Physiological imaging of the lung: single-photon-emission computed tomography (SPECT)

Free-breathing 3D phase-resolved functional lung MRI vs breath-hold hyperpolarized 129Xe ventilation MRI in patients with chronic obstructive pulmonary disease and healthy volunteers

OBJECTIVES

3D phase-resolved functional lung (PREFUL) MRI offers evaluation of pulmonary ventilation without inhalation of contrast agent. This study seeks to compare ventilation maps obtained from 3D PREFUL MRI with a direct ventilation measurement derived from 129Xe MRI in both patients with chronic obstructive pulmonary disease (COPD) and healthy volunteers.

METHODS

Thirty-one patients with COPD and 12 healthy controls underwent free-breathing 3D PREFUL MRI and breath-hold 129Xe MRI at 1.5 T. For both MRI techniques, ventilation defect (VD) maps were determined and respective ventilation defect percentage (VDP) values were computed. All parameters of both techniques were compared by Spearman correlation coefficient (r) and the differences between VDP values were quantified by Bland-Altman analysis and tested for significance using Wilcoxon signed-rank test. In a regional comparison of VD maps, spatial overlap and Sørensen-Dice coefficients of healthy and defect areas were computed.

RESULTS

On a global level, all 3D PREFUL VDP values correlated significantly to VDP measure derived by 129Xe ventilation imaging (all r > 0.65; all p < 0.0001). 129Xe VDP was significantly greater than 3D PREFUL derived VDPRVent (mean bias = 10.5%, p < 0.001) and VDPFVL-CM (mean bias = 11.3%, p < 0.0001) but not for VDPCombined (mean bias = 1.7%, p = 0.70). The total regional agreement of 129Xe and 3D PREFUL VD maps ranged between 60% and 63%.

CONCLUSIONS

Free-breathing 3D PREFUL MRI showed a strong correlation with breath-hold hyperpolarized 129Xe MRI regarding the VDP values and modest differences in the detection of VDs on a regional level.

CLINICAL RELEVANCE STATEMENT

3D PREFUL MRI correlated with 129Xe MRI, unveiling regional differences in COPD defect identification. This proposes 3D PREFUL MRI as a ventilation mapping surrogate, eliminating the need for extra hardware or inhaled gases.

KEY POINTS

Current non-invasive evaluation techniques for lung diseases have drawbacks; 129Xe MRI is limited by cost and availability. 3D PREFUL MRI correlated with 129Xe MRI, with regional differences in identifying COPD defects. 3D PREFUL MRI can provide ventilation mapping without the need for additional hardware or inhaled gases.

Establishing a 4D-CT lung function related volumetric dose model to reduce radiation pneumonia

In order to study how to use pulmonary functional imaging obtained through 4D-CT fusion for radiotherapy planning, and transform traditional dose volume parameters into functional dose volume parameters, a functional dose volume parameter model that may reduce level 2 and above radiation pneumonia was obtained. 41 pulmonary tumor patients who underwent 4D-CT in our department from 2020 to 2023 were included. MIM Software (MIM 7.0.7; MIM Software Inc., Cleveland, OH, USA) was used to register adjacent phase CT images in the 4D-CT series. The three-dimensional displacement vector of CT pixels was obtained when changing from one respiratory state to another respiratory state, and this three-dimensional vector was quantitatively analyzed. Thus, a color schematic diagram reflecting the degree of changes in lung CT pixels during the breathing process, namely the distribution of ventilation function strength, is obtained. Finally, this diagram is fused with the localization CT image. Select areas with Jacobi > 1.2 as high lung function areas and outline them as fLung. Import the patient's DVH image again, fuse the lung ventilation image with the localization CT image, and obtain the volume of fLung different doses (V60, V55, V50, V45, V40, V35, V30, V25, V20, V15, V10, V5). Analyze the functional dose volume parameters related to the risk of level 2 and above radiation pneumonia using R language and create a predictive model. By using stepwise regression and optimal subset method to screen for independent variables V35, V30, V25, V20, V15, and V10, the prediction formula was obtained as follows: Risk = 0.23656-0.13784 * V35 + 0.37445 * V30-0.38317 * V25 + 0.21341 * V20-0.10209 * V15 + 0.03815 * V10. These six independent variables were analyzed using a column chart, and a calibration curve was drawn using the calibrate function. It was found that the Bias corrected line and the Apparent line were very close to the Ideal line, The consistency between the predicted value and the actual value is very good. By using the ROC function to plot the ROC curve and calculating the area under the curve: 0.8475, 95% CI 0.7237-0.9713, it can also be determined that the accuracy of the model is very high. In addition, we also used Lasso method and random forest method to filter out independent variables with different results, but the calibration curve drawn by the calibration function confirmed poor prediction performance. The function dose volume parameters V35, V30, V25, V20, V15, and V10 obtained through 4D-CT are key factors affecting radiation pneumonia. Establishing a predictive model can provide more accurate lung restriction basis for clinical radiotherapy planning.

Is individual perfusion dose-response different than ventilation dose-response for lung cancer patients treated with radiotherapy?

OBJECTIVE

Current ventilation and perfusion dose-response studies focus on single-modalities (ventilation or perfusion) and perform pulmonary-toxicity assessment related to radiotherapy on a population-based basis. This study aims at quantitative and clinical evaluation of intrapatient differences between ventilation and perfusion dose-responses among lung cancer patients treated with radiotherapy.

METHODS

20 patients enrolled on a prospective functional avoidance protocol underwent single photon emission computed tomography-CT ventilation and perfusion scans pre- and post-radiotherapy. Relative changes in pre- to post-treatment ventilation and perfusion in lung regions receiving ≥20 Gy were calculated. In addition, the slopes of the linear fit to the relative ventilation and perfusion changes in regions receiving 0-60 Gy were calculated. A radiologist read and assigned a functional defect score to pre- and post-treatment ventilation/perfusion scans.

RESULTS

25% of patients had a difference >35% between ventilation and perfusion pre- to post-treatment changes and 20-30% of patients had opposite directions for ventilation and perfusion pre- to post-treatment changes. Using a semi-quantitative scale, radiologist assessment showed that 20% of patients had different pre- to post-treatment ventilation changes when compared to pre- to post-treatment perfusion changes.

CONCLUSION

Our data showed that ventilation dose-response can differ from perfusion dose-response for 20-30% of patients. Therefore, when performing thoracic dose-response in cancer patients, it is insufficient to look at ventilation or perfusion alone; but rather both modes of functional imaging may be needed when predicting for clinical outcomes.

ADVANCES IN KNOWLEDGE

The significance of this study can be highlighted by the differences between the intrapatient dose-response assessments of this analysis compared to existing population-based dose-response analyses. Elucidating intrapatient ventilation and perfusion dose-response differences may be valuable in predicting pulmonary toxicity in lung cancer patients post-radiotherapy.

Quantitative Imaging Metrics for the Assessment of Pulmonary Pathophysiology: An Official American Thoracic Society and Fleischner Society Joint Workshop Report

Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental "good practice" stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.

Large-scale investigation of deep learning approaches for ventilated lung segmentation using multi-nuclear hyperpolarized gas MRI

Respiratory diseases are leading causes of mortality and morbidity worldwide. Pulmonary imaging is an essential component of the diagnosis, treatment planning, monitoring, and treatment assessment of respiratory diseases. Insights into numerous pulmonary pathologies can be gleaned from functional lung MRI techniques. These include hyperpolarized gas ventilation MRI, which enables visualization and quantification of regional lung ventilation with high spatial resolution. Segmentation of the ventilated lung is required to calculate clinically relevant biomarkers. Recent research in deep learning (DL) has shown promising results for numerous segmentation problems. Here, we evaluate several 3D convolutional neural networks to segment ventilated lung regions on hyperpolarized gas MRI scans. The dataset consists of 759 helium-3 (³He) or xenon-129 (¹²⁹Xe) volumetric scans and corresponding expert segmentations from 341 healthy subjects and patients with a wide range of pathologies. We evaluated segmentation performance for several DL experimental methods via overlap, distance and error metrics and compared them to conventional segmentation methods, namely, spatial fuzzy c-means (SFCM) and K-means clustering. We observed that training on combined ³He and ¹²⁹Xe MRI scans using a 3D nn-UNet outperformed other DL methods, achieving a mean ± SD Dice coefficient of 0.963 ± 0.018, average boundary Hausdorff distance of 1.505 ± 0.969 mm, Hausdorff 95th percentile of 5.754 ± 6.621 mm and relative error of 0.075 ± 0.039. Moreover, limited differences in performance were observed between ¹²⁹Xe and ³He scans in the testing set. Combined training on ¹²⁹Xe and ³He yielded statistically significant improvements over the conventional methods (p < 0.0001). In addition, we observed very strong correlation and agreement between DL and expert segmentations, with Pearson correlation of 0.99 (p < 0.0001) and Bland-Altman bias of - 0.8%. The DL approach evaluated provides accurate, robust and rapid segmentations of ventilated lung regions and successfully excludes non-lung regions such as the airways and artefacts. This approach is expected to eliminate the need for, or significantly reduce, subsequent time-consuming manual editing.

A deep learning method for translating 3D-CT to SPECT ventilation imaging: First comparison with 81m Kr-gas SPECT ventilation imaging

PURPOSE

This study aimed to evaluate the accuracy of deep learning (DL)-based computed tomography (CT) ventilation imaging (CTVI).

METHODS

A total of 71 cases who underwent single-photon emission CT ^81m Kr-gas ventilation (SPECT V) and CT imaging were included. Sixty cases were assigned to the training and validation sets and the remaining 11 cases were assigned to the test set. To directly transform 3DCT (free-breathing CT) images to SPECT V images, a DL-based model was implemented based on the U-Net architecture. The input and output data were 3DCT- and SPECT V-masked, respectively, except for whole-lung volumes. These data were rearranged in voxel size, registered rigidly, cropped, and normalized in pre-processing. In addition to a standard estimation method (i.e., without dropout during the estimation process), a Monte-Carlo Dropout (MCD) method (i.e., with dropout during the estimation process) was used to calculate prediction uncertainty. To evaluate the two models' (CTVI_{MCD U-Net} , CTVI_U-Net ) performance, we used five-fold cross-validation for the training and validation sets. To test the final model performances for both approaches, we applied the test set to each trained model and averaged the test prediction results from the five trained models to acquire the mean test result (bagging) for each approach. For the MCD method, the models were predicted repeatedly (sample size = 200), and the average and standard deviation maps were calculated in each voxel from the predicted results: the average maps were defined as test prediction results in each fold. As an evaluation index, the voxel-wise Spearman rank correlation coefficient (Spearman r_s ) and dice similarity coefficient (DSC) were calculated. The DSC was calculated for three functional regions (high, moderate, and low) separated by an almost equal volume. The coefficient of variation was defined as prediction uncertainty, and these average values were calculated within three functional regions. The Wilcoxon signed-rank test was used to test for a significant difference between the two DL-based approaches RESULTS: The average indexes with one standard deviation (1SD) between CTVI_{MCD U-Net} and SPECT V were 0.76 ± 0.06, 0.69 ± 0.07, 0.51 ± 0.06, and 0.75 ± 0.04 for Spearman r_s , DSC_high , DSC_moderate , and DSC_low , respectively. The average indexes with 1SD between CTVI_U-Net and SPECT V were 0.72 ± 0.05, 0.66 ± 0.04, 0.48 ± 0.04, and 0.74 ± 0.06 for Spearman r_s , DSC_high , DSC_moderate , and DSC_low , respectively. These indexes between CTVI_{MCD U-Net} and CTVI_U-Net showed no significance difference (Spearman r_s , p = 0.175; DSC_high , p = 0.123; DSC_moderate , p = 0.278; DSC_low , p = 0.520). The average coefficient of variations with 1SD were 0.27 ± 0.00, 0.27 ± 0.01, and 0.36 ± 0.03 for the high-, moderate-, and low-functional regions, respectively, and the low-functional region showed a tendency to exhibit larger uncertainties than the others.

CONCLUSION

We evaluated DL-based framework for estimating lung-functional ventilation images only from CT images. The results indicated that the DL-based approach could potentially be used for lung-ventilation estimation. This article is protected by copyright. All rights reserved.

Quantitative assessment of ventilation-perfusion relationships with gallium-68 positron emission tomography/computed tomography imaging in lung cancer patients

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Voxel-wise correlations between gallium-68 (⁶⁸Ga) positron emission tomography/computed tomography (PET/CT)-measured ventilation and perfusion varied widely among 19 patients with lung cancer (range: 0.26–0.88).

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⁶⁸Ga PET/CT-measured percent gas exchanging lung volume was moderately correlated with diffusing capacity of the lung for carbon monoxide (D_LCO) as the reference standard, with the highest correlation coefficient of 0.59 (P < 0.01).

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⁶⁸Ga PET/CT ventilation/perfusion imaging may provide a reasonable surrogate for regional gas exchange.

Pulmonary functional imaging has demonstrated potential to improve thoracic radiotherapy. The purpose of this study was twofold: 1) to quantify ventilation/perfusion relationships in lung cancer patients using a new functional imaging approach, gallium-68 (⁶⁸Ga)-positron emission tomography/computed tomography (PET/CT); and 2) to compare ventilation/perfusion matching with diffusing capacity of the lung for carbon monoxide (D_LCO). Voxel-wise correlations between ventilation and perfusion varied widely among 19 patients (range: 0.26–0.88). ⁶⁸Ga-PET/CT-measured percent gas exchanging lung volume was moderately correlated with D_LCO (≤0.59). Our findings suggested that ⁶⁸Ga-PET/CT ventilation/perfusion imaging provided complementary information and a reasonable surrogate for gas exchange in lung cancer patients.

Prediction of radiation pneumonitis with machine learning using 4D-CT based dose-function features

In this article, we highlight the fundamental importance of the simultaneous use of dose-volume histogram (DVH) and dose-function histogram (DFH) features based on functional images calculated from 4-dimensional computed tomography (4D-CT) and deformable image registration (DIR) in developing a multivariate radiation pneumonitis (RP) prediction model. The patient characteristics, DVH features and DFH features were calculated from functional images by Hounsfield unit (HU) and Jacobian metrics, for an RP grade ≥ 2 multivariate prediction models were computed from 85 non-small cell lung cancer patients. The prediction model is developed using machine learning via a kernel-based support vector machine (SVM) machine. In the patient cohort, 21 of the 85 patients (24.7%) presented with RP grade ≥ 2. The median area under curve (AUC) was 0.58 for the generated 50 prediction models with patient clinical features and DVH features. When HU metric and Jacobian metric DFH features were added, the AUC improved to 0.73 and 0.68, respectively. We conclude that predictive RP models that incorporate DFH features were successfully developed via kernel-based SVM. These results demonstrate that effectiveness of the simultaneous use of DVH features and DFH features calculated from 4D-CT and DIR on functional image-guided radiotherapy.

Synthetic pulmonary perfusion images from 4DCT for functional avoidance using deep learning

Purpose.To develop and evaluate the performance of a deep learning model to generate synthetic pulmonary perfusion images from clinical 4DCT images for patients undergoing radiotherapy for lung cancer.Methods. A clinical data set of 58 pre- and post-radiotherapy^99mTc-labeled MAA-SPECT perfusion studies (32 patients) each with contemporaneous 4DCT studies was collected. Using the inhale and exhale phases of the 4DCT, a 3D-residual network was trained to create synthetic perfusion images utilizing the MAA-SPECT as ground truth. The training process was repeated for a 50-imaging study, five-fold validation with twenty model instances trained per fold. The highest performing model instance from each fold was selected for inference upon the eight-study test set. A manual lung segmentation was used to compute correlation metrics constrained to the voxels within the lungs. From the pre-treatment test cases (N = 5), 50th percentile contours of well-perfused lung were generated from both the clinical and synthetic perfusion images and the agreement was quantified.Results. Across the hold-out test set, our deep learning model predicted perfusion with a Spearman correlation coefficient of 0.70 (IQR: 0.61-0.76) and a Pearson correlation coefficient of 0.66 (IQR: 0.49-0.73). The agreement of the functional avoidance contour pairs was Dice of 0.803 (IQR: 0.750-0.810) and average surface distance of 5.92 mm (IQR: 5.68-7.55).Conclusion. We demonstrate that from 4DCT alone, a deep learning model can generate synthetic perfusion images with potential application in functional avoidance treatment planning.

Characterizing spatial differences between SPECT-ventilation and SPECT-perfusion in patients with lung cancer undergoing radiotherapy

This study investigates agreement between ventilation and perfusion for lung cancer patients undergoing radiotherapy. Ventilation-perfusion scans of nineteen patients with stage III lung cancer from a prospective protocol were compared using voxel-wise Spearman correlation-coefficients. The presented results show in about 25% of patients, ventilation and perfusion exhibit lower agreement.

Combined Assessment of Pulmonary Ventilation and Perfusion with Single-Energy Computed Tomography and Image Processing

RATIONALE AND OBJECTIVES

To establish a proof-of-principle for combined assessment of pulmonary ventilation and perfusion using single-energy computed tomography (CT) and image processing/analysis (denoted as single-energy CT ventilation/perfusion imaging).

MATERIALS AND METHODS

Breath-hold CT scans were acquired at end-expiration and end-inspiration before injection of iodinated contrast agents, and repeated at end-inspiration after contrast injection for 17 canines (8 normal and 9 diseased lung subjects). Ventilation images were calculated with deformable image registration to map the end-expiratory and end-inspiratory CT images and quantitative analysis for regional volume changes as surrogates for ventilation. Perfusion images were calculated by subtracting the end-inspiratory precontrast CT from the deformably registered end-inspiratory postcontrast CT, yielding a map of regional Hounsfield unit enhancement as a surrogate for perfusion. Ventilation-perfusion matching, spatial heterogeneity, and gravitationally directed gradients were compared between two groups using a Wilcoxon rank-sum test.

RESULTS

The normal group had significantly higher Dice similarity coefficients for spatial overlap of segmented functional volumes between ventilation and perfusion (median 0.40 vs. 0.33, p = 0.05), suggesting stronger ventilation-perfusion matching. The normal group also had greater Spearman's correlation coefficients based on 16 regions of interest (median 0.58 vs. 0.40, p = 0.09). The coefficients of variation were comparable (median, ventilation 0.71 vs. 0.91, p = 0.60; perfusion 0.63 vs. 0.75, p = 0.27). The linear regression slopes of gravitationally directed gradient were also comparable for ventilation (median, ventilation -0.26 vs. -0.18, p = 0.19; perfusion -0.17 vs. -0.06, p = 0.11).

CONCLUSION

These findings provide proof-of-principle for single-energy CT ventilation/perfusion imaging.

Chronic lung diseases: prospects for regeneration and repair

COPD and idiopathic pulmonary fibrosis (IPF) together represent a considerable unmet medical need, and advances in their treatment lag well behind those of other chronic conditions. Both diseases involve maladaptive repair mechanisms leading to progressive and irreversible damage. However, our understanding of the complex underlying disease mechanisms is incomplete; with current diagnostic approaches, COPD and IPF are often discovered at an advanced stage and existing definitions of COPD and IPF can be misleading. To halt or reverse disease progression and achieve lung regeneration, there is a need for earlier identification and treatment of these diseases. A precision medicine approach to treatment is also important, involving the recognition of disease subtypes, or endotypes, according to underlying disease mechanisms, rather than the current “one-size-fits-all” approach. This review is based on discussions at a meeting involving 38 leading global experts in chronic lung disease mechanisms, and describes advances in the understanding of the pathology and molecular mechanisms of COPD and IPF to identify potential targets for reversing disease degeneration and promoting tissue repair and lung regeneration. We also discuss limitations of existing disease measures, technical advances in understanding disease pathology, and novel methods for targeted drug delivery.

Treatment outcomes with COPD and IPF are suboptimal. Better understanding of the diseases, such as targetable repair mechanisms, may generate novel therapies, and earlier diagnosis and treatment is needed to stop or even reverse disease progression.https://bit.ly/2Ga8J1g

Ventilation/Perfusion Relationships and Gas Exchange: Measurement Approaches

Ventilation-perfusion ( V ˙ A / Q ˙ ) matching, the regional matching of the flow of fresh gas to flow of deoxygenated capillary blood, is the most important mechanism affecting the efficiency of pulmonary gas exchange. This article discusses the measurement of V ˙ A / Q ˙ matching with three broad classes of techniques: (i) those based in gas exchange, such as the multiple inert gas elimination technique (MIGET); (ii) those derived from imaging techniques such as single-photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance imaging (MRI), computed tomography (CT), and electrical impedance tomography (EIT); and (iii) fluorescent and radiolabeled microspheres. The focus is on the physiological basis of these techniques that provide quantitative information for research purposes rather than qualitative measurements that are used clinically. The fundamental equations of pulmonary gas exchange are first reviewed to lay the foundation for the gas exchange techniques and some of the imaging applications. The physiological considerations for each of the techniques along with advantages and disadvantages are briefly discussed. © 2020 American Physiological Society. Compr Physiol 10:1155-1205, 2020.

V/Q SPECT for the Assessment of Regional Lung Function: Generation of Normal Mean and Standard Deviation 3-D Maps

Background: V/Q SPECT/CT is attractive for regional lung function assessment, but accurate delineation and quantification of functional lung volumes remains a challenge. Physiological intra and inter patient non-uniformity of V/Q SPECT images make conventional delineation methods of functional lung volumes inaccurate. In that context it would be of interest to build statistical maps of normal V/Q SPECT to assess the physiological variability of radiotracers. The aim of this study was to generate normal mean and standard deviation maps of regional lung function as assessed with V/Q SPECT/CT, with (AC) and without (NoAC) attenuation correction. Methods: During a 13 month period, 73 consecutive patients referred for suspected acute pulmonary embolism, that had normal V/Q SPECT/CT based on the interpretation of 2 independent nuclear medicine physicians, were selected. Four set of images were reconstructed: perfusion and ventilation images, AC, and NoAC, respectively. Statistical maps were created as follows: all cases were registered to a reference scan using the CT data, first with a rigid then with a non-rigid method. SPECTs reconstructions were then co-registered and normalized, and mean and standard deviation voxel-wise maps were calculated. To assess the consistency of generated maps to lung physiology and the potential impact of non-rigid registration, visual analysis and quantitative comparison with non-registered data were performed in the whole series. Quantitative comparison was also conducted in two randomly sampled independent subsets. Results: Perfusion mean maps showed a continuous negative posterior to anterior gradient, majored on the AC mean map. Perfusion standard deviation maps showed higher variability in the periphery of the lungs, but especially in the posterior areas. The ventilation mean map showed a slightly positive posterior to anterior gradient on NoAC mean ventilation map, while the AC mean map showed no gradient. The NoAC ventilation SD map showed a higher variability in the periphery of the lungs as compared with AC SD map. No statistical difference in the posterior to anterior gradient measurements was found between the generated mean statistical maps and the non-registered data, either in the whole series or across the two independent datasets. Conclusion: We proposed a methodology to create statistical normal maps for V/Q SPECTs. Maps were consistent with the known physiological non-uniformity and showed the impact of attenuation correction on the posterior to anterior gradient. These maps could be used for a Z-score analysis, and a better segmentation of healthy uptake areas.

Variations Between Dose-Ventilation and Dose-Perfusion Metrics in Radiation Therapy Planning for Lung Cancer

Purpose

Currently, several active clinical trials of functional lung avoidance radiation therapy using different imaging modalities for ventilation or perfusion are underway. Patients with lung cancer often show ventilation-perfusion mismatch, whereas the significance of dose-function metric remains unclear. The aim of the present study was to compare dose-ventilation metrics with dose-perfusion metrics for radiation therapy plan evaluation.

Methods and Materials

Pretreatment 4-dimensional computed tomography and ^99mTc-macroaggregated albumin single-photon emission computed tomography perfusion images of 60 patients with lung cancer treated with radiation therapy were analyzed. Ventilation images were created using the deformable image registration of 4-dimensional computed tomography image sets and image analysis for regional volume changes as a surrogate for ventilation. Ventilation and perfusion images were converted into percentile distribution images. Analyses included Pearson’s correlation coefficient and comparison of agreements between the following dose-ventilation and dose-perfusion metrics: functional mean lung dose and functional percent lung function receiving 5, 10, 20, 30, and 40 Gy (fV₅, fV₁₀, fV₂₀, fV₃₀, and fV₄₀, respectively).

Results

Overall, the dose-ventilation metrics were greater than the dose-perfusion metrics (ie, fV₂₀, 26.3% ± 9.9% vs 23.9% ± 9.8%). Correlations between the dose-ventilation and dose-perfusion metrics were strong (range, r = 0.94-0.97), whereas the agreements widely varied among patients, with differences as large as 6.6 Gy for functional mean lung dose and 11.1% for fV₂₀. Paired t test indicated that the dose-ventilation and dose-perfusion metrics were significantly different.

Conclusions

Strong correlations were present between the dose-ventilation and dose-perfusion metrics. However, the agreement between the dose-ventilation and dose-perfusion metrics widely varied among patients, suggesting that ventilation-based radiation therapy plan evaluation may not be comparable to that based on perfusion. Future studies should elucidate the correlation of dose-function metrics with clinical pulmonary toxicity metrics.

A deep learning method for producing ventilation images from 4DCT: First comparison with technegas SPECT ventilation

PURPOSE

The purpose of this study is to develop a deep learning (DL) method for producing four-dimensional computed tomography (4DCT) ventilation imaging and to evaluate the accuracy of the DL-based ventilation imaging against single-photon emission-computed tomography (SPECT) ventilation imaging (SPECT-VI). The performance of the DL-based method is assessed by comparing with density change- and Jacobian-based (HU and JAC) methods.

MATERIALS AND METHODS

Fifty patients with esophagus or lung cancer who underwent thoracic radiotherapy were enrolled in this study. For each patient, 4DCT scans paired with 99mTc-Technegas SPECT/CT were acquired before the first radiotherapy treatment. 4DCT and SPECT/CT were first rigidly registered using MIMvista and converted to data matrix using MATLAB, and then transferred to a DL model based on U-net for correlating 4DCT features and SPECT-VI. Two forms of 4DCT dataset [(a) ten phases and (b) two phases of peak-exhalation and peak-inhalation] as input are studied. Tenfold cross-validation procedure was used to evaluate the performance of the DL model. For comparative evaluation, HU and JAC methodologies are used to calculate specific ventilation imaging based on 4DCT (CTVI) for each patient. The voxel-wise Spearman's correlation was evaluated over the whole lung between each of CTVI and corresponding SPECT-VI. The SPECT-VI and produced CTVIs were segmented into high, median, and low functional lung (HFL, MFL, and LFL) regions. The spatial overlap of corresponding HFL, MFL, and LFL for each CTVI against SPECT-VI was also evaluated using the dice similarity coefficient (DSC). The averaged DSC of functional lung regions was calculated and statistically analyzed with a one-factor ANONA model among different methods.

RESULTS

The voxel-wise Spearman r_s values were (0.22 ± 0.31), (-0.09 ± 0.18), and (0.73 ± 0.16)/(0.71 ± 0.17) for the CTVI_HU , CTVI_JAC , and CTVI_DL(1) /CTVI_DL(2) . These results showed the DL method yielded the strongest correlation with SPECT-VI. Using the DSC as the spatial overlap metric, we found that the CTVI_HU , CTVI_JAC , and CTVI_DL(1) /CTVI_DL(2) methods achieved averaged DSC values for all patients to be (0.45 ± 0.08), (0.33 ± 0.04), and (0.73 ± 0.09)/(0.71 ± 0.09), respectively. The results demonstrated that the DL method yielded the highest similarity with SPECT-VI with the prominently significant difference (P < 10^-7 ).

CONCLUSIONS

This study developed a DL method for producing CTVI and performed a validation against SPECT-VI. The results demonstrated that DL method can derive CTVI with greatly improved accuracy in comparison to HU and JAC methods. The produced ventilation images can be more accurate and useful for lung functional avoidance radiotherapy and treatment response modeling.

Interstitial Lung Disease in Systemic Sclerosis: Focus on Early Detection and Intervention

Systemic sclerosis (SSc) is a progressive and often devastating disease characterized by autoimmune dysfunction, vasculopathy, and fibrosis. Interstitial lung disease (ILD) is identified in the majority of patients with SSc and is the leading cause of SSc-related mortality. Although clinical manifestations and ILD severity vary among patients, lung function typically declines to the greatest extent during the first 3-4 years after disease onset. We aim to provide an overview of SSc-associated ILD (SSc-ILD) with a focus on current and emerging tools for early diagnosis of ILD and current and novel treatments under investigation. Early detection of ILD provides the opportunity for early therapeutic intervention, which could improve patient outcomes. Thoracic high-resolution computed tomography is the most effective method of identifying ILD in patients with SSc; it enables detection of mild lung abnormalities and plays an important role in monitoring disease progression. Cyclophosphamide and mycophenolate mofetil are the most commonly prescribed treatments for SSc-ILD. Recently, nintedanib (an antifibrotic) was approved by the Food and Drug Administration for patients with SSc-ILD; it is indicated for slowing the rate of decline in pulmonary function. However, there is a need for additional effective and well-tolerated disease-modifying therapy. Ongoing studies are evaluating other antifibrotics and novel agents. We envision that early detection of lung involvement, combined with the emergence and integration of novel therapies, will lead to improved outcomes in patients with SSc-ILD.

CT-based Airway Flow Model to Assess Ventilation in Chronic Obstructive Pulmonary Disease: A Pilot Study

Background The lack of functional information in thoracic CT remains a limitation of its use in the clinical management of chronic obstructive pulmonary disease (COPD). Purpose To compare the distribution of pulmonary ventilation assessed by a CT-based full-scale airway network (FAN) flow model with hyperpolarized xenon 129 (¹²⁹Xe) MRI (hereafter, ¹²⁹Xe MRI) and technetium 99m-diethylenetriaminepentaacetic acid aerosol SPECT ventilation imaging (hereafter, V-SPECT) in participants with COPD. Materials and Methods In this prospective study performed between May and August 2017, pulmonary ventilation in participants with COPD was computed by using the FAN flow model. The modeled pulmonary ventilation was compared with functional imaging data from breath-hold time-series ¹²⁹Xe MRI and V-SPECT. FAN-derived ventilation images on the coronal plane and volumes of interest were compared with functional lung images. Percentage lobar ventilation estimated by the FAN model was compared with that measured at ¹²⁹Xe MRI and V-SPECT. The statistical significance of ventilation distribution between FAN and functional images was demonstrated with the Spearman correlation coefficient and χ² distance. Results For this study, nine participants (seven men [mean age, 65 years ± 5 {standard deviation}] and two women [mean age, 63 years ± 7]) with COPD that was Global Initiative for Chronic Obstructive Lung Disease stage II-IV were enrolled. FAN-modeled ventilation profile showed strong positive correlation with images from ¹²⁹Xe MRI (ρ = 0.67; P < .001) and V-SPECT (ρ = 0.65; P < .001). The χ² distances of the ventilation histograms in the volumes of interest between the FAN and ¹²⁹Xe MRI and FAN and V-SPECT were 0.16 ± 0.08 and 0.28 ± 0.14, respectively. The ratios of lobar ventilations in the models were linearly correlated to images from ¹²⁹Xe MRI (ρ = 0.67; P < .001) and V-SPECT (ρ = 0.59; P < .001). Conclusion A CT-based full-scale airway network flow model provided regional pulmonary ventilation information for chronic obstructive pulmonary disease and correlates with hyperpolarized xenon 129 MRI and technetium 99m-diethylenetriaminepentaacetic acid aerosol SPECT ventilation imaging. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Schiebler and Parraga in this issue.

Time-series hyperpolarized xenon-129 MRI of lobar lung ventilation of COPD in comparison to V/Q-SPECT/CT and CT

Purpose

To derive lobar ventilation in patients with chronic obstructive pulmonary disease (COPD) using a rapid time-series hyperpolarized xenon-129 (HPX) magnetic resonance imaging (MRI) technique and compare this to ventilation/perfusion single-photon emission computed tomography (V/Q-SPECT), correlating the results with high-resolution computed tomography (CT) and pulmonary function tests (PFTs).

Materials and methods

Twelve COPD subjects (GOLD stages I–IV) participated in this study and underwent HPX-MRI, V/Q-SPECT/CT, high-resolution CT, and PFTs. HPX-MRI was performed using a novel time-series spiral k-space sampling approach. Relative percentage ventilations were calculated for individual lobe for comparison to the relative SPECT lobar ventilation and perfusion. The absolute HPX-MRI percentage ventilation in each lobe was compared to the absolute CT percentage emphysema score calculated using a signal threshold method. Pearson’s correlation and linear regression tests were performed to compare each imaging modality.

Results

Strong correlations were found between the relative lobar percentage ventilation with HPX-MRI and percentage ventilation SPECT (r = 0.644; p < 0.001) and percentage perfusion SPECT (r = 0.767; p < 0.001). The absolute CT percentage emphysema and HPX percentage ventilation correlation was also statistically significant (r = 0.695, p < 0.001). The whole lung HPX percentage ventilation correlated with the PFT measurements (FEV₁ with r = − 0.886, p < 0.001*, and FEV₁/FVC with r = − 0.861, p < 0.001*) better than the whole lung CT percentage emphysema score (FEV₁ with r = − 0.635, p = 0.027; and FEV₁/FVC with r = − 0.652, p = 0.021).

Conclusion

Lobar ventilation with HPX-MRI showed a strong correlation with lobar ventilation and perfusion measurements derived from SPECT/CT, and is better than the emphysema score obtained with high-resolution CT.

Key Points

• The ventilation hyperpolarized xenon-129 MRI correlates well with ventilation and perfusion with SPECT/CT with the advantage of higher temporal and spatial resolution.

• The hyperpolarized xenon-129 MRI correlates with the PFT measurements better than the high-resolution CT with the advantage of avoiding the use of ionizing radiation.

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5888-y) contains supplementary material, which is available to authorized users.

Assessment of pulmonary structure-function relationships in young children and adolescents with cystic fibrosis by multivolume proton-MRI and CT

BACKGROUND

Lung disease is the most frequent cause of morbidity and mortality in patients with cystic fibrosis (CF), and there is a shortage of sensitive biomarkers able to regionally monitor disease progression and to assess early responses to therapy.

PURPOSE

To determine the feasibility of noncontrast-enhanced multivolume MRI, which assesses intensity changes between expiratory and inspiratory breath-hold images, to detect and quantify regional ventilation abnormalities in CF lung disease, with a focus on the structure-function relationship.

STUDY TYPE

Retrospective.

POPULATION

Twenty-nine subjects, including healthy young children (n = 9, 7-37 months), healthy adolescents (n = 4, 14-22 years), young children with CF lung disease (n = 10, 7-47 months), and adolescents with CF lung disease (n = 6, 8-18 years) were studied.

FIELD STRENGTH/SEQUENCE

3D spoiled gradient-recalled sequence at 1.5T.

ASSESSMENT

Subjects were scanned during breath-hold at functional residual capacity (FRC) and total lung capacity (TLC) through noncontrast-enhanced MRI and CT. Expiratory-inspiratory differences in MR signal-intensity (Δ1 H-MRI) and CT-density (ΔHU) were computed to estimate regional ventilation. MR and CT images were also evaluated using a CF-specific scoring system.

STATISTICAL TESTS

Quadratic regression, Spearman's correlation, one-way analysis of variance (ANOVA).

RESULTS

Δ1 H-MRI maps were sensitive to ventilation heterogeneity related to gravity dependence in healthy lung and to ventilation impairment in CF lung disease. A high correlation was found between MRI and CT ventilation maps (R2  = 0.79, P < 0.001). Globally, Δ1 H-MRI and ΔHU decrease with increasing morphological score (respectively, R2  = 0.56, P < 0.001 and R2  = 0.31, P < 0.001). Locally, Δ1 H-MRI was higher in healthy regions (median 15%) compared to regions with bronchiectasis, air trapping, consolidation, and to segments fed by airways with bronchial wall thickening (P < 0.001).

DATA CONCLUSION

Multivolume noncontrast-enhanced MRI, as a nonionizing imaging modality that can be used on nearly any MRI scanner without specialized equipment or gaseous tracers, may be particularly valuable in CF care, providing a new imaging biomarker to detect early alterations in regional lung structure-function.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2018;48:531-542.

Estimating regions of air trapping from electrical impedance tomography data

OBJECTIVE

Electrical impedance tomography (EIT) has been shown to be a viable non-invasive, bedside imaging modality to monitor lung function. This paper introduces a method for identifying regions of air trapping from EIT data collected during tidal breathing and breath-holding maneuvers.

APPROACH

Ventilation-perfusion index maps are computed from dynamic EIT images. These maps are then used to identify regions of air trapping in the area of the lung as regions that are poorly ventilated but well perfused throughout the breathing and cardiac cycles. These EIT-identified regions are then compared with independently identified regions of low attenuation, or air trapping, on chest CT. Results of this method are demonstrated in two children with cystic fibrosis and on a healthy control subject.

MAIN RESULTS

In both CF children, the EIT-identified regions of air trapping matched the regions indicated from the chest CT. The EIT-based method is only validated with CT scans within 4 cm of the chest cross-section defined by the electrode plane.

SIGNIFICANCE

The results indicate the potential use of EIT-derived ventilation-perfusion index maps as a non-invasive method for identifying regions of air trapping.

Design and development of a nonrigid phantom for the quantitative evaluation of DIR-based mapping of simulated pulmonary ventilation

PURPOSE

The validation of deformable image registration (DIR)-based pulmonary ventilation mapping is time consuming and prone to inaccuracies and is also affected by deformation parameters. In this study, we developed a nonrigid phantom as a quality assurance (QA) tool that simulates ventilation to evaluate DIR-based images quantitatively.

METHODS

The phantom consists of an acrylic cylinder filled with polyurethane foam designed to simulate pulmonic alveoli. A polyurethane membrane is attached to the inferior end of the phantom to simulate the diaphragm. In addition, tracheobronchial-tree-shaped polyurethane tubes are inserted through the foam and converge outside the phantom to simulate the trachea. Solid polyurethane is also used to model arteries, which closely follow the model airways. Two three-dimensional (3D) CT scans were performed during exhalation and inhalation phases using xenon (Xe) gas as the inhaled contrast agent. The exhalation 3D-CT image is deformed to an inhalation 3D-CT image using our in-house program based on the NiftyReg open-source package. The target registration error (TRE) between the two images was calculated for 16 landmarks located in the simulated lung volume. The DIR-based ventilation image was generated using Jacobian determinant (JD) metrics. Subsequently, differences in the Hounsfield unit (HU) values between the two images were measured. The correlation coefficient between the JD and HU differences was calculated. In addition, three 4D-CT scans are performed to evaluate the reproducibility of the phantom motion and Xe gas distribution.

RESULTS

The phantom exhibited a variety of displacements for each landmark (range: 1-20 mm). The reproducibility analysis indicated that the location differences were <1 mm for all landmarks, and the HU variation in the Xe gas distribution was close to zero. The mean TRE in the evaluation of spatial accuracy according to the DIR software was 1.47 ± 0.71 mm (maximum: 2.6 mm). The relationship between the JD and HU differences had a large correlation (R = -0.71) for the DIR software.

CONCLUSION

The phantom implemented new features, namely, deformation and simulated ventilation. To assess the accuracy of the DIR-based mapping of the simulated pulmonary ventilation, the phantom allows for simulation of Xe gas wash-in and wash-out. The phantom may be an effective QA tool, because the DIR algorithm can be quickly changed and its accuracy evaluated with a high degree of precision.

Pulmonary Delivery of Therapeutic and Diagnostic Gases

The 21st Congress for the International Society for Aerosols in Medicine included, for the first time, a session on Pulmonary Delivery of Therapeutic and Diagnostic Gases. The rationale for such a session within ISAM is that the pulmonary delivery of gaseous drugs in many cases targets the same therapeutic areas as aerosol drug delivery, and is in many scientific and technical aspects similar to aerosol drug delivery. This article serves as a report on the recent ISAM congress session providing a synopsis of each of the presentations. The topics covered are the conception, testing, and development of the use of nitric oxide to treat pulmonary hypertension; the use of realistic adult nasal replicas to evaluate the performance of pulsed oxygen delivery devices; an overview of several diagnostic gas modalities; and the use of inhaled oxygen as a proton magnetic resonance imaging (MRI) contrast agent for imaging temporal changes in the distribution of specific ventilation during recovery from bronchoconstriction. Themes common to these diverse applications of inhaled gases in medicine are discussed, along with future perspectives on development of therapeutic and diagnostic gases.

Technical Note: Correction for the effect of breathing variations in CT pulmonary ventilation imaging

PURPOSE

The accuracy and precision of computed tomography (CT) pulmonary ventilation imaging with conventional CT scanners are limited by breathing variations. We propose a method to correct for the effect of breathing variations in CT ventilation imaging based on external respiratory signals acquired throughout a scan.

METHODS

The proposed method is based on: (a) calculating voxel-by-voxel abdominal surface motion ranges using four-dimensional (4D) CT image datasets spatiotemporally correlated with external respiratory monitor data, and (b) applying the correction factor, which is defined as the ratio of the overall mean of the abdominal surface motion range in the lungs to that of each voxel, to the CT ventilation value. The performance of the proposed method was investigated by comparing voxel-wise correlations of the uncorrected and corrected CT ventilation images with single-photon emission CT (SPECT) ventilation images as a ground truth for nine patients. CT ventilation images were calculated by deformable image registration of the 4D-CT image datasets, followed by calculation of regional volume changes. A Steiger's Z-test was used to determine the statistical significance of the difference between the correlations for the uncorrected and corrected CT ventilation images.

RESULTS

The proposed correction method resulted in significant increases (P < 0.05) in the correlation between CT and SPECT ventilation in three patients, trends toward significant increase (P: 0.13-0.18) in two patients, no significant differences in three patients, and a significantly decreased correlation in one patient. The average standard deviation of the abdominal surface motion range in three patients showing significant increases was 0.27 (range 0.10-0.37), which was greater than 0.17 (range 0.07-0.38) in the other six patients.

CONCLUSIONS

The proposed method to correct for the effect of breathing variations could be readily implemented and has the potential to improve the accuracy of CT ventilation imaging as demonstrated in a nine-patient study.

Imaging Radiation-Induced Normal Tissue Injury to Quantify Regional Dose Response

Noninvasive imaging has and will continue to play a pivotal role in the assessment of radiation-induced normal tissue toxicity. In this review, we will examine key literature regarding the use of anatomic and physiological imaging in relation to radiation-induced normal tissue toxicity. Additionally, this review contains a novel methodology for potentially incorporating dose-response data into treatment planning and normal tissue toxicity modeling.

Contrast-enhanced CT- and MRI-based perfusion assessment for pulmonary diseases: basics and clinical applications

Assessment of regional pulmonary perfusion as well as nodule and tumor perfusions in various pulmonary diseases are currently performed by means of nuclear medicine studies requiring radioactive macroaggregates, dual-energy computed tomography (CT), and dynamic first-pass contrast-enhanced perfusion CT techniques and unenhanced and dynamic first-pass contrast enhanced perfusion magnetic resonance imaging (MRI), as well as time-resolved three-dimensional or four-dimensional contrast-enhanced magnetic resonance angiography (MRA). Perfusion scintigraphy, single-photon emission tomography (SPECT) and SPECT fused with CT have been established as clinically available scintigraphic methods; however, they are limited by perfusion information with poor spatial resolution and other shortcomings. Although positron emission tomography with 15O water can measure absolute pulmonary perfusion, it requires a cyclotron for generation of a tracer with an extremely short half-life (2 min), and can only be performed for academic purposes. Therefore, clinicians are concentrating their efforts on the application of CT-based and MRI-based quantitative and qualitative perfusion assessment to various pulmonary diseases. This review article covers 1) the basics of dual-energy CT and dynamic first-pass contrast-enhanced perfusion CT techniques, 2) the basics of time-resolved contrast-enhanced MRA and dynamic first-pass contrast-enhanced perfusion MRI, and 3) clinical applications of contrast-enhanced CT- and MRI-based perfusion assessment for patients with pulmonary nodule, lung cancer, and pulmonary vascular diseases. We believe that these new techniques can be useful in routine clinical practice for not only thoracic oncology patients, but also patients with different pulmonary vascular diseases.

Framework for radiation pneumonitis risk stratification based on anatomic and perfused lung dosimetry

PURPOSE

To design and apply a framework for predicting symptomatic radiation pneumonitis in patients undergoing thoracic radiation, using both pretreatment anatomic and perfused lung dose-volume parameters.

MATERIALS AND METHODS

Radiation treatment planning CT scans were coregistered with pretreatment [99mTc]MAA perfusion SPECT/CT scans of 20 patients who underwent definitive thoracic radiation. Clinical radiation pneumonitis was defined as grade ≥ 2 (CTCAE v4 grading system). Anatomic lung dose-volume parameters were collected from the treatment planning scans. Perfusion dose-volume parameters were calculated from pretreatment SPECT/CT scans. Equivalent doses in 2 Gy per fraction were calculated in the lung to account for differences in treatment regimens and spatial variations in lung dose (EQD2lung).

RESULTS

Anatomic lung dosimetric parameters (MLD) and functional lung dosimetric parameters (pMLD70%) were identified as candidate predictors of grade ≥ 2 radiation pneumonitis (AUC > 0.93, p < 0.01). Pairing of an anatomic and functional dosimetric parameter (e. g., MLD and pMLD70%) may further improve prediction accuracy. Not all individuals with high anatomic lung dose (MLD > 13.6 GyEQD2lung, 19.3 Gy for patients receiving 60 Gy in 30 fractions) developed radiation pneumonitis, but all individuals who also had high mean dose to perfused lung (pMLD70% > 13.3 GyEQD2) developed radiation pneumonitis.

CONCLUSIONS

The preliminary application of this framework revealed differences between anatomic and perfused lung dosimetry in this limited patient cohort. The addition of perfused lung parameters may help risk stratify patients for radiation pneumonitis, especially in treatment plans with high anatomic mean lung dose. Further investigations are warranted.

Quantification of regional deformation of the lungs by non-rigid registration of three-dimensional contrast-enhanced magnetic resonance imaging

BACKGROUND

Assessment of lung function is vital for the diagnosis of a variety of pathological conditions. Research has been proposed to study pulmonary mechanics and kinematics using two-dimensional (2D) magnetic resonance imaging (MRI). This allows estimation of regional lung tissue mechanics but is limited to 2D information. An approach based on three-dimensional (3D) contrast-enhanced MR angiogram of pulmonary blood vessels and a non-rigid image registration technique is proposed for quantification of lung regional deformations, which can potentially be used for assessment of pulmonary parenchymal mechanics and regional ventilation for disease diagnosis without ionizing radiation.

METHODS

On three volunteers, an end-expiration scan and end-inspiration scan was acquired successively for each volunteer using a 3D breath-hold contrast-enhanced MRI sequence several minutes after gadolinium injection. Subsequently, a rectangle box lung mask is manually selected for each end-expiration scan, applying non-rigid registration algorithms using cubic B-splines as transformations to align each pair of images. This incorporates the Normalized Correlation Coefficient similarity with the bending energy term as cost function with a multi-resolution multi-grid approach. Finally, the lung regional 3D deformations were obtained using the transformations obtained by registration. The alignment accuracy after non-rigid registration was estimated by using a set of branch points of pulmonary blood vessels as anatomical landmarks for each pair of images.

RESULTS

With contrast enhancement, the pulmonary blood vessel signal was enhanced, which greatly facilitated the non-rigid registration in the lung parenchyma. The average landmarks distances in three pairs of datasets are reduced from 17.9, 20.3 and 16.3 mm, to 1.0, 1.6 and 1.2 mm, respectively, by non-rigid registration. After registration, the average distances error of each pair of datasets was less than 0.6 mm in the right-to-left (RL) direction, less than 0.9 mm in the inferior-to-superior (IS) direction, and less than 1.2 mm in the anterior-to-posterior (AP) direction.

CONCLUSIONS

Results demonstrated that the proposed method can accurately register lungs with large deformations to evaluate lung regional deformation. It may be used for quantitative assessment of 3D lung regional ventilation avoiding ionizing radiation.

Single-energy computed tomography-based pulmonary perfusion imaging: Proof-of-principle in a canine model

Purpose:

Radiotherapy (RT) that selectively avoids irradiating highly functional lung regions may reduce pulmonary toxicity, which is substantial in lung cancer RT. Single-energy computed tomography (CT) pulmonary perfusion imaging has several advantages (e.g., higher resolution) over other modalities and has great potential for widespread clinical implementation, particularly in RT. The purpose of this study was to establish proof-of-principle for single-energy CT perfusion imaging.

Methods:

Single-energy CT perfusion imaging is based on the following: (1) acquisition of end-inspiratory breath-hold CT scans before and after intravenous injection of iodinated contrast agents, (2) deformable image registration (DIR) for spatial mapping of those two CT image data sets, and (3) subtraction of the precontrast image data set from the postcontrast image data set, yielding a map of regional Hounsfield unit (HU) enhancement, a surrogate for regional perfusion. In a protocol approved by the institutional animal care and use committee, the authors acquired CT scans in the prone position for a total of 14 anesthetized canines (seven canines with normal lungs and seven canines with diseased lungs). The elastix algorithm was used for DIR. The accuracy of DIR was evaluated based on the target registration error (TRE) of 50 anatomic pulmonary landmarks per subject for 10 randomly selected subjects as well as on singularities (i.e., regions where the displacement vector field is not bijective). Prior to perfusion computation, HUs of the precontrast end-inspiratory image were corrected for variation in the lung inflation level between the precontrast and postcontrast end-inspiratory CT scans, using a model built from two additional precontrast CT scans at end-expiration and midinspiration. The authors also assessed spatial heterogeneity and gravitationally directed gradients of regional perfusion for normal lung subjects and diseased lung subjects using a two-sample two-tailed t-test.

Results:

The mean TRE (and standard deviation) was 0.6 ± 0.7 mm (smaller than the voxel dimension) for DIR between pre contrast and postcontrast end-inspiratory CT image data sets. No singularities were observed in the displacement vector fields. The mean HU enhancement (and standard deviation) was 37.3 ± 10.5 HU for normal lung subjects and 30.7 ± 13.5 HU for diseased lung subjects. Spatial heterogeneity of regional perfusion was found to be higher for diseased lung subjects than for normal lung subjects, i.e., a mean coefficient of variation of 2.06 vs 1.59 (p = 0.07). The average gravitationally directed gradient was strong and significant (R² = 0.99, p < 0.01) for normal lung dogs, whereas it was moderate and nonsignificant (R² = 0.61, p = 0.12) for diseased lung dogs.

Conclusions:

This canine study demonstrated the accuracy of DIR with subvoxel TREs on average, higher spatial heterogeneity of regional perfusion for diseased lung subjects than for normal lung subjects, and a strong gravitationally directed gradient for normal lung subjects, providing proof-of-principle for single-energy CT pulmonary perfusion imaging. Further studies such as comparison with other perfusion imaging modalities will be necessary to validate the physiological significance.

Quantification of regional early stage gas exchange changes using hyperpolarized (129)Xe MRI in a rat model of radiation-induced lung injury

PURPOSE

To assess the feasibility of hyperpolarized (HP) (129)Xe MRI for detection of early stage radiation-induced lung injury (RILI) in a rat model involving unilateral irradiation by assessing differences in gas exchange dynamics between irradiated and unirradiated lungs.

METHODS

The dynamics of gas exchange between alveolar air space and pulmonary tissue (PT), PT and red blood cells (RBCs) was measured using single-shot spiral iterative decomposition of water and fat with echo asymmetry and least-squares estimation images of the right and left lungs of two age-matched cohorts of Sprague Dawley rats. The first cohort (n = 5) received 18 Gy irradiation to the right lung using a (60)Co source and the second cohort (n = 5) was not irradiated and served as the healthy control. Both groups were imaged two weeks following irradiation when radiation pneumonitis (RP) was expected to be present. The gas exchange data were fit to a theoretical gas exchange model to extract measurements of pulmonary tissue thickness (LPT) and relative blood volume (VRBC) from each of the right and left lungs of both cohorts. Following imaging, lung specimens were retrieved and percent tissue area (PTA) was assessed histologically to confirm RP and correlate with MRI measurements.

RESULTS

Statistically significant differences in LPT and VRBC were observed between the irradiated and non-irradiated cohorts. In particular, LPT of the right and left lungs was increased approximately 8.2% and 5.0% respectively in the irradiated cohort. Additionally, VRBC of the right and left lungs was decreased approximately 36.1% and 11.7% respectively for the irradiated cohort compared to the non-irradiated cohort. PTA measurements in both right and left lungs were increased in the irradiated group compared to the non-irradiated cohort for both the left (P < 0.05) and right lungs (P < 0.01) confirming the presence of RP. PTA measurements also correlated with the MRI measurements for both the non-irradiated (r = 0.79, P < 0.01) and irradiated groups (r = 0.91, P < 0.01).

CONCLUSIONS

Regional RILI can be detected two weeks post-irradiation using HP (129)Xe MRI and analysis of gas exchange curves. This approach correlates well with histology and can potentially be used clinically to assess radiation pneumonitis associated with early RILI to improve radiation therapy outcomes.

Evaluation of pulmonary perfusion by SPECT imaging using an endothelial cell tracer in supine humans and dogs

Background

Pulmonary perfusion is not spatially homogeneously distributed, and its variations could be of diagnostic value in lung vascular disease. PulmoBind is a ligand of the adrenomedullin receptor densely expressed in endothelial cells of lung capillaries. The aim of this study was to evaluate spatial distribution of human lung perfusion by using this novel molecular tracer of the pulmonary vascular endothelium.

Methods

Normal humans (n = 19) enrolled into the PulmoBind phase I trial were studied (Clinicaltrials.gov.NCT01539889). They were injected with ^99mTc-PulmoBind for SPECT imaging. Results were compared with ^99mTc-PulmoBind in quadruped mammals (dogs, n = 5). Imaging was performed in the supine position and distribution of activity was determined as a function of cumulative voxels along the different anatomical planes.

Results

PulmoBind uptake in humans was 58 ± 1 % (mean ± SEM) of the injected dose. Dorsal activity was 18.1 ± 2.1 % greater than ventral, and caudal activity was 25.7 ± 1.6 % greater than cranial. Lateral activity was only mildly higher than medial by 7.0 ± 1.0 %. In supine dogs, similar but higher PulmoBind gradients were present: dorsal 28.6 ± 2.5 %, caudal 34.1 ± 5.0 % and lateral 18.1 ± 2.0 %.

Conclusions

The perfused pulmonary circulation of supine humans, assessed by an adrenomedullin receptor ligand, is not homogeneously distributed with more prominent distribution in dorsal and caudal regions. It is qualitatively similar to a supine quadruped mammal confirming the presence of a microcirculatory gravitational perfusion gradient detectable with this tracer. Future studies are needed to determine if this novel endothelial cell tracer could be used to detect physiologic and pathologic variations of lung perfusion such as in pulmonary hypertension.

Clinical trial

ClinicalTrial.gov, NCT01539889

Should we include SPECT lung perfusion in radiotherapy treatment plans of thoracic targets? Evidences from the literature

PURPOSE

To report the available data about the potential impact of integrating lung perfusion SPECT/CT in treatment plans optimization for the irradiation of thoracic targets.

MATERIALS AND METHODS

We searched in the PubMed and Scopus databases, English-written articles published from 2000 to June 2015 dealing with the integration of perfusion SPECT/CT in radiotherapy.

RESULTS

We found and analyzed 16 research articles (10 dosimetric, 6 clinical) for a total of 578 patients. Available data suggest dosimetric and clinical improvements when perfusion SPEC/CT is integrated in the radiotherapy treatment planing of selected patients with thoracic targets. In particular, patients presenting emphysema and/or large areas of deficit of perfusion show the most important improvements. Moreover, some studies show different risk of radiation pneumonitis (RP) depending on the localization of the tumor in the lungs: patients with low-located tumors, present an increased risk of RP, and functional data could be a benefit in treatment plan optimization. Unfortunately, none of the available studies finally reports any dosimetric constraint, which could be used in the clinical practice, even if most of them used the cut-off of the 30% of the maximal perfusion value to define the well-functioning lung.

CONCLUSIONS

Published data support the integration of lung perfusion scintigraphy in some selected categories of patients. Prospective studies should be designed to define the best candidates, and to assess the clinical advantage of this kind of optimization.

Effects of superimposed tissue weight on regional compliance of injured lungs

Computed tomography (CT), together with image analysis technologies, enable the construction of regional volume (VREG) and local transpulmonary pressure (PTP,REG) maps of the lung. Purpose of this study is to assess the distribution of VREG vs PTP,REG along the gravitational axis in healthy (HL) and experimental acute lung injury conditions (eALI) at various positive end-expiratory pressures (PEEPs) and inflation volumes. Mechanically ventilated pigs underwent inspiratory hold maneuvers at increasing volumes simultaneously with lung CT scans. eALI was induced via the iv administration of oleic acid. We computed voxel-level VREG vs PTP,REG curves into eleven isogravitational planes by applying polynomial regressions. Via F-test, we determined that VREG vs PTP,REG curves derived from different anatomical planes (p-values<1.4E-3), exposed to different PEEPs (p-values<1.5E-5) or subtending different lung status (p-values<3E-3) were statistically different (except for two cases of adjacent planes). Lung parenchyma exhibits different elastic behaviors based on its position and the density of superimposed tissue which can increase during lung injury.

Quantification of nonuniform distribution of hemi-lung perfusion in chronic obstructive pulmonary disease

Nonuniform distribution (NUD) of perfusion on single photon emission computed tomography (SPECT) is caused by impaired perfusion-related fluctuations of the functional volume (FFV). It was determined if digital analysis of NUD in each hemi-lung damaged by chronic obstructive pulmonary disease (COPD) could improve the whole lung impairment assessment. We examined 665 subjects and 8 controls by SPECT. The basic whole lung SPECT volume was defined at 10% of maximum whole lung count cutoff threshold (T h). For the whole lung and each hemi-lung, the 10% T h width volume, FFV rate, and misfit from the control were calculated at every T h width number (n) from 1 to 9 for every additional 10% T h from 10 to 100%. The misfit value integrated from 1 to 9 of n was defined by 3 NUD indices: D, whole lung NUD index; D rl , the index for the sum of each hemi-lung NUD; and D (I) , the NUD index with every interpolating pattern in which FFV rates of hemi-lungs comprised negative and positive value at the same n. D rl index was the sum of D and D (I) indices in all patients. D rl and D indices significantly increased in pulmonary disease subjects relative to those of the normal group and non-pulmonary disease subjects. D rl and D indices increased in COPD subjects. Progressive COPD subjects had larger D rl index values and "diffuse and even" hemi-lung impairment. The three indices quantizing FFV itself leading to NUD helped to digitally evaluate the degree of lung impairment of perfusion. Clinically, it is expected that the NUD indices and images obtained by SPECT, which visually and digitally show the pathological fluctuations in perfusion caused by lung impairment, will be able to provide specific and useful information for improving treatment and/or care of subjects with COPD.

Estimating a regional ventilation-perfusion index

This is a methods paper, where an approximation to the local ventilation-perfusion ratio is derived. This approximation, called the ventilation-perfusion index since it is not exactly the physiological ventilation-perfusion ratio, is calculated using conductivity reconstructions obtained using electrical impedance tomography. Since computation of the ventilation-perfusion index only requires knowledge of the internal conductivity, any conductivity reconstruction method may be used. The method is explained and results are presented using conductivities obtained from two EIT systems, one using an iterative method and the other a linearization method.

A new quantitative index of lobar air trapping in chronic obstructive pulmonary disease (COPD): comparison with conventional methods

PURPOSE

To determine the usefulness of newly-proposed index (attenuation-volume index, AVI: increase in mean value of lung attenuation (MVLA) divided by volume decrease ratio (VDR)) for quantitative assessment of lobar air trapping (LAT) using expiratory/inspiratory (E/I) computed tomography (CT) by minimizing influence of respiratory level.

MATERIALS AND METHODS

Institutional review board approved study protocol. Twenty-one moderate or severe COPD (group A), 16 mild COPD (group B) and 26 normal volunteers (group C) underwent both E/I scans via 320-row CT and pulmonary functional test (PFT). Volume image data were automatically segmented into six lung lobes with minimal manual intervention. AVI, pixel index (PI), air trapping ratio (ATR) and relative volume change (RVC860-950) were calculated in total lung (TL) and each lobe. Four indices in TL were correlated with both PFT result and VDR and those in TL and each lobe were compared between three groups.

RESULTS

Similar to ATR, AVI correlated with both FEV1/FVC (r=0.772, p<0.01) and RV/TLC (r=-0.726, p<0.01) and demonstrated a significant difference between three groups in both TL (group A: 1.69±0.45, group B: 2.21±0.45 and group C: 2.80±0.44) and five lobes except for left lingular segment. In a lobe-based analysis regarding relationship with VDR, AVI was much less dependent than ATR, although regression lines of groups A and C were separated for AVI as well as ATR. Coefficient of variation of either PI or RVC860-950 was significantly larger than that of AVI.

CONCLUSION

AVI can be a more suitable CT index for quantitative evaluation of LAT, minimizing influence of respiratory level.

Anatomical, functional and metabolic imaging of radiation-induced lung injury using hyperpolarized MRI

MRI of hyperpolarized (129)Xe gas and (13)C-enriched substrates (e.g. pyruvate) presents an unprecedented opportunity to map anatomical, functional and metabolic changes associated with lung injury. In particular, inhaled hyperpolarized (129)Xe gas is exquisitely sensitive to changes in alveolar microanatomy and function accompanying lung inflammation through decreases in the apparent diffusion coefficient (ADC) of alveolar gas and increases in the transfer time (T(tr)) of xenon exchange from the gas and into the dissolved phase in the lung. Furthermore, metabolic changes associated with hypoxia arising from lung injury may be reflected by increases in lactate-to-pyruvate signal ratio obtained by magnetic resonance spectroscopic imaging following injection of hyperpolarized [1-(13)C]pyruvate. In this work, the application of hyperpolarized (129)Xe and (13)C MRI to radiation-induced lung injury (RILI) is reviewed and results of ADC, T(tr) and lactate-to-pyruvate signal ratio changes in a rat model of RILI are summarized. These results are consistent with conventional functional (i.e. blood gases) and histological (i.e. tissue density) changes, and correlate significantly with inflammatory cell counts (i.e. macrophages). Hyperpolarized MRI may provide an earlier indication of lung injury associated with radiotherapy of thoracic tumors, potentially allowing adjustment of treatment before the onset of severe complications and irreversible fibrosis.

Molecular imaging of the pulmonary circulation in health and disease

The pulmonary circulation, at the unique crossroads between the left and the right heart, is submitted to large physiologic hemodynamic variations and possesses numerous important metabolic functions mediated through its vast endothelial surface. There are many pathologic conditions that can directly or indirectly affect the pulmonary vasculature and modify its physiology and functions. Pulmonary hypertension, the end result of many of these affections, is unfortunately diagnosed too late in the disease process, meaning that there is a crying need for earlier diagnosis and surrogate markers of disease progression and regression. By targeting endothelial, medial and adventitial targets of the pulmonary vasculature, novel molecular imaging agents could provide early detection of physiologic and biologic perturbation in the pulmonary circulation. This review provides the rationale for the development of molecular imaging agents for the diagnosis and follow-up of disorders of the pulmonary circulation and discusses promising targets for SPECT and positron emission tomographic imaging.

Pulmonary ventilation imaging based on 4-dimensional computed tomography: comparison with pulmonary function tests and SPECT ventilation images

PURPOSE

4-dimensional computed tomography (4D-CT)-based pulmonary ventilation imaging is an emerging functional imaging modality. The purpose of this study was to investigate the physiological significance of 4D-CT ventilation imaging by comparison with pulmonary function test (PFT) measurements and single-photon emission CT (SPECT) ventilation images, which are the clinical references for global and regional lung function, respectively.

METHODS AND MATERIALS

In an institutional review board-approved prospective clinical trial, 4D-CT imaging and PFT and/or SPECT ventilation imaging were performed in thoracic cancer patients. Regional ventilation (V4DCT) was calculated by deformable image registration of 4D-CT images and quantitative analysis for regional volume change. V4DCT defect parameters were compared with the PFT measurements (forced expiratory volume in 1 second (FEV1; % predicted) and FEV1/forced vital capacity (FVC; %). V4DCT was also compared with SPECT ventilation (VSPECT) to (1) test whether V4DCT in VSPECT defect regions is significantly lower than in nondefect regions by using the 2-tailed t test; (2) to quantify the spatial overlap between V4DCT and VSPECT defect regions with Dice similarity coefficient (DSC); and (3) to test ventral-to-dorsal gradients by using the 2-tailed t test.

RESULTS

Of 21 patients enrolled in the study, 18 patients for whom 4D-CT and either PFT or SPECT were acquired were included in the analysis. V4DCT defect parameters were found to have significant, moderate correlations with PFT measurements. For example, V4DCT(HU) defect volume increased significantly with decreasing FEV1/FVC (R=-0.65, P<.01). V4DCT in VSPECT defect regions was significantly lower than in nondefect regions (mean V4DCT(HU) 0.049 vs 0.076, P<.01). The average DSCs for the spatial overlap with SPECT ventilation defect regions were only moderate (V4DCT(HU)0.39 ± 0.11). Furthermore, ventral-to-dorsal gradients of V4DCT were strong (V4DCT(HU) R(2) = 0.69, P=.08), which was similar to VSPECT (R(2) = 0.96, P<.01).

CONCLUSIONS

An 18-patient study demonstrated significant correlations between 4D-CT ventilation and PFT measurements as well as SPECT ventilation, providing evidence toward the validation of 4D-CT ventilation imaging.