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Soydan H, Sözmen Cılız D, Cesur T, Tezgör Aksakal E. Primary brain lymphoma and glioblastoma: evaluation of DCE T1 and DSC T2 MRI perfusion findings. Acta Radiol 2024:2841851241256781. [PMID: 38798137 DOI: 10.1177/02841851241256781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
BACKGROUND The accurate differentiation of primary central nervous system lymphoma (PCNSL) from glioblastoma multiforme (GBM) is clinically crucial due to the different treatment strategies between them. PURPOSE To define magnetic resonance imaging (MRI) perfusion findings in PCNSL to make a safe distinction from GBM with dynamic contrast-enhanced (DCE) T1 and DSC T2 MRI perfusion findings. MATERIAL AND METHODS This retrospective analysis included 19 patients with histopathologically diagnosed PCNSL and 21 individuals with GBM. DCE T1 vascular permeability perfusion values including K-trans, Ve, Kep, IAUGC, and DSC T2 perfusion values including cerebral blood volume (CBV) and cerebral blood flow (CBF) in axial sections from the pathological lesion and contralateral normal brain parenchyma were measured quantitatively using region of interest analysis. RESULTS The study observed no statistically significant difference between patients with PCNSL (T/B cell) and GBM in the median values of DCE T1 perfusion ratios (P > 0.05). Nevertheless, the DSC T2 perfusion ratios showed a substantial distinction between the two groups. In contrast to patients with PCNSL (1.185 vs. 1.224, respectively), those with GBM had higher median levels of r-CBV and r-CBF (2.898 vs. 2.467, respectively; P 0.01). A cutoff value of ≤1.473 for r-CBV (Lesion/N) and ≤1.6005 for r-CBF (Lesion/N) was found to estimate the positivity of PCNSL. CONCLUSION DSC T2 MRI perfusion values showed lower r-CBV and r-CBF values in PCNSL patients compared to GBM patients. According to the findings, r-CBV and r-CBF are the most accurate MRI perfusion parameters for distinguishing between PCSNL and GBM.
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Affiliation(s)
- Hamza Soydan
- Department of Radiology, Ankara Sincan Educational and Research Hospital, Ankara, Turkey
| | | | - Turay Cesur
- Department of Radiology, Ankara Atatürk Sanatoryum Educational and Research Hospital, Ankara, Turkey
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Sanvito F, Kaufmann TJ, Cloughesy TF, Wen PY, Ellingson BM. Standardized brain tumor imaging protocols for clinical trials: current recommendations and tips for integration. FRONTIERS IN RADIOLOGY 2023; 3:1267615. [PMID: 38152383 PMCID: PMC10751345 DOI: 10.3389/fradi.2023.1267615] [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: 07/26/2023] [Accepted: 11/24/2023] [Indexed: 12/29/2023]
Abstract
Standardized MRI acquisition protocols are crucial for reducing the measurement and interpretation variability associated with response assessment in brain tumor clinical trials. The main challenge is that standardized protocols should ensure high image quality while maximizing the number of institutions meeting the acquisition requirements. In recent years, extensive effort has been made by consensus groups to propose different "ideal" and "minimum requirements" brain tumor imaging protocols (BTIPs) for gliomas, brain metastases (BM), and primary central nervous system lymphomas (PCSNL). In clinical practice, BTIPs for clinical trials can be easily integrated with additional MRI sequences that may be desired for clinical patient management at individual sites. In this review, we summarize the general concepts behind the choice and timing of sequences included in the current recommended BTIPs, we provide a comparative overview, and discuss tips and caveats to integrate additional clinical or research sequences while preserving the recommended BTIPs. Finally, we also reflect on potential future directions for brain tumor imaging in clinical trials.
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Affiliation(s)
- Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | | | - Timothy F. Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, MA, United States
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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Sanvito F, Raymond C, Cho NS, Yao J, Hagiwara A, Orpilla J, Liau LM, Everson RG, Nghiemphu PL, Lai A, Prins R, Salamon N, Cloughesy TF, Ellingson BM. Simultaneous quantification of perfusion, permeability, and leakage effects in brain gliomas using dynamic spin-and-gradient-echo echoplanar imaging MRI. Eur Radiol 2023; 34:10.1007/s00330-023-10215-z. [PMID: 37882836 PMCID: PMC11045669 DOI: 10.1007/s00330-023-10215-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 07/05/2023] [Accepted: 07/27/2023] [Indexed: 10/27/2023]
Abstract
OBJECTIVE To determine the feasibility and biologic correlations of dynamic susceptibility contrast (DSC), dynamic contrast enhanced (DCE), and quantitative maps derived from contrast leakage effects obtained simultaneously in gliomas using dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI) during a single contrast injection. MATERIALS AND METHODS Thirty-eight patients with enhancing brain gliomas were prospectively imaged with dynamic SAGE-EPI, which was processed to compute traditional DSC metrics (normalized relative cerebral blood flow [nrCBV], percentage of signal recovery [PSR]), DCE metrics (volume transfer constant [Ktrans], extravascular compartment [ve]), and leakage effect metrics: ΔR2,ss* (reflecting T2*-leakage effects), ΔR1,ss (reflecting T1-leakage effects), and the transverse relaxivity at tracer equilibrium (TRATE, reflecting the balance between ΔR2,ss* and ΔR1,ss). These metrics were compared between patient subgroups (treatment-naïve [TN] vs recurrent [R]) and biological features (IDH status, Ki67 expression). RESULTS In IDH wild-type gliomas (IDHwt-i.e., glioblastomas), previous exposure to treatment determined lower TRATE (p = 0.002), as well as higher PSR (p = 0.006), Ktrans (p = 0.17), ΔR1,ss (p = 0.035), ve (p = 0.006), and ADC (p = 0.016). In IDH-mutant gliomas (IDHm), previous treatment determined higher Ktrans and ΔR1,ss (p = 0.026). In TN-gliomas, dynamic SAGE-EPI metrics tended to be influenced by IDH status (p ranging 0.09-0.14). TRATE values above 142 mM-1s-1 were exclusively seen in TN-IDHwt, and, in TN-gliomas, this cutoff had 89% sensitivity and 80% specificity as a predictor of Ki67 > 10%. CONCLUSIONS Dynamic SAGE-EPI enables simultaneous quantification of brain tumor perfusion and permeability, as well as mapping of novel metrics related to cytoarchitecture (TRATE) and blood-brain barrier disruption (ΔR1,ss), with a single contrast injection. CLINICAL RELEVANCE STATEMENT Simultaneous DSC and DCE analysis with dynamic SAGE-EPI reduces scanning time and contrast dose, respectively alleviating concerns about imaging protocol length and gadolinium adverse effects and accumulation, while providing novel leakage effect metrics reflecting blood-brain barrier disruption and tumor tissue cytoarchitecture. KEY POINTS • Traditionally, perfusion and permeability imaging for brain tumors requires two separate contrast injections and acquisitions. • Dynamic spin-and-gradient-echo echoplanar imaging enables simultaneous perfusion and permeability imaging. • Dynamic spin-and-gradient-echo echoplanar imaging provides new image contrasts reflecting blood-brain barrier disruption and cytoarchitecture characteristics.
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Affiliation(s)
- Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
- Unit of Radiology, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Viale Camillo Golgi 19, 27100, Pavia, Italy
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Nicholas S Cho
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, 7400 Boelter Hall, Los Angeles, CA, 90095, USA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
- Department of Radiology, Juntendo University School of Medicine, Bunkyo City, 2-Chōme-1-1 Hongō, Tokyo, 113-8421, Japan
| | - Joey Orpilla
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Richard G Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Phioanh L Nghiemphu
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Albert Lai
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Robert Prins
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, 924 Westwood Blvd, Los Angeles, CA, 90024, USA.
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA.
- Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA.
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, 7400 Boelter Hall, Los Angeles, CA, 90095, USA.
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA.
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, 885 Tiverton Dr, Los Angeles, CA, 90095, USA.
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Yu X, Hong W, Ye M, Lai M, Shi C, Li L, Ye K, Xu J, Ai R, Shan C, Cai L, Luo L. Atypical primary central nervous system lymphoma and glioblastoma: multiparametric differentiation based on non-enhancing volume, apparent diffusion coefficient, and arterial spin labeling. Eur Radiol 2023; 33:5357-5367. [PMID: 37171492 PMCID: PMC10326108 DOI: 10.1007/s00330-023-09681-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 01/02/2023] [Accepted: 02/24/2023] [Indexed: 05/13/2023]
Abstract
OBJECTIVES To evaluate the multiparametric diagnostic performance with non-enhancing tumor volume, apparent diffusion coefficient (ADC), and arterial spin labeling (ASL) to differentiate between atypical primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM). METHODS One hundred and fifty-eight patients with pathologically confirmed typical PCNSL (n = 59), atypical PCNSL (hemorrhage, necrosis, or heterogeneous contrast enhancement, n = 29), and GBM (n = 70) were selected. Relative minimum ADC (rADCmin), mean (rADCmean), maximum (rADCmax), and rADCmax-min (rADCdif) were obtained by standardization of the contralateral white matter. Maximum cerebral blood flow (CBFmax) was obtained according to the ASL-CBF map. The regions of interests (ROIs) were manually delineated on the inner side of the tumor to further generate a 3D-ROI and obtain the non-enhancing tumor (nET) volume. The area under the curve (AUC) was used to evaluate the diagnostic performance. RESULTS Atypical PCNSLs showed significantly lower rADCmax, rADCmean, and rADCdif than that of GBMs. GBMs showed significantly higher CBFmax and nET volume ratios than that of atypical PCNSLs. Combined three-variable models with rADCmean, CBFmax, and nET volume ratio were superior to one- and two-variable models. The AUC of the three-variable model was 0.96, and the sensitivity and specificity were 90% and 96.55%, respectively. CONCLUSION The combined evaluation of rADCmean, CBFmax, and nET volume allowed for reliable differentiation between atypical PCNSL and GBM. KEY POINTS • Atypical PCNSL is easily misdiagnosed as glioblastoma, which leads to unnecessary surgical resection. • The nET volume, ADC, and ASL-derived parameter (CBF) were lower for atypical PCNSL than that for glioblastoma. • The combination of multiple parameters performed well (AUC = 0.96) in the discrimination between atypical PCNSL and glioblastoma.
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Affiliation(s)
- Xiaojun Yu
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No. 613, Huangpu Road West, Tianhe District, Guangdong Province, Guangzhou, 510630, China
| | - Weiping Hong
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, 510510, China
| | - Minting Ye
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, 510510, China
| | - Mingyao Lai
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, 510510, China
| | - Changzheng Shi
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No. 613, Huangpu Road West, Tianhe District, Guangdong Province, Guangzhou, 510630, China
| | - Linzhen Li
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No. 613, Huangpu Road West, Tianhe District, Guangdong Province, Guangzhou, 510630, China
| | - Kunlin Ye
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No. 613, Huangpu Road West, Tianhe District, Guangdong Province, Guangzhou, 510630, China
| | - Jiali Xu
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No. 613, Huangpu Road West, Tianhe District, Guangdong Province, Guangzhou, 510630, China
| | - Ruyu Ai
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, 510510, China
| | - Changguo Shan
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, 510510, China
| | - Linbo Cai
- Department of Oncology, Guangdong Sanjiu Brain Hospital, Guangzhou, 510510, China.
| | - Liangping Luo
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, No. 613, Huangpu Road West, Tianhe District, Guangdong Province, Guangzhou, 510630, China.
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Feng A, Li L, Huang T, Li S, He N, Huang L, Zeng M, Lyu J. Differentiating glioblastoma from primary central nervous system lymphoma of atypical manifestation using multiparametric magnetic resonance imaging: A comparative study. Heliyon 2023; 9:e15150. [PMID: 37095995 PMCID: PMC10121909 DOI: 10.1016/j.heliyon.2023.e15150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 03/24/2023] [Accepted: 03/28/2023] [Indexed: 04/26/2023] Open
Abstract
Background The aim of this study is to evaluate the diagnostic efficiency of magnetic resonance imaging (MRI) of single parameters, unimodality, and bimodality in distinguishing glioblastoma (GBM) from atypical primary central nervous system lymphoma (PCNSL) based on diffusion-weighted imaging (DWI), dynamic susceptibility contrast (DSC) enhancement, diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (1H-MRS) findings. Methods The cohort included 108 patients pathologically diagnosed with GBM and 54 patients pathologically diagnosed with PCNSL. Pretreatment morphological MRI, DWI, DSC, DTI and MRS were all performed on each patient. The quantitative parameters of multimodal MRI were measured and compared between the patients in the GBM and atypical PCNSL groups, and those parameters showing a significant difference (p < 0.05) between patients in the GBM and atypical PCNSL groups were used to develop one-parameters, unimodality, and bimodality models. We evaluated the efficiency of different models in distinguishing GBM from atypical PCNSL by performing receiver operating characteristic analysis (ROC). Results Atypical PCNSL had lower minimum apparent diffusion coefficient (ADCmin), mean ADC (ADCmean), relative ADC (rADC), mean relative cerebral blood volume (rCBVmean), maximum rCBV (rCBVmax), fractional anisotropy (FA), axial diffusion coefficient (DA) and radial diffusion coefficient (DR) values and higher choline/creatine (Cho/Cr) and lipid/creatine (Lip/Cr) ratios than GBM (all p < 0.05). The rCBVmax, DTI and DSC + DTI data were optimal models of single-parameter, unimodality and bimodality for differentiation of GBM from atypical PCNSL, yielding areas under the curves (AUCs) of 0.905, 0.954, and 0.992, respectively. Conclusions Models of single-parameter, unimodality and bimodality based on muti multiparameter functional MRI may help to discriminate GBM from atypical PCNSL.
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Affiliation(s)
- Aozi Feng
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Li Li
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Tao Huang
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Shuna Li
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Ningxia He
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Liying Huang
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Mengnan Zeng
- College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou, Henan 450046, China
- Corresponding author.
| | - Jun Lyu
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
- Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Guangzhou, Guangdong 510632, China
- Corresponding author. Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China.
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Luna LP, Ahmed A, Daftaribesheli L, Deng F, Intrapiromkul J, Lanzman BA, Yedavalli V. Arterial spin labeling clinical applications for brain tumors and tumor treatment complications: A comprehensive case-based review. Neuroradiol J 2023; 36:129-141. [PMID: 35815750 PMCID: PMC10034709 DOI: 10.1177/19714009221114444] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Arterial spin labeling (ASL) is a noninvasive neuroimaging technique that allows for quantifying cerebral blood flow without intravenous contrast. Various neurovascular disorders and tumors have cerebral blood flow alterations. Identifying these perfusion changes through ASL can aid in the diagnosis, especially in entities with normal structural imaging. In addition, complications of tumor treatment and tumor progression can also be monitored using ASL. In this case-based review, we demonstrate the clinical applications of ASL in diagnosing and monitoring brain tumors and treatment complications.
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Affiliation(s)
- Licia P Luna
- Russell H. Morgan Department of
Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, MA, USA
| | - Amara Ahmed
- Florida State University College of
Medicine, Tallahassee, FL, USA
| | - Laleh Daftaribesheli
- Russell H. Morgan Department of
Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, MA, USA
| | - Francis Deng
- Massachusetts General Hospital and
Harvard Medical School, Boston, MA, USA
| | - Jarunee Intrapiromkul
- Russell H. Morgan Department of
Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, MA, USA
| | - Bryan A Lanzman
- Department of Radiology, Stanford University, California, USA
| | - Vivek Yedavalli
- Russell H. Morgan Department of
Radiology and Radiological Science, Johns Hopkins Hospital, Baltimore, MA, USA
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Hernandez J, Davidson C, Reilly T, Hanbali S, Abou-Al-Shaar H, Ebrahim G, Nguyen A, Lucke-Wold B. Research on the Damage of the Central Nervous System Lymphoma to the Nervous System. JOURNAL OF MODERN MEDICAL ONCOLOGY 2023; 3:1. [PMID: 36911420 PMCID: PMC10003645 DOI: 10.53964/jmmo.2023001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
Management of central nervous system (CNS) lymphoma requires multidisciplinary care. The disease can manifest in the context of immunocompromised states or in the context of chronic infections. Nervous system damage from this lymphoma has highly variable presentation that is dependent on the location of the tumor lesions. Damage from disease progression can lead to lasting neurologic deficits and even death. However, some lesions are a consequence of radiation-induced neurotoxicity. This review discusses the sources of and consequences of brain damage due to tumor damage and the associated effect of clinical therapies. We discuss workup, management, and treatments. These include chemotherapy and radiation techniques. We discuss potential complications and avoidance strategies. The review will serve as a user-friendly resource for clinicians.
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Affiliation(s)
- Jairo Hernandez
- Department of Neurosurgery, University of Florida, Gainesville, USA
| | | | - Thomas Reilly
- Department of Neurosurgery, University of Florida, Gainesville, USA
| | - Seif Hanbali
- Department of Neurosurgery, University of Florida, Gainesville, USA
| | - Hussam Abou-Al-Shaar
- Department of Neurosurgery, University of Pittsburgh Medical Center, Pittsburgh, USA
| | - Ghaidaa Ebrahim
- Department of Neurosurgery, University of Florida, Gainesville, USA
| | - Andrew Nguyen
- Department of Neurosurgery, University of Florida, Gainesville, USA
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Chul Lee Y, Suh S, Ryoo I, Jung H, Joo L. Imaging finding and analysis of brain lymphoma in contrast-enhanced fluid attenuated inversion recovery sequence. Eur J Radiol 2022; 155:110490. [PMID: 36030660 DOI: 10.1016/j.ejrad.2022.110490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 08/07/2022] [Accepted: 08/15/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVE The purpose of this retrospective study was to report and analyze the image findings of contrast-enhanced fluid-attenuated inversion recovery (CE-FLAIR) sequence of lymphoma in the brain. MATERIAL AND METHODS Thirty-two immunocompetent patients with biopsy-proven diffuse large B-cell type lymphoma in the brain were evaluated with pre-treatment MRI examinations from August 2014 to April 2020. As stereotactic studies on the day of biopsy, FLAIR and T1-weighted axial images were acquired in 2 mm thickness, before and after administrating gadolinium-based contrast agents, with 3.0 Tesla MR machines. Respective subtraction images were also obtained for both CE-FLAIR and contrast-enhanced T1-wieghted image (CE-T1WI) sequences. The imaging findings, especially the enhancement pattern on CE-FLAIR sequence, were analyzed qualitatively and quantitatively, using semi-automatic segmentation. RESULTS On CE-FLAIR images, brain lymphomas were poorly enhanced, while showing peripheral rim enhancement (54 of 58 lesions, 93.1 %) and central enhancing foci (40 of 58 lesions, 69.0 %). Seventy percent of central enhancing foci were correlated to areas with low signal intensity on CE-T1WI. In quantitative analysis, the mean signal intensity of CE-T1WI subtraction was 490.44 and that of FLAIR subtraction was 206.13. The standard deviation of all signal intensity values in CE-T1WI subtraction sequence was 143.45, while that of CE-FLAIR subtraction sequence was 118.41. CONCLUSION On CE-FLAIR, brain lymphomas showed relatively poor and homogeneous enhancement, when compared to CE-T1WI. Most brain lymphomas displayed peripheral rim enhancement and central enhancing foci.
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Affiliation(s)
- Yoon Chul Lee
- Department of Radiology, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, South Korea
| | - Sangil Suh
- Department of Radiology, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, South Korea.
| | - Inseon Ryoo
- Department of Radiology, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, South Korea
| | - Hyena Jung
- Department of Radiology, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, South Korea
| | - Leehi Joo
- Department of Radiology, Korea University Guro Hospital, 148 Gurodong-ro, Guro-gu, Seoul, South Korea
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Solar P, Hendrych M, Barak M, Valekova H, Hermanova M, Jancalek R. Blood-Brain Barrier Alterations and Edema Formation in Different Brain Mass Lesions. Front Cell Neurosci 2022; 16:922181. [PMID: 35910247 PMCID: PMC9334679 DOI: 10.3389/fncel.2022.922181] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Accepted: 06/20/2022] [Indexed: 12/03/2022] Open
Abstract
Differential diagnosis of brain lesion pathologies is complex, but it is nevertheless crucial for appropriate clinical management. Advanced imaging methods, including diffusion-weighted imaging and apparent diffusion coefficient, can help discriminate between brain mass lesions such as glioblastoma, brain metastasis, brain abscesses as well as brain lymphomas. These pathologies are characterized by blood-brain barrier alterations and have been extensively studied. However, the changes in the blood-brain barrier that are observed around brain pathologies and that contribute to the development of vasogenic brain edema are not well described. Some infiltrative brain pathologies such as glioblastoma are characterized by glioma cell infiltration in the brain tissue around the tumor mass and thus affect the nature of the vasogenic edema. Interestingly, a common feature of primary and secondary brain tumors or tumor-like brain lesions characterized by vasogenic brain edema is the formation of various molecules that lead to alterations of tight junctions and result in blood-brain barrier damage. The resulting vasogenic edema, especially blood-brain barrier disruption, can be visualized using advanced magnetic resonance imaging techniques, such as diffusion-weighted imaging and apparent diffusion coefficient. This review presents a comprehensive overview of blood-brain barrier changes contributing to the development of vasogenic brain edema around glioblastoma, brain metastases, lymphomas, and abscesses.
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Affiliation(s)
- Peter Solar
- Department of Neurosurgery, St. Anne’s University Hospital Brno, Faculty of Medicine, Masaryk University, Brno, Czechia
- Department of Neurosurgery, St. Anne’s University Hospital, Brno, Czechia
| | - Michal Hendrych
- First Department of Pathology, St. Anne’s University Hospital Brno, Faculty of Medicine, Masaryk University, Brno, Czechia
- First Department of Pathology, St. Anne’s University Hospital, Brno, Czechia
| | - Martin Barak
- Department of Neurosurgery, St. Anne’s University Hospital Brno, Faculty of Medicine, Masaryk University, Brno, Czechia
- Department of Neurosurgery, St. Anne’s University Hospital, Brno, Czechia
| | - Hana Valekova
- Department of Neurosurgery, St. Anne’s University Hospital Brno, Faculty of Medicine, Masaryk University, Brno, Czechia
- Department of Neurosurgery, St. Anne’s University Hospital, Brno, Czechia
| | - Marketa Hermanova
- First Department of Pathology, St. Anne’s University Hospital Brno, Faculty of Medicine, Masaryk University, Brno, Czechia
- First Department of Pathology, St. Anne’s University Hospital, Brno, Czechia
| | - Radim Jancalek
- Department of Neurosurgery, St. Anne’s University Hospital Brno, Faculty of Medicine, Masaryk University, Brno, Czechia
- Department of Neurosurgery, St. Anne’s University Hospital, Brno, Czechia
- *Correspondence: Radim Jancalek,
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Michel M, Lucke-Wold N, Hosseini MR, Panther E, Reddy R, Lucke-Wold B. CNS Lymphoma: Clinical Pearls and Management Considerations. BIOMEDICAL RESEARCH AND CLINICAL REVIEWS 2022; 7:121. [PMID: 35832688 PMCID: PMC9275513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
Primary CNS lymphoma presents unique challenges for the clinician. New evidence has emerged regarding the appropriate workup, management considerations, and treatment. In this paper, we highlight the clinical presentations, disease prognosis, and management considerations. We place specific emphasis on the decision tree for immunocompetent and immunocompromised. The key imaging characteristics are discussed. Once biopsy prove lymphoma, important management considerations are addressed. We highlight need for follow up and role for surgery verse radiation. Finally, we present emerging treatment options and pre-clinical work that will be making its way through the pipeline. This up-to-date review will serve as a key learning tool for clinicians and researchers.
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Affiliation(s)
- Michelot Michel
- Department of Neurosurgery, University of Florida, Gainesville
| | | | | | - Eric Panther
- Department of Neurosurgery, University of Florida, Gainesville
| | - Ramya Reddy
- Department of Neurosurgery, University of Florida, Gainesville
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11
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Role of intra-tumoral vasculature imaging features on susceptibility weighted imaging in differentiating primary central nervous system lymphoma from glioblastoma: a multiparametric comparison with pathological validation. Neuroradiology 2022; 64:1801-1818. [DOI: 10.1007/s00234-022-02946-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 04/04/2022] [Indexed: 10/18/2022]
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12
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Cetinkaya E, Aralasmak A, Atasoy B, Tokdemir S, Toprak H, Toprak A, Kurtcan S, Alkan A. Dynamic Contrast-Enhanced MR Perfusion in Differentiation of Benign and Malignant Brain Lesions. Curr Med Imaging 2022; 18:1099-1105. [PMID: 35331119 DOI: 10.2174/1573405618666220324112457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 01/02/2022] [Accepted: 01/18/2022] [Indexed: 11/22/2022]
Abstract
Background- We aimed to differentiate Glioblastoma Multiforme (GBM) from benign lesions like Developmental Venous Anomaly (DVA) and Cavernous Malformation (CM) by Dynamic Contrast-Enhanced MR Perfusion (DCE-MRP) markers such as Ktrans, Ve, Kep, and IAUC. Method-We retrospectively evaluated 20 patients; 10 GBM as the malignant group, 5 CM and 5 DVA as the benign group. Ktrans, Kep, Ve, and IAUC parameters were measured by DCE-MRP, within the lesion, at perilesional nonenhancing white matter (PLWM) and at contralateral normal appearing white matter (CLWM). All benign and malignant lesions exhibited significantly increased Ktrans, Ve, and IAUC values compared to PLWM and CLWM (p < 0.001, p=0.006 and p<0.001). Result-Subtracted Kep values between lesion and PLWM were significantly different between the benign and malignant groups, as the malignant group exhibited higher subtracted Kep values (p 0.035). For the malignant group; Ktrans and IAUC values at the lesion were positively correlated (r 0.911), while Kep and Ve at CLWM were negatively and strongly correlated (r 0.798). For the benign group; Ktrans with Ve and Ktrans with IAUC lesion (r 0.708 and r 0.816 respectively), Ktrans and IAUC at PLWM (r 0.809), Ktrans and IAUC at CLWM(r 0.798) were strongly and positively correlated. Ktrans, Ve, and IAUC values can be used to demarcate the lesion in both groups. Conclusion- Ktrans strongly correlates with IAUC and they can be used instead of each other in both benign and malignant lesions. DCE-MRP cannot be used in the differentiation of malignant lesions from benign vascular lesions. However, subtracted Kep values can be used to differentiate GBM from benign vascular lesions.
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Affiliation(s)
- Ezra Cetinkaya
- Department of Radiology, Bezmialem Vakif University, 34093 Istanbul, Turkey
| | - Ayse Aralasmak
- Department of Radiology, Bezmialem Vakif University, 34093 Istanbul, Turkey
| | - Bahar Atasoy
- Department of Radiology, Bezmialem Vakif University, 34093 Istanbul, Turkey
| | - Sevil Tokdemir
- Department of Radiology, Bezmialem Vakif University, 34093 Istanbul, Turkey
| | - Huseyin Toprak
- Department of Radiology, Bezmialem Vakif University, 34093 Istanbul, Turkey
| | - Ali Toprak
- Department of Biostatistics and Medical Informatics, Bezmialem Vakif University, 34093 Istanbul, Turkey
| | - Serpil Kurtcan
- Department of Radiology, Bezmialem Vakif University, 34093 Istanbul, Turkey
| | - Alpay Alkan
- Department of Radiology, Bezmialem Vakif University, 34093 Istanbul, Turkey
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13
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Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading. Cancers (Basel) 2022; 14:cancers14061432. [PMID: 35326580 PMCID: PMC8946242 DOI: 10.3390/cancers14061432] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/01/2022] [Accepted: 03/08/2022] [Indexed: 11/17/2022] Open
Abstract
Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.
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14
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Batalov AI, Afandiev RM, Zakharova NE, Pogosbekyan EL, Shulgina AA, Kobyakov GL, Potapov AA, Pronin IN. 3D pseudo-continuous arterial spin labeling-MRI (3D PCASL-MRI) in the differential diagnosis between glioblastomas and primary central nervous system lymphomas. Neuroradiology 2022; 64:1539-1545. [PMID: 35112216 DOI: 10.1007/s00234-021-02888-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 12/18/2021] [Indexed: 10/19/2022]
Abstract
PURPOSE The aim of the study was to compare the parameters of blood flow in glioblastomas and primary central nervous system lymphomas (PCNSLs), measured by pseudo-continuous arterial spin labeling MRI (3D PCASL), and to determine the informativeness of this method in the differential diagnosis between these lesions. METHODS The study included MRI data of 139 patients with PCNSL (n = 21) and glioblastomas (n = 118), performed in the Burdenko Neurosurgical Center. No patients received chemotherapy, hormone therapy, or radiation therapy prior to MRI. On the 3D PCASL perfusion map, the absolute and normalized values of tumor blood flow were calculated in the glioblastoma and PCNSL groups (maxTBFmean and nTBF). RESULTS MaxTBFmean and nTBF in the glioblastoma group were significantly higher than those in the PCNSL group: 168.9 ml/100 g/min versus 65.6 and 9.3 versus 3.7, respectively (p < 0.001). Arterial spin labeling perfusion had high sensitivity (86% for maxTBFmean, 95% for nTBF) and specificity (77% for maxTBFmean, 73% for nTBF) in the differential diagnosis between PCNSL and glioblastomas. Blood flow thresholds were 98.9 ml/100 g/min using absolute blood flow values and 6.1 using normalized values, AUC > 0.88. CONCLUSION The inclusion of 3D PCASL in the standard MRI protocol can increase the specificity of the differential diagnosis between glioblastomas and PCNSL.
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Affiliation(s)
- A I Batalov
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - R M Afandiev
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation.
| | - N E Zakharova
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - E L Pogosbekyan
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - A A Shulgina
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - G L Kobyakov
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - A A Potapov
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - I N Pronin
- Federal State Autonomous Institution N.N. Burdenko National Medical Research Center of Neurosurgery of the Ministry of Health of the Russian Federation, Moscow, Russian Federation
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15
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Neuroinflammation preceding primary central nervous system lymphoma (PCNSL) - Case reports and literature review. J Clin Neurosci 2021; 89:381-388. [PMID: 34083111 DOI: 10.1016/j.jocn.2021.05.038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Revised: 05/13/2021] [Accepted: 05/20/2021] [Indexed: 11/22/2022]
Abstract
Primary central nervous system lymphoma (PCNSL) is a rare and aggressive form of extra-nodal non-Hodgkin's lymphoma. Corticosteroids cause transient regression of PCNSL at the radiological and histological level. A growing number of case reports describe histologically confirmed neuroinflammation (sentinel lesions) heralding the development of PCNSL. We present two further cases of sentinel lesions contextualised by a review of past literature. Our aims are to collate existing knowledge on sentinel lesions in PCNSL and explore their pathophysiological significance. Two cases were identified (n = 2) from a cohort of 104 patients with PCNSL referred to a tertiary neurosurgery centre. A literature search identified previously reported cases (n = 14). Median age was 57.5 (range; 26-72); pre-biopsy corticosteroid administration was reported in 50% of cases (n = 8); mean time between biopsies was 10 months (range; 3-60). Common MRI features were homogenous enhancement (10;71.4%) and T2-hyperintensity (11;100%). Histochemical analysis of sentinel lesion biopsy revealed inflammatory CD3/4/5/8-positive T-cells (14; 100%), demyelination (13; 81.3%), rare/scattered CD20-postive B-cells (11;78.6%) and CD68-positive macrophages (10;71.4%). Repeat biopsy confirmed PCNSL in all cases. Waxing and waning CNS inflammation has been identified in 16 patients ultimately diagnosed with PCNSL. Neuro-specialists should be aware of this atypical presentation and maintain a high index of suspicion for lymphoma despite histopathology negative for lymphoma when clinical or radiological features indicate PCNSL.
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16
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Kang KM, Choi SH, Chul-Kee P, Kim TM, Park SH, Lee JH, Lee ST, Hwang I, Yoo RE, Yun TJ, Kim JH, Sohn CH. Differentiation between glioblastoma and primary CNS lymphoma: application of DCE-MRI parameters based on arterial input function obtained from DSC-MRI. Eur Radiol 2021; 31:9098-9109. [PMID: 34003350 DOI: 10.1007/s00330-021-08044-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 04/06/2021] [Accepted: 05/04/2021] [Indexed: 11/24/2022]
Abstract
OBJECTIVE This study aimed to evaluate whether arterial input functions (AIFs) obtained from dynamic susceptibility contrast (DSC)-MRI (AIFDSC) improve the reliability and diagnostic accuracy of dynamic contrast-enhanced (DCE)-derived pharmacokinetic (PK) parameters for differentiating glioblastoma from primary CNS lymphoma (PCNSL) compared with AIFs derived from DCE-MRI (AIFDCE). METHODS This retrospective study included 172 patients with glioblastoma (n = 147) and PCNSL (n = 25). All patients had undergone preoperative DSC- and DCE-MRI. The volume transfer constant (Ktrans), volume of the vascular plasma space (vp), and volume of the extravascular extracellular space (ve) were acquired using AIFDSC and AIFDCE. The relative cerebral blood volume (rCBV) was obtained from DSC-MRI. Intraclass correlation coefficients (ICC) and ROC curves were used to assess the reliability and diagnostic accuracy of individual parameters. RESULTS The mean Ktrans, vp, and ve values revealed better ICCs with AIFDSC than with AIFDCE (Ktrans, 0.911 vs 0.355; vp, 0.766 vs 0.503; ve, 0.758 vs 0.657, respectively). For differentiating all glioblastomas from PCNSL, the mean rCBV (AUC = 0.856) was more accurate than the AIFDSC-driven mean Ktrans, which had the largest AUC (0.711) among the DCE-derived parameters (p = 0.02). However, for glioblastomas with low rCBV (≤ 75th percentile of PCNSL; n = 30), the AIFDSC-driven mean Ktrans and vp were more accurate than rCBV (AUC: Ktrans, 0.807 vs rCBV, 0.515, p = 0.004; vp, 0.715 vs rCBV, p = 0.045). CONCLUSION DCE-derived PK parameters using the AIFDSC showed improved reliability and diagnostic accuracy for differentiating glioblastoma with low rCBV from PCNSL. KEY POINTS • An accurate differential diagnosis of glioblastoma and PCNSL is crucial because of different therapeutic strategies. • In contrast to the rCBV from DSC-MRI, another perfusion imaging technique, the DCE parameters for the differential diagnosis have been limited because of the low reliability of AIFs from DCE-MRI. • When we analyzed DCE-MRI data using AIFs from DSC-MRI (AIFDSC), AIFDSC-driven DCE parameters showed improved reliability and better diagnostic accuracy than rCBV for differentiating glioblastoma with low rCBV from PCNSL.
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Affiliation(s)
- Koung Mi Kang
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea. .,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea. .,Center for Nanoparticle Research, Institute for Basic Science, and School of Chemical and Biological Engineering, Seoul National University, Seoul, Republic of Korea.
| | - Park Chul-Kee
- Department of Neurosurgery and Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Tae Min Kim
- Department of Internal Medicine and Cancer Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Sung-Hye Park
- Department of Pathology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Joo Ho Lee
- Department of Radiation Oncology and Cancer Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Soon-Tae Lee
- Department of Neurology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Roh-Eul Yoo
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Ji-Hoon Kim
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea
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Hatakeyama J, Ono T, Takahashi M, Oda M, Shimizu H. Differentiating between Primary Central Nervous System Lymphoma and Glioblastoma: The Diagnostic Value of Combining 18F-fluorodeoxyglucose Positron Emission Tomography with Arterial Spin Labeling. Neurol Med Chir (Tokyo) 2021; 61:367-375. [PMID: 33967177 PMCID: PMC8258004 DOI: 10.2176/nmc.oa.2020-0375] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Using conventional magnetic resonance imaging (MRI) methods, the differentiation of primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) is often difficult due to overlapping imaging characteristics. This study aimed to evaluate the diagnostic value of combining 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) with arterial spin labeling (ASL) for differentiating PCNSL from GBM. In all, 20 patients with PCNSL and 55 with GBM were retrospectively examined. From the FDG-PET data, the maximum standardized uptake values (SUVmax) and the ratio of tumor to normal contralateral gray matter (T/N_SUVmax) were calculated. From the ASL data, the T/N ratio of the maximum tumor blood flow (relative TBFmax: rTBFmax) was obtained. Diagnostic performance of each parameter was analyzed using univariate and multivariate logistic regression analyses and receiver-operating characteristic (ROC) curve analyses. A generalized linear model was applied for comparing the performance of FDG-PET and ASL individually, and in combination. In univariate analysis, SUVmax and T/N_SUVmax were statistically higher in patients with PCNSL and rTBFmax was higher in patients with GBM. In the multivariate analysis, T/N_SUVmax and rTBFmax were statistically independent. The sensitivity, specificity, and area under the curve (AUC) for discriminating PCNSL from GBM were 100%, 87.3%, and 0.950 in T/N_SUVmax; 90%, 72.7%, and 0.824 in rTBFmax; and 95%, 96.4%, and 0.991 in the combined model, respectively. The combined use of T/N_SUVmax and rTBFmax may contribute to better differentiation between PCNSL and GBM.
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Affiliation(s)
- Junya Hatakeyama
- Department of Neurosurgery, Akita University Graduate School of Medicine
| | - Takahiro Ono
- Department of Neurosurgery, Akita University Graduate School of Medicine
| | - Masataka Takahashi
- Department of Neurosurgery, Akita University Graduate School of Medicine
| | - Masaya Oda
- Department of Neurosurgery, Akita University Graduate School of Medicine
| | - Hiroaki Shimizu
- Department of Neurosurgery, Akita University Graduate School of Medicine
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18
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Radiomics-based differentiation between glioblastoma and primary central nervous system lymphoma: a comparison of diagnostic performance across different MRI sequences and machine learning techniques. Eur Radiol 2021; 31:8703-8713. [PMID: 33890149 DOI: 10.1007/s00330-021-07845-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 02/03/2021] [Accepted: 02/26/2021] [Indexed: 12/22/2022]
Abstract
OBJECTIVES Despite the robust diagnostic performance of MRI-based radiomic features for differentiating between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) reported on prior studies, the best sequence or a combination of sequences and model performance across various machine learning pipelines remain undefined. Herein, we compare the diagnostic performance of multiple radiomics-based models to differentiate GBM from PCNSL. METHODS Our retrospective study included 94 patients (34 with PCNSL and 60 with GBM). Model performance was assessed using various MRI sequences across 45 possible model and feature selection combinations for nine different sequence permutations. Predictive performance was assessed using fivefold repeated cross-validation with five repeats. The best and worst performing models were compared to assess differences in performance. RESULTS The predictive performance, both using individual and a combination of sequences, was fairly robust across multiple top performing models (AUC: 0.961-0.977) but did show considerable variation between the best and worst performing models. The top performing individual sequences had comparable performance to multiparametric models. The best prediction model in our study used a combination of ADC, FLAIR, and T1-CE achieving the highest AUC of 0.977, while the second ranked model used T1-CE and ADC, achieving a cross-validated AUC of 0.975. CONCLUSION Radiomics-based predictive accuracy can vary considerably, based on the model and feature selection methods as well as the combination of sequences used. Also, models derived from limited sequences show performance comparable to those derived from all five sequences. KEY POINTS • Radiomics-based diagnostic performance of various machine learning models for differentiating glioblastoma and PCNSL varies considerably. • ML models using limited or multiple MRI sequences can provide comparable performance, based on the chosen model. • Embedded feature selection models perform better than models using a priori feature reduction.
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19
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Gupta M, Gupta A, Yadav V, Parvaze SP, Singh A, Saini J, Patir R, Vaishya S, Ahlawat S, Gupta RK. Comparative evaluation of intracranial oligodendroglioma and astrocytoma of similar grades using conventional and T1-weighted DCE-MRI. Neuroradiology 2021; 63:1227-1239. [PMID: 33469693 DOI: 10.1007/s00234-021-02636-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 01/05/2021] [Indexed: 11/25/2022]
Abstract
PURPOSE This retrospective study was performed on a 3T MRI to determine the unique conventional MR imaging and T1-weighted DCE-MRI features of oligodendroglioma and astrocytoma and investigate the utility of machine learning algorithms in their differentiation. METHODS Histologically confirmed, 81 treatment-naïve patients were classified into two groups as per WHO 2016 classification: oligodendroglioma (n = 16; grade II, n = 25; grade III) and astrocytoma (n = 10; grade II, n = 30; grade III). The differences in tumor morphology characteristics were evaluated using Z-test. T1-weighted DCE-MRI data were analyzed using an in-house built MATLAB program. The mean 90th percentile of relative cerebral blood flow, relative cerebral blood volume corrected, volume transfer rate from plasma to extracellular extravascular space, and extravascular extracellular space volume values were evaluated using independent Student's t test. Support vector machine (SVM) classifier was constructed to differentiate two groups across grade II, grade III, and grade II+III based on statistically significant features. RESULTS Z-test signified only calcification among conventional MR features to categorize oligodendroglioma and astrocytoma across grade III and grade II+III tumors. No statistical significance was found in the perfusion parameters between two groups and its subtypes. SVM trained on calcification also provided moderate accuracy to differentiate oligodendroglioma from astrocytoma. CONCLUSION We conclude that conventional MR features except calcification and the quantitative T1-weighted DCE-MRI parameters fail to discriminate between oligodendroglioma and astrocytoma. The SVM could not further aid in their differentiation. The study also suggests that the presence of more than 50% T2-FLAIR mismatch may be considered as a more conclusive sign for differentiation of IDH mutant astrocytoma.
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Affiliation(s)
- Mamta Gupta
- Department of Radiology, Fortis Memorial Research Institute, Sector 44, Gurgaon, Haryana, 122002, India
| | - Abhinav Gupta
- Department of Radiology, Fortis Memorial Research Institute, Sector 44, Gurgaon, Haryana, 122002, India
| | - Virendra Yadav
- Centre for Biomedical Engineering, IIT Delhi, New Delhi, India
| | | | - Anup Singh
- Centre for Biomedical Engineering, IIT Delhi, New Delhi, India
| | - Jitender Saini
- National Institute of Mental Health and Neurosciences, Bangalore, Karnataka, India
| | - Rana Patir
- Department of Neurosurgery, Fortis Memorial Research Institute, Sector 44, Gurgaon, Haryana, India
| | - Sandeep Vaishya
- Department of Neurosurgery, Fortis Memorial Research Institute, Sector 44, Gurgaon, Haryana, India
| | - Sunita Ahlawat
- SRL Diagnostics, Fortis Memorial Research Institute, Sector 44, Gurgaon, Haryana, India
| | - Rakesh Kumar Gupta
- Department of Radiology, Fortis Memorial Research Institute, Sector 44, Gurgaon, Haryana, 122002, India.
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20
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Park JE, Kim JY, Kim HS, Shim WH. Comparison of Dynamic Contrast-Enhancement Parameters between Gadobutrol and Gadoterate Meglumine in Posttreatment Glioma: A Prospective Intraindividual Study. AJNR Am J Neuroradiol 2020; 41:2041-2048. [PMID: 33060100 DOI: 10.3174/ajnr.a6792] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Accepted: 07/22/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND AND PURPOSE Differences in molecular properties between one-molar and half-molar gadolinium-based contrast agents are thought to affect parameters obtained from dynamic contrast-enhanced imaging. The aim of our study was to investigate differences in dynamic contrast-enhanced parameters between one-molar nonionic gadobutrol and half-molar ionic gadoterate meglumine in patients with posttreatment glioma. MATERIALS AND METHODS This prospective study enrolled 32 patients who underwent 2 20-minute dynamic contrast-enhanced examinations, one with gadobutrol and one with gadoterate meglumine. The model-free parameter of area under the signal intensity curve from 30 to 1100 seconds and the Tofts model-based pharmacokinetic parameters were calculated and compared intraindividually using paired t tests. Patients were further divided into progression (n = 12) and stable (n = 20) groups, which were compared using Student t tests. RESULTS Gadobutrol and gadoterate meglumine did not show any significant differences in the area under the signal intensity curve or pharmacokinetic parameters of K trans, Ve, Vp, or Kep (all P > .05). Gadobutrol showed a significantly higher mean wash-in rate (0.83 ± 0.64 versus 0.29 ± 0.63, P = .013) and a significantly lower mean washout rate (0.001 ± 0.0001 versus 0.002 ± 0.002, P = .02) than gadoterate meglumine. Trends toward higher area under the curve, K trans, Ve, Vp, wash-in, and washout rates and lower Kep were observed in the progression group in comparison with the treatment-related-change group, regardless of the contrast agent used. CONCLUSIONS Model-free and pharmacokinetic parameters did not show any significant differences between the 2 gadolinium-based contrast agents, except for a higher wash-in rate with gadobutrol and a higher washout rate with gadoterate meglumine, supporting the interchangeable use of gadolinium-based contrast agents for dynamic contrast-enhanced imaging in patients with posttreatment glioma.
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Affiliation(s)
- J E Park
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., W.H.S.), University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - J Y Kim
- Department of Radiology (J.Y.K.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - H S Kim
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., W.H.S.), University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - W H Shim
- From the Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K., W.H.S.), University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
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21
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Chen C, Zheng A, Ou X, Wang J, Ma X. Comparison of Radiomics-Based Machine-Learning Classifiers in Diagnosis of Glioblastoma From Primary Central Nervous System Lymphoma. Front Oncol 2020; 10:1151. [PMID: 33042784 PMCID: PMC7522159 DOI: 10.3389/fonc.2020.01151] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Accepted: 06/08/2020] [Indexed: 02/05/2023] Open
Abstract
Purpose: The purpose of the current study was to evaluate the ability of magnetic resonance (MR) radiomics-based machine-learning algorithms in differentiating glioblastoma (GBM) from primary central nervous system lymphoma (PCNSL). Method: One-hundred and thirty-eight patients were enrolled in this study. Radiomics features were extracted from contrast-enhanced MR images, and the machine-learning models were established using five selection methods (distance correlation, random forest, least absolute shrinkage and selection operator (LASSO), eXtreme gradient boosting (Xgboost), and Gradient Boosting Decision Tree) and three radiomics-based machine-learning classifiers [linear discriminant analysis (LDA), support vector machine (SVM), and logistic regression (LR)]. Sensitivity, specificity, accuracy, and areas under curves (AUC) of models were calculated, with which the performances of classifiers were evaluated and compared with each other. Result: Brilliant discriminative performance would be observed among all classifiers when combined with the suitable selection method. For LDA-based models, the optimal one was Distance Correlation + LDA with AUC of 0.978. For SVM-based models, Distance Correlation + SVM was the one with highest AUC of 0.959, while for LR-based models, the highest AUC was 0.966 established with LASSO + LR. Conclusion: Radiomics-based machine-learning algorithms potentially have promising performances in differentiating GBM from PCNSL.
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Affiliation(s)
- Chaoyue Chen
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center for Biotherapy, Chengdu, China.,Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, China
| | - Aiping Zheng
- West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Xuejin Ou
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center for Biotherapy, Chengdu, China.,West China School of Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Jian Wang
- School of Computer Science, Nanjing University of Science and Technology, Nanjing, China
| | - Xuelei Ma
- State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Collaborative Innovation Center for Biotherapy, Chengdu, China.,Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
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22
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Anderson CE, Johansen M, Erokwu BO, Hu H, Gu Y, Zhang Y, Kavran M, Vincent J, Drumm ML, Griswold MA, Steinmetz NF, Li M, Clark H, Darrah RJ, Yu X, Brady-Kalnay SM, Flask CA. Dynamic, Simultaneous Concentration Mapping of Multiple MRI Contrast Agents with Dual Contrast - Magnetic Resonance Fingerprinting. Sci Rep 2019; 9:19888. [PMID: 31882792 PMCID: PMC6934650 DOI: 10.1038/s41598-019-56531-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Accepted: 12/09/2019] [Indexed: 12/31/2022] Open
Abstract
Synchronous assessment of multiple MRI contrast agents in a single scanning session would provide a new "multi-color" imaging capability similar to fluorescence imaging but with high spatiotemporal resolution and unlimited imaging depth. This multi-agent MRI technology would enable a whole new class of basic science and clinical MRI experiments that simultaneously explore multiple physiologic/molecular events in vivo. Unfortunately, conventional MRI acquisition techniques are only capable of detecting and quantifying one paramagnetic MRI contrast agent at a time. Herein, the Dual Contrast - Magnetic Resonance Fingerprinting (DC-MRF) methodology was extended for in vivo application and evaluated by simultaneously and dynamically mapping the intra-tumoral concentration of two MRI contrast agents (Gd-BOPTA and Dy-DOTA-azide) in a mouse glioma model. Co-registered gadolinium and dysprosium concentration maps were generated with sub-millimeter spatial resolution and acquired dynamically with just over 2-minute temporal resolution. Mean tumor Gd and Dy concentration measurements from both single agent and dual agent DC-MRF studies demonstrated significant correlations with ex vivo mass spectrometry elemental analyses. This initial in vivo study demonstrates the potential for DC-MRF to provide a useful dual-agent MRI platform.
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Affiliation(s)
- Christian E Anderson
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Mette Johansen
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, OH, USA
| | - Bernadette O Erokwu
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - He Hu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Department of NanoEngineering, University of California-San Diego, La Jolla, CA, USA
| | - Yuning Gu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Yifan Zhang
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Michael Kavran
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Jason Vincent
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, OH, USA
| | - Mitchell L Drumm
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, USA
- Department of Pediatrics, Case Western Reserve University, Cleveland, OH, USA
| | - Mark A Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Nicole F Steinmetz
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Department of NanoEngineering, University of California-San Diego, La Jolla, CA, USA
- Department of Radiology, University of California-San Diego, La Jolla, CA, USA
- Moores Cancer Center, University of California-San Diego, La Jolla, CA, USA
| | - Ming Li
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Heather Clark
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
- Institute of Systems Bioanalysis and Chemical Imaging, Northeastern University, Boston, MA, USA
| | - Rebecca J Darrah
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, USA
- Francis Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH, USA
| | - Xin Yu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, OH, USA
| | - Susann M Brady-Kalnay
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, OH, USA
- Department of Neurosciences, Case Western Reserve University, Cleveland, OH, USA
| | - Chris A Flask
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA.
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
- Department of Pediatrics, Case Western Reserve University, Cleveland, OH, USA.
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23
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Okuchi S, Rojas-Garcia A, Ulyte A, Lopez I, Ušinskienė J, Lewis M, Hassanein SM, Sanverdi E, Golay X, Thust S, Panovska-Griffiths J, Bisdas S. Diagnostic accuracy of dynamic contrast-enhanced perfusion MRI in stratifying gliomas: A systematic review and meta-analysis. Cancer Med 2019; 8:5564-5573. [PMID: 31389669 PMCID: PMC6745862 DOI: 10.1002/cam4.2369] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Revised: 05/19/2019] [Accepted: 06/10/2019] [Indexed: 02/06/2023] Open
Abstract
Background T1‐weighted dynamic contrast‐enhanced (DCE) perfusion magnetic resonance imaging (MRI) has been broadly utilized in the evaluation of brain tumors. We aimed at assessing the diagnostic accuracy of DCE‐MRI in discriminating between low‐grade gliomas (LGGs) and high‐grade gliomas (HGGs), between tumor recurrence and treatment‐related changes, and between primary central nervous system lymphomas (PCNSLs) and HGGs. Methods We performed this study based on the Preferred Reporting Items for Systematic Reviews and Meta‐Analysis of Diagnostic Test Accuracy Studies criteria. We systematically surveyed studies evaluating the diagnostic accuracy of DCE‐MRI for the aforementioned entities. Meta‐analysis was conducted with the use of a random effects model. Results Twenty‐seven studies were included after screening of 2945 possible entries. We categorized the eligible studies into three groups: those utilizing DCE‐MRI to differentiate between HGGs and LGGs (14 studies, 546 patients), between recurrence and treatment‐related changes (9 studies, 298 patients) and between PCNSLs and HGGs (5 studies, 224 patients). The pooled sensitivity, specificity, and area under the curve for differentiating HGGs from LGGs were 0.93, 0.90, and 0.96, for differentiating tumor relapse from treatment‐related changes were 0.88, 0.86, and 0.89, and for differentiating PCNSLs from HGGs were 0.78, 0.81, and 0.86, respectively. Conclusions Dynamic contrast‐enhanced‐Magnetic resonance imaging is a promising noninvasive imaging method that has moderate or high accuracy in stratifying gliomas. DCE‐MRI shows high diagnostic accuracy in discriminating between HGGs and their low‐grade counterparts, and moderate diagnostic accuracy in discriminating recurrent lesions and treatment‐related changes as well as PCNSLs and HGGs.
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Affiliation(s)
- Sachi Okuchi
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | | | - Agne Ulyte
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Ingeborg Lopez
- Neuroradiology, Institute of Neurosurgery Dr. A. Asenjo, Santiago, Chile
| | - Jurgita Ušinskienė
- Diagnostic and Interventional Radiology Department, Faculty of Medicine, National Cancer Institute, Vilnius University, Vilnius, Lithuania
| | - Martin Lewis
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | - Sara M Hassanein
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK.,Diagnostic Radiology Department, Faculty of Medicine, Assiut University, Assiut, Egypt
| | - Eser Sanverdi
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | - Stefanie Thust
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, UK
| | | | - Sotirios Bisdas
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, UK
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24
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Ozturk K, Soylu E, Tolunay S, Narter S, Hakyemez B. Dynamic Contrast-Enhanced T1-Weighted Perfusion Magnetic Resonance Imaging Identifies Glioblastoma Immunohistochemical Biomarkers via Tumoral and Peritumoral Approach: A Pilot Study. World Neurosurg 2019; 128:e195-e208. [PMID: 31003026 DOI: 10.1016/j.wneu.2019.04.089] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 04/08/2019] [Accepted: 04/09/2019] [Indexed: 12/13/2022]
Abstract
OBJECTIVE We aimed to evaluate the usefulness of dynamic contrast-enhanced T1-weighted perfusion magnetic resonance imaging (DCE-pMRI) to predict certain immunohistochemical (IHC) biomarkers of glioblastoma (GB) in this pilot study. METHODS We retrospectively reviewed 36 patients (male/female, 25:11; mean age, 53 years; age range, 29-85 years) who had pretreatment DCE-pMRI with IHC analysis of their excised GBs. Regions of interest of the enhancing tumor (ER) and nonenhancing peritumoral region (NER) were used to calculate DCE-pMRI parameters of volume transfer constant, back flux constant, volume of the extravascular extracellular space, initial area under enhancement curve, and maximum slope. IHC biomarkers including Ki-67 labeling index, epidermal growth factor receptor (EGFR), oligodendrocyte transcription factor 2 (OLIG2), isocitrate dehydrogenase 1 (IDH1), and p53 mutation status were determined. The imaging metrics of GB with IHC markers were compared using the Kruskal-Wallis test and Spearman correlation analysis. RESULTS Among 30 patients with available IDH1 status, 14 patients (46.6%) had IDH1 mutation. EGFR amplification was present in 24/36 (66.6%) patients. Mean Ki-67 labeling index was 29% (range, 1.5%-80%). p53 mutation was present in 20/36 GBs (55%), whereas OLIG2 expression was positive in 29/36 GBs (80.5%). Various DCE-pMRI parameters gathered from the ER and NER were significantly correlated with IDH1 mutation, EGFR amplification, and OLIG2 expression (P < 0.05). Ki-67 labeling index showed a strong positive correlation with initial area under enhancement curve (r = 0.619; P < 0.001). CONCLUSIONS DCE-pMRI could determine surrogate IHC biomarkers in GB via tumoral and peritumoral approach, potential targets for individualized treatment protocols.
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Affiliation(s)
- Kerem Ozturk
- Department of Radiology, Uludag University Faculty of Medicine, Bursa, Turkey
| | - Esra Soylu
- Department of Radiology, Uludag University Faculty of Medicine, Bursa, Turkey
| | - Sahsine Tolunay
- Department of Pathology, Uludag University Faculty of Medicine, Bursa, Turkey
| | - Selin Narter
- Department of Pathology, Uludag University Faculty of Medicine, Bursa, Turkey
| | - Bahattin Hakyemez
- Department of Radiology, Uludag University Faculty of Medicine, Bursa, Turkey.
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25
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Permeability measurement using dynamic susceptibility contrast magnetic resonance imaging enhances differential diagnosis of primary central nervous system lymphoma from glioblastoma. Eur Radiol 2019; 29:5539-5548. [DOI: 10.1007/s00330-019-06097-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 01/10/2019] [Accepted: 02/11/2019] [Indexed: 11/25/2022]
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26
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Xi YB, Kang XW, Wang N, Liu TT, Zhu YQ, Cheng G, Wang K, Li C, Guo F, Yin H. Differentiation of primary central nervous system lymphoma from high-grade glioma and brain metastasis using arterial spin labeling and dynamic contrast-enhanced magnetic resonance imaging. Eur J Radiol 2019; 112:59-64. [DOI: 10.1016/j.ejrad.2019.01.008] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 12/02/2018] [Accepted: 01/07/2019] [Indexed: 01/22/2023]
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27
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Suh CH, Kim HS, Jung SC, Park JE, Choi CG, Kim SJ. MRI as a diagnostic biomarker for differentiating primary central nervous system lymphoma from glioblastoma: A systematic review and meta-analysis. J Magn Reson Imaging 2019; 50:560-572. [PMID: 30637843 DOI: 10.1002/jmri.26602] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 11/28/2018] [Accepted: 11/28/2018] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Accurate preoperative differentiation of primary central nervous system lymphoma (PCNSL) and glioblastoma is clinically crucial because the treatment strategies differ substantially. PURPOSE To evaluate the diagnostic performance of MRI for differentiating PCNSL from glioblastoma. STUDY TYPE Systematic review and meta-analysis. SUBJECTS Ovid-MEDLINE and EMBASE databases were searched to find relevant original articles up to November 25, 2018. The search term combined synonyms for "lymphoma," "glioblastoma," and "MRI." FIELD STRENGTH/SEQUENCE Patients underwent at least one MRI sequence including diffusion-weighted imaging (DWI), dynamic susceptibility-weighted contrast-enhanced imaging (DSC), dynamic contrast-enhanced imaging (DCE), arterial spin labeling (ASL), susceptibility-weighted imaging (SWI), intravoxel incoherent motion (IVIM), and magnetic resonance spectroscopy (MRS) using 1.5 or 3 T. ASSESSMENT Quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies-2 tool. STATISTICAL TESTS Hierarchical logistic regression modeling was used to obtain pooled sensitivity and specificity. Meta-regression was performed. RESULTS Twenty-two studies with 1182 patients were included. MRI sequences demonstrated high overall diagnostic performance with pooled sensitivity of 91% (95% confidence interval [CI], 87-93%) and specificity of 89% (95% CI, 85-93%). The area under the hierarchical summary receiver operating characteristic curve was 0.92 (95% CI, 0.90-0.94). Studies using DSC or ASL showed high diagnostic performance (sensitivity of 93% [95% CI, 89-97%] and specificity of 91% [95% CI, 86-96%]). Heterogeneity was only detected in specificity (I2 = 66.84%) and magnetic field strength was revealed to be a significant factor affecting study heterogeneity. DATA CONCLUSION MRI showed overall high diagnostic performance for differentiating PCNSL from glioblastoma, with studies using DSC or ASL showing high diagnostic performance. Therefore, MRI sequences including DSC or ASL is a potential diagnostic tool for differentiating PCNSL from glioblastoma. LEVEL OF EVIDENCE 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:560-572.
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Affiliation(s)
- Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Seung Chai Jung
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Choong Gon Choi
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Sang Joon Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
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28
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Specific Features of Primary Central Nervous System Lymphoma in Comparison with Glioblastoma on Conventional MRI. IRANIAN JOURNAL OF RADIOLOGY 2018. [DOI: 10.5812/iranjradiol78868] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
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29
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Di N, Cheng W, Chen H, Zhai F, Liu Y, Mu X, Chu Z, Lu N, Liu X, Wang B. Utility of arterial spin labelling MRI for discriminating atypical high-grade glioma from primary central nervous system lymphoma. Clin Radiol 2018; 74:165.e1-165.e9. [PMID: 30415766 DOI: 10.1016/j.crad.2018.10.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Accepted: 10/09/2018] [Indexed: 01/19/2023]
Abstract
AIM To evaluate the ability of arterial spin labelling (ASL) magnetic resonance imaging (MRI) in differentiating primary central nervous system lymphoma (PCNSL) from atypical high-grade glioma (HGG), as well as exploring the underlying pathological mechanisms. METHODS AND MATERIALS Twenty-three patients with PCNSL and 17 patients with atypical HGG who underwent ASL-MRI were identified retrospectively. Absolute cerebral blood flow (aCBF) and normalised cerebral blood flow (nCBF) values were obtained, and were compared between PCNSL and atypical HGG using the Mann-Whitney U-test. The performance in discriminating between PCNSL and atypical HGG was evaluated using receiver-operating characteristics analysis and area-under-the-curve (AUC) values for aCBF and nCBF. The correlation between microvessel density (MVD) and aCBF was determined by Spearman's correlation analysis. RESULTS Atypical HGG demonstrated significantly higher aCBF, nCBF, and MVD values than PCNSL (p<0.05). The diagnostic accuracy of discriminating PCNSL from atypical HGG showed AUC=0.877 (95% confidence interval [CI] 0.735-0.959) for aCBF, and AUC=0.836 (95% confidence interval [CI] 0.685-0.934) for nCBF. There was a moderate positive correlation between aCBF values of region of interest (ROI >30 mm2) in the enhanced area and MVD values (rho=0.579, p=0.0001), and a strong positive correlation between aCBF values MVD based on "point-to-point biopsy" (rho=0.83, p=0.0029). Interobserver agreements for aCBF and nCBF were excellent (ICC >0.75). CONCLUSIONS ASL perfusion MRI is a useful imaging technique for the discrimination between atypical HGG and PCNSL, which may be determined by the difference of MVD between them.
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Affiliation(s)
- N Di
- Department of Radiology, Binzhou Medical University Hospital, 661 Huanghe 2nd Rd, 256603 Binzhou, China; Department of Radiology, Huashan Hospital Fudan University, 12 Wulumuqi Rd. Middle, 200040 Shanghai, China
| | - W Cheng
- Department of Pharmacy, Binzhou Medical University Hospital, 661 Huanghe 2nd Rd, 256603 Binzhou, China
| | - H Chen
- Department of Radiology, Weifang Traditional Chinese Hospital, 1055 Weizhou Rd, 261000 Weifang, China
| | - F Zhai
- Department of Radiology, Binzhou Medical University Hospital, 661 Huanghe 2nd Rd, 256603 Binzhou, China
| | - Y Liu
- Department of Pediatrics, Binzhou Medical University Hospital, 661 Huanghe 2nd Rd, 256603 Binzhou, China
| | - X Mu
- Department of Radiology, Binzhou Medical University Hospital, 661 Huanghe 2nd Rd, 256603 Binzhou, China
| | - Z Chu
- Department of Radiology, Binzhou Medical University Hospital, 661 Huanghe 2nd Rd, 256603 Binzhou, China
| | - N Lu
- Department of Radiology, Huashan Hospital Fudan University, 12 Wulumuqi Rd. Middle, 200040 Shanghai, China
| | - X Liu
- Department of Radiology, Binzhou Medical University Hospital, 661 Huanghe 2nd Rd, 256603 Binzhou, China.
| | - B Wang
- Department of Medical Imaging and Nuclear, Binzhou Medical University, 346 Guanhai Rd, 264000 Yantai, China.
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Saini J, Kumar Gupta P, Awasthi A, Pandey C, Singh A, Patir R, Ahlawat S, Sadashiva N, Mahadevan A, Kumar Gupta R. Multiparametric imaging-based differentiation of lymphoma and glioblastoma: using T1-perfusion, diffusion, and susceptibility-weighted MRI. Clin Radiol 2018; 73:986.e7-986.e15. [DOI: 10.1016/j.crad.2018.07.107] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Accepted: 07/31/2018] [Indexed: 01/19/2023]
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31
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MR imaging based fractal analysis for differentiating primary CNS lymphoma and glioblastoma. Eur Radiol 2018; 29:1348-1354. [DOI: 10.1007/s00330-018-5658-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 06/09/2018] [Accepted: 07/12/2018] [Indexed: 12/18/2022]
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32
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Lee B, Park JE, Bjørnerud A, Kim JH, Lee JY, Kim HS. Clinical Value of Vascular Permeability Estimates Using Dynamic Susceptibility Contrast MRI: Improved Diagnostic Performance in Distinguishing Hypervascular Primary CNS Lymphoma from Glioblastoma. AJNR Am J Neuroradiol 2018; 39:1415-1422. [PMID: 30026384 DOI: 10.3174/ajnr.a5732] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 05/01/2018] [Indexed: 12/17/2022]
Abstract
BACKGROUND AND PURPOSE A small subset of primary central nervous system lymphomas exhibits high cerebral blood volume, which is indistinguishable from that in glioblastoma on dynamic susceptibility contrast MR imaging. Our study aimed to test whether estimates of combined perfusion and vascular permeability metrics derived from DSC-MR imaging can improve the diagnostic performance in differentiating hypervascular primary central nervous system lymphoma from glioblastoma. MATERIALS AND METHODS A total of 119 patients (with 30 primary central nervous system lymphomas and 89 glioblastomas) exhibited hypervascular foci using the reference method of leakage-corrected CBV (reference-normalized CBV). An alternative postprocessing method used the tissue residue function to calculate vascular permeability (extraction fraction), leakage-corrected CBV, cerebral blood flow, and mean transit time. Parameters were compared using Mann-Whitney U tests, and the diagnostic performance to distinguish primary central nervous system lymphoma from glioblastoma was calculated using the area under the curve from the receiver operating characteristic curve and was cross-validated with bootstrapping. RESULTS Hypervascular primary central nervous system lymphoma showed similar leakage-corrected normalized CBV and leakage-corrected CBV compared with glioblastoma (P > .05); however, primary central nervous system lymphoma exhibited a significantly higher extraction fraction (P < .001) and CBF (P = .01) and shorter MTT (P < .001) than glioblastoma. The extraction fraction showed the highest diagnostic performance (the area under the receiver operating characteristic curve [AUC], 0.78; 95% confidence interval, 0.69-0.85) for distinguishing hypervascular primary central nervous system lymphoma from glioblastoma, with a significantly higher performance than both CBV (AUC, 0.53-0.59, largest P = .02) and CBF (AUC, 0.72) and MTT (AUC, 0.71). CONCLUSIONS Estimation of vascular permeability with DSC-MR imaging further characterizes hypervascular primary central nervous system lymphoma and improves diagnostic performance in glioblastoma differentiation.
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Affiliation(s)
- B Lee
- From the Department of Radiology (B.L.), Seoul Metropolitan Government-Seoul National University, Boramae Medical Center, Seoul, Korea
| | - J E Park
- Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K.), University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - A Bjørnerud
- Department of Diagnostic Physics (A.B.), Rikshopitalet University Hospital, Oslo, Norway
| | - J H Kim
- NordicNeuroLab (J.H.K.), Seoul, Korea
| | - J Y Lee
- Department of Radiology (J.Y.L.), Soonchunhyang University Bucheon Hospital, Bucheon, Korea
| | - H S Kim
- Department of Radiology and Research Institute of Radiology (J.E.P., H.S.K.), University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
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Gómez Roselló E, Quiles Granado A, Laguillo Sala G, Pedraza Gutiérrez S. Primary central nervous system lymphoma in immunocompetent patients: Spectrum of findings and differential characteristics. RADIOLOGIA 2018. [DOI: 10.1016/j.rxeng.2018.04.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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34
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Lee JY, Ahn KJ, Lee YS, Jang JH, Jung SL, Kim BS. Differentiation of grade II and III oligodendrogliomas from grade II and III astrocytomas: a histogram analysis of perfusion parameters derived from dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) MRI. Acta Radiol 2018; 59:723-731. [PMID: 28862024 DOI: 10.1177/0284185117728981] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Background Since oligodendroglial tumors are sensitive to chemotherapy and have a better prognosis, the differentiation of oligodendroglial tumors (OT) from astrocytic tumors (AT) is important. Purpose To investigate the perfusion and permeability parameters that differentiate grade II and III OT from AT, using dynamic contrast-enhanced (DCE) and dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI). Material and Methods We retrospectively reviewed the DCE and DSC MRIs of 39 patients with OT (OTs, n = 19; grade II, n = 12 and grade III, n = 7) and AT (ATs, n = 20; grade II, n = 7 and grade III, n = 13). Glioblastomas were not included. Various histogram parameters of relative cerebral blood volume, volume transfer constant (Ktrans), flux rate constant (Kep), plasma volume fraction (Vp), and extravascular extracellular volume fraction (Ve) from DSC and DCE MRI, were compared between the two groups. Univariable and multivariable logistic regression were used to distinguish OT from AT. Receiver operating characteristic (ROC) curve analysis was performed. Results On the results of DCE MRI, most of the histogram parameters of Ktrans, Kep, and Ve showed tendencies toward higher values in OT than AT. Multivariable logistic regression revealed that the 50th Kep and 95th Ktrans were the most significant parameters predictive of OT, with an odds ratio of 3.7 and 2.5, respectively ( P = 0.004 and 0.03). The area under the curve from the ROC curve analysis for the 50th Kep and the 95th Ktrans were 0.81 and 0.80, respectively. Conclusion The DCE MRI-derived parameters of Ktrans and Kep could facilitate differentiation of OT from AT.
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Affiliation(s)
- Ji Young Lee
- Department of Radiology, Hanyang University Hospital, Hanyang University College of Medicine, Seoul, Republic of Korea
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Kook Jin Ahn
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Youn Soo Lee
- Department of Hospital Pathology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Jin Hee Jang
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - So Lyung Jung
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Bum Soo Kim
- Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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Li L, Rong JH, Feng J. Neuroradiological features of lymphomatosis cerebri: A systematic review of the English literature with a new case report. Oncol Lett 2018; 16:1463-1474. [PMID: 30008825 PMCID: PMC6036370 DOI: 10.3892/ol.2018.8839] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Accepted: 04/04/2018] [Indexed: 12/14/2022] Open
Abstract
Lymphomatosis cerebri is a rare form of diffusely infiltrating primary central nervous system (CNS) lymphoma (PCNSL). The neuroradiological findings of lymphomatosis cerebri have not been adequately characterized, as the relevant literature consists only of case reports and small case series. The present study describes an unusual presentation of lymphomatosis cerebri in a 56-year-old immunocompetent woman who presented with diffusely infiltrating lesions with perivascular curvilinear enhancement on initial magnetic resonance imaging (MRI) and multiple nodules on the later follow-up computed tomography (CT) scan. A systematic review of the literature is also performed searching PubMed between January 1996 and December 2016 to collect all pertinent case reports and series written in the English language with pathologically confirmed lymphomatosis cerebri and diffuse infiltrative PCNSL without cohesive masses on initial MRI. A total of 45 cases were identified from 39 articles and the present case report. The patient ages ranged from 28 to 85 years (mean, 57.3 years). Only 3 patients (6.7%) were immunosuppressed (acquired immune deficiency syndrome patients). The most common clinical presentation was cognitive changes or dementia (46.7%). Cerebrospinal fluid analysis in all cases was non-specific. Diffuse and asymmetric abnormal T2-hyperintensity in deep and subcortical white matter was observed in all cases. Gray matter involvement (17.8%), spreading along the corticospinal tract (35.6%) and a slight mass effect (51.1%) also were observed. Contrast-enhanced patterns on MRI could be divided into three forms of non-enhancement (64.4%) and non-mass-like enhancement (35.6%) on initial MRI, as well as nodular or mass-like enhancement on the later follow-up MRI (15.6%). There were non-specific findings on magnetic resonance spectroscopy for 4 patients, on positron emission tomography/CT for 12 patients and on single-photon emission CT for 1 patient. Diagnosis was established by brain biopsy in 35 cases (77.8%) and autopsy in 9 cases (20%), involving B-cell lymphoma in 40 cases (88.9%) and T-cell lymphoma in 4 cases (8.9%). In conclusion, lymphomatosis cerebri, namely diffuse PCNSL or diffuse lymphoma of the CNS, is characterized by rapidly progressive dementia in the elderly, diffusely infiltrated CNS white matter along the corticospinal tract, possible involvement of the gray matter, a slight mass effect and varied contrast-enhancement patterns on MRI. Non-enhancement or non-mass-like enhancement on MRI may be a special form of diffuse PCNL during disease development and progression.
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Affiliation(s)
- Long Li
- Department of Radiology, Guangdong Provincial Corps Hospital of Chinese People's Armed Police Forces, Guangzhou Medical University, Guangzhou, Guangdong 510507, P.R. China
| | - Jia-Hui Rong
- Department of Radiology, Guangdong Provincial Corps Hospital of Chinese People's Armed Police Forces, Guangzhou Medical University, Guangzhou, Guangdong 510507, P.R. China
| | - Jie Feng
- Diagnostic Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China
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Citterio G, Calimeri T, Ferreri AJM. Challenges and prospects in the diagnosis and treatment of primary central nervous system lymphoma. Expert Rev Neurother 2018; 18:379-393. [PMID: 29633883 DOI: 10.1080/14737175.2018.1462700] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Introduction: Primary central nervous system lymphoma (PCNSL) retains peculiar biological and clinical characteristics and a worse prognosis with respect to other comparable lymphomas. The need for high doses of chemotherapy to achieve valid drug concentrations in cerebral tissues and/or radiotherapy results in severe treatment-related toxicities, mainly neurologic, which are frequently as disabling as the disease itself.Areas covered: Several emerging combined therapies are addressed that focus on treating PCNSL. The prognosis has improved in the last years but several questions remain unanswered and the research of more effective therapies goes on. Information and data were obtained from direct authors' experience and a PubMed search of recent peer-reviewed original articles, review articles, and clinical guidelines.Expert commentary: The substantial progress observed in PCNSL has to be ascribed to a carefully combination of standard chemotherapeutic drugs. High-dose methotrexate-based polychemotherapy followed by mainteinance therapy offers one of the best chances to control the disease. Major issues that deserve many efforts by researchers are the definition of optimal consolidation treatment and a shared management of specific conditions such as elderly population and intra-ocular localization.
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Affiliation(s)
- Giovanni Citterio
- Department of Oncology, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Teresa Calimeri
- Unit of Lymphoid Malignancies, Department of Onco-Hematology, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Andrés J M Ferreri
- Unit of Lymphoid Malignancies, Department of Onco-Hematology, IRCCS San Raffaele Scientific Institute, Milano, Italy
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Suh HB, Choi YS, Bae S, Ahn SS, Chang JH, Kang SG, Kim EH, Kim SH, Lee SK. Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach. Eur Radiol 2018; 28:3832-3839. [PMID: 29626238 DOI: 10.1007/s00330-018-5368-4] [Citation(s) in RCA: 95] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Revised: 01/29/2018] [Accepted: 02/05/2018] [Indexed: 01/12/2023]
Abstract
OBJECTIVES To evaluate the diagnostic performance of magnetic resonance (MR) radiomics-based machine-learning algorithms in differentiating primary central nervous system lymphoma (PCNSL) from non-necrotic atypical glioblastoma (GBM). METHODS Seventy-seven patients (54 individuals with PCNSL and 23 with non-necrotic atypical GBM), diagnosed from January 2009 to April 2017, were enrolled in this retrospective study. A total of 6,366 radiomics features, including shape, volume, first-order, texture, and wavelet-transformed features, were extracted from multi-parametric (post-contrast T1- and T2-weighted, and fluid attenuation inversion recovery images) and multiregional (enhanced and non-enhanced) tumour volumes. These features were subjected to recursive feature elimination and random forest (RF) analysis with nested cross-validation. The diagnostic abilities of a radiomics machine-learning classifier, apparent diffusion coefficient (ADC), and three readers, who independently classified the tumours based on conventional MR sequences, were evaluated using receiver operating characteristic (ROC) analysis. Areas under the ROC curves (AUC) of the radiomics classifier, ADC value, and the radiologists were compared. RESULTS The mean AUC of the radiomics classifier was 0.921 (95 % CI 0.825-0.990). The AUCs of the three readers and ADC were 0.707 (95 % CI 0.622-0.793), 0.759 (95 %CI 0.656-0.861), 0.695 (95 % CI 0.590-0.800) and 0.684 (95 % CI0.560-0.809), respectively. The AUC of the radiomics-based classifier was significantly higher than those of the three readers and ADC (p< 0.001 for all). CONCLUSIONS Large-scale radiomics with a machine-learning algorithm can be useful for differentiating PCNSL from atypical GBM, and yields a better diagnostic performance than human radiologists and ADC values. KEY POINTS • Machine-learning algorithm radiomics can help to differentiate primary central PCNSL from GBM. • This approach yields a higher diagnostic accuracy than visual analysis by radiologists. • Radiomics can strengthen radiologists' diagnostic decisions whenever conventional MRI sequences are available.
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Affiliation(s)
- Hie Bum Suh
- Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Yoon Seong Choi
- Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea.
| | - Sohi Bae
- Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Seok-Gu Kang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Eui Hyun Kim
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Se Hoon Kim
- Department of Pathology, Yonsei University College of Medicine, Seoul, Korea
| | - Seung-Koo Lee
- Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
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You SH, Yun TJ, Choi HJ, Yoo RE, Kang KM, Choi SH, Kim JH, Sohn CH. Differentiation between primary CNS lymphoma and glioblastoma: qualitative and quantitative analysis using arterial spin labeling MR imaging. Eur Radiol 2018; 28:3801-3810. [DOI: 10.1007/s00330-018-5359-5] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Revised: 01/19/2018] [Accepted: 01/29/2018] [Indexed: 10/17/2022]
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Gómez Roselló E, Quiles Granado AM, Laguillo Sala G, Pedraza Gutiérrez S. Primary central nervous system lymphoma in immunocompetent patients: spectrum of findings and differential characteristics. RADIOLOGIA 2018; 60:280-289. [PMID: 29482953 DOI: 10.1016/j.rx.2017.12.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Revised: 12/27/2017] [Accepted: 12/27/2017] [Indexed: 10/18/2022]
Abstract
Primary central nervous system (CNS) lymphomas are uncommon and their management differs significantly from that of other malignant tumors involving the CNS. This article explains how the imaging findings often suggest the diagnosis early. The typical findings in immunocompetent patients consist of a supratentorial intraaxial mass that enhances homogeneously. Other findings to evaluate include multifocality and incomplete ring enhancement. The differential diagnosis of primary CNS lymphomas should consider mainly other malignant tumors of the CNS such as glioblastomas or metastases. Primary CNS lymphomas tend to have less edema and less mass effect; they also tend to spare the adjacent cortex. Necrosis, hemorrhage, and calcification are uncommon in primary CNS lymphomas. Although the findings in morphologic sequences are characteristic, they are not completely specific and atypical types are sometimes encountered. Advanced imaging techniques such as diffusion or especially perfusion provide qualitative and quantitative data that play an important role in differentiating primary CNS lymphomas from other brain tumors.
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Affiliation(s)
- E Gómez Roselló
- Sección de Neurorradiología, Servicio de Radiología (IDI), Hospital Universitario Dr. Josep Trueta, Girona, España.
| | - A M Quiles Granado
- Sección de Neurorradiología, Servicio de Radiología (IDI), Hospital Universitario Dr. Josep Trueta, Girona, España
| | - G Laguillo Sala
- Sección de Neurorradiología, Servicio de Radiología (IDI), Hospital Universitario Dr. Josep Trueta, Girona, España
| | - S Pedraza Gutiérrez
- Sección de Neurorradiología, Servicio de Radiología (IDI), Hospital Universitario Dr. Josep Trueta, Girona, España
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Di N, Yao C, Cheng W, Ren Y, Qu J, Wang B, Yao Z. Correlation of dynamic contrast-enhanced MRI derived volume transfer constant with histological angiogenic markers in high-grade gliomas. J Med Imaging Radiat Oncol 2018; 62:464-470. [PMID: 29330968 DOI: 10.1111/1754-9485.12701] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2016] [Accepted: 12/12/2017] [Indexed: 11/30/2022]
Abstract
INTRODUCTION To ascertain if the volume transfer constant (Ktrans ) derived from T1 dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) correlates with the immunohistological markers of angiogenesis in high-grade gliomas. METHODS Fifty-one image-guided biopsy specimens in 34 patients with newly presenting high-grade gliomas (grade III = 16; grade IV = 18) underwent preoperative imaging (conventional imaging and T1 DCE-MRI). We correlated vascular endothelial growth factor (VEGF) expression and the microvessel density (MVD) of MRI-guided biopsy specimens with the corresponding DCE-derived Ktrans . Histological sections were stained with VEGF and CD34, and examined under light microscopy. These histological and molecular markers of angiogenesis were correlated with the Ktrans of the region of interest corresponding to the biopsy specimen. RESULTS The Ktrans showed a significant positive correlation with VEGF expression (ρ = 0.582, P = 0.001) but not with MVD stained with CD34 antibody (ρ = 0.328, P = 0.072). CONCLUSION The Ktrans derived from DCE-MRI can reflect the VEGF expression of high-grade gliomas but not the MVD.
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Affiliation(s)
- Ningning Di
- Department of Radiology, Binzhou Medical University Hospital, Binzhou, China
- Department of Radiology, Huashan Hospital Fudan University, Shanghai, China
| | - Chenjun Yao
- Department of Neurosurgery, Huashan Hospital Fudan University, Shanghai, China
| | - Wenna Cheng
- Department of Pharmacy, Binzhou Medical University Affiliated Hospital, Binzhou, China
| | - Yan Ren
- Department of Radiology, Huashan Hospital Fudan University, Shanghai, China
| | | | - Bin Wang
- Department of Medical Imaging and Nuclear Medicine, Binzhou Medical University, Yantai, China
| | - Zhenwei Yao
- Department of Radiology, Huashan Hospital Fudan University, Shanghai, China
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Goyal P, Kumar Y, Gupta N, Malhotra A, Gupta S, Gupta S, Mangla M, Mangla R. Usefulness of enhancement-perfusion mismatch in differentiation of CNS lymphomas from other enhancing malignant tumors of the brain. Quant Imaging Med Surg 2017; 7:511-519. [PMID: 29184763 DOI: 10.21037/qims.2017.09.03] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background Surgical planning and treatment options for primary or secondary central nervous system lymphomas (PCNSL or SCNSL) are different from other enhancing malignant lesions such as glioblastoma multiforme (GBM), anaplastic gliomas and metastases; so, it is critical to distinguish them preoperatively. We hypothesized that enhancement-perfusion (E-P) mismatch on dynamic susceptibility weighted magnetic resonance (DSC-MR) perfusion imaging which corresponds to low mean relative cerebral blood volume (mean rCBV) in an enhancing portion of the tumor should allow differentiation of CNS lymphomas from other enhancing malignant lesions. Methods We retrospectively reviewed pre-treatment MRI exams, including DSC-MR perfusion images of 15 lymphoma patients. As a control group, pre-treatment DSC-MR perfusion images of biopsy proven 18 GBMs (group II), 13 metastases (group III), and 10 anaplastic enhancing gliomas (group IV) patients were also reviewed. Region of interests (ROIs) were placed around the most enhancing part of tumor on contrast-enhanced T1WI axial images and images were transferred onto co-registered DSC perfusion maps to obtain CBV in all 4 groups. The mean and maximum relative CBV values were obtained. Statistical analysis was performed on SPSS software and significance of the results between the groups was done with Mann-Whitney test, whereas optimal thresholds for tumor differentiation were done by receiver operating characteristic (ROC) analysis. Results The enhancing component of CNS lymphomas were found to have significantly lower mean rCBV compared to enhancing component of GBM (1.2 versus 4.3; P<0.001), metastasis (1.2 versus 2.7; P<0.001), and anaplastic enhancing gliomas (1.2 versus 2.4; P<0.001). Maximum rCBV of enhancing component of lymphoma were significantly lower than GBM (3.1 versus 6.5; P<0.001) and metastasis (3.1 versus 4.9; P<0.013), and not significantly lower than anaplastic enhancing gliomas (3.9 versus 4.2; P<0.08). On the basis of ROC analysis, mean rCBV provided the best threshold [area under the curve (AUC) =0.92] and had better accuracy in differentiating malignant lesions. Conclusions E-P mismatch in DSC perfusion MR, i.e., low mean rCBV in an enhancing portion of the tumor is strongly suggestive of lymphoma and should allow differentiation of CNS lymphoma from other enhancing malignant lesions.
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Affiliation(s)
- Pradeep Goyal
- Department of Radiology, St. Vincent's Medical Center, Bridgeport, Connecticut, USA
| | - Yogesh Kumar
- Department of Radiology, Columbia University at Bassett Healthcare, Cooperstown, New York, USA
| | - Nishant Gupta
- Department of Radiology, Columbia University Medical Center, New York, NY, USA
| | - Ajay Malhotra
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Saurabh Gupta
- Department of Radiology, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Sonali Gupta
- Department of Medicine, St. Vincent's Medical Center, Bridgeport, Connecticut, USA
| | - Manisha Mangla
- Department of Radiology, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Rajiv Mangla
- Department of Radiology, University of Rochester Medical Center, Rochester, New York, USA
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Reproducibility and relative stability in magnetic resonance imaging indices of tumor vascular physiology over a period of 24h in a rat 9L gliosarcoma model. Magn Reson Imaging 2017; 44:131-139. [PMID: 28887206 DOI: 10.1016/j.mri.2017.09.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2017] [Revised: 08/03/2017] [Accepted: 09/01/2017] [Indexed: 02/06/2023]
Abstract
PURPOSE The objective was to study temporal changes in tumor vascular physiological indices in a period of 24h in a 9L gliosarcoma rat model. METHODS Fischer-344 rats (N=14) were orthotopically implanted with 9L cells. At 2weeks post-implantation, they were imaged twice in a 24h interval using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). Data-driven model-selection-based analysis was used to segment tumor regions with varying vascular permeability characteristics. The region with the maximum number of estimable parameters of vascular kinetics was chosen for comparison across the two time points. It provided estimates of three parameters for an MR contrast agent (MRCA): i) plasma volume (vp), ii) forward volumetric transfer constant (Ktrans) and interstitial volume fraction (ve, ratio of Ktrans to reverse transfer constant, kep). In addition, MRCA extracellular distribution volume (VD) was estimated in the tumor and its borders, along with tumor blood flow (TBF) and peritumoral MRCA flux. Descriptors of parametric distributions were compared between the two times. Tumor extent was examined by hematoxylin and eosin (H&E) staining. Picrosirus red staining of secreted collagen was performed as an additional index for 9L cells. RESULTS Test-retest differences between population summaries for any parameter were not significant (paired t and Wilcoxon signed rank tests). Bland-Altman plots showed no apparent trends between the differences and averages of the test-retest measures for all indices. The intraclass correlation coefficients showed moderate to almost perfect reproducibility for all of the parameters, except vp. H&E staining showed tumor infiltration in parenchyma, perivascular space and white matter tracts. Collagen staining was observed along the outer edges of main tumor mass. CONCLUSION The data suggest the relative stability of these MR indices of tumor microenvironment over a 24h duration in this gliosarcoma model.
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Abstract
Primary central nervous system lymphoma (PCNSL) is a rare aggressive high-grade type of extranodal lymphoma. PCNSL can have a variable imaging appearance and can mimic other brain disorders such as encephalitis, demyelination, and stroke. In addition to PCNSL, the CNS can be secondarily involved by systemic lymphoma. Computed tomography and conventional MRI are the initial imaging modalities to evaluate these lesions. Recently, however, advanced MRI techniques are more often used in an effort to narrow the differential diagnosis and potentially inform diagnostic and therapeutic decisions.
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Murayama K, Nishiyama Y, Hirose Y, Abe M, Ohyu S, Ninomiya A, Fukuba T, Katada K, Toyama H. Differentiating between Central Nervous System Lymphoma and High-grade Glioma Using Dynamic Susceptibility Contrast and Dynamic Contrast-enhanced MR Imaging with Histogram Analysis. Magn Reson Med Sci 2017; 17:42-49. [PMID: 28515410 PMCID: PMC5760232 DOI: 10.2463/mrms.mp.2016-0113] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Purpose: We evaluated the diagnostic performance of histogram analysis of data from a combination of dynamic susceptibility contrast (DSC)-MRI and dynamic contrast-enhanced (DCE)-MRI for quantitative differentiation between central nervous system lymphoma (CNSL) and high-grade glioma (HGG), with the aim of identifying useful perfusion parameters as objective radiological markers for differentiating between them. Methods: Eight lesions with CNSLs and 15 with HGGs who underwent MRI examination, including DCE and DSC-MRI, were enrolled in our retrospective study. DSC-MRI provides a corrected cerebral blood volume (cCBV), and DCE-MRI provides a volume transfer coefficient (Ktrans) for transfer from plasma to the extravascular extracellular space. Ktrans and cCBV were measured from a round region-of-interest in the slice of maximum size on the contrast-enhanced lesion. The differences in t values between CNSL and HGG for determining the most appropriate percentile of Ktrans and cCBV were investigated. The differences in Ktrans, cCBV, and Ktrans/cCBV between CNSL and HGG were investigated using histogram analysis. Receiver operating characteristic (ROC) analysis of Ktrans, cCBV, and Ktrans/cCBV ratio was performed. Results: The 30th percentile (C30) in Ktrans and 80th percentile (C80) in cCBV were the most appropriate percentiles for distinguishing between CNSL and HGG from the differences in t values. CNSL showed significantly lower C80 cCBV, significantly higher C30 Ktrans, and significantly higher C30 Ktrans/C80 cCBV than those of HGG. In ROC analysis, C30 Ktrans/C80 cCBV had the best discriminative value for differentiating between CNSL and HGG as compared to C30 Ktrans or C80 cCBV. Conclusion: The combination of Ktrans by DCE-MRI and cCBV by DSC-MRI was found to reveal the characteristics of vascularity and permeability of a lesion more precisely than either Ktrans or cCBV alone. Histogram analysis of these vascular microenvironments enabled quantitative differentiation between CNSL and HGG.
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Affiliation(s)
| | | | - Yuichi Hirose
- Department of Neurosurgery, Fujita Health University
| | - Masato Abe
- Department of Pathology, School of Health Sciences, Fujita Health University
| | | | | | - Takashi Fukuba
- Department of Radiology, Fujita Health University Hospital
| | - Kazuhiro Katada
- Joint Research Laboratory of Advanced Medical Imaging, Fujita Health University
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Citterio G, Reni M, Gatta G, Ferreri AJM. Primary central nervous system lymphoma. Crit Rev Oncol Hematol 2017; 113:97-110. [DOI: 10.1016/j.critrevonc.2017.03.019] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2016] [Revised: 02/24/2017] [Accepted: 03/15/2017] [Indexed: 12/26/2022] Open
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Alcaide-Leon P, Dufort P, Geraldo AF, Alshafai L, Maralani PJ, Spears J, Bharatha A. Differentiation of Enhancing Glioma and Primary Central Nervous System Lymphoma by Texture-Based Machine Learning. AJNR Am J Neuroradiol 2017; 38:1145-1150. [PMID: 28450433 DOI: 10.3174/ajnr.a5173] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Accepted: 02/01/2017] [Indexed: 01/13/2023]
Abstract
BACKGROUND AND PURPOSE Accurate preoperative differentiation of primary central nervous system lymphoma and enhancing glioma is essential to avoid unnecessary neurosurgical resection in patients with primary central nervous system lymphoma. The purpose of the study was to evaluate the diagnostic performance of a machine-learning algorithm by using texture analysis of contrast-enhanced T1-weighted images for differentiation of primary central nervous system lymphoma and enhancing glioma. MATERIALS AND METHODS Seventy-one adult patients with enhancing gliomas and 35 adult patients with primary central nervous system lymphomas were included. The tumors were manually contoured on contrast-enhanced T1WI, and the resulting volumes of interest were mined for textural features and subjected to a support vector machine-based machine-learning protocol. Three readers classified the tumors independently on contrast-enhanced T1WI. Areas under the receiver operating characteristic curves were estimated for each reader and for the support vector machine classifier. A noninferiority test for diagnostic accuracy based on paired areas under the receiver operating characteristic curve was performed with a noninferiority margin of 0.15. RESULTS The mean areas under the receiver operating characteristic curve were 0.877 (95% CI, 0.798-0.955) for the support vector machine classifier; 0.878 (95% CI, 0.807-0.949) for reader 1; 0.899 (95% CI, 0.833-0.966) for reader 2; and 0.845 (95% CI, 0.757-0.933) for reader 3. The mean area under the receiver operating characteristic curve of the support vector machine classifier was significantly noninferior to the mean area under the curve of reader 1 (P = .021), reader 2 (P = .035), and reader 3 (P = .007). CONCLUSIONS Support vector machine classification based on textural features of contrast-enhanced T1WI is noninferior to expert human evaluation in the differentiation of primary central nervous system lymphoma and enhancing glioma.
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Affiliation(s)
| | - P Dufort
- Department of Medical Imaging (P.D., A.F.G.) Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - A F Geraldo
- Department of Medical Imaging (P.D., A.F.G.) Toronto Western Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - L Alshafai
- Department of Medical Imaging (L.A.), Mount Sinai Hospital, University Health Network, University of Toronto, Toronto, Ontario, Canada
| | - P J Maralani
- Department of Medical Imaging (P.J.M.), Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - J Spears
- Neurosurgery (J.S.), St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - A Bharatha
- From the Departments of Medical Imaging (P.A.-L., A.B.)
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47
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Hatzoglou V, Tisnado J, Mehta A, Peck KK, Daras M, Omuro AM, Beal K, Holodny AI. Dynamic contrast-enhanced MRI perfusion for differentiating between melanoma and lung cancer brain metastases. Cancer Med 2017; 6:761-767. [PMID: 28303695 PMCID: PMC5387174 DOI: 10.1002/cam4.1046] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Revised: 01/25/2017] [Accepted: 01/26/2017] [Indexed: 01/30/2023] Open
Abstract
Brain metastases originating from different primary sites overlap in appearance and are difficult to differentiate with conventional MRI. Dynamic contrast-enhanced (DCE)-MRI can assess tumor microvasculature and has demonstrated utility in characterizing primary brain tumors. Our aim was to evaluate the performance of plasma volume (Vp) and volume transfer coefficient (Ktrans ) derived from DCE-MRI in distinguishing between melanoma and nonsmall cell lung cancer (NSCLC) brain metastases. Forty-seven NSCLC and 23 melanoma brain metastases were retrospectively assessed with DCE-MRI. Regions of interest were manually drawn around the metastases to calculate Vpmean and Kmeantrans. The Mann-Whitney U test and receiver operating characteristic analysis (ROC) were performed to compare perfusion parameters between the two groups. The Vpmean of melanoma brain metastases (4.35, standard deviation [SD] = 1.31) was significantly higher (P = 0.03) than Vpmean of NSCLC brain metastases (2.27, SD = 0.96). The Kmeantrans values were higher in melanoma brain metastases, but the difference between the two groups was not significant (P = 0.12). Based on ROC analysis, a cut-off value of 3.02 for Vpmean (area under curve = 0.659 with SD = 0.074) distinguished between melanoma brain metastases and NSCLC brain metastases (P < 0.01) with 72% specificity. Our data show the DCE-MRI parameter Vpmean can differentiate between melanoma and NSCLC brain metastases. The ability to noninvasively predict tumor histology of brain metastases in patients with multiple malignancies can have important clinical implications.
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Affiliation(s)
- Vaios Hatzoglou
- Department of RadiologyMemorial Sloan Kettering Cancer CenterNew York CityNew York
- Brain Tumor CenterMemorial Sloan Kettering Cancer CenterNew York CityNew York
| | - Jamie Tisnado
- Department of RadiologyMemorial Sloan Kettering Cancer CenterNew York CityNew York
| | - Alpesh Mehta
- Department of RadiologyMemorial Sloan Kettering Cancer CenterNew York CityNew York
| | - Kyung K. Peck
- Department of RadiologyMemorial Sloan Kettering Cancer CenterNew York CityNew York
- Department of Medical PhysicsMemorial Sloan Kettering Cancer CenterNew York CityNew York
| | - Mariza Daras
- Department of NeurologyMemorial Sloan Kettering Cancer CenterNew York CityNew York
| | - Antonio M. Omuro
- Brain Tumor CenterMemorial Sloan Kettering Cancer CenterNew York CityNew York
- Department of NeurologyMemorial Sloan Kettering Cancer CenterNew York CityNew York
| | - Kathryn Beal
- Brain Tumor CenterMemorial Sloan Kettering Cancer CenterNew York CityNew York
- Department of Radiation OncologyMemorial Sloan Kettering Cancer CenterNew York CityNew York
| | - Andrei I. Holodny
- Department of RadiologyMemorial Sloan Kettering Cancer CenterNew York CityNew York
- Brain Tumor CenterMemorial Sloan Kettering Cancer CenterNew York CityNew York
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48
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Clinical Applications of Contrast-Enhanced Perfusion MRI Techniques in Gliomas: Recent Advances and Current Challenges. CONTRAST MEDIA & MOLECULAR IMAGING 2017; 2017:7064120. [PMID: 29097933 PMCID: PMC5612612 DOI: 10.1155/2017/7064120] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 02/23/2017] [Indexed: 01/12/2023]
Abstract
Gliomas possess complex and heterogeneous vasculatures with abnormal hemodynamics. Despite considerable advances in diagnostic and therapeutic techniques for improving tumor management and patient care in recent years, the prognosis of malignant gliomas remains dismal. Perfusion-weighted magnetic resonance imaging techniques that could noninvasively provide superior information on vascular functionality have attracted much attention for evaluating brain tumors. However, nonconsensus imaging protocols and postprocessing analysis among different institutions impede their integration into standard-of-care imaging in clinic. And there have been very few studies providing a comprehensive evidence-based and systematic summary. This review first outlines the status of glioma theranostics and tumor-associated vascular pathology and then presents an overview of the principles of dynamic contrast-enhanced MRI (DCE-MRI) and dynamic susceptibility contrast-MRI (DSC-MRI), with emphasis on their recent clinical applications in gliomas including tumor grading, identification of molecular characteristics, differentiation of glioma from other brain tumors, treatment response assessment, and predicting prognosis. Current challenges and future perspectives are also highlighted.
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49
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Xu W, Wang Q, Shao A, Xu B, Zhang J. The performance of MR perfusion-weighted imaging for the differentiation of high-grade glioma from primary central nervous system lymphoma: A systematic review and meta-analysis. PLoS One 2017; 12:e0173430. [PMID: 28301491 PMCID: PMC5354292 DOI: 10.1371/journal.pone.0173430] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 02/19/2017] [Indexed: 12/16/2022] Open
Abstract
It is always a great challenge to distinguish high-grade glioma (HGG) from primary central nervous system lymphoma (PCNSL). We conducted a meta-analysis to assess the performance of MR perfusion-weighted imaging (PWI) in differentiating HGG from PCNSL. The heterogeneity and threshold effect were evaluated, and the sensitivity (SEN), specificity (SPE) and areas under summary receiver operating characteristic curve (SROC) were calculated. Fourteen studies with a total of 598 participants were included in this meta-analysis. The results indicated that PWI had a high level of accuracy (area under the curve (AUC) = 0.9415) for differentiating HGG from PCNSL by using the best parameter from each study. The dynamic susceptibility-contrast (DSC) technique might be an optimal index for distinguishing HGGs from PCNSLs (AUC = 0.9812). Furthermore, the DSC had the best sensitivity 0.963 (95%CI: 0.924, 0.986), whereas the arterial spin-labeling (ASL) displayed the best specificity 0.896 (95% CI: 0.781, 0.963) among those techniques. However, the variability of the optimal thresholds from the included studies suggests that further evaluation and standardization are needed before the techniques can be extensively clinically used.
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Affiliation(s)
- Weilin Xu
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Qun Wang
- Department of Neurosurgery, Chinese PLA General Hospital, Haidian District, Beijing, China
| | - Anwen Shao
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Bainan Xu
- Department of Neurosurgery, Chinese PLA General Hospital, Haidian District, Beijing, China
- * E-mail: (JZ); (BX)
| | - Jianmin Zhang
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
- Brain Research Institute, Zhejiang University, Hangzhou, Zhejiang, China
- Collaborative Innovation Center for Brain Science, Zhejiang University, Hangzhou, Zhejiang, China
- * E-mail: (JZ); (BX)
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50
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Quantitative Evaluation of Diffusion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Differentiation Between Primary Central Nervous System Lymphoma and Glioblastoma. J Comput Assist Tomogr 2017; 41:898-903. [DOI: 10.1097/rct.0000000000000622] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
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