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How Much does Patient Repositioning using On-Treatment-Table CT Imaging Improve Prostate Cancer Treatment Outcome? Mark S. Foskey, Julian G. Rosenman, Lav K. Goyal, Daniel B. Fried, Elaine M. Zeman, Jun Lian, Sarang C. Joshi Department of Radiation Oncology, University of North Carolina Introduction Idea: Simulate dose delivery with and without image guided radiotherapy (IGRT) based on CT data from actual patients Treatment procedure • Currently being used in clinic • Patient scanned with in-room CT (CT-on-rails), with fiducial markers • Image initially aligned to planning image by markers • Then manually aligned, prostate-to-prostate • Table is shifted (no rotation) Methods • 29 anonymous image sets with 538 treatment images • Number of images per patient varied from 3 to 38 • Scanned before treatment on a Siemens Primatom scanner, resolution 0.098 × 0.098 × 0.3 cm. • Simple, very tight standardized treatment plan created for simulation • • • • • Treatment Plan Criteria CTV: the prostate + 5 mm margin, excluding the rectum PTV: prostate + 1 cm margin, excluding rectum Beam Angles: AP, left and right at 40° above horizontal, left and right at 10° below horizontal Dose: 78 Gy in 2Gy fractions Optimization targets: • Beams outline conforms to PTV, optimized to target dose of 78 Gy on all of CTV • Rectum: PV65 < 17%, PV40 < 35% (PVn = percent of volume receiving at least n Gy.) Display from treatment planning system showing beam angles and relevant anatomical structures Dose Calculation • Calculate a dose distribution for each day • Registrations were checked visually on an axial and sagittal slice through the prostate • Apply fluid registration (Joshi ’00) to deform each image into correspondence with the planning image • Apply resulting deformation to the daily dose distribution • Sum dose at each voxel Metrics Evaluated • For CTV and prostate, equivalent uniform dose (EUD) calculated using the generalized Niemierko formula with exponent a 10 . • EUD calculated both for accumulated dose and for each day • For the rectum, the volumes receiving more than 40 and 65 Gy were calculated Planned dose, dose simulated without correction, and dose simulated with correction. Cases are sorted by uncorrected dose. The number of images used for each case is shown along the horizontal axis. Results Rectum CTV: • 13 patients saw an improvement in EUD of at least 2 Gy • 2 patients saw a worsening of the dose distribution • Median improvement 1.62 Gy (p < .0001) Prostate: • 1 patient improved by at least 2 Gy • 21 saw some improvement • 7 saw a worsening • Median improvement .33 Gy (p < .0001) • With IGRT, rectal dose tended to be closer to the plan than without • True in 19 out of 29 cases for percentage of volume receiving 40 Gy (PV40), 17/29 for PV65 Differences between proximity to planned rectal dose values with and without IGRT. Positive values mean dose is closer to plan with IGRT than without Histograms of EUD improvement for the prostate and CTV. • Without IGRT, rectal dose tended to be less than in the plan (20 of 29 cases for PV40, 23 for PV65) • No consistent direction of change between IGRT and conventional treatment • Results of Fowler ’05 suggest a 2-Gy improvement could lead to a 5% increase in biochemical relapsefree survival EUD improvement achieved (Gy) Relationship of Improvement to Initial Deficit • Improvement in the CTV EUD resulting from IGRT correlates well with the severity of the initial undertreatment (ρ=.74) Histogram of differences between rectal dose with and without IGRT. Positive values mean IGRT dose is greater • Fewer patients exceeded prescribed thresholds with IGRT than without (2 vs. 6 for PV40, 0 vs. 2 for PV65) Conclusion EUD improvement needed (Gy) Improvement due to correction, plotted against the improvement that would be needed to match planned EUD. • With tight margins, IGRT, can provide substantial improvement in delivered dose • Dose improvement suggests improvement in bRFS of 5% or more for some cases • IGRT seems to improve correspondence between predicted and delivered rectal dose Supported by DOD Program DAMD17-03-1-0134, NIH Grant 5 R01 RR01861503, and Siemens Corporation