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      Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography

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          Abstract

          Background

          To determine the optimal approach to delineating patient-specific internal gross target volumes (IGTV) from four-dimensional (4-D) computed tomography (CT) image data sets used in the planning of radiation treatment for lung cancers.

          Methods

          We analyzed 4D-CT image data sets of 27 consecutive patients with non-small-cell lung cancer (stage I: 17, stage III: 10). The IGTV, defined to be the envelope of respiratory motion of the gross tumor volume in each 4D-CT data set was delineated manually using four techniques: ( 1) combining the gross tumor volume (GTV) contours from ten respiratory phases (IGTV AllPhases); ( 2) combining the GTV contours from two extreme respiratory phases (0% and 50%) (IGTV 2Phases); ( 3) defining the GTV contour using the maximum intensity projection (MIP) (IGTV MIP); and ( 4) defining the GTV contour using the MIP with modification based on visual verification of contours in individual respiratory phase (IGTV MIP-Modified). Using the IGTV AllPhases as the optimum IGTV, we compared volumes, matching indices, and extent of target missing using the IGTVs based on the other three approaches.

          Results

          The IGTV MIP and IGTV 2Phases were significantly smaller than the IGTV AllPhases ( p < 0.006 for stage I and p < 0.002 for stage III). However, the values of the IGTV MIP-Modified were close to those determined from IGTV AllPhases ( p = 0.08). IGTV MIP-Modified also matched the best with IGTV AllPhases.

          Conclusion

          IGTV MIP and IGTV 2Phases underestimate IGTVs. IGTV MIP-Modified is recommended to improve IGTV delineation in lung cancer.

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          Most cited references15

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          Acquiring a four-dimensional computed tomography dataset using an external respiratory signal.

          Four-dimensional (4D) methods strive to achieve highly conformal radiotherapy, particularly for lung and breast tumours, in the presence of respiratory-induced motion of tumours and normal tissues. Four-dimensional radiotherapy accounts for respiratory motion during imaging, planning and radiation delivery, and requires a 4D CT image in which the internal anatomy motion as a function of the respiratory cycle can be quantified. The aims of our research were (a) to develop a method to acquire 4D CT images from a spiral CT scan using an external respiratory signal and (b) to examine the potential utility of 4D CT imaging. A commercially available respiratory motion monitoring system provided an 'external' tracking signal of the patient's breathing. Simultaneous recording of a TTL 'X-Ray ON' signal from the CT scanner indicated the start time of CT image acquisition, thus facilitating time stamping of all subsequent images. An over-sampled spiral CT scan was acquired using a pitch of 0.5 and scanner rotation time of 1.5 s. Each image from such a scan was sorted into an image bin that corresponded with the phase of the respiratory cycle in which the image was acquired. The complete set of such image bins accumulated over a respiratory cycle constitutes a 4D CT dataset. Four-dimensional CT datasets of a mechanical oscillator phantom and a patient undergoing lung radiotherapy were acquired. Motion artefacts were significantly reduced in the images in the 4D CT dataset compared to the three-dimensional (3D) images, for which respiratory motion was not accounted. Accounting for respiratory motion using 4D CT imaging is feasible and yields images with less distortion than 3D images. 4D images also contain respiratory motion information not available in a 3D CT image.
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            4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT.

            We propose a new scanning protocol for generating 4D-CT image data sets influenced by respiratory motion. A cine scanning protocol is used during data acquisition, and two registration methods are used to sort images into temporal phases. A volume is imaged in multiple acquisitions of 1 or 2 cm length along the cranial-caudal direction. In each acquisition, the scans are continuously acquired for a time interval greater than or equal to the average respiratory cycle plus the duration of the data for an image reconstruction. The x ray is turned off during CT table translation and the acquisition is repeated until the prescribed volume is completely scanned. The scanning for 20 cm coverage takes about 1 min with an eight-slice CT or 2 mins with a four-slice CT. After data acquisition, the CT data are registered into respiratory phases based on either an internal anatomical match or an external respiratory signal. The internal approach registers the data according to correlation of anatomy in the CT images between two adjacent locations in consecutive respiratory cycles. We have demonstrated the technique with ROIs placed in the region of diaphragm. The external approach registers the image data according to an externally recorded respiratory signal generated by the Real-Time Position Management (RPM) Respiratory Gating System (Varian Medical Systems, Palo Alto, CA). Compared with previously reported prospective or retrospective imaging of the respiratory motion with a single-slice or multi-slice CT, the 4D-CT method proposed here provides (1) a shorter scan time of three to six times faster than the single-slice CT with prospective gating; (2) a shorter scan time of two to four times improvement over a previously reported multi-slice CT implementation, and (3) images over all phases of a breathing cycle. We have applied the scanning and registration methods on phantom, animal and patients, and initial results suggest the applicability of both the scanning and the registration methods.
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              Assessing respiration-induced tumor motion and internal target volume using four-dimensional computed tomography for radiotherapy of lung cancer.

              To assess three-dimensional tumor motion caused by respiration and internal target volume (ITV) for radiotherapy of lung cancer. Respiration-induced tumor motion was analyzed for 166 tumors from 152 lung cancer patients, 57.2% of whom had Stage III or IV non-small-cell lung cancer. All patients underwent four-dimensional computed tomography (4DCT) during normal breathing before treatment. The expiratory phase of 4DCT images was used as the reference set to delineate gross tumor volume (GTV). Gross tumor volumes on other respiratory phases and resulting ITVs were determined using rigid-body registration of 4DCT images. The association of GTV motion with various clinical and anatomic factors was analyzed statistically. The proportions of tumors that moved >0.5 cm along the superior-inferior (SI), lateral, and anterior-posterior (AP) axes during normal breathing were 39.2%, 1.8%, and 5.4%, respectively. For 95% of the tumors, the magnitude of motion was less than 1.34 cm, 0.40 cm, and 0.59 cm along the SI, lateral, and AP directions. The principal component of tumor motion was in the SI direction, with only 10.8% of tumors moving >1.0 cm. The tumor motion was found to be associated with diaphragm motion, the SI tumor location in the lung, size of the GTV, and disease T stage. Lung tumor motion is primarily driven by diaphragm motion. The motion of locally advanced lung tumors is unlikely to exceed 1.0 cm during quiet normal breathing except for small lesions located in the lower half of the lung.
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                Author and article information

                Journal
                Radiat Oncol
                Radiation Oncology (London, England)
                BioMed Central
                1748-717X
                2009
                27 January 2009
                : 4
                : 4
                Affiliations
                [1 ]Department of Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, USA
                [2 ]Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, USA
                Article
                1748-717X-4-4
                10.1186/1748-717X-4-4
                2645420
                19173738
                9199e93e-dfcd-4738-91ba-d9897820954b
                Copyright © 2009 Ezhil et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 October 2008
                : 27 January 2009
                Categories
                Research

                Oncology & Radiotherapy
                Oncology & Radiotherapy

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