1
|
Lee J, Chen MM, Liu HL, Ucisik FE, Wintermark M, Kumar VA. MR Perfusion Imaging for Gliomas. Magn Reson Imaging Clin N Am 2024; 32:73-83. [PMID: 38007284 DOI: 10.1016/j.mric.2023.07.003] [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: 11/27/2023]
Abstract
Accurate diagnosis and treatment evaluation of patients with gliomas is imperative to make clinical decisions. Multiparametric MR perfusion imaging reveals physiologic features of gliomas that can help classify them according to their histologic and molecular features as well as distinguish them from other neoplastic and nonneoplastic entities. It is also helpful in distinguishing tumor recurrence or progression from radiation necrosis, pseudoprogression, and pseudoresponse, which is difficult with conventional MR imaging. This review provides an update on MR perfusion imaging for the diagnosis and treatment monitoring of patients with gliomas following standard-of-care chemoradiation therapy and other treatment regimens such as immunotherapy.
Collapse
Affiliation(s)
- Jina Lee
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA
| | - Melissa M Chen
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA
| | - Ho-Ling Liu
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA
| | - F Eymen Ucisik
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA
| | - Max Wintermark
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA
| | - Vinodh A Kumar
- Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA.
| |
Collapse
|
2
|
Richter V, Nägele T, Erb G, Klose U, Ernemann U, Hauser TK. Improved diagnostic confidence and tumor type prediction in adult-type diffuse glioma by multimodal imaging including DCE perfusion and diffusion kurtosis mapping - A standardized multicenter study. Eur J Radiol 2024; 171:111293. [PMID: 38218066 DOI: 10.1016/j.ejrad.2024.111293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 01/04/2024] [Indexed: 01/15/2024]
Abstract
BACKGROUND AND PURPOSE To evaluate the feasibility of a multimodal approach involving dynamic contrast-enhanced (DCE) perfusion imaging and diffusion kurtosis imaging (DKI) in the preoperative imaging of brain tumors in a multicenter setting, and to evaluate the effect on diagnostic confidence and accuracy for tumor grade and type prediction. MATERIALS AND METHODS One hundred and thirty-three patients with brain tumors were imaged in six hospitals with a standardized multimodal protocol. Standard imaging and six parameter maps derived from DCE and DKI sequences were reviewed off-site by two independent readers. Image quality and diagnostic confidence were evaluated in qualitative analyses. Quantitative analyses were performed to assess diagnostic accuracy and the performance of DKI and DCE parameters for tumor grade differentiation and molecular tumor type determination. RESULTS Standardized acquisition of DCE and DKI maps was feasible with excellent image quality. Diagnostic confidence was significantly improved from 85 % to 96 % (p = 0.0005) by additional review of the DCE and DKI maps. The combination of mean kurtosis and CBV was particularly advantageous for differentiating low-grade and high-grade glioma, oligodendroglial vs. astrocytic, and IDH1/2 wild type vs. mutated tumors. CONCLUSION A multimodal imaging approach with DCE and DKI improves diagnostic confidence and yields higher diagnostic accuracy for predicting tumor grade and type in adult-type glioma.
Collapse
Affiliation(s)
- Vivien Richter
- University of Tübingen, Department of Radiology, Diagnostic and Interventional Neuroradiology, Germany.
| | - Thomas Nägele
- University of Tübingen, Department of Radiology, Diagnostic and Interventional Neuroradiology, Germany.
| | - Günther Erb
- Bracco Group, Medical and Regulatory Affairs, Konstanz, Germany.
| | - Uwe Klose
- University of Tübingen, Department of Radiology, Diagnostic and Interventional Neuroradiology, Germany.
| | - Ulrike Ernemann
- University of Tübingen, Department of Radiology, Diagnostic and Interventional Neuroradiology, Germany.
| | - Till-Karsten Hauser
- University of Tübingen, Department of Radiology, Diagnostic and Interventional Neuroradiology, Germany.
| |
Collapse
|
3
|
Griffith JF, Yip SWY, van der Heijden RA, Valenzuela RF, Yeung DKW. Perfusion Imaging of the Musculoskeletal System. Magn Reson Imaging Clin N Am 2024; 32:181-206. [PMID: 38007280 DOI: 10.1016/j.mric.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2023]
Abstract
Perfusion imaging is the aspect of functional imaging, which is most applicable to the musculoskeletal system. In this review, the anatomy and physiology of bone perfusion is briefly outlined as are the methods of acquiring perfusion data on MR imaging. The current clinical indications of perfusion related to the assessment of soft tissue and bone tumors, synovitis, osteoarthritis, avascular necrosis, Keinbock's disease, diabetic foot, osteochondritis dissecans, and Paget's disease of bone are reviewed. Challenges and opportunities related to perfusion imaging of the musculoskeletal system are also briefly addressed.
Collapse
Affiliation(s)
- James F Griffith
- Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong.
| | - Stefanie W Y Yip
- Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong
| | - Rianne A van der Heijden
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands; Department of Radiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Raul F Valenzuela
- Department of Musculoskeletal Imaging, The University of Texas, MD Anderson Cancer Center, USA
| | - David K W Yeung
- Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong
| |
Collapse
|
4
|
Seo M, Choi Y, Soo Lee Y, Ahn KJ, Kim BS, Park JS, Jeon SS. Glioma grading using multiparametric MRI: head-to-head comparison among dynamic susceptibility contrast, dynamic contrast-enhancement, diffusion-weighted images, and MR spectroscopy. Eur J Radiol 2023; 165:110888. [PMID: 37257338 DOI: 10.1016/j.ejrad.2023.110888] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 05/20/2023] [Indexed: 06/02/2023]
Abstract
PURPOSE To assess the diagnostic accuracy of dynamic susceptibility contrast, dynamic contrast-enhancement, MR spectroscopy (MRS), and diffusion-weighted imaging for differentiating high-grade (HGGs) from low-grade gliomas (LGGs). METHODS Seventy-two patients (16 LGGs, 56 HGGs) with pathologically confirmed gliomas were retrospectively included. From three-dimensionally segmented tumor, histogram analyses of relative cerebral blood volume (rCBV), volume transfer constant (Ktrans), and apparent diffusion coefficient (ADC) were performed. Choline-to-creatinine ratio (Cho/Cr) was calculated using MRS. Logistic regression analyses were performed to differentiate HGGs (grade ≥ 3) from LGGs (grade ≤ 2). Areas under the receiver operating characteristics curves (AUC) were plotted. Subgroup analysis was performed between IDH-wildtype glioblastomas and IDH-mutant astrocytomas. Pairwise Spearman's correlation coefficients (ρ) were computed. RESULTS HGGs had higher 95th percentile rCBV, Ktrans and Cho/Cr (P < 0.01) than LGGs. AUC of 95th percentiles of rCBV and Ktrans were 0.79 (95% CI, 0.67-0.91) and 0.74 (95% CI, 0.59-0.88), respectively. AUC of 5th percentile of ADC was 0.63 (95% CI, 0.48-0.79), and that of Cho/Cr was 0.67 (95% CI, 0.52-0.81). IDH-wildtype glioblastomas and IDH-mutant astrocytomas showed significantly different 95th percentile rCBV (P = 0.04) and Ktrans (P < 0.01), with Ktrans showing the highest AUC (0.73, 95% CI 0.57-0.89) in IDH status prediction. Moderate correlations were observed between 95th percentile rCBV and Ktrans (ρ = 0.47), Cho/Cr (ρ = 0.40), and 5th percentile ADC (ρ = -0.36) (all P < 0.01). CONCLUSIONS The 95th percentile rCBV may be most helpful in discriminating HGGs from LGGs. The 95th percentile Ktrans may aid predicting IDH status of diffuse gliomas.
Collapse
Affiliation(s)
- Minkook Seo
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Yangsean Choi
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea; Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 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
| | - Kook-Jin Ahn
- 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
| | - Jae-Sung Park
- Department of Neurosurgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sin-Soo Jeon
- Department of Neurosurgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| |
Collapse
|
5
|
van Santwijk L, Kouwenberg V, Meijer F, Smits M, Henssen D. A systematic review and meta-analysis on the differentiation of glioma grade and mutational status by use of perfusion-based magnetic resonance imaging. Insights Imaging 2022; 13:102. [PMID: 35670981 PMCID: PMC9174367 DOI: 10.1186/s13244-022-01230-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 04/20/2022] [Indexed: 01/17/2023] Open
Abstract
Background Molecular characterization plays a crucial role in glioma classification which impacts treatment strategy and patient outcome. Dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) perfusion imaging have been suggested as methods to help characterize glioma in a non-invasive fashion. This study set out to review and meta-analyze the evidence on the accuracy of DSC and/or DCE perfusion MRI in predicting IDH genotype and 1p/19q integrity status. Methods After systematic literature search on Medline, EMBASE, Web of Science and the Cochrane Library, a qualitative meta-synthesis and quantitative meta-analysis were conducted. Meta-analysis was carried out on aggregated AUC data for different perfusion metrics. Results Of 680 papers, twelve were included for the qualitative meta-synthesis, totaling 1384 patients. It was observed that CBV, ktrans, Ve and Vp values were, in general, significantly higher in IDH wildtype compared to IDH mutated glioma. Meta-analysis comprising of five papers (totaling 316 patients) showed that the AUC of CBV, ktrans, Ve and Vp were 0.85 (95%-CI 0.75–0.93), 0.81 (95%-CI 0.74–0.89), 0.84 (95%-CI 0.71–0.97) and 0.76 (95%-CI 0.61–0.90), respectively. No conclusive data on the prediction of 1p/19q integrity was available from these studies. Conclusions Future research should aim to predict 1p/19q integrity based on perfusion MRI data. Additionally, correlations with other clinically relevant outcomes should be further investigated, including patient stratification for treatment and overall survival. Supplementary Information The online version contains supplementary material available at 10.1186/s13244-022-01230-7.
Collapse
Affiliation(s)
- Lusien van Santwijk
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Valentina Kouwenberg
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Frederick Meijer
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Dylan Henssen
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands.
| |
Collapse
|
6
|
Stumpo V, Guida L, Bellomo J, Van Niftrik CHB, Sebök M, Berhouma M, Bink A, Weller M, Kulcsar Z, Regli L, Fierstra J. Hemodynamic Imaging in Cerebral Diffuse Glioma-Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions. Cancers (Basel) 2022; 14:1342. [PMID: 35267650 PMCID: PMC8909110 DOI: 10.3390/cancers14051342] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/01/2022] [Accepted: 03/02/2022] [Indexed: 02/05/2023] Open
Abstract
Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.
Collapse
Affiliation(s)
- Vittorio Stumpo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Lelio Guida
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jacopo Bellomo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Christiaan Hendrik Bas Van Niftrik
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Martina Sebök
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Moncef Berhouma
- Department of Neurosurgical Oncology and Vascular Neurosurgery, Pierre Wertheimer Neurological and Neurosurgical Hospital, Hospices Civils de Lyon, 69500 Lyon, France;
| | - Andrea Bink
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Michael Weller
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neurology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Zsolt Kulcsar
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| |
Collapse
|
7
|
Smith HJ. The history of magnetic resonance imaging and its reflections in Acta Radiologica. Acta Radiol 2021; 62:1481-1498. [PMID: 34657480 DOI: 10.1177/02841851211050857] [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] [Indexed: 12/11/2022]
Abstract
The first reports in Acta Radiologica on magnetic resonance imaging (MRI) were published in 1984, four years after the first commercial MR scanners became available. For the first two years, all MR papers originated from the USA. Nordic contributions started in 1986, and until 2020, authors from 44 different countries have published MR papers in Acta Radiologica. Papers on MRI have constituted, on average, 30%-40% of all published original articles in Acta Radiologica, with a high of 49% in 2019. The MR papers published since 1984 document tremendous progress in several areas such as magnet and coil design, motion compensation techniques, faster image acquisitions, new image contrast, contrast-enhanced MRI, functional MRI, and image analysis. In this historical review, all of these aspects of MRI are discussed and related to Acta Radiologica papers.
Collapse
Affiliation(s)
- Hans-Jørgen Smith
- Department of Radiology and Nuclear Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| |
Collapse
|
8
|
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.
Collapse
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.
| |
Collapse
|
9
|
Zhang HW, Lyu GW, He WJ, Lei Y, Lin F, Wang MZ, Zhang H, Liang LH, Feng YN, Yang JH. DSC and DCE Histogram Analyses of Glioma Biomarkers, Including IDH, MGMT, and TERT, on Differentiation and Survival. Acad Radiol 2020; 27:e263-e271. [PMID: 31983532 DOI: 10.1016/j.acra.2019.12.010] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 12/06/2019] [Accepted: 12/07/2019] [Indexed: 12/25/2022]
Abstract
RATIONALE AND OBJECTIVES The World Health Organization 2016 classification of central nervous system tumors added the molecular classification of gliomas and has guiding significance for the operation and prognosis of glioma patients. At present, the perfusion technique plays an important role in judging the malignant degree of glioma. To evaluate the performance of dynamic susceptibility contrast (DSC)- and dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) histogram analyses in discriminating the states of molecular biomarkers and survival in glioma patients. MATERIALS AND METHODS Forty-three glioma patients who underwent DCE- and DSC-MRI were enrolled. Relevant molecular test results, including those on isocitrate dehydrogenase (IDH), O6-methylguanine-DNA methyltransferase (MGMT) and telomere reverse transcriptase (TERT), were collected. The mean relative cerebral blood volume of DSC-MRI and histogram parameters derived from DCE-MRI (volume transfer coefficient (Ktrans), fractional volume of the extravascular extracellular space (Ve), fractional blood plasma volume (Vp), rate constant between the extravascular extracellular space and blood plasma (Kep) and area under the curve (AUC)) were calculated. Differences in each parameter between gliomas with different expression states (IDH, MGMT, and TERT) were evaluated. The diagnostic efficiency of each parameter was analyzed. The overall survival of all patients was assessed. RESULTS The 10th percentile AUC (AUC = 0.830, sensitivity = 0.78, specificity = 0.80), the 90th percentile Ve (AUC = 0.816, sensitivity = 0.84, specificity = 0.79), and the mean Kep (AUC = 0.818, sensitivity = 0.76, specificity = 0.78) provided the highest differential efficiency for IDH, MGMT, and TERT, respectively. Kaplan-Meier curves showed a significant difference between subjects with a 10th percentile AUC higher or lower than 0.028 (log-rank = 7.535; p = 0.006) for IDH and between subjects with different 90th percentile Ve values (log-rank = 6.532; p = 0.011) for MGMT. CONCLUSION Histogram DCE-MRI demonstrates good diagnostic performance in identifying different molecular types and for the prognostic assessment of glioma.
Collapse
Affiliation(s)
- Han-Wen Zhang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen 518035, China
| | - Gui-Wen Lyu
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen 518035, China
| | - Wen-Jie He
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen 518035, China
| | - Yi Lei
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen 518035, China.
| | - Fan Lin
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen 518035, China
| | - Meng-Zhu Wang
- Department of MR Scientific Marketing, Siemens Healthineers, Guangzhou, Guangdong Province, China
| | - Hong Zhang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen 518035, China
| | - Li-Hong Liang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen 518035, China
| | - Yu-Ning Feng
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen 518035, China
| | - Ji-Hu Yang
- Department of Neurosurgery, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, Shenzhen, China
| |
Collapse
|
10
|
Song S, Wang L, Yang H, Shan Y, Cheng Y, Xu L, Dong C, Zhao G, Lu J. Static 18F-FET PET and DSC-PWI based on hybrid PET/MR for the prediction of gliomas defined by IDH and 1p/19q status. Eur Radiol 2020; 31:4087-4096. [PMID: 33211141 DOI: 10.1007/s00330-020-07470-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 08/26/2020] [Accepted: 11/04/2020] [Indexed: 12/25/2022]
Abstract
OBJECTIVES To investigate the predictive value of static O-(2-18F-fluoroethyl)-L-tyrosine positron emission tomography (18F-FET PET) and cerebral blood volume (CBV) for glioma grading and determining isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status. METHODS Fifty-two patients with newly diagnosed gliomas who underwent simultaneous 18F-FET PET and dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) examinations on hybrid PET/MR were retrospectively enrolled. The mean and max tumor-to-brain ratio (TBR) and normalized CBV (nCBV) were calculated based on whole tumor volume segmentations with reference to PET/MR images. The predictive efficacy of FET PET and CBV in glioma according to the 2016 World Health Organization (WHO) classification was evaluated by receiver operating characteristic curve analyses with the area under the curve (AUC). RESULTS TBRmean, TBRmax, nCBVmean, and nCBVmax differed between low- and high-grade gliomas, with the highest AUC of nCBVmean (0.920). TBRmax and nCBVmean showed significant differences between gliomas with and without IDH mutation (p = 0.032 and 0.010, respectively). Furthermore, TBRmean, TBRmax, and nCBVmean discriminated between IDH-wildtype glioblastomas and IDH-mutated astrocytomas (p = 0.049, 0.034 and 0.029, respectively). The combination of TBRmax and nCBVmean showed the best predictive performance (AUC, 0.903). Only nCBVmean differentiated IDH-mutated with 1p/19q codeletion oligodendrogliomas from IDH-wildtype glioblastomas (p < 0.001) (AUC, 0.829), but none of the parameters discriminated between oligodendrogliomas and astrocytomas. CONCLUSIONS Both FET PET and DSC-PWI might be non-invasive predictors for glioma grades and IDH mutation status. FET PET combined with CBV could improve the differentiation of IDH-mutated astrocytomas and IDH-wildtype glioblastomas. However, FET PET and CBV might be limited for identifying oligodendrogliomas. KEY POINTS • Static 18F-FET PET and DSC-PWI parameters differed between low- and high-grade gliomas, with the highest AUC of the mean value of normalized CBV. • Static 18F-FET PET and DSC-PWI parameters based on hybrid PET/MR showed predictive value in identifying glioma IDH mutation subtypes, which have gained importance for both determining the diagnosis and prognosis of gliomas according to the 2016 WHO classification. • Static 18F-FET PET and DSC-PWI parameters have limited potential in differentiating IDH-mutated with 1p/19q codeletion oligodendrogliomas from IDH-wildtype glioblastomas or IDH-mutated astrocytomas.
Collapse
Affiliation(s)
- Shuangshuang Song
- Department of Radiology, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China.,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
| | - Leiming Wang
- Department of Pathology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Hongwei Yang
- Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yongzhi Shan
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Ye Cheng
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Lixin Xu
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | | | - Guoguang Zhao
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China. .,Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China. .,Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.
| |
Collapse
|
11
|
Zhang Y, Yue B, Zhao X, Chen H, Sun L, Zhang X, Hao D. Benign or Malignant Characterization of Soft-Tissue Tumors by Using Semiquantitative and Quantitative Parameters of Dynamic Contrast-Enhanced Magnetic Resonance Imaging. Can Assoc Radiol J 2020; 71:92-99. [PMID: 32062994 DOI: 10.1177/0846537119888409] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To evaluate the efficacy of the semiquantitative and quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating between benign and malignant soft-tissue tumors. METHODS A total of 45 patients with pathologically confirmed soft-tissue tumors (15 benign and 30 malignant tumors) underwent DCE-MRI. The semiquantitative parameters assessed were as follows: time to peak (TTP), maximum concentration (MAX Conc), area under the curve of time-concentration curve (AUC-TC), and maximum rise slope (MAX Slope). Quantitative DCE-MRI was analyzed with the extended Tofts-Kety model to assess the following quantitative parameters: volume transfer constant (Ktrans), microvascular permeability reflux constant (Kep), and distribute volume per unit tissue volume (Ve). Data were evaluated using the independent t test or Mann-Whitney U test and receiver operating characteristic (ROC) curves. RESULTS The TTP (P = .0035), MAX Conc (P = .0018), AUC-TC (P = .0018), MAX Slope (P = .0018), Ktrans (P = .0018), and Kep (P = .0035) were significantly different between the benign and malignant soft-tissue tumors. The AUC of the ROC curve demonstrated the diagnostic potential of TTP (0.778), MAX Conc (0.849), AUC-TC (0.831), MAX Slope (0.847), Ktrans (0.836), Kep (0.778), and Ve (0.638). CONCLUSIONS The use of semiquantitative and quantitative parameters of DCE-MRI enabled differentiation between benign and malignant soft-tissue tumors. The values of TTP were lower, while those of MAX Conc, AUC-TC, MAX Slope, Ktrans, and Kep were higher in malignant than in benign tumors.
Collapse
Affiliation(s)
- Yu Zhang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Bin Yue
- Department of Orthopedics, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xiaodan Zhao
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Haisong Chen
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Lingling Sun
- Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | | | - Dapeng Hao
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| |
Collapse
|
12
|
Zhao YY, Chen SH, Hao Z, Zhu HX, Xing ZL, Li MH. A Nomogram for Predicting Individual Prognosis of Patients with Low-Grade Glioma. World Neurosurg 2019; 130:e605-e612. [DOI: 10.1016/j.wneu.2019.06.169] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 06/19/2019] [Accepted: 06/20/2019] [Indexed: 01/25/2023]
|
13
|
Shen Y, Goerner FL, Heverhagen JT, Snyder C, Hu D, Li X, Runge VM. In vitro T2 relaxivities of the Gd-based contrast agents (GBCAs) in human blood at 1.5 and 3 T. Acta Radiol 2019; 60:694-701. [PMID: 30205704 DOI: 10.1177/0284185118799538] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND The availability of data in the medical literature for the T2 relaxivities of the Gd-based contrast agents (GBCAs) is limited. A comprehensive comparison between the agents available commercially (other than in Europe) is lacking, with no data available that most closely reflect the clinic, which is in human whole blood at body temperature. PURPOSE To complement the existing literature by determining T2 relaxivity data for eight GBCAs in vitro. MATERIAL AND METHODS The relaxivities of eight GBCAs diluted in human whole blood at 1.5 and 3 T were determined at 37 ± 0.5 °C. Gd was in the range of 0-4 mM. Multi-echo sequences with variable echo times were acquired using a phantom containing a dilution series with each agent, and SigmaPlot 12.0 was used to calculate the R2 relaxation rate and finally r2. Statistical comparisons between agents and field strengths were conducted. RESULTS The relationship between R2 vs. Gd was observed to be linear at 1.5 and 3 T, with a mild increase in r2 from 1.5 to 3 T for all GBCAs. T2 relaxivity data were compared with prior results. The GBCAs are closely clustered into two groups, with higher r2 noted for the two lipophilic (those with partial hepatobiliary excretion) compounds. CONCLUSION The r2 values at 1.5 and 3 T, determined for the eight GBCAs still clinically available (other than in Europe), provide a definitive baseline for future evaluations, including theoretical calculations of signal intensity and their clinical impact on T2-weighted scans.
Collapse
Affiliation(s)
- Yaqi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, Hubei, PR China
| | | | - Johannes T Heverhagen
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, University Hospital, University of Bern, Switzerland
| | | | - Daoyu Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, Hubei, PR China
| | - Xiaoming Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (HUST), Wuhan, Hubei, PR China
| | - Val M Runge
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, University Hospital, University of Bern, Switzerland
| |
Collapse
|
14
|
Colip C, Oztek MA, Lo S, Yuh W, Fink J. Updates in the Neuoroimaging and WHO Classification of Primary CNS Gliomas: A Review of Current Terminology, Diagnosis, and Clinical Relevance From a Radiologic Prospective. Top Magn Reson Imaging 2019; 28:73-84. [PMID: 31022050 DOI: 10.1097/rmr.0000000000000195] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
As new advances in the genomics and imaging of CNS tumors continues to evolve, a standardized system for classification is increasingly essential to diagnosis and management. The molecular markers introduced in the 2016 WHO classification of CNS tumors bring both practical and conceptual advances to the characterization of gliomas, strengthening the prognostic and predictive value of terminology while shedding light on the underlying mechanisms that drive biologic behavior. The purpose of this article is to provide a succinct overview of primary intracranial gliomas from a neuroradiologic prospective and according to the 5th edition WHO classification that was revised in 2016. An update of the molecular markers pertinent to defining the major lineages of brain gliomas will be provided, followed by discussion of the terminology, grading and imaging features associated with individual entities. Neuroradiologists should be aware of the key genomic and radiomic features of common brain gliomas, and familiar with an integrated approach to their diagnosis and grading.
Collapse
Affiliation(s)
- Charles Colip
- University of Washington Medical Center, Department of Radiology, Seattle, WA
| | - Murat Alp Oztek
- University of Washington Medical Center, Department of Radiology, Seattle, WA
| | - Simon Lo
- University of Washington Medical Center, Department of Radiation Oncology, Seattle, WA
| | - Willam Yuh
- University of Washington Medical Center, Department of Radiology, Seattle, WA
| | - James Fink
- University of Washington Medical Center, Department of Radiology, Seattle, WA
| |
Collapse
|
15
|
Surov A, Meyer HJ, Leifels L, Höhn AK, Richter C, Winter K. Histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging can predict histopathological findings including proliferation potential, cellularity, and nucleic areas in head and neck squamous cell carcinoma. Oncotarget 2018; 9:21070-21077. [PMID: 29765520 PMCID: PMC5940412 DOI: 10.18632/oncotarget.24920] [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: 11/03/2017] [Accepted: 03/06/2018] [Indexed: 02/07/2023] Open
Abstract
Our purpose was to analyze possible associations between histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging DCE MRI and histopathological findings like proliferation index, cell count and nucleic areas in head and neck squamous cell carcinoma (HNSCC). 30 patients (mean age 57.0 years) with primary HNSCC were included in the study. In every case, histogram analysis parameters of Ktrans, Ve, and Kep were estimated using a mathlab based software. Tumor proliferation index, cell count, and nucleic areas were estimated on Ki 67 antigen stained specimens. Spearman's non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters. KI 67 correlated with Ktrans min (p = −0.386, P = 0.043) and s Ktrans skewness (p = 0.382, P = 0.045), Ve min (p = −0.473, P = 0.011), Ve entropy (p = 0.424, P = 0.025), and Kep entropy (p = 0.464, P = 0.013). Cell count correlated with Ktrans kurtosis (p = 0.40, P = 0.034), Ve entropy (p = 0.475, P = 0.011). Total nucleic area correlated with Ve max (p = 0.386, P = 0.042) and Ve entropy (p = 0.411, P = 0.030). In G1/2 tumors, only Ktrans entropy correlated well with total (P =0.78, P =0.013) and average nucleic areas (p = 0.655, P = 0.006). In G3 tumors, KI 67 correlated with Ve min (p = −0.552, P = 0.022) and Ve entropy (p = 0.524, P = 0.031). Ve max correlated with total nucleic area (p = 0.483, P = 0.049). Kep max correlated with total area (p = −0.51, P = 0.037), and Kep entropy with KI 67 (p = 0.567, P = 0.018). We concluded that histogram-based parameters skewness, kurtosis and entropy of Ktrans, Ve, and Kep can be used as markers for proliferation activity, cellularity and nucleic content in HNSCC. Tumor grading influences significantly associations between perfusion and histopathological parameters.
Collapse
Affiliation(s)
- Alexey Surov
- Department of Diagnostic and Interventional Radiology, University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Hans Jonas Meyer
- Department of Diagnostic and Interventional Radiology, University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Leonard Leifels
- Department of Diagnostic and Interventional Radiology, University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Anne-Kathrin Höhn
- Department of Pathology University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Cindy Richter
- Institute of Anatomy, University Hospital of Leipzig, 04103 Leipzig, Germany
| | - Karsten Winter
- Institute of Anatomy, University Hospital of Leipzig, 04103 Leipzig, Germany
| |
Collapse
|