Estimation of Error in Maximal Intensity Projection-Based Internal Target Volume of Lung Tumors: A Simulation and Comparison Study Using Dynamic Magnetic Resonance Imaging

Sorting lung tumor volumes from 4D-MRI data using an automatic tumor-based signal reduces stitching artifacts

PURPOSE

To investigate whether a novel signal derived from tumor motion allows more precise sorting of 4D-magnetic resonance (4D-MR) image data than do signals based on normal anatomy, reducing levels of stitching artifacts within sorted lung tumor volumes.

METHODS

(4D-MRI) scans were collected for 10 lung cancer patients using a 2D T2-weighted single-shot turbo spin echo sequence, obtaining 25 repeat frames per image slice. For each slice, a tumor-motion signal was generated using the first principal component of movement in the tumor neighborhood (TumorPC1). Signals were also generated from displacements of the diaphragm (DIA) and upper and lower chest wall (UCW/LCW) and from slice body area changes (BA). Pearson r coefficients of correlations between observed tumor movement and respiratory signals were determined. TumorPC1, DIA, and UCW signals were used to compile image stacks showing each patient's tumor volume in a respiratory phase. Unsorted image stacks were also built for comparison. For each image stack, the presence of stitching artifacts was assessed by measuring the roughness of the compiled tumor surface according to a roughness metric (Rg). Statistical differences in weighted means of Rg between any two signals were determined using an exact permutation test.

RESULTS

The TumorPC1 signal was most strongly correlated with superior-inferior tumor motion, and had significantly higher Pearson r values (median 0.86) than those determined for correlations of UCW, LCW, and BA with superior-inferior tumor motion (p < 0.05). Weighted means of ratios of Rg values in TumorPC1 image stacks to those in unsorted, UCW, and DIA stacks were 0.67, 0.69, and 0.71, all significantly favoring TumorPC1 (p = 0.02-0.05). For other pairs of signals, weighted mean ratios did not differ significantly from one.

CONCLUSION

Tumor volumes were smoother in 3D image stacks compiled using the first principal component of tumor motion than in stacks compiled with signals based on normal anatomy.

Dosimetric comparison of four-dimensional computed tomography based internal target volume against variations in respiratory motion during treatment between volumetric modulated arc therapy and three-dimensional conformal radiotherapy in lung stereotactic body radiotherapy

This study focused on the dosimetric impact of variations in respiratory motion during lung stereotactic body radiotherapy (SBRT). Dosimetric comparisons between volumetric modulated arc therapy (VMAT) and three-dimensional conformal radiotherapy (3DCRT) were performed using four-dimensional computed tomography (4DCT)-based internal target volumes (ITV). We created retrospective plans for ten patients with lung cancer who underwent SBRT using 3DCRT and VMAT techniques. A Delta4 Phantom + (ScandiDos, Uppsala, Sweden) was used to evaluate the dosimetric robustness of 4DCT-based ITV against variations in respiratory motion during treatment. We analyzed respiratory motion during treatment. Dose-volume histogram parameters were evaluated for the 95% dose (D95%) to the planning target volume (PTV) contoured on CT images obtained under free breathing. The correlations between patient respiratory parameters and dosimetric errors were also evaluated. In the phantom study, the average PTV D95% dose differences for all fractions were - 2.9 ± 4.4% (- 16.0 - 1.2%) and - 2.0 ± 2.8% (- 11.2 - 0.7%) for 3DCRT and VMAT, respectively. The average dose difference was < 3% for both 3DCRT and VMAT; however, in 5 out of 42 fractions in 3DCRT, the difference in PTV D95% was > 10%. Dosimetric errors were correlated with respiratory amplitude and velocity, and differences in respiratory amplitude between 4DCT and treatment days were the main factors causing dosimetric errors. The overall average dose error of the PTV D95% was small; however, both 3DCRT and VMAT cases exceeding 10% error were observed. Larger errors occurred with amplitude variation or baseline drift, indicating limited robustness of 4DCT-based ITV.

Individualized breathing trace quality assurance for lung radiotherapy patients undergoing 4DCT simulation

4DCT simulation is a popular solution for radiotherapy simulation of lung cancer patients as it allows the clinician to gain an appreciation for target motion during the patient breathing cycle. Resultant binning of images and production of the 4DCT dataset relies heavily on the recorded breathing trace; but quality assurance is not routinely performed on these and there lacks any substantial recommendations thereof. An application was created for Windows in C# that was able to analyze the VXP breathing trace files from Varian RPM/RGSC and quantify various metrics associated with the patient breathing cycle. This data was then used to consider errors in voluming of targets for several example cases in order to justify recommendations on quality assurance. For 281 real patient breathing traces from 4DCT simulation of lung targets, notable differences were found between RGSC and application calculations of phase data. For any new patient without individualized QA, the average marked phase calculation (which is used for 4DCT reconstruction) is only accurate to within 19% of the actual phases. The error in BPM within the scan due to breathing rate variation is 37%. The uncertainty in amplitude due to breathing variation is 34% in the mean. Phase uncertainty leads to misbinning which we have shown can lead to missing 66% of the target for gated treatment. Variation in inhalation/exhalation level leads to voluming errors which, without individualized QA, can be assumed to be 11% (PTV is smaller than actual). Without individualized quality assurance of patient breathing traces, large uncertainties have to be assumed for metrics of both phase and amplitude, leading to clinically significant uncertainties in treatment. It is recommended to perform individualized quality assurance as this provides the clinician with an accurate quantification of uncertainty for their patient.

Dosimetric robustness of lung tumor photon radiotherapy evaluated from multiple event CT imaging

PURPOSE

Intrafractional respiratory motion is a concern for lung tumor radiotherapy but full evaluation of its impact is hampered by the lack of images representing the true motion. This study presents a novel evaluation using free-breathing images acquired over realistic treatment times to study the dosimetric impact of respiratory motion in photon radiotherapy.

METHODS

Cine-CT images of 14 patients with lung cancer acquired during eight minutes of free-breathing at three occasions were used to simulate dose tracking of four different planning methods. These methods aimed to deliver 54 Gy in three fractions to D_50% of the target and were denoted as robust 4D (RB4), homogeneous fluence to the ITV (FLU) and an isodose prescription to the ITV with a high central dose (ISD), concurrently renormalized (IRN). Differences in dose coverage probability and homogeneity between the methods were quantified. Correlations between underdosage and attributes regarding the tumor and its motion were investigated.

RESULTS

Despite tumor motion amplitudes being larger than in the 4DCT all but FLU achieved the intended CTV D_50% for the cohort average. For all methods but IRN at least 93% of the patients would have received 95% of the intended dose. No differences in D_50% were found between RB4 and ISD nor IRN. However, RB4 led to better homogeneity.

CONCLUSIONS

Tumor motion in free-breathing not covered by the 4DCT had a small impact on dose. The RB4 is recommended for planning of free-breathing treatments. No factor was found that consistently correlated dose degradation with patient or motion attributes.

Evaluation of irregular breathing effects on internal target volume definition for lung cancer radiotherapy

PURPOSE

Irregular breathing may compromise the treated volume for free-breathing lung cancer patients during radiotherapy. We try to find a measure based on a breathing amplitude surrogate that can be used to select the patients who need further investigation of tumor motion to ensure that the internal target volume (ITV) provides reliant coverage of the tumor.

MATERIAL AND METHODS

Fourteen patients were scanned with four-dimensional computed tomography (4DCT) during free-breathing. The breathing motion was detected by a pneumatic bellows device used as a breathing amplitude surrogate. In addition to the 4DCT, a breath-hold (BH) scan and three cine CT imaging sessions were acquired. The cine images were taken at randomized intervals at a rate of 12 per minute for 8 minutes to allow tumor motion determination during a typical hypo-fractionated treatment scenario. A clinical target volume (CTV) was segmented in the BH CT and propagated over all cine images and 4DCT bins. The center-of-volume of the translated CTV (CTV_COV ) in the ten 4DCT bins were interconnected to define the 4DCT determined tumor trajectory (4DCT-TT). The volume of CTV inside ITV for all cine CTs was calculated and reported at the 10th percentile (V_CTV10% ). The deviations between CTV_COV in the cine CTs and the 4DCT-TT were calculated and reported at its 90th percentile (d_90% ). The standard deviation of the bellows amplitude peaks (SDP) and the ratio between large and normal inspirations, κ_rel , were tested as surrogates for V_CTV10% and d_90% .

RESULTS

The values of d_90% ranged from 0.6 to 5.2 mm with a mean of 2.2 mm. The values of V_CTV10% ranged from 59-93% with a mean of 78 %. The SDP had a moderate correlation (r = 0.87) to d_90% . Less correlation was seen between SDP and V_CTV10% (r = 0.77), κ_rel and d_90% (r = 0.75) and finally κ_rel and V_CTV10% (r = 0.75).

CONCLUSIONS

The ITV coverage had a large variation for some patients. SDP seems to be a feasible surrogate measure to select patients that needs further tumor motion determination.

Adaptive respiratory signal prediction using dual multi-layer perceptron neural networks

PURPOSE

To improve the prediction accuracy of respiratory signals by adapting the multi-layer perceptron neural network (MLP-NN) model to changing respiratory signals. We have previously developed an MLP-NN to predict respiratory signals obtained from a real-time position management (RPM) device. Preliminary testing results indicated that poor prediction accuracy may be observed after several seconds for irregular breathing patterns as only a set of fixed data was used in one-time training. To improve the prediction accuracy, we introduced a continuous learning technique using the updated training data to replace one-time learning using the fixed training data. We carried on this new prediction using an adaptation approach with dual MLP-NNs rather than single MLP-NN. When one MLP-NN was performing prediction of the respiratory signals, another one was being trained using the updated data and vice versa. The predicted performance was evaluated by root-mean-square-error (RMSE) between the predicted and true signals from 202 patients' respiratory patterns each with 1 min recording length. The effects of adding an additional network, training parameter, and respiratory signal irregularity on the performance of the new predictor were investigated based on four different network configurations: a single MLP-NN, high-computation dual MLP-NNs (U1), two different combinations of high- and low-computation dual MLP-NNs (U2 and U3). The RMSEs using U1 method were reduced by 34%, 19%, and 10% compared to those using MLP-NN, U2 and U3 methods, respectively. Continuous training of an MLP-NN based on a dual-network configuration using updated respiratory signals improved prediction accuracy compared to one-time training of an MLP-NN using fixed signals.

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.

Development and prospective in-patient proof-of-concept validation of a surface photogrammetry + CT-based volumetric motion model for lung radiotherapy

PURPOSE

We develop and validate a motion model that uses real-time surface photogrammetry acquired concurrently with four-dimensional computed tomography (4DCT) to estimate respiration-induced changes within the entire irradiated volume, over arbitrarily many respiratory cycles.

METHODS

A research, couch-mounted, VisionRT (VRT) system was used to acquire optical surface data (15 Hz, ROI = 15 × 20 cm² ) from the thoraco-abdominal surface of a consented lung SBRT patient, concurrently with their standard-of-care 4DCT. The end-exhalation phase from the 4DCT was regarded as reference and for each remaining phase, deformation vector fields (DVFs) with respect to the reference phase were computed. To reduce dimensionality, the first two principal components (PCs) of the matrix of nine DVFs were calculated. In parallel, ten phase-averaged VRT surfaces were created. Surface DVFs and corresponding PCs were computed. A principal least squares regression was used to relate the PCs of surface DVF to those of volume DVFs, establishing a relationship between time-varying surface and the underlying time-varying volume. Proof-of-concept validation was performed during each treatment fraction by concurrently acquiring 30 s time series of real-time surface data and "ground truth" kV fluoroscopic data (FL). A ray-tracing algorithm was used to create a digitally reconstructed fluorograph (DRF), and motion trajectories of high-contrast, soft-tissue, anatomical features in the DRF were compared with those from kV FL.

RESULTS

For five of the six fluoroscopic acquisition sessions, the model out-performed 4DCT in predicting contour Dice coefficient with respect to fluoroscopy-derived contours. Similarly, the model exhibited a marked improvement over 4DCT for patch positions on the diaphragm. Model patch position errors varied from 5 to -15 mm while 4DCT errors ranged between 5 and -22.4 mm. For one fluoroscopic acquisition, a marked change in the a priori internal-external correlation resulted in model errors comparable to those of 4DCT.

CONCLUSIONS

We described the development and a proof-of-concept validation for a volumetric motion model that uses surface photogrammetry to correlate the time-varying thoraco-abdominal surface to the time-varying internal thoraco-abdominal volume. These early results indicate that the proposed approach can result in a marked improvement over 4DCT. While limited by the duration of the fluoroscopic acquisitions as well as the resolution of the acquired images, the DRF-based proof-of-concept technique developed here is model-agnostic, and therefore, has the potential to be used as an in-patient validation tool for other volumetric motion models.

The irregular breathing effect on target volume and coverage for lung stereotactic body radiotherapy

The major challenge in treating a mobile target is obtaining the temporal and spatial information imaging and treatment details. This phantom study quantitatively evaluates the geometric and dosimetric effects of various treatment techniques under different respiratory patterns. The regular motion model was a sinusoidal waveform with a longitudinal range of ±1.5 cm and a period of 4 sec, while irregular motion models were generated by extracting signals from clinical cases. Helical CT for a static target and 4D CT with retrospective sorting were acquired. Phase bin, maximum, and average intensity projection (MIP and AIP) CT datasets were reconstructed. RapidArc and IMRT plans were generated on static and moving target CT datasets with different motion patterns using the phase-based gating and nongating treatment. Dose measurements were performed using EBT3 films. Dose profile and gamma analysis (±3%/1 mm criteria) were used for dose comparisons. For the irregular motions, internal target volume variations between AIP and MIP datasets (AIP/MIP) had slight differences (-6.2% to -7.7%) for gated plans, and larger differences (-12.3% to -15.2%) for nongated plans. Dosimetric measurements showed a high gamma passing rate (>98.5%) for the static plan in the target region, while the AIP and MIP gated plans had average passing rates of 92.2% ± 5.7% and 85.8% ± 9.5%, respectively. Nongated plans had significantly lower and deviated passing rates, while the AIP and MIP plans had passing rates of 43.6% ± 22.2% and 66.7% ± 28.2%, respectively (p < 0.05). Lung stereotactic body radiotherapy treatment delivered with the gated technique did not compromise the gross tumor volumes coverage, and was insensitive to the breathing irregularities and plan techniques. Adequate margins should be accounted to cover the mis-gating effect when using the phase-based gating under irregular motion.

Initial clinical observations of intra- and interfractional motion variation in MR-guided lung SBRT

OBJECTIVE

To evaluate variations in intra- and interfractional tumour motion, and the effect on internal target volume (ITV) contour accuracy, using deformable image registration of real-time two-dimensional-sagittal cine-mode MRI acquired during lung stereotactic body radiation therapy (SBRT) treatments.

METHODS

Five lung tumour patients underwent free-breathing SBRT treatments on the ViewRay system, with dose prescribed to a planning target volume (defined as a 3-6 mm expansion of the 4DCT-ITV). Sagittal slice cine-MR images (3.5 × 3.5 mm² pixels) were acquired through the centre of the tumour at 4 frames per second throughout the treatments (3-4 fractions of 21-32 min). Tumour gross tumour volumes (GTVs) were contoured on the first frame of the MR cine and tracked for the first 20 min of each treatment using offline optical-flow based deformable registration implemented on a GPU cluster. A ground truth ITV (MR-ITV_20 min) was formed by taking the union of tracked GTV contours. Pseudo-ITVs were generated from unions of the GTV contours tracked over 10 s segments of image data (MR-ITV_10 s).

RESULTS

Differences were observed in the magnitude of median tumour displacement between days of treatments. MR-ITV_10 s areas were as small as 46% of the MR-ITV_20 min.

CONCLUSION

An ITV offers a "snapshot" of breathing motion for the brief period of time the tumour is imaged on a specific day. Real-time MRI over prolonged periods of time and over multiple treatment fractions shows that ITV size varies. Further work is required to investigate the dosimetric effect of these results. Advances in knowledge: Five lung tumour patients underwent free-breathing MRI-guided SBRT treatments, and their tumours tracked using deformable registration of cine-mode MRI. The results indicate that variability of both intra- and interfractional breathing amplitude should be taken into account during planning of lung radiotherapy.

Contour propagation for lung tumor delineation in 4D-CT using tensor-product surface of uniform and non-uniform closed cubic B-splines

A robust contour propagation method is proposed to help physicians delineate lung tumors on all phase images of four-dimensional computed tomography (4D-CT) by only manually delineating the contours on a reference phase. The proposed method models the trajectory surface swept by a contour in a respiratory cycle as a tensor-product surface of two closed cubic B-spline curves: a non-uniform B-spline curve which models the contour and a uniform B-spline curve which models the trajectory of a point on the contour. The surface is treated as a deformable entity, and is optimized from an initial surface by moving its control vertices such that the sum of the intensity similarities between the sampling points on the manually delineated contour and their corresponding ones on different phases is maximized. The initial surface is constructed by fitting the manually delineated contour on the reference phase with a closed B-spline curve. In this way, the proposed method can focus the registration on the contour instead of the entire image to prevent the deformation of the contour from being smoothed by its surrounding tissues, and greatly reduce the time consumption while keeping the accuracy of the contour propagation as well as the temporal consistency of the estimated respiratory motions across all phases in 4D-CT. Eighteen 4D-CT cases with 235 gross tumor volume (GTV) contours on the maximal inhale phase and 209 GTV contours on the maximal exhale phase are manually delineated slice by slice. The maximal inhale phase is used as the reference phase, which provides the initial contours. On the maximal exhale phase, the Jaccard similarity coefficient between the propagated GTV and the manually delineated GTV is 0.881 [Formula: see text] 0.026, and the Hausdorff distance is 3.07 [Formula: see text] 1.08 mm. The time for propagating the GTV to all phases is 5.55 [Formula: see text] 6.21 min. The results are better than those of the fast adaptive stochastic gradient descent B-spline method, the 3D  +  t B-spline method and the diffeomorphic demons method. The proposed method is useful for helping physicians delineate target volumes efficiently and accurately.

Comparison of lung tumor motion measured using a model-based 4DCT technique and a commercial protocol

PURPOSE

To compare lung tumor motion measured with a model-based technique to commercial 4-dimensional computed tomography (4DCT) scans and describe a workflow for using model-based 4DCT as a clinical simulation protocol.

METHODS AND MATERIALS

Twenty patients were imaged using a model-based technique and commercial 4DCT. Tumor motion was measured on each commercial 4DCT dataset and was calculated on model-based datasets for 3 breathing amplitude percentile intervals: 5th to 85th, 5th to 95th, and 0th to 100th. Internal target volumes (ITVs) were defined on the 4DCT and 5th to 85th interval datasets and compared using Dice similarity. Images were evaluated for noise and rated by 2 radiation oncologists for artifacts.

RESULTS

Mean differences in tumor motion magnitude between commercial and model-based images were 0.47 ± 3.0, 1.63 ± 3.17, and 5.16 ± 4.90 mm for the 5th to 85th, 5th to 95th, and 0th to 100th amplitude intervals, respectively. Dice coefficients between ITVs defined on commercial and 5th to 85th model-based images had a mean value of 0.77 ± 0.09. Single standard deviation image noise was 11.6 ± 9.6 HU in the liver and 6.8 ± 4.7 HU in the aorta for the model-based images compared with 57.7 ± 30 and 33.7 ± 15.4 for commercial 4DCT. Mean model error within the ITV regions was 1.71 ± 0.81 mm. Model-based images exhibited reduced presence of artifacts at the tumor compared with commercial images.

CONCLUSION

Tumor motion measured with the model-based technique using the 5th to 85th percentile breathing amplitude interval corresponded more closely to commercial 4DCT than the 5th to 95th or 0th to 100th intervals, which showed greater motion on average. The model-based technique tended to display increased tumor motion when breathing amplitude intervals wider than 5th to 85th were used because of the influence of unusually deep inhalations. These results suggest that care must be taken in selecting the appropriate interval during image generation when using model-based 4DCT methods.

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.

Impact of incorporating visual biofeedback in 4D MRI

Precise radiation therapy (RT) for abdominal lesions is complicated by respiratory motion and suboptimal soft tissue contrast in 4D CT. 4D MRI offers improved con-trast although long scan times and irregular breathing patterns can be limiting. To address this, visual biofeedback (VBF) was introduced into 4D MRI. Ten volunteers were consented to an IRB-approved protocol. Prospective respiratory-triggered, T2-weighted, coronal 4D MRIs were acquired on an open 1.0T MR-SIM. VBF was integrated using an MR-compatible interactive breath-hold control system. Subjects visually monitored their breathing patterns to stay within predetermined tolerances. 4D MRIs were acquired with and without VBF for 2- and 8-phase acquisitions. Normalized respiratory waveforms were evaluated for scan time, duty cycle (programmed/acquisition time), breathing period, and breathing regularity (end-inhale coefficient of variation, EI-COV). Three reviewers performed image quality assessment to compare artifacts with and without VBF. Respiration-induced liver motion was calculated via centroid difference analysis of end-exhale (EE) and EI liver contours. Incorporating VBF reduced 2-phase acquisition time (4.7 ± 1.0 and 5.4 ± 1.5 min with and without VBF, respectively) while reducing EI-COV by 43.8% ± 16.6%. For 8-phase acquisitions, VBF reduced acquisition time by 1.9 ± 1.6 min and EI-COVs by 38.8% ± 25.7% despite breathing rate remaining similar (11.1 ± 3.8 breaths/min with vs. 10.5 ± 2.9 without). Using VBF yielded higher duty cycles than unguided free breathing (34.4% ± 5.8% vs. 28.1% ± 6.6%, respectively). Image grading showed that out of 40 paired evaluations, 20 cases had equivalent and 17 had improved image quality scores with VBF, particularly for mid-exhale and EI. Increased liver excursion was observed with VBF, where superior-inferior, anterior-posterior, and left-right EE-EI displacements were 14.1± 5.8, 4.9 ± 2.1, and 1.5 ± 1.0 mm, respectively, with VBF compared to 11.9 ± 4.5, 3.7 ± 2.1, and 1.2 ± 1.4 mm without. Incorporating VBF into 4D MRI substantially reduced acquisition time, breathing irregularity, and image artifacts. However, differences in excursion were observed, thus implementation will be required throughout the RT workflow.

Magnetic resonance imaging in lung: a review of its potential for radiotherapy

MRI has superior soft-tissue definition compared with existing imaging modalities in radiation oncology; this has the added benefit of functional as well as anatomical imaging. This review aimed to evaluate the current use of MRI for lung cancer and identify the potential of a MRI protocol for lung radiotherapy (RT). 30 relevant studies were identified. Improvements in MRI technology have overcome some of the initial limitations of utilizing MRI for lung imaging. A number of commercially available and novel sequences have shown image quality to be adequate for the detection of pulmonary nodules with the potential for tumour delineation. Quantifying tumour motion is also feasible and may be more representative than that seen on four-dimensional CT. Functional MRI sequences have shown correlation with flu-deoxy-glucose positron emission tomography (FDG-PET) in identifying malignant involvement and treatment response. MRI can also be used as a measure of pulmonary function. While there are some limitations for the adoption of MRI in RT-planning process for lung cancer, MRI has shown the potential to compete with both CT and PET for tumour delineation and motion definition, with the added benefit of functional information. MRI is well placed to become a significant imaging modality in RT for lung cancer.

Lung dynamic MRI deblurring using low-rank decomposition and dictionary learning

PURPOSE

Lung dynamic MRI (dMRI) has emerged to be an appealing tool to quantify lung motion for both planning and treatment guidance purposes. However, this modality can result in blurry images due to intrinsically low signal-to-noise ratio in the lung and spatial/temporal interpolation. The image blurring could adversely affect the image processing that depends on the availability of fine landmarks. The purpose of this study is to reduce dMRI blurring using image postprocessing.

METHODS

To enhance the image quality and exploit the spatiotemporal continuity of dMRI sequences, a low-rank decomposition and dictionary learning (LDDL) method was employed to deblur lung dMRI and enhance the conspicuity of lung blood vessels. Fifty frames of continuous 2D coronal dMRI frames using a steady state free precession sequence were obtained from five subjects including two healthy volunteer and three lung cancer patients. In LDDL, the lung dMRI was decomposed into sparse and low-rank components. Dictionary learning was employed to estimate the blurring kernel based on the whole image, low-rank or sparse component of the first image in the lung MRI sequence. Deblurring was performed on the whole image sequences using deconvolution based on the estimated blur kernel. The deblurring results were quantified using an automated blood vessel extraction method based on the classification of Hessian matrix filtered images. Accuracy of automated extraction was calculated using manual segmentation of the blood vessels as the ground truth.

RESULTS

In the pilot study, LDDL based on the blurring kernel estimated from the sparse component led to performance superior to the other ways of kernel estimation. LDDL consistently improved image contrast and fine feature conspicuity of the original MRI without introducing artifacts. The accuracy of automated blood vessel extraction was on average increased by 16% using manual segmentation as the ground truth.

CONCLUSIONS

Image blurring in dMRI images can be effectively reduced using a low-rank decomposition and dictionary learning method using kernels estimated by the sparse component.

Feasibility of automated pancreas segmentation based on dynamic MRI

OBJECTIVE

MRI-guided radiotherapy is particularly attractive for abdominal targets with low CT contrast. To fully utilize this modality for pancreas tracking, automated segmentation tools are needed. A hybrid gradient, region growth and shape constraint (hGReS) method to segment two-dimensional (2D) upper abdominal dynamic MRI (dMRI) is developed for this purpose.

METHODS

2D coronal dynamic MR images of two healthy volunteers were acquired with a frame rate of 5 frames per second. The regions of interest (ROIs) included the liver, pancreas and stomach. The first frame was used as the source where the centres of the ROIs were manually annotated. These centre locations were propagated to the next dMRI frame. Four-neighborhood region transfer growth was performed from these initial seeds before refinement using shape constraints. RESULTS from hGReS and two other automated segmentation methods using integrated edge detection and region growth (IER) and level set, respectively, were compared with manual contours using Dice's index (DI).

RESULTS

For the first patient, the hGReS resulted in the organ segmentation accuracy as a measure by the DI (0.77) for the pancreas, superior to the level set method (0.72) and IER (0.71). The hGReS was shown to be reproducible on the second subject, achieving a DI of 0.82, 0.92 and 0.93 for the pancreas, stomach and liver, respectively. Motion trajectories derived from the hGReS were highly correlated to respiratory motion.

CONCLUSION

We have shown the feasibility of automated segmentation of the pancreas anatomy on dMRI.

ADVANCES IN KNOWLEDGE

Using the hybrid method improves segmentation robustness of low-contrast images.

Determination of internal target volume for radiation treatment planning of esophageal cancer by using 4-dimensional computed tomography (4DCT)

PURPOSE

To determine an efficient strategy for the generation of the internal target volume (ITV) for radiation treatment planning for esophageal cancer using 4-dimensional computed tomography (4DCT).

METHODS AND MATERIALS

4DCT sets acquired for 20 patients with esophageal carcinoma were analyzed. Each of the 4DCT sets was binned into 10 respiratory phases. For each patient, the gross tumor volume (GTV) was delineated on the 4DCT set at each phase. Various strategies to derive ITV were explored, including the volume from the maximum intensity projection (MIP; ITV_MIP), unions of the GTVs from selected multiple phases ITV2 (0% and 50% phases), ITV3 (ITV2 plus 80%), and ITV4 (ITV3 plus 60%), as well as the volumes expanded from ITV2 and ITV3 with a uniform margin. These ITVs were compared to ITV10 (the union of the GTVs for all 10 phases) and the differences were measured with the overlap ratio (OR) and relative volume ratio (RVR) relative to ITV10 (ITVx/ITV10).

RESULTS

For all patients studied, the average GTV from a single phase was 84.9% of ITV10. The average ORs were 91.2%, 91.3%, 94.5%, and 96.4% for ITV_MIP, ITV2, ITV3, and ITV4, respectively. Low ORs were associated with irregular breathing patterns. ITV3s plus 1 mm uniform margins (ITV3+1) led to an average OR of 98.1% and an average RVR of 106.4%.

CONCLUSIONS

The ITV generated directly from MIP underestimates the range of the respiration motion for esophageal cancer. The ITV generated from 3 phases (ITV3) may be used for regular breathers, whereas the ITV generated from 4 phases (ITV4) or ITV3 plus a 1-mm uniform margin may be applied for irregular breathers.

Strategies of dose escalation in the treatment of locally advanced non-small cell lung cancer: image guidance and beyond

Radiation dose in the setting of chemo-radiation for locally advanced non-small cell lung cancer (NSCLC) has been historically limited by the risk of normal tissue toxicity and this has been hypothesized to correlate with the poor results in regard to local tumor recurrences. Dose escalation, as a means to improve local control, with concurrent chemotherapy has been shown to be feasible with three-dimensional conformal radiotherapy in early phase studies with good clinical outcome. However, the potential superiority of moderate dose escalation to 74 Gy has not been shown in phase III randomized studies. In this review, the limitations in target volume definition in previous studies; and the factors that may be critical to safe dose escalation in the treatment of locally advanced NSCLC, such as respiratory motion management, image guidance, intensity modulation, FDG-positron emission tomography incorporation in the treatment planning process, and adaptive radiotherapy, are discussed. These factors, along with novel treatment approaches that have emerged in recent years, are proposed to warrant further investigation in future trials in a more comprehensive and integrated fashion.

Efficacy evaluation of retrospectively applying the Varian normal breathing predictive filter for volume definition and artifact reduction in 4D CT lung patients

Phase-based sorting of four-dimensional computed tomography (4D CT) datasets is prone to image artifacts due to patient's breathing irregularities that occur during the image acquisition. The purpose of this study is to investigate the effect of the Varian normal breathing predictive filter (NBPF) as a retrospective phase-sorting parameter in 4D CT. Ten 4D CT lung cancer datasets were obtained. The volumes of all tumors present, as well as the total lung volume, were calculated on the maximum intensity projection (MIP) images as well as each individual phase image. The NBPF was varied retrospectively within the available range, and changes in volume and image quality were recorded. The patients' breathing trace was analysed and the magnitude and location of any breathing irregularities were correlated to the behavior of the NBPF. The NBPF was found to have a considerable effect on the quality of the images in MIP and single-phase datasets. When used appropriately, the NBPF is shown to have the ability to account for and correct image artifacts. However, when turned off (0%) or set above a critical level (approximately 40%), it resulted in erroneous volume reconstructions with variations in tumor volume up to 26.6%. Those phases associated with peak inspiration were found to be more susceptible to changes in the NBPF. The NBPF settings selected prior to exporting the breathing trace for patients evaluated using 4D CT directly affect the accuracy of the targeting and volume estimation of lung tumors. Recommendations are made to address potential errors in patient anatomy introduced by breathing irregularities, specifically deep breath or cough irregularities, by implementing the proper settings and use of this tool.

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.

Dosimetric comparison of treatment plans based on free breathing, maximum, and average intensity projection CTs for lung cancer SBRT

PURPOSE

To determine whether there is a CT dataset may be more favorable for planning and dose calculation by comparing dosimetric characteristics between treatment plans calculated using free breathing (FB), maximum and average intensity projection (MIP and AIP, respectively) CTs for lung cancer patients receiving stereotactic body radiation therapy (SBRT).

METHODS

Twenty lung cancer SBRT patients, treated on a linac with 2.5 mm width multileaf-collimator (MLC), were analyzed retrospectively. Both FB helical and four-dimensional CT scans were acquired for each patient. Internal target volume (ITV) was delineated based on MIP CTs and modified based on both ten-phase datasets and FB CTs. Planning target volume (PTV) was then determined by adding additional setup margin to ITV. The PTVs and beams in the optimized treatment plan based on FB CTs were copied to MIP and AIP CTs, with the same isocenters, MLC patterns and monitor units. Mean effective depth (MED) of beams, and some dosimetric parameters for both PTVs and most important organ at risk (OAR), lung minus PTV, were compared between any two datasets using two-tail paired t test.

RESULTS

The MEDs in FB and AIP plans were similar but significantly smaller (Ps < 0.001) than that in MIP plans. Minimum dose, mean dose, dose covering at least 90% and 95% of PTVs in MIP plans were slightly higher than two other plans (Ps < 0.008). The absolute volume of lung minus PTV receiving greater than 5, 10, and 20 Gy in MIP plans were significantly smaller than those in both FB and AIP plans (Ps < 0.008). Conformity index for FB plans showed a small but statistically significantly higher.

CONCLUSIONS

Dosimetric characteristics of AIP plans are similar to those of FB plans. Slightly better target volume coverage and significantly lower low-dose region (≤30 Gy) in lung was observed in MIP plans. The decrease in low-dose region in lung was mainly caused by the change of lung volume contoured on two datasets rather than the differences of dose distribution between AIP and MIP plans. Compare with AIP datasets, FB datasets were more prone to significant image artifacts and MIP datasets may overestimate or underestimate the target volume when the target is closer to the denser tissue, so AIP seems favorable for planning and dose calculation for lung SBRT.

Quantification and minimization of uncertainties of internal target volume for stereotactic body radiation therapy of lung cancer

PURPOSE

To quantify uncertainties in delineating an internal target volume (ITV) and to understand how these uncertainties may be individually minimized for stereotactic body radiation therapy (SBRT) of early stage non-small cell lung cancer (NSCLC).

METHODS AND MATERIALS

Twenty patients with NSCLC who were undergoing SBRT were imaged with free-breathing 3-dimensional computed tomography (3DCT) and 10-phase 4-dimensional CT (4DCT) for delineating gross tumor volume (GTV)(3D) and ITV(10Phase) (ITV3). The maximum intensity projection (MIP) CT was also calculated from 10-phase 4DCT for contouring ITV(MIP) (ITV1). Then, ITV(COMB) (ITV2), ITV(10Phase+GTV3D) (ITV4), and ITV(10Phase+ITVCOMB) (ITV5) were generated by combining ITV(MIP) and GTV(3D), ITV(10phase) and GTV(3D), and ITV(10phase) and ITV(COMB), respectively. All 6 volumes (GTV(3D) and ITV1 to ITV5) were delineated in the same lung window by the same radiation oncologist. The percentage of volume difference (PVD) between any 2 different volumes was determined and was correlated to effective tumor diameter (ETD), tumor motion ranges, R(3D), and the amplitude variability of the recorded breathing signal (v) to assess their volume variations.

RESULTS

The mean (range) tumor motion (R(SI), R(AP), R(ML), and R(3D)) and breathing variability (v) were 7.6 mm (2-18 mm), 4.0 mm (2-8 mm), 3.3 mm (0-7.5 mm), 9.9 mm (4.1-18.7 mm), and 0.17 (0.07-0.37), respectively. The trend of volume variation was GTV(3D) <ITV1 <ITV2 ≈ ITV3 < ITV4 < ITV5. The means ± SDs of these volumes were 11.1 ± 9.3 cc, 13.2 ± 10.5 cc, 14.9 ± 11.0 cc, 14.7 ± 11.4 cc, 15.9 ± 11.7 cc, and 16.4 ± 11.8 cc, respectively. All comparisons between the target volumes showed statistical significance (P≤.001), except for ITV2 and ITV3 (P=.594). The PVDs for all volume pairs correlated negatively with ETD (r≤-0.658, P≤.006) and positively with R(3D) (r≥0.503, P≤.047). The PVDs for pairs of ITV2 vs ITV5 and ITV5 vs ITV4 negatively correlated with ETD (r=0.502, -0.626; P=.047, .010). No other correlation was found.

CONCLUSION

Uncertainties in individualized ITVs for SBRT of early stage NSCLC could effectively be minimized by combining information from 3DCT, 4DCT, and MIP. If these images cannot be efficiently contoured, a combination of ITV(MIP) and GTV(3D) could be an effective alternative.

Maximum intensity projection (MIP) imaging using slice-stacking MRI

PURPOSE

To evaluate the feasibility of acquiring maximum intensity projection (MIP) images using a novel slice-stacking MRI (SS-MRI) technique.

METHODS

The proposed technique employed a steady state acquisition sequence to image multiple axial slices. At each axial slice, the scan is repeated throughout one respiratory cycle. Four objects (small, medium, and large triangles, and a cylinder) moving with a patient breathing trajectory were imaged repeatedly for six times using the slice-stacking MRI and 4D-CT. MIP(SS-MRI) and MIP(4D-CT) were reconstructed. The internal target volume (ITV) was segmented for each object on the six scans and compared between MIP(SS-MRI) and MIP(4D-CT). The medium triangle was also imaged with various motion patterns using slice-stacking MRI, 4D-CT, and sagittal cine-MRI. The corresponding MIP images were reconstructed and volume/area measurements were performed and compared between different imaging methods. Three healthy volunteers underwent the slice-stacking MRI and sagittal cine-MRI scans. A region of interest (ROI) was selected and contoured for each subject in both MIP(SS-MRI) and MIP(cine-MRI). The area of the selected ROI was computed and compared.

RESULTS

Volume comparison between MIP(SS-MRI) and MIP(4D-CT) showed statistically insignificant (p > 0.05 in all cases) difference in the mean ITVs for all four objects. For the study of the medium triangle with multiple motion patterns, there was a good agreement in the measured ITVs between MIP(SS-MRI) and MIP(4D-CT) (p = 0.46, correlation coefficient = 0.91), with a mean difference of 1.4% +/- 4.4%. The area measurements between MIP(SS-MRI) and MIP(cine-MRI) also showed good agreement (p=0.47, correlation coefficient = 0.97), with a mean difference of 0.2% +/- 2.9%. For the healthy volunteer study, the average difference in the area of selected ROI was -2.5% +/- 2.5% between MIP(SS-MRI) and MIP(cine-MRI).

CONCLUSIONS

These preliminary results showed good agreement in volume/area measurements between the slice-stacking MRI technique and 4D-CT/cine-MRI, indicating that it is feasible to use this technique for MIP imaging.

Extra-cranial Stereotactic Radiation Therapy (ESRT) in the treatment of inoperable stage 1 & 2 non-small-cell lung cancer patients with highly mobile tumours: a literature review

Objective: Extra-cranial Stereotactic Radiation Therapy (ESRT) techniques and equipment utilised in the treatment of Stage 1 or 2 inoperable non-small-cell lung cancer (NSCLC); accounting for Respiratory Induced Tumour Motion (RITM).

Methods: A narrative review of current world literature.

Results: Four main strategies are employed to address RITM: (1) tumour movement minimisation/immobilisation; (2) integration of respiratory movements into planning; (3) respiratory-gating techniques; and (iv) tumour-tracking techniques.

Discussion: Analysis of data gathered suggests that due to inherent difficulties with respiratory function, combined with co-morbidities and the level of dose escalation facilitated by ESRT: techniques that do not require patient ability to comply are more likely to be effective with a wider range of patients. Similarly, treatment planning must incorporate accurate four-dimensional (4D) data to ensure target coverage, although setup and verification should be controlled to smaller margins for error.

Conclusion: The disparate nature of reporting methods restricts statistical comparison. However, this paper suggests that the ESRT technique using abdominal compression (AC), free-breathing respiratory-gating (FBRG), 4D computed tomography (4DCT) planning, combined with daily on board kV cone beam computed tomography (CBCT) imaging for setup and target verification, is a possible candidate for further treatment regime assessments in large multi-centre trials.

On correlated sources of uncertainty in four dimensional computed tomography data sets

The purpose of this work is to estimate the degree of uncertainty inherent to a given four dimensional computed tomography (4D-CT) imaging modality and to test for interaction of the investigated factors (i.e., object displacement, velocity, and the period of motion) when determining the object motion coordinates, motion envelope, and the confomality in which it can be defined within a time based data series. A motion phantom consisting of four glass spheres imbedded in low density foam on a one dimensional moving platform was used to investigate the interaction of uncertainty factors in motion trajectory that could be used in comparison of trajectory definition, motion envelope definition and conformality in an optimal 4D-CT imaging environment. The motion platform allowed for a highly defined motion trajectory that could be as the ground truth in the comparison with observed motion in 4D-CT data sets. 4D-CT data sets were acquired for 9 different motion patterns. Multifactor analysis of variance (ANOVA) was performed where the factors considered were the phantom maximum velocity, object volume, and the image intensity used to delineate the high density objects. No statistical significance was found for three factor interaction for definition of the motion trajectory, motion envelope, or Dice Similarity Coefficient (DSC) conformality. Two factor interactions were found to be statistically significant for the DSC for the interactions of 1) object volume and the HU threshold used for delineation and 2) the object velocity and object volume. Moreover, a statistically significant single factor direct proportionality was observed between the maximum velocity and the mean tracking error. In this work multiple factors impacting on the uncertainty in 4D data sets have been considered and some statistically significant two-factor interactions have been identified. Therefore, the detailed evaluation of errors and uncertainties in 4D imaging modalities is recommended in order to assess the clinical implications of interaction among the various uncertainty factors.

A study on the dosimetric accuracy of treatment planning for stereotactic body radiation therapy of lung cancer using average and maximum intensity projection images

PURPOSE

To assess the accuracy of current stereotactic body radiation therapy (SBRT) lung treatment planning methodologies on irregular breathing patterns, we have performed a systematic dosimetric evaluation in phantoms by utilizing maximum intensity projection (MIP) and average (AVG) images generated from four dimensional computed tomography (4DCT).

METHODS

A custom built programmable lung phantom was used to simulate tumor motions due to various breathing patterns of patients. 4DCT scans were obtained in helical mode, and reconstructed AVG and MIP datasets were imported into the Pinnacle 8.0 h treatment planning system. SBRT plans were generated and executed, and delivered doses were measured by radiochromic film for analysis.

RESULTS

For targets moving regularly or irregularly within a small range (7.0+/-1.8 mm, n=6), we observed good agreement between the measured and computed dose distributions. However, for targets moving irregularly with a larger range (20.8+/-2.6 mm, n=4), the measured isodose lines were found to be shifted relative to the planned distribution, resulting in an under-dosing (over 10%) in a portion of the PTV. We further observed that the discrepancy between planned and measured dose distribution is due to the inaccurate representation of irregular target motion in the MIP images generated from 4DCT.

CONCLUSIONS

Caution should be used when planning from 4DCT images in the presence of large and irregular target motion. The inaccuracy inherent in 4DCT MIP and AVG images can be mitigated through the application of methodologies to reduce respiratory motion, such as abdominal compression, and through the use of volumetric image guidance (e.g., cone beam CT-CBCT) to assure precise targeting with minimal shifts.

Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography

Background

To determine the optimal approach to delineating patient-specific internal gross target volumes (IGTV) from four-dimensional (4-D) computed tomography (CT) image data sets used in the planning of radiation treatment for lung cancers.

Methods

We analyzed 4D-CT image data sets of 27 consecutive patients with non-small-cell lung cancer (stage I: 17, stage III: 10). The IGTV, defined to be the envelope of respiratory motion of the gross tumor volume in each 4D-CT data set was delineated manually using four techniques: (1) combining the gross tumor volume (GTV) contours from ten respiratory phases (IGTV_AllPhases); (2) combining the GTV contours from two extreme respiratory phases (0% and 50%) (IGTV_2Phases); (3) defining the GTV contour using the maximum intensity projection (MIP) (IGTV_MIP); and (4) defining the GTV contour using the MIP with modification based on visual verification of contours in individual respiratory phase (IGTV_MIP-Modified). Using the IGTV_AllPhases as the optimum IGTV, we compared volumes, matching indices, and extent of target missing using the IGTVs based on the other three approaches.

Results

The IGTV_MIP and IGTV_2Phases were significantly smaller than the IGTV_AllPhases (p < 0.006 for stage I and p < 0.002 for stage III). However, the values of the IGTV_MIP-Modified were close to those determined from IGTV_AllPhases (p = 0.08). IGTV_MIP-Modified also matched the best with IGTV_AllPhases.

Conclusion

IGTV_MIP and IGTV_2Phases underestimate IGTVs. IGTV_MIP-Modified is recommended to improve IGTV delineation in lung cancer.

Reproducibility of interfraction lung motion probability distribution function using dynamic MRI: statistical analysis

PURPOSE

To investigate the statistical reproducibility of craniocaudal probability distribution function (PDF) of interfraction lung motion using dynamic magnetic resonance imaging.

METHODS AND MATERIALS

A total of 17 subjects, 9 healthy volunteers and 8 lung tumor patients, underwent two to three continuous 300-s magnetic resonance imaging scans in the sagittal plane, repeated 2 weeks apart. Three pulmonary vessels from different lung regions (upper, middle, and lower) in the healthy subjects and lung tumor patients were selected for tracking, and the displacement PDF reproducibility was evaluated as a function of scan time and frame rate.

RESULTS

For both healthy subjects and patients, the PDF reproducibility improved with increased scan time and converged to an equilibrium state during the 300-s scan. The PDF reproducibility at 300 s (mean, 0.86; range, 0.70-0.96) were significantly (p < 0.001) increased compared with those at 5 s (mean, 0.65; range, 0.25-0.79). PDF reproducibility showed less sensitivity to imaging frame rates that were >2 frames/s.

CONCLUSION

A statistically significant improvement in PDF reproducibility was observed with a prolonged scan time among the 17 participants. The confirmation of PDF reproducibility over times much shorter than stereotactic body radiotherapy delivery duration is a vital part of the initial validation process of probability-based treatment planning for stereotactic body radiotherapy for lung cancer.

Cine computed tomography without respiratory surrogate in planning stereotactic radiotherapy for non-small-cell lung cancer

PURPOSE

To determine whether cine computed tomography (CT) can serve as an alternative to four-dimensional (4D)-CT by providing tumor motion information and producing equivalent target volumes when used to contour in radiotherapy planning without a respiratory surrogate.

METHODS AND MATERIALS

Cine CT images from a commercial CT scanner were used to form maximum intensity projection and respiratory-averaged CT image sets. These image sets then were used together to define the targets for radiotherapy. Phantoms oscillating under irregular motion were used to assess the differences between contouring using cine CT and 4D-CT. We also retrospectively reviewed the image sets for 26 patients (27 lesions) at our institution who had undergone stereotactic radiotherapy for Stage I non-small-cell lung cancer. The patients were included if the tumor motion was >1 cm. The lesions were first contoured using maximum intensity projection and respiratory-averaged CT image sets processed from cine CT and then with 4D-CT maximum intensity projection and 10-phase image sets. The mean ratios of the volume magnitude were compared with intraobserver variation, the mean centroid shifts were calculated, and the volume overlap was assessed with the normalized Dice similarity coefficient index.

RESULTS

The phantom studies demonstrated that cine CT captured a greater extent of irregular tumor motion than did 4D-CT, producing a larger tumor volume. The patient studies demonstrated that the gross tumor defined using cine CT imaging was similar to, or slightly larger than, that defined using 4D-CT.

CONCLUSION

The results of our study have shown that cine CT is a promising alternative to 4D-CT for stereotactic radiotherapy planning.