Anthropomorphic lung phantom based validation of in-room proton therapy 4D-CBCT image correction for dose calculation.

PURPOSE: Ventilation-induced tumour motion remains a challenge for the accuracy of proton therapy treatments in lung patients. We investigated the feasibility of using a 4D virtual CT (4D-vCT) approach based on deformable image registration (DIR) and motion-aware 4D CBCT reconstruction (MA-ROOSTER) to enable accurate daily proton dose calculation using a gantry-mounted CBCT scanner tailored to proton therapy. METHODS: Ventilation correlated data of 10 breathing phases were acquired from a porcine ex-vivo functional lung phantom using CT and CBCT. 4D-vCTs were generated by (1) DIR of the mid-position 4D-CT to the mid-position 4D-CBCT (reconstructed with the MA-ROOSTER) using a diffeomorphic Morphons algorithm and (2) subsequent propagation of the obtained mid-position vCT to the individual 4D-CBCT phases. Proton therapy treatment planning was performed to evaluate dose calculation accuracy of the 4D-vCTs. A robust treatment plan delivering a nominal dose of 60Gy was generated on the average intensity image of the 4D-CT for an approximated internal target volume (ITV). Dose distributions were then recalculated on individual phases of the 4D-CT and the 4D-vCT based on the optimized plan. Dose accumulation was performed for 4D-vCT and 4D-CT using DIR of each phase to the mid position, which was chosen as reference. Dose based on the 4D-vCT was then evaluated against the dose calculated on 4D-CT both, phase-by-phase as well as accumulated, by comparing dose volume histogram (DVH) values (Dmean, D2%, D98%, D95%) for the ITV, and by a 3D-gamma index analysis (global, 3%/3mm, 5Gy, 20Gy and 30Gy dose thresholds). RESULTS: Good agreement was found between the 4D-CT and 4D-vCT-based ITV-DVH curves. The relative differences ((CT-vCT)/CT) between accumulated values of ITV Dmean, D2%, D95% and D98% for the 4D-CT and 4D-vCT-based dose distributions were -0.2%, 0.0%, -0.1% and -0.1%, respectively. Phase specific values varied between -0.5% and 0.2%, -0.2% and 0.5%, -3.5% and 1.5%, and -5.7% and 2.3%. The relative difference of accumulated Dmean over the lungs was 2.3% and Dmean for the phases varied between -5.4% and 5.8%. The gamma pass-rates with 5Gy, 20Gy and 30Gy thresholds for the accumulated doses were 96.7%, 99.6% and 99.9%, respectively. Phase-by-phase comparison yielded pass-rates between 86% and 97%, 88% and 98%, and 94% and 100%. CONCLUSIONS: Feasibility of the suggested 4D-vCT workflow using proton therapy specific imaging equipment was shown. Results indicate the potential of the method to be applied for daily 4D proton dose estimation.

Validation of proton dose calculation on scatter corrected 4D cone beam computed tomography using a porcine lung phantom.

Proton therapy treatment for lungs remains challenging as images enabling the detection of inter- and intra-fractional motion, which could be used for proton dose adaptation, are not readily available. 4D computed tomography (4DCT) provides high image quality but is rarely available in-room, while in-room 4D cone beam computed tomography (4DCBCT) suffers from image quality limitations stemming mostly from scatter detection. This study investigated the feasibility of using virtual 4D computed tomography (4DvCT) as a prior for a phase-per-phase scatter correction algorithm yielding a 4D scatter corrected cone beam computed tomography image (4DCBCTcor), which can be used for proton dose calculation. 4DCT and 4DCBCT scans of a porcine lung phantom, which generated reproducible ventilation, were acquired with matching breathing patterns. Diffeomorphic Morphons, a deformable image registration algorithm, was used to register the mid-position 4DCT to the mid-position 4DCBCT and yield a 4DvCT. The 4DCBCT was reconstructed using motion-aware reconstruction based on spatial and temporal regularization (MA-ROOSTER). Successively for each phase, digitally reconstructed radiographs of the 4DvCT, simulated without scatter, were exploited to correct scatter in the corresponding CBCT projections. The 4DCBCTcorwas then reconstructed with MA-ROOSTER using the corrected CBCT projections and the same settings and deformation vector fields as those already used for reconstructing the 4DCBCT. The 4DCBCTcorand the 4DvCT were evaluated phase-by-phase, performing proton dose calculations and comparison to those of a ground truth 4DCT by means of dose-volume-histograms (DVH) and gamma pass-rates (PR). For accumulated doses, DVH parameters deviated by at most 1.7% in the 4DvCT and 2.0% in the 4DCBCTcorcase. The gamma PR for a (2%, 2 mm) criterion with 10% threshold were at least 93.2% (4DvCT) and 94.2% (4DCBCTcor), respectively. The 4DCBCTcortechnique enabled accurate proton dose calculation, which indicates the potential for applicability to clinical 4DCBCT scans.

Measurement-based range evaluation for quality assurance of CBCT-based dose calculations in adaptive proton therapy.

PURPOSE: The implementation of volumetric in-room imaging for online adaptive radiotherapy makes extensive testing of this image data for treatment planning necessary. Especially for proton beams the higher sensitivity to stopping power properties of the tissue results in more stringent requirements. Current approaches mainly focus on recalculation of the plans on the new image data, lacking experimental verification, and ignoring the impact on the plan re-optimization process. The aim of this study was to use gel and film dosimetry coupled with a three-dimensional (3D) printed head phantom (based on the planning CT of the patient) for 3D range verification of intensity-corrected cone beam computed tomography (CBCT) image data for adaptive proton therapy. METHODS: Single field uniform dose pencil beam scanning proton plans were optimized for three different patients on the patients' planning CT (planCT) and the patients' intensity-corrected CBCT (scCBCT) for the same target volume using the same optimization constraints. The CBCTs were corrected on projection level using the planCT as a prior. The dose optimized on planCT and recalculated on scCBCT was compared in terms of proton range differences (80% distal fall-off, recalculation). Moreover, the dose distribution resulting from recalculation of the scCBCT-optimized plan on the planCT and the original planCT dose distribution were compared (simulation). Finally, the two plans of each patient were irradiated on the corresponding patient-specific 3D printed head phantom using gel dosimetry inserts for one patient and film dosimetry for all three patients. Range differences were extracted from the measured dose distributions. The measured and the simulated range differences were corrected for range differences originating from the initial plans and evaluated. RESULTS: The simulation approach showed high agreement with the standard recalculation approach. The median values of the range differences of these two methods agreed within 0.1 mm and the interquartile ranges (IQRs) within 0.3 mm for all three patients. The range differences of the film measurement were accurately matching with the simulation approach in the film plane. The median values of these range differences deviated less than 0.1 mm and the IQRs less than 0.4 mm. For the full 3D evaluation of the gel range differences, the median value and IQR matched those of the simulation approach within 0.7 and 0.5 mm, respectively. scCBCT- and planCT-based dose distributions were found to have a range agreement better than 3 mm (median and IQR) for all considered scenarios (recalculation, simulation, and measurement). CONCLUSIONS: The results of this initial study indicate that an online adaptive proton workflow based on scatter-corrected CBCT image data for head irradiations is feasible. The novel presented measurement- and simulation-based method was shown to be equivalent to the standard literature recalculation approach. Additionally, it has the capability to catch effects of image differences on the treatment plan optimization. This makes the measurement-based approach particularly interesting for quality assurance of CBCT-based online adaptive proton therapy. The observed uncertainties could be kept within those of the registration and positioning. The proposed validation could also be applied for other alternative in-room images, e.g. for MR-based pseudoCTs.

Porcine lung phantom-based validation of estimated 4D-MRI using orthogonal cine imaging for low-field MR-Linacs.

Real-time motion monitoring of lung tumors with low-field magnetic resonance imaging-guided linear accelerators (MR-Linacs) is currently limited to sagittal 2D cine magnetic resonance imaging (MRI). To provide input data for improved intrafractional and interfractional adaptive radiotherapy, the 4D anatomy has to be inferred from data with lower dimensionality. The purpose of this study was to experimentally validate a previously proposed propagation method that provides continuous time-resolved estimated 4D-MRI based on orthogonal cine MRI for a low-field MR-Linac. Ex vivo porcine lungs were injected with artificial nodules and mounted in a dedicated phantom that allows for the simulation of periodic and reproducible breathing motion. The phantom was scanned with a research version of a commercial 0.35 T MR-Linac. Respiratory-correlated 4D-MRI were reconstructed and served as ground truth images. Series of interleaved orthogonal slices in sagittal and coronal orientation, intersecting the injected targets, were acquired at 7.3 Hz. Estimated 4D-MRI at 3.65 Hz were created in post-processing using the propagation method and compared to the ground truth 4D-MRI. Eight datasets at different breathing frequencies and motion amplitudes were acquired for three porcine lungs. The overall median (95[Formula: see text] percentile) deviation between ground truth and estimated deformation vector fields was 2.3 mm (5.7 mm), corresponding to 0.7 (1.6) times the in-plane imaging resolution (3.5 × 3.5 mm2). Median (95[Formula: see text] percentile) estimated nodule position errors were 1.5 mm (3.8 mm) for nodules intersected by orthogonal slices and 2.1 mm (7.1 mm) for nodules located more than 2 cm away from either of the orthogonal slices. The estimation error depended on the breathing phase, the motion amplitude and the location of the estimated position with respect to the orthogonal slices. By using the propagation method, the 4D motion within the porcine lung phantom could be accurately and robustly estimated. The method could provide valuable information for treatment planning, real-time motion monitoring, treatment adaptation, and post-treatment evaluation of MR-guided radiotherapy treatments.

Diagnostic accuracy of magnetic resonance imaging for the detection of pulmonary nodules simulated in a dedicated porcine chest phantom.

OBJECTIVE: CT serves as gold standard for the evaluation of pulmonary nodules. However, CT exposes patients to ionizing radiation, a concern especially in screening scenarios with repeated examinations. Due to recent technological advances, MRI emerges as a potential alternative for lung imaging using 3D steady state free precession and ultra-short echo-time sequences. Therefore, in this study we assessed the performance of three state-of-the-art MRI sequences for the evaluation of pulmonary nodules. METHODS: Lesions of variable sizes were simulated in porcine lungs placed in a dedicated chest phantom mimicking a human thorax, followed by CT and MRI examinations. Two blinded readers evaluated the acquired MR-images locating and measuring every suspect lesion. Using the CT-images as reference, logistic regression was performed to investigate the sensitivity of the tested MRI-sequences for the detection of pulmonary nodules. RESULTS: For nodules with a diameter of 6 mm, all three sequences achieved high sensitivity values above 0.91. However, the sensitivity dropped for smaller nodules, yielding an average of 0.83 for lesions with 4 mm in diameter and less than 0.69 for lesions with 2 mm in diameter. The positive predictive values ranged between 0.91 and 0.96, indicating a low amount of false positive findings. Furthermore, the size measurements done on the MR-images were subject to a bias ranging from 0.83 mm to -1.77 mm with standard deviations ranging from 1.40 mm to 2.11 mm. There was no statistically significant difference between the three tested sequences. CONCLUSION: While showing promising sensitivity values for lesions larger than 4 mm, MRI appears to be not yet suited for lung cancer screening. Nonetheless, the three tested MRI sequences yielded high positive predictive values and accurate size measurements; therefore, MRI could potentially figure as imaging method of the chest in selected follow-up scenarios, e.g. of incidental findings subject to the Fleischner Criteria.

Automated evaluation of probe-based confocal laser endomicroscopy in the lung.

RATIONALE: Probe-based confocal endomicroscopy provides real time videos of autoflourescent elastin structures within the alveoli. With it, multiple changes in the elastin structure due to different diffuse parenchymal lung diseases have previously been described. However, these evaluations have mainly relied on qualitative evaluation by the examiner and manually selected parts post-examination. OBJECTIVES: To develop a fully automatic method for quantifying structural properties of the imaged alveoli elastin and to perform a preliminary assessment of their diagnostic potential. METHODS: 46 patients underwent probe-based confocal endomicroscopy, of which 38 were divided into 4 groups categorizing different diffuse parenchymal lung diseases. 8 patients were imaged in representative healthy lung areas and used as control group. Alveolar elastin structures were automatically segmented with a trained machine learning algorithm and subsequently evaluated with two methods developed for quantifying the local thickness and structural connectivity. MEASUREMENTS AND MAIN RESULTS: The automatic segmentation algorithm performed generally well and all 4 patient groups showed statistically significant differences with median elastin thickness, standard deviation of thickness and connectivity compared to the control group. CONCLUSION: Alveoli elastin structures can be quantified based on their structural connectivity and thickness statistics with a fully-automated algorithm and initial results highlight its potential for distinguishing parenchymal lung diseases from normal alveoli.

Nonuniform Fourier-decomposition MRI for ventilation- and perfusion-weighted imaging of the lung.

PURPOSE: To improve the robustness of pulmonary ventilation- and perfusion-weighted imaging with Fourier decomposition (FD) MRI in the presence of respiratory and cardiac frequency variations by replacing the standard fast Fourier transform with the more general nonuniform Fourier transform. THEORY AND METHODS: Dynamic coronal single-slice MRI of the thorax was performed in 11 patients and 5 healthy volunteers on a 1.5T whole-body scanner using a 2D ultra-fast balanced steady-state free-precession sequence with temporal resolutions of 4-9 images/s. For the proposed nonuniform Fourier-decomposition (NUFD) approach, the original signal with variable physiological frequencies that was acquired with constant sampling rate was retrospectively transformed into a signal with (ventilation or perfusion) frequency-adapted sampling rate. For that purpose, frequency tracking was performed with the synchro-squeezed wavelet transform. Ventilation- and perfusion-weighted NUFD amplitude and signal delay maps were generated and quantitatively compared with regularly sampled FD maps based on their signal-to-noise ratio (SNR). RESULTS: Volunteers and patients showed statistically significant increases of SNR in frequency-adapted NUFD results compared to regularly sampled FD results. For ventilation data, the mean SNR increased by 43.4%±25.3% and 24.4%±31.9% in volunteers and patients, respectively; for perfusion data, SNR increased by 93.0%±36.1% and 75.6%±62.8% . Two patients showed perfusion signal in pulmonary areas with NUFD that could not be imaged with FD. CONCLUSION: This study demonstrates that using nonuniform Fourier transform in combination with frequency tracking can significantly increase SNR and reduce frequency overlaps by collecting the signal intensity onto single frequency bins.

Feasibility of 4DCBCT-based proton dose calculation: An ex vivo porcine lung phantom study.

Inter-fractional variations of breathing pattern and patient anatomy introduce dose uncertainties in proton therapy. One approach to monitor these variations is to utilize the cone-beam computed tomography (CT, CBCT) scans routinely taken for patient positioning, reconstruct them as 4DCBCTs, and generate 'virtual CTs' (vCTs), combining the accurate CT numbers of the diagnostic 4DCT and the geometry of the daily 4DCBCT by using deformable image registration (DIR). In this study different algorithms for 4DCBCT reconstruction and DIR were evaluated. For this purpose, CBCT scans of a moving ex vivo porcine lung phantom with 663 and 2350 projections respectively were acquired, accompanied by an additional 4DCT as reference. The CBCT projections were sorted in 10 phase bins with the Amsterdam-shroud method and reconstructed phase-by-phase using first a FDK reconstruction from the Reconstruction Toolkit (RTK) and again an iterative reconstruction algorithm implemented in the Gadgetron Toolkit. The resulting 4DCBCTs were corrected by DIR of the corresponding 4DCT phases, using both a morphons algorithm from REGGUI and a b-spline deformation from Plastimatch. The resulting 4DvCTs were compared to the 4DCT by visual inspection and by calculating water equivalent thickness (WET) maps from the phantom's surface to the distal edge of a target from various angles. The optimized procedure was successfully repeated with mismatched input phases and on a clinical patient dataset. Proton treatment plans were simulated on the 4DvCTs and the dose distributions compared to the reference based on the 4DCT via gamma pass rate analysis. A combination of iterative reconstruction and morphons DIR yielded the most accurate 4DvCTs, with median WET differences under 2mm and 3%/3mm gamma pass rates per phase between 89% and 99%. These results suggest that image correction of iteratively reconstructed 4DCBCTs with a morphons DIR of the planning CT may yield sufficiently accurate 4DvCTs for daily time resolved proton dose calculations.

Detection of artificial pulmonary lung nodules in ultralow-dose CT using an ex vivo lung phantom.

OBJECTIVES: To assess the image quality of 3 different ultralow-dose CT protocols on pulmonary nodule depiction in a ventilated ex vivo-system. MATERIALS AND METHODS: Four porcine lungs were inflated inside a dedicated chest phantom and prepared with n = 195 artificial nodules (0.5-1 mL). The artificial chest wall was filled with water to simulate the absorption of a human chest. Images were acquired with a 2x192-row detector CT using low-dose (reference protocol with a tube voltage of 120 kV) and 3 different ULD protocols (respective effective doses: 1mSv and 0.1mSv). A different tube voltage was used for each ULD protocol: 70kV, 100kV with tin filter (100kV_Sn) and 150kV with tin filter (150kV_Sn). Nodule delineation was assessed by two observers (scores 1-5, 1 = unsure, 5 = high confidence). RESULTS: The diameter of the 195 detected artificial nodules ranged from 0.9-21.5 mm (mean 7.84 mm ± 5.31). The best ULD scores were achieved using 100kV_Sn and 70 kV ULD protocols (4.14 and 4.06 respectively). Both protocols were not significantly different (p = 0.244). The mean score of 3.78 in ULD 150kV_Sn was significantly lower compared to the 100kV_Sn ULD protocol (p = 0.008). CONCLUSION: The results of this experiment, conducted in a realistic setting show the feasibility of ultralow-dose CT for the detection of pulmonary nodules.