2401 - Conformal Simulation Omitted Treatment of Palliative Patients

M. Rahman, C. Shen, J. Dubas, K. Nguyen, M. H. Lin, D. Sher, and A. R. Godley; Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX

Purpose/Objective(s): In our clinic, we will plan palliative patients based on a recent diagnostic scan instead of simulating the patient, termed simulation omitted (SO). Uncertainties in this process limited plans to simple AP/PA. We present a method to extend SO to 3D conformal arcs, consistent with our department practice for simulated palliative patients, that can reduce toxicity to bowel, lungs and central structures. Materials/

Methods: For AP/PA patients we measure patient separation at treatment and update the plan monitor units (MU) if separation has changed since the diagnostic scan used for planning. For 3D arcs we propose to take a cone beam CT (CBCT) of the patient after setup on the LINAC. We developed a program to calculate the effective depth at each control point of the arc. AP/PA SO cases are calculated homogeneously, but 3D cases will be calculated heterogeneously. Effective depth was determined by segmenting the CBCT into tissue, bone and lung and assigning electron densities of 1, 1.6 and 0.25 respectively. This enabled recalculation of MU for any changes in anatomy between the diagnostic scan and treatment. We calculated the effective depth per control point, then used the average effective depth for calculations as 3D conformal arcs use the same MU per control point. Anatomy that is cutoff by the field of view of the diagnostic scan, a frequent occurrence, can be corrected for at treatment with this method, by insuring the CBCT captures the full patient surface. Two patients previously treated with AP/PA SO were re-planned with 3D conformal arcs. The effective depths were recalculated on their CBCTs and change in MU and dose distribution reported.
Results: The accuracy of the program was first confirmed by recalculating the planned MU on the CT, giving <3% difference. The average effective depth changed by 6 and 20 mm for the two patients. This resulted in a change in MU of 4 and 6%. Without correcting for the MU change, the V99% dropped from 97.4 and 90.7% to 62.5 and 88.8% for the two patients. By accounting for the depth change with updated MU, the V99% raised to 99.9 and 97.3%. The program calculated the updated MU in 11±1 seconds.
Conclusion: We have demonstrated that we can quickly determine change of anatomy at the time of treatment, and update a 3D SO plan generated on a diagnostic scan. SO has already been shown to greatly reduce time in the radiation oncology department for the patient. Our 3D method will allow the same quality we achieve with CT simulation based plans, in the shortened time frame.

Patient	1		2
Image	CT	CBCT	CT	CBCT
Ave Depth, mm [Range]	108 [83,145]	112 [75, 172]	175[140, 231]	179 [134, 229]
Ave Eff. Depth, mm [Range]	117 [90, 157]	123 [82, 196]	172 [136, 220]	192[139,247]
Dose/MU Difference Per Control Point, % [Range]	2 [-1, 6]	3 [-9, 12]	-1[-8, 3]	3 [-1,6]
MUTPS, Heterog.	904	-	972	-
MUCalced, Heterog.	921	945	994	1036
V99% Original MU	97.4%	62.5%	90.7%	88.8%
V99% Updated MU	-	99.9%	-	97.3%