Browsing by Author "Rankine, Leith John"
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Item Open Access On the Utility of 129Xe Gas Exchange Magnetic Resonance Imaging for Assessing, Classifying, and Preventing Fibrotic Lung Diseases(2021) Rankine, Leith JohnPulmonary fibrosis is the process of lung tissue becoming damaged and scarred, losing its elastic and diffusive properties needed for proper lung function. This change in tissue structure can make it difficult to draw in a breath (ventilation) and cause a decrease in the amount of oxygen and carbon dioxide that can transfer between the alveoli and blood vessels (gas exchange). Therefore, the most common symptom of progressive pulmonary fibrosis is shortness of breath, or dyspnea. Pulmonary fibrosis can be caused by environmental pollutants, treatment-related toxicity from a drug or therapy, or interstitial lung diseases.
Regardless of its origin, pulmonary fibrosis can have devastating outcomes for patients. For example, the median survival for patients with idiopathic pulmonary fibrosis (IPF), an interstitial lung disease of unknown origin, is historically less than 3 years. For patients with IPF, the path of clinical decline is often sporadic and plagued with acute exacerbations and hospitalizations. Idiopathic pulmonary fibrosis currently affects between 100,000-200,000 people in the United States alone, and over a million worldwide. Unfortunately, the tools currently available to classify disease severity, determine prognosis, and assess disease progression or treatment response are simply inadequate. Patients with IPF exhibit distinct and unpredictable clinical trajectories, and a tool with the ability to predict these trajectories could improve targeted interventions. One such set of tools, pulmonary function tests (PFTs) can measure global ventilation and gas exchange, but have high variability and no spatial information. Another, high resolution computed tomography (HRCT), provides a 3D image, but function must be inferred from tissue density or structure, which comes with a number of limitations. A new tool that can spatially resolve and quantify regional pulmonary function could be invaluable in improving the clinical management of IPF.
In addition to fibrotic lung diseases, such as IPF, pulmonary fibrosis may also transpire as a treatment-related toxicity. Over 100,000 people per year in the U.S. will receive thoracic radiation therapy (RT) as treatment for cancer, putting them at risk for radiation-induced lung injury (RILI). Approximately 5-25% of patients that receive conventional thoracic RT develop clinically significant symptomatic radiation pneumonitis (RP), the acute form of RILI, causing patients to experience dyspnea, persistent coughing, pain, and fever. Radiation pneumonitis can lead to chronic radiation pulmonary fibrosis (RPF), or even result in death for an estimated 1-2% of patients. Current methods to assess RILI and grade RP rely on a clinical diagnosis and patient- and physician-reported symptoms. This leads to large variability in toxicity grading for thoracic RT clinical trials, hampering the effort to design treatments that reduce side effects. Further, a recently proposed treatment planning technique, “functional avoidance”, was designed to preserve pulmonary function and reduce the incidence or severity of RP by minimizing radiation dose to areas with high pulmonary function. However, clinically available tools can only measure ventilation or perfusion, neither of which are a true representation of end-to-end pulmonary gas exchange, a fact that may be limiting the potential effectiveness of this technique. Once again, a tool that can spatially resolve and quantify regional pulmonary function could offer improvements to functional avoidance treatment planning and the prevention of RP. If such a tool was sensitive enough to detect radiation-induced changes in function, this could reduce the variability in the current guidelines for the toxicity grading of RP.
In this work, we investigated non-invasive hyperpolarized-129Xe gas exchange magnetic resonance imaging (MRI), which acquires 3D maps of lung ventilation, alveolar barrier uptake, and capillary red blood cell (RBC) transfer. This unique tool can quantify and spatially resolve the gas exchange capabilities of a human lung in a single 15-second breath-hold MRI acquisition. Currently limited to research studies, the clinical utility of this new technique is yet to be firmly established. Therefore, the objectives of this dissertation are to: 1) identify metrics from baseline 129Xe gas exchange MRI that are predictive of clinical outcomes in IPF; 2) quantify the extent to which ventilation and gas exchange distributions are spatially correlated, and the effect that this may have on functional avoidance treatment planning; and 3) establish a relationship between regional changes in gas exchange and local radiation therapy dose in RT patients.
First, we sought to identify 129Xe gas exchange MRI features in IPF patients, and establish 129Xe-based imaging metrics to be used for classifying patients into groups, as detailed in Chapter 3. As previously mentioned, subjects with IPF exhibit distinct clinical trajectories that are difficult to predict prospectively using currently available means. We acquired baseline 129Xe MRI for 12 newly diagnosed IPF patients, and prospectively grouped these subjects based on percentage-volumes of abnormal barrier uptake and RBC transfer, using thresholds we derived from 129Xe MRI of a healthy subject cohort (N=13). We then followed these subjects for 36 months and analyzed the clinically acquired PFT and outcome data. We examined the differences in clinical outcomes and temporal changes in PFTs based on these groupings. We also observed changes in 129Xe metrics over time for those subjects with serial time-point imaging. Our results indicated that 129Xe MRI characteristics appear to group disease in a way that was distinct from traditional clinical or radiographic approaches; in particular, excessive volumes of lung with elevated barrier uptake and reduced RBC transfer were associated with poor clinical outcome. This study provided preliminary evidence that IPF patients can be classified by 129Xe MRI, and that this classification may predict clinical outcomes. These results open the door for larger, prospective studies using 129Xe MRI in IPF. More generally, and perhaps most importantly, this work established 129Xe gas exchange MRI as a prognostic biomarker in fibrotic lung disease.
Our results from Chapter 3 established that, when accompanied by an increase in 129Xe MRI barrier signal, which is a hallmark characteristic of IPF, a reduction in RBC transfer signal is associated with clinical decline in IPF patients. Extending this work to fibrotic lung processes beyond IPF, we hypothesize that the RBC signal is an important marker for regional lung function, and preserving and protecting the volumes of lung exhibiting “healthy” RBC transfer could translate to preservation of overall pulmonary function. In RT treatment planning, the concept of avoiding excess radiation dose to highly functioning areas of lung is not new; “functional avoidance” (or “functional guidance”) has previously been proposed and implemented using both perfusion and ventilation imaging. In Chapter 4, however, we establish 129Xe gas exchange MRI as a unique marker of regional lung function compared to ventilation, which is the most popular functional avoidance planning technique due to its “free” derivation from the 4 dimensional (4D) CT acquired during the RT planning process. In this chapter, we examined the correlation of ventilation and RBC signals in a healthy volunteer cohort and a handful of thoracic RT patients. Our results indicated a weak-to-moderate correlation, which determined that the RBC signal was indeed spatially unique from the ventilation signal, but did not explore the extent to which this affects functional plans created using one or the other (ventilation or RBC gas exchange) for guidance. Therefore, Chapter 5 details our study of 11 patients that received RT for treatment of lung cancer in which we re-planned these patients’ clinically approved plans using ventilation and RBC gas exchange functional information. This study established a methodology for 129Xe gas exchange MRI functional avoidance planning, and the results showed that, for some RP-predictive metrics, gas exchange-guided planning produced significantly different dose distributions than ventilation-guided planning.
Finally, in Chapter 6 we focused on furthering our understanding of RILI in RT patients, and examined the sensitivity of 129Xe MRI for detecting pulmonary radiation damage. In this study, we quantified changes in regional gas exchange as a function of radiation dose for six patients undergoing conventional radiotherapy for lung cancer. As briefly described earlier, RT of tumors in or around the thorax is known to cause regional lung injury, with the acute injury phase symptoms of RP typically emerging 1-6 months after RT. Previous studies using SPECT have established that perfusion changes are dose-dependent and evident at 3-6 months after RT. Therefore, we acquired 129Xe MRI scans before RT and at 3- and 6-months after RT to evaluate the progression of the acute inflammatory phase of RILI, as it relates to changes in regional gas exchange. We co-registered the MRI data to the RT treatment planning data, to evaluate regional changes in ventilation, barrier uptake, and RBC transfer, as a function of delivered radiation dose. Our results indicated that the barrier uptake signal increased with radiation doses above 20 Gy, and that the magnitude of change was dose-dependent. This potentially confirms increased barrier uptake as a marker of regional inflammation. In addition, we observed that the RBC transfer signal decreased with radiation doses above 35 Gy, possibly quantifying a reduction in overall gas exchange properties of the tissue at these high doses. Our observations of this dose-dependent relationship are consistent with historic ventilation and perfusion data, and gives rise to the idea that 129Xe MRI may be a powerful tool in furthering understanding of the subclinical progression of RILI and potentially other causes of lung fibrosis.
Overall, we have demonstrated the potential of 129Xe-MRI gas exchange to 1) improve disease classification in IPF, 2) add unique functional information to the planning of thoracic radiation treatments, and 3) assess RT-associated subclinical changes in regional lung function. We have established a strong foundation for this non-invasive technology, enabling further development and validation of these MRI biomarkers in larger studies. The work presented herein marks the beginning of a journey to advance our understanding of fibrotic progression in IPF, RILI, and all other causes of pulmonary fibrosis.
Item Open Access The Effects of PET Reconstruction Parameters on Radiotherapy Response Assessment and an Investigation of SUV-peak Sampling Parameters(2013) Rankine, Leith JohnPurpose: Our primary goal was to examine the effect of PET image reconstruction parameters on baseline and early-treatment FDG-PET/CT quantitative imaging. Early-treatment changes in tumor metabolism in primary tumor and nodes can potentially determine if the patient is responding to therapy, but this assessment can change based on the reconstruction parameters. We investigated the effect of the following reconstruction parameters: number of Ordered-Subset-Expectation-Maximization (OSEM) iterations, post-reconstruction smoothing, and quantitative metrics (SUV-max, SUV-mean, SUV-peak).
A concurrent investigation explored in detail the sampling parameters of SUV-peak by way of a Monte Carlo digital phantom study. SUV-peak was proposed as a compromise between SUV-max and SUV-mean, in hope to retain key attractive features of these two metrics (inter-physician independence of SUV-max, noise-averaging of SUV-mean) but reduce unwanted errors (noise dependence of SUV-max, contour-dependence of SUV-mean). Sampling parameters have vaguely been defined, in particular, the scanning resolution (i.e. 1 voxel, 1/2 voxel, 1/4 voxel, etc.) of the SUV-peak spherical ROI . We examined the role that partial-voxel scanning plays in tumor SUV recovery in both noise-free and realistic OS-EM noise environments.
Materials and Methods: The response assessment investigation involved 19 patients on an IRB-approved study who underwent 2 baseline PET scans (mean-separation = 11 days) prior to chemoradiotherapy (70 Gy, 2 Gy/fraction). An intra-treatment PET scan was performed early in the course of therapy (10-20 Gy, mean = 14 Gy). The images were reconstructed with varying OS-EM iterations (1-12) and Gaussian post-smoothing (0-7 mm). Patients were analyzed in two separate groups, distinguished by the PET/CT scanner used to acquire data: (1) GE Discovery STE; and (2) Siemens Biograph mCT. For each combination of iterations and smoothing, Bland-Altman analysis was applied to quantitative metrics (SUV-max, SUV-mean, SUV-peak) from the baseline scans to evaluate metabolic variability (repeatability, R = 1.96&sigma). The number and extent of early treatment changes that were significant, i.e., exceeding repeatability, was assessed.
An original SUV-peak algorithm was developed, which measures SUV-max and SUV-peak for as small as 1/32 voxel scanning. Two rounds of digital phantoms were generated for the SUV-peak investigation. First, 10,000 spherical tumors were generated at a random matrix location for each diameter 1-4 cm and smoothed with an isotropic Gaussian, FWHM = 0.8 cm, then evaluated using the SUV-peak algorithm. Next, realistic body-sized phantoms were generated with background activity, and 1,000 spherical tumors of activity 4 time the background for each diameter (1-4cm) were placed inside (8 tumors per phantom, location randomized within certain constraints). These images received realistic corrections in projection space for attenuation, spatial resolution, and noise, were reconstructed with an in-house OS-EM algorithm, and then assessed using the SUV-peak algorithm. The mean recovered activity above background and its coefficient of variation were calculated for all metrics for each tumor size, for both simulations. For the realistic noise simulation, various levels of Gaussian smoothing was applied post-reconstruction, the effects summarized in plots showing coefficient of variation vs. mean recovered activity above background - a comparison of the effectiveness of SUV-max and SUV-peak.
Results: For the GE Discovery STE 2D cases averaged over all metrics (SUV-max, SUV-mean, SUV-peak) and structures (GTV, LN), repeatability, R, improved with increasing smoothing and decreasing iterations. Individually, SUV-mean repeatability was less affected by the number of iterations, but demonstrated the same relationship with smoothing. SUV-mean outperformed SUV-max and SUV-peak with regards to the number of cases exceeding repeatability, N. Considering R, N, and the sum of relative metric change outside repeatability, &Omega, averaged over all metrics and all structures, and normalized, several combinations of reconstruction parameters produced five optimal combinations above set thresholds: 1 iteration with 0.1-3.0 mm smoothing; and 2 iterations with 2.0-3.0 mm smoothing. Current GE 2D reconstruction protocol for HN cases uses 2 iterations and 3.0 mm post-smoothing, which lies on the edge, but within these recommendations.
The relationship between repeatability and number of iterations for the 3D cases was more complex; SUV-max demonstrated the best repeatability with 2 iterations, with both SUV-mean and SUV-peak reaching the best repeatability with 4 iterations. The same dependence on smoothing was noted, i.e. increased smoothing gives lover (desirable) repeatability. SUV-mean once again outperformed SUV-max and SUV-peak with regards to the number of cases exceeding repeatability, N. The calculations of N and &Omega averaged over all metrics were limited severely by the low number of cases, damaging the statistical significance of the following recommendation. Three optimal combinations with averaged and normalized R, N, &Omega, above a set threshold are recommended as most effective reconstruction parameter combinations: 4 iterations with 2.0-4.0 mm smoothing. Current Siemens 3D reconstruction protocol for HN cases uses 4 iterations and 3.0 mm post-smoothing, which lies within these recommended parameters. However, no statistically significant conclusions could be drawn from this analysis for this scanner, and performing similar data analysis on a larger patient pool is proposed.
The minimum spherical tumor diameter required for full recovery was 3.0-3.5 cm for SUV-peak, and 2.5-3.0 cm for SUV-max. SUV-max was found to overestimate the recovered value of tumors by up to 46% (vs. 10% for SUV-peak); above the minimum diameter for full recovery, SUV-peak values were significantly closer to actual tumor activity. Considering only the realistic noise tumors, the coefficient of variation for SUV-max ranged from 5.5-17.7%, whereas for SUV-peak these values were lower, 2.7-13.2%. Partial-voxel scanning did not substantially affect the coefficient of variation (<0.2%). Comparison of coefficient of variation vs. mean recovered value demonstrated that SUV-max with additional Gaussian smoothing outperforms SUV-peak by up to 0.8% for 1 cm tumors and 0.2% for 4 cm tumors. Other tumor sizes showed little difference between the two metrics.
Conclusion: For patients scanned on the GE Discovery STE using the HN protocol (2D acquisition mode), images reconstructed for quantitative analysis may benefit from a low number of OS-EM iterations (≤ 2). Some post-reconstruction smoothing proved to be beneficial (1.0 mm ≤ FWHM ≤ 3.0 mm), however, over-smoothing for the sake of more qualitatively appealing images or improved image quality metric (e.g. SNR, CNR) may prove detrimental to quantitative response assessment analysis. Our results for the Siemens Biograph mCT using the HN protocol (3D acquisition mode) demonstrated favor towards 4 iterations and limited range of smoothing (2.0 mm ≤ FWHM ≤ 4.0 mm). These results are statistically limited, further cases are necessary for any conclusive recommendations on reconstruction parameters.
SUV-peak was shown to reduce uncertainties associated with quantitative PET image analysis when compared directly to SUV-max. Above the minimum tumor diameter required for full recovery, SUV-peak also provides a better estimate of the actual tumor activity. However, initial comparisons of SUV-peak and SUV-max over various levels of additional Gaussian smoothing found SUV-max more favorable. Partial-voxel scanning of SUV-peak did not reduce the metric's coefficient of variation in images with realistic noise. Therefore, a phantom investigation is proposed to compare SUV-peak and SUV-max of real scanned images with various levels of post-smoothing, which may conclusively eliminate the need for SUV-peak.