A complete 4<scp>DCT</scp>‐ventilation functional avoidance virtual trial: Developing strategies for prospective clinical trials

Waxweiler, Timothy V.; Schubert, Laura; Diot, Quentin; Faught, Austin M.; Stuhr, Kelly; Castillo, Richard; Castillo, Edward M.; Guerrero, Thomas; Rusthoven, Chad G.; Gaspar, Laurie E.; Kavanagh, Brian D.; Miften, Moyed; Vinogradskiy, Yevgeniy

doi:10.1002/acm2.12086

Cited by 29 publications

(21 citation statements)

References 36 publications

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“…This retrospective work on 4D CT ventilation imaging has provided the framework for design of clinical trials using 4D CT, ventilation imaging for functional avoidance radiotherapy [ 67 ], NCT02528942. To provide practical data for guidance on assessment of patient eligibility, planning strategies and methods of assessment for functional treatment plans, Waxweiler et al recently published a complete virtual trial using retrospective data from 96 LA-NSCLC patients [ 68 ]. Their functional planning demonstrated than an average reduction of 2.8 Gy to the mean lung dose can be expected relative to standard thoracic plans.…”

Section: New Frontiersmentioning

confidence: 99%

Radiation Pneumonitis: Old Problem, New Tricks

Jain

Berman

2018

Cancers

131

104

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Radiation therapy is a major treatment modality for management of non-small cell lung cancer. Radiation pneumonitis is a dose limiting toxicity of radiotherapy, affecting its therapeutic ratio. This review presents patient and treatment related factors associated with the development of radiation pneumonitis. Research focusing on reducing the incidence of radiation pneumonitis by using information about lung ventilation, imaging-based biomarkers as well as normal tissue complication models is discussed. Recent advances in our understanding of molecular mechanisms underlying lung injury has led to the development of several targeted interventions, which are also explored in this review.

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Section: New Frontiersmentioning

confidence: 99%

Radiation Pneumonitis: Old Problem, New Tricks

Jain

Berman

2018

Cancers

131

104

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“…This personalization of treatment is especially important in patients with non-small cell lung cancer (NSCLC), who are known to have comorbidities and functional lung defects that change during the course of fractionated RT (13–16). Recent clinical studies have shown significant differences between anatomic-and functional-guided radiation treatment plans using a variety of functional imaging modalities, such as single-photon emission computed tomography (SPECT) (17–20), 4-dimensional computed tomography (CT) (21–24), and hyperpolarized magnetic resonance imaging (25, 26). Although preliminary studies have predicted toxicity reduction using functional-guided RT (27, 28), further work is still required to explicitly understand normal-tissue dose-function response and its effect on radiation-induced lung toxicity (RILT) incidence.…”

Section: Introductionmentioning

confidence: 99%

Modeling Patient-Specific Dose-Function Response for Enhanced Characterization of Personalized Functional Damage

Owen

Boonstra

Viglianti

et al. 2018

International Journal of Radiation Oncology*Biology*Physics

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This study modeled the patient-specific dose-function response in patients with non-small cell lung cancer during and after radiation treatment. The generated population-level dose-function response models were derived from individual patient assessment and have the potential to inform functional-guided treatment plans regarding the expected functional lung damage. This type of patient-specific modeling approach can be applied broadly to other functional response analyses to better capture intrapatient dependencies and characterize personalized functional damage.

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“…), as well as the potential dosimetric consequences of IJF on radiotherapy functional avoidance planning studies (such as those in Ref. ).…”

Section: Discussionmentioning

confidence: 99%

Robust CT ventilation from the integral formulation of the Jacobian

Castillo

Vinogradskiy

et al. 2019

Medical Physics

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Computed tomography (CT) derived ventilation algorithms estimate the apparent voxel volume changes within an inhale/exhale CT image pair. Transformation-based methods compute these estimates solely from the spatial transformation acquired by applying a deformable image registration (DIR) algorithm to the image pair. However, approaches based on finite difference approximations of the transformation’s Jacobian have been shown to be numerically unstable. As a result, transformation-based CT ventilation is poorly reproducible with respect to both DIR algorithm and CT acquisition method. Purpose: We introduce a novel Integrated Jacobian Formulation (IJF) method for estimating voxel volume changes under a DIR recovered spatial transformation. The method is based on computing volume estimates of DIR mapped subregions using the hit-or-miss sampling algorithm for integral approximation. The novel approach allows for regional volume change estimates that 1) respect the resolution of the digital grid and 2) are based on approximations with quantitatively characterized and controllable levels of uncertainty. As such, the IJF method is designed to be robust to variations in DIR solutions and thus overall more reproducible. Methods: Numerically, Jacobian estimates are recovered by solving a simple constrained linear least squares problem that guarantees the recovered global volume change is equal to the global volume change obtained from the inhale and exhale lung segmentation masks. Reproducibility of the IJF method with respect to DIR solution was assessed using the expert-determined landmark point pairs and inhale/exhale phases from 10 4DCTs available on www.dir-lab.com. Reproducibility with respect to CT acquisition was assessed on the 4DCT and 4D cone beam CT (4DCBCT) images acquired for five lung cancer patients prior to radiotherapy. Results: The ten Dir-Lab 4DCT cases were registered twice with the same DIR algorithm, but with different smoothing parameter. Finite difference Jacobian (FDJ) and IFJ images were computed for both solutions. The average spatial errors (300 landmarks per case) for the two DIR solution methods were 0.98 (1.10) and 1.02 (1.11). The average Pearson correlation between the FDJ images computed from the two DIR solutions was 0.83 (0.03), while for the IJF images it was 1.00 (0.00). For inter-modality assessment, the IJF and FDJ images were computed from the 4DCT and 4DCBCT of five patients. The average Pearson correlation of the spatially aligned FDJ images was 0.27 (0.11), while it was 0.77 (0.13) for the IFJ method. Conclusion: The mathematical theory underpinning the IJF method allows for the generation of ventilation images that are 1) computed with respect to DIR spatial accuracy on the digital voxel grid and 2) based on DIR measured subregional volume change estimates acquired with quantifiable and controllable levels of uncertainty. Analyses of the experiments are consistent with the mathematical theory and indicate that IJF ventilation imaging has a higher reproducibility with res...

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A complete 4DCT‐ventilation functional avoidance virtual trial: Developing strategies for prospective clinical trials

Cited by 29 publications

References 36 publications

Radiation Pneumonitis: Old Problem, New Tricks

Radiation Pneumonitis: Old Problem, New Tricks

Modeling Patient-Specific Dose-Function Response for Enhanced Characterization of Personalized Functional Damage

Robust CT ventilation from the integral formulation of the Jacobian

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