A review of PET attenuation correction methods for PET-MR

Despite being thirteen years since the installation of the first PET-MR system, the scanners constitute a very small proportion of the total hybrid PET systems installed. This is in stark contrast to the rapid expansion of the PET-CT scanner, which quickly established its importance in patient diagnosis within a similar timeframe. One of the main hurdles is the development of an accurate, reproducible and easy-to-use method for attenuation correction. Quantitative discrepancies in PET images between the manufacturer-provided MR methods and the more established CT- or transmission-based attenuation correction methods have led the scientific community in a continuous effort to develop a robust and accurate alternative. These can be divided into four broad categories: (i) MR-based, (ii) emission-based, (iii) atlas-based and the (iv) machine learning-based attenuation correction, which is rapidly gaining momentum. The first is based on segmenting the MR images in various tissues and allocating a predefined attenuation coefficient for each tissue. Emission-based attenuation correction methods aim in utilising the PET emission data by simultaneously reconstructing the radioactivity distribution and the attenuation image. Atlas-based attenuation correction methods aim to predict a CT or transmission image given an MR image of a new patient, by using databases containing CT or transmission images from the general population. Finally, in machine learning methods, a model that could predict the required image given the acquired MR or non-attenuation-corrected PET image is developed by exploiting the underlying features of the images. Deep learning methods are the dominant approach in this category. Compared to the more traditional machine learning, which uses structured data for building a model, deep learning makes direct use of the acquired images to identify underlying features. This up-to-date review goes through the literature of attenuation correction approaches in PET-MR after categorising them. The various approaches in each category are described and discussed. After exploring each category separately, a general overview is given of the current status and potential future approaches along with a comparison of the four outlined categories.

Effect of PET-CT misalignment on the quantitative accuracy of cardiac 15O-water PET

BACKGROUND

Quantification of myocardial blood flow (MBF) with PET requires accurate attenuation correction, which is performed using a separate CT. Misalignment between PET and CT scans has been reported to be a common problem. The purpose of the present study was to assess the effect of PET CT misalignment on the quantitative accuracy of cardiac 15O-water PET.

METHODS

Ten clinical patients referred for evaluation of ischemia and assessment of MBF with 15O-water were included in the study. Eleven different misalignments between PET and CT were induced in 6 different directions with 10 and 20 mm amplitudes: caudal (+Z), cranial (- Z), lateral (±X), anterior (+Y), and anterior combined with cranial (+ Y and - Z). Blood flow was quantified from rates of washout (MBF) and uptake (transmural MBF, MBFt) for the whole left ventricle and the three coronary territories. The results from all misalignments were compared to the original scan without misalignment.

RESULTS

MBF was only minorly affected by misalignments, but larger effects were seen in MBFt. On the global level, average absolute deviation across all misalignments for MBF was 1.7% ± 1.4% and for MBFt 5.4% ± 3.2 Largest deviation for MBF was - 4.8% ± 5.8% (LCX, X + 20) and for MBFt - 19.3% ± 9.6% (LCX, X + 20). In general, larger effects were seen in LAD and LCX compared to in RCA.

CONCLUSION

The quantitative accuracy of MBF from 15O-water PET, based on the washout of the tracer, is only to a minor extent affected by misalignment between PET and CT.

Motion Correction and Its Impact on Absolute Myocardial Blood Flow Measures with PET

PURPOSE OF REVIEW

Motion artifacts, due to cardiac and respiratory cycles, myocardial cardiac creep, or gross patient movements, have been extensively investigated in the context of relative myocardial perfusion imaging with SPECT and PET. These movements have been identified as a major source of errors in image quantification and diagnosis. Recently, as dynamic PET quantification for myocardial blood flow assessment has entered clinical practice, similar questions have arisen on the impact of motion on final blood flow values.

RECENT FINDINGS

While preliminary investigations have underlined the potential impact of these motions on MBF quantification, their correction on dynamic acquisition remains challenging and limited to research studies. Gross patient's body movements occur in a consistent number of cases, particularly during stress acquisition, typically involving a limited number of image frames. If undetected, these movements can lead to great differences in flow values and consequently misdiagnosis. Quality control routines can be applied to automatically inspect the shape of time activity curves and to help identify motion artifacts. Cyclic cardiac and respiratory motion may have a considerable impact on final flow values. Correction of gross body motion represents a priority in the context of optimizing absolute flow clinical routine utilization and protocol standardization.

The Effects of Misalignment between PET and CT Scans on Brain PET Study Using CT-based Attenuation Correction: A Phantom Study

PURPOSE

The aim of this study was to evaluate the effects of inaccurate attenuation correction due to the misalignment between the computed tomography (CT)-based μ-map and the positron emission tomography (PET) data on a brain PET.

METHODS

CT and PET scans were performed on a 3-dimension (3D) brain phantom, in which the grey matter region was filled with ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG), and the skull region was filled with/without the bone-equivalent solution. The shifted PET images relative to the CT image were generated by the software-based translation of PET data in the cephalad/caudal and right directions, with a magnitude of the shift up to 30 mm and a step size of 5 mm. The regions of interest (ROIs) were drawn on the areas of the temporal lobes, parietal lobes, thalami, and cerebellums in the no-shifted image (reference). For each ROI, the radioactivity concentrations in the shifted images were compared with those of the reference.

RESULTS

The errors in the radioactivity concentrations were increased with the increasing magnitude of the shift in all brain regions except for thalamus. For a 5 mm shift in the right direction, ± 10% errors were observed in the left/right temporal lobes. The accuracy of the radioactivity concentration in the temporal lobe was very sensitive to misalignment in the right directions.

CONCLUSION

The misalignment between CT-based μ-map and PET data had larger effects on the surface regions of the brain rather than on deep brain structures.

Simultaneous reconstruction of attenuation and activity in cardiac PET can remove CT misalignment artifacts

BACKGROUND

Misalignment between positron emission tomography (PET) and computed tomography (CT) data is known to generate artifactual defects in cardiac PET images due to imprecise attenuation correction (AC). In this work, the use of a maximum likelihood attenuation and activity (MLAA) algorithm is proposed to avoid such artifacts in time-of-flight (TOF) PET.

METHODS

MLAA was implemented and tested using a thorax/heart phantom and retrospectively on fourteen (13)N-ammonia PET/CT perfusion studies. Global and local misalignments between PET and CT data were generated by shifting matched CT images or using CT data representative of the end-inspiration phase. PET images were reconstructed with MLAA and a 3D-ordered-subsets-expectation-maximization (OSEM)-TOF algorithm. Images obtained with 3D-OSEM-TOF and matched CT were used as references. These images were compared (qualitatively and semi-quantitatively) with those reconstructed with 3D-OSEM-TOF and MLAA for which a misaligned CT was used, respectively, for AC and initialization.

RESULTS

Phantom experiment proved the capability of MLAA to converge toward the correct emission and attenuation distributions using, as input, only PET emission data, but convergence was very slow. Initializing MLAA with phantom CT images markedly improved convergence speed. In patient studies, when shifted or end-inspiration CT images were used for AC, 3D-OSEM-TOF reconstructions showed artifacts of increasing severity, size, and frequency with increasing mismatch. Such artifacts were absent in the corresponding MLAA images.

CONCLUSION

The proposed implementation of the MLAA algorithm is a feasible and robust technique to avoid AC mismatch artifacts in cardiac PET studies provided that a CT of the source is available, even if poorly aligned.

64-slice CT perfusion imaging of pancreatic adenocarcinoma and mass-forming chronic pancreatitis

RATIONALE AND OBJECTIVES

To investigate 64 computed tomography (CT) perfusion imaging features of patients with pancreatic cancer and mass-forming chronic pancreatitis.

MATERIALS AND METHODS

Between January 2003 and April 2010, 234 patients with pancreatic mass underwent 64-CT perfusion imaging. Among them, the histopathological results of 64 patients were proven to be pancreatic adenocarcinoma and 15 patients were proven to be mass-forming chronic pancreatitis. Additionally, CT perfusion imaging was performed in 33 healthy volunteers served as controls. The slice data were processed using CT perfusion software. Perfusion parameters including time density curve, blood flow, blood volume, permeability, peak enhancement, and time to peak were recorded.

RESULTS

Blood flow was 77% lower in patients with pancreatic adenocarcinoma than in controls, 48% lower in patients with mass-forming chronic pancreatitis than in controls, and 56% lower in patients with pancreatic adenocarcinoma than with mass-forming chronic pancreatitis (P < .016). Blood volume was 65% lower in pancreatic adenocarcinoma than in controls, 27% lower in mass-forming chronic pancreatitis than in controls, and 53% lower in cancer than mass-forming chronic pancreatitis (P < .016). Permeability was 559% higher in pancreatic adenocarcinoma than in controls, 821% higher in mass-forming chronic pancreatitis than in controls, and 28% lower in cancer than mass-forming chronic pancreatitis (P < .016). Peak enhancement was 27% lower and time to peak 23% longer in pancreatic adenocarcinoma than mass-forming chronic pancreatitis (P < .016). Time-density curve showed the peak of mass-forming chronic pancreatitis is earlier and higher than that of pancreatic adenocarcinoma, and the peak of mass-forming chronic pancreatitis is later and lower than that of controls.

CONCLUSION

CT perfusion imaging can provide additional quantitative hemodynamic information of pancreatic adenocarcinoma and mass-forming chronic pancreatitis.