Spatial Comparison of CT-Based Surrogates of Lung Ventilation With Hyperpolarized Helium-3 and Xenon-129 Gas MRI in Patients Undergoing Radiation Therapy

Tahir, Bilal; Hughes, Paul; Robinson, Stephen; Marshall, Helen; Stewart, Neil J.; Norquay, Graham; Biancardi, Alberto; Chan, Ho‐Fung; Collier, Guilhem J.; Hart, Kerry; Swinscoe, James; Hatton, Matthew; Wild, Jim M.; Ireland, R.H.

doi:10.1016/j.ijrobp.2018.04.077

Cited by 30 publications

(50 citation statements)

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“…Comparisons with Xenon CT in mechanically ventilated sheep, and ex vivo imaging of fluorescent microspheres in mice have featured highly controlled experimental conditions and achieved strong cross‐modality correlations (e.g., with voxel‐level correlations exceeding ∼0.8 for small lung subvolumes). 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 .…”

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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^{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

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

Self Cite

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“…The percentage ventilated volume (%VV) was calculated for each patient by taking the ratio of the binary lung segmentations of 3 He and 1 H MRI. For spatial comparison of 3 He MRI and CT ventilation, for each patient, MR images were registered to the TLC-CT image's spatial domain via the anatomical same-breath 1 H MRI as previously described (Tahir et al, 2014) and Dice similarity coefficients (DSCs) were computed separately for the binary segmentations of both CT ventilation percentiles with that of FRC+1L and TLC He MRI. The workflow for the comparison method of FRC+1L and TLC 3 He MRI with CT ventilation is shown in Figure 1.…”

Section: Comparison Of 3 He Mri and Ctmentioning

confidence: 99%

“…Whilst we can say that CT ventilation derived from TLC and FRC may not provide measures of ventilation which are as sensitive as FRC+1L 3 He MRI at depicting ventilation defects, we cannot say that this will be the case for CT ventilation derived from a different pair of inflation levels. For example, we recently demonstrated that CT ventilation maps derived from FRC and FRC+1L show moderate correlations with hyperpolarised gas MRI and marked ventilation defects (Tahir et al, 2018). To comprehensively answer this question, we require CT acquired at more than two inflation levels (e.g.…”

Section: Impact Of 3 He Mr Inflation Level On Correlation With Ct Venmentioning

confidence: 99%

“…129 Xe is a naturally-abundant isotope for hyperpolarised gas MRI and has demonstrated good correlations with 3 He in static lung ventilation and diffusion-weighted MRI (Stewart et al, 2018). We have recently compared both gases with CT ventilation imaging in lung cancer patients and demonstrated moderately low correlations of CT at the voxel-level against both gases, increasing with larger regional analysis, while strong correlations were observed between 3 He and 129 Xe (Tahir et al, 2018). Technical developments in the field of multiple-breath washout imaging with 129 Xe may pave the way for improved comparative studies with CT ventilation imaging.…”

Section: Impact Of 3 He Mr Inflation Level On Correlation With Ct Venmentioning

confidence: 99%

“…Over the past decade, CTbased methods of mapping regional ventilation, sometimes referred to as 'CT ventilation imaging', which are based on image registration of non-contrast lung CT images acquired at two different inflation levels, have been proposed as a surrogate method to image lung 'ventilation' (Guerrero et al, 2005;Reinhardt et al, 2008). Although the technique has gained considerable interest, relatively few papers have addressed the issue of validation against established direct ventilation imaging modalities such as hyperpolarised gas MRI (Mathew et al, 2012;Tahir et al, 2016;Tahir et al, 2018). However, direct comparison of CT ventilation imaging and gas ventilation MRI requires consideration of the potential sensitivity of both methods to lung inflation state.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of CT ventilation imaging and hyperpolarised gas MRI: effects of breathing manoeuvre

Tahir¹,

Marshall²,

Hughes³

et al. 2019

Phys. Med. Biol.

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Image registration of lung CT images acquired at different inflation levels has been proposed as a surrogate method to map lung 'ventilation'. Prior to clinical use, it is important to understand how this technique compares with direct ventilation imaging modalities such as hyperpolarised gas MRI. However, variations in lung inflation level have been shown to affect regional ventilation distributions. Therefore, the aim of this study was to evaluate the impact of lung inflation levels when comparing CT ventilation imaging to ventilation from 3 He-MRI.

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A pilot study of function‐based radiation therapy planning for lung cancer using hyperpolarized xenon‐129 ventilation MRI

Ding

Yang

Zhou

et al. 2022

J Applied Clin Med Phys

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Purpose Radiation‐induced lung injury (RILI) is a common side effect in patients with non‐small cell lung cancer (NSCLC) treated with radiotherapy. Minimizing irradiation into highly functional areas of the lung may reduce the occurrence of RILI. The aim of this study is to evaluate the feasibility and utility of hyperpolarized xenon‐129 magnetic resonance imaging (MRI), an imaging tool for evaluation of the pulmonary function, to guide radiotherapy planning. Methods Ten locally advanced NSCLC patients were recruited. Each patient underwent a simulation computed tomography (CT) scan and hyperpolarized xenon‐129 MRI, then received 64 Gyin 32 fractions for radiotherapy. Clinical contours were drawn on CT. Lung regions with good ventilation were contoured based on the MRI. Two intensity‐modulated radiation therapy plans were made for each patient: an anatomic plan (Plan‐A) based on CT alone and a function‐based plan (Plan‐F) based on CT and MRI results. Compared to Plan‐A, Plan‐F was generated with two additional steps: (1) beam angles were carefully chosen to minimize direct radiation entering well‐ventilated areas, and (2) additional optimization criteria were applied to well‐ventilated areas to minimize dose exposure. V20Gy, V10Gy, V5Gy, and the mean dose in the lung were compared between the two plans. Results Plan‐A and Plan‐F were both clinically acceptable and met similar target coverage and organ‐at‐risk constraints (p > 0.05) except for the ventilated lungs. Compared with Plan‐A, V5Gy (Plan‐A: 30.7 ± 11.0%, Plan‐F: 27.2 ± 9.3%), V10Gy (Plan‐A: 22.0 ± 8.6%, Plan‐F: 19.3 ± 7.0%), and V20Gy (Plan‐A: 12.5 ± 5.6%, Plan‐F: 11.0 ± 4.1%) for well‐ventilated lung areas were significantly reduced in Plan‐F (p < 0.05). Conclusion In this pilot study, function‐based radiotherapy planning using hyperpolarized xenon‐129 MRI is demonstrated to be feasible in 10 patients with NSCLC with the potential to reduce radiation exposure in well‐ventilated areas of the lung defined by hyperpolarized xenon‐129 MRI.

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Spatial Comparison of CT-Based Surrogates of Lung Ventilation With Hyperpolarized Helium-3 and Xenon-129 Gas MRI in Patients Undergoing Radiation Therapy

Abstract: Spatial comparison of CT-based surrogates of lung ventilation with hyperpolarized Helium-3 and Xenon-129 gas MRI in patients undergoing radiation therapy

Cited by 30 publications

References 56 publications

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

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

Comparison of CT ventilation imaging and hyperpolarised gas MRI: effects of breathing manoeuvre

A pilot study of function‐based radiation therapy planning for lung cancer using hyperpolarized xenon‐129 ventilation MRI

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