J Cates

Anti-VEGF antibodies mitigate the development of radiation necrosis in mouse brain

Purpose: To quantify the effectiveness of anti-VEGF antibodies (bevacizumab and B20-4.1.1) as mitigators of radiation-induced, central nervous system (brain) necrosis in a mouse model. Experimental Design: Cohorts of mice were irradiated with single-fraction 50- or 60-Gy doses of radiation targeted to the left hemisphere (brain) using the Leksell Perfexion Gamma Knife. The onset and progression of radiation necrosis were monitored longitudinally by in vivo, small-animal MRI, beginning 4 weeks after irradiation. MRI-derived necrotic volumes for antibody (Ab)-treated and untreated mice were compared. MRI results were supported by correlative histology. Results: Hematoxylin and eosin–stained sections of brains from irradiated, non–Ab-treated mice confirmed profound tissue damage, including regions of fibrinoid vascular necrosis, vascular telangiectasia, hemorrhage, loss of neurons, and edema. Treatment with the murine anti-VEGF antibody B20-4.1.1 mitigated radiation-induced changes in an extraordinary, highly statistically significant manner. The development of radiation necrosis in mice under treatment with bevacizumab (a humanized anti-VEGF antibody) was intermediate between that for B20-4.1.1–treated and non–Ab-treated animals. MRI findings were validated by histologic assessment, which confirmed that anti-VEGF antibody treatment dramatically reduced late-onset necrosis in irradiated brain. Conclusions: The single-hemispheric irradiation mouse model, with longitudinal MRI monitoring, provides a powerful platform for studying the onset and progression of radiation necrosis and for developing and testing new therapies. The observation that anti-VEGF antibodies are effective mitigants of necrosis in our mouse model will enable a wide variety of studies aimed at dose optimization and timing and mechanism of action with direct relevance to ongoing clinical trials of bevacizumab as a treatment for radiation necrosis. Clin Cancer Res; 20(10); 2695–702. ©2014 AACR.

Toward Distinguishing Recurrent Tumor From Radiation Necrosis: DWI and MTC in a Gamma Knife–Irradiated Mouse Glioma Model

PURPOSE Accurate noninvasive diagnosis is vital for effective treatment planning. Presently, standard anatomical magnetic resonance imaging (MRI) is incapable of differentiating recurring tumor from delayed radiation injury, as both lesions are hyperintense in both postcontrast T1- and T2-weighted images. Further studies are therefore necessary to identify an MRI paradigm that can differentially diagnose these pathologies. Mouse glioma and radiation injury models provide a powerful platform for this purpose. METHODS AND MATERIALS Two MRI contrasts that are widely used in the clinic were chosen for application to a glioma/radiation-injury model: diffusion weighted imaging, from which the apparent diffusion coefficient (ADC) is obtained, and magnetization transfer contrast, from which the magnetization transfer ratio (MTR) is obtained. These metrics were evaluated longitudinally, first in each lesion type alone-glioma versus irradiation - and then in a combined irradiated glioma model. RESULTS MTR was found to be consistently decreased in all lesions compared to nonlesion brain tissue (contralateral hemisphere), with limited specificity between lesion types. In contrast, ADC, though less sensitive to the presence of pathology, was increased in radiation injury and decreased in tumors. In the irradiated glioma model, ADC also increased immediately after irradiation, but decreased as the tumor regrew. CONCLUSIONS ADC is a better metric than MTR for differentiating glioma from radiation injury. However, MTR was more sensitive to both tumor and radiation injury than ADC, suggesting a possible role in detecting lesions that do not enhance strongly on T1-weighted images.

A Gamma-Knife-Enabled Mouse Model of Cerebral Single-Hemisphere Delayed Radiation Necrosis

Purpose To develop a Gamma Knife-based mouse model of late time-to-onset, cerebral radiation necrosis (RN) with serial evaluation by magnetic resonance imaging (MRI) and histology. Methods and Materials Mice were irradiated with the Leksell Gamma Knife® (GK) PerfexionTM (Elekta AB; Stockholm, Sweden) with total single-hemispheric radiation doses (TRD) of 45- to 60-Gy, delivered in one to three fractions. RN was measured using T2-weighted MR images, while confirmation of tissue damage was assessed histologically by hematoxylin & eosin, trichrome, and PTAH staining. Results MRI measurements demonstrate that TRD is a more important determinant of both time-to-onset and progression of RN than fractionation. The development of RN is significantly slower in mice irradiated with 45-Gy than 50- or 60-Gy, where RN development is similar. Irradiated mouse brains demonstrate all of the pathologic features observed clinically in patients with confirmed RN. A semi-quantitative (0 to 3) histologic grading system, capturing both the extent and severity of injury, is described and illustrated. Tissue damage, as assessed by a histologic score, correlates well with total necrotic volume measured by MRI (correlation coefficient = 0.948, with p<0.0001), and with post-irradiation time (correlation coefficient = 0.508, with p<0.0001). Conclusions Following GK irradiation, mice develop late time-to-onset cerebral RN histology mirroring clinical observations. MR imaging provides reliable quantification of the necrotic volume that correlates well with histologic score. This mouse model of RN will provide a platform for mechanism of action studies, the identification of imaging biomarkers of RN, and the development of clinical studies for improved mitigation and neuroprotection.

A GSK-3β Inhibitor Protects Against Radiation Necrosis in Mouse Brain

PURPOSE To quantify the effectiveness of SB415286, a specific inhibitor of GSK-3β, as a neuroprotectant against radiation-induced central nervous system (brain) necrosis in a mouse model. METHODS AND MATERIALS Cohorts of mice were treated with SB415286 or dimethyl sulfoxide (DMSO) prior to irradiation with a single 45-Gy fraction targeted to the left hemisphere (brain) using a gamma knife machine. The onset and progression of radiation necrosis (RN) were monitored longitudinally by noninvasive in vivo small-animal magnetic resonance imaging (MRI) beginning 13 weeks postirradiation. MRI-derived necrotic volumes for SB415286- and DMSO-treated mice were compared. MRI results were supported by correlative histology. RESULTS Mice treated with SB415286 showed significant protection from radiation-induced necrosis, as determined by in vivo MRI with histologic validation. MRI-derived necrotic volumes were significantly smaller at all postirradiation time points in SB415286-treated animals. Although the irradiated hemispheres of the DMSO-treated mice demonstrated many of the classic histologic features of RN, including fibrinoid vascular necrosis, vascular telangiectasia, hemorrhage, and tissue loss, the irradiated hemispheres of the SB415286-treated mice consistently showed only minimal tissue damage. These studies confirmed that treatment with a GSK-3β inhibitor dramatically reduced delayed time-to-onset necrosis in irradiated brain. CONCLUSIONS The unilateral cerebral hemispheric stereotactic radiation surgery mouse model in concert with longitudinal MRI monitoring provided a powerful platform for studying the onset and progression of RN and for developing and testing new neuroprotectants. Effectiveness of SB415286 as a neuroprotectant against necrosis motivates potential clinical trials of it or other GSK-3β inhibitors.

SU‐E‐T‐371: Evaluating the Convolution Algorithm of a Commercially Available Radiosurgery Irradiator Using a Novel Phantom

Purpose: The purpose of this study was to develop and use a novel phantom to evaluate the accuracy and usefulness of the Leskell Gamma Plan convolution-based dose calculation algorithm compared with the current TMR10 algorithm. Methods: A novel phantom was designed to fit the Leskell Gamma Knife G Frame which could accommodate various materials in the form of one inch diameter, cylindrical plugs. The plugs were split axially to allow EBT2 film placement. Film measurements were made during two experiments. The first utilized plans generated on a homogeneous acrylic phantom setup using the TMR10 algorithm, with various materials inserted into the phantom during film irradiation to assess the effect on delivered dose due to unplanned heterogeneities upstream in the beam path. The second experiment utilized plans made on CT scans of different heterogeneous setups, with one plan using the TMR10 dose calculation algorithm and the second using the convolution-based algorithm. Materials used to introduce heterogeneities included air, LDPE, polystyrene, Delrin, Teflon, and aluminum. Results: The data shows that, as would be expected, having heterogeneities in the beam path does induce dose delivery error when using the TMR10 algorithm, with the largest errors being due to the heterogeneities with electron densities most different from that of water, i.e. air, Teflon, and aluminum. Additionally, the Convolution algorithm did account for the heterogeneous material and provided a more accurate predicted dose, in extreme cases up to a 7–12% improvement over the TMR10 algorithm. The convolution algorithm expected dose was accurate to within 3% in all cases. Conclusion: This study proves that the convolution algorithm is an improvement over the TMR10 algorithm when heterogeneities are present. More work is needed to determine what the heterogeneity size/volume limits are where this improvement exists, and in what clinical and/or research cases this would be relevant.

SU‐E‐T‐430: Planning and Dosimetric Comparison of the Gamma Knife Convolution and TMR 10 Algorithms

PURPOSE To compare the dose distributions for identical treatment plans calculated by the Gamma Knife TMR 10 and convolution algorithms and measured with film dosimetry. METHODS An anthropomorphic head phantom was CT imaged with EBT2 film placed between each of seven axial sections. The resulting data set was used to plan three 16mm collimated targets on the Gamma Knife Perfexion, with each target centered on a film plane. Target 1 was placed within a homogeneous region while Targets 2 and 3 were placed in heterogeneous regions, i.e. tissue-air and bone-tissue interfaces, respectively. Plans using the same targets were made using both the TMR 10 and convolution algorithms. The prescription was delivered to the phantom using the TMR 10 treatment plans after which the convolution treatment plans were adjusted to Result in identical treatment times, thus ensuring identical dose delivery. Film dosimetry was done to determine actual dose delivered at target center and was compared to the predicted dose for each algorithm. RESULTS While there was strong correlation between both algorithms, the convolution algorithm predicted a higher delivered maximum dose than TMR 10, up to 2.5% higher in homogeneous tissue and up to 7% near an air cavity. Film dosimetry results were consistent with the convolution algorithm predictions, with an error of less than three percent. CONCLUSION The Gamma Knife convolution algorithm predicts delivered dose to a clinically acceptable level, which was confirmed by film dosimetry. However, film in an anthropomorphic head phantom may not be adequate to measure the most significant differences between the two algorithms. Precise stereotactic treatments will require precise dosimetry, and a phantom developed specifically with Gamma Knife geometry in mind may be necessary to fully characterize the dosimetry at anatomy interfaces.

SU‐GG‐T‐338: Accuracy of Superficial Dose Calculation for Breast Cancer Treatments on Tomotherapy

Purpose: To evaluate the effect of breathing motion and setup error on the accuracy of treatment planningsurface dose calculation for breast cancertreatments on helical Tomotherapy. Method and Materials: In‐vivo dosimetry with MOSFETdetectors was performed on a cohort of patients treated for breast cancer on helical Tomotherapy. The detectors were placed under the 0.5‐cm tissue‐equivalent bolus used for patient treatments. The pre‐treatment MVCT images were used to localize the MOSFETdetectors. Tomotherapys Planned Adaptive software was used to compare the measurements against both the planned surface doses at the locations of the dosimeters as well as the recalculated doses based on the MVCT scan. This allowed for evaluation of the combined impact of breathing and setup error on the surface dose contribution, and the quantification of dosimetric accuracy of the Tomotherapy treatment planning system for breast cancer patients. Results: The differences between dose values at the locations of the dosimeters from the plan and those calculated from the MVCT image were on average within 1% of each other. The average dosimetric differences between measured and calculated doses were 7.8 and 8 percent for the planned and adaptive calculated doses, respectively. Overall, the treatment planning system overestimated the dose at the skin/bolus interface. Conclusion: The treatment planning system was previously shown to overestimate dose at a 5‐mm depth by about 4%. The possible setup error is taken into account by the adaptive software since it recalculates the dose distribution based on the MVCT image associated with the treatment for which the measurement was made. Since the setup error was shown to be within 1%, it is therefore estimated that the dosimetric consequence of breathing motion may be as high as 3%. Conflict of Interest: This work was partially supported by a grant from Tomotherapy, Inc.

SU‐GG‐T‐27: Use of Tomotherapy Exit Detector Data to Detect Changes in Patient Anatomy

Purpose: To demonstrate the use of TomoTherapys exit detector data to identify changes in patient anatomy for GYN radiation therapy.Methods and Materials: A pelvic anthropomorphic phantom with six layers of 0.5 cm bolus was used to simulate a patient with excess body fat in the lower abdomen and pelvis. The phantom was CT‐simulated, and a GYN helical IMRTtreatment plan was created using TomoTherapy treatment planning system. The contours, treatment plan quality, and fractionation were consistent with our department protocols. Two fractions were delivered to the phantom with six layers of bolus. Subsequent fractions following the removal of 1 layer of 0.5 cm bolus to simulate patient weight loss were treated until all layers of bolus were removed. Following each fraction, the exit detector data was collected using TomoTherapy TQA software and analyzed in MATLAB. MVCT scans were for the length of the target volume were obtained following the removal of 1.5 cm and 3.0 cm layers of bolus, and TomoTherapy Adaptive software was used to calculate modified dose distributions and DVHs on the ‘thinner’ phantom. Results: The exit detector data for each fraction is a sinogram with a width of 640 (the number of exit detectors) and a length of 51 × RG, where RG is the number of gantry rotations required by the treatment plan. Analysis of sinogram differences and ratios (relative to the first fraction with all six bolus layers in place) yields 2‐D plots useful for qualitative indications of weight loss. Conclusions: Anatomical changes are observed following simple analysis of TomoTherapy exit detector data. Simulated weight loss in a phantom suggests these data will be useful for monitoring anatomical changes in patients. Minor changes have been observed for one GYN patient thus far, and we have begun collecting data for more patients.

SU‐GG‐T‐224: Quality Assurance of Tomotherapy BreastTreatments Using Exit Detector Data: A Feasibility Study

Purpose: Purpose of this study is to explore the feasibility of utilizing Tomotherapys exit‐detector‐data for identifying setup‐errors in treatments of breast‐cancer patients. Material and methods: Tomotherapy treatment plan mimicing breast treatment, generated on an anthropomorphic phantom, was used in this study. Thorax phantom was irradiated with the planned delivery sinogram after registering MVCT with kVCT. TomoTherapys exit‐detector‐data‐sinograms (EDDSs) were downloaded and ported into MatLab for further analysis. The phantom was then shifted by known offsets in x‐,y‐,z directions and collected the EDDSs after each irradiation. EDDSs from repeated irradiations were used to characterize the noise in the detector‐signals. Average EDDS of the unshifted irradiations was subtracted from the individual EDDSs of the shifted simulations. Resulting difference EDDSs were analyzed to determine the extent of sinograms changes in frequency and magnitude. EDDSs from five clinically treated breast patients were downloaded after completion of their daily treatments and analyzed the data. Results and Discussion Difference EDDSs show that sinogram differences in frequency and magnitude were increased with increase in shifts. Linear regression analysis revealed a good correlation with regression coefficients >0.97. The features of the difference EDDSs are quite predictable; the difference EDDSs were positive for +X‐shifts due to missing tissue; negative for +Y‐shifts near sloping portion of the chest‐wall and also for +Z‐shifts due to increase in attenuation. Different histogram plots of the shifted simulations show that the maximum deviations were up to ±60% and ±250% for shifts of 5mm and 20mm, respectively. Maximum deviation in the EDDSs of five clinically treated breast patients were within ±50% suggesting a ∼5mm residual uncertainty in the patient setup. Conclusion: Preliminary investigation of exit detector sinograms data suggests that EDDSs are useful to identify the inter‐fraction and intra‐fraction setup errors and has great potential for in‐vivo QA of the patient treatments.