S Park

Evaluation of the combined effects of target size, respiratory motion and background activity on 3D and 4D PET/CT images

Gated (4D) PET/CT has the potential to greatly improve the accuracy of radiotherapy at treatment sites where internal organ motion is significant. However, the best methodology for applying 4D-PET/CT to target definition is not currently well established. With the goal of better understanding how to best apply 4D information to radiotherapy, initial studies were performed to investigate the effect of target size, respiratory motion and target-to-background activity concentration ratio (TBR) on 3D (ungated) and 4D PET images. Using a PET/CT scanner with 4D or gating capability, a full 3D-PET scan corrected with a 3D attenuation map from 3D-CT scan and a respiratory gated (4D) PET scan corrected with corresponding attenuation maps from 4D-CT were performed by imaging spherical targets (0.5-26.5 mL) filled with (18)F-FDG in a dynamic thorax phantom and NEMA IEC body phantom at different TBRs (infinite, 8 and 4). To simulate respiratory motion, the phantoms were driven sinusoidally in the superior-inferior direction with amplitudes of 0, 1 and 2 cm and a period of 4.5 s. Recovery coefficients were determined on PET images. In addition, gating methods using different numbers of gating bins (1-20 bins) were evaluated with image noise and temporal resolution. For evaluation, volume recovery coefficient, signal-to-noise ratio and contrast-to-noise ratio were calculated as a function of the number of gating bins. Moreover, the optimum thresholds which give accurate moving target volumes were obtained for 3D and 4D images. The partial volume effect and signal loss in the 3D-PET images due to the limited PET resolution and the respiratory motion, respectively were measured. The results show that signal loss depends on both the amplitude and pattern of respiratory motion. However, the 4D-PET successfully recovers most of the loss induced by the respiratory motion. The 5-bin gating method gives the best temporal resolution with acceptable image noise. The results based on the 4D scan protocols can be used to improve the accuracy of determining the gross tumor volume for tumors in the lung and abdomen.

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.

Motion artifacts occurring at the lung/diaphragm interface using 4D CT attenuation correction of 4D PET scans

For PET/CT, fast CT acquisition time can lead to errors in attenuation correction, particularly at the lung/diaphragm interface. Gated 4D PET can reduce motion artifacts, though residual artifacts may persist depending on the CT dataset used for attenuation correction. We performed phantom studies to evaluate 4D PET images of targets near a density interface using three different methods for attenuation correction: a single 3D CT (3D CTAC), an averaged 4D CT (CINE CTAC), and a fully phase matched 4D CT (4D CTAC). A phantom was designed with two density regions corresponding to diaphragm and lung. An 8 mL sphere phantom loaded with 18F‐FDG was used to represent a lung tumor and background FDG included at an 8:1 ratio. Motion patterns of sin(x) and sin4(x) were used for dynamic studies. Image data was acquired using a GE Discovery DVCT‐PET/CT scanner. Attenuation correction methods were compared based on normalized recovery coefficient (NRC), as well as a novel quantity “fixed activity volume” (FAV) introduced in our report. Image metrics were compared to those determined from a 3D PET scan with no motion present (3D STATIC). Values of FAV and NRC showed significant variation over the motion cycle when corrected by 3D CTAC images. 4D CTAC‐ and CINE CTAC–corrected PET images reduced these motion artifacts. The amount of artifact reduction is greater when the target is surrounded by lower density material and when motion was based on sin4(x). 4D CTAC reduced artifacts more than CINE CTAC for most scenarios. For a target surrounded by water equivalent material, there was no advantage to 4D CTAC over CINE CTAC when using the sin(x) motion pattern. Attenuation correction using both 4D CTAC or CINE CTAC can reduce motion artifacts in regions that include a tissue interface such as the lung/diaphragm border. 4D CTAC is more effective than CINE CTAC at reducing artifacts in some, but not all, scenarios. PACS numbers: 87.57.qp, 87.57.cp

MO-E-M100F-02: Marker-Less Intra-Fraction Position Verification of Lung Tumors with An EPID in Cine Mode

Purpose: Patient positioning represents one of the most challenging problems in radiation therapy, especially for some thoracic and abdominal target locations that are under the influence of respiratory motion. To monitor the target during treatment, we have developed an algorithm using a conventional EPID in cine mode and a prior 4DCT scan. A study based on patient data is presented to demonstrate the feasibility of the method. Materials and Methods: Based on the 4DCT recorded prior to treatment, a digitally reconstructed fluoroscopic (DRF) series is produced for each of the treatment fields. During the treatment, a cine EPID acquisition is performed for each field as it is delivered. Post‐treatment, we produce an image mask for the individual EPID and DRF images based on the MLC leaf positions. The masks are spatially registered and the required changes are induced so that the two images have consistent field shape and size. Following the image processing, the two image series are passed through a correlation algorithm that identifies the closest DRF image for each EPIDimage. This enables us to associate a 4DCT predetermined breathing phase to the EPID series of images, hence allowing us to recover the tumor position during the treatment relative to the planned position. Results: Depending on the number of acquired EPIDimages per treatment field (depending on the prescribed treatmentdose per field) we were able to recover between 70% (4 images per field) and 91% (6 images) of the 4DCT prerecorded tumor motion. Conclusion: Based on a prior 4DCT and a cine EPIDimagesequence taken during the treatment, we have developed a computational algorithm that enabled us to quantify the differences between the tumor motion within the 4DCT that was used to plan the dose distribution on and the actual tumor motion during the treatment.

SU‐EE‐A3‐03: Automatic Target Position Verification with 3‐D Reconstruction of Implanted Markers Using EPID Images

Introduction: In previous studies, a technique using an electronic portal imaging devices(EPIDs) in cine mode has been validated for tracking gold fiducials implanted in the liver for respiratory gating and stereotactic body radiation therapy. However, it was time‐consuming and labor‐intensive since the marker recognition was not performed automatically. In this study, we present an automatic algorithm to quickly and accurately extract the markers in EPIDimages and reconstruct their 3‐D positions. Materials and Methods: The markers were placed in a solid water phantom. Images were acquired using a linear accelerator operating with the 6 MV photon beam at several gantry angles and couch angle positions. A sequence of images was created by collecting the exit radiation using the EPID in cine mode. The fiducials were recognized and detected using a sequence of filters including the Wiener, median, and Laplacian filters. The position of each seed in the EPIDimages was backprojected towards the source position at each beam angle. To reconstruct the optimized seed position in 3‐D, the centroid and Gaussian fit were applied respectively to the distribution of the center points. Results: The average displacement between the seed positions reconstructed with the EPIDimages and the seed locations in 3‐D CTimage is measured to be 3.57 ± 2.59 mm (0.44–7.66 mm) using the centroid. Using Gaussian fit we can accurately reconstruct the marker locations with 0.98 ± 0.38 mm positioning error (0.39–1.47 mm) by significantly reducing the statistical error introduced by the outliers arising from anti‐parallel beam projections. Conclusions: The 3D positions of implanted fiducials can be reconstructed using images from several beam angles. This algorithm will be used for patient data to find the average 3D target position duringradiotherapy treatment. This work was partially supported by a grant from Varian Medical Systems, Inc.

SU‐FF‐T‐650: Dosimetric Benefit of a Combination of Respiratory‐Gating, Image‐Guidance and Intensity Modulated Radiation Therapy for Pancreatic Cancer Treatment

Introduction: In order to account for internal tumor motion and setup uncertainty, 3D‐conformal treatment (3D‐CRT) for upper gastrointestinal malignancies requires the placement of margins around the clinical target volume (CTV). These larger margins can result in excessive dose to normal tissue. To spare critical structures while elevating the dose to the tumor, we have investigated the dosimetric benefits of combinations of respiratory‐gating, image‐guidance and intensity modulated radiation therapy (gated‐IG‐IMRT) for pancreatic cancertreatment.Materials and Methods: Both 4D‐CT and 3D‐CT were acquired for each of the cases under study. For respiratory‐gated treatment, contours for the gross tumor volume (GTV) and critical structures on the end‐of‐exhale 4D‐CT were generated from the original contours on 3D‐CT using the MIMvista deformable registration algorithm. A reduced setup margin for image‐guided plans was used to create the planning target volume (PTV). IMRT plans were optimized based on dose volume histograms and published normal tissue constraints. Six plans for each patient were created and the PTV coverage and the dose distributions in critical structures were compared. Results: The six combinations of treatment modalities provide clinically acceptable PTV coverage and normal tissuedoses that meet all dose constraints for organs at risk. IMRT and image‐guided plans provided equivalent or lower mean doses to normal tissues than 3D‐CRT and non‐image‐guided plans, respectively. Respiratory‐gated treatment plans provided slightly lower doses to liver, stomach, right kidney, spinal cord, and spleen, but significantly reduced dose (60–70%) to left kidney when compared with non‐gated plans. Conclusions: By combining technologies and decreasing the margin, dose escalation will be possible in the treatment of pancreatic cancer without compromising the dose to normal tissue. This work was partially supported by Technology and Innovation Grant at Dana‐Farber/Brigham and Womens Cancer Center.

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 EPIDimages 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 CTimages 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 <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 CTimage.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.

SU‐FF‐I‐142: Quantifying the 4D PET/CT Volumetric Distortions: A 4D Dynamic Phantom Study Based On Pre‐Recorded Patient Data

Introduction 4DPET/CT imaging is a powerful technique to assist clinicians in accurate definition of gross‐tumor‐volumes (GTV) in the lung and abdomen. We present the results of phantom studies designed to evaluate the accuracy of 4DPET/CT at reconstructing the true GTV when tumor motion and abdominal motion are reproduced based on pre‐recorded data from real patients. Methods Measurements were conducted using a 4D dynamic phantom control system capable of reproducing a time‐dependent 3D motion (GTV) and a synchronous, decoupled 1D motion (abdominal surface). The tumor and the abdominal motion trajectories programmed into the phantom are based on pre‐recorded patient data (tumor and abdominal motion). A 4ml spherical vial of FDG, representing the tumor, was used within a water‐FDG mixture adjusted to produce a target‐to‐background activity‐ratio of 8:1. The image reconstruction was done using 10 phase bins over the respiratory cycle. The patient selection was based on the amplitude of the internal marker motion (> 1cm). Results and Discussion Based on a 3DPET scan with no target motion, two methodologies were used to determine the activity threshold that recovers the active volume of the target (4ml) relative to: (1) the maximum intensity voxel; (2) the average intensity obtained from the five highest intensity voxels;. The percentage difference between the true and calculated volume was determined for each phase bin of the 4D studies. Errors as large as 45% were observed for specific patients and phases with a statistical bias towards overestimation of the target volume. However, the activity threshold based on the average intensity has shown to reduce the inter‐phase volumetric distortions. Conclusion Our results have quantified volumetric distortions that occur during 4D PET/CT imaging based on previously recorded internal target and abdominal motions in patients. These results are relevant to the accurate application of 4D PET/CT to radiotherapy target definition.

SU‐GG‐I‐141: Automatic Segmentation of Static and Moving Target Volumes Using Respiratory Ungated (3D) and Gated (4D) PET/CT Images

Purpose: Thresholding methods are commonly used to segment lesion volumes in PETimages. However, the presence of motion makes it difficult to determine the optimum threshold. To measure the threshold needed to produce the true volume of a moving target, we have investigated the effect of respiratory motion on the threshold at varying target‐to‐background activity concentration ratios (TBRs) using gated (4D) and ungated (3D) PETimages.Method and Materials: Using a PET/CT scanner with gating capability, spherical targets (0.5–26.5 mL) filled with 18 F ‐ FDG in a NEMA IEC body phantom were imaged with both a 3D‐PET scan corrected with a 3D‐CT attenuation map and a 4D‐PET scan corrected with phase‐matched 4D‐CT maps. . The phantom was either at rest or moving sinusoidally in the superior‐inferior direction with an amplitude of 2 cm and a period of 4.5 s to simulate respiratory motion. The optimum threshold values which give the true volumes of the spheres were derived from the 3D and 4D‐PET images at TBR = 4, 8, and infinite. For the 4D‐PET images, 5‐bin gating data were used in this analysis.Results: The TBR‐threshold‐volume curves show that the optimum threshold exponentially decreases as the volume increases. In addition, the threshold increases as the TBR decreases. The results also illustrate that the threshold values applied to the 4D‐PET images for the moving targets are well correlated with the optimum threshold values applied to the 3D‐PET images for the targets at rest. However, the same thresholds significantly over‐estimate the target volume if applied to the 3D‐PET images of moving targets. Conclusion: The TBR‐threshold‐volume curves clearly demonstrate the advantage of gating for detecting the true volume of moving target. Therefore, respiratory‐gated PET acquisition should be performed in the presence of relatively large organ movement to accurately determine the gross tumor volume for clinical applications.

TU‐C‐332‐10: Evaluation of Combined Effects of Target Size, Background Activity, and Respiratory Motion On 3D and 4D PET/CT Images

Purpose: In recent years, quantitative analysis of gated (4D) PET/CT images has been introduced for diagnosis, staging, and prediction of tumor response where internal organ motion is significant. However, the best methodology for applying 4D information to radiotherapy target definition is not currently well established. In order to accurately determine moving target volume, we have investigated the combined effects of target size, respiratory motion, target‐to‐background activity concentration ratio (TBR) on ungated (3D) and 4D PETimages as well as gating methods. Method and Materials: Using a GE Discovery PET/CT scanner, a 3D‐PET scan corrected with a 3D attenuation map from 3D‐CT scan and a 4D‐PET scan corrected with matching attenuation maps from 4D‐CT were performed using spherical targets (0.5–26.5 mL) filled with 18 F ‐ FDG in a NEMA IEC body phantom at different TBRs (infinite, 8, and 4). To simulate respiratory motion, the phantoms were driven sinusoidally in the superior‐inferior direction with amplitudes of 0, 1, and 2 cm and a period of 4.5 s. Recovery coefficients were determined on PETimages. In addition, gating methods using different numbers of gating bins (1–20 bins) were evaluated by determining imagenoise and temporal resolution. Results: Signal loss in 3D‐PET images was measured from both the partial volume effect, due to the limited PET resolution, as well as respiratory motion. The results show that signal loss depends on both the amplitude and shape of respiratory motion. However, 4D‐PET successfully recovers most of the loss induced by respiratory motion. The 5‐bin gating method gives the best temporal resolution with acceptable imagenoise.Conclusion: The results based on the 4D scan protocols can be used to improve the accuracy of gross tumor volume definition in the lung and abdomen.