CT-based Attenuation Map Research Articles

Deep learning approximation of attenuation maps for myocardial perfusion SPECT with an IQvarvec{cdot {}}SPECT collimator

BackgroundThe use of CT images for attenuation correction of myocardial perfusion imaging with single photon emission computer tomography (SPECT) increases diagnostic confidence. However, acquiring a CT image registered to a SPECT image is often not possible because most scanners are SPECT-only. It is possible to approximate attenuation maps using deep learning, but this has not yet been shown to work for a SPECT scanner with an IQvarvec{cdot {}}SPECT collimator. This study investigates whether it is possible to approximate attenuation maps from non-attenuation-corrected (nAC) reconstructions acquired with a SPECT scanner equipped with an IQvarvec{cdot {}}SPECT collimator.MethodsAttenuation maps and reconstructions were acquired retrospectively for 150 studies. A U–Net was trained to predict attenuation maps from nAC reconstructions using the conditional generative adversarial network framework. Predicted attenuation maps are compared to real attenuation maps using the normalized mean absolute error (NMAE). Attenuation-corrected reconstructions were computed, and the resulting polar maps were compared by pixel and by average perfusion per segment using the absolute percent error (APE). The training and evaluation code is available at https://gitlab.ub.uni-bielefeld.de/thuxohl/mu-map.ResultsPredicted attenuation maps are similar to real attenuation maps, achieving an NMAE of 0.020±0.007. The same is true for polar maps generated from reconstructions with predicted attenuation maps compared to CT-based attenuation maps. Their pixel-wise absolute distance is 3.095±3.199, and the segment-wise APE is 1.155±0.769.ConclusionsIt is feasible to approximate attenuation maps from nAC reconstructions acquired by a scanner with an IQvarvec{cdot {}}SPECT collimator using deep learning.

Attenuation Correction for Dedicated Cardiac SPECT Imaging Without Using Transmission Data.

Attenuation correction (AC) using transmission scanning-like computed tomography (CT) is the standard method to increase the accuracy of cardiac single-photon emission computed tomography (SPECT) images. Recently developed dedicated cardiac SPECT do not support CT, and thus, scans on these systems are vulnerable to attenuation artifacts. This study presented a new method for generating an attenuation map directly from emission data by segmentation of precisely non-rigid registration extended cardiac-torso (XCAT)-digital phantom with cardiac SPECT images. In-house developed non-rigid registration algorithm automatically aligns the XCAT- phantom with cardiac SPECT image to precisely segment the contour of organs. Pre-defined attenuation coefficients for given photon energies were assigned to generate attenuation maps. The CT-based attenuation maps were used for validation with which cardiac SPECT/CT data of 38 patients were included. Segmental myocardial counts of a 17-segment model from these databases were compared based on the basis of the paired t-test. The mean, and standard deviation of the mean square error and structural similarity index measure of the female stress phase between the proposed attenuation maps and the CT attenuation maps were 6.99±1.23% and 92±2.0%, of the male stress were 6.87±3.8% and 96±1.0%. Proposed attenuation correction and computed tomography based attenuation correction average myocardial perfusion count was significantly higher than that in non-AC in the mid-inferior, mid-lateral, basal-inferior, and lateral regions (p<0.001). The proposed attenuation maps showed good agreement with the CT-based attenuation map. Therefore, it is feasible to enable AC for a dedicated cardiac SPECT or SPECT standalone scanners.

Deep learning-based attenuation map generation with simultaneously reconstructed PET activity and attenuation and low-dose application

Objective. In PET/CT imaging, CT is used for positron emission tomography (PET) attenuation correction (AC). CT artifacts or misalignment between PET and CT can cause AC artifacts and quantification errors in PET. Simultaneous reconstruction (MLAA) of PET activity (λ-MLAA) and attenuation (μ-MLAA) maps was proposed to solve those issues using the time-of-flight PET raw data only. However, λ-MLAA still suffers from quantification error as compared to reconstruction using the gold-standard CT-based attenuation map (μ-CT). Recently, a deep learning (DL)-based framework was proposed to improve MLAA by predicting μ-DL from λ-MLAA and μ-MLAA using an image domain loss function (IM-loss). However, IM-loss does not directly measure the AC errors according to the PET attenuation physics. Our preliminary studies showed that an additional physics-based loss function can lead to more accurate PET AC. The main objective of this study is to optimize the attenuation map generation framework for clinical full-dose 18F-FDG studies. We also investigate the effectiveness of the optimized network on predicting attenuation maps for synthetic low-dose oncological PET studies. Approach. We optimized the proposed DL framework by applying different preprocessing steps and hyperparameter optimization, including patch size, weights of the loss terms and number of angles in the projection-domain loss term. The optimization was performed based on 100 skull-to-toe 18F-FDG PET/CT scans with minimal misalignment. The optimized framework was further evaluated on 85 clinical full-dose neck-to-thigh 18F-FDG cancer datasets as well as synthetic low-dose studies with only 10% of the full-dose raw data. Main results. Clinical evaluation of tumor quantification as well as physics-based figure-of-merit metric evaluation validated the promising performance of our proposed method. For both full-dose and low-dose studies, the proposed framework achieved <1% error in tumor standardized uptake value measures. Significance. It is of great clinical interest to achieve CT-less PET reconstruction, especially for low-dose PET studies.

Post-reconstruction attenuation correction for SPECT myocardium perfusion imaging facilitated by deep learning-based attenuation map generation

BackgroundAttenuation correction can improve the quantitative accuracy of single-photon emission computed tomography (SPECT) images. Existing SPECT-only systems normally can only provide non-attenuation corrected (NC) images which are susceptible to attenuation artifacts. In this work, we developed a post-reconstruction attenuation correction (PRAC) approach facilitated by a deep learning-based attenuation map for myocardial perfusion SPECT imaging. MethodsIn the PRAC method, new projection data were estimated via forwardly projecting the scanner-generated NC image. Then an attenuation map, generated from NC image using a pretrained deep learning (DL) convolutional neural network, was incorporated into an offline reconstruction algorithm to obtain the attenuation-corrected images from the forwardly projected projections. We evaluated the PRAC method using 30 subjects with a DL network trained with 40 subjects, using the vendor-generated AC images and CT-based attenuation maps as the ground truth. ResultsThe PRAC methods using DL-generated and CT-based attenuation maps were both highly consistent with the scanner-generated AC image. The globally normalized mean absolute errors were 1.1% ± .6% and .7% ± .4% and the localized absolute percentage errors were 8.9% ± 13.4% and 7.8% ± 11.4% in the left ventricular (LV) blood pool, respectively, and − 1.3% ± 8.0% and − 3.8% ± 4.5% in the LV myocardium for PRAC methods using DL-generated and CT-based attenuation maps, respectively. The summed stress scores after PRAC using both attenuation maps were more consistent with the ground truth than those of the NC images. ConclusionWe developed a PRAC approach facilitated by deep learning-based attenuation maps for SPECT myocardial perfusion imaging. It may be feasible for this approach to provide AC images for SPECT-only scanner data.

Comparison of maximum likelihood and conventional PET scatter scaling methods for 18 F-FDG and 68 Ga-DOTATATE PET/CT.

We aim to quantify differences between a new maximum likelihood (ML) background scaling (MLBS) algorithm and two conventional scatter scaling methods for clinical PET/CT. A common source of reduced image quantification with conventional scatter corrections is attributed to erroneous scaling of the initial scatter estimate to match acquired scattered events in the sinogram. MLBS may have performance advantages over conventional methods by using all available data intersecting the subject. A retrospective analysis was performed on subjects injected with 18 F-FDG (N=71) and 68 Ga-DOTATATE (N=11) and imaged using time-of-flight (TOF) PET/CT. The scatter distribution was estimated with single scatter simulation approaches. Conventional scaling algorithms included (a) tail fitted background scaling (TFBS), which scales the scatter to "tails" outside the emission support, and (b) absolute scatter correction (ABS), which utilizes the simulated scatter distribution with no scaling applied. MLBS consisted of an alternating iterative reconstruction with a TOF-based ML activity image update allowing negative values (NEG-ML) and nested loop ML scatter scaling estimation. Scatter corrections were compared using reconstructed images as follows: (a) normalized relative difference images were generated and used for voxel-wise analysis, (b) liver and suspected lesion ROIs were drawn to compute mean SUVs, and (c) a qualitative analysis of overall diagnostic image quality, impact of artifacts, and lesion conspicuity was performed. Absolute quantification and normalized relative differences were also assessed with an 18 F-FDG phantom study. For human subjects 18 F-FDG data, Bland-Altman plots demonstrated that the largest normalized voxel-wise differences were observed close to the lower limit (SUV=1.0). MLBS reconstructions trended towards higher scatter fractions compared to TFBS and ABS images, with median voxel differences across all subjects for TFBS-MLBS measured at 1.7% and 7.6% for 18 F-FDG and 68 Ga-DOTATATE, respectively. For mean SUV analysis, there was a high degree of correlation between the scatter corrections. For 18 F-FDG, ABS scatter correction reconstructions trended towards higher liver mean SUVs relative to MLBS. The qualitative image analysis revealed no significant differences between TFBS and MLBS image reconstructions. For a uniformly filled relatively large 37cm diameter phantom, MLBS produced the lowest bias in absolute quantification, while normalized voxel-wise differences showed a trend in scatter correction performance consistent with the human subjects study. For 18 F-FDG, MLBS is at least a valid substitute to TFBS, providing reconstructed image performance comparable to TFBS in most subjects but exhibiting quantitative differences in cases where TFBS is typically prone to inaccuracies (e.g., due to patient motion and CT-based attenuation map truncation). Particularly for low contrast regions, quantification differs for ABS compared to MLBS and TFBS, and caution should be taken when utilizing ABS for decision-making based on quantitative metrics.

CT-based attenuation correction of whole-body radiotherapy treatment positioning devices in PET/MRI hybrid imaging

Objective.To implement computed tomography (CT)-based attenuation maps of radiotherapy (RT) positioning hardware and radiofrequency (RF) coils to enable hybrid positron emission tomography/magnetic resonance imaging (PET/MRI)-based RT treatment planning. Materials and Methods. The RT positioning hardware consisted of a flat RT table overlay, coil holders for abdominal scans, coil holders for head and neck scans and an MRI compatible hip and leg immobilization device. CT images of each hardware element were acquired on a CT scanner. Based on the CT images, attenuation maps of the devices were created. Validation measurements were performed on a PET/MR scanner using a 68Ge phantom (48 MBq, 10 min scan time). Scans with each device in treatment position were performed. Then, reference scans containing only the phantom were taken. The scans were reconstructed online (at the PET/MRI scanner) and offline (via e7tools on a PC) using identical reconstruction parameters. Average reconstructed activity concentrations of the device and reference scans were compared. Results. The device attenuation maps were successfully implemented. The RT positioning devices caused an average decrease of reconstructed PET activity concentration in the range between −8.3 ± 2.1% (mean ± SD) (head and neck coil holder with coils) to −1.0 ± 0.5% (abdominal coil holder). With attenuation correction taking into account RT hardware, these values were reduced to −2.0 ± 1.2% and −0.6 ± 0.5%, respectively. The results of the offline and online reconstructions were nearly identical, with a difference of up to 0.2%. Conclusion. The decrease in reconstructed activity concentration caused by the RT positioning devices is clinically relevant and can successfully be corrected using CT-based attenuation maps. Both the offline and online reconstruction methods are viable options.

Deep learning-based attenuation map generation for myocardial perfusion SPECT.

Attenuation correction using CT transmission scanning increases the accuracy of single-photon emission computed tomography (SPECT) and enables quantitative analysis. Current existing SPECT-only systems normally do not support transmission scanning and therefore scans on these systemsare susceptible to attenuation artifacts. Moreover, the use of CT scans also increases radiation dose to patients and significant artifacts can occur due to the misregistration between the SPECT and CT scans as a result of patient motion. The purpose of this study is to develop an approach to estimate attenuation maps directly from SPECT emission data using deep learning methods. Both photopeak window and scatter window SPECT images were used as inputs to better utilize the underlying attenuation information embedded in the emission data. The CT-based attenuation maps were used as labels with which cardiac SPECT/CT images of 65 patients were included for training and testing. We implemented and evaluated deep fully convolutional neural networks using both standard training and training using an adversarial strategy. The synthetic attenuation maps were qualitatively and quantitatively consistent with the CT-based attenuation map. The globally normalized mean absolute error (NMAE) between the synthetic and CT-based attenuation maps were 3.60% ± 0.85% among the 25 testing subjects. The SPECT reconstructed images corrected using the CT-based attenuation map and synthetic attenuation map are highly consistent. The NMAE between the reconstructed SPECT images that were corrected using the synthetic and CT-based attenuation maps was 0.26% ± 0.15%, whereas the localized absolute percentage error was 1.33% ± 3.80% in the left ventricle (LV) myocardium and 1.07% ± 2.58% in the LV blood pool. We developed a deep convolutional neural network to estimate attenuation maps for SPECT directly from the emission data. The proposed method is capable of generating highly reliable attenuation maps to facilitate attenuation correction for SPECT-only scanners for myocardial perfusion imaging.

Validation of MR-Based Attenuation Correction of a Newly Released Whole-Body Simultaneous PET/MR System.

The aim of this study was to validate quantitative performance of a newly released simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) scanner, by using MR-based attenuation correction (MRAC), both in phantom study and in patient study. PET/MRI image uniformities of a phantom under different hardware configurations were tested and compared. Thirty patients were examined with 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) PET/computed tomography (CT) and subsequent PET/MRI. PET images from PET/MRI were corrected with MRAC (PETMR), CT-based attenuation maps (μ-maps, PETCT), and segmented CT μ-maps (PETCTSeg) derived from PET/CT. Standardized uptake values (SUVs) were compared among the 3 sets of PET in main organs (bone, liver and lung) and in 52 FDG-avid lesions, including soft-tissue lesions and bone lesions. The result showed that PET imaging uniformities of PET/MRI under different configurations were good (<8.8%). The SUV differences among the 3 sets of PET varied with organs and lesion types. In detail, the mean relative differences of SUV between PETMR and PETCT were as follows: −18.8%, bone (SUVmean); −8.0%, liver (SUVmean); −12.2%, lung (SUVmean); −18.1%, bone lesions (SUVmean); −13.3%, bone lesions (SUVmax); −8.2%, soft-tissue lesions (SUVmean); and −7.3%, soft-tissue lesions (SUVmax). The mean relative differences between PETMR and PETCTSeg were as follows: −19.0%, bone (SUVmean); −3.5%, liver (SUVmean); −3.3%, lung (SUVmean); −19.3%, bone lesions (SUVmean); −17.5%, bone lesions (SUVmax); −5.5%, soft-tissue lesions (SUVmean); and −4.4%, soft-tissue lesions (SUVmax). The differences of SUV between PETMR and PETCT were larger than those between PETMR and PETCTSeg, in both soft tissue and soft-tissue lesions (P < 0.001), but not in bone or bone lesions. In conclusion, MRAC in the newly released PET/MR system is accurate in most tissues, with SUV deviations being generally less than 10%, compared to PET/CT. In bone, however, underestimations can be substantial, which may be partially attributed to segmentation of the MR-based μ-maps.

EP-2050 Implementation of CT-based attenuation maps of RT positioning devices in PET/MRI -online vs offline

EP-2050 Implementation of CT-based attenuation maps of RT positioning devices in PET/MRI -online vs offline

A dual-tuned 13 C/1 H head coil for PET/MR hybrid neuroimaging: Development, attenuation correction, and first evaluation.

This study aims to develop, implement, and evaluate a dual-tuned 13 C/1 H head coil for integrated positron emission tomography/magnetic resonance (PET/MR) neuroimaging. The radiofrequency (RF) head coil is designed for optimized MR imaging performance and PET transparency and attenuation correction (AC) is applied for accurate PET quantification. A dual-tuned 13 C/1 H RF head coil featuring a 16-rung birdcage was designed to be used for integrated PET/MR hybrid imaging. While the open birdcage design can be considered inherently PET transparent, all further electronic RF components were placed as far as possible outside of the field-of-view (FOV) of the PET detectors. The RF coil features a rigid geometry and thin-walled casing. Attenuation correction of the RF head coil is performed by generating and applying a dedicated 3D CT-based template attenuation map (μmap). Attenuation correction was systematically evaluated in phantom experiments using a large-volume cylindrical emission phantom filled with 18-F-Fluordesoxyglucose (FDG) radiotracer. The PET/MR imaging performance and PET attenuation correction were then evaluated in a patient study including six patients. The dual-tuned RF head coil causes a mean relative attenuation difference of 8.8% across the volume of the cylindrical phantom, while the local relative differences range between 1% and 25%. Applying attenuation correction, the relative difference between the two measurements with and without RF coil is reduced to mean value of 0.5%, with local differences of ±3.6%. The quantitative results of the phantom measurements were corroborated by patient PET/MR measurements. Patient scans using the RF head coil show a decrease of PET signal of 5.17% ± 0.81% when compared to the setup without RF head coil in place, which served as a reference scan. When applying attenuation correction of the RF coil in the patient measurements, the mean difference to a measurement without RF coil was reduced to -0.87% ± 0.65%. A dual-tuned 13 C/1 H RF head coil was designed and evaluated regarding its potential use in integrated PET/MR hybrid imaging. Attenuation correction was successfully applied. In conclusion, the RF head coil was successfully integrated into PET/MR hybrid imaging and can now be used for 13 C/1 H multinuclear hybrid neuroimaging in future studies.

Performance evaluation of RF coils integrated with an RF-penetrable PET insert for simultaneous PET/MRI.

An "RF-penetrable" PET insert that allows the MR body coil to be used for RF transmission was developed to make it easier for an existing MR center to achieve simultaneous PET/MRI. This study focuses on experiments and analyses to study PET/RF coil configurations for simultaneous PET/MR studies. To investigate the appropriate RF coil design, a transmit/receive (TX/RX) birdcage coil and an RX-only phased-array coil (TX from body coil), both fitting inside the PET ring were built and characterized. For MR performance evaluation, B1 field uniformity and MR image SNR were calculated. PET photon attenuation due to each coil was studied by means of CT-based attenuation maps and reconstructed PET images. When using the RX-only phased-array coil (TX from body coil), compared with the TX/RX birdcage coil, the B1 field uniformity and the MR image (gradient echo and fast spin echo) SNR increased by 2.4±4.8%, 386.1±62.3%, and 205.0±56.5%, respectively. Although some components of the coil were distributed within the PET FOV, no significant PET photon attenuation was shown in the CT-based attenuation map and reconstructed PET images. RF coil configurations for an RF-penetrable PET insert for simultaneous PET/MRI were studied. The RX-only phased-array coil (TX from body coil) outperformed the TX/RX birdcage coil with improved MR performance as well as negligible PET photon attenuation.

Zero-Extra-Dose PET Delayed Imaging with Data-Driven Attenuation Correction Estimation.

Delayed positron emission tomography (PET) imaging may improve sensitivity and specificity in lesion detection. We proposed a PET data-driven method to estimate the attenuation map (AM) for the delayed scan without an additional x-ray computed tomography (CT). An emission-attenuation-scatter joint estimation framework was developed. Several practical issues for clinical datasets were addressed. Particularly, the unknown scatter correction was incorporated in the joint estimation algorithm. The scaling problem was solved using prior information from the early CT scan. Fourteen patient datasets were added to evaluate the method. These patients went through two separate PET/CT scans. The delayed CT-based AM served as ground truth for the delayed scan. Standard uptake values (SUVmean and SUVmax) of lesion and normal tissue regions of interests (ROIs) in the early and delayed phase and the respective %DSUV (percentage change of SUVmean at two different time points) were analyzed, all with estimated and the true AM. Three radiologists participated in lesion detection tasks with images reconstructed with both AMs and rated scores for detectability. The mean relative difference of SUVmean in lesion and normal liver tissue were 3.30 and 6.69%. The average lesion-to-background contrast (detectability) with delayed PET images using CT AM was 60% higher than that of the earlier PET image, and was 64% higher when using the data-based AM. %DSUV for lesions and liver backgrounds with CT-based AM were - 0.058 ± 0.25 and - 0.33 ± 0.08 while with data-based AM were - 0.00 ± 0.26 and - 0.28 ± 0.08. Only slight significance difference was found between using CT-based AM and using the data-based AM reconstruction delay phase on %DSUV of lesion. The scores associated with the two AMs matched well consistently. Our method may be used in delayed PET imaging, which allows no secondary CT radiation in delayed phase. The quantitative analysis for lesion detection purpose could be ensured.

The effect of tissue-segmented attenuation maps on PET quantification with a special focus on large arteries

ObjectivesAccuracy on quantitative PET image analysis relies on the correct application of attenuation correction which is one of the major challenges for PET/MRI that remains to be solved. The purpose of this study is to evaluate the effect of MRI-based attenuation maps and the use of flexible coils on the quantitative accuracy of PET images with a special focus on large arteries. Materials and methodsPET/CT data from eight oncologic patients was used. PET data was reconstructed using attenuation maps with different level of detail emulating several approaches available on current PET/MRI scanners. PET images obtained with CT-based and MRI-based attenuation maps were compared to evaluate the quantitative biases obtained. The quantitative effect produced by flexible MRI receiver coils on the attenuation maps was also studied. ResultsThe use of simpler attenuation maps produced increased biases between PET data reconstructed with CT-based and MRI-based attenuation maps for fat, non-fat soft-tissues and bone. Biases in lung were very high due to the large heterogeneity and inter-patient variability of the lung. The quantification on large arteries had small deviations except for the case when flexible coils were used. The TBRprovided smaller biases in all cases as it cancelled out the similar deviations obtained for arteries and reference veins. ConclusionsSimplified attenuation maps used on PET/MRI significantly increase the quantitative variability of PET images especially on lungs and bones. The quantification of PET images acquired with PET/MRI scanners applied to studies of atherosclerosis has small deviations, especially when the TBR is considered.

Direct Reconstruction of CT-based Attenuation Correction Images for PET with Cluster-Based Penalties.

Extremely low-dose CT acquisitions used for PET attenuation correction have high levels of noise and potential bias artifacts due to photon starvation. This work explores the use of a priori knowledge for iterative image reconstruction of the CT-based attenuation map. We investigate a maximum a posteriori framework with cluster-based multinomial penalty for direct iterative coordinate decent (dICD) reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction used a Poisson log-likelihood data fit term and evaluated two image penalty terms of spatial and mixture distributions. The spatial regularization is based on a quadratic penalty. For the mixture penalty, we assumed that the attenuation map may consist of four material clusters: air+background, lung, soft tissue, and bone. Using simulated noisy sinogram data, dICD reconstruction was performed with different strengths of the spatial and mixture penalties. The combined spatial and mixture penalties reduced the RMSE by roughly 2 times compared to a weighted least square and filtered backprojection reconstruction of CT images. The combined spatial and mixture penalties resulted in only slightly lower RMSE compared to a spatial quadratic penalty alone. For direct PET attenuation map reconstruction from ultra-low dose CT acquisitions, the combination of spatial and mixture penalties offers regularization of both variance and bias and is a potential method to reconstruct attenuation maps with negligible patient dose. The presented results, using a best-case histogram suggest that the mixture penalty does not offer a substantive benefit over conventional quadratic regularization and diminishes enthusiasm for exploring future application of the mixture penalty.

Integrated PET/MR breast cancer imaging: Attenuation correction and implementation of a 16-channel RF coil.

This study aims to develop, implement, and evaluate a 16-channel radiofrequency (RF) coil for integrated positron emission tomography/magnetic resonance (PET/MR) imaging of breast cancer. The RF coil is designed for optimized MR imaging performance and PET transparency and attenuation correction (AC) is applied for accurate PET quantification. A 16-channel breast array RF coil was designed for integrated PET/MR hybrid imaging of breast cancer lesions. The RF coil features a lightweight rigid design and is positioned with a spacer at a defined position on the patient table of an integrated PET/MR system. Attenuation correction is performed by generating and applying a dedicated 3D CT-based template attenuation map. Reposition accuracy of the RF coil on the system patient table while using the positioning frame was tested in repeated measurements using MR-visible markers. The MR, PET, and PET/MR imaging performances were systematically evaluated using modular breast phantoms. Attenuation correction of the RF coil was evaluated with difference measurements of the active breast phantoms filled with radiotracer in the PET detector with and without the RF coil in place, serving as a standard of reference measurement. The overall PET/MR imaging performance and PET quantification accuracy of the new 16-channel RF coil and its AC were then evaluated in first clinical examinations on ten patients with local breast cancer. The RF breast array coil provides excellent signal-to-noise ratio and signal homogeneity across the volume of the breast phantoms in MR imaging and visualizes small structures in the phantoms down to 0.4 mm in plane. Difference measurements with PET revealed a global loss and thus attenuation of counts by 13% (mean value across the whole phantom volume) when the RF coil is placed in the PET detector. Local attenuation ranging from 0% in the middle of the phantoms up to 24% was detected in the peripheral regions of the phantoms at positions closer to attenuating hardware structures of the RF coil. The position accuracy of the RF coil on the patient table when using the positioning frame was determined well below 1 mm for all three spatial dimensions. This ensures perfect position match between the RF coil and its three-dimensional attenuation template during the PET data reconstruction process. When applying the CT-based AC of the RF coil, the global attenuation bias was mostly compensated to ±0.5% across the entire breast imaging volume. The patient study revealed high quality MR, PET, and combined PET/MR imaging of breast cancer. Quantitative activity measurements in all 11 breast cancer lesions of the ten patients resulted in increased mean difference values of SUVmax 11.8% (minimum 3.2%; maximum 23.2%) between nonAC images and images when AC of the RF breast coil was applied. This supports the quantitative results of the phantom study as well as successful attenuation correction of the RF coil. A 16-channel breast RF coil was designed for optimized MR imaging performance and PET transparency and was successfully integrated with its dedicated attenuation correction template into a whole-body PET/MR system. Systematic PET/MR imaging evaluation with phantoms and an initial study on patients with breast cancer provided excellent MR and PET image quality and accurate PET quantification.

&lt;sup&gt;15&lt;/sup&gt;O ガスPET/CT 検査においてわずかな体動により臨床所見との乖離を示した症例についての検討

近年のPET 検査は，CT による吸収補正を行うことで検査の迅速化，画像の高分解能化，信号雑音比向上が実現された反面，CT とPET データとの位置ずれによる再構成画像の定量精度低下やアーチファクトが指摘されている．本研究では，脳15O ガスPET 検査中のわずかな体動により臨床所見とは異なる画像所見を呈した症例について検討した．臨床所見との乖離や明らかなエラーと思われる画像所見を呈し，2 cm までの位置ずれが確認できた6 症例を対象とし，位置ずれの影響について評価した．また正常ボランティアの画像を用いて位置ずれによる定量値の変動について検討した．2 例はOEF 画像にてリング状のアーチファクトが見られ，検査中に下向きの体動を確認した．2 例は病変と反対側，1 例は同側の血流，代謝の低下を認め，左右方向への位置ずれが原因であった．1 例は検査後右向きの位置ずれがみられ，OEF 画像で深部白質の集積が著明に亢進していた．定量値の変動は位置ずれが5 mm 以上で著明となり，視覚的にも左右差が確認された．CT での補正により，わずかな体動が結果に大きな影響を及ぼす可能性が示唆された．

Comparison of Template-Based Versus CT-Based Attenuation Correction for Hybrid MR/PET Scanners

Attenuation correction (AC) of cerebral PET data acquired in hybrid MR/PET scanners is still a challenge. To overcome this problem we previously proposed a correction method by obtaining template-based attenuation maps (AM) using MR and ECAT EXACT HR+ transmission scans. In the present study we investigated (a) the basic difference between template-based and CT-based AC methods and (b) their influence on reconstructed PET images. The data of 11 subjects undergoing $^{18}{\rm FDG}$ imaging in the Siemens 3T MR-BrainPET scanner were used. Additionally, from all participants a CT scan of the whole head was acquired at the same day. These CT images were transformed to CT-based AMs. They were filtered by a 3D Gaussian kernel with 3 mm (BrainPET resolution) filter width, which was considered as reference. Comparisons between both AMs (CT-based and template-based) were performed by estimating the Dice coefficients D and calculating the numbers of true positive, true negative and false negative voxels. The BrainPET emission data were reconstructed with both AMs ( ${\rm AM}_{{\rm CT}3{\rm mm}}$ and ${\rm AM}_{\rm Template}$ ). All reconstructed PET images were scaled to standardized uptake values (SUVs) and normalized to the MNI brain for using the AAL-VOI Atlas analysis. Correlation plots with regression equation, coefficients of determination ${{\rm R}^2}$ and relative differences (RD) between ${\rm AM}_{{\rm CT}3{\rm mm}}$ and the ${\rm AM}_{\rm Template}$ were derived. The fraction of the overall true positive voxels averaged over the 11 subjects was $80.4 \pm 7.5\% $ for ${\rm AM}_{\rm Template}$ compared to ${\rm AM}_{{\rm CT}3{\rm mm}}$ ( ${{\rm D}_{\rm bone}} = 0.63 \pm 0.08$ ; ${{\rm D}_{\rm soft - tissue}} = 0.85 \pm 0.08$ ; ${{\rm D}_{\rm air}} = 0.79 \pm 0.04$ ). A misclassification of bone as soft tissue and vice versa was evident in the comparison. The correlation plot of all VOIs considered (1,276 values) showed a mean ${{\rm R}^2}$ of 0.964 and a slope of 1.02. A mean RD of $1.33 \pm 0.95\%$ ( ${\min} = - 0.12\% $ , ${\max} = 2.85\% $ ) was found. The template-based AC method proposed by our group shows considerable differences in comparison to the higher resolution CT-based AM with respect to the Dice coefficients, in particular in the classification of bone and soft tissue. However, this has no major influence on the reconstructed $^{18}{\rm FDG}$ PET data.

Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study.

BackgroundHybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) with computed tomography (CT). Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR) on the image quality of the low-dose CT images.Methodology/Principal FindingsExaminations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU) values reconstructed by ASIR were correlated to the FBP HU values(R2 ≥ 0.88) and the contrast-to-noise ratio (CNR) was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04). In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001).Conclusion/SignificanceIn general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality.

Markerless attenuation correction for carotid MRI surface receiver coils in combined PET/MR imaging

The purpose of the study was to evaluate the effect of attenuation of MR coils on quantitative carotid PET/MR exams. Additionally, an automated attenuation correction method for flexible carotid MR coils was developed and evaluated.The attenuation of the carotid coil was measured by imaging a uniform water phantom injected with 37 MBq of 18F-FDG in a combined PET/MR scanner for 24 min with and without the coil. In the same session, an ultra-short echo time (UTE) image of the coil on top of the phantom was acquired. Using a combination of rigid and non-rigid registration, a CT-based attenuation map was registered to the UTE image of the coil for attenuation and scatter correction. After phantom validation, the effect of the carotid coil attenuation and the attenuation correction method were evaluated in five subjects.Phantom studies indicated that the overall loss of PET counts due to the coil was 6.3% with local region-of-interest (ROI) errors reaching up to 18.8%. Our registration method to correct for attenuation from the coil decreased the global error and local error (ROI) to 0.8% and 3.8%, respectively. The proposed registration method accurately captured the location and shape of the coil with a maximum spatial error of 2.6 mm. Quantitative analysis in human studies correlated with the phantom findings, but was dependent on the size of the ROI used in the analysis.MR coils result in significant error in PET quantification and thus attenuation correction is needed. The proposed strategy provides an operator-free method for attenuation and scatter correction for a flexible MRI carotid surface coil for routine clinical use.

Clinical evaluation of respiration-induced attenuation uncertainties in pulmonary 3D PET/CT.

BackgroundIn contemporary positron emission tomography (PET)/computed tomography (CT) scanners, PET attenuation correction is performed by means of a CT-based attenuation map. Respiratory motion can however induce offsets between the PET and CT data. Studies have demonstrated that these offsets can cause errors in quantitative PET measures. The purpose of this study is to quantify the effects of respiration-induced CT differences on the attenuation correction of pulmonary 18-fluordeoxyglucose (FDG) 3D PET/CT in a patient population and to investigate contributing factors.MethodsFor 32 lung cancer patients, 3D-CT, 4D-PET and 4D-CT data were acquired. The 4D FDG PET data were attenuation corrected (AC) using a free-breathing 3D-CT (3D-AC), the end-inspiration CT (EI-AC), the end-expiration CT (EE-AC) or phase-by-phase (P-AC). After reconstruction and AC, the 4D-PET data were averaged. In the 4Davg data, we measured maximum tumour standardised uptake value (SUV)max in the tumour, SUVmean in a lung volume of interest (VOI) and average SUV (SUVmean) in a muscle VOI. On the 4D-CT, we measured the lung volume differences and CT number changes between inhale and exhale in the lung VOI.ResultsCompared to P-AC, we found −2.3% (range −9.7% to 1.2%) lower tumour SUVmax in EI-AC and 2.0% (range −0.9% to 9.5%) higher SUVmax in EE-AC. No differences in the muscle SUV were found. The use of 3D-AC led to respiration-induced SUVmax differences up to 20% compared to the use of P-AC.SUVmean differences in the lung VOI between EI-AC and EE-AC correlated to average CT differences in this region (ρ = 0.83). SUVmax differences in the tumour correlated to the volume changes of the lungs (ρ = −0.55) and the motion amplitude of the tumour (ρ = 0.53), both as measured on the 4D-CT.ConclusionsRespiration-induced CT variations in clinical data can in extreme cases lead to SUV effects larger than 10% on PET attenuation correction. These differences were case specific and correlated to differences in CT number in the lungs.