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Purpose: To separate the dosimetric consequences of changing tumor volume from positional uncertainty for patients undergoing conventionally fractionated lung radiation therapy (RT) and to quantify which factor has a larger impact on dose to target volumes and organs at risk (OAR)., Methods and Materials: Clinical treatment plans from 20 patients who had received conventionally fractionated RT were retrospectively altered by replacing tumor and atelectasis with lung equivalent tissue in the treatment planning system calculations. To simulate positional uncertainty, the isocenter was shifted in both the altered and original plans by 2 and 5 mm in 6 directions. Rotational uncertainty was introduced by rotating each computed tomographic image set by ± 3 degrees about a superior-inferior axis extending through patient center. Additionally, after rotation the isocenter was translated back to its original point within the patient to evaluate whether purely translational corrections could minimize dosimetric consequences due to rotations., Results: Dosimetric statistics for each altered plan were compared with the original. Average changes in the planning target volume (PTV) receiving 95% of prescription dose (PTV V95%) resulting from changing tumor anatomy alone were approximately 0.1%. Average changes in PTV V95% resulting from positional uncertainty were greater (0.2%-4.2%) but were largely independent of whether or not the original tumor volume was present. For 3 patients, increases in volumes receiving 110% of the prescription dose were seen but were largely limited to within the PTV. Translational corrections for patient rotations were effective in minimizing differences in target coverage but had less effect on reducing the maximum spinal cord dose., Conclusions: Anatomic changes alone, such as reductions in tumor volume and atelectasis, had minimal effect on the overall dose distribution. Greater dosimetric consequences were seen with positional uncertainty. With accurate patient localization, replanning during the course of treatment for conventionally fractionated lung cancer patients may not be necessary.

The purpose of the present study was to compare the impact of pulmonary function, body habitus, and stereotactic body radiation therapy (SBRT) immobilization on setup and reproducibility for upper lung tumor. From 2008 through 2011, our institution's prospective SBRT database was searched for patients with upper lung tumors. Two SBRT immobilization strategies were used: full-length BodyFIX and thermoplastic S-frame. At simulation, free-breathing, four-dimensional computed tomography was performed. For each treatment, patients were set up to isocenter with in-room lasers and skin tattoos. Shifts from initial and subsequent couch positions with cone-beam computed tomography (CBCT) were analyzed. Accounting for setup uncertainties, institutional tolerance of CBCT-based shifts for treatment was 2, 2, and 4 mm in left-right, anterior-posterior, and cranial-caudal directions, respectively; shifts exceeding these limits required reimaging. Each patient's pretreatment pulmonary function test was recorded. A multistep, multivariate linear regression model was performed to elucidate intervariable dependency for three-dimensional calculated couch shift parameters. BodyFIX was applied to 76 tumors and S-frame to 17 tumors. Of these tumors, 41 were non-small cell lung cancer and 15 were metastatic from other sites. Lesions measured < 1 (15%), 1.1 to 2 (50%), 2.1 to 3 (25%), and > 3 (11%) cm. Errors from first shifts of first fractions were significantly less with S-frame than BodyFIX (p < 0.001). No difference in local control (LC) was found between S-frame and BodyFIX (p = 0.35); two-year LC rate was 94%. Multivariate modeling confirmed that the ratio of forced expiratory volume in the first second of expiration to forced vital capacity, body habitus, and the immobilization device significantly impacted couch shift errors. For upper lung tumors, initial setup was more consistent with S-frame than BodyFIX, resulting in fewer CBCT scans. Patients with obese habitus and poor lung function had more SBRT setup uncertainty; however, outcome and probability for LC remained excellent.

Purpose: To evaluate the dependence of an automatic match process on the size of the user-defined region of interest (ROI), the structure volume of interest (VOI), and changes in tumor volume when using cone-beam computed tomography (CBCT) for tumor localization and to compare these results with a gold standard defined by a physician's manual match., Methods and Materials: Daily CBCT images for 11 patients with lung cancer treated with conventionally fractionated radiation therapy were retrospectively matched to a reference CT image using the Varian On Board Imager software (Varian, Palo Alto, CA) and a 3-step automatic matching protocol. Matches were performed with 3 ROI sizes (small, medium, large), with and without a structure VOI (internal target volume [ITV] or planning target volume [PTV]) used in the last step. Additionally, matches were performed using an intensity range that isolated the bony anatomy of the spinal column. All automatic matches were compared with a manual match made by a physician., Results: The CBCT images from 109 fractions were analyzed. Automatic match results depend on ROI size and the structure VOI. Compared with the physician's manual match, automatic matches using the PTV as the structure VOI and a small ROI resulted in differences ≥ 5 mm in 1.8% of comparisons. Automatic matches using no VOI and a large ROI differed by ≥ 5 mm in 30.3% of comparisons. Differences between manual and automatic matches using the ITV as the structure VOI increased as tumor size decreased during the treatment course., Conclusions: Users of automatic matching techniques should carefully consider how user-defined parameters affect tumor localization. Automatic matches using the PTV as the structure VOI and a small ROI were most consistent with a physician's manual match, and were independent of volumetric tumor changes., (Copyright © 2014 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.)