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Zatcepin A, Kopczak A, Holzgreve A, Hein S, Schindler A, Duering M, Kaiser L, Lindner S, Schidlowski M, Bartenstein P, Albert N, Brendel M, Ziegler SI. Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients. Z Med Phys 2024; 34:218-230. [PMID: 36682921 PMCID: PMC11156782 DOI: 10.1016/j.zemedi.2022.11.008] [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: 08/03/2022] [Revised: 11/18/2022] [Accepted: 11/19/2022] [Indexed: 01/21/2023]
Abstract
INTRODUCTION Neuroinflammation evaluation after acute ischemic stroke is a promising option for selecting an appropriate post-stroke treatment strategy. To assess neuroinflammation in vivo, translocator protein PET (TSPO PET) can be used. However, the gold standard TSPO PET quantification method includes a 90 min scan and continuous arterial blood sampling, which is challenging to perform on a routine basis. In this work, we determine what information is required for a simplified quantification approach using a machine learning algorithm. MATERIALS AND METHODS We analyzed data from 18 patients with ischemic stroke who received 0-90 min [18F]GE-180 PET as well as T1-weigted (T1w), FLAIR, and arterial spin labeling (ASL) MRI scans. During PET scans, five manual venous blood samples at 5, 15, 30, 60, and 85 min post injection (p.i.) were drawn, and plasma activity concentration was measured. Total distribution volume (VT) was calculated using Logan plot with the full dynamic PET and an image-derived input function (IDIF) from the carotid arteries. IDIF was scaled by a calibration factor derived from all the measured plasma activity concentrations. The calculated VT values were used for training a random forest regressor. As input features for the model, we used three late PET frames (60-70, 70-80, and 80-90 min p.i.), the ASL image reflecting perfusion, the voxel coordinates, the lesion mask, and the five plasma activity concentrations. The algorithm was validated with the leave-one-out approach. To estimate the impact of the individual features on the algorithm's performance, we used Shapley Additive Explanations (SHAP). Having determined that the three late PET frames and the plasma activity concentrations were the most important features, we tested a simplified quantification approach consisting of dividing a late PET frame by a plasma activity concentration. All the combinations of frames/samples were compared by means of concordance correlation coefficient and Bland-Altman plots. RESULTS When using all the input features, the algorithm predicted VT values with high accuracy (87.8 ± 8.3%) for both lesion and non-lesion voxels. The SHAP values demonstrated high impact of the late PET frames (60-70, 70-80, and 80-90 min p.i.) and plasma activity concentrations on the VT prediction, while the influence of the ASL-derived perfusion, voxel coordinates, and the lesion mask was low. Among all the combinations of the late PET frames and plasma activity concentrations, the 70-80 min p.i. frame divided by the 30 min p.i. plasma sample produced the closest VT estimate in the ischemic lesion. CONCLUSION Reliable TSPO PET quantification is achievable by using a single late PET frame divided by a late blood sample activity concentration.
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Affiliation(s)
- Artem Zatcepin
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.
| | - Anna Kopczak
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Adrien Holzgreve
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Sandra Hein
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Andreas Schindler
- Department of Neuroradiology, University Hospital, LMU Munich, Munich, Germany
| | - Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany; Medical Image Analysis Center (MIAC) & Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Lena Kaiser
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Simon Lindner
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Martin Schidlowski
- Department of Epileptology, University Hospital Bonn, Bonn, Germany; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Peter Bartenstein
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Nathalie Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Sibylle I Ziegler
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
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NiftyPAD - Novel Python Package for Quantitative Analysis of Dynamic PET Data. Neuroinformatics 2023; 21:457-468. [PMID: 36622500 PMCID: PMC10085912 DOI: 10.1007/s12021-022-09616-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/30/2022] [Indexed: 01/10/2023]
Abstract
Current PET datasets are becoming larger, thereby increasing the demand for fast and reproducible processing pipelines. This paper presents a freely available, open source, Python-based software package called NiftyPAD, for versatile analyses of static, full or dual-time window dynamic brain PET data. The key novelties of NiftyPAD are the analyses of dual-time window scans with reference input processing, pharmacokinetic modelling with shortened PET acquisitions through the incorporation of arterial spin labelling (ASL)-derived relative perfusion measures, as well as optional PET data-based motion correction. Results obtained with NiftyPAD were compared with the well-established software packages PPET and QModeling for a range of kinetic models. Clinical data from eight subjects scanned with four different amyloid tracers were used to validate the computational performance. NiftyPAD achieved [Formula: see text] correlation with PPET, with absolute difference [Formula: see text] for linearised Logan and MRTM2 methods, and [Formula: see text] correlation with QModeling, with absolute difference [Formula: see text] for basis function based SRTM and SRTM2 models. For the recently published SRTM ASL method, which is unavailable in existing software packages, high correlations with negligible bias were observed with the full scan SRTM in terms of non-displaceable binding potential ([Formula: see text]), indicating reliable model implementation in NiftyPAD. Together, these findings illustrate that NiftyPAD is versatile, flexible, and produces comparable results with established software packages for quantification of dynamic PET data. It is freely available ( https://github.com/AMYPAD/NiftyPAD ), and allows for multi-platform usage. The modular setup makes adding new functionalities easy, and the package is lightweight with minimal dependencies, making it easy to use and integrate into existing processing pipelines.
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Tjoa E, Guan C. A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2021; 32:4793-4813. [PMID: 33079674 DOI: 10.1109/tnnls.2020.3027314] [Citation(s) in RCA: 328] [Impact Index Per Article: 109.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Recently, artificial intelligence and machine learning in general have demonstrated remarkable performances in many tasks, from image processing to natural language processing, especially with the advent of deep learning (DL). Along with research progress, they have encroached upon many different fields and disciplines. Some of them require high level of accountability and thus transparency, for example, the medical sector. Explanations for machine decisions and predictions are thus needed to justify their reliability. This requires greater interpretability, which often means we need to understand the mechanism underlying the algorithms. Unfortunately, the blackbox nature of the DL is still unresolved, and many machine decisions are still poorly understood. We provide a review on interpretabilities suggested by different research works and categorize them. The different categories show different dimensions in interpretability research, from approaches that provide "obviously" interpretable information to the studies of complex patterns. By applying the same categorization to interpretability in medical research, it is hoped that: 1) clinicians and practitioners can subsequently approach these methods with caution; 2) insight into interpretability will be born with more considerations for medical practices; and 3) initiatives to push forward data-based, mathematically grounded, and technically grounded medical education are encouraged.
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Tournier N, Comtat C, Lebon V, Gennisson JL. Challenges and Perspectives of the Hybridization of PET with Functional MRI or Ultrasound for Neuroimaging. Neuroscience 2021; 474:80-93. [DOI: 10.1016/j.neuroscience.2020.10.015] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Revised: 10/06/2020] [Accepted: 10/08/2020] [Indexed: 02/08/2023]
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Krohn KA, Vera DR. Concepts for design and analysis of receptor radiopharmaceuticals: The Receptor-Binding Radiotracers series of meetings provided the foundation. Nucl Med Biol 2021; 92:5-23. [PMID: 32331709 PMCID: PMC8049838 DOI: 10.1016/j.nucmedbio.2020.03.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Accepted: 03/08/2020] [Indexed: 12/14/2022]
Abstract
A symposium at George Washington University on Receptor-Binding Radiotracers in 1980 and three follow-up meetings held at University of California, San Diego provided a forum for debating the critical concepts involved in the new field of designing and evaluating radiotracers for imaging receptors and transporters. This review is intended to educate young investigators who may be relatively new to receptor radiopharmaceutical development. Our anticipated audience includes researchers in basic pharmacology, radiochemistry, imaging technology and kinetic data analysis and how these disciplines have worked together to build our understanding of the human biology of transporters and receptor signaling in health and disease. We have chosen to focus on radiochemical design of a useful imaging agent and how design is coupled to analysis of data collected from dynamic imaging with that agent. Some pharmacology may be required for designing the imaging agent and some imaging physics may be important in optimizing the quality of data that is collected. However, the key to a successful imaging agent is matching the radiotracer to the target receptor and to analysis of the time-course data that is used to parse delivery from specific binding and subsequent metabolism or degradation. Properly designed imaging agents are providing critical information about human biology in health and disease as well as pharmacodynamic response to drug interventions. The review emphasizes some of the ideas that were controversial at the 1980 conference and chronicles with literature examples how they have resolved over the four decades of using radiotracers to study transporters and receptors in human subjects. These examples show that there are situations where a very small KD, i.e. high affinity, has the potential to yield an image that reflects blood flow more than receptor density. The examples also show that by combining two studies, one with high specific activity and a second with low specific activity injections one can unravel the pseudo-first order rate B'max into the true second-order rate constant, k3, and the unoccupied receptor density. The final section describes how mathematical methods first presented to the receptor-imaging community in 1980 are now being used to provide confidence in the analysis of kinetic biodistribution studies. Our hope is that by bringing these concepts together in a single review, the next generation of scientists developing receptor imaging agents can be much more efficient than their pioneers in developing useful imaging methods.
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Affiliation(s)
- Kenneth A Krohn
- Center for Radiochemistry Research, Department of Diagnostic Radiology, Mail Code L104, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR 97239, United States of America.
| | - David R Vera
- UCSD Moores Cancer Center, Department of Radiology, Mail Code 0819, University of California, San Diego, CA 92037, United States of America
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Puig O, Henriksen OM, Vestergaard MB, Hansen AE, Andersen FL, Ladefoged CN, Rostrup E, Larsson HB, Lindberg U, Law I. Comparison of simultaneous arterial spin labeling MRI and 15O-H 2O PET measurements of regional cerebral blood flow in rest and altered perfusion states. J Cereb Blood Flow Metab 2020; 40:1621-1633. [PMID: 31500521 PMCID: PMC7370368 DOI: 10.1177/0271678x19874643] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Arterial spin labelling (ASL) is a non-invasive magnetic resonance imaging (MRI) technique that may provide fully quantitative regional cerebral blood flow (rCBF) images. However, before its application in clinical routine, ASL needs to be validated against the clinical gold standard, 15O-H2O positron emission tomography (PET). We aimed to compare the two techniques by performing simultaneous quantitative ASL-MRI and 15O-H2O-PET examinations in a hybrid PET/MRI scanner. Duplicate rCBF measurements were performed in healthy young subjects (n = 14) in rest, during hyperventilation, and after acetazolamide (post-ACZ), yielding 63 combined PET/MRI datasets in total. Average global CBF by ASL-MRI and 15O-H2O-PET was not significantly different in any state (40.0 ± 6.5 and 40.6 ± 4.1 mL/100 g/min, respectively in rest, 24.5 ± 5.1 and 23.4 ± 4.8 mL/100 g/min, respectively, during hyperventilation, and 59.1 ± 10.4 and 64.7 ± 10.0 mL/100 g/min, respectively, post-ACZ). Overall, strong correlation between the two methods was found across all states (slope = 1.01, R2 = 0.82), while the correlations within individual states and of reactivity measures were weaker, in particular in rest (R2 = 0.05, p = 0.03). Regional distribution was similar, although ASL yielded higher perfusion and absolute reactivity in highly vascularized areas. In conclusion, ASL-MRI and 15O-H2O-PET measurements of rCBF are highly correlated across different perfusion states, but with variable correlation within and between hemodynamic states, and systematic differences in regional distribution.
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Affiliation(s)
- Oriol Puig
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark
| | - Otto M Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark
| | - Mark B Vestergaard
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark
| | - Adam E Hansen
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark
| | - Flemming L Andersen
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark
| | - Claes N Ladefoged
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark
| | - Egill Rostrup
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark
| | - Henrik Bw Larsson
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark
| | - Ulrich Lindberg
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark
| | - Ian Law
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark
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Sander CY, Hansen HD, Wey HY. Advances in simultaneous PET/MR for imaging neuroreceptor function. J Cereb Blood Flow Metab 2020; 40:1148-1166. [PMID: 32169011 PMCID: PMC7238372 DOI: 10.1177/0271678x20910038] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Hybrid imaging using PET/MRI has emerged as a platform for elucidating novel neurobiology, molecular and functional changes in disease, and responses to physiological or pharmacological interventions. For the central nervous system, PET/MRI has provided insights into biochemical processes, linking selective molecular targets and distributed brain function. This review highlights several examples that leverage the strengths of simultaneous PET/MRI, which includes measuring the perturbation of multi-modal imaging signals on dynamic timescales during pharmacological challenges, physiological interventions or behavioral tasks. We discuss important considerations for the experimental design of dynamic PET/MRI studies and data analysis approaches for comparing and quantifying simultaneous PET/MRI data. The primary focus of this review is on functional PET/MRI studies of neurotransmitter and receptor systems, with an emphasis on the dopamine, opioid, serotonin and glutamate systems as molecular neuromodulators. In this context, we provide an overview of studies that employ interventions to alter the activity of neuroreceptors or the release of neurotransmitters. Overall, we emphasize how the synergistic use of simultaneous PET/MRI with appropriate study design and interventions has the potential to expand our knowledge about the molecular and functional dynamics of the living human brain. Finally, we give an outlook on the future opportunities for simultaneous PET/MRI.
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Affiliation(s)
- Christin Y Sander
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, MA, USA
| | - Hanne D Hansen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, MA, USA.,Neurobiology Research Unit and NeuroPharm, Copenhagen University Hospital (Rigshospitalet), Copenhagen, Denmark
| | - Hsiao-Ying Wey
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, MA, USA
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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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