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Herings SDA, van den Elshout R, de Wit R, Mannil M, Ravesloot C, Scheenen TWJ, Arens A, van der Kolk A, Meijer FJA, Henssen DJHA. How to evaluate perfusion imaging in post-treatment glioma: a comparison of three different analysis methods. Neuroradiology 2024; 66:1279-1289. [PMID: 38714545 PMCID: PMC11246270 DOI: 10.1007/s00234-024-03374-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 05/01/2024] [Indexed: 05/10/2024]
Abstract
INTRODUCTION Dynamic susceptibility contrast (DSC) perfusion weighted (PW)-MRI can aid in differentiating treatment related abnormalities (TRA) from tumor progression (TP) in post-treatment glioma patients. Common methods, like the 'hot spot', or visual approach suffer from oversimplification and subjectivity. Using perfusion of the complete lesion potentially offers an objective and accurate alternative. This study aims to compare the diagnostic value and assess the subjectivity of these techniques. METHODS 50 Glioma patients with enhancing lesions post-surgery and chemo-radiotherapy were retrospectively included. Outcome was determined by clinical/radiological follow-up or biopsy. Imaging analysis used the 'hot spot', volume of interest (VOI) and visual approach. Diagnostic accuracy was compared using receiving operator characteristics (ROC) curves for the VOI and 'hot spot' approach, visual assessment was analysed with contingency tables. Inter-operator agreement was determined with Cohens kappa and intra-class coefficient (ICC). RESULTS 29 Patients suffered from TP, 21 had TRA. The visual assessment showed poor to substantial inter-operator agreement (κ = -0.72 - 0.68). Reliability of the 'hot spot' placement was excellent (ICC = 0.89), while reference placement was variable (ICC = 0.54). The area under the ROC (AUROC) of the mean- and maximum relative cerebral blood volume (rCBV) (VOI-analysis) were 0.82 and 0.72, while the rCBV-ratio ('hot spot' analysis) was 0.69. The VOI-analysis had a more balanced sensitivity and specificity compared to visual assessment. CONCLUSIONS VOI analysis of DSC PW-MRI data holds greater diagnostic accuracy in single-moment differentiation of TP and TRA than 'hot spot' or visual analysis. This study underlines the subjectivity of visual placement and assessment.
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Affiliation(s)
- Siem D A Herings
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands.
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands.
| | - Rik van den Elshout
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Rebecca de Wit
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Manoj Mannil
- University Clinic for Radiology, Westfälische Wilhelms-University Muenster and University Hospital Muenster, Albert-Schweitzer-Campus 1, E48149, Muenster, Germany
| | - Cécile Ravesloot
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Anne Arens
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Anja van der Kolk
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frederick J A Meijer
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
| | - Dylan J H A Henssen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
- Radboudumc Center of Expertise Neuro-Oncology, Nijmegen, The Netherlands
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Prah MA, Schmainda KM. Practical guidance to identify and troubleshoot suboptimal DSC-MRI results. FRONTIERS IN RADIOLOGY 2024; 4:1307586. [PMID: 38445104 PMCID: PMC10913595 DOI: 10.3389/fradi.2024.1307586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 02/02/2024] [Indexed: 03/07/2024]
Abstract
Relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast (DSC) perfusion MR imaging (pMRI) has been shown to be a robust marker of neuroradiological tumor burden. Recent consensus recommendations in pMRI acquisition strategies have provided a pathway for pMRI inclusion in diverse patient care centers, regardless of size or experience. However, even with proper implementation and execution of the DSC-MRI protocol, issues will arise that many centers may not easily recognize or be aware of. Furthermore, missed pMRI issues are not always apparent in the resulting rCBV images, potentiating inaccurate or missed radiological diagnoses. Therefore, we gathered from our database of DSC-MRI datasets, true-to-life examples showcasing the breakdowns in acquisition, postprocessing, and interpretation, along with appropriate mitigation strategies when possible. The pMRI issues addressed include those related to image acquisition and postprocessing with a focus on contrast agent administration, timing, and rate, signal-to-noise quality, and susceptibility artifact. The goal of this work is to provide guidance to minimize and recognize pMRI issues to ensure that only quality data is interpreted.
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Affiliation(s)
- Melissa A. Prah
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI,United States
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Iv M, Naya L, Sanan S, Van Buskirk SL, Nagpal S, Thomas RP, Recht LD, Patel CB. Tumor treating fields increases blood-brain barrier permeability and relative cerebral blood volume in patients with glioblastoma. Neuroradiol J 2024; 37:107-118. [PMID: 37931176 PMCID: PMC10863570 DOI: 10.1177/19714009231207083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND AND OBJECTIVE 200 kHz tumor treating fields (TTFields) is clinically approved for newly-diagnosed glioblastoma (nGBM). Because its effects on conventional surveillance MRI brain scans are equivocal, we investigated its effects on perfusion MRI (pMRI) brain scans. METHODS Each patient underwent institutional standard pMRI: dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) pMRI at three time points: baseline, 2-, and 6-months on-adjuvant therapy. At each timepoint, the difference between T1 pre- versus post-contrast tumor volume (ΔT1) and these pMRI metrics were evaluated: normalized and standardized relative cerebral blood volume (nRCBV, sRCBV); fractional plasma volume (Vp), volume of extravascular extracellular space (EES) per volume of tissue (Ve), blood-brain barrier (BBB) permeability (Ktrans), and time constant for gadolinium reflux from EES back into the vascular system (Kep). Between-group comparisons were performed using rank-sum analysis, and bootstrapping evaluated likely reproducibility of the results. RESULTS Among 13 pMRI datasets (11 nGBM, 2 recurrent GBM), therapies included temozolomide-only (n = 9) and temozolomide + TTFields (n = 4). No significant differences were found in patient or tumor characteristics. Compared to temozolomide-only, temozolomide + TTFields did not significantly affect the percent-change in pMRI metrics from baseline to 2 months. But during the 2- to 6-month period, temozolomide + TTFields significantly increased the percent-change in nRCBV (+26.9% [interquartile range 55.1%] vs -39.1% [37.0%], p = 0.049), sRCBV (+9.5% [39.7%] vs -30.5% [39.4%], p = 0.049), Ktrans (+54.6% [1768.4%] vs -26.9% [61.2%], p = 0.024), Ve (+111.0% [518.1%] vs -13.0% [22.5%], p = 0.048), and Vp (+98.8% [2172.4%] vs -24.6% [53.3%], p = 0.024) compared to temozolomide-only. CONCLUSION Using pMRI, we provide initial in-human validation of pre-clinical studies regarding the effects of TTFields on tumor blood volume and BBB permeability in GBM.
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Affiliation(s)
- Michael Iv
- Division of Neuroradiology, Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA
| | - Lewis Naya
- Stanford Cancer Institute, Stanford, CA, USA
| | - Sajal Sanan
- School of Medicine, University of Washington, Seattle, WA, USA
| | - Samuel L Van Buskirk
- Department of Psychology, University of Texas at San Antonio, San Antonio, TX, USA
| | - Seema Nagpal
- Division of Neuro-Oncology, Department of Neurology, Stanford University School of Medicine, Stanford, CA, USA
| | - Reena P Thomas
- Division of Neuro-Oncology, Department of Neurology, Stanford University School of Medicine, Stanford, CA, USA
| | - Lawrence D Recht
- Division of Neuro-Oncology, Department of Neurology, Stanford University School of Medicine, Stanford, CA, USA
| | - Chirag B Patel
- Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Cancer Biology Program, The University of Texas MD Anderson Cancer Center, University of Texas at Houston Graduate School of Biomedical Sciences (GSBS), Houston, TX, USA
- Neuroscience Graduate Program, The University of Texas MD Anderson Cancer Center-University of Texas at Houston Graduate School of Biomedical Sciences (GSBS), USA
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Botros NE, Polinger-Hyman D, Beck RT, Kleefisch C, Mrachek EKS, Connelly J, Schmainda KM, Krucoff MO. Magnetic resonance imaging-derived relative cerebral blood volume characteristics in a case of pathologically confirmed neurocysticercosis: illustrative case. JOURNAL OF NEUROSURGERY. CASE LESSONS 2023; 6:CASE23446. [PMID: 38109728 PMCID: PMC10732321 DOI: 10.3171/case23446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 11/10/2023] [Indexed: 12/20/2023]
Abstract
BACKGROUND Neurocysticercosis (NCC) is a parasitic infection of the brain caused by ingesting water or food contaminated with tapeworm eggs. When it presents as a solitary mass, differentiation from a primary brain tumor on imaging can be difficult. Magnetic resonance imaging (MRI)-derived relative cerebral blood volume (rCBV) is a newer imaging technique used to identify areas of neovascularization in tumors, which may advance the differential diagnosis. OBSERVATIONS A 25-year-old male presented after a seizure. Computed tomography (CT) and MRI demonstrated a partially enhancing lesion with microcalcifications and vasogenic edema. Follow-up rCBV assessment demonstrated mild hyperperfusion and/or small vessels at the lesional margins consistent with either an intermediate grade glioma or infection. Given the radiological equipoise, surgical accessibility, and differential diagnosis including primary neoplasm, metastatic disease, NCC, and abscess, resection was pursued. The calcified mass was excised en bloc and was confirmed as larval-stage NCC. LESSONS CT or MRI may not always provide sufficient information to distinguish NCC from brain tumors. Although reports have suggested that rCBV may aid in identifying NCC, here the authors describe a case of pathologically confirmed NCC in which preoperative, qualitative, standardized rCBV findings raised concern for a primary neoplasm. This case documents the first standardized rCBV values reported in a pathologically confirmed case of NCC in the United States.
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Affiliation(s)
| | | | | | | | - E Kelly S Mrachek
- 4Pathology, and Division of Neuropathology, Froedtert Hospital, Medical College of Wisconsin, Milwaukee, Wisconsin
| | | | | | - Max O Krucoff
- Departments of2Neurosurgery
- 7Joint Department of Biomedical Engineering, Marquette University & Medical College of Wisconsin, Wisconsin
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Shiroishi MS, Weinert D, Cen SY, Varghese B, Dondlinger T, Prah M, Mendoza J, Nazemi S, Ameli N, Amini N, Shohas S, Chen S, Bigjahan B, Zada G, Chen T, Neman-Ebrahim J, Chang EL, Chow FE, Fan Z, Yang W, Attenello FJ, Ye J, Kim PE, Patel VN, Lerner A, Acharya J, Hu LS, Quarles CC, Boxerman JL, Wu O, Schmainda KM. A cross-sectional study to test equivalence of low- versus intermediate-flip angle dynamic susceptibility contrast MRI measures of relative cerebral blood volume in patients with high-grade gliomas at 1.5 Tesla field strength. Front Oncol 2023; 13:1156843. [PMID: 37799462 PMCID: PMC10548232 DOI: 10.3389/fonc.2023.1156843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 08/21/2023] [Indexed: 10/07/2023] Open
Abstract
Introduction 1.5 Tesla (1.5T) remain a significant field strength for brain imaging worldwide. Recent computer simulations and clinical studies at 3T MRI have suggested that dynamic susceptibility contrast (DSC) MRI using a 30° flip angle ("low-FA") with model-based leakage correction and no gadolinium-based contrast agent (GBCA) preload provides equivalent relative cerebral blood volume (rCBV) measurements to the reference-standard acquisition using a single-dose GBCA preload with a 60° flip angle ("intermediate-FA") and model-based leakage correction. However, it remains unclear whether this holds true at 1.5T. The purpose of this study was to test this at 1.5T in human high-grade glioma (HGG) patients. Methods This was a single-institution cross-sectional study of patients who had undergone 1.5T MRI for HGG. DSC-MRI consisted of gradient-echo echo-planar imaging (GRE-EPI) with a low-FA without preload (30°/P-); this then subsequently served as a preload for the standard intermediate-FA acquisition (60°/P+). Both normalized (nrCBV) and standardized relative cerebral blood volumes (srCBV) were calculated using model-based leakage correction (C+) with IBNeuro™ software. Whole-enhancing lesion mean and median nrCBV and srCBV from the low- and intermediate-FA methods were compared using the Pearson's, Spearman's and intraclass correlation coefficients (ICC). Results Twenty-three HGG patients composing a total of 31 scans were analyzed. The Pearson and Spearman correlations and ICCs between the 30°/P-/C+ and 60°/P+/C+ acquisitions demonstrated high correlations for both mean and median nrCBV and srCBV. Conclusion Our study provides preliminary evidence that for HGG patients at 1.5T MRI, a low FA, no preload DSC-MRI acquisition can be an appealing alternative to the reference standard higher FA acquisition that utilizes a preload.
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Affiliation(s)
- Mark S. Shiroishi
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Marina del Rey, CA, United States
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Dane Weinert
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Steven Y. Cen
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Bino Varghese
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | | | - Melissa Prah
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Jesse Mendoza
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Sina Nazemi
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Nima Ameli
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Negin Amini
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Salman Shohas
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Shannon Chen
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Bavrina Bigjahan
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Gabriel Zada
- Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Thomas Chen
- Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Josh Neman-Ebrahim
- Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Eric L. Chang
- Department of Radiation Oncology, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Frances E. Chow
- Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Zhaoyang Fan
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
- Department of Radiation Oncology, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Wensha Yang
- Department of Radiation Oncology, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Frank J. Attenello
- Department of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Jason Ye
- Department of Radiation Oncology, Keck School of Medicine of USC, Los Angeles, CA, United States
| | - Paul E. Kim
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Vishal N. Patel
- Department of Radiology, Mayo Clinic, Jacksonville, FL, United States
| | - Alexander Lerner
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Jay Acharya
- Department of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States
| | - Leland S. Hu
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - C. Chad Quarles
- Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jerrold L. Boxerman
- Department of Diagnostic Imaging, The Warren Alpert Medical School of Brown University, Providence, RI, United States
| | - Ona Wu
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
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Eraky AM. Radiological Biomarkers for Brain Metastases Prognosis: Quantitative Magnetic Resonance Imaging (MRI) Modalities As Non-invasive Biomarkers for the Effect of Radiotherapy. Cureus 2023; 15:e38353. [PMID: 37266043 PMCID: PMC10229388 DOI: 10.7759/cureus.38353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/28/2023] [Indexed: 06/03/2023] Open
Abstract
Radiotherapy effect is achieved by its ability to cause DNA damage and induce apoptosis. In contrast, radiation can induce tumor cells' proliferation, invasiveness, and epithelial-mesenchymal transition (EMT). Besides developing radioresistance, this paradoxical effect of radiotherapy is considered a challenging problem in the field of radiotherapy. This highlights the importance of developing new modalities to diagnose radioresistance early to avoid any unnecessary exposure to radiation and differentiate between metastases recurrence versus post-radiation changes. Quantitative magnetic resonance imaging (MRI) techniques including diffusion-weighted imaging (DWI), dynamic susceptibility contrast (DSC), arterial spin labeling (ASL), and dynamic contrast-enhanced (DCE) represent potential biomarkers to diagnose metastases recurrence and radioresistance. In this review, we will focus on recent studies discussing the possibility of using DWI, DSC, ASL, and DCE to diagnose radioresistance and recurrence in patients with brain metastases.
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Affiliation(s)
- Akram M Eraky
- Neurological Surgery, Medical College of Wisconsin, Milwaukee, USA
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7
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Cho NS, Hagiwara A, Sanvito F, Ellingson BM. A multi-reader comparison of normal-appearing white matter normalization techniques for perfusion and diffusion MRI in brain tumors. Neuroradiology 2023; 65:559-568. [PMID: 36301349 PMCID: PMC9905164 DOI: 10.1007/s00234-022-03072-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 10/14/2022] [Indexed: 02/08/2023]
Abstract
PURPOSE There remains no consensus normal-appearing white matter (NAWM) normalization method to compute normalized relative cerebral blood volume (nrCBV) and apparent diffusion coefficient (nADC) in brain tumors. This reader study explored nrCBV and nADC differences using different NAWM normalization methods. METHODS Thirty-five newly diagnosed glioma patients were studied. For each patient, two readers created four NAWM regions of interests: (1) a single plane in the centrum semiovale (CSOp), (2) 3 spheres in the centrum semiovale (CSOs), (3) a single plane in the slice of the tumor center (TUMp), and (4) 3 spheres in the slice of the tumor center (TUMs). Readers repeated NAWM segmentations 1 month later. Differences in nrCBV and nADC of the FLAIR hyperintense tumor, inter-/intra-reader variability, and time to segment NAWM were assessed. As a validation step, the diagnostic performance of each method for IDH-status prediction was evaluated. RESULTS Both readers obtained significantly different nrCBV (P < .001), nADC (P < .001), and time to segment NAWM (P < .001) between the four normalization methods. nrCBV and nADC were significantly different between CSO and TUM methods, but not between planar and spherical methods in the same NAWM region. Broadly, CSO methods were quicker than TUM methods, and spherical methods were quicker than planar methods. For all normalization techniques, inter-reader reproducibility and intra-reader repeatability were excellent (intraclass correlation coefficient > 0.9), and the IDH-status predictive performance remained similar. CONCLUSION The selected NAWM region significantly impacts nrCBV and nADC values. CSO methods, particularly CSOs, may be preferred because of time reduction, similar reader variability, and similar diagnostic performance compared to TUM methods.
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Affiliation(s)
- Nicholas S Cho
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Francesco Sanvito
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Unit of Radiology, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy
| | - Benjamin M Ellingson
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
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Boxerman JL, Snyder BS, Barboriak DP, Schmainda KM. Early post-bevacizumab change in rCBV from DSC-MRI identifies pseudoresponse in recurrent glioblastoma: Results from ACRIN 6677/RTOG 0625. Front Oncol 2023; 13:1061502. [PMID: 36776298 PMCID: PMC9909012 DOI: 10.3389/fonc.2023.1061502] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 01/02/2023] [Indexed: 01/27/2023] Open
Abstract
Background Progressive enhancement predicted poor survival in ACRIN 6677/RTOG 0625, a multi-center trial of bevacizumab with irinotecan or temozolomide in recurrent glioblastoma, but pseudoresponse likely limited enhancement-based survival prognostication in T1 non-progressors. We aimed to determine whether early change in cerebral blood volume from baseline (ΔCBV) could further stratify the T1 non-progressors according to overall (OS) and progression-free (PFS) survival. Methods 37/123 enrolled patients had DSC-MRI, including 13, 15, and 8 patients without 2D-T1 progression at 2, 8, and 16 weeks post-treatment initiation, respectively. Mean CBV normalized to white matter (nRCBV) and mean standardized CBV (sRCBV) were extracted from enhancing tumor. ROC curves were derived for ΔCBV using six-month PFS and one-year OS as reference standards. Kaplan-Meier survival estimates and log-rank test compared PFS and OS for both ΔCBV (increase vs. decrease) and T1 response status (stable vs. decreasing enhancement). Results PFS and OS were significantly worse for increasing CBV at 2 weeks (p=0.003 and p=0.002 for nRCBV, and p=0.03 and p=0.03 for sRCBV, respectively), but not for 2D-T1 patients with stable vs. decreasing enhancement (p=0.44 and p=0.86, respectively). ΔCBV at week 2 was also a good prognostic marker for OS-1 and PFS-6 using ROC analysis. By contrast, 2D-T1 response status at weeks 2, 8, and 16 was not associated with PFS-6. ΔCBV at 16 weeks (p=0.008 for sRCBV) but not 8 weeks (p=0.74 for nRCBV and p=0.56 for sRCBV) was associated with significant difference in median survival, but no difference in survival was observed for 2D-T1 patients with stable vs. decreasing enhancement at 8 weeks (p=0.69) or 16 weeks (p=0.21). At 16 weeks, OS did not differ significantly between 2D-T1 progressors and 2D-T1 non-progressors with increasing CBV (median survival 3.3 months post week 16 scan vs. 9.2 months, respectively; p=0.13), suggesting that 2D-T1 non-progressors with increasing CBV may have a prognosis like that of 2D-T1 progressors. Conclusion After 2 weeks of anti-angiogenic therapy, ΔCBV in 2D-T1 non-progressors significantly prognosticated PFS and OS, whereas 2D-T1 response status did not, identifying a subpopulation that benefits from bevacizumab. Combining 2D-T1 progression and ΔCBV may yield a response assessment paradigm with 3-tiered OS stratification.
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Affiliation(s)
- Jerrold L. Boxerman
- Department of Diagnostic Imaging, Rhode Island Hospital and Alpert Medical School of Brown University, Providence, RI, United States
| | - Bradley S. Snyder
- Center for Statistical Sciences, Brown University School of Public Health, Providence, RI, United States
| | - Daniel P. Barboriak
- Department of Radiology, Duke University Medical Center, Durham, NC, United States
| | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
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Anil A, Stokes AM, Chao R, Hu LS, Alhilali L, Karis JP, Bell LC, Quarles CC. Identification of single-dose, dual-echo based CBV threshold for fractional tumor burden mapping in recurrent glioblastoma. Front Oncol 2023; 13:1046629. [PMID: 36733305 PMCID: PMC9887158 DOI: 10.3389/fonc.2023.1046629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 01/03/2023] [Indexed: 01/18/2023] Open
Abstract
Background Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is widely used to distinguish high grade glioma recurrence from post treatment radiation effects (PTRE). Application of rCBV thresholds yield maps to distinguish between regional tumor burden and PTRE, a biomarker termed the fractional tumor burden (FTB). FTB is generally measured using conventional double-dose, single-echo DSC-MRI protocols; recently, a single-dose, dual-echo DSC-MRI protocol was clinically validated by direct comparison to the conventional double-dose, single-echo protocol. As the single-dose, dual-echo acquisition enables reduction in the contrast agent dose and provides greater pulse sequence parameter flexibility, there is a compelling need to establish dual-echo DSC-MRI based FTB mapping. In this study, we determine the optimum standardized rCBV threshold for the single-dose, dual-echo protocol to generate FTB maps that best match those derived from the reference standard, double-dose, single-echo protocol. Methods The study consisted of 23 high grade glioma patients undergoing perfusion scans to confirm suspected tumor recurrence. We sequentially acquired single dose, dual-echo and double dose, single-echo DSC-MRI data. For both protocols, we generated leakage-corrected standardized rCBV maps. Standardized rCBV (sRCBV) thresholds of 1.0 and 1.75 were used to compute single-echo FTB maps as the reference for delineating PTRE (sRCBV < 1.0), tumor with moderate angiogenesis (1.0 < sRCBV < 1.75), and tumor with high angiogenesis (sRCBV > 1.75) regions. To assess the sRCBV agreement between acquisition protocols, the concordance correlation coefficient (CCC) was computed between the mean tumor sRCBV values across the patients. A receiver operating characteristics (ROC) analysis was performed to determine the optimum dual-echo sRCBV threshold. The sensitivity, specificity, and accuracy were compared between the obtained optimized threshold (1.64) and the standard reference threshold (1.75) for the dual-echo sRCBV threshold. Results The mean tumor sRCBV values across the patients showed a strong correlation (CCC = 0.96) between the two protocols. The ROC analysis showed maximum accuracy at thresholds of 1.0 (delineate PTRE from tumor) and 1.64 (differentiate aggressive tumors). The reference threshold (1.75) and the obtained optimized threshold (1.64) yielded similar accuracy, with slight differences in sensitivity and specificity which were not statistically significant (1.75 threshold: Sensitivity = 81.94%; Specificity: 87.23%; Accuracy: 84.58% and 1.64 threshold: Sensitivity = 84.48%; Specificity: 84.97%; Accuracy: 84.73%). Conclusions The optimal sRCBV threshold for single-dose, dual-echo protocol was found to be 1.0 and 1.64 for distinguishing tumor recurrence from PTRE; however, minimal differences were observed when using the standard threshold (1.75) as the upper threshold, suggesting that the standard threshold could be used for both protocols. While the prior study validated the agreement of the mean sRCBV values between the protocols, this study confirmed that their voxel-wise agreement is suitable for reliable FTB mapping. Dual-echo DSC-MRI acquisitions enable robust single-dose sRCBV and FTB mapping, provide pulse sequence parameter flexibility and should improve reproducibility by mitigating variations in preload dose and incubation time.
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Affiliation(s)
- Aliya Anil
- Division of Neuroimaging Research and Barrow Neuroimaging Innovation Center, Barrow Neuroimaging Institute, Phoenix, AZ, United States
| | - Ashley M. Stokes
- Division of Neuroimaging Research and Barrow Neuroimaging Innovation Center, Barrow Neuroimaging Institute, Phoenix, AZ, United States
| | - Renee Chao
- Division of Neuroimaging Research and Barrow Neuroimaging Innovation Center, Barrow Neuroimaging Institute, Phoenix, AZ, United States
| | - Leland S. Hu
- Department of Radiology, Division of Neuroradiology, Mayo Clinic Arizona, Phoenix, AZ, United States
| | - Lea Alhilali
- Neuroradiology, Southwest Neuroimaging at Barrow Neurological Institute, Phoenix, AZ, United States
| | - John P. Karis
- Neuroradiology, Southwest Neuroimaging at Barrow Neurological Institute, Phoenix, AZ, United States
| | - Laura C. Bell
- Early Clinical Development, Genentech, San Francisco, CA, United States
| | - C. Chad Quarles
- Cancer System Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States,*Correspondence: C. Chad Quarles,
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10
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Kuo F, Ng NN, Nagpal S, Pollom EL, Soltys S, Hayden-Gephart M, Li G, Born DE, Iv M. DSC Perfusion MRI-Derived Fractional Tumor Burden and Relative CBV Differentiate Tumor Progression and Radiation Necrosis in Brain Metastases Treated with Stereotactic Radiosurgery. AJNR Am J Neuroradiol 2022; 43:689-695. [PMID: 35483909 PMCID: PMC9089266 DOI: 10.3174/ajnr.a7501] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 03/14/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND AND PURPOSE Differentiation between tumor and radiation necrosis in patients with brain metastases treated with stereotactic radiosurgery is challenging. We hypothesized that MR perfusion and metabolic metrics can differentiate radiation necrosis from progressive tumor in this setting. MATERIALS AND METHODS We retrospectively evaluated MRIs comprising DSC, dynamic contrast-enhanced, and arterial spin-labeling perfusion imaging in subjects with brain metastases previously treated with stereotactic radiosurgery. For each lesion, we obtained the mean normalized and standardized relative CBV and fractional tumor burden, volume transfer constant, and normalized maximum CBF, as well as the maximum standardized uptake value in a subset of subjects who underwent FDG-PET. Relative CBV thresholds of 1 and 1.75 were used to define low and high fractional tumor burden. RESULTS Thirty subjects with 37 lesions (20 radiation necrosis, 17 tumor) were included. Compared with radiation necrosis, tumor had increased mean normalized and standardized relative CBV (P = .002) and high fractional tumor burden (normalized, P = .005; standardized, P = .003) and decreased low fractional tumor burden (normalized, P = .03; standardized, P = .01). The area under the curve showed that relative CBV (normalized = 0.80; standardized = 0.79) and high fractional tumor burden (normalized = 0.77; standardized = 0.78) performed the best to discriminate tumor and radiation necrosis. For tumor prediction, the normalized relative CBV cutoff of ≥1.75 yielded a sensitivity of 76.5% and specificity of 70.0%, while the standardized cutoff of ≥1.75 yielded a sensitivity of 41.2% and specificity of 95.0%. No significance was found with the volume transfer constant, normalized CBF, and standardized uptake value. CONCLUSIONS Increased relative CBV and high fractional tumor burden (defined by a threshold relative CBV of ≥1.75) best differentiated tumor from radiation necrosis in subjects with brain metastases treated with stereotactic radiosurgery. Performance of normalized and standardized approaches was similar.
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Affiliation(s)
- F Kuo
- From the Department of Radiology, Division of Neuroimaging and Neurointervention (F.K., N.N.N., M.I.)
| | - N N Ng
- From the Department of Radiology, Division of Neuroimaging and Neurointervention (F.K., N.N.N., M.I.)
| | - S Nagpal
- Departments of Neurology (Neuro-Oncology) (S.N.)
| | | | - S Soltys
- Radiation Oncology (E.L.P., S.S.)
| | | | - G Li
- Neurosurgery (M.H.-G., G.L.)
| | - D E Born
- Pathology (D.E.B.), Stanford University, Stanford, California
| | - M Iv
- From the Department of Radiology, Division of Neuroimaging and Neurointervention (F.K., N.N.N., M.I.)
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11
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Malik DG, Rath TJ, Urcuyo Acevedo JC, Canoll PD, Swanson KR, Boxerman JL, Quarles CC, Schmainda KM, Burns TC, Hu LS. Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions. FRONTIERS IN RADIOLOGY 2022; 2:809373. [PMID: 37492687 PMCID: PMC10365126 DOI: 10.3389/fradi.2022.809373] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 03/01/2022] [Indexed: 07/27/2023]
Abstract
In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.
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Affiliation(s)
- Dania G. Malik
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Tanya J. Rath
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Javier C. Urcuyo Acevedo
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Peter D. Canoll
- Departments of Pathology and Cell Biology, Columbia University, New York, NY, United States
| | - Kristin R. Swanson
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Jerrold L. Boxerman
- Department of Diagnostic Imaging, Brown University, Providence, RI, United States
| | - C. Chad Quarles
- Department of Neuroimaging Research & Barrow Neuroimaging Innovation Center, Barrow Neurologic Institute, Phoenix, AZ, United States
| | - Kathleen M. Schmainda
- Department of Biophysics & Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Terry C. Burns
- Departments of Neurologic Surgery and Neuroscience, Mayo Clinic, Rochester, MN, United States
| | - Leland S. Hu
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
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12
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Henriksen OM, del Mar Álvarez-Torres M, Figueiredo P, Hangel G, Keil VC, Nechifor RE, Riemer F, Schmainda KM, Warnert EAH, Wiegers EC, Booth TC. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques. Front Oncol 2022; 12:810263. [PMID: 35359414 PMCID: PMC8961422 DOI: 10.3389/fonc.2022.810263] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 01/05/2022] [Indexed: 01/16/2023] Open
Abstract
Objective Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics). Results High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies. Conclusion Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.
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Affiliation(s)
- Otto M. Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | | | - Patricia Figueiredo
- Department of Bioengineering and Institute for Systems and Robotics-Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Gilbert Hangel
- Department of Neurosurgery, Medical University, Vienna, Austria
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University, Vienna, Austria
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Ruben E. Nechifor
- International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Department of Clinical Psychology and Psychotherapy, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | | | - Evita C. Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Thomas C. Booth
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School of Biomedical Engineering and Imaging Sciences, St. Thomas’ Hospital, King’s College London, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
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13
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Pruis IJ, Koene SR, van der Voort SR, Incekara F, Vincent AJPE, van den Bent MJ, Lycklama à Nijeholt GJ, Nandoe Tewarie RDS, Veldhuijzen van Zanten SEM, Smits M. Noninvasive differentiation of molecular subtypes of adult non-enhancing glioma using MRI perfusion and diffusion parameters. Neurooncol Adv 2022; 4:vdac023. [PMID: 35300151 PMCID: PMC8923005 DOI: 10.1093/noajnl/vdac023] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Background Nonenhancing glioma typically have a favorable outcome, but approximately 19–44% have a highly aggressive course due to a glioblastoma genetic profile. The aim of this retrospective study is to use physiological MRI parameters of both perfusion and diffusion to distinguish the molecular profiles of glioma without enhancement at presentation. Methods Ninety-nine patients with nonenhancing glioma were included, in whom molecular status (including 1p/19q codeletion status and IDH mutation) and preoperative MRI (T2w/FLAIR, dynamic susceptibility-weighted, and diffusion-weighted imaging) were available. Tumors were segmented semiautomatically using ITK-SNAP to derive whole tumor histograms of relative Cerebral Blood Volume (rCBV) and Apparent Diffusion Coefficient (ADC). Tumors were divided into three clinically relevant molecular profiles: IDH mutation (IDHmt) with (n = 40) or without (n = 41) 1p/19q codeletion, and (n = 18) IDH-wildtype (IDHwt). ANOVA, Kruskal-Wallis, and Chi-Square analyses were performed using SPSS. Results rCBV (mean, median, 75th and 85th percentile) and ADC (mean, median, 15th and 25th percentile) showed significant differences across molecular profiles (P < .01). Posthoc analyses revealed that IDHwt and IDHmt 1p/19q codeleted tumors showed significantly higher rCBV compared to IDHmt 1p/19q intact tumors: mean rCBV (mean, SD) 1.46 (0.59) and 1.35 (0.39) versus 1.08 (0.31), P < .05. Also, IDHwt tumors showed significantly lower ADC compared to IDHmt 1p/19q codeleted and IDHmt 1p/19q intact tumors: mean ADC (mean, SD) 1.13 (0.23) versus 1.27 (0.15) and 1.45 (0.20), P < .001). Conclusions A combination of low ADC and high rCBV, reflecting high cellularity and high perfusion respectively, separates IDHwt from in particular IDHmt 1p/19q intact glioma.
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Affiliation(s)
- Ilanah J Pruis
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Stephan R Koene
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | | | - Fatih Incekara
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | | | | | | | | | | | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
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14
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Stokes AM, Bergamino M, Alhilali L, Hu LS, Karis JP, Baxter LC, Bell LC, Quarles CC. Evaluation of single bolus, dual-echo dynamic susceptibility contrast MRI protocols in brain tumor patients. J Cereb Blood Flow Metab 2021; 41:3378-3390. [PMID: 34415211 PMCID: PMC8669280 DOI: 10.1177/0271678x211039597] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is adversely impacted by contrast agent leakage in brain tumors. Using simulations, we previously demonstrated that multi-echo DSC-MRI protocols provide improvements in contrast agent dosing, pulse sequence flexibility, and rCBV accuracy. The purpose of this study is to assess the in-vivo performance of dual-echo acquisitions in patients with brain tumors (n = 59). To verify pulse sequence flexibility, four single-dose dual-echo acquisitions were tested with variations in contrast agent dose, flip angle, and repetition time, and the resulting dual-echo rCBV was compared to standard single-echo rCBV obtained with preload (double-dose). Dual-echo rCBV was comparable to standard double-dose single-echo protocols (mean (standard deviation) tumor rCBV 2.17 (1.28) vs. 2.06 (1.20), respectively). High rCBV similarity was observed (CCC = 0.96), which was maintained across both flip angle (CCC = 0.98) and repetition time (CCC = 0.96) permutations, demonstrating that dual-echo acquisitions provide flexibility in acquisition parameters. Furthermore, a single dual-echo acquisition was shown to enable quantification of both perfusion and permeability metrics. In conclusion, single-dose dual-echo acquisitions provide similar rCBV to standard double-dose single-echo acquisitions, suggesting contrast agent dose can be reduced while providing significant pulse sequence flexibility and complementary tumor perfusion and permeability metrics.
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Affiliation(s)
- Ashley M Stokes
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Maurizio Bergamino
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Lea Alhilali
- Neuroradiology, Southwest Neuroimaging at Barrow Neurological Institute, Phoenix, AZ, USA
| | - Leland S Hu
- Department of Radiology, Division of Neuroradiology, Mayo Clinic Arizona, Phoenix, AZ, USA
| | - John P Karis
- Neuroradiology, Southwest Neuroimaging at Barrow Neurological Institute, Phoenix, AZ, USA
| | - Leslie C Baxter
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, USA.,Department of Radiology, Division of Neuroradiology, Mayo Clinic Arizona, Phoenix, AZ, USA
| | - Laura C Bell
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, USA
| | - C Chad Quarles
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, USA
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15
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Ozturk K, Soylu E, Cayci Z. Differentiation between primary CNS lymphoma and atypical glioblastoma according to major genomic alterations using diffusion and susceptibility-weighted MR imaging. Eur J Radiol 2021; 141:109784. [PMID: 34051685 DOI: 10.1016/j.ejrad.2021.109784] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 04/26/2021] [Accepted: 05/18/2021] [Indexed: 11/30/2022]
Abstract
PURPOSE We aimed to differentiate primary central nervous system lymphoma (PCNSL) from atypical glioblastoma (GB) and distinguish major genomic subtypes between these tumors using susceptibility-weighted imaging (SWI) along with diffusion-weighted imaging (DWI). METHODS Thirty-one immuno-competent patients with PCNSL stratified by BCL2 and MYC rearrangement, and 57 patients with atypical GB (no visible necrosis) grouped according to isocitrate dehydrogenase-1 (IDH1) mutation status underwent 3.0-Tesla MRI before treatment in this retrospective study. Region of interest analysis with apparent diffusion coefficient (ADC) and SWI signal intensity values of the tumors were normalized by dividing those of contralateral white matter. The independent-samples t-test and Kruskal-Wallis test were utilized to compare parameters. The diagnostic ability of each parameter and their optimal combination was evaluated by logistic regression analysis and receiver operating characteristic. RESULTS PCNSL with rearrangement of both MYC and BCL2 (n = 7) [mean relative (r) ADCmean:0.87 ± 0.06, rADCmin:0.72 ± 0.08] demonstrated significantly lower rADCmean, and rADCmin compared to other PCNSLs (n = 24) (rADCmean:1.19 ± 0.18, rADCmin:1.03 ± 0.17;p < 0.001) and GBs (p < 0.001). GB without IDH1 mutation (n = 44) (mean rSWI value:0.95 ± 0.15) demonstrated significantly lower rSWI value compared to GB with IDH1 mutation (n = 13) (rSWI value:1.13 ± 0.09;p < 0.001) and PCNSL (p < 0.001). The incorporation of rADCmean and rSWI parameters distinguished GB with IDH1 mutation [Area under the curve (AUC):0.985] with sensitivity and specificity of 94.3 and 100 % respectively; and PCNSL with rearrangement of both MYC and BCL2 (AUC:0.982) with sensitivity and specificity of 100 % and 95.4 %, respectively. CONCLUSıONS: Combined analysis of SWI and DWI could differentiate atypical GB from PCNSL and distinguish major genomic subtypes between these tumors.
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Affiliation(s)
- Kerem Ozturk
- Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Esra Soylu
- Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Zuzan Cayci
- Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA.
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16
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Schmainda KM, Prah MA, Marques H, Kim E, Barboriak DP, Boxerman JL. Value of dynamic contrast perfusion MRI to predict early response to bevacizumab in newly diagnosed glioblastoma: results from ACRIN 6686 multicenter trial. Neuro Oncol 2021; 23:314-323. [PMID: 32678438 PMCID: PMC7906067 DOI: 10.1093/neuonc/noaa167] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND In Radiation Therapy Oncology Group (RTOG) 0825, a phase III trial of standard therapy with bevacizumab or without (placebo) in newly diagnosed glioblastoma, 44 patients underwent dynamic contrast enhanced (DCE) and/or dynamic susceptibility contrast (DSC) MRI in the American College of Radiology Imaging Network (ACRIN) trial 6686. The association between early changes in relative cerebral blood volume (rCBV) and volume transfer constant (Ktrans) with overall survival (OS) was evaluated. METHODS MRI was performed at postop baseline (S0), immediately before (S1), 1 day after (S2), and 7 weeks after (S3) bevacizumab or placebo initiation. Mean normalized and standardized rCBV (nRCBV, sRCBV) and Ktrans were measured within contrast-enhancing lesion. Wilcoxon rank sum tests compared parameter changes from S1-S2 and S1-S3. Association with OS and progression-free survival (PFS) were determined using Kaplan-Meier and log-rank tests. Treatment response for groups stratified by pretreatment nRCBV (S0, S1) was explored. The intraclass correlation coefficient and repeatability coefficient for the placebo arm (S1-S2) were used to assess repeatability. RESULTS Evaluable were 27-36 datasets per time point. Significant differences between treatment arms were found for changes in nRCBV and sRCBV from S1-S2 and S1-S3, and in Ktrans for S1-S3. Improved PFS (P = 0.05) but not OS (P = 0.46) was observed. High pretreatment rCBV predicted improved OS for bevacizumab-treated patients. Based on the intraclass correlation coefficient, sRCBV (0.92) was more repeatable than nRCBV (0.71) and Ktrans (0.75), consistent with repeatability coefficient values. CONCLUSIONS Bevacizumab significantly changes rCBV but not Ktrans as early as 1 day posttreatment in newly diagnosed glioblastoma unrelated to outcomes. Improvements in clinical trial design to maximize rCBV benefit are indicated.
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Affiliation(s)
- Kathleen M Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin.,Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Melissa A Prah
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Helga Marques
- Department of Biostatistics and Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | - Eunhee Kim
- Merck Research Laboratories, Kenilworth, New Jersey
| | | | - Jerrold L Boxerman
- Department of Diagnostic Imaging, Rhode Island Hospital, and Warren Alpert Medical School of Brown University, Providence, Rhode Island
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17
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Assessment of tumor hypoxia and perfusion in recurrent glioblastoma following bevacizumab failure using MRI and 18F-FMISO PET. Sci Rep 2021; 11:7632. [PMID: 33828310 PMCID: PMC8027395 DOI: 10.1038/s41598-021-84331-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 02/03/2021] [Indexed: 01/16/2023] Open
Abstract
Tumoral hypoxia correlates with worse outcomes in glioblastoma (GBM). While bevacizumab is routinely used to treat recurrent GBM, it may exacerbate hypoxia. Evofosfamide is a hypoxia-targeting prodrug being tested for recurrent GBM. To characterize resistance to bevacizumab and identify those with recurrent GBM who may benefit from evofosfamide, we ascertained MRI features and hypoxia in patients with GBM progression receiving both agents. Thirty-three patients with recurrent GBM refractory to bevacizumab were enrolled. Patients underwent MR and 18F-FMISO PET imaging at baseline and 28 days. Tumor volumes were determined, MRI and 18F-FMISO PET-derived parameters calculated, and Spearman correlations between parameters assessed. Progression-free survival decreased significantly with hypoxic volume [hazard ratio (HR) = 1.67, 95% confidence interval (CI) 1.14 to 2.46, P = 0.009] and increased significantly with time to the maximum value of the residue (Tmax) (HR = 0.54, 95% CI 0.34 to 0.88, P = 0.01). Overall survival decreased significantly with hypoxic volume (HR = 1.71, 95% CI 1.12 to 12.61, p = 0.01), standardized relative cerebral blood volume (srCBV) (HR = 1.61, 95% CI 1.09 to 2.38, p = 0.02), and increased significantly with Tmax (HR = 0.31, 95% CI 0.15 to 0.62, p < 0.001). Decreases in hypoxic volume correlated with longer overall and progression-free survival, and increases correlated with shorter overall and progression-free survival. Hypoxic volume and volume ratio were positively correlated (rs = 0.77, P < 0.0001), as were hypoxia volume and T1 enhancing tumor volume (rs = 0.75, P < 0.0001). Hypoxia is a key biomarker in patients with bevacizumab-refractory GBM. Hypoxia and srCBV were inversely correlated with patient outcomes. These radiographic features may be useful in evaluating treatment and guiding treatment considerations.
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18
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Boxerman JL, Quarles CC, Hu LS, Erickson BJ, Gerstner ER, Smits M, Kaufmann TJ, Barboriak DP, Huang RH, Wick W, Weller M, Galanis E, Kalpathy-Cramer J, Shankar L, Jacobs P, Chung C, van den Bent MJ, Chang S, Al Yung WK, Cloughesy TF, Wen PY, Gilbert MR, Rosen BR, Ellingson BM, Schmainda KM. Consensus recommendations for a dynamic susceptibility contrast MRI protocol for use in high-grade gliomas. Neuro Oncol 2020; 22:1262-1275. [PMID: 32516388 PMCID: PMC7523451 DOI: 10.1093/neuonc/noaa141] [Citation(s) in RCA: 103] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Despite the widespread clinical use of dynamic susceptibility contrast (DSC) MRI, DSC-MRI methodology has not been standardized, hindering its utilization for response assessment in multicenter trials. Recently, the DSC-MRI Standardization Subcommittee of the Jumpstarting Brain Tumor Drug Development Coalition issued an updated consensus DSC-MRI protocol compatible with the standardized brain tumor imaging protocol (BTIP) for high-grade gliomas that is increasingly used in the clinical setting and is the default MRI protocol for the National Clinical Trials Network. After reviewing the basis for controversy over DSC-MRI protocols, this paper provides evidence-based best practices for clinical DSC-MRI as determined by the Committee, including pulse sequence (gradient echo vs spin echo), BTIP-compliant contrast agent dosing (preload and bolus), flip angle (FA), echo time (TE), and post-processing leakage correction. In summary, full-dose preload, full-dose bolus dosing using intermediate (60°) FA and field strength-dependent TE (40-50 ms at 1.5 T, 20-35 ms at 3 T) provides overall best accuracy and precision for cerebral blood volume estimates. When single-dose contrast agent usage is desired, no-preload, full-dose bolus dosing using low FA (30°) and field strength-dependent TE provides excellent performance, with reduced contrast agent usage and elimination of potential systematic errors introduced by variations in preload dose and incubation time.
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Affiliation(s)
- Jerrold L Boxerman
- Department of Diagnostic Imaging, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA
- Representative of the Eastern Cooperative Oncology Group–American College of Radiology Imaging Network (ECOG-ACRIN) Cancer Research Group
- Representative of the American Society of Neuroradiology (ASNR)
- Representative of the American Society of Functional Neuroradiology (ASFNR)
| | - Chad C Quarles
- Department of Neuroimaging Research and Barrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Leland S Hu
- Department of Radiology, Mayo Clinic, Phoenix, Arizona, USA
- Representative of the Alliance for Clinical Trials in Oncology
- Representative of the American Society of Neuroradiology (ASNR)
| | - Bradley J Erickson
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Representative of the Alliance for Clinical Trials in Oncology
- Representative of the RSNA Quantitative Imaging Biomarker Alliance (QIBA)
- Representative of the American Society of Neuroradiology (ASNR)
| | - Elizabeth R Gerstner
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Representative of the Adult Brain Tumor Consortium (ABTC)
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC–University Medical Center Rotterdam, Rotterdam, Netherlands
- Representative of the European Organisation for Research and Treatment of Cancer (EORTC)
| | - Timothy J Kaufmann
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Representative of the Alliance for Clinical Trials in Oncology
| | - Daniel P Barboriak
- Department of Radiology, Duke University School of Medicine, Durham, North Carolina, USA
- Representative of the Eastern Cooperative Oncology Group–American College of Radiology Imaging Network (ECOG-ACRIN) Cancer Research Group
- Representative of the RSNA Quantitative Imaging Biomarker Alliance (QIBA)
- Representative of the American Society of Neuroradiology (ASNR)
| | - Raymond H Huang
- Department of Radiology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Wolfgang Wick
- Department of Neurooncology, National Center of Tumor Disease, University Clinic Heidelberg, Heidelberg, Germany
- Representative of the European Organisation for Research and Treatment of Cancer (EORTC)
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
- Representative of the European Organisation for Research and Treatment of Cancer (EORTC)
| | - Evanthia Galanis
- Division of Medical Oncology, Department of Oncology, Mayo Clinic, Rochester, Minnesota, USA
- Representative of the Alliance for Clinical Trials in Oncology
| | - Jayashree Kalpathy-Cramer
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Lalitha Shankar
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), Bethesda, Maryland, USA
| | - Paula Jacobs
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), Bethesda, Maryland, USA
| | - Caroline Chung
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Representative of the Alliance for Clinical Trials in Oncology
| | - Martin J van den Bent
- Department of Neuro-Oncology, Erasmus MC Cancer Institute, Rotterdam, Netherlands
- Representative of the European Organisation for Research and Treatment of Cancer (EORTC)
| | - Susan Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California, USA
| | - W K Al Yung
- Department of Neuro-Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program and UCLA Brain Tumor Imaging Laboratory (BTIL), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, Massachusetts, USA
- Representative of the Adult Brain Tumor Consortium (ABTC)
| | - Mark R Gilbert
- Neuro-Oncology Branch, National Cancer Institute (NCI), Bethesda, Maryland, USA
- Representative of the Radiation Therapy Oncology Group (RTOG)
| | - Bruce R Rosen
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Benjamin M Ellingson
- UCLA Neuro-Oncology Program and UCLA Brain Tumor Imaging Laboratory (BTIL), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Departments of Radiological Sciences, Psychiatry, and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Representative of the Adult Brain Tumor Consortium (ABTC)
- Representative of the Ivy Consortium for Early Phase Clinical Trials
- Representative of the Eastern Cooperative Oncology Group–American College of Radiology Imaging Network (ECOG-ACRIN) Cancer Research Group
- Representative of the RSNA Quantitative Imaging Biomarker Alliance (QIBA)
- Representative of the American Society of Neuroradiology (ASNR)
| | - Kathleen M Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Representative of the Eastern Cooperative Oncology Group–American College of Radiology Imaging Network (ECOG-ACRIN) Cancer Research Group
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Perfusion and diffusion in meningioma tumors: a preliminary multiparametric analysis with Dynamic Susceptibility Contrast and IntraVoxel Incoherent Motion MRI. Magn Reson Imaging 2020; 67:69-78. [DOI: 10.1016/j.mri.2019.12.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2019] [Revised: 11/15/2019] [Accepted: 12/05/2019] [Indexed: 12/19/2022]
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20
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Hoxworth JM, Eschbacher JM, Gonzales AC, Singleton KW, Leon GD, Smith KA, Stokes AM, Zhou Y, Mazza GL, Porter AB, Mrugala MM, Zimmerman RS, Bendok BR, Patra DP, Krishna C, Boxerman JL, Baxter LC, Swanson KR, Quarles CC, Schmainda KM, Hu LS. Performance of Standardized Relative CBV for Quantifying Regional Histologic Tumor Burden in Recurrent High-Grade Glioma: Comparison against Normalized Relative CBV Using Image-Localized Stereotactic Biopsies. AJNR Am J Neuroradiol 2020; 41:408-415. [PMID: 32165359 DOI: 10.3174/ajnr.a6486] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 12/23/2019] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Perfusion MR imaging measures of relative CBV can distinguish recurrent tumor from posttreatment radiation effects in high-grade gliomas. Currently, relative CBV measurement requires normalization based on user-defined reference tissues. A recently proposed method of relative CBV standardization eliminates the need for user input. This study compares the predictive performance of relative CBV standardization against relative CBV normalization for quantifying recurrent tumor burden in high-grade gliomas relative to posttreatment radiation effects. MATERIALS AND METHODS We recruited 38 previously treated patients with high-grade gliomas (World Health Organization grades III or IV) undergoing surgical re-resection for new contrast-enhancing lesions concerning for recurrent tumor versus posttreatment radiation effects. We recovered 112 image-localized biopsies and quantified the percentage of histologic tumor content versus posttreatment radiation effects for each sample. We measured spatially matched normalized and standardized relative CBV metrics (mean, median) and fractional tumor burden for each biopsy. We compared relative CBV performance to predict tumor content, including the Pearson correlation (r), against histologic tumor content (0%-100%) and the receiver operating characteristic area under the curve for predicting high-versus-low tumor content using binary histologic cutoffs (≥50%; ≥80% tumor). RESULTS Across relative CBV metrics, fractional tumor burden showed the highest correlations with tumor content (0%-100%) for normalized (r = 0.63, P < .001) and standardized (r = 0.66, P < .001) values. With binary cutoffs (ie, ≥50%; ≥80% tumor), predictive accuracies were similar for both standardized and normalized metrics and across relative CBV metrics. Median relative CBV achieved the highest area under the curve (normalized = 0.87, standardized = 0.86) for predicting ≥50% tumor, while fractional tumor burden achieved the highest area under the curve (normalized = 0.77, standardized = 0.80) for predicting ≥80% tumor. CONCLUSIONS Standardization of relative CBV achieves similar performance compared with normalized relative CBV and offers an important step toward workflow optimization and consensus methodology.
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Affiliation(s)
- J M Hoxworth
- From the Departments of Radiology (J.M.H., Y.Z., L.S.H.)
| | | | | | - K W Singleton
- Precision Neurotherapeutics Lab (K.W.S., G.D.L., B.R.B., K.R.S.), Mayo Clinic in Arizona, Phoenix, Arizona
| | - G D Leon
- Precision Neurotherapeutics Lab (K.W.S., G.D.L., B.R.B., K.R.S.), Mayo Clinic in Arizona, Phoenix, Arizona
| | - K A Smith
- Keller Center for Imaging Innovation (A.M.S.), Barrow Neurological Institute, Phoenix, Arizona
| | - A M Stokes
- Keller Center for Imaging Innovation (A.M.S.), Barrow Neurological Institute, Phoenix, Arizona
| | - Y Zhou
- From the Departments of Radiology (J.M.H., Y.Z., L.S.H.)
| | - G L Mazza
- Department of Health Sciences Research (G.L.M.), Division of Biomedical Statistics and Informatics, Mayo Clinic Scottsdale, Scottsdale, Arizona
| | | | | | | | - B R Bendok
- Precision Neurotherapeutics Lab (K.W.S., G.D.L., B.R.B., K.R.S.), Mayo Clinic in Arizona, Phoenix, Arizona
| | - D P Patra
- Departments of Neurosurgery (D.P.P.)
| | | | - J L Boxerman
- Department of Diagnostic Imaging (J.L.B.), Rhode Island Hospital, Providence, Rhode Island
| | - L C Baxter
- Neuropsychology (L.C.B.), Mayo Clinic Hospital, Phoenix, Arizona
| | - K R Swanson
- Precision Neurotherapeutics Lab (K.W.S., G.D.L., B.R.B., K.R.S.), Mayo Clinic in Arizona, Phoenix, Arizona
| | | | - K M Schmainda
- Department of Radiology (K.M.S.), Medical College of Wisconsin, Milwaukee, Wisconsin
| | - L S Hu
- From the Departments of Radiology (J.M.H., Y.Z., L.S.H.)
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21
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Schmainda KM, Prah MA, Zhang Z, Snyder BS, Rand SD, Jensen TR, Barboriak DP, Boxerman JL. Quantitative Delta T1 (dT1) as a Replacement for Adjudicated Central Reader Analysis of Contrast-Enhancing Tumor Burden: A Subanalysis of the American College of Radiology Imaging Network 6677/Radiation Therapy Oncology Group 0625 Multicenter Brain Tumor Trial. AJNR Am J Neuroradiol 2019; 40:1132-1139. [PMID: 31248863 DOI: 10.3174/ajnr.a6110] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Accepted: 05/08/2019] [Indexed: 01/08/2023]
Abstract
BACKGROUND AND PURPOSE Brain tumor clinical trials requiring solid tumor assessment typically rely on the 2D manual delineation of enhancing tumors by ≥2 expert readers, a time-consuming step with poor interreader agreement. As a solution, we developed quantitative dT1 maps for the delineation of enhancing lesions. This retrospective analysis compares dT1 with 2D manual delineation of enhancing tumors acquired at 2 time points during the post therapeutic surveillance period of the American College of Radiology Imaging Network 6677/Radiation Therapy Oncology Group 0625 (ACRIN 6677/RTOG 0625) clinical trial. MATERIALS AND METHODS Patients enrolled in ACRIN 6677/RTOG 0625, a multicenter, randomized Phase II trial of bevacizumab in recurrent glioblastoma, underwent standard MR imaging before and after treatment initiation. For 123 patients from 23 institutions, both 2D manual delineation of enhancing tumors and dT1 datasets were evaluable at weeks 8 (n = 74) and 16 (n = 57). Using dT1, we assessed the radiologic response and progression at each time point. Percentage agreement with adjudicated 2D manual delineation of enhancing tumor reads and association between progression status and overall survival were determined. RESULTS For identification of progression, dT1 and adjudicated 2D manual delineation of enhancing tumor reads were in perfect agreement at week 8, with 73.7% agreement at week 16. Both methods showed significant differences in overall survival at each time point. When nonprogressors were further divided into responders versus nonresponders/nonprogressors, the agreement decreased to 70.3% and 52.6%, yet dT1 showed a significant difference in overall survival at week 8 (P = .01), suggesting that dT1 may provide greater sensitivity for stratifying subpopulations. CONCLUSIONS This study shows that dT1 can predict early progression comparable with the standard method but offers the potential for substantial time and cost savings for clinical trials.
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Affiliation(s)
- K M Schmainda
- From the Departments of Biophysics (K.M.S., M.A.P.) .,Radiology (K.M.S., S.D.R.), Medical College of Wisconsin, Milwaukee, Wisconsin
| | - M A Prah
- From the Departments of Biophysics (K.M.S., M.A.P.)
| | - Z Zhang
- Department of Biostatistics (Z.Z.).,Center for Statistical Sciences (Z.Z., B.S.S.), Brown University School of Public Health, Providence, Rhode Island
| | - B S Snyder
- Center for Statistical Sciences (Z.Z., B.S.S.), Brown University School of Public Health, Providence, Rhode Island
| | - S D Rand
- Radiology (K.M.S., S.D.R.), Medical College of Wisconsin, Milwaukee, Wisconsin
| | - T R Jensen
- Jensen Informatics LLC (T.R.J.), Brookfield, Wisconsin
| | - D P Barboriak
- Department of Radiology (D.P.B.), Duke University Medical Center, Durham, North Carolina.,Department of Diagnostic Imaging (D.P.B., J.L.B.), Rhode Island Hospital, Providence, Rhode Island
| | - J L Boxerman
- Department of Diagnostic Imaging (D.P.B., J.L.B.), Rhode Island Hospital, Providence, Rhode Island.,Warren Alpert Medical School of Brown University (J.L.B.), Providence, Rhode Island
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22
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Schmainda KM, Prah MA, Hu LS, Quarles CC, Semmineh N, Rand SD, Connelly JM, Anderies B, Zhou Y, Liu Y, Logan B, Stokes A, Baird G, Boxerman JL. Moving Toward a Consensus DSC-MRI Protocol: Validation of a Low-Flip Angle Single-Dose Option as a Reference Standard for Brain Tumors. AJNR Am J Neuroradiol 2019; 40:626-633. [PMID: 30923088 DOI: 10.3174/ajnr.a6015] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Accepted: 01/18/2019] [Indexed: 12/21/2022]
Abstract
BACKGROUND AND PURPOSE DSC-MR imaging using preload, intermediate (60°) flip angle and postprocessing leakage correction has gained traction as a standard methodology. Simulations suggest that DSC-MR imaging with flip angle = 30° and no preload yields relative CBV practically equivalent to the reference standard. This study tested this hypothesis in vivo. MATERIALS AND METHODS Eighty-four patients with brain lesions were enrolled in this 3-institution study. Forty-three patients satisfied the inclusion criteria. DSC-MR imaging (3T, single-dose gadobutrol, gradient recalled-echo-EPI, TE = 20-35 ms, TR = 1.2-1.63 seconds) was performed twice for each patient, with flip angle = 30°-35° and no preload (P-), which provided preload (P+) for the subsequent intermediate flip angle = 60°. Normalized relative CBV and standardized relative CBV maps were generated, including postprocessing with contrast agent leakage correction (C+) and without (C-) contrast agent leakage correction. Contrast-enhancing lesion volume, mean relative CBV, and contrast-to-noise ratio obtained with 30°/P-/C-, 30°/P-/C+, and 60°/P+/C- were compared with 60°/P+/C+ using the Lin concordance correlation coefficient and Bland-Altman analysis. Equivalence between the 30°/P-/C+ and 60°/P+/C+ protocols and the temporal SNR for the 30°/P- and 60°/P+ DSC-MR imaging data was also determined. RESULTS Compared with 60°/P+/C+, 30°/P-/C+ had closest mean standardized relative CBV (P = .61), highest Lin concordance correlation coefficient (0.96), and lowest Bland-Altman bias (μ = 1.89), compared with 30°/P-/C- (P = .02, Lin concordance correlation coefficient = 0.59, μ = 14.6) and 60°/P+/C- (P = .03, Lin concordance correlation coefficient = 0.88, μ = -10.1) with no statistical difference in contrast-to-noise ratios across protocols. The normalized relative CBV and standardized relative CBV were statistically equivalent at the 10% level using either the 30°/P-/C+ or 60°/P+/C+ protocols. Temporal SNR was not significantly different for 30°/P- and 60°/P+ (P = .06). CONCLUSIONS Tumor relative CBV derived from low-flip angle, no-preload DSC-MR imaging with leakage correction is an attractive single-dose alternative to the higher dose reference standard.
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Affiliation(s)
- K M Schmainda
- From the Departments of Biophysics (K.M.S., M.A.P.) .,Radiology (K.M.S., S.D.R.)
| | - M A Prah
- From the Departments of Biophysics (K.M.S., M.A.P.)
| | - L S Hu
- Departments of Radiology (L.S.H., Y.Z.)
| | - C C Quarles
- Division of Imaging Research (C.C.Q., N.S., A.S.), Barrow Neurological Institute, Phoenix, Arizona
| | - N Semmineh
- Division of Imaging Research (C.C.Q., N.S., A.S.), Barrow Neurological Institute, Phoenix, Arizona
| | | | | | - B Anderies
- Neurosurgery (B.A.), Mayo Clinic, Scottsdale, Arizona
| | - Y Zhou
- Departments of Radiology (L.S.H., Y.Z.)
| | - Y Liu
- Division of Biostatistics, Institute for Health and Society (Y.L., B.L.), Medical College of Wisconsin, Milwaukee, Wisconsin
| | - B Logan
- Division of Biostatistics, Institute for Health and Society (Y.L., B.L.), Medical College of Wisconsin, Milwaukee, Wisconsin
| | - A Stokes
- Division of Imaging Research (C.C.Q., N.S., A.S.), Barrow Neurological Institute, Phoenix, Arizona
| | - G Baird
- Department of Diagnostic Imaging (J.L.B., G.B.), Rhode Island Hospital and Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - J L Boxerman
- Department of Diagnostic Imaging (J.L.B., G.B.), Rhode Island Hospital and Warren Alpert Medical School of Brown University, Providence, Rhode Island
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Qin L, Li X, Li A, Cheng S, Qu J, Reinshagen K, Hu J, Himes N, Lu G, Xu X, Young GS. Clinical Validation of Automatable Gaussian Normalized CBV in Brain Tumor Analysis: Superior Reproducibility and Slightly Better Association with Survival than Current Standard Manual Normal Appearing White Matter Normalization. Transl Oncol 2018; 11:1398-1405. [PMID: 30216765 PMCID: PMC6138997 DOI: 10.1016/j.tranon.2018.07.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 07/23/2018] [Accepted: 07/30/2018] [Indexed: 10/28/2022] Open
Abstract
PURPOSE To validate Gaussian normalized cerebral blood volume (GN-nCBV) by association with overall survival (OS) in newly diagnosed glioblastoma patients and compare this association with current standard white matter normalized cerebral blood volume (WN-nCBV). METHODS We retrieved spin-echo echo-planar dynamic susceptibility contrast MRI acquired after maximal resection and prior to radiation therapy between 2006 and 2011 in 51 adult patients (28 male, 23 female; age 23-87 years) with newly diagnosed glioblastoma. Software code was developed in house to perform Gaussian normalization of CBV to the standard deviation of the whole brain CBV. Three expert readers manually selected regions of interest in tumor and normal-appearing white matter on CBV maps. Receiver operating characteristics (ROC) curves associating nCBV with 15-month OS were calculated for both GN-nCBV and WN-nCBV. Reproducibility and interoperator variability were compared using within-subject coefficient of variation (wCV) and intraclass correlation coefficients (ICCs). RESULTS GN-nCBV ICC (≥0.82) and wCV (≤21%) were superior to WN-nCBV ICC (0.54-0.55) and wCV (≥46%). The area under the ROC curve analysis demonstrated both GN-nCBV and WN-nCBV to be good predictors of OS, but GN-nCBV was consistently superior, although the difference was not statistically significant. CONCLUSION GN-nCBV has a slightly better association with clinical gold standard OS than conventional WM-nCBV in our glioblastoma patient cohort. This equivalent or superior validity, combined with the advantages of higher reproducibility, lower interoperator variability, and easier automation, makes GN-nCBV superior to WM-nCBV for clinical and research use in glioma patients. We recommend widespread adoption and incorporation of GN-nCBV into commercial dynamic susceptibility contrast processing software.
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Affiliation(s)
- Lei Qin
- Dana-Farber Cancer Institute, Department of Imaging, Boston, MA, USA; Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Xiang Li
- Brigham and Women's Hospital, Department of Radiology, Boston, MA, USA; Affiliated Cancer Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, Henan, China
| | - Angie Li
- Brigham and Women's Hospital, Department of Radiology, Boston, MA, USA; The Robert Larner, M.D. College of Medicine at the University of Vermont, Burlington, VT, USA
| | - Suchun Cheng
- Dana-Farber Cancer Institute, Department of Biostatistics and Computational Biology, Boston, MA, USA
| | - Jinrong Qu
- Brigham and Women's Hospital, Department of Radiology, Boston, MA, USA; Affiliated Cancer Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, Henan, China
| | - Katherine Reinshagen
- Harvard Medical School, Department of Radiology, Boston, MA, USA; Brigham and Women's Hospital, Department of Radiology, Boston, MA, USA; Massachusetts Eye and Ear Infirmary, Department of Radiology, Boston, MA, USA
| | - Jiani Hu
- Dana-Farber Cancer Institute, Department of Biostatistics and Computational Biology, Boston, MA, USA
| | - Nathan Himes
- Brigham and Women's Hospital, Department of Radiology, Boston, MA, USA; Medical Imaging of Lehigh Valley, Lehigh Valley Hospital, Allentown, PA, USA
| | - Gao Lu
- Brigham and Women's Hospital, Department of Radiology, Boston, MA, USA; Peking Union Medical College Hospital, Department of Neurosurgery, Beijing, China
| | - Xiaoyin Xu
- Peking Union Medical College Hospital, Department of Neurosurgery, Beijing, China; Peking Union Medical College Hospital, Department of Neurosurgery, Beijing, China
| | - Geoffrey S Young
- Dana-Farber Cancer Institute, Department of Imaging, Boston, MA, USA; Harvard Medical School, Department of Radiology, Boston, MA, USA; Brigham and Women's Hospital, Department of Radiology, Boston, MA, USA.
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Choi CH, Yi KS, Lee SR, Lee Y, Jeon CY, Hwang J, Lee C, Choi SS, Lee HJ, Cha SH. A novel voxel-wise lesion segmentation technique on 3.0-T diffusion MRI of hyperacute focal cerebral ischemia at 1 h after permanent MCAO in rats. J Cereb Blood Flow Metab 2018; 38:1371-1383. [PMID: 28598225 PMCID: PMC6092770 DOI: 10.1177/0271678x17714179] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
To assess hyperacute focal cerebral ischemia in rats on 3.0-Tesla diffusion-weighted imaging (DWI), we developed a novel voxel-wise lesion segmentation technique that overcomes intra- and inter-subject variation in apparent diffusion coefficient (ADC) distribution. Our novel technique involves the following: (1) intensity normalization including determination of the optimal type of region of interest (ROI) and its intra- and inter-subject validation, (2) verification of focal cerebral ischemic lesions at 1 h with gross and high-magnification light microscopy of hematoxylin-eosin (H&E) pathology, (3) voxel-wise segmentation on ADC with various thresholds, and (4) calculation of dice indices (DIs) to compare focal cerebral ischemic lesions at 1 h defined by ADC and matching H&E pathology. The best coefficient of variation was the mode of the left hemisphere after normalization using whole left hemispheric ROI, which showed lower intra- (2.54 ± 0.72%) and inter-subject (2.67 ± 0.70%) values than the original. Focal ischemic lesion at 1 h after middle cerebral artery occlusion (MCAO) was confirmed on both gross and microscopic H&E pathology. The 83 relative threshold of normalized ADC showed the highest mean DI (DI = 0.820 ± 0.075). We could evaluate hyperacute ischemic lesions at 1 h more reliably on 3-Tesla DWI in rat brains.
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Affiliation(s)
- Chi-Hoon Choi
- 1 Department of Radiology, Chungbuk National University Hospital, Cheongju-si, Chungcheongbuk-do, Republic of Korea
| | - Kyung Sik Yi
- 1 Department of Radiology, Chungbuk National University Hospital, Cheongju-si, Chungcheongbuk-do, Republic of Korea
| | - Sang-Rae Lee
- 2 National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology, Cheongju-si, Chungcheongbuk-do, Republic of Korea
| | - Youngjeon Lee
- 2 National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology, Cheongju-si, Chungcheongbuk-do, Republic of Korea
| | - Chang-Yeop Jeon
- 2 National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology, Cheongju-si, Chungcheongbuk-do, Republic of Korea
| | - Jinwoo Hwang
- 3 Clinical Science, Philips Healthcare, Seoul, Republic of Korea
| | - Chulhyun Lee
- 4 Bioimaging Research Team, Korea Basic Science Institute, Cheongju-si, Chungcheongbuk-do, Republic of Korea
| | - Sung Sik Choi
- 5 Medical Research Institute, Chung-Ang University, Seoul, Republic of Korea
| | - Hong Jun Lee
- 5 Medical Research Institute, Chung-Ang University, Seoul, Republic of Korea
| | - Sang-Hoon Cha
- 1 Department of Radiology, Chungbuk National University Hospital, Cheongju-si, Chungcheongbuk-do, Republic of Korea.,6 College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju-si, Chungcheongbuk-do, Republic of Korea
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25
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Schmainda KM, Prah MA, Rand SD, Liu Y, Logan B, Muzi M, Rane SD, Da X, Yen YF, Kalpathy-Cramer J, Chenevert TL, Hoff B, Ross B, Cao Y, Aryal MP, Erickson B, Korfiatis P, Dondlinger T, Bell L, Hu L, Kinahan PE, Quarles CC. Multisite Concordance of DSC-MRI Analysis for Brain Tumors: Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project. AJNR Am J Neuroradiol 2018; 39:1008-1016. [PMID: 29794239 DOI: 10.3174/ajnr.a5675] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 02/07/2018] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Standard assessment criteria for brain tumors that only include anatomic imaging continue to be insufficient. While numerous studies have demonstrated the value of DSC-MR imaging perfusion metrics for this purpose, they have not been incorporated due to a lack of confidence in the consistency of DSC-MR imaging metrics across sites and platforms. This study addresses this limitation with a comparison of multisite/multiplatform analyses of shared DSC-MR imaging datasets of patients with brain tumors. MATERIALS AND METHODS DSC-MR imaging data were collected after a preload and during a bolus injection of gadolinium contrast agent using a gradient recalled-echo-EPI sequence (TE/TR = 30/1200 ms; flip angle = 72°). Forty-nine low-grade (n = 13) and high-grade (n = 36) glioma datasets were uploaded to The Cancer Imaging Archive. Datasets included a predetermined arterial input function, enhancing tumor ROIs, and ROIs necessary to create normalized relative CBV and CBF maps. Seven sites computed 20 different perfusion metrics. Pair-wise agreement among sites was assessed with the Lin concordance correlation coefficient. Distinction of low- from high-grade tumors was evaluated with the Wilcoxon rank sum test followed by receiver operating characteristic analysis to identify the optimal thresholds based on sensitivity and specificity. RESULTS For normalized relative CBV and normalized CBF, 93% and 94% of entries showed good or excellent cross-site agreement (0.8 ≤ Lin concordance correlation coefficient ≤ 1.0). All metrics could distinguish low- from high-grade tumors. Optimum thresholds were determined for pooled data (normalized relative CBV = 1.4, sensitivity/specificity = 90%:77%; normalized CBF = 1.58, sensitivity/specificity = 86%:77%). CONCLUSIONS By means of DSC-MR imaging data obtained after a preload of contrast agent, substantial consistency resulted across sites for brain tumor perfusion metrics with a common threshold discoverable for distinguishing low- from high-grade tumors.
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Affiliation(s)
- K M Schmainda
- From the Department of Radiology (K.M.S., M.A.P., S.D.R.)
| | - M A Prah
- From the Department of Radiology (K.M.S., M.A.P., S.D.R.)
| | - S D Rand
- From the Department of Radiology (K.M.S., M.A.P., S.D.R.).,Department of Radiology (M.M., S.D.R., P.E.K.), University of Washington, Seattle, Washington
| | - Y Liu
- Division of Biostatistics (Y.L., B.L.), Institute for Health and Society, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - B Logan
- Division of Biostatistics (Y.L., B.L.), Institute for Health and Society, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - M Muzi
- Department of Radiology (M.M., S.D.R., P.E.K.), University of Washington, Seattle, Washington
| | - S D Rane
- From the Department of Radiology (K.M.S., M.A.P., S.D.R.)
| | - X Da
- Department of Radiology (X.D.), Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts
| | - Y-F Yen
- Athinoula A. Martinos Center for Biomedical Imaging (Y.-F.Y., J.K.-C.), Department of Radiology, Harvard Medical School/Massachusetts General Hospital, Charlestown, Massachusetts
| | - J Kalpathy-Cramer
- Athinoula A. Martinos Center for Biomedical Imaging (Y.-F.Y., J.K.-C.), Department of Radiology, Harvard Medical School/Massachusetts General Hospital, Charlestown, Massachusetts
| | | | - B Hoff
- Department of Radiology (T.L.C., B.H., B.R.)
| | - B Ross
- Department of Radiology (T.L.C., B.H., B.R.)
| | - Y Cao
- Departments of Radiation Oncology, Radiology, and Biomedical Engineering (Y.C., M.P.A.), University of Michigan, Ann Arbor, Michigan
| | - M P Aryal
- Departments of Radiation Oncology, Radiology, and Biomedical Engineering (Y.C., M.P.A.), University of Michigan, Ann Arbor, Michigan
| | - B Erickson
- Department of Radiology (B.E., P.K.), Mayo Clinic, Rochester, Minnesota
| | - P Korfiatis
- Department of Radiology (B.E., P.K.), Mayo Clinic, Rochester, Minnesota
| | - T Dondlinger
- Imaging Biometrics LLC (T.D.), Elm Grove, Wisconsin
| | - L Bell
- Division of Imaging Research (L.B., C.C.Q.), Barrow Neurological Institute, Phoenix, Arizona
| | - L Hu
- Department of Radiology (L.H.), Mayo Clinic, Scottsdale, Arizona
| | - P E Kinahan
- Department of Radiology (M.M., S.D.R., P.E.K.), University of Washington, Seattle, Washington
| | - C C Quarles
- Division of Imaging Research (L.B., C.C.Q.), Barrow Neurological Institute, Phoenix, Arizona
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Oei MTH, Meijer FJA, Mordang JJ, Smit EJ, Idema AJS, Goraj BM, Laue HOA, Prokop M, Manniesing R. Observer variability of reference tissue selection for relativecerebral blood volume measurements in glioma patients. Eur Radiol 2018; 28:3902-3911. [PMID: 29572637 PMCID: PMC6096614 DOI: 10.1007/s00330-018-5353-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Revised: 12/27/2017] [Accepted: 01/23/2018] [Indexed: 11/05/2022]
Abstract
Objectives To assess observer variability of different reference tissues used for relative CBV (rCBV) measurements in DSC-MRI of glioma patients. Methods In this retrospective study, three observers measured rCBV in DSC-MR images of 44 glioma patients on two occasions. rCBV is calculated by the CBV in the tumour hotspot/the CBV of a reference tissue at the contralateral side for normalization. One observer annotated the tumour hotspot that was kept constant for all measurements. All observers annotated eight reference tissues of normal white and grey matter. Observer variability was evaluated using the intraclass correlation coefficient (ICC), coefficient of variation (CV) and Bland-Altman analyses. Results For intra-observer, the ICC ranged from 0.50–0.97 (fair–excellent) for all reference tissues. The CV ranged from 5.1–22.1 % for all reference tissues and observers. For inter-observer, the ICC for all pairwise observer combinations ranged from 0.44–0.92 (poor–excellent). The CV ranged from 8.1–31.1 %. Centrum semiovale was the only reference tissue that showed excellent intra- and inter-observer agreement (ICC>0.85) and lowest CVs (<12.5 %). Bland-Altman analyses showed that mean differences for centrum semiovale were close to zero. Conclusion Selecting contralateral centrum semiovale as reference tissue for rCBV provides the lowest observer variability. Key Points • Reference tissue selection for rCBV measurements adds variability to rCBV measurements. • rCBV measurements vary depending on the choice of reference tissue. • Observer variability of reference tissue selection varies between poor and excellent. • Centrum semiovale as reference tissue for rCBV provides the lowest observer variability.
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Affiliation(s)
- Marcel T H Oei
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.
| | - Frederick J A Meijer
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Jan-Jurre Mordang
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Ewoud J Smit
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Albert J S Idema
- Department of Neurosurgery, Radboudumc, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Bozena M Goraj
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | | | - Mathias Prokop
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
| | - Rashindra Manniesing
- Department of Radiology and Nuclear Medicine, Radboudumc, Geert Grooteplein 10, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands
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Prah MA, Al-Gizawiy MM, Mueller WM, Cochran EJ, Hoffmann RG, Connelly JM, Schmainda KM. Spatial discrimination of glioblastoma and treatment effect with histologically-validated perfusion and diffusion magnetic resonance imaging metrics. J Neurooncol 2017; 136:13-21. [PMID: 28900832 DOI: 10.1007/s11060-017-2617-3] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2017] [Accepted: 09/04/2017] [Indexed: 11/30/2022]
Abstract
The goal of this study is to spatially discriminate tumor from treatment effect (TE), within the contrast-enhancing lesion, for brain tumor patients at all stages of treatment. To this end, the diagnostic accuracy of MRI-derived diffusion and perfusion parameters to distinguish pure TE from pure glioblastoma (GBM) was determined utilizing spatially-correlated biopsy samples. From July 2010 through June 2015, brain tumor patients who underwent pre-operative DWI and DSC-MRI and stereotactic image-guided biopsy were considered for inclusion in this IRB-approved study. MRI-derived parameter maps included apparent diffusion coefficient (ADC), normalized cerebral blood flow (nCBF), normalized and standardized relative cerebral blood volume (nRCBV, sRCBV), peak signal-height (PSR) and percent signal-recovery (PSR). These were co-registered to the Stealth MRI and median values extracted from the spatially-matched biopsy regions. A ROC analysis accounting for multiple subject samples was performed, and the optimal threshold for distinguishing TE from GBM determined for each parameter. Histopathologic diagnosis of pure TE (n = 10) or pure GBM (n = 34) was confirmed in tissue samples from 15 consecutive subjects with analyzable data. Perfusion thresholds of sRCBV (3575; SN/SP% = 79.4/90.0), nRCBV (1.13; SN/SP% = 82.1/90.0), and nCBF (1.05; SN/SP% = 79.4/80.0) distinguished TE from GBM (P < 0.05), whereas ADC, PSR, and PH could not (P > 0.05). The thresholds for CBF and CBV can be applied to lesions with any admixture of tumor or treatment effect, enabling the identification of true tumor burden within enhancing lesions. This approach overcomes current limitations of averaging values from both tumor and TE for quantitative assessments.
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Affiliation(s)
- Melissa A Prah
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI, 53226, USA
| | - Mona M Al-Gizawiy
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI, 53226, USA
| | - Wade M Mueller
- Department of Neurosurgery, Medical College of Wisconsin, 9200 W. Wisconsin Avenue, Milwaukee, WI, 53226, USA
| | - Elizabeth J Cochran
- Department of Pathology, Medical College of Wisconsin, 9200 W. Wisconsin Avenue, Milwaukee, WI, 53226, USA
| | - Raymond G Hoffmann
- Department of Pediatrics, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI, 53226, USA
| | - Jennifer M Connelly
- Department of Neurology, Medical College of Wisconsin, 9200 W. Wisconsin Avenue, Milwaukee, WI, 53226, USA
| | - Kathleen M Schmainda
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI, 53226, USA. .,Department of Biophysics, Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI, 53226, USA.
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28
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Schindler S, Schreiber J, Bazin PL, Trampel R, Anwander A, Geyer S, Schönknecht P. Intensity standardisation of 7T MR images for intensity-based segmentation of the human hypothalamus. PLoS One 2017; 12:e0173344. [PMID: 28253330 PMCID: PMC5333904 DOI: 10.1371/journal.pone.0173344] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Accepted: 02/20/2017] [Indexed: 11/25/2022] Open
Abstract
The high spatial resolution of 7T MRI enables us to identify subtle volume changes in brain structures, providing potential biomarkers of mental disorders. Most volumetric approaches require that similar intensity values represent similar tissue types across different persons. By applying colour-coding to T1-weighted MP2RAGE images, we found that the high measurement accuracy achieved by high-resolution imaging may be compromised by inter-individual variations in the image intensity. To address this issue, we analysed the performance of five intensity standardisation techniques in high-resolution T1-weighted MP2RAGE images. Twenty images with extreme intensities in the GM and WM were standardised to a representative reference image. We performed a multi-level evaluation with a focus on the hypothalamic region—analysing the intensity histograms as well as the actual MR images, and requiring that the correlation between the whole-brain tissue volumes and subject age be preserved during standardisation. The results were compared with T1 maps. Linear standardisation using subcortical ROIs of GM and WM provided good results for all evaluation criteria: it improved the histogram alignment within the ROIs and the average image intensity within the ROIs and the whole-brain GM and WM areas. This method reduced the inter-individual intensity variation of the hypothalamic boundary by more than half, outperforming all other methods, and kept the original correlation between the GM volume and subject age intact. Mixed results were obtained for the other four methods, which sometimes came at the expense of unwarranted changes in the age-related pattern of the GM volume. The mapping of the T1 relaxation time with the MP2RAGE sequence is advertised as being especially robust to bias field inhomogeneity. We found little evidence that substantiated the T1 map’s theoretical superiority over the T1-weighted images regarding the inter-individual image intensity homogeneity.
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Affiliation(s)
- Stephanie Schindler
- Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- * E-mail:
| | - Jan Schreiber
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Pierre-Louis Bazin
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Alfred Anwander
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Stefan Geyer
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Peter Schönknecht
- Department of Psychiatry and Psychotherapy, University Hospital Leipzig, Leipzig, Germany
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Belliveau JG, Bauman G, Macdonald DR. Detecting tumor progression in glioma: current standards and new techniques. Expert Rev Anticancer Ther 2016; 16:1177-1188. [PMID: 27661768 DOI: 10.1080/14737140.2016.1240621] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
INTRODUCTION The post-treatment monitoring of glioma patients remains an area of active research and development. Conventional imaging with MRI is a highly sensitive modality for detecting and monitoring primary and secondary brain tumors and includes multi-parametric sequences to better characterize the disease. Standardized schemes for measuring response to treatment are in wide clinical use; however, the introduction of new therapeutics have introduced new patterns of response that can confound interpretation of conventional MRI and can cause uncertainty in the proper management following therapy. Areas covered: A summary of current and evolving techniques for assessing glioma response in this era of new therapies that address these challenges are presented in this review. While this review focuses more on clinical and early clinical methodologies for MRI and nuclear medicine techniques some promising pre-clinical techniques are also presented. Expert commentary: While successful single institution results have been widely reported in the literature, any new methodologies must be undertaken in multi-center settings. Additionally, the need for standardization of protocols in quantitative measured are an important area that must be addressed for new and promising techniques to be implemented to a wide array of patients.
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Affiliation(s)
- Jean-Guy Belliveau
- a Department of Medical Biophysics , University of Western Ontario , London , ON , Canada
| | - Glenn Bauman
- b Department of Medical Biophysics and Oncology , University of Western Ontario , London , ON , Canada
| | - David R Macdonald
- c Department of Oncology , University of Western Ontario , London , ON , Canada
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Salice S, Esposito R, Ciavardelli D, delli Pizzi S, di Bastiano R, Tartaro A. Combined 3 Tesla MRI Biomarkers Improve the Differentiation between Benign vs Malignant Single Ring Enhancing Brain Masses. PLoS One 2016; 11:e0159047. [PMID: 27410226 PMCID: PMC4943588 DOI: 10.1371/journal.pone.0159047] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2015] [Accepted: 06/27/2016] [Indexed: 01/23/2023] Open
Abstract
PURPOSE To evaluate whether the combination of imaging biomarkers obtained by means of different 3 Tesla (3T) Magnetic Resonance Imaging (MRI) advanced techniques can improve the diagnostic accuracy in the differentiation between benign and malignant single ring-enhancing brain masses. MATERIALS AND METHODS 14 patients presenting at conventional 3T MRI single brain mass with similar appearance as regard ring enhancement, presence of peri-lesional edema and absence of hemorrhage signs were included in the study. All lesions were histologically proven: 5 pyogenic abscesses, 6 glioblastomas, and 3 metastases. MRI was performed at 3 Tesla and included Diffusion Weighted Imaging (DWI), Dynamic Susceptibility Contrast -Perfusion Weighted Imaging (DSC-PWI), Magnetic Resonance Spectroscopy (MRS), and Diffusion Tensor Imaging (DTI). Imaging biomarkers derived by those advanced techniques [Cerebral Blood Flow (CBF), relative Cerebral Blood Volume (rCBV), relative Main Transit Time (rMTT), Choline (Cho), Creatine (Cr), Succinate, N-Acetyl Aspartate (NAA), Lactate (Lac), Lipids, relative Apparent Diffusion Coefficient (rADC), and Fractional Anisotropy (FA)] were detected by two experienced neuroradiologists in joint session in 4 areas: Internal Cavity (IC), Ring Enhancement (RE), Peri-Lesional edema (PL), and Contralateral Normal Appearing White Matter (CNAWM). Significant differences between benign (n = 5) and malignant (n = 9) ring enhancing lesions were tested with Mann-Withney U test. The diagnostic accuracy of MRI biomarkers taken alone and MRI biomarkers ratios were tested with Receiver Operating Characteristic (ROC) analysis with an Area Under the Curve (AUC) ≥ 0.9 indicating a very good diagnostic accuracy of the variable. RESULTS Five MRI biomarker ratios achieved excellent accuracy: IC-rADC/PL-NAA (AUC = 1), IC-rADC/IC-FA (AUC = 0.978), RE-rCBV/RE-FA (AUC = 0.933), IC-rADC/RE-FA (AUC = 0.911), and IC-rADC/PL-FA (AUC = 0.911). Only IC-rADC achieved a very good diagnostic accuracy (AUC = 0.909) among MRI biomarkers taken alone. CONCLUSION Although the major limitation of the study was the small sample size, preliminary results seem to suggest that combination of multiple 3T MRI biomarkers is a feasible approach to MRI biomarkers in order to improve diagnostic accuracy in the differentiation between benign and malignant single ring enhancing brain masses. Further studies in larger cohorts are needed to reach definitive conclusions.
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Affiliation(s)
- Simone Salice
- Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, Chieti, Italy
| | - Roberto Esposito
- Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, Chieti, Italy
- AO Ospedali Riuniti Marche Nord, Pesaro, Italy
| | - Domenico Ciavardelli
- School of Human and Social Science, “Kore” University of Enna, Enna, Italy
- Molecular Neurology Unit, Center of Excellence on Aging and Translational Medicine (Ce.S.I.-MeT), University “G. d’Annunzio” of Chieti-Pescara, Chieti, Italy
| | - Stefano delli Pizzi
- Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, Chieti, Italy
| | - Rossella di Bastiano
- Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, Chieti, Italy
| | - Armando Tartaro
- Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, Chieti, Italy
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Response Assessment and Magnetic Resonance Imaging Issues for Clinical Trials Involving High-Grade Gliomas. Top Magn Reson Imaging 2016; 24:127-36. [PMID: 26049816 DOI: 10.1097/rmr.0000000000000054] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
There exist multiple challenges associated with the current response assessment criteria for high-grade gliomas, including the uncertain role of changes in nonenhancing T2 hyperintensity, and the phenomena of pseudoresponse and pseudoprogression in the setting of antiangiogenic and chemoradiation therapies, respectively. Advanced physiological magnetic resonance imaging (MRI), including diffusion and perfusion (dynamic susceptibility contrast MRI and dynamic contrast-enhanced MRI) sensitive techniques for overcoming response assessment challenges, has been proposed, with their own potential advantages and inherent shortcomings. Measurement variability exists for conventional and advanced MRI techniques, necessitating the standardization of image acquisition parameters in order to establish the utility of these imaging methods in multicenter trials for high-grade gliomas. This review chapter highlights the important features of MRI in clinical brain tumor trials, focusing on the current state of response assessment in brain tumors, advanced imaging techniques that may provide additional value for determining response, and imaging issues to be considered for multicenter trials.
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Normalized Apparent Diffusion Coefficient in the Prognostication of Patients with Glioblastoma Multiforme. Can J Neurol Sci 2016; 43:127-33. [PMID: 26786643 DOI: 10.1017/cjn.2015.356] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Glioblastoma multiforme (GBM) is known to have poor prognosis, with no available imaging marker that can predict survival at the time of diagnosis. Diffusion weighted images are used in characterisation of cellularity and necrosis of GBM. The purpose of this study was to assess whether pattern or degree of diffusion restriction could help in the prognostication of patients with GBM. MATERIAL AND METHODS We retrospectively analyzed 84 consecutive patients with confirmed GBM on biopsy or resection. The study was approved by the institutional ethics committee. The total volume of the tumor and total volume of tumor showing restricted diffusion were calculated. The lowest Apparent Diffusion Coefficient (ADC) in the region of the tumor and in the contralateral Normal Appearing White Matter were calculated in order to calculate the nADC. Treatment and follow-up data in these patients were recorded. Multivariate analsysis was completed to determine significant correlations between different variables and the survival of these patients. RESULTS Patient survival was significantly related to the age of the patient (p<0.0001; 95% CI-1.022-1.043) and the nADC value (p=0.014; 95% CI-0.269-0.860) in the tumor. The correlation coefficients of age and nADC with survival were -0.335 (p=0.002) and 0.390 (p<0.001), respectively. Kaplan Meier survival function, grouped by normalized Apparent Diffusion Coefficient cut off value of 0.75, was significant (p=0.007). CONCLUSION The survival of patients with GBM had small, but significant, correlations with the patient's age and nADC within the tumor.
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Boonzaier NR, Piccirillo SGM, Watts C, Price SJ. Assessing and monitoring intratumor heterogeneity in glioblastoma: how far has multimodal imaging come? CNS Oncol 2015; 4:399-410. [PMID: 26497327 DOI: 10.2217/cns.15.20] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Glioblastoma demonstrates imaging features of intratumor heterogeneity that result from underlying heterogeneous biological properties. This stems from variations in cellular behavior that result from genetic mutations that either drive, or are driven by, heterogeneous microenvironment conditions. Among all imaging methods available, only T1-weighted contrast-enhancing and T2-weighted fluid-attenuated inversion recovery are used in standard clinical glioblastoma assessment and monitoring. Advanced imaging modalities are still considered emerging techniques as appropriate end points and robust methodologies are missing from clinical trials. Discovering how these images specifically relate to the underlying tumor biology may aid in improving quality of clinical trials and understanding the factors involved in regional responses to treatment, including variable drug uptake and effect of radiotherapy. Upon validation and standardization of emerging MR techniques, providing information based on the underlying tumor biology, these images may allow for clinical decision-making that is tailored to an individual's response to treatment.
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Affiliation(s)
- Natalie R Boonzaier
- Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK.,Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, Cambridge Biomedical Campus, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Sara G M Piccirillo
- Cambridge Centre for Brain Repair, Department of Clinical Neurosciences, Forvie Site, Robinson Way, Cambridge CB2 0PY, UK
| | - Colin Watts
- Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Stephen J Price
- Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK.,Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, Cambridge Biomedical Campus, University of Cambridge, Cambridge CB2 0QQ, UK
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Wang H, Feng M, Jackson A, Ten Haken RK, Lawrence TS, Cao Y. Local and Global Function Model of the Liver. Int J Radiat Oncol Biol Phys 2015; 94:181-188. [PMID: 26700712 DOI: 10.1016/j.ijrobp.2015.09.044] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2015] [Revised: 09/21/2015] [Accepted: 09/28/2015] [Indexed: 02/08/2023]
Abstract
PURPOSE To develop a local and global function model in the liver based on regional and organ function measurements to support individualized adaptive radiation therapy (RT). METHODS AND MATERIALS A local and global model for liver function was developed to include both functional volume and the effect of functional variation of subunits. Adopting the assumption of parallel architecture in the liver, the global function was composed of a sum of local function probabilities of subunits, varying between 0 and 1. The model was fit to 59 datasets of liver regional and organ function measures from 23 patients obtained before, during, and 1 month after RT. The local function probabilities of subunits were modeled by a sigmoid function in relating to MRI-derived portal venous perfusion values. The global function was fitted to a logarithm of an indocyanine green retention rate at 15 minutes (an overall liver function measure). Cross-validation was performed by leave-m-out tests. The model was further evaluated by fitting to the data divided according to whether the patients had hepatocellular carcinoma (HCC) or not. RESULTS The liver function model showed that (1) a perfusion value of 68.6 mL/(100 g · min) yielded a local function probability of 0.5; (2) the probability reached 0.9 at a perfusion value of 98 mL/(100 g · min); and (3) at a probability of 0.03 [corresponding perfusion of 38 mL/(100 g · min)] or lower, the contribution to global function was lost. Cross-validations showed that the model parameters were stable. The model fitted to the data from the patients with HCC indicated that the same amount of portal venous perfusion was translated into less local function probability than in the patients with non-HCC tumors. CONCLUSIONS The developed liver function model could provide a means to better assess individual and regional dose-responses of hepatic functions, and provide guidance for individualized treatment planning of RT.
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Affiliation(s)
- Hesheng Wang
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
| | - Mary Feng
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Andrew Jackson
- Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, New York
| | - Randall K Ten Haken
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Theodore S Lawrence
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Radiology, University of Michigan, Ann Arbor, Michigan; Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
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Boxerman JL, Schmainda KM, Zhang Z, Barboriak DP. Dynamic susceptibility contrast MRI measures of relative cerebral blood volume continue to show promise as an early response marker in the setting of bevacizumab treatment. Neuro Oncol 2015; 17:1538-9. [PMID: 26361983 DOI: 10.1093/neuonc/nov163] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2015] [Accepted: 07/22/2015] [Indexed: 11/14/2022] Open
Affiliation(s)
- Jerrold L Boxerman
- Medical College of Wisconsin, Department of Radiology, Milwaukee, Wisconsin
| | | | - Zheng Zhang
- Medical College of Wisconsin, Department of Radiology, Milwaukee, Wisconsin
| | - Daniel P Barboriak
- Medical College of Wisconsin, Department of Radiology, Milwaukee, Wisconsin
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Prah MA, Stufflebeam SM, Paulson ES, Kalpathy-Cramer J, Gerstner ER, Batchelor TT, Barboriak DP, Rosen BR, Schmainda KM. Repeatability of Standardized and Normalized Relative CBV in Patients with Newly Diagnosed Glioblastoma. AJNR Am J Neuroradiol 2015; 36:1654-61. [PMID: 26066626 DOI: 10.3174/ajnr.a4374] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2014] [Accepted: 01/23/2015] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE For more widespread clinical use advanced imaging methods such as relative cerebral blood volume must be both accurate and repeatable. The aim of this study was to determine the repeatability of relative CBV measurements in newly diagnosed glioblastoma multiforme by using several of the most commonly published estimation techniques. MATERIALS AND METHODS The relative CBV estimates were calculated from dynamic susceptibility contrast MR imaging in double-baseline examinations for 33 patients with treatment-naïve and pathologically proved glioblastoma multiforme (men = 20; mean age = 55 years). Normalized and standardized relative CBV were calculated by using 6 common postprocessing methods. The repeatability of both normalized and standardized relative CBV, in both tumor and contralateral brain, was examined for each method with metrics of repeatability, including the repeatability coefficient and within-subject coefficient of variation. The minimum sample size required to detect a parameter change of 10% or 20% was also determined for both normalized relative CBV and standardized relative CBV for each estimation method. RESULTS When ordered by the repeatability coefficient, methods using postprocessing leakage correction and ΔR2*(t) techniques offered superior repeatability. Across processing techniques, the standardized relative CBV repeatability in normal-appearing brain was comparable with that in tumor (P = .31), yet inferior in tumor for normalized relative CBV (P = .03). On the basis of the within-subject coefficient of variation, tumor standardized relative CBV estimates were less variable (13%-20%) than normalized relative CBV estimates (24%-67%). The minimum number of participants needed to detect a change of 10% or 20% is 118-643 or 30-161 for normalized relative CBV and 109-215 or 28-54 for standardized relative CBV. CONCLUSIONS The ΔR2* estimation methods that incorporate leakage correction offer the best repeatability for relative CBV, with standardized relative CBV being less variable and requiring fewer participants to detect a change compared with normalized relative CBV.
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Affiliation(s)
- M A Prah
- From the Departments of Radiology (M.A.P., K.M.S., E.S.P.)
| | - S M Stufflebeam
- Department of Radiology (S.M.S., J.K.-C., E.R.G., T.T.B., B.R.R.), Massachusetts General Hospital, Boston, Massachusetts
| | - E S Paulson
- From the Departments of Radiology (M.A.P., K.M.S., E.S.P.) Radiation Oncology (E.S.P.), Medical College of Wisconsin, Milwaukee, Wisconsin
| | - J Kalpathy-Cramer
- Department of Radiology (S.M.S., J.K.-C., E.R.G., T.T.B., B.R.R.), Massachusetts General Hospital, Boston, Massachusetts
| | - E R Gerstner
- Department of Radiology (S.M.S., J.K.-C., E.R.G., T.T.B., B.R.R.), Massachusetts General Hospital, Boston, Massachusetts
| | - T T Batchelor
- Department of Radiology (S.M.S., J.K.-C., E.R.G., T.T.B., B.R.R.), Massachusetts General Hospital, Boston, Massachusetts
| | - D P Barboriak
- Department of Radiology (D.P.B.), Duke University Medical Center, Durham, North Carolina
| | - B R Rosen
- Department of Radiology (S.M.S., J.K.-C., E.R.G., T.T.B., B.R.R.), Massachusetts General Hospital, Boston, Massachusetts
| | - K M Schmainda
- From the Departments of Radiology (M.A.P., K.M.S., E.S.P.)
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Ellingson BM, Bendszus M, Sorensen AG, Pope WB. Emerging techniques and technologies in brain tumor imaging. Neuro Oncol 2015; 16 Suppl 7:vii12-23. [PMID: 25313234 DOI: 10.1093/neuonc/nou221] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
The purpose of this report is to describe the state of imaging techniques and technologies for detecting response of brain tumors to treatment in the setting of multicenter clinical trials. Within currently used technologies, implementation of standardized image acquisition and the use of volumetric estimates and subtraction maps are likely to help to improve tumor visualization, delineation, and quantification. Upon further development, refinement, and standardization, imaging technologies such as diffusion and perfusion MRI and amino acid PET may contribute to the detection of tumor response to treatment, particularly in specific treatment settings. Over the next few years, new technologies such as 2(3)Na MRI and CEST imaging technologies will be explored for their use in expanding the ability to quantitatively image tumor response to therapies in a clinical trial setting.
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Affiliation(s)
- Benjamin M Ellingson
- Department of Radiological Sciences, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E., W.B.P.); Department of Biomedical Physics, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); Department of Bioengineering, Henry Samueli School of Engineering and Applied Science at University of California, Los Angeles, California (B.M.E.); Brain Research Institute, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); UCLA Neuro-Oncology Program, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany (M.B.); Siemens Healthcare, Erlangen, Germany (A.G.S.)
| | - Martin Bendszus
- Department of Radiological Sciences, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E., W.B.P.); Department of Biomedical Physics, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); Department of Bioengineering, Henry Samueli School of Engineering and Applied Science at University of California, Los Angeles, California (B.M.E.); Brain Research Institute, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); UCLA Neuro-Oncology Program, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany (M.B.); Siemens Healthcare, Erlangen, Germany (A.G.S.)
| | - A Gregory Sorensen
- Department of Radiological Sciences, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E., W.B.P.); Department of Biomedical Physics, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); Department of Bioengineering, Henry Samueli School of Engineering and Applied Science at University of California, Los Angeles, California (B.M.E.); Brain Research Institute, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); UCLA Neuro-Oncology Program, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany (M.B.); Siemens Healthcare, Erlangen, Germany (A.G.S.)
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E., W.B.P.); Department of Biomedical Physics, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); Department of Bioengineering, Henry Samueli School of Engineering and Applied Science at University of California, Los Angeles, California (B.M.E.); Brain Research Institute, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); UCLA Neuro-Oncology Program, David Geffen School of Medicine at University of California, Los Angeles, California (B.M.E.); Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany (M.B.); Siemens Healthcare, Erlangen, Germany (A.G.S.)
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Jafari-Khouzani K, Emblem KE, Kalpathy-Cramer J, Bjørnerud A, Vangel MG, Gerstner ER, Schmainda KM, Paynabar K, Wu O, Wen PY, Batchelor T, Rosen B, Stufflebeam SM. Repeatability of Cerebral Perfusion Using Dynamic Susceptibility Contrast MRI in Glioblastoma Patients. Transl Oncol 2015; 8:137-46. [PMID: 26055170 PMCID: PMC4486737 DOI: 10.1016/j.tranon.2015.03.002] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2014] [Revised: 03/10/2015] [Accepted: 03/17/2015] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVES This study evaluates the repeatability of brain perfusion using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a variety of post-processing methods. METHODS Thirty-two patients with newly diagnosed glioblastoma were recruited. On a 3-T MRI using a dual-echo, gradient-echo spin-echo DSC-MRI protocol, the patients were scanned twice 1 to 5 days apart. Perfusion maps including cerebral blood volume (CBV) and cerebral blood flow (CBF) were generated using two contrast agent leakage correction methods, along with testing normalization to reference tissue, and application of arterial input function (AIF). Repeatability of CBV and CBF within tumor regions and healthy tissues, identified by structural images, was assessed with intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs). Coefficients of variation (CVs) were reported for selected methods. RESULTS CBV and CBF were highly repeatable within tumor with ICC values up to 0.97. However, both CBV and CBF showed lower ICCs for healthy cortical tissues (up to 0.83), healthy gray matter (up to 0.95), and healthy white matter (WM; up to 0.93). The values of CV ranged from 6% to 10% in tumor and 3% to 11% in healthy tissues. The values of RC relative to the mean value of measurement within healthy WM ranged from 22% to 42% in tumor and 7% to 43% in healthy tissues. These percentages show how much variation in perfusion parameter, relative to that in healthy WM, we expect to observe to consider it statistically significant. We also found that normalization improved repeatability, but AIF deconvolution did not. CONCLUSIONS DSC-MRI is highly repeatable in high-grade glioma patients.
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Affiliation(s)
- Kourosh Jafari-Khouzani
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Kyrre E Emblem
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA; The Intervention Centre, Rikshospitalet, Oslo University Hospital, Oslo, Norway
| | - Jayashree Kalpathy-Cramer
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Atle Bjørnerud
- The Intervention Centre, Rikshospitalet, Oslo University Hospital, Oslo, Norway; Department of Physics, University of Oslo, Oslo, Norway
| | - Mark G Vangel
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Elizabeth R Gerstner
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, USA
| | - Kathleen M Schmainda
- Department of Radiology & Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Kamran Paynabar
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Ona Wu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Tracy Batchelor
- Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, USA
| | - Bruce Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Steven M Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard-MIT Health Sciences & Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
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Welker K, Boxerman J, Kalnin A, Kaufmann T, Shiroishi M, Wintermark M. ASFNR recommendations for clinical performance of MR dynamic susceptibility contrast perfusion imaging of the brain. AJNR Am J Neuroradiol 2015; 36:E41-51. [PMID: 25907520 DOI: 10.3174/ajnr.a4341] [Citation(s) in RCA: 151] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2015] [Accepted: 02/20/2015] [Indexed: 11/07/2022]
Abstract
MR perfusion imaging is becoming an increasingly common means of evaluating a variety of cerebral pathologies, including tumors and ischemia. In particular, there has been great interest in the use of MR perfusion imaging for both assessing brain tumor grade and for monitoring for tumor recurrence in previously treated patients. Of the various techniques devised for evaluating cerebral perfusion imaging, the dynamic susceptibility contrast method has been employed most widely among clinical MR imaging practitioners. However, when implementing DSC MR perfusion imaging in a contemporary radiology practice, a neuroradiologist is confronted with a large number of decisions. These include choices surrounding appropriate patient selection, scan-acquisition parameters, data-postprocessing methods, image interpretation, and reporting. Throughout the imaging literature, there is conflicting advice on these issues. In an effort to provide guidance to neuroradiologists struggling to implement DSC perfusion imaging in their MR imaging practice, the Clinical Practice Committee of the American Society of Functional Neuroradiology has provided the following recommendations. This guidance is based on review of the literature coupled with the practice experience of the authors. While the ASFNR acknowledges that alternate means of carrying out DSC perfusion imaging may yield clinically acceptable results, the following recommendations should provide a framework for achieving routine success in this complicated-but-rewarding aspect of neuroradiology MR imaging practice.
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Affiliation(s)
- K Welker
- From the Department of Radiology (K.W., T.K.), Mayo Clinic, Rochester, Minnesota
| | - J Boxerman
- Department of Diagnostic Imaging (J.B.), Rhode Island Hospital and Alpert Medical School of Brown University, Providence, Rhode Island
| | - A Kalnin
- Department of Radiology (A.K.), Wexner Medical Center, The Ohio State University, Columbus, Ohio
| | - T Kaufmann
- From the Department of Radiology (K.W., T.K.), Mayo Clinic, Rochester, Minnesota
| | - M Shiroishi
- Division of Neuroradiology, Department of Radiology (M.S.), Keck School of Medicine, University of Southern California, Los Angeles, California
| | - M Wintermark
- Department of Radiology, Neuroradiology Section (M.W.), Stanford University, Stanford, California
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Schmainda KM. Diffusion-weighted MRI as a biomarker for treatment response in glioma. CNS Oncol 2015; 1:169-80. [PMID: 23936625 DOI: 10.2217/cns.12.25] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Diffusion-weighted imaging (DWI) is a powerful MRI method, which probes abnormalities of tissue structure by detecting microscopic changes in water mobility at a cellular level beyond what is available with other imaging techniques. Accordingly, DWI has the potential to identify pathology before gross anatomic changes are evident on standard anatomical brain images. These features of tissue characterization and earlier detection are what make DWI particularly appealing for the evaluation of gliomas and the newer therapies where standard anatomical imaging is proving insufficient. This article focuses on the basic principles and applications of DWI, and its derived parameter, the apparent diffusion coefficient, for the purposes of diagnosis and evaluation of glioma, especially in the context of monitoring response to therapy.
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Huang RY, Neagu MR, Reardon DA, Wen PY. Pitfalls in the neuroimaging of glioblastoma in the era of antiangiogenic and immuno/targeted therapy - detecting illusive disease, defining response. Front Neurol 2015; 6:33. [PMID: 25755649 PMCID: PMC4337341 DOI: 10.3389/fneur.2015.00033] [Citation(s) in RCA: 110] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2014] [Accepted: 02/09/2015] [Indexed: 02/04/2023] Open
Abstract
Glioblastoma, the most common malignant primary brain tumor in adults is a devastating diagnosis with an average survival of 14–16 months using the current standard of care treatment. The determination of treatment response and clinical decision making is based on the accuracy of radiographic assessment. Notwithstanding, challenges exist in the neuroimaging evaluation of patients undergoing treatment for malignant glioma. Differentiating treatment response from tumor progression is problematic and currently combines long-term follow-up using standard magnetic resonance imaging (MRI), with clinical status and corticosteroid-dependency assessments. In the clinical trial setting, treatment with gene therapy, vaccines, immunotherapy, and targeted biologicals similarly produces MRI changes mimicking disease progression. A neuroimaging method to clearly distinguish between pseudoprogression and tumor progression has unfortunately not been found to date. With the incorporation of antiangiogenic therapies, a further pitfall in imaging interpretation is pseudoresponse. The Macdonald criteria that correlate tumor burden with contrast-enhanced imaging proved insufficient and misleading in the context of rapid blood–brain barrier normalization following antiangiogenic treatment that is not accompanied by expected survival benefit. Even improved criteria, such as the RANO criteria, which incorporate non-enhancing disease, clinical status, and need for corticosteroid use, fall short of definitively distinguishing tumor progression, pseudoresponse, and pseudoprogression. This review focuses on advanced imaging techniques including perfusion MRI, diffusion MRI, MR spectroscopy, and new positron emission tomography imaging tracers. The relevant image analysis algorithms and interpretation methods of these promising techniques are discussed in the context of determining response and progression during treatment of glioblastoma both in the standard of care and in clinical trial context.
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Affiliation(s)
- Raymond Y Huang
- Center of Neuro-Oncology, Dana-Farber/Brigham and Women's Cancer Center , Boston, MA , USA
| | - Martha R Neagu
- Center of Neuro-Oncology, Dana-Farber/Brigham and Women's Cancer Center , Boston, MA , USA
| | - David A Reardon
- Center of Neuro-Oncology, Dana-Farber/Brigham and Women's Cancer Center , Boston, MA , USA
| | - Patrick Y Wen
- Center of Neuro-Oncology, Dana-Farber/Brigham and Women's Cancer Center , Boston, MA , USA
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Schmainda KM, Zhang Z, Prah M, Snyder BS, Gilbert MR, Sorensen AG, Barboriak DP, Boxerman JL. Dynamic susceptibility contrast MRI measures of relative cerebral blood volume as a prognostic marker for overall survival in recurrent glioblastoma: results from the ACRIN 6677/RTOG 0625 multicenter trial. Neuro Oncol 2015; 17:1148-56. [PMID: 25646027 DOI: 10.1093/neuonc/nou364] [Citation(s) in RCA: 91] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2014] [Accepted: 12/24/2014] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND The study goal was to determine whether changes in relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast (DSC) MRI are predictive of overall survival (OS) in patients with recurrent glioblastoma multiforme (GBM) when measured 2, 8, and 16 weeks after treatment initiation. METHODS Patients with recurrent GBM (37/123) enrolled in ACRIN 6677/RTOG 0625, a multicenter, randomized, phase II trial of bevacizumab with irinotecan or temozolomide, consented to DSC-MRI plus conventional MRI, 21 with DSC-MRI at baseline and at least 1 postbaseline scan. Contrast-enhancing regions of interest were determined semi-automatically using pre- and postcontrast T1-weighted images. Mean tumor rCBV normalized to white matter (nRCBV) and standardized rCBV (sRCBV) were determined for these regions of interest. The OS rates for patients with positive versus negative changes from baseline in nRCBV and sRCBV were compared using Wilcoxon rank-sum and Kaplan-Meier survival estimates with log-rank tests. RESULTS Patients surviving at least 1 year (OS-1) had significantly larger decreases in nRCBV at week 2 (P = .0451) and sRCBV at week 16 (P = .014). Receiver operating characteristic analysis found the percent changes of nRCBV and sRCBV at week 2 and sRCBV at week 16, but not rCBV data at week 8, to be good prognostic markers for OS-1. Patients with positive change from baseline rCBV had significantly shorter OS than those with negative change at both week 2 and week 16 (P = .0015 and P = .0067 for nRCBV and P = .0251 and P = .0004 for sRCBV, respectively). CONCLUSIONS Early decreases in rCBV are predictive of improved survival in patients with recurrent GBM treated with bevacizumab.
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Affiliation(s)
- Kathleen M Schmainda
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin (K.M.S., M.P.); Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, Rhode Island (Z.Z., B.S.S.); Department of Neuro-Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas (M.R.G.); Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts (A.G.S.); Department of Radiology, Duke University Medical Center, Durham, North Carolina (D.P.B.); Department of Diagnostic Imaging, Rhode Island Hospital, Providence, Rhode Island (J.L.B.); Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.)
| | - Zheng Zhang
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin (K.M.S., M.P.); Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, Rhode Island (Z.Z., B.S.S.); Department of Neuro-Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas (M.R.G.); Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts (A.G.S.); Department of Radiology, Duke University Medical Center, Durham, North Carolina (D.P.B.); Department of Diagnostic Imaging, Rhode Island Hospital, Providence, Rhode Island (J.L.B.); Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.)
| | - Melissa Prah
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin (K.M.S., M.P.); Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, Rhode Island (Z.Z., B.S.S.); Department of Neuro-Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas (M.R.G.); Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts (A.G.S.); Department of Radiology, Duke University Medical Center, Durham, North Carolina (D.P.B.); Department of Diagnostic Imaging, Rhode Island Hospital, Providence, Rhode Island (J.L.B.); Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.)
| | - Bradley S Snyder
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin (K.M.S., M.P.); Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, Rhode Island (Z.Z., B.S.S.); Department of Neuro-Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas (M.R.G.); Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts (A.G.S.); Department of Radiology, Duke University Medical Center, Durham, North Carolina (D.P.B.); Department of Diagnostic Imaging, Rhode Island Hospital, Providence, Rhode Island (J.L.B.); Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.)
| | - Mark R Gilbert
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin (K.M.S., M.P.); Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, Rhode Island (Z.Z., B.S.S.); Department of Neuro-Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas (M.R.G.); Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts (A.G.S.); Department of Radiology, Duke University Medical Center, Durham, North Carolina (D.P.B.); Department of Diagnostic Imaging, Rhode Island Hospital, Providence, Rhode Island (J.L.B.); Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.)
| | - A Gregory Sorensen
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin (K.M.S., M.P.); Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, Rhode Island (Z.Z., B.S.S.); Department of Neuro-Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas (M.R.G.); Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts (A.G.S.); Department of Radiology, Duke University Medical Center, Durham, North Carolina (D.P.B.); Department of Diagnostic Imaging, Rhode Island Hospital, Providence, Rhode Island (J.L.B.); Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.)
| | - Daniel P Barboriak
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin (K.M.S., M.P.); Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, Rhode Island (Z.Z., B.S.S.); Department of Neuro-Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas (M.R.G.); Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts (A.G.S.); Department of Radiology, Duke University Medical Center, Durham, North Carolina (D.P.B.); Department of Diagnostic Imaging, Rhode Island Hospital, Providence, Rhode Island (J.L.B.); Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.)
| | - Jerrold L Boxerman
- Department of Radiology, Medical College of Wisconsin, Milwaukee, Wisconsin (K.M.S., M.P.); Department of Biostatistics and Center for Statistical Sciences, Brown University, Providence, Rhode Island (Z.Z., B.S.S.); Department of Neuro-Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas (M.R.G.); Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts (A.G.S.); Department of Radiology, Duke University Medical Center, Durham, North Carolina (D.P.B.); Department of Diagnostic Imaging, Rhode Island Hospital, Providence, Rhode Island (J.L.B.); Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.)
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Leu K, Enzmann DR, Woodworth DC, Harris RJ, Tran AN, Lai A, Nghiemphu PL, Pope WB, Cloughesy TF, Ellingson BM. Hypervascular tumor volume estimated by comparison to a large-scale cerebral blood volume radiographic atlas predicts survival in recurrent glioblastoma treated with bevacizumab. Cancer Imaging 2014; 14:31. [PMID: 25608485 PMCID: PMC4331836 DOI: 10.1186/s40644-014-0031-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Accepted: 10/09/2014] [Indexed: 11/30/2022] Open
Abstract
Background Dynamic susceptibility contrast (DSC)-MRI is a well-established perfusion MR imaging technique for estimating relative cerebral blood volume (CBV) in primary brain tumors; however, tumors localized to regions with naturally elevated perfusion, including cortical tissue and common vascular territories, make evaluation of tumor vascularity difficult to assess. In the current study, we have constructed a large-scale radiographic atlas of CBV to assess treatment response to bevacizumab in individual patients with recurrent glioblastoma. Methods Z-score normalized CBV maps were registered to stereotactic atlas space in 450 patients with brain tumors. A CBV atlas was created by calculating the voxel-wise mean and variability in CBV. MRI and CBV maps from 32 recurrent glioblastoma patients were then obtained prior to and following treatment with bevacizumab, registered to and compared with the CBV atlas. The volume of tumor tissue with elevated CBV, percentage of enhancing tumor with elevated CBV, and the mean and maximum change in normalized CBV intensity relative to the atlas were computed. Results Voxel-wise comparison of individual patient CBV maps to the atlas allowed delineation of elevated tumor perfusion from artery and normal cortical tissue. An atlas-defined hypervascular tumor blood volume greater than 2.35 cc prior to treatment, 0.14 cc after treatment, and a decrease in atlas-defined hypervascular tumor volume less than 80% following treatment were characteristic of a shorter PFS and OS. Traditional measures of CBV were not predictive of PFS or OS. Conclusions This study highlights the advantages of large-scale population maps to identify abnormal biological tissues.
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Korfiatis P, Erickson B. The basics of diffusion and perfusion imaging in brain tumors. APPLIED RADIOLOGY 2014; 43:22-29. [PMID: 26456989 PMCID: PMC4599787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
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Shiroishi MS, Castellazzi G, Boxerman JL, D'Amore F, Essig M, Nguyen TB, Provenzale JM, Enterline DS, Anzalone N, Dörfler A, Rovira À, Wintermark M, Law M. Principles of T2*-weighted dynamic susceptibility contrast MRI technique in brain tumor imaging. J Magn Reson Imaging 2014; 41:296-313. [DOI: 10.1002/jmri.24648] [Citation(s) in RCA: 85] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2013] [Accepted: 04/03/2014] [Indexed: 01/17/2023] Open
Affiliation(s)
- Mark S. Shiroishi
- Keck School of Medicine; University of Southern California; Los Angeles California USA
| | - Gloria Castellazzi
- Department of Industrial and Information Engineering; University of Pavia; Pavia Italy
- Brain Connectivity Center, IRCCS “C. Mondino Foundation,”; Pavia Italy
| | - Jerrold L. Boxerman
- Warren Alpert Medical School of Brown University; Providence Rhode Island USA
| | - Francesco D'Amore
- Keck School of Medicine; University of Southern California; Los Angeles California USA
- Department of Neuroradiology; IRCCS “C. Mondino Foundation,” University of Pavia; Pavia Italy
| | - Marco Essig
- University of Manitoba's Faculty of Medicine; Winnipeg Manitoba Canada
| | - Thanh B. Nguyen
- Faculty of Medicine, Ottawa University; Ottawa Ontario Canada
| | - James M. Provenzale
- Duke University Medical Center; Durham North Carolina USA
- Emory University School of Medicine; Atlanta Georgia USA
| | | | | | - Arnd Dörfler
- University of Erlangen-Nuremberg, Erlangen; Germany
| | - Àlex Rovira
- Vall d'Hebron University Hospital; Barcelona Spain
| | - Max Wintermark
- School of Medicine; University of Virginia; Charlottesville Virginia USA
| | - Meng Law
- Keck School of Medicine; University of Southern California; Los Angeles California USA
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Schmainda KM, Prah M, Connelly J, Rand SD, Hoffman RG, Mueller W, Malkin MG. Dynamic-susceptibility contrast agent MRI measures of relative cerebral blood volume predict response to bevacizumab in recurrent high-grade glioma. Neuro Oncol 2014; 16:880-8. [PMID: 24431219 DOI: 10.1093/neuonc/not216] [Citation(s) in RCA: 85] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND The anti-VEGF antibody, bevacizumab, is standard treatment for patients with recurrent glioblastoma. In this setting, traditional anatomic MRI methods such as post-contrast T1-weighted and T2-weighted imaging are proving unreliable for monitoring response. Here we evaluate the prognostic significance of pre- and posttreatment relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast MRI to predict response to bevacizumab. METHODS Thirty-six participants with recurrent high-grade gliomas who underwent rCBV imaging 60 days before and 20-60 days after starting bevacizumab treatment were enrolled. Tumor regions of interest (ROIs) were determined from deltaT1 maps computed from the difference between standardized post and precontrast T1-weighted images. Both pre- and posttreatment rCBV maps were corrected for leakage and standardized (stdRCBV) to a consistent intensity scale. The Kaplan-Meier method was used to determine if either the pre- or post-bevacizumab stdRCBV within the tumor ROI was predictive of overall survival (OS) or progression free survival (PFS). RESULTS The OS was significantly longer if either the pre- (380d vs 175d; P=.0024) or posttreatment stdRCBV (340d vs 186d; P = .0065) was <4400. The posttreatment stdRCBV was also predictive of PFS (167d vs 78d; P = .0006). When the stdRCBV values were both above versus both below threshold, the OS was significantly worse (100.5d vs 395d; P < .0001). With a 32.5% decrease in stdRCBV, the risk of death was reduced by about 68% but increased by 140% with a 29% increase in stdRCBV. CONCLUSIONS Standardized rCBV is predictive of OS and PFS in patients with recurrent high-grade brain tumor treated with bevacizumab.
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Affiliation(s)
- Kathleen M Schmainda
- Department of Radiology, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., M.P., S.D.R.); Department of Biophysics, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S.); Translational Brain Tumor Research Program, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., J.C., S.D.R., W.M., M.G.M.); Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., M.G.M.); Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin (R.G.H); Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., W.M., M.G.M.)
| | - Melissa Prah
- Department of Radiology, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., M.P., S.D.R.); Department of Biophysics, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S.); Translational Brain Tumor Research Program, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., J.C., S.D.R., W.M., M.G.M.); Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., M.G.M.); Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin (R.G.H); Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., W.M., M.G.M.)
| | - Jennifer Connelly
- Department of Radiology, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., M.P., S.D.R.); Department of Biophysics, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S.); Translational Brain Tumor Research Program, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., J.C., S.D.R., W.M., M.G.M.); Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., M.G.M.); Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin (R.G.H); Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., W.M., M.G.M.)
| | - Scott D Rand
- Department of Radiology, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., M.P., S.D.R.); Department of Biophysics, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S.); Translational Brain Tumor Research Program, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., J.C., S.D.R., W.M., M.G.M.); Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., M.G.M.); Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin (R.G.H); Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., W.M., M.G.M.)
| | - Raymond G Hoffman
- Department of Radiology, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., M.P., S.D.R.); Department of Biophysics, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S.); Translational Brain Tumor Research Program, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., J.C., S.D.R., W.M., M.G.M.); Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., M.G.M.); Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin (R.G.H); Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., W.M., M.G.M.)
| | - Wade Mueller
- Department of Radiology, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., M.P., S.D.R.); Department of Biophysics, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S.); Translational Brain Tumor Research Program, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., J.C., S.D.R., W.M., M.G.M.); Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., M.G.M.); Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin (R.G.H); Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., W.M., M.G.M.)
| | - Mark G Malkin
- Department of Radiology, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., M.P., S.D.R.); Department of Biophysics, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S.); Translational Brain Tumor Research Program, Medical College of Wisconsin, Milwaukee Wisconsin (K.M.S., J.C., S.D.R., W.M., M.G.M.); Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., M.G.M.); Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin (R.G.H); Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin (J.C., W.M., M.G.M.)
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Shiroishi MS, Booker MT, Agarwal M, Jain N, Naghi I, Lerner A, Law M. Posttreatment evaluation of central nervous system gliomas. Magn Reson Imaging Clin N Am 2013; 21:241-68. [PMID: 23642552 DOI: 10.1016/j.mric.2013.02.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Although conventional contrast-enhanced MR imaging remains the standard-of-care imaging method in the posttreatment evaluation of gliomas, recent developments in therapeutic options such as chemoradiation and antiangiogenic agents have caused the neuro-oncology community to rethink traditional imaging criteria. This article highlights the latest recommendations. These recommendations should be viewed as works in progress. As more is learned about the pathophysiology of glioma treatment response, quantitative imaging biomarkers will be validated within this context. There will likely be further refinements to glioma response criteria, although the lack of technical standardization in image acquisition, postprocessing, and interpretation also need to be addressed.
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Affiliation(s)
- Mark S Shiroishi
- Division of Neuroradiology, Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.
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Cohen AD, LaViolette PS, Prah M, Connelly J, Malkin MG, Rand SD, Mueller WM, Schmainda KM. Effects of perfusion on diffusion changes in human brain tumors. J Magn Reson Imaging 2013; 38:868-75. [PMID: 23389889 DOI: 10.1002/jmri.24042] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2012] [Accepted: 12/13/2012] [Indexed: 11/06/2022] Open
Abstract
PURPOSE To characterize the influence of perfusion on the measurement of diffusion changes over time when ADC is computed using standard two-point methods. MATERIALS AND METHODS Functional diffusion maps (FDMs), which depict changes in diffusion over time, were compared with rCBV changes in patients with brain tumors. The FDMs were created by coregistering and subtracting ADC maps from two time points and categorizing voxels where ADC significantly increased (iADC), decreased (dADC), or did not change (ncADC). Traditional FDMs (tFDMs) were computed using b = 0,1000 s/mm(2). Flow-compensated FDMs (fcFDMs) were calculated using b = 500,1000 s/mm(2). Perfusion's influence on FDMs was determined by evaluating changes in rCBV in areas where the ADC change significantly differed between the two FDMs. RESULTS The mean ΔrCBV in voxels that changed from iADC (dADC) on the tFDM to ncADC on the fcFDM was significantly greater (less) than zero. In addition, mean ΔrCBV in iADC (dADC) voxels on the tFDM was significantly higher (lower) than in iADC (dADC) voxels on the fcFDM. CONCLUSION The ability to accurately identify changes in diffusion on traditional FDMs is confounded in areas where perfusion and diffusion changes are colocalized. Flow-compensated FDMs, which use only non-zero b-values, should therefore be the standard approach.
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Affiliation(s)
- Alexander D Cohen
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA; Translational Brain Tumor Research Program, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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LaViolette PS, Cohen AD, Prah MA, Rand SD, Connelly J, Malkin MG, Mueller WM, Schmainda KM. Vascular change measured with independent component analysis of dynamic susceptibility contrast MRI predicts bevacizumab response in high-grade glioma. Neuro Oncol 2013; 15:442-50. [PMID: 23382287 DOI: 10.1093/neuonc/nos323] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Standard pre- and postcontrast (T1 + C) anatomical MR imaging is proving to be insufficient for accurately monitoring bevacizumab treatment response in recurrent glioblastoma (GBM). We present a novel imaging biomarker that detects abnormal tumor vasculature exhibiting both arterial and venous perfusion characteristics. We hypothesized that a decrease in the extent of this abnormal vasculature after bevacizumab treatment would predict treatment efficacy and overall survival. METHODS Dynamic susceptibility contrast perfusion MRI was gathered in 43 patients with high-grade glioma. Independent component analysis separated vasculature into arterial and venous components. Voxels with perfusion characteristics of both arteries and veins (ie, arterio-venous overlap [AVOL]) were measured in patients with de novo untreated GBM and patients with recurrent high-grade glioma before and after bevacizumab treatment. Treated patients were separated on the basis of an increase or decrease in AVOL volume (+/-ΔAVOL), and overall survival following bevacizumab onset was then compared between +/-ΔAVOL groups. RESULTS AVOL in untreated GBM was significantly higher than in normal vasculature (P < .001). Kaplan-Meier survival curves revealed a greater median survival (348 days) in patients with GBM with a negative ΔAVOL after bevacizumab treatment than in patients with a positive change (197 days; hazard ratio, 2.51; P < .05). Analysis of patients with combined grade III and IV glioma showed similar results, with median survivals of 399 days and 153 days, respectively (hazard ratio, 2.71; P < .01). Changes in T1+C volume and ΔrCBV after treatment were not significantly different across +/-ΔAVOL groups, and ΔAVOL was not significantly correlated with ΔT1+C or ΔrCBV. CONCLUSIONS The independent component analysis dynamic susceptibility contrast-derived biomarker AVOL adds additional information for determining bevacizumab treatment efficacy.
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Affiliation(s)
- Peter S LaViolette
- Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Rd., Milwaukee, WI 53226, USA.
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Harris RJ, Cloughesy TF, Pope WB, Godinez S, Natsuaki Y, Nghiemphu PL, Meyer H, Paul D, Behbahanian Y, Lai A, Ellingson BM. Pre- and post-contrast three-dimensional double inversion-recovery MRI in human glioblastoma. J Neurooncol 2013; 112:257-66. [PMID: 23344788 DOI: 10.1007/s11060-013-1057-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2012] [Accepted: 01/15/2013] [Indexed: 11/26/2022]
Abstract
Fluid attenuated inversion recovery (FLAIR) MRI sequences have become an indispensible tool for defining the malignant boundary in patients with brain tumors by nulling the signal contribution from cerebrospinal fluid allowing both regions of edema and regions of non-enhancing, infiltrating tumor to become hyperintense on resulting images. In the current study we examined the utility of a three-dimensional double inversion recovery (DIR) sequence that additionally nulls the MR signal associated with white matter, implemented either pre-contrast or post-contrast, in order to determine whether this sequence allows for better differentiation between tumor and normal brain tissue. T1- and T2-weighted, FLAIR, dynamic susceptibility contrast (DSC)-MRI estimates of cerebral blood volume (rCBV), contrast-enhanced T1-weighted images (T1+C), and DIR data (pre- or post-contrast) were acquired in 22 patients with glioblastoma. Contrast-to-noise (CNR) and tumor volumes were compared between DIR and FLAIR sequences. Line profiles across regions of tumor were generated to evaluate similarities between image contrasts. Additionally, voxel-wise associations between DIR and other sequences were examined. Results suggested post-contrast DIR images were hyperintense (bright) in regions spatially similar those having FLAIR hyperintensity and hypointense (dark) in regions with contrast-enhancement or elevated rCBV due to the high sensitivity of 3D turbo spin echo sequences to susceptibility differences between different tissues. DIR tumor volumes were statistically smaller than tumor volumes as defined by FLAIR (Paired t test, P = 0.0084), averaging a difference of approximately 14 mL or 24 %. DIR images had approximately 1.5× higher lesion CNR compared with FLAIR images (Paired t test, P = 0.0048). Line profiles across tumor regions and scatter plots of voxel-wise coherence between different contrasts confirmed a positive correlation between DIR and FLAIR signal intensity and a negative correlation between DIR and both post-contrast T1-weighted image signal intensity and rCBV. Additional discrepancies between FLAIR and DIR abnormal regions were also observed, together suggesting DIR may provide additional information beyond that of FLAIR.
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Affiliation(s)
- Robert J Harris
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
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