Tinsu Pan

4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT.

We propose a new scanning protocol for generating 4D-CT image data sets influenced by respiratory motion. A cine scanning protocol is used during data acquisition, and two registration methods are used to sort images into temporal phases. A volume is imaged in multiple acquisitions of 1 or 2 cm length along the cranial-caudal direction. In each acquisition, the scans are continuously acquired for a time interval greater than or equal to the average respiratory cycle plus the duration of the data for an image reconstruction. The x ray is turned off during CT table translation and the acquisition is repeated until the prescribed volume is completely scanned. The scanning for 20 cm coverage takes about 1 min with an eight-slice CT or 2 mins with a four-slice CT. After data acquisition, the CT data are registered into respiratory phases based on either an internal anatomical match or an external respiratory signal. The internal approach registers the data according to correlation of anatomy in the CT images between two adjacent locations in consecutive respiratory cycles. We have demonstrated the technique with ROIs placed in the region of diaphragm. The external approach registers the image data according to an externally recorded respiratory signal generated by the Real-Time Position Management (RPM) Respiratory Gating System (Varian Medical Systems, Palo Alto, CA). Compared with previously reported prospective or retrospective imaging of the respiratory motion with a single-slice or multi-slice CT, the 4D-CT method proposed here provides (1) a shorter scan time of three to six times faster than the single-slice CT with prospective gating; (2) a shorter scan time of two to four times improvement over a previously reported multi-slice CT implementation, and (3) images over all phases of a breathing cycle. We have applied the scanning and registration methods on phantom, animal and patients, and initial results suggest the applicability of both the scanning and the registration methods.

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 patients 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 patients 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 patients 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.

Computed Tomography: from Photon Statistics to Modern Cone-Beam CT

This book provides an overview of x-ray technology, describes the historic developmental milestones of modern CT systems, and gives comprehensive insight into reconstruction methods. Its intended audience is graduate students in biomedical engineering, electrical engineering, and medical physics. This book is different from many books on x-ray physics and CT in the way the reconstruction methods are treated. There is an abundance of equations to describe the reconstruction methods for 2-dimensional CT and cone-beam CT. Scattered among many different journals are descriptions of the various CT reconstruction methods: from 2-dimensional parallel-beam, fanbeam, helical scan trajectory, and cardiac CT to 3-dimensional cone-beam. The author did an excellent job of bringing these descriptions together into a single book. The book consists of an introductory chapter followed by chapters on the fundamentals of x-ray physics, the milestones of CT, the fundamentals of signal processing, 2-dimensional Fourier-based reconstruction, algebraic and statistical reconstruction, technical implementations, 3-dimensional Fourier-based reconstruction, image quality and artifacts, practical aspects of CT, and dose. One drawback of this book is the 3-dimensional images. The sagittal and coronal images in Figures 1.8, 9.26, and 9.28 are not representative of images from modern CT scanners. I strongly recommend this book for students, scientists, and physicists who are interested in reconstruction theory and algorithms. For people who are not as interested in the equations, chapters 1–3 and 9–10 will enrich their knowledge of CT.

Frequent Diagnostic Errors in Cardiac PET/CT Due to Misregistration of CT Attenuation and Emission PET Images: A Definitive Analysis of Causes, Consequences, and Corrections

Cardiac PET combined with CT is rapidly expanding despite artifactual defects and false-positive results due to misregistration of PET and CT attenuation correction data—the frequency, cause, and correction of which remain undetermined. Methods: Two hundred fifty-nine consecutive patients underwent diagnostic rest–dipyridamole myocardial perfusion PET/CT using 82Rb, a 16-slice PET/CT scanner, helical CT attenuation correction with breathing and also at end-expiratory breath-hold, and averaged cine CT data during breathing. Misregistration on superimposed PET/CT fusion images was objectively measured in millimeters and correlated with associated quantitative size and severity of PET defects. Misregistration artifacts were defined as PET defects with corresponding misregistration on helical CT-PET fusion images that resolved after correct coregistration using a repeat CT scan, cine CT averaged attenuation during normal breathing, or shifted cine CT data that coregistered with PET data. Results: Misregistration of standard helical CT PET images caused artifactual PET defects in 103 of 259 (40%) patients that were moderate to severe in 59 (23%) (P = 0.0000) and quantitatively normalized on cine or shifted cine CT PET (P = 0.0000). Quantitative misregistration was a powerful predictor of artifact size and severity (P = 0.0000), particularly for transaxial misregistration >6 mm occurring in anterior or lateral areas in 76%, in inferior areas in 16%, and at the apex in 8% of 103 artifactual defects. Conclusion: Misregistration of helical CT attenuation and PET emission images causes artifactual defects with false-positive results in 40% of patients that normalize on cine CT PET using averaged CT attenuation data during normal breathing comparable to normal breathing during PET emission scanning and shifting cine CT images to coregister visually with PET.

Quantitation of respiratory motion during 4D-PET/CT acquisition

We report on the variability of the respiratory motion during 4D-PET/CT acquisition. The respiratory motion for five lung cancer patients was monitored by tracking external markers placed on the abdomen. CT data were acquired over an entire respiratory cycle at each couch position. The x-ray tube status was recorded by the tracking system, for retrospective sorting of the CT data as a function of respiration phase. Each respiratory cycle was sampled in ten equal bins. 4D-PET data were acquired in gated mode, where each breathing cycle was divided into ten 500 ms bins. For both CT and PET acquisition, patients received audio prompting to regularize breathing. The 4D-CT and 4D-PET data were then correlated according to their respiratory phases. The respiratory periods, and average amplitude within each phase bin, acquired in both modality sessions were then analyzed. The average respiratory motion period during 4D-CT was within 18% from that in the 4D-PET sessions. This would reflect up to 1.8% fluctuation in the duration of each 4D-CT bin. This small uncertainty enabled good correlation between CT and PET data, on a phase-to-phase basis. Comparison of the average-amplitude within the respiration trace, between 4D-CT and 4D- PET, on a bin-by-bin basis show a maximum deviation of approximately 15%. This study has proved the feasibility of performing 4D-PET/CT acquisition. Respiratory motion was in most cases consistent between PET and CT sessions, thereby improving both the attenuation correction of PET images, and co-registration of PET and CT images. On the other hand, in two patients, there was an increased partial irregularity in their breathing motion, which would prevent accurately correlating the corresponding PET and CT images.

A motion-incorporated reconstruction method for gated PET studies

Cardiac and respiratory motion artefacts in PET imaging have been traditionally resolved by acquiring the data in gated mode. However, gated PET images are usually characterized by high noise content due to their low photon statistics. In this paper, we present a novel 4D model for the PET imaging system, which can incorporate motion information to generate a motion-free image with all acquired data. A computer simulation and a phantom study were conducted to test the performance of this approach. The computer simulation was based on a digital phantom that was continuously scaled during data acquisition. The phantom study, on the other hand, used two spheres in a tank of water, all of which were filled with (18)F water. One of the spheres was stationary while the other moved in a sinusoidal fashion to simulate tumour motion in the thorax. Data were acquired using both 4D CT and gated PET. Motion information was derived from the 4D CT images and then used in the 4D PET model. Both studies showed that this 4D PET model had a good motion-compensating capability. In the phantom study, this approach reduced quantification error of the radioactivity concentration by 95% when compared to a corresponding static acquisition, while signal-to-noise ratio was improved by 210% when compared to a corresponding gated image.

Dynamic ventilation imaging from four-dimensional computed tomography

A novel method for dynamic ventilation imaging of the full respiratory cycle from four-dimensional computed tomography (4D CT) acquired without added contrast is presented. Three cases with 4D CT images obtained with respiratory gated acquisition for radiotherapy treatment planning were selected. Each of the 4D CT data sets was acquired during resting tidal breathing. A deformable image registration algorithm mapped each (voxel) corresponding tissue element across the 4D CT data set. From local average CT values, the change in fraction of air per voxel (i.e. local ventilation) was calculated. A 4D ventilation image set was calculated using pairs formed with the maximum expiration image volume, first the exhalation then the inhalation phases representing a complete breath cycle. A preliminary validation using manually determined lung volumes was performed. The calculated total ventilation was compared to the change in contoured lung volumes between the CT pairs (measured volume). A linear regression resulted in a slope of 1.01 and a correlation coefficient of 0.984 for the ventilation images. The spatial distribution of ventilation was found to be case specific and a 30% difference in mass-specific ventilation between the lower and upper lung halves was found. These images may be useful in radiotherapy planning.

Attenuation compensation for cardiac single-photon emission computed tomographic imaging: Part 1. Impact of attenuation and methods of estimating attenuation maps

Attenuation is believed to be one of the major causes of false-positive cardiac single-photon emission computed tomographic (SPECT) perfusion images. This article reviews the physics of attenuation, the artifacts produced by attenuation, and the need for scatter correction in combination with attenuation correction. The review continues with a comparison of the various configurations for transmission imaging that could be used to estimate patient specific attenuation maps, and an overview of how these are being developed for use on multiheaded SPECT systems, including discussions of truncation, noise, and spatial resolution of the estimated attenuation maps. Ways of estimating patient specific attenuation maps besides transmission imaging are also discussed.

Low Dose CT Reconstruction via Edge-preserving Total Variation Regularization

High radiation dose in computed tomography (CT) scans increases the lifetime risk of cancer and has become a major clinical concern. Recently, iterative reconstruction algorithms with total variation (TV) regularization have been developed to reconstruct CT images from highly undersampled data acquired at low mAs levels in order to reduce the imaging dose. Nonetheless, the low-contrast structures tend to be smoothed out by the TV regularization, posing a great challenge for the TV method. To solve this problem, in this work we develop an iterative CT reconstruction algorithm with edge-preserving TV (EPTV) regularization to reconstruct CT images from highly undersampled data obtained at low mAs levels. The CT image is reconstructed by minimizing energy consisting of an EPTV norm and a data fidelity term posed by the x-ray projections. The EPTV term is proposed to preferentially perform smoothing only on the non-edge part of the image in order to better preserve the edges, which is realized by introducing a penalty weight to the original TV norm. During the reconstruction process, the pixels at the edges would be gradually identified and given low penalty weight. Our iterative algorithm is implemented on graphics processing unit to improve its speed. We test our reconstruction algorithm on a digital NURBS-based cardiac-troso phantom, a physical chest phantom and a Catphan phantom. Reconstruction results from a conventional filtered backprojection (FBP) algorithm and a TV regularization method without edge-preserving penalty are also presented for comparison purposes. The experimental results illustrate that both the TV-based algorithm and our EPTV algorithm outperform the conventional FBP algorithm in suppressing the streaking artifacts and image noise under a low-dose context. Our edge-preserving algorithm is superior to the TV-based algorithm in that it can preserve more information of low-contrast structures and therefore maintain acceptable spatial resolution.

Comparison of helical and cine acquisitions for 4D-CT imaging with multislice CT

We proposed a data sufficiency condition (DSC) for four-dimensional-CT (4D-CT) imaging on a multislice CT scanner, designed a pitch factor for a helical 4D-CT, and compared the acquisition time, slice sensitivity profile (SSP), effective dose, ability to cope with an irregular breathing cycle, and gating technique (retrospective or prospective) of the helical 4D-CT and the cine 4D-CT on the General Electric (GE) LightSpeed RT (4-slice), Plus (4-slice), Ultra (8-slice) and 16 (16-slice) multislice CT scanners. To satisfy the DSC, a helical or cine 4D-CT acquisition has to collect data at each location for the duration of a breathing cycle plus the duration of data acquisition for an image reconstruction. The conditions for the comparison were 20 cm coverage in the cranial-caudal direction, a 4 s breathing cycle, and half-scan reconstruction. We found that the helical 4D-CT has the advantage of a shorter scan time that is 10% shorter than that of the cine 4D-CT, and the disadvantages of 1.8 times broadening of SSP and requires an additional breathing cycle of scanning to ensure an adequate sampling at the start and end locations. The cine 4D-CT has the advantages of maintaining the same SSP as slice collimation (e.g., 8 x 2.5 mm slice collimation generates 2.5 mm SSP in the cine 4D-CT as opposed to 4.5 mm in the helical 4D-CT) and a lower dose by 4% on the 8- and 16-slice systems, and 8% on the 4-slice system. The advantage of faster scanning in the helical 4D-CT will diminish if a repeat scan at the location of a breathing irregularity becomes necessary. The cine 4D-CT performs better than the helical 4D-CT in the repeat scan because it can scan faster and is more dose efficient.