Segmentation-Based MR Attenuation Correction Including Bones Also Affects Quantitation in Brain Studies: An Initial Result of 18F-FP-CIT PET/MR for Patients with Parkinsonism

A systematic review of the challenges, emerging solutions and applications, and future directions of PET/MRI in Parkinson's disease

PET/MRI is a hybrid imaging modality that boasts the simultaneous acquisition of high-resolution anatomical data and metabolic information. Having these exceptional capabilities, it is often implicated in clinical research for diagnosing and grading, as well as tracking disease progression and response to interventions. Despite this, its low level of clinical widespread use is questioned. This is especially the case with Parkinson's disease (PD), the fastest progressively disabling and neurodegenerative cause of death. To optimise the clinical applicability of PET/MRI for diagnosing, differentiating, and tracking PD progression, the emerging novel uses, and current challenges must be identified. This systematic review aimed to present the specific challenges of PET/MRI use in PD. Further, this review aimed to highlight the possible resolution of these challenges, the emerging applications and future direction of PET/MRI use in PD. EBSCOHost (indexing CINAHL Plus, PsycINFO) Ovid (Medline, EMBASE) PubMed, Web of Science, and Scopus from 2006 (the year of first integrated PET/MRI hybrid system) to 30 September 2022 were used to search for relevant primary articles. A total of 933 studies were retrieved and following the screening procedure, 18 peer-reviewed articles were included in this review. This present study is of great clinical relevance and significance, as it informs the reasoning behind hindered widespread clinical use of PET/MRI for PD. Despite this, the emerging applications of image reconstruction developed by PET/MRI research data to the use of fully automated systems show promising and desirable utility. Furthermore, many of the current challenges and limitations can be resolved by using much larger-sampled and longitudinal studies. Meanwhile, the development of new fast-binding tracers that have specific affinity to PD pathological processes is warranted.

Symmetric and Profound Monoaminergic Degeneration in Parkinson's Disease with Premotor REM Sleep Behavior Disorder

Background

Rapid eye movement sleep behavior disorder (RBD) may precede or follow motor symptoms in Parkinson's disease (PD). While over 70% of idiopathic RBD cases phenoconvert within a decade, a small subset develops PD after a more extended period or remains nonconverted. These heterogeneous manifestations of RBD in PD prompt subtype investigations. Premotor RBD may signify "body-first" PD with bottom-up, symmetric synucleinopathy propagation.

Objective

Explore brainstem and nigrostriatal monoaminergic degeneration pattern differences based on premotor RBD presence and duration in de novo PD patients.

Methods

In a cross-sectional analysis of de novo PD patients (n = 150) undergoing FP-CIT PET and RBD Single-Question Screen, the cohort was categorized into groups with and without premotor RBD (PDRBD +/-), with further classification of PDRBD + based on a 10-year duration of premotor RBD. Analysis of FP-CIT binding in the striatum and pons, striatal asymmetry, and striatum-to-pons ratios compared patterns of nigrostriatal and brainstem monoaminergic degeneration.

Results

PDRBD + exhibited more severe and symmetrical striatal dopaminergic denervation compared to PDRBD-, with the difference in severity accentuated in the least-affected hemisphere. The PDRBD +<10Y subgroup displayed the most prominent striatal symmetry, supporting a more homogeneous "body-first" subtype. Pontine uptakes remained lower in PDRBD + even after adjusting for striatal uptake, suggesting early degeneration of pontine monoaminergic nuclei.

Conclusions

Premotor RBD in PD is associated with severe, symmetrical nigrostriatal and brainstem monoaminergic degeneration, especially in cases with PD onset within 10 years of RBD. This supports the concept of a "widespread, bottom-up" pathophysiological mechanism associated with premotor RBD in PD.

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.

Suitability of visual cues for freezing of gait in patients with idiopathic Parkinson's disease: a case-control pilot study

BACKGROUND

Freezing of gait (FOG) is one of the most debilitating symptoms in patients with idiopathic Parkinson's disease (IPD). Visual cues can relieve FOG symptoms. However, there is no consensus on patient characteristics that can benefit from visual cues. Therefore, we examined the differences in IPD patient characteristics according to the effectiveness of visual cueing.

METHODS

Through gait experiments, we investigated the number of FOG occurrences, average FOG period per episode, proportion of FOG duration in the total gait cycles, and FOG-free period gait spatiotemporal parameters in ten participants diagnosed with FOG due to IPD. Subsequently, the differences between their clinical characteristics and striatal dopamine active transporter availability from six subregions of the striatum were compared by dividing them into two groups based on the three reduction rates: occurrence numbers, mean durations per episode, and proportion of FOG duration in the total gait cycles improved by visual cueing using laser shoes. The relationships among these three reduction rates and other FOG-related parameters were also investigated using Spearman correlation analyses.

RESULTS

According to the three FOG-related reduction rates, the group assignments were the same, which was also related to the baseline self-reported FOG severity score (New Freezing of Gait Questionnaire): the more severe the FOG, the poorer the response to the visual cueing. By visual cueing, the better response group demonstrated the characteristics of lower new FOG questionnaire total scores, higher dopamine active transporter availability of the anterior and posterior putamen, and shorter mean duration of FOG per episode in the absence of cueing. These results were replicated using Spearman correlation analyses.

CONCLUSIONS

For FOG symptoms following IPD, gait assistance by visual cueing may be more effective when the total NFOGQ score is lower and the DAT of putamen is higher. Through this study, we demonstrated clinical and striatal dopaminergic conditions to select patients who may be more likely to benefit from visual cueing with laser shoes, and these findings lead to the need for early diagnosis of FOG in patients with IPD.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT05080413. Registered on September 14, 2021.

A Brief History of Nuclear Medicine Physics, Instrumentation, and Data Sciences in Korea

We review the history of nuclear medicine physics, instrumentation, and data sciences in Korea to commemorate the 60^th anniversary of the Korean Society of Nuclear Medicine. In the 1970s and 1980s, the development of SPECT, nuclear stethoscope, and bone densitometry systems, as well as kidney and cardiac image analysis technology, marked the beginning of nuclear medicine physics and engineering in Korea. With the introduction of PET and cyclotron in Korea in 1994, nuclear medicine imaging research was further activated. With the support of large-scale government projects, the development of gamma camera, SPECT, and PET systems was carried out. Exploiting the use of PET scanners in conjunction with cyclotrons, extensive studies on myocardial blood flow quantification and brain image analysis were also actively pursued. In 2005, Korea's first domestic cyclotron succeeded in producing radioactive isotopes, and the cyclotron was provided to six universities and university hospitals, thereby facilitating the nationwide supply of PET radiopharmaceuticals. Since the late 2000s, research on PET/MRI has been actively conducted, and the advanced research results of Korean scientists in the fields of silicon photomultiplier PET and simultaneous PET/MRI have attracted significant attention from the academic community. Currently, Korean researchers are actively involved in endeavors to solve a variety of complex problems in nuclear medicine using artificial intelligence and deep learning technologies.

Evaluation of a model-based attenuation correction method on whole-body 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging

The bone cannot be evaluated using magnetic resonance attenuation correction (MRAC) with the Dixon sequence. To solve this issue, the present study aimed to evaluate model-based AC for whole-body 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (¹⁸F-FDG) positron emission tomography (PET)/magnetic resonance imaging (MRI) by creating bone segmentation. We analyzed and evaluated the data of 31 consecutive patients. The Biograph mMR (Siemens Healthcare) was used for clinical whole-body ¹⁸F-FDG PET/MRI with the conventional MRAC method, and OSIRIX MD software was used to analyze the images. After the examination, the new model-based post-processing MRAC was applied to create μ-maps with bone segmentation, and retrospective PET reconstruction was performed using this μ-map. The bone structures of all patients created using model-based MRAC were visually evaluated. Standard uptake values (SUVs) at 11 anatomical positions in PET images, corrected using the μ-map with and without bone segmentation, were measured and compared. The model-based post-processing MRAC was run for all patients, without errors. Visual evaluation revealed that the model-based post-processing MRAC exhibited poor results for six patients. Furthermore, it exhibited an increasing trend of SUV in the brain compared to the conventional method. Locations other than the brain indicated a similar or decreasing trend. The two methods showed a good linear correlation for all patients. However, patients aged < 20 years exhibited a different trend from those aged ≥ 20 years. We should exercise caution when applying this model-based MRAC for younger patients.

MR Image-Based Attenuation Correction of Brain PET Imaging: Review of Literature on Machine Learning Approaches for Segmentation

Recent emerging hybrid technology of positron emission tomography/magnetic resonance (PET/MR) imaging has generated a great need for an accurate MR image-based PET attenuation correction. MR image segmentation, as a robust and simple method for PET attenuation correction, has been clinically adopted in commercial PET/MR scanners. The general approach in this method is to segment the MR image into different tissue types, each assigned an attenuation constant as in an X-ray CT image. Machine learning techniques such as clustering, classification and deep networks are extensively used for brain MR image segmentation. However, only limited work has been reported on using deep learning in brain PET attenuation correction. In addition, there is a lack of clinical evaluation of machine learning methods in this application. The aim of this review is to study the use of machine learning methods for MR image segmentation and its application in attenuation correction for PET brain imaging. Furthermore, challenges and future opportunities in MR image-based PET attenuation correction are discussed.

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.

Comparison of the Performances of (18)F-FP-CIT Brain PET/MR and Simultaneous PET/CT: a Preliminary Study

PURPOSE

(18)F-FP-CIT [(18)F-fluorinated N-3-fluoropropyl-2-beta-carboxymethoxy-3-beta-(4-iodophenyl) nortropane] has been well established and used for the differential diagnosis of atypical parkinsonian disorders. Recently, combined positron emission tomography (PET)/magnetic resonance (MR) was proposed as a viable alternative to PET/computed tomography (CT). The aim of this study was to compare the performances of conventional (18)F-FP-CIT brain PET/CT and simultaneous PET/MR by visual inspection and quantitative analysis.

METHODS

Fifteen consecutive patients clinically suspected of having Parkinson's disease were recruited for the study.(18)F-FP-CIT PET was performed during PET/CT and PET/MR. PET/CT image acquisition was started 90 min after intravenous injection of (18)F-FP-CIT and then PET/MR images were acquired. Dopamine transporter (DAT) density in bilateral striatal subregions was assessed visually. Quantitative analyses were performed on bilateral striatal volumes of interest (VOIs) using average standardized uptake values (SUVmeans). Intraclass correlation coefficients (ICCs) and their 95 % confidence intervals (CIs) were assessed to compare PET/CT and PET/MR data. Bland-Altman plots were drawn to perform method-comparisons.

RESULTS

All subjects showed a preferential decrease in DAT binding in the posterior putamen (PP), with relative sparing of the ventral putamen (VP). Bilateral striatal subregional binding ratio (BR) determined PET/CT and PET/MR demonstrated close interequipment correspondence (BRright caudate - ICC, 0.944; 95 % CI, 0.835-0.981, BRleft caudate - ICC, 0.917; 95 % CI, 0.753-0.972, BRright putamen - ICC, 0.976; 95 % CI, 0.929-0.992 and BRleft putamen - ICC, 0.970; 95 % CI, 0.911-0.990, respectively), and Bland-Altman plots showed interequipment agreement between the two modalities.

CONCLUSIONS

It is known that MR provides more information about anatomical changes associated with brain diseases and to enable the anatomical allocations of subregions than CT, though this was not observed in the present study. Although the subregional BR of simultaneous PET/MR was comparable to that of PET/CT in Parkinson's disease, our isocontouring method could make bias. A future automated method using standard template study or manual segmentation of putamen/caudate based on MR or CT is needed.

Comparison between MRI-based attenuation correction methods for brain PET in dementia patients

INTRODUCTION

The combination of Positron Emission Tomography (PET) with magnetic resonance imaging (MRI) in hybrid PET/MRI scanners offers a number of advantages in investigating brain structure and function. A critical step of PET data reconstruction is attenuation correction (AC). Accounting for bone in attenuation maps (μ-map) was shown to be important in brain PET studies. While there are a number of MRI-based AC methods, no systematic comparison between them has been performed so far. The aim of this work was to study the different performance obtained by some of the recent methods presented in the literature. To perform such a comparison, we focused on [¹⁸F]-Fluorodeoxyglucose-PET/MRI neurodegenerative dementing disorders, which are known to exhibit reduced levels of glucose metabolism in certain brain regions.

METHODS

Four novel methods were used to calculate μ-maps from MRI data of 15 patients with Alzheimer's dementia (AD). The methods cover two atlas-based methods, a segmentation method, and a hybrid template/segmentation method. Additionally, the Dixon-based and a UTE-based method, offered by a vendor, were included in the comparison. Performance was assessed at three levels: tissue identification accuracy in the μ-map, quantitative accuracy of reconstructed PET data in specific brain regions, and precision in diagnostic images at identifying hypometabolic areas.

RESULTS

Quantitative regional errors of -20--10 % were obtained using the vendor's AC methods, whereas the novel methods produced errors in a margin of ±5 %. The obtained precision at identifying areas with abnormally low levels of glucose uptake, potentially regions affected by AD, were 62.9 and 79.5 % for the two vendor AC methods, the former ignoring bone and the latter including bone information. The precision increased to 87.5-93.3 % in average for the four new methods, exhibiting similar performances.

CONCLUSION

We confirm that the AC methods based on the Dixon and UTE sequences provided by the vendor are inferior to alternative techniques. As a novel finding, there was no substantial difference between the recently proposed atlas-based, template-based and segmentation-based methods.

PET/MR in cancers of the head and neck

One early application of PET/MRI in clinical practice may be the imaging of head and neck cancers. This is because the morphologic imaging modalities, CT and MR, are recognized as similarly effective tools in cross-sectional oncological imaging of the head and neck. The addition of PET with FDG is believed to enhance the accuracy of both modalities to a similar degree. However, there are a few specific scenarios in head and neck cancer imaging where MR is thought to provide an edge over CT, including perineural spread of tumors and the infiltration of important anatomical landmarks, such as the prevertebral fascia and great vessel walls. Here, hybrid PET/MR might provide higher diagnostic certainty than PET/CT or a separate acquisition of PET/CT and MR. Another advantage of MR is the availability of several functional techniques. Although some of them might enhance the imaging of head and neck cancer with PET/MR, other functional techniques actually might prove dispensable in the presence of PET. In this overview, we discuss current trends and potential clinical applications of PET/MR in the imaging of head and neck cancers, including clinical protocols. We also discuss potential benefits of implementing functional MR techniques into hybrid PET/MRI of head and neck cancers.

PET/MR in dementia and other neurodegenerative diseases

The spectrum of neurodegenerative diseases covers the dementias, parkinsonian syndromes, Huntington disease, amyotrophic lateral sclerosis, and prion diseases. In these entities, brain MRI is often used in clinical routine to exclude other pathologies and to demonstrate specific atrophy patterns. [18F]FDG PET delivers early and sensitive readouts of neural tissue loss, and more specific PET tracers currently in use clinically target β-amyloid plaques or dopaminergic deficiency. The recent integration of PET into MR technology offers a new chance to improve early and differential diagnosis of many neurodegenerative diseases. Initial evidence in the literature is available to support this notion. New emerging PET tracers, such as tracers that bind to tau or α-synuclein aggregates, as well as MR techniques, like diffusion-tensor imaging, resting-state functional MRI, and arterial spin labeling, have the potential to broaden the diagnostic capabilities of combined PET/MRI to image dementias, Parkinson disease, and other neurodegenerative diseases. The ultimate goal is to establish combined PET/MRI as a first-line imaging technique to provide, in a one-stop-shop fashion with improved patient comfort, all biomarker information required to increase diagnostic confidence toward specific diagnoses. The technical challenge of accurate PET data attenuation correction within PET/MRI systems needs yet to be solved. Apart from the projected clinical routine applications, future research would need to answer the questions of whether combined brain PET/MRI is able to improve basic research of neurodegenerative diseases and antineurodegeneration drug testing.

Gray matter correlates of dopaminergic degeneration in Parkinson's disease: A hybrid PET/MR study using (18) F-FP-CIT

Dopaminergic degeneration is a hallmark of Parkinson's disease (PD), which causes various symptoms affected by corticostriatal circuits. So far, the relationship between cortical changes and dopamine loss in the striatum is unclear. Here, we evaluate the gray matter (GM) changes in accordance with striatal dopaminergic degeneration in PD using hybrid PET/MR. Sixteen patients with idiopathic PD underwent (18) F-FP-CIT PET/MR. To measure dopaminergic degeneration in PD, binding ratio (BR) of dopamine transporter in striatum was evaluated by (18) F-FP-CIT. Voxel-based morphometry (VBM) was used to evaluate GM density. We obtained voxelwise correlation maps of GM density according to the striatal BR. Voxel-by-voxel correlation between BR maps and GM density maps was done to evaluate region-specific correlation of striatal dopaminergic degeneration. There was a trend of positive correlation between striatal BR and GM density in the cerebellum, parahippocampal gyri, and frontal cortex. A trend of negative correlation between striatal BR and GM density in the medial occipital cortex was found. Voxel-by-voxel correlation revealed that the positive correlation was mainly dependent on anterior striatal BR, while posterior striatal BR mostly showed negative correlation with GM density in occipital and temporal cortices. Decreased GM density related to anterior striatal dopaminergic degeneration might demonstrate degeneration of dopaminergic nonmotor circuits. Furthermore, the negative correlation could be related to the motor circuits of posterior striatum. Our integrated PET/MR study suggests that the widespread structural progressive changes in PD could denote the cortical functional correlates of the degeneration of striatal dopaminergic circuits. Hum Brain Mapp 37:1710-1721, 2016. © 2016 Wiley Periodicals, Inc.

PET/MR brain imaging: evaluation of clinical UTE-based attenuation correction

One of the greatest challenges in PET/MR imaging is that of accurate MR-based attenuation correction (AC) of the acquired PET data, which must be solved if the PET/MR modality is to reach its full potential. The aim of this study was to investigate the performance of Siemens' most recent version (VB20P) of MR-based AC of head PET data, by comparing it to CT-based AC.

METHODS

(18)F-FDG PET data from seven lymphoma and twelve lung cancer patients examined with a Biograph mMR PET/MR system were reconstructed with both CT-based and MR-based AC, avoiding sources of error arising when comparing PET data from different systems. The resulting images were compared quantitatively by measuring changes in mean SUV in ten different brain regions in both hemispheres, as well as the brainstem. In addition, the attenuation maps (μ maps) were compared regarding volume and localization of cranial bone.

RESULTS

The UTE μ maps clearly overestimate the amount of bone in the neck, while slightly underestimating the amount of bone in the cranium, and the localization of bone in the cranial region also differ from the CT μ maps. In air/tissue interfaces in the sinuses and ears, the MRAC method struggles to correctly classify the different tissues. The misclassification of tissue is most likely caused by a combination of artefacts and the insufficiency of the UTE method to accurately separate bone. Quantitatively, this results in a combination of overestimation (0.5-3.6 %) and underestimation (2.7-5.2 %) of PET activity throughout the brain, depending on the proximity to the inaccurate regions.

CONCLUSIONS

Our results indicate that the performance of the UTE method as implemented in VB20P is close to the theoretical maximum of such an MRAC method in the brain, while it does not perform satisfactorily in the neck or face/nasal area. Further improvement of the UTE MRAC or other available methods for more accurate segmentation of bone should be incorporated.