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Malmberg MA, Odéen H, Hofstetter LW, Hadley JR, Parker DL. Validation of single reference variable flip angle (SR-VFA) dynamic T 1 mapping with T 2 * correction using a novel rotating phantom. Magn Reson Med 2024; 91:1419-1433. [PMID: 38115639 PMCID: PMC10872756 DOI: 10.1002/mrm.29944] [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: 06/27/2023] [Revised: 10/12/2023] [Accepted: 11/09/2023] [Indexed: 12/21/2023]
Abstract
PURPOSE To validate single reference variable flip angle (SR-VFA) dynamic T1 mapping with and without T2 * correction against inversion recovery (IR) T1 measurements. METHODS A custom cylindrical phantom with three concentric compartments was filled with variably doped agar to produce a smooth spatial gradient of the T1 relaxation rate as a function of angle across each compartment. IR T1 , VFA T1 , and B1 + measurements were made on the phantom before rotation, and multi-echo stack-of-radial dynamic images were acquired during rotation via an MRI-compatible motor. B1 + -corrected SR-VFA and SR-VFA-T2 * T1 maps were computed from the sliding window reconstructed images and compared against rotationally registered IR and VFA T1 maps to determine the percentage error. RESULTS Both VFA and SR-VFA-T2 * T1 maps fell within 10% of IR T1 measurements for a low rotational speed, with a mean accuracy of 2.3% ± 2.6% and 2.8% ± 2.6%, respectively. Increasing rotational speed was found to decrease the accuracy due to increasing temporal smoothing over ranges where the T1 change had a nonconstant slope. SR-VFA T1 mapping was found to have similar accuracy as the SR-VFA-T2 * and VFA methods at low TEs (˜<2 ms), whereas accuracy degraded strongly with later TEs. T2 * correction of the SR-VFA T1 maps was found to consistently improve accuracy and precision, especially at later TEs. CONCLUSION SR-VFA-T2 * dynamic T1 mapping was found to be accurate against reference IR T1 measurements within 10% in an agar phantom. Further validation is needed in mixed fat-water phantoms and in vivo.
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Affiliation(s)
- Michael A. Malmberg
- Department of Bioengineering, University of Utah, Salt Lake City, UT, USA
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Henrik Odéen
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | | | - J. Rock Hadley
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Dennis L. Parker
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
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Zou M, Zhang B, Shi L, Mao H, Huang Y, Zhao Z. Correlation of MRI quantitative perfusion parameters with EGFR, VEGF and EGFR gene mutations in non-small cell cancer. Sci Rep 2024; 14:4447. [PMID: 38396128 PMCID: PMC10891079 DOI: 10.1038/s41598-024-55033-5] [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: 11/05/2023] [Accepted: 02/19/2024] [Indexed: 02/25/2024] Open
Abstract
To explore the relationship between quantitative perfusion histogram parameters of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) with the expression of tumor tissue epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF) and EGFR gene mutations in non-small cell lung cancer (NSCLC). A total of 44 consecutive patients with known NSCLC were recruited from March 2018 to August 2021. Histogram parameters (mean, uniformity, skewness, energy, kurtosis, entropy, percentile) of each (Ktrans, Kep, Ve, Vp, Fp) were obtained by Omni Kinetics software. Immunohistochemistry staining was used in the detection of the expression of VEGF and EGFR protein, and the mutation of EGFR gene was detected by PCR. Corresponding statistical test was performed to compare the parameters and protein expression between squamous cell carcinoma (SCC) and adenocarcinoma (AC), as well as EGFR mutations and wild-type. Correlation analysis was used to evaluate the correlation between parameters with the expression of VEGF and EGFR protein. Fp (skewness, kurtosis, energy) were statistically significant between SCC and AC, and the area under the ROC curve were 0.733, 0.700 and 0.675, respectively. The expression of VEGF in AC was higher than in SCC. Fp (skewness, kurtosis, energy) were negatively correlated with VEGF (r = - 0.527, - 0.428, - 0.342); Ktrans (Q50) was positively correlated with VEGF (r = 0.32); Kep (energy), Ktrans (skewness, kurtosis) were positively correlated with EGFR (r = 0.622, r = 0.375, 0.358), some histogram parameters of Kep, Ktrans (uniformity, entropy) and Ve (kurtosis) were negatively correlated with EGFR (r = - 0.312 to - 0.644). Some perfusion histogram parameters were statistically significant between EGFR mutations and wild-type, they were higher in wild-type than mutated (P < 0.05). Quantitative perfusion histogram parameters of DCE-MRI have a certain value in the differential diagnosis of NSCLC, which have the potential to non-invasively evaluate the expression of cell signaling pathway-related protein.
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Affiliation(s)
- Mingyue Zou
- Department of Radiology, The Cancer Hospital of the University of Chinese Academy of Science (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China
- Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Bingqian Zhang
- Department of Radiology, The Cancer Hospital of the University of Chinese Academy of Science (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China
- Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Lei Shi
- Department of Radiology, The Cancer Hospital of the University of Chinese Academy of Science (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, China
- Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Haijia Mao
- Department of Radiology, Shaoxing People's Hospital, Shaoxing, Zhejiang, China
| | - Yanan Huang
- Department of Radiology, Shaoxing People's Hospital, Shaoxing, Zhejiang, China
| | - Zhenhua Zhao
- Department of Radiology, Shaoxing People's Hospital, Shaoxing, Zhejiang, China.
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Boeke S, Winter RM, Leibfarth S, Krueger MA, Bowden G, Cotton J, Pichler BJ, Zips D, Thorwarth D. Machine learning identifies multi-parametric functional PET/MR imaging cluster to predict radiation resistance in preclinical head and neck cancer models. Eur J Nucl Med Mol Imaging 2023; 50:3084-3096. [PMID: 37148296 PMCID: PMC10382355 DOI: 10.1007/s00259-023-06254-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 04/25/2023] [Indexed: 05/08/2023]
Abstract
PURPOSE Tumor hypoxia and other microenvironmental factors are key determinants of treatment resistance. Hypoxia positron emission tomography (PET) and functional magnetic resonance imaging (MRI) are established prognostic imaging modalities to identify radiation resistance in head-and-neck cancer (HNC). The aim of this preclinical study was to develop a multi-parametric imaging parameter specifically for focal radiotherapy (RT) dose escalation using HNC xenografts of different radiation sensitivities. METHODS A total of eight human HNC xenograft models were implanted into 68 immunodeficient mice. Combined PET/MRI using dynamic [18F]-fluoromisonidazole (FMISO) hypoxia PET, diffusion-weighted (DW), and dynamic contrast-enhanced MRI was carried out before and after fractionated RT (10 × 2 Gy). Imaging data were analyzed on voxel-basis using principal component (PC) analysis for dynamic data and apparent diffusion coefficients (ADCs) for DW-MRI. A data- and hypothesis-driven machine learning model was trained to identify clusters of high-risk subvolumes (HRSs) from multi-dimensional (1-5D) pre-clinical imaging data before and after RT. The stratification potential of each 1D to 5D model with respect to radiation sensitivity was evaluated using Cohen's d-score and compared to classical features such as mean/peak/maximum standardized uptake values (SUVmean/peak/max) and tumor-to-muscle-ratios (TMRpeak/max) as well as minimum/valley/maximum/mean ADC. RESULTS Complete 5D imaging data were available for 42 animals. The final preclinical model for HRS identification at baseline yielding the highest stratification potential was defined in 3D imaging space based on ADC and two FMISO PCs ([Formula: see text]). In 1D imaging space, only clusters of ADC revealed significant stratification potential ([Formula: see text]). Among all classical features, only ADCvalley showed significant correlation to radiation resistance ([Formula: see text]). After 2 weeks of RT, FMISO_c1 showed significant correlation to radiation resistance ([Formula: see text]). CONCLUSION A quantitative imaging metric was described in a preclinical study indicating that radiation-resistant subvolumes in HNC may be detected by clusters of ADC and FMISO using combined PET/MRI which are potential targets for future functional image-guided RT dose-painting approaches and require clinical validation.
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Affiliation(s)
- Simon Boeke
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - René M Winter
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
| | - Sara Leibfarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
| | - Marcel A Krueger
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Gregory Bowden
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Jonathan Cotton
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
| | - Bernd J Pichler
- Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, University of Tübingen, Tübingen, Germany
- Cluster of Excellence iFIT (EXC 2180) "Image Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Daniel Zips
- Department of Radiation Oncology, University of Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniela Thorwarth
- German Cancer Consortium (DKTK), partner site Tübingen, and German Cancer Research Center (DKFZ), Heidelberg, Germany.
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany.
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Gouel P, Decazes P, Vera P, Gardin I, Thureau S, Bohn P. Advances in PET and MRI imaging of tumor hypoxia. Front Med (Lausanne) 2023; 10:1055062. [PMID: 36844199 PMCID: PMC9947663 DOI: 10.3389/fmed.2023.1055062] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 01/30/2023] [Indexed: 02/11/2023] Open
Abstract
Tumor hypoxia is a complex and evolving phenomenon both in time and space. Molecular imaging allows to approach these variations, but the tracers used have their own limitations. PET imaging has the disadvantage of low resolution and must take into account molecular biodistribution, but has the advantage of high targeting accuracy. The relationship between the signal in MRI imaging and oxygen is complex but hopefully it would lead to the detection of truly oxygen-depleted tissue. Different ways of imaging hypoxia are discussed in this review, with nuclear medicine tracers such as [18F]-FMISO, [18F]-FAZA, or [64Cu]-ATSM but also with MRI techniques such as perfusion imaging, diffusion MRI or oxygen-enhanced MRI. Hypoxia is a pejorative factor regarding aggressiveness, tumor dissemination and resistance to treatments. Therefore, having accurate tools is particularly important.
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Affiliation(s)
- Pierrick Gouel
- Département d’Imagerie, Centre Henri Becquerel, Rouen, France,QuantIF-LITIS, EA 4108, IRIB, Université de Rouen, Rouen, France
| | - Pierre Decazes
- Département d’Imagerie, Centre Henri Becquerel, Rouen, France,QuantIF-LITIS, EA 4108, IRIB, Université de Rouen, Rouen, France
| | - Pierre Vera
- Département d’Imagerie, Centre Henri Becquerel, Rouen, France,QuantIF-LITIS, EA 4108, IRIB, Université de Rouen, Rouen, France
| | - Isabelle Gardin
- Département d’Imagerie, Centre Henri Becquerel, Rouen, France,QuantIF-LITIS, EA 4108, IRIB, Université de Rouen, Rouen, France
| | - Sébastien Thureau
- QuantIF-LITIS, EA 4108, IRIB, Université de Rouen, Rouen, France,Département de Radiothérapie, Centre Henri Becquerel, Rouen, France
| | - Pierre Bohn
- Département d’Imagerie, Centre Henri Becquerel, Rouen, France,QuantIF-LITIS, EA 4108, IRIB, Université de Rouen, Rouen, France,*Correspondence: Pierre Bohn,
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Tomanic T, Rogelj L, Stergar J, Markelc B, Bozic T, Brezar SK, Sersa G, Milanic M. Estimating quantitative physiological and morphological tissue parameters of murine tumor models using hyperspectral imaging and optical profilometry. JOURNAL OF BIOPHOTONICS 2023; 16:e202200181. [PMID: 36054067 DOI: 10.1002/jbio.202200181] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2022] [Revised: 07/27/2022] [Accepted: 08/05/2022] [Indexed: 06/15/2023]
Abstract
Understanding tumors and their microenvironment are essential for successful and accurate disease diagnosis. Tissue physiology and morphology are altered in tumors compared to healthy tissues, and there is a need to monitor tumors and their surrounding tissues, including blood vessels, non-invasively. This preliminary study utilizes a multimodal optical imaging system combining hyperspectral imaging (HSI) and three-dimensional (3D) optical profilometry (OP) to capture hyperspectral images and surface shapes of subcutaneously grown murine tumor models. Hyperspectral images are corrected with 3D OP data and analyzed using the inverse-adding doubling (IAD) method to extract tissue properties such as melanin volume fraction and oxygenation. Blood vessels are segmented using the B-COSFIRE algorithm from oxygenation maps. From 3D OP data, tumor volumes are calculated and compared to manual measurements using a vernier caliper. Results show that tumors can be distinguished from healthy tissue based on most extracted tissue parameters ( p < 0.05 ). Furthermore, blood oxygenation is 50% higher within the blood vessels than in the surrounding tissue, and tumor volumes calculated using 3D OP agree within 26% with manual measurements using a vernier caliper. Results suggest that combining HSI and OP could provide relevant quantitative information about tumors and improve the disease diagnosis.
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Affiliation(s)
- Tadej Tomanic
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
| | - Luka Rogelj
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
| | - Jost Stergar
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
- Jozef Stefan Institute, Ljubljana, Slovenia
| | - Bostjan Markelc
- Department of Experimental Oncology, Institute of Oncology Ljubljana, Ljubljana, Slovenia
- Faculty of Health Sciences, University of Ljubljana, Ljubljana, Slovenia
| | - Tim Bozic
- Department of Experimental Oncology, Institute of Oncology Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Simona Kranjc Brezar
- Department of Experimental Oncology, Institute of Oncology Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Gregor Sersa
- Department of Experimental Oncology, Institute of Oncology Ljubljana, Ljubljana, Slovenia
- Faculty of Health Sciences, University of Ljubljana, Ljubljana, Slovenia
| | - Matija Milanic
- Faculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia
- Jozef Stefan Institute, Ljubljana, Slovenia
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6
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Bluemke E, Bertrand A, Chu KY, Syed N, Murchison AG, Cooke R, Greenhalgh T, Burns B, Craig M, Taylor N, Shah K, Gleeson F, Bulte D. Oxygen-enhanced MRI and radiotherapy in patients with oropharyngeal squamous cell carcinoma. Clin Transl Radiat Oncol 2022; 39:100563. [PMID: 36655119 PMCID: PMC9841018 DOI: 10.1016/j.ctro.2022.100563] [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: 03/29/2022] [Revised: 12/08/2022] [Accepted: 12/14/2022] [Indexed: 12/23/2022] Open
Abstract
Background and purpose This study aimed to assess the role of T1 mapping and oxygen-enhanced MRI in patients undergoing radical dose radiotherapy for HPV positive oropharyngeal cancer, which has not yet been examined in an OE-MRI study. Materials and methods Variable Flip Angle T1 maps were acquired on a 3T MRI scanner while patients (n = 12) breathed air and/or 100 % oxygen, before and after fraction 10 of the planned 30 fractions of chemoradiotherapy ('visit 1' and 'visit 2', respectively). The analysis aimed to assess to what extent (1) native R1 relates to patient outcome; (2) OE-MRI response relates to patient outcome; (3) changes in mean R1 before and after radiotherapy related to clinical outcome in patients with oropharyngeal squamous cell carcinoma. Results Due to the radiotherapy being largely successful, the sample sizes of non-responder groups were small, and therefore it was not possible to properly assess the predictive nature of OE-MRI. The tumour R1 increased in some patients while decreasing in others, in a pattern that was overall consistent with the underlying OE-MRI theory and previously reported tumour OE-MRI responses. In addition, we discuss some practical challenges faced when integrating this technique into a clinical trial, with the aim that sharing this is helpful to researchers planning to use OE-MRI in future clinical studies. Conclusion Altogether, these results suggest that further clinical OE-MRI studies to assess hypoxia and radiotherapy response are worth pursuing, and that there is important work to be done to improve the robustness of the OE-MRI technique in human applications in order for it to be useful as a widespread clinical technique.
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Affiliation(s)
- Emma Bluemke
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK,Corresponding author at: Old Road Campus Research Building, University of Oxford, Headington, Oxford OX3 7DQ, UK.
| | - Ambre Bertrand
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK
| | - Kwun-Ye Chu
- MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, UK,Radiotherapy Department, Oxford University Hospitals NHS Foundation Trust, UK
| | - Nigar Syed
- MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, UK
| | - Andrew G. Murchison
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, UK
| | - Rosie Cooke
- MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, UK,Radiotherapy Department, Oxford University Hospitals NHS Foundation Trust, UK
| | - Tessa Greenhalgh
- MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, UK,University Hospital Southampton NHS Foundation Trust, UK
| | | | | | - Nia Taylor
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, UK
| | - Ketan Shah
- MRC Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, UK,Radiotherapy Department, Oxford University Hospitals NHS Foundation Trust, UK
| | - Fergus Gleeson
- Department of Radiology, Oxford University Hospitals NHS Foundation Trust, UK
| | - Daniel Bulte
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, UK
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7
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Drzał A, Jasiński K, Gonet M, Kowolik E, Bartel Ż, Elas M. MRI and US imaging reveal evolution of spatial heterogeneity of murine tumor vasculature. Magn Reson Imaging 2022; 92:33-44. [DOI: 10.1016/j.mri.2022.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/25/2022] [Accepted: 06/02/2022] [Indexed: 11/15/2022]
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Using Variable Flip Angle (VFA) and Modified Look-Locker Inversion Recovery (MOLLI) T1 mapping in clinical OE-MRI. Magn Reson Imaging 2022; 89:92-99. [PMID: 35341905 DOI: 10.1016/j.mri.2022.03.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 03/16/2022] [Accepted: 03/19/2022] [Indexed: 11/20/2022]
Abstract
BACKGROUND AND PURPOSE The imaging technique known as Oxygen-Enhanced MRI is under development as a noninvasive technique for imaging hypoxia in tumours and pulmonary diseases. While promising results have been shown in preclinical experiments, clinical studies have mentioned experiencing difficulties with patient motion, image registration, and the limitations of single-slice images compared to 3D volumes. As clinical studies begin to assess feasibility of using OE-MRI in patients, it is important for researchers to communicate about the practical challenges experienced when using OE-MRI on patients to help the technique advance. MATERIALS AND METHODS We report on our experience with using two types of T1 mapping (MOLLI and VFA) for a recently completed OE-MRI clinical study on oropharyngeal squamous cell carcinoma. RESULTS We report: (1) the artefacts and practical difficulties encountered in this study; (2) the difference in estimated T1 from each method used - the VFA T1 estimation was higher than the MOLLI estimation by 27% on average; (3) the standard deviation within the tumour ROIs - there was no significant difference in the standard deviation seen within the tumour ROIs from the VFA versus MOLLI; and (4) the OE-MRI response collected from either method. Lastly, we collated the MRI acquisition details from over 45 relevant manuscripts as a convenient reference for researchers planning future studies. CONCLUSION We have reported our practical experience from an OE-MRI clinical study, with the aim that sharing this is helpful to researchers planning future studies. In this study, VFA was a more useful technique for using OE-MRI in tumours than MOLLI T1 mapping.
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9
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Raghunand N, Gatenby RA. Bridging Spatial Scales From Radiographic Images to Cellular and Molecular Properties in Cancers. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00053-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
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10
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Bendinger AL, Peschke P, Peter J, Debus J, Karger CP, Glowa C. High Doses of Photons and Carbon Ions Comparably Increase Vascular Permeability in R3327-HI Prostate Tumors: A Dynamic Contrast-Enhanced MRI Study. Radiat Res 2020; 194:465-475. [PMID: 33045073 DOI: 10.1667/rade-20-00112.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 09/04/2020] [Indexed: 11/03/2022]
Abstract
Carbon- (12C-) ion radiotherapy exhibits enhanced biological effectiveness compared to photon radiotherapy, however, the contribution of its interaction with the vasculature remains debatable. The effect of high-dose 12C-ion and photon irradiation on vascular permeability in moderately differentiated rat prostate tumors was compared using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Syngeneic R3327-HI rat prostate tumors were irradiated with a single dose of either 18 or 37 Gy 12C ions, or 37 or 75 Gy 6-MV photons (sub-curative and curative dose levels, respectively). DCE-MRI was performed one day prior to and 3, 7, 14 and 21 days postirradiation. Voxel-based tumor concentration-time curves were clustered based on their curve shape and treatment response was assessed as the longitudinal changes in the relative abundance per cluster. Radiation-induced vascular damage and increased permeability occurred at day 7 postirradiation for all treatment groups except for the 75 Gy photon-irradiated group, where the onset of vascular damage was delayed until day 14. No differences between irradiation modalities were found. Therefore, early vascular damage cannot explain the higher effectiveness of 12C ions relative to photons in terms of local tumor control for this moderately differentiated prostate tumor and the applied single high doses.
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Affiliation(s)
- Alina L Bendinger
- Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Biosciences, University of Heidelberg, Heidelberg, Germany
| | - Peter Peschke
- Heidelberg Institute for Radiation Oncology (HIRO) and National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany.,Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jörg Peter
- Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jürgen Debus
- Clinical Cooperation Unit, Radiation Therapy, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Heidelberg Institute for Radiation Oncology (HIRO) and National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany.,Department of Radiation Oncology and Radiotherapy, University Hospital Heidelberg, Heidelberg, Germany
| | - Christian P Karger
- Heidelberg Institute for Radiation Oncology (HIRO) and National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany.,Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Christin Glowa
- Heidelberg Institute for Radiation Oncology (HIRO) and National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany.,Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology and Radiotherapy, University Hospital Heidelberg, Heidelberg, Germany
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11
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Exploring MRI based radiomics analysis of intratumoral spatial heterogeneity in locally advanced nasopharyngeal carcinoma treated with intensity modulated radiotherapy. PLoS One 2020; 15:e0240043. [PMID: 33017440 PMCID: PMC7535039 DOI: 10.1371/journal.pone.0240043] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Accepted: 09/18/2020] [Indexed: 01/28/2023] Open
Abstract
Background We hypothesized that spatial heterogeneity exists between recurrent and non-recurrent regions within a tumor. The aim of this study was to determine if there is a difference between radiomics features derived from recurrent versus non recurrent regions within the tumor based on pre-treatment MRI. Methods A total of 14 T4NxM0 NPC patients with histologically proven “in field” recurrence in the post nasal space following curative intent IMRT were included in this study. Pretreatment MRI were co-registered with MRI at the time of recurrence for the delineation of gross tumor volume at diagnosis(GTV) and at recurrence(GTVr). A total of 7 histogram features and 40 texture features were computed from the recurrent(GTVr) and non-recurrent region(GTV-GTVr). Paired t-tests and Wilcoxon signed-rank tests were carried out on the 47 quantified radiomics features. Results A total of 7 features were significantly different between recurrent and non-recurrent regions. Other than the variance from intensity-based histogram, the remaining six significant features were either from the gray-level size zone matrix (GLSZM) or the neighbourhood gray-tone difference matrix (NGTDM). Conclusions The radiomic features extracted from pre-treatment MRI can potentially reflect the difference between recurrent and non-recurrent regions within a tumor and has a potential role in pre-treatment identification of intra-tumoral radio-resistance for selective dose escalation.
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12
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Syed AK, Whisenant JG, Barnes SL, Sorace AG, Yankeelov TE. Multiparametric Analysis of Longitudinal Quantitative MRI data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer. Cancers (Basel) 2020; 12:cancers12061682. [PMID: 32599906 PMCID: PMC7352623 DOI: 10.3390/cancers12061682] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 06/20/2020] [Accepted: 06/22/2020] [Indexed: 12/11/2022] Open
Abstract
This study identifies physiological tumor habitats from quantitative magnetic resonance imaging (MRI) data and evaluates their alterations in response to therapy. Two models of breast cancer (BT-474 and MDA-MB-231) were imaged longitudinally with diffusion-weighted MRI and dynamic contrast-enhanced MRI to quantify tumor cellularity and vascularity, respectively, during treatment with trastuzumab or albumin-bound paclitaxel. Tumors were stained for anti-CD31, anti-Ki-67, and H&E. Imaging and histology data were clustered to identify tumor habitats and percent tumor volume (MRI) or area (histology) of each habitat was quantified. Histological habitats were correlated with MRI habitats. Clustering of both the MRI and histology data yielded three clusters: high-vascularity high-cellularity (HV-HC), low-vascularity high-cellularity (LV-HC), and low-vascularity low-cellularity (LV-LC). At day 4, BT-474 tumors treated with trastuzumab showed a decrease in LV-HC (p = 0.03) and increase in HV-HC (p = 0.03) percent tumor volume compared to control. MDA-MB-231 tumors treated with low-dose albumin-bound paclitaxel showed a longitudinal decrease in LV-HC percent tumor volume at day 3 (p = 0.01). Positive correlations were found between histological and imaging-derived habitats: HV-HC (BT-474: p = 0.03), LV-HC (MDA-MB-231: p = 0.04), LV-LC (BT-474: p = 0.04; MDA-MB-231: p < 0.01). Physiologically distinct tumor habitats associated with therapeutic response were identified with MRI and histology data in preclinical models of breast cancer.
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Affiliation(s)
- Anum K Syed
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA
| | - Jennifer G Whisenant
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Stephanie L Barnes
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Anna G Sorace
- Department of Biomedical Engineering, The University of Alabama at Birmingham, Birmingham, AL 35294, USA
- Department of Radiology, The University of Alabama at Birmingham, Birmingham, AL 35294, USA
- O'Neal Comprehensive Cancer Center, The University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Thomas E Yankeelov
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Diagnostic Medicine, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Oncology, The University of Texas at Austin, Austin, TX 78712, USA
- Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA
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13
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An Automated Segmentation Pipeline for Intratumoural Regions in Animal Xenografts Using Machine Learning and Saturation Transfer MRI. Sci Rep 2020; 10:8063. [PMID: 32415137 PMCID: PMC7228927 DOI: 10.1038/s41598-020-64912-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 04/24/2020] [Indexed: 11/16/2022] Open
Abstract
Saturation transfer MRI can be useful in the characterization of different tumour types. It is sensitive to tumour metabolism, microstructure, and microenvironment. This study aimed to use saturation transfer to differentiate between intratumoural regions, demarcate tumour boundaries, and reduce data acquisition times by identifying the imaging scheme with the most impact on segmentation accuracy. Saturation transfer-weighted images were acquired over a wide range of saturation amplitudes and frequency offsets along with T1 and T2 maps for 34 tumour xenografts in mice. Independent component analysis and Gaussian mixture modelling were used to segment the images and identify intratumoural regions. Comparison between the segmented regions and histopathology indicated five distinct clusters: three corresponding to intratumoural regions (active tumour, necrosis/apoptosis, and blood/edema) and two extratumoural (muscle and a mix of muscle and connective tissue). The fraction of tumour voxels segmented as necrosis/apoptosis quantitatively matched those calculated from TUNEL histopathological assays. An optimal protocol was identified providing reasonable qualitative agreement between MRI and histopathology and consisting of T1 and T2 maps and 22 magnetization transfer (MT)-weighted images. A three-image subset was identified that resulted in a greater than 90% match in positive and negative predictive value of tumour voxels compared to those found using the entire 24-image dataset. The proposed algorithm can potentially be used to develop a robust intratumoural segmentation method.
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14
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Yang DM, Arai TJ, Campbell JW, Gerberich JL, Zhou H, Mason RP. Oxygen-sensitive MRI assessment of tumor response to hypoxic gas breathing challenge. NMR IN BIOMEDICINE 2019; 32:e4101. [PMID: 31062902 PMCID: PMC6581571 DOI: 10.1002/nbm.4101] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Revised: 02/16/2019] [Accepted: 03/08/2019] [Indexed: 06/09/2023]
Abstract
Oxygen-sensitive MRI has been extensively used to investigate tumor oxygenation based on the response (R2 * and/or R1 ) to a gas breathing challenge. Most studies have reported response to hyperoxic gas indicating potential biomarkers of hypoxia. Few studies have examined hypoxic gas breathing and we have now evaluated acute dynamic changes in rat breast tumors. Rats bearing syngeneic subcutaneous (n = 15) or orthotopic (n = 7) 13762NF breast tumors were exposed to a 16% O2 gas breathing challenge and monitored using blood oxygen level dependent (BOLD) R2 * and tissue oxygen level dependent (TOLD) T1 -weighted measurements at 4.7 T. As a control, we used a traditional hyperoxic gas breathing challenge with 100% O2 on a subset of the subcutaneous tumor bearing rats (n = 6). Tumor subregions identified as responsive on the basis of R2 * dynamics coincided with the viable tumor area as judged by subsequent H&E staining. As expected, R2 * decreased and T1 -weighted signal increased in response to 100% O2 breathing challenge. Meanwhile, 16% O2 breathing elicited an increase in R2 *, but divergent response (increase or decrease) in T1 -weighted signal. The T1 -weighted signal increase may signify a dominating BOLD effect triggered by 16% O2 in the relatively more hypoxic tumors, whereby the influence of increased paramagnetic deoxyhemoglobin outweighs decreased pO2 . The results emphasize the importance of combined BOLD and TOLD measurements for the correct interpretation of tumor oxygenation properties.
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Affiliation(s)
- Donghan M Yang
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Tatsuya J Arai
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas, USA
| | - James W Campbell
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas, USA
| | | | - Heling Zhou
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Ralph P Mason
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas, USA
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15
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Jardim-Perassi BV, Huang S, Dominguez-Viqueira W, Poleszczuk J, Budzevich MM, Abdalah MA, Pillai SR, Ruiz E, Bui MM, Zuccari DAPC, Gillies RJ, Martinez GV. Multiparametric MRI and Coregistered Histology Identify Tumor Habitats in Breast Cancer Mouse Models. Cancer Res 2019; 79:3952-3964. [PMID: 31186232 DOI: 10.1158/0008-5472.can-19-0213] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Revised: 04/23/2019] [Accepted: 06/05/2019] [Indexed: 12/31/2022]
Abstract
It is well-recognized that solid tumors are genomically, anatomically, and physiologically heterogeneous. In general, more heterogeneous tumors have poorer outcomes, likely due to the increased probability of harboring therapy-resistant cells and regions. It is hypothesized that the genomic and physiologic heterogeneity are related, because physiologically distinct regions will exert variable selection pressures leading to the outgrowth of clones with variable genomic/proteomic profiles. To investigate this, methods must be in place to interrogate and define, at the microscopic scale, the cytotypes that exist within physiologically distinct subregions ("habitats") that are present at mesoscopic scales. MRI provides a noninvasive approach to interrogate physiologically distinct local environments, due to the biophysical principles that govern MRI signal generation. Here, we interrogate different physiologic parameters, such as perfusion, cell density, and edema, using multiparametric MRI (mpMRI). Signals from six different acquisition schema were combined voxel-by-voxel into four clusters identified using a Gaussian mixture model. These were compared with histologic and IHC characterizations of sections that were coregistered using MRI-guided 3D printed tumor molds. Specifically, we identified a specific set of MRI parameters to classify viable-normoxic, viable-hypoxic, nonviable-hypoxic, and nonviable-normoxic tissue types within orthotopic 4T1 and MDA-MB-231 breast tumors. This is the first coregistered study to show that mpMRI can be used to define physiologically distinct tumor habitats within breast tumor models. SIGNIFICANCE: This study demonstrates that noninvasive imaging metrics can be used to distinguish subregions within heterogeneous tumors with histopathologic correlation.
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Affiliation(s)
- Bruna V Jardim-Perassi
- Department of Cancer Physiology, Moffitt Cancer Center, Tampa, Florida.,Faculdade de Medicina de Sao Jose do Rio Preto, Sao Jose do Rio Preto, Brazil
| | - Suning Huang
- Department of Cancer Physiology, Moffitt Cancer Center, Tampa, Florida.,Guangxi Tumor Hospital, Nanning Guangxi, China
| | | | - Jan Poleszczuk
- Department of Integrative Mathematical Oncology, Moffitt Cancer Center, Tampa, Florida
| | | | - Mahmoud A Abdalah
- Image Response Assessment Team, Moffitt Cancer Center, Tampa, Florida
| | - Smitha R Pillai
- Department of Cancer Physiology, Moffitt Cancer Center, Tampa, Florida
| | - Epifanio Ruiz
- Small Animal Imaging Laboratory, Moffitt Cancer Center, Tampa, Florida
| | - Marilyn M Bui
- Department of Anatomic Pathology, Moffitt Cancer Center, Tampa, Florida
| | | | - Robert J Gillies
- Department of Cancer Physiology, Moffitt Cancer Center, Tampa, Florida.
| | - Gary V Martinez
- Small Animal Imaging Laboratory, Moffitt Cancer Center, Tampa, Florida.
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16
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Jalnefjord O, Montelius M, Arvidsson J, Forssell-Aronsson E, Starck G, Ljungberg M. Data-driven identification of tumor subregions based on intravoxel incoherent motion reveals association with proliferative activity. Magn Reson Med 2019; 82:1480-1490. [PMID: 31081969 PMCID: PMC6767386 DOI: 10.1002/mrm.27820] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 04/29/2019] [Accepted: 04/29/2019] [Indexed: 12/16/2022]
Abstract
PURPOSE Intravoxel incoherent motion (IVIM) analysis gives information on tissue diffusion and perfusion and may thus have a potential for e.g. tumor tissue characterization. This work aims to study if clustering based on IVIM parameter maps can identify tumor subregions, and to assess the relevance of obtained subregions by histological analysis. METHODS Fourteen mice with human neuroendocrine tumors were examined with diffusion-weighted imaging to obtain IVIM parameter maps. Gaussian mixture models with IVIM maps from all tumors as input were used to partition voxels into k clusters, where k = 2 was chosen for further analysis based on goodness of fit. Clustering was performed with and without the perfusion-related IVIM parameter D * , and with and without including spatial information. The validity of the clustering was assessed by comparison with corresponding histologically stained tumor sections. A Ki-67-based index quantifying the degree of tumor proliferation was considered appropriate for the comparison based on the obtained cluster characteristics. RESULTS The clustering resulted in one class with low diffusion and high perfusion and another with slightly higher diffusion and low perfusion. Strong agreement was found between tumor subregions identified by clustering and subregions identified by histological analysis, both regarding size and spatial agreement. Neither D * nor spatial information had substantial effects on the clustering results. CONCLUSIONS The results of this study show that IVIM parameter maps can be used to identify tumor subregions using a data-driven framework based on Gaussian mixture models. In the studied tumor model, the obtained subregions showed agreement with proliferative activity.
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Affiliation(s)
- Oscar Jalnefjord
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Mikael Montelius
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Jonathan Arvidsson
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Eva Forssell-Aronsson
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Göran Starck
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Maria Ljungberg
- Department of Radiation Physics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
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17
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Moosvi F, Baker JH, Yung A, Kozlowski P, Minchinton AI, Reinsberg SA. Fast and sensitive dynamic oxygen‐enhanced MRI with a cycling gas challenge and independent component analysis. Magn Reson Med 2018; 81:2514-2525. [DOI: 10.1002/mrm.27584] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 10/04/2018] [Accepted: 10/07/2018] [Indexed: 12/14/2022]
Affiliation(s)
- Firas Moosvi
- Department of Physics & Astronomy University of British Columbia Vancouver Canada
| | - Jennifer H.E. Baker
- Radiation Biology Unit British Columbia Cancer Research Centre Vancouver Canada
| | - Andrew Yung
- UBC MRI Research Centre Life Sciences Centre Vancouver Canada
| | - Piotr Kozlowski
- UBC MRI Research Centre Life Sciences Centre Vancouver Canada
- Department of Radiology University of British Columbia Vancouver Canada
| | | | - Stefan A. Reinsberg
- Department of Physics & Astronomy University of British Columbia Vancouver Canada
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