Do Tumors in the Lung Deform During Normal Respiration? An Image Registration Investigation

Real-time 4D MRI using MR signature matching (MRSIGMA) on a 1.5T MR-Linac system

Objective. To develop real-time 4D MRI using MR signature matching (MRSIGMA) for volumetric motion imaging in patients with pancreatic cancer on a 1.5T MR-Linac system.Approach. Two consecutive MRI scans with 3D golden-angle radial stack-of-stars acquisitions were performed on ten patients with inoperable pancreatic cancer. The complete first scan (905 angles) was used to compute a 4D motion dictionary including ten pairs of 3D motion images and signatures. The second scan was used for real-time imaging, where each angle (275 ms) was processed separately to match it to one of the dictionary entries. The complete second scan was also used to compute a 4D reference to assess motion tracking performance.Dicecoefficients of the gross tumor volume (GTV) and two organs-at-risk (duodenum-stomach and small bowel) were calculated between signature matching and reference. In addition, volume changes, displacements, center of mass shifts, andDicescores over time were calculated to characterize motion.Main results. Total imaging latency of MRSIGMA (acquisition + matching) was less than 300 ms. TheDicecoefficients were 0.87 ± 0.06 (GTV), 0.86 ± 0.05 (duodenum-stomach), and 0.85 ± 0.05 (small bowel), which indicate high accuracy (high mean value) and low uncertainty (low standard deviation) of MRSIGMA for real-time motion tracking. The center of mass shift was 3.1 ± 2.0 mm (GTV), 5.3 ± 3.0 mm (duodenum-stomach), and 3.4 ± 1.5 mm (small bowel). TheDicescores over time (0.97 ± [0.01-0.03]) were similarly high for MRSIGMA and reference scans in all the three contours.Significance. This work demonstrates the feasibility of real-time 4D MRI using MRSIGMA for volumetric motion tracking on a 1.5T MR-Linac system. The high accuracy and low uncertainty of real-time MRSIGMA is an essential step towards continuous treatment adaptation of tumors affected by real-time respiratory motion and could ultimately improve treatment safety by optimizing ablative dose delivery near gastrointestinal organs.

A markerless beam's eye view tumor tracking algorithm based on unsupervised deformable registration learning framework of VoxelMorph in medical image with partial data

PURPOSE

To propose an unsupervised deformable registration learning framework-based markerless beam's eye view (BEV) tumor tracking algorithm for the inferior quality megavolt (MV) images with occlusion and deformation.

METHODS

Quality assurance (QA) plans for thorax phantom were delivered to the linear accelerator with artificially treatment offsets. Electronic portal imaging device (EPID) images (682 in total) and corresponding digitally reconstructed radiograph (DRR) were gathered as the moving and fixed image pairs, which were randomly divided into training and testing set in a ratio of 0.7:0.3 to train a non-rigid registration model with Voxelmorph. Simultaneously, 533 pairs of patient images from 21 lung tumor plans were acquired for tumor tracking investigation to offer quantifiable tumor motion data. Tracking error and image similarity measures were employed to evaluate the algorithm's accuracy.

RESULTS

The tracking algorithm can handle image registration with non-rigid deformation and losses ranging from 10 % to 80 %. The tracking errors in the phantom study were below 3 mm in about 86.8 % of cases, and below 2 mm in about 80 % of cases. The normalized mutual information (NMI) changes from 1.182 ± 0.024 to 1.198 ± 0.024 (p < 0.005). The patient target had an average translation of 3.784 mm and a maximum comprehensive displacement value of 7.455 mm. NMI of patient images changes from 1.209 ± 0.027 to 1.217 ± 0.026 (p < 0.005), indicating the presence of non-negligible non-rigid deformation.

CONCLUSIONS

The study provides a robust markerless tumor tracking algorithm for multi-modal, partial data and inferior quality image processing.

A Simulation Study of Tolerance of Breathing Amplitude Variations in Radiotherapy of Lung Cancer Using 4DCT and Time-Resolved 4DMRI

As patient breathing irregularities can introduce a large uncertainty in targeting the internal tumor volume (ITV) of lung cancer patients, and thereby affect treatment quality, this study evaluates dose tolerance of tumor motion amplitude variations in ITV-based volumetric modulated arc therapy (VMAT). A motion-incorporated planning technique was employed to simulate treatment delivery of 10 lung cancer patients' clinical VMAT plans using original and three scaling-up (by 0.5, 1.0, and 2.0 cm) motion waveforms from single-breath four-dimensional computed tomography (4DCT) and multi-breath time-resolved 4D magnetic resonance imaging (TR-4DMRI). The planning tumor volume (PTV = ITV + 5 mm margin) dose coverage (PTV D95%) was evaluated. The repeated waveforms were used to move the isocenter in sync with the clinical leaf motion and gantry rotation. The continuous VMAT arcs were broken down into many static beam fields at the control points (2°-interval) and the composite plan represented the motion-incorporated VMAT plan. Eight motion-incorporated plans per patient were simulated and the plan with the native 4DCT waveform was used as a control. The first (D95% ≤ 95%) and second (D95% ≤ 90%) plan breaching points due to motion amplitude increase were identified and analyzed. The PTV D95% in the motion-incorporated plans was 99.4 ± 1.0% using 4DCT, closely agreeing with the corresponding ITV-based VMAT plan (PTV D95% = 100%). Tumor motion irregularities were observed in TR-4DMRI and triggered D95% ≤ 95% in one case. For small tumors, 4 mm extra motion triggered D95% ≤ 95%, and 6-8 mm triggered D95% ≤ 90%. For large tumors, 14 mm and 21 mm extra motions triggered the first and second breaching points, respectively. This study has demonstrated that PTV D95% breaching points may occur for small tumors during treatment delivery. Clinically, it is important to monitor and avoid systematic motion increase, including baseline drift, and large random motion spikes through threshold-based beam gating.

Dosimetric evaluation of MRI-guided multi-leaf collimator tracking and trailing for lung stereotactic body radiation therapy

PURPOSE

The treatment margins for lung stereotactic body radiotherapy (SBRT) are often large to cover the tumor excursions resulting from respiration, such that underdosage of the tumor can be avoided. Magnetic resonance imaging (MRI)-guided multi-leaf collimator (MLC) tracking can potentially reduce the influence of respiration to allow for smaller treatment margins. However, tracking is accompanied by system latency that may induce residual tracking errors. Alternatively, a simpler mid-position delivery combined with trailing can be used. Trailing reduces influences of respiration by compensating for baseline motion, to potentially improve target coverage. In this study, we aim to show the feasibility of MRI-guided tracking and trailing to reduce influences of respiration during lung SBRT.

METHODS

We implemented MRI-guided tracking on the MR-linac using an Elekta research tracking interface to track tumor motion during intensity modulated radiotherapy (IMRT). A Quasar MRI 4 D phantom was used to generate Lujan motion ( cos 4 , 4 s period, 20 mm peak-to-peak amplitude) with and without 1.0 mm/min cranial drift. Phantom tumor positions were estimated from sagittal 2D cine-MRI (4 or 8 Hz) using cross-correlation-based template matching. To compensate the anticipated system latency, a linear ridge regression predictor was optimized for online MRI by comparing two predictor training approaches: training on multiple traces and training on a single trace. We created 15-beam clinical-grade lung SBRT plans for central targets (8 × 7.5 Gy) and peripheral targets (3 × 18 Gy) with different PTV margins for mid-position based motion management (3-5 mm) and for MLC tracking (3 mm). We used a film insert with a 3 cm spherical target to measure the spatial distribution and quantity of the delivered dose. A 1%/1 mm local gamma-analysis quantified dose differences between motion management strategies and reference cases. Additionally, a dose area histogram (DAH) revealed the target coverage relative to the reference scenario.

RESULTS

The prediction filter gain was on average 25% when trained on multiple traces and 44% when trained on a single trace. The filter reduced system latency from 313 ± 2 ms to 0 ± 5 ms for 4 Hz imaging and from 215 ± 3 ms to 3 ± 3 ms for 8 Hz. The local gamma analysis for the central delivery showed that tracking improved the gamma pass-rate from 23% to 96% for periodic motion and from 14% to 93% when baseline drift was applied. For the peripheral delivery during periodic motion, delivery pass-rates improved from 22% to 93%. Comparing mid-position delivery to trailing for periodic+drift motion increased the local gamma pass rate from 15% to 98% for a central delivery and from 8% to 98% for a peripheral delivery. Furthermore, the DAHs revealed a relative D 98 % GTV coverage of 101% and 97% compared to the reference scenario for, respectively, central and peripheral tracking of periodic+drift motion. For trailing, a relative D 98 % of 99% for central and 98% for peripheral trailing was found.

CONCLUSIONS

We provided a first experimental demonstration of the technical feasibility of MRI-guided MLC tracking and trailing for central and peripheral lung SBRT. Tracking maximizes the sparing of healthy tissue, while trailing is highly effective in mitigating baseline motion.

Feasibility of MR-guided radiotherapy using beam-eye-view 2D-cine with tumor-volume projection

PURPOSE

Current magnetic resonance imaging (MRI) guided radiotherapy (MRgRT) applies sagittal/coronal 2D-cine to monitor major tumor motions, however, the beam eye's view (BEV) with volumetric tumor projection would be the best measure for radiation beam conformality, independent of tumor through-plane motion. The goal is to assess the feasibility, accuracy, and performance of the BEV approach.

METHODS

Beam-specific BEV 2D-cine with volume-projected tumor contours were simulated to establish a 2D/3D tumor match against a tumor-motion library based on multi-breath time-resolved (TR) 4DMRI images. Two BEV-library-matching methods were developed: (1) fast screening with tumor center-of-mass (∆COM), in-plane area ratio, and DICE similarity, and finalizing with the highest DICE score and (2) DICE screening for top-3 candidates and finalizing with rigid registration. A 4D-XCAT digital phantom and 8 lung-cancer patients were used for assessment. For each patient, 3 sets of 40 s TR-4DMRI were acquired at 2 Hz and 6 representative BEV were created with the isocenter set at tumor COM in mid-respiration. One TR-4DMRI set (40 × 2 = 80-images) was used to simulate BEV 2D-cine and the other two (160-images) were used to create a library. The matching result was validated against the ground truth within the test set. Using a leave-one-out strategy, the success rate, accuracy, and speed of tumor matching were assessed for volume-projected tumors over 11520 time-points (=8patients•3sets•80images•6BEVs).

RESULTS

Volume-projected tumor contour area on the 6 BEVs varies by 60% ± 8% and [Formula: see text] (in-plane/volume-projected) varies by 82% ± 9%. The [Formula: see text] changes with tumor shape, orientation, and through-plane motion. Method-1 produces 96% matching success (ΔCOM = 0.7 ± 0.2 mm, [Formula: see text]=1.01 ± 0.02, Dice=0.92 ± 0.02) with the computational time of 15 ± 1 ms/match, while method-2 produces 94% ± 1% success (ΔCOM = 0.2 ± 0.1 mm, [Formula: see text]=1.00 ± 0.01, Dice = 0.94 ± 0.02) with 223 ± 13 ms/match.

CONCLUSION

This study has demonstrated the feasibility, accuracy, and benefits of BEV 2D-cine imaging with tumor-volume projection, allowing real-time tumor motion monitoring and beam conformality checking. Further clinical evaluation is necessary before MRgRT applications.

Quality assurance of four-dimensional computed tomography in a multicentre trial of stereotactic body radiotherapy of centrally located lung tumours

Background and Purpose

Extensive radiation therapy quality assurance (RTQA) programs are needed when advanced radiotherapy treatments are used. As part of the RTQA four dimensional computed tomography (4DCT) imaging performance needs to be assessed. Here we present the RTQA data related to 4DCT procedures used within the context of stereotactic body radiotherapy (SBRT) of centrally located lung tumours. It provides an overview of the 4DCT acquisition methods and achievable accuracy of imaging lung tumour volumes.

Materials and Methods

3DCT and 4DCT images were acquired from a CIRS phantom with spheres of 7.5 and 12.5 mm radius using the institutional scan protocols. Regular asymmetric tumour motion was simulated with varying amplitudes and periods. Target volumes were reconstructed using auto-contouring with scanner specific thresholds. Volume and amplitudes deviations were assessed.

Results

Although acquisition parameters were rather homogeneous over the eleven institutions analysed, volume deviations were observed. Average volume deviations for the 12.5 mm sphere were 15% (−4% to 69%) at end of inspiration, 2% (−2% to 9.0%) at end of expiration and 12% (0% to 36%) at mid-ventilation. For the 7.5 mm sphere deviations were 13% (−99% to 65%), 16% (−34% to 66%) and 1% (−13% to 20%), respectively. The amplitude deviation was generally within 2 mm although underestimations up to 6 mm were observed.

Conclusions

The expiration phase was the most accurate phase to define the tumour volume and should be preferred for GTV delineation of tumours exhibiting large motion causing motion artefacts when using mid-ventilation or tracking techniques. The large variation found among the institutions indicated that further improvements in 4DCT imaging were possible. Recommendations for 4DCT QA have been formulated.

Discriminating lung adenocarcinoma from lung squamous cell carcinoma using respiration-induced tumor shape changes

Based on 4D-CT, we aimed to characterize the pattern of morphological changes in lung tumors during respiration, and investigated its potential in non-invasively differentiating lung adenocarcinoma (AC) and squamous cell carcinoma (SCC). We applied a 3D surface analysis on 22 tumors (13 AC, 9 SCC) to investigate the tumor regional morphological fluctuations in response to respiration phases. Tumor surface vertices among ten respiratory phases were matched using surface-based registration, and the shape descriptors (ρ and detJ) were calculated and tracked across respiration stages in a regionally aligned scenario. Pair-wise group comparisons were performed between lung AC and SCC subtypes, in terms of ratios of maximal shape changes as well as correlation coefficients between tumor shape and respiratory stage indicators from the lung. AC type tumors had averaged larger surface measurements at exhale than at inhale, and these surface measurements were negatively correlated with lung volumes across respiratory stages. In contrast, SCC type tumors had averaged smaller surface measurements at exhale than at inhale, and the correlations with lung volumes were positive. The group differences in maximal shape changes as well as correlations were both statistically significant (p  <  0.05). We developed a non-invasive lung tumor sub-type detection pipeline based on respiration-induced tumor surface deformation. Significant differences in deformation patterns were detected between lung AC and SCC. The derived surface measurements may potentially serve as a new non-invasive imaging biomarker of lung cancer subtypes.

Attenuation correction in 4D-PET using a single-phase attenuation map and rigidity-adaptive deformable registration

PURPOSE

Four-dimensional positron emission tomography (4D-PET) imaging is a potential solution to the respiratory motion effect in the thoracic region. Computed tomography (CT)-based attenuation correction (AC) is an essential step toward quantitative imaging for PET. However, due to the temporal difference between 4D-PET and a single attenuation map from CT, typically available in routine clinical scanning, motion artifacts are observed in the attenuation-corrected PET images, leading to errors in tumor shape and uptake. We introduced a practical method to align single-phase CT with all other 4D-PET phases for AC.

METHODS

A penalized non-rigid Demons registration between individual 4D-PET frames without AC provides the motion vectors to be used for warping single-phase attenuation map. The non-rigid Demons registration was used to derive deformation vector fields (DVFs) between PET matched with the CT phase and other 4D-PET images. While attenuated PET images provide useful data for organ borders such as those of the lung and the liver, tumors cannot be distinguished from the background due to loss of contrast. To preserve the tumor shape in different phases, an ROI-covering tumor was excluded from nonrigid transformation. Instead the mean DVF of the central region of the tumor was assigned to all voxels in the ROI. This process mimics a rigid transformation of the tumor along with a nonrigid transformation of other organs. A 4D-XCAT phantom with spherical lung tumors, with diameters ranging from 10 to 40 mm, was used to evaluate the algorithm. The performance of the proposed hybrid method for attenuation map estimation was compared to (a) the Demons nonrigid registration only and (b) a single attenuation map based on quantitative parameters in individual PET frames.

RESULTS

Motion-related artifacts were significantly reduced in the attenuation-corrected 4D-PET images. When a single attenuation map was used for all individual PET frames, the normalized root-mean-square error (NRMSE) values in tumor region were 49.3% (STD: 8.3%), 50.5% (STD: 9.3%), 51.8% (STD: 10.8%) and 51.5% (STD: 12.1%) for 10-mm, 20-mm, 30-mm, and 40-mm tumors, respectively. These errors were reduced to 11.9% (STD: 2.9%), 13.6% (STD: 3.9%), 13.8% (STD: 4.8%), and 16.7% (STD: 9.3%) by our proposed method for deforming the attenuation map. The relative errors in total lesion glycolysis (TLG) values were -0.25% (STD: 2.87%) and 3.19% (STD: 2.35%) for 30-mm and 40-mm tumors, respectively, in proposed method. The corresponding values for Demons method were 25.22% (STD: 14.79%) and 18.42% (STD: 7.06%). Our proposed hybrid method outperforms the Demons method especially for larger tumors. For tumors smaller than 20 mm, nonrigid transformation could also provide quantitative results.

CONCLUSION

Although non-AC 4D-PET frames include insignificant anatomical information, they are still useful to estimate the DVFs to align the attenuation map for accurate AC. The proposed hybrid method can recover the AC-related artifacts and provide quantitative AC-PET images.

Topology guided demons registration with local rigidity preservation

Demons has been well recognized for its deformable registration capability. However, it might lead to misregistration due to the large spatial distance between the expected corresponding contents or erroneous diffusion tendency. In this paper, we propose a new energy function with topology energy, distance function and demons energy for deformable registration. The new energy function incorporates topological relationships to guide the correct diffusion and deformation, and contributes to local rigidity preservation. The distance function contributes to pulling the corresponding regions into accurate alignment despite of a possible large distance gap. The method was validated on synthetic, phantom and real medical image data.

A Feasibility Study on Ribs as Anatomical Landmarks for Motion Tracking of Lung and Liver Tumors at External Beam Radiotherapy

At external beam radiotherapy for some tumors located at thorax region due to lack of information in gray scale fluoroscopic images tumor position determination is problematic. One of the clinical strategies is to implant clip as internal fiducial marker inside or near tumor to represent tumor position while the contrast of implanted clip is highly observable rather than tumor. As alternative, using natural anatomical landmarks located at thorax region of patient body is proposed to extract tumor position information without implanting clips that is invasive method with possible side effect. Among natural landmarks, ribs of rib-cage structure that result proper visualization at X-ray images may be optimal as representative for tumor motion. In this study, we investigated the existence of possible correlation between ribs as natural anatomical landmarks and various lung and liver tumors located at different sites as challenging issue. A simulation study was performed using data extracted from 4-dimensional extended cardiac-torso anthropomorphic phantom that is able to simulate motion effect of dynamic organs, as well. Several tumor sites with predefined distances originated from chosen ribs at anterior-posterior direction were simulated at 3 upper, middle, and lower parts of chest. Correlation coefficient between ribs and tumors was calculated to investigate the robustness of ribs as anatomical landmarks for tumor motion tracking. Moreover, a consistent correlation model was taken into account to track tumor motion with a rib as best candidate among selected ribs. Final results represent availability of using rib cage as anatomical landmark to track lung and liver tumors in a noninvasive way. Observations of our calculations showed a proper correlation between tumors and ribs while the degree of this correlation is changing depends on tumor site while lung tumors are more varied and complex with less correlation with ribs motion against liver tumors.

The use of strain tensor to estimate thoracic tumors deformation

PURPOSE

Respiration-induced kinematics of thoracic tumors suggests a simple analogy with elasticity, where a strain tensor is used to characterize the volume of interests. The application of the biomechanical framework allows for the objective determination of tumor characteristics.

METHODS

Four-dimensional computed tomography provides the snapshots of the patient's anatomy at the end of inspiration and expiration. Image registration was used to obtain the displacement vector fields and deformation fields, which allows one for the determination of the strain tensor. Its departure from the identity matrix gauges the departure of the medium from rigidity. The tensorial characteristic of each GTV voxel was determined and averaged. To this end, the standard Euclidean matrix norm as well as the Log-Euclidean norm were employed. Tensorial anisotropy was gauged with the fractional anisotropy measure which is based on the normalized variance of the tensors eigenvalues. Anisotropy was also evaluated with the geodesic distance in the Log-Euclidean framework of a given strain tensor to its closest isotropic counterpart.

RESULTS

The averaged strain tensor was determined for each of the 15 retrospectively analyzed thoracic GTVs. The amplitude of GTV motion varied from 0.64 to 4.21 with the average of 1.20 cm. The GTV size ranged from 5.16 to 149.99 cc with the average of 43.19 cc. The tensorial analysis shows that deformation is inconsiderable and that the tensorial anisotropy is small. The Log-Euclidean distance of averaged strain tensors from the identity matrix ranged from 0.06 to 0.31 with the average of 0.19. The Frobenius distance from the identity matrix is similar and ranged from 0.06 to 0.35 with the average of 0.21. Their fractional anisotropy ranged from 0.02 to 0.12 with the average of 0.07. Their geodesic anisotropy ranged from 0.03 to 0.16 with the average of 0.09. These values also indicate insignificant deformation.

CONCLUSIONS

The tensorial framework allows for direct measurements of tissue deformation. It goes beyond the evaluation of deformation via comparison of shapes. It is an independent and objective determination of tissue properties. This methodology can be used to determine possible changes in lung properties due to radiation therapy and possible toxicities.

A kernel-based method for markerless tumor tracking in kV fluoroscopic images

Markerless tracking of respiration-induced tumor motion in kilo-voltage (kV) fluoroscopic image sequence is still a challenging task in real time image-guided radiation therapy (IGRT). Most of existing markerless tracking methods are based on a template matching technique or its extensions that are frequently sensitive to non-rigid tumor deformation and involve expensive computation. This paper presents a kernel-based method that is capable of tracking tumor motion in kV fluoroscopic image sequence with robust performance and low computational cost. The proposed tracking system consists of the following three steps. To enhance the contrast of kV fluoroscopic image, we firstly utilize a histogram equalization to transform the intensities of original images to a wider dynamical intensity range. A tumor target in the first frame is then represented by using a histogram-based feature vector. Subsequently, the target tracking is then formulated by maximizing a Bhattacharyya coefficient that measures the similarity between the tumor target and its candidates in the subsequent frames. The numerical solution for maximizing the Bhattacharyya coefficient is performed by a mean-shift algorithm. The proposed method was evaluated by using four clinical kV fluoroscopic image sequences. For comparison, we also implement four conventional template matching-based methods and compare their performance with our proposed method in terms of the tracking accuracy and computational cost. Experimental results demonstrated that the proposed method is superior to conventional template matching-based methods.

Investigating strategies to reduce toxicity in stereotactic ablative radiotherapy for central lung tumors

BACKGROUND

[corrected] Stereotactic radiotherapy for central lung tumors has a narrower therapeutic index than that for peripheral tumors. Tumor tracking strategies have been proposed to reduce treatment volumes and toxicity, however they need to consider uncertainties in tumor size and shape change throughout respiration to ensure optimal local control. We quantified these uncertainties and explored strategies to account for them.

MATERIAL AND METHODS

Ten patients with central tumors, PTV > 100 cm(3), motion > 5 mm and a 10-phase 4DCT without significant artifact in the tumor region were evaluated. Uncertainties were quantified using GTV size in different phases, and the Hausdorff distance (HD) between the phase 50% GTV and other phases after soft-tissue rigid registration. An individualized internal target volume for tracking (ITV(T)) was generated from the union of the GTVs in all phases after rigid registration. This was compared to ITVs generated for tracking based on the phase 50% GTV alone or with isotropic margins of 3 or 5 mm for size and volume overlap.

RESULTS

Median free-breathing PTV size and motion were 162.1 cm(3) (110-210) and 8.9 mm (6.1-14.1). Overall, median GTV size variation and HD were 4.7% (0.2-22.3) and 6.3 mm (3.9-17.6). Tracking using GTV 50% alone resulted in median volume overlap with ITV(T) of 71.7% (range 56.8-85.1). Isotropic margins of 3 or 5mm always resulted in a volume overlap less than 95% or a volume larger than the ITV(T).

CONCLUSIONS

Changes in size and shape of central lung tumors are substantial during respiration. These limit the ability to reduce treatment volumes with tracking, especially if isotropic margins are used. An individualized ITV for tracking, such as the ITV(T) is preferred.

A mass-conserving 4D XCAT phantom for dose calculation and accumulation

PURPOSE

The XCAT phantom is a realistic 4D digital torso phantom that is widely used in imaging and therapy research. However, lung mass is not conserved between respiratory phases of the phantom, making detailed dosimetric simulations and dose accumulation unphysical. A framework is developed to correct this issue by enforcing local mass conservation in the XCAT lung. Dose calculations are performed to assess the implications of neglecting mass conservation, and to demonstrate an application of the phantom to calculate the accumulated delivered dose in an irregularly breathing patient.

METHODS

A displacement vector field (DVF) between each respiratory state and a reference image is generated from the XCAT motion model and its divergence is calculated and used to correct the lung density. A series of phantoms with regular and irregular breathing (based on patient data) are generated and modified to conserve mass. Monte Carlo methods are used to simulate conventional and SBRT treatment delivery. The calculated dose is deformed and accumulated using the DVF. Results from the mass-conserving and original XCAT are compared. A 4DCT is simulated for the irregularly breathing patient, and a 4DCT-based dose estimate is compared with the accumulated delivered dose.

RESULTS

The presented framework successfully conserves mass in the XCAT lung. The spatial distribution of the lung dose was qualitatively changed by the use of a mass conservation in the XCAT; however, the corresponding DVH did not change significantly. The comparison of the delivered dose with the 4DCT-based prediction shows similar lung metric results, however dose differences of 10% can be seen in some spatial regions.

CONCLUSIONS

The XCAT phantom has been successfully modified so that it conserves lung mass during respiration, enabling it to be used as a tool to perform dose accumulation studies in the lung without relying on deformable image registration. Neglecting mass conservation can result in erroneous spatial distributions of the dose in the lung. Using this tool to simulate patient treatments reveals differences between the planned dose and the calculated delivered dose for the full treatment. The software is freely available from the authors.

Evaluation of methods for selecting the midventilation bin in 4DCT scans of lung cancer patients

BACKGROUND

In lung cancer radiotherapy, planning on the midventilation (MidV) bin of a four-dimensional (4D) CT scan can reduce the systematic errors introduced by respiratory tumour motion compared to conventional CT. In this study four different methods for MidV bin selection are evaluated.

MATERIAL AND METHODS

The study is based on 4DCT scans of 19 patients with a total of 23 peripheral lung tumours having peak-to-peak displacement ≥ 5 mm in at least one of the left-right (LR), anterior-posterior (AP) or cranio-caudal (CC) directions. For each tumour, the MidV bin was selected based on: 1) visual evaluation of tumour displacement; 2) rigid registration of tumour position; 3) diaphragm displacement in the CC direction; and 4) carina displacement in the CC direction. Determination of the MidV bin based on the displacement of the manually delineated gross tumour volume (GTV) was used as a reference method. The accuracy of each method was evaluated by the distance between GTV position in the selected MidV bin and the time-weighted mean position of GTV throughout the bins (i.e. the geometric MidV error).

RESULTS

Median (range) geometric MidV error was 1.4 (0.4-5.4) mm, 1.4 (0.4-5.4) mm, 1.9 (0.5-6.9) mm, 2.0 (0.5-12.3) mm and 1.1 (0.4-5.4) mm for the visual, rigid registration, diaphragm, carina, and reference method. Median (range) absolute difference between geometric MidV error for the evaluated methods and the reference method was 0.0 (0.0-1.2) mm, 0.0 (0.0-1.7) mm, 0.7 (0.0-3.9) mm and 1.0 (0.0-6.9) mm for the visual, rigid registration, diaphragm and carina method.

CONCLUSION

The visual and semi-automatic rigid registration methods were equivalent in accuracy for selecting the MidV bin of a 4DCT scan. The methods based on diaphragm and carina displacement cannot be recommended without modifications.

Migration of implanted markers for image-guided lung tumor stereotactic ablative radiotherapy

The purpose of this study was to quantify postimplantation migration of percutaneously implanted cylindrical gold seeds (“seeds”) and platinum endovascular embolization coils (“coils”) for tumor tracking in pulmonary stereotactic ablative radiotherapy (SABR). We retrospectively analyzed the migration of markers in 32 consecutive patients with computed tomography scans postimplantation and at simulation. We implanted 147 markers (59 seeds, 88 coils) in or around 34 pulmonary tumors over 32 procedures, with one lesion implanted twice. Marker coordinates were rigidly aligned by minimizing fiducial registration error (FRE), the root mean square of the differences in marker locations for each tumor between scans. To also evaluate whether single markers were responsible for most migration, we aligned with and without the outlier causing the largest FRE increase per tumor. We applied the resultant transformation to all markers. We evaluated migration of individual markers and FRE of each group. Median scan interval was 8 days. Median individual marker migration was 1.28 mm (interquartile range [IQR] 0.78−2.63 mm). Median lesion FRE was 1.56 mm (IQR 0.92−2.95 mm). Outlier identification yielded 1.03 mm median migration (IQR 0.52−2.21 mm) and 1.97 mm median FRE (IQR 1.44−4.32 mm). Outliers caused a mean and median shift in the centroid of 1.22 and 0.80 mm (95th percentile 2.52 mm). Seeds and coils had no statistically significant difference. Univariate analysis suggested no correlation of migration with the number of markers, contact with the chest wall, or time elapsed. Marker migration between implantation and simulation is limited and unlikely to cause geometric miss during tracking.

PACS number: 87.57.N‐; 87.57.nm; 87.53.Ly

Changes in lung tumor shape during respiration

Evidence that some lung tumors change shape during respiration is derived from respiratory gated CT data by statistical shape modeling and image manipulation. Some tumors behave as rigid objects while others show systematic shape changes. Two views of lung motion are presented to allow analysis of the results. In the first, lung motion is viewed as a wave motion in which inertial effects arising from mass are present and in the second it is a quasistatic motion in which the mass of the lung tissues is neglected. In the first scenario, the extremes of tumor compression and expansion are expected to correlate with maximum upward and downward velocity of the tumor, respectively. In the second, they should occur at end exhale and end inhale, respectively. An observed correlation between tumor strain and tumor velocity provides more support for the first view of lung motion and may explain why previous attempts at observing tumor shape changes during respiration have largely failed. The implications for the optimum gating of radiation therapy are discussed.

Improving target delineation on 4-dimensional CT scans in stage I NSCLC using a deformable registration tool

INTRODUCTION

Correct target definition is crucial in stereotactic radiotherapy for lung tumors. We evaluated use of deformable registration (DR) for target contouring on 4-dimensional (4D) CT scans.

MATERIALS AND METHODS

Three clinicians contoured gross tumor volume (GTV) in an end-inspiration phase of 4DCT of 6 patients on two occasions. Two clinicians contoured GTVs in all phases of 4DCT and on maximum intensity projections (MIP). The initial GTV was auto-propagated to 9 other phases using a B-spline algorithm (VelocityAI). Internal target volumes (ITVs) generated were (i) ITV(10manual) encompassing all physician-contoured GTVs, (ii) ITV-MIP(optimized) from MIP after review of individual 4DCT phases, (iii) ITV(10deformed) encompassing auto-propagated GTVs using DR, and (iv) ITV(10deformed-optimized), from an ITV(10deformed) target that was modified to form a 'clinically optimal' ITV. Volume-overlaps were scored using Dice's Similarity Coefficients (DSCs).

RESULTS

Intra-clinician GTV reproducibility was greater than inter-clinician reproducibility (mean DSC 0.93 vs. 0.88, p<0.0004). In five of 6 patients, ITV-MIP(optimized) differed from the ITV(10deformed-optimized). In all patients, the DSC between ITV(10deformed-optimized) and ITV(10deformed) was higher than that between ITV(10deformed-optimized) and ITV-MIP(optimized) (p<0.02 T-test).

CONCLUSION

ITVs created in stage I tumors using DR were closer to 'clinically optimal' ITVs than was the case with a MIP-modified approach.

Four-dimensional intensity-modulated radiation therapy planning for dynamic tracking using a direct aperture deformation (DAD) method

PURPOSE

Planning for the delivery of intensity-modulated radiation therapy (IMRT) to a moving target, referred to as four-dimensional (4D) IMRT planning, is a crucial step for achieving the treatment objectives for sites that move during treatment delivery. The authors proposed a simplistic method that accounts for both rigid and nonrigid respiration-induced target motion based on 4D computed tomography (4DCT) data sets.

METHODS

A set of MLC apertures and weights was first optimized on a reference phase of a 4DCT data set. At each beam angle, the apertures were morphed from the reference phase to each of the remaining phases according to the relative shape changes in the beam's eye view of the target. Three different planning schemes were evaluated for two lung cases and one pancreas patient: (1) Individually optimizing each breathing phase; (2) optimizing the reference phase and shifting the optimized apertures to other breathing phases based on a rigid-body image registration; and (3) optimizing the reference phase and deforming the optimized apertures to the other phases based on the deformation and translation of target contours. Planning results using scheme 1 serves as the "gold standard" for plan quality assessment; scheme 2 is the method previously proposed in the literature; and scheme 3 is the method the authors proposed in this article. The optimization results were compared between the three schemes for all three cases.

RESULTS

The proposed scheme 3 is comparable to scheme 1 in plan quality, and provides improved target coverage and conformity with similar normal tissue dose compared with scheme 2.

CONCLUSIONS

Direct aperture deformation method for 4D IMRT planning improves upon methods that only consider rigid-body motion and achieves a plan quality close to that optimized for each of the phases.

Inferring positions of tumor and nodes in Stage III lung cancer from multiple anatomical surrogates using four-dimensional computed tomography

PURPOSE

To investigate the feasibility of modeling Stage III lung cancer tumor and node positions from anatomical surrogates.

METHODS AND MATERIALS

To localize their centroids, the primary tumor and lymph nodes from 16 Stage III lung cancer patients were contoured in 10 equal-phase planning four-dimensional (4D) computed tomography (CT) image sets. The centroids of anatomical respiratory surrogates (carina, xyphoid, nipples, mid-sternum) in each image set were also localized. The correlations between target and surrogate positions were determined, and ordinary least-squares (OLS) and partial least-squares (PLS) regression models based on a subset of respiratory phases (three to eight randomly selected) were created to predict the target positions in the remaining images. The three-phase image sets that provided the best predictive information were used to create models based on either the carina alone or all surrogates.

RESULTS

The surrogate most correlated with target motion varied widely. Depending on the number of phases used to build the models, mean OLS and PLS errors were 1.0 to 1.4 mm and 0.8 to 1.0 mm, respectively. Models trained on the 0%, 40%, and 80% respiration phases had mean (+/- standard deviation) PLS errors of 0.8 +/- 0.5 mm and 1.1 +/- 1.1 mm for models based on all surrogates and carina alone, respectively. For target coordinates with motion >5 mm, the mean three-phase PLS error based on all surrogates was 1.1 mm.

CONCLUSIONS

Our results establish the feasibility of inferring primary tumor and nodal motion from anatomical surrogates in 4D CT scans of Stage III lung cancer. Using inferential modeling to decrease the processing time of 4D CT scans may facilitate incorporation of patient-specific treatment margins.