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Chen Y, Kan K, Liu S, Lin H, Lue K. Impact of respiratory motion on 18 F-FDG PET radiomics stability: Clinical evaluation with a digital PET scanner. J Appl Clin Med Phys 2023; 24:e14200. [PMID: 37937706 PMCID: PMC10691638 DOI: 10.1002/acm2.14200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 10/13/2023] [Accepted: 10/30/2023] [Indexed: 11/09/2023] Open
Abstract
PURPOSE 18 F-FDG PET quantitative features are susceptible to respiratory motion. However, studies using clinical patient data to explore the impact of respiratory motion on 18 F-FDG PET radiomic features are limited. In this study, we investigated the impact of respiratory motion on radiomics stability with clinical 18 F-FDG PET images using a data-driven gating (DDG) algorithm on the digital PET scanner. MATERIALS AND METHODS A total of 101 patients who underwent oncological 18 F-FDG PET scans were retrospectively included. A DDG algorithm combined with a motion compensation technique was used to extract the PET images with respiratory motion correction. 18 F-FDG-avid lesions from the thorax to the upper abdomen were analyzed on the non-DDG and DDG PET images. The lesions were segmented with a 40% threshold of the maximum standardized uptake. A total of 725 radiomic features were computed from the segmented lesions, including first-order, shape, texture, and wavelet features. The intraclass correlation coefficient (ICC) and coefficient of variation (COV) were calculated to evaluate feature stability. An ICC above 0.9 and a COV below 5% were considered high stability. RESULTS In total, 168 lesions with and without respiratory motion correction were analyzed. Our results indicated that most 18 F-FDG PET radiomic features are sensitive to respiratory motion. Overall, only 27 out of 725 (3.72%) radiomic features were identified as highly stable, including one from the first-order features (entropy), one from the shape features (sphericity), four from the gray-level co-occurrence matrix features (normalized and unnormalized inverse difference moment, joint entropy, and sum entropy), one from the gray-level run-length matrix features (run entropy), and 20 from the wavelet filter-based features. CONCLUSION Respiratory motion has a significant impact on 18 F-FDG PET radiomics stability. The highly stable features identified in our study may serve as potential candidates for further applications, such as machine learning modeling.
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Affiliation(s)
- Yu‐Hung Chen
- Department of Nuclear MedicineHualien Tzu Chi HospitalBuddhist Tzu Chi Medical FoundationHualienTaiwan
- School of MedicineCollege of MedicineTzu Chi UniversityHualienTaiwan
- Department of Medical Imaging and Radiological SciencesTzu Chi University of Science and TechnologyHualienTaiwan
| | - Kuo‐Yi Kan
- Department of Nuclear MedicineFu Jen Catholic University HospitalNew Taipei CityTaiwan
| | - Shu‐Hsin Liu
- Department of Nuclear MedicineHualien Tzu Chi HospitalBuddhist Tzu Chi Medical FoundationHualienTaiwan
- Department of Medical Imaging and Radiological SciencesTzu Chi University of Science and TechnologyHualienTaiwan
| | - Hsin‐Hon Lin
- Department of Medical Imaging and Radiological SciencesCollege of MedicineChang Gung UniversityTaoyuanTaiwan
- Department of Nuclear MedicineChang Gung Memorial HospitalLinkouTaiwan
| | - Kun‐Han Lue
- Department of Medical Imaging and Radiological SciencesTzu Chi University of Science and TechnologyHualienTaiwan
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Ren W, Deán-Ben XL, Skachokova Z, Augath MA, Ni R, Chen Z, Razansky D. Monitoring mouse brain perfusion with hybrid magnetic resonance optoacoustic tomography. BIOMEDICAL OPTICS EXPRESS 2023; 14:1192-1204. [PMID: 36950237 PMCID: PMC10026577 DOI: 10.1364/boe.482205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/10/2023] [Accepted: 01/10/2023] [Indexed: 06/18/2023]
Abstract
Progress in brain research critically depends on the development of next-generation multi-modal imaging tools capable of capturing transient functional events and multiplexed contrasts noninvasively and concurrently, thus enabling a holistic view of dynamic events in vivo. Here we report on a hybrid magnetic resonance and optoacoustic tomography (MROT) system for murine brain imaging, which incorporates an MR-compatible spherical matrix array transducer and fiber-based light illumination into a 9.4 T small animal scanner. An optimized radiofrequency coil has further been devised for whole-brain interrogation. System's utility is showcased by acquiring complementary angiographic and soft tissue anatomical contrast along with simultaneous dual-modality visualization of contrast agent dynamics in vivo.
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Affiliation(s)
- Wuwei Ren
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich 8093, Switzerland
- Present address: School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China
- equal contribution
| | - Xosé Luís Deán-Ben
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich 8093, Switzerland
- equal contribution
| | - Zhiva Skachokova
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
| | - Mark-Aurel Augath
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich 8093, Switzerland
| | - Ruiqing Ni
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Zurich Neuroscience Center, University of Zurich and ETH Zurich, Zurich 8093, Switzerland
- Institute for Regenerative Medicine, Faculty of Medicine, University of Zurich, Zurich 8952, Switzerland
| | - Zhenyue Chen
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich 8093, Switzerland
| | - Daniel Razansky
- Institute for Biomedical Engineering and Institute of Pharmacology and Toxicology, Faculty of Medicine, University of Zurich, Zurich 8052, Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical Engineering, ETH Zurich, Zurich 8093, Switzerland
- Zurich Neuroscience Center, University of Zurich and ETH Zurich, Zurich 8093, Switzerland
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Lamare F, Bousse A, Thielemans K, Liu C, Merlin T, Fayad H, Visvikis D. PET respiratory motion correction: quo vadis? Phys Med Biol 2021; 67. [PMID: 34915465 DOI: 10.1088/1361-6560/ac43fc] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 12/16/2021] [Indexed: 11/12/2022]
Abstract
Positron emission tomography (PET) respiratory motion correction has been a subject of great interest for the last twenty years, prompted mainly by the development of multimodality imaging devices such as PET/computed tomography (CT) and PET/magnetic resonance imaging (MRI). PET respiratory motion correction involves a number of steps including acquisition synchronization, motion estimation and finally motion correction. The synchronization steps include the use of different external device systems or data driven approaches which have been gaining ground over the last few years. Patient specific or generic motion models using the respiratory synchronized datasets can be subsequently derived and used for correction either in the image space or within the image reconstruction process. Similar overall approaches can be considered and have been proposed for both PET/CT and PET/MRI devices. Certain variations in the case of PET/MRI include the use of MRI specific sequences for the registration of respiratory motion information. The proposed review includes a comprehensive coverage of all these areas of development in field of PET respiratory motion for different multimodality imaging devices and approaches in terms of synchronization, estimation and subsequent motion correction. Finally, a section on perspectives including the potential clinical usage of these approaches is included.
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Affiliation(s)
- Frederic Lamare
- Nuclear Medicine Department, University Hospital Centre Bordeaux Hospital Group South, ., Bordeaux, Nouvelle-Aquitaine, 33604, FRANCE
| | - Alexandre Bousse
- LaTIM, INSERM UMR1101, Université de Bretagne Occidentale, ., Brest, Bretagne, 29285, FRANCE
| | - Kris Thielemans
- University College London Institute of Nuclear Medicine, UCL Hospital, Tower 5, 235 Euston Road, London, NW1 2BU, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Chi Liu
- Department of Diagnostic Radiology, Yale University School of Medicine Department of Radiology and Biomedical Imaging, PO Box 208048, 801 Howard Avenue, New Haven, Connecticut, 06520-8042, UNITED STATES
| | - Thibaut Merlin
- LaTIM, INSERM UMR1101, Universite de Bretagne Occidentale, ., Brest, Bretagne, 29285, FRANCE
| | - Hadi Fayad
- Weill Cornell Medicine - Qatar, ., Doha, ., QATAR
| | - Dimitris Visvikis
- LaTIM, UMR1101, Universite de Bretagne Occidentale, INSERM, Brest, Bretagne, 29285, FRANCE
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Low-Dose PET Imaging of Tumors in Lung and Liver Regions Using Internal Motion Estimation. Diagnostics (Basel) 2021; 11:diagnostics11112138. [PMID: 34829485 PMCID: PMC8625002 DOI: 10.3390/diagnostics11112138] [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: 10/01/2021] [Revised: 11/12/2021] [Accepted: 11/15/2021] [Indexed: 11/23/2022] Open
Abstract
Motion estimation and compensation are necessary for improvement of tumor quantification analysis in positron emission tomography (PET) images. The aim of this study was to propose adaptive PET imaging with internal motion estimation and correction using regional artificial evaluation of tumors injected with low-dose and high-dose radiopharmaceuticals. In order to assess internal motion, molecular sieves imitating tumors were loaded with 18F and inserted into the lung and liver regions in rats. All models were classified into two groups, based on the injected radiopharmaceutical activity, to compare the effect of tumor intensity. The PET study was performed with injection of F-18 fluorodeoxyglucose (18F-FDG). Respiratory gating was carried out by external trigger device. Count, signal to noise ratio (SNR), contrast and full width at half maximum (FWHM) were measured in artificial tumors in gated images. Motion correction was executed by affine transformation with estimated internal motion data. Monitoring data were different from estimated motion. Contrast in the low-activity group was 3.57, 4.08 and 6.19, while in the high-activity group it was 10.01, 8.36 and 6.97 for static, 4 bin and 8 bin images, respectively. The results of the lung target in 4 bin and the liver target in 8 bin showed improvement in FWHM and contrast with sufficient SNR. After motion correction, FWHM was improved in both regions (lung: 24.56%, liver: 10.77%). Moreover, with the low dose of radiopharmaceuticals the PET image visualized specific accumulated radiopharmaceutical areas in the liver. Therefore, low activity in PET images should undergo motion correction before quantification analysis using PET data. We could improve quantitative tumor evaluation by considering organ region and tumor intensity.
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Polycarpou I, Soultanidis G, Tsoumpas C. Synergistic motion compensation strategies for positron emission tomography when acquired simultaneously with magnetic resonance imaging. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20200207. [PMID: 34218675 PMCID: PMC8255946 DOI: 10.1098/rsta.2020.0207] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/15/2021] [Indexed: 05/04/2023]
Abstract
Subject motion in positron emission tomography (PET) is a key factor that degrades image resolution and quality, limiting its potential capabilities. Correcting for it is complicated due to the lack of sufficient measured PET data from each position. This poses a significant barrier in calculating the amount of motion occurring during a scan. Motion correction can be implemented at different stages of data processing either during or after image reconstruction, and once applied accurately can substantially improve image quality and information accuracy. With the development of integrated PET-MRI (magnetic resonance imaging) scanners, internal organ motion can be measured concurrently with both PET and MRI. In this review paper, we explore the synergistic use of PET and MRI data to correct for any motion that affects the PET images. Different types of motion that can occur during PET-MRI acquisitions are presented and the associated motion detection, estimation and correction methods are reviewed. Finally, some highlights from recent literature in selected human and animal imaging applications are presented and the importance of motion correction for accurate kinetic modelling in dynamic PET-MRI is emphasized. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.
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Affiliation(s)
- Irene Polycarpou
- Department of Health Sciences, European University of Cyprus, Nicosia, Cyprus
| | - Georgios Soultanidis
- Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Charalampos Tsoumpas
- Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Biomedical Imaging Science Department, University of Leeds, West Yorkshire, UK
- Invicro, London, UK
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Black DG, Yazdi YO, Wong J, Fedrigo R, Uribe C, Kadrmas DJ, Rahmim A, Klyuzhin IS. Design of an anthropomorphic PET phantom with elastic lungs and respiration modeling. Med Phys 2021; 48:4205-4217. [PMID: 34031896 DOI: 10.1002/mp.14998] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 05/06/2021] [Accepted: 05/10/2021] [Indexed: 11/11/2022] Open
Abstract
PURPOSE Respiratory motion during positron emission tomography (PET) scans can be a major detriment to image quality in oncological imaging. The impact of motion on lesion quantification and detectability can be assessed using phantoms with realistic anatomy representation and motion modeling. In this work, we develop an anthropomorphic phantom for PET imaging that combines anatomic fidelity and a realistic breathing mechanism with deformable lungs. METHODS We start from a previously developed anatomically accurate but static phantom of a human torso, and add elastic lungs with a highly controllable actuation mechanism which replicates the physics of breathing. The space outside the lungs is filled with a radioactive water solution. To maintain anatomical accuracy and realistic gamma ray attenuation in the torso, all motion mechanisms and actuators are positioned outside of the phantom compartment. The actuation mechanism can produce custom respiratory waveforms with breathing rates up to 25 breaths per minute and tidal volumes up to 1200 mL. RESULTS Several tests were performed to validate the performance of the phantom assembly, in which the phantom was filled with water and given respiratory waveforms to execute. All parts demonstrated expected performance. Force requirements were not exceeded and no leaks were detected, although continued use of the phantom is required to evaluate wear. The motion of the lungs was determined to be within a reasonable realistic range. CONCLUSIONS The full mechanical design is described in this paper, as well as a software application with graphical user interface which was developed to plan and visualize respiratory patterns. Both are available online as open source files. The developed phantom will facilitate future work in evaluating the impact of respiratory motion on lesion quantification and detectability in clinical practice.
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Affiliation(s)
- David G Black
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Yas Oloumi Yazdi
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Jeremy Wong
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Roberto Fedrigo
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,BC Cancer Research Institute, Vancouver, BC, Canada
| | - Carlos Uribe
- Department of Functional Imaging, BC Cancer, Vancouver, BC, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Dan J Kadrmas
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Arman Rahmim
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,BC Cancer Research Institute, Vancouver, BC, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Ivan S Klyuzhin
- BC Cancer Research Institute, Vancouver, BC, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada
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Li H, Meng X, Guan X, Zhou N, Liu H, Zhang Y, Yu B, Zhu H, Li N, Yang Z. Clinical Evaluation of MR-Gated Respiratory Motion Correction in Simultaneous PET/MRI. Clin Nucl Med 2021; 46:297-302. [PMID: 33512946 DOI: 10.1097/rlu.0000000000003510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
PURPOSE The recently available gated T1-weighted imaging with the Dixon technique enables the synchronized gating signal for both MR acquisition and PET reconstruction. Herein, we evaluated the clinical value of this MR-gated PET reconstruction in the thoracic-abdominal PET/MRI compared with non-MR-gated method. METHODS Twenty patients (28 hypermetabolic target lesions) underwent PET/MRI. Four types of PET images were reconstructed: non-MR-gating + gated attenuation correction (AC) (group A), MR-gating + gated AC (group B), non-MR-gating + breath-hold (BH) AC (group C), and MR-gating + BH AC (group D). A 4-point objective scale (from well match to obvious mismatch was scored from 3 to 0) was proposed to evaluate the mismatch. The detection rate and quantitative metrics were also evaluated. RESULTS In the patient-based analysis, for groups A through D, the detection rates were 90%, 100%, 85%, and 90% as well as 95%, 100%, 85%, and 85%, assessed by readers 1 and 2, respectively, and significant difference of mismatch score was observed with the highest proportion of 3 points in group B (85%, 90%, 35%, and 40%, and 80%, 90%, 35%, and 20%, assessed by readers 1 and 2, respectively). The lesion-based analysis demonstrated significant differences in quantitative metrics for groups A through D (all P's < 0.05), with the highest quantitative metrics in group B (SUVmax: 7.49 ± 3.37, 8.45 ± 3.82, 6.90 ± 3.24, and 7.69 ± 3.50; SUVmean: 3.90 ± 1.60, 4.34 ± 1.84, 3.67 ± 1.61, and 4.03 ± 1.81; SUVpeak: 5.60 ± 2.50, 6.10 ± 2.80, 5.22 ± 2.40, and 5.65 ± 2.68; signal-to-noise ratio: 136.06 ± 90.58, 136.24 ± 81.63, 99.52 ± 53.16, and 107.57 ± 69.05). CONCLUSIONS The MR-gated reconstruction using gated AC reduced the mismatch between MR and PET images and improved the thoracic-abdominal PET image quality in simultaneous PET/MRI systems.
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Affiliation(s)
- Hui Li
- From the Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing
| | - Xiangxi Meng
- From the Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing
| | - Xiangping Guan
- From the Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing
| | - Nina Zhou
- From the Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing
| | - Hui Liu
- United Imaging Healthcare, Shanghai, China
| | - Yan Zhang
- From the Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing
| | - Boqi Yu
- From the Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing
| | - Hua Zhu
- From the Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing
| | - Nan Li
- From the Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing
| | - Zhi Yang
- From the Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Nuclear Medicine, Peking University Cancer Hospital and Institute, Beijing
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Beyer T, Bidaut L, Dickson J, Kachelriess M, Kiessling F, Leitgeb R, Ma J, Shiyam Sundar LK, Theek B, Mawlawi O. What scans we will read: imaging instrumentation trends in clinical oncology. Cancer Imaging 2020; 20:38. [PMID: 32517801 PMCID: PMC7285725 DOI: 10.1186/s40644-020-00312-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 04/17/2020] [Indexed: 12/16/2022] Open
Abstract
Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non-invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/CT), advanced MRI, optical or ultrasound imaging.This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and, then point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now.Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by advances in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as "data", and - through the wider adoption of advanced analysis, including machine learning approaches and a "big data" concept - move to the next stage of non-invasive tumour phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi-dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging.
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Affiliation(s)
- Thomas Beyer
- QIMP Team, Centre for Medical Physics and Biomedical Engineering, Medical University Vienna, Währinger Gürtel 18-20/4L, 1090, Vienna, Austria.
| | - Luc Bidaut
- College of Science, University of Lincoln, Lincoln, UK
| | - John Dickson
- Institute of Nuclear Medicine, University College London Hospital, London, UK
| | - Marc Kachelriess
- Division of X-ray imaging and CT, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, DE, Germany
| | - Fabian Kiessling
- Institute for Experimental Molecular Imaging, University Clinic and Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstrasse 20, 52074, Aachen, DE, Germany
- Fraunhofer Institute for Digital Medicine MEVIS, Am Fallturm 1, 28359, Bremen, DE, Germany
| | - Rainer Leitgeb
- Centre for Medical Physics and Biomedical Engineering, Medical University Vienna, Vienna, AT, Austria
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Lalith Kumar Shiyam Sundar
- QIMP Team, Centre for Medical Physics and Biomedical Engineering, Medical University Vienna, Währinger Gürtel 18-20/4L, 1090, Vienna, Austria
| | - Benjamin Theek
- Institute for Experimental Molecular Imaging, University Clinic and Helmholtz Institute for Biomedical Engineering, RWTH Aachen University, Pauwelsstrasse 20, 52074, Aachen, DE, Germany
- Fraunhofer Institute for Digital Medicine MEVIS, Am Fallturm 1, 28359, Bremen, DE, Germany
| | - Osama Mawlawi
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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AI-based applications in hybrid imaging: how to build smart and truly multi-parametric decision models for radiomics. Eur J Nucl Med Mol Imaging 2019; 46:2673-2699. [PMID: 31292700 DOI: 10.1007/s00259-019-04414-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 06/21/2019] [Indexed: 12/13/2022]
Abstract
INTRODUCTION The quantitative imaging features (radiomics) that can be obtained from the different modalities of current-generation hybrid imaging can give complementary information with regard to the tumour environment, as they measure different morphologic and functional imaging properties. These multi-parametric image descriptors can be combined with artificial intelligence applications into predictive models. It is now the time for hybrid PET/CT and PET/MRI to take the advantage offered by radiomics to assess the added clinical benefit of using multi-parametric models for the personalized diagnosis and prognosis of different disease phenotypes. OBJECTIVE The aim of the paper is to provide an overview of current challenges and available solutions to translate radiomics into hybrid PET-CT and PET-MRI imaging for a smart and truly multi-parametric decision model.
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Johnson PM, Taylor R, Whelan T, Thiessen JD, Anazodo U, Drangova M. Rigid-body motion correction in hybrid PET/MRI using spherical navigator echoes. Phys Med Biol 2019; 64:08NT03. [PMID: 30884475 DOI: 10.1088/1361-6560/ab10b2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Integrated positron emission tomography and magnetic resonance imaging (PET/MRI) is an imaging technology that provides complementary anatomical and functional information for medical diagnostics. Both PET and MRI are highly susceptible to motion artifacts due, in part, to long acquisition times. The simultaneous acquisition of the two modalities presents the opportunity to use MRI navigator techniques for motion correction of both PET and MRI data. For this task, we propose spherical navigator echoes (SNAVs)-3D k-space navigators that can accurately and rapidly measure rigid body motion in all six degrees of freedom. SNAVs were incorporated into turbo FLASH (tfl)-a product fast gradient echo sequence-to create the tfl-SNAV pulse sequence. Acquiring in vivo brain images from a healthy volunteer with both sequences first compared the tfl-SNAV and product tfl sequences. It was observed that incorporation of the SNAVs into the image sequence did not have any detrimental impact on the image quality. The SNAV motion correction technique was evaluated using an anthropomorphic brain phantom. Following a stationary reference image where the tfl-SNAV sequence was acquired along with simultaneous list-mode PET, three identical PET/MRI scans were performed where the phantom was moved several times throughout each acquisition. This motion-up to 11° and 14 mm-resulted in motion artifacts in both PET and MR images. Following SNAV motion correction of the MRI and PET list-mode data, artifact reduction was achieved for both the PET and MR images in all three motion trials. The corrected images have improved image quality and are quantitatively more similar to the ground truth reference images.
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Affiliation(s)
- P M Johnson
- Robarts Research Institute, Western University, London, ON, Canada. Department of Medical Biophysics, Western University, London, ON, Canada
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