TomoTherapy Related Projects. An image guidance alternative on Tomo Low dose MVCT reconstruction Patient Quality Assurance using Sinogram

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Transcription:

TomoTherapy Related Projects An image guidance alternative on Tomo Low dose MVCT reconstruction Patient Quality Assurance using Sinogram

Development of A Novel Image Guidance Alternative for Patient Localization using Topographic Images for TomoTherapy X. Sharon Qi*, PhD, Benjamin White, PhD, Daniel Low, PhD Department of Radiation Oncology, David of Geffen School of Medicine at UCLA, Los Angeles, CA 90095 *xqi@mednet.ucla.edu. Tel: (310)983-3463 FAX: (310)983-3603 OBJECTIVES The unique geometric design and integrated on-board imaging system allows for acquisition of topographic images on Tomotherapy Hi ART system. The objective is to develop a faster and lower dose topogram based image registration for TomoTherapy as an alternative image guidance tool to volumetric MVCT. METHODS Topogram procedures were created and performed for three anthropomorphic phantoms, including head (20 cm length), thorax (45 cm length) and spine (17 cm length) phantoms. The topogram procedures consisted of four couch speeds, 1 cm/s, 2 cm/s, 3 cm/s, and 3.99 cm/s (maximum couch speed) with a scanning duration of 30 seconds. All MLC leaves were opened to provide the largest field of view. A data compression factor of 1 was used for the topographic scans. An air scan was acquired to normalize the raw detector output. For patient localization, two topograms were acquired for each phantom and four different couch speeds at gantry angles of 0 and 90. To obtain the correct reference image from the simulation CT, a digitally reconstructed topogram (DRT, Figure 1) was generated in the TomoTherapy beam and detector geometry. To assess daily setup errors, known shifts were applied to the phantom for the topographic images (Figure 2). Image registration was performed by rigidly aligning the visible anatomy of the phantom in the topogram with the anatomy of the created DRT (Figure 3). MVCT scans were performed for the same phantoms using the normal imaging jaw width (4 mm). For MVCT imaging registration, we used bony and soft tissue to align the MVCT to the kvct. The MVCT was set up with known shifts from the kvct position. The shifts derived from topogram were compared to the MVCT image. RESULTS MVCT yielded positional offsets of 2 mm in the medio-lateral (ML), cranial-caudal (CC), and anterior-posterior (AP) directions. For the thorax phantom, the relative positional errors observed in all topograms (with different couch speeds) were 1.5 mm in the ML, 8.1 mm in the CC, and 2.5 mm in the AP direction. Between couch speeds of 1 cm/s, 2 cm/s and 3 cm/s, the relative shifts were within 3 mm in all ML and AP directions, and 5 mm in CC direction; while for fast couch speed such as 4.0 cm/s, larger relative shifts in CC direction between different couch speeds was seen (Table 1). At maximum couch speed, the topogram was markedly blurred in the CC direction. However, the blurred voxels resulted in a high positional error of 8.1 mm in the CC direction. The errors in the ML and AP directions were on the order of the slice thickness of the MVCT, which are at clinical acceptable level. Based on our preliminary measurements, a couch speed of 3 cm/s might be the fastest couch speed achievable with reasonable positional errors due to voxel deformation in the topogram. Compared with the imaging acquisition time of 3-5 min for MVCT scans, the time required to acquire clinically acceptable topograms for the selected phantom were significantly longer using topograms. Based on these results, a couch speed of 3 cm/s is the fasted couch speed achievable with reasonable positional errors due to voxel deformation in the topogram. Figure 2: Reconstructed MV TomoTherapy Topograms at couch speeds of 1 and 4 cm/s generated in the TomoTherapy beam and detector geometry. (a) and (b)couch speed of 1 cm/s; (c) and (d) couch speed of 4.0 cm/s. (a) (b) Figure 3: MV topogram based registration by rigid aligning the reconstructed Topogram to the DRT for (a) a thorax phantom and (b) a head phantom. (c) (d) (d) Figure 1: Digitally Reconstructed Topogram (the reference image) generated from the CT simulation in the TomoTherapy beam and detector geometry for a thorax phantom. (a) anteroposterior MV topogram and (b) left lateral MV topogram. (a) (b) (a) (b) *(b) Courtesy of Dr. Kevin Moore. Table 1: Relative positional errors at different couch speeds using MV Topogram registration versus MVCT registration on TomoTherapy. Direction CONCLUSION Topograms with proper couch speed (<3 cm/s) provide reliable patient localization while significantly reducing pre-treatment imaging time as well as imaging doses. Topogram can be used as an alternative and/or additional patient alignment tool to MVCT on TomoTherapy. References: * Relative positional errors for the topograms at different couch speeds. 1. Morre, KL et al., Fast, low-dose patent localization on TomoTherapy via Tomogram registration, Med. Phys. 37 (8), 4068 (2010). 2. Meeks, SL et al., Performance characterization of megavoltage computed tomography imaging on a helical tomotherapy unit, Med. Phys. 32 (8), 2673 (2005). 3. Keller, H et al., Monte Carlo study of a highly efficient gas ionization detector for megavoltage imaging and image-guided radiotherapy, Med. Phys. 29 (2), 165 (2002). ICCR 2013, 6-9 May 2013 Melbourne, Australia

ASTRO 2013 Oral

FIG. 2. Resolution slice reconstruction results from the Siemens image quality phantom. (a), (b), and (c) are from FBP, TV, TF with 100% data; (d), (e), and (f) are from FBP, TV, TF with 25% data. The zoom-in details are shown for the ROI in the selected square.

FIG. 4. H&N patient results. (a), (b), and (c) are from FBP, TV, and TF with 100% data; (d), (e), and (f) are from FBP, TV, and TF with 25% data.

Med Phys. 2013 Aug;40(8):081919. doi: 10.1118/1.4816303.

Clinical Outcome Assessment TCP/NTCP Clinical dose-response assessment Outcome prediction

Fig. 2. Dose response curves for malignant gliomas at 0.5, 1.0, and 1.5 years. The patient survival rates given by Walker et al. (9) and Salazar et al. ( 10 and 11) are considered. The lines represent the fitting to the data points for the survival rates given at 0.5, 1.0, and 1.5 years, respectively. The fitting yields: α = 0.06 ± 0.05 Gy 1 and α/β = 10.0 ± 15.1 Gy. The error bars represent statistical uncertainty.

Fig. 5. Fitting of different grades of astrocytomas using the data of Salazar et al. ( 10 and 11). For Grade 3 astrocytoma, our fitting yields: α = 0.11 ± 0.10 Gy 1 and α/β = 5.8 ± 11.8 Gy; whereas, for Grade 4 astrocytoma, α = 0.04 ± 0.06 Gy 1 and α/β = 5.6 ± 9.4 Gy. Int. J. Radiation Oncology Biol. Phys., Vol. 64, No. 5, pp. 1570 1580, 2006

Data Mining Data analysis Time series analysis

ICCR 2013, 6-9 May 2013 Melbourne, Australia Analysis of Patient Setup Errors and Autocorrelation for Head-and-neck Radiotherapy Using Volumetric Computed Tomography X. Sharon Qi, Angie Hu Department of Radiation Oncology, David of Geffen School of Medicine at UCLA, Los Angeles, CA, USA