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Lo YW, Lin KH, Lee CY, Li CW, Lin CY, Chen YW, Wang LW, Wu YH, Huang WS. The impact of ZTE-based MR attenuation correction compared to CT-AC in 18F-FBPA PET before boron neutron capture therapy. Sci Rep 2024; 14:13950. [PMID: 38886395 PMCID: PMC11183148 DOI: 10.1038/s41598-024-63248-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 05/27/2024] [Indexed: 06/20/2024] Open
Abstract
Tumor-to-normal ratio (T/N) measurement of 18F-FBPA is crucial for patient eligibility to receive boron neutron capture therapy. This study aims to compare the difference in standard uptake value ratios on brain tumors and normal brains using PET/MR ZTE and atlas-based attenuation correction with the current standard PET/CT attenuation correction. Regarding the normal brain uptake, the difference was not significant between PET/CT and PET/MR attenuation correction methods. The T/N ratio of PET/CT-AC, PET/MR ZTE-AC and PET/MR AB-AC were 2.34 ± 0.95, 2.29 ± 0.88, and 2.19 ± 0.80, respectively. The T/N ratio comparison showed no significance using PET/CT-AC and PET/MR ZTE-AC. As for the PET/MRI AB-AC, significantly lower T/N ratio was observed (- 5.18 ± 9.52%; p < 0.05). The T/N difference between ZTE-AC and AB-AC was also significant (4.71 ± 5.80%; p < 0.01). Our findings suggested PET/MRI imaging using ZTE-AC provided superior quantification on 18F-FBPA-PET compared to atlas-based AC. Using ZTE-AC on 18F-FBPA-PET /MRI might be crucial for BNCT pre-treatment planning.
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Affiliation(s)
- Yi-Wen Lo
- Integrated PET/MR Imaging Center, Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan ROC
- Clinical Imaging Research Center (CIRC), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ko-Han Lin
- Integrated PET/MR Imaging Center, Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan ROC.
| | - Chien-Ying Lee
- Integrated PET/MR Imaging Center, Department of Nuclear Medicine, Taipei Veterans General Hospital, Taipei, Taiwan ROC
- Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming Chiao Tung University, Taipei, Taiwan ROC
| | | | | | - Yi-Wei Chen
- Division of Radiotherapy, Department of Oncology, Taipei Veterans General Hospital, Taipei, Taiwan ROC
| | - Ling-Wei Wang
- Division of Radiotherapy, Department of Oncology, Taipei Veterans General Hospital, Taipei, Taiwan ROC
| | - Yuan-Hung Wu
- Division of Radiotherapy, Department of Oncology, Taipei Veterans General Hospital, Taipei, Taiwan ROC
| | - Wen-Sheng Huang
- Department of Nuclear Medicine, Chang Bing Show Chwan Memorial Hospital, Taipei, Taiwan ROC.
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Siva NK, Bauer C, Glover C, Stolin A, Chandi S, Melnick H, Marano G, Parker B, Mandich M, Lewis JW, Qi J, Gao S, Nott K, Majewski S, Brefczynski-Lewis JA. Real-time motion-enabling positron emission tomography of the brain of upright ambulatory humans. COMMUNICATIONS MEDICINE 2024; 4:117. [PMID: 38872007 PMCID: PMC11176317 DOI: 10.1038/s43856-024-00547-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 06/05/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND Mobile upright PET devices have the potential to enable previously impossible neuroimaging studies. Currently available options are imagers with deep brain coverage that severely limit head/body movements or imagers with upright/motion enabling properties that are limited to only covering the brain surface. METHODS In this study, we test the feasibility of an upright, motion-compatible brain imager, our Ambulatory Motion-enabling Positron Emission Tomography (AMPET) helmet prototype, for use as a neuroscience tool by replicating a variant of a published PET/fMRI study of the neurocorrelates of human walking. We validate our AMPET prototype by conducting a walking movement paradigm to determine motion tolerance and assess for appropriate task related activity in motor-related brain regions. Human participants (n = 11 patients) performed a walking-in-place task with simultaneous AMPET imaging, receiving a bolus delivery of F18-Fluorodeoxyglucose. RESULTS Here we validate three pre-determined measure criteria, including brain alignment motion artifact of less than <2 mm and functional neuroimaging outcomes consistent with existing walking movement literature. CONCLUSIONS The study extends the potential and utility for use of mobile, upright, and motion-tolerant neuroimaging devices in real-world, ecologically-valid paradigms. Our approach accounts for the real-world logistics of an actual human participant study and can be used to inform experimental physicists, engineers and imaging instrumentation developers undertaking similar future studies. The technical advances described herein help set new priorities for facilitating future neuroimaging devices and research of the human brain in health and disease.
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Affiliation(s)
- Nanda K Siva
- Department of Neuroscience, West Virginia University, P.O. Box 9303, Morgantown, WV, USA
| | | | - Colson Glover
- Department of Neuroscience, West Virginia University, P.O. Box 9303, Morgantown, WV, USA
| | - Alexander Stolin
- Department of Neuroscience, West Virginia University, P.O. Box 9303, Morgantown, WV, USA
| | - Sonia Chandi
- Department of Neuroscience, West Virginia University, P.O. Box 9303, Morgantown, WV, USA
| | - Helen Melnick
- Department of Neuroscience, West Virginia University, P.O. Box 9303, Morgantown, WV, USA
| | - Gary Marano
- Department of Neuroscience, West Virginia University, P.O. Box 9303, Morgantown, WV, USA
| | - Benjamin Parker
- Department of Neuroscience, West Virginia University, P.O. Box 9303, Morgantown, WV, USA
| | - MaryBeth Mandich
- Department of Neuroscience, West Virginia University, P.O. Box 9303, Morgantown, WV, USA
| | - James W Lewis
- Department of Neuroscience, West Virginia University, P.O. Box 9303, Morgantown, WV, USA
| | - Jinyi Qi
- Department of Biomedical Engineering, University of California, Davis, Davis, CA, USA
| | - Si Gao
- Department of Neuroscience, West Virginia University, P.O. Box 9303, Morgantown, WV, USA
| | - Kaylee Nott
- Department of Neuroscience, West Virginia University, P.O. Box 9303, Morgantown, WV, USA
| | - Stan Majewski
- Department of Biomedical Engineering, University of California, Davis, Davis, CA, USA
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Krokos G, MacKewn J, Dunn J, Marsden P. A review of PET attenuation correction methods for PET-MR. EJNMMI Phys 2023; 10:52. [PMID: 37695384 PMCID: PMC10495310 DOI: 10.1186/s40658-023-00569-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 08/07/2023] [Indexed: 09/12/2023] Open
Abstract
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.
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Affiliation(s)
- Georgios Krokos
- School of Biomedical Engineering and Imaging Sciences, The PET Centre at St Thomas' Hospital London, King's College London, 1st Floor Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK.
| | - Jane MacKewn
- School of Biomedical Engineering and Imaging Sciences, The PET Centre at St Thomas' Hospital London, King's College London, 1st Floor Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK
| | - Joel Dunn
- School of Biomedical Engineering and Imaging Sciences, The PET Centre at St Thomas' Hospital London, King's College London, 1st Floor Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK
| | - Paul Marsden
- School of Biomedical Engineering and Imaging Sciences, The PET Centre at St Thomas' Hospital London, King's College London, 1st Floor Lambeth Wing, Westminster Bridge Road, London, SE1 7EH, UK
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4
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Gao F. Integrated Positron Emission Tomography/Magnetic Resonance Imaging in clinical diagnosis of Alzheimer's disease. Eur J Radiol 2021; 145:110017. [PMID: 34826792 DOI: 10.1016/j.ejrad.2021.110017] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 08/30/2021] [Accepted: 10/31/2021] [Indexed: 12/01/2022]
Abstract
Alzheimer's disease (AD), a progressive neurodegenerative disease which seriously endangers the health of the aged, is the most common etiology of senile dementia. With the increasing progress of neuroimaging technology, more and more imaging methods have been applied to study Alzheimer's disease. The emergence of integrated PET/MRI (Positron Emission Tomography/Magnetic Resonance Imaging) is a major advance in multimodal molecular imaging with many advantages on the structure of resolution and contrast of image over computed tomography (CT), PET and MRI. PET/MRI is now used stepwise in neurodegenerative diseases, and also has broad prospect of application in the early diagnosis of AD. In this review, we emphatically introduce the imaging advances of AD including functional imaging and molecular imaging, the advantages of PET/MRI over other imaging methods and prospects of PET/MRI in AD clinical diagnosis, especially in early diagnosis, clinical assessment and prediction on AD.
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Affiliation(s)
- Feng Gao
- Key Laboratory for Experimental Teratology of the Ministry of Education and Center for Experimental Nuclear Medicine, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China.
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5
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Gong K, Han PK, Johnson KA, El Fakhri G, Ma C, Li Q. Attenuation correction using deep Learning and integrated UTE/multi-echo Dixon sequence: evaluation in amyloid and tau PET imaging. Eur J Nucl Med Mol Imaging 2021; 48:1351-1361. [PMID: 33108475 PMCID: PMC8411350 DOI: 10.1007/s00259-020-05061-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Accepted: 09/30/2020] [Indexed: 02/07/2023]
Abstract
PURPOSE PET measures of amyloid and tau pathologies are powerful biomarkers for the diagnosis and monitoring of Alzheimer's disease (AD). Because cortical regions are close to bone, quantitation accuracy of amyloid and tau PET imaging can be significantly influenced by errors of attenuation correction (AC). This work presents an MR-based AC method that combines deep learning with a novel ultrashort time-to-echo (UTE)/multi-echo Dixon (mUTE) sequence for amyloid and tau imaging. METHODS Thirty-five subjects that underwent both 11C-PiB and 18F-MK6240 scans were included in this study. The proposed method was compared with Dixon-based atlas method as well as magnetization-prepared rapid acquisition with gradient echo (MPRAGE)- or Dixon-based deep learning methods. The Dice coefficient and validation loss of the generated pseudo-CT images were used for comparison. PET error images regarding standardized uptake value ratio (SUVR) were quantified through regional and surface analysis to evaluate the final AC accuracy. RESULTS The Dice coefficients of the deep learning methods based on MPRAGE, Dixon, and mUTE images were 0.84 (0.91), 0.84 (0.92), and 0.87 (0.94) for the whole-brain (above-eye) bone regions, respectively, higher than the atlas method of 0.52 (0.64). The regional SUVR error for the atlas method was around 6%, higher than the regional SUV error. The regional SUV and SUVR errors for all deep learning methods were below 2%, with mUTE-based deep learning method performing the best. As for the surface analysis, the atlas method showed the largest error (> 10%) near vertices inside superior frontal, lateral occipital, superior parietal, and inferior temporal cortices. The mUTE-based deep learning method resulted in the least number of regions with error higher than 1%, with the largest error (> 5%) showing up near the inferior temporal and medial orbitofrontal cortices. CONCLUSION Deep learning with mUTE can generate accurate AC for amyloid and tau imaging in PET/MR.
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Affiliation(s)
- Kuang Gong
- Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Paul Kyu Han
- Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Keith A Johnson
- Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Chao Ma
- Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Quanzheng Li
- Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
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6
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Kubo H, Nemoto A, Ukon N, Ito H. Evaluation of a model-based attenuation correction method on whole-body 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging. Radiol Phys Technol 2021; 14:70-81. [PMID: 33400065 DOI: 10.1007/s12194-020-00605-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 12/19/2020] [Accepted: 12/22/2020] [Indexed: 10/22/2022]
Abstract
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.
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Affiliation(s)
- Hitoshi Kubo
- Preparing Section for New Faculty of Medical Science, Fukushima Medical University, 1 Hikariga-oka, Fukushima, Fukushima, 960-1295, Japan. .,Advanced Clinical Research Center, Fukushima Medical University, Fukushima, Japan.
| | - Ayaka Nemoto
- Advanced Clinical Research Center, Fukushima Medical University, Fukushima, Japan
| | - Naoyuki Ukon
- Advanced Clinical Research Center, Fukushima Medical University, Fukushima, Japan
| | - Hiroshi Ito
- Advanced Clinical Research Center, Fukushima Medical University, Fukushima, Japan.,Department of Radiology and Nuclear Medicine, Fukushima Medical University, Fukushima, Japan
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7
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The impact of atlas-based MR attenuation correction on the diagnosis of FDG-PET/MR for Alzheimer's diseases- A simulation study combining multi-center data and ADNI-data. PLoS One 2020; 15:e0233886. [PMID: 32492074 PMCID: PMC7269241 DOI: 10.1371/journal.pone.0233886] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 05/14/2020] [Indexed: 11/19/2022] Open
Abstract
Background The purpose of this study was to assess the impact of vendor-provided atlas-based MRAC on FDG PET/MR for the evaluation of Alzheimer’s disease (AD) by using simulated images. Methods We recruited 47 patients, from two institutions, who underwent PET/CT and PET/MR (GE SIGNA) examination for oncological staging. From the PET raw data acquired on PET/MR, two FDG-PET series were generated, using vendor-provided MRAC (atlas-based) and CTAC. The following simulation steps were performed in MNI space: After spatial normalization and smoothing of the PET datasets, we calculated the error map for each patient, PETMRAC/PETCTAC. We multiplied each of these 47 error maps with each of the 203 Alzheimer’s Disease Neuroimaging Initiative (ADNI) cases after the identical normalization and smoothing. This resulted in 203*47 = 9541 datasets. To evaluate the probability of AD in each resulting image, a cumulative t-value was calculated automatically using commercially-available software (PMOD PALZ) which has been used in multiple large cohort studies. The diagnostic accuracy for the discrimination of AD and predicting progression from mild cognitive impairment (MCI) to AD were evaluated in simulated images compared with ADNI original images. Results The accuracy and specificity for the discrimination of AD-patients from normal controls were not substantially impaired, but sensitivity was slightly impaired in 5 out of 47 datasets (original vs. error; 83.2% [CI 75.0%-89.0%], 83.3% [CI 74.2%-89.8%] and 83.1% [CI 75.6%-88.3%] vs. 82.7% [range 80.4–85.0%], 78.5% [range 72.9–83.3%,] and 86.1% [range 81.4–89.8%]). The accuracy, sensitivity and specificity for predicting progression from MCI to AD during 2-year follow-up was not impaired (original vs. error; 62.5% [CI 53.3%-69.3%], 78.8% [CI 65.4%-88.6%] and 54.0% [CI 47.0%-69.1%] vs. 64.8% [range 61.5–66.7%], 75.7% [range 66.7–81.8%,] and 59.0% [range 50.8–63.5%]). The worst 3 error maps show a tendency towards underestimation of PET scores. Conclusion FDG-PET/MR based on atlas-based MR attenuation correction showed similar diagnostic accuracy to the CT-based method for the diagnosis of AD and the prediction of progression of MCI to AD using commercially-available software, although with a minor reduction in sensitivity.
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8
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Torrado-Carvajal A. Importance of attenuation correction in PET/MR image quantification: Methods and applications. Rev Esp Med Nucl Imagen Mol 2020. [DOI: 10.1016/j.remnie.2020.03.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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9
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Torrado-Carvajal A. Importance of attenuation correction in PET/MR image quantification: Methods and applications. Rev Esp Med Nucl Imagen Mol 2020; 39:163-168. [PMID: 32345573 DOI: 10.1016/j.remn.2020.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 03/02/2020] [Accepted: 03/03/2020] [Indexed: 10/24/2022]
Abstract
The generation of accurate attenuation correction (AC) maps is a basic step to allow for quantitative PET/MR imaging. However, generating MR-based AC maps is a challenge because there is no direct relationship between the PET attenuation coefficients (μ) and the intensity of the MR signal, contrary to what happens with the intensity of CT images. In fact, ignoring the bone causes a distorted and biased distribution of the calculated SUV values. To solve this problem, several MR-based AC methods have been proposed in the literature. In this paper we describe how these methods work, and the challenge they faced to translate into full body applications. Currently, in research environments, the accuracy of AC methods is no longer a limiting factor to solve in order to carry out quantitative in vivo molecular imaging studies. However, many of these methods present a series of limitations for their real implementation in the clinical practice due to insufficient clinical validation and the difficulty of their implementation in a real environment (as described in the examples of clinical applications). Thus, we need the PET/MR community to work on the standardization of the use and assessment of different AC methods. In this scenario, the opening and access by vendors to the implementation of new AC methods in their PET/MR scanners plays a crucial role.
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Affiliation(s)
- A Torrado-Carvajal
- Laboratorio de Análisis de Imagen Médica y Biometría, Universidad Rey Juan Carlos, Madrid, España; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, Estados Unidos.
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10
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Blanc-Durand P, Khalife M, Sgard B, Kaushik S, Soret M, Tiss A, El Fakhri G, Habert MO, Wiesinger F, Kas A. Attenuation correction using 3D deep convolutional neural network for brain 18F-FDG PET/MR: Comparison with Atlas, ZTE and CT based attenuation correction. PLoS One 2019; 14:e0223141. [PMID: 31589623 PMCID: PMC6779234 DOI: 10.1371/journal.pone.0223141] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 09/13/2019] [Indexed: 11/23/2022] Open
Abstract
One of the main technical challenges of PET/MRI is to achieve an accurate PET attenuation correction (AC) estimation. In current systems, AC is accomplished by generating an MRI-based surrogate computed tomography (CT) from which AC-maps are derived. Nevertheless, all techniques currently implemented in clinical routine suffer from bias. We present here a convolutional neural network (CNN) that generated AC-maps from Zero Echo Time (ZTE) MR images. Seventy patients referred to our institution for 18FDG-PET/MR exam (SIGNA PET/MR, GE Healthcare) as part of the investigation of suspected dementia, were included. 23 patients were added to the training set of the manufacturer and 47 were used for validation. Brain computed tomography (CT) scan, two-point LAVA-flex MRI (for atlas-based AC) and ZTE-MRI were available in all patients. Three AC methods were evaluated and compared to CT-based AC (CTAC): one based on a single head-atlas, one based on ZTE-segmentation and one CNN with a 3D U-net architecture to generate AC maps from ZTE MR images. Impact on brain metabolism was evaluated combining voxel and regions-of-interest based analyses with CTAC set as reference. The U-net AC method yielded the lowest bias, the lowest inter-individual and inter-regional variability compared to PET images reconstructed with ZTE and Atlas methods. The impact on brain metabolism was negligible with average errors of -0.2% in most cortical regions. These results suggest that the U-net AC is more reliable for correcting photon attenuation in brain FDG-PET/MR than atlas-AC and ZTE-AC methods.
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Affiliation(s)
- Paul Blanc-Durand
- Nuclear Medicine Department, Groupe Hospitalier Pitié-Salpêtrière C. Foix, APHP, Paris, France
- * E-mail:
| | - Maya Khalife
- Centre de Neuroimagerie de Recherche (CENIR), Institut du Cerveau et de la Moëlle, Paris, France
| | - Brian Sgard
- Nuclear Medicine Department, Groupe Hospitalier Pitié-Salpêtrière C. Foix, APHP, Paris, France
| | | | - Marine Soret
- Nuclear Medicine Department, Groupe Hospitalier Pitié-Salpêtrière C. Foix, APHP, Paris, France
| | - Amal Tiss
- Gordon Center for Medical Imaging, Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Marie-Odile Habert
- Nuclear Medicine Department, Groupe Hospitalier Pitié-Salpêtrière C. Foix, APHP, Paris, France
- Laboratoire d’Imagerie Biomédicale, Sorbonne Université, Paris, France
| | | | - Aurélie Kas
- Nuclear Medicine Department, Groupe Hospitalier Pitié-Salpêtrière C. Foix, APHP, Paris, France
- Laboratoire d’Imagerie Biomédicale, Sorbonne Université, Paris, France
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11
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Øen SK, Keil TM, Berntsen EM, Aanerud JF, Schwarzlmüller T, Ladefoged CN, Karlberg AM, Eikenes L. Quantitative and clinical impact of MRI-based attenuation correction methods in [ 18F]FDG evaluation of dementia. EJNMMI Res 2019; 9:83. [PMID: 31446507 PMCID: PMC6708519 DOI: 10.1186/s13550-019-0553-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Accepted: 08/15/2019] [Indexed: 01/03/2023] Open
Abstract
Background Positron emission tomography/magnetic resonance imaging (PET/MRI) is a promising diagnostic imaging tool for the diagnosis of dementia, as PET can add complementary information to the routine imaging examination with MRI. The purpose of this study was to evaluate the influence of MRI-based attenuation correction (MRAC) on diagnostic assessment of dementia with [18F]FDG PET. Quantitative differences in both [18F]FDG uptake and z-scores were calculated for three clinically available (DixonNoBone, DixonBone, UTE) and two research MRAC methods (UCL, DeepUTE) compared to CT-based AC (CTAC). Furthermore, diagnoses based on visual evaluations were made by three nuclear medicine physicians and one neuroradiologist (PETCT, PETDeepUTE, PETDixonBone, PETUTE, PETCT + MRI, PETDixonBone + MRI). In addition, pons and cerebellum were compared as reference regions for normalization. Results The mean absolute difference in z-scores were smallest between MRAC and CTAC with cerebellum as reference region: 0.15 ± 0.11 σ (DeepUTE), 0.15 ± 0.12 σ (UCL), 0.23 ± 0.20 σ (DixonBone), 0.32 ± 0.28 σ (DixonNoBone), and 0.54 ± 0.40 σ (UTE). In the visual evaluation, the diagnoses agreed with PETCT in 74% (PETDeepUTE), 67% (PETDixonBone), and 70% (PETUTE) of the patients, while PETCT + MRI agreed with PETDixonBone + MRI in 89% of the patients. Conclusion The MRAC research methods performed close to that of CTAC in the quantitative evaluation of [18F]FDG uptake and z-scores. Among the clinically implemented MRAC methods, DixonBone should be preferred for diagnostic assessment of dementia with [18F]FDG PET/MRI. However, as artifacts occur in DixonBone attenuation maps, they must be visually inspected to assure proper quantification. Electronic supplementary material The online version of this article (10.1186/s13550-019-0553-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Silje Kjærnes Øen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Postbox 8905, N-7491, Trondheim, Norway.
| | - Thomas Morten Keil
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim, Norway
| | - Erik Magnus Berntsen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Postbox 8905, N-7491, Trondheim, Norway.,Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim, Norway
| | - Joel Fredrik Aanerud
- Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Aarhus, Denmark
| | - Thomas Schwarzlmüller
- Department of Radiology, Haukeland University Hospital, Bergen, Norway.,Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Claes Nøhr Ladefoged
- Department of Clinical Physiology, Nuclear Medicine & PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Anna Maria Karlberg
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Postbox 8905, N-7491, Trondheim, Norway.,Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim, Norway
| | - Live Eikenes
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Postbox 8905, N-7491, Trondheim, Norway
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12
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Cabello J, Avram M, Brandl F, Mustafa M, Scherr M, Leucht C, Leucht S, Sorg C, Ziegler SI. Impact of non-uniform attenuation correction in a dynamic [ 18F]-FDOPA brain PET/MRI study. EJNMMI Res 2019; 9:77. [PMID: 31428975 PMCID: PMC6702490 DOI: 10.1186/s13550-019-0547-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 07/25/2019] [Indexed: 12/31/2022] Open
Abstract
Background PET (positron emission tomography) biokinetic modelling relies on accurate quantitative data. One of the main corrections required in PET imaging to obtain high quantitative accuracy is tissue attenuation correction (AC). Incorrect non-uniform PET-AC may result in local bias in the emission images, and thus in relative activity distributions and time activity curves for different regions. MRI (magnetic resonance imaging)-based AC is an active area of research in PET/MRI neuroimaging, where several groups developed in the last few years different methods to calculate accurate attenuation (μ-)maps. Some AC methods have been evaluated for different PET radioisotopes and pathologies. However, AC in PET/MRI has scantly been investigated in dynamic PET studies where the aim is to get quantitative kinetic parameters, rather than semi-quantitative parameters from static PET studies. In this work, we investigated the impact of AC accuracy in PET image absolute quantification and, more importantly, in the slope of the Patlak analysis based on the simplified reference tissue model, from a dynamic [18F]-fluorodopa (FDOPA) PET/MRI study. In the study, we considered the two AC methods provided by the vendor and an in-house AC method based on the dual ultrashort time echo MRI sequence, using as reference a multi-atlas-based AC method based on a T1-weighted MRI sequence. Results Non-uniform bias in absolute PET quantification across the brain, from − 20% near the skull to − 10% in the central region, was observed using the two vendor’s μ-maps. The AC method developed in-house showed a − 5% and 1% bias, respectively. Our study resulted in a 5–9% overestimation of the PET kinetic parameters with the vendor-provided μ-maps, while our in-house-developed AC method showed < 2% overestimation compared to the atlas-based AC method, using the cerebellar cortex as reference region. The overestimation obtained using the occipital pole as reference region resulted in a 7–10% with the vendor-provided μ-maps, while our in-house-developed AC method showed < 6% overestimation. Conclusions PET kinetic analyses based on a reference region are especially sensitive to the non-uniform bias in PET quantification from AC inaccuracies in brain PET/MRI. Depending on the position of the reference region and the bias with respect to the analysed region, kinetic analyses suffer different levels of bias. Considering bone in the μ-map can potentially result in larger errors, compared to the absence of bone, when non-uniformities in PET quantification are introduced.
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Affiliation(s)
- Jorge Cabello
- Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany. .,Present Address: Siemens Healthineers Molecular Imaging, Knoxville, TN, USA.
| | - Mihai Avram
- Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Felix Brandl
- Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Mona Mustafa
- Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Martin Scherr
- Klinik und Poliklinik für Psychiatrie, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Universitätsklinik für Psychiatrie und Psychotherapie, Paracelsus Medical University, Salzburg, Austria
| | - Claudia Leucht
- Klinik und Poliklinik für Psychiatrie, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Stefan Leucht
- Klinik und Poliklinik für Psychiatrie, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Christian Sorg
- Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Klinik und Poliklinik für Psychiatrie, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Sibylle I Ziegler
- Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.,Klinik und Poliklinik für Nuklearmedizin, Klinikum der Universität München, Ludwig-Maximilians-Universität, Munich, Germany
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13
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Caldeira L, Rota Kops E, Yun SD, da Silva N, Mauler J, Weirich C, Scheins J, Herzog H, Tellmann L, Lohmann P, Langen KJ, Lerche C, Shah NJ. The Jülich Experience With Simultaneous 3T MR-BrainPET: Methods and Technology. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2019. [DOI: 10.1109/trpms.2018.2863953] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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14
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No significant difference found in PET/MRI CBF values reconstructed with CT-atlas-based and ZTE MR attenuation correction. EJNMMI Res 2019; 9:26. [PMID: 30888559 PMCID: PMC6424990 DOI: 10.1186/s13550-019-0494-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 03/06/2019] [Indexed: 01/31/2023] Open
Abstract
Background Accurate attenuation correction (AC) is one of the most important issues to be addressed in quantitative brain PET/MRI imaging. Atlas-based MRI AC (AB-MRAC), one of the representative MRAC methods, has been used to estimate the skull attenuation in brain scans. The zero echo time (ZTE) pulse sequence is also expected to provide a better MRAC estimation in brain PET scans. The difference in quantitative measurements of cerebral blood flow (CBF) using H215O-PET/MRI was compared between the two MRAC methods, AB and ZTE. Method Twelve patients with cerebrovascular disease (4 males, 43.2 ± 11.7 years) underwent H215O-PET/MRI studies with a 3-min PET scan and MRI scans including the ZTE sequence. Eleven of them were also studied under the conditions of baseline and 10 min after acetazolamide administration, and 2 of them were followed up after several months interval. A total of 25 PET images were reconstructed as dynamic data using 2 sets of reconstruction parameters to obtain the image-derived input function (IDIF), the time-activity curves of the major cerebral artery extracted from images, and CBF images. The CBF images from AB- and ZTE-MRAC were then compared for global and regional differences. Results The mean differences of IDIF curves at each point obtained from AB- and ZTE-MRAC dynamic data were less than 5%, and the differences in time-activity curves were very small. The means of CBF from AB- and ZTE-MRAC reconstructions calculated using each IDIF showed differences of less than 5% for all cortical regions. CBF images from AB-MRAC tended to show greater values in the parietal region and smaller values in the skull base region. Conclusion The CBF images from AB- and ZTE-MRAC reconstruction showed no significant differences in regional values, although the parietal region tended to show greater values in AB-MRAC reconstruction. Quantitative values in the skull base region were very close, and almost the same IDIFs were obtained.
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15
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Baran J, Chen Z, Sforazzini F, Ferris N, Jamadar S, Schmitt B, Faul D, Shah NJ, Cholewa M, Egan GF. Accurate hybrid template-based and MR-based attenuation correction using UTE images for simultaneous PET/MR brain imaging applications. BMC Med Imaging 2018; 18:41. [PMID: 30400875 PMCID: PMC6220492 DOI: 10.1186/s12880-018-0283-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Accepted: 10/24/2018] [Indexed: 12/29/2022] Open
Abstract
Background Attenuation correction is one of the most crucial correction factors for accurate PET data quantitation in hybrid PET/MR scanners, and computing accurate attenuation coefficient maps from MR brain acquisitions is challenging. Here, we develop a method for accurate bone and air segmentation using MR ultrashort echo time (UTE) images. Methods MR UTE images from simultaneous MR and PET imaging of five healthy volunteers was used to generate a whole head, bone and air template image for inclusion into an improved MR derived attenuation correction map, and applied to PET image data for quantitative analysis. Bone, air and soft tissue were segmented based on Gaussian Mixture Models with probabilistic tissue maps as a priori information. We present results for two approaches for bone attenuation coefficient assignments: one using a constant attenuation correction value; and another using an estimated continuous attenuation value based on a calibration fit. Quantitative comparisons were performed to evaluate the accuracy of the reconstructed PET images, with respect to a reference image reconstructed with manually segmented attenuation maps. Results The DICE coefficient analysis for the air and bone regions in the images demonstrated improvements compared to the UTE approach, and other state-of-the-art techniques. The most accurate whole brain and regional brain analyses were obtained using constant bone attenuation coefficient values. Conclusions A novel attenuation correction method for PET data reconstruction is proposed. Analyses show improvements in the quantitative accuracy of the reconstructed PET images compared to other state-of-the-art AC methods for simultaneous PET/MR scanners. Further evaluation is needed with radiopharmaceuticals other than FDG, and in larger cohorts of participants.
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Affiliation(s)
- Jakub Baran
- Monash Biomedical Imaging, Monash University, Melbourne, Australia. .,Department of Biophysics, Faculty of Mathematics and Natural Sciences, University of Rzeszow, Rzeszow, Poland. .,Institute of Nuclear Physics Polish Academy of Science, Krakow, Poland.
| | - Zhaolin Chen
- Monash Biomedical Imaging, Monash University, Melbourne, Australia.,Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Australia
| | | | - Nicholas Ferris
- Monash Biomedical Imaging, Monash University, Melbourne, Australia.,Monash Imaging, Monash Health, Clayton, Australia
| | - Sharna Jamadar
- Monash Biomedical Imaging, Monash University, Melbourne, Australia.,Monash Institute of Cognitive and Clinical Neurosciences and School of Psychological Sciences, Monash University, Melbourne, Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Monash University, Melbourne, Australia
| | - Ben Schmitt
- Siemens Healthcare Pty Ltd, Sydney, Australia
| | - David Faul
- Siemens Healthcare Pty Ltd, New York, USA
| | - Nadim Jon Shah
- Monash Biomedical Imaging, Monash University, Melbourne, Australia.,Institute of Neuroscience and Medicine, Forschungszentrum Juelich GmbH, Juelich, Germany
| | - Marian Cholewa
- Department of Biophysics, Faculty of Mathematics and Natural Sciences, University of Rzeszow, Rzeszow, Poland
| | - Gary F Egan
- Monash Biomedical Imaging, Monash University, Melbourne, Australia.,Monash Institute of Cognitive and Clinical Neurosciences and School of Psychological Sciences, Monash University, Melbourne, Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Monash University, Melbourne, Australia
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16
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Aiello M, Cavaliere C, Marchitelli R, d'Albore A, De Vita E, Salvatore M. Hybrid PET/MRI Methodology. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2018; 141:97-128. [PMID: 30314608 DOI: 10.1016/bs.irn.2018.07.026] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
The hybrid PET/MR scanner represents the first implementation of the effective integration of two modalities allowing truly synchronous/simultaneous acquisition of their imaging signals. This integration, resulting from the innovation and development of specific hardware components has paved the way for new approaches in the study of neurodegenerative diseases. This chapter will describe the hardware development that has led to the availability of different clinical solutions for PET/MR imaging as well as the still-open technological challenges and opportunities related to the processing and exploitation of the simultaneous acquisition in neurological studies.
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Affiliation(s)
| | | | | | | | - Enrico De Vita
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, King's Health Partners, St Thomas' Hospital, London, United Kingdom
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17
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Chen Z, Jamadar SD, Li S, Sforazzini F, Baran J, Ferris N, Shah NJ, Egan GF. From simultaneous to synergistic MR-PET brain imaging: A review of hybrid MR-PET imaging methodologies. Hum Brain Mapp 2018; 39:5126-5144. [PMID: 30076750 DOI: 10.1002/hbm.24314] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Revised: 06/25/2018] [Accepted: 07/02/2018] [Indexed: 12/17/2022] Open
Abstract
Simultaneous Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) scanning is a recent major development in biomedical imaging. The full integration of the PET detector ring and electronics within the MR system has been a technologically challenging design to develop but provides capacity for simultaneous imaging and the potential for new diagnostic and research capability. This article reviews state-of-the-art MR-PET hardware and software, and discusses future developments focusing on neuroimaging methodologies for MR-PET scanning. We particularly focus on the methodologies that lead to an improved synergy between MRI and PET, including optimal data acquisition, PET attenuation and motion correction, and joint image reconstruction and processing methods based on the underlying complementary and mutual information. We further review the current and potential future applications of simultaneous MR-PET in both systems neuroscience and clinical neuroimaging research. We demonstrate a simultaneous data acquisition protocol to highlight new applications of MR-PET neuroimaging research studies.
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Affiliation(s)
- Zhaolin Chen
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.,Department of Electrical and Computer Systems Engineering, Monash University, Clayton, Victoria, Australia
| | - Sharna D Jamadar
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.,Monash Institute of Cognitive and Clinical Neuroscience, Monash University, Clayton, Victoria, Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
| | - Shenpeng Li
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.,Department of Electrical and Computer Systems Engineering, Monash University, Clayton, Victoria, Australia
| | | | - Jakub Baran
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.,Department of Biophysics, Faculty of Mathematics and Natural Sciences, University of Rzeszów, Rzeszów, Poland
| | - Nicholas Ferris
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.,Monash Imaging, Monash Health, Clayton, Victoria, Australia
| | - Nadim Jon Shah
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.,Institute of Neuroscience and Medicine 4, INM-4, Forschungszentrum, Jülich, Germany
| | - Gary F Egan
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.,Monash Institute of Cognitive and Clinical Neuroscience, Monash University, Clayton, Victoria, Australia.,Australian Research Council Centre of Excellence for Integrative Brain Function, Monash University, Clayton, Victoria, Australia
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18
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Musafargani S, Ghosh KK, Mishra S, Mahalakshmi P, Padmanabhan P, Gulyás B. PET/MRI: a frontier in era of complementary hybrid imaging. Eur J Hybrid Imaging 2018; 2:12. [PMID: 29998214 PMCID: PMC6015803 DOI: 10.1186/s41824-018-0030-6] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2017] [Accepted: 03/14/2018] [Indexed: 12/19/2022] Open
Abstract
With primitive approaches, the diagnosis and therapy were operated at the cellular, molecular, or even at the genetic level. As the diagnostic techniques are more concentrated towards molecular level, multi modal imaging becomes specifically essential. Multi-modal imaging has extensive applications in clinical as well as in pre-clinical studies. Positron Emission Tomography (PET) has flourished in the field of nuclear medicine, which has motivated it to fuse with Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) for PET/CT and PET/MRI respectively. However, the challenges in PET/CT are due to the inability of simultaneous acquisition and reduced soft tissue contrast, which has led to the development of PET/MRI. Also, MRI offers the better soft tissue contrast over CT. Hence, fusion of PET and MRI results in combining structural information with functional image from PET. Yet, it has many technical challenges due to the interference between the modalities. Also, it must be resolved with various approaches for addressing the shortcomings of each system and improvise on the image quantification system. This review elaborates on the various challenges in the present PET/MRI system and the future directions of the hybrid modality. Also, the different data acquisition and analysis techniques of PET/MRI system are discussed with enhanced details on the software tools.
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Affiliation(s)
- Sikkandhar Musafargani
- Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921 Singapore
| | - Krishna Kanta Ghosh
- Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921 Singapore
| | - Sachin Mishra
- Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921 Singapore
| | | | - Parasuraman Padmanabhan
- Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921 Singapore
| | - Balázs Gulyás
- Lee Kong Chian School of Medicine, Nanyang Technological University, 59 Nanyang Drive, Singapore, 636921 Singapore
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19
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Del Guerra A, Ahmad S, Avram M, Belcari N, Berneking A, Biagi L, Bisogni MG, Brandl F, Cabello J, Camarlinghi N, Cerello P, Choi CH, Coli S, Colpo S, Fleury J, Gagliardi V, Giraudo G, Heekeren K, Kawohl W, Kostou T, Lefaucheur JL, Lerche C, Loudos G, Morrocchi M, Muller J, Mustafa M, Neuner I, Papadimitroulas P, Pennazio F, Rajkumar R, Brambilla CR, Rivoire J, Kops ER, Scheins J, Schimpf R, Shah NJ, Sorg C, Sportelli G, Tosetti M, Trinchero R, Wyss C, Ziegler S. TRIMAGE: A dedicated trimodality (PET/MR/EEG) imaging tool for schizophrenia. Eur Psychiatry 2018; 50:7-20. [PMID: 29358016 DOI: 10.1016/j.eurpsy.2017.11.007] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Revised: 11/15/2017] [Accepted: 11/16/2017] [Indexed: 02/02/2023] Open
Abstract
Simultaneous PET/MR/EEG (Positron Emission Tomography - Magnetic Resonance - Electroencephalography), a new tool for the investigation of neuronal networks in the human brain, is presented here within the framework of the European Union Project TRIMAGE. The trimodal, cost-effective PET/MR/EEG imaging tool makes use of cutting edge technology both in PET and in MR fields. A novel type of magnet (1.5T, non-cryogenic) has been built together with a PET scanner that makes use of the most advanced photodetectors (i.e., SiPM matrices), scintillators matrices (LYSO) and digital electronics. The combined PET/MR/EEG system is dedicated to brain imaging and has an inner diameter of 260 mm and an axial Field-of-View of 160 mm. It enables the acquisition and assessment of molecular metabolic information with high spatial and temporal resolution in a given brain simultaneously. The dopaminergic system and the glutamatergic system in schizophrenic patients are investigated via PET, the same physiological/pathophysiological conditions with regard to functional connectivity, via fMRI, and its electrophysiological signature via EEG. In addition to basic neuroscience questions addressing neurovascular-metabolic coupling, this new methodology lays the foundation for individual physiological and pathological fingerprints for a wide research field addressing healthy aging, gender effects, plasticity and different psychiatric and neurological diseases. The preliminary performances of two components of the imaging tool (PET and MR) are discussed. Initial results of the search of possible candidates for suitable schizophrenia biomarkers are also presented as obtained with PET/MR systems available to the collaboration.
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Affiliation(s)
- Alberto Del Guerra
- Dipartimento di Fisica "E. Fermi", Università di Pisa, Italy; INFN, Sezione di Pisa, Pisa, Italy.
| | | | - Mihai Avram
- Nuklearmedinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany; Department of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany; Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Nicola Belcari
- Dipartimento di Fisica "E. Fermi", Università di Pisa, Italy; INFN, Sezione di Pisa, Pisa, Italy
| | - Arne Berneking
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, INM4, Jülich, Germany
| | - Laura Biagi
- IRCSS, Stella Maris, Calambrone, Pisa, Italy
| | - Maria Giuseppina Bisogni
- Dipartimento di Fisica "E. Fermi", Università di Pisa, Italy; INFN, Sezione di Pisa, Pisa, Italy
| | - Felix Brandl
- Department of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany; Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Jorge Cabello
- Nuklearmedinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Niccolò Camarlinghi
- Dipartimento di Fisica "E. Fermi", Università di Pisa, Italy; INFN, Sezione di Pisa, Pisa, Italy
| | | | - Chang-Hoon Choi
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, INM4, Jülich, Germany
| | - Silvia Coli
- Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Torino, Italy
| | | | | | - Vito Gagliardi
- Dipartimento di Fisica "E. Fermi", Università di Pisa, Italy; INFN, Sezione di Pisa, Pisa, Italy
| | - Giuseppe Giraudo
- Istituto Nazionale di Fisica Nucleare, Sezione di Torino, Torino, Italy
| | - Karsten Heekeren
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry Zurich, University of Zurich, Switzerland
| | - Wolfram Kawohl
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry Zurich, University of Zurich, Switzerland; Department of Psychiatry and Psychotherapy, Psychiatric Services of Aargovia, Switzerland
| | | | | | - Christoph Lerche
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, INM4, Jülich, Germany
| | - George Loudos
- Technological Educational Institute of Athens, Greece
| | - Matteo Morrocchi
- Dipartimento di Fisica "E. Fermi", Università di Pisa, Italy; INFN, Sezione di Pisa, Pisa, Italy
| | | | - Mona Mustafa
- Nuklearmedinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Irene Neuner
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, INM4, Jülich, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University, JARA Brain, Aachen, Germany
| | | | | | - Ravichandran Rajkumar
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, INM4, Jülich, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, Faculty of Medicine, RWTH Aachen University, JARA Brain, Aachen, Germany
| | - Cláudia Régio Brambilla
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, INM4, Jülich, Germany
| | | | - Elena Rota Kops
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, INM4, Jülich, Germany
| | - Jürgen Scheins
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, INM4, Jülich, Germany
| | | | - N Jon Shah
- Forschungszentrum Jülich GmbH, Institute of Neuroscience and Medicine, INM4, Jülich, Germany
| | - Christian Sorg
- Department of Neuroradiology, Klinikum rechts der Isar, Technische Universität München, Munich, Germany; Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Munich, Germany; Department of Psychiatry, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Giancarlo Sportelli
- Dipartimento di Fisica "E. Fermi", Università di Pisa, Italy; INFN, Sezione di Pisa, Pisa, Italy
| | | | | | - Christine Wyss
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry Zurich, University of Zurich, Switzerland
| | - Sibylle Ziegler
- Nuklearmedinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany; Department of Nuclear Medicine, University Hospital, LMU, Munich, Germany
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20
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Lebon V, Jan S, Fontyn Y, Tiret B, Pottier G, Jaumain E, Valette J. Using 31P-MRI of hydroxyapatite for bone attenuation correction in PET-MRI: proof of concept in the rodent brain. EJNMMI Phys 2017; 4:16. [PMID: 28466279 PMCID: PMC5413461 DOI: 10.1186/s40658-017-0183-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 04/20/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The correction of γ-photon attenuation in PET-MRI remains a critical issue, especially for bone attenuation. This problem is of great importance for brain studies due to the density of the skull. Current techniques for skull attenuation correction (AC) provide indirect estimates of cortical bone density, leading to inaccurate estimates of brain activity. The purpose of this study was to develop an alternate method for bone attenuation correction based on NMR. The proposed approach relies on the detection of hydroxyapatite crystals by zero echo time (ZTE) MRI of 31P, providing individual and quantitative assessment of bone density. This work presents a proof of concept of this approach. The first step of the method is a calibration experiment to determine the conversion relationship between the 31P signal and the linear attenuation coefficient μ. Then 31P-ZTE was performed in vivo in rodent to estimate the μ-map of the skull. 18F-FDG PET data were acquired in the same animal and reconstructed with three different AC methods: 31P-based AC, AC neglecting the bone and the gold standard, CT-based AC, used to comparison for the other two methods. RESULTS The calibration experiment provided a conversion factor of 31P signal into μ. In vivo 31P-ZTE made it possible to acquire 3D images of the rat skull. Brain PET images showed underestimation of 18F activity in peripheral regions close to the skull when AC neglected the bone (as compared with CT-based AC). The use of 31P-derived μ-map for AC leads to increased peripheral activity, and therefore a global overestimation of brain 18F activity. CONCLUSIONS In vivo 31P-ZTE MRI of hydroxyapatite provides μ-map of the skull, which can be used for attenuation correction of 18F-FDG PET images. This study is limited by several intrinsic biases associated with the size of the rat brain, which are unlikely to affect human data on a clinical PET-MRI system.
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Affiliation(s)
- Vincent Lebon
- Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut d'Imagerie Biomedicale (I2BM), MIRCen, Fontenay-aux-Roses, France.
- Centre National de la Recherche Scientifique (CNRS), Neurodegenerative Diseases Laboratory, Université Paris-Sud, Université Paris-Saclay, UMR 9199, Fontenay-aux-Roses, France.
| | - Sébastien Jan
- Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut d'Imagerie Biomedicale (I2BM), SHFJ, Orsay, France
- Inserm/CEA/Université Paris Sud, Université Paris-Saclay, UMR 1023-CNRS ERL 9218, IMIV, Orsay, France
| | - Yoann Fontyn
- Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut d'Imagerie Biomedicale (I2BM), SHFJ, Orsay, France
- Inserm/CEA/Université Paris Sud, Université Paris-Saclay, UMR 1023-CNRS ERL 9218, IMIV, Orsay, France
| | - Brice Tiret
- Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut d'Imagerie Biomedicale (I2BM), MIRCen, Fontenay-aux-Roses, France
- Centre National de la Recherche Scientifique (CNRS), Neurodegenerative Diseases Laboratory, Université Paris-Sud, Université Paris-Saclay, UMR 9199, Fontenay-aux-Roses, France
| | - Géraldine Pottier
- Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut d'Imagerie Biomedicale (I2BM), SHFJ, Orsay, France
- Inserm/CEA/Université Paris Sud, Université Paris-Saclay, UMR 1023-CNRS ERL 9218, IMIV, Orsay, France
| | - Emilie Jaumain
- Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut d'Imagerie Biomedicale (I2BM), SHFJ, Orsay, France
- Inserm/CEA/Université Paris Sud, Université Paris-Saclay, UMR 1023-CNRS ERL 9218, IMIV, Orsay, France
| | - Julien Valette
- Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Direction de la Recherche Fondamentale (DRF), Institut d'Imagerie Biomedicale (I2BM), MIRCen, Fontenay-aux-Roses, France
- Centre National de la Recherche Scientifique (CNRS), Neurodegenerative Diseases Laboratory, Université Paris-Sud, Université Paris-Saclay, UMR 9199, Fontenay-aux-Roses, France
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Savio AM, Schutte M, Graña M, Yakushev I. Pypes: Workflows for Processing Multimodal Neuroimaging Data. Front Neuroinform 2017; 11:25. [PMID: 28443013 PMCID: PMC5387693 DOI: 10.3389/fninf.2017.00025] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2017] [Accepted: 03/17/2017] [Indexed: 11/13/2022] Open
Affiliation(s)
- Alexandre M. Savio
- Department of Nuclear Medicine, Klinikum Rechts der Isar, Technische Universität MünchenMunich, Germany
- Asociación Python San Sebastián (ACPySS)San Sebastián, Spain
| | - Michael Schutte
- Department of Nuclear Medicine, Klinikum Rechts der Isar, Technische Universität MünchenMunich, Germany
| | - Manuel Graña
- Asociación Python San Sebastián (ACPySS)San Sebastián, Spain
- Computational Intelligence Group, University of the Basque Country (UPV/EHU)San Sebastián, Spain
| | - Igor Yakushev
- Department of Nuclear Medicine, Klinikum Rechts der Isar, Technische Universität MünchenMunich, Germany
- Neuroimaging Center at Technische Universität München (TUM-NIC), Technische Universität MünchenMunich, Germany
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22
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Del Sole A, Malaspina S, Magenta Biasina A. Magnetic resonance imaging and positron emission tomography in the diagnosis of neurodegenerative dementias. FUNCTIONAL NEUROLOGY 2017; 31:205-215. [PMID: 28072381 DOI: 10.11138/fneur/2016.31.4.205] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Neuroimaging, both with magnetic resonance imaging (MRI) and positron emission tomography (PET), has gained a pivotal role in the diagnosis of primary neurodegenerative diseases. These two techniques are used as biomarkers of both pathology and progression of Alzheimer's disease (AD) and to differentiate AD from other neurodegenerative diseases. MRI is able to identify structural changes including patterns of atrophy characterizing neurodegenerative diseases, and to distinguish these from other causes of cognitive impairment, e.g. infarcts, space-occupying lesions and hydrocephalus. PET is widely used to identify regional patterns of glucose utilization, since distinct patterns of distribution of cerebral glucose metabolism are related to different subtypes of neurodegenerative dementia. The use of PET in mild cognitive impairment, though controversial, is deemed helpful for predicting conversion to dementia and the dementia clinical subtype. Recently, new radiopharmaceuticals for the in vivo imaging of amyloid burden have been licensed and more tracers are being developed for the assessment of tauopathies and inflammatory processes, which may underlie the onset of the amyloid cascade. At present, the cerebral amyloid burden, imaged with PET, may help to exclude the presence of AD as well as forecast its possible onset. Finally PET imaging may be particularly useful in ongoing clinical trials for the development of dementia treatments. In the near future, the use of the above methods, in accordance with specific guidelines, along with the use of effective treatments will likely lead to more timely and successful treatment of neurodegenerative dementias.
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