Static Dose Research Articles

Technical aspects of real time positron emission tracking for gated radiotherapy.

Respiratory motion can lead to treatment errors in the delivery of radiotherapy treatments. Respiratory gating can assist in better conforming the beam delivery to the target volume. We present a study of the technical aspects of a real time positron emission tracking system for potential use in gated radiotherapy. The tracking system, called PeTrack, uses implanted positron emission markers and position sensitive gamma ray detectors to track breathing motion in real time. PeTrack uses an expectation-maximization algorithm to track the motion of fiducial markers. A normalized least mean squares adaptive filter predicts the location of the markers a short time ahead to account for system response latency. The precision and data collection efficiency of a prototype PeTrack system were measured under conditions simulating gated radiotherapy. The lung insert of a thorax phantom was translated in the inferior-superior direction with regular sinusoidal motion and simulated patient breathing motion (maximum amplitude of motion ±10 mm, period 4 s). The system tracked the motion of a (22)Na fiducial marker (0.34 MBq) embedded in the lung insert every 0.2 s. The position of the was marker was predicted 0.2 s ahead. For sinusoidal motion, the equation used to model the motion was fitted to the data. The precision of the tracking was estimated as the standard deviation of the residuals. Software was also developed to communicate with a Linac and toggle beam delivery. In a separate experiment involving a Linac, 500 monitor units of radiation were delivered to the phantom with a 3 × 3 cm photon beam and with 6 and 10 MV accelerating potential. Radiochromic films were inserted in the phantom to measure spatial dose distribution. In this experiment, the period of motion was set to 60 s to account for beam turn-on latency. The beam was turned off when the marker moved outside of a 5-mm gating window. The precision of the tracking in the IS direction was 0.53 mm for a sinusoidally moving target, with an average count rate ∼250 cps. The average prediction error was 1.1 ± 0.6 mm when the marker moved according to irregular patient breathing motion. Across all beam deliveries during the radiochromic film measurements, the average prediction error was 0.8 ± 0.5 mm. The maximum error was 2.5 mm and the 95th percentile error was 1.5 mm. Clear improvement of the dose distribution was observed between gated and nongated deliveries. The full-width at halfmaximum of the dose profiles of gated deliveries differed by 3 mm or less than the static reference dose distribution. Monitoring of the beam on/off times showed synchronization with the location of the marker within the latency of the system. PeTrack can track the motion of internal fiducial positron emission markers with submillimeter precision. The system can be used to gate the delivery of a Linac beam based on the position of a moving fiducial marker. This highlights the potential of the system for use in respiratory-gated radiotherapy.

Dosimetric effect of intra-fractional and inter-fractional target motion in lung cancer radiotherapy techniques

Purpose: The purpose of present study was to experimentally evaluate the dosimetric uncertainties in 3-dimensional conformal radiotherapy (3DCRT), dynamic intensity modulated radiotherapy (D-IMRT), step-shoot (SS-IMRT), and volumetric modulated arc therapy (VMAT) treatment delivery techniques due to intra- and inter-fractional target motion. Methods: A previously treated lung patient was selected for this study and was replanned for 60 Gy in 30 fractions using four techniques (3DCRT, D-IMRT, SS-IMRT, and VMAT). These plans were delivered in a clinical linear accelerator equipped with HexaPOD™ evo RT System. The target dose of static QUASAR phantom was calculated that served as reference dose to the target. The QUASAR respiratory body phantom along with patients breathing wave form and HexaPOD™ evo RT System was used to simulate the intra-fraction and inter-fraction motions. Dose measurements were done by applying the intra-fractional and inter-fractional motions in all the four treatment delivery techniques. Results: The maximum percentage deviation in a single field was -4.3%, 10.4%, and -12.2% for 3DCRT, D-IMRT and SS-IMRT deliveries, respectively. Similarly, the deviation for a single fraction was -1.51%, -1.88%, -2.22%, and -3.03% for 3DCRT, D-IMRT, SS-IMRT and VMAT deliveries, respectively. Conclusion: The impact of inter-fractional and intra-fractional uncertainties calculated as deviation between dynamic and static condition dose was large in some fractions, however average deviation calculated for thirty fractions was well within 0.5% in all the four techniques. Therefore, inter- and intra-fractional uncertainties could be concern in fewer fraction treatments such as stereotactic body radiation therapy, and should be used in conjunction with intra- and inter-fractional motion management techniques.

Effect of deformable registration uncertainty on lung SBRT dose accumulation.

Deformable image registration (DIR) plays an important role in dose accumulation, such as incorporating breathing motion into the accumulation of the delivered dose based on daily 4DCBCT images. However, it is not yet well understood how the uncertainties associated with DIR methods affect the dose calculations and resulting clinical metrics. The purpose of this study is to evaluate the impact of DIR uncertainty on the clinical metrics derived from its use in dose accumulation. A biomechanical model based DIR method and a biomechanical-intensity-based hybrid method, which reduced the average registration error by 1.6 mm, were applied to ten lung cancer patients. A clinically relevant dose parameter [minimum dose to 0.5 cm(3) (Dmin)] was calculated for three dose scenarios using both algorithms. Dose scenarios included static (no breathing motion), predicted (breathing motion at the time of planning), and total accumulated (interfraction breathing motion). The relationship between the dose parameter and a combination of DIR uncertainty metrics, tumor volume, and dose heterogeneity of the plan was investigated. Depending on the dose heterogeneity, tumor volume, and DIR uncertainty, in over 50% of the patients, differences greater than 1.0 Gy were observed in the Dmin of the tumor in the static dose calculation on exhale phase of the 4DCT. Such differences were due to the errors in propagating the tumor contours from the reference planning 4DCT phase onto a subsequent 4DCT phase using each DIR algorithm and calculating the dose on that phase. The differences in predicted dose were more subtle when breathing motion was modeled explicitly at the time of planning with only one patient exhibiting a greater than 1.0 Gy difference in Dmin. Dmin differences of up to 2.5 Gy were found in the total accumulated delivered dose due to difference in quantifying the interfraction variations. Such dose uncertainties could potentially be clinically significant. Reductions in average uncertainty in DIR algorithms by 1.6 mm may have a clinically significant impact on the decision-making metrics used in dose planning and dose accumulation assessment.

4-D Predicted Accumulated Dose Versus Time Weighted Average 4D-CBCT Recalculated Dose Variations in Liver SABR

Quantify the variations to tumor and normal tissues between 4D predicted accumulated dose and doses recalculated on time weighted average 4D CBCT static derived series in liver SABR 25 pts with 38 liver metastatic lesions underwent gold seed fiducial placement, triphasic liver scan, respiratory correlated 4D CT. Lesions were localized on the static Hepatic arterial/portal venous phase CT (as they were well visualized) and fused to corresponding 4D-dataset and ITV thus defined. A dose of 39gy in 6 fractions was planned using step using step and shoot IMRT. The finalized plan Structure were deform registered and dose warped across all the 4D datasets by intensity-based-free-form deformable registration and final 4D predicted accumulated dose thus calculated. Treatment was executed using 4D-CBCT image guidance on a 6 DOF couch. The final planned CT dataset is further dose deformed on to first set-up corrected time weighted Avg. derived static series from 4D-CBCT dataset. Using deformable image registration, subsequent fraction doses on reference geometry (first time weighted average series) were added up to get final delivered doses. The contribution of different geometric errors to changes between the accumulated and delivered dose were quantified and changes greater than 1 gray, reported as percent change (normalized to prescription dose) were considered significant All patients had accumulated dose deviations relative to the planned static prescription dose >5%, ranging 3-18% in tumors and 5-25% in normal tissues. Residual setup errors were most often the largest cause of the deviations, followed by deformations and breathing variations. Gold seed markers, while producing delineation artifacts and deformation errors, were good surrogate for treatment verification when 4D CBCT was used (with acquisition time of 3mts). These deformation errors were minimized with proper deformation QA using registration refining tools and alignment locks Accumulated dose deviations ranging from 5-20% relative to the static plan are observed in all pts undergoing liver SABR. Modalities which impede breathing motion like diaphragmatic compression will produce more deformation errors leading to erroneous prediction of 4D dose and accumulated dose.

VMAT-SBRT planning based on an average intensity projection for lung tumors located in close proximity to the diaphragm: a phantom and clinical validity study.

The aim of the this study was to validate the use of an average intensity projection (AIP) for volumetric-modulated arc therapy for stereotactic body radiation therapy (VMAT–SBRT) planning for a moving lung tumor located near the diaphragm. VMAT–SBRT plans were created using AIPs reconstructed from 10 phases of 4DCT images that were acquired with a target phantom moving with amplitudes of 5, 10, 20 and 30 mm. To generate a 4D dose distribution, the static dose for each phase was recalculated and the doses were accumulated by using the phantom position known for each phase. For 10 patients with lung tumors, a deformable registration was used to generate 4D dose distributions. Doses to the target volume obtained from the AIP plan and the 4D plan were compared, as were the doses obtained from each plan to the organs at risk (OARs). In both phantom and clinical study, dose discrepancies for all parameters of the dose volume (Dmin, D99, Dmax, D1 and Dmean) to the target were <3%. The discrepancies of Dmax for spinal cord, esophagus and heart were <1 Gy, and the discrepancy of V20 for lung tissue was <1%. However, for OARs with large respiratory motion, the discrepancy of the Dmax was as much as 9.6 Gy for liver and 5.7 Gy for stomach. Thus, AIP is clinically acceptable as a planning CT image for predicting 4D dose, but doses to the OARs with large respiratory motion were underestimated with the AIP approach.

SU-F-303-17: Real Time Dose Calculation of MRI Guided Co-60 Radiotherapy Treatments On Free Breathing Patients, Using a Motion Model and Fast Monte Carlo Dose Calculation

Purpose: To demonstrate real-time dose calculation of free-breathing MRI guided Co−60 treatments, using a motion model and Monte-Carlo dose calculation to accurately account for the interplay between irregular breathing motion and an IMRT delivery. Methods: ViewRay Co-60 dose distributions were optimized on ITVs contoured from free-breathing CT images of lung cancer patients. Each treatment plan was separated into 0.25s segments, accounting for the MLC positions and beam angles at each time point. A voxel-specific motion model derived from multiple fast-helical free-breathing CTs and deformable registration was calculated for each patient. 3D images for every 0.25s of a simulated treatment were generated in real time, here using a bellows signal as a surrogate to accurately account for breathing irregularities. Monte-Carlo dose calculation was performed every 0.25s of the treatment, with the number of histories in each calculation scaled to give an overall 1% statistical uncertainty. Each dose calculation was deformed back to the reference image using the motion model and accumulated. The static and real-time dose calculations were compared. Results: Image generation was performed in real time at 4 frames per second (GPU). Monte-Carlo dose calculation was performed at approximately 1frame per second (CPU), giving a total calculation time of approximately 30 minutes per treatment. Results show both cold- and hot-spots in and around the ITV, and increased dose to contralateral lung as the tumor moves in and out of the beam during treatment. Conclusion: An accurate motion model combined with a fast Monte-Carlo dose calculation allows almost real-time dose calculation of a free-breathing treatment. When combined with sagittal 2D-cine-mode MRI during treatment to update the motion model in real time, this will allow the true delivered dose of a treatment to be calculated, providing a useful tool for adaptive planning and assessing the effectiveness of gated treatments.

TH-AB-303-01: Benchmarking Real-Time Adaptive Radiotherapy Systems: A Multi- Platform Multi-Institutional Study

Purpose: The era of real-time adaptive radiotherapy is here: patients are being treated by CyberKnife (since 2004), Vero (2011) and MLC tracking (2013) technology, with couch tracking planned to be clinical in 2015. We have developed a common set of tools for benchmarking real-time adaptive radiotherapy systems and to test the hypothesis that, across delivery systems and institutions, real-time adaptive radiotherapy improves the dosimetric accuracy over non-adaptive radiotherapy in the presence of realistic tumor motion. Methods: Ten institutions with CyberKnife, Vero, MLC or couch tracking technology were involved in the study. Common materials were anonymized lung and prostate CT and structure sets, patient-measured motion traces (four lung, four prostate) and SBRT planning protocols (lung: RTOG1021, prostate: RTOG0938). The institutions delivered lung and prostate plans to a moving dosimeter programmed with tumor motion. For each trace the plan was delivered twice; with and without motion adaptation, each measurement was compared to the static dosimeter dose and the percentage of failed points for γ-tests recorded. Results: Eleven measurement sets were obtained for this study; two CyberKnife, two Vero, five MLC and two couch tracking sets. For all lung traces all sets show improved dose accuracy from a mean 2%/2mm γ-failrate of 1.6% with adaptation and 14.7% with no motion correction(p<0.001). For all prostate traces the mean 2%/2mm γ-failrate was 1.6% with adaptation and 17.4% with no motion correction (p<0.001). The difference between the four adaptive systems was small with an average 2%/2mm γ-failrate of <3% for all systems with adaptation for lung and prostate. Conclusion: A common set of tools has been developed for benchmarking real-time adaptive radiotherapy systems and a multi-platform multi-institutional study performed. The results show the systems all account for realistic tumor motion accurately and performed to a similar high standard, with real-time adaptation significantly outperforming non-adaptive methods.

SU-E-T-293: Dosimetric Analysis of Microscopic Disease in SBRT for Lung Cancers

Purpose: To evaluate the dosimetry of microscopic disease (MD) region of lung cancer in stereotactic body radiation therapy (SBRT). Methods: For simplicity, we assume organ moves along one dimension. The probability distribution function of tumor position was calculated according to the breathing cycle. The dose to the MD region was obtained through accumulating the treatment planning system calculated doses at different positions in a breathing cycle. A phantom experiment was then conducted to validate the calculated results using a motion phantom (The CIRS ‘Dynamic’ Thorax Phantom). The simulated breathing pattern used a cos4(x) curve with an amplitude of 10mm. A 3-D conformal 7-field plan with 6X energy was created and the dose was calculated in the average intensity projection (AIP) simulation CT images. Both films (EBT2) and optically stimulated luminescence (OSL) detectors were inserted in the target of the phantom to measure the dose during radiation delivery (Varian Truebeam) and results were compared to planning dose parameters. Results: The Gamma analysis (3%/3mm) between measured dose using EBT2 film and calculated dose using AIP was 80.5%, indicating substantial dosimetric differences. While the Gamma analysis (3%/3mm) between measured dose using EBT2 and accumulated dose using 4D-CT was 98.9%, indicating the necessity of dose accumulation using 4D-CT. The measured doses using OSL and theoretically calculated doses using probability distribution function at the corresponding position were comparable. Conclusion: Use of static dose calculation in the treatment planning system could substantially underestimate the actually delivered dose in the MD region for a moving target. Funding Supported by NSFC, No.81372436

TU-AB-BRB-03: Coverage-Based Treatment Planning to Accommodate Organ Deformable Motions and Contouring Uncertainties for Prostate Treatment

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. The treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: 1. To understand robust-planning as a clinical alternative to using margin-based planning. 2. To understand conceptual differences between uncertainty and predictable motion. 3. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. 4. To understand the major contributing factors to target and normal tissue coverage probability. 5. To understand the similarities and differences of various robust planning techniques 6. To understand the benefits and limitations of robust planning techniques

TU‐AB‐BRB‐00: New Methods to Ensure Target Coverage

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV‐to‐CTV and CTV‐to‐PTV margins during the planning process to design a PTV‐conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. &gt;95%) target coverage probability (CP) in spite of inherent inter‐ and intra‐fractional positional variations, tissue motions, and initial contouring uncertainties.Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage‐based planning objectives. The treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP‐evaluation for the underlying CTVs and OARs to design an optimal treated volume.This symposium will describe CP‐evaluation methods as well as various robust planning techniques including use of probability‐weighted dose distributions, probability‐weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter‐fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra‐fractional organ motion. Clinical examples will be used to inter‐compare robust and margin‐based planning, highlighting advantages of robust‐plans in terms of target and normal tissue coverage. Robust‐planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning.Learning Objectives: To understand robust‐planning as a clinical alternative to using margin‐based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques

TU‐AB‐BRB‐01: Coverage Evaluation and Probabilistic Treatment Planning as a Margin Alternative

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV‐to‐CTV and CTV‐to‐PTV margins during the planning process to design a PTV‐conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. &gt;95%) target coverage probability (CP) in spite of inherent inter‐ and intra‐fractional positional variations, tissue motions, and initial contouring uncertainties.Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage‐based planning objectives. The treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP‐evaluation for the underlying CTVs and OARs to design an optimal treated volume.This symposium will describe CP‐evaluation methods as well as various robust planning techniques including use of probability‐weighted dose distributions, probability‐weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter‐fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra‐fractional organ motion. Clinical examples will be used to inter‐compare robust and margin‐based planning, highlighting advantages of robust‐plans in terms of target and normal tissue coverage. Robust‐planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning.Learning Objectives: To understand robust‐planning as a clinical alternative to using margin‐based planning. To understand conceptual differences between uncertainty and predictable motion. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. To understand the major contributing factors to target and normal tissue coverage probability. To understand the similarities and differences of various robust planning techniques To understand the benefits and limitations of robust planning techniques

TU-AB-BRB-02: Stochastic Programming Methods for Handling Uncertainty and Motion in IMRT Planning

The accepted clinical method to accommodate targeting uncertainties inherent in fractionated external beam radiation therapy is to utilize GTV-to-CTV and CTV-to-PTV margins during the planning process to design a PTV-conformal static dose distribution on the planning image set. Ideally, margins are selected to ensure a high (e.g. >95%) target coverage probability (CP) in spite of inherent inter- and intra-fractional positional variations, tissue motions, and initial contouring uncertainties. Robust optimization techniques, also known as probabilistic treatment planning techniques, explicitly incorporate the dosimetric consequences of targeting uncertainties by including CP evaluation into the planning optimization process along with coverage-based planning objectives. The treatment planner no longer needs to use PTV and/or PRV margins; instead robust optimization utilizes probability distributions of the underlying uncertainties in conjunction with CP-evaluation for the underlying CTVs and OARs to design an optimal treated volume. This symposium will describe CP-evaluation methods as well as various robust planning techniques including use of probability-weighted dose distributions, probability-weighted objective functions, and coverage optimized planning. Methods to compute and display the effect of uncertainties on dose distributions will be presented. The use of robust planning to accommodate inter-fractional setup uncertainties, organ deformation, and contouring uncertainties will be examined as will its use to accommodate intra-fractional organ motion. Clinical examples will be used to inter-compare robust and margin-based planning, highlighting advantages of robust-plans in terms of target and normal tissue coverage. Robust-planning limitations as uncertainties approach zero and as the number of treatment fractions becomes small will be presented, as well as the factors limiting clinical implementation of robust planning. Learning Objectives: 1. To understand robust-planning as a clinical alternative to using margin-based planning. 2. To understand conceptual differences between uncertainty and predictable motion. 3. To understand fundamental limitations of the PTV concept that probabilistic planning can overcome. 4. To understand the major contributing factors to target and normal tissue coverage probability. 5. To understand the similarities and differences of various robust planning techniques 6. To understand the benefits and limitations of robust planning techniques

Tagged MRI based cardiac motion modeling and toxicity evaluation in breast cancer radiotherapy.

Recent research showed radiation for breast cancer can increase heart risks (1, 2). In Ref. (2), it has been noted that for every Gy of radiation a women’s heart risk rises 7.4%. However, the correlation between radiation dose and heart tissue damage is still an open problem. A more accurate model of heart damage will significantly improve the heart safety for patients underwent radiotherapy. Modern radiation treatment planning systems (TPS) use computed tomography (CT) images for dose calculation and evaluation. For evaluation of heart toxicity from radiotherapy, the dose-volume histogram (DVH), which is generated by overlying radiation dose distribution on heart delineations in CT images, is widely used. However, there are three major factors that deteriorate the accuracy of TPS-calculated heart dose distribution. First conventional CT is a fundamentally static imaging modality without the capability to capture and depict the cardiac motion. Instead, heart is usually blurred in CT images due to the motion artifacts. Second, without special contrast dye, CT provides limited contrast between blood in heart chambers and the surrounding myocardium. The heart region in TPS is actually a mixture of myocardium and blood, although only the radiation dose to the myocardium is accountable for heart risks. Finally, there is significant intra- and inter-fractional heart motion. As heart beats involuntarily during and between radiation treatments, myocardium deforms and moves non-rigidly against the fixed radiation beam so that the static dose distribution calculated in CT based TPS does not reflect the accurate radiation dose distribution in heart. There is also concern on the choice of the heart function for the evaluation of radiation damage. Based on radiation beam geometry, only part of the heart will receive clinically significant level of radiation during breast cancer treatment. It is possible that the global heart function remains stable temporarily while cells in the irradiated part of the myocardium lose part or all of their functions. In this case, regional heart function, which can be derived from regional heart wall motion and strain analysis, is a better indication of heart damage corresponding to radiation dose. Although cardiac MRI is widely used in radiology for the diagnosis of heart disease, its application in radiation treatment planning is limited. For multiple reasons, it is not practical to use MRI directly for radiation treatment planning of breast cancer patients. However, via multimodality deformable image registration (DIR) between MRI and CT, MRI images may play a more critical role in the evaluation of the heart damage from whole breast radiation. Tagged MRI (tMRI) (3) is a relatively new imaging protocol that has been implemented in the detection and diagnosis of regional heart functional loss. tMRI methods record regional heart wall motion information as they create identifiable landmark bands (tags) in the myocardium to establish dense point to point correspondence between images. ECG-gated tMRI image sets can be acquired at different phases of the cardiac cycle using the corresponding pulse sequence. The 4D (3D plus time) cardiac motion model can be retrieved by image registration between tMRIs at different phases. In the following sessions, we use tMRI as an example to explain how additional heart function information in MRI is retrieved. It is our objective to demonstrate the additional information retrieved from MRI can help the evaluation and protection of heart risks for breast cancer patients, and we want to discuss the possibility of using MRI to establish a more accurate correlation between regional heart functional loss and radiation dose.

Pharmacodynamic target evaluation of a novel oral glucan synthase inhibitor, SCY-078 (MK-3118), using an in vivo murine invasive candidiasis model.

Echinocandins inhibit the synthesis of β-1,3-D-glucan in Candida and are the first-line therapy in numerous clinical settings. Their use is limited by poor oral bioavailability, and they are available only as intravenous therapies. Derivatives of enfumafungin are novel orally bioavailable glucan synthase inhibitors. We performed an in vivo pharmacodynamic (PD) evaluation with a novel enfumafungin derivative, SCY-078 (formerly MK-3118), in a well-established neutropenic murine model of invasive candidiasis against C. albicans, C. glabrata, and C. parapsilosis. The SCY-078 MICs varied 8-fold. Oral doses of 3.125 to 200 mg/kg SCY-078 salt in sterile water produced peak levels of 0.04 to 2.66 μg/ml, elimination half-lives of 5.8 to 8.5 h, areas under the concentration-time curve from 0 to 24 h (AUC0-24 h) of 0.61 to 41.10 μg·h/ml, and AUC from 0 to infinity (AUC0-∞) values of 0.68 to 40.31 μg·h/ml. The pharmacokinetics (PK) were approximately linear over the dose range studied. Maximum response (Emax) and PK/PD target identification studies were performed with 4 C. albicans, 4 C. glabrata, and 3 C. parapsilosis isolates. The PD index AUC/MIC was explored by using total (tAUC) and free (fAUC) drug concentrations. The maximum responses were 4.0, 4.0, and 4.3 log10 CFU/kidney reductions for C. albicans, C. glabrata, and C. parapsilosis, respectively. The AUC/MIC was a robust predictor of efficacy (R2, 0.53 to 0.91). The 24-h PD targets were a static dose of 63.5 mg/kg, a tAUC/MIC of 500, and an fAUC/MIC of 1.0 for C. albicans; a static dose of 58.4 mg/kg, a tAUC/MIC of 315, and an fAUC/MIC of 0.63 for C. glabrata; and a static dose of 84.4 mg/kg, a tAUC/MIC of 198, and an fAUC/MIC of 0.40 for C. parapsilosis. The mean fAUC/MIC values associated with a 1-log kill endpoint against these species were 1.42, 1.26, and 0.91 for C. albicans, C. glabrata, and C. parapsilosis, respectively. The static and 1-log kill endpoints were measured relative to the burden at the start of therapy. The static and 1-log kill doses, as well as the total and free drug AUC/MIC PD targets, were not statistically different between species but were numerically lower than those observed for echinocandins. SCY-078 is a promising novel oral glucan synthase inhibitor against Candida species, and further investigation is warranted.

The Susceptibility of &lt;formula formulatype="inline"&gt; &lt;tex Notation="TeX"&gt;${\hbox {TaO}}_{\rm x}$&lt;/tex&gt;&lt;/formula&gt;-Based Memristors to High Dose Rate Ionizing Radiation and Total Ionizing Dose

This paper investigates the effects of high dose rate ionizing radiation and total ionizing dose (TID) on tantalum oxide (TaOx) memristors. Transient data were obtained during the pulsed exposures for dose rates ranging from approximately 5.0 ×107 rad(Si)/s to 4.7 ×108 rad(Si)/s and for pulse widths ranging from 50 ns to 50 μs. The cumulative dose in these tests did not appear to impact the observed dose rate response. Static dose rate upset tests were also performed at a dose rate of ~3.0 ×108 rad(Si)/s. This is the first dose rate study on any type of memristive memory technology. In addition to assessing the tolerance of TaOx memristors to high dose rate ionizing radiation, we also evaluated their susceptibility to TID. The data indicate that it is possible for the devices to switch from a high resistance off-state to a low resistance on-state in both dose rate and TID environments. The observed radiation-induced switching is dependent on the irradiation conditions and bias configuration. Furthermore, the dose rate or ionizing dose level at which a device switches resistance states varies from device to device; the enhanced susceptibility observed in some devices is still under investigation. As a result, numerical simulations aremore » used to qualitatively capture the observed transient radiation response and provide insight into the physics of the induced current/voltages.« less

Evaluation of dosimetric misrepresentations from 3D conventional planning of liver SBRT using 4D deformable dose integration.

The purpose of this study is to evaluate dosimetric errors in 3D conventional planning of stereotactic body radiotherapy (SBRT) by using a 4D deformable image registration (DIR)‐based dose‐warping and integration technique. Respiratory‐correlated 4D CT image sets with 10 phases were acquired for four consecutive patients with five liver tumors. Average intensity projection (AIP) images were used to generate 3D conventional plans of SBRT. Quasi‐4D path‐integrated dose accumulation was performed over all 10 phases using dose‐warping techniques based on DIR. This result was compared to the conventional plan in order to evaluate the appropriateness of 3D (static) dose calculations. In addition, we consider whether organ dose metrics derived from contours defined on the average intensity projection (AIP), or on a reference phase, provide the better approximation of the 4D values. The impact of using fewer (<10) phases was also explored. The AIP‐based 3D planning approach overestimated doses to targets by 1.4% to 8.7% (mean 4.2%) and underestimated dose to normal liver by up to 8% (mean −5.5%; range −2.3% to −8.0%), compared to the 4D methodology. The homogeneity of the dose distribution was overestimated when using conventional 3D calculations by up to 24%. OAR doses estimated by 3D planning were, on average, within 10% of the 4D calculations; however, differences of up to 100% were observed. Four‐dimensional dose calculation using 3 phases gave a reasonable approximation of that calculated from the full 10 phases for all patients, which is potentially useful from a workload perspective. 4D evaluation showed that conventional 3D planning on an AIP can significantly overestimate target dose (ITV and GTV+5mm), underestimate normal liver dose, and overestimate dose homogeneity. Implementing nonadaptive quasi‐4D dose calculation can highlight the potential limitation of 3D conventional SBRT planning and the resultant misrepresentations of dose in some regions affected by motion and deformation. Where the 4D approach is unavailable, contouring on the full expiration phase may yield more accurate dose calculations, most relevant in the case of the healthy liver, but the absolute dose differences are in general small for the other healthy organs. The technique has the potential to quantify under‐ and over‐dosage and improve treatment plan evaluation, retrospective plan analysis, and clinical outcome correlation.PACS numbers: 87.55.‐x, 87.55.D‐, 87.55.de, 87.55.dk, 87.55.Qr, 87.57.nj

Prospect of increasing secondary ion yields in ToF‐SIMS using water cluster primary ion beams

Low ionization yields in time of flight secondary ion mass spectrometry (ToF‐SIMS) particularly from single cells and tissues are proving to be a significant limitation in allowing this technique to reach its full potential. A number of approaches including embedding the sample in water or spraying water above sample surface has shown great prospective for increasing the ionization yield by a factor of 10 to 100 through ‘proton mediated’ reaction. Based on this hypothesis, a water cluster primary ion source has been developed in collaboration with Ionoptika Ltd to generate giant water cluster ions (H2O)n+ (n = 1−10 000) using a similar supersonic jet expansion methodology as for argon cluster beams. The ion yields of arginine, cholesterol, angiotensin II and a lipid mix have been measured under static and high ion dose conditions using (H2O)5000+, (H2O)3000+, Ar3000+ and C60+ primary ion beams at 20 keV. An enhancement in yields up to a factor of around 4 is observed under water cluster impact, in comparison with C60+ at 1 × 1011 ions/cm2 ion dose, whereas this increases by around 10–50 times at high ion dose conditions. Copyright © 2014 John Wiley &amp; Sons, Ltd.

SU‐E‐J‐81: Interplay Effect in Non‐Gated Dynamic Treatment Delivery of a Lung Phantom with Simulated Respiratory Motion

Purpose:To quantify the interplay effect in non‐gated VMAT external beam delivery using realistic, clinically relevant 3D motion in an anthropomorphic lung phantom, and to determine if adding margins is sufficient to account for motion or if gating is required in all cases.Methods:A 4D motion stage was used to move a Virtual Water (VW) lung target containing a piece of radiochromic EBT3 film in an anthropomorphic chest phantom. A five‐arc stereotactic body radiation therapy (SBRT) treatment was planned using a CT scan of the phantom in its stationary position, using planning parameters chosen to push the optimizer to achieve a highly‐modulated plan. Two scenarios were delivered using a Varian TrueBeam: the first was delivered with the phantom and target both stationary and the second was delivered with the phantom stationary but the target moving in a realistic, irregular 3D elliptical pattern. A single piece of 4×4 cm2 film was used per fraction, located in the central coronal plane of the target. Film was calibrated on a 6 MV beam with dose values from 0.20 to 20 Gy.Results:Preliminary test films were analyzed in ImageJ and MatLab software. Dose maps were calculated on a central region of interest (ROI) delineated on both the motion‐induced and stationary films. Both static and dynamic film dose maps agreed with planning values within acceptable uncertainty.Conclusion:Including a large number of arcs in a clinically realistic SBRT treatment could reduce the effect of motion interplay due to averaging. Because all clinics do not employ multiple arcs for SBRT lung treatments, it is still important to consider the effects of motion on treatment delivery. Further analysis on the treatment films, as well as a broader investigation other planning parameters, will be conducted.

SU-E-T-551: PTV Is the Worst-Case of CTV in Photon Therapy

Purpose: To examine the supposition of the static dose cloud and adequacy of the planning target volume (PTV) dose distribution as the worst-case representation of clinical target volume (CTV) dose distribution for photon therapy in head and neck (H&N) plans. Methods: Five diverse H&N plans clinically delivered at our institution were selected. Isocenter for each plan was shifted positively and negatively in the three cardinal directions by a displacement equal to the PTV expansion on the CTV (3 mm) for a total of six shifted plans per original plan. The perturbed plan dose was recalculated in Eclipse (AAA v11.0.30) using the same, fixed fluence map as the original plan. The dose distributions for all plans were exported from the treatment planning system to determine the worst-case CTV dose distributions for each nominal plan. Two worst-case distributions, cold and hot, were defined by selecting the minimum or maximum dose per voxel from all the perturbed plans. The resulting dose volume histograms (DVH) were examined to evaluate the worst-case CTV and nominal PTV dose distributions. Results: Inspection demonstrates that the CTV DVH in the nominal dose distribution is indeed bounded by the CTV DVHs in the worst-case dose distributions. Furthermore, comparison of the D95% for the worst-case (cold) CTV and nominal PTV distributions by Pearson's chi-square test shows excellent agreement for all plans. Conclusion: The assumption that the nominal dose distribution for PTV represents the worst-case dose distribution for CTV appears valid for the five plans under examination. Although the worst-case dose distributions are unphysical since the dose per voxel is chosen independently, the cold worst-case distribution serves as a lower bound for the worst-case possible CTV coverage. Minor discrepancies between the nominal PTV dose distribution and worst-case CTV dose distribution are expected since the dose cloud is not strictly static. This research was supported by the NCI through grant K25CA168984, by The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, and by the Fraternal Order of Eagles Cancer Research Fund, the Career Development Award Program at Mayo Clinic.

Impact of in vivo triazole and echinocandin combination therapy for invasive pulmonary aspergillosis: enhanced efficacy against Cyp51 mutant isolates.

Previous studies examining combination therapy for invasive pulmonary aspergillosis (IPA) have revealed conflicting results, including antagonism, indifference, and enhanced effects. The most commonly employed combination for this infection includes a mold-active triazole and echinocandin. Few studies have evaluated combination therapy from a pharmacodynamic (PD) perspective, and even fewer have examined combination therapy against both wild-type and azole-resistant Cyp51 mutant isolates. The current studies aim to fill this gap in knowledge. Four Aspergillus fumigatus isolates were utilized, including a wild-type strain, an Fks1 mutant (posaconazole susceptible and caspofungin resistant), and two Cyp51 mutants (posaconazole resistant). A neutropenic murine model of IPA was used for the treatment studies. The dosing design included monotherapy with posaconazole, monotherapy with caspofungin, and combination therapy with both. Efficacy was determined using quantitative PCR, and results were normalized to known quantities of conidia (conidial equivalents [CE]). The static dose, 1-log kill dose, and associated PD target area under the curve (AUC)/MIC ratio were determined for monotherapy and combination therapy. Monotherapy experiments revealed potent activity for posaconazole, with reductions of 3 to 4 log10 Aspergillus CE/ml with the two "low"-MIC isolates. Posaconazole alone was less effective for the two isolates with higher MICs. Caspofungin monotherapy did not produce a significant decrease in fungal burden for any strain. Combination therapy with the two antifungals did not enhance efficacy for the two posaconazole-susceptible isolates. However, the drug combination produced synergistic activity against both posaconazole-resistant isolates. Specifically, the combination resulted in a 1- to 2-log10 decline in burden that would not have been predicted based on the monotherapy results for each drug. This corresponded to a reduction in the free-drug posaconazole AUC/MIC ratio needed for stasis of up to 17-fold. The data suggest that combination therapy using a triazole and an echinocandin may be a beneficial treatment strategy for triazole-resistant isolates.