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Costin IC, Marcu LG. Affinity of PET-MRI Tracers for Hypoxic Cells in Breast Cancer: A Systematic Review. Cells 2024; 13:1048. [PMID: 38920676 PMCID: PMC11202228 DOI: 10.3390/cells13121048] [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: 04/26/2024] [Revised: 06/04/2024] [Accepted: 06/14/2024] [Indexed: 06/27/2024] Open
Abstract
Tumour hypoxia is a known microenvironmental culprit for treatment resistance, tumour recurrence and promotion of metastatic spread. Despite the long-known existence of this factor within the tumour milieu, hypoxia is still one of the greatest challenges in cancer management. The transition from invasive and less reliable detection methods to more accurate and non-invasive ways to identify and quantify hypoxia was a long process that eventually led to the promising results showed by functional imaging techniques. Hybrid imaging, such as PET-CT, has the great advantage of combining the structural or anatomical image (offered by CT) with the functional or metabolic one (offered by PET). However, in the context of hypoxia, it is only the PET image taken after appropriate radiotracer administration that would supply hypoxia-specific information. To overcome this limitation, the development of the latest hybrid imaging systems, such as PET-MRI, enables a synergistic approach towards hypoxia imaging, with both methods having the potential to provide functional information on the tumour microenvironment. This study is designed as a systematic review of the literature on the newest developments of PET-MRI for the imaging of hypoxic cells in breast cancer. The analysis includes the affinity of various PET-MRI tracers for hypoxia in this patient group as well as the correlations between PET-specific and MRI-specific parameters, to offer a broader view on the potential for the widespread clinical implementation of this hybrid imaging technique.
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Affiliation(s)
- Ioana-Claudia Costin
- Faculty of Physics, West University of Timisoara, 300223 Timisoara, Romania;
- Bihor County Emergency Clinical Hospital, 410167 Oradea, Romania
| | - Loredana G. Marcu
- Faculty of Informatics & Science, University of Oradea, 410087 Oradea, Romania
- UniSA Allied Health & Human Performance, University of South Australia, Adelaide, SA 5001, Australia
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Oba M, Taguchi M, Kudo Y, Yamashita K, Yasui H, Matsumoto S, Kirilyuk IA, Inanami O, Hirata H. Partial Acquisition of Spectral Projections Accelerates Four-dimensional Spectral-spatial EPR Imaging for Mouse Tumor Models: A Feasibility Study. Mol Imaging Biol 2024; 26:459-472. [PMID: 38811467 DOI: 10.1007/s11307-024-01924-y] [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: 03/26/2024] [Revised: 05/16/2024] [Accepted: 05/20/2024] [Indexed: 05/31/2024]
Abstract
PURPOSE Our study aimed to accelerate the acquisition of four-dimensional (4D) spectral-spatial electron paramagnetic resonance (EPR) imaging for mouse tumor models. This advancement in EPR imaging should reduce the acquisition time of spectroscopic mapping while reducing quality degradation for mouse tumor models. PROCEDURES EPR spectra under magnetic field gradients, called spectral projections, were partially measured. Additional spectral projections were later computationally synthesized from the measured spectral projections. Four-dimensional spectral-spatial images were reconstructed from the post-processed spectral projections using the algebraic reconstruction technique (ART) and assessed in terms of their image qualities. We applied this approach to a sample solution and a mouse Hs766T xenograft model of human-derived pancreatic ductal adenocarcinoma cells to demonstrate the feasibility of our concept. The nitroxyl radical imaging agent 2H,15N-DCP was exogenously infused into the mouse xenograft model. RESULTS The computation code of 4D spectral-spatial imaging was tested with numerically generated spectral projections. In the linewidth mapping of the sample solution, we achieved a relative standard uncertainty (standard deviation/| mean |) of 0.76 μT/45.38 μT = 0.017 on the peak-to-peak first-derivative EPR linewidth. The qualities of the linewidth maps and the effect of computational synthesis of spectral projections were examined. Finally, we obtained the three-dimensional linewidth map of 2H,15N-DCP in a Hs766T tumor-bearing leg in vivo. CONCLUSION We achieved a 46.7% reduction in the acquisition time of 4D spectral-spatial EPR imaging without significantly degrading the image quality. A combination of ART and partial acquisition in three-dimensional raster magnetic field gradient settings in orthogonal coordinates is a novel approach. Our approach to 4D spectral-spatial EPR imaging can be applied to any subject, especially for samples with less variation in one direction.
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Affiliation(s)
- Misa Oba
- Division of Bioengineering and Bioinformatics, Graduate School of Information Science and Technology, Hokkaido University, North 14, West 9, Kita-ku, Sapporo, 060-0814, Japan
| | - Mai Taguchi
- Division of Bioengineering and Bioinformatics, Graduate School of Information Science and Technology, Hokkaido University, North 14, West 9, Kita-ku, Sapporo, 060-0814, Japan
| | - Yohei Kudo
- Division of Bioengineering and Bioinformatics, Graduate School of Information Science and Technology, Hokkaido University, North 14, West 9, Kita-ku, Sapporo, 060-0814, Japan
| | - Koya Yamashita
- Laboratory of Radiation Biology, Graduate School of Veterinary Medicine, Hokkaido University, North 18, West 9, Kita-ku, Sapporo, 060-0818, Japan
| | - Hironobu Yasui
- Laboratory of Radiation Biology, Faculty of Veterinary Medicine, Hokkaido University, North 18, West 9, Kita-ku, Sapporo, 060-0818, Japan
| | - Shingo Matsumoto
- Division of Bioengineering and Bioinformatics, Faculty of Information Science and Technology, Hokkaido University, North 14, West 9, Kita-ku, Sapporo, 060-0814, Japan
| | - Igor A Kirilyuk
- N. N. Vorozhtsov Novosibirsk Institute of Organic Chemistry, 9, Ac. Lavrentieva Ave, Novosibirsk, 630090, Russia
| | - Osamu Inanami
- Laboratory of Radiation Biology, Faculty of Veterinary Medicine, Hokkaido University, North 18, West 9, Kita-ku, Sapporo, 060-0818, Japan
| | - Hiroshi Hirata
- Division of Bioengineering and Bioinformatics, Faculty of Information Science and Technology, Hokkaido University, North 14, West 9, Kita-ku, Sapporo, 060-0814, Japan.
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The Challenges of O 2 Detection in Biological Fluids: Classical Methods and Translation to Clinical Applications. Int J Mol Sci 2022; 23:ijms232415971. [PMID: 36555613 PMCID: PMC9786805 DOI: 10.3390/ijms232415971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/10/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022] Open
Abstract
Dissolved oxygen (DO) is deeply involved in preserving the life of cellular tissues and human beings due to its key role in cellular metabolism: its alterations may reflect important pathophysiological conditions. DO levels are measured to identify pathological conditions, explain pathophysiological mechanisms, and monitor the efficacy of therapeutic approaches. This is particularly relevant when the measurements are performed in vivo but also in contexts where a variety of biological and synthetic media are used, such as ex vivo organ perfusion. A reliable measurement of medium oxygenation ensures a high-quality process. It is crucial to provide a high-accuracy, real-time method for DO quantification, which could be robust towards different medium compositions and temperatures. In fact, biological fluids and synthetic clinical fluids represent a challenging environment where DO interacts with various compounds and can change continuously and dynamically, and further precaution is needed to obtain reliable results. This study aims to present and discuss the main oxygen detection and quantification methods, focusing on the technical needs for their translation to clinical practice. Firstly, we resumed all the main methodologies and advancements concerning dissolved oxygen determination. After identifying the main groups of all the available techniques for DO sensing based on their mechanisms and applicability, we focused on transferring the most promising approaches to a clinical in vivo/ex vivo setting.
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Gertsenshteyn I, Epel B, Ahluwalia A, Kim H, Fan X, Barth E, Zamora M, Markiewicz E, Tsai HM, Sundramoorthy S, Leoni L, Lukens J, Bhuiyan M, Freifelder R, Kucharski A, Giurcanu M, Roman BB, Karczmar G, Kao CM, Halpern H, Chen CT. The optimal 18F-fluoromisonidazole PET threshold to define tumor hypoxia in preclinical squamous cell carcinomas using pO 2 electron paramagnetic resonance imaging as reference truth. Eur J Nucl Med Mol Imaging 2022; 49:4014-4024. [PMID: 35792927 PMCID: PMC9529789 DOI: 10.1007/s00259-022-05889-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 06/19/2022] [Indexed: 11/04/2022]
Abstract
PURPOSE To identify the optimal threshold in 18F-fluoromisonidazole (FMISO) PET images to accurately locate tumor hypoxia by using electron paramagnetic resonance imaging (pO2 EPRI) as ground truth for hypoxia, defined by pO2 [Formula: see text] 10 mmHg. METHODS Tumor hypoxia images in mouse models of SCCVII squamous cell carcinoma (n = 16) were acquired in a hybrid PET/EPRI imaging system 2 h post-injection of FMISO. T2-weighted MRI was used to delineate tumor and muscle tissue. Dynamic contrast enhanced (DCE) MRI parametric images of Ktrans and ve were generated to model tumor vascular properties. Images from PET/EPR/MRI were co-registered and resampled to isotropic 0.5 mm voxel resolution for analysis. PET images were converted to standardized uptake value (SUV) and tumor-to-muscle ratio (TMR) units. FMISO uptake thresholds were evaluated using receiver operating characteristic (ROC) curve analysis to find the optimal FMISO threshold and unit with maximum overall hypoxia similarity (OHS) with pO2 EPRI, where OHS = 1 shows perfect overlap and OHS = 0 shows no overlap. The means of dice similarity coefficient, normalized Hausdorff distance, and accuracy were used to define the OHS. Monotonic relationships between EPRI/PET/DCE-MRI were evaluated with the Spearman correlation coefficient ([Formula: see text]) to quantify association of vasculature on hypoxia imaged with both FMISO PET and pO2 EPRI. RESULTS FMISO PET thresholds to define hypoxia with maximum OHS (both OHS = 0.728 [Formula: see text] 0.2) were SUV [Formula: see text] 1.4 [Formula: see text] SUVmean and SUV [Formula: see text] 0.6 [Formula: see text] SUVmax. Weak-to-moderate correlations (|[Formula: see text]|< 0.70) were observed between PET/EPRI hypoxia images with vascular permeability (Ktrans) or fractional extracellular-extravascular space (ve) from DCE-MRI. CONCLUSION This is the first in vivo comparison of FMISO uptake with pO2 EPRI to identify the optimal FMISO threshold to define tumor hypoxia, which may successfully direct hypoxic tumor boosts in patients, thereby enhancing tumor control.
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Affiliation(s)
- Inna Gertsenshteyn
- Department of Radiology, The University of Chicago, Chicago, IL, USA
- Department of Radiation and Cellular Oncology, The University of Chicago, Chicago, IL, USA
- Center for EPR Imaging In Vivo Physiology, The University of Chicago, Chicago, IL, USA
| | - Boris Epel
- Department of Radiation and Cellular Oncology, The University of Chicago, Chicago, IL, USA
- Center for EPR Imaging In Vivo Physiology, The University of Chicago, Chicago, IL, USA
| | | | - Heejong Kim
- Department of Radiology, The University of Chicago, Chicago, IL, USA
| | - Xiaobing Fan
- Department of Radiology, The University of Chicago, Chicago, IL, USA
- Integrated Small Animal Imaging Research Resource, OSRF, The University of Chicago, Chicago, IL, USA
| | - Eugene Barth
- Department of Radiation and Cellular Oncology, The University of Chicago, Chicago, IL, USA
- Center for EPR Imaging In Vivo Physiology, The University of Chicago, Chicago, IL, USA
| | - Marta Zamora
- Department of Radiology, The University of Chicago, Chicago, IL, USA
- Integrated Small Animal Imaging Research Resource, OSRF, The University of Chicago, Chicago, IL, USA
| | - Erica Markiewicz
- Integrated Small Animal Imaging Research Resource, OSRF, The University of Chicago, Chicago, IL, USA
| | - Hsiu-Ming Tsai
- Integrated Small Animal Imaging Research Resource, OSRF, The University of Chicago, Chicago, IL, USA
| | - Subramanian Sundramoorthy
- Department of Radiation and Cellular Oncology, The University of Chicago, Chicago, IL, USA
- Center for EPR Imaging In Vivo Physiology, The University of Chicago, Chicago, IL, USA
| | - Lara Leoni
- Integrated Small Animal Imaging Research Resource, OSRF, The University of Chicago, Chicago, IL, USA
| | - John Lukens
- Department of Radiation and Cellular Oncology, The University of Chicago, Chicago, IL, USA
- Center for EPR Imaging In Vivo Physiology, The University of Chicago, Chicago, IL, USA
| | - Mohammed Bhuiyan
- Department of Radiology, The University of Chicago, Chicago, IL, USA
| | | | - Anna Kucharski
- Department of Radiology, The University of Chicago, Chicago, IL, USA
| | - Mihai Giurcanu
- Department of Public Health Sciences, The University of Chicago, Chicago, IL, USA
| | - Brian B Roman
- Department of Radiology, The University of Chicago, Chicago, IL, USA
- Integrated Small Animal Imaging Research Resource, OSRF, The University of Chicago, Chicago, IL, USA
| | - Gregory Karczmar
- Department of Radiology, The University of Chicago, Chicago, IL, USA
- Integrated Small Animal Imaging Research Resource, OSRF, The University of Chicago, Chicago, IL, USA
| | - Chien-Min Kao
- Department of Radiology, The University of Chicago, Chicago, IL, USA
- Integrated Small Animal Imaging Research Resource, OSRF, The University of Chicago, Chicago, IL, USA
| | - Howard Halpern
- Department of Radiation and Cellular Oncology, The University of Chicago, Chicago, IL, USA
- Center for EPR Imaging In Vivo Physiology, The University of Chicago, Chicago, IL, USA
| | - Chin-Tu Chen
- Department of Radiology, The University of Chicago, Chicago, IL, USA.
- Integrated Small Animal Imaging Research Resource, OSRF, The University of Chicago, Chicago, IL, USA.
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Subasinghe SAAS, Pautler RG, Samee MAH, Yustein JT, Allen MJ. Dual-Mode Tumor Imaging Using Probes That Are Responsive to Hypoxia-Induced Pathological Conditions. BIOSENSORS 2022; 12:bios12070478. [PMID: 35884281 PMCID: PMC9313010 DOI: 10.3390/bios12070478] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 06/22/2022] [Accepted: 06/26/2022] [Indexed: 05/02/2023]
Abstract
Hypoxia in solid tumors is associated with poor prognosis, increased aggressiveness, and strong resistance to therapeutics, making accurate monitoring of hypoxia important. Several imaging modalities have been used to study hypoxia, but each modality has inherent limitations. The use of a second modality can compensate for the limitations and validate the results of any single imaging modality. In this review, we describe dual-mode imaging systems for the detection of hypoxia that have been reported since the start of the 21st century. First, we provide a brief overview of the hallmarks of hypoxia used for imaging and the imaging modalities used to detect hypoxia, including optical imaging, ultrasound imaging, photoacoustic imaging, single-photon emission tomography, X-ray computed tomography, positron emission tomography, Cerenkov radiation energy transfer imaging, magnetic resonance imaging, electron paramagnetic resonance imaging, magnetic particle imaging, and surface-enhanced Raman spectroscopy, and mass spectrometric imaging. These overviews are followed by examples of hypoxia-relevant imaging using a mixture of probes for complementary single-mode imaging techniques. Then, we describe dual-mode molecular switches that are responsive in multiple imaging modalities to at least one hypoxia-induced pathological change. Finally, we offer future perspectives toward dual-mode imaging of hypoxia and hypoxia-induced pathophysiological changes in tumor microenvironments.
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Affiliation(s)
| | - Robia G. Pautler
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA; (R.G.P.); (M.A.H.S.)
| | - Md. Abul Hassan Samee
- Department of Integrative Physiology, Baylor College of Medicine, Houston, TX 77030, USA; (R.G.P.); (M.A.H.S.)
| | - Jason T. Yustein
- Integrative Molecular and Biomedical Sciences and the Department of Pediatrics in the Texas Children’s Cancer and Hematology Centers and The Faris D. Virani Ewing Sarcoma Center, Baylor College of Medicine, Houston, TX 77030, USA;
| | - Matthew J. Allen
- Department of Chemistry, Wayne State University, 5101 Cass Avenue, Detroit, MI 48202, USA;
- Correspondence:
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Paudyal R, Grkovski M, Oh JH, Schöder H, Nunez DA, Hatzoglou V, Deasy JO, Humm JL, Lee NY, Shukla-Dave A. Application of Community Detection Algorithm to Investigate the Correlation between Imaging Biomarkers of Tumor Metabolism, Hypoxia, Cellularity, and Perfusion for Precision Radiotherapy in Head and Neck Squamous Cell Carcinomas. Cancers (Basel) 2021; 13:3908. [PMID: 34359810 PMCID: PMC8345739 DOI: 10.3390/cancers13153908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 07/26/2021] [Accepted: 07/30/2021] [Indexed: 11/17/2022] Open
Abstract
The present study aimed to investigate the correlation at pre-treatment (TX) between quantitative metrics derived from multimodality imaging (MMI), including 18F-FDG-PET/CT, 18F-FMISO-PET/CT, DW- and DCE-MRI, using a community detection algorithm (CDA) in head and neck squamous cell carcinoma (HNSCC) patients. Twenty-three HNSCC patients with 27 metastatic lymph nodes underwent a total of 69 MMI exams at pre-TX. Correlations among quantitative metrics derived from FDG-PET/CT (SUL), FMSIO-PET/CT (K1, k3, TBR, and DV), DW-MRI (ADC, IVIM [D, D*, and f]), and FXR DCE-MRI [Ktrans, ve, and τi]) were investigated using the CDA based on a "spin-glass model" coupled with the Spearman's rank, ρ, analysis. Mean MRI T2 weighted tumor volumes and SULmean values were moderately positively correlated (ρ = 0.48, p = 0.01). ADC and D exhibited a moderate negative correlation with SULmean (ρ ≤ -0.42, p < 0.03 for both). K1 and Ktrans were positively correlated (ρ = 0.48, p = 0.01). In contrast, Ktrans and k3max were negatively correlated (ρ = -0.41, p = 0.03). CDA revealed four communities for 16 metrics interconnected with 33 edges in the network. DV, Ktrans, and K1 had 8, 7, and 6 edges in the network, respectively. After validation in a larger population, the CDA approach may aid in identifying useful biomarkers for developing individual patient care in HNSCC.
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Affiliation(s)
- Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - Milan Grkovski
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - Jung Hun Oh
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - Heiko Schöder
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (H.S.); (V.H.)
| | - David Aramburu Nunez
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - Vaios Hatzoglou
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (H.S.); (V.H.)
| | - Joseph O. Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - John L. Humm
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
| | - Nancy Y. Lee
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA;
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (R.P.); (M.G.); (J.H.O.); (D.A.N.); (J.O.D.); (J.L.H.)
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; (H.S.); (V.H.)
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