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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

The Use of High Energy Heavy Ion Facilities for Single Event Effects (SEE) Testing: A Perspective on Return on Investment (ROI)

With challenges related to testing highly complex integrated circuits as well as entire systems continuing to grow, the use of higher energy heavy ions for single-event effects (SEE) testing becomes a critical technical need. This presentation, however, focuses only partially on the technical side with the main emphasis on the economics of using a high-energy heavy ion beam and comparing via notional cost models for testing.

Kenneth A. LaBel↗
DOE OSTI2017

Increasing ROI Using Your Digital Twin for Model Based Engineering

The purpose of this work is to identify innovative ways of using the plant reference simulator or digital twin differently than it has traditionally been used in the past. This paper will identify reasons that the plant reference simulator will support varying levels of model based design and engineering. I will point out real world examples in which the plant reference simulator was used to identify problems with engineering designs, digital control systems and plant modifications. The earlier these issues can be identified and resolved, the less impact they have on the plant modification or upgrade. By using the plant reference simulator earlier in the engineering process, utilities and engineering organizations can minimize costly outage extensions and increase the return on the investment made in the simulator.

42 ENGINEERING↗
DOE OSTI2015

SU-E-J-32: Dosimetric Evaluation Based On Pre-Treatment Cone Beam CT for Spine Stereotactic Body Radiotherapy: Does Region of Interest Focus Matter?

Purpose: Spine stereotactic body radiotherapy requires very conformal dose distributions and precise delivery. Prior to treatment, a KV cone-beam CT (KV-CBCT) is registered to the planning CT to provide image-guided positional corrections, which depend on selection of the region of interest (ROI) because of imperfect patient positioning and anatomical deformation. Our objective is to determine the dosimetric impact of ROI selections. Methods: Twelve patients were selected for this study with the treatment regions varied from C-spine to T-spine. For each patient, the KV-CBCT was registered to the planning CT three times using distinct ROIs: one encompassing the entire patient, a large ROI containing large bony anatomy, and a small target-focused ROI. Each registered CBCT volume, saved as an aligned dataset, was then sent to the planning system. The treated plan was applied to each dataset and dose was recalculated. The tumor dose coverage (percentage of target volume receiving prescription dose), maximum point dose to 0.03 cc of the spinal cord, and dose to 10% of the spinal cord volume (V10) for each alignment were compared to the original plan. Results: The average magnitude of tumor coverage deviation was 3.9%±5.8% with external contour, 1.5%±1.1% with large ROI, 1.3%±1.1% with small ROI. Spinal cord V10 deviation from plan was 6.6%±6.6% with external contour, 3.5%±3.1% with large ROI, and 1.2%±1.0% with small ROI. Spinal cord max point dose deviation from plan was: 12.2%±13.3% with external contour, 8.5%±8.4% with large ROI, and 3.7%±2.8% with small ROI. Conclusion: A small ROI focused on the target results in the smallest deviation from planned dose to target and cord although rotations at large distances from the targets were observed. It is recommended that image fusion during CBCT focus narrowly on the target volume to minimize dosimetric error. Improvement in patient setups may further reduce residual errors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-183: Interior Region-Of-Interest Tomography by Using Inverse Geometry System

Purpose: The inverse geometry computed tomography (IGCT) composed of multiple source and small size detector has several merits such as reduction of scatter effect and large volumetric imaging within one rotation without cone-beam artifact, compared to conventional cone-beam computed tomography (CBCT). By using this multi-source characteristics, we intend to present a selective and multiple interior region-of-interest (ROI) imaging method by using a designed source on-off sequence of IGCT. Methods: All of the IGCT sources are operated one by one sequentially, and each projection in the shape of narrow cone-beam covers its own partial volume of full field of view (FOV) determined from system geometry. Thus, through controlling multi source operation, limited irradiation within ROI is possible and selective radon space data for ROI imaging can be acquired without additional X-ray filtration. With this feature, we designed a source on-off sequence for multi ROI-IGCT imaging, and projections of ROI-IGCT were generated by using the on-off sequence. Multi ROI-IGCT images were reconstructed by using filtered back-projection algorithm. All these imaging process of our study has been performed by utilizing digital phantom and patient CT data. ROI-IGCT images of the phantom were compared to CBCT image and the phantom data for the image quality evaluation. Results: Image quality of ROI-IGCT was comparable to that of CBCT. However, the distal axial-plane from the FOV center, large cone-angle region, ROI-IGCT showed uniform image quality without significant cone-beam artifact contrary to CBCT. Conclusion: ROI-IGCT showed comparable image quality and has the capability to provide multi ROI image within a rotation. Projection of ROI-IGCT is performed by selective irradiation, hence unnecessary imaging dose to non-interest region can be reduced. In this regard, it seems to be useful for diagnostic or image guidance purpose in radiotherapy such as low dose target localization and patient alignment. This research was supported by the Mid-career Researcher Program through NRF funded by the Ministry of Science, ICT & Future Planning of Korea (NRF-2014R1A2A1A10050270) and by the Radiation Technology R&D program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (No. 2013M2A2A7038291)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-37: Low-Dose Real-Time Region-Of-Interest X-Ray Fluoroscopic Imaging with a GPU-Accelerated Spatially Different Bilateral Filtering

Purpose: The purpose of our study is to reduce imaging radiation dose while maintaining image quality of region of interest (ROI) in X-ray fluoroscopy. A low-dose real-time ROI fluoroscopic imaging technique which includes graphics-processing-unit- (GPU-) accelerated image processing for brightness compensation and noise filtering was developed in this study. Methods: In our ROI fluoroscopic imaging, a copper filter is placed in front of the X-ray tube. The filter contains a round aperture to reduce radiation dose to outside of the aperture. To equalize the brightness difference between inner and outer ROI regions, brightness compensation was performed by use of a simple weighting method that applies selectively to the inner ROI, the outer ROI, and the boundary zone. A bilateral filtering was applied to the images to reduce relatively high noise in the outer ROI images. To speed up the calculation of our technique for real-time application, the GPU-acceleration was applied to the image processing algorithm. We performed a dosimetric measurement using an ion-chamber dosimeter to evaluate the amount of radiation dose reduction. The reduction of calculation time compared to a CPU-only computation was also measured, and the assessment of image quality in terms of image noise and spatial resolution was conducted. Results: More than 80% of dose was reduced by use of the ROI filter. The reduction rate depended on the thickness of the filter and the size of ROI aperture. The image noise outside the ROI was remarkably reduced by the bilateral filtering technique. The computation time for processing each frame image was reduced from 3.43 seconds with single CPU to 9.85 milliseconds with GPU-acceleration. Conclusion: The proposed technique for X-ray fluoroscopy can substantially reduce imaging radiation dose to the patient while maintaining image quality particularly in the ROI region in real-time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

TU-G-BRD-02: Automated Systematic Quality Assurance Program for Radiation Oncology Information System Upgrades

Purpose: To: (1) describe an independent, automated, systematic software-based protocol for verifying clinical data accuracy/integrity for mitigation of data corruption/loss risks following radiation oncology information system (ROIS) upgrades; and (2) report on application of this approach in an academic/community practice environment. Methods: We propose a robust approach to perform quality assurance on the ROIS after an upgrade, targeting four data sources: (1) ROIS relational database; (2) ROIS DICOM interface; (3) ROIS treatment machine data configuration; and (4) ROIS-generated clinical reports. We investigated the database schema for differences between pre-/post-upgrade states. Paired DICOM data streams for the same object (such as RT-Plan/Treatment Record) were compared between pre-/post-upgrade states for data corruption. We examined machine configuration and related commissioning data files for changes and corruption. ROIS-generated treatment appointment and treatment parameter reports were compared to ensure patient encounter and treatment plan accuracy. This protocol was supplemented by an end-to-end clinical workflow test to verify essential ROI functionality and integrity of components interfaced during patient care chain of activities. We describe the implementation of this protocol during a Varian ARIA system upgrade at our clinic. Results: We verified 1,638 data tables with 2.4 billion data records. For 222 under-treatment patients, 605 DICOM RT plans and 13,480 DICOM treatment records retrieved from the ROIS DICOM interface were compared, with no differences in fractions, doses delivered, or treatment parameters. We identified 82 new data tables and 78 amended/deleted tables consistent with the upgrade. Reports for 5,073 patient encounters over a 2-week horizon were compared and were identical to those before the upgrade. Content in 12,237 xml machine files was compared, with no differences identified. Conclusion: An independent QA/validation approach for ROIS upgrades was developed and implemented at our clinic. The success of this approach ensures a robust QA of ROIS upgrades without manual paper/electronic checks and associated intensive labor.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-AB-BRA-12: Impact of Image Registration Algorithms On the Prediction of Pathological Response with Radiomic Textures

Purpose: Tumor regions-of-interest (ROI) can be propagated from the pre-onto the post-treatment PET/CT images using image registration of their CT counterparts, providing an automatic way to compute texture features on longitudinal scans. This exploratory study assessed the impact of image registration algorithms on textures to predict pathological response. Methods: Forty-six esophageal cancer patients (1 tumor/patient) underwent PET/CT scans before and after chemoradiotherapy. Patients were classified into responders and non-responders after the surgery. Physician-defined tumor ROIs on pre-treatment PET were propagated onto the post-treatment PET using rigid and ten deformable registration algorithms. One co-occurrence, two run-length and size zone matrix textures were computed within all ROIs. The relative difference of each texture at different treatment time-points was used to predict the pathologic responders. Their predictive value was assessed using the area under the receiver-operating-characteristic curve (AUC). Propagated ROIs and texture quantification resulting from different algorithms were compared using overlap volume (OV) and coefficient of variation (CoV), respectively. Results: Tumor volumes were better captured by ROIs propagated by deformable rather than the rigid registration. The OV between rigidly and deformably propagated ROIs were 69%. The deformably propagated ROIs were found to be similar (OV∼80%) except for fast-demons (OV∼60%). Rigidly propagated ROIs with run-length matrix textures failed to significantly differentiate between responders and non-responders (AUC=0.65, p=0.07), while the differentiation was significant with other textures (AUC=0.69–0.72, p<0.03). Among the deformable algorithms, fast-demons was the least predictive (AUC=0.68–0.71, p<0.04). ROIs propagated by all other deformable algorithms with any texture significantly predicted pathologic responders (AUC=0.71–0.78, p<0.01) despite substantial variation in texture quantification (CoV>70%). Conclusion: Propagated ROIs using deformable registration for all textures can lead to accurate prediction of pathologic response, potentially expediting the temporal texture analysis process. However, rigid and fast-demons deformable algorithms are not recommended due to their inferior performance compared to other algorithms. The project was supported in part by a Kaye Scholar Award.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Single reader between-cases AUC estimator with nested data

The area under the receiver operating characteristic curve (AUC) is widely used in evaluating diagnostic performance for many clinical tasks. It is still challenging to evaluate the reading performance of distinguishing between positive and negative regions of interest (ROIs) in the nested-data problem, where multiple ROIs are nested within the cases. To address this issue, we identify two kinds of AUC estimators, within-cases AUC and between-cases AUC. We focus on the between-cases AUC estimator, since our main research interest is in patient-level diagnostic performance rather than location-level performance (the ability to separate ROIs with and without disease within each patient). Another reason is that as the case number increases, the number of between-cases paired ROIs is much larger than the number of within-cases ROIs. We provide estimators for the variance of the between-cases AUC and for the covariance when there are two readers. We derive and prove the above estimators’ theoretical values based on a simulation model and characterize their behavior using Monte Carlo simulation results. We also provide a real-data example. Moreover, we connect the distribution-based simulation model with the simulation model based on the linear mixed-effect model, which helps better understand the sources of variation in the simulated dataset.

Health Care Sciences & Services↗
DOE OSTI2020

How Do Electricity Pricing Programs Impact the Selection of Energy Efficiency Measures? - A Case Study with U.S. Medium Office Buildings

Building owners usually select energy efficiency measures (EEMs) by referring to return on investment (ROI). Current studies tend to apply static energy price to estimate ROI. However, more and more buildings are adopting dynamic electricity pricing programs. To understand how electricity pricing programs impact the selection of EEMs, this paper presents an analysis of the ROIs of EEMs under different pricing programs using U.S. medium office buildings as an example. Eight EEMs in four typical cities are selected as case studies. Considering five electricity pricing programs scenarios (one static program and four dynamic programs), EEMs are selected based on their ROIs. The main findings are: (1) The ROIs of EEMs change under different pricing programs. (2) In Honolulu, Buffalo, and Denver, replacing interior fixtures with higher-efficiency fixtures has a significantly higher ROI than the rest EEMs under all five pricing programs. However, the ROI of this EEM in Honolulu ranges from 28% to 47% for different pricing programs. (3) Similarly, in Fairbanks, replace heating coil with higher-efficiency coil produce higher ROI than the rest under all five pricing programs. (4) For other EEMs, their ROI rankings vary according to electricity pricing programs.

demand response↗
DOE OSTI2015

SU-D-204-07: Comparison of AAPM TG150 Draft Image Receptor Tests with Vendor Automated QC Tests for Five Mobile DR Units

Purpose: To determine the consistency of digital detector (DR) tests recommended by AAPM TG150 and tests provided by commercially available DirectView Total Quality Tool (TQT). Methods: The DR tests recommended by the TG150 Detector Subgroup[1] were performed on 4 new Carestream DRX-Revolution and one Carestream DRX1C retrofit of a GE AMX-4 that had been in service for three years. After detector calibration, flat-field images plus images of two bar patterns oriented parallel and perpendicular to the A-C axis, were acquired at conditions recommended by TG150. Raw images were harvested and then analyzed using a MATLAB software previously validated[2,3,4]. Data were analyzed using ROIs of two different dimensions: 1) 128 x 128 ROIs matching the detector electronics; and 2) 256 x 256 ROIs, each including 4 adjacent smaller ROIs. TG150 metrics from 128 x 128 ROIs were compared to TQT metrics, which are also obtained from 128 x 128 ROIs[5]. Results: The results show that both TG150 and TQT measurements were consistent among these detectors. Differences between TG150 and TQT values appear systematic. Compared with 128 x 128 ROIs, noise and SNR non-uniformity were lower with 256 x 256 ROIs, although signal non-uniformity was similar, indicating detectors were appropriately calibrated for gain and offset. MTF of the retrofit unit remained essentially the same between 2012 and 2015, but was inferior to the new units. The older generator focal spot is smaller (0.75mm vs. 1.2mm), and the SID for acquisition is 182cm as well, so focal spot dimensions cannot explain the difference. The difference in MTF may be secondary to differences in generator X-ray spectrum or by unannounced changes in detector architecture. Further investigation is needed. Conclusion: The study shows that both TG150 and TQT tests are consistent. The numerical value of some metrics are dependent on ROI size.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-202-04: Validation of Deformable Image Registration Algorithms for Head and Neck Adaptive Radiotherapy in Routine Clinical Setting

Purpose: To evaluate the ROI contours and accumulated dose difference using different deformable image registration (DIR) algorithms for head and neck (H&N) adaptive radiotherapy. Methods: Eight H&N cancer patients were randomly selected from the affiliated hospital. During the treatment, patients were rescanned every week with ROIs well delineated by radiation oncologist on each weekly CT. New weekly treatment plans were also re-designed with consistent dose prescription on the rescanned CT and executed for one week on Siemens CT-on-rails accelerator. At the end, we got six weekly CT scans from CT1 to CT6 including six weekly treatment plans for each patient. The primary CT1 was set as the reference CT for DIR proceeding with the left five weekly CTs using ANACONDA and MORFEUS algorithms separately in RayStation and the external skin ROI was set to be the controlling ROI both. The entire calculated weekly dose were deformed and accumulated on corresponding reference CT1 according to the deformation vector field (DVFs) generated by the two different DIR algorithms respectively. Thus we got both the ANACONDA-based and MORFEUS-based accumulated total dose on CT1 for each patient. At the same time, we mapped the ROIs on CT1 to generate the corresponding ROIs on CT6 using ANACONDA and MORFEUS DIR algorithms. DICE coefficients between the DIR deformed and radiation oncologist delineated ROIs on CT6 were calculated. Results: For DIR accumulated dose, PTV D95 and Left-Eyeball Dmax show significant differences with 67.13 cGy and 109.29 cGy respectively (Table1). For DIR mapped ROIs, PTV, Spinal cord and Left-Optic nerve show difference with −0.025, −0.127 and −0.124 (Table2). Conclusion: Even two excellent DIR algorithms can give divergent results for ROI deformation and dose accumulation. As more and more TPS get DIR module integrated, there is an urgent need to realize the potential risk using DIR in clinical.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-14: PET Based Radiomics to Predict Outcomes in Patients with Hodgkin Lymphoma

Purpose: To identify PET-based radiomics features associated with high refractory/relapsed disease risk for Hodgkin lymphoma patients. Methods: A total of 251 Hodgkin lymphoma patients including 19 primary refractory and 9 relapsed patients were investigated. All patients underwent an initial pre-treatment diagnostic FDG PET/CT scan. All cancerous lymph node regions (ROIs) were delineated by an experienced physician based on thresholding each volume of disease in the anatomical regions to SUV>2.5. We extracted 122 image features and evaluated the effect of ROI selection (the largest ROI, the ROI with highest mean SUV, merged ROI, and a single anatomic region [e.g. mediastinum]) on classification accuracy. Random forest was used as a classifier and ROC analysis was used to assess the relationship between selected features and patient’s outcome status. Results: Each patient had between 1 and 9 separate ROIs, with much intra-patient variability in PET features. The best model, which used features from a single anatomic region (the mediastinal ROI, only volumes>5cc: 169 patients with 12 primary refractory) had a classification accuracy of 80.5% for primary refractory disease. The top five features, based on Gini index, consist of shape features (max 3D-diameter and volume) and texture features (correlation and information measure of correlation1&2). In the ROC analysis, sensitivity and specificity of the best model were 0.92 and 0.80, respectively. The area under the ROC (AUC) and the accuracy were 0.86 and 0.86, respectively. The classification accuracy was less than 60% for other ROI models or when ROIs less than 5cc were included. Conclusion: This study showed that PET-based radiomics features from the mediastinal lymph region are associated with primary refractory disease and therefore may play an important role in predicting outcomes in Hodgkin lymphoma patients. These features could be additive beyond baseline tumor and clinical characteristics, and may warrant more aggressive treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-BRC-01: A Data-Driven Pre-Optimization Method for Prediction of Achievability of Clinical Objectives in IMRT

Purpose: We propose a novel data-driven method to predict the achievability of clinical objectives upfront before invoking the IMRT optimization. Methods: A new metric called “Geometric Complexity (GC)” is used to estimate the achievability of clinical objectives. Here, GC is the measure of the number of “unmodulated” beamlets or rays that intersect the Region-of-interest (ROI) and the target volume. We first compute the geometric complexity ratio (GCratio) between the GC of a ROI (say, parotid) in a reference plan and the GC of the same ROI in a given plan. The GCratio of a ROI indicates the relative geometric complexity of the ROI as compared to the same ROI in the reference plan. Hence GCratio can be used to predict if a defined clinical objective associated with the ROI can be met by the optimizer for a given case. Basically a higher GCratio indicates a lesser likelihood for the optimizer to achieve the clinical objective defined for a given ROI. Similarly, a lower GCratio indicates a higher likelihood for the optimizer to achieve the clinical objective defined for the given ROI. We have evaluated the proposed method on four Head and Neck cases using Pinnacle3 (version 9.10.0) Treatment Planning System (TPS). Results: Out of the total of 28 clinical objectives from four head and neck cases included in the study, 25 were in agreement with the prediction, which implies an agreement of about 85% between predicted and obtained results. The Pearson correlation test shows a positive correlation between predicted and obtained results (Correlation = 0.82, r2 = 0.64, p < 0.005). Conclusion: The study demonstrates the feasibility of the proposed method in head and neck cases for predicting the achievability of clinical objectives with reasonable accuracy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-CAMPUS-JeP3-02: A Novel Setup Approach to Improve C-Spine Curvature Reproducibility for Head and Neck Radiotherapy Using Optical Surface Imaging with Two Regions of Interest

Purpose: To develop a novel approach to improve cervical spine (c-spine) curvature reproducibility for head and neck (HN) patients using optical surface imaging (OSI) with two regions of interests (ROIs). Methods: The OSI-guided, two-step setup procedure requires two ROIs: ROI-1 of the shoulders and ROI-2 of the face. The neck can be stretched or squeezed in superior-inferior (SI) direction using a specially-designed sliding head support. We hypothesize that when these two ROIs are aligned, the c-spine should fall into a naturally reproducible position under same setup conditions. An anthropomorphous phantom test was performed to examine neck pitch angles comparing with the calculated angles. Three volunteers participated in the experiments, which start with conventional HN setup using skin markers and room lasers. An OSI image and lateral photo-picture were acquired as the references. In each of the three replicate tests, conventional setup was first applied after volunteers got on the couch. ROI-1 was aligned by moving the body, followed by ROI-2 alignment via adjusting head position and orientation under real-time OSI guidance. A final static OSI image and lateral picture were taken to evaluate both anterior and posterior surface alignments. Three degrees of freedom can be adjusted if an open-face mask was applied, including head SI shift using the sliding head support and pitch-and-roll rotations using a commercial couch extension. Surface alignment was analyzed comparing with conventional setup. Results: The neck pitch angle measured by OSI is consistent with the calculated (0.2±0.6°). Volunteer study illustrated improved c-spine setup reproducibility using OSI comparing with conventional setup. ROI alignments with 2mm/1° tolerance are achieved within 3 minutes. Identical knee support is important to achieve ROI-1 pitch alignment. Conclusion: The feasibility of this novel approach has been demonstrated for c-spine curvature setup reproducibility. Further evaluation is necessary with bony alignment variation in patient studies. This study is in part supported by the NIH (U54CA137788).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-201-06: Impact of Temporal Image Coregistration Methods On 3D Internal Dose Calculations in Targeted Radionuclide Therapy

Purpose: The calculation of 3D internal dose calculations in targeted radionuclide therapy requires the acquisition and temporal coregistration of a serial PET/CT or SPECT/CT images. This work investigates the dosimetric impact of different temporal coregistration methods commonly used for 3D internal dosimetry. Methods: PET/CT images of four mice were acquired at 1, 24, 48, 72, 96, 144 hrs post-injection of {sup 124}I-CLR1404. The therapeutic {sup 131}I-CLR1404 absorbed dose rate (ADR) was calculated at each time point using a Geant4-based MC dosimetry platform using three temporal image coregistration Methods: (1) no coregistration (NC), whole body sequential CT-CT affine coregistration (WBAC), and individual sequential ROI-ROI affine coregistration (IRAC). For NC, only the ROI mean ADR was integrated to obtain ROI mean doses. For WBAC, the CT at each time point was coregistered to a single reference CT. The CT transformations were applied to the corresponding ADR images and the dose was calculated on a voxel-basis within the whole CT volume. For IRAC, each individual ROI was isolated and sequentially coregistered to a single reference ROI. The ROI transformations were applied to the corresponding ADR images and the dose was calculated on a voxel-basis within the ROI volumes. Results: The percent differences in the ROI mean doses were as large as 109%, 88%, and 32%, comparing the WBAC vs. IRAC, NC vs. IRAC, and NC vs. WBAC methods, respectively. The CoV in the mean dose between the all three methods ranged from 2–36%. The pronounced curvature of the spinal cord was not adequately coregistered using WBAC which resulted in large difference between the WBAC and IRAC. Conclusion: The method used for temporal image coregistration can result in large differences in 3D internal dosimetry calculations. Care must be taken to choose the most appropriate method depending on the imaging conditions, clinical site, and specific application. This work is partially funded by NIH Grant R21 CA198392-01.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Are State-Sponsored New Radiation Therapy Facilities Economically Viable in Low- and Middle-Income Countries?

Purpose: The economic viability of establishing a state-funded radiation therapy (RT) infrastructure in low- and middle-income countries (LMICs) in accordance with the World Bank definition has been assessed through computation of a return on investment (ROI). Methods and Materials: Of the 139 LMICs, 100 were evaluated according to their RT facilities, gross national income (GNI) per capita, and employment/population ratio. The assumption was an investment of US$5 million for a basic RT center able to treat 1000 patients annually. The national breakeven points and percentage of ROI (%ROI) were calculated according to the GNI per capita and patient survival rates of 10% to 50% at 2 years. It was assumed that 50% of these patients would be of working age and that, if employed and able to work after treatment, they would contribute to the country's GNI for at least 2 years. The cumulative GNI after attaining the breakeven point until the end of the 15-year lifespan of the teletherapy unit was calculated to estimate the %ROI. The recurring and overhead costs were assumed to vary from 5.5% to 15% of the capital investment. Results: The %ROI was dependent on the GNI per capita, employment/population ratio and 2-year patient survival (all P<.001). Accordingly, none of the low-income countries would attain an ROI. If 50% of the patients survived for 2 years, the %ROI in the lower-middle and upper-middle income countries could range from 0% to 159.9% and 11.2% to 844.7%, respectively. Patient user fees to offset recurring and overhead costs could vary from “nil” to US$750, depending on state subsidies. Conclusions: Countries with a greater GNI per capita, higher employment/population ratio, and better survival could achieve a faster breakeven point, resulting in a higher %ROI. Additional factors such as user fees have also been considered. These can be tailored to the patient's ability to pay to cover the recurring costs. Certain pragmatic steps that could be undertaken to address these issues are discussed in the present study.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗