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At least 217 records · Page 12

Rare events and Griffiths phases in topological quantum error correction

The performance of quantum error correcting (QEC) codes is often studied under the assumption of spatiotemporally uniform error rates. On the other hand, experimental implementations almost always produce heterogeneous error rates, in either space or time, as a result of effects such as imperfect fabrication and/or cosmic rays. It is therefore important to understand if and how their presence can affect the performance of QEC in qualitative ways. Here, in this work, we study the effects of nonuniform error rates in the representative examples of the 1D repetition code and the 2D toric code, focusing on when they have extended spatiotemporal correlations; these may arise, for instance, from rare events (such as cosmic rays) that temporarily elevate error rates over the entire code patch. These effects can be described in the corresponding statistical mechanics models for decoding, where long-range correlations in the error rates lead to extended rare regions of weaker coupling. For the 1D repetition code where the rare regions are linear, we find two distinct decodable phases: a conventional ordered phase in which logical failure rates decay exponentially with the code distance, and a rare-region dominated Griffiths phase in which failure rates are parametrically larger and decay as a stretched exponential. In particular, the latter phase is present when the error rates in the rare regions are above the bulk threshold. For the 2D toric code where the rare regions are planar, we find no decodable Griffiths phase: rare events which boost error rates above the bulk threshold lead to an asymptotic loss of threshold and failure to decode. Unpacking the failure mechanism implies that techniques for suppressing extended sequences of repeated rare events (which, without intervention, will be statistically present with high probability) will be crucial for QEC with the toric code.

classical statistical mechanics↗

Magnetic resonance imaging-targeted, 3D transrectal ultrasound-guided fusion biopsy for prostate cancer: Quantifying the impact of needle delivery error on diagnosis

Purpose: Magnetic resonance imaging (MRI)-targeted, 3D transrectal ultrasound (TRUS)-guided “fusion” prostate biopsy intends to reduce the ∼23% false negative rate of clinical two-dimensional TRUS-guided sextant biopsy. Although it has been reported to double the positive yield, MRI-targeted biopsies continue to yield false negatives. Therefore, the authors propose to investigate how biopsy system needle delivery error affects the probability of sampling each tumor, by accounting for uncertainties due to guidance system error, image registration error, and irregular tumor shapes. Methods: T2-weighted, dynamic contrast-enhanced T1-weighted, and diffusion-weighted prostate MRI and 3D TRUS images were obtained from 49 patients. A radiologist and radiology resident contoured 81 suspicious regions, yielding 3D tumor surfaces that were registered to the 3D TRUS images using an iterative closest point prostate surface-based method to yield 3D binary images of the suspicious regions in the TRUS context. The probabilityP of obtaining a sample of tumor tissue in one biopsy core was calculated by integrating a 3D Gaussian distribution over each suspicious region domain. Next, the authors performed an exhaustive search to determine the maximum root mean squared error (RMSE, in mm) of a biopsy system that gives P ≥ 95% for each tumor sample, and then repeated this procedure for equal-volume spheres corresponding to each tumor sample. Finally, the authors investigated the effect of probe-axis-direction error on measured tumor burden by studying the relationship between the error and estimated percentage of core involvement. Results: Given a 3.5 mm RMSE for contemporary fusion biopsy systems,P ≥ 95% for 21 out of 81 tumors. The authors determined that for a biopsy system with 3.5 mm RMSE, one cannot expect to sample tumors of approximately 1 cm{sup 3} or smaller with 95% probability with only one biopsy core. The predicted maximum RMSE giving P ≥ 95% for each tumor was consistently greater when using spherical tumor shapes as opposed to no shape assumption. However, an assumption of spherical tumor shape for RMSE = 3.5 mm led to a mean overestimation of tumor sampling probabilities of 3%, implying that assuming spherical tumor shape may be reasonable for many prostate tumors. The authors also determined that a biopsy system would need to have a RMS needle delivery error of no more than 1.6 mm in order to sample 95% of tumors with one core. The authors’ experiments also indicated that the effect of axial-direction error on the measured tumor burden was mitigated by the 18 mm core length at 3.5 mm RMSE. Conclusions: For biopsy systems with RMSE ≥ 3.5 mm, more than one biopsy core must be taken from the majority of tumors to achieveP ≥ 95%. These observations support the authors’ perspective that some tumors of clinically significant sizes may require more than one biopsy attempt in order to be sampled during the first biopsy session. This motivates the authors’ ongoing development of an approach to optimize biopsy plans with the aim of achieving a desired probability of obtaining a sample from each tumor, while minimizing the number of biopsies. Optimized planning of within-tumor targets for MRI-3D TRUS fusion biopsy could support earlier diagnosis of prostate cancer while it remains localized to the gland and curable.

60 APPLIED LIFE SCIENCES↗

SU-E-J-15: A Patient-Centered Scheme to Mitigate Impacts of Treatment Setup Error

Purpose: Current Intensity Modulated Radiation Therapy (IMRT) is plan-centered. At each treatment fraction, we position the patient to match the setup in treatment plan. Inaccurate setup can compromise delivered dose distribution, and hence leading to suboptimal treatments. Moreover, current setup approach via couch shift under image guidance can correct translational errors, while rotational and deformation errors are hard to address. To overcome these problems, we propose in this abstract a patient-centered scheme to mitigate impacts of treatment setup errors. Methods: In the patient-centered scheme, we first position the patient on the couch approximately matching the planned-setup. Our Supercomputing Online Replanning Environment (SCORE) is then employed to design an optimal treatment plan based on the daily patient geometry. It hence mitigates the impacts of treatment setup error and reduces the requirements on setup accuracy. We have conducted simulations studies in 10 head-and-neck (HN) patients to investigate the feasibility of this scheme. Rotational and deformation setup errors were simulated. Specifically, 1, 3, 5, 7 degrees of rotations were put on pitch, roll, and yaw directions; deformation errors were simulated by splitting neck movements into four basic types: rotation, lateral bending, flexion and extension. Setup variation ranges are based on observed numbers in previous studies. Dosimetric impacts of our scheme were evaluated on PTVs and OARs in comparison with original plan dose with original geometry and original plan recalculated dose with new setup geometries. Results: With conventional plan-centered approach, setup error could lead to significant PTV D99 decrease (−0.25∼+32.42%) and contralateral-parotid Dmean increase (−35.09∼+42.90%). The patientcentered approach is effective in mitigating such impacts to 0∼+0.20% and −0.03∼+5.01%, respectively. Computation time is <128 s. Conclusion: Patient-centered scheme is proposed to mitigate setup error impacts using replanning. Its superiority in terms of dosimetric impacts and feasibility has been shown through simulation studies on HN cases.

60 APPLIED LIFE SCIENCES↗

SU-E-T-450: Dosimetric Impact of Rotational Error On Multiple-Target Intensity-Modulated Radiosurgery (IMRS) with Single-Isocenter

Purpose: Evaluating the dosimetric-impact on multiple-targets placed away from the isocenter-target with varying rotational-error introduced by initial setup uncertainty and/or intrafractional-movement Methods: CyberKnife-Phantom was scanned with the Intracranial SRS-protocol of 1.25mm slice-thickness and the multiple-targets(GTV) of 1mm and 10mm in diameter were contoured on the Eclipse. PTV for distal-target only was drawn with 1mm expansion around the GTV to find out how much margin is needed to compensate for the rotational-error. The separation between the isocenter-target and distal-target was varied from 3cm to 7cm. RapidArc-based IMRS plans of 16Gy single-fraction were generated with five non-coplanar arcs by using Varian TrueBeam-STx equipped with high resolution MLC leaves of 2.5mm at center and with dose-rate of 1400MU/min at 6MV for flatteringfilter- free(FFF). An identical CT image with intentionally introduced 1° rotational-error was registered with the planning CT image, and the isodose distribution and Dose-Volume-Histogram(DVH) were compared with the original plans. Additionally, the dosimetric-impact of rotational error was evaluated with that of 6X photon energy which was generated with the same target-coverage. Results: For the 1mm-target with 6X-FFF, PTV-coverage(D100) of the distal-target with 1° rotational-error decreased from 1.00 to 0.35 as the separation between isocenter-target and distal-target increased from 3cm to 7cm. However, GTV-coverage(D100) was 1.0 except that of 7cm-separation(0.55), which resulted from the 1mm-margin around the distal-target. For 6X photon, GTV-coverage remained at 1.0 regardless of the separation of targets, showing that the dosimetric-impact of rotational error depends on the degree of rotational-error, separation of targets, and dose distribution around targets. For 10mm-target, PTV-coverage of distaltarget located 3cm-away was better than that of 1mm-target(0.93 versus 0.7) and GTV-coverage was 1.0 regardless of 6X-FFF/6X photon beams. Conclusion: RapidArc-based Multiple-target IMRS may Resultin a compromised outcome due to the setup-error for distal-targets. With 1mm-margin, GTV-coverage of distal-target was 1.0 although the separation of targets was up to 5cm.

07 ISOTOPE AND RADIATION SOURCES↗

TU-C-BRE-05: Clinical Implications of AAA Commissioning Errors and Ability of Common Commissioning ' Credentialing Procedures to Detect Them

Purpose: To test the ability of the TG-119 commissioning process and RPC credentialing to detect errors in the commissioning process for a commercial Treatment Planning System (TPS). Methods: We introduced commissioning errors into the commissioning process for the Anisotropic Analytical Algorithm (AAA) within the Eclipse TPS. We included errors in Dosimetric Leaf Gap (DLG), electron contamination, flattening filter material, and beam profile measurement with an inappropriately large farmer chamber (simulated using sliding window smoothing of profiles). We then evaluated the clinical impact of these errors on clinical intensity modulated radiation therapy (IMRT) plans (head and neck, low and intermediate risk prostate, mesothelioma, and scalp) by looking at PTV D99, and mean and max OAR dose. Finally, for errors with substantial clinical impact we determined sensitivity of the RPC IMRT film analysis at the midpoint between PTV and OAR using a 4mm distance to agreement metric, and of a 7% TLD dose comparison. We also determined sensitivity of the 3 dose planes of the TG-119 C-shape IMRT phantom using gamma criteria of 3% 3mm. Results: The largest clinical impact came from large changes in the DLG with a change of 1mm resulting in up to a 5% change in the primary PTV D99. This resulted in a discrepancy in the RPC TLDs in the PTVs and OARs of 7.1% and 13.6% respectively, which would have resulted in detection. While use of incorrect flattening filter caused only subtle errors (<1%) in clinical plans, the effect was most pronounced for the RPC TLDs in the OARs (>6%). Conclusion: The AAA commissioning process within the Eclipse TPS is surprisingly robust to user error. When errors do occur, the RPC and TG-119 commissioning credentialing criteria are effective at detecting them; however OAR TLDs are the most sensitive despite the RPC currently excluding them from analysis.

60 APPLIED LIFE SCIENCES↗

TU-C-BRE-07: Quantifying the Clinical Impact of VMAT Delivery Errors Relative to Prior Patients’ Plans and Adjusted for Anatomical Differences

Purpose: There is increased interest in the Radiation Oncology Physics community regarding sensitivity of pre-treatment IMRT/VMAT QA to delivery errors. Consequently, tools mapping pre-treatment QA to the patient DVH have been developed. However, the quantity of plan degradation that is acceptable remains uncertain. Using DVHs adapted from prior patients’ plans, we developed a technique to determine the magnitude of various delivery errors required to degrade a treatment plan to outside the clinically accepted range. Methods: DVHs for relevant organs at risk were adapted from a population of prior patients’ plans using a machine learning algorithm to establish the clinically acceptable DVH range specific to the patient’s anatomy. We applied this technique to six low-risk prostate cancer patients treated with single-arc VMAT and compared error-induced DVH changes to the adapted DVHs to determine the magnitude of error required to push the plan outside of the acceptable range. The procedure follows: (1) Errors (systematic ' random shift of MLCs, gantry-MLC desynchronization, dose rate fluctuations, etc.) were simulated and degraded DVHs calculated using the Varian Eclipse TPS. (2) Adapted DVHs and acceptable ranges for DVHs were established. (3) Relevant dosimetric indices and corresponding acceptable ranges were calculated from the DVHs. Key indices included NTCP (Lyman-Kutcher-Burman Model) and QUANTEC’s dose-volume Objectives: s of V75Gy≤0.15 for the rectum and V75Gy≤0.25 for the bladder. Results: Degradations to the clinical plan became “unacceptable” for 19±29mm and 1.9±2.0mm systematic outward shifts of a single leaf and leaf bank, respectively. All other simulated errors fell within the acceptable range. Conclusion: Utilizing machine learning and prior patients’ plans one can predict a clinically acceptable range of DVH degradation for a specific patient. Comparing error-induced DVH degradations to this range, it is shown that single-arc VMAT plans for low-risk prostate are relatively insensitive to many potential delivery errors.

60 APPLIED LIFE SCIENCES↗

SU-E-P-21: Impact of MLC Position Errors On Simultaneous Integrated Boost Intensity-Modulated Radiotherapy for Nasopharyngeal Carcinoma

Purpose: To investigate the impact of MLC position errors on simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT) for patients with nasopharyngeal carcinoma. Methods: To compare the dosimetric differences between the simulated plans and the clinical plans, ten patients with locally advanced NPC treated with SIB-IMRT were enrolled in this study. All plans were calculated with an inverse planning system (Pinnacle3, Philips Medical System{sub )}. Random errors −2mm to 2mm{sub )},shift errors{sub (} 2mm,1mm and 0.5mm) and systematic extension/ contraction errors (±2mm, ±1mm and ±0.5mm) of the MLC leaf position were introduced respectively into the original plans to create the simulated plans. Dosimetry factors were compared between the original and the simulated plans. Results: The dosimetric impact of the random and system shift errors of MLC position was insignificant within 2mm, the maximum changes in D95% of PGTV,PTV1,PTV2 were-0.92±0.51%,1.00±0.24% and 0.62±0.17%, the maximum changes in the D0.1cc of spinal cord and brainstem were 1.90±2.80% and −1.78±1.42%, the maximum changes in the Dmean of parotids were1.36±1.23% and −2.25±2.04%.However,the impact of MLC extension or contraction errors was found significant. For 2mm leaf extension errors, the average changes in D95% of PGTV,PTV1,PTV2 were 4.31±0.67%,4.29±0.65% and 4.79±0.82%, the averaged value of the D0.1cc to spinal cord and brainstem were increased by 7.39±5.25% and 6.32±2.28%,the averaged value of the mean dose to left and right parotid were increased by 12.75±2.02%,13.39±2.17% respectively. Conclusion: The dosimetric effect was insignificant for random MLC leaf position errors up to 2mm. There was a high sensitivity to dose distribution for MLC extension or contraction errors.We should pay attention to the anatomic changes in target organs and anatomical structures during the course,individual radiotherapy was recommended to ensure adaptive doses.

60 APPLIED LIFE SCIENCES↗

SU-E-J-88: The Study of Setup Error Measured by CBCT in Postoperative Radiotherapy for Cervical Carcinoma

Purpose: To compare two registration methods in the CBCT guided radiotherapy for cervical carcinoma, analyze the setup errors and registration methods, determine the margin required for clinical target volume(CTV) extending to planning target volume(PTV). Methods: Twenty patients with cervical carcinoma were enrolled. All patients were underwent CT simulation in the supine position. Transfering the CT images to the treatment planning system and defining the CTV, PTV and the organs at risk (OAR), then transmit them to the XVI workshop. CBCT scans were performed before radiotherapy and registered to planning CT images according to bone and gray value registration methods. Compared two methods and obtain left-right(X), superior-inferior(Y), anterior-posterior (Z) setup errors, the margin required for CTV to PTV were calculated. Results: Setup errors were unavoidable in postoperative cervical carcinoma irradiation. The setup errors measured by method of bone (systemic ± random) on X(1eft.right),Y(superior.inferior),Z(anterior.posterior) directions were(0.24±3.62),(0.77±5.05) and (0.13±3.89)mm, respectively, the setup errors measured by method of grey (systemic ± random) on X(1eft-right), Y(superior-inferior), Z(anterior-posterior) directions were(0.31±3.93), (0.85±5.16) and (0.21±4.12)mm, respectively.The spatial distributions of setup error was maximum in Y direction. The margins were 4 mm in X axis, 6 mm in Y axis, 4 mm in Z axis respectively.These two registration methods were similar and highly recommended. Conclusion: Both bone and grey registration methods could offer an accurate setup error. The influence of setup errors of a PTV margin would be suggested by 4mm, 4mm and 6mm on X, Y and Z directions for postoperative radiotherapy for cervical carcinoma.

60 APPLIED LIFE SCIENCES↗

SU-F-T-383: Robustness for Patient Setup Error in Total Body Irradiation Using Volumetric Modulated Arc Therapy (VMAT)

Purpose: Total body irradiation (TBI) and total marrow irradiation (TMI) using Tomotherapy have been reported. A gantry-based linear accelerator uses one isocenter during one rotational irradiation. Thus, 3–5 isocenter points should be used for a whole plan of TBI-VMAT during smoothing out the junctional dose distribution. IGRT provides accurate and precise patient setup for the multiple junctions, however it is evident that some setup errors should occur and affect accuracy of dose distribution in the area. In this study, we evaluated the robustness for patient’s setup error in VMAT-TBI. Methods: VMAT-TBI Planning was performed in an adult whole-body human phantom using Eclipse. Eight full arcs with four isocenter points using 6MV-X were used to cover the entire whole body. Dose distribution was optimized using two structures of patient’s body as PTV and lung. The two arcs were shared with one isocenter and the two arcs were 5 cm-overlapped with the other two arcs. Point absolute dose using ionization-chamber and planer relative dose distribution using film in the junctional regions were performed using water-equivalent slab phantom. In the measurements, several setup errors of (+5∼−5mm) were added. Results: The result of the chamber measurement shows the deviations were within ±3% when the setup errors were within ±3 mm. In the planer evaluation, the pass ratio of gamma evaluation (3%/2mm) shows more than 90% if the errors within ±3 mm. However, there were hot/cold areas in the edge of the junction even with acceptable gamma pass ratio. 5 mm setup error caused larger hot and cold areas and the dosimetric acceptable areas were decreased in the overlapped areas. Conclusion: It can be clinically acceptable for VMAT-TBI when patient setup error is within ±3mm. Averaging effects from patient random error would be helpful to blur the hot/cold area in the junction.

60 APPLIED LIFE SCIENCES↗

SU-G-BRB-11: On the Sensitivity of An EPID-Based 3D Dose Verification System to Detect Delivery Errors in VMAT Treatments

Purpose: To investigate the sensitivity of an EPID-based 3D dose verification system to detect delivery errors in VMAT treatments. Methods: For this study 41 EPID-reconstructed 3D in vivo dose distributions of 15 different VMAT plans (H&N, lung, prostate and rectum) were selected. To simulate the effect of delivery errors, their TPS plans were modified by: 1) scaling of the monitor units by ±3% and ±6% and 2) systematic shifting of leaf bank positions by ±1mm, ±2mm and ±5mm. The 3D in vivo dose distributions where then compared to the unmodified and modified treatment plans. To determine the detectability of the various delivery errors, we made use of a receiver operator characteristic (ROC) methodology. True positive and false positive rates were calculated as a function of the γ-parameters γmean, γ1% (near-maximum γ) and the PTV dose parameter ΔD{sub 50} (i.e. D{sub 50}(EPID)-D{sub 50}(TPS)). The ROC curve is constructed by plotting the true positive rate vs. the false positive rate. The area under the ROC curve (AUC) then serves as a measure of the performance of the EPID dosimetry system in detecting a particular error; an ideal system has AUC=1. Results: The AUC ranges for the machine output errors and systematic leaf position errors were [0.64 – 0.93] and [0.48 – 0.92] respectively using γmean, [0.57 – 0.79] and [0.46 – 0.85] using γ1% and [0.61 – 0.77] and [ 0.48 – 0.62] using ΔD{sub 50}. Conclusion: For the verification of VMAT deliveries, the parameter γmean is the best discriminator for the detection of systematic leaf position errors and monitor unit scaling errors. Compared to γmean and γ1%, the parameter ΔD{sub 50} performs worse as a discriminator in all cases.

60 APPLIED LIFE SCIENCES↗

MO-FG-BRA-06: Electromagnetic Beacon Insertion in Lung Cancer Patients and Resultant Surrogacy Errors for Dynamic MLC Tumour Tracking

Purpose: To assess endo-bronchial electromagnetic beacon insertion and to quantify the geometric accuracy of using beacons as a surrogate for tumour motion in real-time multileaf collimator (MLC) tracking of lung tumours. Methods: The LIGHT SABR trial is a world-first clinical trial in which the MLC leaves move with lung tumours in real time on a standard linear accelerator. Tracking is performed based on implanted electromagnetic beacons (CalypsoTM, Varian Medical Systems, USA) as a surrogate for tumour motion. Five patients have been treated and have each had three beacons implanted endo-bronchially under fluoroscopic guidance. The centre of mass (C.O.M) has been used to adapt the MLC in real-time. The geometric error in using the beacon C.O.M as a surrogate for tumour motion was measured by measuring the tumour and beacon C.O.M in all phases of the respiratory cycle of a 4DCT. The surrogacy error was defined as the difference in beacon and tumour C.O.M relative to the reference phase (maximum exhale). Results: All five patients have had three beacons successfully implanted with no migration between simulation and end of treatment. Beacon placement relative to tumour C.O.M varied from 14 to 74 mm and in one patient spanned two lobes. Surrogacy error was measured in each patient on the simulation 4DCT and ranged from 0 to 3 mm. Surrogacy error as measured on 4DCT was subject to artefacts in mid-ventilation phases. Surrogacy error was a function of breathing phase and was typically larger at maximum inhale. Conclusion: Beacon placement and thus surrogacy error is a major component of geometric uncertainty in MLC tracking of lung tumours. Surrogacy error must be measured on each patient and incorporated into margin calculation. Reduction of surrogacy error is limited by airway anatomy, however should be taken into consideration when performing beacon insertion and planning. This research is funded by Varian Medical Systems via a collaborative research agreement.

60 APPLIED LIFE SCIENCES↗

MO-FG-202-05: Identifying Treatment Planning System Errors in IROC-H Phantom Irradiations

Purpose: Treatment Planning System (TPS) errors can affect large numbers of cancer patients receiving radiation therapy. Using an independent recalculation system, the Imaging and Radiation Oncology Core-Houston (IROC-H) can identify institutions that have not sufficiently modelled their linear accelerators in their TPS model. Methods: Linear accelerator point measurement data from IROC-H’s site visits was aggregated and analyzed from over 30 linear accelerator models. Dosimetrically similar models were combined to create “classes”. The class data was used to construct customized beam models in an independent treatment dose verification system (TVS). Approximately 200 head and neck phantom plans from 2012 to 2015 were recalculated using this TVS. Comparison of plan accuracy was evaluated by comparing the measured dose to the institution’s TPS dose as well as the TVS dose. In cases where the TVS was more accurate than the institution by an average of >2%, the institution was identified as having a non-negligible TPS error. Results: Of the ∼200 recalculated plans, the average improvement using the TVS was ∼0.1%; i.e. the recalculation, on average, slightly outperformed the institution’s TPS. Of all the recalculated phantoms, 20% were identified as having a non-negligible TPS error. Fourteen plans failed current IROC-H criteria; the average TVS improvement of the failing plans was ∼3% and 57% were found to have non-negligible TPS errors. Conclusion: IROC-H has developed an independent recalculation system to identify institutions that have considerable TPS errors. A large number of institutions were found to have non-negligible TPS errors. Even institutions that passed IROC-H criteria could be identified as having a TPS error. Resolution of such errors would improve dose delivery for a large number of IROC-H phantoms and ultimately, patients.

60 APPLIED LIFE SCIENCES↗

MO-FG-CAMPUS-JeP3-01: A Statistical Model for Analyzing the Rotational Error of Single Iso-Center Technique

Purpose: To develop a generalized statistical model that incorporates the treatment uncertainty from the rotational error of single iso-center technique, and calculate the additional PTV (planning target volume) margin required to compensate for this error. Methods: The random vectors for setup and additional rotation errors in the three-dimensional (3D) patient coordinate system were assumed to follow the 3D independent normal distribution with zero mean, and standard deviations σx, σy, σz, for setup error and a uniform σR for rotational error. Both random vectors were summed, normalized and transformed to the spherical coordinates to derive the chi distribution with 3 degrees of freedom for the radical distance ρ. PTV margin was determined using the critical value of this distribution for 0.05 significant level so that 95% of the time the treatment target would be covered by ρ. The additional PTV margin required to compensate for the rotational error was calculated as a function of σx, σy, σz and σR. Results: The effect of the rotational error is more pronounced for treatments that requires high accuracy/precision like stereotactic radiosurgery (SRS) or stereotactic body radiotherapy (SBRT). With a uniform 2mm PTV margin (or σx =σy=σz=0.7mm), a σR=0.32mm will decrease the PTV coverage from 95% to 90% of the time, or an additional 0.2mm PTV margin is needed to prevent this loss of coverage. If we choose 0.2 mm as the threshold, any σR>0.3mm will lead to an additional PTV margin that cannot be ignored, and the maximal σR that can be ignored is 0.0064 rad (or 0.37°) for iso-to-target distance=5cm, or 0.0032 rad (or 0.18°) for iso-to-target distance=10cm. Conclusions: The rotational error cannot be ignored for high-accuracy/-precision treatments like SRS/SBRT, particularly when the distance between the iso-center and target is large.

60 APPLIED LIFE SCIENCES↗

WE-AB-209-01: A Monte Carlo-Based Method to Include Random Errors in Robust Optimization

Purpose: To develop an efficient method to implement random set-up errors and organ motion in robust optimization for proton therapy treatment planning. Methods: The plans were created with an in-house robust optimizer, coupled with a super-fast Monte Carlo (MC) engine (less than 1 minute for final dose). MC simulates random errors by shifting randomly the starting point of each particle, according to their probability distribution. Such strategy assumes a sufficient number of treatment fractions. Two strategies are presented: 1) Full robust optimization with beamlets that already include the effect of random errors and 2) Mixed robust optimization, where the nominal beamlets are involved but a correction term C modifies the prescription. Starting from C=0, the method alternates optimization of the spot weights with the nominal beamlets and updates of C, with C=Drandom-Dnominal and where Drandom results from a regular MC computation (without pre-computed beamlets) that simulates random errors. Updates of C can be triggered as often as necessary by running the MC engine with the last corrected values for the spot weights as input. The method was applied to lung and prostate cases. For both patients the range error was set to 3%, systematic setup error to 5mm and standard deviation for random errors to 5 mm. Comparison between full robust optimization and the mixed strategy (with 3 updates of C) is presented. Results: Target coverage was far below the clinical constraints (D{sub 95} > 95% of the prescribed dose) for plans where random errors were not simulated, especially for lung case. However, by using the proposed strategies the plans achieved a target coverage above clinical constraints. Conclusion: Full robust optimization gives better results than the mixed strategy, but the latter can be useful in cases where a MC engine is not available or too computationally intensive for beamlets calculation.

60 APPLIED LIFE SCIENCES↗

WE-H-BRC-05: Catastrophic Error Metrics for Radiation Therapy

Purpose: Intuitive evaluation of complex radiotherapy treatments is impractical, while data transfer anomalies create the potential for catastrophic treatment delivery errors. Contrary to prevailing wisdom, logical scrutiny can be applied to patient-specific machine settings. Such tests can be automated, applied at the point of treatment delivery and can be dissociated from prior states of the treatment plan, potentially revealing errors introduced early in the process. Methods: Analytical metrics were formulated for conventional and intensity modulated RT (IMRT) treatments. These were designed to assess consistency between monitor unit settings, wedge values, prescription dose and leaf positioning (IMRT). Institutional metric averages for 218 clinical plans were stratified over multiple anatomical sites. Treatment delivery errors were simulated using a commercial treatment planning system and metric behavior assessed via receiver-operator-characteristic (ROC) analysis. A positive result was returned if the erred plan metric value exceeded a given number of standard deviations, e.g. 2. The finding was declared true positive if the dosimetric impact exceeded 25%. ROC curves were generated over a range of metric standard deviations. Results: Data for the conventional treatment metric indicated standard deviations of 3%, 12%, 11%, 8%, and 5 % for brain, pelvis, abdomen, lung and breast sites, respectively. Optimum error declaration thresholds yielded true positive rates (TPR) between 0.7 and 1, and false positive rates (FPR) between 0 and 0.2. Two proposed IMRT metrics possessed standard deviations of 23% and 37%. The superior metric returned TPR and FPR of 0.7 and 0.2, respectively, when both leaf position and MUs were modelled. Isolation to only leaf position errors yielded TPR and FPR values of 0.9 and 0.1. Conclusion: Logical tests can reveal treatment delivery errors and prevent large, catastrophic errors. Analytical metrics are able to identify errors in monitor units, wedging and leaf positions with favorable sensitivity and specificity. In part by Varian.

60 APPLIED LIFE SCIENCES↗

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiple causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.

60 APPLIED LIFE SCIENCES↗

Estimating Aboveground Biomass in Tropical Forests: Field Methods and Error Analysis for the Calibration of Remote Sensing Observations

Mapping and monitoring of forest carbon stocks across large areas in the tropics will necessarily rely on remote sensing approaches, which in turn depend on field estimates of biomass for calibration and validation purposes. Here, we used field plot data collected in a tropical moist forest in the central Amazon to gain a better understanding of the uncertainty associated with plot-level biomass estimates obtained specifically for the calibration of remote sensing measurements. In addition to accounting for sources of error that would be normally expected in conventional biomass estimates (e.g., measurement and allometric errors), we examined two sources of uncertainty that are specific to the calibration process and should be taken into account in most remote sensing studies: the error resulting from spatial disagreement between field and remote sensing measurements (i.e., co-location error), and the error introduced when accounting for temporal differences in data acquisition. We found that the overall uncertainty in the field biomass was typically 25% for both secondary and primary forests, but ranged from 16 to 53%. Co-location and temporal errors accounted for a large fraction of the total variance (>65%) and were identified as important targets for reducing uncertainty in studies relating tropical forest biomass to remotely sensed data. Although measurement and allometric errors were relatively unimportant when considered alone, combined they accounted for roughly 30% of the total variance on average and should not be ignored. Lastly, our results suggest that a thorough understanding of the sources of error associated with field-measured plot-level biomass estimates in tropical forests is critical to determine confidence in remote sensing estimates of carbon stocks and fluxes, and to develop strategies for reducing the overall uncertainty of remote sensing approaches.

54 ENVIRONMENTAL SCIENCES↗

Characterization of the Impact of Soft Errors on Iterative Methods

Soft errors caused by transient bit flips have the potential to significantly impact an application’s behavior. This has motivated the design of an array of techniques to detect, isolate, and correct soft errors using microarchitectural, architectural, compilation-based, or application-level techniques to minimize their impact on the executing application. The first step towards the design of good error detection/correction techniques involves an understanding of an application’s vulnerability to soft errors. In this paper, we present the first comprehensive characterization of the impact of soft errors on the convergence characteristics of six iterative methods using application-level fault injection. In particular, we consider the use of iterative methods to incrementally solve a linear systems of equations, which constitutes the core kernel in many scientific applications. We analyze the impact of soft errors in terms of the type of error (single- vs multi-bit), the distribution and location of bits affected, the data structure and the statement impacted, and variation with time. In addition to understanding the vulnerability of iterative solvers to soft errors, this characterization can aid the design of fault injection campaigns that ensure systematic coverage.

fault injection, iterative methods, Silent data co↗