Acquiring a four-dimensional computed tomography dataset using an external respiratory signal

Four-dimensional (4D) methods strive to achieve highly conformal radiotherapy, particularly for lung and breast tumours, in the presence of respiratory-induced motion of tumours and normal tissues. Four-dimensional radiotherapy accounts for respiratory motion during imaging, planning and radiation delivery, and requires a 4D CT image in which the internal anatomy motion as a function of the respiratory cycle can be quantified. The aims of our research were (a) to develop a method to acquire 4D CT images from a spiral CT scan using an external respiratory signal and (b) to examine the potential utility of 4D CT imaging. A commercially available respiratory motion monitoring system provided an 'external' tracking signal of the patient's breathing. Simultaneous recording of a TTL 'X-Ray ON' signal from the CT scanner indicated the start time of CT image acquisition, thus facilitating time stamping of all subsequent images. An over-sampled spiral CT scan was acquired using a pitch of 0.5 and scanner rotation time of 1.5 s. Each image from such a scan was sorted into an image bin that corresponded with the phase of the respiratory cycle in which the image was acquired. The complete set of such image bins accumulated over a respiratory cycle constitutes a 4D CT dataset. Four-dimensional CT datasets of a mechanical oscillator phantom and a patient undergoing lung radiotherapy were acquired. Motion artefacts were significantly reduced in the images in the 4D CT dataset compared to the three-dimensional (3D) images, for which respiratory motion was not accounted. Accounting for respiratory motion using 4D CT imaging is feasible and yields images with less distortion than 3D images. 4D images also contain respiratory motion information not available in a 3D CT image.     

Quantifying the accuracy of automated structure segmentation in 4D CT images using a deformable image registration algorithm

Four-dimensional (4D) radiotherapy is the explicit inclusion of the temporal changes in anatomy during the imaging, planning, and delivery of radiotherapy. One key component of 4D radiotherapy planning is the ability to automatically ("auto") create contours on all of the respiratory phase computed tomography (CT) datasets comprising a 4D CT scan, based on contours manually drawn on one CT image set from one phase. A tool that can be used to automatically propagate manually drawn contours to CT scans of other respiratory phases is deformable image registration. The purpose of the current study was to geometrically quantify the difference between automatically generated contours with manually drawn contours. Four-DCT data sets of 13 patients consisting of ten three-dimensional CT image sets acquired at different respiratory phases were used for this study. Tumor and normal tissue structures [gross tumor volume (GTV), esophagus, right lung, left lung, heart and cord] were manually drawn on each respiratory phase of each patient. Large deformable diffeomorphic image registration was performed to map each CT set from the peak-inhale respiration phase to the CT image sets corresponding with subsequent respiration phases. The calculated displacement vector fields were used to deform contours automatically drawn on the inhale phase to the other respiratory phase CT image sets. The code was interfaced to a treatment planning system to view the resulting images and to obtain the volumetric, displacement, and surface congruence information; 692 automatically generated structures were compared with 692 manually drawn structures. The auto- and manual methods showed similar trends, with a smaller difference observed between the GTVs than other structures. The auto-contoured structures agree with the manually drawn structures, especially in the case of the GTV, to within published interobserver variations. For the GTV, fractional volumes agree to within 0.2+/-0.1, center of mass displacements agree to within 0.5+/-1.5 mm, and agreement of surface congruence is 0.0+/-1.1 mm. The surface congruence between automatic and manual contours for the GTV, heart, left lung, right lung and esophagus was less than 5 mm in 99%, 94%, 94%, 91% and 89%, respectively. Careful assessment of the performance of automatic algorithms is needed in the presence of 4D CT artifacts.     

A method for the reconstruction of four-dimensional synchronized CT scans acquired during free breathing

Breathing motion is a significant source of error in radiotherapy treatment planning for the thorax and upper abdomen. Accounting for breathing motion has a profound effect on the size of conformal radiation portals employed in these sites. Breathing motion also causes artifacts and distortions in treatment planning computed tomography (CT) scans acquired during free breathing and also causes a breakdown of the assumption of the superposition of radiation portals in intensity-modulated radiation therapy, possibly leading to significant dose delivery errors. Proposed voluntary and involuntary breath-hold techniques have the potential for reducing or eliminating the effects of breathing motion, however, they are limited in practice, by the fact that many lung cancer patients cannot tolerate holding their breath. We present an alternative solution to accounting for breathing motion in radiotherapy treatment planning, where multislice CT scans are collected simultaneously with digital spirometry over many free breathing cycles to create a four-dimensional (4-D) image set, where tidal lung volume is the additional dimension. An analysis of this 4-D data leads to methods for digital-spirometry, based elimination or accounting of breathing motion artifacts in radiotherapy treatment planning for free breathing patients. The 4-D image set is generated by sorting free-breathing multislice CT scans according to user-defined tidal-volume bins. A multislice CT scanner is operated in the ciné mode, acquiring 15 scans per couch position, while the patient undergoes simultaneous digital-spirometry measurements. The spirometry is used to retrospectively sort the CT scans by their correlated tidal lung volume within the patient's normal breathing cycle. This method has been prototyped using data from three lung cancer patients. The actual tidal lung volumes agreed with the specified bin volumes within standard deviations ranging between 22 and 33 cm3. An analysis of sagittal and coronal images demonstrated relatively small (<1 cm) motion artifacts along the diaphragm, even for tidal volumes where the rate of breathing motion is greatest. While still under development, this technology has the potential for revolutionizing the radiotherapy treatment planning for the thorax and upper abdomen.     

Spatial correspondence of 4D CT ventilation and SPECT pulmonary perfusion defects in patients with malignant airway stenosis

To determine the spatial overlap agreement between four-dimensional computed tomography (4D CT) ventilation and single photon emission computed tomography (SPECT) perfusion hypo-functioning pulmonary defect regions in a patient population with malignant airway stenosis. Treatment planning 4D CT images were obtained retrospectively for ten lung cancer patients with radiographically demonstrated airway obstruction due to gross tumor volume. Each patient also received a SPECT perfusion study within one week of the planning 4D CT, and prior to the initiation of treatment. Deformable image registration was used to map corresponding lung tissue elements between the extreme component phase images, from which quantitative three-dimensional (3D) images representing the local pulmonary specific ventilation were constructed. Semi-automated segmentation of the percentile perfusion distribution was performed to identify regional defects distal to the known obstructing lesion. Semi-automated segmentation was similarly performed by multiple observers to delineate corresponding defect regions depicted on 4D CT ventilation. Normalized Dice similarity coefficient (NDSC) indices were determined for each observer between SPECT perfusion and 4D CT ventilation defect regions to assess spatial overlap agreement. Tidal volumes determined from 4D CT ventilation were evaluated versus measurements obtained from lung parenchyma segmentation. Linear regression resulted in a linear fit with slope = 1.01 (R2 = 0.99). Respective values for the average DSC, NDSC(1 mm) and NDSC(2 mm) for all cases and multiple observers were 0.78, 0.88 and 0.99, indicating that, on average, spatial overlap agreement between ventilation and perfusion defect regions was comparable to the threshold for agreement within 1-2 mm uncertainty. Corresponding coefficients of variation for all metrics were similarly in the range: 0.10%-19%. This study is the first to quantitatively assess 3D spatial overlap agreement between clinically acquired SPECT perfusion and specific ventilation from 4D CT. Results suggest high correlation between methods within the sub-population of lung cancer patients with malignant airway stenosis.     

Acquiring 4D thoracic CT scans using a multislice helical method

Respiratory motion degrades anatomic position reproducibility during imaging, necessitates larger margins during radiotherapy planning and causes errors during radiation delivery. Computed tomography (CT) scans acquired synchronously with the respiratory signal can be used to reconstruct 4D CT scans, which can be employed for 4D treatment planning to explicitly account for respiratory motion. The aim of this research was to develop, test and clinically implement a method to acquire 4D thoracic CT scans using a multislice helical method. A commercial position-monitoring system used for respiratory-gated radiotherapy was interfaced with a third generation multislice scanner. 4D cardiac reconstruction methods were modified to allow 4D thoracic CT acquisition. The technique was tested on a phantom under different conditions: stationary, periodic motion and non-periodic motion. 4D CT was also implemented for a lung cancer patient with audio-visual breathing coaching. For all cases, 4D CT images were successfully acquired from eight discrete breathing phases, however, some limitations of the system in terms of respiration reproducibility and breathing period relative to scanner settings were evident. Lung mass for the 4D CT patient scan was reproducible to within 2.1% over the eight phases, though the lung volume changed by 20% between end inspiration and end expiration (870 cm3). 4D CT can be used for 4D radiotherapy, respiration-gated radiotherapy, 'slow' CT acquisition and tumour motion studies.     

Novel method to calculate pulmonary compliance images in rodents from computed tomography acquired at constant pressures

Our goal was to develop a method for generating high-resolution three-dimensional pulmonary compliance images in rodents from computed tomography (CT) images acquired at a series of constant pressures in ventilated animals. One rat and one mouse were used to demonstrate this technique. A pre-clinical GE flat panel CT scanner (maximum 31 line-pairs cm(-1) resolution) was utilized for image acquisition. The thorax of each animal was imaged with breath-holds at 2, 6, 10, 14 and 18 cm H2O pressure in triplicate. A deformable image registration algorithm was applied to each pair of CT images to map corresponding tissue elements. Pulmonary compliance was calculated on a voxel by voxel basis using adjacent pairs of CT images. Triplicate imaging was used to estimate the measurement error of this technique. The 3D pulmonary compliance images revealed regional heterogeneity of compliance. The maximum total lung compliance measured 0.080 (+/-0.007) ml air per cm H2O per ml of lung and 0.039 (+/-0.004) ml air per cm H2O per ml of lung for the rat and mouse, respectively. In this study, we have demonstrated a unique method of quantifying regional lung compliance from 4 to 16 cm H2O pressure with sub-millimetre spatial resolution in rodents.     

基于4DCT和形变配准技术评估呼吸运动对肺癌立体定向放射治疗过程中剂量的影响

目的:探讨肺下叶肿瘤患者立体定向放射治疗（SBRT）治疗时,呼吸运动对肿瘤和正常器官受量的影响。方法:选取14例肺下叶肿瘤患者,均行平扫CT和四维CT（4DCT）扫描定位,获得平扫及10个呼吸时相的序列图像,同时记录患者放疗时的呼吸曲线,并得到各呼吸时相维持时间占比。利用MIM工作站勾画肿瘤和正常器官,基于平扫CT制定放疗计划,将3DCT计划移植到各呼吸时相的序列图像中并计算剂量,按照时间占比叠加各个时相的剂量。结果:比较平扫CT计划剂量分布和叠加剂量分布,得出相比平扫CT计划剂量。叠加剂量中,PTV平均剂量、患侧肺V20、患侧肺平均剂量、健侧肺平均剂量和全肺平均剂量的4D加权叠加均小于3D剂量,分别减小了2.37%、5.08%、5.19%、3.61%和3.46%,差异均有统计学意义（P<0.05）。结论:患者的呼吸运动导致肿瘤和肺受量的降低,但在较小的变化范围内。利用4DCT和形变配准技术,引入患者各呼吸时相维持时间占比的因素,可更合理评估呼吸运动对肺下叶肿瘤SBRT放射治疗过程中剂量的影响。     

Geometrical differences in target volumes between slow CT and 4D CT imaging in stereotactic body radiotherapy for lung tumors in the upper and middle lobe

Since stereotactic body radiotherapy (SBRT) was started for patients with lung tumor in 1998 in our institution, x-ray fluoroscopic examination and slow computed tomography (CT) scan with a rotation time of 4 s have been routinely applied to determine target volumes. When lung tumor motion observed with x-ray fluoroscopy is larger than 8 mm, diaphragm control (DC) is used to reduce tumor motion during respiration. After the installation of a four-dimensional (4D) CT scanner in 2006, 4D CT images have been supplementarily acquired to determine target volumes. It was found that target volumes based on slow CT images were substantially different from those on 4D CT images, even for patients with lung tumor motion no larger than 8 mm. Although slow CT scan might be expected to fare well for lung tumors with motion range of 8 mm or less, the potential limitations of slow CT scan are unknown. The purpose of this study was to evaluate the geometrical differences in target volumes between slow CT and 4D CT imaging for lung tumors with motion range no larger than 8 mm in the upper and middle lobe. Of the patients who underwent SBR between October 2006 and April 2008, 32 patients who had lung tumor with motion range no larger than 8 mm and did not need to use DC were enrolled in this study. Slow CT and 4D CT images were acquired under free breathing for each patient. Target volumes were manually delineated on slow CT images (TV(slow CT)). Gross tumor volumes were also delineated on each of the 4D CT volumes and their union (TV(4D CT)) was constructed. Volumetric and statistical analyses were performed for each patient. The mean +/- standard deviation (S.D.) of TV(slow CT)/TV(4D CT) was 0.75 +/- 0.17 (range, 0.38-1.10). The difference between sizes of TV(slow CT) and TV(4D CT) was not statistically significant (P = 0.096). A mean of 8% volume of TV(slow CT) was not encompassed in TV(4D CT) (mean +/- S.D. = 0.92 +/- 0.07). The patients were separated into two groups to test whether the quality of target delineation on slow CT scans depends on respiratory periods below or above the CT rotation time of 4 s. No significant difference was observed between these groups (P = 0.229). Even lung tumors with motion range no larger than 8 mm might not be accurately depicted on slow CT images. When only a single slow CT scan was used for lung tumors with motion range of 8 mm or less, 95% confidence values for additional margins for TV(slow CT) to encompass TV(4D CT) were 4.0, 5.4, 4.9, 5.1, 1.8, and 1.7 mm for lateral, medial, ventral, dorsal, cranial, and caudal directions, respectively.     

Evaluation of the combined effects of target size, respiratory motion and background activity on 3D and 4D PET/CT images

Gated (4D) PET/CT has the potential to greatly improve the accuracy of radiotherapy at treatment sites where internal organ motion is significant. However, the best methodology for applying 4D-PET/CT to target definition is not currently well established. With the goal of better understanding how to best apply 4D information to radiotherapy, initial studies were performed to investigate the effect of target size, respiratory motion and target-to-background activity concentration ratio (TBR) on 3D (ungated) and 4D PET images. Using a PET/CT scanner with 4D or gating capability, a full 3D-PET scan corrected with a 3D attenuation map from 3D-CT scan and a respiratory gated (4D) PET scan corrected with corresponding attenuation maps from 4D-CT were performed by imaging spherical targets (0.5-26.5 mL) filled with (18)F-FDG in a dynamic thorax phantom and NEMA IEC body phantom at different TBRs (infinite, 8 and 4). To simulate respiratory motion, the phantoms were driven sinusoidally in the superior-inferior direction with amplitudes of 0, 1 and 2 cm and a period of 4.5 s. Recovery coefficients were determined on PET images. In addition, gating methods using different numbers of gating bins (1-20 bins) were evaluated with image noise and temporal resolution. For evaluation, volume recovery coefficient, signal-to-noise ratio and contrast-to-noise ratio were calculated as a function of the number of gating bins. Moreover, the optimum thresholds which give accurate moving target volumes were obtained for 3D and 4D images. The partial volume effect and signal loss in the 3D-PET images due to the limited PET resolution and the respiratory motion, respectively were measured. The results show that signal loss depends on both the amplitude and pattern of respiratory motion. However, the 4D-PET successfully recovers most of the loss induced by the respiratory motion. The 5-bin gating method gives the best temporal resolution with acceptable image noise. The results based on the 4D scan protocols can be used to improve the accuracy of determining the gross tumor volume for tumors in the lung and abdomen.     

Four-dimensional computed tomography: image formation and clinical protocol

Respiratory motion can introduce significant errors in radiotherapy. Conventional CT scans as commonly used for treatment planning can include severe motion artifacts that result from interplay effects between the advancing scan plane and object motion. To explicitly include organ/target motion in treatment planning and delivery, time-resolved CT data acquisition (4D Computed Tomography) is needed. 4DCT can be accomplished by oversampled CT data acquisition at each slice. During several CT tube rotations projection data are collected in axial cine mode for the duration of the patient's respiratory cycle (plus the time needed for a full CT gantry rotation). Multiple images are then reconstructed per slice that are evenly distributed over the acquisition time. Each of these images represents a different anatomical state during a respiratory cycle. After data acquisition at one couch position is completed, x rays are turned off and the couch advances to begin data acquisition again until full coverage of the scan length has been obtained. Concurrent to CT data acquisition the patient's abdominal surface motion is recorded in precise temporal correlation. To obtain CT volumes at different respiratory states, reconstructed images are sorted into different spatio-temporally coherent volumes based on respiratory phase as obtained from the patient's surface motion. During binning, phase tolerances are chosen to obtain complete volumetric information since images at different couch positions are reconstructed at different respiratory phases. We describe 4DCT image formation and associated experiments that characterize the properties of 4DCT. Residual motion artifacts remain due to partial projection effects. Temporal coherence within resorted 4DCT volumes is dominated by the number of reconstructed images per slice. The more images are reconstructed, the smaller phase tolerances can be for retrospective sorting. From phantom studies a precision of about 2.5 mm for quasiregular motion and typical respiratory periods could be concluded. A protocol for 4DCT scanning was evaluated and clinically implemented at the MGH. Patient data are presented to elucidate how additional patient specific parameters can impact 4DCT imaging.     

Lung metastases detection in CT images using 3D template matching

The aim of this study is to demonstrate a novel, fully automatic computer detection method applicable to metastatic tumors to the lung with a diameter of 4-20 mm in high-risk patients using typical computed tomography (CT) scans of the chest. Three-dimensional (3D) spherical tumor appearance models (templates) of various sizes were created to match representative CT imaging parameters and to incorporate partial volume effects. Taking into account the variability in the location of CT sampling planes cut through the spherical models, three offsetting template models were created for each appearance model size. Lung volumes were automatically extracted from computed tomography images and the correlation coefficients between the subregions around each voxel in the lung volume and the set of appearance models were calculated using a fast frequency domain algorithm. To determine optimal parameters for the templates, simulated tumors of varying sizes and eccentricities were generated and superposed onto a representative human chest image dataset. The method was applied to real image sets from 12 patients with known metastatic disease to the lung. A total of 752 slices and 47 identifiable tumors were studied. Spherical templates of three sizes (6, 8, and 10 mm in diameter) were used on the patient image sets; all 47 true tumors were detected with the inclusion of only 21 false positives. This study demonstrates that an automatic and straightforward 3D template-matching method, without any complex training or postprocessing, can be used to detect small lung metastases quickly and reliably in the clinical setting.     

Concurrent multimodality image segmentation by active contours for radiotherapy treatment planning

Multimodality imaging information is regularly used now in radiotherapy treatment planning for cancer patients. The authors are investigating methods to take advantage of all the imaging information available for joint target registration and segmentation, including multimodality images or multiple image sets from the same modality. In particular, the authors have developed variational methods based on multivalued level set deformable models for simultaneous 2D or 3D segmentation of multimodality images consisting of combinations of coregistered PET, CT, or MR data sets. The combined information is integrated to define the overall biophysical structure volume. The authors demonstrate the methods on three patient data sets, including a nonsmall cell lung cancer case with PET/CT, a cervix cancer case with PET/CT, and a prostate patient case with CT and MRI. CT, PET, and MR phantom data were also used for quantitative validation of the proposed multimodality segmentation approach. The corresponding Dice similarity coefficient (DSC) was 0.90 +/- 0.02 (p < 0.0001) with an estimated target volume error of 1.28 +/- 1.23% volume. Preliminary results indicate that concurrent multimodality segmentation methods can provide a feasible and accurate framework for combining imaging data from different modalities and are potentially useful tools for the delineation of biophysical structure volumes in radiotherapy treatment planning.     

Influences of Motion Artifacts on Three-Dimensional Reconstruction Volume and Conformal Radiotherapy Planning

Objective ：To investigate the influences of motion artifacts on three-dimensional （3D） reconstruction volume and conformal radiotherapy planning. Methods： A phantom which can mimic the clip motion of lung tumor along the cranial-caudal direction is constructed by step motor, small ball of polyethylene and potato. Ten different scan protocols were set and CT data of the phantom were acquired by using a commercial GE LightSpeedl6 CT scanner. The 3D reconstruction of the CT data was implemented by adopting volume-rendering technology of GE AdvantageSim 6.0 system. The reconstructed volumes of each target in different scan protocols were measured through 3D measuring tools. Thus, relative deviations of the reconstruction volumes between moving targets and static ones were determined. The three-dimensional conformal radiation therapy （3D- CRT） plans and conformal fields were created and compared for a static/moving target with the WiMRT treatment planning system （TPS）. Results：For a static target, there was no obvious difference among the 3D reconstruction volumes when the CT data were acquired with different pitches and slices. The appearance of 3D reconstruction volume and 3D conformal field of a moving target was quite different from that of static one. The maximum relative deviation is nearly 90% for a moving target scanned with different scan protocols. The relative deviations are variable among the different targets, about from -39.8% to 89.5% for a smaller target and from - 18.4% to 20.5% for a larger one. Conclusion ：The motion artifacts have great effects on 3 D-CRT planning and reconstruction volume, which will greatly induce distorted conformal radiation fields and false DVHs for a moving target.     

Optimization of a retrospective technique for respiratory-gated high speed micro-CT of free-breathing rodents

The objective of this study was to develop a technique for dynamic respiratory imaging using retrospectively gated high-speed micro-CT imaging of free-breathing mice. Free-breathing C57Bl6 mice were scanned using a dynamic micro-CT scanner, comprising a flat-panel detector mounted on a slip-ring gantry. Projection images were acquired over ten complete gantry rotations in 50 s, while monitoring the respiratory motion in synchrony with projection-image acquisition. Projection images belonging to a selected respiratory phase were retrospectively identified and used for 3D reconstruction. The effect of using fewer gantry rotations--which influences both image quality and the ability to quantify respiratory function--was evaluated. Images reconstructed using unique projections from six or more gantry rotations produced acceptable images for quantitative analysis of lung volume, CT density, functional residual capacity and tidal volume. The functional residual capacity (0.15 +/- 0.03 mL) and tidal volumes (0.08 +/- 0.03 mL) measured in this study agree with previously reported measurements made using prospectively gated micro-CT and at higher resolution (150 microm versus 90 microm voxel spacing). Retrospectively gated micro-CT imaging of free-breathing mice enables quantitative dynamic measurement of morphological and functional parameters in the mouse models of respiratory disease, with scan times as short as 30 s, based on the acquisition of projection images over six gantry rotations.     

An enhanced block matching algorithm for fast elastic registration in adaptive radiotherapy

Image registration has many medical applications in diagnosis, therapy planning and therapy. Especially for time-adaptive radiotherapy, an efficient and accurate elastic registration of images acquired for treatment planning, and at the time of the actual treatment, is highly desirable. Therefore, we developed a fully automatic and fast block matching algorithm which identifies a set of anatomical landmarks in a 3D CT dataset and relocates them in another CT dataset by maximization of local correlation coefficients in the frequency domain. To transform the complete dataset, a smooth interpolation between the landmarks is calculated by modified thin-plate splines with local impact. The concept of the algorithm allows separate processing of image discontinuities like temporally changing air cavities in the intestinal track or rectum. The result is a fully transformed 3D planning dataset (planning CT as well as delineations of tumour and organs at risk) to a verification CT, allowing evaluation and, if necessary, changes of the treatment plan based on the current patient anatomy without time-consuming manual re-contouring. Typically the total calculation time is less than 5 min, which allows the use of the registration tool between acquiring the verification images and delivering the dose fraction for online corrections. We present verifications of the algorithm for five different patient datasets with different tumour locations (prostate, paraspinal and head-and-neck) by comparing the results with manually selected landmarks, visual assessment and consistency testing. It turns out that the mean error of the registration is better than the voxel resolution (2 x 2 x 3 mm(3)). In conclusion, we present an algorithm for fully automatic elastic image registration that is precise and fast enough for online corrections in an adaptive fractionated radiation treatment course.     

Simulation of four-dimensional CT images from deformable registration between inhale and exhale breath-hold CT scans

PURPOSE: We propose to simulate an artificial four-dimensional (4-D) CT image of the thorax during breathing. It is performed by deformable registration of two CT scans acquired at inhale and exhale breath-hold. MATERIALS AND METHODS: Breath-hold images were acquired with the ABC (Active Breathing Coordinator) system. Dense deformable registrations were performed. The method was a minimization of the sum of squared differences (SSD) using an approximated second-order gradient. Gaussian and linear-elastic vector field regularizations were compared. A new preprocessing step, called a priori lung density modification (APLDM), was proposed to take into account lung density changes due to inspiration. It consisted of modulating the lung densities in one image according to the densities in the other, in order to make them comparable. Simulated 4-D images were then built by vector field interpolation and image resampling of the two initial CT images. A variation in the lung density was taken into account to generate intermediate artificial CT images. The Jacobian of the deformation was used to compute voxel values in Hounsfield units. The accuracy of the deformable registration was assessed by the spatial correspondence of anatomic landmarks located by experts. RESULTS: APLDM produced statistically significantly better results than the reference method (registration without APLDM preprocessing). The mean (and standard deviation) of distances between automatically found landmark positions and landmarks set by experts were 2.7(1.1) mm with APLDM, and 6.3(3.8) mm without. Interexpert variability was 2.3(1.2) mm. The differences between Gaussian and linear elastic regularizations were not statistically significant. In the second experiment using 4-D images, the mean difference between automatic and manual landmark positions for intermediate CT images was 2.6(2.0) mm. CONCLUSION: The generation of 4-D CT images by deformable registration of inhale and exhale CT images is feasible. This can lower the dose needed for 4-D CT acquisitions or can help to correct 4-D acquisition artifacts. The 4-D CT model can be used to propagate contours, to compute a 4-D dose map, or to simulate CT acquisitions with an irregular breathing signal. It could serve as a basis for 4-D radiation therapy planning. Further work is needed to make the simulation more realistic by taking into account hysteresis and more complex voxel trajectories.     

Four-dimensional (4D) PET/CT imaging of the thorax

We have reported in our previous studies on the methodology, and feasibility of 4D-PET (Gated PET) acquisition, to reduce respiratory motion artifact in PET imaging of the thorax. In this study, we expand our investigation to address the problem of respiration motion in PET/CT imaging. The respiratory motion of four lung cancer patients were monitored by tracking external markers placed on the thorax. A 4D-CT acquisition was performed using a "step-and-shoot" technique, in which computed tomography (CT) projection data were acquired over a complete respiratory cycle at each couch position. The period of each CT acquisition segment was time stamped with an "x-ray ON" signal, which was recorded by the tracking system. 4D-CT data were then sorted into 10 groups, according to their corresponding phase of the breathing cycle. 4D-PET data were acquired in the gated mode, where each breathing cycle was divided into ten 0.5 s bins. For both CT and PET acquisitions, patients received audio prompting to regularize breathing. The 4D-CT and 4D-PET data were then correlated according to respiratory phase. The effect of 4D acquisition on improving the co-registration of PET and CT images, reducing motion smearing, and consequently increase the quantitation of the SUV, were investigated. Also, quantitation of the tumor motions in PET, and CT, were studied and compared. 4D-PET with matching phase 4D-CTAC showed an improved accuracy in PET-CT image co-registration of up to 41%, compared to measurements from 4D-PET with clinical-CTAC. Gating PET data in correlation with respiratory motion reduced motion-induced smearing, thereby decreasing the observed tumor volume, by as much as 43%. 4D-PET lesions volumes showed a maximum deviation of 19% between clinical CT and phase- matched 4D-CT attenuation corrected PET images. In CT, 4D acquisition resulted in increasing the tumor volume in two patients by up to 79%, and decreasing it in the other two by up to 35%. Consequently, these corrections have yielded an increase in the measured SUV by up to 16% over the clinical measured SUV, and 36% over SUV's measured in 4D-PET with clinical-CT Attenuation Correction (CTAC) SUV's. Quantitation of the maximum tumor motion amplitude, using 4D-PET and 4D-CT, showed up to 30% discrepancy between the two modalities. We have shown that 4D PET/CT is clinically a feasible method, to correct for respiratory motion artifacts in PET/CT imaging of the thorax. 4D PET/CT acquisition can reduce smearing, improve the accuracy in PET-CT co-registration, and increase the measured SUV. This should result in an improved tumor assessment for patients with lung malignancies.