B Paliwal

High dose rate intracavitary brachytherapy for carcinoma of the cervix: the Madison system: I. Clinical and radiobiological considerations.

The decision to use five high dose rate intracavitary (HDR-ICR) insertions at weekly intervals for invasive carcinoma of the cervix treated at the University of Wisconsin Comprehensive Cancer Center (UWCCC) was made clinically. It was based on practical considerations and on previous clinical experience worldwide which showed that between 2 and 16 insertions have been used with apparently acceptable results. Although radiobiological considerations favor a large number of small doses, such a large number of HDR-ICR insertions is not clinically practical. Our strategy was to keep the biological effects of external beam and intracavitary insertions in the same ratio as used on a large series of patients treated here with low dose rate (LDR) therapy. This means keeping the same external beam treatment scheme and finding high dose rate (HDR) doses that are biologically equivalent to the previous LDR therapy, as far as possible. External beam and HDR intracavitary dose schedules for the Madison System of treating cervical carcinoma are described in detail. Because there is more repairable damage in late-reacting normal tissues, there is a bigger loss of sparing in these tissues than in tumors when changing from LDR to HDR, so total doses should be reduced more for equal late complications than for equal tumor control. The clinical decision was made to aim at equal tumor control. The possible increase in late complications has to be avoided by reducing the doses to critical normal tissues using extremely careful anatomic positioning of the HDR sources. Critical normal tissues must be kept further away from the radiation sources so that their doses are about 20% lower than with LDR geometry. This requires an extra separation of some millimeters depending on the anatomy and geometry of the individual insertion. The strategy is that the unfavourable radiobiological effects of a few large fractions must be counteracted by better physical dose distributions with HDR-ICR than with the previous LDR insertions. These good distributions are obtainable with the short exposures at HDR.

TU‐D‐AUD‐05: Comparison for Analytical Anisotropic Algorithm and Adaptive Collapse Cone Convolution Algorithm for Small Field Dosimetry

Purpose: The objective of this study is to compare the calculation accuracy of Analytical Anisotropic Algorithm (AAA) to that of Adaptive Collapse Cone Convolution (CCC) algorithm for small beam sizes where the electron disequilibrium becomes significant. Method and Materials: The comparison of CCC and AAA calculations were performed for various field sizes (2×2, 4×4, 6×6 and 10×10) at 6‐ and 10‐MV photon energies on different phantom situations (homogeneous water phantom, cork/water heterogeneous phantoms, step phantom and IMRTlung phantom). Treatment plans for open beams, MLC shaped beams and IMRT plans were created and calculated by each algorithm. Absolute dose comparisons were made based on measurements, calculations and Monte Carlo Simulations. The XV radiographic films, GAFCHROMIC_EBT radiochromic films, PTW Ion Chamber and Sun Nuclear Map checker were used for measurements. Results and Conclusions: Point dose comparison along the central axis of beams shows that in homogeneous phantom AAA predicts dose within 2%, which is compatible to CCC. For the heterogeneous phantom with vertical density gradient, AAA predicts an up to 5% difference and compared to CCC with less than 2.5% difference. Depth Dose curves also showed that AAA overestimates the dose after passing through low density region. But inside the low density region, AAA gives a compatible prediction to CCC for very small fields. For those points far from heterogeneity, AAA results show a relatively good estimation. Profiles at different depths in the phantoms with density gradient along horizontal direction show that AAA does not model lateral scatter adequately which leads to discrepancies of up to ± 7% in the region of ±1cm lateral from the heterogeneous interface, compared to less than 2% for CCC. Planar dose comparison for IMRT plans shows AAA calculated dose fluence matches with film measured data.

TU‐C‐J‐6B‐03: Deformable Fusion of 4D PET Images

Purpose: PET images are useful in defining treatment targets. Removing distortion from respiratory motion in the PET images is of importance for gated or 4D radiation treatments. We developed a deformable fusion method to sum up the PET images at different phases. The motion-blurring-free PET images are obtained without the sacrifice of signal to noise ratio (SNR) or increase of scanning time. Method and Materials: A GE Discovery CT/PET scanner was interfaced with Varians RPM breathing tracking system. 4D CT and 4D PET images were correlated according to the breathing phases. Full exhalation phase was used as the planning phase. Deformable image registrations of the 4D CT images yielded the displacement maps of the lungs relative to the planning phase. PET images at each breathing phase were then warped into the planning phase using the displacement maps. Motion-blurring-free PET images were obtained by summing the warped PET images. Results: Gated PET images at each individual phase are very noisy. The uncertainty from intensity fluctuations compromises the motion reduction by gating the scan. PET images are too fuzzy to be directly used in elastic registration. Instead, we registered the 4D CT images. With regular patient breathing patterns, 4D CT images correlate with 4D PET images. Consequently, the displacement maps from registration of the 4D CT images can be used in warping the 4D PET. Image warping removed the motion distortion in the PET images. The summed images have reduced motion blurring and the same SNR as that of non-gated PET images. Conclusion: Deformable fusion of 4D PET images reduce the motion distortion in PET image and retain the SNR without increasing data acquisition time. The resultant PET images can be used in more accurate target definition in gated or 4D radiation treatments.

SU‐EE‐A3‐05: Evaluation of Kilo‐Voltage Cone Beam CT Image Quality in Context to Dose Re‐Computation

Purpose: The purpose of this study was to evaluate volumetric kV Cone Beam CT(CBCT)image quality at different scan parameter settings in context to treatment planning tolerances. Method and Materials: Both large and small density phantoms with eight density inserts were scanned by GE LS CT/PET system, as well as the Varians OBITM system in half fan and full fan scanning modes. Scans for CBCTimages were performed at different tube currents (20‐, 40‐ and 80‐mA) and source‐imager distance (SID) (150cm and 160cm) after prior calibration of each mode. Deviation of the Hounsfield Unit (HU) values at different settings compared to conventional kV CTimages were obtained for further evaluation. We also adjusted the CT number in CTimages to simulate CBCT artifacts that was not produced by our experiments, and to see how much degradation of image would violate dosimetric feasibility of CBCT based treatment planning. Treatment plans for single beam or multiple beams were calculated based on CT,CBCT and modified CTimages for various phantoms geometries and patients. Results and Conclusions: Results show that the HU for different anatomies in the body have different amount of change for different scan parameters settings (including current, SID and fan angle used) for CBCTimage acquisition. Larger variations in HU appeared in lung and dense bone regions, compared to those with HU closer to tissue. Maximum variations in HU were found in the images with data truncation. Dose profiles, dose volume histograms, isodose distributions and Gamma values of CBCT based plan with images scanned at full fan mode agree relatively well with CT based plan. Larger dose discrepancy appears in lung or dense bone region. Results from the CT‐modified images based plans show that the dosimetric error becomes significant as the HU variation goes beyond 50.

SU-FF-T-448: Validation of a New Photon Dose Calculation Model-Analytical Anisotropic Algorithm

Purpose: To validate a new photon dose calculation model Analytical Anisotropic Algorithm (AAA) on Eclipse™ treatment planning system (TPS). Comparison of AAA dose calculation was performed with measurements and other two conventional algorithms, Pencil Beam Convolution (PBC) algorithm on Eclipse™ and Collapsed Cone Convolution/Superposition (CCC) algorithm on Pinnacle3.0 TPS. Method and Materials: Four phantoms were CT scanned and the image set was imported into both TPS for dose computation and analysis. The four phantoms were: 1) homogenous tissue equivalent phantom, 2) tissue equivalent phantom with infinite lung heterogeneity, 3) tissue equivalent phantom with finite lung, 4) IMRT dose verification phantom. Measurements were made by exposing the phantom using Varian Linac. Point measurement and film measurements were compared with calculated results from the three algorithms. Dose responses for high and low energy photon beams were investigated for several different depths and PDD curves were compared in the phantom for various field sizes. The IMRT plans were generated by both TPS and were performed on the IMRT phantom to compare fluence maps. Results: AAA dose prediction fits the film measurements well except that there is up to ±6% discrepancy for dose profile perpendicular to the interface of tissue and lung. Point measurements support the AAA algorithm calculations. AAA also accurately predicts the decrease in PDD curves due to the lung inhomogeneity for 6MV energy. For the high energy photon beam and very small field size (2cm*2cm) in lung region, AAA prediction is up to 8% lower than the measurements. Conclusion: AAA algorithm accounts for attenuation corrections and electron transport, and models the deposited dose in the lung with greater accuracy than PBC. It is also faster than CCC algorithm. AAA algorithm can not accurately model the lateral scattering in tissue heterogeneity, but it can still give a reasonably close (within ±6%) prediction.

SU‐FF‐J‐42: Cone Beam CT Based Treatment Planning

Purpose: To evaluate treatment planning based on cone beam CT(CBCT) using latest software on a LINAC 21IX CBCTimaging system. Method and Materials: An anthropomorphic chest phantom having bone, soft tissue, and lung components was used to create and evaluate treatment plans based on conventional CT and CBCTimages. Conventional CTimages of 2.5 mm slice thickness were taken with a GE discovery LS CT/PET system. CBCTimages slices were also reconstructed from flat panel system on a Varian LINAC 21IX. Eclipse treatment planning system was used to compare treatment plans from the conventional CT and CBCTimages. The AAA algorithm was used in the treatment planning system for inhomogeneity correction. Regions of interest around the bone, soft tissue, and lung in both CT and CBCTimages using identical HU threshold values were drawn. Identical targets located in the lung were used in each treatment plan. Analysis of the treatment plans was performed by comparison of geometrical dimensions, total volumes and dose volume histograms of the target and regions of interest. Results: Geometric comparison of actual external spatial dimensions and others in lung and bone were found to be within 1 mm. Volumetric comparison of the regions of interest resulted in a 2.8% difference of the vertebrae, 3.3% of the right lung, and 3.7% of the total external volume. Dosimetric results show similar dose distributions. Dose volume histograms are also comparable. Conclusion: Results demonstrate that treatment planning based on CBCT is feasible. Plans created from CBCTimages are comparable to plans created with conventional CT systems. Conflict of Interest: Partly funded by Prostate Cancer Foundation grant UW 133‐HR30.

On the use of virtual simulation in radiotherapy of the intact breast.

In this paper a method of breast cancer treatment planning using virtual simulation implemented at the Department of Human Oncology at the University of Wisconsin is described. All patients in this procedure are placed in a custom vacuum mold in treatment position with both arms up to avoid collision with the CT scanner aperture. For all patients a CT scan of 5‐mm‐slice thickness is acquired. The ipsilateral and contralateral breast, the ipsilateral lung and the heart are delineated and a three‐dimensional plan is generated that tries to minimize the dose to the ipsilateral lung and heart while ensuring adequate coverage of the affected breast. Digitally reconstructed radiographs are used to verify the patient setup on the treatment machine.

TH‐A‐220‐06: Four‐Dimensional MRI/CT Based Auto‐Adaptive Segmentation for Real‐Time Radiotherapy in Lung Cancer Treatment

Purpose: To enable real‐time magnetic resonance (MR)/computer tomography(CT)image‐guidedradiotherapy (IGRT) and to reduce treatment planning durations in the radiotherapy of lungcancer through the design and implementation of computationally efficient four‐dimensional (4D) MR/CT based automated segmentation algorithms. Methods: Hyperpolarized helium‐3 (HP3He) and proton‐density 4DMRI lung data was acquired for six subjects. Thoracic 4DCT data often subjects with lungcancer was also acquired. Automated segmentation was performed using a novel Morphological Processing and Successive Localization (MPSL) approach. Three different MPSL segmentation algorithms were developed to segment the regions of tumor, body and lung respectively. MPSL segmentation: A mask that includes the intensity range of the region‐of‐interest was generated. Then morphological processing (and/or reconstruction) was performed to separate the target volume(s) from other regions. Then the different connected regions were labeled using the union‐find algorithm and their areas/volumes were calculated. A limit on the maximum/minimum possible area/volume of the target volume was used as a filter to segment the target volume. Morphological processing/reconstruction were performed again to create the final contours. Results: MPSL was shown to successfully segment the regions‐of‐interest (tumors,lung and body) from the images with both high and low signal‐to‐ noise ratio. With the use of 3D processing and successive localization MPSL was shown to separately classify tumor and diaphragm (that may appear within the 2D contours of the lung). MPSL segmentation was compared with manual segmentation. Average computational time for achieving automated lung segmentation using MPSL on one phase volume (128×128×128) of 4D HP3He MR data was 0.5s. For proton‐density 4DMRI data, the average time for automated segmentation of body and lung on one phase volume (128×128×128) was 2s. Conclusions: With the computation speed of the order of seconds for achieving automated segmentation, MPSL has realistic potential for application in real‐time image‐guidance for adaptive radiotherapy.

Implementing Hybrid CT/PET: The University of Wisconsin Experience

Oncology Issues November/December 2006 In Brief In late 2001, the University of Wisconsin’s Radiation Oncology Department installed one of the first radiotherapy-dedicated hybrid CT/PET scanners in the country. This scanner is shared between Radiation Oncology and Nuclear Medicine. In the last five years, the technology has proven valuable for diagnostic purposes and radiotherapy treatment planning. While the CT/PET acquisition benefited our hospital and patients, implementation of the new technology was not a seamless process. The adoption of the hybrid CT/PET posed challenges to our institution and, in particular, to the Radiation Oncology and Nuclear Medicine Departments that jointly share the equipment (see box, page 27). Now, a few years after its acquisition, the CT/PET scanner plays a vital role in the functioning of both departments. This new technology has significantly altered the way we design radiation treatment plans for our cancer patients.

TH-CD-202-11: Implications for Online Adaptive and Non-Adaptive Radiotherapy of Gastic and Gastroesophageal Junction Cancers Using MRI-Guided Radiotherapy

PURPOSE Radiotherapy for gastric and gastroesophageal junction (GEJ) tumors commonly requires large margins due to deformation, motion and variable changes of the stomach anatomy, at the risk of increased normal tissue toxicities. This work quantifies the interfraction variation of stomach deformation from daily MRI-guided radiotherapy to allow for a more targeted determination of margin expansion in the treatment of gastric and GEJ tumors. METHODS Five patients treated for gastric (n=3) and gastroesophageal junction (n=2) cancers with conventionally fractionated radiotherapy underwent daily MR imaging on a clinical MR-IGRT system. Treatment planning and contours were performed based on the MR simulation. The stomach was re-contoured on each daily volumetric setup MR. Dice similarity coefficients (DSC) of the daily stomach were computed to evaluate the stomach interfraction deformation. To evaluate the stomach margin, the maximum Hausdorff distance (HD) between the initial and fractional stomach surface was measured for each fraction. The margin expansion, needed to encompass all fractions, was evaluated from the union of all fractional stomachs. RESULTS In total, 94 fractions with daily stomach contours were evaluated. For the interfraction stomach differences, the average DSC was 0.67±0.1 for gastric and 0.62±0.1 for GEJ cases. The maximum HD of each fraction was 3.5±2.0cm (n=94) with mean HD of 0.8±0.4cm (across all surface voxels for all fractions). The margin expansion required to encompass all individual fractions (averaged across 5 patients) was 1.4 cm(superior), 2.3 cm(inferior), 2.5 cm(right), 3.2 cm(left), 3.7 cm(anterior), 3.4 cm(posterior). Maximum observed difference for margin expansion was 8.7cm(posterior) among one patient. CONCLUSION We observed a notable interfractional change in daily stomach shape (i.e., mean DSC of 0.67, p<0.0001) in both gastric and GEJ patients, for which adaptive radiotherapy is indicated. A minimum PTV margin of 3 cm is indicated to account for interfraction stomach changes when adaptive radiotherapy is not available. M. Bassetti: Travel funding from ViewRay, Inc.