1
|
Wongsawaeng D, Schwartz D, Li X, Muldoon LL, Stoller J, Stateler C, Holland S, Szidonya L, Rooney WD, Wyatt C, Ambady P, Fu R, Neuwelt EA, Barajas RF. Comparison of dynamic susceptibility contrast (DSC) using gadolinium and iron-based contrast agents in high-grade glioma at high-field MRI. Neuroradiol J 2024; 37:473-482. [PMID: 38544404 PMCID: PMC11366198 DOI: 10.1177/19714009241242596] [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] [Indexed: 04/12/2024] Open
Abstract
PURPOSE To compare DSC-MRI using Gadolinium (GBCA) and Ferumoxytol (FBCA) in high-grade glioma at 3T and 7T MRI field strengths. We hypothesized that using FBCA at 7T would enhance the performance of DSC, as measured by contrast-to-noise ratio (CNR). METHODS Ten patients (13 lesions) were assigned to 3T (6 patients, 6 lesions) or 7T (4 patients, 7 lesions). All lesions received 0.1 mmol/kg of GBCA on day 1. Ten lesions (4 at 3T and 6 at 7T) received a lower dose (0.6 mg/kg) of FBCA, followed by a higher dose (1.0-1.2 mg/kg), while 3 lesions (2 at 3T and 1 at 7T) received only a higher dose on Day 2. CBV maps with leakage correction for GBCA but not for FBCA were generated. The CNR and normalized CBV (nCBV) were analyzed on enhancing and non-enhancing high T2W lesions. RESULTS Regardless of FBCA dose, GBCA showed higher CNR than FBCA at 7T, which was significant for high-dose FBCA (p < .05). Comparable CNR between GBCA and high-dose FBCA was observed at 3T. There was a trend toward higher CNR for FBCA at 3T than 7T. GBCA also showed nCBV twice that of FBCA at both MRI field strengths with significance at 7T. CONCLUSION GBCA demonstrated higher image conspicuity, as measured by CNR, than FBCA on 7T. The stronger T2* weighting realized with higher magnetic field strength, combined with FBCA, likely results in more signal loss rather than enhanced performance on DSC. However, at clinical 3T, both GBCA and FBCA, particularly a dosage of 1.0-1.2 mg/kg (optimal for perfusion imaging), yielded comparable CNR.
Collapse
Affiliation(s)
- Doonyaporn Wongsawaeng
- Department of Radiology, Faculty of Medicine Siriraj Hospital, Mahidol University, Thailand
| | - Daniel Schwartz
- Advanced Imaging Research Center, Oregon Health and Science University, USA
| | - Xin Li
- Advanced Imaging Research Center, Oregon Health and Science University, USA
| | - Leslie L Muldoon
- Department of Neurology, Oregon Health & Science University, USA
| | - Jared Stoller
- Department of Radiology, Oregon Health & Science University, USA
| | | | - Samantha Holland
- Department of Neurology, Oregon Health & Science University, USA
| | - Laszlo Szidonya
- Department of Radiology, Oregon Health & Science University, USA
| | - William D Rooney
- Advanced Imaging Research Center, Oregon Health and Science University, USA
| | - Cory Wyatt
- Department of Radiology, Oregon Health & Science University, USA
| | | | - Rongwei Fu
- School of Public Health, Oregon Health & Science University, USA
| | - Edward A Neuwelt
- Department of Neurology, Oregon Health & Science University, USA
- Department of Neurosurgery, Oregon Health & Science University, USA
| | - Ramon F Barajas
- Advanced Imaging Research Center, Oregon Health and Science University, USA
- Department of Radiology, Oregon Health & Science University, USA
- Knight Cancer Institute, Oregon Health & Science University, USA
| |
Collapse
|
2
|
Si G, Du Y, Tang P, Ma G, Jia Z, Zhou X, Mu D, Shen Y, Lu Y, Mao Y, Chen C, Li Y, Gu N. Unveiling the next generation of MRI contrast agents: current insights and perspectives on ferumoxytol-enhanced MRI. Natl Sci Rev 2024; 11:nwae057. [PMID: 38577664 PMCID: PMC10989670 DOI: 10.1093/nsr/nwae057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 01/23/2024] [Accepted: 02/05/2024] [Indexed: 04/06/2024] Open
Abstract
Contrast-enhanced magnetic resonance imaging (CE-MRI) is a pivotal tool for global disease diagnosis and management. Since its clinical availability in 2009, the off-label use of ferumoxytol for ferumoxytol-enhanced MRI (FE-MRI) has significantly reshaped CE-MRI practices. Unlike MRI that is enhanced by gadolinium-based contrast agents, FE-MRI offers advantages such as reduced contrast agent dosage, extended imaging windows, no nephrotoxicity, higher MRI time efficiency and the capability for molecular imaging. As a leading superparamagnetic iron oxide contrast agent, ferumoxytol is heralded as the next generation of contrast agents. This review delineates the pivotal clinical applications and inherent technical superiority of FE-MRI, providing an avant-garde medical-engineering interdisciplinary lens, thus bridging the gap between clinical demands and engineering innovations. Concurrently, we spotlight the emerging imaging themes and new technical breakthroughs. Lastly, we share our own insights on the potential trajectory of FE-MRI, shedding light on its future within the medical imaging realm.
Collapse
Affiliation(s)
- Guangxiang Si
- Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China
| | - Yue Du
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 210029, China
| | - Peng Tang
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 210029, China
| | - Gao Ma
- Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Zhaochen Jia
- Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China
| | - Xiaoyue Zhou
- MR Collaboration, Siemens Healthineers Ltd., Shanghai 200126, China
| | - Dan Mu
- Department of Radiology, Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Yan Shen
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 210029, China
| | - Yi Lu
- School of Mathematical Sciences, Capital Normal University, Beijing 100048, China
| | - Yu Mao
- Nanjing Key Laboratory for Cardiovascular Information and Health Engineering Medicine, Institute of Clinical Medicine, Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing 210093, China
| | - Chuan Chen
- Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China
| | - Yan Li
- Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China
| | - Ning Gu
- Nanjing Key Laboratory for Cardiovascular Information and Health Engineering Medicine, Institute of Clinical Medicine, Nanjing Drum Tower Hospital, Medical School, Nanjing University, Nanjing 210093, China
- Jiangsu Key Laboratory for Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China
| |
Collapse
|
3
|
Powell SJ, Withey SB, Sun Y, Grist JT, Novak J, MacPherson L, Abernethy L, Pizer B, Grundy R, Morgan PS, Jaspan T, Bailey S, Mitra D, Auer DP, Avula S, Arvanitis TN, Peet A. Applying machine learning classifiers to automate quality assessment of paediatric dynamic susceptibility contrast (DSC-) MRI data. Br J Radiol 2023; 96:20201465. [PMID: 36802769 PMCID: PMC10161906 DOI: 10.1259/bjr.20201465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023] Open
Abstract
OBJECTIVE Investigate the performance of qualitative review (QR) for assessing dynamic susceptibility contrast (DSC-) MRI data quality in paediatric normal brain and develop an automated alternative to QR. METHODS 1027 signal-time courses were assessed by Reviewer 1 using QR. 243 were additionally assessed by Reviewer 2 and % disagreements and Cohen's κ (κ) were calculated. The signal drop-to-noise ratio (SDNR), root mean square error (RMSE), full width half maximum (FWHM) and percentage signal recovery (PSR) were calculated for the 1027 signal-time courses. Data quality thresholds for each measure were determined using QR results. The measures and QR results trained machine learning classifiers. Sensitivity, specificity, precision, classification error and area under the curve from a receiver operating characteristic curve were calculated for each threshold and classifier. RESULTS Comparing reviewers gave 7% disagreements and κ = 0.83. Data quality thresholds of: 7.6 for SDNR; 0.019 for RMSE; 3 s and 19 s for FWHM; and 42.9 and 130.4% for PSR were produced. SDNR gave the best sensitivity, specificity, precision, classification error and area under the curve values of 0.86, 0.86, 0.93, 14.2% and 0.83. Random forest was the best machine learning classifier, giving sensitivity, specificity, precision, classification error and area under the curve of 0.94, 0.83, 0.93, 9.3% and 0.89. CONCLUSION The reviewers showed good agreement. Machine learning classifiers trained on signal-time course measures and QR can assess quality. Combining multiple measures reduces misclassification. ADVANCES IN KNOWLEDGE A new automated quality control method was developed, which trained machine learning classifiers using QR results.
Collapse
Affiliation(s)
- Stephen J Powell
- Physical Sciences for Health CDT, University of Birmingham, Birmingham, United Kingdom.,Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Stephanie B Withey
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom.,Department of Oncology, Birmingham Children's Hospital, Birmingham, United Kingdom.,RRPPS, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
| | - Yu Sun
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom.,School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, China
| | - James T Grist
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Jan Novak
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom.,Department of Oncology, Birmingham Children's Hospital, Birmingham, United Kingdom.,Department of Psychology, Aston Brain Centre, School of Life and Health Sciences, Aston University, Birmingham, United Kingdom
| | - Lesley MacPherson
- Radiology, Birmingham Children's Hospital, Birmingham, United Kingdom
| | - Laurence Abernethy
- Radiology, Alder Hey Children's NHS Foundation Trust, Liverpool, United Kingdom
| | - Barry Pizer
- Oncology, Alder Hey Children's NHS Foundation Trust, Liverpool, United Kingdom
| | - Richard Grundy
- The Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, United Kingdom
| | - Paul S Morgan
- The Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, United Kingdom.,Medical Physics, Nottingham University Hospitals, Nottingham, United Kingdom.,NIHR Nottingham Biomedical Research Centre, Nottingham, United Kingdom
| | - Tim Jaspan
- The Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, United Kingdom.,Radiology, Nottingham University Hospitals, Nottingham, United Kingdom
| | - Simon Bailey
- Sir James Spence Institute of Child Health, Royal Victoria Infirmary, Newcastle upon Tyne, United Kingdom
| | - Dipayan Mitra
- Neuroradiology, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom
| | - Dorothee P Auer
- Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
| | - Shivaram Avula
- Radiology, Alder Hey Children's NHS Foundation Trust, Liverpool, United Kingdom
| | - Theodoros N Arvanitis
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom.,Department of Oncology, Birmingham Children's Hospital, Birmingham, United Kingdom.,Institute of Digital Healthcare, WMG, University of Warwick, Coventry, United Kingdom
| | - Andrew Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom.,Department of Oncology, Birmingham Children's Hospital, Birmingham, United Kingdom
| |
Collapse
|
4
|
One-pot synthesis of carboxymethyl-dextran coated iron oxide nanoparticles (CION) for preclinical fMRI and MRA applications. Neuroimage 2021; 238:118213. [PMID: 34116153 PMCID: PMC8418149 DOI: 10.1016/j.neuroimage.2021.118213] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 05/15/2021] [Accepted: 05/25/2021] [Indexed: 11/21/2022] Open
Abstract
Superparamagnetic iron-oxide nanoparticles are robust contrast agents for magnetic resonance imaging (MRI) used for sensitive structural and functional mapping of the cerebral blood volume (CBV) when administered intravenously. To date, many CBV-MRI studies are conducted with Feraheme, manufactured for the clinical treatment of iron-deficiency. Unfortunately, Feraheme is currently not available outside the United States due to commercial and regulatory constraints, making CBV-MRI methods either inaccessible or very costly to achieve. To address this barrier, we developed a simple, one-pot recipe to synthesize Carboxymethyl-dextran coated Iron Oxide Nanoparticles, namely, “CION”, suitable for preclinical CBV-MRI applications. Here we disseminate a step-by-step instruction of our one-pot synthesis protocol, which allows CION to be produced in laboratories with minimal cost. We also characterized different CION-conjugations by manipulating polymer to metal stoichiometric ratio in terms of their size, surface chemistry, and chemical composition, and shifts in MR relaxivity and pharmacokinetics. We performed several proof-of-concept experiments in vivo, demonstrating the utility of CION for functional and structural MRI applications, including hypercapnic CO2 challenge, visual stimulation, targeted optogenetic stimulation, and microangiography. We also present evidence that CION can serve as a cross-modality research platform by showing concurrent in vivo optical and MRI measurement of CBV using fluorescent-labeled CION. The simplicity and cost-effectiveness of our one-pot synthesis method should allow researchers to reproduce CION and tailor the relaxivity and pharmacokinetics according to their imaging needs. It is our hope that this work makes CBV-MRI more openly available and affordable for a variety of research applications.
Collapse
|
5
|
Ponrartana S, Moore MM, Chan SS, Victoria T, Dillman JR, Chavhan GB. Safety issues related to intravenous contrast agent use in magnetic resonance imaging. Pediatr Radiol 2021; 51:736-747. [PMID: 33871726 DOI: 10.1007/s00247-020-04896-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 09/12/2020] [Accepted: 10/19/2020] [Indexed: 02/06/2023]
Abstract
Gadolinium-based contrast agents (GBCAs) have been used to improve image quality of MRI examinations for decades and have an excellent overall safety record. However, there are well-documented risks associated with GBCAs and our understanding and management of these risks continue to evolve. The purpose of this review is to discuss the safety of GBCAs used in MRI in adult and pediatric populations. We focus particular attention on acute adverse reactions, nephrogenic systemic fibrosis and gadolinium deposition. We also discuss the non-GBCA MRI contrast agent ferumoxytol, which is increasing in use and has its own risk profile. Finally, we identify special populations at higher risk of harm from GBCA administration.
Collapse
Affiliation(s)
- Skorn Ponrartana
- Department of Radiology, Children's Hospital Los Angeles, 4650 Sunset Blvd., MS# 81, Los Angeles, CA, 90064, USA. .,Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| | - Michael M Moore
- Department of Radiology, Penn State Children's Hospital, Penn State Health, Hershey, PA, USA
| | - Sherwin S Chan
- Department of Radiology, University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA.,Department of Radiology, Children's Mercy Hospital, Kansas City, MO, USA
| | - Teresa Victoria
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jonathan R Dillman
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.,Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Govind B Chavhan
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada.,Medical Imaging, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
6
|
Theruvath AJ, Aghighi M, Iv M, Nejadnik H, Lavezo J, Pisani LJ, Daldrup-Link HE. Brain iron deposition after Ferumoxytol-enhanced MRI: A study of Porcine Brains. Nanotheranostics 2020; 4:195-200. [PMID: 32637297 PMCID: PMC7332795 DOI: 10.7150/ntno.46356] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 05/31/2020] [Indexed: 12/14/2022] Open
Abstract
Recent evidence of gadolinium deposition in the brain has raised safety concerns. Iron oxide nanoparticles are re-emerging as promising alternative MR contrast agents, because the iron core can be metabolized. However, long-term follow up studies of the brain after intravenous iron oxide administration have not been reported thus far. In this study, we investigated, if intravenously administered ferumoxytol nanoparticles are deposited in porcine brains. Methods: In an animal care and use committee-approved prospective case-control study, ten Göttingen minipigs received either intravenous ferumoxytol injections at a dose of 5 mg Fe/kg (n=4) or remained untreated (n=6). Nine to twelve months later, pigs were sacrificed and the brains of all pigs underwent ex vivo MRI at 7T with T2 and T2*-weighted sequences. MRI scans were evaluated by measuring R2* values (R2*=1000/T2*) of the bilateral caudate nucleus, lentiform nucleus, thalamus, dentate nucleus, and choroid plexus. Pig brains were sectioned and stained with Prussian blue and evaluated for iron deposition using a semiquantitative scoring system. Data of ferumoxytol exposed and unexposed groups were compared with an unpaired t-test and a Mann-Whitney U test. Results: T2 and T2* signal of the different brain regions was not visually different between ferumoxytol exposed and unexposed controls. There were no significant differences in R2* values of the different brain regions in the ferumoxytol exposed group compared to controls (p>0.05). Prussian blue stains of the same brain regions, scored according to a semiquantitative score, were not significantly different either between the ferumoxytol exposed group and unexposed controls (p>0.05). Conclusions: Our study shows that intravenous ferumoxytol doses of 5-10 mg Fe/kg do not lead to iron deposition in the brain of pigs. We suggest iron oxide nanoparticles as a promising alternative for gadolinium-enhanced MRI.
Collapse
Affiliation(s)
- Ashok Joseph Theruvath
- Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, CA, USA.,Department of Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University Mainz, 55131 Mainz, Germany
| | - Maryam Aghighi
- Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, CA, USA
| | - Michael Iv
- Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, CA, USA
| | - Hossein Nejadnik
- Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, CA, USA
| | - Jonathan Lavezo
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Laura Jean Pisani
- Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, CA, USA
| | | |
Collapse
|
7
|
Thust SC, van den Bent MJ, Smits M. Pseudoprogression of brain tumors. J Magn Reson Imaging 2018; 48:571-589. [PMID: 29734497 PMCID: PMC6175399 DOI: 10.1002/jmri.26171] [Citation(s) in RCA: 178] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2018] [Accepted: 04/07/2018] [Indexed: 12/11/2022] Open
Abstract
This review describes the definition, incidence, clinical implications, and magnetic resonance imaging (MRI) findings of pseudoprogression of brain tumors, in particular, but not limited to, high-grade glioma. Pseudoprogression is an important clinical problem after brain tumor treatment, interfering not only with day-to-day patient care but also the execution and interpretation of clinical trials. Radiologically, pseudoprogression is defined as a new or enlarging area(s) of contrast agent enhancement, in the absence of true tumor growth, which subsides or stabilizes without a change in therapy. The clinical definitions of pseudoprogression have been quite variable, which may explain some of the differences in reported incidences, which range from 9-30%. Conventional structural MRI is insufficient for distinguishing pseudoprogression from true progressive disease, and advanced imaging is needed to obtain higher levels of diagnostic certainty. Perfusion MRI is the most widely used imaging technique to diagnose pseudoprogression and has high reported diagnostic accuracy. Diagnostic performance of MR spectroscopy (MRS) appears to be somewhat higher, but MRS is less suitable for the routine and universal application in brain tumor follow-up. The combination of MRS and diffusion-weighted imaging and/or perfusion MRI seems to be particularly powerful, with diagnostic accuracy reaching up to or even greater than 90%. While diagnostic performance can be high with appropriate implementation and interpretation, even a combination of techniques, however, does not provide 100% accuracy. It should also be noted that most studies to date are small, heterogeneous, and retrospective in nature. Future improvements in diagnostic accuracy can be expected with harmonization of acquisition and postprocessing, quantitative MRI and computer-aided diagnostic technology, and meticulous evaluation with clinical and pathological data. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.
Collapse
Affiliation(s)
- Stefanie C. Thust
- Lysholm Neuroradiology DepartmentNational Hospital for Neurology and NeurosurgeryLondonUK
- Department of Brain Rehabilitation and RepairUCL Institute of NeurologyLondonUK
- Imaging DepartmentUniversity College London HospitalLondonUK
| | - Martin J. van den Bent
- Department of NeurologyThe Brain Tumor Centre at Erasmus MC Cancer InstituteRotterdamThe Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MCUniversity Medical Centre RotterdamRotterdamThe Netherlands
| |
Collapse
|