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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

The effect of irregular breathing patterns on internal target volumes in four-dimensional CT and cone-beam CT images in the context of stereotactic lung radiotherapy

Purpose: Stereotactic lung radiotherapy is complicated by tumor motion from patient respiration. Four-dimensional CT (4DCT) imaging is a motion compensation method used in treatment planning to generate a maximum intensity projection (MIP) internal target volume (ITV). Image guided radiotherapy during treatment may involve acquiring a volumetric cone-beam CT (CBCT) image and visually aligning the tumor to the planning 4DCT MIP ITV contour. Moving targets imaged with CBCT can appear blurred and currently there are no studies reporting on the effect that irregular breathing patterns have on CBCT volumes and their alignment to 4DCT MIP ITV contours. The objective of this work was therefore to image a phantom moving with irregular breathing patterns to determine whether any configurations resulted in errors in volume contouring or alignment. Methods: A Perspex thorax phantom was used to simulate a patient. Three wooden 'lung' inserts with embedded Perspex 'lesions' were moved up to 4 cm with computer-generated motion patterns, and up to 1 cm with patient-specific breathing patterns. The phantom was imaged on 4DCT and CBCT with the same acquisition settings used for stereotactic lung patients in the clinic and the volumes on all phantom images were contoured. This project assessed the volumes for qualitative and quantitative changes including volume, length of the volume, and errors in alignment between CBCT volumes and 4DCT MIP ITV contours. Results: When motion was introduced 4DCT and CBCT volumes were reduced by up to 20% and 30% and shortened by up to 7 and 11 mm, respectively, indicating that volume was being under-represented at the extremes of motion. Banding artifacts were present in 4DCT MIP images, while CBCT volumes were largely reduced in contrast. When variable amplitudes from patient traces were used and CBCT ITVs were compared to 4DCT MIP ITVs there was a distinct trend in reduced ITV with increasing amplitude that was not seen when compared to true ITVs. Breathing patterns with a rest period following expiration resulted in well-defined superior edges and were better aligned using an edge-to-edge alignment technique. In most cases, sinusoidal motion patterns resulted in the closest agreements to true values and the smallest misalignments. Conclusions: Strategies are needed to compensate for volume losses at the extremes of motion for both 4DCT MIP and CBCT images for larger and varied amplitudes, and for patterns with rest periods following expiration. Lesions moving greater than 2 cm would warrant larger treatment margins added to the 4DCT MIP ITV to account for the volume being under-represented at the extremes of motion. Lesions moving with a rest period following expiration would be better aligned using an edge-to-edge alignment technique. Sinusoidal patterns represented the ideal clinical scenario, reinforcing the importance of investigating clinically relevant motions and their effects on 4DCT MIP and CBCT volumes. Since most patients do not breathe sinusoidally this may lead to misinterpretation of previous studies using only sinusoidal motion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-F-207-06: CT-Based Assessment of Tumor Volume in Malignant Pleural Mesothelioma

Purpose: To determine the potential utility of computed tomography (CT) scans in the assessment of physical tumor bulk in malignant pleural mesothelioma patients. Methods: Twenty-eight patients with malignant pleural mesothelioma were used for this study. A CT scan was acquired for each patient prior to surgical resection of the tumor (median time between scan and surgery: 27 days). After surgery, the ex-vivo tumor volume was measured by a pathologist using a water displacement method. Separately, a radiologist identified and outlined the tumor boundary on each CT section that demonstrated tumor. These outlines then were analyzed to determine the total volume of disease present, the number of sections with outlines, and the mean volume of disease per outlined section. Subsets of the initial patient cohort were defined based on these parameters, i.e. cases with at least 30 sections of disease with a mean disease volume of at least 3mL per section. For each subset, the R- squared correlation between CT-based tumor volume and physical ex-vivo tumor volume was calculated. Results: The full cohort of 28 patients yielded a modest correlation between CT-based tumor volume and the ex-vivo tumor volume with an R-squared value of 0.66. In general, as the mean tumor volume per section increased, the correlation of CT-based volume with the physical tumor volume improved substantially. For example, when cases with at least 40 CT sections presenting a mean of at least 2mL of disease per section were evaluated (n=20) the R-squared correlation increased to 0.79. Conclusion: While image-based volumetry for mesothelioma may not generally capture physical tumor volume as accurately as one might expect, there exists a set of conditions in which CT-based volume is highly correlated with the physical tumor volume. SGA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Contaminated Soil Volume Estimation at the Maywood Site - 12292

As part of the ongoing remediation process at the Maywood Formerly Utilized Sites Remedial Action Program properties, Argonne National Laboratory assisted the U.S. Army Corps of Engineers (USACE) New York District in revising contaminated soil volume estimates for the remaining areas of the Stepan/Sears properties that require soil remediation. As part of the volume estimation process, an initial conceptual site model (ICSM) was prepared for the entire site that captured existing information (with the exception of soil sampling results) pertinent to the possible location of surface and subsurface contamination above cleanup requirements. This ICSM was based on historical anecdotal information, aerial photographs, and the logs from several hundred soil cores that identified the depth of fill material and the depth to bedrock under the site. Specialized geostatistical software developed by Argonne was used to update the ICSM with historical sampling results and down-hole gamma survey information for hundreds of soil core locations; both sampling results and down-hole gamma data were coded to identify whether the results indicated the presence of contamination above site cleanup requirements. Significant effort was invested in developing complete electronic data sets for the site by incorporating data contained in various scanned documents, maps, etc. The updating process yielded both a best guess estimate of contamination volumes and upper and lower bounds on the volume estimate that reflected the estimate's uncertainty. The site-wide contaminated volume estimate (with associated uncertainty) was adjusted to reflect areas where remediation was complete; the result was a revised estimate of the remaining soil volumes requiring remediation that the USACE could use for planning. Other environmental projects may benefit from this process for estimating the volume of contaminated soil. A comparison of sample and DHG results for various stations with the site ICSM provides one measure of the quality of site understanding relative to the presence of contamination and its likely extent. A second measure of the quality of a contaminated soil volume estimate, in the case of BAASS, is a comparison of the best guess volume estimate with the conservative volume estimate. For Maywood, the conservative volume estimate is more than double the best guess. The data available for the site indicate that the preponderance of this difference is attributable to uncertainty about the exact depth of known contamination. The observed depth of contamination based on sample results and DHG data often varied significantly among adjacent soil cores. In the case of Maywood, where a significant amount of remediation has already taken place, a third measure of the quality of the volume estimates is the retrospective estimate of contaminated soil volumes for areas that have already been remediated [2]. The USACE is currently comparing the latest BAASS volume estimates for those areas with records indicating what was actually removed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

GIS-Based Modeling of Contaminated Soil Volumes at Multiple Sites in the Formerly Utilized Sites Remedial Action Program - 20149

The remediation of hazardous, toxic, and radioactive waste (HTRW) sites produces cost-related risks associated with the estimation of contaminated soil or debris volumes. Historical risk-management techniques include cost contingencies to cover volume uncertainties that affect project budgeting and decision-making. The Buffalo District teamed with project partners to lessen volume uncertainty and reduce project risks at multiple HTRW sites managed under the Formerly Utilized Sites Remedial Action Program (FUSRAP). Historical remedial investigations under FUSRAP commonly identified the presence of radiological material in site media, the associated human health risk, and then areas of remediation. To manage remedial execution and reduce risk, pre-design or remediation-phase sampling essentially 'chased' contamination, which was not conducive to efficient predictive budgeting derived from Feasibility Study (FS) cost analyses. The Buffalo District first optimized their approach to better understand volume uncertainty by utilizing the Argonne National Laboratory's Bayesian Approaches for Adaptive Spatial Sampling (BAASS) software [1]. BAASS processed soft data (e.g., gamma walk-over data) and spatial sampling data to estimate the lateral extent of contaminated soil irrespective of depth (i.e., gross contamination extent) and define areas of contaminant uncertainty. The software performed a binary transformation of contaminant concentrations at all sampling points based upon remedial action goals or a sum of ratios approach (i.e., clean, impacted, or range of impacts in soil). The model produced two-dimensional (horizontal) contaminant probability contours and statistical uncertainty in the sampling coverage and resulting contaminant extents. This method was translated vertically by partitioning the sampling data into depth brackets that produced a stacked representation of contaminant extents and uncertainty in the subsurface (i.e., similar to construction lifts). The results commonly led to a better understanding of project uncertainty and the need for sampling strategies that produce high-confidence soil volumes, which control costs. The BAASS-based delineations were eventually replaced by Empirical Bayesian Kriging (EBK) methods available in ArcGIS Spatial or 3D Analysts [2]. The EBK method calculates contaminant probability zones derived from user-controlled semivariograms of the spatial datasets. The resulting probability zones (e.g., 50% or 80% of contaminant probability) represent the two-dimensional surface delineation of the overall horizontal remedial area, similarly to BAASS. However, unlike BAASS, the vertical sampling data within these probability zones became vertical control points to contour a subterranean surface that connects subsurface points to the land-surface delineations of contamination. The resulting representation of horizontal and vertical impacts within an enclosed envelop (volume) of soil included uncertainty distributions that are used to plan uncertainty-reduction sampling. These data-driven and math-based models of three-dimensional sampling results produced well-bounded remedial volumes for project planning and better uncertainty predictions during project budgeting. The EBK method was applied to several FUSRAP sites managed by the Buffalo District and compared to less rigorously modeled sites previously remediated by the District. The comparison of modeled to actual remediated volumes provide a basis for validating the volume-estimation method. This comparison is important to ensure modeled volumes match physical boundaries of site remediation. FUSRAP sites with denser investigative sampling and lesser volume uncertainty proved useful in remedial planning and contracting. The Buffalo District noted that historical sites with sparser sampling arrays had greater disparity between estimated volumes and final remedial volumes. The benefit achieved over the cost of detailed soil sampling appears positive for FUSRAP projects, especially where impacts vary widely and appear unbounded by investigation-phase sampling. The subsequent Empirical Bayesian Kriging of contamination coupled with vertical contouring for soil estimations reduces uncertainty in soil volumes or indicates where sampling is required to reduce uncertainty, which together optimize remedial planning and budgeting. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Decreasing Irradiated Rat Lung Volume Changes Dose-Limiting Toxicity From Early to Late Effects

Purpose: Technological developments in radiation therapy result in smaller irradiated volumes of normal tissue. Because the risk of radiation therapy-induced toxicity generally depends on irradiated volume, changing volume could change the dose-limiting toxicity of a treatment. Recently, in our rat model, we found that early radiation-induced lung dysfunction (RILD) was closely related to irradiated volume dependent vascular remodeling besides inflammation. The exact relationship between early and late RILD is still unknown. Therefore, in this preclinical study we investigated the dose-volume relationship of late RILD, assessed its dependence on early and late pathologies and studied if decreasing irradiated volume changed the dose-limiting toxicity. Methods and Materials: A volume of 25%, 32%, 50%, 63%, 88%, or 100% of the rat lung was irradiated using protons. Until 26 weeks after irradiation, respiratory rates were measured. Macrovascular remodeling, pulmonary inflammation, and fibrosis were assessed at 26 weeks after irradiation. For all endpoints dose-volume response curves were made. These results were compared to our previously published early lung effects. Results: Early vascular remodeling and inflammation correlated significantly with early RILD. Late RILD correlated with inflammation and fibrosis, but not with vascular remodeling. In contrast to the early effects, late vascular remodeling, inflammation and fibrosis showed a primarily dose but not volume dependence. Comparison of respiratory rate increases early and late after irradiation for the different dose-distributions indicated that with decreasing irradiated volumes, the dose-limiting toxicity changed from early to late RILD. Conclusions: In our rat model, different pathologies underlie early and late RILD with different dose-volume dependencies. Consequently, the dose-limiting toxicity changed from early to late dysfunction when the irradiated volume was reduced. In patients, early and late RILD are also due to different pathologies. As such, new radiation techniques reducing irradiated volume might change the dose-limiting toxicity of the radiation therapy treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Tumor response parameters for head and neck cancer derived from tumor-volume variation during radiation therapy

Purpose: The main goal of this paper is to reconstruct a distribution of cell survival fractions from tumor-volume variation for a heterogeneous group of head and neck cancer patients and compare this distribution to the data from predictive assays. Methods: To characterize the tumor-volume variation during radiation therapy treatment, the authors use a two-level tumor-volume model of cell population that separates the entire tumor cell population into two subpopulations of viable cells and lethally damaged cells. This parameterized radiobiological model is integrated with a least squares objective function and a simulated annealing optimization algorithm to describe time-dependent tumor-volume variation rates in individual patients. Several constraints have been used in the optimization problem because tumor-volume variation during radiotherapy is described by a sum of exponentials; therefore, the problem of accurately fitting a model to measured data is ill-posed. The model was applied to measured tumor-volume variation curves from a clinical study on tumor-volume variation during radiotherapy for 14 head and neck cancer patients in which an integrated CT/linear particle accelerator (LINAC) system was used for tumor-volume measurements. Results: The two-level cell population tumor-volume modeling is capable of describing tumor-volume variation throughout the entire treatment for 11 of the 14 patients. For three patients, the tumor-volume variation was described only during the initial part of treatment, a fact that may be related to the neglected hypoxia in the two-level approximation. The predicted probability density distribution for the survival fractions agrees with the data obtained using in vitro studies with predictive assays. The mean value 0.35 of survival fraction obtained in this study is larger than the value 0.32 from in vitro studies, which could be expected because of greater repair in vivo. The mean half-life obtained in this study for the head-and-neck squamous cell carcinoma (SCC) is equal to 3.8 mean potential doubling times, which agrees with 4.0 mean potential doubling times obtained previously for lung SCC. Conclusions: The distribution of cell survival fractions obtained in this study support the hypothesis that the tumor-volume variation during radiotherapy treatment for head and neck cancer can be described by the two-level cell population tumor-volume model. This model can be used for in vivo evaluation of patient-specific radiobiological parameters that are needed for tumor-control probability evaluation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Globally Gridded Groundwater Extraction Volumes and Costs under Six Depletion and Ponded Depth Targets

This repository contains simulated outputs from superwell – a hydro-economic tool for long-term assessment of groundwater cost and supply – providing globally gridded groundwater extractable volumes and associated unit costs ($/km³) for accessible groundwater production, based on a variety of user-defined depletion and ponded depth scenarios. Key model documentation: Niazi, H., Ferencz, S. B., Graham, N. T., Yoon, J., Wild, T. B., Hejazi, M., Watson, D. J., & Vernon, C. R. (2025). Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1. Geoscientific Model Development, 18(5), 1737-1767. https://doi.org/10.5194/gmd-18-1737-2025 Find the source code of the superwell model on GitHub: https://github.com/JGCRI/superwell Repository Overview Main output: superwell_outputs.7z contains 6 files (4.5 GB) named as superwell_py_deep_all_0.*PD_0.*DL.csv. These files present superwell outputs of global groundwater extraction volumes and cost estimates on a 0.5° scale for six scenarios with different Ponded Depth (PD; 0.3 and 0.6 m) and Depletion Limit (DL; 5%, 25%, and 40% of available volume) targets over the entire pumping lifetime of a grid cell superwell_py_deep_all_0.3PD_0.25DL_sample_100.csv contains superwell outputs for 100 data points sampled to match the global inputs' distribution superwell_py_deep_all_0.3PD_0.25DL_Grid_72548.csv contains superwell output for a single grid cell concept_v5.png provides an overview of the superwell workflow Outputs Description year_number: year of pumping depletion_limit: set depletion limit (DL) as a volume fraction of total available groundwater Mappings: continent, country, gcam_basin_id, Basin_long_name, grid_id: geographic identifiers and basin information Inputs: grid_area (km²): area of the grid cell whyclass: hydrogeological classification of the aquifer permeability (m/day), porosity (%), total_thickness (m), depth_to_water (m): aquifer properties. The geo-processed input data has been published separately: https://doi.org/10.57931/2307831 Model outputs: orig_aqfr_sat_thickness (m), aqfr_sat_thickness (m): original and remaining/instantaneous saturated thickness of the aquifer hydraulic_conductivity (m/day), transmissivity (m²/day): hydraulic properties of the aquifer radius_of_influence (m), areal_extent (km²): well radius and area of influence from the center of the well number_of_wells (-): number of wells in a grid cell determined by a ratio of well area and grid area max_drawdown (m), drawdown (m), drawdown_interference (m): well and aquifer drawdown during extraction total_head (m): total lift for the groundwater (depth to water plus drawdown) total_well_length (m): total depth of wells drilled well_yield (m³/day): pumping rate or well yield power (kW), energy (kWh): power and energy required for pumping groundwater Volume Outputs: volume_produced_perwell (m³), cumulative_vol_produced_perwell (m³): production volume metrics per well volume_produced_allwells (m³), cumulative_vol_produced_allwells (m³): aggregate extraction volumes for all wells in a grid cell available_volume (m³): available groundwater in storage for the grid cell as determined by aquifer properties depleted_vol_fraction: fraction of total volume pumped over available volumes in a grid cell (same as depletion limit) Cost Outputs: well_installation_cost ($): well installation cost based on the hydrogeological complexity of the aquifer annual_capital_cost, maintenance_cost, nonenergy_cost ($): nonenergy costs energy_cost_rate ($/kWh): electricity rate energy_cost ($): energy cost of pumping groundwater total_cost_perwell ($), total_cost_allwells ($): total annual energy and non-energy cost for each and all wells in a grid cell a unit_cost ($/m³), unit_cost_per_km3 ($/km³), unit_cost_per_acreft ($/acre-ft): total cost of pumping a unit of groundwater, indicated for different spatial units Key Resources Model documentation: Niazi, H., Ferencz, S., Graham, N., Yoon, J., Wild, T., Hejazi, M., Watson, D., & Vernon, C. (2024; In-prep). Long-term Hydro-economic Assessment Tool for Evaluating Global Groundwater Cost and Supply: Superwell v1. Geoscientific Model Development. Input data: Niazi, H., Watson, D., Hejazi, M., Yonkofski, C., Ferencz, S., Vernon, C., Graham, N., Wild, T., & Yoon, J. (2024). Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins. MSD-LIVE Data repository. https://doi.org/10.57931/2307831 superwell source code: https://github.com/JGCRI/superwell Cite as Niazi, H., Ferencz, S., Yoon, J., Graham, N., Wild, T., Hejazi, M., Watson, D., & Vernon, C. (2024). Globally Gridded Groundwater Extraction Volumes and Costs under Six Depletion and Ponded Depth Targets. MSD-LIVE Data repository. https://doi.org/10.57931/2307832 Contact Reach out to Hassan Niazi or Stephen Ferencz or open an issue in the superwell repository for questions or suggestions.

Earth Systems↗
DOE OSTI2020

Excavation Volume Growth Factors at Environmental Remediation Sites - 20318

The U.S. Army Corps of Engineers (USACE) manages numerous environmental remediation projects in accordance with the Comprehensive Environmental Response, Compensation, and Liability Act, otherwise known as CERCLA. These include projects for the Formerly Utilized Sites Remedial Action Program (FUSRAP). Utilizing the CERCLA framework to address these projects requires detailed cost estimates and a significant portion of costs are associated with the volume of material to be excavated and that material's final disposition. Accordingly, understanding the expected volumes and uncertainty associated with those volumes is vital to project cost estimating. These estimates are completed at various stages of the CERCLA process, thus the project team has varying degrees of information available from which to develop these estimates depending on how far along the project is. Understanding the factors contributing to volume growth (increase in volume of material from that originally estimated) is a crucial element to determining volume and cost uncertainty. This paper presents a case study of a FUSRAP site which involves excavation and offsite disposal of contaminated soils from complex commercial, industrial, and residential properties. Original volume estimates were compared to post excavation volumes on a property by property basis. Reasons for differences are determined along with magnitude of impacts to cost estimating. For both residential and commercial property types, volume estimating factors, uncertainty considerations, and methods to account for each are discussed with emphasis on volume growth considerations. Cost estimating model input considerations are discussed with specific emphasis on accounting for volume uncertainty at the Feasibility Study (FS) phase of CERCLA. Underestimating or overestimating costs at the FS phase has repercussions under CERCLA that may impact project close out or completion schedule. Discussions presented will be helpful to both reviewers and preparers of cost estimates involving excavations. Additionally, project planners may be able to use the information to plan for volume growth contingencies. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

Primary Tumor Volume Is an Important Predictor of Clinical Outcomes Among Patients With Locally Advanced Squamous Cell Cancer of the Head and Neck Treated With Definitive Chemoradiotherapy

Purpose: The tumor volume has been established as a significant predictor of outcomes among patients with head-and-neck cancer undergoing radiotherapy alone. The present study attempted to add to the existing data on tumor volume as a prognostic factor among patients undergoing chemoradiotherapy. Methods and Materials: A total of 78 patients who had undergone definitive chemoradiotherapy for Stage III-IV squamous cell cancer of the hypopharynx, oropharynx, and larynx were identified. The primary tumor volumes were calculated from the treatment planning computed tomography scans, and these were correlated to the survival and tumor control data obtained from the retrospective analysis. Results: The interval to progression correlated with the primary tumor volume (p = .007). The critical cutoff point for the tumor volume was identified as 35 cm{sup 3}, and patients with a tumor volume <35 cm{sup 3} had a significantly better prognosis than those with a tumor volume >35 cm{sup 3} at 5 years (43% vs. 71%, p = .010). Longer survival was also correlated with smaller primary tumor volumes (p = .022). Similarly, patients with a primary tumor volume <35 cm{sup 3} had a better prognosis in terms of both progression-free survival (61% vs. 33%, p = .004) and overall survival (84% vs. 41%, p = < .001). On multivariate analysis, the primary tumor volume was the best predictor of recurrence (hazard ratio 4.7, 95% confidence interval 1.9-11.6; p = .001) and survival (hazard ratio 10.0, 95% confidence interval 2.9-35.1; p = < .001). In contrast, the T stage and N stage were not significant factors. Analysis of variance revealed that tumors with locoregional failure were on average 21.6 cm{sup 3} larger than tumors without locoregional failure (p = .028) and 27.1-cm{sup 3} larger than tumors that recurred as distant metastases (p = .020). Conclusion: The results of our study have shown that the primary tumor volume is a significant prognostic factor in patients with advanced cancer of the head and neck undergoing definitive chemoradiotherapy and correlated with the treatment outcomes better than the T or N stage.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Evaluation of an Automatic Registration-Based Algorithm for Direct Measurement of Volume Change in Tumors

Purpose: Assuming that early tumor volume change is a biomarker for response to therapy, accurate quantification of early volume changes could aid in adapting an individual patient's therapy and lead to shorter clinical trials. We investigated an image registration-based approach for tumor volume change quantification that may more reliably detect smaller changes that occur in shorter intervals than can be detected by existing algorithms. Methods and Materials: Variance and bias of the registration-based approach were evaluated using retrospective, in vivo, very-short-interval diffusion magnetic resonance imaging scans where true zero tumor volume change is unequivocally known and synthetic data, respectively. The interval scans were nonlinearly registered using two similarity measures: mutual information (MI) and normalized cross-correlation (NCC). Results: The 95% confidence interval of the percentage volume change error was (-8.93% to 10.49%) for MI-based and (-7.69%, 8.83%) for NCC-based registrations. Linear mixed-effects models demonstrated that error in measuring volume change increased with increase in tumor volume and decreased with the increase in the tumor's normalized mutual information, even when NCC was the similarity measure being optimized during registration. The 95% confidence interval of the relative volume change error for the synthetic examinations with known changes over {+-}80% of reference tumor volume was (-3.02% to 3.86%). Statistically significant bias was not demonstrated. Conclusion: A low-noise, low-bias tumor volume change measurement algorithm using nonlinear registration is described. Errors in change measurement were a function of tumor volume and the normalized mutual information content of the tumor.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Assessing and accounting for the impact of respiratory motion on FDG uptake and viable volume for liver lesions in free-breathing PET using respiration-suspended PET images as reference

Purpose: To assess and account for the impact of respiratory motion on the variability of activity and volume determination of liver tumor in positron emission tomography (PET) through a comparison between free-breathing (FB) and respiration-suspended (RS) PET images. Methods: As part of a PET/computed tomography (CT) guided percutaneous liver ablation procedure performed on a PET/CT scanner, a patient's breathing is suspended on a ventilator, allowing the acquisition of a near-motionless PET and CT reference images of the liver. In this study, baseline RS and FB PET/CT images of 20 patients undergoing thermal ablation were acquired. The RS PET provides near-motionless reference in a human study, and thereby allows a quantitative evaluation of the effect of respiratory motion on PET images obtained under FB conditions. Two methods were applied to calculate tumor activity and volume: (1) threshold-based segmentation (TBS), estimating the total lesion glycolysis (TLG) and the segmented volume and (2) histogram-based estimation (HBE), yielding the background-subtracted lesion (BSL) activity and associated volume. The TBS method employs 50% of the maximum standardized uptake value (SUV{sub max}) as the threshold for tumors with SUV{sub max} ≥ 2× SUV{sub liver-bkg}, and tumor activity above this threshold yields TLG{sub 50%}. The HBE method determines local PET background based on a Gaussian fit of the low SUV peak in a SUV-volume histogram, which is generated within a user-defined and optimized volume of interest containing both local background and lesion uptakes. Voxels with PET intensity above the fitted background were considered to have originated from the tumor and used to calculate the BSL activity and its associated lesion volume. Results: Respiratory motion caused SUV{sub max} to decrease from RS to FB by −15% ± 11% (p = 0.01). Using TBS method, there was also a decrease in SUV{sub mean} (−18% ± 9%, p = 0.01), but an increase in TLG{sub 50%} (18% ± 36%) and in the segmented volume (47% ± 52%, p = 0.01) from RS to FB PET images. The background uptake in normal liver was stable, 1% ± 9%. In contrast, using the HBE method, the differences in both BSL activity and BSL volume from RS to FB were −8% ± 10% (p = 0.005) and 0% ± 16% (p = 0.94), respectively. Conclusions: This is the first time that almost motion-free PET images of the human liver were acquired and compared to free-breathing PET. The BSL method's results are more consistent, for the calculation of both tumor activity and volume in RS and FB PET images, than those using conventional TBS. This suggests that the BSL method might be less sensitive to motion blurring and provides an improved estimation of tumor activity and volume in the presence of respiratory motion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-242: Volume-Dependence of Quantitative Imaging Features From CT and CE-CT Images of NSCLC

Purpose: To determine whether tumor volume plays a significant role in the values obtained for texture features when they are extracted from computed tomography (CT) images of non-small cell lung cancer (NSCLC). We also sought to identify whether features can be reliably measured at all volumes or if a minimum volume threshold should be recommended. Methods: Eleven features were measured on 40 CT and 32 contrast-enhanced CT (CECT) patient images for this study. Features were selected for their prognostic/diagnostic value in previous publications. Direct correlations between these textures and volume were evaluated using the Spearman correlation coefficient. Any texture that the Wilcoxon rank-sum test was used to compare the variation above and below a volume cutoff. Four different volume thresholds (5, 10, 15, and 20 cm{sup 3}) were tested. Results: Four textures were found to be significantly correlated with volume in both the CT and CE-CT images. These were busyness, coarseness, gray-level nonuniformity, and run-length nonuniformity with correlation coefficients of 0.92, −0.96, 0.94, and 0.98 for the CT images and 0.95, −0.97, 0.98, and 0.98 for the CE-CT images. After volume normalization, the correlation coefficients decreased substantially. For the data obtained from the CT images, the results of the Wilcoxon rank-sum test were significant when volume thresholds of 5–15 cm3 were used. No volume threshold was shown to be significant for the CE-CT data. Conclusion: Equations for four features that have been used in several published studies were found to be volume-dependent. Future studies should consider implementing normalization factors or removing these features entirely to prevent this potential source of redundancy or bias. This work was supported in part by National Cancer Institute grant R03CA178495-01. Xenia Fave is a recipient of the American Association of Physicists in Medicine Graduate Fellowship.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-378: Evaluation of Dose-Volume Variability and Parameters Between Prostate IMRT and VMAT Plans

Purpose: This study compared the rectal dose-volume consistency, equivalent uniform dose (EUD) and normal tissue complication probability (NTCP) in prostate intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). Methods: For forty prostate IMRT and fifty VMAT patients treated using the same dose prescription (78 Gy/39 fraction) and dose-volume criteria in inverse planning optimization, the rectal EUD and NTCP were calculated for each patient. The rectal dose-volume consistency, showing the variability of dose-volume histogram (DVH) among patients, was defined and calculated based on the deviation between the mean and corresponding rectal DVH. Results: From both the prostate IMRT and VMAT plans, the rectal EUD and NTCP were found decreasing with the rectal volume. The decrease rates for the IMRT plans (EUD = 0.47 × 10{sup −3} Gy cm{sup −3} and NTCP = 3.94 × 10{sup −2} % cm{sup −3}) were higher than those for the VMAT (EUD = 0.28 × 10{sup −3} Gy cm{sup −3} and NTCP = 2.61 × 10{sup −2} % cm{sup −3}). In addition, the dependences of the rectal EUD and NTCP on the dose-volume consistency were found very similar between the prostate IMRT and VMAT plans. This shows that both delivery techniques have similar variations of the rectal EUD and NTCP on the dose-volume consistency. Conclusion: Dependences of the dose-volume consistency on the rectal EUD and NTCP were compared between the prostate IMRT and VMAT plans. It is concluded that both rectal EUD and NTCP decreased with an increase of the rectal volume. The variation rates of the rectal EUD and NTCP on the rectal volume were higher for the IMRT plans than VMAT. However, variations of the rectal dose-volume consistency on the rectal EUD and NTCP were found not significant for both delivery techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Spatial Transferability of Machine Learning Based Volume Estimation Models

High-quality traffic volume data is essential for efficient transportation planning and operations. However, such high-quality data is expensive to collect, owing primarily to the high capital cost of installing and maintaining continuous counting stations (CCSs). Recent availability of probe-based vehicle data offers a cost-effective solution for increasing the observability of traffic volumes. However, having ample ground truth traffic data is a prerequisite for developing robust volume estimation models. Though this might not be a big issue in many states, states with scarce CCS data might be able to benefit from robust volume estimation models developed in (adjacent) data-rich states. While there is a reasonable amount of spatial transferability research in the transportation domain, there is a dearth of knowledge on the spatial transferability of probe-based volume estimation models. To address this gap, this paper explores spatial transferability of volume estimation models developed from data in three states (Colorado, North Carolina, and Pennsylvania). Results indicate that it is extremely important to maintain temporal consistency when attempting spatial transferability of volume estimation models. It was also found that models trained on regions with lower peak traffic volumes will limit the performance of models transferred to states with higher peak hourly traffic volumes. Corroborating findings from existing spatial transferability research on other topics, it was found that a meta-model (developed using data from multiple states) performs better than volume estimation models developed within any one of the states.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2012

Vaginal Motion and Bladder and Rectal Volumes During Pelvic Intensity-Modulated Radiation Therapy After Hysterectomy

Purpose: To evaluate variations in bladder and rectal volume and the position of the vaginal vault during a 5-week course of pelvic intensity-modulated radiation therapy (IMRT) after hysterectomy. Methods and Materials: Twenty-four patients were instructed how to fill their bladders before simulation and treatment. These patients underwent computed tomography simulations with full and empty bladders and then underwent rescanning twice weekly during IMRT; patients were asked to have full bladder for treatment. Bladder and rectal volumes and the positions of vaginal fiducial markers were determined, and changes in volume and position were calculated. Results: The mean full and empty bladder volumes at simulation were 480 cc (range, 122-1,052) and 155 cc (range, 49-371), respectively. Bladder volumes varied widely during IMRT: the median difference between the maximum and minimum volumes was 247 cc (range, 96-585). Variations in rectal volume during IMRT were less pronounced. For the 16 patients with vaginal fiducial markers in place throughout IMRT, the median maximum movement of the markers during IMRT was 0.59 cm in the right-left direction (range, 0-0.9), 1.46 cm in the anterior-posterior direction (range, 0.8-2.79), and 1.2 cm in the superior-inferior direction (range, 0.6-2.1). Large variations in rectal or bladder volume frequently correlated with significant displacement of the vaginal apex. Conclusion: Although treatment with a full bladder is usually preferred because of greater sparing of small bowel, our data demonstrate that even with detailed instruction, patients are unable to maintain consistent bladder filling. Variations in organ position during IMRT can result in marked changes in the position of the target volume and the volume of small bowel exposed to high doses of radiation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2012

Tumor Volume Reduction Rate After Preoperative Chemoradiotherapy as a Prognostic Factor in Locally Advanced Rectal Cancer

Purpose: To investigate the prognostic significance of tumor volume reduction rate (TVRR) after preoperative chemoradiotherapy (CRT) in locally advanced rectal cancer (LARC). Methods and Materials: In total, 430 primary LARC (cT3-4) patients who were treated with preoperative CRT and curative radical surgery between May 2002 and March 2008 were analyzed retrospectively. Pre- and post-CRT tumor volumes were measured using three-dimensional region-of-interest MR volumetry. Tumor volume reduction rate was determined using the equation TVRR (%) = (pre-CRT tumor volume - post-CRT tumor volume) Multiplication-Sign 100/pre-CRT tumor volume. The median follow-up period was 64 months (range, 27-99 months) for survivors. Endpoints were disease-free survival (DFS) and overall survival (OS). Results: The median TVRR was 70.2% (mean, 64.7% {+-} 22.6%; range, 0-100%). Downstaging (ypT0-2N0M0) occurred in 183 patients (42.6%). The 5-year DFS and OS rates were 77.7% and 86.3%, respectively. In the analysis that included pre-CRT and post-CRT tumor volumes and TVRR as continuous variables, only TVRR was an independent prognostic factor. Tumor volume reduction rate was categorized according to a cutoff value of 45% and included with clinicopathologic factors in the multivariate analysis; ypN status, circumferential resection margin, and TVRR were significant prognostic factors for both DFS and OS. Conclusions: Tumor volume reduction rate was a significant prognostic factor in LARC patients receiving preoperative CRT. Tumor volume reduction rate data may be useful for tailoring surgery and postoperative adjuvant therapy after preoperative CRT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models

Purpose: The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Methods: Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. Results: In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: −11.6%–23.8%) and 14.6% (range: −7.3%–27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: −6.8%–40.3%) and 13.1% (range: −1.5%–52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: −11.1%–20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. Conclusions: A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography images and facilitate improved treatment management.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-J-12: A New Stereological Method for Tumor Volume Evaluation for Esophageal Cancer

Purpose: Stereological method used to obtain three dimensional quantitative information from two dimensional images is a widely used tool in the study of cells and pathology. But the feasibility of the method for quantitative evaluation of volumes with 3D image data sets for radiotherapy clinical application has not been explored. On the other hand, a quick, easy-to-use and reliable method is highly desired in image-guided-radiotherapy(IGRT) for tumor volume measurement for the assessment of response to treatment. To meet this need, a stereological method for evaluating tumor volumes for esophageal cancer is presented in this abstract. Methods: The stereology method was optimized by selecting the appropriate grid point distances and sample types. 7 patients with esophageal cancer were selected retrospectively for this study, each having pre and post treatment computed tomography (CT) scans. Stereological measurements were performed for evaluating the gross tumor volume (GTV) changes after radiotherapy and the results was compared with the ones by planimetric measurements. Two independent observers evaluated the reproducibility for volume measurement using the new stereological technique. Results: The intraobserver variation in the GTV volume estimation was 3.42±1.68cm3 (the Wilcoxon matched-pairs test Resultwas Z=−1.726,P=0.084>0.05); the interobserver variation in the GTV volume estimation was 22.40±7.23 cm3 (Z=−3.296,P=0.083>0.05), which showed the consistency in GTV volume calculation with the new method for the same and different users. The agreement level between the results from the two techniques was also evaluated. Difference between the measured GTVs was 20.10±5.35 cm3 (Z=−3.101,P=0.089>0.05). Variation of the measurement results using the two techniques was low and clinically acceptable. Conclusion: The good agreement between stereological and planimetric techniques proves the reliability of the stereological tumor volume estimations. The optimized stereological technique described in this abstract may provide a quick, unbiased and reproducible tool for tumor volume estimation for treatment response assessment. Supported by NSFC (#81041107, #81171342 and #31000784)

60 APPLIED LIFE SCIENCES↗