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Veit-Haibach P, Ahlström H, Boellaard R, Delgado Bolton RC, Hesse S, Hope T, Huellner MW, Iagaru A, Johnson GB, Kjaer A, Law I, Metser U, Quick HH, Sattler B, Umutlu L, Zaharchuk G, Herrmann K. International EANM-SNMMI-ISMRM consensus recommendation for PET/MRI in oncology. Eur J Nucl Med Mol Imaging 2023; 50:3513-3537. [PMID: 37624384 PMCID: PMC10547645 DOI: 10.1007/s00259-023-06406-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 08/16/2023] [Indexed: 08/26/2023]
Abstract
PREAMBLE The Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote the science, technology, and practical application of nuclear medicine. The European Association of Nuclear Medicine (EANM) is a professional non-profit medical association that facilitates communication worldwide between individuals pursuing clinical and research excellence in nuclear medicine. The EANM was founded in 1985. The merged International Society for Magnetic Resonance in Medicine (ISMRM) is an international, nonprofit, scientific association whose purpose is to promote communication, research, development, and applications in the field of magnetic resonance in medicine and biology and other related topics and to develop and provide channels and facilities for continuing education in the field.The ISMRM was founded in 1994 through the merger of the Society of Magnetic Resonance in Medicine and the Society of Magnetic Resonance Imaging. SNMMI, ISMRM, and EANM members are physicians, technologists, and scientists specializing in the research and practice of nuclear medicine and/or magnetic resonance imaging. The SNMMI, ISMRM, and EANM will periodically define new guidelines for nuclear medicine practice to help advance the science of nuclear medicine and/or magnetic resonance imaging and to improve the quality of service to patients throughout the world. Existing practice guidelines will be reviewed for revision or renewal, as appropriate, on their fifth anniversary or sooner, if indicated. Each practice guideline, representing a policy statement by the SNMMI/EANM/ISMRM, has undergone a thorough consensus process in which it has been subjected to extensive review. The SNMMI, ISMRM, and EANM recognize that the safe and effective use of diagnostic nuclear medicine imaging and magnetic resonance imaging requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guideline by those entities not providing these services is not authorized. These guidelines are an educational tool designed to assist practitioners in providing appropriate care for patients. They are not inflexible rules or requirements of practice and are not intended, nor should they be used, to establish a legal standard of care. For these reasons and those set forth below, the SNMMI, the ISMRM, and the EANM caution against the use of these guidelines in litigation in which the clinical decisions of a practitioner are called into question. The ultimate judgment regarding the propriety of any specific procedure or course of action must be made by the physician or medical physicist in light of all the circumstances presented. Thus, there is no implication that an approach differing from the guidelines, standing alone, is below the standard of care. To the contrary, a conscientious practitioner may responsibly adopt a course of action different from that set forth in the guidelines when, in the reasonable judgment of the practitioner, such course of action is indicated by the condition of the patient, limitations of available resources, or advances in knowledge or technology subsequent to publication of the guidelines. The practice of medicine includes both the art and the science of the prevention, diagnosis, alleviation, and treatment of disease. The variety and complexity of human conditions make it impossible to always reach the most appropriate diagnosis or to predict with certainty a particular response to treatment. Therefore, it should be recognized that adherence to these guidelines will not ensure an accurate diagnosis or a successful outcome. All that should be expected is that the practitioner will follow a reasonable course of action based on current knowledge, available resources, and the needs of the patient to deliver effective and safe medical care. The sole purpose of these guidelines is to assist practitioners in achieving this objective.
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Affiliation(s)
- Patrick Veit-Haibach
- Joint Department Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, Toronto General Hospital, 1 PMB-275, 585 University Avenue, Toronto, Ontario, M5G 2N2, Canada
- Joint Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Håkan Ahlström
- Department of Surgical Sciences, Uppsala University, 751 85, Uppsala, Sweden
- Antaros Medical AB, BioVenture Hub, 431 53, Mölndal, Sweden
| | - Ronald Boellaard
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Roberto C Delgado Bolton
- Department of Diagnostic Imaging (Radiology) and Nuclear Medicine, University Hospital San Pedro and Centre for Biomedical Research of La Rioja (CIBIR), Logroño, La Rioja, Spain
| | - Swen Hesse
- Department of Nuclear Medicine, University of Leipzig Medical Center, Leipzig, Germany
| | - Thomas Hope
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Martin W Huellner
- Department of Nuclear Medicine, University Hospital Zürich, University of Zürich, Rämistrasse 100, 8091, Zurich, Switzerland
| | - Andrei Iagaru
- Department of Radiology, Division of Nuclear Medicine, Stanford University Medical Center, Stanford, CA, USA
| | - Geoffrey B Johnson
- Division of Nuclear Medicine, Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Andreas Kjaer
- Department of Clinical Physiology, Nuclear Medicine & PET and Cluster for Molecular Imaging, Rigshospitalet and University of Copenhagen, Copenhagen, Denmark
| | - Ian Law
- Department of Clinical Physiology, Nuclear Medicine & PET, Rigshospitalet, Copenhagen, Denmark
| | - Ur Metser
- Joint Department of Medical Imaging, University Health Network, Mount Sinai Hospital and Women's College Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Harald H Quick
- High-Field and Hybrid MR Imaging, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
- Erwin L. Hahn Institute for MR Imaging, University of Duisburg-Essen, Essen, Germany
| | - Bernhard Sattler
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany
| | - Lale Umutlu
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
| | - Greg Zaharchuk
- Division of Neuroradiology, Department of Radiology, Stanford University, 300 Pasteur Drive, Room S047, Stanford, CA, 94305-5105, USA
| | - Ken Herrmann
- Department of Nuclear Medicine, University of Duisburg-Essen and German Cancer Consortium (DKTK), University Hospital Essen, Essen, Germany.
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Ahangari S, Beck Olin A, Kinggård Federspiel M, Jakoby B, Andersen TL, Hansen AE, Fischer BM, Littrup Andersen F. A deep learning-based whole-body solution for PET/MRI attenuation correction. EJNMMI Phys 2022; 9:55. [PMID: 35978211 PMCID: PMC9385907 DOI: 10.1186/s40658-022-00486-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 08/08/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Deep convolutional neural networks have demonstrated robust and reliable PET attenuation correction (AC) as an alternative to conventional AC methods in integrated PET/MRI systems. However, its whole-body implementation is still challenging due to anatomical variations and the limited MRI field of view. The aim of this study is to investigate a deep learning (DL) method to generate voxel-based synthetic CT (sCT) from Dixon MRI and use it as a whole-body solution for PET AC in a PET/MRI system. MATERIALS AND METHODS Fifteen patients underwent PET/CT followed by PET/MRI with whole-body coverage from skull to feet. We performed MRI truncation correction and employed co-registered MRI and CT images for training and leave-one-out cross-validation. The network was pretrained with region-specific images. The accuracy of the AC maps and reconstructed PET images were assessed by performing a voxel-wise analysis and calculating the quantification error in SUV obtained using DL-based sCT (PETsCT) and a vendor-provided atlas-based method (PETAtlas), with the CT-based reconstruction (PETCT) serving as the reference. In addition, region-specific analysis was performed to compare the performances of the methods in brain, lung, liver, spine, pelvic bone, and aorta. RESULTS Our DL-based method resulted in better estimates of AC maps with a mean absolute error of 62 HU, compared to 109 HU for the atlas-based method. We found an excellent voxel-by-voxel correlation between PETCT and PETsCT (R2 = 0.98). The absolute percentage difference in PET quantification for the entire image was 6.1% for PETsCT and 11.2% for PETAtlas. The regional analysis showed that the average errors and the variability for PETsCT were lower than PETAtlas in all regions. The largest errors were observed in the lung, while the smallest biases were observed in the brain and liver. CONCLUSIONS Experimental results demonstrated that a DL approach for whole-body PET AC in PET/MRI is feasible and allows for more accurate results compared with conventional methods. Further evaluation using a larger training cohort is required for more accurate and robust performance.
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Affiliation(s)
- Sahar Ahangari
- Department of Clinical Physiology, Nuclear Medicine, and PET, Rigshospitalet, Copenhagen, Denmark.
| | - Anders Beck Olin
- Department of Clinical Physiology, Nuclear Medicine, and PET, Rigshospitalet, Copenhagen, Denmark
| | | | | | - Thomas Lund Andersen
- Department of Clinical Physiology, Nuclear Medicine, and PET, Rigshospitalet, Copenhagen, Denmark
| | - Adam Espe Hansen
- Department of Clinical Physiology, Nuclear Medicine, and PET, Rigshospitalet, Copenhagen, Denmark.,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.,Department of Diagnostic Radiology, Rigshospitalet, Copenhagen, Denmark
| | - Barbara Malene Fischer
- Department of Clinical Physiology, Nuclear Medicine, and PET, Rigshospitalet, Copenhagen, Denmark.,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Flemming Littrup Andersen
- Department of Clinical Physiology, Nuclear Medicine, and PET, Rigshospitalet, Copenhagen, Denmark.,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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Grafe H, Lindemann ME, Weber M, Kirchner J, Binse I, Umutlu L, Herrmann K, Quick HH. Intra-Individual Comparison of 124I-PET/CT and 124I-PET/MR Hybrid Imaging of Patients with Resected Differentiated Thyroid Carcinoma: Aspects of Attenuation Correction. Cancers (Basel) 2022; 14:cancers14133040. [PMID: 35804811 PMCID: PMC9264885 DOI: 10.3390/cancers14133040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 06/03/2022] [Accepted: 06/15/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary This study evaluates the qualitative and quantitative differences between 124-iodine PET/CT and PET/MR in oncologic patients with differentiated thyroid carcinoma after thyroidectomy. The impact of improved MR-based attenuation correction (AC) using a bone atlas was analysed in PET/MR data. Despite different patient positioning and AC methods PET/CT and PET/MR provide overall comparable results in a clinical setting. The overall number of detected 124I-active lesions and the measured average SUVmean values for congruent lesions were higher for PET/MR when compared to PET/CT. The addition of bone to the MR-based AC in PET/MR slightly increased the SUVmean values for all detected lesions. Abstract Background: This study evaluates the quantitative differences between 124-iodine (I) positron emission tomography/computed tomography (PET/CT) and PET/magnetic resonance imaging (PET/MR) in patients with resected differentiated thyroid carcinoma (DTC). Methods: N = 43 124I PET/CT and PET/MR exams were included. CT-based attenuation correction (AC) in PET/CT and MR-based AC in PET/MR with bone atlas were compared concerning bone AC in the head-neck region. AC-map artifacts (e.g., dentures) were noted. Standardized uptake values (SUV) were measured in lesions in each PET data reconstruction. Relative differences in SUVmean were calculated between PET/CT and PET/MR with bone atlas. Results: Overall, n = 111 124I-avid lesions were detected in all PET/CT, while n = 132 lesions were detected in PET/MR. The median in SUVmean for n = 98 congruent lesions measured in PET/CT was 12.3. In PET/MR, the median in SUVmean was 16.6 with bone in MR-based AC. Conclusions: 124I-PET/CT and 124I-PET/MR hybrid imaging of patients with DTC after thyroidectomy provides overall comparable quantitative results in a clinical setting despite different patient positioning and AC methods. The overall number of detected 124I-avid lesions was higher for PET/MR compared to PET/CT. The measured average SUVmean values for congruent lesions were higher for PET/MR.
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Affiliation(s)
- Hong Grafe
- Department of Nuclear Medicine, University Hospital Essen, University Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany; (M.W.); (I.B.); (K.H.)
- Correspondence: ; Tel.: +49-201-723-2033
| | - Maike E. Lindemann
- High-Field and Hybrid MR Imaging, University Hospital Essen, University Duisburg-Essen, 45147 Essen, Germany; (M.E.L.); (H.H.Q.)
| | - Manuel Weber
- Department of Nuclear Medicine, University Hospital Essen, University Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany; (M.W.); (I.B.); (K.H.)
| | - Julian Kirchner
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University Hospital Dusseldorf, 40225 Dusseldorf, Germany;
| | - Ina Binse
- Department of Nuclear Medicine, University Hospital Essen, University Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany; (M.W.); (I.B.); (K.H.)
| | - Lale Umutlu
- Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, University Duisburg-Essen, 45147 Essen, Germany;
| | - Ken Herrmann
- Department of Nuclear Medicine, University Hospital Essen, University Duisburg-Essen, Hufelandstr. 55, 45147 Essen, Germany; (M.W.); (I.B.); (K.H.)
| | - Harald H. Quick
- High-Field and Hybrid MR Imaging, University Hospital Essen, University Duisburg-Essen, 45147 Essen, Germany; (M.E.L.); (H.H.Q.)
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, 45141 Essen, Germany
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Lindemann ME, Gratz M, Blumhagen JO, Jakoby B, Quick HH. MR-based truncation correction using an advanced HUGE method to improve attenuation correction in PET/MR imaging of obese patients. Med Phys 2022; 49:865-877. [PMID: 35014697 DOI: 10.1002/mp.15446] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 12/08/2021] [Accepted: 12/18/2021] [Indexed: 10/19/2022] Open
Abstract
PURPOSE Truncation artifacts in the periphery of the magnetic resonance (MR) field-of-view (FOV) and thus, in the MR-based attenuation correction (AC) map, may hamper accurate positron emission tomography (PET) quantification in whole-body PET/MR, which is especially problematic in patients with obesity with overall large body dimensions. Therefore, an advanced truncation correction (TC) method to extend the conventional MR FOV is needed. METHODS The extent of MR-based AC-map truncations in obese patients was determined in a data set including n = 10 patients that underwent whole-body PET/MR exams. Patient inclusion criteria were defined as BMI > 30 kg/m2 and body weight > 100 kg. Truncations in PET/MR patients with obesity were quantified comparing the MR-based AC-map volume to segmented non-AC PET data, serving as the reference body volume without truncations to demonstrate the need of improved TC. The new method implemented in this study, termed "advanced HUGE", was modified and extended from the original HUGE method by Blumhagen et al. in order to provide improved TC across the entire axial MR FOV and to unlock new clinical applications of PET/MR. Advanced HUGE was then systematically tested in PET/MR NEMA phantom measurements. Relative differences between computed tomography (CT) AC PET data of the phantom setup (reference) and MR-based Dixon AC, respectively Dixon + advanced HUGE AC, were calculated. The applicability of the method for advanced TC was then demonstrated in first MR-based measurements in healthy volunteers. RESULTS It was found that the MR-based AC maps of obese patients often reveal truncations in anterior-posterior direction. Especially the abdominal region could benefit from improved TC, where maximal relative differences in the AC-map volume up to -17 % were calculated. Applying advanced HUGE to improve the MR-based AC in PET/MR, PET quantification errors in the large-volume phantom setup could be considerably reduced from average -18.6 % (Dixon AC) to 4.6 % compared to the CT AC reference. Volunteer measurements demonstrate that formerly missing AC-map volume in the Dixon-VIBE AC-map could be added due to advanced HUGE in anterior-posterior direction and thus, potentially improves AC in PET/MR. CONCLUSIONS The advanced HUGE method for truncation correction considerably reduces truncations in anterior-posterior direction demonstrated in phantom measurements and healthy volunteers and thus, further improves MR-based AC in PET/MR imaging. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Maike E Lindemann
- High-Field and Hybrid MR Imaging, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Marcel Gratz
- High-Field and Hybrid MR Imaging, University Hospital Essen, University Duisburg-Essen, Essen, Germany.,Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany
| | | | | | - Harald H Quick
- High-Field and Hybrid MR Imaging, University Hospital Essen, University Duisburg-Essen, Essen, Germany.,Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany
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Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study. Diagnostics (Basel) 2021; 11:diagnostics11020319. [PMID: 33669416 PMCID: PMC7920458 DOI: 10.3390/diagnostics11020319] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 02/09/2021] [Accepted: 02/15/2021] [Indexed: 11/30/2022] Open
Abstract
Recently, the total variation (TV) algorithm has been used for noise reduction distribution in degraded nuclear medicine images. To acquire positron emission tomography (PET) to correct the attenuation region in the PET/magnetic resonance (MR) system, the MR Dixon pulse sequence, which is based on controlled aliasing in parallel imaging, results from higher acceleration (CAIPI; MR-ACDixon-CAIPI) and generalized autocalibrating partially parallel acquisition (GRAPPA; MR-ACDixon-GRAPPA) algorithms are used. Therefore, this study aimed to evaluate the image performance of the TV noise reduction algorithm for PET/MR images using the Jaszczak phantom by injecting 18F radioisotopes with PET/MR, which is called mMR (Siemens, Germany), compared with conventional noise-reduction techniques such as Wiener and median filters. The contrast-to-noise (CNR) and coefficient of variation (COV) were used for quantitative analysis. Based on the results, PET images with the TV algorithm were improved by approximately 7.6% for CNR and decreased by approximately 20.0% for COV compared with conventional noise-reduction techniques. In particular, the image quality for the MR-ACDixon-CAIPI PET image was better than that of the MR-ACDixon-GRAPPA PET image. In conclusion, the TV noise-reduction algorithm is efficient for improving the PET image quality in PET/MR systems.
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