Feasibility of image registration and intensity-modulated radiotherapy planning with hyperpolarized helium-3 magnetic resonance imaging for non-small-cell lung cancer

Incorporation of Functional Lung Imaging Into Radiation Therapy Planning in Patients With Lung Cancer: A Systematic Review and Meta-Analysis

Our purpose was to provide an understanding of current functional lung imaging (FLI) techniques and their potential to improve dosimetry and outcomes for patients with lung cancer receiving radiation therapy (RT). Excerpta Medica dataBASE (EMBASE), PubMed, and Cochrane Library were searched from 1990 until April 2023. Articles were included if they reported on FLI in one of: techniques, incorporation into RT planning for lung cancer, or quantification of RT-related outcomes for patients with lung cancer. Studies involving all RT modalities, including stereotactic body RT and particle therapy, were included. Meta-analyses were conducted to investigate differences in dose-function parameters between anatomic and functional RT planning techniques, as well as to investigate correlations of dose-function parameters with grade 2+ radiation pneumonitis (RP). One hundred seventy-eight studies were included in the narrative synthesis. We report on FLI modalities, dose-response quantification, functional lung (FL) definitions, FL avoidance techniques, and correlations between FL irradiation and toxicity. Meta-analysis results show that FL avoidance planning gives statistically significant absolute reductions of 3.22% to the fraction of well-ventilated lung receiving 20 Gy or more, 3.52% to the fraction of well-perfused lung receiving 20 Gy or more, 1.3 Gy to the mean dose to the well-ventilated lung, and 2.41 Gy to the mean dose to the well-perfused lung. Increases in the threshold value for defining FL are associated with decreases in functional parameters. For intensity modulated RT and volumetric modulated arc therapy, avoidance planning results in a 13% rate of grade 2+ RP, which is reduced compared with results from conventional planning cohorts. A trend of increased predictive ability for grade 2+ RP was seen in models using FL information but was not statistically significant. FLI shows promise as a method to spare FL during thoracic RT, but interventional trials related to FL avoidance planning are sparse. Such trials are critical to understanding the effect of FL avoidance planning on toxicity reduction and patient outcomes.

Systematic Evaluation of the Impact of Lung Segmentation Methods on 4-Dimensional Computed Tomography Ventilation Imaging Using a Large Patient Database

PURPOSE

A novel form of lung functional imaging applied for functional avoidance radiation therapy has been developed that uses 4-dimensional computed tomography (4DCT) data and image processing techniques to calculate lung ventilation (4DCT-ventilation). Lung segmentation is a common step to define a region of interest for 4DCT-ventilation generation. The purpose of this study was to quantitatively evaluate the sensitivity of 4DCT-ventilation imaging using different lung segmentation methods.

METHODS AND MATERIALS

The 4DCT data of 350 patients from 2 institutions were used. Lung contours were generated using 3 methods: (1) reference segmentations that removed airways and pulmonary vasculature manually (Lung-Manual), (2) standard lung contours used for planning (Lung-RadOnc), and (3) artificial intelligence (AI)-based contours that removed the airways and pulmonary vasculature (Lung-AI). The AI model was based on a residual 3-dimensional U-Net and was trained using the Lung-Manual contours of 279 patients. We compared the Lung-RadOnc or Lung-AI with Lung-Manual contours for the entire 4DCT-ventilation functional avoidance process including lung segmentation (surface Dice similarity coefficient [Surface DSC]), 4DCT-ventilation generation (correlation), and subanalysis of 10 patients on a dosimetric endpoint (percentage of high functional volume of lung receiving ≥20 Gy [fV20{%}]).

RESULTS

Surface DSC comparing Lung-Manual/Lung-RadOnc and Lung-Manual/Lung-AI contours was 0.40 ± 0.06 and 0.86 ± 0.04, respectively. The correlation between 4DCT-ventilation images generated with Lung-Manual/Lung-RadOnc and Lung-Manual/Lung-AI were 0.48 ± 0.14 and 0.85 ± 0.14, respectively. The difference in fV20[%] between 4DCT-ventilation generated with Lung-Manual/Lung-RadOnc and Lung-Manual/Lung-AI was 2.5% ± 4.1% and 0.3% ± 0.5%, respectively.

CONCLUSIONS

Our work showed that using standard planning lung contours can result in significantly variable 4DCT-ventilation images. The study demonstrated that AI-based segmentations generate lung contours and 4DCT-ventilation images that are similar to those generated using manual methods. The significance of the study is that it characterizes the lung segmentation sensitivity of the 4DCT-ventilation process and develops methods that can facilitate the integration of this novel imaging in busy clinics.

Deep Learning Approaches for Quantifying Ventilation Defects in Hyperpolarized Gas Magnetic Resonance Imaging of the Lung: A Review

This paper provides an in-depth overview of Deep Neural Networks and their application in the segmentation and analysis of lung Magnetic Resonance Imaging (MRI) scans, specifically focusing on hyperpolarized gas MRI and the quantification of lung ventilation defects. An in-depth understanding of Deep Neural Networks is presented, laying the groundwork for the exploration of their use in hyperpolarized gas MRI and the quantification of lung ventilation defects. Five distinct studies are examined, each leveraging unique deep learning architectures and data augmentation techniques to optimize model performance. These studies encompass a range of approaches, including the use of 3D Convolutional Neural Networks, cascaded U-Net models, Generative Adversarial Networks, and nnU-net for hyperpolarized gas MRI segmentation. The findings highlight the potential of deep learning methods in the segmentation and analysis of lung MRI scans, emphasizing the need for consensus on lung ventilation segmentation methods.

Targeted Imaging of Lung Cancer with Hyperpolarized 129Xe MRI Using Surface-Modified Iron Oxide Nanoparticles as Molecular Contrast Agents

Hyperpolarized 129Xe (HP 129Xe) MRI enables functional imaging of various lung diseases but has been scarcely applied to lung cancer imaging. The aim of this study is to investigate the feasibility of targeted imaging of lung cancer with HP 129Xe MRI using surface-modified iron oxide nanoparticles (IONPs) as molecular targeting contrast agents. A mouse model of lung cancer (LC) was induced in nine mice by intra-peritoneal injection of urethane. Three months after the urethane administration, the mice underwent lung imaging with HP 129Xe MRI at baseline (0 h). Subsequently, the LC group was divided into two sub-groups: mice administered with polyethylene glycol-coated IONPs (PEG-IONPs, n = 4) and folate-conjugated dextran-coated IONPs (FA@Dex-IONPs, n = 5). The mice were imaged at 3, 6, and 24 h after the intravenous injection of IONPs. FA@Dex-IONPs mice showed a 25% reduction in average signal intensity at cancer sites at 3 h post injection, and a 24% reduction at 24 h post injection. On the other hand, in PEG-IONPs mice, while a signal reduction of approximately 28% was observed at cancer sites at 3 to 6 h post injection, the signal intensity was unchanged from that of the baseline at 24 h. Proton MRI of LC mice (n = 3) was able to detect cancer five months after urethane administration, i.e., later than HP 129Xe MRI (3 months). Furthermore, a significant decrease in averaged 1H T2 values at cancer sites was observed at only 6 h post injection of FA@Dex-IONPs (p < 0.05). As such, the targeted delivery of IONPs to cancer tissue was successfully imaged with HP 129Xe MRI, and their surface modification with folate likely has a high affinity with LC, which causes overexpression of folate receptors.

The future of MRI in radiation therapy: Challenges and opportunities for the MR community

Radiation therapy is a major component of cancer treatment pathways worldwide. The main aim of this treatment is to achieve tumor control through the delivery of ionizing radiation while preserving healthy tissues for minimal radiation toxicity. Because radiation therapy relies on accurate localization of the target and surrounding tissues, imaging plays a crucial role throughout the treatment chain. In the treatment planning phase, radiological images are essential for defining target volumes and organs-at-risk, as well as providing elemental composition (e.g., electron density) information for radiation dose calculations. At treatment, onboard imaging informs patient setup and could be used to guide radiation dose placement for sites affected by motion. Imaging is also an important tool for treatment response assessment and treatment plan adaptation. MRI, with its excellent soft tissue contrast and capacity to probe functional tissue properties, holds great untapped potential for transforming treatment paradigms in radiation therapy. The MR in Radiation Therapy ISMRM Study Group was established to provide a forum within the MR community to discuss the unmet needs and fuel opportunities for further advancement of MRI for radiation therapy applications. During the summer of 2021, the study group organized its first virtual workshop, attended by a diverse international group of clinicians, scientists, and clinical physicists, to explore our predictions for the future of MRI in radiation therapy for the next 25 years. This article reviews the main findings from the event and considers the opportunities and challenges of reaching our vision for the future in this expanding field.

CT-derived vessel segmentation for analysis of post-radiation therapy changes in vasculature and perfusion

Vessel segmentation in the lung is an ongoing challenge. While many methods have been able to successfully identify vessels in normal, healthy, lungs, these methods struggle in the presence of abnormalities. Following radiotherapy, these methods tend to identify regions of radiographic change due to post-radiation therapytoxicities as vasculature falsely. By combining texture analysis and existing vasculature and masking techniques, we have developed a novel vasculature segmentation workflow that improves specificity in irradiated lung while preserving the sensitivity of detection in the rest of the lung. Furthermore, radiation dose has been shown to cause vascular injury as well as reduce pulmonary function post-RT. This work shows the improvements our novel vascular segmentation method provides relative to existing methods. Additionally, we use this workflow to show a dose dependent radiation-induced change in vasculature which is correlated with previously measured perfusion changes (R² = 0.72) in both directly irradiated and indirectly damaged regions of perfusion. These results present an opportunity to extend non-contrast CT-derived models of functional change following radiation therapy.

State of the Art: Lung Cancer Staging Using Updated Imaging Modalities

Lung cancer is among the most common mortality causes worldwide. This scientific article is a comprehensive review of current knowledge regarding screening, subtyping, imaging, staging, and management of treatment response for lung cancer. The traditional imaging modality for screening and initial lung cancer diagnosis is computed tomography (CT). Recently, a dual-energy CT was proven to enhance the categorization of variable pulmonary lesions. The National Comprehensive Cancer Network (NCCN) recommends usage of fluorodeoxyglucose positron emission tomography (FDG PET) in concert with CT to properly stage lung cancer and to prevent fruitless thoracotomies. Diffusion MR is an alternative to FDG PET/CT that is radiation-free and has a comparable diagnostic performance. For response evaluation after treatment, FDG PET/CT is a potent modality which predicts survival better than CT. Updated knowledge of lung cancer genomic abnormalities and treatment regimens helps to improve the radiologists’ skills. Incorporating the radiologic experience is crucial for precise diagnosis, therapy planning, and surveillance of lung cancer.

Combining Serial and Parallel Functionality in Functional Lung Avoidance Radiation Therapy

PURPOSE

Functional lung avoidance (FLA) radiation therapy (RT) aims to minimize post-RT pulmonary toxicity by preferentially avoiding dose to high-functioning lung (HFL) regions. A common limitation is that FLA approaches do not consider the conducting architecture for gas exchange. We previously proposed the functionally weighted airway sparing (FWAS) method to spare airways connected to HFL regions, showing that it is possible to substantially reduce risk of radiation-induced airway injury. Here, we compare the performance of FLA and FWAS and propose a novel method combining both approaches.

METHODS

We used breath-hold computed tomography (BHCT) and simulation 4-dimensional computed tomography (4DCT) from 12 lung stereotactic ablative radiation therapy patients. Four planning strategies were examined: (1) Conventional: no sparing other than clinical dose-volume constraints; (2) FLA: using a 4DCT-based ventilation map to delineate the HFL, plans were optimized to reduce mean dose and V_13.50 in HFL; (3) FWAS: we autosegemented 11 to 13 generations of individual airways from each patient's BHCT and assigned priorities based on the relative contribution of each airway to total ventilation. We used these priorities in the optimization along with airway dose constraints, estimated as a function of airway diameter and 5% probability of collapse; and (4) FLA + FWAS: we combined information from the 2 strategies. We prioritized clinical dose constraints for organs at risk and planning target volume in all plans. We performed the evaluation in terms of ventilation preservation accounting for radiation-induced damage to both lung parenchyma and airways.

RESULTS

We observed average ventilation preservation for FLA, FWAS, and FLA + FWAS as 3%, 8.5%, and 14.5% higher, respectively, than for Conventional plans for patients with ventilation preservation in Conventional plans <90%. Generalized estimated equations showed that all improvements were statistically significant (P ≤ .036). We observed no clinically relevant improvements in outcomes of the sparing techniques in patients with ventilation preservation in Conventional plans ≥90%.

CONCLUSIONS

These initial results suggest that it is crucial to consider the parallel and the serial nature of the lung to improve post-radiation therapy lung function and, consequently, quality of life for patients.

Investigating the use of machine learning to generate ventilation images from CT scans

Background

Radiotherapy treatment planning incorporating ventilation imaging can reduce the incidence of radiation‐induced lung injury. The gold‐standard of ventilation imaging, using nuclear medicine, has limitations with respect to availability and cost.

Purpose

An alternative type of ventilation imaging to nuclear medicine uses 4DCT (or breath‐hold CT [BHCT] pair) with deformable image registration (DIR) and a ventilation metric to produce a CT ventilation image (CTVI). The purpose of this study is to investigate the application of machine learning as an alternative to DIR‐based methods when producing CTVIs.

Methods

A patient dataset of 15 inhale and exhale BHCTs and Galligas PET ventilation images were used to train and test a 2D U‐Net style convolutional neural network. The neural network established relationships between axial input BHCT image pairs and axial labeled Galligas PET images and was evaluated using eightfold cross‐validation. Once trained, the neural network could produce a CTVI from an input BHCT image pair. The CTVIs produced by the neural network were qualitatively assessed visually and quantitatively compared to a Galligas PET ventilation image using a Spearman correlation and Dice similarity coefficient (DSC). The DSC measured the spatial overlap between three segmented equal lung volumes by ventilation (high, medium, and low functioning lung [LFL]).

Results

The mean Spearman correlation between the CTVIs and the Galligas PET ventilation images was 0.58 ± 0.14. The mean DSC over high, medium, and LFL between the CTVIs and Galligas PET ventilation images was 0.55 ± 0.06. Visually, a systematic overprediction of ventilation within the lung was observed in the CTVIs with respect to the Galligas PET ventilation images, with jagged regions of ventilation in the sagittal and coronal planes.

Conclusions

A convolutional neural network was developed that could produce a CTVI from a BHCT image pair, which was then compared with a Galligas PET ventilation image. The performance of this machine learning method was comparable to previous benchmark studies investigating a DIR‐based CTVI, warranting future development, and investigation of applying machine learning to a CTVI.

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

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. V_20Gy , V_10Gy , V_5Gy , 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, V_5Gy (Plan-A: 30.7 ± 11.0%, Plan-F: 27.2 ± 9.3%), V_10Gy (Plan-A: 22.0 ± 8.6%, Plan-F: 19.3 ± 7.0%), and V_20Gy (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.

Predicting radiation pneumonitis with fuzzy clustering neural network using 4DCT ventilation image based dosimetric parameters

Background

To develop a fuzzy clustering neural network to predict radiation-induced pneumonitis (RP) using four-dimensional computed tomography (4DCT) ventilation image (VI) based dosimetric parameters for thoracic cancer patients.

Methods

The VI were retrospectively calculated from pre-treatment 4DCT data using a deformable image registration (DIR) and an improved VI algorithm. Similar to dose-volume histogram (DVH) of intensity modulated radiotherapy (IMRT), dose-function histogram (DFH) was derived from dose distribution and VI. Then, the dose-function metrics were calculated from DFH. For comparison, the dose-volume metrics were calculated from DVH. Correspondingly, two sets of feature vectors were formed from the dose-volume metrics and the dose-function metrics, respectively. For the feature vectors of each set, they were first pre-processed by principal component analysis (PCA) to reduce feature dimensions. Then, they were grouped to few clusters determined by fuzzy c-means (FCM) algorithm. Next, the neural network was trained to correlate the dosimetric parameters with RP based on the feature vectors of each cluster. Finally, the occurrence of RP was predicted by the neural network on the test data.

Results

Through PCA analysis, the top 5 principal components were selected. Their contribution is more than 98%, which is adequate to represent the original feature space of input data. Based on the clustering validity indexes, the optimal number of clusters is 4 and used for subsequent fuzzy clustering of the input data. After network training, the areas under the curve (AUC) of the prediction model is 0.77 using VI-based dosimetric parameters and 0.67 using structure-based dosimetric parameters.

Conclusions

Compared to the structure-based dosimetric features, the VI-based dosimetric features are more relevant to lung function and presented higher prediction accuracy of RP. The fuzzy clustering neural network improved the prediction accuracy of RP compared to the conventional neural network. The combination of VI-based dose-function metrics and fuzzy clustering neural network provides an effective predictive model for assessing lung toxicity risk after radiotherapy.

Preliminary Study on the Effect of 4DCT-Ventilation-Weighted Dose on the Radiation Induced Pneumonia Probability (RIPP)

Purpose

The purpose of the present study was to evaluate the feasibility of using 4-dimensional computed tomography (4DCT)-ventilation-weighted dose analysis to predict radiation-induced pneumonia probability (RIPP).

Methods and Materials

The study population for this retrospective analysis included 16 patients with stage III lung cancer. Each patient's 4DCT images, including end-inhale and end-exhale sequences, were used for the deformable image registration, and the Hounsfield units (HU) density-change was used to calculate the ventilation. A previously established equation was used to convert the original dose (OD) D _{0, i} in the lungs in the original plan (OP) to the weighted-dose (WD) D _{w, i} in the weighted plan (WP). The patients were divided into 2 groups, one with radiation-induced pneumonia (RIP), and one without. The Spearman correlation analysis was used to analyze the correlation of RIP with ΔV₂₀ (ΔV _x = V _{w, x} in the WP - V _{0, x} in the OP), ΔMLD (ΔMLD = mean lung dose (MLD) in the WP - MLD in the OP), and ΔV₅.

Results

The results showed that 5 of the 16 patients were suffering from acute RIP, 4 of which had higher ΔV₂₀ and ΔMLD values than the rest of the patients. The results of the Spearman correlation analysis for those 4 patients were as follows: RIP vs. ΔV₂₀, r = 0.5123; RIP vs. ΔMLD, r = 0.5119; RIP vs. ΔV₅, r = 0.1904.

Conclusions

The 4DCT-ventilation-based weighted-dose analysis showed some correlation between RIPP and both ΔV₂₀ and ΔMLD, when comparing the weighted-dose and the conventional dose-volume histogram (DVH) analyses.

Hyperpolarized 129Xe Magnetic Resonance Imaging for Functional Avoidance Treatment Planning in Thoracic Radiation Therapy: A Comparison of Ventilation- and Gas Exchange-Guided Treatment Plans

PURPOSE

To present a methodology to use pulmonary gas exchange maps to guide functional avoidance treatment planning in radiation therapy (RT) and evaluate its efficacy compared with ventilation-guided treatment planning.

METHODS AND MATERIALS

Before receiving conventional RT for non-small cell lung cancer, 11 patients underwent hyperpolarized ¹²⁹Xe gas exchange magnetic resonance imaging to map the distribution of xenon in its gas phase (ventilation) and transiently bound to red blood cells in the alveolar capillaries (gas exchange). Both ventilation and gas exchange maps were independently used to guide development of new functional avoidance treatment plans for every patient, while adhering to institutional dose-volume constraints for normal tissues and target coverage. Furthermore, dose-volume histogram (DVH)-based reoptimizations of the clinical plan, with reductions in mean lung dose (MLD) equal to the functional avoidance plans, were created to serve as the control group. To evaluate each plan (regardless of type), gas exchange maps, representing end-to-end lung function, were used to calculate gas exchange-weighted MLD (fMLD), gas exchange-weighted volume receiving ≥20 Gy (fV20), and mean dose in the highest gas exchanging 33% and 50% volumes of lung (MLD-f33% and MLD-f50%). Using each clinically approved plan as a baseline, the reductions in functional metrics were compared for ventilation-optimization, gas exchange optimization, and DVH-based reoptimization. Statistical significance was determined using the Freidman test, with subsequent subdivision when indicated by P values less than .10 and post hoc testing with Wilcoxon signed rank tests to determine significant differences (P < .05). Toxicity modeling was performed using an established function-based model to estimate clinical significance of the results.

RESULTS

Compared with DVH-based reoptimization of the clinically approved plans, gas exchange-guided functional avoidance planning more effectively reduced the gas exchange-weighted metrics fMLD (average ± SD, -78 ± 79 cGy for gas exchange, compared with -45 ± 34 cGy for DVH-based; P = .03), MLD-f33% (-135 ± 136 cGy, compared with -52 ± 47 cGy; P = .004), and MLD-f50% (-96 ± 95 cGy, compared with -47 ± 40 cGy; P = .01). Comparing the 2 functional planning types, gas exchange-guided planning more effectively reduced MLD-f33% compared with ventilation-guided planning (-64 ± 95; P = .009). For some patients, gas exchange-guided functional avoidance plans demonstrated clinically significant reductions in model-predicted toxicity, more so than the accompanying ventilation-guided plans and DVH-based reoptimizations.

CONCLUSION

Gas exchange-guided planning effectively reduced dose to high gas exchanging regions of lung while maintaining clinically acceptable plan quality. In many patients, ventilation-guided planning incidentally reduced dose to higher gas exchange regions, to a lesser extent. This methodology enables future prospective trials to examine patient outcomes.

Inflammation during Lung Cancer Progression and Ethyl Pyruvate Treatment Observed by Pulmonary Functional Hyperpolarized 129Xe MRI in Mice

This study aimed to assess the suitability of hyperpolarized ¹²⁹Xe (HPXe) MRI for noninvasive longitudinal evaluation of pulmonary function in preclinical lung cancer models. A mouse model of lung cancer (LC) was induced in 5 mice by intraperitoneal injection of urethane, while a negative-control (NC) mice (N = 5) was prepared by injection of saline solution. Longitudinal HPXe MRI was performed over a 5-month period to monitor lung ventilation and gas exchange. The treatment efficacy of ethyl pyruvate (EP), an anti-inflammatory drug, to the mouse LC model was monitored using HPXe MRI by commencing administration of EP pre (early-phase) and 1-month post (late-phase) injection of urethane (N = 5 mice for each group). Gas-exchange function in LC mice was significantly reduced at 1-month after urethane injection compared with NC mice administered with saline (P < 0.01). Thereafter, it remained consistently lower than that of the NC group for the full 5-month measurement period. In contrast, the ventilation function of the LC model mice was not significantly different to that of the NC mice. Histological analysis revealed alveolar epithelial hyperplasia in LC mice alveoli at 1 month after urethane injection, and adenoma was confirmed 3 months after the injection. The early- and late-phase EP interventions were found to improve HPXe MRI metrics (reduced at 1 month postinjection of urethane) and significantly inhibit tumor growth. These results suggest that HPXe MRI gas-exchange metrics can be used to quantitatively assess changes in the precancerous lesion microenvironment and to evaluate therapeutic efficacy in cancer. Thus, HPXe MRI can be utilized to noninvasively monitor pulmonary pathology during LC progression and can visualize functional changes during therapy.

Functionally weighted airway sparing (FWAS): a functional avoidance method for preserving post-treatment ventilation in lung radiotherapy

Recent changes to the guidelines for screening and early diagnosis of lung cancer have increased the interest in preserving post-radiotherapy lung function. Current investigational approaches are based on spatially mapping functional regions and generating regional avoidance plans that preferentially spare highly ventilated/perfused lung. A potentially critical, yet overlooked, aspect of functional avoidance is radiation injury to peripheral airways, which serve as gas conduits to and from functional lung regions. Dose redistribution based solely on regional function may cause irreparable damage to the 'supply chain'. To address this deficiency, we propose the functionally weighted airway sparing (FWAS) method. FWAS (i) maps the bronchial pathways to each functional sub-lobar lung volume; (ii) assigns a weighting factor to each airway based on the relative contribution of the sub-volume to overall lung function; and (iii) creates a treatment plan that aims to preserve these functional pathways. To evaluate it, we used four cases from a retrospective cohort of SAbR patients treated for lung cancer. Each patient's airways were auto-segmented from a diagnostic-quality breath-hold CT using a research virtual bronchoscopy software. A ventilation map was generated from the planning 4DCT to map regional lung function. For each terminal airway, as resolved by the segmentation software, the total ventilation within the sub-lobar volume supported by that airway was estimated and used as a function-based weighting factor. Upstream airways were weighted based on the cumulative volumetric ventilation supported by corresponding downstream airways. Using a previously developed model for airway radiosensitivity, dose constraints were determined for each airway corresponding to a <5% probability of airway collapse. Airway dose constraints, ventilation scores, and clinical dose constraints were input to a swarm optimization-based inverse planning engine to create a 3D conformal SAbR plan (CRT). The FWAS plans were compared to the patients' prescribed CRT clinical plans and the inverse-optimized clinical plans. Depending on the size and location of the tumour, the FWAS plan showed superior preservation of ventilation due to airflow preservation through open pathways (i.e. cumulative ventilation score from the sub-lobar volumes of open pathways). Improvements ranged between 3% and 23%, when comparing to the prescribed clinical plans, and between 3% and 35%, when comparing to the inverse-optimized clinical plans. The three plans satisfied clinical requirements for PTV coverage and OAR dose constraints. These initial results suggest that by sparing pathways to high-functioning lung subregions it is possible to reduce post-SAbR loss of respiratory function.

Evaluation of four-dimensional cone beam computed tomography ventilation images acquired with two different linear accelerators at various gantry speeds using a deformable lung phantom

We evaluated four-dimensional cone beam computed tomography (4D-CBCT) ventilation images (VI_CBCT) acquired with two different linear accelerator systems at various gantry speeds using a deformable lung phantom. The 4D-CT and 4D-CBCT scans were performed using a computed tomography (CT) scanner, an X-ray volume imaging system (Elekta XVI) mounted in Versa HD, and an On-Board Imager (OBI) system mounted in TrueBeam. Intensity-based deformable image registration (DIR) was performed between peak-exhale and peak-inhale images. VI_CBCT- and 4D-CT-based ventilation images (VI_CT) were derived by DIR using two metrics: one based on the Jacobian determinant and one on changes in the Hounsfield unit (HU). Three different DIR regularization values (λ) were used for VI_CBCT. Correlations between the VI_CBCT and VI_CT values were evaluated using voxel-wise Spearman's rank correlation coefficient (r). In case of both metrics, the Jacobian-based VI_CBCT with a gantry speed of 0.6 deg/sec in Versa HD showed the highest correlation for all the gantry speeds (e.g., λ = 0.05 and r = 0.68). Thus, the r value of the Jacobian-based VI_CBCT was greater or equal to that of the HU-based VI_CBCT. In addition, the ventilation accuracy of VI_CBCT increased at low gantry speeds. Thus, the image quality of VI_CBCT was affected by the change in gantry speed in both the imaging systems. Additionally, DIR regularization considerably influenced VI_CBCT in both the imaging systems. Our results have the potential to assist in designing CBCT protocols, incorporating VI_CBCT imaging into the functional avoidance planning process.

Comparison of postoperative CT- and preoperative MRI-based breast tumor bed contours in prone position for radiotherapy after breast-conserving surgery

Objectives

To compare the target volume of tumor bed defined by postoperative computed tomography (post-CT) in prone position registered with or without preoperative magnetic resonance imaging (pre-MRI).

Methods

A total of 22 patients were included with early-stage breast invasive ductal cancer, who have undergone breast-conservative surgery and received the pre-MRI and post-CT in prone position. The MRI sequences (T1W, T2W, T2W-SPAIR, DWI, dyn-eTHRIVE, sdyn-eTHRIVE) were delineated and manually registered to CT, respectively. The clinical target volumes (CTVs) and planning target volumes (PTVs) were contoured on CT and different MRI sequences, respectively. Differences were measured in terms of consistence index (CI), dice coefficient (DC), geographical miss index (GMI), and normal tissue index (NTI).

Results

The differences of delineation volumes among CT and MRIs were significant, both in the CTVs (p = 0.035) and PTVs (p < 0.001). The values of CI and DC for sdyn-eTHRIVE registration to CT were the largest among all MRI sequences, but GMI and NTI were the smallest. No obvious linear correlation (p > 0.05) between the CI derived from the registration of CT and sdyn-eTHRIVE of CTV with the breast volume, the cavity visualization score (CVS) of CT, time interval from surgery to CT simulation, the maximum diameter of the intraoperative mass, and the number of titanium clips, respectively.

Conclusions

The CTVs and PTVs in MRI sequences were all smaller than those in CT. The pre-MRI, especially the sdyn-eTHRIVE, could be used to optimize the post-CT-based target delineation of breast cancer.

Key Points

• Registered pre-MRI to post-CT in order to improve the accuracy of target volume delineation of breast cancer.

• The CTVs and PTVs in MRI sequences were all smaller than those in CT.

• The sdyn-eTHRIVE of pre-MRIs may be a better choice to improve the delineation of CT-based CTV and PTV.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07085-0) contains supplementary material, which is available to authorized users.

Accounting for respiratory motion in small serial structures during radiotherapy planning: proof of concept in virtual bronchoscopy-guided lung functional avoidance radiotherapy

Respiratory motion management techniques in radiotherapy (RT) planning are primarily focused on maintaining tumor target coverage. An inadequately addressed need is accounting for motion in dosimetric estimations in smaller serial structures. Accurate dose estimations in such structures are more sensitive to motion because respiration can cause them to move completely in or out of a high dose-gradient field. In this work, we study three motion management strategies (m1-m3) to find an accurate method to estimate the dosimetry in airways. To validate these methods, we generated a 'ground truth' digital breathing model based on a 4DCT scan from a lung stereotactic ablative radiotherapy (SAbR) patient. We simulated 225 breathing cycles with  ±10% perturbations in amplitude, respiratory period, and time per respiratory phase. A high-resolution breath-hold CT (BHCT) was also acquired and used with a research virtual bronchoscopy software to autosegment 239 airways. Contours for planning target volume (PTV) and organs at risk (OARs) were defined on the maximum intensity projection of the 4DCT (CT_MIP) and transferred to the average of the 10 4DCT phases (CT_AVG). To design the motion management methods, the RT plan was recreated using different images and structure definitions. Methods m1 and m2 recreated the plan using the CT_AVG image. In method m1, airways were deformed to the CT_AVG. In m2, airways were deformed to each of the 4DCT phases, and union structures were transferred onto the CT_AVG. In m3, the RT plan was recreated on each of the 10 phases, and the dose distribution from each phase was deformed to the BHCT and summed. Dose errors (mean [min, max]) in airways were: m1: 21% (0.001%, 93%); m2: 45% (0.1%, 179%); and m3: 4% (0.006%, 14%). Our work suggests that accurate dose estimation in moving small serial structures requires customized motion management techniques (like m3 in this work) rather than current clinical and investigational approaches.

CT-based ventilation imaging in radiation oncology

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.

Robust CT ventilation from the integral formulation of the Jacobian

Computed tomography (CT) derived ventilation algorithms estimate the apparent voxel volume changes within an inhale/exhale CT image pair. Transformation‐based methods compute these estimates solely from the spatial transformation acquired by applying a deformable image registration (DIR) algorithm to the image pair. However, approaches based on finite difference approximations of the transformation's Jacobian have been shown to be numerically unstable. As a result, transformation‐based CT ventilation is poorly reproducible with respect to both DIR algorithm and CT acquisition method.

Purpose

We introduce a novel Integrated Jacobian Formulation (IJF) method for estimating voxel volume changes under a DIR‐recovered spatial transformation. The method is based on computing volume estimates of DIR mapped subregions using the hit‐or‐miss sampling algorithm for integral approximation. The novel approach allows for regional volume change estimates that (a) respect the resolution of the digital grid and (b) are based on approximations with quantitatively characterized and controllable levels of uncertainty. As such, the IJF method is designed to be robust to variations in DIR solutions and thus overall more reproducible.

Methods

Numerically, Jacobian estimates are recovered by solving a simple constrained linear least squares problem that guarantees the recovered global volume change is equal to the global volume change obtained from the inhale and exhale lung segmentation masks. Reproducibility of the IJF method with respect to DIR solution was assessed using the expert‐determined landmark point pairs and inhale/exhale phases from 10 four‐dimensional computed tomographies (4DCTs) available on http://www.dir-lab.com. Reproducibility with respect to CT acquisition was assessed on the 4DCT and 4D cone beam CT (4DCBCT) images acquired for five lung cancer patients prior to radiotherapy.

Results

The ten Dir‐Lab 4DCT cases were registered twice with the same DIR algorithm, but with different smoothing parameter. Finite difference Jacobian (FDJ) and IFJ images were computed for both solutions. The average spatial errors (300 landmarks per case) for the two DIR solution methods were 0.98 (1.10) and 1.02 (1.11). The average Pearson correlation between the FDJ images computed from the two DIR solutions was 0.83 (0.03), while for the IJF images it was 1.00 (0.00). For intermodality assessment, the IJF and FDJ images were computed from the 4DCT and 4DCBCT of five patients. The average Pearson correlation of the spatially aligned FDJ images was 0.27 (0.11), while it was 0.77 (0.13) for the IFJ method.

Conclusion

The mathematical theory underpinning the IJF method allows for the generation of ventilation images that are (a) computed with respect to DIR spatial accuracy on the digital voxel grid and (b) based on DIR‐measured subregional volume change estimates acquired with quantifiable and controllable levels of uncertainty. Analyses of the experiments are consistent with the mathematical theory and indicate that IJF ventilation imaging has a higher reproducibility with respect to both DIR algorithm and CT acquisition method, in comparison to the standard finite difference approach.

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

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 ³He-MRI. Seven asthma patients underwent breath-hold CT at total lung capacity (TLC) and functional residual capacity (FRC). ³He-MRI and a same-breath ¹H-MRI were acquired at FRC+1L and TLC. Percentage ventilated volumes (%VVs) were calculated for FRC+1L and TLC ³He-MRI. TLC-CT and registered FRC-CT were used to compute a surrogate ventilation map from voxel-wise intensity differences in Hounsfield unit values, which was thresholded at the 10th and 20th percentiles. For direct comparison of CT and ³He-MRI ventilation, FRC+1L and TLC ³He-MRI were registered to TLC-CT indirectly via the corresponding same-breath ¹H-MRI data. For ³He-MRI and CT ventilation comparison, Dice similarity coefficients (DSCs) between the binary segmentations were computed. The median (range) of %VVs for FRC+1L and TLC ³He-MRI were 90.5 (54.9-93.6) and 91.8 (67.8-96.2), respectively (p   =  0.018). For MRI versus CT ventilation comparison, statistically significant improvements in DSCs were observed for TLC ³He MRI when compared with FRC+1L, with median (range) values of 0.93 (0.86-0.93) and 0.86 (0.68-0.92), respectively (p   =  0.017), for the 10-100th percentile and 0.87 (0.83-0.88) and 0.81 (0.66-0.87), respectively (p   =  0.027), for the 20-100th percentile. Correlation of CT ventilation imaging and hyperpolarised gas MRI is sensitive to lung inflation level. For ventilation maps derived from CT acquired at FRC and TLC, a higher correlation with gas ventilation MRI can be achieved if the MRI is acquired at TLC.

Advanced pulmonary MRI to quantify alveolar and acinar duct abnormalities: Current status and future clinical applications

There are serious clinical gaps in our understanding of chronic lung disease that require novel, sensitive, and noninvasive in vivo measurements of the lung parenchyma to measure disease pathogenesis and progressive changes over time as well as response to treatment. Until recently, our knowledge and appreciation of the tissue changes that accompany lung disease has depended on ex vivo biopsy and concomitant histological and stereological measurements. These measurements have revealed the underlying pathologies that drive lung disease and have provided important observations about airway occlusion, obliteration of the terminal bronchioles and airspace enlargement, or fibrosis and their roles in disease initiation and progression. ex vivo tissue stereology and histology are the established gold standards and, more recently, micro-computed tomography (CT) measurements of ex vivo tissue samples has also been employed to reveal new mechanistic findings about the progression of obstructive lung disease in patients. While these approaches have provided important understandings using ex vivo analysis of excised samples, recently developed hyperpolarized noble gas MRI methods provide an opportunity to noninvasively measure acinar duct and terminal airway dimensions and geometry in vivo, and, without radiation burden. Therefore, in this review we summarize emerging pulmonary MRI morphometry methods that provide noninvasive in vivo measurements of the lung in patients with bronchopulmonary dysplasia and chronic obstructive pulmonary disease, among others. We discuss new findings, future research directions, as well as clinical opportunities to address current gaps in patient care and for testing of new therapies. Level of Evidence: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019;50:28-40.

Interim Analysis of a Two-Institution, Prospective Clinical Trial of 4DCT-Ventilation-based Functional Avoidance Radiation Therapy

PURPOSE

Functional imaging has been proposed that uses 4DCT images to calculate 4DCT-based lung ventilation (4DCT-ventilation). We have started a 2-institution, phase 2 prospective trial evaluating the feasibility, safety, and preliminary efficacy of 4DCT-ventilation functional avoidance. The trial hypothesis is that the rate of grade ≥2 radiation pneumonitis could be reduced to 12% with functional avoidance, compared with a 25% rate of pneumonitis with a historical control. The trial employed a Simon 2-stage design with a planned futility analysis after 17 evaluable patients. The purpose of this work is to present the trial design and implementation, dosimetric data, and clinical results for the planned futility analysis.

METHODS AND MATERIALS

Eligible patients were patients with lung cancer who were prescribed doses of 45 to 75 Gy. For each patient, the 4DCT data were used to generate a 4DCT-ventilation image using the Hounsfield unit technique along with a compressible flow-based image registration algorithm. Two intensity modulated radiation therapy treatment plans were generated: (1) a standard lung plan and (2) a functional avoidance treatment plan that aimed to reduce dose to functional lung while meeting target and normal tissue constraints. Patients were treated with the functional avoidance plan and evaluated for thoracic toxicity (presented as rate and 95% confidence intervals [CI]) with a 1-year follow-up.

RESULTS

The V20 to functional lung was 21.6% ± 9.5% (mean ± standard deviation) with functional avoidance, representing a decrease of 3.2% (P < .01) relative to standard, nonfunctional treatment plans. The rates of grade ≥2 and grade ≥3 radiation pneumonitis were 17.6% (95% CI, 3.8%-43.4%) and 5.9% (95% CI, 0.1%-28.7%), respectively.

CONCLUSIONS

Dosimetrically, functional avoidance achieved reduction in doses to functional lung while meeting target and organ at risk constraints. On the basis of Simon's 2-stage design and the 17.6% grade ≥2 pneumonitis rate, the trial met its futility criteria and has continued accrual.

Changes in Regional Ventilation During Treatment and Dosimetric Advantages of CT Ventilation Image Guided Radiation Therapy for Locally Advanced Lung Cancer

PURPOSE

Lung functional image guided radiation therapy (RT) that avoids irradiating highly functional regions has potential to reduce pulmonary toxicity following RT. Tumor regression during RT is common, leading to recovery of lung function. We hypothesized that computed tomography (CT) ventilation image-guided treatment planning reduces the functional lung dose compared to standard anatomic image-guided planning in 2 different scenarios with or without plan adaptation.

METHODS AND MATERIALS

CT scans were acquired before RT and during RT at 2 time points (16-20 Gy and 30-34 Gy) for 14 patients with locally advanced lung cancer. Ventilation images were calculated by deformable image registration of four-dimensional CT image data sets and image analysis. We created 4 treatment plans at each time point for each patient: functional adapted, anatomic adapted, functional unadapted, and anatomic unadapted plans. Adaptation was performed at 2 time points. Deformable image registration was used for accumulating dose and calculating a composite of dose-weighted ventilation used to quantify the lung accumulated dose-function metrics. The functional plans were compared with the anatomic plans for each scenario separately to investigate the hypothesis at a significance level of 0.05.

RESULTS

Tumor volume was significantly reduced by 20% after 16 to 20 Gy (P = .02) and by 32% after 30 to 34 Gy (P < .01) on average. In both scenarios, the lung accumulated dose-function metrics were significantly lower in the functional plans than in the anatomic plans without compromising target volume coverage and adherence to constraints to critical structures. For example, functional planning significantly reduced the functional mean lung dose by 5.0% (P < .01) compared to anatomic planning in the adapted scenario and by 3.6% (P = .03) in the unadapted scenario.

CONCLUSIONS

This study demonstrated significant reductions in the accumulated dose to the functional lung with CT ventilation image-guided planning compared to anatomic image-guided planning for patients showing tumor regression and changes in regional ventilation during RT.

Characterizing Spatial Lung Function for Esophageal Cancer Patients Undergoing Radiation Therapy

PURPOSE

Patients with esophageal cancer treated with chemoradiation and surgery can develop pulmonary complications. Four-dimensional computed tomography-ventilation (4DCT-ventilation) is a developing imaging modality that uses 4DCT data to calculate lung ventilation. 4DCT-ventilation has been studied in the lung-cancer population but has yet to be extended to patients with esophageal cancer. The purpose of this study was to characterize 4DCT-ventilation-based spatial lung function for patients with esophageal cancer.

METHODS AND MATERIALS

Thirty-five patients with esophageal cancer who underwent 4DCT scans participated in the study. A 4DCT-ventilation map was calculated using the patient's 4DCT imaging and a density change-based algorithm. To assess each patient's ventilation profile, radiologist interpretations and quantitative metrics were used. A radiologist interpreted the 4DCT-ventilation images for lobar-based defects and gravity-dependent atelectasis. The 4DCT-ventilation maps were reduced to single metrics intended to reflect the degree of ventilation heterogeneity. The quantitative metrics included the coefficient of variation and metrics based on the ventilation in each lung and each lung third (superior-inferior ventilation [Vent-SI] and anteroposterior ventilation). The functional profile of patients with esophageal cancer was characterized and compared (using the Mann-Whitney test) for cohorts based on thoracic comorbidities and radiologist-identified defects.

RESULTS

Radiologist observations revealed that 26% of patients with esophageal cancer had lobar-based defects and 46% had gravity-dependent atelectasis. The baseline values were 0.52 ± 0.20 (mean ± SD), 11.2 ± 12.5, and 72.5 ± 14.6 for the coefficient of variation, the ventilation ratio of right to left lung, and Vent-SI metrics, respectively. The Vent-SI values were significantly different between patients with and without thoracic comorbidities (P = .05), and the anteroposterior ventilation metric was able to delineate patients with and without gravity-dependent atelectasis (P < .01).

CONCLUSIONS

Our data demonstrate that approximately 30% of patients with esophageal cancer have significant ventilation heterogeneities. The current work uses radiologist observations and quantitative metrics to characterize 4DCT ventilation-based lung function for patients with esophageal cancer and presents data that can be used for future applications of 4DCT-ventilation to reduce thoracic toxicity for patients with esophageal cancer.

Evaluation of lung toxicity risk with computed tomography ventilation image for thoracic cancer patients

Background

Four-dimensional computed tomography (4D-CT) ventilation is an emerging imaging modality. Functional avoidance of regions according to 4D-CT ventilation may reduce lung toxicity after radiation therapy. This study evaluated associations between 4D-CT ventilation-based dosimetric parameters and clinical outcomes.

Methods

Pre-treatment 4D-CT data were used to retrospectively construct ventilation images for 40 thoracic cancer patients retrospectively. Fifteen patients were treated with conventional radiation therapy, 6 patients with hyperfractionated radiation therapy and 19 patients with stereotactic body radiation therapy (SBRT). Ventilation images were calculated from 4D-CT data using a deformable image registration and Jacobian-based algorithm. Each ventilation map was normalized by converting it to percentile images. Ventilation-based dosimetric parameters (Mean Dose, V5 [percent lung volume receiving ≥5 Gy], and V20 [percent lung volume receiving ≥20 Gy]) were calculated for highly and poorly ventilated regions. To test whether the ventilation-based dosimetric parameters could be used predict radiation pneumonitis of ≥Grade 2, the area under the curve (AUC) was determined from the receiver operating characteristic analysis.

Results

For Mean Dose, poorly ventilated lung regions in the 0–30% range showed the highest AUC value (0.809; 95% confidence interval [CI], 0.663–0.955). For V20, poorly ventilated lung regions in the 0–20% range had the highest AUC value (0.774; 95% [CI], 0.598–0.915), and for V5, poorly ventilated lung regions in the 0–30% range had the highest AUC value (0.843; 95% [CI], 0.732–0.954). The highest AUC values for Mean Dose, V20, and V5 were obtained in poorly ventilated regions. There were significant differences in all dosimetric parameters between radiation pneumonitis of Grade 1 and Grade ≥2.

Conclusions

Poorly ventilated lung regions identified on 4D-CT had higher AUC values than highly ventilated regions, suggesting that functional planning based on poorly ventilated regions may reduce the risk of lung toxicity in radiation therapy.

Functional lung imaging in radiation therapy for lung cancer: A systematic review and meta-analysis

RATIONALE

Advanced imaging techniques allow functional information to be derived and integrated into treatment planning.

METHODS

A systematic review was conducted with the primary objective to evaluate the ability of functional lung imaging to predict risk of radiation pneumonitis. Secondary objectives were to evaluate dose-response relationships on post treatment functional imaging and assess the utility in including functional lung information into treatment planning. A structured search for publications was performed following PRISMA guidelines and registered on PROSPERO.

RESULTS

814 articles were screened against review criteria and 114 publications met criteria. Methods of identifying functional lung included using CT, MRI, SPECT and PET to image ventilation or perfusion. Six studies compared differences between functional and anatomical lung imaging at predicting radiation pneumonitis. These found higher predictive values using functional lung imaging. Twenty-one studies identified a dose-response relationship on post-treatment functional lung imaging. Nineteen planning studies demonstrated the ability of functional lung optimised planning techniques to spare regions of functional lung. Meta-analysis of these studies found that mean (95% CI) functional volume receiving 20 Gy was reduced by 4.2% [95% CI: 2.3: 6.0] and mean lung dose by 2.2 Gy [95% CI: 1.2: 3.3] when plans were optimised to spare functional lung. There was significant variation between publications in the definition of functional lung.

CONCLUSION

Functional lung imaging may have potential utility in radiation therapy planning and delivery, although significant heterogeneity was identified in approaches and reporting. Recommendations have been made based on the available evidence for future functional lung trials.

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

PURPOSE

Functional-guided radiation therapy (RT) plans have the potential to limit damage to normal tissue and reduce toxicity. Although functional imaging modalities have continued to improve, a limited understanding of the functional response to radiation and its application to personalized therapy has hindered clinical implementation. The purpose of this study was to retrospectively model the longitudinal, patient-specific dose-function response in non-small cell lung cancer patients treated with RT to better characterize the expected functional damage in future, unknown patients.

METHODS AND MATERIALS

Perfusion single-photon emission computed tomography/computed tomography scans were obtained at baseline (n = 81), midtreatment (n = 74), 3 months post-treatment (n = 51), and 1 year post-treatment (n = 26) and retrospectively analyzed. Patients were treated with conventionally fractionated RT or stereotactic body RT. Normalized perfusion single-photon emission computed tomography voxel intensity was used as a surrogate for local lung function. A patient-specific logistic model was applied to each individual patient's dose-function response to characterize functional reduction at each imaging time point. Patient-specific model parameters were averaged to create a population-level logistic dose-response model.

RESULTS

A significant longitudinal decrease in lung function was observed after RT by analyzing the voxelwise change in normalized perfusion intensity. Generated dose-function response models represent the expected voxelwise reduction in function, and the associated uncertainty, for an unknown patient receiving conventionally fractionated RT or stereotactic body RT. Differential treatment responses based on the functional status of the voxel at baseline suggest that initially higher functioning voxels are damaged at a higher rate than lower functioning voxels.

CONCLUSIONS

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

MRI-guided lung SBRT: Present and future developments

Stereotactic body radiotherapy (SBRT) is rapidly becoming an alternative to surgery for the treatment of early-stage non-small cell lung cancer patients. Lung SBRT is administered in a hypo-fractionated, conformal manner, delivering high doses to the target. To avoid normal-tissue toxicity, it is crucial to limit the exposure of nearby healthy organs-at-risk (OAR). Current image-guided radiotherapy strategies for lung SBRT are mostly based on X-ray imaging modalities. Although still in its infancy, magnetic resonance imaging (MRI) guidance for lung SBRT is not exposure-limited and MRI promises to improve crucial soft-tissue contrast. Looking beyond anatomical imaging, functional MRI is expected to inform treatment decisions and adaptations in the future. This review summarises and discusses how MRI could be advantageous to the different links of the radiotherapy treatment chain for lung SBRT: diagnosis and staging, tumour and OAR delineation, treatment planning, and inter- or intrafractional motion management. Special emphasis is placed on a new generation of hybrid MRI treatment devices and their potential for real-time adaptive radiotherapy.

Integration of PET/MR Hybrid Imaging into Radiation Therapy Treatment

Hybrid PET/MR imaging is in early development for treatment planning. This article briefly reviews research and clinical applications of PET/MR imaging in radiation oncology. With improvements in workflow, more specific tracers, and fast and robust acquisition protocols, PET/MR imaging will play an increasingly important role in better target delineation for treatment planning and have clear advantages in the evaluation of tumor response and in a better understanding of tumor heterogeneity. With advances in treatment delivery and the potential of integrating PET/MR imaging with research on radiomics for radiation oncology, quantitative and physiologic information could lead to more precise and personalized RT.

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

Introduction

4DCT‐ventilation is an exciting new imaging modality that uses 4DCT data to calculate lung‐function maps. Because 4DCTs are acquired as standard of care for lung cancer patients undergoing radiotherapy, 4DCT‐ventiltation provides functional information at no extra dosimetric or monetary cost to the patient. The development of clinical trials is underway to use 4DCT‐ventilation imaging to spare functional lung in patients undergoing radiotherapy. The purpose of this work was to perform a virtual trial using retrospective data to develop the practical aspects of a 4DCT‐ventilation functional avoidance clinical trial.

Methods

The study included 96 stage III lung cancer patients. A 4DCT‐ventilation map was calculated using the patient's 4DCT‐imaging, deformable registration, and a density‐change‐based algorithm. Clinical trial inclusion assessment used quantitative and qualitative metrics based on the patient's spatial ventilation profile. Clinical and functional plans were generated for 25 patients. The functional plan aimed to reduce dose to functional lung while meeting standard target and critical structure constraints. Standard and dose‐function metrics were compared between the clinical and functional plans.

Results

Our data showed that 69% and 59% of stage III patients have regional variability in function based on qualitative and quantitative metrics, respectively. Functional planning demonstrated an average reduction of 2.8 Gy (maximum 8.2 Gy) in the mean dose to functional lung.

Conclusions

Our work demonstrated that 60–70% of stage III patients would be eligible for functional planning and that a typical functional lung mean dose reduction of 2.8 Gy can be expected relative to standard clinical plans. These findings provide salient data for the development of functional clinical trials.

Thoracic CT-MRI coregistration for regional pulmonary structure-function measurements of obstructive lung disease

PURPOSE

Recent pulmonary imaging research has revealed that in patients with chronic obstructive pulmonary disease (COPD) and asthma, structural and functional abnormalities are spatially heterogeneous. This novel information may help optimize treatment in individual patients, monitor interventional efficacy, and develop new treatments. Moreover, by automating the measurement of regional biomarkers for the 19 different anatomical lung segments, there is an opportunity to embed imaging biomarkers into clinically acceptable clinical workflows and improve lung disease clinical care. Therefore, to exploit the regional structure-function information provided by thoracic imaging, and as a first step toward this goal, our objective was to develop a fully automated registration pipeline for thoracic x-ray computed tomography (CT) and inhaled gas functional magnetic resonance imaging (MRI) whole lung and segmental structure-function biomarkers.

METHODS

Thirty-five patients including 15 severe, poorly controlled asthmatics and 20 COPD patients [classified according to the global initiative for chronic obstructive lung disease (GOLD) criteria)] provided written informed consent to a study protocol approved by Health Canada and underwent pulmonary function tests, MRI, and CT during a single 2-hour visit. Using this diverse patient dataset, we developed and evaluated a joint deformable registration approach to simultaneously coregister CT with both ¹ H and ³ He MRI by enforcing the similarity of the deformation fields from the two individual registrations. We derived a simpler model that was equivalent to the original challenging optimization problem through variational analysis and the simpler model gave rise to an efficient numerical solver that was parallelized on a graphics processing unit. The coregistered CT-³ He MRI and whole lung/segmental lung masks were used to generate whole lung and segmental ³ He MRI ventilation defect percent (VDP). To estimate fiducial localization reproducibility, a single observer manually identified 109 pairs of CT and ³ He MRI fiducials for 35 patient images on five separate occasions and determined the fiducial localization error (FLE). CT-³ He MRI registration accuracy was evaluated using the target registration error (TRE). Whole lung VDP generated using the algorithm was compared with VDP generated using a previously validated semiautomated approach and computational efficiency was evaluated using run time.

RESULTS

In 35 patients including 15 with severe asthma and 20 with COPD, mean forced expiratory volume in 1 s (FEV₁ ) was 63±24%_pred and FEV₁ /forced vital capacity (FVC) was 54 ± 17%. FLE was 0.16 mm and 0.34 mm for ³ He MRI and CT, respectively. TRE was 4.5 ± 2.0 mm, 4.0 ± 1.7 mm, 4.8 ± 2.3 mm for asthma, COPD GOLD II, and GOLD III groups, respectively, with a mean of 4.4 ± 2.0 mm for the entire dataset. TRE was significantly improved for joint CT-¹ H/³ He MRI registration compared with CT-¹ H MRI rigid registration (P < 0.0001). Whole lung VDP generated using the pipeline was not significantly different (P = 0.37) compared to a semiautomated method with which it was strongly correlated (r = 0.93, P < 0.0001). The fully automated pipeline required 11 ± 0.4 min to generate whole lung and segmental VDP.

CONCLUSIONS

For a diverse group of patients with COPD and asthma, whole lung and segmental VDP was measured using an automated lung image analysis pipeline which provides a way to incorporate lung functional biomarkers into clinical research and patient care.

Magnetic resonance imaging with hyperpolarized agents: methods and applications

In the past decade, hyperpolarized (HP) contrast agents have been under active development for MRI applications to address the twin challenges of functional and quantitative imaging. Both HP helium (³He) and xenon (¹²⁹Xe) gases have reached the stage where they are under study in clinical research. HP ¹²⁹Xe, in particular, is poised for larger scale clinical research to investigate asthma, chronic obstructive pulmonary disease, and fibrotic lung diseases. With advances in polarizer technology and unique capabilities for imaging of ¹²⁹Xe gas exchange into lung tissue and blood, HP ¹²⁹Xe MRI is attracting new attention. In parallel, HP ¹³C and ¹⁵N MRI methods have steadily advanced in a wide range of pre-clinical research applications for imaging metabolism in various cancers and cardiac disease. The HP [1-¹³C] pyruvate MRI technique, in particular, has undergone phase I trials in prostate cancer and is poised for investigational new drug trials at multiple institutions in cancer and cardiac applications. This review treats the methodology behind both HP gases and HP ¹³C and ¹⁵N liquid state agents. Gas and liquid phase HP agents share similar technologies for achieving non-equilibrium polarization outside the field of the MRI scanner, strategies for image data acquisition, and translational challenges in moving from pre-clinical to clinical research. To cover the wide array of methods and applications, this review is organized by numerical section into (1) a brief introduction, (2) the physical and biological properties of the most common polarized agents with a brief summary of applications and methods of polarization, (3) methods for image acquisition and reconstruction specific to improving data acquisition efficiency for HP MRI, (4) the main physical properties that enable unique measures of physiology or metabolic pathways, followed by a more detailed review of the literature describing the use of HP agents to study: (5) metabolic pathways in cancer and cardiac disease and (6) lung function in both pre-clinical and clinical research studies, concluding with (7) some future directions and challenges, and (8) an overall summary.

Optimizing global liver function in radiation therapy treatment planning

Liver stereotactic body radiation therapy (SBRT) patients differ in both pre-treatment liver function (e.g. due to degree of cirrhosis and/or prior treatment) and radiosensitivity, leading to high variability in potential liver toxicity with similar doses. This work investigates three treatment planning optimization models that minimize risk of toxicity: two consider both voxel-based pre-treatment liver function and local-function-based radiosensitivity with dose; one considers only dose. Each model optimizes different objective functions (varying in complexity of capturing the influence of dose on liver function) subject to the same dose constraints and are tested on 2D synthesized and 3D clinical cases. The normal-liver-based objective functions are the linearized equivalent uniform dose ([Formula: see text]) (conventional '[Formula: see text] model'), the so-called perfusion-weighted [Formula: see text] ([Formula: see text]) (proposed 'fEUD model'), and post-treatment global liver function (GLF) (proposed 'GLF model'), predicted by a new liver-perfusion-based dose-response model. The resulting [Formula: see text], fEUD, and GLF plans delivering the same target [Formula: see text] are compared with respect to their post-treatment function and various dose-based metrics. Voxel-based portal venous liver perfusion, used as a measure of local function, is computed using DCE-MRI. In cases used in our experiments, the GLF plan preserves up to [Formula: see text] more liver function than the fEUD ([Formula: see text]) plan does in 2D cases, and up to [Formula: see text] in 3D cases. The GLF and fEUD plans worsen in [Formula: see text] of functional liver on average by 1.0 Gy and 0.5 Gy in 2D and 3D cases, respectively. Liver perfusion information can be used during treatment planning to minimize the risk of toxicity by improving expected GLF; the degree of benefit varies with perfusion pattern. Although fEUD model optimization is computationally inexpensive and often achieves better GLF than [Formula: see text] model optimization does, the GLF model directly optimizes a more clinically relevant metric and can further improve fEUD plan quality.

Magnetic resonance imaging in lung: a review of its potential for radiotherapy

MRI has superior soft-tissue definition compared with existing imaging modalities in radiation oncology; this has the added benefit of functional as well as anatomical imaging. This review aimed to evaluate the current use of MRI for lung cancer and identify the potential of a MRI protocol for lung radiotherapy (RT). 30 relevant studies were identified. Improvements in MRI technology have overcome some of the initial limitations of utilizing MRI for lung imaging. A number of commercially available and novel sequences have shown image quality to be adequate for the detection of pulmonary nodules with the potential for tumour delineation. Quantifying tumour motion is also feasible and may be more representative than that seen on four-dimensional CT. Functional MRI sequences have shown correlation with flu-deoxy-glucose positron emission tomography (FDG-PET) in identifying malignant involvement and treatment response. MRI can also be used as a measure of pulmonary function. While there are some limitations for the adoption of MRI in RT-planning process for lung cancer, MRI has shown the potential to compete with both CT and PET for tumour delineation and motion definition, with the added benefit of functional information. MRI is well placed to become a significant imaging modality in RT for lung cancer.

Functional imaging of the lungs with gas agents

This review focuses on the state-of-the-art of the three major classes of gas contrast agents used in magnetic resonance imaging (MRI)-hyperpolarized (HP) gas, molecular oxygen, and fluorinated gas--and their application to clinical pulmonary research. During the past several years there has been accelerated development of pulmonary MRI. This has been driven in part by concerns regarding ionizing radiation using multidetector computed tomography (CT). However, MRI also offers capabilities for fast multispectral and functional imaging using gas agents that are not technically feasible with CT. Recent improvements in gradient performance and radial acquisition methods using ultrashort echo time (UTE) have contributed to advances in these functional pulmonary MRI techniques. The relative strengths and weaknesses of the main functional imaging methods and gas agents are compared and applications to measures of ventilation, diffusion, and gas exchange are presented. Functional lung MRI methods using these gas agents are improving our understanding of a wide range of chronic lung diseases, including chronic obstructive pulmonary disease, asthma, and cystic fibrosis in both adults and children.

A Comparison of Lumpectomy Cavity Delineations Between Use of Magnetic Resonance Imaging and Computed Tomography Acquired With Patient in Prone Position for Radiation Therapy Planning of Breast Cancer

PURPOSE

To compare lumpectomy cavity (LC) and planning target volume (PTV) delineated with the use of magnetic resonance imaging (MRI) and computed tomography (CT) and to examine the possibility of replacing CT with MRI for radiation therapy (RT) planning for breast cancer.

METHODS AND MATERIALS

MRI and CT data were acquired for 15 patients with early-stage breast cancer undergoing lumpectomy during RT simulation in prone positions, the same as their RT treatment positions. The LCs were delineated manually on both CT (LC-CT) and MRI acquired with 4 sequences: T1, T2, STIR, and DCE. Various PTVs were created by expanding a 15-mm margin from the corresponding LCs and from the union of the LCs for the 4 MRI sequences (PTV-MRI). Differences were measured in terms of cavity visualization score (CVS) and dice coefficient (DC).

RESULTS

The mean CVSs for T1, T2, STIR, DCE, and CT defined LCs were 3.47, 3.47, 3.87, 3.50. and 2.60, respectively, implying that the LC is mostly visible with a STIR sequence. The mean reductions of LCs from those for CT were 22%, 43%, 36%, and 17% for T1, T2, STIR, and DCE, respectively. In 14 of 15 cases, MRI (union of T1, T2, STIR, and DCE) defined LC included extra regions that would not be visible from CT. The DCs between CT and MRI (union of T1, T2, STIR, and DCE) defined volumes were 0.65 ± 0.20 for LCs and 0.85 ± 0.06 for PTVs. There was no obvious difference between the volumes of PTV-MRI and PTV-CT, and the average PTV-STIR/PTV-CT volume ratio was 0.83 ± 0.23.

CONCLUSIONS

The use of MRI improves the visibility of LC in comparison with CT. The volumes of LC and PTV generated based on a MRI sequence are substantially smaller than those based on CT, and the PTV-MRI volumes, defined by the union of T1, T2, STIR, and DCE, were comparable with those of PTV-CT for most of the cases studied.