Cine Mode Research Articles

Automatic marker detection and 3D position reconstruction using cine EPID images for SBRT verification

In previous studies, an electronic portal imaging device (EPID) in cine mode was used for validating respiratory gating and stereotactic body radiation therapy (SBRT) by tracking implanted fiducials. The manual marker tracking methods that were used were time and labor intensive, limiting the utility of the validation. The authors have developed an automatic algorithm to quickly and accurately extract the markers in EPID images and reconstruct their 3D positions. Studies have been performed with gold fiducials placed in solid water and dynamic thorax phantoms. In addition, the authors have examined the cases of five patients being treated under an SBRT protocol for hepatic metastases. For each case, a sequence of images was created by collecting the exit radiation using the EPID. The markers were detected and recognized using an image processing algorithm based on the Laplacian of Gaussian function. To reduce false marker detection, a marker registration technique was applied using image intensity as well as the geometric spatial transformations between the reference marker positions produced from the projection of 3D CT images and the estimated marker positions. An average marker position in 3D was reconstructed by backprojecting, towards the source, the position of each marker on the 2D image plane. From the static phantom study, spatial accuracies of <1 mm were achieved in both 2D and 3D marker locations. From the dynamic phantom study, using only the Laplacian of the Gaussian algorithm, the marker detection success rate was 88.8%. However, adding a marker registration technique which utilizes prior CT information, the detection success rate was increased to 100%. From the SBRT patient study, intrafractional tumor motion (3.1-11.3 mm) in the SI direction was measured using the 2D images. The interfractional patient setup errors (0.1-12.7 mm) in the SI, AP, and LR directions were obtained from the average marker locations reconstructed in 3D and compared to the reference planning CT image. The authors have developed an automatic algorithm to extract marker locations from MV images and have evaluated its performance. The measured intrafractional tumor motion and the interfractional daily patient setup error can be used for off-line retrospective verification of SBRT.

Image-Guided Radiotherapy in Near Real Time With Intensity-Modulated Radiotherapy Megavoltage Treatment Beam Imaging

To utilize image-guided radiotherapy (IGRT) in near real time by obtaining and evaluating the online positions of implanted fiducials from continuous electronic portal imaging device (EPID) imaging of prostate intensity-modulated radiotherapy (IMRT) delivery. Upon initial setup using two orthogonal images, the three-dimensional (3D) positions of all implanted fiducial markers are obtained, and their expected two-dimensional (2D) locations in the beam's-eye-view (BEV) projection are calculated for each treatment field. During IMRT beam delivery, EPID images of the megavoltage treatment beam are acquired in cine mode and subsequently analyzed to locate 2D locations of fiducials in the BEV. Simultaneously, 3D positions are estimated according to the current EPID image, information from the setup portal images, and images acquired at other gantry angles (the completed treatment fields). The measured 2D and 3D positions of each fiducial are compared with their expected 2D and 3D setup positions, respectively. Any displacements larger than a predefined tolerance may cause the treatment system to suspend the beam delivery and direct the therapists to reposition the patient. Phantom studies indicate that the accuracy of 2D BEV and 3D tracking are better than 1 mm and 1.4 mm, respectively. A total of 7330 images from prostate treatments were acquired and analyzed, showing a maximum 2D displacement of 6.7 mm and a maximum 3D displacement of 6.9 mm over 34 fractions. This EPID-based, real-time IGRT method can be implemented on any external beam machine with portal imaging capabilities without purchasing any additional equipment, and there is no extra dose delivered to the patient.

Comparison of Respiratory-Gated and Respiratory-Ungated Planning in Scattered Carbon Ion Beam Treatment of the Pancreas Using Four-Dimensional Computed Tomography

We compared respiratory-gated and respiratory-ungated treatment strategies using four-dimensional (4D) scattered carbon ion beam distribution in pancreatic 4D computed tomography (CT) datasets. Seven inpatients with pancreatic tumors underwent 4DCT scanning under free-breathing conditions using a rapidly rotating cone-beam CT, which was integrated with a 256-slice detector, in cine mode. Two types of bolus for gated and ungated treatment were designed to cover the planning target volume (PTV) using 4DCT datasets in a 30% duty cycle around exhalation and a single respiratory cycle, respectively. Carbon ion beam distribution for each strategy was calculated as a function of respiratory phase by applying the compensating bolus to 4DCT at the respective phases. Smearing was not applied to the bolus, but consideration was given to drill diameter. The accumulated dose distributions were calculated by applying deformable registration and calculating the dose-volume histogram. Doses to normal tissues in gated treatment were minimized mainly on the inferior aspect, which thereby minimized excessive doses to normal tissues. Over 95% of the dose, however, was delivered to the clinical target volume at all phases for both treatment strategies. Maximum doses to the duodenum and pancreas averaged across all patients were 43.1/43.1 GyE (ungated/gated) and 43.2/43.2 GyE (ungated/gated), respectively. Although gated treatment minimized excessive dosing to normal tissue, the difference between treatment strategies was small. Respiratory gating may not always be required in pancreatic treatment as long as dose distribution is assessed. Any application of our results to clinical use should be undertaken only after discussion with oncologists, particularly with regard to radiotherapy combined with chemotherapy.

4D CT sorting based on patient internal anatomy

Respiratory motion during free-breathing computed tomography (CT) scan may cause significant errors in target definition for tumors in the thorax and upper abdomen. A four-dimensional (4D) CT technique has been widely used for treatment simulation of thoracic and abdominal cancer radiotherapy. The current 4D CT techniques require retrospective sorting of the reconstructed CT slices oversampled at the same couch position. Most sorting methods depend on external surrogates of respiratory motion recorded by extra instruments. However, respiratory signals obtained from these external surrogates may not always accurately represent the internal target motion, especially when irregular breathing patterns occur. We have proposed a new sorting method based on multiple internal anatomical features for multi-slice CT scan acquired in the cine mode. Four features are analyzed in this study, including the air content, lung area, lung density and body area. We use a measure called spatial coherence to select the optimal internal feature at each couch position and to generate the respiratory signals for 4D CT sorting. The proposed method has been evaluated for ten cancer patients (eight with thoracic cancer and two with abdominal cancer). For nine patients, the respiratory signals generated from the combined internal features are well correlated to those from external surrogates recorded by the real-time position management (RPM) system (average correlation: 0.95 ± 0.02), which is better than any individual internal measures at 95% confidence level. For these nine patients, the 4D CT images sorted by the combined internal features are almost identical to those sorted by the RPM signal. For one patient with an irregular breathing pattern, the respiratory signals given by the combined internal features do not correlate well with those from RPM (correlation: 0.68 ± 0.42). In this case, the 4D CT image sorted by our method presents fewer artifacts than that from the RPM signal. Our 4D CT internal sorting method eliminates the need of externally recorded surrogates of respiratory motion. It is an automatic, accurate, robust, cost efficient and yet simple method and therefore can be readily implemented in clinical settings.

Effect of Breathing Motion in Radiotherapy of Breast Cancer

To evaluate the influence of breathing motion in postoperative whole-breast radiotherapy. For ten patients with left-sided breast cancer, radiotherapy treatment plans were generated based on conventional three-dimensional computed tomography (3D CT) studies: two techniques (segmented and wedge-based tangential fields) were compared. The influence of breathing motion on the dose to the target and organs at risk (OARs) was evaluated with four-dimensional (4D) dose calculation based on respiration-correlated CTs. Reproducibility of breathing motion was evaluated with electronic portal images (EPID) acquired in cine mode during treatment. Differences in dose distributions were small between segmented and wedge techniques based on 3D studies. Because of small motion amplitude of the chest in the 4D CT studies (1.8 mm +/- 0.9 mm), target coverage was reduced by < 5% due to breathing motion. Differences between 3D and 4D dose calculation were similar for segmented and wedge techniques. Blurring of the dose distribution in 4D dose calculation resulted in lower doses to the OARs. Analysis of EPID movies proved good reproducibility of breathing motion observed in the 4D CT study. Breathing motion was of minor relevance in postoperative radiotherapy treatment of breast cancer for both segmented and wedge tangential field techniques.

SU‐FF‐J‐67: Marker‐Less Verification of Respiratory‐Gated Radiotherapy for Lung Cancer

Purpose: To maximize the potential benefit of respiratory gating for lung tumors, a method of image‐guided verification is necessary. We propose using the MV EPID in cine mode during respiratory‐gated radiotherapy to verify the location of the tumor without the aid of implanted fiducials. Method and Materials: The verification procedure to be studied is as follows: prior to each fraction of gated radiation therapy, a gated radiograph is acquired for each of the therapy beam angles. This reference image is then compared to cine EPID images acquired during respiratory‐gated radiotherapy. The target can be visualized in the images and the deviation from the reference position calculated. Phantom studies were performed using a dynamic phantom and internal respiratory traces derived from patients undergoing lung SBRT treatments. Setup images were taken when the external surrogate signal was in the reference (exhale) position and gated radiotherapy was simulated using clinically realistic fields. The reference and treatment images were loaded into offline research software and the location of the target relative to the reference was calculated using a template matching algorithm. Clinical patient data has also been used to demonstrate the feasibility of the technique for an oblique treatment beam. Results: Preliminary phantom and clinical studies demonstrate that the target can be tracked through a series of MV cine EPID images. From both studies, accuracy was assessed to be better than 1 mm. Conclusion: A procedure for confirming the target location during lung cancer respiratory‐gated radiotherapy without the aid of internal fiducials has been defined. Although the proposed procedure is demonstrated retrospectively, in principle, in could be performed in real‐time.Conflict of interest: Research funded, in part, by Varian Medical Systems, Inc.

SU‐FF‐I‐33: Evaluation of Z‐Axis Resolution for Axial and Helical Scanning Modes On MDCT

Purpose: To evaluate Z‐axis resolution for axial and low pitch helical scanning modes on a multi‐detector CT (MDCT). Axial scanning, performed in a cine mode, and helical scanning are both presently used to acquire 4D‐CT data sets. Method and Materials: The slice sensitivity profile (SSP) is considered as an indicator of Z‐axis resolution. The CT‐SSP Phantom (Model 76‐412, Fluke Biomedical) was used. The scans were performed on a Philip's Brilliance Big Bore 16 slice scanner. The phantom was scanned at incremental distances from the CT isocenter from 0mm to 200mm. The 16×1.5mm collimation mode, standard resolution and standard recon filter were used for both helical and axial modes. For helical scans, the pitch was varied between 0.04 and 0.08. The slices were reconstructed at 0.2mm increments. For axial mode, a 0.5mm increment was used. The effective slice thickness or Z‐axis resolution was calculated as the full width at half maximum (FWHM) of the SSP. Results: For helical scan modes, the measured slice thickness remained below 2mm for all points in the X/Y plane. In axial mode, the FWHM of the SSP plot was 1.5 +/−0.3mm with the phantom well centered. At 20cm from the CT isocenter, the measured Z‐axis resolution was close to 5.0mm. Conclusions: When imaging with high Z‐axis resolution is required, axial mode scanning should be utilized when the region of interest is small and the patient is well centered within CT gantry. For scans where Z‐axis resolution must be maintained over a large area, helical mode scanning would be preferred. When performing 4D‐CT using cine axial scans, the Z‐axis resolution can be compromised near the periphery of the imaging plane.

TU-D-304A-09: Evaluation of Localization Accuracy of Motion in 4DCT

Purpose: To develop a method and corresponding analysis tool to accurately evaluate the performance of 4DCT in localizing moving objects and to verify the correlation between motion characterization and the respiratory curve. Methods: Several radio opaque markers were affixed to the surface of a Varian Real‐time Positioning Management (RPM) infrared reflective block which was mounted on a moving platform. One of the markers was located right between the two infrared reflective markers of the RPM block. The CTimages of the moving system were acquired with a GE Discovery STEscanner in cine mode. GE Advantage4D was applied to create phased images by dividing the motion cycle into 10 bins. A software tool was developed to process the phased image sets and an algorithm was developed to find the number of markers and to analyze the most probable location of each marker. The motion amplitude was compared with the respiratory curve as recorded by the RPM system during imaging.Results: The multiple markers were identified from the 4DCT image sets simultaneously by the model algorithm. Their phase motion matches the recording of the RPM infrared sensor in both pattern and magnitude. The positioning error of the procedure is <0.5 mm along lateral directions, and 2.5mm along sup‐inf direction, which is within the scope of the image acquisition setup. Conclusion: Tracking multiple point‐like fiducials provides an accurate and efficient means of evaluating the localization performance in 4DCT images. Phantom studies have validated the 4DCT performance in imaging moving object. The method and tool developed in this work can be useful for radiation therapy target margin study and imaging QA alike.

SU‐EE‐A4‐04: Evaluation of Two Optical Systems for Respiratory Sensing in 4DCT

Purpose:. The purpose of this study is to assess the temporal and reconstruction accuracy of two different optical systems for respiratory motion detection for 4DCT. Materials and methods: A clinical CT scanner, run in cine mode, was used with two optical devices, the Gate CT®, (Vision RT, London, UK) and the RPM® (Varian, Palo Alto, CA), to detect respiratory motion. A radiation detector, GM‐10 (Blackcat, Westminster, MD), triggers the Xray on/off to Gate CT system, while the RPM is directly synchronized with the CT scanner through an electronic connection. Two phantoms were imaged: the first phantom translated a rigid plate along the antero‐posterior direction, and was used to assess the temporal synchronization of each optical system with the CT scanner. The second phantom consisted of 4 spheres that translated 3cm peak‐to‐peak in the superior inferior direction, used to assess the rebinned images created by Gate CT and RPM. Results: Calibration assessment showed a nearly perfect synchronization with the scanner for both the RPM and Gate CT systems, thus demonstrating the good performance of the radiation detector. Results for the volume rebinding test showed a variations in volumes for the 3D reconstruction of up to 15% for Gate CT and up to 12% for RPM. The mean of the standard deviations errors were 11% and 9% respectively. Errors are mainly due to phase detection inaccuracies and to the large motion of the phantom. Conclusions: This feasibility study assessed the consistency of our two optical systems in synchronizing the respiratory signal with the image acquisition. A new patient protocol based on both RPM and GateCT will be soon started.

TH‐C‐303A‐09: 4D CT Sorting Based On Patient Internal Anatomy

Purpose: To obtain a robust 4D CT sorting algorithm based on patient internal anatomy by combining multiple respiratory features and to compare with sorting algorithms based on external surrogates. Method and Materials: A four‐slice GE LightSpeed™ CT scanner was used to acquire the CT data in cine mode and respiratory signals were synchronously recorded by the Varian RPM system for comparison purposes. To generate respiratory signals directly from the axial CT images, five respiratory features have been evaluated, namely, air content, body area, lung volume, conditional mean with threshold and conditional mean with percentile. For each four‐slice couch position, a quantitative measure called spatial coherence was used to select the optimal internal features for generation of respiratory phases for slice sorting, which, along with the sorted CT images were compared with those obtained from RPM, respectively. Results: Patient studies showed that the respiratory signals generated from internal features are similar to RPM signals for patients with regular breathing patterns (average correlation with RPM signals at all couch positions is above 0.92 in 9 out of 10 patients) and result in sorted images with fewer motion artifacts for patients who exhibited relatively irregular breathing patterns. Conclusion: This work demonstrates the feasibility and potential benefits of using internal anatomy for 4D CT sorting in thoracic and abdominal cancer patients. The sorting results are similar to those obtained with RPM signals for regular breathing patterns and better when irregular ones occur. The proposed algorithm is simple and robust, which makes it amenable for clinical implementation. In the future, alternative measures for the quality of respiratory signals may be investigated in the temporal domain, e.g., smoothness. In parallel, other useful respiratory features may be combined easily with existing ones for better accuracy and more robustness.

SU‐FF‐I‐10: Evaluation of a Generalized Contrast Enhancement Protocol for 4D‐CT Imaging of Liver Tumors

Purpose: Intravenous contrast is needed to enhance tumor visibility in the liver. Unfortunately, conventional diagnostic CT protocols cannot be used due to the extended acquisition time required. We present results of a generalized contrast enhancement protocol for 4D‐CT imaging of liver tumors. Method and Materials: 92 patients (metastases: 39, cholangiocarcinomas: 44 hepatocellular carcinomas: 9) were enrolled in the study. All 4D‐CT images were acquired on a GE Discovery ST PET/CT scanner in cine mode. 150 mL of intravenous contrast was delivered at a rate 5 mL/s. Liver metastases and cholangiocarcinomas were imaged in the portal venous phase with a delay of 45 seconds while hepatocellular carcinomas were imaged in the delayed phase at 270 seconds. A region of interest inside and outside of the tumor was created, and the average CT numbers were analyzed. Results: The protocol produced enhancement of greater than 35 CT numbers in 72% of patients with liver metastases and cholangiocarcinomas and 44% in patients with hepatocellular carcinomas. The image quality of the metastases and cholangiocarcinomas patients was improved considerably (vessels and the tumor borders could be more easily distinguished) but modest improvement was detected in hepatocellular carcinomas. Tumor contrast enhancement was not directly correlated with body surface area, but rather with the inherent contrast of the tumor. Average absolute delay time of tumor imaging was 70 seconds for cholangiocarcinomas (σ=15 s) and 66 seconds for metastases (σ=13 s). In this range the degree of enhancement in metastases was more sensitive to the absolute delay time compared to the cholangiocarcinomas and for longer delays less contrast enhancement was observed. Conclusion: The protocol works well for the majority of patients with cholangiocarcinomas and liver metastases. For tumors located well below the dome of the liver, a reduction in delay time may enhance tumor visibility.

SU‐DD‐A3‐06: Fully Automated Internal Marker Tracking Algorithm for Cine EPID Images

Introduction: An electronic portal imaging device (EPID) in cine mode can be used for validating respiratory gating and stereotactic body radiation therapy (SBRT) by tracking implanted fiducials. Manual tracking methods are time and labor intensive, limiting the utility of the validation. We have developed a fully automated algorithm to quickly and accurately extract the markers in EPID images and reconstruct their 3D positions. Materials and Methods: The markers were detected and recognized using an image processing algorithm based on the Laplacian of Gaussian (LoG) filter. To reduce false marker detection, a marker registration technique was applied using image intensity as well as the geometric spatial transformations between the reference marker positions produced from the projection of 3D CT images and the estimated marker positions. An average marker position in 3D was reconstructed by backprojecting, towards the source, the position of each marker on the 2D image. Results: From phantom studies, spatial accuracies of &lt;1 mm were achieved in both 2D and 3D marker locations. Using only the LoG algorithm, the marker detection success rate was 88.8%. However, adding the registration technique which utilizes prior CT information, the success rate was increased to 100%. In addition, we have examined the cases of 5 patients being treated under an SBRT protocol for hepatic metastases. The intrafractional tumor motion (3.1–11.3 mm) in the SI direction was measured using the 2D images. The interfractional patient setup errors (0.1–12.7 mm) in the SI, AP, and LR directions were obtained from the marker locations reconstructed in 3D and compared to the reference planning CT image. Conclusions: The measured intrafractional tumor motion and the interfractional daily patient setup error can be used for off‐line retrospective verification of SBRT.This work was partially supported by a grant from Varian Medical Systems, Inc.

TU-D-304A-05: An Improved Phase-Based 4DCT Reconstruction Using Local Breathing Variation Without RPM

Purpose: To develop a 4DCT sorting method based on the 2DCT breathing volume variation. Method and Materials: Current 4DCT techniques require an external surrogate (e.g., the Varian RPM system) to retrospectively sort 2DCT slices. Artifacts are often observed due to the imperfect correlation between the RPM and breathing motion. Our new method uses local breathing volume variations at each scan position as a surrogate. Six patients with severe 4DCT artifacts based on RPM sorting were retrospectively studied. These patients acquired 22–26 scans per couch position using a 16-slice CT scanner operated in Cine mode. For each couch position, the patient body contour was segmented using thresholding and region growing. The number of the pixels inside the body contour was counted as breathing volume, indicating the current breathing phase. For each scan position, standard respiratory phases were generated based on the nearest breathing volumes. 4DCT sorting was accomplished using CT images at the standard breathing phases. Results: For 6 patients studied, 4DCT images sorted from the RPM and our method were reviewed by experts. Most artifacts observed in RPM based 4DCT were removed by our method especially near the diaphragm and regions where the RPM signal was less correlated. For one patient, the RPM showed irregular breathing for one slice position resulting in severe artifacts in reconstructed 4DCT. However, local volume variation indicated regular breathing and the reconstructed 4DCT images were artifact free using our new method. For some scan positions where large irregular breathing occurred, our method, as well as the RPM method, did not work well and a rescan was recommended. Conclusion: The proposed sorting method provides a highly correlated individual respiratory signal for each scan position. The proposed method has the advantages of (1) significantly reduced 4DCT artifacts, (2) without RPM and (3) without complex organ segmentation.

SU-FF-J-111: On the Estimation of Error in 4D Imaging in Regard to Radiotherapy Tumor Motion Management

Purpose: To quantify the accuracy of 4D‐CT as it relates to radiotherapy motion management techniques, specifically determination of tumor motion trajectory (x,y,z)(t), tumor motion envelope, and delineation of the GTV throughout 4D datasets. Methods: An ideal motion tracking configuration was created with a Standard Imaging Respiratory Gating Platform and four glass marbles of various diameter suspended in polyurethane foam. 4D‐CT images were acquired for motion periods and displacements ranging from 3 – 6 s and 1 – 3 cm, respectively. Phase binned 4D images were acquired with a 4‐slice GE LightSpeed CT scanner and RPM tracking system. Scans were performed in cine mode with a 2.5 mm slice thickness and a 0.4 s gantry rotation. Cine mode duration for each scanning position was performed for at least one gantry rotation greater than the phantom motion period. Marbles were autocontoured at −500, 0, 500, 1000, and 1500 HU in all ten phases of the nine total 4DCT image sets. Centroid positions were determined for each auto‐contour threshold. Actual motion trajectories were recorded to compare to the observed. Results: Maximum errors in tumor position throughout a given motion trajectory ranged from 1 – 4 mm. The observed errors showed an inverse relationship with the auto‐contour HU threshold used and a direct relationship with the phantom velocity. Motion envelope underestimations ranged from 0 – 7 mm with the highest CT threshold auto‐contour resulting in the largest error. Conformality indices were also determined for each contoured marble throughout all 4D image sets. Conclusion: Considerable errors in the definition of tumor trajectory and the motion envelope were observed in an idealized motion phantom using clinical imaging acquisition parameters and realistic tumor motion settings. Methods defined are useful in quantifying errors associated with 4D imaging modalities as they relate to radiotherapy motion management. Research supported by Philips Medical Systems.

SU‐FF‐J‐52: Towards On‐Line Treatment Verification Using Cine EPID Images for Hypofractionated Lung IMRT

Purpose: To develop a computational algorithm based on an artificial neural network (ANN) that allows treatment verification using an EPID in cine mode for hypofractionated lung IMRT. Method and Materials: We developed a novel ANN based technique that can extract tumor information from cine EPID images of each segment in an IMRT field and verify that we are treating the planned treatment area. We simulated training images for ANN using DRRs, by shifting DRRs relative to the beam aperture of the segment. We also carefully related each segment to the entire IMRT field in terms of tumor location. With a pre‐defined threshold p%, we associated category 1 to the training image if more than p% of the tumor projection in the beam eye view was in the corresponding entire treatment field of the training image, and category −1 otherwise. The trained network could therefore analyze the cine EPID images of IMRT segments obtained during the treatment and classify them into the corresponding category 1 or −1. Results: Two patients were included in our feasibility study. A radiation oncologist read the cine EPID images and classified them into category 1 or −1; this served as our ground truth. The ANN was applied to the training images to build the neural network. We set p% = 95% for this study. For each IMRT segment, one neural network needed to be built. Averaging over both patients and all segments, the trained network successfully classified 97% of the cine EPID images. Conclusion: We are the first who can analyze cine EPID images of hypofractionated lung IMRT without implanted fiducial markers. The proposed technique provides an important clinical safeguard—whenever the planned treatment area moves out of the irradiation segment, the treatment beam can be interrupted, so that radiation won't be unnecessarily delivered to normal tissues.

Respiratory gating with EPID-based verification: the MDACC experience

We have investigated the feasibility and accuracy of using a combination of internal and external fiducials for respiratory-gated image-guided radiotherapy of liver tumors after screening for suitable patients using a mock treatment. Five patients were enrolled in the study. Radio-opaque fiducials implanted adjacent to the liver tumor were used for daily online positioning using either electronic portal or kV images. Patient eligibility was assessed by determining the degree of correlation between the external and internal fiducials as analyzed during a mock treatment. Treatment delivery was based on the modification of conventional amplitude-based gating. Finally, the accuracy of respiratory-gated treatment using an external fiducial was verified offline using the cine mode of an electronic portal imaging device. For all patients, interfractional contribution to the random error was 2.0 mm in the supero-inferior direction, which is the dominant direction of motion due to respiration, while the interfractional contribution to the systematic error was 0.9 mm. The intrafractional contribution to the random error was 1.0 mm. One of the significant advantages to this technique is improved patient set-up using implanted fiducials and gated imaging. Daily assessment of images acquired during treatment verifies the accuracy of the delivered treatment and uncovers problems in patient set-up.

Impact of motion velocity on four‐dimensional target volumes: A phantom study

This study aims to assess the impact of motion velocity that may cause motion artifacts on target volumes (TVs) using a one-dimensional moving phantom. A 20 mm diameter spherical object embedded in a QUASAR phantom sinusoidally moved with approximately 5.0 or 10.0 mm amplitude (A) along the longitudinal axis of the computed tomography (CT) couch. The motion period was manually set in the range of 2.0-10.0 s at approximately 2.0 s interval. Four-dimensional (4D) CT images were acquired by a four-slice CT scanner (LightSpeed RT; General Electric Medical Systems, Waukesha, WI) with a slice thickness of 1.25 mm in axial cine mode. The minimum gantry rotation of 1.0 s was employed to achieve the maximum in-slice temporal resolution. Projection data over a full gantry rotation (1.0 s) were used for image reconstruction. Reflective marker position was recorded by the real-time positioning management system (Varian Medical Systems, Palo Alto, CA). ADVANTAGE 4D software exported ten respiratory phase volumes and the maximum intensity volume generated from all reconstructed data (MIV). The threshold to obtain static object volume (V0, 4.19 ml) was used to automatically segment TVs on CT images, and then the union of TVs on 4D CT images (TV(4D)) was constructed. TVs on MIV (TV(MIV)) were also segmented by the threshold that can determine the area occupied within the central slice of TV(MIV). The maximum motion velocity for each phase bin was calculated using the actual averaged motion period displayed on ADVANTAGE 4D software (T), the range of phases used to construct the target phase bin (phase range), and a mathematical model of sinusoidal function. Each volume size and the motion range of TV in the cranial-caudal (CC) direction were measured. Subsequently, cross-correlation coefficients between TV size and motion velocity as well as phase range were calculated. Both misalignment and motion-blurring artifacts were caused by high motion velocity, Less than 6% phase range was needed to construct the 4D CT data set, except for T of 2.0 s. While the positional differences between the TV and ideal centroid in the CC direction were within the voxel size for T > or = 6.0 s, the differences were up to 2.43 and 4.15 mm for (A,T) = (5.0 mm, 2.0 s) and (10.0 mm, 2.0 s), respectively. The maximum volumetric deviations between TV sizes and V0 were 43.68% and 91.41% for A of 5.0 and 10.0 mm, respectively. TV(MIV) sizes were slightly larger than TV(4D) sizes. Volumetric deviation between TV size and V0 had a stronger correlation with motion velocity rather than phase range. This phantom study demonstrated that motion artifacts were substantially reduced when the phantom moved longitudinally at low motion velocity during 4D CT image acquisition; therefore, geometrical uncertainties due to motion artifacts should be recognized when determining TVs, especially with a fast period.

Retrospective data-driven respiratory gating for PET/CT

Respiratory motion can adversely affect both PET and CT acquisitions. Respiratory gating allows an acquisition to be divided into a series of motion-reduced bins according to the respiratory signal, which is typically hardware acquired. In order that the effects of motion can potentially be corrected for, we have developed a novel, automatic, data-driven gating method which retrospectively derives the respiratory signal from the acquired PET and CT data. PET data are acquired in listmode and analysed in sinogram space, and CT data are acquired in cine mode and analysed in image space. Spectral analysis is used to identify regions within the CT and PET data which are subject to respiratory motion, and the variation of counts within these regions is used to estimate the respiratory signal. Amplitude binning is then used to create motion-reduced PET and CT frames. The method was demonstrated with four patient datasets acquired on a 4-slice PET/CT system. To assess the accuracy of the data-derived respiratory signal, a hardware-based signal was acquired for comparison. Data-driven gating was successfully performed on PET and CT datasets for all four patients. Gated images demonstrated respiratory motion throughout the bin sequences for all PET and CT series, and image analysis and direct comparison of the traces derived from the data-driven method with the hardware-acquired traces indicated accurate recovery of the respiratory signal.

Computer-aided Diagnosis of Focal Liver Lesions by Use of Physicians' Subjective Classification of Echogenic Patterns in Baseline and Contrast-enhanced Ultrasonography

To develop a computer-aided diagnostic (CAD) scheme for classifying focal liver lesions (FLLs) by use of physicians' subjective classification of echogenic patterns of FLLs on baseline and contrast-enhanced ultrasonography (US). A total of 137 hepatic lesions in 137 patients were evaluated with B-mode and NC100100 (Sonazoid)-enhanced pulse-inversion US; lesions included 74 hepatocellular carcinomas (HCCs) (23: well-differentiated, 36: moderately differentiated, 15: poorly differentiated HCCs), 33 liver metastases, and 30 liver hemangiomas. Three physicians evaluated single images at B-mode and arterial phases with a cine mode. Physicians were asked to classify each lesion into one of eight B-mode and one of eight enhancement patterns, but did not make a diagnosis. To classify five types of FLLs, we employed a decision tree model with four decision nodes and four artificial neural networks (ANNs). The results of the physicians' pattern classifications were used successively for four different ANNs in making decisions at each of the decision nodes in the decision tree model. The classification accuracies for the 137 FLLs were 84.8% for metastasis, 93.3% for hemangioma, and 98.6% for all HCCs. In addition, the classification accuracies for histological differentiation types of HCCs were 65.2% for well-differentiated HCC, 41.7% for moderately differentiated HCC, and 80.0% for poorly differentiated HCC. This CAD scheme has the potential to improve the diagnostic accuracy of liver lesions. However, the accuracy in the histologic differential diagnosis of HCC based on baseline and contrast-enhanced US is still limited.

Four-dimensional measurement of intrafractional respiratory motion of pancreatic tumors using a 256 multi-slice CT scanner

Purpose To quantify pancreas and pancreatic tumor movement due to respiratory motion using volumetric cine CT images. Materials and methods Six patients with pancreatic tumors were scanned in cine mode with a 256 multi-slice CT scanner under free breathing conditions. Gross tumor volume (GTV) and pancreas were manually contoured on the CT data set by a radiation oncologist. Intrafractional respiratory movement of the GTV and pancreas was calculated, and the results were compared between the respiratory ungated and gated phases, which is a 30% duty cycle around exhalation. Results Respiratory-induced organ motion was observed mainly in the anterior abdominal side than the posterior side. Average GTV displacement (ungated/gated phases) was 0.7 mm/0.2 mm in both the left and right directions, and 2.5 mm/0.9 mm in the anterior, 0.1 mm/0 mm in the posterior, and 8.9 mm/2.6 mm in the inferior directions. Average pancreas center of mass displacement relative to that at peak exhalation was mainly in the inferior direction, at 9.6 mm in the ungated phase and 2.3 mm in the gated phase. Conclusions By allowing accurate determination of the margin, quantitative analysis of tumor and pancreas displacement provides useful information in treatment planning in all radiation approaches for pancreatic tumors.