Respiratory motion artifacts in radionuclide imaging can substantially increase the apparent volume of malignant lesions, and result in reduced activity and signal-to-noise ratios (SNRs) within the tumor region. We present a corrective algorithm, coined retrospective stacking (RS), that combines retrospective amplitude-based binning of data acquired in small time intervals, with rigid or deformable image registration methods. Retrospective stacking is first applied to numerically simulated radionuclide images of a lesion moving with regular and irregular linear motion, as well as hysteresis characteristic of tumors near the lung. The dependence of RS on spatial and temporal resolution is explored, by comparing cross-section visualizations, activity profiles, and SNRs of retrospectively stacked images with those from a simulated motionless lesion. The simulation results are subsequently validated with a phantom positron emission tomography experiment representing a hot lesion oscillating within a warm background. It is seen that by sufficiently reducing the data acquisition timestep, RS can restore the lesion image to nearly its original shape, intensity and SNR, even under noisy conditions.

Newly emerged 4D-imaging techniques such as 4D-CT, -CBCT, -MRI and -PET afford effective tools to reveal spatio-temporal details of patients' anatomy. To utilize the 4D data acquired under different conditions or using different modalities, an algorithm for registering 4D images must be in place. The purpose of this work is to develop an automated 4D-4D deformable registration method to fully take advantage of 4D information. 4D-4D registration is to establish a spatial-temporal correspondence between the two sets of input 4D images. Mathematically, this is to find the transformation matrix, that maps an arbitrary point from the fixed image to the corresponding point on the floating image (or vice versa). The most general way to proceed is to first represent each input dataset by a 4D model and then match the two 4D models using 4D deformable algorithm. Our 4D-4D deformable model can be divided into two steps: (i) using BSpline model to built a 4D representation for the fixed and moving 4D images (which is a typical application of deformable model and familiar to most researchers); and (ii) iteratively adjusting the coefficients of the spline model of the moving images in such a way that the warped image maximally correlates with the fixed image as judged by the registration metric function. The Mattes formulation of the mutual information was chosen as the metric function for the 4D deformable matching. A search algorithm was implemented to simultaneously find the best BSpline parameters for optimal phase and spatial match of two 4D inputs. A number digital phantom and a number of lung and liver patient studies were performed to evaluate the performance of the proposed algorithm. The technique was also applied to register 4D-CT images acquired at multiple time points as well as 4D-CT and 4D-MRI, 4D-CT and 4D-CBCT, and 4D-CT and 4D-PET images for a series of patients with thoracic tumors. A novel strategy for 4D-4D deformable registration has been developed. Digital phantom study with intentionally introduced 4D deformations suggested that a spatial accuracy better than 2–3 mm is readily achievable using the proposed technique. In the patient studies, because of the local nature of the BSpline model, the 4D-4D registration was able to identify the regions where the spatio-temporal deformations are most pronounced. Registration of 4D-CT images acquired at multiple time points indicated that the patient anatomy barely repeats itself without any deformation, which highlights the importance of the development of a robust 4D-4D deformable model for information transfer among different image sessions. Inter-modality 4D registration was also found clinically indispensable in order to maximally utilize the emerging 4D-MRI and -PET data for improved treatment panning. The 4D-CT and -PET registration is also useful for more adequate PET attenuation correction using 4D-CT generated attenuation maps. Automated deformable 4D-4D registration can find the best possible spatio-temporal match between inter- and intra-modality 4D datasets and is useful for various IGRT applications.

The quantum mechanical density operator provides a consistent treatment of a many-atom system in contact with a physical environment, as needed to describe a complex molecular system undergoing a localized electronic excitation induced by interaction with light, or by atomic collisions. Treatments are presented where the degrees of freedom of the many-atom system are separated into quantal and classical-like ones, and the equation of motion of the density operators are derived by means of a partial Wigner transform. A computational procedure introduces approximations of short wavelengths in phase space, and effective potentials that guide trajectory bundles. The dynamics and spectra of electronically excited systems are treated introducing a basis set of many-electron states calculated in advance, or in terms of time-dependent molecular orbitals in a first principles approach to dynamics, and are used in applications on photodissociation of a diatomic and on collisional excitation in atomic collisions. Interactions with a medium are described by reduced density operators that satisfy equations of motion with dissipation and fluctuation terms. Both delayed and instantanecus dissipation are considered, and are involved in applications to femtosecond photodesorption and to vibrational relaxation of adsorbates.

Purpose: To investigate the potential of FDG‐PET imaging for delineating the surgical cavity in post‐operative partial breast irradiation patients. Method and Materials: A DCIS breast cancer patient was imaged with a GE Discovery ST PET‐CT scanner approximately 2 weeks post lumpectomy. Following the treatment planning CT, a single‐bed (15 cm) FDG‐PET scan was dynamically acquired in 5‐sec intervals over 15 mins. The raw PET data was combined to form bins ranging from 30 sec to 15 min. These data were reconstructed by the GE scanner through an iterative OSEM algorithm, and hardware fused to the treatment planning CT. The value of PET in visualizing the lumpectomy cavity border was investigated through visual comparisons of fused PET‐CT images, the evolution of PET intensity for various breast points, and signal‐to‐noise measurements across the lesion. Results: The PET image showed clear signal enhancement near the lumpectomy cavity. This enhancement formed a ring in each axial slice, matching the locations of surgical clips. Enhancement was also apparent where the cavity border was difficult to evaluate by CT density or clips alone. The ring presented a significantly higher SUV than other breast tissue (2.2 vs. <1.4), while the region inside the ring had a lower SUV than the (presumably benign) glandular tissue in the same breast (1.2 vs. 1.4). The SUV values were transient below 5 min, but remained stable thereafter. Conclusion: FDG‐PET may provide useful information for delineating lumpectomy cavity borders by elucidating regions of enhanced radiotracer uptake due to inflammation. The hypointense PET volume enclosed by the high activity ring may represent fluid and non‐viable tissue stemming from post‐surgical changes, explaining its lower FDG uptake and further supporting the suggestion that the ring corresponds to the cavity border itself. On current hardware, five‐minute scans were required to achieve stable SUVs.

Purpose: 4D‐imaging techniques such as 4D‐CT/MRI/PET reveal spatial and temporal details of patient's anatomy. Here we develop a 4D‐4D registration method to utilize the 4D data acquired under different conditions or using different modalities. Method: A 4D input (model or reference) consists of a number of 3D sets of images, each representing the patient's anatomy at a phase point. When the patient's breathing pattern is repeatable, the task of 4D‐4D matching is to find the appropriate 3D dataset in the model input for each phase in reference. Instead of exhaustively searching for the best match for each phase, a search algorithm was implemented, which can simultaneously find the matches for all phases with consideration of temporal relationship between the 3D image sets in the inputs. An interpolation scheme capable of deriving an image set based on two temporally adjacent 3D‐datasets was implemented to deal with the situation where the discrete temporal points of the two inputs do not coincide. Digital phantom and patient studies were performed to illustrate the inter‐/intra‐modality 4D‐4D registration technique. Results: In the phantom study where the optimal match is known, the proposed technique was able to reproduce the “ground truth” with high spatial fidelity (<1.5mm). In addition, the technique regenerated all deliberately introduced “missing” 3D images at different phase points in one of the inputs because of the temporal interpolation. In a registration of gated‐MRI and 4DCT, the technique enabled us to optimally select the corresponding CT phase. The technique was also found useful for the registration of two sets of 4DCTs acquired at different time points. In this situation, a spatial accuracy of less than 2.5mm was achieved in all three cases. Conclusions: Automated 4D‐4D registration can find the best possible spatio‐temporal match between the two 4D datasets and may have significant implication for IGRT.

Purpose: To investigate the accuracy of gated IMRT delivery on a Varian linear accelerator equipped with the Realtime Position Management (RPM) camera and software. Method and Materials: A non-uniform dose distribution within a solid water phantom was contoured and planned with IMRT. A sinusoidally oscillating platform simulated superioinferior respiratory motion, and a reflecting block was placed on the surface of the platform to provide a “respiratory” signal to the RPM camera. First, the phantom was stationary while the platform served only to provide the respiratory signal. The respiratory period was 5 sec, and the treatment was delivered in phase-gated intervals of 6%, 10%, 25% and 50%. Second, the phantom was placed on the platform, with motion amplitude of 6 cm. Here, dose was delivered to the phantom during a small amplitude-defined interval at end-expiration, with periods 1.7 sec, 5.3 sec and 12.6 sec. Dose distributions were captured on film. Results: Dose profiles generally showed variation between configurations less than 2% the maximal dose, with shorter-interval delivery providing slightly less dose than longer-interval delivery. The only notable difference occurred for the phantom moving with respiratory period of 1.7 sec, where dose fluctuations of nearly 6% occurred at regions of high dose gradient in the direction of motion. It should be noted that the gating interval spanned 15% the respiratory cycle, implying the beam was delivered in only 1.7 × 0.15 = 0.25 sec intervals. Conclusion: Gated IMRT delivery provided dose distributions equivalent to ungated delivery to within clinically acceptable limits. This result held for significant motion amplitude, under a wide range of respiration frequencies and gating intervals. While discrepancies up to 6% arose at high gradient borders for configurations of extremely rapid motion and short beam-on time, these parameters are very unlikely to be seen in any clinical situation.

Purpose: Four‐dimensional (4D) PET can be acquired with gated, dynamic or list mode. In reality, a major problem limiting its clinical application is the poor statistics, since the total coincidence counts in conventional 3D PET are divided into several phase bins and each of them is treated as an independent entity in 4D image reconstruction. We develop a mathematically rigorous system approach that allows one to maximally enhance the signal‐to‐noise ratio (SNR) of 4D PET by simultaneously considering the coincidences acquired at all time points when reconstructing the phase‐resolved images. Method and Materials: A GE Discovery‐ST PET/CT scanner was used to acquire 4D‐CT/PET images. A Real‐time Position Management (RPM) system was used to determine the respiration phases and to correlate temporally the PET and CT images. By deformable registration of the 4D‐CT images, a patient‐specific motion model was derived and incorporated into our “spatial‐temporal PET reconstruction” algorithm based on the maximum likelihood principle. The approach was quantitatively evaluated with numerical and physical phantom experiments. Five clinical studies of pancreatic, lung and liver cancer patients were then carried out. Results: Via a novel concept of “virtual curved line‐of‐response”, we proved that the PET “4D likelihood” can be maximized with a modified expectation‐maximization algorithm. Numerical/physical phantom experiments and patient studies showed that the algorithm converged monotonically. In the former two cases, the “ground truths” were reached within 40 iterations, and the SNRs were enhanced by more than 80% over the regular 4D PET and 35% over 3D PET. Similar level of improvement was observed for the patient studies. Conclusion: A spatial‐temporal reconstruction formalism has been established to fully take advantage of the coincidence information acquired in the 4D acquisition process when reconstructing phase‐resolved PET images. It allows us to obtain the statistically optimal 4D solution and substantially improved SNRs in 4D PET.

Purpose: To quantify the interplay between respiratory motion and CBCT imaging in thoracic and abdominal region. Method and Materials: A Varian Acuity CBCT simulator was used to scan a motion‐simulation phantom and three patients (a pancreatic and two lung cases). Motion phase of the phantom or the patients was stamped with a Varian RPM system. For phantom study, three CBCT gantry rotation speeds (5°, 10°, and 15° per second) were used. Several different motion patterns and speeds of the phantom, simulating a variety of clinical situations, were also investigated with CBCT gantry speed of 10°/s. The patient scans were done with 10°/s rotation speed. The resultant images were compared against the 4D‐CT images acquired on a GE LightSpeed scanner. The HU profiles of the two types of images were analyzed. Results: Given the fact that a regular breathing cycle takes ∼4s, a CBCT scan is usually a time‐average over ∼10 breathing cycles. Large artifacts and anatomical distortions were observed in both phantom and patient scans. In the phantom study, the onset of motion artifacts started at very low “breathing” motion rate, suggesting that CBCT is less proof against motion. The CBCT image quality was worsen as the “breathing” rate increased but this became saturated when the phantom motion rate reached to a certain level. For the patient study, the discrepancies between the CBCT and 4D CT images were also found to be large. The tumor contours, for example, delineated based on the two types of images can differ up to 1cm Conclusion: Respirator motion greatly degrades the quality of CBCT and presents a problem in thorax and abdomen imaging. It is urgently needed to develop a clinically practical means to minimize the adverse effect of breathing motion.

Purpose/Objective: Previous reports of APBI with 3D conformal radiotherapy suggest that a 10 mm clinical target volume-to-planning target volume (CTV-to-PTV) margin is necessary to account for 5 mm of respiratory motion and 5 mm of set-up uncertainty. This study aims to determine if respiratory gating during delivery of 3D conformal APBI can improve normal tissue sparing by reducing the PTV margin without sacrificing tumor coverage. Materials/Methods: Four breast cancer patients eligible for APBI after lumpectomy (2 left-sided and 2 right-sided lesions) underwent 4D-CT scans during free-breathing using a GE Discovery ST hybrid PET-CT scanner with multidetector CT. Respiratory cycles were tracked with Varian's Real-time Position Management (RPM) System. 4-D reconstruction was done on a GE Advantage Workstation. End-expiration phase (EP) and end-inspiration phase (IP) scans were identified by RPM tracings and confirmed by position of the diaphragmatic dome. Normal tissues were contoured for each phase by a single observer, including skin, bilateral breasts, bilateral lungs, and heart. The CTV was defined as a uniform 15 mm margin around the lumpectomy cavity modified to exclude the chest wall, pectoralis muscles, and tissue within 5 mm of the skin. Three PTVs were generated for each EP scan (PTV0, PTV5, PTV10), representing a 0, 5, and 10 mm non-modified margin around the CTV. Each PTV was then copied in exact spatial registration on the IP scan through DICOM coordinate fusion, yielding a total of 6 image sets per patient. A Varian Eclipse System was used to generate treatment plans to deliver 385 cGy fractions BID × 10 fractions for a total of 3850 cGy prescribed to the PTV. Dose volume histograms were analyzed. Results: The overall mean ipsilateral breast dose was 1655 cGy in EP and 1741 cGy in IP. The overall mean ipsilateral lung dose was 68.9 cGy in EP and 79.9 cGy in IP. The overall mean heart dose was 30.4 cGy in EP (19.1 cGy for right-sided tumors, 41.6 cGy for left-sided tumors) and 25.8 cGy in IP (20.5 cGy for right-sided tumors, 31.0 cGy for left-sided tumors). Regardless of respiratory phase, there was a mean increase in ipsilateral breast dose and a mean increase in ipsilateral lung dose of 355.4 cGy (251–522 cGy) and 39.8 cGy (13–68 cGy), respectively, for each 5 mm margin increase. The mean increase in heart dose per 5 mm margin increase for all phases was 9.9 cGy (6.1 cGy for right-sided tumors, 13.6 cGy for left-sided tumors, range 4–19 cGy). The 95% CTV isodose coverage decreased from EP to IP by a mean volume of 8.3% for PTV0 (6–12%), 3.8% for PTV5 (0–10%), and 1.5% for PTV10 (0–3%). Refer to Table 1 for details.Table 1 Conclusions: During APBI, mean ipsilateral breast and lung doses vary with respiratory phase. Also, the mean heart dose decreases with inspiration in left-sided cancers but minimally increases with right-sided cancers, perhaps as the heart shifts midline. When planned at end-expiration, CTV coverage increases with increasing PTV margin and decreases with inspiration. These results suggest that APBI with respiratory gating may decrease normal tissue toxicity while maintaining CTV coverage by reducing PTV margin.

Medical PhysicsVolume 32, Issue 6Part4 p. 1919-1919 General poster discussion: Exhibit hall 4A SU-FF-J-02: A Comparison of Amplitude- and Phase-Based 4D CT B Thorndyke, B Thorndyke Stanford Univ School of Medicine, Stanford, CASearch for more papers by this authorE Schreibmann, E Schreibmann Stanford Univ School of Medicine, Stanford, CASearch for more papers by this authorT Li, T Li Stanford Univ School of Medicine, Stanford, CASearch for more papers by this authorA Boyer, A Boyer Stanford Univ School of Medicine, Stanford, CASearch for more papers by this authorL Xing, L Xing Stanford Univ School of Medicine, Stanford, CASearch for more papers by this author B Thorndyke, B Thorndyke Stanford Univ School of Medicine, Stanford, CASearch for more papers by this authorE Schreibmann, E Schreibmann Stanford Univ School of Medicine, Stanford, CASearch for more papers by this authorT Li, T Li Stanford Univ School of Medicine, Stanford, CASearch for more papers by this authorA Boyer, A Boyer Stanford Univ School of Medicine, Stanford, CASearch for more papers by this authorL Xing, L Xing Stanford Univ School of Medicine, Stanford, CASearch for more papers by this author First published: 26 May 2005 https://doi.org/10.1118/1.1997548Citations: 2About ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract Purpose: Four-dimensional (4D) CT depends on accurate correlation between temporally acquired CT slices and the patient's respiratory cycle. One approach is to record the position of an external marker placed on the abdomen or chest during the scan, and retrospectively match the CT data with the phase of the marker motion. While very effective for regular breathing patterns, the phase-based approach can lead to significant mismatch between adjacent image segments when the respiratory motion exhibits irregularities. We propose a method of extracting amplitude-based 4D CT from cine-acquired CT data sets, and compare the amplitude-based 4D CT with the phase-based 4D CT for both phantom and patient data. Method and Materials: CT data sets were acquired in cine mode on the GE Discovery ST, and motion of an infrared reflecting block was recorded using Varian's Real-time Position Management (RPM) camera. Rather than use the phase-based calculations of the RPM system, we replaced the phase field with pseudo-amplitude values spanning the full respiratory cycle (i.e., differentiating inspiration from expiration). The modified respiratory trace file was then sent, along with the cine CT data, to the GE Advantage Workstation for processing. The method was applied to a thoracic phantom moving irregularly in the longitudinal direction, and to an abdominal 4D scan of a lung cancer patient. Results: For both phantom and patient data, the phase-based 4D CT images showed boundary mismatches of up to 1 cm between couch positions. The mismatch on the amplitude-based sets, however, was less than 2 mm throughout the field of view. Conclusion: Phase-based 4D CT can lead to mismatched slices when the respiratory cycle involves irregularities. In such situations, by replacing phase with a modified definition of amplitude that distinguishes inspiration from expiration, a substantially improved 4D CT image can be generated. Citing Literature Volume32, Issue6Part4June 2005Pages 1919-1919 RelatedInformation

Purpose: High‐field MR techniques makes possible to obtain high quality MRI metabolic images of the prostate to accurately identify the intra‐prostatic lesion(s). However, the use of rigid endorectal probe deforms the shape of the prostate gland and the images so obtained are not directly usable in radiation therapy planning. This work applies a narrow band deformable registration model to faithfully map the MRI information onto treatment planning CT images. Method and Materials: The narrow band is a hybrid method combining the advantages of pixel‐based and distance‐based registration techniques, since the calculation is restricted to those points contained in a region around user‐delineated structures. The narrow band method is inherently efficient because of the use of a priori information of the meaningful contour data. The deformable mapping is described by the B‐spline model. The limited memory algorithm (L‐BFGS) was implemented to optimize a normalized cross correlation metric function. It's convergence behavior was studied by comparing final metrics obtained in 100 registrations self‐registering an MR image starting from 100 randomly initiated positions. The spatial performance of the algorithm was assessed by intentionally distorting an MRI image and an attempt was then made to register the distorted image with the original one. The MRI‐CT mapping was carried out for two clinical cases. Results: The convergence analysis showed absence of local minima. The technique can restore an MR image from the intentionally introduced deformations with an accuracy of ∼2 mm. On clinical cases the method was capable of producing clinically sensible mapping. The whole registration procedure for a complete 3D study took less than 15 minutes on a standard PC. Conclusion: Both hypothetical tests and patient studies have indicated that narrow‐band based registration is reliable and provides a valuable tool to integrate the ER‐based MRI/MRSI information to guide prostate radiation therapy treatment.

Four-dimensional (4D) CT is useful in many clinical situations, where detailed abdominal and thoracic imaging is needed over the course of the respiratory cycle. However, it usually delivers a larger radiation dose than the standard three-dimensional (3D) CT, since multiple scans at each couch position are required in order to provide the temporal information. Our purpose in this work is to develop a method to perform 4D CT scans at relatively low current, hence reducing the radiation exposure of the patients. To deal with the increased statistical noise caused by the low current, we proposed a novel 4D penalized weighted least square (4D-PWLS) smoothing method, which can incorporate both spatial and phase information. The 4D images at different phases were registered to the same phase via a deformable model, thereby, a regularization term combining temporal and spatial neighbors can be designed for the 4D-PWLS objective function. The proposed method was tested with phantom experiments and a patient study, and superior noise suppression and resolution preservation were observed. A quantitative evaluation of the benefit of the proposed method to 4D radiotherapy and 4D PET/CT imaging are under investigation.

Purpose/Objective: Four-dimensional (4D) computed tomography (CT) permits assessment of respiratory-induced tumor and organ motion. Current 4D CT reconstruction methods assume a relatively regular, reproducible breathing pattern. Irregularities in the respiratory pattern can lead to substantial reconstruction artifacts in the 4D image series. We report a quantitative measure of breathing cycle irregularity based on analysis of external marker motion and correlate this parameter with a measure of the severity of reconstruction artifacts in the resulting 4D CT image. Materials/Methods: We analyzed 4D CT images and respiratory traces of twenty patients with abdominal or thoracic tumors. The scans were obtained during free breathing with a GE Discovery ST PET/CT scanner, while the respiratory trace was recorded using the Varian Real-time Position Management (RPM) system to track the motion of a reflecting block placed on the abdomen. For each respiratory cycle, phase was characterized as a percent of the peak to peak time interval. The irregularity of the respiratory trace was quantified by the standard deviation of the respiratory trace amplitude at each phase, in effect measuring the gap between amplitude and phase (GAP). The quality of each 4D scan was assessed by identifying contour mismatches measured at the surface of the mid-abdomen or diaphragm occurring between adjacent CT bed positions. Reconstruction error was scored as the percentage of bed positions with interface artifacts (IA) greater than 2 mm. The correlation of GAP with percentage of IAs was calculated to determine the relationship between respiratory trace irregularity and 4D image quality. Results: GAP correlated well with the percentage of significant IAs (r2 = 0.73). Patients whose GAPs were below 14 had significant IAs in only 5% to 35% of the measured inter-bed boundaries, while patients whose GAPs were above 14 had significant IAs in 33% to 65%. The largest IAs occurred in patients with higher GAPs. The relationship between GAP and percentage of IAs is plotted below. Conclusions: Breathing cycle irregularity as measured by GAP reliably predicts the quality of 4D CT reconstruction as measured by the percent of significant IAs that will appear in the resulting images. Since GAP can be determined from the RPM trace prior to acquiring the 4D CT scan, it should be possible to improve the quality of the scan and consequently also the breathing compensated treatments by applying pre-scan interventions such as coached breathing when the initial GAP exceeds a given threshold.