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Technol Cancer Res Treat ; 10(5): 495-504, 2011 Oct.
Article in English | MEDLINE | ID: mdl-21895034

ABSTRACT

The purpose of this study was to analyze inter- and intra-fractional changes in tumor volume with respect to both spatial and volumetric parameters among patients treated by SBRT for lung cancer. Twelve patients (13 tumors) were treated by SBRT with abdominal compression in 3-5 fractions over a 2 week period to a median dose of 60 Gy (range, 48 to 60 Gy). Kilovoltage cone-beam CT (CBCT) was obtained prior to the delivery of each fraction as well as intra-fractionally yielding a total of 55 CBCT scans. All CBCT scans were registered with the planning CT for target alignment and shifts were recorded and analyzed. Retrospectively, gross tumor volume (GTV) was contoured on all CBCT images and compared to initial planning volumes; positional differences were evaluated utilizing directional and vector analysis. Shifts greater than 5 mm were applied inter-fractionally in 6.8% (lateral), 29.5% (longitudinal), and 6.8% (vertical) of all delivered treatments. Using a 10 mm threshold, the corresponding percentages were 2.3%, 13.6%, and 2.3%, respectively. Across all fractions, the calculated inter-fractional shift vectors ranged from 0 to 31.2 mm, with 40.9%, 15.9%, and 11.4% of all fractions having shift vectors≥5 mm, ≥10 mm, and ≥20 mm, respectively. Intra-fractional shifts were also evaluated and found negligible in a small portion of patients evaluated. The mean overall reduction in GTV was 21.1% during SBRT. Significant changes in both position and volume occur during SBRT for lung cancer. Shifts (particularly in the superior-inferior axis) may exceed applied margins and compromise target coverage. Due to the extreme hypofractionation associated with SBRT, inter-fractional image guidance is necessary.


Subject(s)
Carcinoma, Non-Small-Cell Lung/surgery , Lung Neoplasms/surgery , Radiosurgery/methods , Surgery, Computer-Assisted , Tumor Burden , Carcinoma, Non-Small-Cell Lung/pathology , Dose Fractionation, Radiation , Humans , Lung Neoplasms/pathology , Radiotherapy Planning, Computer-Assisted , Treatment Outcome
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