability of predictors was calculated and compared based on the area under receiver-operating characteristic (ROC) curve (AUC). Relative volumes of functional lung receiving more than a threshold dose of 5-50Gy at increments of 5Gy and elevated levels of serum SOD after delivery of 40Gy/4weeks were associated with RP (p<0.05). The best predictive efficacy of SOD was observed for a cutoff value of 56U/ml, with a sensitivity of 0.80 (95% CI 0.28-0.99) and a specificity of 0.67 (95% CI 0.43-0.65) (p=0.040). Functional DVH provided better predictive outcome (AUC 0.76-0.98) than standard DVH (AUC 0.62-0.86) for patients with poor baseline lung function. Functional metrics were identified to be better predictors for RP in patients with poor baseline lung function. SOD seemed to be a potential predictor for RP; however, it will need to be further verified using a larger sample size.

Sci—Fri AM: Imaging — 04: SPECT‐based functional lung imaging in the prediction of radiation pneumonitis: A retrospective clinical and dosimetric correlation

To investigate whether functionally-weighted dose-volume histogram (DVH) parameters are more predictive of radiation-induced pneumonitis (RP) than standard parameters such as V20 and mean lung dose (MLD). A retrospective chart review identified 26 patients who received curative-intent radiation therapy for primary carcinoma of the lung. Prior to treatment, all patients received single photon emission computed tomography (SPECT) to assess both lung ventilation and lung perfusion. Patients were assessed for clinical RP using standard criteria and were separated into a non-RP group (RP grade < 2) and an RP-group (RP grade ≥ 2). Standard DVH parameters (V10, V20, V30, MLD) and their function-weighted counterparts (for perfusion: pF10, pF20, pF30, pMLD; for ventilation: vF10, vF20, vF30, vMLD) were evaluated for each group. Receiver operating characteristics (ROC) curves were created and the area under the curve (AUC) computed. 7 of 26 patients had grade ≥ 2 pneumonitis. Both pF20 (p=0.022) and vF20 (p=0.036) were significantly different between the 2 groups; V20 was not (p=0.06). Both pF30 (p=0.008) and vF30 (p=0.025) were significantly different between groups while V30 failed to reach significance (p=0.072). Standard MLD (p=0.011), pMLD (p=0.001), and vMLD (p=0.011) were all significantly different. The ROC curves indicated that both the perfusion-weighted parameters and the ventilation-weighted parameters outperformed the standard DVH parameters as predictors of RP grade ≥2. SPECT-based, function-weighted DVH parameters appear to be useful as predictors of RP.

Functional dosimetric metrics for predicting radiation-induced lung injury in non-small cell lung cancer patients treated with chemoradiotherapy

BackgroundRadiation-induced lung injury (RILI) is an important dose-limiting toxicity during thoracic radiotherapy. The purpose of this study is to investigate single photon emission computed tomography (SPECT) perfusion-weighted functional dose-volume histogram (FDVH) for predicting RILI in non-small cell lung cancer (NSCLC) patients treated with definitive chemoradiotherapy.MethodsFifty-seven locally advanced NSCLC patients receiving chemoradiotherapy were enrolled prospectively. Patients had treatment scans and dose calculations to provide a standard dose-volume histogram (DVH). Fusion of SPECT and computed tomography scans provided perfusion-weighted FDVH and associated functional dosimetric parameters (relative volumes of functional lung receiving more than a threshold dose of 5 – 60 Gy at increments of 5 Gy [FV5 – FV60]). The predictive abilities of FDVH and DVH were calculated and compared based on the area under receiver operating characteristic (ROC) curve (AUC).ResultsThe accumulative incidence of ≥ 2 grade RILI was 19.3% with a median follow-up of 12 months. Univariate analysis showed that the functional (FV5 – FV60) and standard (V5 – V40) parameters were associated with RILI (all value of p < 0.05). Close correlations between a variety of functional and standard parameters were found. By ROC curve analysis, functional metrics (AUCs were 0.784 – 0.869) provided similarly (p value 0.233 – 1.000) predictive outcome to standard metrics (AUCs were 0.695 – 0.902) in lower – median dose level parameters (FV5 – FV40). However, FDVH seemed to add some predictive value in higher dose level, the best statistical significance for comparing FV60 with V60 was 0.693 vs. 0.511 (p = 0.055).ConclusionsFunctional metrics are identified as reliable predictors for RILI, however, this observation still needs to be further verified using a larger sample size.

Role of Principal Component Analysis in Predicting Toxicity in Prostate Cancer Patients Treated With Hypofractionated Intensity-Modulated Radiation Therapy

To determine if principal component analysis (PCA) and standard parameters of rectal and bladder wall dose-volume histograms (DVHs) of prostate cancer patients treated with hypofractionated image-guided intensity-modulated radiotherapy (hypo-IMRT) can predict acute and late gastrointestinal (GI) toxicity. One hundred twenty-one patients underwent hypo-IMRT at 3 Gy/fraction, 5 days/week to either 60 Gy or 66 Gy, with daily online image guidance. Acute and late GI and genitourinary (GU) toxicity were recorded weekly during treatment and at each follow-up. All Radiation Therapy Oncology Group (RTOG) criteria toxicity scores were dichotomized as <2 and ≥2. Standard dosimetric parameters and the first five to six principal components (PCs) of bladder and rectal wall DVHs were tested for association with the dichotomized toxicity outcomes, using logistic regression. Median follow-up of all patients was 47 months (60 Gy cohort = 52 months; 66 Gy cohort = 31 months). The incidence rates of ≥2 acute GI and GU toxicity were 14% and 29%, respectively, with no Grade ≥3 acute GU toxicity. Late GI and GU toxicity scores ≥2 were 16% and 15%, respectively. There was a significant difference in late GI toxicity ≥2 when comparing the 66 Gy to the 60 Gy cohort (38% vs. 8%, respectively, p = 0.0003). The first PC of the rectal DVH was associated with late GI toxicity (odds ratio [OR], 6.91; p < 0.001), though it was not significantly stronger than standard DVH parameters such as Dmax (OR, 6.9; p < 0.001) or percentage of the organ receiving a 50% dose (V50) (OR, 5.95; p = 0 .001). Hypofractionated treatment with 60 Gy in 3 Gy fractions is well tolerated. There is a steep dose response curve between 60 Gy and 66 Gy for RTOG Grade ≥2 GI effects with the dose constraints employed. Although PCA can predict late GI toxicity for patients treated with hypo-IMRT for prostate cancer, it provides no additional information over using more standard DVH parameters.

Modeling late rectal toxicities based on a parameterized representation of the 3D dose distribution

Many models exist for predicting toxicities based on dose-volume histograms (DVHs) or dose-surface histograms (DSHs). This approach has several drawbacks as firstly the reduction of the dose distribution to a histogram results in the loss of spatial information and secondly the bins of the histograms are highly correlated with each other. Furthermore, some of the complex nonlinear models proposed in the past lack a direct physical interpretation and the ability to predict probabilities rather than binary outcomes. We propose a parameterized representation of the 3D distribution of the dose to the rectal wall which explicitly includes geometrical information in the form of the eccentricity of the dose distribution as well as its lateral and longitudinal extent. We use a nonlinear kernel-based probabilistic model to predict late rectal toxicity based on the parameterized dose distribution and assessed its predictive power using data from the MRC RT01 trial (ISCTRN 47772397). The endpoints under consideration were rectal bleeding, loose stools, and a global toxicity score. We extract simple rules identifying 3D dose patterns related to a specifically low risk of complication. Normal tissue complication probability (NTCP) models based on parameterized representations of geometrical and volumetric measures resulted in areas under the curve (AUCs) of 0.66, 0.63 and 0.67 for predicting rectal bleeding, loose stools and global toxicity, respectively. In comparison, NTCP models based on standard DVHs performed worse and resulted in AUCs of 0.59 for all three endpoints. In conclusion, we have presented low-dimensional, interpretable and nonlinear NTCP models based on the parameterized representation of the dose to the rectal wall. These models had a higher predictive power than models based on standard DVHs and their low dimensionality allowed for the identification of 3D dose patterns related to a low risk of complication.

WE-C-BRC-10: The Utility of Surrogates of the Distribution of Pulmonary Function in Individualizing Thoracic Radiotherapy

Purpose: Heterogeneity of lung tissue density and function is a hallmark of pathologic changes in chronic obstructive pulmonary disease (COPD). However, the standard risk assessment approaches, based on dose-volume histograms (DVH), do not currently use the functional information in evaluating pulmonary tolerance to radiation therapy. We investigated the utility of weighting of dose distributions by surrogate metrics of the lung function (parenchyma density, ventilation distribution) as complementary sources of information for assessing the risk of complications, and for further individualizing of thoracic radiation therapy. Methods: The tissue density and the distribution of ventilatory activity were estimated from respiration-correlated CT scans of 19 patients. Dose distributions from clinical IMRT (N=17) and proton (N=2) therapy plans were reevaluated by applying importance weighting to separate 1-cc volume elements in the lung, accordingly with their estimated relative functional load. The histogram metrics: mean lung dose (MLD), share of the 5-Gy isodose (V5), etc., were compared between various dose-weighting methods. Regions characterized by high ventilatory activity were segmented, and research IMRT plans were optimized with objectives aiming to maximize sparing of lung function. Results: Substantial differences between the metrics of DVH and ventilation-weighted histograms were observed, e.g., change of over 5% in MLD in 8 patients, relative increase of over 10% in V20 in 3 patients out of 19. The correlation between the density- and ventilation-weighted metrics was insignificant. The use of additional optimization constraints for highly-ventilated lung subvolumes allowed for a reduction in the ventilation-weighted MLD, without compromising the target coverage, or causing deterioration in the standard DVH. Conclusions: Elevated values of ventilation-weighted MLD may indicate the increased risk of complications in patients with COPD. The use of ventilation distribution maps for selection of beam angles, and definition of optimization constraints for functional avoidance, can potentially reduce the risk, without compromising the therapy efficiency.