Patient-specific Attenuation Map Research Articles

List-mode quantitative joint reconstruction of activity and attenuation maps in Time-of-Flight PET

Quantitative PET imaging requires accurate determination of patient-specific attenuation maps, which remains challenging on hybrid PET/MRI systems owing to the lack of a direct relationship between MR image intensity and attenuation coefficients. The aim of the present study is to develop a list-mode based algorithm for accurate and robust attenuation correction of PET data using time-of-flight (TOF) emission information. We analyze and address the challenges of list-mode emission-based maximum-likelihood joint estimation of activity and attenuation (LM-MLAA) in state-of-the-art PET imaging. The proposed method exploits a rapid on-the-fly system matrix calculation algorithm based on elliptic integrals while updating the attenuation map from accumulating list-mode coincidences to achieve accelerated image reconstruction. The scattering compensation is incorporated inside it using an iterative approach in such that the current estimation of attenuation map used on a course grid sampling scattering points to make an estimate of scattering. The performance of the proposed LM-MLAA approach was evaluated on Monte Carlo simulations of a phantom at different time resolutions. The contrast and noise for hot and cold regions on reconstructed images at different time resolutions were analysed. The estimated attenuation map exhibits resilience against noise, effectively eliminates high-frequency cross-talk even in the absence of prior information on attenuation coefficients, and enables discrimination among different anatomical regions in the reconstructed image. The error in the mean estimated attenuation coefficients after 50 iterations was ∼ 2% in water and ∼ -14% in Teflon regions for TOF resolutions corresponding to those of most current commercial PET systems (∼ 500 ps). The proposed LM-MLAA framework can be used for joint reconstruction of activity and attenuation maps from list-mode emission data as standalone or a complementary approach to existing in multimodality imaging such as PET/MRI, where direct measurement attenuation maps is not possible.

Deep learning for Dixon MRI-based attenuation correction in PET/MRI of head and neck cancer patients

BackgroundQuantitative whole-body PET/MRI relies on accurate patient-specific MRI-based attenuation correction (AC) of PET, which is a non-trivial challenge, especially for the anatomically complex head and neck region. We used a deep learning model developed for dose planning in radiation oncology to derive MRI-based attenuation maps of head and neck cancer patients and evaluated its performance on PET AC.MethodsEleven head and neck cancer patients, referred for radiotherapy, underwent CT followed by PET/MRI with acquisition of Dixon MRI. Both scans were performed in radiotherapy position. PET AC was performed with three different patient-specific attenuation maps derived from: (1) Dixon MRI using a deep learning network (PETDeep). (2) Dixon MRI using the vendor-provided atlas-based method (PETAtlas). (3) CT, serving as reference (PETCT). We analyzed the effect of the MRI-based AC methods on PET quantification by assessing the average voxelwise error within the entire body, and the error as a function of distance to bone/air. The error in mean uptake within anatomical regions of interest and the tumor was also assessed.ResultsThe average (± standard deviation) PET voxel error was 0.0 ± 11.4% for PETDeep and −1.3 ± 21.8% for PETAtlas. The error in mean PET uptake in bone/air was much lower for PETDeep (−4%/12%) than for PETAtlas (−15%/84%) and PETDeep also demonstrated a more rapidly decreasing error with distance to bone/air affecting only the immediate surroundings (less than 1 cm). The regions with the largest error in mean uptake were those containing bone (mandible) and air (larynx) for both methods, and the error in tumor mean uptake was −0.6 ± 2.0% for PETDeep and −3.5 ± 4.6% for PETAtlas.ConclusionThe deep learning network for deriving MRI-based attenuation maps of head and neck cancer patients demonstrated accurate AC and exceeded the performance of the vendor-provided atlas-based method both overall, on a lesion-level, and in vicinity of challenging regions such as bone and air.

Techniques for generating attenuation map using cardiac SPECT emission data only: a systematic review.

To reliably interpret and perform quantitative analysis, attenuation correction for cardiac single-photon emission computed tomography (SPECT) is fundamental. Thus, knowledge of the patient-specific attenuation map for accurate correction is required in SPECT quantitative imaging. The aim of this systematic review is to present general principles of attenuation correction and provide a structured summary of the approaches that have been proposed for generating the attenuation map for cardiac SPECT. We identified relevant articles published in English pertaining to the attenuation map (AM) determination using SPECT emission data only by searching PubMed, EMBASE, Scopus, and Web of Science databases. Moreover, other articles were hand searched. The protocol of this systematic review was registered in PROSPERO and the code given is CRD42017060512. Transmissionless techniques of determining attenuation map including calculated methods, statistical modeling for simultaneous estimation of attenuation and emission, consistency conditions criteria, using scattered data and other methods were reviewed. Methods for performing attenuation map for cardiac SPECT are developing and the progresses made are promising. However, much work is needed to assess the efficacy of the correction schemes in the clinical routine.

PATIENT-SPECIFIC DOSIMETRY FOR PEDIATRIC IMAGING OF 99mTc-DIMERCAPTOSUCCINIC ACID WITH GATE MONTE CARLO CODE.

In this study, radiation absorbed dose of 99mTc-dimercaptosuccinic acid (DMSA) in critical organs was calculated using Monte Carlo simulation. Ten child patients with genitourinary abnormalities were imaged using a series of planar, SPECT and MRI, after injection with 99mTc-DMSA. Patient-specific organ segmentation was performed on MRI and used as input in GATE. Organs with substantial uptake included kidneys, bladder and liver. The mean organ absorbed dose coefficients (mGy/MBq) were 0.063, 0.058, 0.018, 0.016, 0.013 and 0.010 for the right kidney, left kidney, bones, urinary bladder wall, liver and gonads, respectively. The absorbed dose coefficients in the remainder of the body was 0.012 mGy/MBq. The authors implemented an image-based Monte Carlo method for patient-specific 3D absorbed dose calculation. This study also demonstrates the possibility to obtain patient-specific attenuation map from MRI to be used for the simulations of radiation transport and energy deposition in phantom using Monte Carlo methods.

Multi-contrast attenuation map synthesis for PET/MR scanners: assessment on FDG and Florbetapir PET tracers.

Positron Emission Tomography/Magnetic Resonance Imaging (PET/MR) scanners are expected to offer a new range of clinical applications. Attenuation correction is an essential requirement for quantification of PET data but MRI images do not directly provide a patient-specific attenuation map. Methods We further validate and extend a Computed Tomography (CT) and attenuation map (μ-map) synthesis method based on pre-acquired MRI-CT image pairs. The validation consists of comparing the CT images synthesised with the proposed method to the original CT images. PET images were acquired using two different tracers (18F-FDG and 18F-florbetapir). They were then reconstructed and corrected for attenuation using the synthetic μ-maps and compared to the reference PET images corrected with the CT-based μ-maps. During the validation, we observed that the CT synthesis was inaccurate in areas such as the neck and the cerebellum, and propose a refinement to mitigate these problems, as well as an extension of the method to multi-contrast MRI data. Results With the improvements proposed, a significant enhancement in CT synthesis, which results in a reduced absolute error and a decrease in the bias when reconstructing PET images, was observed. For both tracers, on average, the absolute difference between the reference PET images and the PET images corrected with the proposed method was less than 2%, with a bias inferior to 1%. Conclusion With the proposed method, attenuation information can be accurately derived from MRI images by synthesising CT using routine anatomical sequences. MRI sequences, or combination of sequences, can be used to synthesise CT images, as long as they provide sufficient anatomical information.Electronic Supplementary MaterialThe online version of this article (doi:10.1007/s00259-015-3082-x) contains supplementary material, which is available to authorized users.

Attenuation correction synthesis for hybrid PET-MR scanners: application to brain studies.

Attenuation correction is an essential requirement for quantification of positron emission tomography (PET) data. In PET/CT acquisition systems, attenuation maps are derived from computed tomography (CT) images. However, in hybrid PET/MR scanners, magnetic resonance imaging (MRI) images do not directly provide a patient-specific attenuation map. The aim of the proposed work is to improve attenuation correction for PET/MR scanners by generating synthetic CTs and attenuation maps. The synthetic images are generated through a multi-atlas information propagation scheme, locally matching the MRI-derived patient's morphology to a database of MRI/CT pairs, using a local image similarity measure. Results show significant improvements in CT synthesis and PET reconstruction accuracy when compared to a segmentation method using an ultrashort-echo-time MRI sequence and to a simplified atlas-based method.

Classification of bones from MR images in torso PET-MR imaging using a statistical shape model

There have been exclusive features for hybrid PET/MRI systems in comparison with its PET/CT counterpart in terms of reduction of radiation exposure, improved soft-tissue contrast and truly simultaneous and multi-parametric imaging capabilities. However, quantitative imaging on PET/MR is challenged by attenuation of annihilation photons through their pathway. The correction for photon attenuation requires the availability of patient-specific attenuation map, which accounts for the spatial distribution of attenuation coefficients of biological tissues. However, the lack of information on electron density in the MR signal poses an inherent difficulty to the derivation of the attenuation map from MR images. In other words, the MR signal correlates with proton densities and tissue relaxation properties, rather than with electron density and, as such, it is not directly related to attenuation coefficients. In order to derive the attenuation map from MR images at 511keV, various strategies have been proposed and implemented on prototype and commercial PET/MR systems. Segmentation-based methods generate an attenuation map by classification of T1-weighted or high resolution Dixon MR sequences followed by assignment of predefined attenuation coefficients to various tissue types. Intensity-based segmentation approaches fail to include bones in the attenuation map since the segmentation of bones from conventional MR sequences is a difficult task. Most MR-guided attenuation correction techniques ignore bones owing to the inherent difficulties associated with bone segmentation unless specialized MR sequences such as ultra-short echo (UTE) sequence are utilized. In this work, we introduce a new technique based on statistical shape modeling to segment bones and generate a four-class attenuation map. Our segmentation approach requires a torso bone shape model based on principle component analysis (PCA). A CT-based training set including clearly segmented bones of the torso region of 20 clinical studies was designed. Using this training set, a bone atlas was trained taking advantage of PCA analysis. Our active shape segmentation technique uses the trained shape model to segment bones from user defined initial seed points. The segmentation algorithm was evaluated using 10 clinical datasets (aligned MR and CT pairs). The resulting attenuation maps were compared to corresponding attenuation maps derived from CT resulting in a mean relative difference less than 7%.

An APD-based iterative reconstruction method for simultaneous technetium-99m/iodine-123 SPECT imaging

Dual-isotope SPECT (DI-SPECT) studies offer significant advantages over sequential scans, foremost among them faster acquisition and perfect image registration. However, reconstructed images may be affected by substantial cross-talk contamination rendering them inadequate for diagnosis. This effect is especially strong for isotopes with close photopeak energies, such as 99mTc (140 keV) and 123I (159 keV). In this paper we present an iterative DI-SPECT reconstruction method which includes accurate, analytically computed scatter corrections provided by the APD (analytical photon distribution) algorithm. This algorithm calculates first and second order Compton scatter (based on the Klein–Nishina formula) and first order Rayleigh scatter. Both self-scatter and cross-talk between the two isotopes are evaluated using patient specific attenuation maps and an initial activity distribution estimate. To validate our method we performed experiments using the Data Spectrum, Inc. thorax phantom and a SPECT/CT camera system. Reconstructed images demonstrate significant improvement in data quantitation. Their quantitative accuracy increases up to a factor of two, even for activity ratios which strongly enhance cross-talk effects and seriously degrade projections.

The Impact of PET and SPECT on Dosimetry for Targeted Radionuclide Therapy

Targeted radionuclide therapy (TRT) is an increasingly used treatment modality for a range of cancers. To date, few treatments have involved the use of dosimetry either to plan treatment or to retrospectively ascertain the absorbed dose delivered during treatment. Also the correlation between absorbed dose and biological effect has been difficult to establish.Tomographic methods permit the determination of the activity volume on a macroscopic scale at different time points. Proper attenuation correction in tomographic imaging requires a patient-specific attenuation map. This can be obtained from scintillation-camera transmission scanning, CT, or by using segmented scatter-emission images. Attenuation corrections can be performed either on the projection images, on the reconstructed images, or as part of an iterative reconstruction method. The problem of image quantification for therapy radionuclides, particularly for I-131, is exacerbated by the fact that most cameras are optimised for diagnostic imaging with Tc-99m. In addition, problems may arise when high activities are to be measured due to count losses and mis-positioned events, because of insufficient pile-up and dead time correction methods.Sufficient image quantification, however, is only possible if all effects that degrade the quantitative content of the image have been corrected for. Monte Carlo simulations are an appealing tool that can help to model interactions occurring in the patient or in the detector system. This is helpful to develop and test correction techniques, or to help to define detectors better suited to quantitative imaging.PET is probably the most accurate imaging method for the determination of activity concentrations in tissue. PET imaging can be considered for pre-therapeutic treatment planning but ideally requires the use of a radioisotope from the same element as that used for treatment (e.g. I-124 for I-131; Y-86 for Y-90). Problems, however, are that–some of the positron emitting isotopes have a shorter half-life–non-standard quantification procedures have to be performed–the availability of the radiopharmaceutical is presently limited;Many 3D-tools and -techniques are now available to the physicist and clinician to enable absorbed dose calculations to both target and critical organs-at-risk. The challenge now facing nuclear medicine is to enable this methodology to be routinely available to the clinic, to ensure common standard operating procedures between centres and in particular to correlate response criteria with absorbed dose estimates.

Atlas-guided non-uniform attenuation correction in cerebral 3D PET imaging

Photon attenuation in tissues is the primary physical degrading factor limiting both visual qualitative interpretation and quantitative analysis capabilities of reconstructed Positron Emission Tomography (PET) images. This study investigates the implementation and applicability of transmission atlas-guided attenuation correction in cerebral 3D PET imaging, thus eliminating the need for acquisition of a measured transmission scan. Patient-specific attenuation map is derived by anatomic standardization through nonlinear warping of a stereotactic transmission template obtained by averaging 11 scans of normal subjects. This template is coregistered to a specially designed tracer-specific 18F-[FDG] template constructed by scanning 17 normal subjects in resting condition during tracer uptake in a dark room. This emission template is first coregistered and spatially normalized to preliminary PET images of subjects corrected for scatter and attenuation using an approximate calculated method. The resulting transformation matrices are recorded and re-applied to the transmission template. The derived attenuation map is then forward projected to generate attenuation correction factors to be used for correcting the subjects' PET data. Twelve cerebral clinical studies are used for evaluation of the developed attenuation correction technique as compared to the standard pre-injection measured transmission-based method used in clinical routine. Statistical Parametric Mapping (SPM2) analysis is used to assess significant differences between images obtained using both techniques. The subjective qualitative assessment shows no significant visual differences between atlas-guided and transmission-based attenuation correction methods. However, the quantitative voxel-based analysis comparing atlas-guided to transmission-based attenuation corrections suggest that regional brain metabolic activity increases significantly bilaterally in the superior frontal and precentral gyri, in addition to the left middle temporal gyrus and the left frontal lobe. Conversely, activity decreases in the corpus callosum in the left parasagittal region. A new non-uniform attenuation correction method is thus proposed, which is suitable for both research and clinical routine applications in 3D brain PET imaging on a transmissionless PET scanner or when a patient-specific transmission scan is not available.

Numerical Observer Study of MAP-OSEM Regularization Methods With Anatomical Priors for Lesion Detection in<tex>$^67$</tex>Ga Images

With the increasing number of multimodality systems, registered anatomical data is becoming available for use as patient-specific attenuation maps and anatomical priors in iterative reconstruction. The goal of this work is to investigate whether the introduction of anatomical information in MAP-EM reconstruction can improve lesion detection in /sup 67/Ga images of the chest region. Specifically we investigated three hypotheses. The first hypothesis was that use of information on organ boundaries in MAP-EM will increase the accuracy of tumor detection. The second hypothesis was that use of lesion boundaries in addition to organ boundaries will increase the detection accuracy of lesions when the lesion actually has an elevated concentration of activity compared to background. The third hypothesis was that use of the organ boundary prior in MAP-EM results in improved lesion detection accuracy for lesions with an elevated activity concentration even when the lesion boundary prior was also used for sites where there was not an elevated activity concentration. These hypotheses were investigated using Monte Carlo simulated projections of the mathematical cardiac-torso (MCAT) phantom. The organ and lesion boundaries for use as anatomical priors were obtained from segmentation of the original MCAT activity slices. The priors were used to determine voxel inclusion in the neighborhood of a voxel for a quadratic smoothing prior employed in De Pierro's MAP-OSEM reconstruction algorithm. Two contrasts for lesion/background were investigated, 12/1, and 22.5/1. Three values for /spl beta/, the parameter controlling the weighting of the prior, were also investigated. A numerical observer was used to determine the average lesion detection accuracy for multiple sites throughout the mediastinum. The area under the ROC curve (AUC) for the numerical observer was used as the metric for detection accuracy. No evidence was observed in support of the first hypothesis. That is, use of the anatomical prior including just organ boundaries did not tend to increase the AUC over that of not using priors. Evidence was found in support of the second hypothesis however. That is, especially for the lower contrast lesions, the AUC increased when the lesion boundary was included in the prior. Finally, evidence was also observed in support of the third hypothesis. That is, again especially at the lower contrast, the use of the anatomical prior increased detection accuracy for lesions with increased uptake even when the prior was also used for matching sites with no elevation in uptake. Thus, use of the anatomical prior for lesion boundary when there was no elevated lesion uptake did not tend to increase the false-positive rate as one might have guessed would happen.

Use of asymmetric fan‐beam transmission computed tomography for attenuation correction of cardiac SPECT imaging

Photon attenuation is often the largest source of infidelity in cardiac single photon emission computed tomography (SPECT). This investigation evaluates the feasibility of using an asymmetric fan‐beam transmission CT (AsF–TCT), acquired immediately before or after the emission computed tomogram (ECT), to correct for photon attenuation in cardiac SPECT. AsF–TCTs are reconstructed to generate patient‐specific attenuation maps. The maps are used with an iterative maximum‐likelihood algorithm to reconstruct attenuation‐corrected (AC) SPECT images. AsF attenuation correction significantly improves the accuracy of images of a cardiac‐thorax phantom modeling a large patient with a normal myocardial perfusion study. Similar improvements in image uniformity are obtained for patient studies. Using a high‐activity line source and rapid camera rotation, a suitable attenuation map is obtained with a four minute transmission acquisition; shorter acquisitions could be used for SPECT systems with higher count‐rate performance. Misregistration between the ECT and TCT can create artifacts in the reconstructed AC images, with lateral patient shifts as small as 2–3 cm causing severe artifacts. Axial, anterior‐posterior, and rotational misregistrations require larger shifts before artifacts become significant. Finally, applying AC improves assessments of both defect size and severity. Without AC, cardiac SPECT can significantly over‐estimate the size of perfusion defects, particularly in the septum and inferior wall of the left ventricle. AC improves estimates of lesion severity and results in better contrast between adjacent normal and defect regions. This investigation demonstrates that AsF–TCT is a viable technique for attenuation correction for cardiac SPECT, and may improve the diagnostic accuracy of this modality.

Estimation of attenuation maps from scatter and photopeak window single photon-emission computed tomographic images of technetium 99m-labeled sestamibi

Background. In single photon-emission computed tomographic imaging of the chest, nonuniform attenuation correction requires use of a patient-specific attenuation map. The aim of this study was to determine whether an estimate of the regions of the lungs and nonpulmonary tissues of the chest could be obtained by segmenting the photopeak and Compton scatter window images in a phantom and in patients to estimate patient-specific attenuation maps. Methods and Results. The photopeak and scatter window slices from 16 consecutive 99mTc-labeled sestamibi perfusion studies were segmented interactively. In these studies, visually reasonable regions could be obtained by estimating a “cold” lung region from scatter window data with additional anatomic information of the myocardium region, the backbone and sternum locations, the liver, and the rib cage from the photopeak window data. In an anthropomorphic torso phantom study and a patient study, comparison was made between the attenuation maps based on segmentation of the emission images and transmission imaging with a slant-hole collimator. It was determined that good agreement in the estimation of the body regions can be achieved with segmentation of the emission images in both the phantom and patient data. Attenuation correction using the maximum-likelihood expectation maximization method was performed on the phantom and the patient data. In both studies, attenuation correction with the segmented attenuation map improved uniformity of the inferior wall region in comparison with the other walls. Conclusions. The estimation of patient-specific attenuation maps by segmenting the scatter and photopeak window slices of 99mTc-labeled sestamibi studies may be a way of reducing the loss of specificity due to attenuation artifacts. The potential limitations on the accuracy of correction inherent in the method due to the estimation of the regions and assignment of the attenuation coefficients need to be determined further, and the method needs to be further automated before it can be considered for routine clinical use.

Segmentation of the body and lungs from Compton scatter and photopeak window data in SPECT: a Monte-Carlo investigation

In SPECT imaging of the chest, nonuniform attenuation correction requires use of a patient specific attenuation (mu) map. Such a map can be obtained by estimating the regions of (1) the lungs and (2) the soft tissues and bones, and then assigning an appropriate value of attenuation coefficient (mu) to each region. The authors proposed a method to segment such regions from the Compton scatter and photopeak window SPECT slices of Tc-99m Sestamibi studies. The Compton scatter slices are used to segment the body outline and to estimate the regions of the lungs. Locations of the back bone and sternum are estimated from the photopeak window slices to assist in the segmentation. To investigate the accuracy of using Compton scatter slices in estimating the regions of the body and the lungs, a Monte-Carlo SPECT simulation of an anthropomorphic phantom with an activity distribution and noise characteristics similar to patient data was conducted. Energy windows of various widths were simulated for use in locating a suitable Compton scatter window for imaging, The effects of attenuation correction using a mu map based on segmentation were also studied. The results demonstrated for the activity and mu maps studied herein that: (1) reasonable contrast could be obtained from Compton scatter data for the segmentation of the lung regions, (2) true positive rates of 99% and 89% for determining the body and lung regions, respectively, with total error rates of 4% and 29%, could be achieved, (3) usage of a mu map based on segmentation for attenuation correction improved relative quantification over filtered backprojection, (4) variations in the assigned mu value of 40% smaller or 40% larger in the lung regions had an insignificant impact on the results of relative quantification, (5) a wide energy window away from the photopeak window for recording scattered events could benefit both the segmentation of the lung regions and the attenuation correction of the activity in the myocardium region, and (6) usage of a smaller than true mu value in the lung regions of an assigned mu map might benefit attenuation correction for absolute quantification.

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.

Noise, resolution, and sensitivity considerations in the design of a single‐slice emission–transmission computed tomographic system

A prototype Emission-Transmission Computed Tomography (ETCT) system is being developed that will acquire single-slice x-ray transmission CT images simultaneously with single photon emission computed tomography (SPECT) images. This system will permit the correlation of anatomical information from x-ray CT with functional information from SPECT images. The patient-specific attenuation map derived from the x-ray CT images can be used to perform attenuation correction of the SPECT images, so that accurate quantitative information can be obtained. The fan-beam scanning geometry and the use of a segmented HPGe detector array impose special constraints on the design of the collimator for the system. Based on a signal detection model, an efficiency-resolution figure of merit (ERFM) as a function of the collimator geometric efficiency, system resolution width, and object diameter is defined. The ERFM is proportional to the square of the detection signal-to-noise ratio. The collimator design parameters can then be optimized by optimizing the ERFM for an anticipated object diameter. The collimator point-spread function, geometric efficiency, and resolution are calculated. The collimator optimized for the detection of a 1-cm object will have a single-slice point source efficiency of 1.2 X 10(-4), and a FWHM of 6.5 mm at the center of the reconstruction circle, at 12 cm from the collimator face. The minimum object contrast which will give a detection SNR of 5 is 74%, for a total accumulated count per slice of 2 X 10(6).