Effect of PET-MR Inconsistency in the Kernel Image Reconstruction Method

Anatomically driven image reconstruction algorithms have become very popular in positron emission tomography (PET) where they have demonstrated improved image resolution and quantification. This paper examines the effects of spatial inconsistency between MR and PET images in hot and cold regions of PET images using the hybrid kernelized expectation maximization (HKEM) machine learning method. Our evaluation was conducted on Jaszczak phantom and patient data acquired with the Biograph Siemens mMR. The results show that even a small shift can cause a significant change in activity concentration. In general, the PET-MR inconsistencies can induce the partial volume effect, more specifically the “spill-in” for cold regions and the “spill-out” for hot regions. The maximum change was about 100% for the cold region and 10% for the hot lesion using kernelized expectation maximization, against the 37% and 8% obtained with HKEM. The findings of this paper suggest that including PET information in the kernel enhances the robustness of the reconstruction in case of spatial inconsistency. Nevertheless, accurate registration and choice of the appropriate MR image for the creation of the kernel is essential to avoid artifacts, blurring, and bias

Comparison of Correction Techniques for the Spill in Effect in Emission Tomography

In positron emission tomography (PET) imaging, accurate clinical assessment is often affected by the partial volume effect (PVE) leading to overestimation (spill-in) or underestimation (spill-out) of activity in various small regions. The spill-in correction, in particular, can be very challenging when the target region is close to a hot background region. Therefore, this study evaluates and compares the performance of various recently developed spill-in correction techniques, namely: background correction (BC), local projection (LP), and hybrid kernelized (HKEM) methods. We used a simulated digital phantom and 18F-NaF PET data of three patients with abdominal aortic aneurysms (AAA) acquired with Siemens Biograph mMRTM and mCTTM scanners respectively. Region of Interest (ROI) analysis was performed and the extracted SUVmean, SUVmax and target-to-background ratio (TBR) scores were compared. Results showed substantial spill-in effects from hot regions to targeted regions, which are more prominent in small structures. The phantom experiment demonstrated the feasibility of spill-in correction with all methods. For the patient data, large differences in SUVmean, SUVmax and TBRmax scores were observed between the ROIs drawn over the entire aneurysm and ROIs excluding some regions close to the bone. Overall, BC yielded the best performance in spill-in correction in both phantom and patient studies

Hybrid PET-MR list-mode kernelized expectation maximization reconstruction for quantitative PET images of the carotid arteries

Ordered subsets expectation maximization (OSEM) has been widely used in PET imaging. Although Bayesian algorithms have been shown to perform better, they are still not used in the clinical practice due to the difficulty of choosing appropriate and robust regularization parameters. The recently introduced kernelized expectation maximization (KEM) has shown some promise to work successfully for different applications. Therefore, we propose a list mode hybrid KEM (LM-HKEM) for static reconstructions, which we implemented in the open source Software for Tomographic Image Reconstruction (STIR) library. The proposed algorithm uses both MR and PET update images to create a feature vector for each voxel in the image, which contains the information about the local neighborhood. So as not to over-smooth the reconstructed images a 3×3×3 voxels kernel was used. Three real datasets were acquired with the Siemens mMR: a phantom to validate the algorithm and two patient carotid artery studies to show the possible applications of the method. The reconstructed images are assessed and compared for different algorithms: OSEM, OSEM with median root prior (MRP), KEM and LM-HKEM. The results show better quantification performance for the phantom low count images with around 4% bias compared to 7% for KEM and over 11% for OSEM and OSEM with (MRP). Our results show that the proposed technique can be used to improve quantification at low- count condition and it shows promising performance in terms of stability as for different subsets, with comparable number of events, we used the same parameters values. Emphasis is given on the reconstruction of the carotid artery and the characterization of atherosclerosis

Hybrid PET-MR list-mode kernelized expectation maximization reconstruction

The recently introduced kernelized expectation maximization (KEM) method has shown promise across varied applications. These studies have demonstrated the benefits and drawbacks of the technique when the kernel matrix is estimated from separate anatomical information, for example from magnetic resonance (MR), or from a preliminary PET reconstruction. The contribution of this work is to propose and investigate a list-mode-hybrid KEM (LM-HKEM) reconstruction algorithm with the aim of maintaining the benefits of the anatomically-guided methods and overcome their limitations by incorporating synergistic information iteratively. The HKEM is designed to reduce negative bias associated with low-counts, the problem of PET unique feature suppression reported in the previously mentioned studies using only the MR-based kernel, and to improve contrast of lesions at different count levels. The proposed algorithm is validated using a simulation study, a phantom dataset and two clinical datasets. For each of the real datasets high and low count-levels were investigated. The reconstructed images are assessed and compared with different LM algorithms implemented in STIR. The findings obtained using simulated and real datasets show that anatomically-guided techniques provide reduced partial volume effect and higher contrast compared to standard techniques, and HKEM provides even higher contrast and reduced bias in almost all the cases. This work, therefore argues that using synergistic information, via the kernel method, increases the accuracy of the PET clinical diagnostic examination. The promising quantitative features of the HKEM method give the opportunity to explore many possible clinical applications, such as cancer and inflammation

Hybrid PET- and MR-driven attenuation correction for enhanced ¹⁸F-NaF and ¹⁸F-FDG quantification in cardiovascular PET/MR imaging

Background: The standard MR Dixon-based attenuation correction (AC) method in positron emission tomography/magnetic resonance (PET/MR) imaging segments only the air, lung, fat and soft-tissues (4-class), thus neglecting the highly attenuating bone tissues and affecting quantification in bones and adjacent vessels. We sought to address this limitation by utilizing the distinctively high bone uptake rate constant Ki expected from ¹⁸F-Sodium Fluoride (¹⁸F-NaF) to segment bones from PET data and support 5-class hybrid PET/MR-driven AC for ¹⁸F-NaF and ¹⁸F-Fluorodeoxyglucose (¹⁸F-FDG) PET/MR cardiovascular imaging. Methods: We introduce 5-class Ki/MR-AC for (i) ¹⁸F-NaF studies where the bones are segmented from Patlak Ki images and added as the 5th tissue class to the MR Dixon 4-class AC map. Furthermore, we propose two alternative dual-tracer protocols to permit 5-class Ki/MR-AC for (ii) ¹⁸F-FDG-only data, with a streamlined simultaneous administration of ¹⁸F-FDG and ¹⁸F-NaF at 4:1 ratio (R4:1), or (iii) for ¹⁸F-FDG-only or both ¹⁸F-FDG and ¹⁸F-NaF dual-tracer data, by administering ¹⁸F-NaF 90 minutes after an equal ¹⁸F-FDG dosage (R1:1). The Ki-driven bone segmentation was validated against computed tomography (CT)-based segmentation in rabbits, followed by PET/MR validation on 108 vertebral bone and carotid wall regions in 16 human volunteers with and without prior indication of carotid atherosclerosis disease (CAD). Results: In rabbits, we observed similar (< 1.2% mean difference) vertebral bone ¹⁸F-NaF SUVmean scores when applying 5-class AC with Ki-segmented bone (5-class Ki/CT-AC) vs CT-segmented bone (5-class CT-AC) tissue. Considering the PET data corrected with continuous CT-AC maps as gold-standard, the percentage SUVmean bias was reduced by 17.6% (¹⁸F-NaF) and 15.4% (R4:1) with 5-class Ki/CT-AC vs 4-class CT-AC. In humans without prior CAD indication, we reported 17.7% and 20% higher ¹⁸F-NaF target-to-background ratio (TBR) at carotid bifurcations wall and vertebral bones, respectively, with 5- vs 4-class AC. In the R4:1 human cohort, the mean ¹⁸F-FDG:¹⁸F-NaF TBR increased by 12.2% at carotid bifurcations wall and 19.9% at vertebral bones. For the R1:1 cohort of subjects without CAD indication, mean TBR increased by 15.3% (¹⁸F-FDG) and 15.5% (¹⁸F-NaF) at carotid bifurcations and 21.6% (¹⁸F-FDG) and 22.5% (¹⁸F-NaF) at vertebral bones. Similar TBR enhancements were observed when applying the proposed AC method to human subjects with prior CAD indication. Conclusions: Ki-driven bone segmentation and 5-class hybrid PET/MR-driven AC is feasible and can significantly enhance ¹⁸F-NaF and ¹⁸F-FDG contrast and quantification in bone tissues and carotid walls

Brain death, states of impaired consciousness, and physician-assisted death for end-of-life organ donation and transplantation

In 1968, the Harvard criteria equated irreversible coma and apnea (i.e., brain death) with human death and later, the Uniform Determination of Death Act was enacted permitting organ procurement from heart-beating donors. Since then, clinical studies have defined a spectrum of states of impaired consciousness in human beings: coma, akinetic mutism (locked-in syndrome), minimally conscious state, vegetative state and brain death. In this article, we argue against the validity of the Harvard criteria for equating brain death with human death. (1) Brain death does not disrupt somatic integrative unity and coordinated biological functioning of a living organism. (2) Neurological criteria of human death fail to determine the precise moment of an organism’s death when death is established by circulatory criterion in other states of impaired consciousness for organ procurement with non-heart-beating donation protocols. The criterion of circulatory arrest 75 s to 5 min is too short for irreversible cessation of whole brain functions and respiration controlled by the brain stem. (3) Brain-based criteria for determining death with a beating heart exclude relevant anthropologic, psychosocial, cultural, and religious aspects of death and dying in society. (4) Clinical guidelines for determining brain death are not consistently validated by the presence of irreversible brain stem ischemic injury or necrosis on autopsy; therefore, they do not completely exclude reversible loss of integrated neurological functions in donors. The questionable reliability and varying compliance with these guidelines among institutions amplify the risk of determining reversible states of impaired consciousness as irreversible brain death. (5) The scientific uncertainty of defining and determining states of impaired consciousness including brain death have been neither disclosed to the general public nor broadly debated by the medical community or by legal and religious scholars. Heart-beating or non-heart-beating organ procurement from patients with impaired consciousness is de facto a concealed practice of physician-assisted death, and therefore, violates both criminal law and the central tenet of medicine not to do harm to patients. Society must decide if physician-assisted death is permissible and desirable to resolve the conflict about procuring organs from patients with impaired consciousness within the context of the perceived need to enhance the supply of transplantable organs

Iterative reconstruction incorporating background correction improves quantification of [18F]-NaF PET/CT images of patients with abdominal aortic aneurysm

Background A confounding issue in [18F]-NaF PET/CT imaging of abdominal aortic aneurysms (AAA) is the spill in contamination from the bone into the aneurysm. This study investigates and corrects for this spill in contamination using the background correction (BC) technique without the need to manually exclude the part of the AAA region close to the bone. Methods Seventy-two (72) datasets of patients with AAA were reconstructed with the standard ordered subset expectation maximization (OSEM) algorithm incorporating point spread function (PSF) modelling. The spill in effect in the aneurysm was investigated using two target regions of interest (ROIs): one covering the entire aneurysm (AAA), and the other covering the aneurysm but excluding the part close to the bone (AAAexc). ROI analysis was performed by comparing the maximum SUV in the target ROI (SUVmax(T)), the corrected cSUVmax (SUVmax(T) − SUVmean(B)) and the target-to-blood ratio (TBR = SUVmax(T)/SUVmean(B)) with respect to the mean SUV in the right atrium region. Results There is a statistically significant higher [18F]-NaF uptake in the aneurysm than normal aorta and this is not correlated with the aneurysm size. There is also a significant difference in aneurysm uptake for OSEM and OSEM + PSF (but not OSEM + PSF + BC) when quantifying with AAA and AAAexc due to the spill in from the bone. This spill in effect depends on proximity of the aneurysms to the bone as close aneurysms suffer more from spill in than farther ones. Conclusion The background correction (OSEM + PSF + BC) technique provided more robust AAA quantitative assessments regardless of the AAA ROI delineation method, and thus it can be considered as an effective spill in correction method for [18F]-NaF AAA studies