Hossein Arabi

Vision 20/20: Magnetic resonance imaging‐guided attenuation correction in PET/MRI: Challenges, solutions, and opportunities

Attenuation correction is an essential component of the long chain of data correction techniques required to achieve the full potential of quantitative positron emission tomography (PET) imaging. The development of combined PET/magnetic resonance imaging (MRI) systems mandated the widespread interest in developing novel strategies for deriving accurate attenuation maps with the aim to improve the quantitative accuracy of these emerging hybrid imaging systems. The attenuation map in PET/MRI should ideally be derived from anatomical MR images; however, MRI intensities reflect proton density and relaxation time properties of biological tissues rather than their electron density and photon attenuation properties. Therefore, in contrast to PET/computed tomography, there is a lack of standardized global mapping between the intensities of MRI signal and linear attenuation coefficients at 511 keV. Moreover, in standard MRI sequences, bones and lung tissues do not produce measurable signals owing to their low proton density and short transverse relaxation times. MR images are also inevitably subject to artifacts that degrade their quality, thus compromising their applicability for the task of attenuation correction in PET/MRI. MRI-guided attenuation correction strategies can be classified in three broad categories: (i) segmentation-based approaches, (ii) atlas-registration and machine learning methods, and (iii) emission/transmission-based approaches. This paper summarizes past and current state-of-the-art developments and latest advances in PET/MRI attenuation correction. The advantages and drawbacks of each approach for addressing the challenges of MR-based attenuation correction are comprehensively described. The opportunities brought by both MRI and PET imaging modalities for deriving accurate attenuation maps and improving PET quantification will be elaborated. Future prospects and potential clinical applications of these techniques and their integration in commercial systems will also be discussed.

Magnetic resonance imaging-guided attenuation correction in whole-body PET/MRI using a sorted atlas approach

Quantitative whole-body PET/MR imaging is challenged by the lack of accurate and robust strategies for attenuation correction. In this work, a new pseudo-CT generation approach, referred to as sorted atlas pseudo-CT (SAP), is proposed for accurate extraction of bones and estimation of lung attenuation properties. This approach improves the Gaussian process regression (GPR) kernel proposed by Hofmann et al. which relies on the information provided by a co-registered atlas (CT and MRI) using a GPR kernel to predict the distribution of attenuation coefficients. Our approach uses two separate GPR kernels for lung and non-lung tissues. For non-lung tissues, the co-registered atlas dataset was sorted on the basis of local normalized cross-correlation similarity to the target MR image to select the most similar image in the atlas for each voxel. For lung tissue, the lung volume was incorporated in the GPR kernel taking advantage of the correlation between lung volume and corresponding attenuation properties to predict the attenuation coefficients of the lung. In the presence of pathological tissues in the lungs, the lesions are segmented on PET images corrected for attenuation using MRI-derived three-class attenuation map followed by assignment of soft-tissue attenuation coefficient. The proposed algorithm was compared to other techniques reported in the literature including Hofmanns approach and the three-class attenuation correction technique implemented on the Philips Ingenuity TF PET/MR where CT-based attenuation correction served as reference. Fourteen patients with head and neck cancer undergoing PET/CT and PET/MR examinations were used for quantitative analysis. SUV measurements were performed on 12 normal uptake regions as well as high uptake malignant regions. Moreover, a number of similarity measures were used to evaluate the accuracy of extracted bones. The Dice similarity metric revealed that the extracted bone improved from 0.58 ± 0.09 to 0.65 ± 0.07 when using the SAP technique compared to Hofmanns approach. This enabled to reduce the SUVmean bias in bony structures for the SAP approach to -1.7 ± 4.8% as compared to -7.3 ± 6.0% and -27.4 ± 10.1% when using Hofmanns approach and the three-class attenuation map, respectively. Likewise, the three-class attenuation map produces a relative absolute error of 21.7 ± 11.8% in the lungs. This was reduced on average to 15.8 ± 8.6% and 8.0 ± 3.8% when using Hofmanns and SAP techniques, respectively. The SAP technique resulted in better overall PET quantification accuracy than both Hofmanns and the three-class approaches owing to the more accurate extraction of bones and better prediction of lung attenuation coefficients. Further improvement of the technique and reduction of the computational time are still required.

Atlas-guided generation of pseudo-CT images for MRI-only and hybrid PET-MRI-guided radiotherapy treatment planning

Magnetic resonance imaging (MRI)-guided attenuation correction (AC) of positron emission tomography (PET) data and/or radiation therapy (RT) treatment planning is challenged by the lack of a direct link between MRI voxel intensities and electron density. Therefore, even if this is not a trivial task, a pseudo-computed tomography (CT) image must be predicted from MRI alone. In this work, we propose a two-step (segmentation and fusion) atlas-based algorithm focusing on bone tissue identification to create a pseudo-CT image from conventional MRI sequences and evaluate its performance against the conventional MRI segmentation technique and a recently proposed multi-atlas approach. The clinical studies consisted of pelvic CT, PET and MRI scans of 12 patients with loco-regionally advanced rectal disease. In the first step, bone segmentation of the target image is optimized through local weighted atlas voting. The obtained bone map is then used to assess the quality of deformed atlases to perform voxel-wise weighted atlas fusion. To evaluate the performance of the method, a leave-one-out cross-validation (LOOCV) scheme was devised to find optimal parameters for the model. Geometric evaluation of the produced pseudo-CT images and quantitative analysis of the accuracy of PET AC were performed. Moreover, a dosimetric evaluation of volumetric modulated arc therapy photon treatment plans calculated using the different pseudo-CT images was carried out and compared to those produced using CT images serving as references. The pseudo-CT images produced using the proposed method exhibit bone identification accuracy of 0.89 based on the Dice similarity metric compared to 0.75 achieved by the other atlas-based method. The superior bone extraction resulted in a mean standard uptake value bias of  -1.5  ±  5.0% (mean  ±  SD) in bony structures compared to  -19.9  ±  11.8% and  -8.1  ±  8.2% achieved by MRI segmentation-based (water-only) and atlas-guided AC. Dosimetric evaluation using dose volume histograms and the average difference between minimum/maximum absorbed doses revealed a mean error of less than 1% for the both target volumes and organs at risk. Two-dimensional (2D) gamma analysis of the isocenter dose distributions at 1%/1 mm criterion revealed pass rates of 91.40  ±  7.56%, 96.00  ±  4.11% and 97.67  ±  3.6% for MRI segmentation, atlas-guided and the proposed methods, respectively. The proposed method generates accurate pseudo-CT images from conventional Dixon MRI sequences with improved bone extraction accuracy. The approach is promising for potential use in PET AC and MRI-only or hybrid PET/MRI-guided RT treatment planning.

Quantitative analysis of MRI-guided attenuation correction techniques in time-of-flight brain PET/MRI.

PURPOSE In quantitative PET/MR imaging, attenuation correction (AC) of PET data is markedly challenged by the need of deriving accurate attenuation maps from MR images. A number of strategies have been developed for MRI-guided attenuation correction with different degrees of success. In this work, we compare the quantitative performance of three generic AC methods, including standard 3-class MR segmentation-based, advanced atlas-registration-based and emission-based approaches in the context of brain time-of-flight (TOF) PET/MRI. MATERIALS AND METHODS Fourteen patients referred for diagnostic MRI and (18)F-FDG PET/CT brain scans were included in this comparative study. For each study, PET images were reconstructed using four different attenuation maps derived from CT-based AC (CTAC) serving as reference, standard 3-class MR-segmentation, atlas-registration and emission-based AC methods. To generate 3-class attenuation maps, T1-weighted MRI images were segmented into background air, fat and soft-tissue classes followed by assignment of constant linear attenuation coefficients of 0, 0.0864 and 0.0975 cm(-1) to each class, respectively. A robust atlas-registration based AC method was developed for pseudo-CT generation using local weighted fusion of atlases based on their morphological similarity to target MR images. Our recently proposed MRI-guided maximum likelihood reconstruction of activity and attenuation (MLAA) algorithm was employed to estimate the attenuation map from TOF emission data. The performance of the different AC algorithms in terms of prediction of bones and quantification of PET tracer uptake was objectively evaluated with respect to reference CTAC maps and CTAC-PET images. RESULTS Qualitative evaluation showed that the MLAA-AC method could sparsely estimate bones and accurately differentiate them from air cavities. It was found that the atlas-AC method can accurately predict bones with variable errors in defining air cavities. Quantitative assessment of bone extraction accuracy based on Dice similarity coefficient (DSC) showed that MLAA-AC and atlas-AC resulted in DSC mean values of 0.79 and 0.92, respectively, in all patients. The MLAA-AC and atlas-AC methods predicted mean linear attenuation coefficients of 0.107 and 0.134 cm(-1), respectively, for the skull compared to reference CTAC mean value of 0.138cm(-1). The evaluation of the relative change in tracer uptake within 32 distinct regions of the brain with respect to CTAC PET images showed that the 3-class MRAC, MLAA-AC and atlas-AC methods resulted in quantification errors of -16.2 ± 3.6%, -13.3 ± 3.3% and 1.0 ± 3.4%, respectively. Linear regression and Bland-Altman concordance plots showed that both 3-class MRAC and MLAA-AC methods result in a significant systematic bias in PET tracer uptake, while the atlas-AC method results in a negligible bias. CONCLUSION The standard 3-class MRAC method significantly underestimated cerebral PET tracer uptake. While current state-of-the-art MLAA-AC methods look promising, they were unable to noticeably reduce quantification errors in the context of brain imaging. Conversely, the proposed atlas-AC method provided the most accurate attenuation maps, and thus the lowest quantification bias.

One registration multi-atlas-based pseudo-CT generation for attenuation correction in PET/MRI

PurposeThe outcome of a detailed assessment of various strategies for atlas-based whole-body bone segmentation from magnetic resonance imaging (MRI) was exploited to select the optimal parameters and setting, with the aim of proposing a novel one-registration multi-atlas (ORMA) pseudo-CT generation approach.MethodsThe proposed approach consists of only one online registration between the target and reference images, regardless of the number of atlas images (N), while for the remaining atlas images, the pre-computed transformation matrices to the reference image are used to align them to the target image. The performance characteristics of the proposed method were evaluated and compared with conventional atlas-based attenuation map generation strategies (direct registration of the entire atlas images followed by voxel-wise weighting (VWW) and arithmetic averaging atlas fusion). To this end, four different positron emission tomography (PET) attenuation maps were generated via arithmetic averaging and VWW scheme using both direct registration and ORMA approaches as well as the 3-class attenuation map obtained from the Philips Ingenuity TF PET/MRI scanner commonly used in the clinical setting. The evaluation was performed based on the accuracy of extracted whole-body bones by the different attenuation maps and by quantitative analysis of resulting PET images compared to CT-based attenuation-corrected PET images serving as reference.ResultsThe comparison of validation metrics regarding the accuracy of extracted bone using the different techniques demonstrated the superiority of the VWW atlas fusion algorithm achieving a Dice similarity measure of 0.82 ± 0.04 compared to arithmetic averaging atlas fusion (0.60 ± 0.02), which uses conventional direct registration. Application of the ORMA approach modestly compromised the accuracy, yielding a Dice similarity measure of 0.76 ± 0.05 for ORMA-VWW and 0.55 ± 0.03 for ORMA-averaging. The results of quantitative PET analysis followed the same trend with less significant differences in terms of SUV bias, whereas massive improvements were observed compared to PET images corrected for attenuation using the 3-class attenuation map. The maximum absolute bias achieved by VWW and VWW-ORMA methods was 06.4 ± 5.5 in the lung and 07.9 ± 4.8 in the bone, respectively.ConclusionsThe proposed algorithm is capable of generating decent attenuation maps. The quantitative analysis revealed a good correlation between PET images corrected for attenuation using the proposed pseudo-CT generation approach and the corresponding CT images. The computational time is reduced by a factor of 1/N at the expense of a modest decrease in quantitative accuracy, thus allowing us to achieve a reasonable compromise between computing time and quantitative performance.

Comparison of atlas-based bone segmentation methods in whole-body PET/MRI

The aim of this work is to compare bone extraction accuracy of commonly used atlas-based segmentation algorithms for generation of pseudo-CT images in whole-body PET/MRI. Eight different bone segmentation methods from whole-body MR images were implemented. The study comprised 23 patients who underwent sequential PET/CT and PET/MRI scans, thus enabling to produce pairs of aligned 3D Dixon MR and CT images. The voxel-wise weighting method, which employs local normalized cross-correlation similarity measure to give appropriate weights locally, outperformed other pseudo-CT generation approaches, yielding a Dice similarity index of 0.77±0.04 (P<;0.05) compared to 0.60±0.02 (P<;0.05) achieved by bone segmentation using simple averaging of all CT atlases. This approach is promising for MRI-guided attenuation correction in whole-body PET/MRI.

Fast atlas-based MRI-guided PET attenuation map generation in whole-body PET/MR imaging

We propose a one registration multi atlas (ORMA) pseudo-CT generation algorithm for attenuation correction in whole-body PET/MRI based on an optimized atlas-guided bone segmentation procedure. The proposed approach requires only one online registration between the target and reference images regardless of the number of atlas images N, while for the remaining subjects belonging to the atlas dataset, the pre-computed transformation matrices obtained from registration to the reference image is used to align them to the target image. The performance characteristics of the proposed method were evaluated and compared to conventional atlas-based attenuation map generation consisting of direct registration of the entire atlas images to the target. Four different PET attenuation maps were produced using direct registration and ORMA, voxelwise weighted (VWW-Direct and VWW-ORMA) and arithmetic average (AA-Direct and AA-ORMA) atlas fusion strategies. The comparison of validation measures characterizing the accuracy of extracted whole-body bone demonstrated the superiority of VWW-Direct atlas fusion technique resulting in a Dice similarity measure of 0.82±0.04 compared to 0.60±0.02 for AA-Direct. Conversely, the ORMA approach yielded a Dice similarity measure of 0.76±0.05 for VWW-ORMA and 0.55±0.03 for AA-ORMA. Quantitative analysis of PET data revealed good correlation (y=1.01x+0.1, R2=0.99) between PET images corrected for attenuation using the proposed pseudo-CT method and the corresponding reference CT images. The proposed method generates decent attenuation maps and enables to reduce the processing time for atlas-based pseudo-CT generation reduced by a factor N.

Comparison of atlas-based techniques for whole-body bone segmentation

HIGHLIGHTSComparative assessment of atlas‐guided whole‐body bone segmentation techniques in whole‐body MR imaging using a common database of MR/CT image pairs.Implementation and optimization of conventional atlas‐guided methods.Identifying promising algorithms for whole‐body bone segmentation from MR images.Potential application of the most promising algorithms in MRI‐guided attenuation correction in hybrid PET/MRI. ABSTRACT We evaluate the accuracy of whole‐body bone extraction from whole‐body MR images using a number of atlas‐based segmentation methods. The motivation behind this work is to find the most promising approach for the purpose of MRI‐guided derivation of PET attenuation maps in whole‐body PET/MRI. To this end, a variety of atlas‐based segmentation strategies commonly used in medical image segmentation and pseudo‐CT generation were implemented and evaluated in terms of whole‐body bone segmentation accuracy. Bone segmentation was performed on 23 whole‐body CT/MR image pairs via leave‐one‐out cross validation procedure. The evaluated segmentation techniques include: (i) intensity averaging (IA), (ii) majority voting (MV), (iii) global and (iv) local (voxel‐wise) weighting atlas fusion frameworks implemented utilizing normalized mutual information (NMI), normalized cross‐correlation (NCC) and mean square distance (MSD) as image similarity measures for calculating the weighting factors, along with other atlas‐dependent algorithms, such as (v) shape‐based averaging (SBA) and (vi) Hofmanns pseudo‐CT generation method. The performance evaluation of the different segmentation techniques was carried out in terms of estimating bone extraction accuracy from whole‐body MRI using standard metrics, such as Dice similarity (DSC) and relative volume difference (RVD) considering bony structures obtained from intensity thresholding of the reference CT images as the ground truth. Considering the Dice criterion, global weighting atlas fusion methods provided moderate improvement of whole‐body bone segmentation (DSC = 0.65 ± 0.05) compared to non‐weighted IA (DSC = 0.60 ± 0.02). The local weighed atlas fusion approach using the MSD similarity measure outperformed the other strategies by achieving a DSC of 0.81 ± 0.03 while using the NCC and NMI measures resulted in a DSC of 0.78 ± 0.05 and 0.75 ± 0.04, respectively. Despite very long computation time, the extracted bone obtained from both SBA (DSC = 0.56 ± 0.05) and Hofmanns methods (DSC = 0.60 ± 0.02) exhibited no improvement compared to non‐weighted IA. Finding the optimum parameters for implementation of the atlas fusion approach, such as weighting factors and image similarity patch size, have great impact on the performance of atlas‐based segmentation approaches. The voxel‐wise atlas fusion approach exhibited excellent performance in terms of cancelling out the non‐systematic registration errors leading to accurate and reliable segmentation results. Denoising and normalization of MR images together with optimization of the involved parameters play a key role in improving bone extraction accuracy.

Whole-body bone segmentation from MRI for PET/MRI attenuation correction using shape- based averaging

PURPOSE The authors evaluate the performance of shape-based averaging (SBA) technique for whole-body bone segmentation from MRI in the context of MRI-guided attenuation correction (MRAC) in hybrid PET/MRI. To enhance the performance of the SBA scheme, the authors propose to combine it with statistical atlas fusion techniques. Moreover, a fast and efficient shape comparison-based atlas selection scheme was developed and incorporated into the SBA method. METHODS Clinical studies consisting of PET/CT and MR images of 21 patients were used to assess the performance of the SBA method. In addition, the authors assessed the performance of simultaneous truth and performance level estimation (STAPLE) and the selective and iterative method for performance level estimation (SIMPLE) combined with SBA. In addition, a local shape comparison scheme (L-Shp) was proposed to improve the performance of SBA. The SIMPLE method was applied globally (G-SIMPLE) while STAPLE method was employed at both global (G-STAPLE) and local (L-STAPLE) levels. The evaluation was performed based on the accuracy of extracted whole-body bones, fragmentation, and computation time achieved by the different methods. The majority voting (MV) atlas fusion scheme was also evaluated as a conventional and commonly used method. MRI-guided attenuation maps were generated using the different segmentation methods. Thereafter, quantitative analysis of PET attenuation correction was performed using CT-based attenuation correction as reference. RESULTS The SBA and MV methods resulted in considerable underestimation of bone identification (Dice ≈ 0.62) and high factious fragmentation error of contiguous structures. Applying global atlas selection or regularization (G-STAPLE and G-SIMPLE) to the SBA method enhanced bone segmentation accuracy up to a Dice = 0.66. The best results were achieved when applying the L-STAPLE method with a Dice of 0.76 and the L-Shp method with a Dice of 0.75. However, L-STAPLE required up to five-fold increased computation time compared to the L-Shp method. Moreover, both L-STAPLE and L-Shp methods resulted in less than 3% SUV mean relative error and 6% SUV mean absolute error in bony structures owing to superior bone identification accuracy. The quantitative analysis using joint histograms revealed good correlation between PET-MRAC images using the proposed L-Shp algorithm and the corresponding reference PET-CT images. CONCLUSIONS The performance of SBA was enhanced through application of local atlas weighting or regularization schemes (L-STAPLE and L-Shp). Bone recognition, fragmentation of the contiguous structures, and quantitative PET uptake recovery improved dramatically using these methods while the proposed L-Shp method significantly reduced the computation time.

Monte Carlo-based assessment of the trade-off between spatial resolution, field-of-view and scattered radiation in the variable resolution X-ray CT scanner

OBJECTIVE The purpose of this work is to evaluate the impact of optimization of magnification on performance parameters of the variable resolution X-ray (VRX) CT scanner. METHODS A realistic model based on an actual VRX CT scanner was implemented in the GATE Monte Carlo simulation platform. To evaluate the influence of system magnification, spatial resolution, field-of-view (FOV) and scatter-to-primary ratio of the scanner were estimated for both fixed and optimum object magnification at each detector rotation angle. Comparison and inference between these performance parameters were performed angle by angle to determine appropriate object position at each opening half angle. RESULTS Optimization of magnification resulted in a trade-off between spatial resolution and FOV of the scanner at opening half angles of 90°-12°, where the spatial resolution increased up to 50% and the scatter-to-primary ratio decreased from 4.8% to 3.8% at a detector angle of about 90° for the same FOV and X-ray energy spectrum. The disadvantage of magnification optimization at these angles is the significant reduction of the FOV (up to 50%). Moreover, magnification optimization was definitely beneficial for opening half angles below 12° improving the spatial resolution from 7.5 cy/mm to 20 cy/mm. Meanwhile, the FOV increased by more than 50% at these angles. CONCLUSION It can be concluded that optimization of magnification is essential for opening half angles below 12°. For opening half angles between 90° and 12°, the VRX CT scanner magnification should be set according to the desired spatial resolution and FOV.