CT ventilation imaging derived from breath hold CT exhibits good regional accuracy with Galligas PET

Eslick, Enid M.; Kipritidis, John; Gradinscak, Denis J.; Stevens, Michael G.; Bailey, Dale L.; Harris, Benjamin; Booth, Jeremy; Keall, Paul J.

doi:10.1016/j.radonc.2017.12.010

Cited by 18 publications

(25 citation statements)

References 19 publications

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“…Neural networks have also been proposed as a means of generating ventilation images. 21 The majority of described CT ventilation methods have been applied to 4DCT data; however, Eslick et al 23 recently demonstrated improved accuracy of CT ventilation images using breath-hold CTs for ventilation image calculation. Although these more recently proposed methods of calculating CT ventilation are in their nascent state, early results suggest promise in overcoming some of the challenges associated with conventional CT-ventilation calculation methodologies.…”

Section: Calculation Methodologies Of Ct-based Ventilation Imagingmentioning

confidence: 99%

CT-based ventilation imaging in radiation oncology

Vinogradskiy

2019

BJR|Open

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A form of lung function imaging is emerging that uses phase-resolved four-dimensional CT (4DCT or breath-hold CT) images along with image processing techniques to generate lung function maps that provide a surrogate of lung ventilation. CT-based ventilation (referred to as CT-ventilation) research has gained momentum in Radiation Oncology because many lung cancer patients undergo four-dimensional CT simulation as part of the standard treatment planning process. Therefore, generating CT-ventilation images provides functional information without burdening the patient with an extra imaging procedure. CT-ventilation has progressed from an image processing calculation methodology, to validation efforts, to retrospective demonstration of clinical utility in Radiation Oncology. In particular, CT-ventilation has been proposed for two main clinical applications: functional avoidance radiation therapy and thoracic dose–response assessment. The idea of functional avoidance radiation therapy is to preferentially spare functional portions of the lung (as measured by CT-ventilation) during radiation therapy with the hypothesis that reducing dose to functional portions of the lung will lead to reduced rates of radiation-related thoracic toxicity. The idea of imaging-based dose–response assessment is to evaluate pre- to post-treatment CT-ventilation-based imaging changes. The hypothesis is that early, imaging-change-based response can be an early predictor of subsequent thoracic toxicity. Based on the retrospective evidence, the clinical applications of CT-ventilation have progressed from the retrospective setting to on-going prospective clinical trials. This review will cover basic CT-ventilation calculation methodologies, validation efforts, presentation of clinical applications, summarize on-going clinical trials, review potential uncertainties and shortcomings of CT-ventilation, and discuss future directions of CT-ventilation research.

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Section: Calculation Methodologies Of Ct-based Ventilation Imagingmentioning

confidence: 99%

CT-based ventilation imaging in radiation oncology

Vinogradskiy

2019

BJR|Open

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“…In contrast, clinical human studies using single photon emission computed tomography (SPECT) with technetium‐99m (

^{99 m} Tc

), positron emission tomography (PET) with gallium‐68 (

^{68} Ga

),, and hyperpolarized gas MRI with either helium‐3 (

^{3} He

) or xenon‐129 (

^{129} Xe

) have all shown variable cross‐modality correlations (mean Spearman correlations in the range 0.1–0.8), which has been variously attributed to poor image quality in the 4DCT dataset or the RefVI scan, time delays between intrapatient scans, or poor reproducibility of breathing patterns/maneuvers. A recent study by Eslick et al . evaluated CTVI against Galligas PET and suggests the possibility for substantial improvement in cross‐modality correlations when the CTVI is derived from high‐quality exhale/inhale BHCT as opposed to 4DCT.…”

Section: Introductionmentioning

confidence: 99%

The VAMPIRE challenge: A multi‐institutional validation study of CT ventilation imaging

et al. 2019

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Purpose CT ventilation imaging (CTVI) is being used to achieve functional avoidance lung cancer radiation therapy in three clinical trials (NCT02528942, NCT02308709, NCT02843568). To address the need for common CTVI validation tools, we have built the Ventilation And Medical Pulmonary Image Registration Evaluation (VAMPIRE) Dataset, and present the results of the first VAMPIRE Challenge to compare relative ventilation distributions between different CTVI algorithms and other established ventilation imaging modalities. Methods The VAMPIRE Dataset includes 50 pairs of 4DCT scans and corresponding clinical or experimental ventilation scans, referred to as reference ventilation images (RefVIs). The dataset includes 25 humans imaged with Galligas 4DPET/CT, 21 humans imaged with DTPA‐SPECT, and 4 sheep imaged with Xenon‐CT. For the VAMPIRE Challenge, 16 subjects were allocated to a training group (with RefVI provided) and 34 subjects were allocated to a validation group (with RefVI blinded). Seven research groups downloaded the Challenge dataset and uploaded CTVIs based on deformable image registration (DIR) between the 4DCT inhale/exhale phases. Participants used DIR methods broadly classified into B‐splines, Free‐form, Diffeomorphisms, or Biomechanical modeling, with CT ventilation metrics based on the DIR evaluation of volume change, Hounsfield Unit change, or various hybrid approaches. All CTVIs were evaluated against the corresponding RefVI using the voxel‐wise Spearman coefficient rS, and Dice similarity coefficients evaluated for low function lung (DSClow) and high function lung (DSChigh). Results A total of 37 unique combinations of DIR method and CT ventilation metric were either submitted by participants directly or derived from participant‐submitted DIR motion fields using the in‐house software, VESPIR. The rS and DSC results reveal a high degree of inter‐algorithm and intersubject variability among the validation subjects, with algorithm rankings changing by up to ten positions depending on the choice of evaluation metric. The algorithm with the highest overall cross‐modality correlations used a biomechanical model‐based DIR with a hybrid ventilation metric, achieving a median (range) of 0.49 (0.27–0.73) for rS, 0.52 (0.36–0.67) for DSClow, and 0.45 (0.28–0.62) for DSChigh. All other algorithms exhibited at least one negative rS value, and/or one DSC value less than 0.5. Conclusions The VAMPIRE Challenge results demonstrate that the cross‐modality correlation between CTVIs and the RefVIs varies not only with the choice of CTVI algorithm but also with the choice of RefVI modality, imaging subject, and the evaluation metric used to compare relative ventilation distributions. This variability may arise from the fact that each of the different CTVI algorithms and RefVI modalities provides a distinct physiologic measurement. Ultimately this variability, coupled with the lack of a “gold standard,” highlights the ongoing importance of further validation studies before CTVI can be widely translated from academic ce...

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Section: Perspective and Future Challengesmentioning

confidence: 99%

“…4D CT based methods have also shown promising results to estimate regional ventilation lung function (89,90). However, high quality CT imaging is a key requirement given the potential for artifacts (90,91). Furthermore, data in the literature seem to favor the use of perfusion data rather than ventilation for functional optimization of dose delivery to the lung.…”

Section: Perspective and Future Challengesmentioning

confidence: 99%

Radiation Therapy Planning of Thoracic Tumors: A Review of Challenges Associated With Lung Toxicities and Potential Perspectives of Gallium-68 Lung PET/CT Imaging

et al. 2021

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Despite the introduction of new radiotherapy techniques, such as intensity modulated radiation therapy or stereotactic body radiation therapy, radiation induced lung injury remains a significant treatment related adverse event of thoracic radiation therapy. Functional lung avoidance radiation therapy is an emerging concept in the treatment of lung disease to better preserve lung function and to reduce pulmonary toxicity. While conventional ventilation/perfusion (V/Q) lung scintigraphy is limited by a relatively low spatial and temporal resolution, the recent advent of 68Gallium V/Q lung PET/CT imaging offers a potential to increase the accuracy of lung functional mapping and to better tailor lung radiation therapy plans to the individual's lung function. Lung PET/CT imaging may also improve our understanding of radiation induced lung injury compared to the current anatomical based dose–volume constraints. In this review, recent advances in radiation therapy for the management of primary and secondary lung tumors and in V/Q PET/CT imaging for the assessment of functional lung volumes are reviewed. The new opportunities and challenges arising from the integration of V/Q PET/CT imaging in radiation therapy planning are also discussed.

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CT ventilation imaging derived from breath hold CT exhibits good regional accuracy with Galligas PET

Abstract: High quality CT imaging is a key requirement for accurate CT ventilation imaging. The use of exhale/inhale BHCT can improve the accuracy of CTVI for human subjects.

Cited by 18 publications

References 19 publications

CT-based ventilation imaging in radiation oncology

CT-based ventilation imaging in radiation oncology

The VAMPIRE challenge: A multi‐institutional validation study of CT ventilation imaging

Radiation Therapy Planning of Thoracic Tumors: A Review of Challenges Associated With Lung Toxicities and Potential Perspectives of Gallium-68 Lung PET/CT Imaging

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