- Email: [email protected]
228
S126
I. J. Radiation Oncology
228
● Biology ● Physics
Volume 66, Number 3, Supplement, 2006
A Novel Inverse Planning Tool for Intensity Modulated Arc Therapy
1
D. Cao , M. K. N. Afghan1, M. A. Earl1, T. W. Holmes2, D. M. Shepard1 University of Maryland at Baltimore, Baltimore, MD, 2St. Agnes HealthCare, Baltimore, MD
1
Purpose/Objective(s): Intensity modulated arc therapy (IMAT) is a rotational approach to IMRT delivery that can serve as an alternative to tomotherapy. The key features of IMAT include: (1) it can be delivered on a conventional linear accelerator with an integrated MLC; and (2) IMAT plans can include noncoplanar arcs. A lack of robust inverse planning tools has served as a primary obstacle to the routine clinical implementation of IMAT. In this work, we have developed a new approach to IMAT treatment planning called arc sequencing. The performance of the arc-sequencer has been evaluated and plan comparisons were performed between IMAT and helical tomotherapy. Materials/Methods: With the arc-sequencing algorithm, each arc is approximated as a series of static beams. An optimized IMRT plan is produced, and the arc sequencer translates the optimized fluence maps into deliverable IMAT arcs. Using a simulated annealing algorithm, the sequencer determines the arc shapes and weights that minimize the discrepancy between the optimized and sequenced intensity maps. The sequencer has been applied to 15 patients covering a variety of sites including head-&-neck, prostate, lung, and brain. IMAT plans were developed for 10 patients previously treated with helical tomotherapy and plan comparisons were performed. Results: The results demonstrate that the arc-sequencer is able to consistently produce highly conformal and efficient IMAT plans. For cases with coplanar delivery, the IMAT plans used average of 4.5 arcs and 664 monitor units. For cases planned with non-coplanar arcs, an average of 16 arcs and 498 monitor units were used. The plan comparisons with tomotherapy demonstrated that in 8 of 10 cases IMAT was able to match or exceed to plan quality provided by tomotherapy. In 3 cases, significant additional sparing of critical structures was achieved through the use of noncoplanar arcs. As shown in Figure 1, the mean doses to the brainstem and optic nerve in the non-coplanar IMAT plan were reduced from 1866 and 606 cGy to 388 and 96 cGy, respectively. In 2 complex cases involving multiple prescription levels and multiple targets, the more restrictive nature of the IMAT delivery constraints resulted in less uniform target doses than could be achieved using helical tomotherapy. Conclusions: An arc sequencer has been developed as a robust inverse planning tool for IMAT. The sequencer can generate efficient IMAT plans with highly conformal dose distributions. In most cases, IMAT can provide equivalent plan quality to that provided by tomotherapy. While for some intracranial tumors, the ability to use non-coplanar arcs led to significant reduction in the dose to critical organs.
Author Disclosure: D. Cao, None; M.K.N. Afghan, None; M.A. Earl, None; T.W. Holmes, None; D.M. Shepard, None.
229
Optimization of Opacity Function for CT Volume Rendered Images of the Prostate Using MR Reference Images
A. B. Jani, C. A. Pelizzari University of Chicago Hospitals, Chicago, IL Background: Volume rendering (VR) is a visualization technique whose use for CT has been limited due to challenges in designing an optimum opacity function ␣ [used to enhance/suppress tissues on the rendered image]. An advantage of MR over CT images of the prostate includes superior soft-tissue visualization. Purpose/Objectives: To attempt to improve ␣ for CT-based prostate VR using reference MR images. Materials/Methods: A spherical phantom was used to model CT and MR datasets in exact registration. Then, 10 patients were identified who had matching CT and MR (T2 turbo pin echo sequence) datasets, which were registered. Assuming a trapezoid form of ␣ [⫽␣ (t1, t2, t3, t4)], optimal matching of the VR prostate partial surface with its corresponding axially-defined target was performed, and errors eMR-MR [mean distance in voxel units from MR VR partial surface to MR-defined target], and eCT-CT were computed. Then, on each CT dataset, ␣ was optimized using the MR-based reference target, permitting computation of eCT-MR and ediff (⫽ 兩 eCT-MR - eMR-MR兩 ). A transformation ␦ was then computed and for verification was applied to each individual ␣ to obtain (e’CT-MR) and e’diff (⫽ 兩 e’CT-MR - eMR-MR 兩). Results: Figure 1 shows similar qualitative results between the CT-CT (left) and CT-MR (right) VR images for the phantom (upper) and sample patient (lower). However, as Table 1 shows, although eCT-CT was greater than eMR-MR, eCT-MR was
I. J. Radiation Oncology
228
● Biology ● Physics
Volume 66, Number 3, Supplement, 2006
A Novel Inverse Planning Tool for Intensity Modulated Arc Therapy
1
D. Cao , M. K. N. Afghan1, M. A. Earl1, T. W. Holmes2, D. M. Shepard1 University of Maryland at Baltimore, Baltimore, MD, 2St. Agnes HealthCare, Baltimore, MD
1
Purpose/Objective(s): Intensity modulated arc therapy (IMAT) is a rotational approach to IMRT delivery that can serve as an alternative to tomotherapy. The key features of IMAT include: (1) it can be delivered on a conventional linear accelerator with an integrated MLC; and (2) IMAT plans can include noncoplanar arcs. A lack of robust inverse planning tools has served as a primary obstacle to the routine clinical implementation of IMAT. In this work, we have developed a new approach to IMAT treatment planning called arc sequencing. The performance of the arc-sequencer has been evaluated and plan comparisons were performed between IMAT and helical tomotherapy. Materials/Methods: With the arc-sequencing algorithm, each arc is approximated as a series of static beams. An optimized IMRT plan is produced, and the arc sequencer translates the optimized fluence maps into deliverable IMAT arcs. Using a simulated annealing algorithm, the sequencer determines the arc shapes and weights that minimize the discrepancy between the optimized and sequenced intensity maps. The sequencer has been applied to 15 patients covering a variety of sites including head-&-neck, prostate, lung, and brain. IMAT plans were developed for 10 patients previously treated with helical tomotherapy and plan comparisons were performed. Results: The results demonstrate that the arc-sequencer is able to consistently produce highly conformal and efficient IMAT plans. For cases with coplanar delivery, the IMAT plans used average of 4.5 arcs and 664 monitor units. For cases planned with non-coplanar arcs, an average of 16 arcs and 498 monitor units were used. The plan comparisons with tomotherapy demonstrated that in 8 of 10 cases IMAT was able to match or exceed to plan quality provided by tomotherapy. In 3 cases, significant additional sparing of critical structures was achieved through the use of noncoplanar arcs. As shown in Figure 1, the mean doses to the brainstem and optic nerve in the non-coplanar IMAT plan were reduced from 1866 and 606 cGy to 388 and 96 cGy, respectively. In 2 complex cases involving multiple prescription levels and multiple targets, the more restrictive nature of the IMAT delivery constraints resulted in less uniform target doses than could be achieved using helical tomotherapy. Conclusions: An arc sequencer has been developed as a robust inverse planning tool for IMAT. The sequencer can generate efficient IMAT plans with highly conformal dose distributions. In most cases, IMAT can provide equivalent plan quality to that provided by tomotherapy. While for some intracranial tumors, the ability to use non-coplanar arcs led to significant reduction in the dose to critical organs.
Author Disclosure: D. Cao, None; M.K.N. Afghan, None; M.A. Earl, None; T.W. Holmes, None; D.M. Shepard, None.
229
Optimization of Opacity Function for CT Volume Rendered Images of the Prostate Using MR Reference Images
A. B. Jani, C. A. Pelizzari University of Chicago Hospitals, Chicago, IL Background: Volume rendering (VR) is a visualization technique whose use for CT has been limited due to challenges in designing an optimum opacity function ␣ [used to enhance/suppress tissues on the rendered image]. An advantage of MR over CT images of the prostate includes superior soft-tissue visualization. Purpose/Objectives: To attempt to improve ␣ for CT-based prostate VR using reference MR images. Materials/Methods: A spherical phantom was used to model CT and MR datasets in exact registration. Then, 10 patients were identified who had matching CT and MR (T2 turbo pin echo sequence) datasets, which were registered. Assuming a trapezoid form of ␣ [⫽␣ (t1, t2, t3, t4)], optimal matching of the VR prostate partial surface with its corresponding axially-defined target was performed, and errors eMR-MR [mean distance in voxel units from MR VR partial surface to MR-defined target], and eCT-CT were computed. Then, on each CT dataset, ␣ was optimized using the MR-based reference target, permitting computation of eCT-MR and ediff (⫽ 兩 eCT-MR - eMR-MR兩 ). A transformation ␦ was then computed and for verification was applied to each individual ␣ to obtain (e’CT-MR) and e’diff (⫽ 兩 e’CT-MR - eMR-MR 兩). Results: Figure 1 shows similar qualitative results between the CT-CT (left) and CT-MR (right) VR images for the phantom (upper) and sample patient (lower). However, as Table 1 shows, although eCT-CT was greater than eMR-MR, eCT-MR was