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Purpose: With increasing concern for patient dose from CT scan, we are trying to reduce CT scan and use intravenous contrast-enhanced CT (contrast CT) in treatment planning. This study is to investigate dose calculation accuracy using contrast CT in treatment planning for lung, esophagus and pancreas cancer., Methods: We analyzed treatment plans for 8 patients for whom CT simulation was performed both with and without intravenous contrast agent (CA) (non-contrast CT). IMRT/3D plans were generated with inhomogeneity correction on the non-contrast CT scan. Contrast CTs were fused to the non-contrast studies and all contours and plans were copied to the contrast CT scans. For each patient, we analyzed dose-volume histograms (DVH) for planning volumes (PTV) and the organs-at-risk (OAR), comparing the doses generated on non-contrast CT scans with those generated on contrast CT scans., Results: Maximum doses ratio Dmax(contrast)/Dmax (non-contrast) in PTVs was 1.0009±0.0013. The ratio of D05 (contrast)/D05 (non-contrast) was 0.996±0.005. The ratio of mean PTV dose Dmean(contrast)/Dmean(non-contrast) was 0.990±0.005%. The ratio of minimum dose Dmin(contrast)/Dmin(non-contrast) and D95(contrast)/D95(non-contrast) were 0.970±0.030 and 0.984±0.009, respectively. Contrast CT raised cord dose slightly. The ratio of cord Dmax was 1.005±0.026. However there were two cases the ratio of cord Dmax were 1.035., Conclusions: The PTV D95 is usually normalized to prescription dose and the D95 differences between contrast and regular CT were within 2%. In most cases, the contrast CT could be used to treatment planning clinically. However more attention should be paid to maximum cord dose if it is already close to criteria limit., (© 2012 American Association of Physicists in Medicine.)

To effectively deliver radiation dose to lung tumors, respiratory motion has to be considered in treatment planning. In this paper we first present a new lung IMRT planning algorithm, referred as the dose shaping (DS) method, that shapes the dose distribution according to the probability distribution of the tumor over the breathing cycle to account for respiratory motion. In IMRT planning a dose-based convolution method was generally adopted to compensate for random organ motion by performing 4-D dose calculations using a tumor motion probability density function. We modified the CON-DOSE method to a dose volume histogram based convolution method (CON-DVH) that allows nonuniform dose distribution to account for respiratory motion. We implemented the two new planning algorithms on an in-house IMRT planning system that uses the Eclipse (Varian, Palo Alto, CA) planning workstation as the dose calculation engine. The new algorithms were compared with (1) the conventional margin extension approach in which margin is generated based on the extreme positions of the tumor, (2) the dose-based convolution method, and (3) gating with 3 mm residual motion. Dose volume histogram, tumor control probability, normal tissue complication probability, and mean lung dose were calculated and used to evaluate the relative performance of these approaches at the end-exhale phase of the respiratory cycle. We recruited six patients in our treatment planning study. The study demonstrated that the two new methods could significantly reduce the ipsilateral normal lung dose and outperformed the margin extension method and the dose-based convolution method. Compared with the gated approach that has the best performance in the low dose region, the two methods we proposed have similar potential to escalate tumor dose, but could be more efficient because dose is delivered continuously.