Investigation of sliced body volume (SBV) as respiratory surrogate

Validation of four-dimensional computed tomography without external reference respiratory signals for radiation treatment planning of lung tumors

Deviceless four-dimensional (4D) computed tomography (CT) allows the acquisition of respiratory signals from six features without requiring an external device for cine CT processing. This method has been recently introduced in radiation treatment planning of lung tumors. To validate deviceless 4D CT, it must be compared with conventional 4D CT, which requires an external monitoring device. We compared the two methods using a multicell 4D phantom that simulates patient's movement during respiration regarding the target volume (TV), target position (TP), and internal TV for lung tumor radiation therapy. We retrospectively obtained images of 10 patients who underwent radiation treatment planning of lung tumors and compared the two methods, as in the phantom study. For the phantom study, the mean TV, root mean square errors of the TP, and mean internal TV differences between the two methods ranged from -4.5% to 1.2%, 0.7 to 2.6 mm, and -1.1% to 3.4%, respectively. The corresponding results of the clinical study ranged from -1.5% to 14.9%, 0.1 to 5.9 mm, and -9.7% to 10.1%, respectively. The results of deviceless 4D CT for the clinical study were consistent with those of conventional 4D CT, except for target movements with high excursions. Therefore, deviceless 4D CT can be an alternative to conventional 4D CT for radiation treatment planning of lung tumors.

Stability and Reliability of Enhanced External-Internal Motion Correlation via Dynamic Phase-Shift Corrections Over 30-min Timeframe for Respiratory-Gated Radiotherapy

To assess the stability of patient-specific phase shifts between external- and internal-respiratory motion waveforms, the reliability of enhanced external–internal correlation with phase-shift correction, and the feasibility of guiding respiratory-gated radiotherapy (RGRT) over 30 min. In this clinical feasibility investigation, external bellows and internal-navigator waveforms were simultaneously and prospectively acquired along with two four-dimensional magnetic resonance imaging (4DMRI) scans (6–15 m each) with 15–20 m intervals in 10 volunteers. A bellows was placed 5 cm inferior to the xiphoid to monitor abdominal motion, and an MR navigator was used to track the diaphragmatic motion. The mean phase-domain (MPD) method was applied, which combines three individual phase-calculating methods: phase-space oval fitting, principal component analysis, and analytic signal analysis, weighted by the reciprocal of their residual errors (RE) excluding outliers (RE >2σ). The time-domain cross-correlation (TCC) analysis was applied for comparison. Dynamic phase-shift correction was performed based on the phase shift detected on the fly within two 10 s moving datasets. Simulating bellows-triggered gating, the median and 95% confidence interval for the navigator's position at beam-on/beam-off and %harm (percentage of beam-on time outside the safety margin) were calculated. Averaged across all subjects, the mean phase shifts are found indistinguishable (p > .05) between scan 1 (55˚ ± 9˚) and scan 2 (59˚ ± 11˚). Using the MPD method the averaged correlation increases from 0.56 ± 0.22 to 0.85 ± 0.11 for scan 1 and from 0.47 ± 0.30 to 0.84 ± 0.08 for scan 2. The TCC correction results in similar results. After phase-shift correction, the number of cases that were suitable for amplitude gating (with <10%harm) increased from 2 to 17 out of 20 cases. A patient-specific, stable phase-shift between the external and internal motions was observed and corrected using the MPD and TCC methods, producing long-lasting enhanced motion correlation over 30m. Phase-shift correction offers a feasible strategy for improving the accuracy of tumor-motion prediction during RGRT.

Respiratory-Correlated (RC) vs. Time-Resolved (TR) Four-Dimensional Magnetic Resonance Imaging (4DMRI) for Radiotherapy of Thoracic and Abdominal Cancer

Recent technological and clinical advancements of both respiratory-correlated (RC) and time-resolved (TR) four-dimensional magnetic resonance imaging (4DMRI) techniques are reviewed in light of tumor/organ motion simulation, monitoring, and assessment in radiotherapy. For radiotherapy of thoracic and abdominal cancer, respiratory-induced tumor motion, and motion variation due to breathing irregularities are the major uncertainties in treatment. RC-4DMRI is developed to assess tumor motion for treatment planning, whereas TR-4DMRI is developed to assess both motion and motion variation for treatment planning, delivery and assessment. RC-4DMRI is reconstructed to provide one-breathing-cycle motion, similar to 4D computed tomography (4DCT), the current clinical standard, but with higher soft-tissue contrast, no ionizing radiation, and less binning artifacts due to the use of an internal respiratory surrogate. Recent studies have shown that its spatial resolution has reached or exceeded that of 4DCT and scanning time becomes clinically acceptable. TR-4DMRI is recently developed with an adequate spatiotemporal resolution to assess tumor motion and motion variations for treatment simulation, delivery and assessment. The super-resolution approach is most promising since it can image any organ/body motion, whereas RC-4D MRI are limited to resolve only respiration-induced motion and some TR-4DMRI approaches may more or less depend on RC-4DMRI. TR-4DMRI provides multi-breath motion data that are useful not only in MR-guided radiotherapy but also for building a patient-specific motion model to guide radiotherapy treatment using an non-MR-equipped linear accelerator. Based on 4DMRI motion data, motion-corrected dynamic contrast imaging and diffusion-weighted imaging have also been reported, aiming to facilitate tumor delineation for more accurate radiotherapy targeting. Both RC- and TR-4DMRI have been evaluated for potential clinical applications, such as delineation of tumor volumes, where sufficiently high spatial resolution and large field-of-view are required. The 4DMRI techniques are promising to play a role in motion assessment in radiotherapy treatment planning, delivery, assessment, and adaptation.

Enhancement of Long-Term External-Internal Correlation by Phase-Shift Detection and Correction Based on Concurrent External Bellows and Internal Navigator Signals

Purpose

The purpose of this study was to enhance the correlation between external and internal respiratory motions by dynamically determining and correcting the patient-specific phase shift between external and internal respiratory waveforms acquired concurrently during respiratory-correlated 4-dimensional magnetic resonance imaging scans.

Methods and Materials

Internal-navigator and external-bellows waveforms were acquired simultaneously during 6- to 15-minute respiratory-correlated 4-dimensional magnetic resonance imaging scans in 10 healthy participants under an institutional review board–approved protocol. The navigator was placed at the right lung–diaphragm interface, and the bellows were placed ∼5 cm inferior to the sternum. Three segments of each respiratory waveform, at the beginning, middle, and end of a scan, were analyzed. Three phase-domain methods were employed to estimate the phase shift, including analytical signal analysis, phase-space oval fitting, and principal component analysis. A robust strategy for estimating the phase shift was realized by combining these methods in a weighted average and by eliminating outliers (>2 σ) caused by breathing irregularities. Whether phase-shift correction affects the external-internal correlation was evaluated. The cross-correlation between the 2 waveforms in the time domain provided an independent check of the correlation enhancement.

Results

Phase-shift correction significantly enhanced the external-internal correlation in all participants across the entire 6- to 15-minute scans. On average, the correlation increased from 0.45 ± 0.28 to 0.85 ± 0.15 for the combined method. The combined method exhibited a 99.5% success rate and revealed that the phase of the external waveform leads that of the internal waveform in all 10 participants by 57 ^o ± 17^o (1.6 ± 0.5 bins) on average. Seven participants exhibited highly reproducible phase shifts over time, evidenced by standard deviations (σ) < 4^o, whereas 8^o < σ < 12^o in the remaining 3 participants. Regardless, phase-shift correction significantly improved the correlation in all participants.

Conclusions

Correcting the phase shift estimated by the phase-domain methods provides a new approach for enhancing the correlation between external and internal respiratory motions. This strategy holds promise for improving the accuracy of respiratory-gated radiation therapy.

Respiratory signal prediction based on adaptive boosting and multi-layer perceptron neural network

To improve the prediction accuracy of respiratory signals using adaptive boosting and multi-layer perceptron neural network (ADMLP-NN) for gated treatment of moving target in radiation therapy. The respiratory signals acquired using a real-time position management (RPM) device from 138 previous 4DCT scans were retrospectively used in this study. The ADMLP-NN was composed of several artificial neural networks (ANNs) which were used as weaker predictors to compose a stronger predictor. The respiratory signal was initially smoothed using a Savitzky-Golay finite impulse response smoothing filter (S-G filter). Then, several similar multi-layer perceptron neural networks (MLP-NNs) were configured to estimate future respiratory signal position from its previous positions. Finally, an adaptive boosting (Adaboost) decision algorithm was used to set weights for each MLP-NN based on the sample prediction error of each MLP-NN. Two prediction methods, MLP-NN and ADMLP-NN (MLP-NN plus adaptive boosting), were evaluated by calculating correlation coefficient and root-mean-square-error between true and predicted signals. For predicting 500 ms ahead of prediction, average correlation coefficients were improved from 0.83 (MLP-NN method) to 0.89 (ADMLP-NN method). The average of root-mean-square-error (relative unit) for 500 ms ahead of prediction using ADMLP-NN were reduced by 27.9%, compared to those using MLP-NN. The preliminary results demonstrate that the ADMLP-NN respiratory prediction method is more accurate than the MLP-NN method and can improve the respiration prediction accuracy.

Retrospective four-dimensional magnetic resonance imaging with image-based respiratory surrogate: a sagittal-coronal-diaphragm point of intersection motion tracking method

A four-dimensional magnetic resonance imaging (4-D-MRI) technique with Sagittal-Coronal-Diaphragm Point-of-Intersection (SCD-PoI) as a respiratory surrogate is proposed. To develop an image-based respiratory surrogate, the SCD-PoI motion tracking method is used for retrospective 4-D-MRI reconstruction. Single-slice sagittal MR cine was acquired at a location near the center of the diaphragmatic dome. Multiple-slice coronal MR cines were acquired for 4-D-MRI reconstruction. As a motion surrogate, the diaphragm motion was measured from the PoI among the sagittal MRI cine plane, coronal MRI cine planes, and the diaphragm surface. These points were defined as the SCD-PoI. This point is used as a one-dimensional diaphragmatic navigator in our study. The 4-D-MRI technique was evaluated on a 4-D digital extended cardiac-torso (XCAT) human phantom, a motion phantom, and seven human subjects (five healthy volunteers and two cancer patients). Motion trajectories of a selected region of interest were measured on 4-D-MRI and compared with the known XCAT motion that served as references. The mean absolute amplitude difference ([Formula: see text]) and the cross-correlation coefficient (CC) of the comparisons were determined. 4-D-MRI of the XCAT phantom demonstrated highly accurate motion information ([Formula: see text], [Formula: see text]). Motion trajectories of the motion phantom measured on 4-D-MRI matched well with the references ([Formula: see text], [Formula: see text]). 4-D-MRI of human subjects showed minimal artifacts and clearly revealed the respiratory motion of organs and tumor (mean [Formula: see text]; mean [Formula: see text]). A 4-D-MRI technique with image-based respiratory surrogate has been developed and tested on phantoms and human subjects.

Extraction of Respiratory Signal Based on Image Clustering and Intensity Parameters at Radiotherapy with External Beam: A Comparative Study

BACKGROUND

Since tumors located in thorax region of body mainly move due to respiration, in the modern radiotherapy, there have been many attempts such as; external markers, strain gage and spirometer represent for monitoring patients' breathing signal. With the advent of fluoroscopy technique, indirect methods were proposed as an alternative approach to extract patients' breathing signals.

MATERIALS AND METHODS

The purpose of this study is to extract respiratory signals using two available methods based on clustering and intensity strategies on medical image dataset of XCAT phantom.

RESULTS

For testing and evaluation methods, correlation coefficient, standard division, amplitude ratio and different phases are utilized. Phantom study showed excellent match between correlation coefficient, standard division, amplitude ratio and different phase. Both techniques segmenting medical images are robust due to their inherent mathematical properties. Using clustering strategy, lung region borders are remarkably extracted regarding intensity-based method. This may also affect the amount of amplitude signal.

CONCLUSION

To evaluate the performance of these methods, results are compared with slice body volume (SBV) method. Moreover, all methods have shown the same correlation coefficient of 99%, but at different amplitude ratio and different phase. In SBV method, standard division and different phase are better than clustering and intensity methods with SDR=4.71 mm, and SDL=4.12 mm and average different phase 1.47 %, but amplitude ration of clustering method is significantly more remarkable than SBV and intensity methods.

T2-weighted four dimensional magnetic resonance imaging with result-driven phase sorting

PURPOSE

T2-weighted MRI provides excellent tumor-to-tissue contrast for target volume delineation in radiation therapy treatment planning. This study aims at developing a novel T2-weighted retrospective four dimensional magnetic resonance imaging (4D-MRI) phase sorting technique for imaging organ/tumor respiratory motion.

METHODS

A 2D fast T2-weighted half-Fourier acquisition single-shot turbo spin-echo MR sequence was used for image acquisition of 4D-MRI, with a frame rate of 2-3 frames/s. Respiratory motion was measured using an external breathing monitoring device. A phase sorting method was developed to sort the images by their corresponding respiratory phases. Besides, a result-driven strategy was applied to effectively utilize redundant images in the case when multiple images were allocated to a bin. This strategy, selecting the image with minimal amplitude error, will generate the most representative 4D-MRI. Since we are using a different image acquisition mode for 4D imaging (the sequential image acquisition scheme) with the conventionally used cine or helical image acquisition scheme, the 4D dataset sufficient condition was not obviously and directly predictable. An important challenge of the proposed technique was to determine the number of repeated scans (NR) required to obtain sufficient phase information at each slice position. To tackle this challenge, the authors first conducted computer simulations using real-time position management respiratory signals of the 29 cancer patients under an IRB-approved retrospective study to derive the relationships between NR and the following factors: number of slices (NS), number of 4D-MRI respiratory bins (NB), and starting phase at image acquisition (P0). To validate the authors' technique, 4D-MRI acquisition and reconstruction were simulated on a 4D digital extended cardiac-torso (XCAT) human phantom using simulation derived parameters. Twelve healthy volunteers were involved in an IRB-approved study to investigate the feasibility of this technique.

RESULTS

4D data acquisition completeness (Cp) increases as NR increases in an inverse-exponential fashion (Cp = 100 - 99 × exp(-0.18 × NR), when NB = 6, fitted using 29 patients' data). The NR required for 4D-MRI reconstruction (defined as achieving 95% completeness, Cp = 95%, NR = NR,95) is proportional to NB (NR,95 ∼ 2.86 × NB, r = 1.0), but independent of NS and P0. Simulated XCAT 4D-MRI showed a clear pattern of respiratory motion. Tumor motion trajectories measured on 4D-MRI were comparable to the average input signal, with a mean relative amplitude error of 2.7% ± 2.9%. Reconstructed 4D-MRI for healthy volunteers illustrated clear respiratory motion on three orthogonal planes, with minimal image artifacts. The artifacts were presumably caused by breathing irregularity and incompleteness of data acquisition (95% acquired only). The mean relative amplitude error between critical structure trajectory and average breathing curve for 12 healthy volunteers is 2.5 ± 0.3 mm in superior-inferior direction.

CONCLUSIONS

A novel T2-weighted retrospective phase sorting 4D-MRI technique has been developed and successfully applied on digital phantom and healthy volunteers.

Internal respiratory surrogate in multislice 4D CT using a combination of Fourier transform and anatomical features

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Four-dimensional magnetic resonance imaging using axial body area as respiratory surrogate: initial patient results

PURPOSE

To evaluate the feasibility of a retrospective binning technique for 4-dimensional magnetic resonance imaging (4D-MRI) using body area (BA) as a respiratory surrogate.

METHODS AND MATERIALS

Seven patients with hepatocellular carcinoma (4 of 7) or liver metastases (3 of 7) were enrolled in an institutional review board-approved prospective study. All patients were simulated with both computed tomography (CT) and MRI to acquire 3-dimensional and 4D images for treatment planning. Multiple-slice multiple-phase cine-MR images were acquired in the axial plane for 4D-MRI reconstruction. Image acquisition time per slice was set to 10-15 seconds. Single-slice 2-dimensional cine-MR images were also acquired across the center of the tumor in orthogonal planes. Tumor motion trajectories from 4D-MRI, cine-MRI, and 4D-CT were analyzed in the superior-inferior (SI), anterior-posterior (AP), and medial-lateral (ML) directions, respectively. Their correlation coefficients (CC) and differences in tumor motion amplitude were determined. Tumor-to-liver contrast-to-noise ratio (CNR) was measured and compared between 4D-CT, 4D-MRI, and conventional T2-weighted fast spin echo MRI.

RESULTS

The means (± standard deviations) of CC comparing 4D-MRI with cine-MRI were 0.97 ± 0.03, 0.97 ± 0.02, and 0.99 ± 0.04 in SI, AP, and ML directions, respectively. The mean differences were 0.61 ± 0.17 mm, 0.32 ± 0.17 mm, and 0.14 ± 0.06 mm in SI, AP, and ML directions, respectively. The means of CC comparing 4D-MRI and 4D-CT were 0.95 ± 0.02, 0.94 ± 0.02, and 0.96 ± 0.02 in SI, AP, and ML directions, respectively. The mean differences were 0.74 ± 0.02 mm, 0.33 ± 0.13 mm, and 0.18 ± 0.07 mm in SI, AP, and ML directions, respectively. The mean tumor-to-tissue CNRs were 2.94 ± 1.51, 19.44 ± 14.63, and 39.47 ± 20.81 in 4D-CT, 4D-MRI, and T2-weighted MRI, respectively.

CONCLUSIONS

The preliminary evaluation of our 4D-MRI technique results in oncologic patients demonstrates its potential usefulness to accurately measure tumor respiratory motion with improved tumor CNR compared with 4D-CT.