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Roudi R, Pisani LJ, Pisani F, Liang T, Daldrup-Link HE. Reproducibility and repeatability of quantitative T2 and T2* mapping of osteosarcomas in a mouse model. Eur Radiol Exp 2024; 8:74. [PMID: 38872042 DOI: 10.1186/s41747-024-00467-9] [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: 02/12/2024] [Accepted: 04/10/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND New immunotherapies activate tumor-associated macrophages (TAMs) in the osteosarcoma microenvironment. Iron oxide nanoparticles (IONPs) are phagocytosed by TAMs and, therefore, enable TAM detection on T2*- and T2-weighted magnetic resonance images. We assessed the repeatability and reproducibility of T2*- and T2-mapping of osteosarcomas in a mouse model. METHODS Fifteen BALB/c mice bearing-murine osteosarcomas underwent magnetic resonance imaging (MRI) on 3-T and 7-T scanners before and after intravenous IONP infusion, using T2*-weighted multi-gradient-echo, T2-weighted fast spin-echo, and T2-weighted multi-echo sequences. Each sequence was repeated twice. Tumor T2 and T2* relaxation times were measured twice by two independent investigators. Repeatability and reproducibility of measurements were assessed. RESULTS We found excellent agreement between duplicate acquisitions for both T2* and T2 measurements at either magnetic field strength, by the same individual (repeatability), and between individuals (reproducibility). The repeatability concordance correlation coefficient (CCC) for T2* values were 0.99 (coefficients of variation (CoV) 4.43%) for reader 1 and 0.98 (CoV 5.82%) for reader 2. The reproducibility of T2* values between the two readers was 0.99 (CoV 3.32%) for the first acquisitions and 0.99 (CoV 6.30%) for the second acquisitions. Regarding T2 values, the repeatability of CCC was similar for both readers, 0.98 (CoV 3.64% for reader 1 and 4.45% for reader 2). The CCC of the reproducibility of T2 was 0.99 (CoV 3.1%) for the first acquisition and 0.98 (CoV 4.38%) for the second acquisition. CONCLUSIONS Our results demonstrated high repeatability and reproducibility of quantitative T2* and T2 mapping for monitoring the presence of TAMs in osteosarcomas. RELEVANCE STATEMENT T2* and T2 measurements of osteosarcomas on IONP-enhanced MRI could allow identifying patients who may benefit from TAM-modulating immunotherapies and for monitoring treatment response. The technique described here could be also applied across a wide range of other solid tumors. KEY POINTS • Optimal integration of TAM-modulating immunotherapies with conventional chemotherapy remains poorly elucidated. • We found high repeatability of T2* and T2 measurements of osteosarcomas in a mouse model, both with and without IONPs contrast, at 3-T and 7-T MRI field strengths. • T2 and T2* mapping may be used to determine response to macrophage-modulating cancer immunotherapies.
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Affiliation(s)
- Raheleh Roudi
- Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, Stanford, CA, 94305, USA.
| | - Laura J Pisani
- Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, Stanford, CA, 94305, USA
| | - Fabrizio Pisani
- Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, Stanford, CA, 94305, USA
| | - Tie Liang
- Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, Stanford, CA, 94305, USA
| | - Heike E Daldrup-Link
- Department of Radiology, Molecular Imaging Program at Stanford, Stanford University, Stanford, CA, 94305, USA.
- Department of Pediatrics, Hematology/Oncology, Stanford University School of Medicine, Stanford, CA, USA.
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Bano W, Holmes W, Goodburn R, Golbabaee M, Gupta A, Withey S, Tree A, Oelfke U, Wetscherek A. Joint radial trajectory correction for accelerated T 2 * mapping on an MR-Linac. Med Phys 2023; 50:7027-7038. [PMID: 37245075 PMCID: PMC10946747 DOI: 10.1002/mp.16479] [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: 08/04/2022] [Revised: 04/20/2023] [Accepted: 04/28/2023] [Indexed: 05/29/2023] Open
Abstract
BACKGROUND T2 * mapping can characterize tumor hypoxia, which may be associated with resistance to therapy. Acquiring T2 * maps during MR-guided radiotherapy could inform treatment adaptation by, for example, escalating the dose to resistant sub-volumes. PURPOSE The purpose of this work is to demonstrate the feasibility of the accelerated T2 * mapping technique using model-based image reconstruction with integrated trajectory auto-correction (TrACR) for MR-guided radiotherapy on an MR-Linear accelerator (MR-Linac). MATERIALS AND METHODS The proposed method was validated in a numerical phantom, where two T2 * mapping approaches (sequential and joint) were compared for different noise levels (0,0.1,0.5,1) and gradient delays ([1, -1] and [1, -2] in units of dwell time for x- and y-axis, respectively). Fully sampled k-space was retrospectively undersampled using two different undersampling patterns. Root mean square errors (RMSEs) were calculated between reconstructed T2 * maps and ground truth. In vivo data was acquired twice weekly in one prostate and one head and neck cancer patient undergoing treatment on a 1.5 T MR-Linac. Data were retrospectively undersampled and T2 * maps reconstructed, with and without trajectory corrections were compared. RESULTS Numerical simulations demonstrated that, for all noise levels, T2 * maps reconstructed with a joint approach demonstrated less error compared to an uncorrected and sequential approach. For a noise level of 0.1, uniform undersampling and gradient delay [1, -1] (in units of dwell time for x- and y-axis, respectively), RMSEs for sequential and joint approaches were 13.01 and 9.32 ms, respectively, which reduced to 10.92 and 5.89 ms for a gradient delay of [1, 2]. Similarly, for alternate undersampling and gradient delay [1, -1], RMSEs for sequential and joint approaches were 9.80 and 8.90 ms, respectively, which reduced to 9.10 and 5.40 ms for gradient delay [1, 2]. For in vivo data, T2 * maps reconstructed with our proposed approach resulted in less artifacts and improved visual appearance compared to the uncorrected approach. For both prostate and head and neck cancer patients, T2 * maps reconstructed from different treatment fractions showed changes within the planning target volume (PTV). CONCLUSION Using the proposed approach, a retrospective data-driven gradient delay correction can be performed, which is particularly relevant for hybrid devices, where full information on the machine configuration is not available for image reconstruction. T2 * maps were acquired in under 5 min and can be integrated into MR-guided radiotherapy treatment workflows, which minimizes patient burden and leaves time for additional imaging for online adaptive radiotherapy on an MR-Linac.
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Affiliation(s)
- Wajiha Bano
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUK
| | - Will Holmes
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUK
| | - Rosie Goodburn
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUK
| | | | - Amit Gupta
- The Royal Marsden NHS Foundation Trust and The Institute of Cancer ResearchLondonUK
| | - Sam Withey
- The Royal Marsden NHS Foundation Trust and The Institute of Cancer ResearchLondonUK
| | - Alison Tree
- The Royal Marsden NHS Foundation Trust and The Institute of Cancer ResearchLondonUK
| | - Uwe Oelfke
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUK
| | - Andreas Wetscherek
- Joint Department of PhysicsThe Institute of Cancer Research and The Royal Marsden NHS Foundation TrustLondonUK
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Kooreman ES, van Pelt V, Nowee ME, Pos F, van der Heide UA, van Houdt PJ. Longitudinal Correlations Between Intravoxel Incoherent Motion (IVIM) and Dynamic Contrast-Enhanced (DCE) MRI During Radiotherapy in Prostate Cancer Patients. Front Oncol 2022; 12:897130. [PMID: 35747819 PMCID: PMC9210504 DOI: 10.3389/fonc.2022.897130] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/03/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose Intravoxel incoherent motion (IVIM) is a promising technique that can acquire perfusion information without the use of contrast agent, contrary to the more established dynamic contrast-enhanced (DCE) technique. This is of interest for treatment response monitoring, where patients can be imaged on each treatment fraction. In this study, longitudinal correlations between IVIM- and DCE parameters were assessed in prostate cancer patients receiving radiation treatment. Materials and Methods 20 prostate cancer patients were treated on a 1.5 T MR-linac with 20 x 3 or 3.1 Gy. Weekly IVIM and DCE scans were acquired. Tumors, the peripheral zone (PZ), and the transition zone (TZ) were delineated on a T2-weighted scan acquired on the first fraction. IVIM and DCE scans were registered to this scan and the delineations were propagated. Median values from these delineations were used for further analysis. The IVIM parameters D, f, D* and the product fD* were calculated. The Tofts model was used to calculate the DCE parameters Ktrans, kep and ve. Pearson correlations were calculated for the IVIM and DCE parameters on values from the first fraction for each region of interest (ROI). For longitudinal analysis, the repeated measures correlation coefficient was used to determine correlations between IVIM and DCE parameters in each ROI. Results When averaging over patients, an increase during treatment in all IVIM and DCE parameters was observed in all ROIs, except for D in the PZ and TZ. No significant Pearson correlations were found between any pair of IVIM and DCE parameters measured on the first fraction. Significant but low longitudinal correlations were found for some combinations of IVIM and DCE parameters in the PZ and TZ, while no significant longitudinal correlations were found in the tumor. Notably in the TZ, for both f and fD*, significant longitudinal correlations with all DCE parameters were found. Conclusions The increase in IVIM- and DCE parameters when averaging over patients indicates a measurable response to radiation treatment with both techniques. Although low, significant longitudinal correlations were found which suggests that IVIM could potentially be used as an alternative to DCE for treatment response monitoring.
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Kim Y, Park JJ, Kim CK. Blood oxygenation level-dependent MRI at 3T for differentiating prostate cancer from benign tissue: a preliminary experience. Br J Radiol 2022; 95:20210461. [PMID: 34235962 PMCID: PMC8978237 DOI: 10.1259/bjr.20210461] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
OBJECTIVE Blood oxygenation-level dependent (BOLD) MRI may identify or quantify the regional distribution of hypoxia within a tumor. We aimed to evaluate the feasibility of BOLD MRI at 3 T in differentiating prostate cancer from benign tissue. METHODS A total of 145 patients with biopsy-proven prostate cancer underwent BOLD MRI at 3 T. BOLD MRI was performed using a multiple fast field echo sequence to acquire 12 T2*-weighted images. The R2* value (rate of relaxation, s-1) was measured in the index tumor, and benign peripheral (PZ) and transition zone (TZ), and the results were compared. The variability of R2* measurements was evaluated. RESULTS Tumor R2* values (25.95 s-1) were significantly different from the benign PZ (27.83 s-1) and benign TZ (21.66 s-1) (p < 0.001). For identifying the tumor, the area under the receiver operating characteristic of R2* was 0.606, with an optimal cut-off value of 22.8 s-1 resulting in 73.8% sensitivity and 52% specificity. In the Bland-Altman test, the mean differences in R2* values were 8.5% for tumors, 13.3% for benign PZ, and 6.8% for benign TZ. No associations between tumor R2* value and Gleason score, age, prostate volume, prostate-specific antigen, or tumor size. CONCLUSION BOLD MRI at 3 T appears to be a feasible tool for differentiating between prostate cancer and benign tissue. However, further studies are required for a direct clinical application. ADVANCES IN KNOWLEDGE The R2* values are significantly different among prostate cancer, benign PZ, and benign TZ.
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Affiliation(s)
- Yongtae Kim
- Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jung Jae Park
- Department of Radiology, Chungnam National University Hospital, Daejeon, Republic of Korea
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Zabel WJ, Allam N, Foltz WD, Flueraru C, Taylor E, Vitkin IA. Bridging the macro to micro resolution gap with angiographic optical coherence tomography and dynamic contrast enhanced MRI. Sci Rep 2022; 12:3159. [PMID: 35210476 PMCID: PMC8873467 DOI: 10.1038/s41598-022-07000-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 02/09/2022] [Indexed: 11/25/2022] Open
Abstract
Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is emerging as a valuable tool for non-invasive volumetric monitoring of the tumor vascular status and its therapeutic response. However, clinical utility of DCE-MRI is challenged by uncertainty in its ability to quantify the tumor microvasculature (\documentclass[12pt]{minimal}
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\begin{document}$$\mu \mathrm{m}$$\end{document}μm scale) given its relatively poor spatial resolution (mm scale at best). To address this challenge, we directly compared DCE-MRI parameter maps with co-registered micron-scale-resolution speckle variance optical coherence tomography (svOCT) microvascular images in a window chamber tumor mouse model. Both semi and fully quantitative (Toft’s model) DCE-MRI metrics were tested for correlation with microvascular svOCT biomarkers. svOCT’s derived vascular volume fraction (VVF) and the mean distance to nearest vessel (\documentclass[12pt]{minimal}
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\begin{document}$$P<0.0001$$\end{document}P<0.0001 for both), the area under the gadolinium-time concentration curve (\documentclass[12pt]{minimal}
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\begin{document}$$P<0.0001$$\end{document}P<0.0001 for both) and \documentclass[12pt]{minimal}
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\begin{document}$$P<0.0001$$\end{document}P<0.0001 for both). Several other correlated micro–macro vascular metric pairs were also noted. The microvascular insights afforded by svOCT may help improve the clinical utility of DCE-MRI for tissue functional status assessment and therapeutic response monitoring applications.
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Affiliation(s)
- W Jeffrey Zabel
- Department of Medical Biophysics, University of Toronto, Toronto, Canada.
| | - Nader Allam
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Warren D Foltz
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Costel Flueraru
- National Research Council Canada, Information Communication Technology, Ottawa, Canada
| | - Edward Taylor
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - I Alex Vitkin
- Department of Medical Biophysics, University of Toronto, Toronto, Canada.,Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Canada.,Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
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Wang YF, Tadimalla S, Hayden AJ, Holloway L, Haworth A. Artificial intelligence and imaging biomarkers for prostate radiation therapy during and after treatment. J Med Imaging Radiat Oncol 2021; 65:612-626. [PMID: 34060219 DOI: 10.1111/1754-9485.13242] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/18/2021] [Accepted: 05/02/2021] [Indexed: 12/15/2022]
Abstract
Magnetic resonance imaging (MRI) is increasingly used in the management of prostate cancer (PCa). Quantitative MRI (qMRI) parameters, derived from multi-parametric MRI, provide indirect measures of tumour characteristics such as cellularity, angiogenesis and hypoxia. Using Artificial Intelligence (AI), relevant information and patterns can be efficiently identified in these complex data to develop quantitative imaging biomarkers (QIBs) of tumour function and biology. Such QIBs have already demonstrated potential in the diagnosis and staging of PCa. In this review, we explore the role of these QIBs in monitoring treatment response during and after PCa radiotherapy (RT). Recurrence of PCa after RT is not uncommon, and early detection prior to development of metastases provides an opportunity for salvage treatments with curative intent. However, the current method of monitoring treatment response using prostate-specific antigen levels lacks specificity. QIBs, derived from qMRI and developed using AI techniques, can be used to monitor biological changes post-RT providing the potential for accurate and early diagnosis of recurrent disease.
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Affiliation(s)
- Yu-Feng Wang
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
| | - Sirisha Tadimalla
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
| | - Amy J Hayden
- Sydney West Radiation Oncology, Westmead Hospital, Wentworthville, New South Wales, Australia
- Faculty of Medicine, Western Sydney University, Sydney, New South Wales, Australia
- Faculty of Medicine, Health & Human Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Lois Holloway
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
- Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia
- Liverpool and Macarthur Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia
| | - Annette Haworth
- Institute of Medical Physics, School of Physics, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia
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Quantitative MRI: Defining repeatability, reproducibility and accuracy for prostate cancer imaging biomarker development. Magn Reson Imaging 2021; 77:169-179. [PMID: 33388362 DOI: 10.1016/j.mri.2020.12.018] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/25/2020] [Accepted: 12/29/2020] [Indexed: 01/09/2023]
Abstract
INTRODUCTION Quantitative MRI (qMRI) parameters have been increasingly used to develop predictive models to accurately monitor treatment response in prostate cancer after radiotherapy. To reliably detect changes in signal due to treatment response, predictive models require qMRI parameters with high repeatability and reproducibility. The purpose of this study was to measure qMRI parameter uncertainties in both commercial and in-house developed phantoms to guide the development of robust predictive models for monitoring treatment response. MATERIALS AND METHODS ADC, T1, and R2* values were acquired across three 3 T scanners with a prostate-specific qMRI protocol using the NIST/ISMRM system phantom, RSNA/NIST diffusion phantom, and an in-house phantom. A B1 field map was acquired to correct for flip angle inhomogeneity in T1 maps. All sequences were repeated in each scan to assess within-session repeatability. Weekly scans were acquired on one scanner for three months with the in-house phantom. Between-session repeatability was measured with test-retest scans 6-months apart on all scanners with all phantoms. Accuracy, defined as percentage deviation from reference value for ADC and T1, was evaluated using the system and diffusion phantoms. Repeatability and reproducibility coefficients of variation (%CV) were calculated for all qMRI parameters on all phantoms. RESULTS Overall, repeatability CV of ADC was <2.40%, reproducibility CV was <3.98%, and accuracy ranged between -8.0% to 2.7% across all scanners. Applying B1 correction on T1 measurements significantly improved the repeatability and reproducibility (p<0.05) but increased error in accuracy (p<0.001). Repeatability and reproducibility of R2* was <4.5% and <7.3% respectively in the system phantom across all scanners. CONCLUSION Repeatability, reproducibility, and accuracy in qMRI parameters from a prostate-specific protocol was estimated using both commercial and in-house phantoms. Results from this work will be used to identify robust qMRI parameters for use in the development of predictive models to longitudinally monitor treatment response for prostate cancer in current and future clinical trials.
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Okada T, Suzuki H, Travis ZD, Zhang JH. The Stroke-Induced Blood-Brain Barrier Disruption: Current Progress of Inspection Technique, Mechanism, and Therapeutic Target. Curr Neuropharmacol 2020; 18:1187-1212. [PMID: 32484111 PMCID: PMC7770643 DOI: 10.2174/1570159x18666200528143301] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 04/23/2020] [Accepted: 05/23/2020] [Indexed: 02/07/2023] Open
Abstract
Stroke is one of the leading causes of mortality and morbidity worldwide. The blood-brain barrier (BBB) is a characteristic structure of microvessel within the brain. Under normal physiological conditions, the BBB plays a role in the prevention of harmful substances entering into the brain parenchyma within the central nervous system. However, stroke stimuli induce the breakdown of BBB leading to the influx of cytotoxic substances, vasogenic brain edema, and hemorrhagic transformation. Therefore, BBB disruption is a major complication, which needs to be addressed in order to improve clinical outcomes in stroke. In this review, we first discuss the structure and function of the BBB. Next, we discuss the progress of the techniques utilized to study BBB breakdown in in-vitro and in-vivo studies, along with biomarkers and imaging techniques in clinical settings. Lastly, we highlight the mechanisms of stroke-induced neuroinflammation and apoptotic process of endothelial cells causing BBB breakdown, and the potential therapeutic targets to protect BBB integrity after stroke. Secondary products arising from stroke-induced tissue damage provide transformation of myeloid cells such as microglia and macrophages to pro-inflammatory phenotype followed by further BBB disruption via neuroinflammation and apoptosis of endothelial cells. In contrast, these myeloid cells are also polarized to anti-inflammatory phenotype, repairing compromised BBB. Therefore, therapeutic strategies to induce anti-inflammatory phenotypes of the myeloid cells may protect BBB in order to improve clinical outcomes of stroke patients.
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Affiliation(s)
- Takeshi Okada
- Department of Physiology and Pharmacology, Loma Linda University, Loma Linda, CA, USA, Risley Hall, Room 219,
11041 Campus St, Loma Linda, CA 92354, USA,Department of Neurosurgery, Mie University Graduate School of Medicine, Mie, Japan, 2-174 Edobashi, Tsu, Mie 514-8507, Japan
| | - Hidenori Suzuki
- Department of Neurosurgery, Mie University Graduate School of Medicine, Mie, Japan, 2-174 Edobashi, Tsu, Mie 514-8507, Japan
| | - Zachary D Travis
- Department of Physiology and Pharmacology, Loma Linda University, Loma Linda, CA, USA, Risley Hall, Room 219,
11041 Campus St, Loma Linda, CA 92354, USA,Department of Earth and Biological Sciences, Loma Linda University, Loma Linda, CA, USA , Risley Hall, Room 219, 11041 Campus St, Loma Linda, CA 92354, USA
| | - John H Zhang
- Department of Physiology and Pharmacology, Loma Linda University, Loma Linda, CA, USA, Risley Hall, Room 219,
11041 Campus St, Loma Linda, CA 92354, USA,Department of Anesthesiology, Loma Linda University, Loma Linda, CA, USA, Risley Hall, Room 219, 11041 Campus St, Loma Linda, CA 92354, USA,Department of Neurosurgery, Loma Linda University, Loma Linda, CA, USA, Risley Hall, Room 219, 11041 Campus St, Loma Linda, CA 92354, USA
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Knight SP, Meaney JF, Fagan AJ. DCE‐MRI protocol for constraining absolute pharmacokinetic modeling errors within specific accuracy limits. Med Phys 2019; 46:3592-3602. [DOI: 10.1002/mp.13635] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 04/30/2019] [Accepted: 05/21/2019] [Indexed: 01/01/2023] Open
Affiliation(s)
- Silvin P. Knight
- School of Medicine Trinity College University of Dublin Dublin Ireland
- National Centre for Advanced Medical Imaging (CAMI) St James's Hospital Dublin Ireland
| | - James F. Meaney
- School of Medicine Trinity College University of Dublin Dublin Ireland
- National Centre for Advanced Medical Imaging (CAMI) St James's Hospital Dublin Ireland
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Schwier M, van Griethuysen J, Vangel MG, Pieper S, Peled S, Tempany C, Aerts HJWL, Kikinis R, Fennessy FM, Fedorov A. Repeatability of Multiparametric Prostate MRI Radiomics Features. Sci Rep 2019; 9:9441. [PMID: 31263116 PMCID: PMC6602944 DOI: 10.1038/s41598-019-45766-z] [Citation(s) in RCA: 147] [Impact Index Per Article: 29.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2018] [Accepted: 06/12/2019] [Indexed: 12/17/2022] Open
Abstract
In this study we assessed the repeatability of radiomics features on small prostate tumors using test-retest Multiparametric Magnetic Resonance Imaging (mpMRI). The premise of radiomics is that quantitative image-based features can serve as biomarkers for detecting and characterizing disease. For such biomarkers to be useful, repeatability is a basic requirement, meaning its value must remain stable between two scans, if the conditions remain stable. We investigated repeatability of radiomics features under various preprocessing and extraction configurations including various image normalization schemes, different image pre-filtering, and different bin widths for image discretization. Although we found many radiomics features and preprocessing combinations with high repeatability (Intraclass Correlation Coefficient > 0.85), our results indicate that overall the repeatability is highly sensitive to the processing parameters. Neither image normalization, using a variety of approaches, nor the use of pre-filtering options resulted in consistent improvements in repeatability. We urge caution when interpreting radiomics features and advise paying close attention to the processing configuration details of reported results. Furthermore, we advocate reporting all processing details in radiomics studies and strongly recommend the use of open source implementations.
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Affiliation(s)
- Michael Schwier
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | | | - Mark G Vangel
- Harvard Medical School, Boston, MA, USA
- Massachusetts General Hospital, Charlestown, MA, USA
| | | | - Sharon Peled
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Clare Tempany
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Hugo J W L Aerts
- Harvard Medical School, Boston, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
| | - Ron Kikinis
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Fraunhofer MEVIS, Bremen, Germany
- Mathematics/Computer Science Faculty, University of Bremen, Bremen, Germany
| | - Fiona M Fennessy
- Brigham and Women's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
| | - Andriy Fedorov
- Brigham and Women's Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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11
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Winfield JM, Miah AB, Strauss D, Thway K, Collins DJ, deSouza NM, Leach MO, Morgan VA, Giles SL, Moskovic E, Hayes A, Smith M, Zaidi SH, Henderson D, Messiou C. Utility of Multi-Parametric Quantitative Magnetic Resonance Imaging for Characterization and Radiotherapy Response Assessment in Soft-Tissue Sarcomas and Correlation With Histopathology. Front Oncol 2019; 9:280. [PMID: 31106141 PMCID: PMC6494941 DOI: 10.3389/fonc.2019.00280] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Accepted: 03/27/2019] [Indexed: 02/05/2023] Open
Abstract
Purpose: To evaluate repeatability of quantitative multi-parametric MRI in retroperitoneal sarcomas, assess parameter changes with radiotherapy, and correlate pre-operative values with histopathological findings in the surgical specimens. Materials and Methods: Thirty patients with retroperitoneal sarcoma were imaged at baseline, of whom 27 also underwent a second baseline examination for repeatability assessment. 14/30 patients were treated with pre-operative radiotherapy and were imaged again after completing radiotherapy (50.4 Gy in 28 daily fractions, over 5.5 weeks). The following parameter estimates were assessed in the whole tumor volume at baseline and following radiotherapy: apparent diffusion coefficient (ADC), parameters of the intra-voxel incoherent motion model of diffusion-weighted MRI (D, f, D*), transverse relaxation rate, fat fraction, and enhancing fraction after gadolinium-based contrast injection. Correlation was evaluated between pre-operative quantitative parameters and histopathological assessments of cellularity and fat fraction in post-surgical specimens (ClinicalTrials.gov, registration number NCT01902667). Results: Upper and lower 95% limits of agreement were 7.1 and -6.6%, respectively for median ADC at baseline. Median ADC increased significantly post-radiotherapy. Pre-operative ADC and D were negatively correlated with cellularity (r = -0.42, p = 0.01, 95% confidence interval (CI) -0.22 to -0.59 for ADC; r = -0.45, p = 0.005, 95% CI -0.25 to -0.62 for D), and fat fraction from Dixon MRI showed strong correlation with histopathological assessment of fat fraction (r = 0.79, p = 10-7, 95% CI 0.69-0.86). Conclusion: Fat fraction on MRI corresponded to fat content on histology and therefore contributes to lesion characterization. Measurement repeatability was excellent for ADC; this parameter increased significantly post-radiotherapy even in disease categorized as stable by size criteria, and corresponded to cellularity on histology. ADC can be utilized for characterizing and assessing response in heterogeneous retroperitoneal sarcomas.
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Affiliation(s)
- Jessica M. Winfield
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Aisha B. Miah
- Sarcoma Unit, Department of Radiotherapy and Physics, The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
| | - Dirk Strauss
- Department of Surgery, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Khin Thway
- Sarcoma Unit, Department of Radiotherapy and Physics, The Royal Marsden NHS Foundation Trust, London, United Kingdom
- Department of Histopathology, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - David J. Collins
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Nandita M. deSouza
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Martin O. Leach
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
| | - Veronica A. Morgan
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Sharon L. Giles
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Eleanor Moskovic
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
| | - Andrew Hayes
- Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Surgery, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Myles Smith
- Department of Surgery, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Shane H. Zaidi
- Sarcoma Unit, Department of Radiotherapy and Physics, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Daniel Henderson
- Sarcoma Unit, Department of Radiotherapy and Physics, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Christina Messiou
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- Department of Radiology, The Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
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12
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Klawer EME, van Houdt PJ, Simonis FFJ, van den Berg CAT, Pos FJ, Heijmink SWTPJ, Isebaert S, Haustermans K, van der Heide UA. Improved repeatability of dynamic contrast-enhanced MRI using the complex MRI signal to derive arterial input functions: a test-retest study in prostate cancer patients. Magn Reson Med 2019; 81:3358-3369. [PMID: 30656738 PMCID: PMC6590420 DOI: 10.1002/mrm.27646] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 11/07/2018] [Accepted: 12/04/2018] [Indexed: 12/31/2022]
Abstract
Purpose The arterial input function (AIF) is a major source of uncertainty in tracer kinetic (TK) analysis of dynamic contrast‐enhanced (DCE)‐MRI data. The aim of this study was to investigate the repeatability of AIFs extracted from the complex signal and of the resulting TK parameters in prostate cancer patients. Methods Twenty‐two patients with biopsy‐proven prostate cancer underwent a 3T MRI exam twice. DCE‐MRI data were acquired with a 3D spoiled gradient echo sequence. AIFs were extracted from the magnitude of the signal (AIFMAGN), phase (AIFPHASE), and complex signal (AIFCOMPLEX). The Tofts model was applied to extract Ktrans, kep and ve. Repeatability of AIF curve characteristics and TK parameters was assessed with the within‐subject coefficient of variation (wCV). Results The wCV for peak height and full width at half maximum for AIFCOMPLEX (7% and 8%) indicated an improved repeatability compared to AIFMAGN (12% and 12%) and AIFPHASE (12% and 7%). This translated in lower wCV values for Ktrans (11%) with AIFCOMPLEX in comparison to AIFMAGN (24%) and AIFPHASE (15%). For kep, the wCV was 16% with AIFMAGN, 13% with AIFPHASE, and 13% with AIFCOMPLEX. Conclusion Repeatability of AIFPHASE and AIFCOMPLEX is higher than for AIFMAGN, resulting in a better repeatability of TK parameters. Thus, use of either AIFPHASE or AIFCOMPLEX improves the robustness of quantitative analysis of DCE‐MRI in prostate cancer.
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Affiliation(s)
- Edzo M E Klawer
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Petra J van Houdt
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Frank F J Simonis
- Department of Radiation Oncology, Imaging Division, University Medical Center, Utrecht, The Netherlands
| | - Cornelis A T van den Berg
- Department of Radiation Oncology, Imaging Division, University Medical Center, Utrecht, The Netherlands
| | - Floris J Pos
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, The Netherlands
| | | | - Sofie Isebaert
- Department of Radiation Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium
| | - Karin Haustermans
- Department of Radiation Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium
| | - Uulke A van der Heide
- Department of Radiation Oncology, the Netherlands Cancer Institute, Amsterdam, The Netherlands
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13
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Shukla-Dave A, Obuchowski NA, Chenevert TL, Jambawalikar S, Schwartz LH, Malyarenko D, Huang W, Noworolski SM, Young RJ, Shiroishi MS, Kim H, Coolens C, Laue H, Chung C, Rosen M, Boss M, Jackson EF. Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials. J Magn Reson Imaging 2018; 49:e101-e121. [PMID: 30451345 DOI: 10.1002/jmri.26518] [Citation(s) in RCA: 219] [Impact Index Per Article: 36.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 09/06/2018] [Accepted: 09/06/2018] [Indexed: 12/14/2022] Open
Abstract
Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion-weighted imaging and dynamic contrast-enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101-e121.
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Affiliation(s)
- Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Nancy A Obuchowski
- Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Thomas L Chenevert
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Sachin Jambawalikar
- Department of Radiology, Columbia University Irving Medical Center, New York, New York, USA
| | - Lawrence H Schwartz
- Department of Radiology, Columbia University Irving Medical Center, New York, New York, USA
| | - Dariya Malyarenko
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Wei Huang
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Susan M Noworolski
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Robert J Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Mark S Shiroishi
- Division of Neuroradiology, Department of Radiology, University of Southern California, Los Angeles, California, USA
| | - Harrison Kim
- Department of Radiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Catherine Coolens
- Department of Radiation Oncology, Princess Margaret Cancer Centre, Toronto, Canada
| | | | - Caroline Chung
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas, USA
| | - Mark Rosen
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Michael Boss
- Applied Physics Division, National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Edward F Jackson
- Departments of Medical Physics, Radiology, and Human Oncology, University of Wisconsin School of Medicine, Madison, Wisconsin, USA
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14
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A simulation study comparing nine mathematical models of arterial input function for dynamic contrast enhanced MRI to the Parker model. AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE 2018; 41:507-518. [DOI: 10.1007/s13246-018-0632-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 03/20/2018] [Indexed: 02/06/2023]
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15
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Multiparametric Magnetic Resonance Imaging of the Prostate: Repeatability of Volume and Apparent Diffusion Coefficient Quantification. Invest Radiol 2018; 52:538-546. [PMID: 28463931 PMCID: PMC5544576 DOI: 10.1097/rli.0000000000000382] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVES The aim of this study was to evaluate the repeatability of a region of interest (ROI) volume and mean apparent diffusion coefficient (ADC) in standard-of-care 3 T multiparametric magnetic resonance imaging (mpMRI) of the prostate obtained with the use of endorectal coil. MATERIALS AND METHODS This prospective study was Health Insurance Portability and Accountability Act compliant, with institutional review board approval and written informed consent. Men with confirmed or suspected treatment-naive prostate cancer scheduled for mpMRI were offered a repeat mpMRI within 2 weeks. Regions of interest corresponding to the whole prostate gland, the entire peripheral zone (PZ), normal PZ, and suspected tumor ROI (tROI) on axial T2-weighted, dynamic contrast-enhanced subtract, and ADC images were annotated and assessed using Prostate Imaging Reporting and Data System (PI-RADS) v2. Repeatability of the ROI volume for each of the analyzed image types and mean ROI ADC was summarized with repeatability coefficient (RC) and RC%. RESULTS A total of 189 subjects were approached to participate in the study. Of 40 patients that gave initial agreement, 15 men underwent 2 mpMRI examinations and completed the study. Peripheral zone tROIs were identified in 11 subjects. Tumor ROI volume was less than 0.5 mL in 8 of 11 subjects. PI-RADS categories were identical between baseline-repeat studies in 11/15 subjects and differed by 1 point in 4/15. Peripheral zone tROI volume RC (RC%) was 233 mm (71%) on axial T2-weighted, 422 mm (112%) on ADC, and 488 mm (119%) on dynamic contrast-enhanced subtract. Apparent diffusion coefficient ROI mean RC (RC%) were 447 × 10 mm/s (42%) in PZ tROI and 471 × 10 mm/s (30%) in normal PZ. Significant difference in repeatability of the tROI volume across series was observed (P < 0.005). The mean ADC RC% was lower than volume RC% for tROI ADC (P < 0.05). CONCLUSIONS PI-RADS v2 overall assessment was highly repeatable. Multiparametric magnetic resonance imaging sequences differ in volume measurement repeatability. The mean tROI ADC is more repeatable compared with tROI volume in ADC. Repeatability of prostate ADC is comparable with that in other abdominal organs.
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16
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Towards intrinsic R2* imaging in the prostate at 3 and 7 tesla. Magn Reson Imaging 2017; 42:16-21. [DOI: 10.1016/j.mri.2017.04.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2016] [Revised: 03/26/2017] [Accepted: 04/30/2017] [Indexed: 12/17/2022]
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17
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He D, Zamora M, Oto A, Karczmar GS, Fan X. Comparison of region-of-interest-averaged and pixel-averaged analysis of DCE-MRI data based on simulations and pre-clinical experiments. Phys Med Biol 2017; 62:N445-N459. [PMID: 28786402 DOI: 10.1088/1361-6560/aa84d6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Differences between region-of-interest (ROI) and pixel-by-pixel analysis of dynamic contrast enhanced (DCE) MRI data were investigated in this study with computer simulations and pre-clinical experiments. ROIs were simulated with 10, 50, 100, 200, 400, and 800 different pixels. For each pixel, a contrast agent concentration as a function of time, C(t), was calculated using the Tofts DCE-MRI model with randomly generated physiological parameters (K trans and v e) and the Parker population arterial input function. The average C(t) for each ROI was calculated and then K trans and v e for the ROI was extracted. The simulations were run 100 times for each ROI with new K trans and v e generated. In addition, white Gaussian noise was added to C(t) with 3, 6, and 12 dB signal-to-noise ratios to each C(t). For pre-clinical experiments, Copenhagen rats (n = 6) with implanted prostate tumors in the hind limb were used in this study. The DCE-MRI data were acquired with a temporal resolution of ~5 s in a 4.7 T animal scanner, before, during, and after a bolus injection (<5 s) of Gd-DTPA for a total imaging duration of ~10 min. K trans and v e were calculated in two ways: (i) by fitting C(t) for each pixel, and then averaging the pixel values over the entire ROI, and (ii) by averaging C(t) over the entire ROI, and then fitting averaged C(t) to extract K trans and v e. The simulation results showed that in heterogeneous ROIs, the pixel-by-pixel averaged K trans was ~25% to ~50% larger (p < 0.01) than the ROI-averaged K trans. At higher noise levels, the pixel-averaged K trans was greater than the 'true' K trans, but the ROI-averaged K trans was lower than the 'true' K trans. The ROI-averaged K trans was closer to the true K trans than pixel-averaged K trans for high noise levels. In pre-clinical experiments, the pixel-by-pixel averaged K trans was ~15% larger than the ROI-averaged K trans. Overall, with the Tofts model, the extracted physiological parameters from the pixel-by-pixel averages were larger than the ROI averages. These differences were dependent on the heterogeneity of the ROI.
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Affiliation(s)
- Dianning He
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, People's Republic of China. Department of Radiology, The University of Chicago, Chicago, IL 60637, United States of America
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18
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Incorporating Oxygen-Enhanced MRI into Multi-Parametric Assessment of Human Prostate Cancer. Diagnostics (Basel) 2017; 7:diagnostics7030048. [PMID: 28837092 PMCID: PMC5617948 DOI: 10.3390/diagnostics7030048] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Revised: 08/13/2017] [Accepted: 08/21/2017] [Indexed: 12/18/2022] Open
Abstract
Hypoxia is associated with prostate tumor aggressiveness, local recurrence, and biochemical failure. Magnetic resonance imaging (MRI) offers insight into tumor pathophysiology and recent reports have related transverse relaxation rate (R2*) and longitudinal relaxation rate (R1) measurements to tumor hypoxia. We have investigated the inclusion of oxygen-enhanced MRI for multi-parametric evaluation of tumor malignancy. Multi-parametric MRI sequences at 3 Tesla were evaluated in 10 patients to investigate hypoxia in prostate cancer prior to radical prostatectomy. Blood oxygen level dependent (BOLD), tissue oxygen level dependent (TOLD), dynamic contrast enhanced (DCE), and diffusion weighted imaging MRI were intercorrelated and compared with the Gleason score. The apparent diffusion coefficient (ADC) was significantly lower in tumor than normal prostate. Baseline R2* (BOLD-contrast) was significantly higher in tumor than normal prostate. Upon the oxygen breathing challenge, R2* decreased significantly in the tumor tissue, suggesting improved vascular oxygenation, however changes in R1 were minimal. R2* of contralateral normal prostate decreased in most cases upon oxygen challenge, although the differences were not significant. Moderate correlation was found between ADC and Gleason score. ADC and R2* were correlated and trends were found between Gleason score and R2*, as well as maximum-intensity-projection and area-under-the-curve calculated from DCE. Tumor ADC and R2* have been associated with tumor hypoxia, and thus the correlations are of particular interest. A multi-parametric approach including oxygen-enhanced MRI is feasible and promises further insights into the pathophysiological information of tumor microenvironment.
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19
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van Schie MA, Steenbergen P, Dinh CV, Ghobadi G, van Houdt PJ, Pos FJ, Heijmink SWTJP, van der Poel HG, Renisch S, Vik T, van der Heide UA. Repeatability of dose painting by numbers treatment planning in prostate cancer radiotherapy based on multiparametric magnetic resonance imaging. ACTA ACUST UNITED AC 2017; 62:5575-5588. [DOI: 10.1088/1361-6560/aa75b8] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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20
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Knight SP, Browne JE, Meaney JF, Smith DS, Fagan AJ. A novel anthropomorphic flow phantom for the quantitative evaluation of prostate DCE-MRI acquisition techniques. Phys Med Biol 2016; 61:7466-7483. [PMID: 27694709 DOI: 10.1088/0031-9155/61/20/7466] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
A novel anthropomorphic flow phantom device has been developed, which can be used for quantitatively assessing the ability of magnetic resonance imaging (MRI) scanners to accurately measure signal/concentration time-intensity curves (CTCs) associated with dynamic contrast-enhanced (DCE) MRI. Modelling of the complex pharmacokinetics of contrast agents as they perfuse through the tumour capillary network has shown great promise for cancer diagnosis and therapy monitoring. However, clinical adoption has been hindered by methodological problems, resulting in a lack of consensus regarding the most appropriate acquisition and modelling methodology to use and a consequent wide discrepancy in published data. A heretofore overlooked source of such discrepancy may arise from measurement errors of tumour CTCs deriving from the imaging pulse sequence itself, while the effects on the fidelity of CTC measurement of using rapidly-accelerated sequences such as parallel imaging and compressed sensing remain unknown. The present work aimed to investigate these features by developing a test device in which 'ground truth' CTCs were generated and presented to the MRI scanner for measurement, thereby allowing for an assessment of the DCE-MRI protocol to accurately measure this curve shape. The device comprised a four-pump flow system wherein CTCs derived from prior patient prostate data were produced in measurement chambers placed within the imaged volume. The ground truth was determined as the mean of repeat measurements using an MRI-independent, custom-built optical imaging system. In DCE-MRI experiments, significant discrepancies between the ground truth and measured CTCs were found for both tumorous and healthy tissue-mimicking curve shapes. Pharmacokinetic modelling revealed errors in measured K trans, v e and k ep values of up to 42%, 31%, and 50% respectively, following a simple variation of the parallel imaging factor and number of signal averages in the acquisition protocol. The device allows for the quantitative assessment and standardisation of DCE-MRI protocols (both existing and emerging).
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Affiliation(s)
- Silvin P Knight
- National Centre for Advanced Medical Imaging (CAMI), St James's Hospital/School of Medicine, Trinity College University of Dublin, Dublin, Ireland
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21
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Panek R, Welsh L, Dunlop A, Wong KH, Riddell AM, Koh DM, Schmidt MA, Doran S, Mcquaid D, Hopkinson G, Richardson C, Nutting CM, Bhide SA, Harrington KJ, Robinson SP, Newbold KL, Leach MO. Repeatability and sensitivity of T2* measurements in patients with head and neck squamous cell carcinoma at 3T. J Magn Reson Imaging 2016; 44:72-80. [PMID: 26800280 PMCID: PMC4915498 DOI: 10.1002/jmri.25134] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2015] [Accepted: 12/02/2015] [Indexed: 12/17/2022] Open
Abstract
PURPOSE To determine whether quantitation of T2* is sufficiently repeatable and sensitive to detect clinically relevant oxygenation levels in head and neck squamous cell carcinoma (HNSCC) at 3T. MATERIALS AND METHODS Ten patients with newly diagnosed locally advanced HNSCC underwent two magnetic resonance imaging (MRI) scans between 24 and 168 hours apart prior to chemoradiotherapy treatment. A multiple gradient echo sequence was used to calculate T2* maps. A quadratic function was used to model the blood transverse relaxation rate as a function of blood oxygenation. A set of published coefficients measured at 3T were incorporated to account for tissue hematocrit levels and used to plot the dependence of fractional blood oxygenation (Y) on T2* values, together with the corresponding repeatability range. Repeatability of T2* using Bland-Altman analysis, and calculation of limits of agreement (LoA), was used to assess the sensitivity, defined as the minimum difference in fractional blood oxygenation that can be confidently detected. RESULTS T2* LoA for 22 outlined tumor volumes were 13%. The T2* dependence of fractional blood oxygenation increases monotonically, resulting in increasing sensitivity of the method with increasing blood oxygenation. For fractional blood oxygenation values above 0.11, changes in T2* were sufficient to detect differences in blood oxygenation greater than 10% (Δ T2* > LoA for ΔY > 0.1). CONCLUSION Quantitation of T2* at 3T can detect clinically relevant changes in tumor oxygenation within a wide range of blood volumes and oxygen tensions, including levels reported in HNSCC. J. Magn. Reson. Imaging 2016;44:72-80.
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Affiliation(s)
- Rafal Panek
- CR-UK Cancer Imaging Centre, London, UK
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | - Liam Welsh
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | - Alex Dunlop
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | - Kee H Wong
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | - Angela M Riddell
- CR-UK Cancer Imaging Centre, London, UK
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | - Dow-Mu Koh
- CR-UK Cancer Imaging Centre, London, UK
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | - Maria A Schmidt
- CR-UK Cancer Imaging Centre, London, UK
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | - Simon Doran
- CR-UK Cancer Imaging Centre, London, UK
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | - Dualta Mcquaid
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | | | | | | | - Shreerang A Bhide
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | - Kevin J Harrington
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | - Simon P Robinson
- CR-UK Cancer Imaging Centre, London, UK
- Institute of Cancer Research, London, UK
| | - Kate L Newbold
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
| | - Martin O Leach
- CR-UK Cancer Imaging Centre, London, UK
- Institute of Cancer Research, London, UK
- Royal Marsden NHS Trust, London, UK
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22
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Huang W, Chen Y, Fedorov A, Li X, Jajamovich GH, Malyarenko DI, Aryal MP, LaViolette PS, Oborski MJ, O'Sullivan F, Abramson RG, Jafari-Khouzani K, Afzal A, Tudorica A, Moloney B, Gupta SN, Besa C, Kalpathy-Cramer J, Mountz JM, Laymon CM, Muzi M, Schmainda K, Cao Y, Chenevert TL, Taouli B, Yankeelov TE, Fennessy F, Li X. The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge. ACTA ACUST UNITED AC 2016; 2:56-66. [PMID: 27200418 PMCID: PMC4869732 DOI: 10.18383/j.tom.2015.00184] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Dynamic contrast-enhanced MRI (DCE-MRI) has been widely used in tumor detection and therapy response evaluation. Pharmacokinetic analysis of DCE-MRI time-course data allows estimation of quantitative imaging biomarkers such as Ktrans(rate constant for plasma/interstitium contrast reagent (CR) transfer) and ve (extravascular and extracellular volume fraction). However, the use of quantitative DCE-MRI in clinical prostate imaging islimited, with uncertainty in arterial input function (AIF, i.e., the time rate of change of the concentration of CR in the blood plasma) determination being one of the primary reasons. In this multicenter data analysis challenge to assess the effects of variations in AIF quantification on estimation of DCE-MRI parameters, prostate DCE-MRI data acquired at one center from 11 prostate cancer patients were shared among nine centers. Each center used its site-specific method to determine the individual AIF from each data set and submitted the results to the managing center. Along with a literature population averaged AIF, these AIFs and their reference-tissue-adjusted variants were used by the managing center to perform pharmacokinetic analysis of the DCE-MRI data sets using the Tofts model (TM). All other variables including tumor region of interest (ROI) definition and pre-contrast T1 were kept the same to evaluate parameter variations caused by AIF variations only. Considerable pharmacokinetic parameter variations were observed with the within-subject coefficient of variation (wCV) of Ktrans obtained with unadjusted AIFs as high as 0.74. AIF-caused variations were larger in Ktrans than ve and both were reduced when reference-tissue-adjusted AIFs were used. The parameter variations were largely systematic, resulting in nearly unchanged parametric map patterns. The CR intravasation rate constant, kep (= Ktrans/ve), was less sensitive to AIF variation than Ktrans (wCV for unadjusted AIFs: 0.45 for kepvs. 0.74 for Ktrans), suggesting that it might be a more robust imaging biomarker of prostate microvasculature than Ktrans.
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Affiliation(s)
- Wei Huang
- Oregon Health and Science University, Portland, OR
| | - Yiyi Chen
- Oregon Health and Science University, Portland, OR
| | - Andriy Fedorov
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Xia Li
- General ElectricGlobal Research, Niskayuna, NY
| | | | | | | | | | | | | | | | | | - Aneela Afzal
- Oregon Health and Science University, Portland, OR
| | | | | | | | - Cecilia Besa
- Icahn School ofMedicine at Mount Sinai, New York, NY
| | | | | | | | - Mark Muzi
- University of Washington, Seattle, WA
| | | | - Yue Cao
- University of Michigan, Ann Arbor, MI
| | | | - Bachir Taouli
- Icahn School ofMedicine at Mount Sinai, New York, NY
| | | | - Fiona Fennessy
- Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Xin Li
- Oregon Health and Science University, Portland, OR
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Jafari-Khouzani K, Emblem KE, Kalpathy-Cramer J, Bjørnerud A, Vangel MG, Gerstner ER, Schmainda KM, Paynabar K, Wu O, Wen PY, Batchelor T, Rosen B, Stufflebeam SM. Repeatability of Cerebral Perfusion Using Dynamic Susceptibility Contrast MRI in Glioblastoma Patients. Transl Oncol 2015; 8:137-46. [PMID: 26055170 PMCID: PMC4486737 DOI: 10.1016/j.tranon.2015.03.002] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2014] [Revised: 03/10/2015] [Accepted: 03/17/2015] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVES This study evaluates the repeatability of brain perfusion using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a variety of post-processing methods. METHODS Thirty-two patients with newly diagnosed glioblastoma were recruited. On a 3-T MRI using a dual-echo, gradient-echo spin-echo DSC-MRI protocol, the patients were scanned twice 1 to 5 days apart. Perfusion maps including cerebral blood volume (CBV) and cerebral blood flow (CBF) were generated using two contrast agent leakage correction methods, along with testing normalization to reference tissue, and application of arterial input function (AIF). Repeatability of CBV and CBF within tumor regions and healthy tissues, identified by structural images, was assessed with intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs). Coefficients of variation (CVs) were reported for selected methods. RESULTS CBV and CBF were highly repeatable within tumor with ICC values up to 0.97. However, both CBV and CBF showed lower ICCs for healthy cortical tissues (up to 0.83), healthy gray matter (up to 0.95), and healthy white matter (WM; up to 0.93). The values of CV ranged from 6% to 10% in tumor and 3% to 11% in healthy tissues. The values of RC relative to the mean value of measurement within healthy WM ranged from 22% to 42% in tumor and 7% to 43% in healthy tissues. These percentages show how much variation in perfusion parameter, relative to that in healthy WM, we expect to observe to consider it statistically significant. We also found that normalization improved repeatability, but AIF deconvolution did not. CONCLUSIONS DSC-MRI is highly repeatable in high-grade glioma patients.
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Affiliation(s)
- Kourosh Jafari-Khouzani
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Kyrre E Emblem
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA; The Intervention Centre, Rikshospitalet, Oslo University Hospital, Oslo, Norway
| | - Jayashree Kalpathy-Cramer
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Atle Bjørnerud
- The Intervention Centre, Rikshospitalet, Oslo University Hospital, Oslo, Norway; Department of Physics, University of Oslo, Oslo, Norway
| | - Mark G Vangel
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Elizabeth R Gerstner
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, USA
| | - Kathleen M Schmainda
- Department of Radiology & Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Kamran Paynabar
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Ona Wu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Tracy Batchelor
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, USA
| | - Bruce Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Steven M Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
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24
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Abramson RG, Burton KR, Yu JPJ, Scalzetti EM, Yankeelov TE, Rosenkrantz AB, Mendiratta-Lala M, Bartholmai BJ, Ganeshan D, Lenchik L, Subramaniam RM. Methods and challenges in quantitative imaging biomarker development. Acad Radiol 2015; 22:25-32. [PMID: 25481515 PMCID: PMC4258641 DOI: 10.1016/j.acra.2014.09.001] [Citation(s) in RCA: 67] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2014] [Revised: 09/03/2014] [Accepted: 09/03/2014] [Indexed: 12/18/2022]
Abstract
Academic radiology is poised to play an important role in the development and implementation of quantitative imaging (QI) tools. This article, drafted by the Association of University Radiologists Radiology Research Alliance Quantitative Imaging Task Force, reviews current issues in QI biomarker research. We discuss motivations for advancing QI, define key terms, present a framework for QI biomarker research, and outline challenges in QI biomarker development. We conclude by describing where QI research and development is currently taking place and discussing the paramount role of academic radiology in this rapidly evolving field.
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Affiliation(s)
- Richard G. Abramson
- Department of Radiology and Radiological Sciences Vanderbilt University 1161 21 Ave. S, CCC-1121 MCN Nashville, TN 37232-2675 (615)322-6759 Fax (615) 322-3764
| | - Kirsteen R. Burton
- Dept. of Medical Imaging and Institute of Health Policy, Management and Evaluation University of Toronto 263 McCaul Street, 4th Floor Toronto, ON M5T1W7 (416) 978-6801
| | - John-Paul J. Yu
- Department of Radiology and Biomedical Imaging University of California, San Francisco 505 Parnassus Ave., M-391 Box 0628 San Francisco, CA 94143-0628
| | - Ernest M. Scalzetti
- Department of Radiology SUNY Upstate Medical University 750 E. Adams St. Syracuse NY 13210
| | - Thomas E. Yankeelov
- Institute of Imaging Science Vanderbilt University 1161 21 Ave. S, AA-1105 MCN Nashville, TN 37232-2310
| | - Andrew B. Rosenkrantz
- Department of Radiology NYU Langone Medical Center 550 First Avenue New York, NY 10016 (212) 263-0232 fax: (212) 263-6634
| | - Mishal Mendiratta-Lala
- Abdominal and Cross-sectional Interventional Radiology Henry Ford Hospital 2799 West Grand Blvd. Detroit, MI 48202 (313) 461-1648
| | - Brian J. Bartholmai
- Chair, Division of Radiology Informatics Mayo Clinic Rochester, MN Phone 507-284-4292 FAX: 507-284-8996
| | - Dhakshinamoorthy Ganeshan
- Department of Abdominal Imaging University of Texas MD Anderson Cancer Center Houston, TX 77030 713-792-2486 Fax: 713-745-1151
| | - Leon Lenchik
- Department of Radiology Wake Forest School of Medicine Medical Center Boulevard Winston-Salem, NC 27157 Phone: 336-716-4316 Fax: 336-716-1278
| | - Rathan M. Subramaniam
- Russell H Morgan Department of Radiology and Radiological Sciences Johns Hopkins School of Medicine Department of Health Policy and Management Johns Hopkins Bloomberg School of Public Health Johns Hopkins University Baltimore, MD
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Veksler R, Shelef I, Friedman A. Blood-brain barrier imaging in human neuropathologies. Arch Med Res 2014; 45:646-52. [PMID: 25453223 DOI: 10.1016/j.arcmed.2014.11.016] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2014] [Accepted: 11/20/2014] [Indexed: 01/22/2023]
Abstract
The blood-brain barrier (BBB) is essential for normal function of the brain, and its role in many brain pathologies has been the focus of numerous studies during the last decades. Dysfunction of the BBB is not only being shown in numerous brain diseases, but animal studies have indicated that it plays a direct key role in the genesis of neurovascular dysfunction and associated neurodegeneration. As such evidence accumulates, the need for robust and clinically applicable methods for minimally invasive assessment of BBB integrity is becoming urgent. This review provides an introduction to BBB imaging methods in the clinical scenario. First, imaging modalities are reviewed, with a focus on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). We then proceed to review image analysis methods, including quantitative and semi-quantitative methods. The advantages and limitations of each approach are discussed, and future directions and questions are highlighted.
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Affiliation(s)
- Ronel Veksler
- Departments of Physiology and Cell Biology, Brain and Cognitive Sciences, Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ilan Shelef
- Department of Medical Imaging, Soroka University Medical Center and the Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Alon Friedman
- Departments of Physiology and Cell Biology, Brain and Cognitive Sciences, Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel; Department of Medical Neuroscience, Faculty of Medicine, Dalhousie University, Halifax, Canada.
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26
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Tartare G, Hamad D, Azahaf M, Puech P, Betrouni N. Spectral clustering applied for dynamic contrast-enhanced MR analysis of time-intensity curves. Comput Med Imaging Graph 2014; 38:702-13. [PMID: 25179917 DOI: 10.1016/j.compmedimag.2014.07.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2014] [Revised: 06/24/2014] [Accepted: 07/21/2014] [Indexed: 10/24/2022]
Abstract
Dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) represents an emerging method for the prediction of biomarker responses in cancer. However, DCE images remain difficult to analyze and interpret. Although pharmacokinetic approaches, which involve multi-step processes, can provide a general framework for the interpretation of these data, they are still too complex for robust and accurate implementation. Therefore, statistical data analysis techniques were recently suggested as another valid interpretation strategy for DCE-MRI. In this context, we propose a spectral clustering approach for the analysis of DCE-MRI time-intensity signals. This graph theory-based method allows for the grouping of signals after spatial transformation. Subsequently, these data clusters can be labeled following comparison to arterial signals. Here, we have performed experiments with simulated (i.e., generated via pharmacokinetic modeling) and clinical (i.e., obtained from patients scanned during prostate cancer diagnosis) data sets in order to demonstrate the feasibility and applicability of this kind of unsupervised and non-parametric approach.
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Affiliation(s)
- Guillaume Tartare
- INSERM, U703, 152 rue du Docteur Yersin, 59120 CHRU Lille, France; Université Littoral Côte d'Opale, Laboratoire d'Informatique, Signal et Image de la Côte d'Opale, France
| | - Denis Hamad
- Université Littoral Côte d'Opale, Laboratoire d'Informatique, Signal et Image de la Côte d'Opale, France
| | - Mustapha Azahaf
- INSERM, U703, 152 rue du Docteur Yersin, 59120 CHRU Lille, France; Université Littoral Côte d'Opale, Laboratoire d'Informatique, Signal et Image de la Côte d'Opale, France; Service de Radiologie, Hôpital Claude Huriez, CHRU de Lille, France
| | - Philippe Puech
- INSERM, U703, 152 rue du Docteur Yersin, 59120 CHRU Lille, France; Université Littoral Côte d'Opale, Laboratoire d'Informatique, Signal et Image de la Côte d'Opale, France; Service de Radiologie, Hôpital Claude Huriez, CHRU de Lille, France
| | - Nacim Betrouni
- INSERM, U703, 152 rue du Docteur Yersin, 59120 CHRU Lille, France; Université Littoral Côte d'Opale, Laboratoire d'Informatique, Signal et Image de la Côte d'Opale, France.
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27
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Fennessy FM, McKay RR, Beard CJ, Taplin ME, Tempany CM. Dynamic contrast-enhanced magnetic resonance imaging in prostate cancer clinical trials: potential roles and possible pitfalls. Transl Oncol 2014; 7:120-9. [PMID: 24772215 PMCID: PMC3998683 DOI: 10.1593/tlo.13922] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2013] [Revised: 03/04/2014] [Accepted: 03/06/2014] [Indexed: 12/21/2022] Open
Abstract
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) evaluates the tissue microvasculature and may have a role in assessing and predicting therapeutic response in prostate cancer (PCa). In this review, we review principles of DCE-MRI and present the potential quantitative information that can be obtained. We discuss how it may be used as a biomarker for treatment with antiangiogenic and antivascular agents and potentially identify patients with PCa who may benefit from this form of therapy. Likewise, DCE-MRI may play a role in assessing response to combined androgen deprivation therapy and radiation therapy and theoretically could be a prognostic biomarker in evaluating second-generation hormone therapies. We also address the challenges of using DCE-MRI in PCa clinical trials and discuss the difficulties with standardization of this methodology to allow for biomarker validation, with particular reference to PCa.
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Affiliation(s)
- Fiona M Fennessy
- Department of Radiology, Brigham and Women's Hospital, Boston, MA ; Department of Radiology, Dana-Farber Cancer Institute, Boston, MA
| | - Rana R McKay
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Clair J Beard
- Department of Radiation Oncology, Brigham and Women's Hospital, Boston, MA
| | - Mary-Ellen Taplin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
| | - Clare M Tempany
- Department of Radiology, Brigham and Women's Hospital, Boston, MA
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28
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Rischke HC, Nestle U, Fechter T, Doll C, Volegova-Neher N, Henne K, Scholber J, Knippen S, Kirste S, Grosu AL, Jilg CA. 3 Tesla multiparametric MRI for GTV-definition of Dominant Intraprostatic Lesions in patients with Prostate Cancer--an interobserver variability study. Radiat Oncol 2013; 8:183. [PMID: 23875672 PMCID: PMC3828667 DOI: 10.1186/1748-717x-8-183] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2013] [Accepted: 07/20/2013] [Indexed: 01/28/2023] Open
Abstract
PURPOSE To evaluate the interobserver variability of gross tumor volume (GTV) - delineation of Dominant Intraprostatic Lesions (DIPL) in patients with prostate cancer using published MRI criteria for multiparametric MRI at 3 Tesla by 6 different observers. MATERIAL AND METHODS 90 GTV-datasets based on 15 multiparametric MRI sequences (T2w, diffusion weighted (DWI) and dynamic contrast enhanced (DCE)) of 5 patients with prostate cancer were generated for GTV-delineation of DIPL by 6 observers. The reference GTV-dataset was contoured by a radiologist with expertise in diagnostic imaging of prostate cancer using MRI. Subsequent GTV-delineation was performed by 5 radiation oncologists who received teaching of MRI-features of primary prostate cancer before starting contouring session. GTV-datasets were contoured using Oncentra Masterplan® and iplan® Net. For purposes of comparison GTV-datasets were imported to the Artiview® platform (Aquilab®), GTV-values and the similarity indices or Kappa indices (KI) were calculated with the postulation that a KI > 0.7 indicates excellent, a KI > 0.6 to < 0.7 substantial and KI > 0.5 to < 0.6 moderate agreement. Additionally all observers rated difficulties of contouring for each MRI-sequence using a 3 point rating scale (1 = easy to delineate, 2 = minor difficulties, 3 = major difficulties). RESULTS GTV contouring using T2w (KI-T2w = 0.61) and DCE images (KI-DCE = 0.63) resulted in substantial agreement. GTV contouring using DWI images resulted in moderate agreement (KI-DWI = 0.51). KI-T2w and KI-DCE was significantly higher than KI-DWI (p = 0.01 and p = 0.003). Degree of difficulty in contouring GTV was significantly lower using T2w and DCE compared to DWI-sequences (both p < 0.0001). Analysis of delineation differences revealed inadequate comparison of functional (DWI, DCE) to anatomical sequences (T2w) and lack of awareness of non-specific imaging findings as a source of erroneous delineation. CONCLUSIONS Using T2w and DCE sequences at 3 Tesla for GTV-definition of DIPL in prostate cancer patients by radiation oncologists with knowledge of MRI features results in substantial agreement compared to an experienced MRI-radiologist, but for radiotherapy purposes higher KI are desirable, strengthen the need for expert surveillance. DWI sequence for GTV delineation was considered as difficult in application.
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Affiliation(s)
- Hans Christian Rischke
- Department of Radiation Oncology, University of Freiburg, Robert Koch Str. 3, 79106 Freiburg, Germany.
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Heye T, Davenport MS, Horvath JJ, Feuerlein S, Breault SR, Bashir MR, Merkle EM, Boll DT. Reproducibility of Dynamic Contrast-enhanced MR Imaging. Part I. Perfusion Characteristics in the Female Pelvis by Using Multiple Computer-aided Diagnosis Perfusion Analysis Solutions. Radiology 2013; 266:801-11. [DOI: 10.1148/radiol.12120278] [Citation(s) in RCA: 90] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Abstract
Prostate cancer hypoxia is associated with inferior prognosis and resistance to treatment. The use of androgen deprivation therapy, both prior to and during radiotherapy, may exacerbate underlying hypoxia. Whilst larger radiation doses per fraction may achieve therapeutic gain, this is balanced by the reduced opportunity for re-oxygenation to take place during the course of treatment. Improving the underlying hypoxic tumour environment may therefore improve the treatment outcomes. Strategies to combat tumour hypoxia, with particular focus on the use of carbogen gas breathing concurrently with radiotherapy, is the subject of this review.
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Affiliation(s)
- Kent Yip
- Department of Oncology, Mount Vernon Cancer Centre, Northwood, UK
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31
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Ter Voert EGW, Heijmen L, de Wilt JHW, Bussink J, Punt CJA, van Laarhoven HWM, Heerschap A. Reproducibility and biological basis of in vivo T(2)* magnetic resonance imaging of liver metastasis of colorectal cancer. Magn Reson Med 2012; 70:1145-52. [PMID: 23165899 DOI: 10.1002/mrm.24543] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2012] [Revised: 09/29/2012] [Accepted: 10/05/2012] [Indexed: 11/06/2022]
Abstract
In this study, the reproducibility of T2* MR imaging in colorectal liver metastases was assessed and T2* values were correlated with the expression of the hypoxia-related markers GLUT-1 and CA-IX as well as the relative vascular area, and the vessel density in resected tumors. The reproducibility of T2* was analyzed in 18 patients with in total 22 colorectal liver metastases using the Bland and Altman method for the 16th, 50th, and 84th percentile values. Immunohistochemical staining was performed on 17 resected tumors obtained from 16 patients. The median T2* of all liver metastases was 25.0 ± 5.6 ms vs. 23.0 ± 4.1 ms (median ± st.dev.) in normal liver. The coefficient of repeatability was 11.2 ms and the limits of agreement were -13.2 ms and 9.1 ms for median T2* values. On average, T2* showed fair reproducibility. No correlations between T2* values, hypoxia- and vascularity-related markers were observed.
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Affiliation(s)
- E G W Ter Voert
- Department of Radiology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
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32
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Peripheral Zone Prostate Cancer Localization by Multiparametric Magnetic Resonance at 3 T. Invest Radiol 2012; 47:624-33. [DOI: 10.1097/rli.0b013e318263f0fd] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
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33
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van der Heide UA, Houweling AC, Groenendaal G, Beets-Tan RGH, Lambin P. Functional MRI for radiotherapy dose painting. Magn Reson Imaging 2012; 30:1216-23. [PMID: 22770686 DOI: 10.1016/j.mri.2012.04.010] [Citation(s) in RCA: 118] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2012] [Revised: 03/26/2012] [Accepted: 04/01/2012] [Indexed: 02/07/2023]
Abstract
Modern radiation therapy techniques are exceptionally flexible in the deposition of radiation dose in a target volume. Complex distributions of dose can be delivered reliably, so that the tumor is exposed to a high dose, whereas nearby healthy structures can be avoided. As a result, an increase in curative dose is no longer invariably associated with an increased level of toxicity. This modern technology can be exploited further by modulating the required dose in space so as to match the variation in radiation sensitivity in the tumor. This approach is called dose painting. For dose painting to be effective, functional imaging techniques are essential to identify regions in a tumor that require a higher dose. Several techniques are available in nuclear medicine and radiology. In recent years, there has been a considerable research effort concerning the integration of magnetic resonance imaging (MRI) into the external radiotherapy workflow motivated by the superior soft tissue contrast as compared to computed tomography. In MRI, diffusion-weighted MRI reflects the cell density of tissue and thus may indicate regions with a higher tumor load. Dynamic contrast-enhanced MRI reflects permeability of the microvasculature and blood flow, correlated to the oxygenation of the tumor. These properties have impact on its radiation sensitivity. New questions must be addressed when these techniques are applied in radiation therapy: scanning in treatment position requires alternative solutions to the standard patient setup in the choice of receive coils compared to a diagnostic department. This standard positioning also facilitates repeated imaging. The geometrical accuracy of MR images is critical for high-precision radiotherapy. In particular, when multiparametric functional data are used for dose painting, quantification of functional parameters at a high spatial resolution becomes important. In this review, we will address these issues and describe clinical developments in MRI-guided dose painting.
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Affiliation(s)
- Uulke A van der Heide
- Department of Radiation Oncology, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, 1066 CX Amsterdam, The Netherlands.
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Li X, Priest RA, Woodward WJ, Siddiqui F, Beer TM, Garzotto MG, Rooney WD, Springer CS. Cell membrane water exchange effects in prostate DCE-MRI. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2012; 218:77-85. [PMID: 22578558 PMCID: PMC3532863 DOI: 10.1016/j.jmr.2012.03.019] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2011] [Revised: 03/17/2012] [Accepted: 03/17/2012] [Indexed: 05/25/2023]
Abstract
Prostate Dynamic-Contrast-Enhanced (DCE) MRI often exhibits fast and extensive global contrast reagent (CR) extravasation - measured by K(trans), a pharmacokinetic parameter proportional to its rate. This implies that the CR concentration [CR] is high in the extracellular, extravascular space (EES) during a large portion of the DCE-MRI study. Since CR is detected indirectly, through water proton signal change, the effects of equilibrium transcytolemmal water exchange may be significant in the data and thus should be admitted in DCE-MRI pharmacokinetic modeling. The implications for parameter values were investigated through simulations, and analyses of actual prostate data, with different models. Model parameter correlation and precision were also explored. A near-optimal version of the exchange-sensitized model was found. Our results indicate that ΔK(trans) (the K(trans) difference returned by this version and a model assuming exchange to be effectively infinitely fast) may be a very useful biomarker for discriminating malignant from benign prostate tissue. Using an exchange-sensitized model, we find that the mean intracellular water lifetime (τ(i)) - an exchange measure - can be meaningfully mapped for the prostate. Our results show prostate glandular zone differences in τ(i) values.
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Affiliation(s)
- Xin Li
- W.M. Keck Foundation High-Field MRI Laboratory, Advanced Imaging Research Center, Portland, OR 97239, USA.
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35
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Quantitative perfusion analysis of malignant liver tumors: dynamic computed tomography and contrast-enhanced ultrasound. Invest Radiol 2012; 47:18-24. [PMID: 21788906 DOI: 10.1097/rli.0b013e318229ff0d] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVE To prospectively analyze the correlation between quantitative parameters of perfusion derived from dynamic contrast-enhanced CT (DCE-CT) and contrast-enhanced ultrasound (DCE-US) in patients with malignant liver tumors. MATERIALS AND METHODS Thirty patients (mean age: 59.4 ± 12.3 years) with primary malignant liver tumors or hepatic metastases of various origin underwent DCE-CT (4D spiral mode, scan range, 14.8 cm; 15 scans; cycle time, 3 seconds) and DCE-US (low mechanical index, <0.1, 2.4 mL microbubbles). DCE-CT and DCE-US images were evaluated by 2 radiologists regarding quantitative perfusion parameters including arterial liver perfusion (ALP), portal-venous perfusion (PVP), and total perfusion (P = ALP + PVP) from DCE-CT, as well as blood inflow velocity (B) and the normalized slope within the calculation range (CVan) from DCE-US. RESULTS Quantitative assessment was possible with DCE-CT in 12/30 (40%) patients before and in all patients after automated motion correction. With DCE-US, quantitative assessment could not be performed in 9/30 (30.0%) patients due to respiratory motion. Interreader agreements for quantitative perfusion analysis were good with DCE-CT (r = 0.640-0.892, each P < 0.001) and DCE-US (r = 0.761-0.909, each P < 0.001). Moderate significant correlations were found between the perfusion parameters from DCE-CT (P, ALP) and DCE-US (B, CVan) (r = 0.446-0.621, each P < 0.05). No significant correlations were found between PVP from CT and perfusion parameters from DCE-US (B, CVan; each P = nonsignificant). CONCLUSIONS Quantitative evaluation of DCE-CT data was feasible in all patients after automated motion correction, whereas DCE-US data could not be quantitatively evaluated in 30% of patients due to respiratory motion and lack of motion correction software. Quantitative arterial perfusion analysis showed moderate significant correlations for blood flow parameters among modalities.
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Li X, Priest RA, Woodward WJ, Tagge IJ, Siddiqui F, Huang W, Rooney WD, Beer TM, Garzotto MG, Springer CS. Feasibility of shutter-speed DCE-MRI for improved prostate cancer detection. Magn Reson Med 2012; 69:171-8. [PMID: 22457233 DOI: 10.1002/mrm.24211] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2011] [Revised: 12/26/2011] [Accepted: 01/19/2012] [Indexed: 01/28/2023]
Abstract
The feasibility of shutter-speed model dynamic-contrast-enhanced MRI pharmacokinetic analyses for prostate cancer detection was investigated in a prebiopsy patient cohort. Differences of results from the fast-exchange-regime-allowed (FXR-a) shutter-speed model version and the fast-exchange-limit-constrained (FXL-c) standard model are demonstrated. Although the spatial information is more limited, postdynamic-contrast-enhanced MRI biopsy specimens were also examined. The MRI results were correlated with the biopsy pathology findings. Of all the model parameters, region-of-interest-averaged K(trans) difference [ΔK(trans) ≡ K(trans)(FXR-a) - K(trans)(FXL-c)] or two-dimensional K(trans)(FXR-a) vs. k(ep)(FXR-a) values were found to provide the most useful biomarkers for malignant/benign prostate tissue discrimination (at 100% sensitivity for a population of 13, the specificity is 88%) and disease burden determination. (The best specificity for the fast-exchange-limit-constrained analysis is 63%, with the two-dimensional plot.) K(trans) and k(ep) are each measures of passive transcapillary contrast reagent transfer rate constants. Parameter value increases with shutter-speed model (relative to standard model) analysis are larger in malignant foci than in normal-appearing glandular tissue. Pathology analyses verify the shutter-speed model (FXR-a) promise for prostate cancer detection. Parametric mapping may further improve pharmacokinetic biomarker performance.
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Affiliation(s)
- Xin Li
- W. M. Keck Foundation High-Field MRI Laboratory, Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon 97239, USA.
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