Evaluation of template matching for tumor motion management with cine-MR images in lung cancer patients.

PURPOSE: Accurate determination of tumor position is crucial for successful application of motion compensated radiotherapy in lung cancer patients. This study tested the performance of an automated template matching algorithm in tracking the tumor position on cine-MR images by examining the tracking error and further comparing the tracking error to the interoperator variability of three human reviewers. METHODS: Cine-MR images of 12 lung cancer patients were analyzed. Tumor positions were determined both automatically with template matching and manually by a radiation oncologist and two additional reviewers trained by the radiation oncologist. Performance of the automated template matching was compared against the ground truth established by the radiation oncologist. Additionally, the tracking error of template matching, defined as the difference in the tumor positions determined with template matching and the ground truth, was investigated and compared to the interoperator variability for all patients in the anterior-posterior (AP) and superior-inferior (SI) directions, respectively. RESULTS: The median tracking error for ten out of the 12 patients studied in both the AP and SI directions was less than 1 pixel (= 1.95 mm). Furthermore, the median tracking error for seven patients in the AP direction and nine patients in the SI direction was less than half a pixel (= 0.975 mm). The median tracking error was positively correlated with the tumor motion magnitude in both the AP (R = 0.55, p = 0.06) and SI (R = 0.67, p = 0.02) directions. Also, a strong correlation was observed between tracking error and interoperator variability (y = 0.26 + 1.25x, R = 0.84, p < 0.001) with the latter larger. CONCLUSIONS: Results from this study indicate that the performance of template matching is comparable with or better than that of manual tumor localization. This study serves as preliminary investigations towards developing online motion tracking techniques for hybrid MRI-Linac systems. Accuracy of template matching makes it a suitable candidate to replace the labor intensive manual tumor localization for obtaining the ground truth when testing other motion management techniques.

Evaluation of fractional regional ventilation using 4D-CT and effects of breathing maneuvers on ventilation.

PURPOSE: Current implementations of methods based on Hounsfield units to evaluate regional lung ventilation do not directly incorporate tissue-based mass changes that occur over the respiratory cycle. To overcome this, we developed a 4-dimensional computed tomography (4D-CT)-based technique to evaluate fractional regional ventilation (FRV) that uses an individualized ratio of tidal volume to end-expiratory lung volume for each voxel. We further evaluated the effect of different breathing maneuvers on regional ventilation. The results from this work will help elucidate the relationship between global and regional lung function. METHODS AND MATERIALS: Eight patients underwent 3 sets of 4D-CT scans during 1 session using free-breathing, audiovisual guidance, and active breathing control. FRV was estimated using a density-based algorithm with mass correction. Internal validation between global and regional ventilation was performed by use of the imaging data collected during the use of active breathing control. The impact of breathing maneuvers on FRV was evaluated comparing the tidal volume from 3 breathing methods. RESULTS: Internal validation through comparison between the global and regional changes in ventilation revealed a strong linear correlation (slope of 1.01, R2 of 0.97) between the measured global lung volume and the regional lung volume calculated by use of the "mass corrected" FRV. A linear relationship was established between the tidal volume measured with the automated breathing control system and FRV based on 4D-CT imaging. Consistently larger breathing volumes were observed when coached breathing techniques were used. CONCLUSIONS: The technique presented improves density-based evaluation of lung ventilation and establishes a link between global and regional lung ventilation volumes. Furthermore, the results obtained are comparable with those of other techniques of functional evaluation such as spirometry and hyperpolarized-gas magnetic resonance imaging. These results were demonstrated on retrospective analysis of patient data, and further research using prospective data is under way to validate this technique against established clinical tests.

Improving temporal resolution of pulmonary perfusion imaging in rats using the partially separable functions model.

Dynamic contrast-enhanced MRI (or DCE-MRI) is a useful tool for measuring blood flow and perfusion, and it has found use in the study of pulmonary perfusion in animal models. However, DCE-MRI experiments are difficult in small animals such as rats. A recently developed method known as Interleaved Radial Imaging and Sliding window-keyhole (IRIS) addresses this problem by using a data acquisition scheme that covers (k,t)-space with data acquired from multiple bolus injections of a contrast agent. However, the temporal resolution of IRIS is limited by the effects of temporal averaging inherent in the sliding window and keyhole operations. This article describes a new method to cover (k,t)-space based on the theory of partially separable functions (PSF). Specifically, a sparse sampling of (k,t)-space is performed to acquire two data sets, one with high-temporal resolution and the other with extended k-space coverage. The high-temporal resolution training data are used to determine the temporal basis functions of the PSF model, whereas the other data set is used to determine the spatial variations of the model. The proposed method was validated by simulations and demonstrated by an experimental study. In this particular study, the proposed method achieved a temporal resolution of 32 msec.

Ventilation/perfusion imaging in a rat model of airway obstruction.

The global increase in asthma, chronic obstructive pulmonary disease, and other pulmonary diseases has stimulated interest in preclinical rat models of pulmonary disease. Imaging methods for study of these models is particularly appealing since the results can be readily translated to the clinical setting. Comprehensive understanding of lung function can be achieved by performing registered pulmonary ventilation and perfusion imaging studies in the same animal. While ventilation imaging has been addressed for small animals, quantitative pulmonary perfusion imaging has not been feasible until recently, with our proposed technique for quantitative perfusion imaging using multiple contrast-agent injections and a view-sharing radial imaging technique. Here, we combine the method with registered ventilation imaging using hyperpolarized (3)He in an airway obstruction rodent model. To our knowledge, this is the first comprehensive quantitative assessment of lung function in small animals at high spatial resolution. Standard deviation of the log (V/Q) is used as a quantitative biomarker to differentiate heterogeneity between the control and treatment group. The estimated value of the biomarker lies within the normal range of values reported in the literature. The biomarker that was extracted using the imaging technique described in this work showed statistically significant differences between the control rats and those with airway obstruction.

Quantitative analysis of hyperpolarized 3He ventilation changes in mice challenged with methacholine.

The capability to use high-resolution (3)He MRI to depict regional ventilation changes and airway narrowing in mice challenged with methacholine (MCh) offers the opportunity to gain new insights into the study of asthma. However, to fully exploit the value of this novel technique, it is important to move beyond visual inspection of the images toward automated and quantitative analysis. To address this gap, we describe a postprocessing approach to create ventilation difference maps to better visualize and quantify regional ventilation changes before and after MCh challenge. We show that difference maps reveal subtle changes in airway caliber, and highlight both focal and diffuse regional alterations in ventilation. Ventilation changes include both hypoventilation and compensatory areas of hyperventilation. The difference maps can be quantified by a histogram plot of the ventilation changes, in which the standard deviation increases with MCh dose (R(2) = 0.89). This method of analysis is shown to be more sensitive than simple threshold-based detection of gross ventilation defects.

A high-precision contrast injector for small animal x-ray digital subtraction angiography.

The availability of genetically altered animal models of human disease for basic research has generated great interest in new imaging methodologies. Digital subtraction angiography (DSA) offers an appealing approach to functional imaging in small animals because of the high spatial and temporal resolution, and the ability to visualize and measure blood flow. The micro-injector described here meets crucial performance parameters to ensure optimal vessel enhancement without significantly increasing the total blood volume or producing overlap of enhanced structures. The micro-injector can inject small, reproducible volumes of contrast agent at high flow rates with computer-controlled timing synchronized to cardiopulmonary activity. Iterative bench-top and live animal experiments with both rat and mouse have been conducted to evaluate the performance of this computer-controlled micro-injector, a first demonstration of a new device designed explicitly for the unique requirements of DSA in small animals. Injection protocols were optimized and screened for potential physiological impact. For the optimized protocols, we found that changes in the time-density curves for representative regions of interest in the thorax were due primarily to physiological changes, independent of micro-injector parameters.

Pulmonary perfusion imaging in the rodent lung using dynamic contrast-enhanced MRI.

With the development of various models of pulmonary disease, there is tremendous interest in quantitative regional assessment of pulmonary function. While ventilation imaging has been addressed to a certain extent, perfusion imaging for small animals has not kept pace. In humans and large animals perfusion can be assessed using dynamic contrast-enhanced (DCE) MRI with a single bolus injection of a gadolinium (Gd)-based contrast agent. But the method developed for the clinic cannot be translated directly to image the rodent due to the combined requirements of higher spatial and temporal resolution. This work describes a novel image acquisition technique staggered over multiple, repeatable bolus injections of contrast agent using an automated microinjector, synchronized with image acquisition to achieve dynamic first-pass contrast enhancement in the rat lung. This allows dynamic first-pass imaging that can be used to quantify pulmonary perfusion. Further improvements are made in the spatial and temporal resolution by combining the multiple injection acquisition method with Interleaved Radial Imaging and "Sliding window-keyhole" reconstruction (IRIS). The results demonstrate a simultaneous increase in spatial resolution (<200 mum) and temporal resolution (<200 ms) over previous methods, with a limited loss in signal-to-noise-ratio.

Retrospective distortion correction for 3D MR diffusion tensor microscopy using mutual information and Fourier deformations.

Magnetic resonance diffusion tensor imaging (DTI) can be complicated by distortions that contribute to errors in tissue characterization and loss of fine structures. This work presents a correction scheme based on retrospective registration via mutual information (MI), using Fourier transform (FT)-based deformations to enhance the reliability of the entropy-based image registration. The registration methodology is applied to correct distortions in 3D high-resolution DTI datasets, incorporating a complete set of affine deformations. The results demonstrate that the proposed methodology can consistently and significantly reduce the number of misregistered pixels, leading to marked improvement in the visualization of internal brain white matter (WM) structure via DTI. Post-registration analysis revealed that eddy-current effects cannot fully account for the observed image distortions. Combined, these findings support the non-model-based, postprocessing approach for correcting distortions, and demonstrate the advantages of combining FT-based deformations and MI registration to enhance the practical utility of DTI.