2009 IEEE Nuclear Science Symposium Conference Record
M13-237
Evaluation of Radiotherapy Treatment Planning with Mega-Voltage Cone Beam CT Hannah. Mary Thomas. T, Devakumar Devadhas, S. Purnima, S. Balukrishna, B. Paul Ravindran
Abstract–The prospective use for MV CT for patient treatment planning are for consecutive phase plans in 3D conformal and intensity modulated radiotherapy, patients with metal implants, adaptive radiation therapy and single fraction palliative treatment. This study is to validate the authors’ previous work on MV cone beam CT (MV CBCT) images reconstructed with bespoke FDK algorithm based 3D reconstruction software for treatment planning. MV CBCT images were fused with planning CT images to include complimentary data which help elucidate visualization and segmentation of different anatomical structures for better treatment planning. The landmark based manual registration of planning CT and MV CBCT images was done. The registration was validated using quantitative and qualitative measures. A relative dose calculation was done where the whole brain was delineated as the target volume. Forward planning with parallel oppose fields with micro multi-leaf collimator shaping and 6 MV beam was performed on both kV and MV CBCT images. Dose volume histograms and volume comparisons of the target were done. The volumes of the target were measured on kV and MV CBCT .The relative dose for the points in the target volume in MV CBCT was within 3% difference from dose calculated with planning CT. The results of this study show that MV CBCT images could be effectively used for planning in a commercial treatment planning system, if the necessary corrections mentioned are incorporated.
I. INTRODUCTION
I
MAGING is ubiquitous in all stages of radiotherapy treatment process. Recent advances in diagnosis, planning, therapy and tumor targeting and after treatment monitoring of patients’ response to treatment rely heavily on its development. Treatment planning for conformal radiotherapy requires accurate delineation of tumor volumes and surrounding healthy tissues. Even a minimal shift in volumes and overlap regions can result in different optimized plans. One of the few approaches available to obtain CT images in the treatment position include megavoltage cone beam CT (MV CBCT)[1]. The idea of using the treatment beam for imaging and extending it to treatment planning is appealing since it requires no additional hardware and the image Manuscript received November 13, 2009. Hannah. Mary Thomas is with Department of Bioengineering, Christian Medical College, Vellore, Tamilnadu, India. Devakumar Devadhas is with Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA, on leave from Department of Nuclear Medicine, Christian Medical College, Vellore, Tamilnadu, India. S. Purnima is with Department of Radiotherapy, Christian Medical College, Vellore, Tamilnadu, India. S. Balukrishna is with Department of Radiotherapy, Christian Medical College, Vellore, Tamilnadu, India. B. Paul Ravindran is with Department of Radiotherapy, Christian Medical College, Vellore, Tamilnadu, India(email:
[email protected]).
9781-4244-3962-1/09/$25.00 ©2009 IEEE
obtained is in geometric coincidence with the treatment. The rationale for MV CT for patient treatment planning are prospective use in treatment planning for consecutive phases in 3D conformal and intensity modulated radiotherapy, patients with metal implants[2], adaptive radiation therapy[3] and single fraction palliative treatment,[4] this modality has potential for further growth. This study is to validate the authors’ previous work on MV cone beam CT (MV CBCT) images reconstructed with bespoke FDK algorithm based 3D reconstruction software for treatment planning[5]. The motivation for registering the image is to create displays that contain relevant features from each modality. It also provides complimentary data which help elucidate visualization and segmentation of different anatomical structures for better tumor volume delineation. II. METHODS AND MATERIALS A. Data acquisition In this study, planning CT scans were acquired using Siemens SOMATOM Emotion diagnostic CT scanner (Siemens Medical Solutions USA, Inc.). Alderson Rando head phantom (Radiology Support Device, Long Beach, USA) was used for imaging. A 6 MV beam from Primus Linear Accelerator (Siemens, USA) with a-Si flat panel EPID (Optivue 500 Siemens, Germany) mounted on a gantry 150 cm from the source was used for the acquisition of transmission images. Image registrations of planning CT and MV cone beam CT were done using BrainScan v. 5.3 (BrainLAB, Germany) treatment planning system. Treatment plans were generated on the external beam software PLATO SunRise (Nucletron, Holland). B. Megavoltage cone beam CT imaging The projection images were acquired based on half scan cone beam technique from the EPID system of the linear accelerator and reconstructed using software that was developed based on the FDK algorithm. Since the treatment planning system calculated the HU from the pixel values of the images and not from the DICOM header of the CT images, the pixel values in the MV CBCT images were rescaled to represent a pixel value equivalent to that of the planning CT images. This ensured the use of the MV CBCT images with the commercial treatment planning system (TPS). The rescaling was done by plotting the pixel values MV CBCT images of the calibration phantom against the corresponding pixel values of planning CT for locations of known densities. After rescaling, the images were converted to DICOM format
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with the header bearing the rescale slope andd intercept as that of the planning CT images which is 1 and -11024 respectively. A calibration phantom was designed andd developed for verification of HU and geometric accuracy. The CT number was also calculated by the standard method ussing the equation HU = 1000 (μmaterial μwater)/μwater
(1)
where μwater is the linear attenuation coeffficient of water. μwater was observed after the initial rreconstruction of projections from calibration phantom and uused in the above equation to get the CT number for each pixel location. The CT numbers calculated with both methods were ccomparable to the CT number of planning CT. C. Validation of image fusion and registratioon Image fusion and registration techniquess are used in all stages of radiotherapy treatment process. Im mage data fusion from various modalities help map informatiion derived from one study to another. To fully realize thee benefits of the information available from the different imaaging modalities, data they provide must be mapped to a ssingle coordinate system, typically that of the treatment planninng system. This is image registration. Once they are all linkeed to a common coordinate system, data can be transferred aand integrated to construct a more complete and accurate reprresentation of the patient. This is data fusion.[6] The landmark based manual registration off planning CT and MVCBCT images was done in BrainScan trreatment planning software. Before clinical use of the fused daatasets, validation of the registration and fusion were done usingg quantitative and qualitative measures. Bony landmarks that weere clearly visible on both MV CBCT and planning CT were delineated. They were the dens, the maxillary antrum and thhe mandible. Soft tissue could not be clearly visualized on MV CBCT hence not used for structure delineation. The quantitative measures were (i) to define a set of landmarks for corresponding anatomical positions on both datasets and compute distance between acctual location of points defined in planning CT and the resullting transformed location of points from the planning CT. (iii) the volumes of the structures delineated on both datasets weree compared. Qualitative measures were visualization techniques that help evaluate results based on data mapping aand fusion display features. (i) A spyglass tool was run over thee overlaid dataset to cross verify the perfection of the fusion. This helps to uncover even the small areas of missed regisstration (Fig 1 a). (ii) The checkerboard function splits the ddisplay screen to show quadrants of both datasets at same tim me (Fig 1 b). (iii) Outlines of anatomical structures delineatedd were displayed one over the other. The agreement of the planning CT based outlines at different levels and planes withh the MV CBCT images demonstrate the accuracy of registraation (Fig 2). The delineation was done by the same oncologist for all structures. This was to avoid intra-observer variability.
D. Dose calculation The whole brain was delineated as the target volume and ose fields with micro multiforward planning with parallel oppo leaf collimator shaping and 6 MV V beam was performed on both planning CT and MV CBCT T images. Six points were identified within the target volume on both datasets. Relative me histograms and volume doses were calculated. Dose volum comparisons of the structures were done. d
III. RESULTS AND DISCUSSION D The planning CT and MV CBCT T images were overlaid and verified with checker board and sp py glass controls and was found to be matching. (Fig 1)
Fig 1: Visual verification using (a) spy glass tool t (b) checkerboard control
Fig 2: Outlines of the structures delineated on both datasets and overlaid on MV CBCT image. (Pink is planning CT vollume and green is the MV CBCT volume)
The volumes of the structures delineated d for registration were compared and tabulated (table 1). A variation of about 32 he poor image contrast and % was noted. This is attributed to th resolution in the MV CBCT imag ges and thus the error in delineation of structures.
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TABLE 1.
Relative Volume (cc) kV MV 0.83 0.56 11.26 7.89 10.34 12.37 26.52 19.54
Structures Dens Lt maxilla Rt Maxilla Rt Hemimandible
% Difference 32.5 29.9 -19.6 26.3
The volumes of the target for dose calculation were measured on planning CT and MV CBCT as 940.9 cc and 1020 cc respectively. The relative doses for the points in the target volume in MV CBCT were within 3% difference from the dose calculated with planning CT (table 1). TABLE 2.
Points 1 2 3 4 5 6
Relative dose kV
MV
101.9 94.6 99.6 93 93.4 99.9
102.6 97.2 102.5 95.5 95.5 102.1
Difference -0.7 -2.6 -2.9 -2.5 -2.1 -2.2
IV. CONCLUSION A variation in structure volume delineation is noted due to poor image contrast and resolution. With further experiments if the variation is found to be consistent, an additional margin could be included to ensure that the target is well within the region to be irradiated and is comparable to the volumes delineated using planning CT. The relative doses on MV CBCT plan were found to be within acceptable limits and comparable to doses calculated using planning CT. The results of this study show that MV CBCT images could be effectively used for planning in a commercial treatment planning system if the necessary corrections mentioned are incorporated. V. REFERENCES [1]
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1. Pouliot, J., Megavoltage imaging, megavoltage cone beam CT and dose-guided radiation therapy. Front. Radiat. Ther. Oncol., 2007. 40: p. 132-42. 2. Aubin, M., et al., The use of megavoltage cone-beam CT to complement CT for target definition in pelvic radiotherapy in the presence of hip replacement. Br. J. Radiol., 2006. 79(947): p. 918-21. 3. Yan, D., et al., Computed tomography guided management of interfractional patient variation. Semin. Radiat. Oncol., 2005. 15(3): p. 168-79. 4. Kachnic, L. and L. Berk, Palliative single-fraction radiation therapy: How much more evidence is needed? J. Natl. Cancer. Inst., 2005. 97(11): p. 786-8. 5. Thomas, T.H., et al., The adaptation of megavoltage cone beam CT for use in standard radiotherapy treatment planning. Phys Med Biol, 2009. 54(7): p. 2067-77. 6. Kessler, M.L., Image registration and data fusion in radiation therapy. Br J Radiol, 2006. 79 Spec No 1: p. S99-108.
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