Effect of novel amplitude/phase binning algorithm on commercial four-dimensional computed tomography quality

Commissioning a four‐dimensional Computed Tomography Simulator for minimum target size due to motion in the Anterior–Posterior direction: a procedure and treatment planning recommendations

The purpose of this work is to develop a procedure for commissioning four‐dimensional computed tomography (4DCT) algorithms for minimum target reconstruction size, to quantify the effect of anterior–posterior (AP) motion artifacts on known object reconstruction for periodic and irregular breathing patterns, and to provide treatment planning recommendations for target sizes below a minimum threshold. A mechanical platform enabled AP motion of a rod and lung phantom during 4DCT acquisition. Static, artifact‐free scans of the phantoms were first acquired. AP sinusoidal and patient breathing motion was applied to obtain 4DCT images. 4DCT reconstruction artifacts were assessed by measuring the apparent width and angle of the rod. Comparison of known tumor diameters and volumes between the static image parameters with the 4DCT image sets was used to quantify the extent of AP reconstruction artifact and contour deformation. Examination of the rod width, under sinusoidal motion, found it was best represented during the inhale and exhale phases for all periods and ranges of motion. From the gradient phases, the apparent width of the rod decreased with increasing amplitude and decreasing period. The rod angle appeared larger on the reconstructed images due to the presence of motion artifact. The apparent diameters of the spherical tumors on the gradient phases were larger/equivalent than the true values in the AP/LR direction, respectively, while the exhale phase consistently displayed the spheres at the approximately correct diameter. The Eclipse calculated diameter matched closely with the true diameter on the exhale phase and was found to be larger on the inhale, MIP, and Avg scans. The procedure detailed here may be used during the acceptance and commissioning period of a computed tomography simulator or retroactively when implementing a SBRT program to determine the minimum target size that can be reliably reconstructed.

A modern review of the uncertainties in volumetric imaging of respiratory-induced target motion in lung radiotherapy

Radiotherapy has become a critical component for the treatment of all stages and types of lung cancer, often times being the primary gateway to a cure. However, given that radiation can cause harmful side effects depending on how much surrounding healthy tissue is exposed, treatment of the lung can be particularly challenging due to the presence of moving targets. Careful implementation of every step in the radiotherapy process is absolutely integral for attaining optimal clinical outcomes. With the advent and now widespread use of stereotactic body radiation therapy (SBRT), where extremely large doses are delivered, accurate, and precise dose targeting is especially vital to achieve an optimal risk to benefit ratio. This has largely become possible due to the rapid development of image-guided technology. Although imaging is critical to the success of radiotherapy, it can often be plagued with uncertainties due to respiratory-induced target motion. There has and continues to be an immense research effort aimed at acknowledging and addressing these uncertainties to further our abilities to more precisely target radiation treatment. Thus, the goal of this article is to provide a detailed review of the prevailing uncertainties that remain to be investigated across the different imaging modalities, as well as to highlight the more modern solutions to imaging motion and their role in addressing the current challenges.

Definition of internal target volumes based on planar X-ray fluoroscopic images for lung and hepatic stereotactic body radiation therapy. Comparison to inhale/exhale CT technique

PURPOSE

To compare tumor motion amplitudes measured with 2D fluoroscopic images (FI) and with an inhale/exhale CT (IECT) technique MATERIALS AND METHODS: Tumor motion of 52 patients (39 lung patients and 13 liver patients) was obtained with both FI and IECT. For FI, tumor detection and tracking was performed by means of a software developed by the authors. Motion amplitude and, thus, internal target volume (ITV), were defined to cover the positions where the tumor spends 95% of the time. The algorithm was validated against two different respiratory motion phantoms. Motion amplitude in IECT was defined as the difference in the position of the centroid of the gross tumor volume in the image sets of both treatments.

RESULTS

Important differences exist when defining ITVs with FI and IECT. Overall, differences larger than 5 mm were obtained for 49%, 31%, and 9.6% of the patients in Superior-Inferior (SI), Anterior-Posterior (AP), and Lateral (LAT) directions, respectively. For tumor location, larger differences were found for tumors in the liver (73.6% SI, 27.3% AP, and 6.7% in LAT had differences larger than 5 mm), while tumors in the upper lobe benefitted less using FI (differences larger than 5 mm were only present in 27.6% (SI), 36.7% (AP), and 0% (LAT) of the patients).

CONCLUSIONS

Use of FI with the linac built-in CBCT system is feasible for ITV definition. Large differences between motion amplitudes detected with FI and IECT methods were found. The method presented in this work based on FI could represent an improvement in ITV definition compared to the method based on IECT due to FI permits tumor motion acquisition in a more realistic situation than IECT.

Clinical evaluation of three respiratory gating schemes for different respiratory patterns on cardiac SPECT

PURPOSE

Respiratory gating reduces respiratory blur in cardiac single photon emission computed tomography (SPECT). It can be implemented as three gating schemes: (a) equal amplitude-based gating (AG); (b) phase or time-based gating (TG); or (c) equal count-based gating (CG), that is, a variant of amplitude-based method. The goal of this study is to evaluate the effectiveness of these respiratory gating methods for patients with different respiratory patterns in myocardial perfusion SPECT.

METHODS

We reviewed 1274 anonymized patient respiratory traces obtained via the Vicon motion-tracking system during their ^99m Tc-sestamibi SPECT scans and grouped them into four breathing categories: (a) regular respiration (RR); (b) periodic respiration (PR); (c) respiration with apnea (AR); and (d) unclassified respiration (UR). For each respiratory pattern, 15 patients were randomly selected and their list-mode data were rebinned using the three gating schemes. A preliminary reconstruction was performed for each gate with the heart region segmented and registered to a reference gate to estimate the respiratory motion. A final reconstruction incorporating respiratory motion correction was done to get a final image set. The estimated respiratory motion, the full-width-at-half-maxima (FWHM) measured across the image intensity profile of the left ventricle wall, as well as the normalized standard deviation measured in a uniform cuboid region of the thorax were analyzed.

RESULTS

There are 47.1%, 24.3%, 13.5%, and 15.1% RR, PR, AR, and UR patients, respectively, among the 1274 patients in this study. The differences among the three gating schemes in RR were smaller than other respiratory patterns. The AG and CG methods showed statistically larger motion estimation than TG particularly in the AR and PR patterns. Noise of AG varied more in different gates, especially for AR and UR patterns.

CONCLUSION

More than half of the patients reviewed exhibited nonregular breathing patterns. Amplitude-based gating, that is, AG and CG, is a preferred gating method for such patterns and is a robust respiratory gating implementation method given the respiratory pattern of the patients is unknown before data acquisition. Phase gating is also a feasible option for regular respiratory pattern.

A novel amplitude binning strategy to handle irregular breathing during 4DMRI acquisition: improved imaging for radiotherapy purposes

Background

For radiotherapy of abdominal cancer, four-dimensional magnetic resonance imaging (4DMRI) is desirable for tumor definition and the assessment of tumor and organ motion. However, irregular breathing gives rise to image artifacts. We developed a outlier rejection strategy resulting in a 4DMRI with reduced image artifacts in the presence of irregular breathing.

Methods

We obtained 2D T2-weighted single-shot turbo spin echo images, with an interleaved 1D navigator acquisition to obtain the respiratory signal during free breathing imaging in 2 patients and 12 healthy volunteers. Prior to binning, upper and lower inclusion thresholds were chosen such that 95% of the acquired images were included, while minimizing the distance between the thresholds (inclusion range (IR)). We compared our strategy (Min95) with three commonly applied strategies: phase binning with all images included (Phase), amplitude binning with all images included (MaxIE), and amplitude binning with the thresholds set as the mean end-inhale and mean end-exhale diaphragm positions (MeanIE). We compared 4DMRI quality based on:

Data included (DI); percentage of images remaining after outlier rejection.

Reconstruction completeness (RC); percentage of bin-slice combinations containing at least one image after binning.

Intra-bin variation (IBV); interquartile range of the diaphragm position within the bin-slice combination, averaged over three central slices and ten respiratory bins.

IR.

Image smoothness (S); quantified by fitting a parabola to the diaphragm profile in a sagittal plane of the reconstructed 4DMRI.

A two-sided Wilcoxon’s signed-rank test was used to test for significance in differences between the Min95 strategy and the Phase, MaxIE, and MeanIE strategies.

Results

Based on the fourteen subjects, the Min95 binning strategy outperformed the other strategies with a mean RC of 95.5%, mean IBV of 1.6 mm, mean IR of 15.1 mm and a mean S of 0.90. The Phase strategy showed a poor mean IBV of 6.2 mm and the MaxIE strategy showed a poor mean RC of 85.6%, resulting in image artifacts (mean S of 0.76). The MeanIE strategy demonstrated a mean DI of 85.6%.

Conclusions

Our Min95 reconstruction strategy resulted in a 4DMRI with less artifacts and more precise diaphragm position reconstruction compared to the other strategies.

Trial registration

Volunteers: protocol W15_373#16.007; patients: protocol NL47713.018.14

Electronic supplementary material

The online version of this article (10.1186/s13014-019-1279-z) contains supplementary material, which is available to authorized users.

Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211

PURPOSE

The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application.

APPROACH

A brief description of the different types of PET-AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET-AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET-AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto-segmentation are addressed.

FINDINGS

A large number of PET-AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi-automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal-to-noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol.

CONCLUSIONS

Available comparison studies suggest that PET-AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to evaluating both existing and future PET-AS algorithms needs to be designed, to aid clinicians in evaluating and selecting PET-AS algorithms and to establish performance limits for their acceptance for clinical use. The initial steps toward designing and building such a standard are undertaken by the task group members.

Correction of hysteretic respiratory motion in SPECT myocardial perfusion imaging: Simulation and patient studies

PURPOSE

Amplitude-based respiratory gating is known to capture the extent of respiratory motion (RM) accurately but results in residual motion in the presence of respiratory hysteresis. In our previous study, we proposed and developed a novel approach to account for respiratory hysteresis by applying the Bouc-Wen (BW) model of hysteresis to external surrogate signals of anterior/posterior motion of the abdomen and chest with respiration. In this work, using simulated and clinical SPECT myocardial perfusion imaging (MPI) studies, we investigate the effects of respiratory hysteresis and evaluate the benefit of correcting it using the proposed BW model in comparison with the abdomen signal typically employed clinically.

METHODS

The MRI navigator data acquired in free-breathing human volunteers were used in the specially modified 4D NCAT phantoms to allow simulating three types of respiratory patterns: monotonic, mild hysteresis, and strong hysteresis with normal myocardial uptake, and perfusion defects in the anterior, lateral, inferior, and septal locations of the mid-ventricular wall. Clinical scans were performed using a Tc-99m sestamibi MPI protocol while recording respiratory signals from thoracic and abdomen regions using a visual tracking system (VTS). The performance of the correction using the respiratory signals was assessed through polar map analysis in phantom and 10 clinical studies selected on the basis of having substantial RM.

RESULTS

In phantom studies, simulations illustrating normal myocardial uptake showed significant differences (P < 0.001) in the uniformity of the polar maps between the RM uncorrected and corrected. No significant differences were seen in the polar map uniformity across the RM corrections. Studies simulating perfusion defects showed significantly decreased errors (P < 0.001) in defect severity and extent for the RM corrected compared to the uncorrected. Only for the strong hysteretic pattern, there was a significant difference (P < 0.001) among the RM corrections. The errors in defect severity and extent for the RM correction using abdomen signal were significantly higher compared to that of the BW (severity = -4.0%, P < 0.001; extent = -65.4%, P < 0.01) and chest (severity = -4.1%, P < 0.001; extent = -52.5%, P < 0.01) signals. In clinical studies, the quantitative analysis of the polar maps demonstrated qualitative and quantitative but not statistically significant differences (P = 0.73) between the correction methods that used the BW signal and the abdominal signal.

CONCLUSIONS

This study shows that hysteresis in respiration affects the extent of residual motion left in the RM-binned data, which can impact wall uniformity and the visualization of defects. Thus, there appears to be the potential for improved accuracy in reconstruction in the presence of hysteretic RM with the BW model method providing a possible step in the direction of improvement.

Automated identification and reduction of artifacts in cine four-dimensional computed tomography (4DCT) images using respiratory motion model

PURPOSE

Four-dimensional computed tomography (4DCT) images are often marred by artifacts that substantially degrade image quality and confound image interpretation. Human observation remains the standard method of 4DCT artifact evaluation, which is time-consuming and subjective. We develop a method to automatically identify and reduce artifacts in cine 4DCT images.

METHODS

We proposed an algorithm that consisted of two main stages: deformable image registration and respiratory motion simulation. Specifically, each 4DCT phase image was registered to the breath-holding CT image using the block-matching method, with erroneous spatial matches removed by the least median of squares filter and the full displacement vector field generated by the moving least squares interpolation. The lung's respiratory motion trajectory was then recovered from the displacement vector field using the parameterized polynomial function, with fitting parameters estimated by combinatorial optimization. In this way, artifacts were located according to deviations between image points and their motion trajectories and further corrected based on position prediction.

RESULTS

The mean spatial error (standard deviation) was 1.00 (0.85) mm after registration as opposed to 6.96 (4.61) mm before registration. In addition, we took human observation conducted by medical experts as the gold standard. The average sensitivity, specificity, and accuracy of the proposed method in artifact identification were 0.97, 0.84, and 0.89, respectively.

CONCLUSIONS

The proposed method identified and reduced artifacts accurately and automatically, providing an alternative way to analyze 4DCT image quality and to correct problematic images for radiation therapy.

Ventilation Series Similarity: A Study for Ventilation Calculation Using Deformable Image Registration and 4DCT to Avoid Motion Artifacts

The major problem with ventilation distribution calculations using DIR and 4DCT is the motion artifacts in 4DCT. Quite often not all phases would exhibit mushroom motion artifacts. If the ventilation series similarity is sufficiently robust, the ventilation distribution can be calculated using only the artifact-free phases. This study investigated the ventilation similarity among the data derived from different respiration phases. Fifteen lung cancer cases were analyzed. In each case, DIR was performed between the end-expiration phase and all other phases. Ventilation distributions were then calculated using the deformation matrices. The similarity was compared between the series ventilation distributions. The correlation between the majority phases was reasonably good, with average SCC values between 0.28 and 0.70 for the original data and 0.30 and 0.75 after smoothing. The better correlation between the neighboring phases, with average SCC values between 0.55 and 0.70 for the original data, revealed the nonlinear property of the dynamic ventilation. DSC analysis showed the same trend. To reduce the errors if motion artifacts are present, the phases without serious mushroom artifacts may be used. To minimize the effect of the nonlinearity in dynamic ventilation, the calculation phase should be chosen as close to the end-inspiration as possible.

Characterization of optical-surface-imaging-based spirometry for respiratory surrogating in radiotherapy

PURPOSE

To provide a comprehensive characterization of a novel respiratory surrogate that uses optical surface imaging (OSI) for accurate tidal volume (TV) measurement, dynamic airflow (TV') calculation, and quantitative breathing pattern (BP) estimation during free breathing (FB), belly breathing (BB), chest breathing (CB), and breath hold (BH).

METHODS

Optical surface imaging, which captures all respiration-induced torso surface motion, was applied to measure respiratory TV, TV', and BP in three common breathing patterns. Eleven healthy volunteers participated in breathing experiments with concurrent OSI-based and conventional spirometric measurements under an institutional review board approved protocol. This OSI-based technique measures dynamic TV from torso volume change (ΔVtorso = TV) in reference to full exhalation and airflow (TV' = dTV/dt). Volume conservation, excluding exchanging air, was applied for OSI-based measurements under negligible pleural pressure variation in FB, BB, and CB. To demonstrate volume conservation, a constant TV was measured during BH while the chest and belly are moving ("pretended" respiration). To assess the accuracy of OSI-based spirometry, a conventional spirometer was used as the standard for both TV and TV'. Using OSI, BP was measured as BP(OSI) = ΔVchest/ΔVtorso and BP can be visualized using BP(SHI) = SHIchest/(SHIchest + SHIbelly), where surface height index (SHI) is defined as the mean vertical distance within a region of interest on the torso surface. A software tool was developed for OSI image processing, volume calculation, and BP visualization, and another tool was implemented for data acquisition using a Bernoulli-type spirometer.

RESULTS

The accuracy of the OSI-based spirometry is -21 ± 33 cm(3) or -3.5% ± 6.3% averaged from 11 volunteers with 76 ± 28 breathing cycles on average in FB. Breathing variations between two separate acquisitions with approximate 30-min intervals are substantial: -1% ± 34% (ranging from -64% to 40%) in TV, 4% ± 20% (ranging from -50% to 26%) in breathing period (T), and -1% ± 34% (ranging from -49% to 44%) in BP. The airflow accuracy and variation (between two exercises) are -1 ± 54 cm(3)/s and -5% ± 30%, respectively. The slope of linear regression between OSI-TV and spirometric TV is 0.93 (R(2) = 0.95) for FB, 0.96 (R(2) = 0.98) for BB, and 0.95 (R(2) = 0.95) for CB. The correlation between the two spirometric measurements is 0.98 ± 0.01. BP increases from BB, FB to CB, while TV increases from FB, BB, to CB. Under BH, 4% volume variation (range) on average was observed.

CONCLUSIONS

The OSI-based technique provides an accurate measurement of tidal volume, airflow rate, and breathing pattern; all affect internal organ motion. This technique can be applied to various breathing patterns, including FB, BB, and CB. Substantial breathing irregularities and irreproducibility were observed and quantified with the OSI-based technique. These breathing parameters are useful to quantify breathing conditions, which could be used for effective tumor motion predictions.

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.

Adaptation of the modified Bouc-Wen model to compensate for hysteresis in respiratory motion for the list-mode binning of cardiac SPECT and PET acquisitions: testing using MRI

PURPOSE

Binning list-mode acquisitions as a function of a surrogate signal related to respiration has been employed to reduce the impact of respiratory motion on image quality in cardiac emission tomography (SPECT and PET). Inherent in amplitude binning is the assumption that there is a monotonic relationship between the amplitude of the surrogate signal and respiratory motion of the heart. This assumption is not valid in the presence of hysteresis when heart motion exhibits a different relationship with the surrogate during inspiration and expiration. The purpose of this study was to investigate the novel approach of using the Bouc-Wen (BW) model to provide a signal accounting for hysteresis when binning list-mode data with the goal of thereby improving motion correction. The study is based on the authors' previous observations that hysteresis between chest and abdomen markers was indicative of hysteresis between abdomen markers and the internal motion of the heart.

METHODS

In 19 healthy volunteers, they determined the internal motion of the heart and diaphragm in the superior-inferior direction during free breathing using MRI navigators. A visual tracking system (vts) synchronized with MRI acquisition tracked the anterior-posterior motions of external markers placed on the chest and abdomen. These data were employed to develop and test the Bouc-Wen model by inputting the vts derived chest and abdomen motions into it and using the resulting output signals as surrogates for cardiac motion. The data of the volunteers were divided into training and testing sets. The training set was used to obtain initial values for the model parameters for all of the volunteers in the set, and for set members based on whether they were or were not classified as exhibiting hysteresis using a metric derived from the markers. These initial parameters were then employed with the testing set to estimate output signals. Pearson's linear correlation coefficient between the abdomen, chest, average of chest and abdomen markers, and Bouc-Wen derived signals versus the true internal motion of the heart from MRI was used to judge the signals match to the heart motion.

RESULTS

The results show that the Bouc-Wen model generated signals demonstrated strong correlation with the heart motion. This correlation was slightly larger on average than that of the external surrogate signals derived from the abdomen marker, and average of the abdomen and chest markers, but was not statistically significantly different from them.

CONCLUSIONS

The results suggest that the proposed model has the potential to be a unified framework for modeling hysteresis in respiratory motion in cardiac perfusion studies and beyond.

Evaluation of 4D CT acquisition methods designed to reduce artifacts

Four-dimensional computed tomography (4D CT) is used to account for respiratory motion in radiation treatment planning, but artifacts resulting from the acquisition and postprocessing limit its accuracy. We investigated the efficacy of three experimental 4D CT acquisition methods to reduce artifacts in a prospective institutional review board approved study. Eighteen thoracic patients scheduled to undergo radiation therapy received standard clinical 4D CT scans followed by each of the alternative 4D CT acquisitions: 1) data oversampling, 2) beam gating with breathing irregularities, and 3) rescanning the clinical acquisition acquired during irregular breathing. Relative values of a validated correlation-based artifact metric (CM) determined the best acquisition method per patient. Each 4D CT was processed by an extended phase sorting approach that optimizes the quantitative artifact metric (CM sorting). The clinical acquisitions were also postprocessed by phase sorting for artifact comparison of our current clinical implementation with the experimental methods. The oversampling acquisition achieved the lowest artifact presence among all acquisitions, achieving a 27% reduction from the current clinical 4D CT implementation (95% confidence interval = 34-20). The rescan method presented a significantly higher artifact presence from the clinical acquisition (37%; p < 0.002), the gating acquisition (26%; p < 0.005), and the oversampling acquisition (31%; p < 0.001), while the data lacked evidence of a significant difference between the clinical, gating, and oversampling methods. The oversampling acquisition reduced artifact presence from the current clinical 4D CT implementation to the largest degree and provided the simplest and most reproducible implementation. The rescan acquisition increased artifact presence significantly, compared to all acquisitions, and suffered from combination of data from independent scans over which large internal anatomic shifts occurred.

Assessment of a quantitative metric for 4D CT artifact evaluation by observer consensus

The benefits of four-dimensional computed tomography (4D CT) are limited by the presence of artifacts that remain difficult to quantify. A correlation-based metric previously proposed for ciné 4D CT artifact identification was further validated as an independent artifact evaluator by using a novel qualitative assessment featuring a group of observers reaching a consensus decision on artifact location and magnitude. The consensus group evaluated ten ciné 4D CT scans for artifacts over each breathing phase of coronal lung views assuming one artifact per couch location. Each artifact was assigned a magnitude score of 1-5, 1 indicating lowest severity and 5 indicating highest severity. Consensus group results served as the ground truth for assessment of the correlation metric. The ten patients were split into two cohorts; cohort 1 generated an artifact identification threshold derived from receiver operating characteristic analysis using the Youden Index, while cohort 2 generated sensitivity and specificity values from application of the artifact threshold. The Pearson correlation coefficient was calculated between the correlation metric values and the consensus group scores for both cohorts. The average sensitivity and specificity values found with application of the artifact threshold were 0.703 and 0.476, respectively. The correlation coefficients of artifact magnitudes for cohort 1 and 2 were 0.80 and 0.61, respectively, (p < 0.001 for both); these correlation coefficients included a few scans with only two of the five possible magnitude scores. Artifact incidence was associated with breathing phase (p < 0.002), with presentation less likely near maximum exhale. Overall, the correlation metric allowed accurate and automated artifact identification. The consensus group evaluation resulted in efficient qualitative scoring, reduced interobserver variation, and provided consistent identification of artifact location and magnitudes.

MRI Investigation of the Linkage Between Respiratory Motion of the Heart and Markers on Patient's Abdomen and Chest: Implications for Respiratory Amplitude Binning List-Mode PET and SPECT Studies

Respiratory motion of the heart impacts the diagnostic accuracy of myocardial-perfusion emission-imaging studies. Amplitude binning has come to be the method of choice for binning list-mode based acquisitions for correction of respiratory motion in PET and SPECT. In some subjects respiratory motion exhibits hysteretic behavior similar to damped non-linear cyclic systems. The detection and correction of hysteresis between the signals from surface movement of the patient's body used in binning and the motion of the heart within the chest remains an open area for investigation. This study reports our investigation in nine volunteers of the combined MRI tracking of the internal respiratory motion of the heart using Navigators with stereo-tracking of markers on the volunteer's chest and abdomen by a visual-tracking system (VTS). The respiratory motion signals from the internal organs and the external markers were evaluated for hysteretic behavior analyzing the temporal correspondence of the signals. In general, a strong, positive correlation between the external marker motion (AP direction) and the internal heart motion (SI direction) during respiration was observed. The average ± standard deviation in the Spearman's ranked correlation coefficient (ρ) over the nine volunteer studied was 0.92 ± 0.1 between the external abdomen marker and the internal heart, and 0.87 ± 0.2 between the external chest marker and the internal heart. However despite the good correlation on average for the nine volunteers, in three studies a poor correlation was observed due to hysteretic behavior between inspiration and expiration for either the chest marker and the internal motion of the heart, or the abdominal marker and the motion of the heart. In all cases we observed a good correlation of at least either the abdomen or the chest with the heart. Based on this result, we propose the use of marker motion from both the chest and abdomen regions when estimating the internal heart motion to detect and address hysteresis when binning list-mode emission data.

Respiration-based sorting of dynamic MRI to derive representative 4D-MRI for radiotherapy planning

PURPOSE

Current pretreatment, 4D imaging techniques are suboptimal in that they sample breathing motion over a very limited "snap-shot" in time. To potentially address this, the authors have developed a longer-duration MRI and postprocessing technique to derive the average or most-probable state of mobile anatomy and meanwhile capture and convey the observed motion variability.

METHODS

Sagittal and coronal multislice, 2D dynamic MRI was acquired in a sequential fashion over extended durations in two abdominal and four lung studies involving healthy volunteers. Two sequences, readily available on a commercial system, were employed. Respiratory interval-correlated, or 4D-MRI, volumes were retrospectively derived using a two-pass approach. In a first pass, a respiratory trace acquired simultaneous with imaging was processed and slice stacking was used to derive a set of MRI volumes, each representing an equal time or proportion of respiration. Herein, all raw 2D frames mapping to the given respiratory interval, per slice location, were averaged. In a second-pass, this prior reconstruction provided a set of template images and a similarity metric was employed to discern the subset of best-matching raw 2D frames for secondary averaging (per slice location and respiratory interval). Breathing variability (per respiratory interval and slice location) was depicted by computing both a maximum intensity projection as well as a pixelwise standard deviation image.

RESULTS

These methods were successfully demonstrated in both the lung and abdomen for both applicable sequences, performing reconstructions with ten respiratory intervals. The first-pass (average) resulted in motion-induced blurring, especially for irregular breathing. The authors have demonstrated qualitatively that the second-pass result can mitigate this blurring.

CONCLUSIONS

They have presented a novel methodology employing dMRI to derive representative 4D-MRI. This set of techniques are practical in that (1) they employ MRI sequences that are standard across commercial vendors; (2) the 2D imaging planes can be oriented onto an arbitrary axis (e.g., sagittal, coronal, axial[ellipsis (horizontal)]); (3) the image processing techniques are relatively simple. Systematically applying this and similar dMRI-based techniques in patients is a crucial next step to demonstrate efficacy beyond CT-only based practice.

Evaluation of the dose variation for prostate heavy charged particle therapy using four-dimensional computed tomography

We quantified dose variation effects due to respiratory-induced intrafractional motion in conventional carbon-ion prostate treatment by using four-dimensional computed tomography (4DCT). 4DCT scans of 20 patients were acquired under free-breathing conditions using a 256 multi-slice CT scanner. The clinical target volume (CTV) was defined as the prostate and the seminal vesicle. Two types of planning target volumes (PTVs) were defined to minimize excessive dose to the rectum. The first PTV (= PTV1) was calculated by adding a 3D uniform margin to the CTV. The second PTV (= PTV2) was cut in a straight line from the top surface of the rectum from PTV1. Compensating boli were designed for the respective PTVs at the peak-exhalation phase, and carbon-ion dose distributions for a single respiratory cycle were calculated using these boli. Dose conformation to prostate, CTV, PTV1 and PTV2 were unchanged for all respiratory phases. The dose for >95% volume irradiation (D95) was 97.7% for prostate, 92.5% for CTV, 74.1% for PTV1 and 96.1% for PTV2 averaged over all patients. The rectum volume at inhalation phase receiving ≤50% of the prescribed dose was smaller than the planning dose due to the abdominal thickness variation. The target dose is not affected by intrafractional respiration in carbon-ion prostate treatment. Small dose variations, however, were observed due to respiratory-induced abdominal thickness variation; therefore the geometrical changes should be considered for prostate particle therapy.

Advances in 4D radiation therapy for managing respiration: part I - 4D imaging

Techniques for managing respiration during imaging and planning of radiation therapy are reviewed, concentrating on free-breathing (4D) approaches. First, we focus on detailing the historical development and basic operational principles of currently-available "first generation" 4D imaging modalities: 4D computed tomography, 4D cone beam computed tomography, 4D magnetic resonance imaging, and 4D positron emission tomography. Features and limitations of these first generation systems are described, including necessity of breathing surrogates for 4D image reconstruction, assumptions made in acquisition and reconstruction about the breathing pattern, and commonly-observed artifacts. Both established and developmental methods to deal with these limitations are detailed. Finally, strategies to construct 4D targets and images and, alternatively, to compress 4D information into static targets and images for radiation therapy planning are described.

Accuracy in the localization of thoracic and abdominal tumors using respiratory displacement, velocity, and phase

Current four dimensional (4D) computed tomography (CT) reconstruction techniques are retrospectively created based on either the phase or displacement of the respiratory signal. Both techniques have known limitations which cause clinically significant motion artifacts in 4D CT images. These artifacts, which appear as undefined or irregular boundaries in the 4D CT images, cause systematic errors in patient contouring and dose calculations. The aim of this work was to evaluate the reproducibility of tumor position as a function of displacement, phase, and velocity of the respiratory signal, respectively, in order to determine the optimum parameter or combination of parameters to use in order to minimize artifacts in 4D CT images or to accurately deliver radiation to relevant structures during treatment.

METHOD AND MATERIALS

Estimated tumor centroid position and respiratory signal data were acquired with the Cyberknife Synchrony system for 26 thoracic radiotherapy patients (52 fractions). A reference respiratory cycle was calculated for each patient. Displacement, phase, and velocity of ten data points were calculated from this reference respiratory cycle, where each point represents an image bin. The corresponding tumor position was then sorted into these image bins if the phase, displacement, simultaneous displacement and phase, or simultaneous displacement and velocity of the respiratory signal were within tolerances of 0.5 mm for displacement and 0.5 mm/s for velocity, respectively, from the corresponding data of the reference cycle for each image bin.

RESULTS

The mean of the standard deviations of tumor positions over all bins and all fractions for the superior-inferior direction were 2.13 +/- 1.01 mm for phase sorting, 1.20 +/- 0.76 mm for displacement sorting, 1.20 +/- 0.71 mm for simultaneous displacement and phase sorting, and 1.10 +/- 0.71 mm for simultaneous displacement and velocity sorting, with maximum deviations of 43.0, 16.1, 15.5, and 14.1 mm for each scenario, respectively. The same trend was observed for the anterior-posterior and left-right directions. A linear dependence was observed between the mean of the standard deviations of tumor positions over all fractions as a function of the velocity of the respiratory signal at each bin for all the sorting scenarios. A substantially larger gradient for the phase sorting scenario, compared to the other scenarios, suggests that tumor localization will become increasingly less accurate as the velocity of the tumor increases during a breathing cycle, e.g., if the amplitude of motion increases while the period of the respiratory cycle stays constant or during mid inhale or exhale phases of the respiratory cycle.

CONCLUSION

This study illustrates that position of a tumor can be determined more accurately if displacement and velocity are used simultaneously as sorting parameters for 4D CT images or during treatment. A real-time displacement and velocity based 4D CT image sorting method may therefore produce fewer and smaller artifacts in 4D CT images than current retrospective sorting methods.

Prospective displacement and velocity-based cine 4D CT

Four dimensional (4D) computed tomography (CT) image sorting is currently a retrospective procedure. Mismatches in displacement and/or phase of a patient's respiratory signal, corresponding with two dimensional images taken at subsequent couch positions, become visible as artifacts in reconstructed 4D CT images. These artifacts appear as undefined or irregular boundaries in the 4D CT images and cause systematic errors in patient contouring and dose calculations. In addition, the substantially higher dose required for 4D CT, compared with 3D CT, is of concern. To minimize these problems, we developed a prospective respiratory displacement and velocity based cine 4D CT (PDV CT) method to trigger image acquisition if the displacement and velocity of the respiratory signal occurred within predetermined tolerances simultaneously. The use of velocity avoids real-time phase estimation. Real-time image acquisition ensures data sufficiency, while avoiding the need for redundant data. This may potentially result in a lower dose to the patient. PDV CT was compared with retrospective 4D CT acquisition methods, using respiratory signals of 24 lung cancer patients (103 sessions) under free breathing conditions. Image acquisition was simulated for each of these sessions from the respiratory signal. The root mean square (RMS) of differences between displacements and velocities of the respiratory signal corresponding to subsequent images was calculated in order to evaluate the image-sorting accuracy of each method. Patient dose reductions of 22 to 50% were achieved during image acquisition depending on the model parameters chosen. The mean RMS differences over all sessions and image bins show that PDV CT produces similar results to retrospective displacement sorting overall, although improvements of the RMS difference up to 20% were achieved depending on the model parameters chosen. Velocity RMS differences improved between 30 and 45% when compared with retrospective phase sorting. The efficiency in acquisition compared with retrospective phase sorting varied from approximately 10% for displacement and velocity tolerances of 1 mm and 4 mm/s, respectively, to 80 to 93% for 4 mm and 4 mm/s. The lower variation in the displacement and velocity of the respiratory signal in each image bin indicates that PDV CT could be a valuable tool for reducing artifacts in 4D CT images and lowering patient dose, although the cost may be increased acquisition time.