TH‐E‐17A‐01: Internal Respiratory Surrogate for 4D CT Using Fourier Transform and Anatomical Features

The purpose of this study was to develop a novel algorithm to create a robust internal respiratory signal (IRS) for retrospective sorting of four-dimensional (4D) computed tomography (CT) images. The proposed algorithm combines information from the Fourier transform of the CT images and from internal anatomical features to form the IRS. The algorithm first extracts potential respiratory signals from low-frequency components in the Fourier space and selected anatomical features in the image space. A clustering algorithm then constructs groups of potential respiratory signals with similar temporal oscillation patterns. The clustered group with the largest number of similar signals is chosen to form the final IRS. To evaluate the performance of the proposed algorithm, the IRS was computed and compared with the external respiratory signal from the real-time position management (RPM) system on 80 patients. In 72 (90%) of the 4D CT data sets tested, the IRS computed by the authors' proposed algorithm matched with the RPM signal based on their normalized cross correlation. For these data sets with matching respiratory signals, the average difference between the end inspiration times (Δtins) in the IRS and RPM signal was 0.11 s, and only 2.1% of Δtins were more than 0.5 s apart. In the eight (10%) 4D CT data sets in which the IRS and the RPM signal did not match, the average Δtins was 0.73 s in the nonmatching couch positions, and 35.4% of them had a Δtins greater than 0.5 s. At couch positions in which IRS did not match the RPM signal, a correlation-based metric indicated poorer matching of neighboring couch positions in the RPM-sorted images. This implied that, when IRS did not match the RPM signal, the images sorted using the IRS showed fewer artifacts than the clinical images sorted using the RPM signal. The authors' proposed algorithm can generate robust IRSs that can be used for retrospective sorting of 4D CT data. The algorithm is completely automatic and requires very little processing time. The algorithm is cost efficient and can be easily adopted for everyday clinical use.

Purpose:To investigate the effectiveness of using a Fourier transformbased internal respiratory signal (IRS) to sort four‐dimensional (4D) CT images, compared to images sorted using the external respiratory signal from the real‐time position management (RPM) system.Methods:80 patients with abdominal or thoracic cancers were retrospectively selected for this study. The IRS were computed using an algorithm previously described by our group. 4D images were then sorted using the end inspiration times calculated from the IRS. We compared the IRS to the RPM signals by assessing their similarities using the normalized cross correlation (NCC), and the end inspiration times identified from the respective signals. The IRS‐sorted 4D images were also compared to the RPM‐sorted clinical images using a correlation‐based metric to compare their image qualities.Results:In 90% of the data sets, the IRS matched with the RPM signal with NCC >= 0.5. In this cohort of matching signals, the average difference between end inspiration times from the IRS and RPM signal was 0.11 s. In the remaining 10% of the data sets, the IRS did not match the RPM signal in at least one couch position (NCC < 0.5). The average difference between end inspiration times was 0.73 s in the non‐matching couch positions. The correlation‐based metric indicated poorer matching of neighboring couch positions in the RPM‐sorted images. This implied that, when the IRS did not match the RPM signal, the images sorted using the IRS showed fewer artifacts than the clinical images sorted using the RPM signal.Conclusion:The IRS is in good agreement with the RPM signal in most cases. In some cases, the IRS provides better sorting than the RPM signal, especially when the RPM system fails. The IRS can therefore be a viable complementary tool or even a replacement for the RPM system.

A data-driven motion tracking system was developed for respiratory gating in positron emission tomography (PET)/computed tomography (CT) studies. The positron emission tracking system (PeTrack) estimates the position of a low-activity fiducial marker placed on the patient during imaging. The aim of this study was to compare the performance of PeTrack against that of the real-time position management (RPM) system as applied to respiratory gating in cardiac PET/CT studies. The list-mode data of 35 patients that were referred for 82 Rb myocardial perfusion studies were retrospectively processed with PeTrack to generate respiratory motion signals and triggers. Fifty acquisitions from the initial cohort, conducted under physiologic rest and stress, were considered for analysis. Respiratory-gated reconstructions were performed using reconstruction software provided by the vendor. The respiratory signals and triggers of the gating systems were compared using quantitative measurements of the respiratory signal correlation, median, and interquartiles range (IQR) of observed respiratory rates and the relative frequencies of respiratory cycle outliers. Quantitative measurements of left-ventricular wall thicknesses and motion due to respiration were also compared. Real-time position management signals were also retrospectively processed using the trigger detection method of PeTrack for a third comparator ("RPMretro") that allowed direct comparison of the motion tracking quality independently of differences in the trigger detection methods. The comparison of PeTrack to the original RPM data represent a practical comparison of the two systems, whereas that of PeTrack and RPMretro represents an equal comparison of the two. Nongated images were also reconstructed to provide reference left-ventricular wall thicknesses. LV wall thickness and motion measurements were repeated for a subset of cases with motion ≥7mm as image artifacts were expected to be more severe in these cases. A significant correlation (P<0.05) was observed between the RPM and PeTrack respiratory signals in 45/50 acquisitions; the mean correlation coefficient was 0.43. Similar results were found between PeTrack and RPMretro. No significant difference was observed between the RPM and PeTrack with respect to median respiratory rates and the percentage of respiratory cycles outliers. Respiratory rate variability (IQR) was significantly higher with PeTrack vs RPM (P=0.002) and RPMretro (P=0.04). Both PeTrack and RPM had a significant increase in the percentage of respiratory rate outliers compared to RPMretro (P<0.001 and P=0.001, respectively). All methods indicated significant differences in LV thickness compared to nongated images (P<0.02). LV thickness was significantly larger for PeTrack compared to RPMretro in the highest motion subset (P=0.009). Images gated with RPMretro showed significant increases in motion compared to both PeTrack (P<0.001) and prospective RPM (P=0.002). In the subset of highest motion cases, the difference between RPM and RPMretro was no longer present. The data-driven PeTrack algorithm performed similarly to the well-established RPM system for respiratory gating of 82 Rb cardiac perfusion PET/CT studies. Real-time position management performance improved after retrospective processing and led to enhanced performance compared to both PeTrack and prospective RPM. With further development PeTrack has the potential to reduce the need for ancillary hardware systems to monitor respiratory motion.

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.

For the management of mobile tumors, respiratory gating is the ideal option, both during imaging and during therapy. The major advantage of respiratory gating during imaging is that it is possible to create a single artifact-free CT data-set during a selected phase of the patient's breathing cycle. The purpose of the present work is to present a simple technique to measure the time delay during acquisition of a prospectively gated CT. The time delay of a Philips Brilliance BigBore™ (Philips Medical Systems, Madison, WI) scanner attached to a Varian Real-Time Position Management™ (RPM) system (Varian Medical Systems, Palo Alto, CA) was measured. Two methods were used to measure the CT time delay: using a motion phantom and using a recorded data file from the RPM system. In the first technique, a rotating wheel phantom was altered by placing two plastic balls on its axis and rim, respectively. For a desired gate, the relative positions of the balls were measured from the acquired CT data and converted into corresponding phases. Phase difference was calculated between the measured phases and the desired phases. Using period of motion, the phase difference was converted into time delay. The Varian RPM system provides an external breathing signal; it also records transistor-transistor logic (TTL) ‘X-Ray ON’ status signal from the CT scanner in a text file. The TTL ‘X-Ray ON’ indicates the start of CT image acquisition. Thus, knowledge of the start time of CT acquisition, combined with the real-time phase and amplitude data from the external respiratory signal, provides time-stamping of all images in an axial CT scan. The TTL signal with time-stamp was used to calculate when (during the breathing cycle) a slice was recorded. Using the two approaches, the time delay between the prospective gating signal and CT simulator has been determined to be 367 ± 40 ms. The delay requires corrections both at image acquisition and while setting gates for the treatment delivery; otherwise the simulation and treatment may not be correlated with the patient's breathing.

The aim of this work was to track and verify the delivery of respiratory-gated irradiations, performed with three versions of TrueBeam linac, using a novel phantom arrangement that combined the OCTAVIUS® SRS 1000 array with a moving platform. The platform was programmed to generate sinusoidal motion of the array. This motion was tracked using the real-time position management (RPM) system and four amplitude gating options were employed to interrupt MV beam delivery when the platform was not located within set limits. Time-resolved spatial information extracted from analysis of x-ray fluences measured by the array was compared to the programmed motion of the platform and to the trace recorded by the RPM system during the delivery of the x-ray field. Temporal data recorded by the phantom and the RPM system were validated against trajectory log files, recorded by the linac during the irradiation, as well as oscilloscope waveforms recorded from the linac target signal. Gamma analysis was employed to compare time-integrated 2D x-ray dose fluences with theoretical fluences derived from the probability density function for each of the gating settings applied, where gamma criteria of 2%/2 mm, 1%/1 mm and 0.5%/0.5 mm were used to evaluate the limitations of the RPM system. Excellent agreement was observed in the analysis of spatial information extracted from the SRS 1000 array measurements. Comparisons of the average platform position with the expected position indicated absolute deviations of <0.5 mm for all four gating settings. Differences were observed when comparing time-resolved beam-on data stored in the RPM files and trajectory logs to the true target signal waveforms. Trajectory log files underestimated the cycle time between consecutive beam-on windows by 10.0 ± 0.8 ms. All measured fluences achieved 100% pass-rates using gamma criteria of 2%/2 mm and 50% of the fluences achieved pass-rates >90% when criteria of 0.5%/0.5 mm were used. Results using this novel phantom arrangement indicate that the RPM system is capable of accurately gating x-ray exposure during the delivery of a fixed-field treatment beam.

The dose delivered to the left anterior descending artery (LAD) in radiotherapy of left-sided breast cancer increased risk of myocardial Infarction. In particular, it has been shown that twenty years after radiotherapy to the left breast cancer there is a double probability to infarction compared with patients treated with radiation therapy who have tumors in right breast.All of which has led with the use of multiple irradiation techniques to minimize the dose to anterior descending artery, such as the deep inspiration breath-hold technique (DIBH) that can decrease radiation dose delivered to the heart. The study was performed on a TrueBeam and ClinaciX Varian linear accelerators, which is equipped with Varian Realtime Position Management (RPM) system, and BrainLAB ExacTrac gating systems. In this study, the two systems were assessed on accuracy of both motion tracking and radiation delivery control. The two techniques allow to quantify and compensate the respiratory movement to analyse the organ motion problems.In addition, we compared times of patient positioning, setting and treatment delivery by the verification of the treatment fields position on different days to document. We analysed advantages and criticalities of both systems trying to explain how these variables can be affect by delivery and workflow.This study involved 16 female patients diagnosed with left sided breast cancer under 65 years’ patients treated by adjuvant radiation therapy; the first 8 treated with the Breath Hold Tracking technique and the next 8 with Breath Hold Gaiting. Patients were followed up during planning and delivery treatment.From the comparison, positive and negative sides emerge. We present an extensive comparison between the use of RPM and Tracking systems on their technical capabilities and operating approach. Infrared tracking system continuously monitors patient positioning throughout treatment that allows for optimal patient positioning in all six degrees of freedom enabling an improved setup accuracy compared to translational corrections alone. In addition, daily patient setup and delivery treatment was lowest than RPM system. In addition, systematic and random errors was lowest than RPM system, even if only little. On the other and, RPM gating system provides both respiratory gating for respiration-synchronized imaging and the treatment beam is turned on, and RPM automatically gates the beam on and off instantly according to the selected upper and lower gating thresholds.The Gating technique, performed through the RPM system, has the advantage of delivering the radiant dose to the patient only when it is able to maintain the breath within the pre-set band. The main disadvantage is that this technique requires a greater active collaboration on the part of the patient.The possibility of having both methods guarantees a greater number of patients the opportunity to perform breath hold therapy, order safeguard possible future radio-induced cardiac pathologies.

Purpose: Respiratory motion artifacts are commonly seen in the abdominal and thoracic CT images. A Real-time Position Management (RPM) system is integrated with CT simulator using abdominal surface as a surrogate for tracking the patient respiratory motion. The respiratory-correlated four-dimensional computed tomography (4DCT) is then reconstructed by GE advantage software. However, there are still artifacts due to inaccurate respiratory motion detecting and sorting methods. We developed an Ultrasonography Respiration Monitoring (URM) system which can directly monitor diaphragm motion to detect respiratory cycles. We also developed a new 4DCT sorting and motion estimation method to reduce the respiratory motion artifacts. The new 4DCT system was compared with RPM and the GE 4DCT system. Methods: Imaging from a GE CT scanner was simultaneously correlated with both the RPM and URM to detect respiratory motion. A radiation detector, Blackcat GM-10, recorded the X-ray on/off and synchronized with URM. The diaphragm images were acquired with Ultrasonix RP system. The respiratory wave was derived from diaphragm images and synchronized with CT scanner. A more precise peaks and valleys detection tool was developed and compared with RPM. The motion is estimated for the slices which are not in the predefined respiratory phases by using block matchingmore » and optical flow method. The CT slices were then sorted into different phases and reconstructed, compared with the images reconstructed from GE Advantage software using respiratory wave produced from RPM system. Results: The 4DCT images were reconstructed for eight patients. The discontinuity at the diaphragm level due to an inaccurate identification of phases by the RPM was significantly improved by URM system. Conclusion: Our URM 4DCT system was evaluated and compared with RPM and GE 4DCT system. The new system is user friendly and able to reduce motion artifacts. It also has the potential to monitor organ motion during therapy.« less

PurposeTo evaluate the use of 3D optical surface imaging as a surrogate for respiratory gated deep-inspiration breath-hold (DIBH) for left breast irradiation.Material and MethodsPatients with left-sided breast cancer treated with lumpectomy or mastectomy were selected as candidates for DIBH treatment for their external beam radiation therapy. Treatment plans were created on both free breathing (FB) and DIBH computed tomography (CT) simulation scans to determine dosimetric benefits from DIBH. The Real-time Position Management (RPM) system was used to acquire patient's breathing trace during DIBH CT acquisition and treatment delivery. The reference 3D surface models from FB and DIBH CT scans were generated and transferred to the “AlignRT” system for patient positioning and real-time treatment monitoring. MV Cine images were acquired during treatment for each beam as quality assurance for intra-fractional position verification. The chest wall excursions measured on these images were used to define the actual target position during treatment, and to investigate the accuracy and reproducibility of RPM and AlignRT.ResultsReduction in heart dose can be achieved using DIBH for left breast/chest wall radiation. RPM was shown to have inferior correlation with the actual target position, as determined by the MV Cine imaging. Therefore, RPM alone may not be an adequate surrogate in defining the breath-hold level. Alternatively, the AlignRT surface imaging demonstrated a superior correlation with the actual target positioning during DIBH. Both the vertical and magnitude real-time deltas (RTDs) reported by AlignRT can be used as the gating parameter, with a recommended threshold of ±3 mm and 5 mm, respectively.ConclusionThe RPM system alone may not be sufficient for the required level of accuracy in left-sided breast/CW DIBH treatments. The 3D surface imaging can be used to ensure patient setup and monitor inter- and intra- fractional motions. Furthermore, the target position accuracy during DIBH treatment can be improved by AlignRT as a superior surrogate, in addition to the RPM system.

We present a feasibility study on extracting the respiratory surrogate signal (RSS) from cone-beam computed tomography (CBCT) projections using a supervised convolutional neural network (CNN) model. Determining the intrinsic RSS instead of using an external surrogate signal, provided by optical tracing hardware such as the Real-time Position Management (RPM) system, has the advantage that it spares patient setup time and hence permits faster 4D CBCT acquisition. Another convenience of such an approach is that it can be applied retrospectively without special preparation or equipment. For the implementation, we made use of the MONAI open source library. Our model is based on a modified version of the MONAI regressor class. We trained the model using CBCT projections with the corresponding RSS as recorded by an external marker block using the RPM system. The model is to deduce the RSS given the CBCT. Using a specific dataset with CBCT from anesthetized animals breathing with the help of a mechanical ventilator, results show a good correlation between the actual and predicted RSS. Unlike the Amsterdam Shroud algorithm, our method shows promising results to predict the normalized amplitude of the breathing signal. Further work could extend the model to permit RSS prediction for its online use in radiation therapy or detection of sudden motion deteriorating CBCT image quality. To conclude, we have made a first step towards proving the concept which consists in using a deep learning model to extract the RSS out of acquired CBCT projection images. The approach is promising but requires more work for robustness, i.e. for sufficient accuracy both in the frequency and normalized amplitude extraction.

A commercially available motion phantom (QUASAR, Modus Medical) was modified for programmable motion control with the aim of reproducing patient respiratory motion in one dimension in both the anterior-posterior and superior-inferior directions, as well as, providing controllable breath-hold and sinusoidal patterns for the testing of radiotherapy gating systems. In order to simulate realistic patient motion, the DC motor was replaced by a stepper motor. A separate 'chest-wall' motion platform was also designed to accommodate a variety of surrogate marker systems. The platform employs a second stepper motor that allows for the decoupling of the chest-wall and insert motion. The platform's accuracy was tested by replicating patient traces recorded with the Varian real-time position management (RPM) system and comparing the motion platform's recorded motion trace with the original patient data. Six lung cancer patient traces recorded with the RPM system were uploaded to the motion platform's in-house control software and subsequently replicated through the phantom motion platform. The phantom's motion profile was recorded with the RPM system and compared to the original patient data. Sinusoidal and breath-hold patterns were simulated with the motion platform and recorded with the RPM system to verify the systems potential for routine quality assurance of commercial radiotherapy gating systems. There was good correlation between replicated and actual patient data (P 0.003). Mean differences between the location of maxima in replicated and patient data-sets for six patients amounted to 0.034 cm with the corresponding minima mean equal to 0.010 cm. The upgraded motion phantom was found to replicate patient motion accurately as well as provide useful test patterns to aid in the quality assurance of motion management methods and technologies.

The purpose of this study was to investigate the accuracy of motion tracking and radiation delivery control of integrated gating systems on a Novalis Tx system. The study was performed on a Novalis Tx system, which is equipped with Varian Real‐time Position Management (RPM) system, and BrainLAB ExacTrac gating systems. In this study, the two systems were assessed on accuracy of both motion tracking and radiation delivery control. To evaluate motion tracking, two artificial motion profiles and five patients' respiratory profiles were used. The motion trajectories acquired by the two gating systems were compared against the references. To assess radiation delivery control, time delays were measured using a single‐exposure method. More specifically, radiation is delivered with a 4 mm diameter cone within the phase range of 10%–45% for the BrainLAB ExacTrac system, and within the phase range of 0%–25% for the Varian RPM system during expiration, each for three times. Radiochromic films were used to record the radiation exposures and to calculate the time delays. In the work, the discrepancies were quantified using the parameters of mean and standard deviation (SD). Pearson's product‐moment correlational analysis was used to test correlation of the data, which is quantified using a parameter of r. The trajectory profiles acquired by the gating systems show good agreement with those reference profiles. A quantitative analysis shows that the average mean discrepancies between BrainLAB ExacTrac system and known references are 1.5 mm and 1.9 mm for artificial and patient profiles, with the maximum motion amplitude of 28.0 mm. As for the Varian RPM system, the corresponding average mean discrepancies are 1.1 mm and 1.7 mm for artificial and patient profiles. With the proposed single‐exposure method, the time delays are found to be 0.20±0.03 seconds and 0.09±0.01 seconds for BrainLAB ExacTrac and Varian RPM systems, respectively. The results indicate the systems can track motion and control radiation delivery with reasonable accuracy. The proposed single‐exposure method has been demonstrated to be feasible in measuring time delay efficiently.PACS numbers: 87.56.bd, 87.56.‐v, 87.55.‐x

To develop a passive gating system incorporating with the real-time position management (RPM) system for the gated radiotherapy. Passive breath gating (PBG) equipment, which consists of a breath-hold valve, a controller mechanism, a mouthpiece kit, and a supporting frame, was designed. A commercial real-time positioning management system was implemented to synchronize the target motion and radiation delivery on a linear accelerator with the patient's breathing cycle. The respiratory related target motion was investigated by using the RPM system for correlating the external markers with the internal target motion while using PBG for passively blocking patient's breathing. Six patients were enrolled in the preclinical feasibility and efficiency study of the PBG system. PBG equipment was designed and fabricated. The PBG can be manually triggered or released to block or unblock patient's breathing. A clinical workflow was outlined to integrate the PBG with the RPM system. After implementing the RPM based PBG system, the breath-hold period can be prolonged to 15-25 s and the treatment delivery efficiency for each field can be improved by 200%-400%. The results from the six patients showed that the diaphragm motion caused by respiration was reduced to less than 3 mm and the position of the diaphragm was reproducible for difference gating periods. A RPM based PBG system was developed and implemented. With the new gating system, the patient's breath-hold time can be extended and a significant improvement in the treatment delivery efficiency can also be achieved.

Purpose: To quantitatively evaluate the reproducibility of patient breathing between the calculated phase from respiratory signal and RPM (real-time position management system, Varian Medical Systems, Palo Alto, CA) within treatment. We developed an independent retrospective verification system (RVS) for gated-radiotherapy using full signal and gating window in RPM system. Methods: RVS was programmed by LabVIEW 2009 with wavelet-based multi-resolution analysis, which is a useful and accurate technique for identifying peaks and valleys of noisy signals. The respiratory signal and real-time calculated phase information from RPM was exported to RVS as a text file. Using this text file, several respiratory parameters were calculated by RVS, and were compared with the generated parameters from RPM. The evaluated parameters included phase-shift, total displacement, residual motion, baseline shift, and so forth. The analysis was conducted for both in-gate and full respiratory signal separately. The analysis report was automatically generated in Excel file format. Eleven patients of abdominal cancer were retrospectively analyzed for the evaluation. Results: The mean phase error of gated signal and full signal between RPM and our software ranged from 1.50% to 3.08% and 1.52% to 3.08%, respectively. Average phase shift was not significant but in-gate phase difference between RVS and RPM was found to be higher than 4% in two cases. At times, real-time phase calculation from RPM caused the beam to be turned on at incorrect time of the breathing cycle when the patient breathing was not regular. The total displacement varied from 0.672 cm to 1.732 cm, which showed patient-specific baseline shift during treatment. Conclusion: The developed software demonstrated competency in analyzing RPM signal and evaluating patient-specific respiratory parameters of radiotherapy. Thus, it can be used as an independent quality assurance tool for RPM phase-based gating treatment.

This study proposes a novel respiratory signal detection system for 4D-CT in radiotherapy by measuring back pressure changes at multiple positions on CT couch. The 12-channel pressure sensor is fixed on CT couch to obtain patient's back pressure signal. The 12-channel signal is transmitted to a PC at a sampling rate of 50 Hz after a signal conditioning circuit and an analog-digital converter. The amplitude of pressure changes is characterized to select the optimal channel. This system is validated by comparing with the respiratory signal collected synchronously with a real-time position management (RPM) system on 10 healthy volunteers. The correlation coefficient between the signals is 0.82 ± 0.09 (standard deviation) and the time shift is 0.32 ± 0.15 second. We conclude that the back pressure signal acquired by the proposed system has the potential to replace the clinical RPM system for respiratory signal detection in 4D-CT data acquisition.