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DOE OSTI2024

Taylor-Expansion-Based Robust Power Flow in Unbalanced Distribution Systems: A Hybrid Data-Aided Method

Traditional power flow methods often adopt certain assumptions designed for passive balanced distribution systems, thus lacking practicality for unbalanced operation. moreover, their computation accuracy and efficiency are heavily subject to unknown errors and bad data in measurements or prediction data of distributed energy resources (ders). to address these issues, this paper proposes a hybrid data-aided robust power flow algorithm in unbalanced distribution systems, which combines taylor series expansion knowledge with a data-driven regression technique. the proposed method initiates a linearization power flow model to derive an explicitly analytical solution by modified taylor expansion. to mitigate the approximation loss that surges due to the der integration and bad data, we further develop a data-aided robust support vector regression approach to estimate the errors efficiently. comparative analysis in the 13-bus and 123-bus ieee unbalanced feeders shows that the proposed hybrid algorithm achieves superior computational efficiency, with guaranteed accuracy and robustness against outliers.

data-driven↗
DOE OSTI2023

Early Alarm: Robust Event Analysis for Power Systems using 1-D Fully Convolutional Network

This work presents a novel deep learning model for early, accurate, and robust detection, recognition, and temporal localization of multi-type events in large-scale power systems. The proposed method develops a unified 1-D fully convolutional network (FCN) model that takes time series of raw frequency signals measured from a power system as input, extracts distinguishing features, and predicts at every temporal point in the time series if an event is happening and what the type of the event is. Compared to existing methods, the proposed model eliminates the necessity for hand-crafted feature extraction or complicated data pre-processing, can flexibly handle input signals of arbitrary length, and precisely infer the event occurrence time. Most importantly, the model is intentionally trained with incomplete patterns, such that it is more robust to partial features of an event which is common in real-world online recognition, resulting in early alarm for power system failures. Extensive experimental results demonstrate that the proposed method achieves superior performance to the state-of-the-art, and also shows strong robustness to noise and system oscillations.

Li, Chengcheng↗
DOE OSTI2013

Estimating nonrigid motion from inconsistent intensity with robust shape features

Purpose: To develop a nonrigid motion estimation method that is robust to heterogeneous intensity inconsistencies amongst the image pairs or image sequence. Methods: Intensity and contrast variations, as in dynamic contrast enhanced magnetic resonance imaging, present a considerable challenge to registration methods based on general discrepancy metrics. In this study, the authors propose and validate a novel method that is robust to such variations by utilizing shape features. The geometry of interest (GOI) is represented with a flexible zero level set, segmented via well-behaved regularized optimization. The optimization energy drives the zero level set to high image gradient regions, and regularizes it with area and curvature priors. The resulting shape exhibits high consistency even in the presence of intensity or contrast variations. Subsequently, a multiscale nonrigid registration is performed to seek a regular deformation field that minimizes shape discrepancy in the vicinity of GOIs. Results: To establish the working principle, realistic 2D and 3D images were subject to simulated nonrigid motion and synthetic intensity variations, so as to enable quantitative evaluation of registration performance. The proposed method was benchmarked against three alternative registration approaches, specifically, optical flow, B-spline based mutual information, and multimodality demons. When intensity consistency was satisfied, all methods had comparable registration accuracy for the GOIs. When intensities among registration pairs were inconsistent, however, the proposed method yielded pronounced improvement in registration accuracy, with an approximate fivefold reduction in mean absolute error (MAE = 2.25 mm, SD = 0.98 mm), compared to optical flow (MAE = 9.23 mm, SD = 5.36 mm), B-spline based mutual information (MAE = 9.57 mm, SD = 8.74 mm) and mutimodality demons (MAE = 10.07 mm, SD = 4.03 mm). Applying the proposed method on a real MR image sequence also provided qualitatively appealing results, demonstrating good feasibility and applicability of the proposed method. Conclusions: The authors have developed a novel method to estimate the nonrigid motion of GOIs in the presence of spatial intensity and contrast variations, taking advantage of robust shape features. Quantitative analysis and qualitative evaluation demonstrated good promise of the proposed method. Further clinical assessment and validation is being performed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

SU-E-T-181: Feasibility and Robustness of Using Overlapping VMAT Arcs for Conformal Irradiation of Large Irregular PTVs

Purpose: To investigate the feasibility and robustness of using multiple overlapping arcs for delivering volumetric modulated arc therapy (VMAT) to irregular PTVs with large superior-inferior (SI) dimensions. Methods: A patient with stage IV alveolar rhabdomyosarcoma, with a combined PTV length of 56 cm in SI direction, was planned and treated in our department using two VMAT arcs overlapped along the SI direction to take advantage of the much needed dose sculpting capabilities of VMAT. The overlapping VMATs, each consisted of two arcs, were optimized simultaneously using Varian Eclipse system. The susceptibility of the resulting plan to uncertainties associated the set up of two separate isocenters during treatment was investigated by comparing the dose distributions resulted from small shifts introduced into the isocenter position. The robustness of this technique was further assessed for plans generated using different amount of overlap between the overlapping arcs. Results: When the plan was generated with 6 cm overlap between adjacent arcs, maximum dose variations observed near overlapping edges was up to 9.2%, 10%, and 26.7% for setup uncertainties of 2 mm, 3 mm, and 5 mm, respectively. By increasing the junction overlap to 16 cm, maximum dose variations was reduced to 4.2%, 6.5%, and 10.2% for setup uncertainties of 2 mm, 3 mm, and 5 mm, respectively. In general, dose variation was found to increase dramatically with increasing magnitude of setup uncertainty. The technique can be made more robust against setup uncertainty by using large overlap between adjacent VMAT arcs. Conclusion: Overlapping VMAT arcs can be used effectively for conformal irradiation of PTVs with large SI dimension. The dosimetric impact of uncertainties in required isocenter shifts can be minimized by planning with large overlap between adjacent arcs and by keeping setup uncertainty ≤ 2mm.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-621: Analysis of Robustness of Proton Pencil Beam Scanning Technique for Delivery of Craniospinal Irradiation

Purpose: To investigate the robustness and safety of craniospinal irradiation (CSI) planned with a proton pencil beam scanning (PBS) technique which overcomes the complexity of the planning associated with feathering match lines. Methods: Six CSI patients were planned with gradient-dose matching using PBS technique. Uniform dose coverage to the entire target volumes was achieved with averaged junction lengths of 6.9±0.3 cm. Robustness of the plans was evaluated by shifting the isocenter of each treatment field by ±3 mm in longitudinal direction and compared with the original non-shifted plan with metrics of conformity number (CN) and homogeneity index (HI). An anthropomorphic phantom study using film measurements was also carried out on a plan with 5 cm junction length. Results: For a given junction length, the dose errors were directly proportional to the setup errors. Setup errors of 3 mm from each field caused on average 3.5% lower CN and 2.1% higher HI. Minimal D95% to PTV and D98% to CTV were reduced by 2.2%±1.5% and 2.8%±1.7% respectively. A drop of maximal 6.8%±5.5% on the minimal dose to the cribriform plate was also observed. When the junction length was 5cm or longer, these 3mm setup errors from each field resulted in up to 12% dose errors. Consistent results were reached between film measurements and planned dose profiles in the junction area. Due to near-zero exit doses beyond the target volume, sparing of anterior organs such as heart, liver, lung and kidney were observed. Conclusions: Longitudinal setup errors directly reduce the dosimetric accuracy of the CSI treatment with matched proton fields. The reported technique creates a slow dose gradient in the junction area, which makes the treatment more robust and safe to longitudinal setup errors compared to conventional feathering methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Robust electromagnetically guided endoscopic procedure using enhanced particle swarm optimization for multimodal information fusion

Purpose: Electromagnetically guided endoscopic procedure, which aims at accurately and robustly localizing the endoscope, involves multimodal sensory information during interventions. However, it still remains challenging in how to integrate these information for precise and stable endoscopic guidance. To tackle such a challenge, this paper proposes a new framework on the basis of an enhanced particle swarm optimization method to effectively fuse these information for accurate and continuous endoscope localization. Methods: The authors use the particle swarm optimization method, which is one of stochastic evolutionary computation algorithms, to effectively fuse the multimodal information including preoperative information (i.e., computed tomography images) as a frame of reference, endoscopic camera videos, and positional sensor measurements (i.e., electromagnetic sensor outputs). Since the evolutionary computation method usually limits its possible premature convergence and evolutionary factors, the authors introduce the current (endoscopic camera and electromagnetic sensor’s) observation to boost the particle swarm optimization and also adaptively update evolutionary parameters in accordance with spatial constraints and the current observation, resulting in advantageous performance in the enhanced algorithm. Results: The experimental results demonstrate that the authors’ proposed method provides a more accurate and robust endoscopic guidance framework than state-of-the-art methods. The average guidance accuracy of the authors’ framework was about 3.0 mm and 5.6° while the previous methods show at least 3.9 mm and 7.0°. The average position and orientation smoothness of their method was 1.0 mm and 1.6°, which is significantly better than the other methods at least with (2.0 mm and 2.6°). Additionally, the average visual quality of the endoscopic guidance was improved to 0.29. Conclusions: A robust electromagnetically guided endoscopy framework was proposed on the basis of an enhanced particle swarm optimization method with using the current observation information and adaptive evolutionary factors. The authors proposed framework greatly reduced the guidance errors from (4.3, 7.8) to (3.0 mm, 5.6°), compared to state-of-the-art methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-653: Quantifying Inter-Fraction Range Uncertainty for Input Into Robust Proton Planning

Purpose: To provide a method for quantifying centre- and tumour site-specific population range uncertainty due to inter-fraction motion for use within robust proton planning and plan analysis. PTV-based and probabilistic/robust plans depend upon accurate knowledge of geometric and range uncertainties. If the uncertainty model is inaccurate, both types of plan, PTV or probabilistic, could produce under-dosing of the target and/or overdosing of OAR. Methods: Daily mega-voltage volumetric imaging data from previously treated radiotherapy patients has been used to investigate inter-fraction changes to water equivalent path-length (WEPL). Daily image-guidance scans were carried out for each patient and corrected for changes in CTV position (using rigid transformations). An effective depth algorithm was used to determine residual range changes, after corrections were applied, by comparing WEPL within the CTV at each fraction for several beam angles. This method has been demonstrated for nine prostate and seven head and neck. Results: Inter-fraction range changes for the head and neck patient sample were Σ=3.39mm, σ=4.72mm and overall mean =−1.82mm; for prostate Σ=5.64mm, σ=5.91mm and overall mean =0.98 mm. The choice of beam angle for head and neck did not affect the inter-fraction range error significantly; however this was not the same for prostate. Greater range changes were seen using a lateral beam compared to an anterior beam for prostate due to relative motion of the prostate and femoral heads. Conclusion: A method has been developed to quantify population range changes due to inter-fraction motion. The results show a non-zero mean for these samples, as well as significant Σ and σ, highlighting the importance of quantifying uncertainties and use of image guidance. Such information can be used in robust optimisation algorithms and for analysing treatment plan robustness. It may also help in establishing beam start conditions at planning and for establishing adaptive planning protocols.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

WE-AB-BRA-01: 3D-2D Image Registration for Target Localization in Spine Surgery: Comparison of Similarity Metrics Against Robustness to Content Mismatch

Purpose: In image-guided spine surgery, mapping 3D preoperative images to 2D intraoperative images via 3D-2D registration can provide valuable assistance in target localization. However, the presence of surgical instrumentation, hardware implants, and soft-tissue resection/displacement causes mismatches in image content, confounding existing registration methods. Manual/semi-automatic methods to mask such extraneous content is time consuming, user-dependent, error prone, and disruptive to clinical workflow. We developed and evaluated 2 novel similarity metrics within a robust registration framework to overcome such challenges in target localization. Methods: An IRB-approved retrospective study in 19 spine surgery patients included 19 preoperative 3D CT images and 50 intraoperative mobile radiographs in cervical, thoracic, and lumbar spine regions. A neuroradiologist provided truth definition of vertebral positions in CT and radiography. 3D-2D registration was performed using the CMA-ES optimizer with 4 gradient-based image similarity metrics: (1) gradient information (GI); (2) gradient correlation (GC); (3) a novel variant referred to as gradient orientation (GO); and (4) a second variant referred to as truncated gradient correlation (TGC). Registration accuracy was evaluated in terms of the projection distance error (PDE) of the vertebral levels. Results: Conventional similarity metrics were susceptible to gross registration error and failure modes associated with the presence of surgical instrumentation: for GI, the median PDE and interquartile range was 33.0±43.6 mm; similarly for GC, PDE = 23.0±92.6 mm respectively. The robust metrics GO and TGC, on the other hand, demonstrated major improvement in PDE (7.6 ±9.4 mm and 8.1± 18.1 mm, respectively) and elimination of gross failure modes. Conclusion: The proposed GO and TGC similarity measures improve registration accuracy and robustness to gross failure in the presence of strong image content mismatch. Such registration capability could offer valuable assistance in target localization without disruption of clinical workflow. G. Kleinszig and S. Vogt are employees of Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Lung motion estimation using dynamic point shifting: An innovative model based on a robust point matching algorithm

Purpose: Image-guided radiotherapy is an advanced 4D radiotherapy technique that has been developed in recent years. However, respiratory motion causes significant uncertainties in image-guided radiotherapy procedures. To address these issues, an innovative lung motion estimation model based on a robust point matching is proposed in this paper. Methods: An innovative robust point matching algorithm using dynamic point shifting is proposed to estimate patient-specific lung motion during free breathing from 4D computed tomography data. The correspondence of the landmark points is determined from the Euclidean distance between the landmark points and the similarity between the local images that are centered at points at the same time. To ensure that the points in the source image correspond to the points in the target image during other phases, the virtual target points are first created and shifted based on the similarity between the local image centered at the source point and the local image centered at the virtual target point. Second, the target points are shifted by the constrained inverse function mapping the target points to the virtual target points. The source point set and shifted target point set are used to estimate the transformation function between the source image and target image. Results: The performances of the authors’ method are evaluated on two publicly available DIR-lab and POPI-model lung datasets. For computing target registration errors on 750 landmark points in six phases of the DIR-lab dataset and 37 landmark points in ten phases of the POPI-model dataset, the mean and standard deviation by the authors’ method are 1.11 and 1.11 mm, but they are 2.33 and 2.32 mm without considering image intensity, and 1.17 and 1.19 mm with sliding conditions. For the two phases of maximum inhalation and maximum exhalation in the DIR-lab dataset with 300 landmark points of each case, the mean and standard deviation of target registration errors on the 3000 landmark points of ten cases by the authors’ method are 1.21 and 1.04 mm. In the EMPIRE10 lung registration challenge, the authors’ method ranks 24 of 39. According to the index of the maximum shear stretch, the authors’ method is also efficient to describe the discontinuous motion at the lung boundaries. Conclusions: By establishing the correspondence of the landmark points in the source phase and the other target phases combining shape matching and image intensity matching together, the mismatching issue in the robust point matching algorithm is adequately addressed. The target registration errors are statistically reduced by shifting the virtual target points and target points. The authors’ method with consideration of sliding conditions can effectively estimate the discontinuous motion, and the estimated motion is natural. The primary limitation of the proposed method is that the temporal constraints of the trajectories of voxels are not introduced into the motion model. However, the proposed method provides satisfactory motion information, which results in precise tumor coverage by the radiation dose during radiotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-19: Robust Region-Of-Interest (ROI) for Consistent Registration On Deteriorated Surface Images

Purpose: For African-American patients receiving breast radiotherapy with a bolus, skin darkening can affect the surface visualization when using optical imaging for daily positioning and gating at deep-inspiration breath holds (DIBH). Our goal is to identify a region-of-interest (ROI) that is robust against deteriorating surface image quality due to skin darkening. Methods: We study four patients whose post-mastectomy surfaces are imaged daily with AlignRT (VisionRT, UK) for DIBH radiotherapy and whose surface image quality is degraded toward the end of treatment. To simulate the effects of skin darkening, surfaces from the first ten fractions of each patient are systematically degraded by 25–35%, 40–50% and 65–75% of the total area of the clinically used ROI-ipsilateral-chestwall. The degraded surfaces are registered to the reference surface in six degrees-of-freedom. To identify a robust ROI, three additional reference ROIs — ROI-chest+abdomen, ROI-bilateral-chest and ROI-extended-ipsilateral-chestwall are created and registered to the degraded surfaces. Differences in registration using these ROIs are compared to that using ROI-ipsilateral-chestwall. Results: For three patients, the deviations in the registrations to ROI-ipsilateral-chestwall are > 2.0, 3.1 and 7.9mm on average for 25–35%, 40–50% and 65–75% degraded surfaces, respectively. Rotational deviations reach 11.1° in pitch. For the last patient, registration is consistent to within 2.6mm even on the 65–75% degraded surfaces, possibly because the surface topography has more distinct features. For ROI-bilateral-chest and ROI-extended-ipsilateral-chest registrations deviate in a similar pattern. However, registration on ROI-chest+abdomen is robust to deteriorating image qualities to within 4.2mm for all four patients. Conclusion: Registration deviations using ROI-ipsilateral-chestwall can reach 9.8mm on the 40–50% degraded surfaces. Caution is required when using AlignRT for patients experiencing skin darkening since the accuracy of AlignRT registration deteriorates. To avoid this inaccuracy, we recommend use of ROI-chest+abdomen, on which registration is consistent within 4.2mm even for highly degraded surfaces.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-185: Study of the Robustness of a Proton Arc Technique Based On PBS Beams

Purpose: One potential technique to realize proton arc is through using PBS beams from many directions to form overlaid Bragg peak (OBP) spots and placing these OBP spots throughout the target volume to achieve desired dose distribution. In this study, we analyzed the robustness of this proton arc technique. Methods: We used a cylindrical water phantom of 20 cm in radius in our robustness analysis. To study the range uncertainty effect, we changed the density of the phantom by ±3%. To study the setup uncertainty effect, we shifted the phantom by 3 & 5 mm. We also combined the range and setup uncertainties (3mm/±3%). For each test plan, we performed dose calculation for the nominal and 6 disturbed scenarios. Two test plans were used, one with single OBP spot and the other consisting of 121 OBP spots covering a 10×10cm{sup 2} area. We compared the dose profiles between the nominal and disturbed scenarios to estimate the impact of the uncertainties. Dose calculation was performed with Gate/GEANT based Monte Carlo software in cloud computing environment. Results: For each of the 7 scenarios, we simulated 100k & 10M events for plans consisting of single OBP spot and 121 OBP spots respectively. For single OBP spot, the setup uncertainty had minimum impact on the spot’s dose profile while range uncertainty had significant impact on the dose profile. For plan consisting of 121 OBP spots, similar effect was observed but the extent of disturbance was much less compared to single OBP spot. Conclusion: For PBS arc technique, range uncertainty has significantly more impact than setup uncertainty. Although single OBP spot can be severely disturbed by the range uncertainty, the overall effect is much less when a large number of OBP spots are used. Robustness optimization for PBS arc technique should consider range uncertainty with priority.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-186: A Treatment Planning Study of Normal Tissue Sparing with Robustness Optimized IMPT, 4Pi IMRT, and VMAT for Head and Neck Cases

Purpose: We performed a retrospective dosimetric comparison study between the robustness optimized Intensity Modulated Proton Therapy (RO-IMPT), volumetric-modulated arc therapy (VMAT), and the non-coplanar 4? intensity modulated radiation therapy (IMRT). These methods represent the most advanced radiation treatment methods clinically available. We compare their dosimetric performance for head and neck cancer treatments with special focus on the OAR sparing near the tumor volumes. Methods: A total of 11 head and neck cases, which include 10 recurrent cases and one bilateral case, were selected for the study. Different dose levels were prescribed to tumor target depending on disease and location. Three treatment plans were created on commercial TPS systems for a novel noncoplanar 4π method (20 beams), VMAT, and RO-IMPT technique (maximum 4 fields). The maximum patient positioning error was set to 3 mm and the maximum proton range uncertainty was set to 3% for the robustness optimization. Line dose profiles were investigated for OARs close to tumor volumes. Results: All three techniques achieved 98% coverage of the CTV target and most photon plans had less than 110% of the hot spots. The RO-IMPT plans show superior tumor dose homogeneity than 4? and VMAT plans. Although RO-IMPT has greater R50 dose spillage to the surrounding normal tissue than 4π and VMAT, the RO-IMPT plans demonstrate better or comparable OAR (parotid, mandible, carotid, oral cavity, pharynx, and etc.) sparing for structures closely abutting tumor targets. Conclusion: The RO-IMPT’s ability of OAR sparing is benchmarked against the C-arm linac based non-coplanar 4π technique and the standard VMAT method. RO-IMPT consistently shows better or comparable OAR sparing even for tissue structures closely abutting treatment target volume. RO-IMPT further reduces treatment uncertainty associated with proton therapy and delivers robust treatment plans to both unilateral and bilateral head and neck cancer patients with desirable treatment time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-188: A Robust Treatment Planning Technique for Proton Pencil Beam Scanning Cranial Spinal Irradiation

Purpose: To propose a proton pencil beam scanning (PBS) cranial spinal irradiation (CSI) treatment planning technique robust against patient roll, isocenter offset and proton range uncertainty. Method: Proton PBS plans were created (Eclipse V11) for three previously treated CSI patients to 36 Gy (1.8 Gy/fractions). The target volume was separated into three regions: brain, upper spine and lower spine. One posterior-anterior (PA) beam was used for each spine region, and two posterior-oblique beams (15° apart from PA direction, denoted as 2PO-15) for the brain region. For comparison, another plan using one PA beam for the brain target (denoted as 1PA) was created. Using the same optimization objectives, 98% CTV was optimized to receive the prescription dose. To evaluate plan robustness against patient roll, the gantry angle was increased by 3° and dose was recalculated without changing the proton spot weights. On the re-calculated plan, doses were then calculated using 12 scenarios that are combinations of isocenter shift (±3mm in X, Y, and Z directions) and proton range variation (±3.5%). The worst-case-scenario (WCS) brain CTV dosimetric metrics were compared to the nominal plan. Results: For both beam arrangements, the brain field(s) and upper-spine field overlap in the T2–T5 region depending on patient anatomy. The maximum monitor unit per spot were 48.7%, 47.2%, and 40.0% higher for 1PA plans than 2PO-15 plans for the three patients. The 2PO-15 plans have better dose conformity. At the same level of CTV coverage, the 2PO-15 plans have lower maximum dose and higher minimum dose to the CTV. The 2PO-15 plans also showed lower WCS maximum dose to CTV, while the WCS minimum dose to CTV were comparable between the two techniques. Conclusion: Our method of using two posterior-oblique beams for brain target provides improved dose conformity and homogeneity, and plan robustness including patient roll.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-205: Effectiveness of Robust Treatment Planning to Account for Inter- Fractional Variation in Intensity Modulated Proton Therapy for Head Neck Cancer

Purpose: To evaluate the potential benefits of robust optimization in intensity modulated proton therapy(IMPT) treatment planning to account for inter-fractional variation for Head Neck Cancer(HNC). Methods: One patient with bilateral HNC previous treated at our institution was used in this study. Ten daily CBCTs were selected. The CT numbers of the CBCTs were corrected by mapping the CT numbers from simulation CT via Deformable Image Registration. The planning target volumes(PTVs) were defined by a 3mm expansion from clinical target volumes(CTVs). The prescription was 70Gy, 54Gy to CTV1, CTV2, and PTV1, PTV2 for robust optimized(RO) and conventionally optimized(CO) plans respectively. Both techniques were generated by RayStation with the same beam angles: two anterior oblique and two posterior oblique angles. The similar dose constraints were used to achieve 99% of CTV1 received 100% prescription dose while kept the hotspots less than 110% of the prescription. In order to evaluate the dosimetric result through the course of treatment, the contours were deformed from simulation CT to daily CBCTs, modified, and approved by a radiation oncologist. The initial plan on the simulation CT was re-replayed on the daily CBCTs followed the bony alignment. The target coverage was evaluated using the daily doses and the cumulative dose. Results: Eight of 10 daily deliveries with using RO plan achieved at least 95% prescription dose to CTV1 and CTV2, while still kept maximum hotspot less than 112% of prescription compared with only one of 10 for the CO plan to achieve the same standards. For the cumulative doses, the target coverage for both RO and CO plans was quite similar, which was due to the compensation of cold and hot spots. Conclusion: Robust optimization can be effectively applied to compensate for target dose deficit caused by inter-fractional target geometric variation in IMPT treatment planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-CAMPUS-TeP3-01: A Model of Baseline Shift to Improve Robustness of Proton Therapy Treatments of Moving Tumors

Purpose: The shift in mean position of a moving tumor also known as “baseline shift”, has been modeled, in order to automatically generate uncertainty scenarios for the assessment and robust optimization of proton therapy treatments in lung cancer. Methods: An average CT scan and a Mid-Position CT scan (MidPCT) of the patient at the planning time are first generated from a 4D-CT data. The mean position of the tumor along the breathing cycle is represented by the GTV contour in the MidPCT. Several studies reported both systematic and random variations of the mean tumor position from fraction to fraction. Our model can simulate this baseline shift by generating a local deformation field that moves the tumor on all phases of the 4D-CT, without creating any non-physical artifact. The deformation field is comprised of normal and tangential components with respect to the lung wall in order to allow the tumor to slip within the lung instead of deforming the lung surface. The deformation field is eventually smoothed in order to enforce its continuity. Two 4D-CT series acquired at 1 week of interval were used to validate the model. Results: Based on the first 4D-CT set, the model was able to generate a third 4D-CT that reproduced the 5.8 mm baseline-shift measured in the second 4D-CT. Water equivalent thickness (WET) of the voxels have been computed for the 3 average CTs. The root mean square deviation of the WET in the GTV is 0.34 mm between week 1 and week 2, and 0.08 mm between the simulated data and week 2. Conclusion: Our model can be used to automatically generate uncertainty scenarios for robustness analysis of a proton therapy plan. The generated scenarios can also feed a TPS equipped with a robust optimizer. Kevin Souris, Ana Barragan, and Dario Di Perri are financially supported by Televie Grants from F.R.S.-FNRS.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Robust Optimal Experimental Design of Infinite-Dimensional Bayesian Nonlinear Inverse Problems

Abstract. We consider robust optimal experimental design (ROED) for nonlinear Bayesian inverse problems governed by partial differential equations (PDEs). An optimal design is one that maximizes some utility quantifying the quality of the solution of an inverse problem. However, the optimal design is dependent on elements of the inverse problem such as the simulation model, the prior, or the measurement error model. ROED aims to produce an optimal design that is aware of the additional uncertainties encoded in the inverse problem and remains optimal even after variations in them. We follow a worst-case scenario approach to develop a new framework for robust optimal design of nonlinear Bayesian inverse problems. The proposed framework (a) is scalable and designed for infinite-dimensional Bayesian nonlinear inverse problems constrained by PDEs; (b) develops efficient approximations of the utility, namely the expected information gain; (c) employs eigenvalue sensitivity techniques to develop analytical forms and efficient evaluation methods of the gradient of the utility with respect to the uncertainties against which we wish to be robust; and (d) employs a probabilistic optimization paradigm that properly defines and efficiently solves the resulting combinatorial max-min optimization problem. The effectiveness of the proposed approach is illustrated for optimal sensor placement problem in an inverse problem governed by an elliptic PDE.

Chowdhary, Abhijit↗
DOE OSTI2024

Robust Containment Queries over Collections of Rational Parametric Curves via Generalized Winding Numbers

Point containment queries for regions bound by watertight geometric surfaces, i.e., closed and without self-intersections, can be evaluated straightforwardly with a number of well-studied algorithms. When this assumption on domain geometry is not met, such methods are either unusable, or prone to misclassifications that can lead to cascading errors in downstream applications. More robust point classification schemes based on generalized winding numbers have been proposed, as they are indifferent to these imperfections. However, existing algorithms are limited to point clouds and collections of linear elements. We extend this methodology to encompass more general curved shapes with an algorithm that evaluates the winding number scalar field over unstructured collections of rational parametric curves. In particular, we evaluate the winding number for each curve independently, making the derived containment query robust to how the curves are arranged. We ensure geometric fidelity in our queries by treating each curve as equivalent to an adaptively constructed polyline that provably has the same generalized winding number at the point of interest. Our algorithm is numerically stable for points that are arbitrarily close to the model, and explicitly treats points that are coincident with curves. We demonstrate the improvements in computational performance granted by this method over conventional techniques as well as the robustness induced by its application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Robust Gene Expression Prognostic Signature for Overall Survival in High-Grade Serous Ovarian Cancer

The objective of this research was to develop a robust gene expression-based prognostic signature and scoring system for predicting overall survival (OS) of patients with high-grade serous ovarian cancer (HGSOC). Transcriptomic data of HGSOC patients were obtained from six independent studies in the NCBI GEO database. Genes significantly deregulated and associated with OS in HGSOCs were selected using GEO2R and Kaplan–Meier analysis with log-rank testing, respectively. Enrichment analysis for biological processes and pathways was performed using Gene Ontology analysis. A resampling/cross-validation method with Cox regression analysis was used to identify a novel gene expression-based signature associated with OS, and a prognostic scoring system was developed and further validated in nine independent HGSOC datasets. We first identified 488 significantly deregulated genes in HGSOC patients, of which 232 were found to be significantly associated with their OS. These genes were significantly enriched for cell cycle division, epithelial cell differentiation, p53 signaling pathway, vasculature development, and other processes. A novel 11-gene prognostic signature was identified and a prognostic scoring system was developed, which robustly predicted OS in HGSOC patients in 100 sampling test sets. The scoring system was further validated successfully in nine additional HGSOC public datasets. In conclusion, our integrative bioinformatics study combining transcriptomic and clinical data established an 11-gene prognostic signature for robust and reproducible prediction of OS in HGSOC patients. This signature could be of clinical value for guiding therapeutic selection and individualized treatment.

60 APPLIED LIFE SCIENCES↗