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Purpose: Hardware integration of fluorodeoxyglucose positron emission tomography (PET) with computed tomography (CT) in combined PET/CT scanners has provided radiation oncologists and physicists with new possibilities for 3-D treatment simulation. The use of PET/CT simulation for target delineation of lung cancer is becoming popular and many studies concerning automatic segmentation of PET images have been performed. Several of these studies consider size and source-to-background (SBR) in their segmentation methods but neglect respiratory motion. The purpose of the current study was to develop a functional relationship between optimal activity concentration threshold, tumor volume, motion extent, and SBR using multiple regression techniques by performing an extensive series of phantom scans simulating tumors of varying sizes, SBR, and motion amplitudes. Segmented volumes on PET were compared with the “motion envelope” of the moving sphere defined on cine CT. Methods: A NEMA IEC thorax phantom containing six spheres (inner diameters ranging from 10 to 37 mm) was placed on a motion platform and moved sinusoidally at 0–30 mm (at 5 mm intervals) and six different SBRs (ranging from 5:1 to 50:1), producing 252 combinations of experimental parameters. PET images were acquired for 18 min and split into three 6 min acquisitions for reproducibility. The spheres (blurred on PET images due to motion) were segmented at 1% of maximum activity concentration intervals. The optimal threshold was determined by comparing deviations between the threshold volume surfaces with a reference volume surface defined on cine CT. Optimal activity concentration thresholds were normalized to background and multiple regression was used to determine the relationship between optimal threshold, volume, motion, and SBR. Standardized regression coefficients were used to assess the relative influence of each variable. The segmentation model was applied to three lung cancer patients and segmented regions of interest were compared with those segmented on cine CT. Results: The resulting model and coefficients provided a functional form that fit the phantom data with an adjusted R2=0.96. The most significant contributor to threshold level was SBR. Surfaces of PET-segmented volumes of three lung cancer patients were within 2 mm of the reference CT volumes on average. Conclusions: The authors successfully developed an expression for optimal activity concentration threshold as a function of object volume, motion, and SBR. [ABSTRACT FROM AUTHOR]

Purpose: To determine the extent of interfractional setup errors and day-to-day organ motion errors by assessing daily bone alignment results and changes in soft tissue tumor position during hypofractionated, in-room computed tomography (CT)-guided stereotactic body radiation therapy (SBRT) of lung cancer. Methods and Materials: Daily alignment results during SBRT were analyzed for 117 tumors in 112 patients. Patients received 40–50 Gy of SBRT in four to five fractions using an integrated CT-LINAC system. The free-breathing CT scans acquired during treatment setup were retrospectively realigned to match with each of the bony references and the gross tumor volume (GTV) defined on the reference CT by rigid-body registration, and the daily deviations were calculated. Results: The mean magnitude (± SD) three-dimensional shift from the initial skin marks to the final bone-aligned positions was 9.4 ± 5.7 mm. The mean daily GTV deviation from the bone position was 0.1 ± 3.8 mm in the anterior–posterior direction, −0.01 ± 4.2 mm in the superior–inferior direction, and 0.2 ± 2.5 mm in the lateral direction. A clinically noteworthy trend (net change >5 mm in any direction) in GTV position relative to the bone was observed in 23 cases (20%). Conclusions: Soft tissue target position can change significantly beyond the motion envelope defined in the original internal target volume in four-dimensional CT-based treatment planning for SBRT of lung cancer. Additional margin should be considered for adequate coverage of interfractional changes. [ABSTRACT FROM AUTHOR]

Purpose: To compare three different methods of propagating the gross tumor volume (GTV) through the respiratory phases that constitute a four-dimensional computed tomography image data set. Methods and Materials: Four-dimensional computed tomography data sets of 20 patients who had undergone definitive hypofractionated radiotherapy to the lung were acquired. The GTV regions of interest (ROIs) were manually delineated on each phase of the four-dimensional computed tomography data set. The ROI from the end-expiration phase was propagated to the remaining nine phases of respiration using the following three techniques: (1) rigid-image registration using in-house software, (2) rigid image registration using research software from a commercial radiotherapy planning system vendor, and (3) rigid-image registration followed by deformable adaptation originally intended for organ-at-risk delineation using the same software. The internal GTVs generated from the various propagation methods were compared with the manual internal GTV using the normalized Dice similarity coefficient (DSC) index. Results: The normalized DSC index of 1.01 ± 0.06 (SD) for rigid propagation using the in-house software program was identical to the normalized DSC index of 1.01 ± 0.06 for rigid propagation achieved with the vendor''s research software. Adaptive propagation yielded poorer results, with a normalized DSC index of 0.89 ± 0.10 (paired t test, p <0.001). Conclusion: Propagation of the GTV ROIs through the respiratory phases using rigid- body registration is an acceptable method within a 1-mm margin of uncertainty. The adaptive organ-at-risk propagation method was not applicable to propagating GTV ROIs, resulting in an unacceptable reduction of the volume and distortion of the ROIs. [Copyright &y& Elsevier]

Purpose: To investigate the motion characteristics of distal esophagus cancer primary tumors using four-dimensional computed tomography (4D CT). Methods and Materials: Thirty-one consecutive patients treated for esophagus cancer who received respiratory-gated 4D CT imaging for treatment planning were selected. Deformable image registration was used to map the full expiratory motion gross tumor volume (GTV) to the full-inspiratory CT image, allowing quantitative assessment of each voxel''s displacement. These displacements were correlated with patient tumor and respiratory characteristics. Results: The mean (SE) tidal volume was 608 (73) mL. The mean GTV volume was 64.3 (10.7) mL on expiration and 64.1 (10.7) mL on inspiration (no significant difference). The mean tumor motion in the x-direction was 0.13 (0.006) cm (average of absolute values), in the y-direction 0.23 (0.01) cm (anteriorly), and in the z-direction 0.71 (0.02) cm (inferiorly). Tumor motion correlated with tidal volume. Comparison of tumor motion above vs. below the diaphragm was significant for the average net displacement (p = 0.014), motion below the diaphragm was greater than above. From the cumulative distribution 95% of the tumors moved less than 0.80 cm radially and 1.75 cm inferiorly. Conclusions: Primary esophagus tumor motion was evaluated with 4D CT. According to the results of this study, when 4D CT is not available, a radial margin of 0.8 cm and axial margin of ±1.8 cm would provide tumor motion coverage for 95% of the cases in our study population. [Copyright &y& Elsevier]

Abstract—: In this article, we describe a clinical mega-voltage cone-beam computed tomography (MV CBCT) system, present the image acquisition and patient setup procedure, discuss the positioning accuracy and image quality, and illustrate its potential use for image-guided radiation therapy (IGRT) through selected clinical examples. The MV CBCT system consists of a standard linear accelerator equipped with an amorphous-silicon flat panel electronic portal-imaging device adapted for mega-electron volt (MeV) photons. An integrated computer workspace provides automated acquisition of projection images, image reconstruction, CT to CBCT image registration, and couch shift calculation. The system demonstrates submillimeter localization precision and sufficient soft-tissue resolution to visualize structures such as the prostate. In our clinic, we have used the MV CBCT system to detect nonrigid spinal cord distortions, monitor tumor growth and shrinkage, and locate and position stationary tumors in the lung. MV CBCT has also greatly improved the delineation of structures in CT images that suffer from metal artifacts. MV CBCT has undergone significant development in the last few years. Current image quality has already proven sufficient for many IGRT applications. Moreover, we expect the range of clinical applications for MV CBCT to grow as imaging technology continues to improve. [Copyright &y& Elsevier]