Four-dimensional image registration for image-guided radiotherapy.

PURPOSE: Newly emerged four-dimensional (4D) imaging techniques such as 4D-computed tomography (CT), 4D-cone beam CT, 4D-magnetic resonance imaging, and 4D-positron emission tomography are effective tools to reveal the spatiotemporal details of patients' anatomy. To use the 4D data acquired under different conditions or using different modalities, an algorithm for registering 4D images must be in place. We developed an automated 4D-4D registration method to take advantage of 4D information. METHODS AND MATERIALS: We used 4D-4D matching to find the appropriate three-dimensional anatomy in the fixed image for each phase of the moving image and spatially register them. A search algorithm was implemented to simultaneously find the best phase and spatial match of two 4D inputs. An interpolation scheme capable of deriving an image set based on temporally adjacent three-dimensional data sets was developed to deal with the situation in which the discrete temporal points of the two inputs do not coincide or correspond. RESULTS: In a phantom study, our technique was able to reproduce the known "ground truth" with high spatial fidelity. The technique regenerated all deliberately introduced "missing" three-dimensional images at different phases of the input using temporal interpolation. In the registration of gated-magnetic resonance imaging and 4D-CT, the algorithm was able to select the appropriate CT phase. The technique was also able to register 4D-CT with 4D-cone beam CT and two 4D-CT scans acquired at different times. A spatial accuracy of <3 mm was achieved in 98% of voxels in all cases. CONCLUSION: Automated 4D-4D registration can find the best possible spatiotemporal match between two 4D data sets and is useful for image-guided radiotherapy applications.

Quantification of motion of different thoracic locations using four-dimensional computed tomography: implications for radiotherapy planning.

PURPOSE: To assess the respiratory motion of different thoracic nodal locations and its dependence on the presence of enlarged nodes; to assess the respiratory motion of different parenchymal tumor locations; and to determine the appropriate margins to cover the respiratory motion of targets at these locations. METHODS AND MATERIALS: We reviewed the four-dimensional computed tomography scans of 20 patients with thoracic tumors treated at our institution. The motion of four central thoracic locations (aortic arch, carina, and bilateral hila), parenchymal tumor locations (upper vs. lower, and anterior vs. middle vs. posterior thorax), and bilateral diaphragmatic domes was measured. RESULTS: For the central thoracic locations, the largest motion was in the superoinferior (SI) dimension (>5 mm for bilateral hila and carina, but <4 mm for aortic arch). No significant difference was found in the motion of these locations in the absence or presence of enlarged nodes. For parenchymal tumors, upper tumors exhibited smaller SI motion than did lower tumors (3.7 vs. 10.4 mm, p = 0.029). Similarly, anterior tumors exhibited smaller motion than did posterior tumors in both the SI (4.0 vs. 8.0 mm, p = 0.013) and lateral (2.8 vs. 4.6 mm, p = 0.045) directions. The margins that would be needed to encompass the respiratory motion of each of the evaluated locations in 95% of patients were tabulated and range from 3.4 to 37.2 mm, depending on the location and direction. CONCLUSIONS: The results of our study have provided data for appropriate site-specific internal target volume expansion that could be useful in the absence of four-dimensional computed tomography-based treatment planning. However, generalizing the results from a small patient population requires discretion.

Impact of integrated PET/CT on variability of target volume delineation in rectal cancer.

Several studies have demonstrated substantial variability among individual radiation oncologists in defining target volumes using computed tomography (CT). The objective of this study was to determine the impact of combined positron emission tomography and computed tomography (PET/CT) on inter-observer variability of target volume delineation in rectal cancer. We also compared the relative concordance of two PET imaging tracers, 18F-fluorodeoxyglucose (FDG) and 18F-fluorodeoxythymidine (FLT), against conventional computed tomography (CT). Six consecutive patients with locally advanced rectal cancer were enrolled onto an institutional protocol involving preoperative chemoradiotherapy and correlative studies including FDG- and FLT-PET scans acquired in the treatment position. Using these image data sets, four radiation oncologists independently delineated primary and nodal gross tumor volumes (GTVp and GTVn) for a hypothetical boost treatment. Contours were first defined based on CT alone with observers blinded to the PET images, then based on combined PET/CT. An inter-observer similarity index (SI), ranging from a value of 0 for complete disagreement to 1 for complete agreement of contoured voxels, was calculated for each set of volumes. For primary gross tumor volume (GTVp), the difference in estimated SI between CT and FDG was modest (CT SI = 0.77 vs. FDG SI = 0.81), but statistically significant (p = 0.013). The SI difference between CT and FLT for GTVp was also slight (FLT SI = 0.80) and marginally non-significant (p < 0.082). For nodal gross tumor volume, (GTVn), SI was significantly lower for CT based volumes with an estimated SI of 0.22 compared to an estimated SI of 0.70 for FDG-PET/CT (p < 0.0001) and an estimated SI of 0.70 for FLT-PET/CT (p < 0.0001). Boost target volumes in rectal cancer based on combined PET/CT results in lower inter-observer variability compared with CT alone, particularly for nodal disease. The use of FDG and FLT did not appear to be different from this perspective.

Quantum dynamics of an excited alkali atom in a noble gas cluster: lithium attached to a helium cluster.

An alkali atom-noble gas cluster system is considered as a model for solvation effects in optical spectra, within a quantum-classical description based on the density operator of a many-atom system and its partial Wigner transform. This leads to an eikonal-time-dependent molecular orbital treatment suitable for a time-dependent description of the coupling of light emission and atom dynamics in terms of the time-dependent electric dipole of the whole system. As an application, we consider an optically excited lithium atom as the dopant in a helium cluster at 0.5 K. We describe the motions of the excited Li atom interacting with a cluster of He atoms and calculate the time-dependent electric dipole of the Li-He(99) system during the dynamics. The electronic Hamiltonian is taken as a sum of three-body Li-He diatomic potentials including electronic polarization and repulsion, with l-dependent atomic pseudopotentials for Li and He, while we use a modified pair potential for He-He. The calculations involve the coupling of 12 quantum states with 300 classical degrees of freedom. We present results for the dynamics and spectra of a Li atom interacting with a model cluster surface of He atoms and also interacting with a droplet of He. We have found that the Li atom is attracted or repulsed from the He surface, depending on the orientation of its 2p orbitals. The spectra and dynamics of Li inside and at the surface of a cluster are found to be strongly dependent on its electronic states, its velocity direction, and whether light is present during emission or not.

Reducing respiratory motion artifacts in positron emission tomography through retrospective stacking.

Respiratory motion artifacts in positron emission tomography (PET) imaging can alter lesion intensity profiles, and result in substantially reduced activity and contrast-to-noise ratios (CNRs). We propose a corrective algorithm, coined "retrospective stacking" (RS), to restore image quality without requiring additional scan time. Retrospective stacking uses b-spline deformable image registration to combine amplitude-binned PET data along the entire respiratory cycle into a single respiratory end point. We applied the method to a phantom model consisting of a small, hot vial oscillating within a warm background, as well as to 18FDG-PET images of a pancreatic and a liver patient. Comparisons were made using cross-section visualizations, activity profiles, and CNRs within the region of interest. Retrospective stacking was found to properly restore the lesion location and intensity profile in all cases. In addition, RS provided CNR improvements up to three-fold over gated images, and up to five-fold over ungated data. These phantom and patient studies demonstrate that RS can correct for lesion motion and deformation, while substantially improving tumor visibility and background noise.

Model-based image reconstruction for four-dimensional PET.

Positron emission tonography (PET) is useful in diagnosis and radiation treatment planning for a variety of cancers. For patients with cancers in thoracic or upper abdominal region, the respiratory motion produces large distortions in the tumor shape and size, affecting the accuracy in both diagnosis and treatment. Four-dimensional (4D) (gated) PET aims to reduce the motion artifacts and to provide accurate measurement of the tumor volume and the tracer concentration. A major issue in 4D PET is the lack of statistics. Since the collected photons are divided into several frames in the 4D PET scan, the quality of each reconstructed frame degrades as the number of frames increases. The increased noise in each frame heavily degrades the quantitative accuracy of the PET imaging. In this work, we propose a method to enhance the performance of 4D PET by developing a new technique of 4D PET reconstruction with incorporation of an organ motion model derived from 4D-CT images. The method is based on the well-known maximum-likelihood expectation-maximization (ML-EM) algorithm. During the processes of forward- and backward-projection in the ML-EM iterations, all projection data acquired at different phases are combined together to update the emission map with the aid of deformable model, the statistics is therefore greatly improved. The proposed algorithm was first evaluated with computer simulations using a mathematical dynamic phantom. Experiment with a moving physical phantom was then carried out to demonstrate the accuracy of the proposed method and the increase of signal-to-noise ratio over three-dimensional PET. Finally, the 4D PET reconstruction was applied to a patient case.

Overview of image-guided radiation therapy.

Radiation therapy has gone through a series of revolutions in the last few decades and it is now possible to produce highly conformal radiation dose distribution by using techniques such as intensity-modulated radiation therapy (IMRT). The improved dose conformity and steep dose gradients have necessitated enhanced patient localization and beam targeting techniques for radiotherapy treatments. Components affecting the reproducibility of target position during and between subsequent fractions of radiation therapy include the displacement of internal organs between fractions and internal organ motion within a fraction. Image-guided radiation therapy (IGRT) uses advanced imaging technology to better define the tumor target and is the key to reducing and ultimately eliminating the uncertainties. The purpose of this article is to summarize recent advancements in IGRT and discussed various practical issues related to the implementation of the new imaging techniques available to radiation oncology community. We introduce various new IGRT concepts and approaches, and hope to provide the reader with a comprehensive understanding of the emerging clinical IGRT technologies. Some important research topics will also be addressed.