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How Should We Delineate the Gross Tumor Volume (GTV) of Nasopharyngeal Cancer (NPC)?
I. J. Radiation Oncology d Biology d Physics
S162
1109
Volume 72, Number 1, Supplement, 2008
Adaptive IMRT for Head and Neck Cancer Based on Automatically Generated Contours using Deformable Image Registration
S. Y. Tsuji, A. Hwang, V. Weinberg, S. S. Yom, J. M. Quivey, P. Xia University of California San Francisco, San Francisco, CA Purpose/Objective(s): For some patients, the initial planning CT may not adequately represent their anatomy throughout the course of radiation treatment, particularly for patients with head and neck cancer, who frequently experience weight loss and/or tumor shrinkage. However, quantifying changes and correcting for them in a new plan requires onerous recontouring of all structures. This study assessed the accuracy of automatically deformed contours with volumetric and dosimetric endpoints for adaptive replanning. Materials/Methods: Sixteen patients with head and neck cancer were selected for this study, each of whom had experienced a change in tumor volume and/or anatomy during radiotherapy that necessitated an adaptive replan based on a mid-course planning CT. Using a commercially available program, contours from the initial planning CT were deformed to the new CT for each patient. The automatically generated volume (Va) was directly compared to the physician-drawn volume (Vm) on the same CT using pixel by pixel analysis to calculate the overlap index (OI). The OI was defined as the overlapping volume divided by the Vm. The automatically generated contours were then used to create a new plan for each patient, keeping the same dose constraints and beam angles as the adaptive plan based on the manual contours. Both adaptive plans were evaluated according to standard dosimetric endpoints. Results: All patients had stage III-IV cancers: 7 nasopharynx, 7 oropharynx, and 2 other. Fourteen patients received concurrent platinum-based chemotherapy. The prescription doses for most patients were 70 Gy for GTV and 59 Gy for CTV1, both in 33 fractions. Structure volumes were similar between the 2 contour sets, except for GTV, which was intentionally unchanged in the physician-drawn volumes. The mean manual volume was 230 mL versus 180 mL for the automatic (p = 0.004). The OI for the target volumes was lower than for the critical structures: 0.63 and 0.68 for GTV and CTV1, versus 0.77, 0.75, 0.73, 0.71, and 0.79 for spinal cord, brainstem, left and right parotid, and mandible. Using the manual contours as the benchmark, the automatic plans showed inferior coverage for the GTV: D95: 69.91 Gy vs. 64.99 Gy (p \ 0.001), V95: 98.6% vs. 89.9% (p = 0.004). For CTV1, results were: D95: 59.89 Gy vs. 48.72 Gy (p = 0.002), V95: 98.4% vs. 89.8% (p \ 0.001). D1cc for the spinal cord was the only normal structure to show a difference between manual and automatic plans: 39.90 Gy vs. 42.77 Gy (p = 0.034). Conclusion: Automatically generated contours using deformable image registration can ease the burden of repeat contouring for adaptive replanning. However, they cannot replace the clinical judgment required for the physician-drawn target volumes. In contrast, it appears feasible to use them for delineation of normal structures. Author Disclosure: S.Y. Tsuji, None; A. Hwang, None; V. Weinberg, None; S.S. Yom, None; J.M. Quivey, None; P. Xia, Siemens Medical Solutions Corp., B. Research Grant.
1110
How Should We Delineate the Gross Tumor Volume (GTV) of Nasopharyngeal Cancer (NPC)?
R. K. Ten Haken, A. Popovtzer, M. Ibrahim, I. Gluck, F. Feng, D. Tatro, M. L. Kessler, A. Eisbruch University of Michigan, Ann Arbor, MI Purpose/Objectives: MRI is established as superior in evaluating the extent of the primary NPC compared to CT. Therefore, outlining the GTV on axial MRI and registering the MRI with the planning CT is common practice. However, which MRI dataset(s) should be used has not been established. The standard approach includes the use of axial images. In this study we evaluated the impact of the different MR imaging planes and modalities on GTV definition. Materials/Methods: We retrospectively studied the planning CT scans as well as the pretherapy MRI images of 12 NPC patients. GTVs were defined on each of 4 MRI datasets [T1 Axial with gadolinium fat suppressed, T2 Axial, T1 coronal (COR), and T1 sagittal (SAG)] by a consensus of 3 physicians: a neuroradiologist, an otolaryngologist, and a radiation oncologist. Registration of each MRI dataset to the planning CT of each patient was achieved using a mutual information rigid translation algorithm tuned to primarily consider C1, C2, and bony skull anatomy. Thus, the soft tissue GTV information from each MRI study was fused to the CT dataset where they could be compared for extension and overlap both qualitatively (via visual inspection on reconstructed axial, sagittal, and coronal planes) and quantitatively (in terms of physical volume, where encompassing and overlapping volumes were computed and averaged). First the COR and SAG datasets were assessed for what they added to the traditional T1 axial datasets, primarily to discover potential GTV extensions due to imaging plane. The T2 axial datasets were subsequently also compared to the T1 axials to investigate differences due to pulse sequence. Results: In all cases both the COR and SAG studies demonstrate GTV extension beyond that defined on the T1 Axials (average combined increase of 30% (sd 22%)). On average only 15% (sd 6%) of the extended volumes are common to both COR and SAG. On average CORs increase the T1 Axial GTVs by 21% (sd 18%), and SAGs increase this by an additional 10% (sd 6%). On average the T2 Axial studies increase the T1 Axial GTVs by 12% (sd 9%). As might be expected, the qualitative assessments illustrate that COR (SAG) images primarily lead to extensions of the inferior or superior GTV borders, somewhat modify lateral or medial (posterior or anterior) borders, but will if used alone often underestimate the posterior or anterior (lateral or medial) GTV extent. The T2 Axials generally lead to non-specific (in terms of direction) extensions into soft tissue regions which are more subtly visualized than on the T1 Axials (and vice versa). Conclusions: The fusion of NPC GTVs delineated on COR and SAG MRI images to those derived from traditional MRI Axial images has a major impact on (i.e., leads to extension of) GTV definition. We suggest incorporating all modalities when planning modern radiation for NPC. Supported by NIH P01-CA59827. Author Disclosure: R.K. Ten Haken, None; A. Popovtzer, None; M. Ibrahim, None; I. Gluck, None; F. Feng, None; D. Tatro, None; M.L. Kessler, None; A. Eisbruch, None.
S162
1109
Volume 72, Number 1, Supplement, 2008
Adaptive IMRT for Head and Neck Cancer Based on Automatically Generated Contours using Deformable Image Registration
S. Y. Tsuji, A. Hwang, V. Weinberg, S. S. Yom, J. M. Quivey, P. Xia University of California San Francisco, San Francisco, CA Purpose/Objective(s): For some patients, the initial planning CT may not adequately represent their anatomy throughout the course of radiation treatment, particularly for patients with head and neck cancer, who frequently experience weight loss and/or tumor shrinkage. However, quantifying changes and correcting for them in a new plan requires onerous recontouring of all structures. This study assessed the accuracy of automatically deformed contours with volumetric and dosimetric endpoints for adaptive replanning. Materials/Methods: Sixteen patients with head and neck cancer were selected for this study, each of whom had experienced a change in tumor volume and/or anatomy during radiotherapy that necessitated an adaptive replan based on a mid-course planning CT. Using a commercially available program, contours from the initial planning CT were deformed to the new CT for each patient. The automatically generated volume (Va) was directly compared to the physician-drawn volume (Vm) on the same CT using pixel by pixel analysis to calculate the overlap index (OI). The OI was defined as the overlapping volume divided by the Vm. The automatically generated contours were then used to create a new plan for each patient, keeping the same dose constraints and beam angles as the adaptive plan based on the manual contours. Both adaptive plans were evaluated according to standard dosimetric endpoints. Results: All patients had stage III-IV cancers: 7 nasopharynx, 7 oropharynx, and 2 other. Fourteen patients received concurrent platinum-based chemotherapy. The prescription doses for most patients were 70 Gy for GTV and 59 Gy for CTV1, both in 33 fractions. Structure volumes were similar between the 2 contour sets, except for GTV, which was intentionally unchanged in the physician-drawn volumes. The mean manual volume was 230 mL versus 180 mL for the automatic (p = 0.004). The OI for the target volumes was lower than for the critical structures: 0.63 and 0.68 for GTV and CTV1, versus 0.77, 0.75, 0.73, 0.71, and 0.79 for spinal cord, brainstem, left and right parotid, and mandible. Using the manual contours as the benchmark, the automatic plans showed inferior coverage for the GTV: D95: 69.91 Gy vs. 64.99 Gy (p \ 0.001), V95: 98.6% vs. 89.9% (p = 0.004). For CTV1, results were: D95: 59.89 Gy vs. 48.72 Gy (p = 0.002), V95: 98.4% vs. 89.8% (p \ 0.001). D1cc for the spinal cord was the only normal structure to show a difference between manual and automatic plans: 39.90 Gy vs. 42.77 Gy (p = 0.034). Conclusion: Automatically generated contours using deformable image registration can ease the burden of repeat contouring for adaptive replanning. However, they cannot replace the clinical judgment required for the physician-drawn target volumes. In contrast, it appears feasible to use them for delineation of normal structures. Author Disclosure: S.Y. Tsuji, None; A. Hwang, None; V. Weinberg, None; S.S. Yom, None; J.M. Quivey, None; P. Xia, Siemens Medical Solutions Corp., B. Research Grant.
1110
How Should We Delineate the Gross Tumor Volume (GTV) of Nasopharyngeal Cancer (NPC)?
R. K. Ten Haken, A. Popovtzer, M. Ibrahim, I. Gluck, F. Feng, D. Tatro, M. L. Kessler, A. Eisbruch University of Michigan, Ann Arbor, MI Purpose/Objectives: MRI is established as superior in evaluating the extent of the primary NPC compared to CT. Therefore, outlining the GTV on axial MRI and registering the MRI with the planning CT is common practice. However, which MRI dataset(s) should be used has not been established. The standard approach includes the use of axial images. In this study we evaluated the impact of the different MR imaging planes and modalities on GTV definition. Materials/Methods: We retrospectively studied the planning CT scans as well as the pretherapy MRI images of 12 NPC patients. GTVs were defined on each of 4 MRI datasets [T1 Axial with gadolinium fat suppressed, T2 Axial, T1 coronal (COR), and T1 sagittal (SAG)] by a consensus of 3 physicians: a neuroradiologist, an otolaryngologist, and a radiation oncologist. Registration of each MRI dataset to the planning CT of each patient was achieved using a mutual information rigid translation algorithm tuned to primarily consider C1, C2, and bony skull anatomy. Thus, the soft tissue GTV information from each MRI study was fused to the CT dataset where they could be compared for extension and overlap both qualitatively (via visual inspection on reconstructed axial, sagittal, and coronal planes) and quantitatively (in terms of physical volume, where encompassing and overlapping volumes were computed and averaged). First the COR and SAG datasets were assessed for what they added to the traditional T1 axial datasets, primarily to discover potential GTV extensions due to imaging plane. The T2 axial datasets were subsequently also compared to the T1 axials to investigate differences due to pulse sequence. Results: In all cases both the COR and SAG studies demonstrate GTV extension beyond that defined on the T1 Axials (average combined increase of 30% (sd 22%)). On average only 15% (sd 6%) of the extended volumes are common to both COR and SAG. On average CORs increase the T1 Axial GTVs by 21% (sd 18%), and SAGs increase this by an additional 10% (sd 6%). On average the T2 Axial studies increase the T1 Axial GTVs by 12% (sd 9%). As might be expected, the qualitative assessments illustrate that COR (SAG) images primarily lead to extensions of the inferior or superior GTV borders, somewhat modify lateral or medial (posterior or anterior) borders, but will if used alone often underestimate the posterior or anterior (lateral or medial) GTV extent. The T2 Axials generally lead to non-specific (in terms of direction) extensions into soft tissue regions which are more subtly visualized than on the T1 Axials (and vice versa). Conclusions: The fusion of NPC GTVs delineated on COR and SAG MRI images to those derived from traditional MRI Axial images has a major impact on (i.e., leads to extension of) GTV definition. We suggest incorporating all modalities when planning modern radiation for NPC. Supported by NIH P01-CA59827. Author Disclosure: R.K. Ten Haken, None; A. Popovtzer, None; M. Ibrahim, None; I. Gluck, None; F. Feng, None; D. Tatro, None; M.L. Kessler, None; A. Eisbruch, None.