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Tseng CH, Jaspers J, Romero AM, Wielopolski P, Smits M, van Osch MJP, Vos F. Improved reliability of perfusion estimation in dynamic susceptibility contrast MRI by using the arterial input function from dynamic contrast enhanced MRI. NMR IN BIOMEDICINE 2024; 37:e5038. [PMID: 37712359 DOI: 10.1002/nbm.5038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 08/02/2023] [Accepted: 08/23/2023] [Indexed: 09/16/2023]
Abstract
The arterial input function (AIF) plays a crucial role in estimating quantitative perfusion properties from dynamic susceptibility contrast (DSC) MRI. An important issue, however, is that measuring the AIF in absolute contrast-agent concentrations is challenging, due to uncertainty in relation to the measuredR 2 ∗ -weighted signal, signal depletion at high concentration, and partial-volume effects. A potential solution could be to derive the AIF from separately acquired dynamic contrast enhanced (DCE) MRI data. We aim to compare the AIF determined from DCE MRI with the AIF from DSC MRI, and estimated perfusion coefficients derived from DSC data using a DCE-driven AIF with perfusion coefficients determined using a DSC-based AIF. AIFs were manually selected in branches of the middle cerebral artery (MCA) in both DCE and DSC data in each patient. In addition, a semi-automatic AIF-selection algorithm was applied to the DSC data. The amplitude and full width at half-maximum of the AIFs were compared statistically using the Wilcoxon rank-sum test, applying a 0.05 significance level. Cerebral blood flow (CBF) was derived with different AIF approaches and compared further. The results showed that the AIFs extracted from DSC scans yielded highly variable peaks across arteries within the same patient. The semi-automatic DSC-AIF had significantly narrower width compared with the manual AIFs, and a significantly larger peak than the manual DSC-AIF. Additionally, the DCE-based AIF provided a more stable measurement of relative CBF and absolute CBF values estimated with DCE-AIFs that were compatible with previously reported values. In conclusion, DCE-based AIFs were reproduced significantly better across vessels, showed more realistic profiles, and delivered more stable and reasonable CBF measurements. The DCE-AIF can, therefore, be considered as an alternative AIF source for quantitative perfusion estimations in DSC MRI.
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Affiliation(s)
- Chih-Hsien Tseng
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
- Medical Delta, Delft, the Netherlands
- Holland Proton Therapy Center Consortium-Erasmus MC, Rotterdam, Holland Proton Therapy Centre, Delft, Leiden University Medical Center, Leiden and Delft University of Technology, Delft, the Netherlands
| | - Jaap Jaspers
- Holland Proton Therapy Center Consortium-Erasmus MC, Rotterdam, Holland Proton Therapy Centre, Delft, Leiden University Medical Center, Leiden and Delft University of Technology, Delft, the Netherlands
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Alejandra Mendez Romero
- Holland Proton Therapy Center Consortium-Erasmus MC, Rotterdam, Holland Proton Therapy Centre, Delft, Leiden University Medical Center, Leiden and Delft University of Technology, Delft, the Netherlands
- Department of Radiotherapy, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Piotr Wielopolski
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Marion Smits
- Medical Delta, Delft, the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Brain Tumour Center, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Matthias J P van Osch
- Medical Delta, Delft, the Netherlands
- Holland Proton Therapy Center Consortium-Erasmus MC, Rotterdam, Holland Proton Therapy Centre, Delft, Leiden University Medical Center, Leiden and Delft University of Technology, Delft, the Netherlands
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Frans Vos
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
- Medical Delta, Delft, the Netherlands
- Holland Proton Therapy Center Consortium-Erasmus MC, Rotterdam, Holland Proton Therapy Centre, Delft, Leiden University Medical Center, Leiden and Delft University of Technology, Delft, the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
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Elschot EP, Backes WH, de Jong JJA, Drenthen GS, Wong SM, Staals J, Postma AA, Rouhl RPW, van Oostenbrugge RJ, Jansen JFA. Assessment of the clinical feasibility of detecting subtle blood-brain barrier leakage in cerebral small vessel disease using dynamic susceptibility contrast MRI. Magn Reson Imaging 2023; 102:55-61. [PMID: 37137345 DOI: 10.1016/j.mri.2023.04.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 04/26/2023] [Accepted: 04/26/2023] [Indexed: 05/05/2023]
Abstract
PURPOSE Cerebral small vessel disease (cSVD) involves several pathologies affecting the small vessels, including blood-brain barrier (BBB) impairment. Dynamic susceptibility contrast (DSC) MRI is sensitive to both blood perfusion and BBB leakage, and correction methods may be crucial for obtaining reliable perfusion measures. These methods might also be applicable to detect BBB leakage itself. This study investigated to what extent DSC-MRI can measure subtle BBB leakage in a clinical feasibility setting. METHODS In vivo DCE and DSC data were collected from fifteen cSVD patients (71 (±10) years, 6F/9M) and twelve elderly controls (71 (±10) years, 4F/8M). DSC-derived leakage fractions were obtained using the Boxerman-Schmainda-Weisskoff method (K2). K2 was compared with the DCE-derived leakage rate Ki, obtained from Patlak analysis. Subsequently, differences were assessed between white matter hyperintensities (WMH), cortical gray matter (CGM), and normal-appearing white matter (NAWM). Additionally, computer simulations were performed to assess the sensitivity of DSC-MRI to BBB leakage. RESULTS K2 showed significant differences between tissue regions (P < 0.001 for CGM-NAWM and CGM-WMH, and P = 0.001 for NAWM-WMH). Conversely, according to the computer simulations the DSC sensitivity was insufficient to measure subtle BBB leakage, as the K2 values were below the derived limit of quantification (4∙10-3 min-1). As expected, Ki was elevated in the WMH compared to CGM and NAWM (P < 0.001). CONCLUSIONS Although clinical DSC-MRI seems capable to detect subtle BBB leakage differences between WMH and normal-appearing brain tissue it is not recommended. K2 as a direct measure for subtle BBB leakage remains ambiguous as its signal effects are due to mixed T1- and T2∗-weighting. Further research is warranted to better disentangle perfusion from leakage effects.
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Affiliation(s)
- Elles P Elschot
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Minderbroedersberg 4-6, Maastricht, the Netherlands
| | - Walter H Backes
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Minderbroedersberg 4-6, Maastricht, the Netherlands; School for Cardiovascular Diseases (CARIM), Maastricht University, Minderbroedersberg 4-6, Maastricht, the Netherlands
| | - Joost J A de Jong
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Minderbroedersberg 4-6, Maastricht, the Netherlands
| | - Gerhard S Drenthen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Minderbroedersberg 4-6, Maastricht, the Netherlands
| | - Sau May Wong
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, Maastricht, the Netherlands
| | - Julie Staals
- Department of Neurology, Maastricht University Medical Center+, P. Debyelaan 25, Maastricht, the Netherlands; School for Cardiovascular Diseases (CARIM), Maastricht University, Minderbroedersberg 4-6, Maastricht, the Netherlands
| | - Alida A Postma
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Minderbroedersberg 4-6, Maastricht, the Netherlands
| | - Rob P W Rouhl
- School for Mental Health and Neuroscience (MHeNs), Maastricht University, Minderbroedersberg 4-6, Maastricht, the Netherlands; Department of Neurology, Maastricht University Medical Center+, P. Debyelaan 25, Maastricht, the Netherlands; Academic Center for Epileptology Kempenhaeghe/MUMC+, Heeze and Maastricht, the Netherlands
| | - Robert J van Oostenbrugge
- School for Mental Health and Neuroscience (MHeNs), Maastricht University, Minderbroedersberg 4-6, Maastricht, the Netherlands; Department of Neurology, Maastricht University Medical Center+, P. Debyelaan 25, Maastricht, the Netherlands; School for Cardiovascular Diseases (CARIM), Maastricht University, Minderbroedersberg 4-6, Maastricht, the Netherlands
| | - Jacobus F A Jansen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, Maastricht, the Netherlands; School for Mental Health and Neuroscience (MHeNs), Maastricht University, Minderbroedersberg 4-6, Maastricht, the Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, Eindhoven, the Netherlands; Academic Center for Epileptology Kempenhaeghe/MUMC+, Heeze and Maastricht, the Netherlands.
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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.
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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
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4
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Withey SB, MacPherson L, Oates A, Powell S, Novak J, Abernethy L, Pizer B, Grundy R, Morgan PS, Bailey S, Mitra D, Arvanitis TN, Auer DP, Avula S, Peet AC. Dynamic susceptibility-contrast magnetic resonance imaging with contrast agent leakage correction aids in predicting grade in pediatric brain tumours: a multicenter study. Pediatr Radiol 2022; 52:1134-1149. [PMID: 35290489 PMCID: PMC9107460 DOI: 10.1007/s00247-021-05266-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 08/31/2021] [Accepted: 12/11/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Relative cerebral blood volume (rCBV) measured using dynamic susceptibility-contrast MRI can differentiate between low- and high-grade pediatric brain tumors. Multicenter studies are required for translation into clinical practice. OBJECTIVE We compared leakage-corrected dynamic susceptibility-contrast MRI perfusion parameters acquired at multiple centers in low- and high-grade pediatric brain tumors. MATERIALS AND METHODS Eighty-five pediatric patients underwent pre-treatment dynamic susceptibility-contrast MRI scans at four centers. MRI protocols were variable. We analyzed data using the Boxerman leakage-correction method producing pixel-by-pixel estimates of leakage-uncorrected (rCBVuncorr) and corrected (rCBVcorr) relative cerebral blood volume, and the leakage parameter, K2. Histological diagnoses were obtained. Tumors were classified by high-grade tumor. We compared whole-tumor median perfusion parameters between low- and high-grade tumors and across tumor types. RESULTS Forty tumors were classified as low grade, 45 as high grade. Mean whole-tumor median rCBVuncorr was higher in high-grade tumors than low-grade tumors (mean ± standard deviation [SD] = 2.37±2.61 vs. -0.14±5.55; P<0.01). Average median rCBV increased following leakage correction (2.54±1.63 vs. 1.68±1.36; P=0.010), remaining higher in high-grade tumors than low grade-tumors. Low-grade tumors, particularly pilocytic astrocytomas, showed T1-dominant leakage effects; high-grade tumors showed T2*-dominance (mean K2=0.017±0.049 vs. 0.002±0.017). Parameters varied with tumor type but not center. Median rCBVuncorr was higher (mean = 1.49 vs. 0.49; P=0.015) and K2 lower (mean = 0.005 vs. 0.016; P=0.013) in children who received a pre-bolus of contrast agent compared to those who did not. Leakage correction removed the difference. CONCLUSION Dynamic susceptibility-contrast MRI acquired at multiple centers helped distinguish between children's brain tumors. Relative cerebral blood volume was significantly higher in high-grade compared to low-grade tumors and differed among common tumor types. Vessel leakage correction is required to provide accurate rCBV, particularly in low-grade enhancing tumors.
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Affiliation(s)
- Stephanie B Withey
- RRPPS, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- Oncology, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Lesley MacPherson
- Radiology, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
| | - Adam Oates
- Radiology, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
| | - Stephen Powell
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Jan Novak
- Oncology, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Department of Psychology, Aston Brain Centre, School of Life and Health Sciences, Aston University, Birmingham, UK
| | | | - Barry Pizer
- Oncology, Alder Hey Children's NHS Foundation Trust, Liverpool, UK
| | - Richard Grundy
- The Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, UK
| | - Paul S Morgan
- The Children's Brain Tumour Research Centre, University of Nottingham, Nottingham, UK
- Medical Physics, Nottingham University Hospitals, Nottingham, UK
- Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK
| | - Simon Bailey
- Sir James Spence Institute of Child Health, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - Dipayan Mitra
- Neuroradiology, Royal Victoria Infirmary, Newcastle upon Tyne, UK
| | - Theodoros N Arvanitis
- Oncology, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- Institute of Digital Healthcare, WMG, University of Warwick, Coventry, UK
| | - Dorothee P Auer
- Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK
- Neuroradiology, Nottingham University Hospitals Trust, Nottingham, UK
- NIHR Nottingham Biomedical Research Centre, Nottingham, UK
| | - Shivaram Avula
- Radiology, Alder Hey Children's NHS Foundation Trust, Liverpool, UK
| | - Andrew C Peet
- Oncology, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK.
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.
- Children's Brain Tumour Research Team, 4th Floor Institute of Child Health, Birmingham Women's and Children's Hospital NHS Foundation Trust, Steelhouse Lane, Birmingham, B4 6NH, UK.
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5
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Steidl E, Müller M, Müller A, Herrlinger U, Hattingen E. Longitudinal, leakage corrected and uncorrected rCBV during the first-line treatment of glioblastoma: a prospective study. J Neurooncol 2019; 144:409-417. [PMID: 31321614 DOI: 10.1007/s11060-019-03244-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Accepted: 07/15/2019] [Indexed: 12/15/2022]
Abstract
PURPOSE Dynamic susceptibility contrast (DSC) MR-perfusion is becoming a standard of care for the monitoring of glioblastoma. Yet, technical standards are lacking and measurements without leakage correction are still common. Also, data on leakage corrected measurements during stable disease is scarce. In this study we hypothesized that basic leakage correction would significantly enhance data quality during stable disease and improve progress detection. We furthermore investigated whether longitudinal data could increase diagnostic performance. METHODS Patients with histologically proven glioblastoma undergoing first-line therapy were prospectively recruited. We conducted DSC perfusion measurements without prebolus administration in 6-week intervals from the end of radiotherapy until progression. Maximum relative cerebral volume values (rCBVmax) with and without leakage correction were calculated using Philips IntelliSpace®. RESULTS We recruited 16 patients and conducted 82 MRI scans with a mean follow up of 7.2 month. During stable disease, corrected rCBVmax was significantly more stable than uncorrected rCBVmax. Detection of progression with a rCBVmax cutoff was better for corrected (specificity 86%) than for uncorrected rCBVmax (specificity 41%). Interestingly, the increase of corrected rCBVmax upon progression also had a good diagnostic performance with a combination of both cutoffs delivering the best result (sensitivity/specificity 89%/93%). CONCLUSION Corrected rCBVmax supports the imaging finding of a stable disease and large increases during longitudinal observation support the diagnosis of tumor progression. rCBV values without prebolus or leakage correction are not reliable to monitor glioblastomas. Further studies to investigate the value of longitudinal rCBV dynamics for the differentiation of real tumor progression from pseudoprogression are warranted.
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Affiliation(s)
- Eike Steidl
- Institute of Neuroradiology, University Hospital Frankfurt, Schleusenweg 2-16, 60528, Frankfurt, Germany.
- Department of Radiology, Neuroradiology, University Hospital Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany.
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Mathias Müller
- Department of Radiology, Neuroradiology, University Hospital Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany
| | - Andreas Müller
- Department of Radiology, Neuroradiology, University Hospital Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany
| | - Ulrich Herrlinger
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany
| | - Elke Hattingen
- Institute of Neuroradiology, University Hospital Frankfurt, Schleusenweg 2-16, 60528, Frankfurt, Germany
- Department of Radiology, Neuroradiology, University Hospital Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
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6
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Quarles CC, Bell LC, Stokes AM. Imaging vascular and hemodynamic features of the brain using dynamic susceptibility contrast and dynamic contrast enhanced MRI. Neuroimage 2018; 187:32-55. [PMID: 29729392 DOI: 10.1016/j.neuroimage.2018.04.069] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2017] [Revised: 04/27/2018] [Accepted: 04/29/2018] [Indexed: 12/22/2022] Open
Abstract
In the context of neurologic disorders, dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) MRI provide valuable insights into cerebral vascular function, integrity, and architecture. Even after two decades of use, these modalities continue to evolve as their biophysical and kinetic basis is better understood, with improvements in pulse sequences and accelerated imaging techniques and through application of more robust and automated data analysis strategies. Here, we systematically review each of these elements, with a focus on how their integration improves kinetic parameter accuracy and the development of new hemodynamic biomarkers that provide sub-voxel sensitivity (e.g., capillary transit time and flow heterogeneity). Regarding contrast mechanisms, we discuss the dipole-dipole interactions and susceptibility effects that give rise to simultaneous T1, T2 and T2∗ relaxation effects, including their quantification, influence on pulse sequence parameter optimization, and use in methods such as vessel size and vessel architectural imaging. The application of technologic advancements, such as parallel imaging, simultaneous multi-slice, undersampled k-space acquisitions, and sliding window strategies, enables improved spatial and/or temporal resolution of DSC and DCE acquisitions. Such acceleration techniques have also enabled the implementation of, clinically feasible, simultaneous multi-echo spin- and gradient echo acquisitions, providing more comprehensive and quantitative interrogation of T1, T2 and T2∗ changes. Characterizing these relaxation rate changes through different post-processing options allows for the quantification of hemodynamics and vascular permeability. The application of different biophysical models provides insight into traditional hemodynamic parameters (e.g., cerebral blood volume) and more advanced parameters (e.g., capillary transit time heterogeneity). We provide insight into the appropriate selection of biophysical models and the necessary post-processing steps to ensure reliable measurements while minimizing potential sources of error. We show representative examples of advanced DSC- and DCE-MRI methods applied to pathologic conditions affecting the cerebral microcirculation, including brain tumors, stroke, aging, and multiple sclerosis. The maturation and standardization of conventional DSC- and DCE-MRI techniques has enabled their increased integration into clinical practice and use in clinical trials, which has, in turn, spurred renewed interest in their technological and biophysical development, paving the way towards a more comprehensive assessment of cerebral hemodynamics.
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Affiliation(s)
- C Chad Quarles
- Division of Neuro imaging Research, Barrow Neurological Institute, 350 W. Thomas Rd, Phoenix, AZ, USA.
| | - Laura C Bell
- Division of Neuro imaging Research, Barrow Neurological Institute, 350 W. Thomas Rd, Phoenix, AZ, USA
| | - Ashley M Stokes
- Division of Neuro imaging Research, Barrow Neurological Institute, 350 W. Thomas Rd, Phoenix, AZ, USA
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7
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Quantitative susceptibility mapping using principles of echo shifting with a train of observations sequence on 1.5 T MRI. Magn Reson Imaging 2017; 42:37-42. [DOI: 10.1016/j.mri.2017.05.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2017] [Revised: 05/08/2017] [Accepted: 05/16/2017] [Indexed: 11/16/2022]
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8
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Utilization of MR angiography in perfusion imaging for identifying arterial input function. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2017; 30:609-620. [PMID: 28744673 DOI: 10.1007/s10334-017-0643-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Revised: 07/06/2017] [Accepted: 07/12/2017] [Indexed: 10/19/2022]
Abstract
OBJECTIVE This research utilizes magnetic resonance angiography (MRA) to identify arterial locations during the parametric evaluation of concentration time curves (CTCs), and to prevent shape distortions in arterial input function (AIF). MATERIALS AND METHODS We carried out cluster analysis with the CTC parameters of voxels located within and around the middle cerebral artery (MCA). Through MRA, we located voxels that meet the AIF criteria and those with distorted CTCs. To minimize partial volume effect, we re-scaled the time integral of CTCs by the time integral of venous output function (VOF). We calculated the steady-state value to area under curve ratio (SS:AUC) of VOF and used it as a reference in selecting AIF. CTCs close to this reference value (selected AIF) and those far from it were used (eliminated AIF) to compute cerebral blood flow (CBF). RESULTS Eliminated AIFs were found to be either on or anterior to MCA, whereas selected AIFs were located superior, inferior, posterior, or anterior to MCA. If the SS:AUC of AIF was far from the reference value, CBF was either under- or over-estimated by a maximum of 41.1 ± 14.3 and 36.6 ± 19.2%, respectively. CONCLUSION MRA enables excluding voxels on the MCA during cluster analysis, and avoiding the risk of shape distortions.
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9
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Morell A, Lennmyr F, Jonsson O, Tovedal T, Pettersson J, Bergquist J, Zemgulis V, Einarsson GM, Thelin S, Ahlström H, Bjørnerud A. Influence of blood/tissue differences in contrast agent relaxivity on tracer-based MR perfusion measurements. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2014; 28:135-47. [PMID: 24973020 DOI: 10.1007/s10334-014-0452-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2014] [Revised: 05/19/2014] [Accepted: 05/27/2014] [Indexed: 11/25/2022]
Abstract
PURPOSE Perfusion assessment by monitoring the transport of a tracer bolus depends critically on conversion of signal intensity into tracer concentration. Two main assumptions are generally applied for this conversion; (1) contrast agent relaxivity is identical in blood and tissue, (2) change in signal intensity depends only on the primary relaxation effect. The purpose of the study was to assess the validity and influence of these assumptions. MATERIALS AND METHODS Blood and cerebral tissue relaxivities r1, r2, and r2* for gadodiamide were measured in four pigs at 1.5 T. Gadolinium concentration was determined by inductively coupled plasma atomic emission spectroscopy. Influence of the relaxivities, secondary relaxation effects and choice of singular value decomposition (SVD) regularization threshold was studied by simulations. RESULTS In vivo relaxivities relative to blood concentration [in s(-1) mM(-1) for blood, gray matter (GM), white matter (WM)] were for r1 (2.614 ± 1.061, 0.010 ± 0.001, 0.004 ± 0.002), r2 (5.088 ± 0.952, 0.091 ± 0.008, 0.059 ± 0.014), and r2* (13.292 ± 3.928, 1.696 ± 0.157, 0.910 ± 0.139). Although substantial, by a nonparametric test for paired samples, the differences were not statistically significant. The GM to WM blood volume ratio was estimated to 2.6 ± 0.9 by r1, 1.6 ± 0.3 by r2, and 1.9 ± 0.2 by r2*. Secondary relaxation was found to reduce the tissue blood flow, as did the SVD regularization threshold. CONCLUSION Contrast agent relaxivity is not identical in blood and tissue leading to substantial errors. Further errors are introduced by secondary relaxation effects and the SVD regularization.
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Affiliation(s)
- Arvid Morell
- Section of Radiology, Department of Radiology, Oncology and Radiation Sciences, Uppsala University, Uppsala, Sweden,
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10
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Xu B, Spincemaille P, Liu T, Prince MR, Dutruel S, Gupta A, Thimmappa ND, Wang Y. Quantification of cerebral perfusion using dynamic quantitative susceptibility mapping. Magn Reson Med 2014; 73:1540-8. [PMID: 24733457 DOI: 10.1002/mrm.25257] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2013] [Revised: 03/27/2014] [Accepted: 03/27/2014] [Indexed: 11/08/2022]
Abstract
PURPOSE The purpose of this study is to develop a dynamic quantitative susceptibility mapping (QSM) technique with sufficient temporal resolution to map contrast agent concentration in cerebral perfusion imaging. METHODS The dynamic QSM used a multiecho three-dimensional (3D) spoiled gradient echo golden angle interleaved spiral sequence during contrast bolus injection. Four-dimensional (4D) space-time resolved magnetic field reconstruction was performed using the temporal resolution acceleration with constrained evolution reconstruction method. Deconvolution of the gadolinium-induced field was performed at each time point with the morphology enabled dipole inversion method to generate a 4D gadolinium concentration map, from which three-dimensional spatial distributions of cerebral blood volume and cerebral blood flow were computed. RESULTS Initial in vivo brain imaging demonstrated the feasibility of using dynamic QSM for generating quantitative 4D contrast agent maps and imaging three-dimensional perfusion. The cerebral blood flow obtained with dynamic QSM agreed with that obtained using arterial spin labeling. CONCLUSION Dynamic QSM can be used to perform 4D mapping of contrast agent concentration in contrast-enhanced magnetic resonance imaging. The perfusion parameters derived from this 4D contrast agent concentration map were in good agreement with those obtained using arterial spin labeling.
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Affiliation(s)
- Bo Xu
- Department of Biomedical Engineering, Cornell University, Ithaca, New York, USA; Department of Radiology, Weill Cornell Medical College, New York, New York, USA
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11
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Willats L, Calamante F. The 39 steps: evading error and deciphering the secrets for accurate dynamic susceptibility contrast MRI. NMR IN BIOMEDICINE 2013; 26:913-931. [PMID: 22782914 DOI: 10.1002/nbm.2833] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2012] [Revised: 03/29/2012] [Accepted: 06/01/2012] [Indexed: 06/01/2023]
Abstract
Dynamic susceptibility contrast (DSC) MRI is the most commonly used MRI method to assess cerebral perfusion and other related haemodynamic parameters. Although the technique is well established and used routinely in clinical centres, there are still many problems that impede accurate perfusion quantification. In this review article, we present 39 steps which guide the reader through the theoretical principles, practical decisions, potential problems, current limitations and latest advances in DSC-MRI. The 39 steps span the collection, analysis and interpretation of DSC-MRI data, expounding issues and possibilities relating to the contrast agent, the acquisition of DSC-MRI data, data pre-processing, the contrast concentration-time course, the arterial input function, deconvolution, common perfusion parameters, post-processing possibilities, patient studies, absolute versus relative quantification and automated analysis methods.
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Affiliation(s)
- Lisa Willats
- Brain Research Institute, Melbourne Brain Centre, 245 Burgundy Street, Heidelberg, Vic., 3084, Australia.
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12
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Wirestam R. Using contrast agents to obtain maps of regional perfusion and capillary wall permeability. ACTA ACUST UNITED AC 2012. [DOI: 10.2217/iim.12.24] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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13
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van Gelderen P, Duyn JH, Ramsey NF, Liu G, Moonen CTW. The PRESTO technique for fMRI. Neuroimage 2012; 62:676-81. [PMID: 22245350 DOI: 10.1016/j.neuroimage.2012.01.017] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2011] [Revised: 10/21/2011] [Accepted: 01/01/2012] [Indexed: 11/18/2022] Open
Abstract
In the early days of BOLD fMRI, the acquisition of T(2)(*) weighted data was greatly facilitated by rapid scan techniques such as EPI. The latter, however, was only available on a few MRI systems that were equipped with specialized hardware that allowed rapid switching of the imaging gradients. For this reason, soon after the invention of fMRI, the scan technique PRESTO was developed to make rapid T(2)(*) weighted scanning available on standard clinical scanners. This method combined echo shifting, which allows for echo times longer than the sequence repetition time, with acquisition of multiple k-space lines per excitation. These two concepts were combined in order to achieve a method fast enough for fMRI, while maintaining a sufficiently long echo time for optimal contrast. PRESTO has been primarily used for 3D scanning, which minimized the contribution of large vessels due to inflow effects. Although PRESTO is still being used today, its appeal has lessened somewhat due to increased gradient performance of modern MRI scanners. Compared to 2D EPI, PRESTO may have somewhat reduced temporal stability, which is a disadvantage for fMRI that may not outweigh the advantage of reduced inflow effects provided by 3D scanning. In this overview, the history of the development of the PRESTO is presented, followed by a qualitative comparison with EPI.
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Affiliation(s)
- P van Gelderen
- Advanced Magnetic Resonance Imaging Section, Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA.
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14
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Wey HY, Wang DJ, Duong TQ. Baseline CBF, and BOLD, CBF, and CMRO2 fMRI of visual and vibrotactile stimulations in baboons. J Cereb Blood Flow Metab 2011; 31:715-24. [PMID: 20827260 PMCID: PMC3049525 DOI: 10.1038/jcbfm.2010.154] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Neurovascular coupling associated with visual and vibrotactile stimulations in baboons anesthetized sequentially with isoflurane and ketamine was evaluated using multimodal functional magnetic resonance imaging (fMRI) on a clinical 3-Tesla scanner. Basal cerebral blood flow (CBF), and combined blood-oxygenation-level-dependent (BOLD) and CBF fMRI of visual and somatosensory stimulations were measured using pseudo-continuous arterial spin labeling. Changes in stimulus-evoked cerebral metabolic rate of oxygen (CMRO(2)) were estimated using calibrated fMRI. Arterial transit time for vessel, gray matter (GM), and white matter (WM) were 250, 570, and 823 ms, respectively. Gray matter and WM CBF, respectively, were 107.8±7.9 and 47.8±3.8 mL per 100 g per minute under isoflurane, and 108.8±10.3 and 48.7±4.2 mL per 100 g per minute under ketamine (mean±s.e.m., N=8 sessions, five baboons). The GM/WM CBF ratio was not statistically different between the two anesthetics, averaging 2.3±0.1. Hypercapnia evoked global BOLD and CBF increases. Blood-oxygenation-level-dependent, CBF, and CMRO(2) signal changes by visual and vibrotactile stimulations were 0.19% to 0.22%, 18% to 23%, and 4.9% to 6.7%, respectively. The CBF/CMRO(2) ratio was 2.9 to 4.7. Basal CBF and fMRI responses were not statistically different between the two anesthetics. This study establishes a multimodal fMRI protocol to probe clinically relevant functional, physiological and metabolic information in large nonhuman primates.
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Affiliation(s)
- Hsiao-Ying Wey
- Research Imaging Institute, University of Texas Health Science Center, San Antonio, Texas 78229, USA
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15
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Bleeker EJW, van Osch MJP, Connelly A, van Buchem MA, Webb AG, Calamante F. New criterion to aid manual and automatic selection of the arterial input function in dynamic susceptibility contrast MRI. Magn Reson Med 2010; 65:448-56. [PMID: 21264935 DOI: 10.1002/mrm.22599] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2010] [Revised: 07/01/2010] [Accepted: 07/20/2010] [Indexed: 01/12/2023]
Abstract
Dynamic susceptibility contrast-MRI requires an arterial input function (AIF) to obtain cerebral blood flow, cerebral blood volume, and mean transit time. The current AIF selection criteria discriminate venous, capillary, and arterial profiles based on shape and timing characteristics of the first passage. Unfortunately, partial volume effects can lead to shape errors in the bolus passage, including a narrower and higher peak, which might be selected as a "correct" AIF. In this study, a new criterion is proposed that detects shape errors based on tracer kinetic principles for computing cerebral blood volume. This criterion uses the ratio of the steady-state value to the area-under-the-curve of the first passage, which should result in an equal value for tissue and arterial responses. By using a reference value from tissue, partial volume effects-induced shape errors of the AIF measurement can be detected. Different factors affecting the ratio were investigated using simulations. These showed that the new criterion should only be used in studies with T(1) -insensitive acquisition. In vivo data were used to evaluate the proposed approach. The data showed that the new criterion enables detection of shape errors, although false positives do occur, which could be easily avoided when combined with current AIF selection criteria.
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Affiliation(s)
- Egbert J W Bleeker
- Department of Radiology, C.J. Gorter Center for High Field MRI, Leiden University Medical Center, Leiden, The Netherlands
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16
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Duong TQ. Diffusion tensor and perfusion MRI of non-human primates. Methods 2010; 50:125-35. [PMID: 19665567 PMCID: PMC2828503 DOI: 10.1016/j.ymeth.2009.08.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2009] [Revised: 07/03/2009] [Accepted: 08/01/2009] [Indexed: 10/20/2022] Open
Abstract
This paper reviews recent non-human primate (NHP) neuroimaging literature using MRI in macaque, baboon and chimpanzee. It describes general challenges and limitations for NHP MRI studies, and reviews recent applications of anatomical, diffusion tensor, cerebral blood flow MRI. Applications to NHP stroke is discussed in some detail.
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Affiliation(s)
- Timothy Q Duong
- Research Imaging Center and Departments of Ophthalmology, Radiology and Physiology, University of Texas Health Science Center at San Antonio, San Antonio, Texas 78229, USA.
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17
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Knutsson L, Ståhlberg F, Wirestam R. Absolute quantification of perfusion using dynamic susceptibility contrast MRI: pitfalls and possibilities. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2009; 23:1-21. [DOI: 10.1007/s10334-009-0190-2] [Citation(s) in RCA: 71] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2009] [Revised: 11/11/2009] [Accepted: 11/12/2009] [Indexed: 10/20/2022]
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18
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Optimal location for arterial input function measurements near the middle cerebral artery in first-pass perfusion MRI. J Cereb Blood Flow Metab 2009; 29:840-52. [PMID: 19142193 DOI: 10.1038/jcbfm.2008.155] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
One of the main difficulties in obtaining quantitative perfusion values from dynamic susceptibility contrast-magnetic resonance imaging is a correct arterial input function (AIF) measurement, as partial volume effects can lead to an erroneous shape and amplitude of the AIF. Cerebral blood flow and volume scale linearly with the area under the AIF, but shape changes of the AIF can lead to large, nonlinear errors. Current manual and automated AIF selection procedures do not guarantee the exclusion of partial volume effects from AIF measurements. This study uses a numerical model, validated by phantom experiments, for predicting the optimal location for AIF measurements in the vicinity of the middle cerebral artery (MCA). Three different sequences were investigated and evaluated on a voxel-by-voxel basis by comparison with the ground truth. Subsequently, the predictions were evaluated in an in vivo example. The findings are fourfold: AIF measurements should be performed in voxels completely outside the artery, here a linear relation should be assumed between DeltaR*2 and the concentration contrast agent, the exact optimal location differs per acquisition type, and voxels including a small MCA yield also correct AIF measurements for segmented echo planar imaging when a short echo time was used.
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19
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Calamante F, Connelly A, van Osch MJP. Nonlinear DeltaR*2 effects in perfusion quantification using bolus-tracking MRI. Magn Reson Med 2009; 61:486-92. [PMID: 19161169 DOI: 10.1002/mrm.21839] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Dynamic susceptibility contrast MRI involves injection of a contrast agent, whose concentration is estimated from DeltaR*2 changes. However, measurement of contrast-agent concentration is prone to various sources of error; in particular, the commonly assumed linear relationship between contrast agent concentration and DeltaR*2 in arterial blood is known to be invalid. In this study, we characterized the associated perfusion errors. Large errors were found when the linear assumption is used; these errors were highly dependent on the choice of tissue relaxivity. The errors were greatly reduced when using the quadratic model, and were further reduced when quantifying perfusion as a relative measure. This study suggests the linear assumption should be abandoned in favor of the quadratic model. Thus, the errors are minimized leading to improved quantification that will enable perfusion MRI to continue to play an important role in quantifying perfusion in brain diseases (e.g., acute stroke).
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20
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Wilkinson I, Hoggard N, Jellinek D, Levy D, Kotsarini C, Batty R, Griffiths P, Romanowski C. MR Perfusion. Neuroradiol J 2008. [DOI: 10.1177/19714009080210s106] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Affiliation(s)
- I.D. Wilkinson
- Academic Unit of Radiology, University of Sheffield; Sheffield, UK
| | - N. Hoggard
- Academic Unit of Radiology, University of Sheffield; Sheffield, UK
| | - D.A. Jellinek
- Departments of Neurosurgery, Royal Hallamshire Hospital, Sheffield Teaching Hospitals Trust; Sheffield, UK
| | - D. Levy
- Neuro-oncology, Royal Hallamshire Hospital, Sheffield Teaching Hospitals Trust; Sheffield, UK
| | - C. Kotsarini
- Academic Unit of Radiology, University of Sheffield; Sheffield, UK
| | - R. Batty
- Neuroradiology, Royal Hallamshire Hospital, Sheffield Teaching Hospitals Trust; Sheffield, UK
| | - P.D. Griffiths
- Academic Unit of Radiology, University of Sheffield; Sheffield, UK
| | - C.A.J. Romanowski
- Neuroradiology, Royal Hallamshire Hospital, Sheffield Teaching Hospitals Trust; Sheffield, UK
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21
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Miyazaki K, Collins DJ, Walker-Samuel S, Taylor JN, Padhani AR, Leach MO, Koh DM. Quantitative mapping of hepatic perfusion index using MR imaging: a potential reproducible tool for assessing tumour response to treatment with the antiangiogenic compound BIBF 1120, a potent triple angiokinase inhibitor. Eur Radiol 2008; 18:1414-21. [PMID: 18351351 DOI: 10.1007/s00330-008-0898-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2007] [Revised: 02/01/2008] [Accepted: 02/05/2008] [Indexed: 10/22/2022]
Abstract
Hepatic metastases are arterially supplied, resulting in an elevated hepatic perfusion index (HPI). The purpose of this study was to use dynamic contrast-enhanced (DCE) MR imaging to quantify the HPI of metastases and the liver before and after treatment with a novel antiangiogenic drug. Ten patients with known metastatic liver disease underwent DCE-MR studies. HPIs of metastases and whole liver were derived using regions of interest (ROIs) and calculated on a pixel-by-pixel basis from quantified changes in gadopentetate dimeglumine (Gd-DTPA) concentration. The HPI measurement error prior to treatment was derived by the Bland-Altman analysis. The median HPI before and after treatment with antiangiogenic drug BIBF 1120 were compared using the Wilcoxon signed rank test. Prior to treatment, the median HPI of metastases, 0.75 +/- 0.14, was significantly higher than that of the whole liver, 0.66 +/- 0.16 (p < 0.01). Bland-Altman reproducibility coefficients of the median HPI from metastases and whole liver were 13.0 and 5.1% respectively. The median HPI of metastases decreased significantly at 28 days after treatment with BIBF 1120 (p < 0.05). This pilot study demonstrates that HPI determined using quantified Gd-DTPA concentration is reproducible and may be useful for monitoring antiangiogenic treatment response of hepatic metastases.
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Affiliation(s)
- Keiko Miyazaki
- CRUK Clinical Magnetic Resonance Research Group, The Institute of Cancer Research, Royal Marsden Hospital, Downs Road, Sutton, Surrey, SM2 5PT, UK.
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22
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Calamante F, Vonken EJPA, van Osch MJP. Contrast agent concentration measurements affecting quantification of bolus-tracking perfusion MRI. Magn Reson Med 2007; 58:544-53. [PMID: 17763347 DOI: 10.1002/mrm.21362] [Citation(s) in RCA: 62] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Measurement of the concentration of the contrast agent using dynamic susceptibility contrast MRI relies on field inhomogeneities caused by the presence of the paramagnetic agent. The usual method for calculation of the concentration from dynamic T2*-weighted images is based on two key assumptions: 1) a linear relation between the change in R2* and the contrast agent concentration, and 2) a negligible effect on the MR signal due to concurrent T1 changes. In this study the effect of inaccuracies in these two assumptions on perfusion measurements was investigated using simulations and in vivo data. The results of the simulations provide a quantitative characterization of the magnitude of these effects for various experimental conditions (e.g., when a 1-sec TR is used with TE=20 ms, the T1 effects can introduce up to 40% cerebral blood flow underestimation depending on the flip angle). These findings can be used as a guide to estimate the errors in specific practical implementations, as well as to optimize the sequence parameters to minimize their effect. In summary, this study shows that the arterial input function measurement should be corrected for nonlinear R2* effects and that care should be taken in the study design to avoid introducing significant T1 effects in perfusion quantification.
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23
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Zhang X, Nagaoka T, Auerbach EJ, Champion R, Zhou L, Hu X, Duong TQ. Quantitative basal CBF and CBF fMRI of rhesus monkeys using three-coil continuous arterial spin labeling. Neuroimage 2006; 34:1074-83. [PMID: 17126036 PMCID: PMC2943966 DOI: 10.1016/j.neuroimage.2006.10.011] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2006] [Revised: 09/18/2006] [Accepted: 10/11/2006] [Indexed: 01/03/2023] Open
Abstract
A three-coil continuous arterial-spin-labeling technique with a separate neck labeling coil was implemented on a Siemens 3T Trio for quantitative cerebral blood flow (CBF) and CBF fMRI measurements in non-human primates (rhesus monkeys). The optimal labeling power was 2 W, labeling efficiency was 92+/-2%, and optimal post-labeling delay was 0.8 s. Gray matter (GM) and white matter (WM) were segmented based on T1 maps. Quantitative CBF were obtained in 3 min with 1.5-mm isotropic resolution. Whole-brain average DeltaS/S was 1.0-1.5%. GM CBF was 104+/-3 ml/100 g/min (n = 6, SD) and WM CBF was 45+/-6 ml/100 g/min in isoflurane-anesthetized rhesus monkeys, with the CBF GM/WM ratio of 2.3+/-0.2. Combined CBF and BOLD (blood-oxygenation-level-dependent) fMRI associated with hypercapnia and hyperoxia were made with 8-s temporal resolution. CBF fMRI responses to 5% CO2 were 59+/-10% (GM) and 37+/-4% (WM); BOLD fMRI responses were 2.0+/-0.4% (GM) and 1.2+/-0.4% (WM). CBF fMRI responses to 100% O2 were -9.4+/-2% (GM) and -3.9+/-2.6% (WM); BOLD responses were 2.4+/-0.7% (GM) and 0.8+/-0.2% (WM). The use of a separate neck coil for spin labeling significantly increased CBF signal-to-noise ratio and the use of small receive-only surface coil significantly increased signal-to-noise ratio and spatial resolution. This study sets the stage for quantitative perfusion imaging and CBF fMRI for neurological diseases in anesthetized and awake monkeys.
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Affiliation(s)
- Xiaodong Zhang
- Yerkes Imaging Center, Yerkes National Primate Research Center, Neurology, Emory University, 954 Gatewood Road, Atlanta, GA 30329, USA
| | - Tsukasa Nagaoka
- Yerkes Imaging Center, Yerkes National Primate Research Center, Neurology, Emory University, 954 Gatewood Road, Atlanta, GA 30329, USA
| | - Edward J. Auerbach
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, MN, USA
| | - Robbie Champion
- Yerkes Imaging Center, Yerkes National Primate Research Center, Neurology, Emory University, 954 Gatewood Road, Atlanta, GA 30329, USA
| | - Lei Zhou
- Biomedical Imaging Technology Center, Department of Biomedical Engineering, Emory University, GA, USA
| | - Xiaoping Hu
- Biomedical Imaging Technology Center, Department of Biomedical Engineering, Emory University, GA, USA
| | - Timothy Q. Duong
- Yerkes Imaging Center, Yerkes National Primate Research Center, Neurology, Emory University, 954 Gatewood Road, Atlanta, GA 30329, USA
- Corresponding author. Fax: +1 404 712 9917. (T.Q. Duong)
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