Patient Setup Correction Research Articles

Dosimetric Evaluation of an Alternative to 6 Degrees of Freedom Robotic Couch Correction

A novel, “beam-centric” algorithm has been previously presented which can theoretically provide patient setup correction that is equivalent to that of a 6 Degree of Freedom (6DOF) robotic couch1. Corrections are made through a “virtual 6DOF correction” consisting of 3 couch translations and a combination of couch yaw, collimator and gantry rotations. One potential advantage of such an approach is the avoidance of a third party add-on robotic couch top for initial rigid setup adjustment of the patient.

Adaptive radiotherapy based on contrast enhanced cone beam CT imaging

Cone beam CT (CBCT) imaging has become an integral part of radiation therapy, with images typically used for offline or online patient setup corrections based on bony anatomy co-registration. Ideally, the co-registration should be based on tumor localization. However, soft tissue contrast in CBCT images may be limited. In the present work, contrast enhanced CBCT (CECBCT) images were used for tumor visualization and treatment adaptation. Material and methods. A spontaneous canine maxillary tumor was subjected to repeated cone beam CT imaging during fractionated radiotherapy (10 fractions in total). At five of the treatment fractions, CECBCT images, employing an iodinated contrast agent, were acquired, as well as pre-contrast CBCT images. The tumor was clearly visible in post-contrast minus pre-contrast subtraction images, and these contrast images were used to delineate gross tumor volumes. IMRT dose plans were subsequently generated. Four different strategies were explored: 1) fully adapted planning based on each CECBCT image series, 2) planning based on images acquired at the first treatment fraction and patient repositioning following bony anatomy co-registration, 3) as for 2), but with patient repositioning based on co-registering contrast images, and 4) a strategy with no patient repositioning or treatment adaptation. The equivalent uniform dose (EUD) and tumor control probability (TCP) calculations to estimate treatment outcome for each strategy. Results. Similar translation vectors were found when bony anatomy and contrast enhancement co-registration were compared. Strategy 1 gave EUDs closest to the prescription dose and the highest TCP. Strategies 2 and 3 gave EUDs and TCPs close to that of strategy 1, with strategy 3 being slightly better than strategy 2. Even greater benefits from strategies 1 and 3 are expected with increasing tumor movement or deformation during treatment. The non-adaptive strategy 4 was clearly inferior to all three adaptive strategies. Conclusion. CECBCT may prove useful for adaptive radiotherapy.

Image-Guided-Radiotherapy Retreatment of Spine Metastasis: A Case Report and Radiobiological Evaluation

The present case report describes vertebral metastasis retreatment using kilovoltage cone-beam computed tomography (CBCT) for setup error correction, in order to improve target irradiation and prevent spinal cord toxicity. We evaluated the feasibility of the second radiation therapy course on the overlapping treatment volume. A patient with metastatic kidney cancer, previously treated to the tenth dorsal vertebra with conventional radiation planning (21 Gy; 3 x 7 Gy), underwent retreatment. In order to deliver 30 Gy (15 x 2 Gy) to the target volume with the second irradiation, we evaluated the residual dose that could be received by the spinal cord. We calculated the biologically effective dose according to the linear-quadratic model, using an alpha/beta ratio of 2 Gy. A 3-dimensional conformal plan was generated; CBCT imaging was used to ensure accurate repositioning. A total of 15 CBCT scans were performed; the mean setup corrections in the lateral, longitudinal and vertical directions were 3.38 mm (SD 2.09; range, -0.2 mm division by 7.6 mm), 2.13 mm (SD 3.38; range, -5.9 mm divison by 6 mm), and -1.28 mm (SD 2.02; range, -7.1 mm division by 0.3 mm), respectively. Image-guided radiotherapy is an alternative approach for the retreatment of spine tumors; it ensures accurate patient setup correction and high-precision treatment delivery, which are required for target volumes very close to critical structures.

TU‐D‐BRA‐01: Treating a Moving Target under the Guidance of Hybrid kV and MV Imaging

In recent years, MV and kV electronic flat panel imaging devices have become commonplace equipment installed on the gantry of many newer medical LINACs. Such imaging devices are now routinely used in the clinic for verification of correct initial patient setup before start of a treatment fraction. This is done through MV portal images, 2D kV fluoroscopic images, or cone‐beam CT. However, these amorphous‐silicon detectors have not been used to their full potential. With high resolution imaging capture rates of ∼ 10 frames per second, the role of these MV and kV detectors can be additionally expanded to include real‐time target tracking during the actual radiation treatment delivery process.This lecture will provide an overview of recent research in the use of MV and kV imagers for real‐time tracking purposes. In addition, an explanation of the basic theory and methods necessary to perform real‐time tracking will be discussed.Learning Objectives:1. Fundamentals of MV and kV flat panel detectors.2. Image processing and prediction methods used for real‐time MV and kV intheclinic.3. Issues involved in implementing hybrid MV and kV in the clinic.

SU‐GG‐J‐92: Motion Control Consistency with Abdominal Compression Device from Daily 4D CBCT

Purpose: To investigate the effectiveness of abdominal compression in tumor motion control for lung cancer radiotherapy. To study the motion control consistency during radiation treatment course through 4D reconstruction of daily cone beam computed tomography(CBCT) images. Method and Materials: Patients with lung tumor were scanned with 4D helical CT and the tumor motion was evaluated in left‐right(LR), superior‐inferior(SI), and anterior‐posterior(AP) directions. Patients with tumor motion greater than 1cm in any of the three directions and who could not tolerate the active breathing control(ABC) were treated with abdominal compression. Kilovoltage(kV) CBCT image was acquired for each treatment fraction to correct patient setup. The CBCT imaging data were then reconstructed using a respiratory‐correlated technique to derive 4D CBCT images with 10 different phases of breathing cycle. Daily tumor motion with abdominal compression was evaluated from the 4D CBCT by recording the tumor center position relative to the treatment isocenter in each phase. Three patient data (1 upper lobe tumor and 2 middle lobe tumors) were included in this study and 4 consecutive treatment fractions for each patient were studied. The extent of tumor motion was compared between different treatment fractions to assess the daily variation of motion control with abdominal compression. Results: Mean value and standard deviation(SD) of tumor motions from all patients and treatment fractions studied were 3.1mm±0.9mm (mean±SD), 6.8mm±1.7mm, and 5.3mm±1.8mm in LR, SI, and AP directions respectively. The variation of tumor motion extent of same patient between different fractions was 1.1mm±0.7mm, 2.0mm±1.9mm, and 2.3mm±2.0mm, in LR, SI, and AP directions respectively. Conclusion: Tumor motions which were greater than lcm with free‐breathing were reduced to less than 1cm with abdominal compression. Variation of motion control during treatment course was significant relative to the tumor motion in the patients and treatment fractions studied.

TU‐D‐204C‐01: Some Uses of Neural Networks in Radiation Therapy

Artificial Neural Networks (ANN) have become a staple of machine learning applications. They can be used for pattern recognition, data classification, and process control problems, several of which come up in modern radiation therapy. In this presentation we will look at two representative applications of ANNs: (1) the prediction of breathing, to compensate instrumental lag time in systems that automatically compensate for respiratory motion of a tumor; (2) the analysis of patient setup corrections generated automatically via rigid image registration, to recognize poor or failed results as a quality assurance (QA) measure.All systems that attempt to actively compensate respiratory motion will have intrinsic delays that necessitate predicting the future tumor position by up to several hundred milliseconds. However, every patient breathes differently, which makes the use of analytical breathing models problematic. An ANN is capable of learning the breathing pattern of any given patient directly from incoming data and making an accurate prediction of its future amplitude. We will show examples of this application.Image‐guided radiation therapy (IGRT) relies on image acquisition and registration to optimally position the patient for treatment. However, rigid image registration algorithms can sometimes fall into local minima that can be far removed from the optimal setup position. If one identifies a set of significant “features” of the registration result, such as the shape of the cost function surface in the neighborhood of the solution at convergence, an ANN can use them to classify a particular registration as good or bad, according to some predetermined criteria. This provides an important QA tool to assess patient setups.Learning objectives:1. learn the basic concepts of ANNs as they are used for pattern recognition and classification.2. learn how to use an ANN in a real‐time tumor tracking process.3. understand how an ANN can be trained and used to recognize imperfect patient setup shifts for QA purposes.

SU‐GG‐J‐27: Assessment of Patient Setup Corrections in External Beam Radiotherapy Using On‐Line Kilo‐Voltage Imaging

Purpose: Image‐Guided Radiation therapy (IGRT) has evolved as a new and better tool for accurate patient setup in radiation therapy. The purpose of this study was to assess patient setup corrections in external beam radiotherapy for head‐and‐neck, breast and prostate tumors by using on‐line kilovoltage (kV) imaging. Method and Materials: Patient position corrected values resulted from on‐line orthogonal kV image matching with DRR were retrospectively collected for three different treatment sites: head‐and‐neck (H&N) (n=19), prostate (n=14) and breast (n=10). The systematic and random setup corrections for each individual patient and the groups were calculated and compared between different treatment sites. Results: For H&N patients, the overall systematic and random setup errors were 0.6±3.0, 0.1±3.6 and −1.2±3.8 mm in the left‐right (LR), anterior‐posterior (AP) and superior‐inferior (SI) directions, respectively. Individual systematic errors greater than 5mm were observed in only 1 of 19 (5.2%) H&N patients. Compared with H&N patients, prostate patients showed similar overall systematic and random errors (0.1±6.4, 0.3±3.9 and 0.6±3.6 mm in the LR, AP and SI directions, respectively). However, a relatively larger fraction (21.4%) of prostate patients had individual systematic offsets greater than 5mm. The overall systematic errors (1.3mm in LR, −2.7mm in AP and 0.6mm in SI) in breast patients were similar to the other two sites. However, significantly larger random setup errors (6.9mm in LR, 4.5mm in AP and 5.7mm in SI) were observed in breast patients. Conclusion: Our study showed that the systematic errors for all anatomic sites are all smaller than 3mm. However, relatively large systematic errors were observed in some individual patients. The random setup errors were found larger in breast patients than other two anatomic sites. These observations support that IGRT is an important and necessary tool in improving the patient setup accuracy.

Assessing the intrinsic precision of 3D/3D rigid image registration results for patient setup in the absence of a ground truth

To assess the precision and robustness of patient setup corrections computed from 3D/3D rigid registration methods using image intensity, when no ground truth validation is possible. Fifteen pairs of male pelvic CTs were rigidly registered using four different in-house registration methods. Registration results were compared for different resolutions and image content by varying the image down-sampling ratio and by thresholding out soft tissue to isolate bony landmarks. Intrinsic registration precision was investigated by comparing the different methods and by reversing the source and the target roles of the two images being registered. The translational reversibility errors for successful registrations ranged from 0.0 to 1.69 mm. Rotations were less than 1 degrees. Mutual information failed in most registrations that used only bony landmarks. The magnitude of the reversibility error was strongly correlated with the success/ failure of each algorithm to find the global minimum. Rigid image registrations have an intrinsic uncertainty and robustness that depends on the imaging modality, the registration algorithm, the image resolution, and the image content. In the absence of an absolute ground truth, the variation in the shifts calculated by several different methods provides a useful estimate of that uncertainty. The difference observed by reversing the source and target images can be used as an indication of robust convergence.

Evaluation of MVCT protocols for brain and head and neck tumor patients treated with helical tomotherapy

Purpose Helical tomotherapy is a modality of radiation treatment delivery which is equipped with an on-board imaging device (MVCT) allowing for daily patient set-up verification and correction in the medial–lateral (m–l), cranial–caudal (c–c), anterior–posterior (a–p) and transversal angular (roll) directions. In this study, we measured set-up deviations and evaluated different MVCT protocols for brain and head and neck (H&N) cancer patients. Materials and methods The daily set-up errors of 75 H&N cancer patients immobilized with 5-point fixation thermoplastic masks and 30 brain cancer patients immobilized with 3-point fixation thermoplastic masks were detected by matching the MVCT with the treatment planning CT images. This co-registration procedure was accomplished automatically by the system’s software (automatic deviations), then corrected manually by the radiation therapists (total deviations). Systematic and random errors were analyzed on a patient and a population basis. Moreover, 2 MVCT protocols were retrospectively evaluated; MVCTs were either acquired during the first five fractions (FFFs) or on alternate week (ALT). Systematic deviations were calculated based upon prior “MVCT” fractions and applied during the “non-MVCT” fractions. The resulting residual deviations were then analyzed. Results The total systematic (and random) deviations reached 1.7 mm (1.4 mm), 1.6 mm (1.5 mm), 1.5 mm (1.5 mm) and 0.6° (0.6°) for H&N cancer patients and reached 1.6 mm (0.9 mm), 1.7 mm (1.1 mm), 1.1 mm (0.8 mm) and 0.9° (0.6°) for brain cancer patients in the m–l, c–c, a–p and roll directions, respectively. A t-test detected small but statistically significant differences between the automatic and total deviations. Both MVCT protocols gave rise to similar residual deviations. However, for H&N cancer patients the ALT protocol resulted in smaller residual deviations and CTV-PTV margins, particularly in the a–p direction. Conclusion The total systematic and random deviations were comparable to the previously published data. No clinical difference exists between the automatic and total deviations. Both MVCT protocols were similar. But, for H&N cancer patients, the ALT protocol gave rise to smaller residual deviations and therefore is the correct formula to adopt in order to reduce the frequency of pre-treatment MVCTs.

Expected clinical impact of the differences between planned and delivered dose distributions in helical tomotherapy for treating head and neck cancer using helical megavoltage CT images.

Helical Tomotherapy (HT) has become increasingly popular over the past few years. However, its clinical efficacy and effectiveness continues to be investigated. Pre‐treatment patient repositioning in highly conformal image‐guided radiation therapy modalities is a prerequisite for reducing setup uncertainties. A MVCT image set has to be acquired to account for daily changes in the patient's internal anatomy and setup position. Furthermore, a comparison should be performed to the kVCT study used for dosimetric planning, by a registration process that results in repositioning the patient according to specific transitional and rotational shifts. Different image registration techniques may lead to different repositioning of the patient and, as a result, to varying delivered doses. This study aims to investigate the expected effect of patient setup correction using the Hi·Art TomoTherapy system by employing radiobiological measures such as the biologically effective uniform dose (D¯¯) and the complication‐free tumor control probability (P+). In this study, a typical case of lung cancer with metastatic head and neck disease was investigated by developing a Helical Tomotherapy plan. For the TomoTherapy Hi·Art plan, the dedicated tomotherapy treatment planning station was used. Three dose distributions (planned and delivered with and without patient setup correction) were compared based on radiobiological measures by using the P+ index and the D¯¯ concept as the common prescription point of the plans, and plotting the tissue response probabilities against the mean target dose for a range of prescription doses. The applied plan evaluation method shows that, in this cancer case, the planned and delivered dose distributions with and without patient setup correction give a P+ of 81.6%, 80.9% and 72.2%, for a D¯¯ to the planning target volume (PTV) of 78.0Gy, 77.7Gy and 75.4Gy, respectively. The corresponding tumor control probabilities are 86.3%, 85.1% and 75.1%, whereas the total complication probabilities are 4.64%, 4.20% and 2.89%, respectively. HT can encompass the often large PTV required while minimizing the volume of the organs at risk receiving high dose. However, the effectiveness of an HT treatment plan can be considerably deteriorated if an accurate patient setup system is not available. Taking into account the dose‐response relations of the irradiated tumors and normal tissues, a radiobiological treatment plan evaluation can be performed, which may provide a closer association of the delivered treatment with the clinical outcome. In such situations, for effective evaluation and comparison of different treatment plans, traditional dose based evaluation tools can be complemented by the use of P+−D¯¯ diagrams.PACS number: 87.55.Qr Quality assurance in radiotherapy

SU‐FF‐J‐73: Targeting Accuracy Using Exac‐Trac® and Synergy® CBCT Image‐Guided Radiotherapy Systems for Lung Stereotactic Body Radiotherapy

Purpose: To analyze the targeting accuracy using Exac‐Trac® (BrainLAB) and Synergy® CBCT (Elekta) systems for lung SBRT, and discuss the difference between these two IGRT systems. Methods: The target localization for lung patients treated with SBRT on Novalis® with Exac‐Trac® system and on Synergy® with CBCT system was analyzed. Prior to each treatment, patient's setup correction using Exac‐Trac® is performed by fusing (bone structure matching) two oblique x‐ray images with related DRRs computed from the planning CT, the correction using the CBCT system is by fusing (grey volume registration) CBCT with the planning CT. The position error is adjusted by shifting the table in lateral, longitudinal and vertical directions. If the shifted distance is >5mm in one direction, we usually repeat the image capturing and fusing procedures to double check the position error—the “second” shifting distance. In this study, we used the “second” shifting distance to analyze the targeting accuracy for both systems. Results: Sixteen and twenty‐nine setup correction cases were studied for Exac‐Trac® and Synergy® CBCT systems, respectively. The first shifted distances were in the ranges of 8.6–22.7mm and 3.5–18.3mm, with the average of 15.2mm and 8.2mm. The “second” shifting distances were in the ranges of 0.5–4.9mm and 0.6–3.4mm, with the averages of 2.8mm and 1.9mm, respectively. For both systems there was no correlation between the first shifted and the “second” shifting distances. The average position error after table shifting in Exac‐Trac® was larger than that in Synergy® CBCT system. We think the 3D volume registration is more practical or accurate than the 2D imaging matching for soft tissue localization. Conclusion: Using volume registration, Synergy® CBCT system is more accurate compared to Exac‐Trac® system in IGRT for lung SBRT. Detailed comparison and discussion of targeting accuracy for different tumor locations between the two systems will be reported.

SU-FF-T-606: Improvement of Patient Setups with Cone Beam CT Using Contour-Assisted Matching in Radiotherapy

Purpose: To improve consistency and efficiency of patient setups in image‐guidedradiotherapy using contour‐assisted image matching. Method and Materials: It is onerous to evaluate accuracy of image registration in the Elekta kV cone beam CT (CBCT)‐based patient setups due to lack of quantitative measures. A technique of automatic contour detection of bone and cavity structures was developed in the Philips Pinnacle3system. Contours of the structures with 2 mm (bone) to 3 mm (trachea and prostate seeds) expansion in each 3‐D direction were employed to evaluate image registration between planning CT and CBCT for patient setup correction. In the contour‐assisted matching, the image registration was performed such that all bony and cavity structures of CBCTimages were confined within contours of their structures with 2 mm and 3 mm expansion (3.4 mm and 5.1 mm in 3‐D) from the planning CT. 5 prostate, 3 head and neck, and 1 lung patients were selected for this study. Efficacy and efficiency of the contour‐assisted image registration was examined in terms of setup evaluation time and inter‐user variations in actual clinical environment. Results: The automatic contour detection of bone and cavity structures required additional 10 minutes during treatment planning, which was reasonably acceptable compared to the whole planning time. Initial setup verification by physicians with the contour‐assisted matching took generally no more than 5 minutes in actual clinical situations. Inter‐user variations were 1.1 ± 0.4 mm and 2.8 ± 1.0 mm for prostate and H&N cases, respectively. The expanded contours also provided a great quantitative tool to evaluate the registration accuracy with maximum 3.4 mm (2 mm expansion) and 5.1 mm (3 mm expansion) uncertainty in 3D space. Conclusion: The contour‐assisted image registration has high potential to improve efficiency of setup verification and reduce inter‐user variations of patient setup in image‐guidedradiotherapy.

Setup Uncertainties of Anatomical Sub-Regions in Head-and-Neck Cancer Patients After Offline CBCT Guidance

To quantify local geometrical uncertainties in anatomical sub-regions during radiotherapy for head-and-neck cancer patients. Local setup accuracy was analyzed for 38 patients, who had received intensity-modulated radiotherapy and were regularly scanned during treatment with cone beam computed tomography (CBCT) for offline patient setup correction. In addition to the clinically used large region of interest (ROI), we defined eight ROIs in the planning CT that contained rigid bony structures: the mandible, larynx, jugular notch, occiput bone, vertebrae C1-C3, C3-C5, and C5-C7, and the vertebrae caudal of C7. By local rigid registration to successive CBCT scans, the local setup accuracy of each ROI was determined and compared with the overall setup error assessed with the large ROI. Deformations were distinguished from rigid body movements by expressing movement relative to a reference ROI (vertebrae C1-C3). The offline patient setup correction protocol using the large ROI resulted in residual systematic errors (1 SD) within 1.2 mm and random errors within 1.5 mm for each direction. Local setup errors were larger, ranging from 1.1 to 3.4 mm (systematic) and 1.3 to 2.5 mm (random). Systematic deformations ranged from 0.4 mm near the reference C1-C3 to 3.8 mm for the larynx. Random deformations ranged from 0.5 to 3.6 mm. Head-and-neck cancer patients show considerable local setup variations, exceeding residual global patient setup uncertainty in an offline correction protocol. Current planning target volume margins may be inadequate to account for these uncertainties. We propose registration of multiple ROIs to drive correction protocols and adaptive radiotherapy to reduce the impact of local setup variations.

A Comprehensive Assessment by Tumor Site of Patient Setup Using Daily MVCT Imaging From More Than 3,800 Helical Tomotherapy Treatments

To assess patient setup corrections based on daily megavoltage CT (MVCT) imaging for four anatomic treatment sites treated on tomotherapy. Translational and rotational setup corrections, based on registration of daily MVCT to planning CT images, were analyzed for 1,179 brain and head and neck (H&N), 1,414 lung, and 1,274 prostate treatment fractions. Frequencies of three-dimensional vector lengths, overall distributions of setup corrections, and patient-specific distributions of random and systematic setup errors were analyzed. Brain and H&N had lower magnitude positioning corrections and smaller variations in translational setup errors but were comparable in roll rotations. Three-dimensional vector translational shifts of larger magnitudes occurred more frequently for lung and prostate than for brain and H&N treatments, yet this was not observed for roll rotations. The global systematic error for prostate was 4.7 mm in the vertical direction, most likely due to couch sag caused by large couch extension distances. Variations in systematic errors and magnitudes of random translational errors ranged from 1.6 to 2.6 mm for brain and H&N and 3.2 to 7.2 mm for lung and prostate, whereas roll rotational errors ranged from 0.8 degrees to 1.2 degrees for brain and H&N and 0.5 degrees to 1.0 degrees for lung and prostate. Differences in setup were observed between brain, H&N, lung, and prostate treatments. Patient setup can be improved if daily imaging is performed. This analysis can assess the utilization of daily image guidance and allows for further investigation into improved anatomic site-specific and patient-specific treatments.

Patient Setup Correction in Treating Head and Neck Cancer with Helical Tomotherapy

To use radiobiological measures in order to quantify the differences between highly conformal planned dose distributions and their delivered dose distributions with and without patient setup correction. Helical Tomotherapy (HT) was employed using the Helical Megavoltage CT (MVCT) scanner of the tomotherapy unit to investigate the expected impact of the dose delivery differences.

A Statistical Framework for the Assessment of Surrogates for Patient Setup Correction in Radiotherapy

A Statistical Framework for the Assessment of Surrogates for Patient Setup Correction in Radiotherapy

Sci-Thurs PM: Delivery-11: Image guidance for prostate IMRT using low dose cone beam CT.

Linac-mounted cone beam computed tomography (CBCT) using Varian's On Board Imager (OBI) currently delivers significant imaging dose and lacks automatic methods for clinical target volume (CTV) registration. In this work, we address these two issues to enable frequent treatment corrections during a course of prostate intensity modulated radiation therapy (IMRT). The process starts by acquiring a low dose (low mAs) CBCT image after patient setup. The image is then used in one of two automatic image guidance strategies. The "global" technique provides the couch corrections necessary to improve patient setup by registering the CBCT to the planning CT. The "local" method involves non-rigid registration of the planning CT to the CBCT followed by automatic treatment re-optimization using the deformed planning CT and contours. Thus, the global method attempts to correct patient setup to match the planned treatment, while the local method corrects the treatment to match the patient setup. Both techniques were evaluated using images of an anthropomorphic male pelvis phantom. Global image guidance resulted in a registration error of 3.6 ± 1.3 mm (imaging dose independent) and high treatment doses to the bladder and rectum for large magnitude motion. The local technique always resulted in clinically acceptable treatment doses due to a reduced registration error of 2.3 ± 0.8 mm, obtained at 15% of the OBI's default dose (125 kVp, 2 mAs per projection). These preliminary results show that our automatic local image guidance technique reduces imaging dose and is sufficiently accurate and robust for application in prostate IMRT.

WE-C-AUD C-07: Expected Clinical Impact of the Differences Between Planned and Delivered Dose Distributions in Helical Tomotherapy

Purpose: To investigate the effectiveness of highly conformal radiation modalities in conjunction with a patient setup correction method, Helical Tomotherapy (HT) was employed using the Helical Megavoltage CT (MVCT) scanner of the tomotherapy unit. Any discrepancy between the planned and delivered dose distributions would likely affect the clinical outcome. Method and Materials: The case of a head and neck cancer was used to evaluate the accuracy of dose delivery. The right parotid, left parotid and spinal cord are the primary organs at risk proximal to the target volume. MVCT images were taken before and after the patient setup correction. MVCT images of the patient were acquired daily. The three dose distributions (planned, with and without patient setup correction) were compared by using the complication‐free tumor control probability (P +) and the biologically effective uniform dose (BEUD) concepts. Results: For the computerized treatment plan, the maximum value of P + is 88.3%, the total control probability, P B is 97.3% and the total risk for complications, P I is 9.3%. For the delivered dose distribution without patient setup correction, the value of P + is 79.8% and the probabilities P B and P I are 83.6% and 3.8%, respectively. Finally, for the delivered dose distribution with patient setup correction in every fraction the value of P + is 87.2% and the probabilities P B and P I are 92.7% and 5.5%, respectively. The expected clinical effectiveness dropped by a ΔP + of 1.1% and 8.5% in the cases with and without patient setup correction. Conclusion: Highly conformal treatment plans can deliver higher doses to the target allowing for increased control rates for the same or a reduced risk for complications. The results show that the effectiveness of the applied dose distribution drops between the treatment plan and the dose delivery with and without patient setup correction.

SU‐GG‐T‐430: Radiobiological Investigation of the Dosimetric Effects of Daily Megavoltage CT Registration Techniques On Adaptive Radiotherapy with Helical Tomotherapy

Purpose: Pre‐treatment patient repositioning in highly conformal radiotherapy modalities is a prerequisite for reducing setup uncertainties. A MVCT image set has to be acquired to account for daily changes in the patient's internal anatomy and setup position. This study aims to investigate the expected effect of patient setup correction with the Hi‐Art tomotherapy system by using radiobiological measures. Method and Materials: Using the Planned Adaptive module (tomotherapy, Inc, Madison, WI), eventual dose discrepancies can be evaluated and corrected. In this study, patients treated for lung, pancreas and prostate carcinomas by Helical Tomotherapy plans are evaluated. In each cancer case, two dose distributions with and without patient setup correction were calculated using the MVCT image sets and they were evaluated using the complication‐free tumor control probability (P+) and biologically effective uniform dose (BEUD) concepts. Results: For the lung cancer case, at the optimum dose levels of the two dose distributions, the P+ value is 57.6% and 56.8% for a BEUDITV of 64.8 Gy, respectively. The respective total control probabilities, PB are 78.1% and 78.1%, whereas the corresponding total complication probabilities, PI are 20.5% and 21.3%. For the pancrease cancer case, the P+ value is 95.0% for a BEUDITV of 67.9 Gy and 97.5% for a BEUDITV of 69.9 Gy, respectively. The respective PB values are 97.8% and 98.7%, whereas the PI values are 2.9% and 1.2%. For the prostate cancer case, the P+ value is 57.7% for a BEUDITV of 90.2 Gy and 55.9% for a BEUDITV of 90.6 Gy, respectively. The respective PB values are 83.7% and 84.7%, whereas the PI values are 26.1% and 28.8%. Conclusion: According to our results, patient setup corrections during registration are adequate to produce the necessary target localization. Clinical cases, which look dosimetrically similar, can be quite different in radiobiological terms.

SU‐GG‐J‐74: Dose Guided Patient Setup Improvement for Head‐And‐Neck Cancer IMRT Using Cone‐Beam CT

Purpose: Accurate dose delivery for H&N IMRT is often compromised by changes in patient anatomy and setup. Verification of setup parameters that have a significant impact on dose delivery presents difficult QA problems. In this work a method was developed to monitor the dose delivery using daily cone beam CT. Method and Materials: A virtual simulation procedure was developed to assure the region of interest is inside the field of view of cone beam CT. The treatment isocenter was placed accordingly for collision‐free patient imaging and treatment. The prescribed isodose surface and other levels of interest in the approved IMRT plan were extracted as auxiliary structures for reference. Patient setup correction was based on vertebral body matching first. Subsequently skin matching between cone beam CT and reference CT was checked. An action level based on phantom studies was established for patient external surface mismatch. Results: Patient external surfaces with beam intersections were acquired by planning on the region of interest for imaging, critical for calculating the delivered dose. The isodose surface shift due to mismatch of external surfaces could be estimated based on the beam path length, and this could affect the correction of patient setup. Repositioning of patient setup was required when an over 2 cm mismatch of external surfaces in any part of beam intersection was observed, which would result in an over 3% change in dose to PTV and critical structures. Conclusion: Planning on the imaging volume is a key step to optimize the clinical workflow for geometric and dosimetric verification using cone beam CT. Displaying planned isodose surfaces is useful for patient setup correction. By imaging the patient's external surface we can monitor the delivery of the planned dose distribution and decide when re‐planning is necessary.