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Arias-Lorza AM, Costello JR, Hingorani SR, Von Hoff DD, Korn RL, Raghunand N. Magnetic resonance imaging of tumor response to stroma-modifying pegvorhyaluronidase alpha (PEGPH20) therapy in early-phase clinical trials. Sci Rep 2024; 14:11570. [PMID: 38773189 PMCID: PMC11109088 DOI: 10.1038/s41598-024-62470-9] [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: 08/31/2023] [Accepted: 05/17/2024] [Indexed: 05/23/2024] Open
Abstract
Pre-clinical and clinical studies have shown that PEGPH20 depletes intratumoral hyaluronic acid (HA), which is linked to high interstitial fluid pressures and poor distribution of chemotherapies. 29 patients with metastatic advanced solid tumors received quantitative magnetic resonance imaging (qMRI) in 3 prospective clinical trials of PEGPH20: HALO-109-101 (NCT00834704), HALO-109-102 (NCT01170897), and HALO-109-201 (NCT01453153). Apparent Diffusion Coefficient of water (ADC), T1, ktrans, vp, ve, and iAUC maps were computed from qMRI acquired at baseline and ≥ 1 time point post-PEGPH20. Tumor ADC and T1 decreased, while iAUC, ktrans, vp, and ve increased, on day 1 post-PEGPH20 relative to baseline values. This is consistent with HA depletion leading to a decrease in tumor extracellular water content and an increase in perfusion, permeability, extracellular matrix space, and vascularity. Baseline parameter values predictive of pharmacodynamic responses were: ADC > 1.46 × 10-3 mm2/s (Balanced Accuracy (BA) = 72%, p < 0.01), T1 > 0.54 s (BA = 82%, p < 0.01), iAUC < 9.2 mM-s (BA = 76%, p < 0.05), ktrans < 0.07 min-1 (BA = 72%, p = 0.2), ve < 0.17 (BA = 68%, p < 0.01), and vp < 0.02 (BA = 60%, p < 0.01). A low ve at baseline was moderately predictive of response in any parameter (BA = 65.6%, p < 0.01 averaged across patients). These qMRI biomarkers are potentially useful for guiding patient pre-selection and post-treatment follow-up in future clinical studies of PEGPH20 and other tumor stroma-modifying anti-cancer therapies.
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Affiliation(s)
| | | | - Sunil R Hingorani
- Division of Hematology and Oncology, Department of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
- Fred & Pamela Buffett Cancer Center, Pancreatic Cancer Center of Excellence, University of Nebraska Medical Center, Omaha, NE, USA
| | - Daniel D Von Hoff
- Translational Genomics Research Institute (TGen), Scottsdale, AZ, USA
- HonorHealth Clinical Research Institute, Phoenix, AZ, USA
| | | | - Natarajan Raghunand
- Department of Cancer Physiology, Moffitt Cancer Center, Tampa, FL, USA.
- Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA.
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2
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Dickie BR, Ahmed Z, Arvidsson J, Bell LC, Buckley DL, Debus C, Fedorov A, Floca R, Gutmann I, van der Heijden RA, van Houdt PJ, Sourbron S, Thrippleton MJ, Quarles C, Kompan IN. A community-endorsed open-source lexicon for contrast agent-based perfusion MRI: A consensus guidelines report from the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI). Magn Reson Med 2024; 91:1761-1773. [PMID: 37831600 PMCID: PMC11337559 DOI: 10.1002/mrm.29840] [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: 05/17/2023] [Revised: 07/25/2023] [Accepted: 08/04/2023] [Indexed: 10/15/2023]
Abstract
This manuscript describes the ISMRM OSIPI (Open Science Initiative for Perfusion Imaging) lexicon for dynamic contrast-enhanced and dynamic susceptibility-contrast MRI. The lexicon was developed by Taskforce 4.2 of OSIPI to provide standardized definitions of commonly used quantities, models, and analysis processes with the aim of reducing reporting variability. The taskforce was established in February 2020 and consists of medical physicists, engineers, clinicians, data and computer scientists, and DICOM (Digital Imaging and Communications in Medicine) standard experts. Members of the taskforce collaborated via a slack channel and quarterly virtual meetings. Members participated by defining lexicon items and reporting formats that were reviewed by at least two other members of the taskforce. Version 1.0.0 of the lexicon was subject to open review from the wider perfusion imaging community between January and March 2022, and endorsed by the Perfusion Study Group of the ISMRM in the summer of 2022. The initial scope of the lexicon was set by the taskforce and defined such that it contained a basic set of quantities, processes, and models to enable users to report an end-to-end analysis pipeline including kinetic model fitting. We also provide guidance on how to easily incorporate lexicon items and definitions into free-text descriptions (e.g., in manuscripts and other documentation) and introduce an XML-based pipeline encoding format to encode analyses using lexicon definitions in standardized and extensible machine-readable code. The lexicon is designed to be open-source and extendable, enabling ongoing expansion of its content. We hope that widespread adoption of lexicon terminology and reporting formats described herein will increase reproducibility within the field.
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Affiliation(s)
- Ben R. Dickie
- Division of Informatics, Imaging, and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Center, Manchester Academic Health Science Center, The University of Manchester, Manchester, UK
| | - Zaki Ahmed
- Corewell Health William Beaumont University Hospital, Royal Oak, Michigan, USA
| | - Jonathan Arvidsson
- Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Laura C. Bell
- Clinical Imaging Group, Genentech, Inc., South San Francisco, California, USA
| | | | | | - Andrey Fedorov
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ralf Floca
- National Center for Radiation Research in Oncology, Heidelberg Institute for Radiation Oncology, Heidelberg, Germany
| | - Ingomar Gutmann
- Faculty of Physics, Physics of Functional Materials, University of Vienna, Vienna, Austria
| | - Rianne A. van der Heijden
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Petra J. van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Steven Sourbron
- Department of Infection, Immunity, and Cardiovascular Diseases, University of Sheffield, Sheffield, UK
| | - Michael J. Thrippleton
- Edinburgh Imaging and Center for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Chad Quarles
- Department of Cancer Systems Imaging, UT MD Anderson Cancer Center, Houston, Texas, USA
| | - Ina N. Kompan
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
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Kalisvaart GM, Van Den Berghe T, Grootjans W, Lejoly M, Huysse WCJ, Bovée JVMG, Creytens D, Gelderblom H, Speetjens FM, Lapeire L, van de Sande MAJ, Sys G, de Geus-Oei LF, Verstraete KL, Bloem JL. Evaluation of response to neoadjuvant chemotherapy in osteosarcoma using dynamic contrast-enhanced MRI: development and external validation of a model. Skeletal Radiol 2024; 53:319-328. [PMID: 37464020 PMCID: PMC10730632 DOI: 10.1007/s00256-023-04402-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 07/03/2023] [Accepted: 07/04/2023] [Indexed: 07/20/2023]
Abstract
OBJECTIVE To identify which dynamic contrast-enhanced (DCE-)MRI features best predict histological response to neoadjuvant chemotherapy in patients with an osteosarcoma. METHODS Patients with osteosarcoma who underwent DCE-MRI before and after neoadjuvant chemotherapy prior to resection were retrospectively included at two different centers. Data from the center with the larger cohort (training cohort) was used to identify which method for region-of-interest selection (whole slab or focal area method) and which change in DCE-MRI features (time to enhancement, wash-in rate, maximum relative enhancement and area under the curve) gave the most accurate prediction of histological response. Models were created using logistic regression and cross-validated. The most accurate model was then externally validated using data from the other center (test cohort). RESULTS Fifty-five (27 poor response) and 30 (19 poor response) patients were included in training and test cohorts, respectively. Intraclass correlation coefficient of relative DCE-MRI features ranged 0.81-0.97 with the whole slab and 0.57-0.85 with the focal area segmentation method. Poor histological response was best predicted with the whole slab segmentation method using a single feature threshold, relative wash-in rate <2.3. Mean accuracy was 0.85 (95%CI: 0.75-0.95), and area under the receiver operating characteristic curve (AUC-index) was 0.93 (95%CI: 0.86-1.00). In external validation, accuracy and AUC-index were 0.80 and 0.80. CONCLUSION In this study, a relative wash-in rate of <2.3 determined with the whole slab segmentation method predicted histological response to neoadjuvant chemotherapy in osteosarcoma. Consistent performance was observed in an external test cohort.
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Affiliation(s)
- Gijsbert M Kalisvaart
- Department of Radiology and Nuclear Medicine, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands.
| | - Thomas Van Den Berghe
- Department of Radiology and Medical Imaging, Ghent University Hospital, Ghent, Belgium
| | - Willem Grootjans
- Department of Radiology and Nuclear Medicine, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Maryse Lejoly
- Department of Radiology and Medical Imaging, Ghent University Hospital, Ghent, Belgium
| | - Wouter C J Huysse
- Department of Radiology and Medical Imaging, Ghent University Hospital, Ghent, Belgium
| | - Judith V M G Bovée
- Department of Pathology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - David Creytens
- Department of Pathology, Ghent University Hospital, Ghent, Belgium
| | - Hans Gelderblom
- Department of Medical Oncology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Frank M Speetjens
- Department of Medical Oncology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Lore Lapeire
- Department of Medical Oncology, Ghent University Hospital, Ghent, Belgium
| | - Michiel A J van de Sande
- Department of Orthopedics, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Gwen Sys
- Department of Orthopedics, Ghent University Hospital, Ghent, Belgium
| | - Lioe-Fee de Geus-Oei
- Department of Radiology and Nuclear Medicine, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
| | - Koenraad L Verstraete
- Department of Radiology and Medical Imaging, Ghent University Hospital, Ghent, Belgium
| | - Johan L Bloem
- Department of Radiology and Nuclear Medicine, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, The Netherlands
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Arias-Lorza AM, Costello JR, Hingorani SR, Von Hoff DD, Korn RL, Raghunand N. Tumor Response to Stroma-Modifying Therapy: Magnetic Resonance Imaging Findings in Early-Phase Clinical Trials of Pegvorhyaluronidase alpha (PEGPH20). RESEARCH SQUARE 2023:rs.3.rs-3314770. [PMID: 37720027 PMCID: PMC10503830 DOI: 10.21203/rs.3.rs-3314770/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/19/2023]
Abstract
Pre-clinical and clinical studies have shown that PEGPH20 depletes intratumoral hyaluronic acid (HA), which is linked to high interstitial fluid pressures and poor distribution of chemotherapies. 29 patients with metastatic advanced solid tumors received quantitative magnetic resonance imaging (qMRI) in 3 prospective clinical trials of PEGPH20, HALO-109-101 (NCT00834704), HALO-109-102 (NCT01170897), and HALO-109-201 (NCT01453153). Apparent Diffusion Coefficient of water (ADC), T1, ktrans, vp, ve, and iAUC maps were computed from qMRI acquired at baseline and ≥ 1 time point post-PEGPH20. Tumor ADC and T1 decreased, while iAUC, ktrans, vp, and ve increased, on day 1 post-PEGPH20 relative to baseline values. This is consistent with HA depletion leading to a decrease in tumor water content and an increase in perfusion, permeability, extracellular matrix space, and vascularity. Baseline parameter values that were predictive of pharmacodynamic responses were: ADC > 1.46×10-3 mm2/s (Balanced Accuracy (BA) = 72%, p < 0.01), T1 > 0.54s (BA = 82%, p < 0.01), iAUC < 9.2 mM-s (BA = 76%, p < 0.05), ktrans<0.07min-1 (BA = 72%, p = 0.2), ve<0.17 (BA = 68%, p < 0.01), and vp<0.02 (BA = 60%, p < 0.01). Further, ve<0.39 at baseline was moderately predictive of response in any parameter (BA = 65.6%, p < 0.01 averaged across patients). These qMRI biomarkers are potentially useful for guiding patient pre-selection and post-treatment follow-up in future clinical studies of PEGPH20 and other tumor stroma-modifying anti-cancer therapies.
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Saha A, Peck KK, Karimi S, Lis E, Holodny AI. Dynamic Contrast-Enhanced MR Perfusion: Role in Diagnosis and Treatment Follow-Up in Patients with Vertebral Body Tumors. Neuroimaging Clin N Am 2023; 33:477-486. [PMID: 37356863 DOI: 10.1016/j.nic.2023.03.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/27/2023]
Abstract
Recent therapeutic advances have led to increased survival times for patients with metastatic disease. Key to survival is early diagnosis and subsequent treatment as well as early detection of treatment failure allowing for therapy modifications. Conventional MR imaging techniques of the spine can be at times suboptimal for identifying viable tumor, as structural changes and imaging characteristics may not differ pretreatment and posttreatment. Advanced imaging techniques such as DCE-MRI can allow earlier and more accurate noninvasive assessment of viable disease by characterizing physiologic changes and tumor microvasculature.
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Affiliation(s)
- Atin Saha
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Department of Radiology, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA.
| | - Kyung K Peck
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Sasan Karimi
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA; Department of Radiology, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA
| | - Eric Lis
- Department of Radiology, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, USA
| | - Andrei I Holodny
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA. https://twitter.com/AndreiHolodny
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Bradley CR, Cox EF, Palaniyappan N, Aithal GP, Francis ST, Guha IN. Variability of noninvasive MRI and biological markers in compensated cirrhosis: insights for assessing disease progression. Eur Radiol Exp 2022; 6:52. [PMID: 36274113 PMCID: PMC9588852 DOI: 10.1186/s41747-022-00303-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 08/04/2022] [Indexed: 11/11/2022] Open
Abstract
Background We annually monitored stable compensated cirrhosis (CC) patients to evaluate serial variation in blood serum, liver stiffness, and multiparametric magnetic resonance imaging (mpMRI) measures to provide reference change values (RCV) and sample size measures for future studies. Methods Patients were recruited from a prospectively followed CC cohort, with assessments at baseline and annually over three years. We report on blood markers, transient elastography liver stiffness measures (LSM) and noninvasive mpMRI (volume, T1 mapping, blood flow, perfusion) of the liver, spleen, kidneys, and heart in a stable CC group and a healthy volunteer (HV) group. Coefficient of variation over time (CoVT) and RCV are reported, along with hazard ratio to assess disease progression. Sample size estimates to power future trials of cirrhosis regression on mpMRI are presented. Results Of 60 CC patients enrolled, 28 with stable CC were followed longitudinally and compared to 10 HVs. CoVT in mpMRI measures was comparable between CC and HV groups. CoVT of Enhanced Liver Fibrosis score was low (< 5%) compared to Fibrosis-4 index (17.9%) and Aspartate Aminotransferase-to-Platelet-Ratio Index (19.4%). A large CoVT (20.7%) and RCV (48.3%) were observed for LSM. CoVT and RCV were low for liver, spleen, and renal T1 values (CoVT < 5%, RCV < 8%) and volume (CoVT < 10%, RCV < 16%); haemodynamic measures were high (CoVT 12–25%, RCV 16–47%). Conclusions Evidence of low CoVT and RCV in multiorgan T1 values. RCV and sample size estimates are provided for future longitudinal multiorgan monitoring in CC patients. Trial registration ClinicalTrials.gov identifier: NCT02037867, Registered: 05/01/2013.
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Guljaš S, Benšić M, Krivdić Dupan Z, Pavlović O, Krajina V, Pavoković D, Šmit Takač P, Hranić M, Salha T. Dynamic Contrast Enhanced Study in Multiparametric Examination of the Prostate—Can We Make Better Use of It? Tomography 2022; 8:1509-1521. [PMID: 35736872 PMCID: PMC9231365 DOI: 10.3390/tomography8030124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 05/18/2022] [Accepted: 06/04/2022] [Indexed: 11/16/2022] Open
Abstract
We sought to investigate whether quantitative parameters from a dynamic contrast-enhanced study can be used to differentiate cancer from normal tissue and to determine a cut-off value of specific parameters that can predict malignancy more accurately, compared to the obturator internus muscle as a reference tissue. This retrospective study included 56 patients with biopsy proven prostate cancer (PCa) after multiparametric magnetic resonance imaging (mpMRI), with a total of 70 lesions; 39 were located in the peripheral zone, and 31 in the transition zone. The quantitative parameters for all patients were calculated in the detected lesion, morphologically normal prostate tissue and the obturator internus muscle. Increase in the Ktrans value was determined in lesion-to-muscle ratio by 3.974368, which is a cut-off value to differentiate between prostate cancer and normal prostate tissue, with specificity of 72.86% and sensitivity of 91.43%. We introduced a model to detect prostate cancer that combines Ktrans lesion-to-muscle ratio value and iAUC lesion-to-muscle ratio value, which is of higher accuracy compared to individual variables. Based on this model, we identified the optimal cut-off value with 100% sensitivity and 64.28% specificity. The use of quantitative DCE pharmacokinetic parameters compared to the obturator internus muscle as reference tissue leads to higher diagnostic accuracy for prostate cancer detection.
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Affiliation(s)
- Silva Guljaš
- Clinical Department of Radiology, University Hospital Centre, 31000 Osijek, Croatia; (Z.K.D.); (M.H.)
- Correspondence:
| | - Mirta Benšić
- Department of Mathematics, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia;
| | - Zdravka Krivdić Dupan
- Clinical Department of Radiology, University Hospital Centre, 31000 Osijek, Croatia; (Z.K.D.); (M.H.)
- Department of Radiology, Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia;
| | - Oliver Pavlović
- Department of Urology, University Hospital Centre Osijek, 31000 Osijek, Croatia; (O.P.); (V.K.); (D.P.)
| | - Vinko Krajina
- Department of Urology, University Hospital Centre Osijek, 31000 Osijek, Croatia; (O.P.); (V.K.); (D.P.)
| | - Deni Pavoković
- Department of Urology, University Hospital Centre Osijek, 31000 Osijek, Croatia; (O.P.); (V.K.); (D.P.)
| | - Petra Šmit Takač
- Clinical Department of Surgery, Osijek University Hospital Centre, 31000 Osijek, Croatia;
| | - Matija Hranić
- Clinical Department of Radiology, University Hospital Centre, 31000 Osijek, Croatia; (Z.K.D.); (M.H.)
| | - Tamer Salha
- Department of Radiology, Faculty of Medicine, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia;
- Department of Teleradiology and Artificial Intelligence, Health Centre Osijek-Baranja County, 31000 Osijek, Croatia
- Faculty of Dental Medicine and Health, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
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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}$$\overline{\mathrm{DNV} }$$\end{document}DNV¯) metrics were correlated with DCE-MRI vascular biomarkers such as time to peak contrast enhancement (\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). 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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Gerwing M, Krähling T, Schliemann C, Harrach S, Schwöppe C, Berdel AF, Klein S, Hartmann W, Wardelmann E, Heindel WL, Lenz G, Berdel WE, Wildgruber M. Multiparametric Magnetic Resonance Imaging for Immediate Target Hit Assessment of CD13-Targeted Tissue Factor tTF-NGR in Advanced Malignant Disease. Cancers (Basel) 2021; 13:cancers13235880. [PMID: 34884988 PMCID: PMC8657298 DOI: 10.3390/cancers13235880] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 11/17/2021] [Accepted: 11/21/2021] [Indexed: 11/30/2022] Open
Abstract
Simple Summary Since the knowledge of tumor biology has advanced, a variety of targeted therapies has been developed. These do not immediately affect the tumor size, so optimized oncological imaging is needed. In this phase I study of patients with advanced malignant disease, a multiparametric imaging approach was used to assess changes in tumor perfusion after vessel-occluding therapy with the CD13 targeted truncated tissue factor with a C-terminal NGR-peptide. It comprises different sequences and the use of two different contrast media, ferucarbotran and gadobutrol. This multiparametric MRI protocol enables assessing the therapy effectiveness as early as five hours after therapy initiation. Abstract Early assessment of target hit in anti-cancer therapies is a major task in oncologic imaging. In this study, immediate target hit and effectiveness of CD13-targeted tissue factor tTF-NGR in patients with advanced malignant disease enrolled in a phase I trial was assessed using a multiparametric MRI protocol. Seventeen patients with advanced solid malignancies were enrolled in the trial and received tTF-NGR for at least one cycle of five daily infusions. Tumor target lesions were imaged with multiparametric MRI before therapy initiation, five hours after the first infusion and after five days. The imaging protocol comprised ADC, calculated from DWI, and DCE imaging and vascular volume fraction (VVF) assessment. DCE and VVF values decreased within 5 h after therapy initiation, indicating early target hit with a subsequent decrease in tumor perfusion due to selective tumor vessel occlusion and thrombosis induced by tTF-NGR. Simultaneously, ADC values increased at five hours after tTF-NGR administration. In four patients, treatment had to be stopped due to an increase in troponin T hs, with subsequent anticoagulation. In these patients, a reversed effect, with DCE and VVF values increasing and ADC values decreasing, was observed after anticoagulation. Changes in imaging parameters were independent of the mean vessel density determined by immunohistochemistry. By using a multiparametric imaging approach, changes in tumor perfusion after initiation of a tumor vessel occluding therapy can be evaluated as early as five hours after therapy initiation, enabling early assessment of target hit.
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Affiliation(s)
- Mirjam Gerwing
- Clinic of Radiology, University Hospital Muenster, D-48149 Muenster, Germany; (T.K.); (W.L.H.); (M.W.)
- Correspondence:
| | - Tobias Krähling
- Clinic of Radiology, University Hospital Muenster, D-48149 Muenster, Germany; (T.K.); (W.L.H.); (M.W.)
| | - Christoph Schliemann
- Department of Medicine A, Hematology, Hemostaseology, Oncology and Pulmonology, University Hospital Muenster, D-48149 Muenster, Germany; (C.S.); (S.H.); (C.S.); (A.F.B.); (G.L.); (W.E.B.)
| | - Saliha Harrach
- Department of Medicine A, Hematology, Hemostaseology, Oncology and Pulmonology, University Hospital Muenster, D-48149 Muenster, Germany; (C.S.); (S.H.); (C.S.); (A.F.B.); (G.L.); (W.E.B.)
| | - Christian Schwöppe
- Department of Medicine A, Hematology, Hemostaseology, Oncology and Pulmonology, University Hospital Muenster, D-48149 Muenster, Germany; (C.S.); (S.H.); (C.S.); (A.F.B.); (G.L.); (W.E.B.)
| | - Andrew F. Berdel
- Department of Medicine A, Hematology, Hemostaseology, Oncology and Pulmonology, University Hospital Muenster, D-48149 Muenster, Germany; (C.S.); (S.H.); (C.S.); (A.F.B.); (G.L.); (W.E.B.)
| | - Sebastian Klein
- Gerhard-Domagk-Institute for Pathology, University of Muenster, D-48149 Muenster, Germany; (S.K.); (W.H.); (E.W.)
| | - Wolfgang Hartmann
- Gerhard-Domagk-Institute for Pathology, University of Muenster, D-48149 Muenster, Germany; (S.K.); (W.H.); (E.W.)
| | - Eva Wardelmann
- Gerhard-Domagk-Institute for Pathology, University of Muenster, D-48149 Muenster, Germany; (S.K.); (W.H.); (E.W.)
| | - Walter L. Heindel
- Clinic of Radiology, University Hospital Muenster, D-48149 Muenster, Germany; (T.K.); (W.L.H.); (M.W.)
| | - Georg Lenz
- Department of Medicine A, Hematology, Hemostaseology, Oncology and Pulmonology, University Hospital Muenster, D-48149 Muenster, Germany; (C.S.); (S.H.); (C.S.); (A.F.B.); (G.L.); (W.E.B.)
| | - Wolfgang E. Berdel
- Department of Medicine A, Hematology, Hemostaseology, Oncology and Pulmonology, University Hospital Muenster, D-48149 Muenster, Germany; (C.S.); (S.H.); (C.S.); (A.F.B.); (G.L.); (W.E.B.)
| | - Moritz Wildgruber
- Clinic of Radiology, University Hospital Muenster, D-48149 Muenster, Germany; (T.K.); (W.L.H.); (M.W.)
- Department of Radiology, University Hospital, LMU Munich, D-81377 Munich, Germany
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10
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Ursprung S, Priest AN, Zaccagna F, Qian W, Machin A, Stewart GD, Warren AY, Eisen T, Welsh SJ, Gallagher FA, Barrett T. Multiparametric MRI for assessment of early response to neoadjuvant sunitinib in renal cell carcinoma. PLoS One 2021; 16:e0258988. [PMID: 34699525 PMCID: PMC8547646 DOI: 10.1371/journal.pone.0258988] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 10/08/2021] [Indexed: 11/29/2022] Open
Abstract
PURPOSE To detect early response to sunitinib treatment in metastatic clear cell renal cancer (mRCC) using multiparametric MRI. METHOD Participants with mRCC undergoing pre-surgical sunitinib therapy in the prospective NeoSun clinical trial (EudraCtNo: 2005-004502-82) were imaged before starting treatment, and after 12 days of sunitinib therapy using morphological MRI sequences, advanced diffusion-weighted imaging, measurements of R2* (related to hypoxia) and dynamic contrast-enhanced imaging. Following nephrectomy, participants continued treatment and were followed-up with contrast-enhanced CT. Changes in imaging parameters before and after sunitinib were assessed with the non-parametric Wilcoxon signed-rank test and the log-rank test was used to assess effects on survival. RESULTS 12 participants fulfilled the inclusion criteria. After 12 days, the solid and necrotic tumor volumes decreased by 28% and 17%, respectively (p = 0.04). However, tumor-volume reduction did not correlate with progression-free or overall survival (PFS/OS). Sunitinib therapy resulted in a reduction in median solid tumor diffusivity D from 1298x10-6 to 1200x10-6mm2/s (p = 0.03); a larger decrease was associated with a better RECIST response (p = 0.02) and longer PFS (p = 0.03) on the log-rank test. An increase in R2* from 19 to 28s-1 (p = 0.001) was observed, paralleled by a decrease in Ktrans from 0.415 to 0.305min-1 (p = 0.01) and a decrease in perfusion fraction from 0.34 to 0.19 (p<0.001). CONCLUSIONS Physiological imaging confirmed efficacy of the anti-angiogenic agent 12 days after initiating therapy and demonstrated response to treatment. The change in diffusivity shortly after starting pre-surgical sunitinib correlated to PFS in mRCC undergoing nephrectomy, however, no parameter predicted OS. TRIAL REGISTRATION EudraCtNo: 2005-004502-82.
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Affiliation(s)
- Stephan Ursprung
- University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, United Kingdom
| | - Andrew N. Priest
- University of Cambridge, Cambridge, United Kingdom
- Addenbrooke’s Hospital, Cambridge University Hospital NHS Foundation Trust, Cambridge, United Kingdom
| | | | - Wendi Qian
- University of Cambridge, Cambridge, United Kingdom
- Cambridge Cancer Trial Centre, Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Andrea Machin
- University of Cambridge, Cambridge, United Kingdom
- Cambridge Cancer Trial Centre, Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Grant D. Stewart
- University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, United Kingdom
- Addenbrooke’s Hospital, Cambridge University Hospital NHS Foundation Trust, Cambridge, United Kingdom
| | - Anne Y. Warren
- University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, United Kingdom
- Addenbrooke’s Hospital, Cambridge University Hospital NHS Foundation Trust, Cambridge, United Kingdom
| | - Timothy Eisen
- University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, United Kingdom
- Addenbrooke’s Hospital, Cambridge University Hospital NHS Foundation Trust, Cambridge, United Kingdom
| | - Sarah J. Welsh
- University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, United Kingdom
- Addenbrooke’s Hospital, Cambridge University Hospital NHS Foundation Trust, Cambridge, United Kingdom
| | - Ferdia A. Gallagher
- University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, United Kingdom
| | - Tristan Barrett
- University of Cambridge, Cambridge, United Kingdom
- Cancer Research UK Cambridge Centre, University of Cambridge, Cambridge, United Kingdom
- Addenbrooke’s Hospital, Cambridge University Hospital NHS Foundation Trust, Cambridge, United Kingdom
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11
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Jacquier M, Arthuis C, Grévent D, Bussières L, Henry C, Millischer-Bellaiche AE, Mahallati H, Ville Y, Siauve N, Salomon LJ. Dynamic contrast enhanced magnetic resonance imaging: A review of its application in the assessment of placental function. Placenta 2021; 114:90-99. [PMID: 34507031 DOI: 10.1016/j.placenta.2021.08.055] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Revised: 06/02/2021] [Accepted: 08/23/2021] [Indexed: 01/02/2023]
Abstract
It is important to develop a better understanding of placental insufficiency given its role in common maternofetal complications such as preeclampsia and fetal growth restriction. Functional magnetic resonance imaging offers unprecedented techniques for exploring the placenta under both normal and pathological physiological conditions. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) is an established and very robust method to investigate the microcirculatory parameters of an organ and more specifically its perfusion. It is currently a gold standard in the physiological and circulatory evaluation of an organ. Its application to the human placenta could enable to access many microcirculatory parameters relevant to the placental function such as organ blood flow, fractional blood volume, and permeability surface area, by the acquisition of serial images, before, during, and after administration of an intravenous contrast agent. Widely used in animal models with gadolinium-based contrast agents, its application to the human placenta could be possible if the safety of contrast agents in pregnancy is established or they are confirmed to not cross the placenta.
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Affiliation(s)
- Mathilde Jacquier
- Obstetrics and Gynecology Department, Assistance Publique - Hôpitaux de Paris, Hôpital Necker - Enfants Malades, 149 Rue de Sèvres, 75015, Paris, France; EA FETUS 7328 and LUMIERE Unit, Université de Paris, France
| | - Chloé Arthuis
- EA FETUS 7328 and LUMIERE Unit, Université de Paris, France; Obstetrics and Gynecology Department, CHU Nantes, 38 Boulevard Jean Monnet, 44000, Nantes, France
| | - David Grévent
- EA FETUS 7328 and LUMIERE Unit, Université de Paris, France; Radiology Department, Assistance Publique - Hôpitaux de Paris, Hôpital Necker - Enfants Malades, 149 Rue de Sèvres, 75015, Paris, France
| | - Laurence Bussières
- Obstetrics and Gynecology Department, Assistance Publique - Hôpitaux de Paris, Hôpital Necker - Enfants Malades, 149 Rue de Sèvres, 75015, Paris, France; EA FETUS 7328 and LUMIERE Unit, Université de Paris, France
| | - Charline Henry
- EA FETUS 7328 and LUMIERE Unit, Université de Paris, France
| | - Anne-Elodie Millischer-Bellaiche
- EA FETUS 7328 and LUMIERE Unit, Université de Paris, France; Radiology Department, Assistance Publique - Hôpitaux de Paris, Hôpital Necker - Enfants Malades, 149 Rue de Sèvres, 75015, Paris, France
| | - Houman Mahallati
- Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Yves Ville
- Obstetrics and Gynecology Department, Assistance Publique - Hôpitaux de Paris, Hôpital Necker - Enfants Malades, 149 Rue de Sèvres, 75015, Paris, France; EA FETUS 7328 and LUMIERE Unit, Université de Paris, France
| | - Nathalie Siauve
- Radiology Department, Assistance Publique - Hôpitaux de Paris, Hôpital Louis Mourier, 178 Rue des Renouillers, 92700, Colombes, France; INSERM, U970, Paris Cardiovascular Research Center - PARCC, Paris, France
| | - Laurent J Salomon
- Obstetrics and Gynecology Department, Assistance Publique - Hôpitaux de Paris, Hôpital Necker - Enfants Malades, 149 Rue de Sèvres, 75015, Paris, France; EA FETUS 7328 and LUMIERE Unit, Université de Paris, France.
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12
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Xie X, Gu L, Guo Z, Tao H, Zhou Y, Shen W, Zhou Z. DCE‐MRI
for early evaluation of therapeutic response in esophageal cancer after concurrent chemoradiotherapy and its values in predicting
HIF
‐1α expression. PRECISION MEDICAL SCIENCES 2021. [DOI: 10.1002/prm2.12049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Affiliation(s)
- Xiaodong Xie
- Department of Radiology Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research Nanjing China
- Department of Radiology Nanjing Drum Tower Hospital, Clinical College of Nanjing Medical University Nanjing China
| | - Lingling Gu
- Department of Radiology Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research Nanjing China
| | - Zhen Guo
- Department of Radiology Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research Nanjing China
| | - Hua Tao
- Department of Radiation Oncology Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research Nanjing China
| | - Yiqin Zhou
- Department of Radiation Oncology Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research Nanjing China
| | - Wenrong Shen
- Department of Radiology Nanjing Medical University Affiliated Cancer Hospital, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research Nanjing China
| | - Zhengyang Zhou
- Department of Radiology Nanjing Drum Tower Hospital, Clinical College of Nanjing Medical University Nanjing China
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13
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Shoghi KI, Badea CT, Blocker SJ, Chenevert TL, Laforest R, Lewis MT, Luker GD, Manning HC, Marcus DS, Mowery YM, Pickup S, Richmond A, Ross BD, Vilgelm AE, Yankeelov TE, Zhou R. Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine. ACTA ACUST UNITED AC 2021; 6:273-287. [PMID: 32879897 PMCID: PMC7442091 DOI: 10.18383/j.tom.2020.00023] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The National Institutes of Health’s (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.
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Affiliation(s)
- Kooresh I Shoghi
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Cristian T Badea
- Department of Radiology, Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC
| | - Stephanie J Blocker
- Department of Radiology, Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC
| | | | - Richard Laforest
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Michael T Lewis
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX
| | - Gary D Luker
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | - H Charles Manning
- Vanderbilt Center for Molecular Probes-Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN
| | - Daniel S Marcus
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Yvonne M Mowery
- Department of Radiation Oncology, Duke University Medical Center, Durham, Durham, NC
| | - Stephen Pickup
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania.,Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
| | - Ann Richmond
- Department of Pharmacology, Vanderbilt School of Medicine, Nashville, TN
| | - Brian D Ross
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | - Anna E Vilgelm
- Department of Pathology, The Ohio State University, Columbus, OH
| | - Thomas E Yankeelov
- Departments of Biomedical Engineering, Diagnostic Medicine, and Oncology, Oden Institute for Computational Engineering and Sciences, Austin, TX; and.,Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX
| | - Rong Zhou
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania.,Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
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14
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Saida Y, Brender JR, Yamamoto K, Mitchell JB, Krishna MC, Kishimoto S. Multimodal Molecular Imaging Detects Early Responses to Immune Checkpoint Blockade. Cancer Res 2021; 81:3693-3705. [PMID: 33837042 DOI: 10.1158/0008-5472.can-20-3182] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 02/17/2021] [Accepted: 04/08/2021] [Indexed: 01/02/2023]
Abstract
Immune checkpoint blockade (ICB) has become a standard therapy for several cancers, however, the response to ICB is inconsistent and a method for noninvasive assessment has not been established to date. To investigate the capability of multimodal imaging to evaluate treatment response to ICB therapy, hyperpolarized 13C MRI using [1-13C] pyruvate and [1,4-13C2] fumarate and dynamic contrast enhanced (DCE) MRI was evaluated to detect early changes in tumor glycolysis, necrosis, and intratumor perfusion/permeability, respectively. Mouse tumor models served as platforms for high (MC38 colon adenocarcinoma) and low (B16-F10 melanoma) sensitivity to dual ICB of PD-L1 and CTLA4. Glycolytic flux significantly decreased following treatment only in the less sensitive B16-F10 tumors. Imaging [1,4-13C2] fumarate conversion to [1,4-13C2] malate showed a significant increase in necrotic cell death following treatment in the ICB-sensitive MC38 tumors, with essentially no change in B16-F10 tumors. DCE-MRI showed significantly increased perfusion/permeability in MC38-treated tumors, whereas a similar, but statistically nonsignificant, trend was observed in B16-F10 tumors. When tumor volume was also taken into consideration, each imaging biomarker was linearly correlated with future survival in both models. These results suggest that hyperpolarized 13C MRI and DCE MRI may serve as useful noninvasive imaging markers to detect early response to ICB therapy. SIGNIFICANCE: Hyperpolarized 13C MRI and dynamic contrast enhanced MRI in murine tumor models provide useful insight into evaluating early response to immune checkpoint blockade therapy.See related commentary by Cullen and Keshari, p. 3444.
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Affiliation(s)
- Yu Saida
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland
| | - Jeffrey R Brender
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland
| | - Kazutoshi Yamamoto
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland
| | - James B Mitchell
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland
| | - Murali C Krishna
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland
| | - Shun Kishimoto
- Radiation Biology Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, Maryland.
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15
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Ianniello C, Moy L, Fogarty J, Schnabel F, Adams S, Axelrod D, Axel L, Brown R, Madelin G. Multinuclear MRI to disentangle intracellular sodium concentration and extracellular volume fraction in breast cancer. Sci Rep 2021; 11:5156. [PMID: 33664340 PMCID: PMC7933187 DOI: 10.1038/s41598-021-84616-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 02/16/2021] [Indexed: 01/31/2023] Open
Abstract
The purpose of this work was to develop a novel method to disentangle the intra- and extracellular components of the total sodium concentration (TSC) in breast cancer from a combination of proton ([Formula: see text]H) and sodium ([Formula: see text]) magnetic resonance imaging (MRI) measurements. To do so, TSC is expressed as function of the intracellular sodium concentration ([Formula: see text]), extracellular volume fraction (ECV) and the water fraction (WF) based on a three-compartment model of the tissue. TSC is measured from [Formula: see text] MRI, ECV is calculated from baseline and post-contrast [Formula: see text]H [Formula: see text] maps, while WF is measured with a [Formula: see text]H chemical shift technique. [Formula: see text] is then extrapolated from the model. Proof-of-concept was demonstrated in three healthy subjects and two patients with triple negative breast cancer. In both patients, TSC was two to threefold higher in the tumor than in normal tissue. This alteration mainly resulted from increased [Formula: see text] ([Formula: see text] 30 mM), which was [Formula: see text] 130% greater than in healthy conditions (10-15 mM) while the ECV was within the expected range of physiological values (0.2-0.25). Multinuclear MRI shows promise for disentangling [Formula: see text] and ECV by taking advantage of complementary [Formula: see text]H and [Formula: see text] measurements.
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Affiliation(s)
- Carlotta Ianniello
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Linda Moy
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Perlmutter Cancer Center, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Justin Fogarty
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Freya Schnabel
- Department of Surgery, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Perlmutter Cancer Center, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Sylvia Adams
- Department of Medicine, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Perlmutter Cancer Center, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Deborah Axelrod
- Department of Surgery, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Perlmutter Cancer Center, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Leon Axel
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Ryan Brown
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY, 10016, USA
| | - Guillaume Madelin
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA.
- Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, 10016, USA.
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY, 10016, USA.
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16
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Musall BC, Abdelhafez AH, Adrada BE, Candelaria RP, Mohamed RMM, Boge M, Le-Petross H, Arribas E, Lane DL, Spak DA, Leung JWT, Hwang KP, Son JB, Elshafeey NA, Mahmoud HS, Wei P, Sun J, Zhang S, White JB, Ravenberg EE, Litton JK, Damodaran S, Thompson AM, Moulder SL, Yang WT, Pagel MD, Rauch GM, Ma J. Functional Tumor Volume by Fast Dynamic Contrast-Enhanced MRI for Predicting Neoadjuvant Systemic Therapy Response in Triple-Negative Breast Cancer. J Magn Reson Imaging 2021; 54:251-260. [PMID: 33586845 DOI: 10.1002/jmri.27557] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 01/26/2021] [Accepted: 01/27/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Dynamic contrast-enhanced (DCE) MRI is useful for diagnosis and assessment of treatment response in breast cancer. Fast DCE MRI offers a higher sampling rate of contrast enhancement curves in comparison to conventional DCE MRI, potentially characterizing tumor perfusion kinetics more accurately for measurement of functional tumor volume (FTV) as a predictor of treatment response. PURPOSE To investigate FTV by fast DCE MRI as a predictor of neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC). STUDY TYPE Prospective. POPULATION/SUBJECTS Sixty patients with biopsy-confirmed TNBC between December 2016 and September 2020. FIELD STRENGTH/SEQUENCE A 3.0 T/3D fast spoiled gradient echo-based DCE MRI ASSESSMENT: Patients underwent MRI at baseline and after four cycles (C4) of NAST, followed by definitive surgery. DCE subtraction images were analyzed in consensus by two breast radiologists with 5 (A.H.A.) and 2 (H.S.M.) years of experience. Tumor volumes (TV) were measured on early and late subtractions. Tumors were segmented on 1 and 2.5-minute early phases subtractions and FTV was determined using optimized signal enhancement thresholds. Interpolated enhancement curves from segmented voxels were used to determine optimal early phase timing. STATISTICAL TESTS Tumor volumes were compared between patients who had a pathologic complete response (pCR) and those who did not using the area under the receiver operating curve (AUC) and Mann-Whitney U test. RESULTS About 26 of 60 patients (43%) had pCR. FTV at 1 minute after injection at C4 provided the best discrimination between pCR and non-pCR, with AUC (95% confidence interval [CI]) = 0.85 (0.74,0.95) (P < 0.05). The 1-minute timing was optimal for FTV measurements at C4 and for the change between C4 and baseline. TV from the early phase at C4 also yielded a good AUC (95%CI) of 0.82 (0.71,0.93) (P < 0.05). DATA CONCLUSION FTV and TV measured at 1 minute after injection can predict response to NAST in TNBC. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: 4.
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Affiliation(s)
- Benjamin C Musall
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Abeer H Abdelhafez
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Beatriz E Adrada
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Rosalind P Candelaria
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Rania M M Mohamed
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Medine Boge
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Huong Le-Petross
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Elsa Arribas
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Deanna L Lane
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - David A Spak
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jessica W T Leung
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ken-Pin Hwang
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jong Bum Son
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Nabil A Elshafeey
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Hagar S Mahmoud
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Peng Wei
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jia Sun
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Shu Zhang
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jason B White
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Elizabeth E Ravenberg
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jennifer K Litton
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Senthil Damodaran
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | | | - Stacy L Moulder
- Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Wei T Yang
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Mark D Pagel
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Gaiane M Rauch
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.,Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Jingfei Ma
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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Guo B, Ouyang F, Ouyang L, Huang X, Guo T, Lin S, Liu Z, Zhang R, Yang SM, Chen H, Hu QG. Intravoxel Incoherent Motion Magnetic Resonance Imaging for Prediction of Induction Chemotherapy Response in Locally Advanced Hypopharyngeal Carcinoma: Comparison With Model-Free Dynamic Contrast-Enhanced Magnetic Resonance Imaging. J Magn Reson Imaging 2021; 54:91-100. [PMID: 33576125 DOI: 10.1002/jmri.27537] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Revised: 01/05/2021] [Accepted: 01/06/2021] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Multiparametric intravoxel incoherent motion (IVIM) provides diffusion and perfusion information for the treatment prediction of cancer. However, the superiority of IVIM over dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in locally advanced hypopharyngeal carcinoma (LAHC) remains unclear. PURPOSE To compare the diagnostic performance of IVIM and model-free DCE in assessing induction chemotherapy (IC) response in patients with LAHC. STUDY TYPE Prospective. POPULATION Forty-two patients with LAHC. FIELD STRENGTH/SEQUENCE 3.0 T MRI, including IVIM (12 b values, 0-800 seconds/mm2 ) with a single-shot echo planar imaging sequence and DCE-MRI with a volumetric interpolated breath-hold examination sequence. IVIM MRI is a commercially available sequence and software for calculation and analysis from vendor. ASSESSMENT The IVIM-derived parameters (diffusion coefficient [D], pseudodiffusion coefficient [D*], and perfusion fraction [f]) and DCE-derived model-free parameters (Wash-in, time to maximum enhancement [Tmax], maximum enhancement [Emax], area under enhancement curve [AUC] over 60 seconds [AUC60 ], and whole area under enhancement curve [AUCw ]) were measured. At the end of IC, patients with complete or partial response were classified as responders according to the Response Evaluation Criteria in Solid Tumors. STATISTICAL TESTS The differences of parameters between responders and nonresponders were assessed using Mann-Whitney U tests. The performance of parameters for predicting IC response was evaluated by the receiver operating characteristic curves. RESULTS Twenty-three (54.8%) patients were classified as responders. Compared with nonresponders, the perfusion parameters D*, f, f × D*, and AUCw were significantly higher whereas Wash-in was lower in responders (all P-values <0.05). The f × D* outperformed other parameters, with an AUC of 0.84 (95% confidence interval [CI]: 0.69-0.93), sensitivity of 79.0% (95% CI: 54.4-93.9), and specificity of 82.6% (95% CI: 61.2-95.0). DATA CONCLUSION The IVIM MRI technique may noninvasively help predict the IC response before treatment in patients with LAHC. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Baoliang Guo
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Fusheng Ouyang
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Lizhu Ouyang
- Department of Ultrasound, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Xiyi Huang
- Department of Clinical Laboratory, The Affiliated Shunde Hospital of Guangzhou, Medical University, Foshan, China
| | - Tiandi Guo
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Shaojia Lin
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Ziwei Liu
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Rong Zhang
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Shao-Min Yang
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Haixiong Chen
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
| | - Qiu-Gen Hu
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde, Foshan), Foshan, China
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Notohamiprodjo S, Varasteh Z, Beer AJ, Niu G, Chen X(S, Weber W, Schwaiger M. Tumor Vasculature. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00090-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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19
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Wang F. Semi-Quantitative RT-PCR: An Effective Method to Explore the Regulation of Gene Transcription Level Affected by Environmental Pollutants. Methods Mol Biol 2021; 2326:95-103. [PMID: 34097263 DOI: 10.1007/978-1-0716-1514-0_7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Semi-quantitative reverse transcription and polymerase chain reaction (sqRT-PCR) is a simple and specific method for quantitative RNA in recent years. The relative quantity of a specific mRNA in the samples can be inferred by reverse transcription of mRNA into cDNA, and PCR amplification and determination of the quantity of PCR products. The semi-quantitative analysis is carried out under a fixed number of PCR cycles, and the total RNA concentration is kept in the exponential phase of the PCR. The method is to use a housekeeping gene (usually actin, GAPDH, and EF1α) as a reference standard in treated and control organisms to observe the expression of the interested genes (upregulated or downregulated) in toxicology. In this chapter, we describe a step-by-step method for determining the differential regulation of target genes in organisms exposed to environmental pollutants.
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Affiliation(s)
- Fan Wang
- School of Biological Science, Luoyang Normal University, Luoyang, China.
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20
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Kim JH, Oh E, Yoon YC, Lee DK, Lee SS, Wang JH. Remnant-Tensioning Single-Bundle Anterior Cruciate Ligament Reconstruction Provides Comparable Stability to and Better Graft Vascularity Than Double-Bundle Anterior Cruciate Ligament Reconstruction in Acute or Subacute Injury: A Prospective Randomized Controlled Study Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging. Arthroscopy 2021; 37:209-221. [PMID: 33221428 DOI: 10.1016/j.arthro.2020.08.035] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 08/24/2020] [Accepted: 08/25/2020] [Indexed: 02/02/2023]
Abstract
PURPOSE To compare the clinical, second-look arthroscopic, magnetic resonance imaging (MRI), and dynamic-contrast-enhanced MRI (DCE-MRI) findings between remnant-tensioning single-bundle (RT-SB) and double-bundle (DB) anterior cruciate ligament reconstruction (ACLR). METHODS Sixty-seven patients with acute or subacute anterior cruciate ligament (ACL) injury were randomized to undergo RT-SB or DB ACLR. Twenty-six patients in the RT-SB group and 28 in the DB group were evaluated using stability tests (Lachman test, pivot-shift test, and KT-2000 arthrometer) and multiple clinical scores. One year postoperatively, all 54 patients underwent MRI for evaluation of graft continuity and graft signal/noise quotient and DCE-MRI for the calculation of normalized area under the curve (nAUC) as a marker of graft vascularity. Among them, 41 patients underwent second-look arthroscopy for the evaluation of graft continuity, graft tension, and synovialization. The results were compared between the 2 groups. RESULTS At the minimum 2-year follow-up (28.7 ± 6.4 months), the stability tests, clinical scores, second-look arthroscopic findings, and MRI findings were not significantly different between the groups. However, the mean nAUC values on DCE-MRI for the ACL graft were significantly higher in the RT-SB group than those in the DB group in all 3 zones (nAUCproximal, P = .005; nAUCmiddle, P = .021; nAUCdistal, P = .027; and nAUCaverage, P = .008). CONCLUSION For acute or subacute ACL injury, the RT-SB ACLR showed an outcome comparable to that of DB ACLR in terms of knee stability, clinical scores, MRI findings, and second-look arthroscopic findings. Moreover, RT-SB ACLR showed better graft vascularity 1 year postoperatively than DB ACLR using DCE-MRI. LEVEL OF EVIDENCE II, prospective randomized controlled trial.
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Affiliation(s)
- Jun Ho Kim
- Department of Orthopedic Surgery, Seoul Medical Center, Seoul, South Korea
| | - Eunsun Oh
- Department of Radiology, Soonchunhyang University Seoul Hospital, Seoul, South Korea
| | - Young Cheol Yoon
- Department of Radiology, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, South Korea; Department of Orthopaedic Surgery, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, South Korea
| | - Do Kyung Lee
- Department of Orthopaedic Surgery, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, South Korea
| | - Sung-Sahn Lee
- Department of Orthopedic Surgery, Ilsan Paik Hospital, Inje University School of Medicine, South Korea
| | - Joon Ho Wang
- Department of Orthopaedic Surgery, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, South Korea; Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Korea; Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul, Korea.
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21
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Kim JH, Oh E, Yoon YC, Lee DK, Lee SS, Song SY, Wang JH. The relationship between graft synovialization and graft revascularization after ACL reconstruction: Assessment using dynamic contrast enhanced-MRI and second-look arthroscopy. Eur J Radiol 2020; 133:109346. [PMID: 33137594 DOI: 10.1016/j.ejrad.2020.109346] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 09/07/2020] [Accepted: 10/06/2020] [Indexed: 02/07/2023]
Abstract
PURPOSE To assess graft vascularity via dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) at 1-year and 2-year postoperatively and to evaluate the relationship between the vascularity using DCE-MRI and the synovialization using second-look arthroscopy. MATERIALS AND METHODS Fifty-four patients from prospective data included who underwent anterior cruciate ligament reconstruction (ACLR) and DCE-MRI. The graft was divided into proximal, middle, and distal zones; average of three zones was calculated. Signal/noise quotient (SNQ) was measured on proton-density image and normalized area under the curve (nAUC) was calculated from DCE-MRI. The results at 1-year (SNQ-1 and nAUC-1) and 2-year (SNQ-2 and nAUC-2) postoperatively were compared between two time points. Forty-one patients underwent second-look arthroscopy were classified into three groups according to the synovialization: Excellent (n = 17), Fair (n = 16), and Poor (n = 8). The SNQs and nAUCs were compared between three groups. RESULTS Fifty-four and 23 patients underwent DCE-MRI at 1-year and 2-year, respectively. A significant decrease was observed from nAUCaverage-1 to nAUCaverage-2 (95 % confidential interval, 0.4-2.3; P = .007). Both SNQaverage-1 and SNQaverage-2 were significantly lower in the excellent than in the poor (SNQaverage-1, P < .001; SNQaverage-2, P = .003). Both SNQaverage-1 and SNQaverage-2 were significantly lower in the fair than in the poor (SNQaverage-1, P=.032; SNQaverage-2, P = .012). Both nAUCaverage-1 and nAUCaverage-2 were significantly higher in the excellent than in the poor (nAUCaverage-1, P < .001; nAUCaverage-2, P = .010). The nAUCaverage-1 was significantly higher in the excellent than the fair (nAUCaverage-1, P < .001). CONCLUSION Well-synovialized grafts showed significantly lower SNQs and significantly higher nAUCs than did poor-synovialized grafts based on the second-look arthroscopic findings. We can indirectly infer from this result that well-synovialized grafts may have better biomechanical properties.
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Affiliation(s)
- Jun Ho Kim
- Department of Orthopedic Surgery, Seoul Medical Center, 156 Sinnae-ro, Jungnang-gu, Seoul, South Korea.
| | - Eunsun Oh
- Department of Radiology, Soonchunhyang University Seoul Hospital, Seoul, South Korea.
| | - Young Cheol Yoon
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Department of Orthopedic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
| | - Do Kyung Lee
- Department of Orthopaedic Surgery, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, South Korea.
| | - Sung-Sahn Lee
- Department of Orthopedic Surgery, Ilsan Paik Hospital, Inje University School of Medicine, South Korea.
| | - Se Yong Song
- Department of Orthopedic Surgery, Seoul Medical Center, 156 Sinnae-ro, Jungnang-gu, Seoul, South Korea.
| | - Joon Ho Wang
- Department of Orthopedic Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Department of Health Sciences and Technology and Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul, South Korea; Investigation Performed at the Department of Orthopedic Surgery, Samsung Medical Center, College of Sungkyunkwan University, Seoul, South Korea.
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22
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Schidlowski M, Stirnberg R, Stöcker T, Rüber T. Reliability of quantitative transverse relaxation time mapping with [Formula: see text]-prepared whole brain pCASL. Sci Rep 2020; 10:18299. [PMID: 33110203 PMCID: PMC7592060 DOI: 10.1038/s41598-020-74680-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Accepted: 09/29/2020] [Indexed: 01/21/2023] Open
Abstract
Arterial spin labeling (ASL) is increasingly applied for cerebral blood flow mapping, but [Formula: see text] relaxation of the ASL signal magnetization is often ignored, although it may be clinically relevant. To investigate the extent, to which quantitative [Formula: see text] values in gray matter (GM) obtained by pseudocontinuous ASL (pCASL) perfusion MRI can be reproduced, are reliable and a potential neuroscientific biomarker, a prospective study was performed with ten healthy volunteers (5F,28 ± 3y) at a 3 T scanner. A [Formula: see text]-prepared pCASL sequence enabled the measurement of quantitative [Formula: see text] and perfusion maps. [Formula: see text] times were modeled per voxel and analyzed within four GM-regions-of-interest (ROI). The intraclass correlation coefficients (ICCs) of the quantified ASL-[Formula: see text] varied across brain regions. When averaged across subjects and postlabeling delays (PLDs), the ICCs ranged from reasonable values in parietal regions (ICC = 0.56) to smaller values in frontal regions (ICC = 0.36). Corresponding subject-averaged within-subject coefficients of variation (WSCVs) showed good test-retest measurement precision ([Formula: see text] for all PLDs), but more pronounced inter-subject variance. Reliability and precision of quantified ASL-[Formula: see text] were region-, PLD- and subject-specific, showing fair to robust results in occipital, parietal and temporal ROIs. The results give rise to consider the method for future cerebral studies, where variable perfusion or altered [Formula: see text] times are suspected.
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Affiliation(s)
- Martin Schidlowski
- Department of Epileptology, University of Bonn Medical Center, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | | | - Tony Stöcker
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department for Physics and Astronomy, University of Bonn, Bonn, Germany
| | - Theodor Rüber
- Department of Epileptology, University of Bonn Medical Center, Bonn, Germany
- Department of Neurology, Epilepsy Center Frankfurt Rhine-Main, Goethe University Frankfurt, Frankfurt/Main, Germany
- Center for Personalized Translational Epilepsy Research (CePTER), Goethe University Frankfurt, Frankfurt/Main, Germany
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23
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Lorza AMA, Ravi H, Philip RC, Galons JP, Trouard TP, Parra NA, Von Hoff DD, Read WL, Tibes R, Korn RL, Raghunand N. Dose-response assessment by quantitative MRI in a phase 1 clinical study of the anti-cancer vascular disrupting agent crolibulin. Sci Rep 2020; 10:14449. [PMID: 32879326 PMCID: PMC7468301 DOI: 10.1038/s41598-020-71246-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 08/10/2020] [Indexed: 02/08/2023] Open
Abstract
The vascular disrupting agent crolibulin binds to the colchicine binding site and produces anti-vascular and apoptotic effects. In a multisite phase 1 clinical study of crolibulin (NCT00423410), we measured treatment-induced changes in tumor perfusion and water diffusivity (ADC) using dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI), and computed correlates of crolibulin pharmacokinetics. 11 subjects with advanced solid tumors were imaged by MRI at baseline and 2–3 days post-crolibulin (13–24 mg/m2). ADC maps were computed from DW-MRI. Pre-contrast T1 maps were computed, co-registered with the DCE-MRI series, and maps of area-under-the-gadolinium-concentration-curve-at-90 s (AUC90s) and the Extended Tofts Model parameters ktrans, ve, and vp were calculated. There was a strong correlation between higher plasma drug \documentclass[12pt]{minimal}
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\begin{document}$${C}^{max}$$\end{document}Cmax and a linear combination of (1) reduction in tumor fraction with \documentclass[12pt]{minimal}
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\begin{document}$${AUC}_{90s}>15.8$$\end{document}AUC90s>15.8 mM s, and, (2) increase in tumor fraction with \documentclass[12pt]{minimal}
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\begin{document}$${v}_{e}<0.3$$\end{document}ve<0.3. A higher plasma drug AUC was correlated with a linear combination of (1) increase in tumor fraction with \documentclass[12pt]{minimal}
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\begin{document}$${\text{ADC}} < 1.1 \times 10^{ - 3} \;{\text{mm}}^{2} /{\text{s}}$$\end{document}ADC<1.1×10-3mm2/s, and, (2) increase in tumor fraction with \documentclass[12pt]{minimal}
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\begin{document}$$v_{e}<0.3$$\end{document}ve<0.3. These findings are suggestive of cell swelling and decreased tumor perfusion 2–3 days post-treatment with crolibulin. The multivariable linear regression models reported here can inform crolibulin dosing in future clinical studies of crolibulin combined with cytotoxic or immune-oncology agents.
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Affiliation(s)
- Andres M Arias Lorza
- Department of Cancer Physiology, Moffitt Cancer Center, SRB-4, Tampa, FL, 33612, USA
| | - Harshan Ravi
- Department of Cancer Physiology, Moffitt Cancer Center, SRB-4, Tampa, FL, 33612, USA
| | - Rohit C Philip
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, 85721, USA
| | | | - Theodore P Trouard
- Department of Biomedical Engineering, University of Arizona, Tucson, AZ, 85724, USA
| | - Nestor A Parra
- Department of Cancer Physiology, Moffitt Cancer Center, SRB-4, Tampa, FL, 33612, USA
| | - Daniel D Von Hoff
- Translational Genomics Research Institute (TGen), Phoenix, AZ, USA.,HonorHealth Clinical Research Institute, Scottsdale, AZ, USA
| | - William L Read
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA, USA
| | - Raoul Tibes
- Department of Internal Medicine II, Julius Maximilians University and Medical Center, Würzburg, Germany
| | | | - Natarajan Raghunand
- Department of Cancer Physiology, Moffitt Cancer Center, SRB-4, Tampa, FL, 33612, USA. .,Department of Oncologic Sciences, University of South Florida, Tampa, FL, USA.
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Lin M, Zhang Q, Song Y, Yu X, Ouyang H, Xie L, Shang Y. Differentiation of endometrial adenocarcinoma from adenocarcinoma of cervix using kinetic parameters derived from DCE-MRI. Eur J Radiol 2020; 130:109190. [PMID: 32745897 DOI: 10.1016/j.ejrad.2020.109190] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 07/16/2020] [Accepted: 07/21/2020] [Indexed: 11/28/2022]
Abstract
PURPOSE This prospective study aimed to investigate the value of kinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating uterine endometrioid adenocarcinoma (EAC) from adenocarcinoma of cervix (AdC). METHODS Seventy-five newly diagnosed patients with distinctive pathology underwent DCE-MRI. Observers independently calculated the tumor diameters and DCE-MRI parameters using both population and individual-based arterial input function (AIF). Inter-observer consistency was evaluated, and a comparative analysis between EAC (n = 47) and AdC (n = 28) was performed. Regression analysis was used to select parameters that best distinguished EAC from AdC, and to generate predictive models. Receiver operating characteristic curve (ROC) was applied to calculate the diagnostic efficiency of single parameter and the predictive models. RESULTS Inter-observer consistency was excellent (intra-class correlation [ICC] = 0.902-0.981), especially when calculated via population AIF with relatively higher ICC and smaller SD on Bland-Altman plot. Tumor diameters were not correlated with tumor types. All the DCE-MRI parameters were lower in EAC compared to AdC, except Kep by population AIF and TTP by both sets of AIFs. The statistical parameters were Ve, Maxslop, and Maxconc by population AIF, and Maxslop and Ktrans by individual AIF included in the predictive models, respectively. The two predictive models with combined parameters showed improved diagnostic efficiency in differentiating these two diseases compared with a single parameter. CONCLUSION DCE-MRI can quantitatively evaluate the perfusion difference between EAC and AdC, thus improving the identification of uterine adenocarcinoma with uncertain biopsy pathology.
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Affiliation(s)
- Meng Lin
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No 17, Panjiayuannanli, Chaoyang District, Beijing, 100021, PR China
| | - Qi Zhang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No 17, Panjiayuannanli, Chaoyang District, Beijing, 100021, PR China
| | - Yan Song
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No 17, Panjiayuannanli, Chaoyang District, Beijing, 100021, PR China
| | - Xiaoduo Yu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No 17, Panjiayuannanli, Chaoyang District, Beijing, 100021, PR China.
| | - Han Ouyang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No 17, Panjiayuannanli, Chaoyang District, Beijing, 100021, PR China
| | - Lizhi Xie
- MR Research China, GE Healthcare, No.1 Yongchang North Road, Beijing Economic-Technological Development Area, Beijing, 100176, PR China
| | - Yuqing Shang
- Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, CT, CT06510, USA
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Mohamed ASR, He R, Ding Y, Wang J, Fahim J, Elgohari B, Elhalawani H, Kim AD, Ahmed H, Garcia JA, Johnson JM, Stafford RJ, Bankson JA, Chambers MS, Sandulache VC, Fuller CD, Lai SY. Quantitative Dynamic Contrast-Enhanced MRI Identifies Radiation-Induced Vascular Damage in Patients With Advanced Osteoradionecrosis: Results of a Prospective Study. Int J Radiat Oncol Biol Phys 2020; 108:1319-1328. [PMID: 32712257 DOI: 10.1016/j.ijrobp.2020.07.029] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 06/20/2020] [Accepted: 07/15/2020] [Indexed: 11/17/2022]
Abstract
PURPOSE We aim to characterize the quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) parameters associated with advanced mandibular osteoradionecrosis (ORN) compared with the contralateral normal mandible. METHODS AND MATERIALS Patients with a diagnosis of advanced ORN after curative-intent radiation treatment of head and neck cancer were prospectively enrolled after institutional review board approval and study-specific informed consent were obtained. Quantitative maps generated with the Tofts and extended Tofts pharmacokinetic models were used for analysis. Manual segmentation of advanced ORN 3-dimensional volume was done using anatomic sequences to create ORN volumes of interest (VOIs). Subsequently, normal mandibular VOIs were segmented on the contralateral healthy mandible of similar volume and anatomic location to create control VOIs. Finally, anatomic sequences were coregistered to DCE sequences, and contours were propagated to the respective parameter maps. RESULTS Thirty patients were included. The median time to ORN diagnosis after completion of IMRT was 38 months (range, 6-184 months), whereas median time to ORN progression to advanced grade after initial diagnosis was 5.6 months (range, 0-128 months). There were statistically significant higher Ktrans and Ve in ORN-VOIs compared with controls (0.23 vs 0.07 min-1, and 0.34 vs 0.15; P < .0001 for both). The average relative increase of Ktrans in ORN-VOIs was 3.2-fold higher than healthy mandibular control VOIs. Moreover, the corresponding rise of Ve in ORN-VOIs was 2.7-fold higher than in the controls. Using combined Ktrans and Ve parameters, 27 patients (90%) had at least a 200% increase of either of the studied parameters in the ORN-VOIs compared with their healthy mandible VOIs. CONCLUSIONS Our results confirm that there is a quantitatively significant higher degree of leakiness in the mandibular vasculature as measured using DCE-MRI parameters of areas with advanced ORN versus healthy mandible.
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Affiliation(s)
- Abdallah S R Mohamed
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Renjie He
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Yao Ding
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Jihong Wang
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Joly Fahim
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Baher Elgohari
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Hesham Elhalawani
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Andrew D Kim
- Department of Head and Neck Surgery, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Hoda Ahmed
- Department of Head and Neck Surgery, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Jose A Garcia
- Department of Head and Neck Surgery, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Jason M Johnson
- Department of Neuroradiology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - R Jason Stafford
- Department of Imaging Physics, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - James A Bankson
- Department of Imaging Physics, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Mark S Chambers
- Department of Head and Neck Surgery, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Vlad C Sandulache
- Department of Otolaryngology, Head and Neck Surgery, Baylor College of Medicine, Houston, Texas
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas
| | - Stephen Y Lai
- Department of Radiation Oncology, The University of Texas, MD Anderson Cancer Center, Houston, Texas; Department of Head and Neck Surgery, The University of Texas, MD Anderson Cancer Center, Houston, Texas.
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26
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Seith F, Pohmann R, Schwartz M, Küstner T, Othman AE, Kolb M, Scheffler K, Nikolaou K, Schick F, Martirosian P. Imaging Pulmonary Blood Flow Using Pseudocontinuous Arterial Spin Labeling (PCASL) With Balanced Steady-State Free-Precession (bSSFP) Readout at 1.5T. J Magn Reson Imaging 2020; 52:1767-1782. [PMID: 32627293 DOI: 10.1002/jmri.27276] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 06/13/2020] [Accepted: 06/15/2020] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Quantitative assessment of pulmonary blood flow and visualization of its temporal and spatial distribution without contrast media is of clinical significance. PURPOSE To assess the potential of electrocardiogram (ECG)-triggered pseudocontinuous arterial spin labeling (PCASL) imaging with balanced steady-state free-precession (bSSFP) readout to measure lung perfusion under free-breathing (FB) conditions and to study temporal and spatial characteristics of pulmonary blood flow. STUDY TYPE Prospective, observational. SUBJECTS Fourteen volunteers; three patients with pulmonary embolism. FIELD STRENGTH/SEQUENCES 1.5T, PCASL-bSSFP. ASSESSMENT The pulmonary trunk was labeled during systole. The following examinations were performed: 1) FB and timed breath-hold (TBH) examinations with a postlabeling delay (PLD) of 1000 msec, and 2) TBH examinations with multiple PLDs (100-1500 msec). Scan-rescan measurements were performed in four volunteers and one patient. Images were registered and the perfusion was evaluated in large vessels, small vessels, and parenchyma. Mean structural similarity indices (MSSIM) was computed and time-to-peak (TTP) of parenchymal perfusion in multiple PLDs was evaluated. Image quality reading was performed with three independent blinded readers. STATISTICAL TESTS Wilcoxon test to compare MSSIM, perfusion, and Likert scores. Spearman's correlation to correlate TTP and cardiac cycle duration. The repeatability coefficient (RC) and within-subject coefficient of variation (wCV) for scan-rescan measurements. Intraclass correlation coefficient (ICC) for interreader agreement. RESULTS Image registration resulted in a significant (P < 0.05) increase of MSSIM. FB perfusion values were 6% higher than TBH (3.28 ± 1.09 vs. 3.10 ± 0.99 mL/min/mL). TTP was highly correlated with individuals' cardiac cycle duration (Spearman = 0.89, P < 0.001). RC and wCV were better for TBH than FB (0.13-0.19 vs. 0.47-1.54 mL/min/mL; 6-7 vs. 19-60%). Image quality was rated very good, with ICCs 0.71-0.89. DATA CONCLUSION ECG-triggered PCASL-bSSFP imaging of the lung at 1.5T can provide very good image quality and quantitative perfusion maps even under FB. The course of labeled blood through the lung shows a strong dependence on the individuals' cardiac cycle duration. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1767-1782.
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Affiliation(s)
- Ferdinand Seith
- Diagnostic and Interventional Radiology, University Department of Radiology, University Hospital of Tuebingen, Tuebingen, Germany
| | - Rolf Pohmann
- High-Field MR Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
| | - Martin Schwartz
- Section on Experimental Radiology, Diagnostic and Interventional Radiology, University Department of Radiology, University Hospital of Tuebingen, Tuebingen, Germany.,Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany
| | - Thomas Küstner
- Section on Experimental Radiology, Diagnostic and Interventional Radiology, University Department of Radiology, University Hospital of Tuebingen, Tuebingen, Germany.,Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany
| | - Ahmed E Othman
- Diagnostic and Interventional Radiology, University Department of Radiology, University Hospital of Tuebingen, Tuebingen, Germany
| | - Manuel Kolb
- Diagnostic and Interventional Radiology, University Department of Radiology, University Hospital of Tuebingen, Tuebingen, Germany
| | - Klaus Scheffler
- High-Field MR Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Department for Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany
| | - Konstantin Nikolaou
- Diagnostic and Interventional Radiology, University Department of Radiology, University Hospital of Tuebingen, Tuebingen, Germany
| | - Fritz Schick
- Section on Experimental Radiology, Diagnostic and Interventional Radiology, University Department of Radiology, University Hospital of Tuebingen, Tuebingen, Germany
| | - Petros Martirosian
- Section on Experimental Radiology, Diagnostic and Interventional Radiology, University Department of Radiology, University Hospital of Tuebingen, Tuebingen, Germany
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27
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Syed AK, Whisenant JG, Barnes SL, Sorace AG, Yankeelov TE. Multiparametric Analysis of Longitudinal Quantitative MRI data to Identify Distinct Tumor Habitats in Preclinical Models of Breast Cancer. Cancers (Basel) 2020; 12:cancers12061682. [PMID: 32599906 PMCID: PMC7352623 DOI: 10.3390/cancers12061682] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 06/20/2020] [Accepted: 06/22/2020] [Indexed: 12/11/2022] Open
Abstract
This study identifies physiological tumor habitats from quantitative magnetic resonance imaging (MRI) data and evaluates their alterations in response to therapy. Two models of breast cancer (BT-474 and MDA-MB-231) were imaged longitudinally with diffusion-weighted MRI and dynamic contrast-enhanced MRI to quantify tumor cellularity and vascularity, respectively, during treatment with trastuzumab or albumin-bound paclitaxel. Tumors were stained for anti-CD31, anti-Ki-67, and H&E. Imaging and histology data were clustered to identify tumor habitats and percent tumor volume (MRI) or area (histology) of each habitat was quantified. Histological habitats were correlated with MRI habitats. Clustering of both the MRI and histology data yielded three clusters: high-vascularity high-cellularity (HV-HC), low-vascularity high-cellularity (LV-HC), and low-vascularity low-cellularity (LV-LC). At day 4, BT-474 tumors treated with trastuzumab showed a decrease in LV-HC (p = 0.03) and increase in HV-HC (p = 0.03) percent tumor volume compared to control. MDA-MB-231 tumors treated with low-dose albumin-bound paclitaxel showed a longitudinal decrease in LV-HC percent tumor volume at day 3 (p = 0.01). Positive correlations were found between histological and imaging-derived habitats: HV-HC (BT-474: p = 0.03), LV-HC (MDA-MB-231: p = 0.04), LV-LC (BT-474: p = 0.04; MDA-MB-231: p < 0.01). Physiologically distinct tumor habitats associated with therapeutic response were identified with MRI and histology data in preclinical models of breast cancer.
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Affiliation(s)
- Anum K Syed
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA
| | - Jennifer G Whisenant
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Stephanie L Barnes
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Anna G Sorace
- Department of Biomedical Engineering, The University of Alabama at Birmingham, Birmingham, AL 35294, USA
- Department of Radiology, The University of Alabama at Birmingham, Birmingham, AL 35294, USA
- O'Neal Comprehensive Cancer Center, The University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Thomas E Yankeelov
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA
- Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Diagnostic Medicine, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Oncology, The University of Texas at Austin, Austin, TX 78712, USA
- Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA
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28
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Savaikar MA, Whitehead T, Roy S, Strong L, Fettig N, Prmeau T, Luo J, Li S, Wahl RL, Shoghi KI. Preclinical PERCIST and 25% of SUV max Threshold: Precision Imaging of Response to Therapy in Co-clinical 18F-FDG PET Imaging of Triple-Negative Breast Cancer Patient-Derived Tumor Xenografts. J Nucl Med 2020; 61:842-849. [PMID: 31757841 PMCID: PMC7262224 DOI: 10.2967/jnumed.119.234286] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Accepted: 10/30/2019] [Indexed: 11/16/2022] Open
Abstract
Numerous recent works highlight the limited utility of established tumor cell lines in recapitulating the heterogeneity of tumors in patients. More realistic preclinical cancer models are thought to be provided by transplantable, patient-derived xenografts (PDXs). The inter- and intratumor heterogeneity of PDXs, however, presents several challenges in developing optimal quantitative pipelines to assess response to therapy. The objective of this work was to develop and optimize image metrics for 18F-FDG PET to assess response to combination docetaxel and carboplatin therapy in a co-clinical trial involving triple-negative breast cancer PDXs. We characterized the reproducibility of standardized uptake value (SUV) metrics to assess response to therapy, and we optimized a preclinical PERCIST paradigm to complement clinical standards. Considerations in this effort included variability in tumor growth rate and tumor size, solid tumors versus tumor heterogeneity and a necrotic phenotype, and optimal selection of tumor slices versus whole tumor. Methods: A test-retest protocol was implemented to optimize the reproducibility of 18F-FDG PET SUV thresholds, SUVpeak metrics, and preclinical PERCIST parameters. In assessing response to therapy, 18F-FDG PET imaging was performed at baseline and 4 d after therapy. The reproducibility, accuracy, variability, and performance of imaging metrics to assess response to therapy were determined. We defined an index called the Quantitative Response Assessment Score to integrate parameters of prediction and precision and thus aid in selecting the optimal image metric to assess response to therapy. Results: Our data suggest that a threshold of 25% of SUVmax (SUV25) was highly reproducible (<9% variability). The concordance and reproducibility of preclinical PERCIST were maximized at α = 0.7 and β = 2.8 and exhibited a high correlation with SUV25 measures of tumor uptake, which in turn correlated with the SUV of metabolic tumor. Conclusion: The Quantitative Response Assessment Score favors SUV25 followed by SUVpeak for a sphere with a volume of 14 mm3 (SUVP14) as optimal metrics of response to therapy. Additional studies are warranted to fully characterize the utility of SUV25 and preclinical PERCIST SUVP14 as image metrics for response to therapy across a wide range of therapeutic regimens and PDX models.
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Affiliation(s)
- Madhusudan A Savaikar
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Timothy Whitehead
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Sudipta Roy
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Lori Strong
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Nicole Fettig
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Tina Prmeau
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Jingqin Luo
- Department of Surgery, Washington University School of Medicine, St. Louis, Missouri; and
| | - Shunqiang Li
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri
| | - Richard L Wahl
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Kooresh I Shoghi
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri
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29
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Koopman T, Martens RM, Lavini C, Yaqub M, Castelijns JA, Boellaard R, Marcus JT. Repeatability of arterial input functions and kinetic parameters in muscle obtained by dynamic contrast enhanced MR imaging of the head and neck. Magn Reson Imaging 2020; 68:1-8. [DOI: 10.1016/j.mri.2020.01.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 12/23/2019] [Accepted: 01/19/2020] [Indexed: 12/13/2022]
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30
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Dikaios N. Stochastic Gradient Langevin dynamics for joint parameterization of tracer kinetic models, input functions, and T1 relaxation-times from undersampled k-space DCE-MRI. Med Image Anal 2020; 62:101690. [DOI: 10.1016/j.media.2020.101690] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 02/16/2020] [Accepted: 03/13/2020] [Indexed: 02/04/2023]
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31
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Paudyal R, Konar AS, Obuchowski NA, Hatzoglou V, Chenevert TL, Malyarenko DI, Swanson SD, LoCastro E, Jambawalikar S, Liu MZ, Schwartz LH, Tuttle RM, Lee N, Shukla-Dave A. Repeatability of Quantitative Diffusion-Weighted Imaging Metrics in Phantoms, Head-and-Neck and Thyroid Cancers: Preliminary Findings. ACTA ACUST UNITED AC 2020; 5:15-25. [PMID: 30854438 PMCID: PMC6403035 DOI: 10.18383/j.tom.2018.00044] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The aim of this study was to establish the repeatability measures of quantitative Gaussian and non-Gaussian diffusion metrics using diffusion-weighted imaging (DWI) data from phantoms and patients with head-and-neck and papillary thyroid cancers. The Quantitative Imaging Biomarker Alliance (QIBA) DWI phantom and a novel isotropic diffusion kurtosis imaging phantom were scanned at 3 different sites, on 1.5T and 3T magnetic resonance imaging systems, using standardized multiple b-value DWI acquisition protocol. In the clinical component of this study, a total of 60 multiple b-value DWI data sets were analyzed for test–retest, obtained from 14 patients (9 head-and-neck squamous cell carcinoma and 5 papillary thyroid cancers). Repeatability of quantitative DWI measurements was assessed by within-subject coefficient of variation (wCV%) and Bland–Altman analysis. In isotropic diffusion kurtosis imaging phantom vial with 2% ceteryl alcohol and behentrimonium chloride solution, the mean apparent diffusion (Dapp × 10−3 mm2/s) and kurtosis (Kapp, unitless) coefficient values were 1.02 and 1.68 respectively, capturing in vivo tumor cellularity and tissue microstructure. For the same vial, Dapp and Kapp mean wCVs (%) were ≤1.41% and ≤0.43% for 1.5T and 3T across 3 sites. For pretreatment head-and-neck squamous cell carcinoma, apparent diffusion coefficient, D, D*, K, and f mean wCVs (%) were 2.38%, 3.55%, 3.88%, 8.0%, and 9.92%, respectively; wCVs exhibited a higher trend for papillary thyroid cancers. Knowledge of technical precision and bias of quantitative imaging metrics enables investigators to properly design and power clinical trials and better discern between measurement variability versus biological change.
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Affiliation(s)
- Ramesh Paudyal
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Nancy A Obuchowski
- Department of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, OH
| | - Vaios Hatzoglou
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | | | - Scott D Swanson
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | - Eve LoCastro
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Sachin Jambawalikar
- Department of Radiology, Columbia University Irving Medical Center, and New York Presbyterian Hospital, New York, NY
| | - Michael Z Liu
- Department of Radiology, Columbia University Irving Medical Center, and New York Presbyterian Hospital, New York, NY
| | - Lawrence H Schwartz
- Department of Radiology, Columbia University Irving Medical Center, and New York Presbyterian Hospital, New York, NY
| | | | - Nancy Lee
- Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Amita Shukla-Dave
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
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32
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A Comparative Study of Two-Compartment Exchange Models for Dynamic Contrast-Enhanced MRI in Characterizing Uterine Cervical Carcinoma. CONTRAST MEDIA & MOLECULAR IMAGING 2019; 2019:3168416. [PMID: 31897081 PMCID: PMC6925719 DOI: 10.1155/2019/3168416] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 10/14/2019] [Indexed: 12/13/2022]
Abstract
A variety of tracer kinetic methods have been employed to assess tumor angiogenesis. The Standard two-Compartment model (SC) used in cervix carcinoma was less frequent, and Adiabatic Approximation to the Tissue Homogeneity (AATH) and Distributed Parameter (DP) model are lacking. This study compares two-compartment exchange models (2CXM) (AATH, SC, and DP) for determining dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters in cervical cancer, with the aim of investigating the potential of various parameters derived from 2CXM for tumor diagnosis and exploring the possible relationship between these parameters in patients with cervix cancer. Parameters (tissue blood flow, Fp; tissue blood volume, Vp; interstitial volume, Ve; and vascular permeability, PS) for regions of interest (ROI) of cervix lesions and normal cervix tissue were estimated by AATH, SC, and DP models in 36 patients with cervix cancer and 17 healthy subjects. All parameters showed significant differences between lesions and normal tissue with a P value less than 0.05, except for PS from the AATH model, Fp from the SC model, and Vp from the DP model. Parameter Ve from the AATH model had the largest AUC (r = 0.85). Parameters Fp and Vp from SC and DP models and Ve and PS from AATH and DP models were highly correlated, respectively, (r > 0.8) in cervix lesions. Cervix cancer was found to have a very unusual microcirculation pattern, with over-growth of cancer cells but without evident development of angiogenesis. Ve has the best performance in identifying cervix cancer. Most physiological parameters derived from AATH, SC, and DP models are linearly correlated in cervix cancer.
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33
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Bandak E, Boesen M, Bliddal H, Riis RGC, Nielsen SM, Klokker L, Bartholdy C, Nybing JD, Henriksen M. Exercise-induced pain changes associate with changes in muscle perfusion in knee osteoarthritis: exploratory outcome analyses of a randomised controlled trial. BMC Musculoskelet Disord 2019; 20:491. [PMID: 31656173 PMCID: PMC6815355 DOI: 10.1186/s12891-019-2858-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Accepted: 09/30/2019] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Exercise therapy is recommended for knee osteoarthritis (OA), but the underlying mechanisms of pain relief are not fully understood. The purpose of this study was to explore the effects of exercise on muscle perfusion assessed by dynamic contrast enhanced MRI (DCE-MRI) and its association with changes in pain in patients with knee OA. METHODS Exploratory outcome analyses of a randomised controlled study with per-protocol analyses ( ClinicalTrials.gov : NCT01545258) performed at an outpatient clinic at a public hospital in Denmark. We compared 12 weeks of supervised exercise therapy 3 times per week (ET) with a no attention control group (CG). Analyses of covariance (ANCOVA) were used to assess group mean differences in changes from baseline to week 12 in knee muscle perfusion quantified by DCE-MRI, patient-reported pain and function using the Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire, knee extensor and flexor muscle strength tests, and the six-minute walking test (6MWT). Spearman's correlation coefficients were used to determine the correlation between changes in DCE-MRI variables, KOOS, muscle strength, and 6MWT. The potential effect mediation of the DCE-MRI perfusion variables was investigated in a post-hoc mediation analysis. RESULTS Of 60 participants randomised with knee osteoarthritis, 33 (ET, n = 16, CG, n = 17) adhered to the protocol and had complete DCE-MRI data. At follow-up, there were significant group differences in muscle perfusion changes and clinically relevant group differences in KOOS pain changes (10.7, 95% CI 3.3 to 18.1, P = 0.006) in favor of ET. There were no significant between-group differences on muscle strength and function. The changes in pain and muscle perfusion were significantly correlated (highest Spearman's rho = 0.42, P = 0.014). The mediation analyses were generally not statistically significant. CONCLUSION The pain-reducing effects of a 12-week exercise program are associated with changes in knee muscle perfusion quantified by DCE-MRI in individuals with knee OA, but whether the effects are mediated by muscle perfusion changes remains unclear. TRIAL REGISTRATION ClinicalTrials.gov: NCT01545258 , first posted March 6, 2012.
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Affiliation(s)
- Elisabeth Bandak
- The Parker Institute, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.
| | - Mikael Boesen
- The Parker Institute, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.,Department of Radiology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Henning Bliddal
- The Parker Institute, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Robert G C Riis
- The Parker Institute, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.,Department of Radiology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Sabrina Mai Nielsen
- The Parker Institute, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.,Research Unit of Rheumatology, Department of Clinical Research, University of Southern Denmark, Odense University Hospital, Odense, Denmark
| | - Louise Klokker
- The Parker Institute, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Cecilie Bartholdy
- The Parker Institute, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.,Department of physical and occupational therapy, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Janus Damm Nybing
- Department of Radiology, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Marius Henriksen
- The Parker Institute, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark.,Department of physical and occupational therapy, Copenhagen University Hospital, Bispebjerg and Frederiksberg, Copenhagen, Denmark
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Waninger JJ, Green MD, Cheze Le Rest C, Rosen B, El Naqa I. Integrating radiomics into clinical trial design. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF RADIOPHARMACEUTICAL CHEMISTRY AND BIOLOGY 2019; 63:339-346. [PMID: 31527581 DOI: 10.23736/s1824-4785.19.03217-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
In radiomics, quantitative features that describe phenotypic tumor characteristics are derived from radiographic images. Because radiomics generates information from routine medical images, it is a powerful way to non-invasively examine the spatial and temporal heterogeneity of disease, and thus has potential to significantly impact clinical trial design, execution, and ultimately patient care. The aim of this review article is to discuss how radiomics may address some of the current challenges in clinical randomized control trials, and the difficulties of integrating robust and repeatable radiomics analysis into trial design. Each step of the radiomics process, including image acquisition and reconstruction, image segmentation, feature extraction, and computational analysis, requires extensive standardization in order to be successfully incorporated into clinical trials and inform clinical decision making. By addressing these challenges, the potential of radiomics may be realized.
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Affiliation(s)
- Jessica J Waninger
- Department of Medical Education, University of Michigan School of Medicine, Ann Arbor, MI, USA.,Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Michael D Green
- Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor, MI, USA.,University of Michigan Rogel Cancer Center, University of Michigan, Ann Arbor, MI, USA
| | | | - Benjamin Rosen
- Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor, MI, USA
| | - Issam El Naqa
- Department of Radiation Oncology, University of Michigan School of Medicine, Ann Arbor, MI, USA -
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Ahmed Z, Levesque IR. Pharmacokinetic modeling of dynamic contrast-enhanced MRI using a reference region and input function tail. Magn Reson Med 2019; 83:286-298. [PMID: 31393033 DOI: 10.1002/mrm.27913] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 06/18/2019] [Accepted: 06/18/2019] [Indexed: 12/20/2022]
Abstract
PURPOSE Quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI) requires an arterial input function (AIF) which is difficult to measure. We propose the reference region and input function tail (RRIFT) approach which uses a reference tissue and the washout portion of the AIF. METHODS RRIFT was evaluated in simulations with 100 parameter combinations at various temporal resolutions (5-30 s) and noise levels (σ = 0.01-0.05 mM). RRIFT was compared against the extended Tofts model (ETM) in 8 studies from patients with glioblastoma multiforme. Two versions of RRIFT were evaluated: one using measured patient-specific AIF tails, and another assuming a literature-based AIF tail. RESULTS RRIFT estimated the transfer constant K trans and interstitial volume v e with median errors within 20% across all simulations. RRIFT was more accurate and precise than the ETM at temporal resolutions slower than 10 s. The percentage error of K trans had a median and interquartile range of -9 ± 45% with the ETM and -2 ± 17% with RRIFT at a temporal resolution of 30 s under noiseless conditions. RRIFT was in excellent agreement with the ETM in vivo, with concordance correlation coefficients (CCC) of 0.95 for K trans , 0.96 for v e , and 0.73 for the plasma volume v p using a measured AIF tail. With the literature-based AIF tail, the CCC was 0.89 for K trans , 0.93 for v e and 0.78 for v p . CONCLUSIONS Quantitative DCE-MRI analysis using the input function tail and a reference tissue yields absolute kinetic parameters with the RRIFT method. This approach was viable in simulation and in vivo for temporal resolutions as low as 30 s.
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Affiliation(s)
- Zaki Ahmed
- Medical Physics Unit, McGill University, Montreal, Canada.,Department of Physics, McGill University, Montreal, Canada
| | - Ives R Levesque
- Medical Physics Unit, McGill University, Montreal, Canada.,Department of Physics, McGill University, Montreal, Canada.,Gerald Bronfman Department of Oncology, McGill University, Montreal, Canada.,Cancer Research Program, Research Institute of the McGill University Health Centre, Montreal, Canada
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36
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Lee JY, Cheng KL, Lee JH, Choi YJ, Kim HW, Sung YS, Chung SR, Ryu KH, Chung MS, Kim SY, Lee SW, Baek JH. Detection of Local Recurrence in Patients with Head and Neck Squamous Cell Carcinoma Using Voxel-Based Color Maps of Initial and Final Area under the Curve Values Derived from DCE-MRI. AJNR Am J Neuroradiol 2019; 40:1392-1401. [PMID: 31320461 DOI: 10.3174/ajnr.a6130] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Accepted: 06/17/2019] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Early detection of local recurrence is important to increase the chance of cure because local recurrence is the main cause of treatment failure in head and neck squamous cell carcinoma. We evaluated the added value of voxel-based color maps of dynamic contrast-enhanced MR imaging compared with conventional MR imaging alone for detecting local recurrence of head and neck squamous cell carcinoma. MATERIALS AND METHODS We retrospectively enrolled 63 consecutive patients with head and neck squamous cell carcinoma after definitive treatment and posttreatment surveillance MR imaging studies that demonstrated focal enhancement at the primary site. Three independent readers assessed conventional MR imaging and a pair of color maps of initial and final 90-second time-signal intensity areas under the curve from dynamic contrast-enhanced MR imaging. The sensitivities, specificities, and accuracies of both conventional MR imaging alone and combined interpretation of conventional and dynamic contrast-enhanced MR imaging were assessed using the clinicopathologic diagnosis as the criterion standard. κ statistics were used to evaluate interreader agreement. RESULTS There were 28 patients with subsequently documented local recurrence and 35 with posttreatment change. Adding dynamic contrast-enhanced MR imaging to conventional MR imaging significantly increased the diagnostic accuracies for detecting local recurrence (48%-54% versus 87%-91%; P < .05), with excellent interreader agreement (κ = 0.8; 95% CI, 0.67-0.92 to κ = 0.81; 95% CI, 0.69-0.93). By all 3 readers, the specificities were also significantly improved by adding dynamic contrast-enhanced MR imaging to conventional MR imaging (22%-43% versus 87%-91%; P < .001) without sacrificing the sensitivities (68%-82% versus 86%-89%; P > .05). CONCLUSIONS Adding voxel-based color maps of initial and final 90-second time-signal intensity areas under the curve from dynamic contrast-enhanced MR imaging to conventional MR imaging increases the diagnostic accuracy to detect local recurrence in head and neck squamous cell carcinoma by improving the specificity without sacrificing the sensitivity.
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Affiliation(s)
- J Y Lee
- From the Department of Radiology (J.Y.L.), Eulji Medical Center, Eulji University College of Medicine, Seoul, Korea
- Department of Radiology and Research Institute of Radiology (J.Y.L., K.L.C., J.H.L., Y.J.C., H.W.K., Y.S.S., S.R.C., J.H.B.)
| | - K L Cheng
- Department of Medical Imaging (K.L.C.)
- School of Medical Imaging and Radiological Sciences (K.L.C.), Chung Shan Medical University, Taichung, Taiwan
- Department of Veterinary Medicine (K.L.C.), National Chung Hsing University, Taichung, Taiwan
- Department of Radiology and Research Institute of Radiology (J.Y.L., K.L.C., J.H.L., Y.J.C., H.W.K., Y.S.S., S.R.C., J.H.B.)
| | - J H Lee
- Department of Radiology and Research Institute of Radiology (J.Y.L., K.L.C., J.H.L., Y.J.C., H.W.K., Y.S.S., S.R.C., J.H.B.)
| | - Y J Choi
- Department of Radiology and Research Institute of Radiology (J.Y.L., K.L.C., J.H.L., Y.J.C., H.W.K., Y.S.S., S.R.C., J.H.B.)
| | - H W Kim
- Department of Radiology and Research Institute of Radiology (J.Y.L., K.L.C., J.H.L., Y.J.C., H.W.K., Y.S.S., S.R.C., J.H.B.)
| | - Y S Sung
- Department of Radiology and Research Institute of Radiology (J.Y.L., K.L.C., J.H.L., Y.J.C., H.W.K., Y.S.S., S.R.C., J.H.B.)
| | - S R Chung
- Department of Radiology and Research Institute of Radiology (J.Y.L., K.L.C., J.H.L., Y.J.C., H.W.K., Y.S.S., S.R.C., J.H.B.)
| | - K H Ryu
- Department of Radiology (K.H.R.), Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Korea
| | - M S Chung
- Department of Radiology (M.S.C.), Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea
| | - S Y Kim
- Departments of Otolaryngology (S.Y.K.)
| | - S-W Lee
- Radiation Oncology (S.-W.L), University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - J H Baek
- Department of Radiology and Research Institute of Radiology (J.Y.L., K.L.C., J.H.L., Y.J.C., H.W.K., Y.S.S., S.R.C., J.H.B.)
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Pepin K, Grimm R, Kargar S, Howe BM, Fritchie K, Frick M, Wenger D, Okuno S, Ehman R, McGee K, James S, Laack N, Herman M, Pafundi D. Soft Tissue Sarcoma Stiffness and Perfusion Evaluation by MRE and DCE-MRI for Radiation Therapy Response Assessment: A Technical Feasibility Study. Biomed Phys Eng Express 2019; 5:10.1088/2057-1976/ab2175. [PMID: 32110433 PMCID: PMC7045581 DOI: 10.1088/2057-1976/ab2175] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Soft tissue sarcomas are a rare and heterogeneous group of malignancies that present significant diagnostic and therapeutic challenges. Patient stratification based on tumor aggressiveness and early therapeutic response based on quantitative imaging may improve prediction of treatment response and the evaluation of new treatment strategies in clinical trials. The purpose of this pilot study was to determine the technical feasibility of magnetic resonance elastography (MRE) and dynamic contrast-enhanced (DCE) MRI for the evaluation of sarcoma stiffness and perfusion in 9 patients with histologically confirmed sarcoma. Additionally, we assessed the feasibility of utilizing MRE and DCE-MRI for the early evaluation of response to radiation therapy in 4 patients to determine the utility of further evaluation in a larger cohort study. Tumor size, stiffness, and perfusion parameters all decreased from baseline at the time of the pre-surgery or follow-up MRI, and results were compared to pathology or conventional imaging. MRE and DCE-MRI may be useful for the quantitative evaluation of tumor stiffness and perfusion, and therapy response assessment in soft tissue sarcomas.
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Affiliation(s)
- Kay Pepin
- Department of Radiation Oncology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
| | - Roger Grimm
- Department of Radiology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
| | - Soudabeh Kargar
- Mayo Clinic Graduate School of Biomedical Sciences, 200 1 Street SW, Rochester, MN 55905
| | - B Matthew Howe
- Department of Radiology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
| | - Karen Fritchie
- Department of Pathology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
| | - Matthew Frick
- Department of Radiology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
| | - Doris Wenger
- Department of Radiology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
| | - Scott Okuno
- Department of Oncology, Mayo Clinic, 200 1 St SW, Rochester MN, 55905
| | - Richard Ehman
- Department of Radiology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
| | - Kiaran McGee
- Department of Radiology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
| | - Sarah James
- Department of Radiation Oncology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
| | - Nadia Laack
- Department of Radiation Oncology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
| | - Michael Herman
- Department of Radiation Oncology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
| | - Deanna Pafundi
- Department of Radiation Oncology, Mayo Clinic, 200 1 Street SW, Rochester, MN 55905
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Modeling Gadoxetate Liver Uptake and Efflux Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging Enables Preclinical Quantification of Transporter Drug-Drug Interactions. Invest Radiol 2019; 53:563-570. [PMID: 29771727 DOI: 10.1097/rli.0000000000000480] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVES The aim of this study was to model the in vivo transporter-mediated uptake and efflux of the hepatobiliary contrast agent gadoxetate in the liver. The efficacy of the proposed technique was assessed for its ability to provide quantitative insights into drug-drug interactions (DDIs), using rifampicin as inhibitor. MATERIALS AND METHODS Three groups of C57 mice were scanned twice with a dynamic gadoxetate-enhanced magnetic resonance imaging protocol, using a 3-dimensional spoiled gradient-echo sequence for approximately 72 minutes. Before the second magnetic resonance imaging session, 2 of the groups received a rifampicin dose of 20 (n = 7) or 40 (n = 7) mg/kg, respectively. Data from regions of interest in the liver were analyzed using 2 simplifications of a 2-compartment uptake and efflux model to provide estimates for the gadoxetate uptake rate (ki) into the hepatocytes and its efflux rate (kef) into the bile. Both models were assessed for goodness-of-fit in the group without rifampicin (n = 9), and the appropriate model was selected for assessing the ability to monitor DDIs in vivo. RESULTS Seven of 9 mice from the group without rifampicin were assessed for model implementation and reproducibility. A simple 3 parameter model (ki, kef, and extracellular space, vecs) adequately described the observed liver concentration time series with mean ki = 0.47 ± 0.11 min and mean kef = 0.039 ± 0.016 min. Visually, the area under the liver concentration time profile was reduced for the groups receiving rifampicin. Furthermore, tracer kinetic modeling demonstrated a significant dose-dependent decrease in the uptake (5.9- and 17.3-fold decrease for 20 mg/kg and 40 mg/kg, respectively) and efflux rates (2.2- and 7.9-fold decrease) compared with the first scan for each group. CONCLUSIONS This study presents the first in vivo implementation of a 2-compartment uptake and efflux model to monitor DDIs at the transporter-protein level, using the clinically relevant organic anion transporting polypeptide inhibitor rifampicin. The technique has the potential to be a novel alternative to other methods, allowing real-time changes in transporter DDIs to be measured directly in vivo.
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Hahn AD, Kammerman J, Evans M, Zha W, Cadman RV, Meyer K, Sandbo N, Fain SB. Repeatability of regional pulmonary functional metrics of Hyperpolarized 129 Xe dissolved-phase MRI. J Magn Reson Imaging 2019; 50:1182-1190. [PMID: 30968993 DOI: 10.1002/jmri.26745] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 03/15/2019] [Accepted: 03/15/2019] [Indexed: 11/08/2022] Open
Abstract
BACKGROUND MRI of hyperpolarized 129 Xenon (HP 129 Xe) is increasingly utilized for investigating pulmonary function. The solubility of HP 129 Xe in lung tissue, blood plasma (Barrier), and red blood cells (RBC), with unique chemical shifts, enables spectroscopic imaging of potential imaging biomarkers of gas exchange and microstructural pulmonary physiology. PURPOSE To quantify global average and regional repeatability of Barrier:gas, RBC:gas, and RBC:Barrier ratios derived from dissolved-phase 129 Xe imaging and their dependence on intervisit changes in lung inflation volume. STUDY TYPE Prospective. POPULATION Fourteen healthy volunteers. One subject was unable to complete the study resulting in 13 subjects for analysis (eight female, five male, ages 24-69, 53.8 ± 13.9). FIELD STRENGTH 1.5T. ASSESSMENT Subjects were imaged using a 3D radial 1-point Dixon method to separate Barrier and RBC component signals, at two different timepoints, with ~1 month between visits. RBC:Gas, Barrier:Gas, and RBC:Barrier measures were compared across time and with pulmonary function tests (PFTs). STATISTICAL TESTS Repeatablilty was quantified using Bland-Altman plots, coefficient of repeatability, coefficient of variation (CV), and intraclass correlation coefficients (ICCs). Dependence of imaging measures on PFTs and lung volume was evaluated using Spearman and Pearson correlation coefficients, respectively. Statistical significance was determined by F-test for intraclass correlations, and t-test for Spearman correlations and regression. RESULTS Mean RBC:Gas, Barrier:Gas, and RBC:Barrier had CVs of 19.2%, 20.0%, and 11.5%, respectively, and had significant ICCs, equal to 0.78, 0.79, and 0.92, respectively. Intervisit differences in RBC:Barrier were significantly correlated with intervisit differences in DLCO (r = 0.93, P = 0.007). Significant correlations with intervisit lung volume differences and intervisit differences in mean RBC:Gas (r = -0.73, P = 0.005) and Barrier:Gas (r = -0.69, P = 0.009) were found. DATA CONCLUSION Three commonly used 129 Xe MRI-based measures of gas-exchange show good repeatability, particularly the Barrier:RBC ratio, which did not depend on lung inflation volume and was strongly associated with intervisit changes in DLCO . LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1182-1190.
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Affiliation(s)
- Andrew D Hahn
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
| | - Jeff Kammerman
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
| | - Michael Evans
- Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, USA
| | - Wei Zha
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
| | - Robert V Cadman
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA
| | - Keith Meyer
- Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA
| | - Nathan Sandbo
- Department of Medicine, University of Wisconsin, Madison, Wisconsin, USA
| | - Sean B Fain
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA.,Department of Biomedical Engineering, University of Wisconsin, Madison, Wisconsin, USA
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Contrast-Enhanced 3-T Perfusion MRI With Quantitative Analysis for the Characterization of Musculoskeletal Tumors: Is It Worth the Trouble? AJR Am J Roentgenol 2018; 211:1092-1098. [DOI: 10.2214/ajr.18.19618] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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41
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Dynamic contrast-enhanced MRI of orbital and anterior visual pathway lesions. Magn Reson Imaging 2018; 51:44-50. [DOI: 10.1016/j.mri.2018.04.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 04/19/2018] [Accepted: 04/26/2018] [Indexed: 01/13/2023]
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Evelhoch JL. In vivo MR in the drug pipeline. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2018; 292:117-128. [PMID: 29716831 DOI: 10.1016/j.jmr.2018.04.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 04/15/2018] [Accepted: 04/23/2018] [Indexed: 06/08/2023]
Abstract
The application of in vivo magnetic resonance (MR) in drug development has several requirements that differ significantly from most applications primarily because the biopharmaceutical industry must develop new safe and effective drugs more quickly and at lower cost in a highly regulated environment. In vivo MR is recognized as a useful method to provide biomarkers for target engagement, treatment response, safety and mechanism of action that can be translated between animal and clinical studies. Thus, it has the potential to help identify drugs that are more likely to be safe and effective earlier in the process of drug development, which may help reduce the time and money required to get new drugs to patients with an unmet medical need. A brief introduction of how novel drugs are discovered and developed, what drives the biopharmaceutical industry's interest in using biomarkers and what it takes to use MR as a biomarker to support drug development, including regulatory concerns, provides context for understanding what makes the application of in vivo MR in drug development different from most others. Exploration of three programs (trebananib, ZD6126 and axitinib) using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in the development of antivascular agents provides insight into how in vivo MR biomarkers impact drug discovery and development and the limitations of biomarkers.
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Affiliation(s)
- Jeffrey L Evelhoch
- Merck & Co., Inc., 770 Sumneytown Pike, WP 42-211, West Point, PA 19486, USA.
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Benz MR, Bongartz G, Froehlich JM, Winkel D, Boll DT, Heye T. Acceleration techniques and their impact on arterial input function sampling: Non-accelerated versus view-sharing and compressed sensing sequences. Eur J Radiol 2018; 104:8-13. [PMID: 29857871 DOI: 10.1016/j.ejrad.2018.04.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 04/20/2018] [Accepted: 04/23/2018] [Indexed: 01/25/2023]
Abstract
PURPOSE The aim was to investigate the variation of the arterial input function (AIF) within and between various DCE MRI sequences. MATERIAL AND METHODS A dynamic flow-phantom and steady signal reference were scanned on a 3T MRI using fast low angle shot (FLASH) 2d, FLASH3d (parallel imaging factor (P) = P0, P2, P4), volumetric interpolated breath-hold examination (VIBE) (P = P0, P3, P2 × 2, P2 × 3, P3 × 2), golden-angle radial sparse parallel imaging (GRASP), and time-resolved imaging with stochastic trajectories (TWIST). Signal over time curves were normalized and quantitatively analyzed by full width half maximum (FWHM) measurements to assess variation within and between sequences. RESULTS The coefficient of variation (CV) for the steady signal reference ranged from 0.07-0.8%. The non-accelerated gradient echo FLASH2d, FLASH3d, and VIBE sequences showed low within sequence variation with 2.1%, 1.0%, and 1.6%. The maximum FWHM CV was 3.2% for parallel imaging acceleration (VIBE P2 × 3), 2.7% for GRASP and 9.1% for TWIST. The FWHM CV between sequences ranged from 8.5-14.4% for most non-accelerated/accelerated gradient echo sequences except 6.2% for FLASH3d P0 and 0.3% for FLASH3d P2; GRASP FWHM CV was 9.9% versus 28% for TWIST. CONCLUSION MRI acceleration techniques vary in reproducibility and quantification of the AIF. Incomplete coverage of the k-space with TWIST as a representative of view-sharing techniques showed the highest variation within sequences and might be less suited for reproducible quantification of the AIF.
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Affiliation(s)
- Matthias R Benz
- Department of Radiology and Nuclear Medicine, University Hospital Basel, Basel, Switzerland.
| | - Georg Bongartz
- Department of Radiology and Nuclear Medicine, University Hospital Basel, Basel, Switzerland
| | | | - David Winkel
- Department of Radiology and Nuclear Medicine, University Hospital Basel, Basel, Switzerland
| | - Daniel T Boll
- Department of Radiology and Nuclear Medicine, University Hospital Basel, Basel, Switzerland
| | - Tobias Heye
- Department of Radiology and Nuclear Medicine, University Hospital Basel, Basel, Switzerland
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Klaassen R, Gurney-Champion OJ, Wilmink JW, Besselink MG, Engelbrecht MRW, Stoker J, Nederveen AJ, van Laarhoven HWM. Repeatability and correlations of dynamic contrast enhanced and T2* MRI in patients with advanced pancreatic ductal adenocarcinoma. Magn Reson Imaging 2018; 50:1-9. [PMID: 29476781 DOI: 10.1016/j.mri.2018.02.005] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 02/15/2018] [Accepted: 02/18/2018] [Indexed: 12/22/2022]
Abstract
BACKGROUND In current oncological practice of pancreatic ductal adenocarcinoma (PDAC), there is a great demand for response predictors and markers for early treatment evaluation. In this study, we investigated the repeatability and the interaction of dynamic contrast enhanced (DCE) and T2* MRI in patients with advanced PDAC to enable for such evaluation using these techniques. MATERIALS & METHODS 15 PDAC patients underwent two DCE, T2* and anatomical 3 T MRI sessions before start of treatment. Parametric maps were calculated for the transfer constant (Ktrans), rate constant (kep), extracellular extravascular space (ve) and perfusion fraction (vp). Quantitative R2* (1/T2*) maps were obtained from the multi-echo T2* images. Differences between normal and cancerous pancreas were determined using a Wilcoxon matched pairs test. Repeatability was obtained using Bland-Altman analysis and relations between DCE and T2*/R2* were observed by Spearman correlation and voxel-wise binned plots of tumor voxels. RESULTS PDAC Ktrans (p = 0.007), kep (p < 0.001), vp (p = 0.035) were lower and ve (p < 0.001) was higher compared to normal pancreas. The coefficient of variation between sessions was 21.8% for Ktrans, 9.9% for kep, 19.3% for ve, 18.2% for vp and 18.7% for R2*. Variation between patients ranged from 20.2% for kep to 43.6% for Ktrans. In the tumor both Ktrans (r = 0.56, p = 0.030) and ve (r = 0.54, p = 0.037) showed a positive correlation with T2*. Voxel wise analysis showed a steep increase in R2* for tumor voxels with lower Ktrans and ve. CONCLUSION We showed good repeatability of DCE and T2* related MRI parameters in advanced PDAC patients. Furthermore, we have illustrated the relation of DCE Ktrans and ve with tissue T2* and R2* indicating substantial value of these parameters for detecting tumor hypoxia in future studies. The results from our study pave the way for further response evaluation studies and patient selection based on DCE and T2* parameters.
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Affiliation(s)
- Remy Klaassen
- Cancer Center Amsterdam, Department of Medical Oncology, Academic Medical Center, Amsterdam, The Netherlands; Cancer Center Amsterdam, LEXOR (Laboratory for Experimental Oncology and Radiobiology), Academic Medical Center, Amsterdam, The Netherlands.
| | - Oliver J Gurney-Champion
- Department of Radiology and Nuclear Medicine, Academic Medical Center, Amsterdam, The Netherlands; Department of Radiation Oncology, Academic Medical Center, Amsterdam, The Netherlands
| | - Johanna W Wilmink
- Cancer Center Amsterdam, Department of Medical Oncology, Academic Medical Center, Amsterdam, The Netherlands
| | - Marc G Besselink
- Department of Surgery, Academic Medical Center, Amsterdam, The Netherlands
| | - Marc R W Engelbrecht
- Department of Radiology and Nuclear Medicine, Academic Medical Center, Amsterdam, The Netherlands
| | - Jaap Stoker
- Department of Radiology and Nuclear Medicine, Academic Medical Center, Amsterdam, The Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Academic Medical Center, Amsterdam, The Netherlands
| | - Hanneke W M van Laarhoven
- Cancer Center Amsterdam, Department of Medical Oncology, Academic Medical Center, Amsterdam, The Netherlands
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Sorace AG, Partridge SC, Li X, Virostko J, Barnes SL, Hippe DS, Huang W, Yankeelov TE. Distinguishing benign and malignant breast tumors: preliminary comparison of kinetic modeling approaches using multi-institutional dynamic contrast-enhanced MRI data from the International Breast MR Consortium 6883 trial. J Med Imaging (Bellingham) 2018; 5:011019. [PMID: 29392160 DOI: 10.1117/1.jmi.5.1.011019] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 12/18/2017] [Indexed: 01/10/2023] Open
Abstract
Comparative preliminary analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data collected in the International Breast MR Consortium 6883 multicenter trial was performed to distinguish benign and malignant breast tumors. Prebiopsy DCE-MRI data from 45 patients with suspicious breast lesions were obtained. Semiquantitative mean signal-enhancement ratio ([Formula: see text]) was calculated for all lesions, and quantitative pharmacokinetic, parameters [Formula: see text], [Formula: see text], and [Formula: see text], were calculated for the subset with available [Formula: see text] maps ([Formula: see text]). Diagnostic performance was estimated for DCE-MRI parameters and compared to standard clinical MRI assessment. Quantitative and semiquantitative metrics discriminated benign and malignant lesions, with receiver operating characteristic area under the curve (AUC) values of 0.71, 0.70, and 0.82 for [Formula: see text], [Formula: see text], and [Formula: see text], respectively ([Formula: see text]). At equal 94% sensitivity, the specificity and positive predictive value of [Formula: see text] (53% and 63%, respectively) and Ktrans (42% and 58%) were higher than clinical MRI assessment (32% and 54%). A multivariable model combining [Formula: see text] and clinical MRI assessment had an AUC value of 0.87. Quantitative pharmacokinetic and semiquantitative analyses of DCE-MRI improves discrimination of benign and malignant breast tumors, with our findings suggesting higher diagnostic accuracy using [Formula: see text]. [Formula: see text] has potential to help reduce unnecessary biopsies resulting from routine breast imaging.
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Affiliation(s)
- Anna G Sorace
- University of Texas at Austin, Department of Diagnostic Medicine, Austin, Texas, United States.,University of Texas at Austin, Livestrong Cancer Institutes, Austin, Texas, United States.,University of Texas at Austin, Department of Biomedical Engineering, Austin, Texas, United States
| | - Savannah C Partridge
- University of Washington, Department of Radiology, Seattle, Washington, United States
| | - Xia Li
- GE Global Research, Niskayuna, New York, United States
| | - Jack Virostko
- University of Texas at Austin, Department of Diagnostic Medicine, Austin, Texas, United States.,University of Texas at Austin, Livestrong Cancer Institutes, Austin, Texas, United States
| | - Stephanie L Barnes
- University of Texas at Austin, Department of Biomedical Engineering, Austin, Texas, United States.,University of Texas at Austin, Institute for Computational and Engineering Sciences, Austin, Texas, United States
| | - Daniel S Hippe
- University of Washington, Department of Radiology, Seattle, Washington, United States
| | - Wei Huang
- Oregon Health and Science University, Advanced Imaging Research Center, Portland, Oregon, United States.,Oregon Health and Science University, Knight Cancer Institute, Portland, Oregon, United States
| | - Thomas E Yankeelov
- University of Texas at Austin, Department of Diagnostic Medicine, Austin, Texas, United States.,University of Texas at Austin, Livestrong Cancer Institutes, Austin, Texas, United States.,University of Texas at Austin, Department of Biomedical Engineering, Austin, Texas, United States.,University of Texas at Austin, Institute for Computational and Engineering Sciences, Austin, Texas, United States
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46
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Jones KM, Pagel MD, Cárdenas-Rodríguez J. Linearization improves the repeatability of quantitative dynamic contrast-enhanced MRI. Magn Reson Imaging 2017; 47:16-24. [PMID: 29155024 DOI: 10.1016/j.mri.2017.11.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Revised: 10/31/2017] [Accepted: 11/13/2017] [Indexed: 12/27/2022]
Abstract
PURPOSE The purpose of this study was to compare the repeatabilities of the linear and nonlinear Tofts and reference region models (RRM) for dynamic contrast-enhanced MRI (DCE-MRI). MATERIALS AND METHODS Simulated and experimental DCE-MRI data from 12 rats with a flank tumor of C6 glioma acquired over three consecutive days were analyzed using four quantitative and semi-quantitative DCE-MRI metrics. The quantitative methods used were: 1) linear Tofts model (LTM), 2) non-linear Tofts model (NTM), 3) linear RRM (LRRM), and 4) non-linear RRM (NRRM). The following semi-quantitative metrics were used: 1) maximum enhancement ratio (MER), 2) time to peak (TTP), 3) initial area under the curve (iauc64), and 4) slope. LTM and NTM were used to estimate Ktrans, while LRRM and NRRM were used to estimate Ktrans relative to muscle (RKtrans). Repeatability was assessed by calculating the within-subject coefficient of variation (wSCV) and the percent intra-subject variation (iSV) determined with the Gage R&R analysis. RESULTS The iSV for RKtrans using LRRM was two-fold lower compared to NRRM at all simulated and experimental conditions. A similar trend was observed for the Tofts model, where LTM was at least 50% more repeatable than the NTM under all experimental and simulated conditions. The semi-quantitative metrics iauc64 and MER were as equally repeatable as Ktrans and RKtrans estimated by LTM and LRRM respectively. The iSV for iauc64 and MER were significantly lower than the iSV for slope and TTP. CONCLUSION In simulations and experimental results, linearization improves the repeatability of quantitative DCE-MRI by at least 30%, making it as repeatable as semi-quantitative metrics.
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Affiliation(s)
- Kyle M Jones
- Department of Biomedical Engineering, University of Arizona, Tucson, AZ, United States; Department of Medical Imaging, University of Arizona, Tucson, AZ, United States
| | - Mark D Pagel
- Department of Biomedical Engineering, University of Arizona, Tucson, AZ, United States; Department of Medical Imaging, University of Arizona, Tucson, AZ, United States.
| | - Julio Cárdenas-Rodríguez
- Department of Biomedical Engineering, University of Arizona, Tucson, AZ, United States; Department of Medical Imaging, University of Arizona, Tucson, AZ, United States
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Quantitative Assessment of Liver Function Using Gadoxetate-Enhanced Magnetic Resonance Imaging: Monitoring Transporter-Mediated Processes in Healthy Volunteers. Invest Radiol 2017; 52:111-119. [PMID: 28002117 PMCID: PMC5228626 DOI: 10.1097/rli.0000000000000316] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Objective The objective of this study was to use noninvasive dynamic contrast-enhanced magnetic resonance imaging (MRI) techniques to study, in vivo, the distribution and elimination of the hepatobiliary contrast agent gadoxetate in the human body and characterize the transport mechanisms involved in its uptake into hepatocytes and subsequent efflux into the bile using a novel tracer kinetic model in a group of healthy volunteers. Materials and Methods Ten healthy volunteers (age range, 18–29 years), with no history of renal or hepatic impairment, were recruited via advertisement. Participants attended 2 MRI visits (at least a week apart) with gadoxetate as the contrast agent. Dynamic contrast-enhanced MRI data were acquired for approximately 50 minutes with a 3-dimensional gradient-echo sequence in the axial plane, at a temporal resolution of 6.2 seconds. Data from regions of interest drawn in the liver were analyzed using the proposed 2-compartment uptake and efflux model to provide estimates for the uptake rate of gadoxetate in hepatocytes and its efflux rate into the bile. Reproducibility statistics for the 2 visits were obtained to examine the robustness of the technique and its dependence in acquisition time. Results Eight participants attended the study twice and were included into the analysis. The resulting images provided the ability to simultaneously monitor the distribution of gadoxetate in multiple organs including the liver, spleen, and kidneys as well as its elimination through the common bile duct, accumulation in the gallbladder, and excretion in the duodenum. The mean uptake (ki) and efflux (kef) rates in hepatocytes, for the 2 visits using the 50-minute acquisition, were 0.22 ± 0.05 and 0.017 ± 0.006/min, respectively. The hepatic extraction fraction was estimated to be 0.19 ± 0.04/min. The variability between the 2 visits within the group level (95% confidence interval; ki: ±0.02/min, kef: ±0.004/min) was lower compared with the individual variability (repeatability; ki: ±0.06/min, kef: ±0.012/min). Data truncation demonstrated that the uptake rate estimates retained their precision as well as their group and individual reproducibility down to approximately 10 minutes of acquisition. Efflux rate estimates were underestimated (compared with the 50-minute acquisition) as the duration of the acquisition decreased, although these effects were more pronounced for acquisition times shorter than approximately 30 minutes. Conclusions This is the first study that reports estimates for the hepatic uptake and efflux transport process of gadoxetate in healthy volunteers in vivo. The results highlight that dynamic contrast-enhanced MRI with gadoxetate can provide novel quantitative insights into liver function and may therefore prove useful in studies that aim to monitor liver pathology, as well as being an alternative approach for studying hepatic drug-drug interactions.
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Chung M, Choi Y, Lee S, Lee J, Lee Y, Rho J, Baek J. Interobserver reproducibility of maximal axial diameter and tumour volume measurements from CT of patients with head and neck squamous cell carcinoma. Clin Radiol 2017; 72:993.e7-993.e13. [DOI: 10.1016/j.crad.2017.06.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2016] [Revised: 04/28/2017] [Accepted: 06/06/2017] [Indexed: 11/16/2022]
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Taxt T, Reed RK, Pavlin T, Rygh CB, Andersen E, Jiřík R. Semi-parametric arterial input functions for quantitative dynamic contrast enhanced magnetic resonance imaging in mice. Magn Reson Imaging 2017; 46:10-20. [PMID: 29066294 DOI: 10.1016/j.mri.2017.10.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Revised: 09/15/2017] [Accepted: 10/17/2017] [Indexed: 01/23/2023]
Abstract
OBJECTIVE An extension of single- and multi-channel blind deconvolution is presented to improve the estimation of the arterial input function (AIF) in quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). METHODS The Lucy-Richardson expectation-maximization algorithm is used to obtain estimates of the AIF and the tissue residue function (TRF). In the first part of the algorithm, nonparametric estimates of the AIF and TRF are obtained. In the second part, the decaying part of the AIF is approximated by three decaying exponential functions with the same delay, giving an almost noise free semi-parametric AIF. Simultaneously, the TRF is approximated using the adiabatic approximation of the Johnson-Wilson (aaJW) pharmacokinetic model. RESULTS In simulations and tests on real data, use of this AIF gave perfusion values close to those obtained with the corresponding previously published nonparametric AIF, and are more noise robust. CONCLUSION When used subsequently in voxelwise perfusion analysis, these semi-parametric AIFs should give more correct perfusion analysis maps less affected by recording noise than the corresponding nonparametric AIFs, and AIFs obtained from arteries. SIGNIFICANCE This paper presents a method to increase the noise robustness in the estimation of the perfusion parameter values in DCE-MRI.
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Affiliation(s)
- Torfinn Taxt
- Dept. of Biomedicine, University of Bergen, Jonas Lies vei 91, Bergen N-5020, Norway; Dept. of Radiology, Haukeland University Hospital, Jonas Lies vei 83, Bergen N-5020, Norway
| | - Rolf K Reed
- Dept. of Biomedicine, University of Bergen, Jonas Lies vei 91, Bergen N-5020, Norway; Centre for Cancer Biomarkers (CCBIO), University of Bergen, Jonas Lies vei 87, Bergen N-5021, Norway
| | - Tina Pavlin
- Dept. of Biomedicine, University of Bergen, Jonas Lies vei 91, Bergen N-5020, Norway; Dept. of Radiology, Haukeland University Hospital, Jonas Lies vei 83, Bergen N-5020, Norway
| | - Cecilie Brekke Rygh
- Dept. of Biomedicine, University of Bergen, Jonas Lies vei 91, Bergen N-5020, Norway
| | - Erling Andersen
- Dept. of Clinical Engineering, Haukeland University Hospital, Jonas Lies vei 83, Bergen N-5020, Norway
| | - Radovan Jiřík
- Czech Academy of Sciences, Inst. of Scientific Instruments, Královopolská 147, Brno 61264, Czech Republic.
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A Multi-Institutional Comparison of Dynamic Contrast-Enhanced Magnetic Resonance Imaging Parameter Calculations. Sci Rep 2017; 7:11185. [PMID: 28894197 PMCID: PMC5593829 DOI: 10.1038/s41598-017-11554-w] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 08/18/2017] [Indexed: 11/15/2022] Open
Abstract
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides quantitative metrics (e.g. Ktrans, ve) via pharmacokinetic models. We tested inter-algorithm variability in these quantitative metrics with 11 published DCE-MRI algorithms, all implementing Tofts-Kermode or extended Tofts pharmacokinetic models. Digital reference objects (DROs) with known Ktrans and ve values were used to assess performance at varying noise levels. Additionally, DCE-MRI data from 15 head and neck squamous cell carcinoma patients over 3 time-points during chemoradiotherapy were used to ascertain Ktrans and ve kinetic trends across algorithms. Algorithms performed well (less than 3% average error) when no noise was present in the DRO. With noise, 87% of Ktrans and 84% of ve algorithm-DRO combinations were generally in the correct order. Low Krippendorff’s alpha values showed that algorithms could not consistently classify patients as above or below the median for a given algorithm at each time point or for differences in values between time points. A majority of the algorithms produced a significant Spearman correlation in ve of the primary gross tumor volume with time. Algorithmic differences in Ktrans and ve values over time indicate limitations in combining/comparing data from distinct DCE-MRI model implementations. Careful cross-algorithm quality-assurance must be utilized as DCE-MRI results may not be interpretable using differing software.
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