Motion compensated cone-beam CT reconstruction using ana priorimotion model from CT simulation: a pilot study.

Objective. To combat the motion artifacts present in traditional 4D-CBCT reconstruction, an iterative technique known as the motion-compensated simultaneous algebraic reconstruction technique (MC-SART) was previously developed. MC-SART employs a 4D-CBCT reconstruction to obtain an initial model, which suffers from a lack of sufficient projections in each bin. The purpose of this study is to demonstrate the feasibility of introducing a motion model acquired during CT simulation to MC-SART, coined model-based CBCT (MB-CBCT).Approach. For each of 5 patients, we acquired 5DCTs during simulation and pre-treatment CBCTs with a simultaneous breathing surrogate. We cross-calibrated the 5DCT and CBCT breathing waveforms by matching the diaphragms and employed the 5DCT motion model parameters for MC-SART. We introduced the Amplitude Reassignment Motion Modeling technique, which measures the ability of the model to control diaphragm sharpness by reassigning projection amplitudes with varying resolution. We evaluated the sharpness of tumors and compared them between MB-CBCT and 4D-CBCT. We quantified sharpness by fitting an error function across anatomical boundaries. Furthermore, we compared our MB-CBCT approach to the traditional MC-SART approach. We evaluated MB-CBCT's robustness over time by reconstructing multiple fractions for each patient and measuring consistency in tumor centroid locations between 4D-CBCT and MB-CBCT.Main results. We found that the diaphragm sharpness rose consistently with increasing amplitude resolution for 4/5 patients. We observed consistently high image quality across multiple fractions, and observed stable tumor centroids with an average 0.74 ± 0.31 mm difference between the 4D-CBCT and MB-CBCT. Overall, vast improvements over 3D-CBCT and 4D-CBCT were demonstrated by our MB-CBCT technique in terms of both diaphragm sharpness and overall image quality.Significance. This work is an important extension of the MC-SART technique. We demonstrated the ability ofa priori5DCT models to provide motion compensation for CBCT reconstruction. We showed improvements in image quality over both 4D-CBCT and the traditional MC-SART approach.

An analysis of the regional heterogeneity in tissue elasticity in lung cancer patients with COPD.

Purpose: Recent advancements in obtaining image-based biomarkers from CT images have enabled lung function characterization, which could aid in lung interventional planning. However, the regional heterogeneity in these biomarkers has not been well documented, yet it is critical to several procedures for lung cancer and COPD. The purpose of this paper is to analyze the interlobar and intralobar heterogeneity of tissue elasticity and study their relationship with COPD severity. Methods: We retrospectively analyzed a set of 23 lung cancer patients for this study, 14 of whom had COPD. For each patient, we employed a 5DCT scanning protocol to obtain end-exhalation and end-inhalation images and semi-automatically segmented the lobes. We calculated tissue elasticity using a biomechanical property estimation model. To obtain a measure of lobar elasticity, we calculated the mean of the voxel-wise elasticity values within each lobe. To analyze interlobar heterogeneity, we defined an index that represented the properties of the least elastic lobe as compared to the rest of the lobes, termed the Elasticity Heterogeneity Index (EHI). An index of 0 indicated total homogeneity, and higher indices indicated higher heterogeneity. Additionally, we measured intralobar heterogeneity by calculating the coefficient of variation of elasticity within each lobe. Results: The mean EHI was 0.223 ± 0.183. The mean coefficient of variation of the elasticity distributions was 51.1% ± 16.6%. For mild COPD patients, the interlobar heterogeneity was low compared to the other categories. For moderate-to-severe COPD patients, the interlobar and intralobar heterogeneities were highest, showing significant differences from the other groups. Conclusion: We observed a high level of lung tissue heterogeneity to occur between and within the lobes in all COPD severity cases, especially in moderate-to-severe cases. Heterogeneity results demonstrate the value of a regional, function-guided approach like elasticity for procedures such as surgical decision making and treatment planning.

Automatic triangulated mesh generation of pulmonary airways from segmented lung 3DCTs for computational fluid dynamics.

PURPOSE: Computational fluid dynamics (CFD) of lung airflow during normal and pathophysiological breathing provides insight into regional pulmonary ventilation. By integrating CFD methods with 4D lung imaging workflows, regions of normal pulmonary function can be spared during treatment planning. To facilitate the use of CFD simulations in a clinical setup, a robust, automated, and CFD-compliant airway mesh generation technique is necessary. METHODS: We define a CFD-compliant airway mesh to be devoid of blockages of airflow and leaks in the airway path, both of which are caused by airway meshing errors that occur when using conventional meshing techniques. We present an algorithm to create a CFD-compliant airway mesh in an automated manner. Beginning with a medial skeleton of the airway segmentation, the branches were tracked, and 3D points at which bifurcations occur were identified. Airway branches and bifurcation features were isolated to allow for automated and careful meshing that considered their anatomical nature. RESULTS: We present the meshing results from three state-of-the-art tools and compare them with the meshes generated by our algorithm. The results show that fully CFD-compliant meshes were automatically generated for an ideal geometry and patient-specific CT scans. Using an open-source smoothed-particle hydrodynamics CFD implementation, we compared the airflow using our approach and conventionally generated airway meshes. CONCLUSION: Our meshing algorithm was able to successfully generate a CFD-compliant mesh from pre-segmented lung CT scans, providing an automatic meshing approach that enables interventional CFD simulations to guide lung procedures such as radiotherapy or lung volume reduction surgery.

Ventilation measurements using fast-helical free-breathing computed tomography.

PURPOSE: To examine the use of multiple fast-helical free breathing computed tomography (FHFBCT) scans for ventilation measurement. METHODS: Ten patients were scanned 25 times in alternating directions using a FHFBCT protocol. Simultaneously, an abdominal pneumatic bellows was used as a real-time breathing surrogate. Regions-of-interest (ROIs) were selected from the upper right lungs of each patient for analysis. The ROIs were first registered using a published registration technique (pTV). A subsequent follow-up registration employed an objective function with two terms, a ventilation-adjusted Hounsfield Unit difference and a conservation-of-mass term labeled ΔΓ that denoted the difference between the deformation Jacobian and the tissue density ratio. The ventilations were calculated voxel-by-voxel as the slope of a first-order fit of the Jacobian as a function of the breathing amplitude. RESULTS: The ventilations of the 10 patients showed different patterns and magnitudes. The average ventilation calculated from the deformation vector fields (DVFs) of the pTV and secondary registration was nearly identical, but the standard deviation of the voxel-to-voxel differences was approximately 0.1. The mean of the 90th percentile values of ΔΓ was reduced from 0.153 to 0.079 between the pTV and secondary registration, implying first that the secondary registration improved the conservation-of-mass criterion by almost 50% and that on average the correspondence between the Jacobian and density ratios as demonstrated by ΔΓ was less than 0.1. This improvement occurred in spite of the average of the 90th percentile changes in the DVF magnitudes being only 0.58 mm. CONCLUSIONS: This work introduces the use of multiple free-breathing CT scans for free-breathing ventilation measurements. The approach has some benefits over the traditional use of 4-dimensional CT (4DCT) or breath-hold scans. The benefit over 4DCT is that FHFBCT does not have sorting artifacts. The benefits over breath-hold scans include the relatively small motion induced by quiet respiration versus deep-inspiration breath hold and the potential for characterizing dynamic breathing processes that disappear during breath hold.

Scalable quorum-based deep neural networks with adversarial learning for automated lung lobe segmentation in fast helical free-breathing CTs.

PURPOSE: Fast helical free-breathing CT (FHFBCT) scans are widely used for 5DCT and 5D Cone Beam imaging protocols. For quantitative analysis of lung physiology and function, it is important to segment the lung lobes in these scans. Since the 5DCT protocols use up to 25 FHFBCT scans, it is important that this segmentation task be automated. In this paper, we present a deep neural network (DNN) framework for segmenting the lung lobes in near real time. METHODS: A total of 22 patient datasets (550 3D CT scans) were used for the study. Each of the lung lobes was manually segmented and considered ground-truth. A supervised and constrained generative adversarial network (CGAN) was employed for learning each set of lobe segmentations for each patient with 12 patients designated for training data. The resulting generator DNNs represented the lobe segmentations for each training dataset. A quorum-based algorithm was then implemented to test validation data consisting of 10 separate patient datasets (250 3D CTs). Each of the DNNs predicted their corresponding lobes for the validation data, and equal weights were given to the 12 generator CGANs. The quorum process worked by selecting the weighted average result of all 12 CGAN results for each lobe. RESULTS: When evaluated against ground-truth segmentations, the quorum-based lobe segmentation was observed to have average structural similarity index, normalized cross-correlation coefficient, and dice coefficient values of 0.929, 0.806, and 0.814, respectively, compared to values of 0.911, 0.698, and 0.696, respectively, using a conventional strategy. CONCLUSION: The proposed quorum-based approach computed segmentations with clinically acceptable accuracy in near real time using a multi-GPU-based computing setup. This method is scalable as more patient-specific CGANs can be added to the quorum over time.

Analysis of Geometric Performance and Dosimetric Impact of Using Automatic Contour Segmentation for Radiotherapy Planning.

Purpose: To analyze geometric discrepancy and dosimetric impact in using contours generated by auto-segmentation (AS) against manually segmented (MS) clinical contours. Methods: A 48-subject prostate atlas was created and another 15 patients were used for testing. Contours were generated using a commercial atlas-based segmentation tool and compared to their clinical MS counterparts. The geometric correlation was evaluated using the Dice similarity coefficient (DSC) and Hausdorff distance (HD). Dosimetric relevance was evaluated for a subset of patients by assessing the DVH differences derived by optimizing plan dose using the AS and MS contours, respectively, and evaluating with respect to each. A paired t-test was employed for statistical comparison. The discrepancy in plan quality with respect to clinical dosimetric endpoints was evaluated. The analysis was repeated for head/neck (HN) with a 31-subject atlas and 15 test cases. Results: Dice agreement between AS and MS differed significantly across structures: from (L:0.92/R: 0.91) for the femoral heads to seminal vesical of 0.38 in the prostate cohort, and from 0.98 for the brain, to 0.36 for the chiasm of the HN group. Despite the geometric disagreement, the paired t-tests showed the lack of statistical evidence for systematic differences in dosimetric plan quality yielded by the AS and MS approach for the prostate cohort. In HN cases, statistically significant differences in dosimetric endpoints were observed in structures with small volumes or elongated shapes such as cord (p = 0.01) and esophagus (p = 0.04). The largest absolute dose difference of 11 Gy was seen in the mean pharynx dose. Conclusion: Varying AS performance among structures suggests a differential approach of using AS on a subset of structures and focus MS on the rest. The discrepancy between geometric and dosimetric-end-point driven evaluation also indicates the clinical utility of AS contours in optimization and evaluating plan quality despite of suboptimal geometrical accuracy.

Systematic feasibility analysis of performing elastography using reduced dose CT lung image pairs.

PURPOSE: Elastography using computer tomography (CT) is a promising methodology that can provide patient-specific regional distributions of lung biomechanical properties. The purpose of this paper is to investigate the feasibility of performing elastography using simulated lower dose CT scans. METHODS: A cohort of eight patient CT image pairs were acquired with a tube current-time product of 40 mAs for estimating baseline lung elastography results. Synthetic low mAs CT scans were generated from the baseline scans to simulate the additional noise that would be present in acquisitions at 30, 25, and 20 mAs, respectively. For the simulated low mAs scans, exhalation and inhalation datasets were registered using an in-house optical flow deformable image registration algorithm. The registered deformation vector fields (DVFs) were taken to be ground truth for the elastography process. A model-based elasticity estimation was performed for each of the reduced mAs datasets, in which the goal was to optimize the elasticity distribution that best represented their respective DVFs. The estimated elasticity and the DVF distributions of the reduced mAs scans were then compared with the baseline elasticity results for quantitative accuracy purposes. RESULTS: The DVFs for the low mAs and baseline scans differed from each other by an average of 1.41 mm, which can be attributed to the noise added by the simulated reduction in mAs. However, the elastography results using the DVFs from the reduced mAs scans were similar from the baseline results, with an average elasticity difference of 0.65, 0.71, and 0.76 kPa, respectively. This illustrates that elastography can provide equivalent results using low-dose CT scans. CONCLUSIONS: Elastography can be performed equivalently using CT image pairs acquired with as low as 20 mAs. This expands the potential applications of CT-based elastography.