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Lazen P, Lima Cardoso P, Sharma S, Cadrien C, Roetzer-Pejrimovsky T, Furtner J, Strasser B, Hingerl L, Lipka A, Preusser M, Marik W, Bogner W, Widhalm G, Rössler K, Trattnig S, Hangel G. A Comparison of 7 Tesla MR Spectroscopic Imaging and 3 Tesla MR Fingerprinting for Tumor Localization in Glioma Patients. Cancers (Basel) 2024; 16:943. [PMID: 38473305 DOI: 10.3390/cancers16050943] [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: 12/08/2023] [Revised: 02/20/2024] [Accepted: 02/23/2024] [Indexed: 03/14/2024] Open
Abstract
This paper investigated the correlation between magnetic resonance spectroscopic imaging (MRSI) and magnetic resonance fingerprinting (MRF) in glioma patients by comparing neuro-oncological markers obtained from MRSI to T1/T2 maps from MRF. Data from 12 consenting patients with gliomas were analyzed by defining hotspots for T1, T2, and various metabolic ratios, and comparing them using Sørensen-Dice similarity coefficients (DSCs) and the distances between their centers of intensity (COIDs). The median DSCs between MRF and the tumor segmentation were 0.73 (T1) and 0.79 (T2). The DSCs between MRSI and MRF were the highest for Gln/tNAA (T1: 0.75, T2: 0.80, tumor: 0.78), followed by Gly/tNAA (T1: 0.57, T2: 0.62, tumor: 0.54) and tCho/tNAA (T1: 0.61, T2: 0.58, tumor: 0.45). The median values in the tumor hotspot were T1 = 1724 ms, T2 = 86 ms, Gln/tNAA = 0.61, Gly/tNAA = 0.28, Ins/tNAA = 1.15, and tCho/tNAA = 0.48, and, in the peritumoral region, were T1 = 1756 ms, T2 = 102 ms, Gln/tNAA = 0.38, Gly/tNAA = 0.20, Ins/tNAA = 1.06, and tCho/tNAA = 0.38, and, in the NAWM, were T1 = 950 ms, T2 = 43 ms, Gln/tNAA = 0.16, Gly/tNAA = 0.07, Ins/tNAA = 0.54, and tCho/tNAA = 0.20. The results of this study constitute the first comparison of 7T MRSI and 3T MRF, showing a good correspondence between these methods.
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Affiliation(s)
- Philipp Lazen
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
- Department for Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, 1090 Vienna, Austria
| | - Pedro Lima Cardoso
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Sukrit Sharma
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Cornelius Cadrien
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
- Department for Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria
| | - Thomas Roetzer-Pejrimovsky
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, 1090 Vienna, Austria
| | - Julia Furtner
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
- Research Center for Medical Image Analysis and Artificial Intelligence (MIAAI), Danube Private University, 3500 Krems, Austria
| | - Bernhard Strasser
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Lukas Hingerl
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Alexandra Lipka
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Matthias Preusser
- Division of Oncology, Department of Internal Medicine I, Medical University of Vienna, 1090 Vienna, Austria
| | - Wolfgang Marik
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
| | - Wolfgang Bogner
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, 1090 Vienna, Austria
| | - Georg Widhalm
- Department for Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria
| | - Karl Rössler
- Department for Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, 1090 Vienna, Austria
| | - Siegfried Trattnig
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, 1090 Vienna, Austria
- Institute for Clinical Molecular MRI, Karl Landsteiner Society, 3100 St. Pölten, Austria
| | - Gilbert Hangel
- High-Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, 1090 Vienna, Austria
- Department for Neurosurgery, Medical University of Vienna, 1090 Vienna, Austria
- Christian Doppler Laboratory for MR Imaging Biomarkers, 1090 Vienna, Austria
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Wu Y, Liu X, Huang Y, Zhou T, Zhang F. An open relaxation-diffusion MRI dataset in neurosurgical studies. Sci Data 2024; 11:177. [PMID: 38326377 PMCID: PMC10850093 DOI: 10.1038/s41597-024-03013-9] [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: 10/04/2023] [Accepted: 01/25/2024] [Indexed: 02/09/2024] Open
Abstract
Diffusion MRI (dMRI) is a safe and noninvasive technique that provides insight into the microarchitecture of brain tissue. Relaxation-diffusion MRI (rdMRI) is an extension of traditional dMRI that captures diffusion imaging data at multiple TEs to detect tissue heterogeneity between relaxation and diffusivity. rdMRI has great potential in neurosurgical research including brain tumor grading and treatment response evaluation. However, the lack of available data has limited the exploration of rdMRI in clinical settings. To address this, we are sharing a high-quality rdMRI dataset from 18 neurosurgical patients with different types of lesions, as well as two healthy individuals as controls. The rdMRI data was acquired using 7 TEs, where at each TE multi-shell dMRI with high spatial and angular resolutions is obtained at each TE. Each rdMRI scan underwent thorough artifact and distortion corrections using a specially designed processing pipeline. The dataset's quality was assessed using standard practices, including quality control and assurance. This resource is a valuable addition to neurosurgical studies, and all data are openly accessible.
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Affiliation(s)
- Ye Wu
- School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China
| | - Xiaoming Liu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China.
| | - Yunzhi Huang
- School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China
| | - Tao Zhou
- School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China
| | - Fan Zhang
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China
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3
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Sanvito F, Kaufmann TJ, Cloughesy TF, Wen PY, Ellingson BM. Standardized brain tumor imaging protocols for clinical trials: current recommendations and tips for integration. FRONTIERS IN RADIOLOGY 2023; 3:1267615. [PMID: 38152383 PMCID: PMC10751345 DOI: 10.3389/fradi.2023.1267615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 11/24/2023] [Indexed: 12/29/2023]
Abstract
Standardized MRI acquisition protocols are crucial for reducing the measurement and interpretation variability associated with response assessment in brain tumor clinical trials. The main challenge is that standardized protocols should ensure high image quality while maximizing the number of institutions meeting the acquisition requirements. In recent years, extensive effort has been made by consensus groups to propose different "ideal" and "minimum requirements" brain tumor imaging protocols (BTIPs) for gliomas, brain metastases (BM), and primary central nervous system lymphomas (PCSNL). In clinical practice, BTIPs for clinical trials can be easily integrated with additional MRI sequences that may be desired for clinical patient management at individual sites. In this review, we summarize the general concepts behind the choice and timing of sequences included in the current recommended BTIPs, we provide a comparative overview, and discuss tips and caveats to integrate additional clinical or research sequences while preserving the recommended BTIPs. Finally, we also reflect on potential future directions for brain tumor imaging in clinical trials.
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Affiliation(s)
- Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | | | - Timothy F. Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, United States
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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4
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You HM, Wang L, Meng HW, Huang C, Fang GY, Li J. Pyroptosis: shedding light on the mechanisms and links with cancers. Front Immunol 2023; 14:1290885. [PMID: 38016064 PMCID: PMC10651733 DOI: 10.3389/fimmu.2023.1290885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 10/20/2023] [Indexed: 11/30/2023] Open
Abstract
Pyroptosis, a novel form of programmed cell death (PCD) discovered after apoptosis and necrosis, is characterized by cell swelling, cytomembrane perforation and lysis, chromatin DNA fragmentation, and the release of intracellular proinflammatory contents, such as Interleukin (IL) 8, IL-1β, ATP, IL-1α, and high mobility group box 1 (HMGB1). Our understanding of pyroptosis has increased over time with an increase in research on the subject: gasdermin-mediated lytic PCD usually, but not always, requires cleavage by caspases. Moreover, new evidence suggests that pyroptosis induction in tumor cells results in a strong inflammatory response and significant cancer regression, which has stimulated great interest among scientists for its potential application in clinical cancer therapy. It's worth noting that the side effects of chemotherapy and radiotherapy can be triggered by pyroptosis. Thus, the intelligent use of pyroptosis, the double-edged sword for tumors, will enable us to understand the genesis and development of cancers and provide potential methods to develop novel anticancer drugs based on pyroptosis. Hence, in this review, we systematically summarize the molecular mechanisms of pyroptosis and provide the latest available evidence supporting the antitumor properties of pyroptosis, and provide a summary of the various antitumor medicines targeting pyroptosis signaling pathways.
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Affiliation(s)
- Hong-mei You
- Department of Pharmacy, Hangzhou Women’s Hospital, Hangzhou, China
| | - Ling Wang
- Department of Pharmacy, Shangyu People’s Hospital of Shaoxing, Shaoxing, China
| | - Hong-wu Meng
- Department of Pharmacy, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Cheng Huang
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei, China
| | - Guo-ying Fang
- Department of Pharmacy, Hangzhou Women’s Hospital, Hangzhou, China
| | - Jun Li
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei, China
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5
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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: 5] [Impact Index Per Article: 5.0] [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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Salihoğlu AK, Booth TC. Editorial for "Apparent Diffusion Coefficient as Imaging Biomarker for Identifying IDH Mutation, 1p19q Codeletion, and MGMT Promoter Methylation Status in Patients With Glioma". J Magn Reson Imaging 2023; 58:739-740. [PMID: 36594487 DOI: 10.1002/jmri.28587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 12/22/2022] [Indexed: 01/04/2023] Open
Affiliation(s)
- Arif K Salihoğlu
- Faculty of Medicine, Department of Physiology, Karadeniz Technical University, Trabzon, Turkey
| | - Thomas C Booth
- School of Biomedical Engineering & Imaging Sciences, King's College London, St. Thomas' Hospital, London, UK
- Department of Neuroradiology, King's College Hospital National Health Service Foundation Trust, London, UK
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7
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von Knebel Doeberitz N, Kroh F, König L, Boyd PS, Graß S, Bauspieß C, Scherer M, Unterberg A, Bendszus M, Wick W, Bachert P, Debus J, Ladd ME, Schlemmer HP, Goerke S, Korzowski A, Paech D. Post-Surgical Depositions of Blood Products Are No Major Confounder for the Diagnostic and Prognostic Performance of CEST MRI in Patients with Glioma. Biomedicines 2023; 11:2348. [PMID: 37760790 PMCID: PMC10525358 DOI: 10.3390/biomedicines11092348] [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: 07/13/2023] [Revised: 08/11/2023] [Accepted: 08/16/2023] [Indexed: 09/29/2023] Open
Abstract
Amide proton transfer (APT) and semi-solid magnetization transfer (ssMT) imaging can predict clinical outcomes in patients with glioma. However, the treatment of brain tumors is accompanied by the deposition of blood products within the tumor area in most cases. For this reason, the objective was to assess whether the diagnostic interpretation of the APT and ssMT is affected by methemoglobin (mHb) and hemosiderin (Hs) depositions at the first follow-up MRI 4 to 6 weeks after the completion of radiotherapy. A total of 34 participants underwent APT and ssMT imaging by applying reconstruction methods described by Zhou et al. (APTwasym), Goerke et al. (MTRRexAPT and MTRRexMT) and Mehrabian et al. (MTconst). Contrast-enhancing tumor (CE), whole tumor (WT), mHb and Hs were segmented on contrast-enhanced T1wCE, T2w-FLAIR, T1w and T2*w images. ROC-analysis, Kaplan-Meier analysis and the log rank test were used to test for the association of mean contrast values with therapy response and overall survival (OS) before (WT and CE) and after correcting tumor volumes for mHb and Hs (CEC and WTC). CEC showed higher associations of the MTRRexMT with therapy response (CE: AUC = 0.677, p = 0.081; CEC: AUC = 0.705, p = 0.044) and of the APTwasym with OS (CE: HR = 2.634, p = 0.040; CEC: HR = 2.240, p = 0.095). In contrast, WTC showed a lower association of the APTwasym with survival (WT: HR = 2.304, p = 0.0849; WTC: HR = 2.990, p = 0.020). Overall, a sophisticated correction for blood products did not substantially influence the clinical performance of APT and ssMT imaging in patients with glioma early after radiotherapy.
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Affiliation(s)
| | - Florian Kroh
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Department of Physics and Astronomy, University of Heidelberg, 69120 Heidelberg, Germany
| | - Laila König
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Philip S. Boyd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Svenja Graß
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Cora Bauspieß
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Moritz Scherer
- Department of Neurosurgery, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Andreas Unterberg
- Department of Neurosurgery, University Hospital Heidelberg, 69120 Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
| | - Martin Bendszus
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
- Department of Neuroradiology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Wolfgang Wick
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
- Department of Neurology, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Department of Physics and Astronomy, University of Heidelberg, 69120 Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, Heidelberg University Hospital, 69120 Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Mark E. Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Department of Physics and Astronomy, University of Heidelberg, 69120 Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
| | - Heinz-Peter Schlemmer
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Faculty of Medicine, University of Heidelberg, 69120 Heidelberg, Germany
| | - Steffen Goerke
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Andreas Korzowski
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Daniel Paech
- Division of Radiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Department of Neuroradiology, University Hospital Bonn, 53127 Bonn, Germany
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Ortega-Martorell S, Olier I, Hernandez O, Restrepo-Galvis PD, Bellfield RAA, Candiota AP. Tracking Therapy Response in Glioblastoma Using 1D Convolutional Neural Networks. Cancers (Basel) 2023; 15:4002. [PMID: 37568818 PMCID: PMC10417313 DOI: 10.3390/cancers15154002] [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: 06/07/2023] [Revised: 07/26/2023] [Accepted: 08/05/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND Glioblastoma (GB) is a malignant brain tumour that is challenging to treat, often relapsing even after aggressive therapy. Evaluating therapy response relies on magnetic resonance imaging (MRI) following the Response Assessment in Neuro-Oncology (RANO) criteria. However, early assessment is hindered by phenomena such as pseudoprogression and pseudoresponse. Magnetic resonance spectroscopy (MRS/MRSI) provides metabolomics information but is underutilised due to a lack of familiarity and standardisation. METHODS This study explores the potential of spectroscopic imaging (MRSI) in combination with several machine learning approaches, including one-dimensional convolutional neural networks (1D-CNNs), to improve therapy response assessment. Preclinical GB (GL261-bearing mice) were studied for method optimisation and validation. RESULTS The proposed 1D-CNN models successfully identify different regions of tumours sampled by MRSI, i.e., normal brain (N), control/unresponsive tumour (T), and tumour responding to treatment (R). Class activation maps using Grad-CAM enabled the study of the key areas relevant to the models, providing model explainability. The generated colour-coded maps showing the N, T and R regions were highly accurate (according to Dice scores) when compared against ground truth and outperformed our previous method. CONCLUSIONS The proposed methodology may provide new and better opportunities for therapy response assessment, potentially providing earlier hints of tumour relapsing stages.
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Affiliation(s)
- Sandra Ortega-Martorell
- Data Science Research Centre, Liverpool John Moores University, Liverpool L3 3AF, UK; (I.O.); (R.A.A.B.)
| | - Ivan Olier
- Data Science Research Centre, Liverpool John Moores University, Liverpool L3 3AF, UK; (I.O.); (R.A.A.B.)
| | - Orlando Hernandez
- Escuela Colombiana de Ingeniería Julio Garavito, Bogota 111166, Colombia; (O.H.); (P.D.R.-G.)
| | | | - Ryan A. A. Bellfield
- Data Science Research Centre, Liverpool John Moores University, Liverpool L3 3AF, UK; (I.O.); (R.A.A.B.)
| | - Ana Paula Candiota
- Centro de Investigación Biomédica en Red: Bioingeniería, Biomateriales y Nanomedicina, 08193 Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Facultat de Biociències, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Spain
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Hangel G, Schmitz‐Abecassis B, Sollmann N, Pinto J, Arzanforoosh F, Barkhof F, Booth T, Calvo‐Imirizaldu M, Cassia G, Chmelik M, Clement P, Ercan E, Fernández‐Seara MA, Furtner J, Fuster‐Garcia E, Grech‐Sollars M, Guven NT, Hatay GH, Karami G, Keil VC, Kim M, Koekkoek JAF, Kukran S, Mancini L, Nechifor RE, Özcan A, Ozturk‐Isik E, Piskin S, Schmainda KM, Svensson SF, Tseng C, Unnikrishnan S, Vos F, Warnert E, Zhao MY, Jancalek R, Nunes T, Hirschler L, Smits M, Petr J, Emblem KE. Advanced MR Techniques for Preoperative Glioma Characterization: Part 2. J Magn Reson Imaging 2023; 57:1676-1695. [PMID: 36912262 PMCID: PMC10947037 DOI: 10.1002/jmri.28663] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/08/2023] [Accepted: 02/09/2023] [Indexed: 03/14/2023] Open
Abstract
Preoperative clinical MRI protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this second part, we review magnetic resonance spectroscopy (MRS), chemical exchange saturation transfer (CEST), susceptibility-weighted imaging (SWI), MRI-PET, MR elastography (MRE), and MR-based radiomics applications. The first part of this review addresses dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) MRI, arterial spin labeling (ASL), diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting (MRF). EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Gilbert Hangel
- Department of NeurosurgeryMedical University of ViennaViennaAustria
- High Field MR Centre, Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Christian Doppler Laboratory for MR Imaging BiomarkersViennaAustria
- Medical Imaging ClusterMedical University of ViennaViennaAustria
| | - Bárbara Schmitz‐Abecassis
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
- Medical Delta FoundationDelftthe Netherlands
| | - Nico Sollmann
- Department of Diagnostic and Interventional RadiologyUniversity Hospital UlmUlmGermany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der IsarTechnical University of MunichMunichGermany
- TUM‐Neuroimaging Center, Klinikum rechts der IsarTechnical University of MunichMunichGermany
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering ScienceUniversity of OxfordOxfordUK
| | | | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamNetherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Thomas Booth
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
- Department of NeuroradiologyKing's College Hospital NHS Foundation TrustLondonUK
| | | | | | - Marek Chmelik
- Department of Technical Disciplines in Medicine, Faculty of Health CareUniversity of PrešovPrešovSlovakia
| | - Patricia Clement
- Department of Diagnostic SciencesGhent UniversityGhentBelgium
- Department of Medical ImagingGhent University HospitalGhentBelgium
| | - Ece Ercan
- Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
| | - Maria A. Fernández‐Seara
- Department of RadiologyClínica Universidad de NavarraPamplonaSpain
- IdiSNA, Instituto de Investigación Sanitaria de NavarraPamplonaSpain
| | - Julia Furtner
- Department of Biomedical Imaging and Image‐guided TherapyMedical University of ViennaViennaAustria
- Research Center of Medical Image Analysis and Artificial IntelligenceDanube Private UniversityAustria
| | - Elies Fuster‐Garcia
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y ComunicacionesUniversitat Politècnica de ValènciaValenciaSpain
| | - Matthew Grech‐Sollars
- Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
| | - N. Tugay Guven
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Gokce Hale Hatay
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Golestan Karami
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Vera C. Keil
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamNetherlands
- Cancer Center AmsterdamAmsterdamNetherlands
| | - Mina Kim
- Centre for Medical Image Computing, Department of Medical Physics & Biomedical Engineering and Department of NeuroinflammationUniversity College LondonLondonUK
| | - Johan A. F. Koekkoek
- Department of NeurologyLeiden University Medical CenterLeidenthe Netherlands
- Department of NeurologyHaaglanden Medical CenterNetherlands
| | - Simran Kukran
- Department of BioengineeringImperial College LondonLondonUK
- Department of Radiotherapy and ImagingInstitute of Cancer ResearchUK
| | - Laura Mancini
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
- Department of Brain Repair and Rehabilitation, Institute of NeurologyUniversity College LondonLondonUK
| | - Ruben Emanuel Nechifor
- Department of Clinical Psychology and Psychotherapy, International Institute for the Advanced Studies of Psychotherapy and Applied Mental HealthBabes‐Bolyai UniversityRomania
| | - Alpay Özcan
- Electrical and Electronics Engineering DepartmentBogazici University IstanbulIstanbulTurkey
| | - Esin Ozturk‐Isik
- Institute of Biomedical EngineeringBogazici University IstanbulIstanbulTurkey
| | - Senol Piskin
- Department of Mechanical Engineering, Faculty of Natural Sciences and EngineeringIstinye University IstanbulIstanbulTurkey
| | | | - Siri F. Svensson
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
- Department of PhysicsUniversity of OsloOsloNorway
| | - Chih‐Hsien Tseng
- Medical Delta FoundationDelftthe Netherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftthe Netherlands
| | - Saritha Unnikrishnan
- Faculty of Engineering and DesignAtlantic Technological University (ATU) SligoSligoIreland
- Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE), ATU SligoSligoIreland
| | - Frans Vos
- Medical Delta FoundationDelftthe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
- Department of Imaging PhysicsDelft University of TechnologyDelftthe Netherlands
| | - Esther Warnert
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
| | - Moss Y. Zhao
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
- Stanford Cardiovascular InstituteStanford UniversityStanfordCaliforniaUSA
| | - Radim Jancalek
- Department of NeurosurgerySt. Anne's University HospitalBrnoCzechia
- Faculty of MedicineMasaryk UniversityBrnoCzechia
| | - Teresa Nunes
- Department of NeuroradiologyHospital Garcia de OrtaAlmadaPortugal
| | - Lydiane Hirschler
- C.J. Gorter MRI Center, Department of RadiologyLeiden University Medical CenterLeidenthe Netherlands
| | - Marion Smits
- Medical Delta FoundationDelftthe Netherlands
- Department of Radiology & Nuclear MedicineErasmus MCRotterdamNetherlands
- Brain Tumour CentreErasmus MC Cancer InstituteRotterdamthe Netherlands
| | - Jan Petr
- Helmholtz‐Zentrum Dresden‐RossendorfInstitute of Radiopharmaceutical Cancer ResearchDresdenGermany
| | - Kyrre E. Emblem
- Department of Physics and Computational RadiologyOslo University HospitalOsloNorway
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10
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Knebel Doeberitz NV, Kroh F, Breitling J, König L, Maksimovic S, Graß S, Adeberg S, Scherer M, Unterberg A, Bendszus M, Wick W, Bachert P, Debus J, Ladd ME, Schlemmer HP, Korzowski A, Goerke S, Paech D. CEST Imaging of the APT and ssMT predict the overall survival of patients with glioma at the first follow-up after completion of radiotherapy at 3T. Radiother Oncol 2023; 184:109694. [PMID: 37150450 DOI: 10.1016/j.radonc.2023.109694] [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: 02/01/2023] [Revised: 04/27/2023] [Accepted: 04/28/2023] [Indexed: 05/09/2023]
Abstract
BACKGROUND AND PURPOSE Outcome prediction of patients with glioma early after the completion of radiotherapy represents a major clinical challenge. Previously, the prognostic value of chemical exchange saturation transfer (CEST) imaging has been demonstrated in patients with newly diagnosed glioma. The objective of this study was to assess the potential of amide proton transfer (APT)-, relayed nuclear Overhauser effect (rNOE)- and semi-solid magnetization transfer (ssMT)-imaging according to Zhou et al. (APTwasym), Goerke et al. (MTRRexAPT, MTRRexNOE and MTRRexMT) and Mehrabian et al. (PeakAreaAPT, PeakAreaNOE and MTconst) for the prognostication of the overall survival (OS) of patients with glioma at the first follow-up after the completion of radiotherapy. MATERIALS AND METHODS 49 of 72 participants with diffuse glioma, who underwent CEST MRI at 3T between July 2018 and December 2021 4 to 6 weeks after the completion of radiotherapy, were analyzed. Contrast-enhancing tumor (CE) and whole tumor (WT) volumes were segmented on T2w-FLAIR and contrast-enhanced T1w images. Kaplan-Meier analysis and logrank-test were used for statistical analyses. RESULTS APTw imaging demonstrated the strongest association with OS (HR=4.66, p<0.001). The MTconst (HR=2.54, p=0.044) was associated with the OS of participants with residual contrast-enhancing glioma tissue, whilst the MTRRexAPT (HR=2.44, p=0.056) showed a trend in this sub-cohort. The MTRRexNOE, MTRRexMT and PeakAreaNOE were not associated with survival. CONCLUSION Imaging of the APT and ssMT at the first follow-up 4 to 6 weeks after the completion of radiotherapy at 3T were associated with the overall survival of patients with glioma.
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Affiliation(s)
| | - Florian Kroh
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Johannes Breitling
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Laila König
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Srdjan Maksimovic
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Svenja Graß
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sebastian Adeberg
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Moritz Scherer
- Department of Neurosurgery, University Hospital Heidelberg, Heidelberg, Germany
| | - Andreas Unterberg
- Department of Neurosurgery, University Hospital Heidelberg, Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University Hospital Heidelberg, Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Wolfgang Wick
- Department of Neurology, University Hospital Heidelberg, Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany; Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Heinz-Peter Schlemmer
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Andreas Korzowski
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Steffen Goerke
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniel Paech
- Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Department of Neuroradiology, University Hospital Bonn, Bonn, Germany.
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11
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Chiu FY, Yen Y. Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives. Biomark Res 2023; 11:35. [PMID: 36991494 DOI: 10.1186/s40364-023-00476-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/16/2023] [Indexed: 03/31/2023] Open
Abstract
Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.
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Affiliation(s)
- Fang-Ying Chiu
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Center for Brain and Neurobiology Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Teaching and Research Headquarters for Sustainable Development Goals, Tzu Chi University, Hualien City, 970374, Taiwan.
| | - Yun Yen
- Center for Cancer Translational Research, Tzu Chi University, Hualien City, 970374, Taiwan.
- Ph.D. Program for Cancer Biology and Drug Discovery, Taipei Medical University, Taipei City, 110301, Taiwan.
- Graduate Institute of Cancer Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei City, 110301, Taiwan.
- TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei City, 110301, Taiwan.
- Cancer Center, Taipei Municipal WanFang Hospital, Taipei City, 116081, Taiwan.
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12
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Wamelink IJHG, Kuijer JPA, Padrela BE, Zhang Y, Barkhof F, Mutsaerts HJMM, Petr J, van de Giessen E, Keil VC. Reproducibility of 3 T APT-CEST in Healthy Volunteers and Patients With Brain Glioma. J Magn Reson Imaging 2023; 57:206-215. [PMID: 35633282 PMCID: PMC10084114 DOI: 10.1002/jmri.28239] [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: 02/23/2022] [Revised: 04/28/2022] [Accepted: 04/29/2022] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Amide proton transfer (APT) imaging is a chemical exchange saturation transfer (CEST) technique offering potential clinical applications such as diagnosis, characterization, and treatment planning and monitoring in glioma patients. While APT-CEST has demonstrated high potential, reproducibility remains underexplored. PURPOSE To investigate whether cerebral APT-CEST with clinically feasible scan time is reproducible in healthy tissue and glioma for clinical use at 3 T. STUDY TYPE Prospective, longitudinal. SUBJECTS Twenty-one healthy volunteers (11 females; mean age ± SD: 39 ± 11 years) and 6 glioma patients (3 females; 50 ± 17 years: 4 glioblastomas, 1 oligodendroglioma, 1 radiologically suspected low-grade glioma). FIELD STRENGTH/SEQUENCE 3 T, Turbo Spin Echo - ampling perfection with application optimized contrasts using different flip angle evolution - chemical exchange saturation transfer (TSE SPACE-CEST). ASSESSMENT APT-CEST measurement reproducibility was assessed within-session (glioma patients, scan session 1; healthy volunteers scan sessions 1, 2, and 3), between-sessions (healthy volunteers scan sessions 1 and 2), and between-days (healthy volunteers, scan sessions 1 and 3). The mean APTCEST values and standard deviation of the within-subject difference (SDdiff ) were calculated in whole tumor enclosed by regions of interest (ROIs) in patients, and eight ROIs in healthy volunteers-whole-brain, cortical gray matter, putamen, thalami, orbitofrontal gyri, occipital lobes, central brain-and compared. STATISTICAL TESTS Brown-Forsythe tests and variance component analysis (VCA) were used to assess the reproducibility of ROIs for the three time intervals. Significance was set at P < 0.003 after Bonferroni correction. RESULTS Intratumoral mean APTCEST was significantly higher than APTCEST in healthy-appearing tissue in patients (0.5 ± 0.46%). The average within-session, between-sessions, and between-days SDdiff of healthy control brains was 0.2% and did not differ significantly with each other (0.76 > P > 0.22). The within-session SDdiff of whole-brain was 0.2% in both healthy volunteers and patients, and 0.21% in the segmented tumor. VCA showed that within-session factors were the most important (60%) for scanning variance. DATA CONCLUSION Cerebral APT-CEST imaging may show good scan-rescan reproducibility in healthy tissue and tumors with clinically feasible scan times at 3 T. Short-term measurement effects may be the dominant components for reproducibility. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Ivar J H G Wamelink
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Joost P A Kuijer
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Beatriz E Padrela
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands.,Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Henk J M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Jan Petr
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands.,Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Elsmarieke van de Giessen
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Vera C Keil
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
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13
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Wang H, Zhou X, Li C, Yan S, Feng C, He J, Li Z, Tu C. The emerging role of pyroptosis in pediatric cancers: from mechanism to therapy. J Hematol Oncol 2022; 15:140. [PMID: 36209102 PMCID: PMC9547461 DOI: 10.1186/s13045-022-01365-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Accepted: 10/04/2022] [Indexed: 11/18/2022] Open
Abstract
Pediatric cancers are the driving cause of death for children and adolescents. Due to safety requirements and considerations, treatment strategies and drugs for pediatric cancers have been so far scarcely studied. It is well known that tumor cells tend to progressively evade cell death pathways, which is known as apoptosis resistance, one of the hallmarks of cancer, dominating tumor drug resistance. Recently, treatments targeting nonapoptotic cell death have drawn great attention. Pyroptosis, a newly specialized form of cell death, acts as a critical physiological regulator in inflammatory reaction, cell development, tissue homeostasis and stress response. The action in different forms of pyroptosis is of great significance in the therapy of pediatric cancers. Pyroptosis could be induced and consequently modulate tumorigenesis, progression, and metastasis if treated with local or systemic therapies. However, excessive or uncontrolled cell death might lead to tissue damage, acute inflammation, or even cytokine release syndrome, which facilitates tumor progression or recurrence. Herein, we aimed to describe the molecular mechanisms of pyroptosis, to highlight and discuss the challenges and opportunities for activating pyroptosis pathways through various oncologic therapies in multiple pediatric neoplasms, including osteosarcoma, neuroblastoma, leukemia, lymphoma, and brain tumors.
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Affiliation(s)
- Hua Wang
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.,Xiangya School of Medicine, Central South University, Changsha, 410011, Hunan, China
| | - Xiaowen Zhou
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.,Xiangya School of Medicine, Central South University, Changsha, 410011, Hunan, China
| | - Chenbei Li
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.,Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Shuxiang Yan
- Xiangya School of Medicine, Central South University, Changsha, 410011, Hunan, China
| | - Chengyao Feng
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.,Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Jieyu He
- Department of Geriatrics, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Zhihong Li
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China. .,Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
| | - Chao Tu
- Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China. .,Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
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