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Xian M, Yu J, Li Z, Piao Y, Wang C, Xian J, Zhang L. Microvessel barrier dysfunction in sinonasal inverted papilloma-associated squamous cell carcinoma and its manifestation in dynamic contrast-enhanced MRI. Int Forum Allergy Rhinol 2024; 14:1173-1181. [PMID: 38247185 DOI: 10.1002/alr.23316] [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: 09/27/2023] [Revised: 12/04/2023] [Accepted: 12/26/2023] [Indexed: 01/23/2024]
Abstract
BACKGROUND To date, an effective means to preoperatively predict the malignant transformation of sinonasal inverted papilloma (SIP) remains lacking due to similarities in clinical appearance. This study aimed to retrospectively evaluate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters and microvessel structure in tumors with histologically confirmed SIP and inverted papilloma-associated squamous cell carcinoma (IP-SCC), as well as correlate DCE-MRI findings with angiogenesis biomarkers. METHODS Absolute quantitative DCE-MRI parameters (Ktrans, Kep, Ve) based on the Tofts model and model-free semi-quantitative indices (Tpeak, WR, MaxSlope) of SIP (n = 22) and IP-SCC (n = 20) were investigated. Regions of interest (ROIs) were oriented according to the tumor subsites in the surgical records. Micro-vessel density (MVD) counts and tight junction protein (claudin-5) expression were evaluated in tumor specimens obtained during surgery. Differences in the above data were compared between the two groups. Correlations between DCE-MRI parameters and angiogenic biomarkers were analyzed. RESULTS Compared with SIP specimens, IP-SCC specimens were characterized by a significantly higher MVD and a leakier microvessel barrier. The values of Tpeak and Ve were significantly higher for SIP than those for IP-SCC, whereas WR, MaxSlope, and Kep were significantly lower, indicating early enhancement and a faster dispersion model in IP-SCC. MVD was positively correlated with WR and Kep and negatively correlated with Tpeak. Tpeak was slightly positively correlated to claudin-5 expression. CONCLUSION DCE-MRI can serve as a noninvasive biomarker of angiogenesis in the malignant transformation from SIP to IP-SCC. DCE-MRI may assist in the differentiation of malignancies and treatment selection.
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Affiliation(s)
- Mu Xian
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jiaqi Yu
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Zheng Li
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Yingshi Piao
- Department of Pathology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Chegnshuo Wang
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Nasal Diseases, Beijing Institute of Otolaryngology, Beijing, China
| | - Junfang Xian
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Luo Zhang
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Nasal Diseases, Beijing Institute of Otolaryngology, Beijing, China
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Zhou J, Hou Z, Tian C, Zhu Z, Ye M, Chen S, Yang H, Zhang X, Zhang B. Review of tracer kinetic models in evaluation of gliomas using dynamic contrast-enhanced imaging. Front Oncol 2024; 14:1380793. [PMID: 38947892 PMCID: PMC11211364 DOI: 10.3389/fonc.2024.1380793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 05/29/2024] [Indexed: 07/02/2024] Open
Abstract
Glioma is the most common type of primary malignant tumor of the central nervous system (CNS), and is characterized by high malignancy, high recurrence rate and poor survival. Conventional imaging techniques only provide information regarding the anatomical location, morphological characteristics, and enhancement patterns. In contrast, advanced imaging techniques such as dynamic contrast-enhanced (DCE) MRI or DCE CT can reflect tissue microcirculation, including tumor vascular hyperplasia and vessel permeability. Although several studies have used DCE imaging to evaluate gliomas, the results of data analysis using conventional tracer kinetic models (TKMs) such as Tofts or extended-Tofts model (ETM) have been ambiguous. More advanced models such as Brix's conventional two-compartment model (Brix), tissue homogeneity model (TH) and distributed parameter (DP) model have been developed, but their application in clinical trials has been limited. This review attempts to appraise issues on glioma studies using conventional TKMs, such as Tofts or ETM model, highlight advancement of DCE imaging techniques and provides insights on the clinical value of glioma management using more advanced TKMs.
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Affiliation(s)
- Jianan Zhou
- Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Zujun Hou
- The Jiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China
| | - Chuanshuai Tian
- Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Zhengyang Zhu
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Meiping Ye
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Sixuan Chen
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Huiquan Yang
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Xin Zhang
- Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Bing Zhang
- Department of Radiology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
- Institute of Medical Imaging and Artificial Intelligence, Nanjing University, Nanjing, China
- Medical Imaging Center, Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
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Foltyn-Dumitru M, Kessler T, Sahm F, Wick W, Heiland S, Bendszus M, Vollmuth P, Schell M. Cluster-based prognostication in glioblastoma: Unveiling heterogeneity based on diffusion and perfusion similarities. Neuro Oncol 2024; 26:1099-1108. [PMID: 38153923 PMCID: PMC11145444 DOI: 10.1093/neuonc/noad259] [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: 09/10/2023] [Indexed: 12/30/2023] Open
Abstract
BACKGROUND While the association between diffusion and perfusion magnetic resonance imaging (MRI) and survival in glioblastoma is established, prognostic models for patients are lacking. This study employed clustering of functional imaging to identify distinct functional phenotypes in untreated glioblastomas, assessing their prognostic significance for overall survival. METHODS A total of 289 patients with glioblastoma who underwent preoperative multimodal MR imaging were included. Mean values of apparent diffusion coefficient normalized relative cerebral blood volume and relative cerebral blood flow were calculated for different tumor compartments and the entire tumor. Distinct imaging patterns were identified using partition around medoids (PAM) clustering on the training dataset, and their ability to predict overall survival was assessed. Additionally, tree-based machine-learning models were trained to ascertain the significance of features pertaining to cluster membership. RESULTS Using the training dataset (231/289) we identified 2 stable imaging phenotypes through PAM clustering with significantly different overall survival (OS). Validation in an independent test set revealed a high-risk group with a median OS of 10.2 months and a low-risk group with a median OS of 26.6 months (P = 0.012). Patients in the low-risk cluster had high diffusion and low perfusion values throughout, while the high-risk cluster displayed the reverse pattern. Including cluster membership in all multivariate Cox regression analyses improved performance (P ≤ 0.004 each). CONCLUSIONS Our research demonstrates that data-driven clustering can identify clinically relevant, distinct imaging phenotypes, highlighting the potential role of diffusion, and perfusion MRI in predicting survival rates of glioblastoma patients.
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Affiliation(s)
- Martha Foltyn-Dumitru
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Section for Computational Neuroimaging, Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Tobias Kessler
- Department of Neurology and Neurooncology Program, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
- Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Felix Sahm
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Department of Neurology and Neurooncology Program, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
- Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Section for Computational Neuroimaging, Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Marianne Schell
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Section for Computational Neuroimaging, Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
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Pons-Escoda A. "Everything Everywhere All at Once": Unraveling perfusion, permeability, and leakage effects in neurooncology with a single-dose, single-acquisition dual-echo DSC. Eur Radiol 2024; 34:3084-3086. [PMID: 37917358 DOI: 10.1007/s00330-023-10277-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 08/16/2023] [Accepted: 08/23/2023] [Indexed: 11/04/2023]
Affiliation(s)
- Albert Pons-Escoda
- Neuroradiology Department, Hospital Universitari de Bellvitge, Barcelona, Spain.
- Neuro-Oncology Unit, Institut d'Investigació Biomèdica de Bellvitge- IDIBELL, Barcelona, Spain.
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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 2024; 34:3087-3101. [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] [MESH Headings] [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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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.
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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.
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Elschot EP, Backes WH, van den Kerkhof M, Postma AA, Kroon AA, Jansen JFA. Cerebral Microvascular Perfusion Assessed in Elderly Adults by Spin-Echo Dynamic Susceptibility Contrast MRI at 7 Tesla. Tomography 2024; 10:181-192. [PMID: 38250960 PMCID: PMC10819808 DOI: 10.3390/tomography10010014] [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: 10/31/2023] [Revised: 01/15/2024] [Accepted: 01/15/2024] [Indexed: 01/23/2024] Open
Abstract
Perfusion measures of the total vasculature are commonly derived with gradient-echo (GE) dynamic susceptibility contrast (DSC) MR images, which are acquired during the early passes of a contrast agent. Alternatively, spin-echo (SE) DSC can be used to achieve specific sensitivity to the capillary signal. For an improved contrast-to-noise ratio, ultra-high-field MRI makes this technique more appealing to study cerebral microvascular physiology. Therefore, this study assessed the applicability of SE-DSC MRI at 7 T. Forty-one elderly adults underwent 7 T MRI using a multi-slice SE-EPI DSC sequence. The cerebral blood volume (CBV) and cerebral blood flow (CBF) were determined in the cortical grey matter (CGM) and white matter (WM) and compared to values from the literature. The relation of CBV and CBF with age and sex was investigated. Higher CBV and CBF values were found in CGM compared to WM, whereby the CGM-to-WM ratios depended on the amount of largest vessels excluded from the analysis. CBF was negatively associated with age in the CGM, while no significant association was found with CBV. Both CBV and CBF were higher in women compared to men in both CGM and WM. The current study verifies the possibility of quantifying cerebral microvascular perfusion with SE-DSC MRI at 7 T.
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Affiliation(s)
- Elles P. Elschot
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, P.O. Box 5800, 6202 AZ Maastricht, The Netherlands; (E.P.E.)
- MHeNs School for Mental Health and Neuroscience, Maastricht University, Minderbroedersberg 4-6, P.O. Box 616, 6200 MD Maastricht, The Netherlands
| | - Walter H. Backes
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, P.O. Box 5800, 6202 AZ Maastricht, The Netherlands; (E.P.E.)
- MHeNs School for Mental Health and Neuroscience, Maastricht University, Minderbroedersberg 4-6, P.O. Box 616, 6200 MD Maastricht, The Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Minderbroedersberg 4-6, P.O. Box 616, 6200 MD Maastricht, The Netherlands
| | - Marieke van den Kerkhof
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, P.O. Box 5800, 6202 AZ Maastricht, The Netherlands; (E.P.E.)
- MHeNs School for Mental Health and Neuroscience, Maastricht University, Minderbroedersberg 4-6, P.O. Box 616, 6200 MD Maastricht, The Netherlands
| | - Alida A. Postma
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, P.O. Box 5800, 6202 AZ Maastricht, The Netherlands; (E.P.E.)
- MHeNs School for Mental Health and Neuroscience, Maastricht University, Minderbroedersberg 4-6, P.O. Box 616, 6200 MD Maastricht, The Netherlands
| | - Abraham A. Kroon
- CARIM School for Cardiovascular Diseases, Maastricht University, Minderbroedersberg 4-6, P.O. Box 616, 6200 MD Maastricht, The Netherlands
- Department of Internal Medicine, Maastricht University Medical Center+, P. Debyelaan 25, P.O. Box 5800, 6202 AZ Maastricht, The Netherlands
| | - Jacobus F. A. Jansen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P. Debyelaan 25, P.O. Box 5800, 6202 AZ Maastricht, The Netherlands; (E.P.E.)
- MHeNs School for Mental Health and Neuroscience, Maastricht University, Minderbroedersberg 4-6, P.O. Box 616, 6200 MD Maastricht, The Netherlands
- Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, P.O. Box 513, 5612 AP Eindhoven, The Netherlands
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8
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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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Zhang Y, Keunen O, Golebiewska A, Gerosa M, Wang J, Ghobadi SN, Huang A, Hou Q, Habte FG, Li N, Grant G, Paulmurugan R, Lee KS, Wintermark M. Immune cell identity behind the K trans mapping of mouse glioblastoma. Magn Reson Imaging 2023; 103:92-101. [PMID: 37353182 PMCID: PMC10528281 DOI: 10.1016/j.mri.2023.06.008] [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: 03/08/2023] [Revised: 05/12/2023] [Accepted: 06/17/2023] [Indexed: 06/25/2023]
Abstract
Dynamic contrast-enhanced MR imaging (DCE-MRI) can assess the integrity of the blood brain barrier (BBB) and has been used in GBM patients to determine glioma grade, predict prognosis, evaluate treatment response, and differentiate treatment-induced effect from recurrence. The volume transfer constant Ktrans is the most frequently used metric in tumor assessment. Based on previous studies that a higher WHO grade of brain tumor was associated with greater impairments of immunity and that Ktrans value was associated with the pathological grading, the relationship between differential composition of immune cells in GBM tissue and dynamic changes in Ktrans mapping was anticipated in this study. The present study utilized an orthotopic allograft model of GBM in which mouse GL26 cells are implanted into Ccr2RFP/wtCx3cr1GFP/wt mice on a C57 background. The brain tumors exhibited heterogenous Ktrans values with the coefficients of variation (CV) above 75%, or relatively homogeneous Ktrans maps with CV values below 50%. The Ktrans values of homogeneous tumors ranged between 0.02/min-0.32/min with a median value of 0.10/min. The immune cell composition defined by quantitative immunohistochemistry and cell sorting was compared between the tumors with Ktrans values above 0.10/min (higher Ktrans) or below 0.10/min (lower Ktrans). Histological analysis showed that tumors with higher Ktrans values exhibited greater numbers of CCR2pos cells (257.60 ± 16.42/mm2 vs 203.23 ± 12.20/mm2, p = 0.04) and an increased ratio of CCR2pos cells to CX3CR1pos cells (1.20 ± 0.02 vs 0.38 ± 0.04, p = 0.001), the numbers of CX3CR1pos cells did not differ significantly based on Ktrans values (219.70 ± 16.20/mm2 vs 250.38 ± 21.20/mm2, p = 0.19). Flowcytometry analysis showed that tumors with higher Ktrans values (above 0.1/min) were associated with greater numbers of both overall monocytes (54.93 ± 6.81% vs 29.75 ± 3.54%, p = 0.01) and inflammatory monocytes (72.38 ± 1.49% vs 59.52 ± 2.44%, p = 0.001). In contrast, tumors with lower Ktrans values (below 0.1/min) exhibited greater numbers of patrolling monocytes (75.65 ± 4.14% vs 63 ± 6.94%, p = 0.05). In the tumors with lower Ktrans values, all three types of tumor associated cells, including patrolling monocytes, inflammatory monocytes, and microglia cells possessed a higher proportion of cells at pro-inflammatory status (41.77 ± 6.13% vs 25.06 ± 6.72%, p = 0.05; 27.50 ± 2.11% vs 20.62 ± 1.87%, p = 0.03; and 55.80 ± 9.88% vs 31.12 ± 7.31%, p = 0.05), inflammatory monocytes showed fewer anti-inflammatory cells (1.25 ± 0.62% vs 3.16 ± 3.56%, p = 0.04). Taken together, differences in Ktrans values were associated with differential immune cell phenotypes and polarizations. Ktrans mapping may therefore represent a novel approach for defining the immune status of GBM.
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Affiliation(s)
- Yanrong Zhang
- Department of Radiology, Neuroradiology Division, Stanford University, CA, USA; Stanford Shared FACS Facility, Stanford University, CA, USA
| | - Olivier Keunen
- Department of Radiology, Neuroradiology Division, Stanford University, CA, USA; In Vivo Imaging Facility, Quantitative Biology Unit, Luxembourg Institute of Health Transversal Activities, 84 Val Fleuri, L-1526, Luxembourg
| | - Anna Golebiewska
- Department of Radiology, Neuroradiology Division, Stanford University, CA, USA; Department of Oncology, Luxembourg Institute of Health, 84, Val Fleuri, L-1526, Luxembourg
| | - Marco Gerosa
- Department of Radiology, Neuroradiology Division, Stanford University, CA, USA; Department of Diagnostic and Public Health, University of Verona, Verona 37135, Italy
| | - Jing Wang
- Department of Radiology, Neuroradiology Division, Stanford University, CA, USA; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, 324 Jing-wu Road, Jinan 250021, China
| | | | - Ai Huang
- Department of Radiology, Neuroradiology Division, Stanford University, CA, USA; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
| | - Qingyi Hou
- Department of Radiology, Neuroradiology Division, Stanford University, CA, USA; Nuclear Medicine Department, Guangdong Provincial People's Hospital, Guangzhou 510080, China
| | - Frezghi G Habte
- Stanford Center for Innovation in In vivo Imaging (SCi3), Stanford University, CA, USA
| | - Ningrui Li
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Gerry Grant
- Department of Neurosurgery, Stanford University School of Medicine, CA 94305, USA
| | - Ramasamy Paulmurugan
- Molecular Imaging Program at Stanford (MIPS), Canary Center for Cancer Early Detection, Department of Radiology, Stanford University, CA, USA
| | - Kevin S Lee
- Departments of Neuroscience and Neurosurgery and Center for Brain Immunology and Glia, School of Medicine, University of Virginia, Charlottesville, Virginia, USA.
| | - Max Wintermark
- Department of Neuroradiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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Zeng S, Ma H, Xie D, Huang Y, Wang M, Zeng W, Zhu N, Ma Z, Yang Z, Chu J, Zhao J. Quantitative susceptibility mapping evaluation of glioma. Eur Radiol 2023; 33:6636-6647. [PMID: 37095360 DOI: 10.1007/s00330-023-09647-4] [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: 04/29/2022] [Revised: 12/28/2022] [Accepted: 02/24/2023] [Indexed: 04/26/2023]
Abstract
OBJECTIVES To comprehensively evaluate the glioma using quantitative susceptibility mapping (QSM). MATERIALS AND METHODS Forty-two patients (18 women; mean age, 45 years) with pathologically confirmed gliomas were retrospectively included. All the patients underwent conventional and advanced MRI examinations (QSM, DWI, MRS, etc.). Five patients underwent paired QSM (pre- and post-enhancement). Four Visually Accessible Rembrandt Image (VASARI) features and intratumoural susceptibility signal (ITSS) were observed. Three ROIs each were manually drawn separately in the tumour parenchyma with relatively high and low magnetic susceptibility. The association between the tumour's magnetic susceptibility and other MRI parameters was also analysed. RESULTS Morphologically, gliomas with heterogeneous ITSS were more similar to high-grade gliomas (p = 0.006, AUC: 0.72, sensitivity: 70%, and specificity: 73%). Heterogeneous ITSS was significantly associated with tumour haemorrhage, necrosis, diffusion restriction, and avid enhancement but did not change between pre- and post-enhanced QSM. Quantitatively, tumour parenchyma magnetic susceptibility had limited value in grading gliomas and identifying IDH mutation status, whereas the relatively low magnetic susceptibility of the tumour parenchyma helped identify oligodendrogliomas in IDH mutated gliomas (AUC = 0.78) with high specificity (100%). The relatively high tumour magnetic susceptibility significantly increased after enhancement (p = 0.039). Additionally, we found that the magnetic susceptibility of the tumour parenchyma was significantly correlated with ADC (r = 0.61) and Cho/NAA (r = 0.40). CONCLUSIONS QSM is a promising candidate for the comprehensive evaluation of gliomas, except for IDH mutation status. The magnetic susceptibility of tumour parenchyma may be affected by tumour cell proliferation. KEY POINTS • Morphologically, gliomas with a heterogeneous intratumoural susceptibility signal (ITSS) are more similar to high-grade gliomas (p = 0.006; AUC, 0.72; sensitivity, 70%; and specificity, 73%). Heterogeneous ITSS was significantly associated with tumour haemorrhage, necrosis, diffusion restriction, and avid enhancement but did not change between pre- and post-enhanced QSM. • Tumour parenchyma's relatively low magnetic susceptibility helped identify oligodendroglioma with high specificity. • Tumour parenchyma magnetic susceptibility was significantly correlated with ADC (r = 0.61) and Cho/NAA (r = 0.40).
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Affiliation(s)
- Shanmei Zeng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Hui Ma
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Dingxiang Xie
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Yingqian Huang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Mengzhu Wang
- Department of MR Scientific Marketing, Siemens Healthineers, Guangzhou, Guangdong, People's Republic of China
| | - Wenting Zeng
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Nengjin Zhu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Zuliwei Ma
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Zhiyun Yang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China
| | - Jianping Chu
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China.
| | - Jing Zhao
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, No. 58 Zhongshan Road 2, Guangdong, 510080, Guangzhou, People's Republic of China.
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11
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Hess CP. MRI of the Brain: What Is Driving Innovation in 2023? Radiology 2023; 308:e231657. [PMID: 37750776 DOI: 10.1148/radiol.231657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Affiliation(s)
- Christopher P Hess
- From the Department of Radiology & Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, Room M-391, San Francisco, CA 94143-0628
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12
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Wu J, Liang Z, Deng X, Xi Y, Feng X, Yao Z, Shu Z, Xie Q. Glioma grade discrimination with dynamic contrast-enhanced MRI: An accurate analysis based on MRI guided stereotactic biopsy. Magn Reson Imaging 2023; 99:91-97. [PMID: 36803634 DOI: 10.1016/j.mri.2023.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 02/05/2023] [Accepted: 02/06/2023] [Indexed: 02/17/2023]
Abstract
PURPOSE To evaluate the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) metrics for glioma grading on a point-to-point basis. METHODS Forty patients with treatment-naïve glioma underwent DCE-MR examination and stereotactic biopsy. DCE-derived parameters including endothelial transfer constant (Ktrans), volume of extravascular-extracellular space (ve), fractional plasma volume (fpv), and reflux transfer rate (kep) were measured within ROIs on DCE maps accurately matched with biopsies used for histologic grades diagnosis. Differences in parameters between grades were evaluated by Kruskal-Wallis tests. Diagnostic accuracy of each parameter and their combination was assessed using receiver operating characteristic curve. RESULTS Eighty-four independent biopsy samples from 40 patients were analyzed in our study. Significant statistical differences in Ktrans and ve were observed between grades except ve between grade 2 and 3. Ktrans showed good to excellent accuracy in discriminating grade 2 from 3, 3 from 4, and 2 from 4 (area under the curve = 0.802, 0.801 and 0.971, respectively). Ve indicated good accuracy in discriminating grade 3 from 4 and 2 from 4 (AUC = 0.874 and 0.899, respectively). The combined parameter demonstrated fair to excellent accuracy in discriminating grade 2 from 3, 3 from 4, and 2 from 4 (AUC = 0.794, 0.899 and 0.982, respectively). CONCLUSION Our study had identified Ktrans, ve and the combination of parameters to be an accurate predictor for grading glioma.
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Affiliation(s)
- Juan Wu
- Department of Radiology, Shanghai TCM-Integrated Hospital affiliated to Shanghai University of Traditional Chinese Medicine, NO. 230 Dalian Road, Shanghai 200082, PR China
| | - Zonghui Liang
- Department of Radiology, Jing'an District Centre Hospital, Fudan University, NO. 266 Xikang Road, Shanghai 200040, PR China
| | - Xiaofei Deng
- Department of Radiology, Shanghai TCM-Integrated Hospital affiliated to Shanghai University of Traditional Chinese Medicine, NO. 230 Dalian Road, Shanghai 200082, PR China
| | - Yan Xi
- Department of Radiology, Shanghai TCM-Integrated Hospital affiliated to Shanghai University of Traditional Chinese Medicine, NO. 230 Dalian Road, Shanghai 200082, PR China
| | - Xiaoyuan Feng
- Department of Radiology, Huashan Hospital, Fudan University, Mid Wulumuqi Road, Shanghai 200040, PR China
| | - Zhenwei Yao
- Department of Radiology, Huashan Hospital, Fudan University, Mid Wulumuqi Road, Shanghai 200040, PR China.
| | - Zheng Shu
- Department of Radiology, Shanghai TCM-Integrated Hospital affiliated to Shanghai University of Traditional Chinese Medicine, NO. 230 Dalian Road, Shanghai 200082, PR China.
| | - Qian Xie
- Department of Radiology, Jing'an District Centre Hospital, Fudan University, NO. 266 Xikang Road, Shanghai 200040, PR China.
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13
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Zhang Y, Wang J, Ghobadi SN, Zhou H, Huang A, Gerosa M, Hou Q, Keunen O, Golebiewska A, Habte FG, Grant GA, Paulmurugan R, Lee KS, Wintermark M. Molecular Identity Changes of Tumor-Associated Macrophages and Microglia After Magnetic Resonance Imaging-Guided Focused Ultrasound-Induced Blood-Brain Barrier Opening in a Mouse Glioblastoma Model. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:1082-1090. [PMID: 36717283 PMCID: PMC10059983 DOI: 10.1016/j.ultrasmedbio.2022.12.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/11/2022] [Accepted: 12/10/2022] [Indexed: 05/11/2023]
Abstract
An orthotopically allografted mouse GL26 glioma model (Ccr2RFP/wt-Cx3cr1GFP/wt) was used to evaluate the effect of transient, focal opening of the blood-brain barrier (BBB) on the composition of tumor-associated macrophages and microglia (TAMs). BBB opening was induced by magnetic resonance imaging (MRI)-guided focused ultrasound (MRgFUS) combined with microbubbles. CX3CR1-GFP cells and CCR2-RFP cells in brain tumors were quantified in microscopic images. Tumors in animals treated with a single session of MRgFUS did not exhibit significant changes in cell numbers when compared with tumors in animals not receiving FUS. However, tumors that received two or three sessions of MRgFUS had significantly increased amounts of both CX3CR1-GFP and CCR2-RFP cells. The effect of MRgFUS on immune cell composition was also characterized and quantified using flow cytometry. Glioma implantation resulted in increased amounts of lymphocytes, monocytes and neutrophils in the brain parenchyma. Tumors administered MRgFUS exhibited increased numbers of monocytes and monocyte-derived TAMs. In addition, MRgFUS-treated tumors exhibited more CD80+ cells in monocytes and microglia. In summary, transient, focal opening of the BBB using MRgFUS combined with microbubbles can activate the homing and differentiation of monocytes and induce a shift toward a more pro-inflammatory status of the immune environment in glioblastoma.
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Affiliation(s)
- Yanrong Zhang
- Department of Radiology, Neuroradiology Division, Stanford University, Stanford, CA, USA
| | - Jing Wang
- Department of Radiology, Neuroradiology Division, Stanford University, Stanford, CA, USA; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Sara Natasha Ghobadi
- Department of Radiology, Neuroradiology Division, Stanford University, Stanford, CA, USA
| | - Haiyan Zhou
- Department of Radiology, Neuroradiology Division, Stanford University, Stanford, CA, USA; Acupuncture and Tuina School/Third Teaching Hospital, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Ai Huang
- Department of Radiology, Neuroradiology Division, Stanford University, Stanford, CA, USA; Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Marco Gerosa
- Department of Radiology, Neuroradiology Division, Stanford University, Stanford, CA, USA; Department of Diagnostic and Public Health, University of Verona, Verona, Italy
| | - Qingyi Hou
- Department of Radiology, Neuroradiology Division, Stanford University, Stanford, CA, USA; Department of Nuclear Medicine, Guangdong Provincial People's Hospital, Guangzhou, China
| | - Olivier Keunen
- In Vivo Imaging Facility, Luxembourg Institute of Health, Luxembourg
| | - Anna Golebiewska
- Department of Oncology, Luxembourg Institute of Health, Luxembourg
| | - Frezghi G Habte
- Department of Radiology, Molecular Imaging Program at Stanford, Stanford, CA, USA
| | - Gerald A Grant
- Division of Pediatric Neurosurgery, Department of Neurosurgery, Lucile Packard Children's Hospital, Stanford University School of Medicine, Stanford, CA, USA
| | - Ramasamy Paulmurugan
- Molecular Imaging Program at Stanford (MIPS), Canary Center for Cancer Early Detection, Department of Radiology, Stanford University, Stanford, CA, USA
| | - Kevin S Lee
- Departments of Neuroscience and Neurosurgery and Center for Brain, Immunology, and Glia, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Max Wintermark
- Department of Neuroradiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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14
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Cho NS, Hagiwara A, Sanvito F, Ellingson BM. A multi-reader comparison of normal-appearing white matter normalization techniques for perfusion and diffusion MRI in brain tumors. Neuroradiology 2023; 65:559-568. [PMID: 36301349 PMCID: PMC9905164 DOI: 10.1007/s00234-022-03072-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 10/14/2022] [Indexed: 02/08/2023]
Abstract
PURPOSE There remains no consensus normal-appearing white matter (NAWM) normalization method to compute normalized relative cerebral blood volume (nrCBV) and apparent diffusion coefficient (nADC) in brain tumors. This reader study explored nrCBV and nADC differences using different NAWM normalization methods. METHODS Thirty-five newly diagnosed glioma patients were studied. For each patient, two readers created four NAWM regions of interests: (1) a single plane in the centrum semiovale (CSOp), (2) 3 spheres in the centrum semiovale (CSOs), (3) a single plane in the slice of the tumor center (TUMp), and (4) 3 spheres in the slice of the tumor center (TUMs). Readers repeated NAWM segmentations 1 month later. Differences in nrCBV and nADC of the FLAIR hyperintense tumor, inter-/intra-reader variability, and time to segment NAWM were assessed. As a validation step, the diagnostic performance of each method for IDH-status prediction was evaluated. RESULTS Both readers obtained significantly different nrCBV (P < .001), nADC (P < .001), and time to segment NAWM (P < .001) between the four normalization methods. nrCBV and nADC were significantly different between CSO and TUM methods, but not between planar and spherical methods in the same NAWM region. Broadly, CSO methods were quicker than TUM methods, and spherical methods were quicker than planar methods. For all normalization techniques, inter-reader reproducibility and intra-reader repeatability were excellent (intraclass correlation coefficient > 0.9), and the IDH-status predictive performance remained similar. CONCLUSION The selected NAWM region significantly impacts nrCBV and nADC values. CSO methods, particularly CSOs, may be preferred because of time reduction, similar reader variability, and similar diagnostic performance compared to TUM methods.
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Affiliation(s)
- Nicholas S Cho
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Akifumi Hagiwara
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Francesco Sanvito
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Unit of Radiology, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, Pavia, Italy
| | - Benjamin M Ellingson
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
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15
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Wang W, Fan X, Yang J, Wang X, Gu Y, Chen M, Jiang Y, Liu L, Zhang M. Preliminary MRI Study of Extracellular Volume Fraction for Identification of Lymphovascular Space Invasion of Cervical Cancer. J Magn Reson Imaging 2023; 57:587-597. [PMID: 36094153 DOI: 10.1002/jmri.28423] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Revised: 08/17/2022] [Accepted: 08/18/2022] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Lymphovascular space invasion (LVSI) is a risk factor for poor prognosis of cervical cancer. Preoperative identification of LVSI is very difficult. PURPOSE To evaluate the potential of extracellular volume (ECV) fraction based on T1 mapping in preoperative identification of LVSI in cervical cancer compared with dynamic contrast-enhanced MRI (DCE-MRI). STUDY TYPE Retrospective. SUBJECTS A total of 79 patients (median age 54 years) with cervical cancer were classified into LVSI group (n = 29) and without LVSI group (n = 50) according to postoperative pathology. FIELD STRENGTH/SEQUENCE A 3-T, noncontrast and contrast-enhanced T1 mapping performed with volume interpolated breath hold examination (VIBE) sequence, DCE-MRI applied with 3D T1-weighted VIBE sequence. ASSESSMENT Regions of interest along the medial edge of the lesion were drawn on slices depicting the maximum cross-section of the tumor. The noncontrast and contrast-enhanced T1 value of the tumor and arteries in the same slice were measured, and ECV was calculated from T1 values. The parametric maps (Ktrans , kep , and ve ) derived from DCE-MRI standard Toft's model were evaluated. STATISTICAL TESTS ECV, Ktrans , kep , and ve between groups with and without LVSI were compared using Student's t-test. The receiver operating characteristic (ROC) curve and DeLong test were used to evaluate and compare the diagnostic performance of ECV, Ktrans , kep , and ve for differentiating LVSI. P < 0.05 was considered statistically significant. RESULTS The ECV and Ktrans of the LVSI group were significantly higher than that of non-LVSI group (52.86% vs. 36.77%, 0.239 vs. 0.176, respectively), and no significant differences in Kep or ve values were observed (P = 0.071 and P = 0.168, respectively). The ECV fraction showed significantly higher area under ROC curve than Ktrans for differentiating LVSI (0.874 vs. 0.655, respectively). DATA CONCLUSION ECV measurements based on T1 mapping might improve the discrimination between patients with and without LVSI in cervical cancer, showing better performance for this purpose than DCE-MRI. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Wei Wang
- Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China
| | - Xiaofei Fan
- Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China
| | - Jie Yang
- Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China
| | - Xuemei Wang
- Department of Pathology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China
| | - Yu Gu
- Department of Pathology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China
| | - Mingxin Chen
- Inpatient Service Center, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China
| | - Yueluan Jiang
- MR Scientific Marketing, Diagnostic Imaging, Siemens Healthineers Ltd., Beijing, China
| | - Lin Liu
- Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China
| | - Mengchao Zhang
- Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China
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16
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Bailo M, Pecco N, Callea M, Scifo P, Gagliardi F, Presotto L, Bettinardi V, Fallanca F, Mapelli P, Gianolli L, Doglioni C, Anzalone N, Picchio M, Mortini P, Falini A, Castellano A. Decoding the Heterogeneity of Malignant Gliomas by PET and MRI for Spatial Habitat Analysis of Hypoxia, Perfusion, and Diffusion Imaging: A Preliminary Study. Front Neurosci 2022; 16:885291. [PMID: 35911979 PMCID: PMC9326318 DOI: 10.3389/fnins.2022.885291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 06/14/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundTumor heterogeneity poses major clinical challenges in high-grade gliomas (HGGs). Quantitative radiomic analysis with spatial tumor habitat clustering represents an innovative, non-invasive approach to represent and quantify tumor microenvironment heterogeneity. To date, habitat imaging has been applied mainly on conventional magnetic resonance imaging (MRI), although virtually extendible to any imaging modality, including advanced MRI techniques such as perfusion and diffusion MRI as well as positron emission tomography (PET) imaging.ObjectivesThis study aims to evaluate an innovative PET and MRI approach for assessing hypoxia, perfusion, and tissue diffusion in HGGs and derive a combined map for clustering of intra-tumor heterogeneity.Materials and MethodsSeventeen patients harboring HGGs underwent a pre-operative acquisition of MR perfusion (PWI), Diffusion (dMRI) and 18F-labeled fluoroazomycinarabinoside (18F-FAZA) PET imaging to evaluate tumor vascularization, cellularity, and hypoxia, respectively. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and T1 post-contrast images, and voxel-wise clustering of each quantitative imaging map identified eight combined PET and physiologic MRI habitats. Habitats’ spatial distribution, quantitative features and histopathological characteristics were analyzed.ResultsA highly reproducible distribution pattern of the clusters was observed among different cases, particularly with respect to morphological landmarks as the necrotic core, contrast-enhancing vital tumor, and peritumoral infiltration and edema, providing valuable supplementary information to conventional imaging. A preliminary analysis, performed on stereotactic bioptic samples where exact intracranial coordinates were available, identified a reliable correlation between the expected microenvironment of the different spatial habitats and the actual histopathological features. A trend toward a higher representation of the most aggressive clusters in WHO (World Health Organization) grade IV compared to WHO III was observed.ConclusionPreliminary findings demonstrated high reproducibility of the PET and MRI hypoxia, perfusion, and tissue diffusion spatial habitat maps and correlation with disease-specific histopathological features.
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Affiliation(s)
- Michele Bailo
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Nicolò Pecco
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Paola Scifo
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Filippo Gagliardi
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Luca Presotto
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Federico Fallanca
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Paola Mapelli
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Luigi Gianolli
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Nicoletta Anzalone
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Maria Picchio
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Pietro Mortini
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Andrea Falini
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Antonella Castellano
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
- *Correspondence: Antonella Castellano,
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Li AY, Iv M. Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging. FRONTIERS IN RADIOLOGY 2022; 2:883293. [PMID: 37492665 PMCID: PMC10365131 DOI: 10.3389/fradi.2022.883293] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/06/2022] [Indexed: 07/27/2023]
Abstract
Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.
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Affiliation(s)
- Anna Y. Li
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
| | - Michael Iv
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
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Malik DG, Rath TJ, Urcuyo Acevedo JC, Canoll PD, Swanson KR, Boxerman JL, Quarles CC, Schmainda KM, Burns TC, Hu LS. Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions. FRONTIERS IN RADIOLOGY 2022; 2:809373. [PMID: 37492687 PMCID: PMC10365126 DOI: 10.3389/fradi.2022.809373] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 03/01/2022] [Indexed: 07/27/2023]
Abstract
In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.
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Affiliation(s)
- Dania G. Malik
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Tanya J. Rath
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Javier C. Urcuyo Acevedo
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Peter D. Canoll
- Departments of Pathology and Cell Biology, Columbia University, New York, NY, United States
| | - Kristin R. Swanson
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Jerrold L. Boxerman
- Department of Diagnostic Imaging, Brown University, Providence, RI, United States
| | - C. Chad Quarles
- Department of Neuroimaging Research & Barrow Neuroimaging Innovation Center, Barrow Neurologic Institute, Phoenix, AZ, United States
| | - Kathleen M. Schmainda
- Department of Biophysics & Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Terry C. Burns
- Departments of Neurologic Surgery and Neuroscience, Mayo Clinic, Rochester, MN, United States
| | - Leland S. Hu
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
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19
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Henriksen OM, del Mar Álvarez-Torres M, Figueiredo P, Hangel G, Keil VC, Nechifor RE, Riemer F, Schmainda KM, Warnert EAH, Wiegers EC, Booth TC. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques. Front Oncol 2022; 12:810263. [PMID: 35359414 PMCID: PMC8961422 DOI: 10.3389/fonc.2022.810263] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 01/05/2022] [Indexed: 01/16/2023] Open
Abstract
Objective Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics). Results High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies. Conclusion Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.
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Affiliation(s)
- Otto M. Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | | | - Patricia Figueiredo
- Department of Bioengineering and Institute for Systems and Robotics-Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Gilbert Hangel
- Department of Neurosurgery, Medical University, Vienna, Austria
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University, Vienna, Austria
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Ruben E. Nechifor
- International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Department of Clinical Psychology and Psychotherapy, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | | | - Evita C. Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Thomas C. Booth
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School of Biomedical Engineering and Imaging Sciences, St. Thomas’ Hospital, King’s College London, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
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20
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Cindil E, Sendur HN, Cerit MN, Erdogan N, Celebi F, Dag N, Celtikci E, Inan A, Oner Y, Tali T. Prediction of IDH Mutation Status in High-grade Gliomas Using DWI and High T1-weight DSC-MRI. Acad Radiol 2022; 29 Suppl 3:S52-S62. [PMID: 33685792 DOI: 10.1016/j.acra.2021.02.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 01/24/2021] [Accepted: 02/03/2021] [Indexed: 01/09/2023]
Abstract
RATIONALE AND OBJECTIVES We aimed to evaluate the diagnostic performance of diffusion-weighted imaging (DWI) and dynamic susceptibility contrast-enhanced (DSC) magnetic resonance imaging (MRI) parameters in the noninvasive prediction of the isocitrate dehydrogenase (IDH) mutation status in high-grade gliomas (HGGs). MATERIALS AND METHODS A total of 58 patients with histopathologically proved HGGs were included in this retrospective study. All patients underwent multiparametric MRI on 3-T, including DSC-MRI and DWI before surgery. The mean apparent diffusion coefficient (ADC), relative maximum cerebral blood volume (rCBV), and percentage signal recovery (PSR) of the tumor core were measured and compared depending on the IDH mutation status and tumor grade. The Mann-Whitney U test was used to detect statistically significant differences in parameters between IDH-mutant-type (IDH-m-type) and IDH-wild-type (IDH-w-type) HGGs. Receiver operating characteristic curve (ROC) analysis was performed to evaluate the diagnostic performance. RESULTS The rCBV was significantly higher, and the PSR value was significantly lower in IDH-w-type tumors than in the IDH-m group (p = 0.002 and <0.001, respectively).The ADC value in IDH-w-type tumors was significantly lower compared with the one in IDH-m types (p = 0.023), but remarkable overlaps were found between the groups. The PSR showed the best diagnostic performance with an AUC of 0.938 and with an accuracy rate of 0.87 at the optimal cutoff value of 86.85. The combination of the PSR and the rCBV for the identification of the IDH mutation status increased the discrimination ability at the AUC level of 0.955. In terms of each tumor grade, the PSR and rCBV showed significant differences between the IDH-m and IDH-w groups (p ≤0.001). CONCLUSION The rCBV and PSR from DSC-MRI may be feasible noninvasive imaging parameters for predicting the IDH mutation status in HGGs. The standardization of the imaging protocol is indispensable to the utility of DSC perfusion MRI in wider clinical usage.
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21
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Booth TC, Wiegers EC, Warnert EAH, Schmainda KM, Riemer F, Nechifor RE, Keil VC, Hangel G, Figueiredo P, Álvarez-Torres MDM, Henriksen OM. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics. Front Oncol 2022; 11:811425. [PMID: 35340697 PMCID: PMC8948428 DOI: 10.3389/fonc.2021.811425] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/28/2021] [Indexed: 01/16/2023] Open
Abstract
Objective To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging). Results The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application. Conclusion Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.
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Affiliation(s)
- Thomas C. Booth
- School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
| | - Evita C. Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Ruben E. Nechifor
- Department of Clinical Psychology and Psychotherapy International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, Netherlands
| | - Gilbert Hangel
- Department of Neurosurgery & High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Patrícia Figueiredo
- Department of Bioengineering and Institute for Systems and Robotics - Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | | | - Otto M. Henriksen
- Department of Clinical Physiology, Nuclear medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
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22
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Gonçalves FG, Viaene AN, Vossough A. Advanced Magnetic Resonance Imaging in Pediatric Glioblastomas. Front Neurol 2021; 12:733323. [PMID: 34858308 PMCID: PMC8631300 DOI: 10.3389/fneur.2021.733323] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 10/12/2021] [Indexed: 12/26/2022] Open
Abstract
The shortly upcoming 5th edition of the World Health Organization Classification of Tumors of the Central Nervous System is bringing extensive changes in the terminology of diffuse high-grade gliomas (DHGGs). Previously "glioblastoma," as a descriptive entity, could have been applied to classify some tumors from the family of pediatric or adult DHGGs. However, now the term "glioblastoma" has been divested and is no longer applied to tumors in the family of pediatric types of DHGGs. As an entity, glioblastoma remains, however, in the family of adult types of diffuse gliomas under the insignia of "glioblastoma, IDH-wildtype." Of note, glioblastomas still can be detected in children when glioblastoma, IDH-wildtype is found in this population, despite being much more common in adults. Despite the separation from the family of pediatric types of DHGGs, what was previously labeled as "pediatric glioblastomas" still remains with novel labels and as new entities. As a result of advances in molecular biology, most of the previously called "pediatric glioblastomas" are now classified in one of the four family members of pediatric types of DHGGs. In this review, the term glioblastoma is still apocryphally employed mainly due to its historical relevance and the paucity of recent literature dealing with the recently described new entities. Therefore, "glioblastoma" is used here as an umbrella term in the attempt to encompass multiple entities such as astrocytoma, IDH-mutant (grade 4); glioblastoma, IDH-wildtype; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and high grade infant-type hemispheric glioma. Glioblastomas are highly aggressive neoplasms. They may arise anywhere in the developing central nervous system, including the spinal cord. Signs and symptoms are non-specific, typically of short duration, and usually derived from increased intracranial pressure or seizure. Localized symptoms may also occur. The standard of care of "pediatric glioblastomas" is not well-established, typically composed of surgery with maximal safe tumor resection. Subsequent chemoradiation is recommended if the patient is older than 3 years. If younger than 3 years, surgery is followed by chemotherapy. In general, "pediatric glioblastomas" also have a poor prognosis despite surgery and adjuvant therapy. Magnetic resonance imaging (MRI) is the imaging modality of choice for the evaluation of glioblastomas. In addition to the typical conventional MRI features, i.e., highly heterogeneous invasive masses with indistinct borders, mass effect on surrounding structures, and a variable degree of enhancement, the lesions may show restricted diffusion in the solid components, hemorrhage, and increased perfusion, reflecting increased vascularity and angiogenesis. In addition, magnetic resonance spectroscopy has proven helpful in pre- and postsurgical evaluation. Lastly, we will refer to new MRI techniques, which have already been applied in evaluating adult glioblastomas, with promising results, yet not widely utilized in children.
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Affiliation(s)
- Fabrício Guimarães Gonçalves
- Division of Neuroradiology, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Angela N Viaene
- Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Arastoo Vossough
- Division of Neuroradiology, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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23
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Wu CH, Lirng JF, Wu HM, Ling YH, Wang YF, Fuh JL, Lin CJ, Ling K, Wang SJ, Chen SP. Blood-Brain Barrier Permeability in Patients With Reversible Cerebral Vasoconstriction Syndrome Assessed With Dynamic Contrast-Enhanced MRI. Neurology 2021; 97:e1847-e1859. [PMID: 34504032 DOI: 10.1212/wnl.0000000000012776] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 08/23/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Blood-brain barrier (BBB) disruption has been proposed to be important in the pathogenesis of reversible cerebral vasoconstriction syndrome (RCVS), but not all patients present an identifiable macroscopic BBB disruption; that is, visible contrast leakage on contrast-enhanced T2 fluid-attenuated inversion recovery imaging. This study aimed to evaluate microscopic BBB permeability and its dynamic change in patients with RCVS. METHODS This prospective cohort implemented 3T dynamic contrast-enhanced MRI. We measured microscopic BBB permeability by determining the whole-brain and white matter hyperintensity (WMH) Ktrans values and evaluated the correlation of whole-brain Ktrans permeability with clinical and vascular measures in transcranial color-coded sonography. RESULTS In total, 176 patients (363 scans) were analyzed and separated into acute (≦30 days) and remission (≧90 days) groups based on the onset-to-examination time. Whole-brain Ktrans values were similar between patients with and without macroscopic BBB disruption in either acute or remission stage. The whole-brain Ktrans was significantly decreased (p < 0.001) from acute to remission stages. The WMH Ktrans was significantly higher than mirror references and decreased from acute to remission stages (p < 0.001). Whole-brain Ktrans correlated with mean pulsatility index (r s = 0.5, p = 0.029), mean resistance index (r s = 0.662, p = 0.002), and distal-to-proximal ratio of resistance index (r s = 0.801, p < 0.001) of M1 segment of middle cerebral arteries at around 10-15 days after onset. The time-trend curve of whole-brain Ktrans depicted dynamic changes during disease course, similar to temporal trends of vasoconstrictions and WMH. DISCUSSION Patients with RCVS presented increased microscopic brain permeability during acute stage, even without discernible macroscopic BBB disruption. The dynamic changes in BBB permeability may be related to impaired cerebral microvascular compliance and WMH formation.
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Affiliation(s)
- Chia-Hung Wu
- From the Department of Radiology (C.-H.W., J.-F.L., H.-M.W., C.-J.L., K.L.), Department of Neurology, Neurological Institute (Y.-H.L., Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), and Division of Translational Research, Department of Medical Research (S.-P.C.), Taipei Veterans General Hospital; and Institute of Clinical Medicine (C.-H.W., S.-P.C.), School of Medicine (C.-H.W., J.-F.L., H.-M.W., Y.-H.L., Y.-F.W., J.-L.F., C.-J.L., K.L., S.-J.W., S.-P.C.), and Brain Research Center (Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jiing-Feng Lirng
- From the Department of Radiology (C.-H.W., J.-F.L., H.-M.W., C.-J.L., K.L.), Department of Neurology, Neurological Institute (Y.-H.L., Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), and Division of Translational Research, Department of Medical Research (S.-P.C.), Taipei Veterans General Hospital; and Institute of Clinical Medicine (C.-H.W., S.-P.C.), School of Medicine (C.-H.W., J.-F.L., H.-M.W., Y.-H.L., Y.-F.W., J.-L.F., C.-J.L., K.L., S.-J.W., S.-P.C.), and Brain Research Center (Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Hsiu-Mei Wu
- From the Department of Radiology (C.-H.W., J.-F.L., H.-M.W., C.-J.L., K.L.), Department of Neurology, Neurological Institute (Y.-H.L., Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), and Division of Translational Research, Department of Medical Research (S.-P.C.), Taipei Veterans General Hospital; and Institute of Clinical Medicine (C.-H.W., S.-P.C.), School of Medicine (C.-H.W., J.-F.L., H.-M.W., Y.-H.L., Y.-F.W., J.-L.F., C.-J.L., K.L., S.-J.W., S.-P.C.), and Brain Research Center (Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yu-Hsiang Ling
- From the Department of Radiology (C.-H.W., J.-F.L., H.-M.W., C.-J.L., K.L.), Department of Neurology, Neurological Institute (Y.-H.L., Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), and Division of Translational Research, Department of Medical Research (S.-P.C.), Taipei Veterans General Hospital; and Institute of Clinical Medicine (C.-H.W., S.-P.C.), School of Medicine (C.-H.W., J.-F.L., H.-M.W., Y.-H.L., Y.-F.W., J.-L.F., C.-J.L., K.L., S.-J.W., S.-P.C.), and Brain Research Center (Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yen-Feng Wang
- From the Department of Radiology (C.-H.W., J.-F.L., H.-M.W., C.-J.L., K.L.), Department of Neurology, Neurological Institute (Y.-H.L., Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), and Division of Translational Research, Department of Medical Research (S.-P.C.), Taipei Veterans General Hospital; and Institute of Clinical Medicine (C.-H.W., S.-P.C.), School of Medicine (C.-H.W., J.-F.L., H.-M.W., Y.-H.L., Y.-F.W., J.-L.F., C.-J.L., K.L., S.-J.W., S.-P.C.), and Brain Research Center (Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jong-Ling Fuh
- From the Department of Radiology (C.-H.W., J.-F.L., H.-M.W., C.-J.L., K.L.), Department of Neurology, Neurological Institute (Y.-H.L., Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), and Division of Translational Research, Department of Medical Research (S.-P.C.), Taipei Veterans General Hospital; and Institute of Clinical Medicine (C.-H.W., S.-P.C.), School of Medicine (C.-H.W., J.-F.L., H.-M.W., Y.-H.L., Y.-F.W., J.-L.F., C.-J.L., K.L., S.-J.W., S.-P.C.), and Brain Research Center (Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chung-Jung Lin
- From the Department of Radiology (C.-H.W., J.-F.L., H.-M.W., C.-J.L., K.L.), Department of Neurology, Neurological Institute (Y.-H.L., Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), and Division of Translational Research, Department of Medical Research (S.-P.C.), Taipei Veterans General Hospital; and Institute of Clinical Medicine (C.-H.W., S.-P.C.), School of Medicine (C.-H.W., J.-F.L., H.-M.W., Y.-H.L., Y.-F.W., J.-L.F., C.-J.L., K.L., S.-J.W., S.-P.C.), and Brain Research Center (Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Kan Ling
- From the Department of Radiology (C.-H.W., J.-F.L., H.-M.W., C.-J.L., K.L.), Department of Neurology, Neurological Institute (Y.-H.L., Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), and Division of Translational Research, Department of Medical Research (S.-P.C.), Taipei Veterans General Hospital; and Institute of Clinical Medicine (C.-H.W., S.-P.C.), School of Medicine (C.-H.W., J.-F.L., H.-M.W., Y.-H.L., Y.-F.W., J.-L.F., C.-J.L., K.L., S.-J.W., S.-P.C.), and Brain Research Center (Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shuu-Jiun Wang
- From the Department of Radiology (C.-H.W., J.-F.L., H.-M.W., C.-J.L., K.L.), Department of Neurology, Neurological Institute (Y.-H.L., Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), and Division of Translational Research, Department of Medical Research (S.-P.C.), Taipei Veterans General Hospital; and Institute of Clinical Medicine (C.-H.W., S.-P.C.), School of Medicine (C.-H.W., J.-F.L., H.-M.W., Y.-H.L., Y.-F.W., J.-L.F., C.-J.L., K.L., S.-J.W., S.-P.C.), and Brain Research Center (Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Pin Chen
- From the Department of Radiology (C.-H.W., J.-F.L., H.-M.W., C.-J.L., K.L.), Department of Neurology, Neurological Institute (Y.-H.L., Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), and Division of Translational Research, Department of Medical Research (S.-P.C.), Taipei Veterans General Hospital; and Institute of Clinical Medicine (C.-H.W., S.-P.C.), School of Medicine (C.-H.W., J.-F.L., H.-M.W., Y.-H.L., Y.-F.W., J.-L.F., C.-J.L., K.L., S.-J.W., S.-P.C.), and Brain Research Center (Y.-F.W., J.-L.F., S.-J.W., S.-P.C.), National Yang Ming Chiao Tung University, Taipei, Taiwan.
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24
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Panara V, Chiacchiaretta P, Rapino M, Maruotti V, Parenti M, Piccirilli E, Pizzi AD, Caulo M. Dynamic susceptibility MR perfusion imaging of the brain: not a question of contrast agent molarity. Neuroradiology 2021; 64:685-692. [PMID: 34557937 DOI: 10.1007/s00234-021-02807-7] [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: 06/10/2021] [Accepted: 09/10/2021] [Indexed: 11/29/2022]
Abstract
PURPOSE Dynamic susceptibility contrast (DSC) perfusion-weighted MR imaging (PWI) is increasingly used in clinical neuroimaging for a range of conditions. More highly concentrated GBCAs (e.g., gadobutrol) are often preferred for DSC imaging because it is thought that more Gd is present in the volume of interest during first pass for a given equivalent injection rate. However, faster injection of a less viscous GBCA (e.g., gadoteridol) might generate a more compact and narrower contrast bolus thus obviating any perceived benefit of higher Gd concentration. This preliminary study aimed to analyze and compare DSC examinations in the healthy brain hemisphere of patients with brain tumors using gadobutrol and gadoteridol administered at injection rates of 4 and 6 mL/s. METHODS Thirty-nine brain tumor patients studied with DSC-PWI were evaluated. A simplified gamma-variate model function was applied to calculate the mean peak, area under the curve (AUC), and full-width at half-maximum (FHWM) of concentration-time curves derived from ΔR2* signals at four different regions-of-interest (ROIs). Qualitative assessment of the derived CBV maps was also performed independently by 2 neuroradiologists. RESULTS No qualitative or quantitative differences between the two GBCAs were observed when administered at a flow rate of 4 mL/s. At a flow rate of 6 mL/s, gadoteridol showed lower FWHM values. CONCLUSION Gadobutrol and gadoteridol are equivalent for clinical assessment of qualitative CBV maps and quantitative perfusion parameters (FHWM) at a flow rate of 4 mL/s. At 6 mL/s, gadoteridol produces a narrower bolus shape and potentially improves quantitative assessment of perfusion parameters.
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Affiliation(s)
- Valentina Panara
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy. .,ITAB - Institute of Advanced Biomedical Technologies, University "G. D'Annunzio" of Chieti, Via Luigi Polacchi 11, 66100, Chieti, Italy.
| | - Piero Chiacchiaretta
- Department of Psychological, Health and Territory Sciences, University "G. D'Annunzio" of Chieti, Pescara, Italy.,Center for Advanced Studies and Technology (CAST), University "G. D'Annunzio" of Chieti, Pescara, Italy
| | - Matteo Rapino
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy.,Department of Neuroscience, Imaging and Clinical Science, University "G. d'Annunzio" of Chieti, Chieti, Italy
| | - Valerio Maruotti
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy.,Department of Neuroscience, Imaging and Clinical Science, University "G. d'Annunzio" of Chieti, Chieti, Italy
| | - Matteo Parenti
- ITAB - Institute of Advanced Biomedical Technologies, University "G. D'Annunzio" of Chieti, Via Luigi Polacchi 11, 66100, Chieti, Italy
| | - Eleonora Piccirilli
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy.,Department of Neuroscience, Imaging and Clinical Science, University "G. d'Annunzio" of Chieti, Chieti, Italy
| | - Andrea Delli Pizzi
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy.,ITAB - Institute of Advanced Biomedical Technologies, University "G. D'Annunzio" of Chieti, Via Luigi Polacchi 11, 66100, Chieti, Italy.,Department of Neuroscience, Imaging and Clinical Science, University "G. d'Annunzio" of Chieti, Chieti, Italy
| | - Massimo Caulo
- Department of Radiology, University "G. d'Annunzio" of Chieti, Chieti, Italy.,ITAB - Institute of Advanced Biomedical Technologies, University "G. D'Annunzio" of Chieti, Via Luigi Polacchi 11, 66100, Chieti, Italy.,Department of Neuroscience, Imaging and Clinical Science, University "G. d'Annunzio" of Chieti, Chieti, Italy
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25
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Yi Z, Xie M, Shi G, Cheng Z, Zeng H, Jiang N, Wu Z. Assessment of quantitative dynamic contrast-enhanced MRI in distinguishing different histologic grades of breast phyllode tumor. Eur Radiol 2021; 32:1601-1610. [PMID: 34491383 DOI: 10.1007/s00330-021-08232-x] [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: 06/23/2021] [Revised: 07/18/2021] [Accepted: 07/22/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVES To investigate whether quantitative DCE-MRI (qDCE-MRI) could help distinguish breast phyllodes tumor (PT) grades. MATERIALS AND METHODS This retrospective study included 67 breast PTs (26 benign lesions, 25 borderline lesions, and 16 malignant lesions) from April 2016 to July 2020. MRI was performed with a 1.5-T MR system. Perfusion parameters (Ktrans, kep, ve, iAUC60) derived from qDCE-MRI, tumor size, and the mean ADC value were correlated with histologic grades using Spearman's rank correlation coefficient. Ktrans, kep, ve, and iAUC60 of three histologic grades were also calculated and compared. RESULTS The Spearman correlation coefficient with histologic grade of the tumor size was 0.578 (p < 0.001); the ADC value was not correlated with histologic grades of breast PT (p = 0.059). The Ktrans, kep, ve, and iAUC60 of benign breast PTs were significantly lower than those of borderline breast PTs (p < 0.001) and lower than those of malignant breast PTs (p < 0.001). In comparison, the Ktrans, ve, and iAUC60 of borderline breast PTs were significantly lower than those of malignant breast PTs (p < 0.001, p < 0.001, p = 0.007, respectively). For ROC analysis, AUCs of Ktrans, ve, and iAUC60 were higher than tumor size and ADC value for differentiating three PT grades. CONCLUSION Quantitative and semi-quantitative perfusion parameters (Ktrans, ve, and iAUC60, especially Ktrans) derived from qDCE-MRI showed better diagnosis efficiency than tumor size and ADC for grading breast PTs. Therefore, qDCE-MRI may be helpful for preoperative differentiating breast PT grades. KEY POINTS • Quantitative dynamic contrast-enhanced MRI can be used as a complementary noninvasive method to improve the differential diagnosis of breast PT. • Ktrans, ve, and iAUC60 derived from qDCE-MRI showed better diagnosis efficiency than tumor size and ADC for grading breast PTs.
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Affiliation(s)
- Zhilong Yi
- Department of Nuclear Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, China.,Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, China
| | - Mingwei Xie
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, China
| | - Guangzi Shi
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, China
| | - Ziliang Cheng
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, China
| | - Hong Zeng
- Department of Pathology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, China
| | - Ningyi Jiang
- Department of Nuclear Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518107, China
| | - Zhuo Wu
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, China. .,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Medical Research Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, China.
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26
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Barajas RF, Politi LS, Anzalone N, Schöder H, Fox CP, Boxerman JL, Kaufmann TJ, Quarles CC, Ellingson BM, Auer D, Andronesi OC, Ferreri AJM, Mrugala MM, Grommes C, Neuwelt EA, Ambady P, Rubenstein JL, Illerhaus G, Nagane M, Batchelor TT, Hu LS. Consensus recommendations for MRI and PET imaging of primary central nervous system lymphoma: guideline statement from the International Primary CNS Lymphoma Collaborative Group (IPCG). Neuro Oncol 2021; 23:1056-1071. [PMID: 33560416 PMCID: PMC8248856 DOI: 10.1093/neuonc/noab020] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Advanced molecular and pathophysiologic characterization of primary central nervous system lymphoma (PCNSL) has revealed insights into promising targeted therapeutic approaches. Medical imaging plays a fundamental role in PCNSL diagnosis, staging, and response assessment. Institutional imaging variation and inconsistent clinical trial reporting diminishes the reliability and reproducibility of clinical response assessment. In this context, we aimed to: (1) critically review the use of advanced positron emission tomography (PET) and magnetic resonance imaging (MRI) in the setting of PCNSL; (2) provide results from an international survey of clinical sites describing the current practices for routine and advanced imaging, and (3) provide biologically based recommendations from the International PCNSL Collaborative Group (IPCG) on adaptation of standardized imaging practices. The IPCG provides PET and MRI consensus recommendations built upon previous recommendations for standardized brain tumor imaging protocols (BTIP) in primary and metastatic disease. A biologically integrated approach is provided to addresses the unique challenges associated with the imaging assessment of PCNSL. Detailed imaging parameters facilitate the adoption of these recommendations by researchers and clinicians. To enhance clinical feasibility, we have developed both “ideal” and “minimum standard” protocols at 3T and 1.5T MR systems that will facilitate widespread adoption.
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Affiliation(s)
- Ramon F Barajas
- Department of Radiology, Neuroradiology Section, Oregon Health & Science University, Portland Oregon, USA.,Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon, USA.,Knight Cancer Institute Translational Oncology Program, Oregon Health & Science University, Portland, Oregon, USA
| | - Letterio S Politi
- Humanitas University and Humanitas Research and Clinical Center - IRCCS, Milan, Italy.,Boston Children's Hospital, Boston, Massachusetts, USA
| | - Nicoletta Anzalone
- Neuroradiology Unit, IRCCS San Raffaele Hospital and Vita-Salute University, Milan, Italy
| | - Heiko Schöder
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Christopher P Fox
- Department of Clinical Haematology, Nottingham University Hospitals NHS Trust, School of Medicine, University of Nottingham, Nottingham, UK
| | - Jerrold L Boxerman
- Department of Diagnostic Imaging, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | | | - C Chad Quarles
- Department of Neuroimaging Research & Barrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Departments of Radiological Sciences and Psychiatry, David Geffen School of Medicine, University of California - Los Angeles, Los Angeles, California, USA.,Departments of Radiological Sciences, Psychiatry, and Biobehavioral Sciences, David Geffen School of Medicine, University of California - Los Angeles, Los Angeles, California, USA
| | - Dorothee Auer
- Versus Arthritis Pain Centre, University of Nottingham, Nottingham, UK.,NIHR Nottingham Biomedical Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK.,Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
| | - Ovidiu C Andronesi
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Andres J M Ferreri
- Lymphoma Unit, Department of Onco-Hematology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maciej M Mrugala
- Department of Medicine, Division of Hematology and Oncology, Mayo Clinic Cancer Center, Phoenix, Arizona, USA.,Department of Neurology, Mayo Clinic, Phoenix, Arizona, USA
| | - Christian Grommes
- Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, New York, USA.,Department of Neurology, Weill Cornell Medical School, New York, New York, USA
| | - Edward A Neuwelt
- Blood-Brain Barrier Program, Oregon Health & Science University, Portland, Oregon, USA.,Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA.,Department of Neurological Surgery, Oregon Health & Science University, Portland, Oregon, USA.,Portland Veterans Affairs Medical Center, Portland, Oregon, USA
| | - Prakash Ambady
- Blood-Brain Barrier Program, Oregon Health & Science University, Portland, Oregon, USA.,Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - James L Rubenstein
- Division of Hematology/Oncology, University of California, San Francisco, California, USA.,Department of Medicine, University of California, San Francisco, California, USA.,Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, California, USA
| | - Gerald Illerhaus
- Clinic of Hematology, Oncology and Palliative Care, Klinikum Stuttgart, Stuttgart, Germany
| | - Motoo Nagane
- Department of Neurosurgery, Kyorin University Faculty of Medicine, Tokyo, Japan
| | - Tracy T Batchelor
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Leland S Hu
- Department of Radiology, Neuroradiology Division, Mayo Clinic, Phoenix, Arizona, USA
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27
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Kamimura K, Nakajo M, Bohara M, Nagano D, Fukukura Y, Fujio S, Takajo T, Tabata K, Iwanaga T, Imai H, Nickel MD, Yoshiura T. Consistency of Pituitary Adenoma: Prediction by Pharmacokinetic Dynamic Contrast-Enhanced MRI and Comparison with Histologic Collagen Content. Cancers (Basel) 2021; 13:cancers13153914. [PMID: 34359814 PMCID: PMC8345382 DOI: 10.3390/cancers13153914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 07/29/2021] [Indexed: 11/17/2022] Open
Abstract
Simple Summary Transsphenoidal resection of hard pituitary adenomas have a particularly high risk of residual tumor and complications. Therefore, prediction of tumor consistency is valuable for planning pituitary adenoma surgery. We prospectively examined whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of pituitary adenoma in 49 participants. We found that the measure of volume of extravascular extracellular space per unit volume of tissue derived from DCE-MRI could predict the consistency of pituitary adenomas. Furthermore, the volume of extravascular extracellular space per unit volume of tissue was significantly positively correlated with histopathologic collagen content of the adenoma. Our results suggest that volume of extravascular extracellular space per unit volume of tissue derived from quantitative pharmacokinetic analysis of DCE-MRI has a predictive value for consistency of pituitary adenomas. Abstract Prediction of tumor consistency is valuable for planning transsphenoidal surgery for pituitary adenoma. A prospective study was conducted involving 49 participants with pituitary adenoma to determine whether quantitative pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for predicting consistency of adenomas. Pharmacokinetic parameters in the adenomas including volume of extravascular extracellular space (EES) per unit volume of tissue (ve), blood plasma volume per unit volume of tissue (vp), volume transfer constant between blood plasma and EES (Ktrans), and rate constant between EES and blood plasma (kep) were obtained. The pharmacokinetic parameters and the histologic percentage of collagen content (PCC) were compared between soft and hard adenomas using Mann–Whitney U test. Pearson’s correlation coefficient was used to correlate pharmacokinetic parameters with PCC. Hard adenomas showed significantly higher PCC (44.08 ± 15.14% vs. 6.62 ± 3.47%, p < 0.01), ve (0.332 ± 0.124% vs. 0.221 ± 0.104%, p < 0.01), and Ktrans (0.775 ± 0.401/min vs. 0.601 ± 0.612/min, p = 0.02) than soft adenomas. Moreover, a significant positive correlation was found between ve and PCC (r = 0.601, p < 0.01). The ve derived using DCE-MRI may have predictive value for consistency of pituitary adenoma.
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Affiliation(s)
- Kiyohisa Kamimura
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544, Japan; (M.N.); (M.B.); (D.N.); (Y.F.); (T.Y.)
- Correspondence: ; Tel.: +81-99-275-5417
| | - Masanori Nakajo
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544, Japan; (M.N.); (M.B.); (D.N.); (Y.F.); (T.Y.)
| | - Manisha Bohara
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544, Japan; (M.N.); (M.B.); (D.N.); (Y.F.); (T.Y.)
| | - Daigo Nagano
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544, Japan; (M.N.); (M.B.); (D.N.); (Y.F.); (T.Y.)
| | - Yoshihiko Fukukura
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544, Japan; (M.N.); (M.B.); (D.N.); (Y.F.); (T.Y.)
| | - Shingo Fujio
- Department of Neurosurgery, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544, Japan; (S.F.); (T.T.)
| | - Tomoko Takajo
- Department of Neurosurgery, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544, Japan; (S.F.); (T.T.)
| | - Kazuhiro Tabata
- Department of Pathology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544, Japan;
| | - Takashi Iwanaga
- Department of Radiological Technology, Kagoshima University Hospital, 8-35-1 Sakuragaoka, Kagoshima 890-8544, Japan;
| | - Hiroshi Imai
- MR Research & Collaboration, Siemens Healthcare K.K., 1-11-1 Osaki, Shinagawa, Tokyo 141-8644, Japan;
| | | | - Takashi Yoshiura
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544, Japan; (M.N.); (M.B.); (D.N.); (Y.F.); (T.Y.)
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28
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Azab MA, Ghozy S, Hassanein SF, Azzam AY. Specific Preoperative Dynamic Contrast-Enhanced MRI Semi-quantitative Markers Can Correlate With Vascularity in Specific Areas of Glioblastoma Tissue and Predict Recurrence. Cureus 2021; 13:e15528. [PMID: 34277164 PMCID: PMC8269995 DOI: 10.7759/cureus.15528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/08/2021] [Indexed: 11/25/2022] Open
Abstract
Background: Glioblastoma is one of the most aggressive tumours despite all advanced therapies. We aimed to investigate the correlation between qualitative markers of dynamic contrast-enhanced magnetic resonance imaging and vascularity in different tumour regions and elucidate their potential in predicting recurrence. Methods: Radiological markers of vascularity as wash-in rate, washout rate, and capillary time to peak in different single tumour regions were extracted for all glioblastoma patients before being surgically resected using preoperative dynamic contrast-enhanced MRI (DCE-MRI). Tissue samples were obtained from different intratumoral regions and peritumoral oedema and evaluated for the vascular endothelial growth factor (VEGF). Results: Two hundred sixty individuals were included in the final analysis, with 180 dead ones and 80 survivors. Radio- and chemo-therapy were received by all surviving patients and 77.8% (n= 140) of the dead ones. The mean time to peak, in seconds, was longest at the peritumoral oedema region (71.7±23.5), followed by the tumour's necrotic centre (50.0±28.5) and its periphery (2.9±1.8). The expression of VEGF at the peritumoral edema region was inversely correlated to the washout rate at the periphery (r= -0.66; P-value= 0.014) and positively correlated to peritumoral TTP (r= 0.94; P-value< 0.001). Conclusion: Using DCE-MRI, VEGF expression may be used as a non-invasive marker to estimate tumour grade for clinical diagnosis and treatment. Moreover, the risk of glioblastoma recurrence could be determined by evaluating the washout rate at the tumour's periphery. Further large-scale studies are needed to validate the results and to have concrete evidence.
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Affiliation(s)
- Mohammed A Azab
- Department of Biochemistry, Boise State University, Boise, USA.,Neurological Surgery, Cairo University Hospital, Cairo, EGY
| | - Sherief Ghozy
- Neurological Surgery, Faculty of Medicine, Mansoura University, Mansoura, EGY
| | | | - Ahmed Y Azzam
- Neurological Surgery, October 6 University, 6th of October City, EGY
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29
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Distinct Cerebrovascular Reactivity Patterns for Brain Radiation Necrosis. Cancers (Basel) 2021; 13:cancers13081840. [PMID: 33924308 PMCID: PMC8069508 DOI: 10.3390/cancers13081840] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 03/31/2021] [Accepted: 04/09/2021] [Indexed: 11/17/2022] Open
Abstract
Background: Current imaging-based discrimination between radiation necrosis versus recurrent glioblastoma contrast-enhancing lesions remains imprecise but is paramount for prognostic and therapeutic evaluation. We examined whether patients with radiation necrosis exhibit distinct patterns of blood oxygenation-level dependent fMRI cerebrovascular reactivity (BOLD-CVR) as the first step to better distinguishing patients with radiation necrosis from recurrent glioblastoma compared with patients with newly diagnosed glioblastoma before surgery and radiotherapy. Methods: Eight consecutive patients with primary and secondary brain tumors and a multidisciplinary clinical and radiological diagnosis of radiation necrosis, and fourteen patients with a first diagnosis of glioblastoma underwent BOLD-CVR mapping. For all these patients, the contrast-enhancing lesion was derived from high-resolution T1-weighted MRI and rendered the volume-of-interest (VOI). From this primary VOI, additional 3 mm concentric expanding VOIs up to 30 mm were created for a detailed perilesional BOLD-CVR tissue analysis between the two groups. Receiver operating characteristic curves assessed the discriminative properties of BOLD-CVR for both groups. Results: Mean intralesional BOLD-CVR values were markedly lower in radiation necrosis than in glioblastoma contrast-enhancing lesions (0.001 ± 0.06 vs. 0.057 ± 0.05; p = 0.04). Perilesionally, a characteristic BOLD-CVR pattern was observed for radiation necrosis and glioblastoma patients, with an improvement of BOLD-CVR values in the radiation necrosis group and persisting lower perilesional BOLD-CVR values in glioblastoma patients. The ROC analysis discriminated against both groups when these two parameters were analyzed together (area under the curve: 0.85, 95% CI: 0.65-1.00). Conclusions: In this preliminary analysis, distinctive intralesional and perilesional BOLD-cerebrovascular reactivity patterns are found for radiation necrosis.
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30
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Castellano A, Bailo M, Cicone F, Carideo L, Quartuccio N, Mortini P, Falini A, Cascini GL, Minniti G. Advanced Imaging Techniques for Radiotherapy Planning of Gliomas. Cancers (Basel) 2021; 13:cancers13051063. [PMID: 33802292 PMCID: PMC7959155 DOI: 10.3390/cancers13051063] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 02/24/2021] [Accepted: 02/26/2021] [Indexed: 02/07/2023] Open
Abstract
The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.
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Affiliation(s)
- Antonella Castellano
- Neuroradiology Unit, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (A.C.); (A.F.)
| | - Michele Bailo
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.B.); (P.M.)
| | - Francesco Cicone
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, and Nuclear Medicine Unit, University Hospital “Mater Domini”, 88100 Catanzaro, Italy;
- Correspondence: ; Tel.: +39-0-961-369-4155
| | - Luciano Carideo
- National Cancer Institute, G. Pascale Foundation, 80131 Naples, Italy;
| | - Natale Quartuccio
- A.R.N.A.S. Ospedale Civico Di Cristina Benfratelli, 90144 Palermo, Italy;
| | - Pietro Mortini
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.B.); (P.M.)
| | - Andrea Falini
- Neuroradiology Unit, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (A.C.); (A.F.)
| | - Giuseppe Lucio Cascini
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, and Nuclear Medicine Unit, University Hospital “Mater Domini”, 88100 Catanzaro, Italy;
| | - Giuseppe Minniti
- Radiation Oncology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Policlinico Le Scotte, 53100 Siena, Italy;
- IRCCS Neuromed, 86077 Pozzilli (IS), Italy
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Cao H, Erson-Omay EZ, Günel M, Moliterno J, Fulbright RK. A Quantitative Assessment of Pre-Operative MRI Reports in Glioma Patients: Report Metrics and IDH Prediction Ability. Front Oncol 2021; 10:600327. [PMID: 33585216 PMCID: PMC7879978 DOI: 10.3389/fonc.2020.600327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Accepted: 11/26/2020] [Indexed: 11/13/2022] Open
Abstract
Objectives To measure the metrics of glioma pre-operative MRI reports and build IDH prediction models. Methods Pre-operative MRI reports of 144 glioma patients in a single institution were collected retrospectively. Words were transformed to lowercase letters. White spaces, punctuations, and stop words were removed. Stemming was performed. A word cloud method applied to processed text matrix visualized language behavior. Spearman's rank correlation assessed the correlation between the subjective descriptions of the enhancement pattern. The T1-contrast images associated with enhancement descriptions were selected. The keywords associated with IDH status were evaluated by χ2 value ranking. Random forest, k-nearest neighbors and Support Vector Machine algorithms were used to train models based on report features and age. All statistical analysis used two-tailed test with significance at p <.05. Results Longer word counts occurred in reports of older patients, higher grade gliomas, and wild type IDH gliomas. We identified 30 glioma enhancement descriptions, eight of which were commonly used: peripheral, heterogeneous, irregular, nodular, thick, rim, large, and ring. Five of eight patterns were correlated. IDH mutant tumors were characterized by words related to normal, symmetric or negative findings. IDH wild type tumors were characterized words by related to pathological MR findings like enhancement, necrosis and FLAIR foci. An integrated KNN model based on report features and age demonstrated high-performance (AUC: 0.89, 95% CI: 0.88-0.90). Conclusion Report length depended on age, glioma grade, and IDH status. Description of glioma enhancement was varied. Report descriptions differed for IDH wild and mutant gliomas. Report features can be used to predict glioma IDH status.
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Affiliation(s)
- Hang Cao
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
| | - E Zeynep Erson-Omay
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, United States
| | - Murat Günel
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, United States
| | - Jennifer Moliterno
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, United States
| | - Robert K Fulbright
- Department of Radiology and Biomedical Imaging, MRRC, Yale School of Medicine, New Haven, CT, United States
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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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Riva M, Lopci E, Gay LG, Nibali MC, Rossi M, Sciortino T, Castellano A, Bello L. Advancing Imaging to Enhance Surgery: From Image to Information Guidance. Neurosurg Clin N Am 2021; 32:31-46. [PMID: 33223024 DOI: 10.1016/j.nec.2020.08.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Conventional magnetic resonance imaging (cMRI) has an established role as a crucial disease parameter in the multidisciplinary management of glioblastoma, guiding diagnosis, treatment planning, assessment, and follow-up. Yet, cMRI cannot provide adequate information regarding tissue heterogeneity and the infiltrative extent beyond the contrast enhancement. Advanced magnetic resonance imaging and PET and newer analytical methods are transforming images into data (radiomics) and providing noninvasive biomarkers of molecular features (radiogenomics), conveying enhanced information for improving decision making in surgery. This review analyzes the shift from image guidance to information guidance that is relevant for the surgical treatment of glioblastoma.
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Affiliation(s)
- Marco Riva
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Via Festa del Perdono 7, Milan 20122, Italy; IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy.
| | - Egesta Lopci
- Unit of Nuclear Medicine, Humanitas Clinical and Research Center - IRCCS, Via Manzoni 56, Rozzano, Milan 20089, Italy. https://twitter.com/LopciEgesta
| | - Lorenzo G Gay
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
| | - Marco Conti Nibali
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy. https://twitter.com/dr_mcn
| | - Marco Rossi
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
| | - Tommaso Sciortino
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
| | - Antonella Castellano
- Neuroradiology Unit and CERMAC, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Via Olgettina 60, Milan 20123, Italy. https://twitter.com/antocastella
| | - Lorenzo Bello
- IRCCS Istituto Ortopedico Galeazzi, U.O. Neurochirurgia Oncologica, Milan, Italy; Department of Oncology and Hemato-Oncology, Via Festa del Perdono 7, Milan 20122, Italy
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Li Z, Xian M, Guo J, Qu X, Wang C, Zhang L, Xian J. Dynamic Contrast-Enhanced MRI Can Quantitatively Discriminate the Original Site From Peripheral Portion of Sinonasal Inverted Papillomas. J Magn Reson Imaging 2020; 53:1522-1527. [PMID: 33368767 DOI: 10.1002/jmri.27474] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 12/01/2020] [Accepted: 12/01/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Identification of the original site of sinonasal inverted papillomas (SIPs) is difficult but essential for reducing the recurrence rate. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may provide information about tissue perfusion and permeability to solve this problem. PURPOSE To investigate the accuracy of DCE-MRI parameters in discriminating between regions of interest (ROIs) in the original site and peripheral portion. STUDY TYPE Retrospective. POPULATION Ninety consecutive patients with pathologically proven SIP. FIELD STRENGTH/SEQUENCE 3.0T/DCE-MRI using fast-spoiled gradient recalled (FSPGR) T1 -weighted images with fat saturation. ASSESSMENT ROIs were placed in the original site and the peripheral portion of SIP by two radiologists according to surgical records. Maximum slope of increase (MaxSlope), contrast-enhancement ratio (CER), bolus arrival time (BAT), initial area under the signal intensity-time curve (IAUGC), volume transfer constant (Ktrans ), volume of the extravascular extracellular space (ve ), and rate constant (Kep ) were calculated and repeated again with a month interval by a radiologist. STATISTICAL TESTS Univariate and multivariate analysis was used to determine the best diagnostic parameters, and their performances in discrimination were evaluated by receiver operating characteristic (ROC) curves. Reproducibility was estimated by the intraclass correlation coefficient (ICC). RESULTS MaxSlope, CER, IAUGC, Ktrans , and ve were significantly lower (P < 0.05) in the original site than the peripheral portion of SIPs. CER (odds ratio [OR] = 0.227, 95% confidence interval [95% CI] = 0.073-0.704) and ve (OR = 0.048, 95% CI = 0.004-0.527) were the best indicators for identifying the original ROIs. The combination of CER and ve had the best diagnostic performance in the discrimination between the ROIs (the area under the curve [AUC]: 0.937; 95% CI: 0.896-0.974). DATA CONCLUSION DCE-MRI derived parameter values differed between the original site and the peripheral portion of SIPs. The model combining CER and ve appears to be able to accurately distinguish the original from peripheral ROIs. LEVEL OF EVIDENCE 4 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
- Zheng Li
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Mu Xian
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jian Guo
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Xiaoxia Qu
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Chengshuo Wang
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Luo Zhang
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Junfang Xian
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
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Park JE, Kim HS, Lee J, Cheong EN, Shin I, Ahn SS, Shim WH. Deep-learned time-signal intensity pattern analysis using an autoencoder captures magnetic resonance perfusion heterogeneity for brain tumor differentiation. Sci Rep 2020; 10:21485. [PMID: 33293590 PMCID: PMC7723041 DOI: 10.1038/s41598-020-78485-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 11/11/2020] [Indexed: 01/10/2023] Open
Abstract
Current image processing methods for dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) do not capture complex dynamic information of time-signal intensity curves. We investigated whether an autoencoder-based pattern analysis of DSC MRI captured representative temporal features that improves tissue characterization and tumor diagnosis in a multicenter setting. The autoencoder was applied to the time-signal intensity curves to obtain representative temporal patterns, which were subsequently learned by a convolutional neural network. This network was trained with 216 preoperative DSC MRI acquisitions and validated using external data (n = 43) collected with different DSC acquisition protocols. The autoencoder applied to time-signal intensity curves and clustering obtained nine representative clusters of temporal patterns, which accurately identified tumor and non-tumoral tissues. The dominant clusters of temporal patterns distinguished primary central nervous system lymphoma (PCNSL) from glioblastoma (AUC 0.89) and metastasis from glioblastoma (AUC 0.95). The autoencoder captured DSC time-signal intensity patterns that improved identification of tumoral tissues and differentiation of tumor type and was generalizable across centers.
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Affiliation(s)
- Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, Korea.
| | - Junkyu Lee
- Department of Medical Science and Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, 43 Olympic-ro 88, Songpa-Gu, Seoul, Korea
| | - E-Nae Cheong
- Department of Medical Science and Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, 43 Olympic-ro 88, Songpa-Gu, Seoul, Korea
| | - Ilah Shin
- Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea
| | - Sung Soo Ahn
- Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea
| | - Woo Hyun Shim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, Korea.,Department of Medical Science and Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, 43 Olympic-ro 88, Songpa-Gu, Seoul, Korea
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Application of Distributed Parameter Model to Assessment of Glioma IDH Mutation Status by Dynamic Contrast-Enhanced Magnetic Resonance Imaging. CONTRAST MEDIA & MOLECULAR IMAGING 2020; 2020:8843084. [PMID: 33299387 PMCID: PMC7704178 DOI: 10.1155/2020/8843084] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 10/16/2020] [Accepted: 11/07/2020] [Indexed: 01/08/2023]
Abstract
Previous studies using contrast-enhanced imaging for glioma isocitrate dehydrogenase (IDH) mutation assessment showed promising yet inconsistent results, and this study attempts to explore this problem by using an advanced tracer kinetic model, the distributed parameter model (DP). Fifty-five patients with glioma examined using dynamic contrast-enhanced imaging sequence at a 3.0 T scanner were retrospectively reviewed. The imaging data were processed using DP, yielding the following parameters: blood flow F, permeability-surface area product PS, fractional volume of interstitial space Ve, fractional volume of intravascular space Vp, and extraction ratio E. The results were compared with the Tofts model. The Wilcoxon test and boxplot were utilized for assessment of differences of model parameters between IDH-mutant and IDH-wildtype gliomas. Spearman correlation r was employed to investigate the relationship between DP and Tofts parameters. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis and quantified using the area under the ROC curve (AUC). Results showed that IDH-mutant gliomas were significantly lower in F (P = 0.018), PS (P < 0.001), Vp (P < 0.001), E (P < 0.001), and Ve (P = 0.002) than IDH-wildtype gliomas. In differentiating IDH-mutant and IDH-wildtype gliomas, Vp had the best performance (AUC = 0.92), and the AUCs of PS and E were 0.82 and 0.80, respectively. In comparison, Tofts parameters were lower in Ktrans (P = 0.013) and Ve (P < 0.001) for IDH-mutant gliomas. No significant difference was observed in Kep (P = 0.525). The AUCs of Ktrans, Ve, and Kep were 0.69, 0.79, and 0.55, respectively. Tofts-derived Ve showed a strong correlation with DP-derived Ve (r > 0.9, P < 0.001). Ktrans showed a weak correlation with F (r < 0.3, P > 0.16) and a very weak correlation with PS (r < 0.06, P > 0.8), both of which were not statistically significant. The findings by DP revealed a tissue environment with lower vascularity, lower vessel permeability, and lower blood flow in IDH-mutant than in IDH-wildtype gliomas, being hostile to cellular differentiation of oncogenic effects in IDH-mutated gliomas, which might help to explain the better outcomes in IDH-mutated glioma patients than in glioma patients of IDH-wildtype. The advantage of DP over Tofts in glioma DCE data analysis was demonstrated in terms of clearer elucidation of tissue microenvironment and better performance in IDH mutation assessment.
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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.
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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.
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Choi KS, Choi SH, Jeong B. Prediction of IDH genotype in gliomas with dynamic susceptibility contrast perfusion MR imaging using an explainable recurrent neural network. Neuro Oncol 2020; 21:1197-1209. [PMID: 31127834 DOI: 10.1093/neuonc/noz095] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND The aim of this study was to predict isocitrate dehydrogenase (IDH) genotypes of gliomas using an interpretable deep learning application for dynamic susceptibility contrast (DSC) perfusion MRI. METHODS Four hundred sixty-three patients with gliomas who underwent preoperative MRI were enrolled in the study. All the patients had immunohistopathologic diagnoses of either IDH-wildtype or IDH-mutant gliomas. Tumor subregions were segmented using a convolutional neural network followed by manual correction. DSC perfusion MRI was performed to obtain T2* susceptibility signal intensity-time curves from each subregion of the tumors: enhancing tumor, non-enhancing tumor, peritumoral edema, and whole tumor. These, with arterial input functions, were fed into a neural network as multidimensional inputs. A convolutional long short-term memory model with an attention mechanism was developed to predict IDH genotypes. Receiver operating characteristics analysis was performed to evaluate the model. RESULTS The IDH genotype predictions had an accuracy, sensitivity, and specificity of 92.8%, 92.6%, and 93.1%, respectively, in the validation set (area under the curve [AUC], 0.98; 95% confidence interval [CI], 0.969-0.991) and 91.7%, 92.1%, and 91.5%, respectively, in the test set (AUC, 0.95; 95% CI, 0.898-0.982). In temporal feature analysis, T2* susceptibility signal intensity-time curves obtained from DSC perfusion MRI with attention weights demonstrated high attention on the combination of the end of the pre-contrast baseline, up/downslopes of signal drops, and/or post-bolus plateaus for the curves used to predict IDH genotype. CONCLUSIONS We developed an explainable recurrent neural network model based on DSC perfusion MRI to predict IDH genotypes in gliomas.
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Affiliation(s)
- Kyu Sung Choi
- Graduate School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea.,KAIST Institute for Health Science and Technology, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea.,KAIST Institute for Artificial Intelligence, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul, Republic of Korea
| | - Bumseok Jeong
- Graduate School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea.,KAIST Institute for Health Science and Technology, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea.,KAIST Institute for Artificial Intelligence, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea
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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: 4] [Impact Index Per Article: 1.0] [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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Lombardi G, Barresi V, Castellano A, Tabouret E, Pasqualetti F, Salvalaggio A, Cerretti G, Caccese M, Padovan M, Zagonel V, Ius T. Clinical Management of Diffuse Low-Grade Gliomas. Cancers (Basel) 2020; 12:E3008. [PMID: 33081358 PMCID: PMC7603014 DOI: 10.3390/cancers12103008] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 10/06/2020] [Accepted: 10/14/2020] [Indexed: 12/21/2022] Open
Abstract
Diffuse low-grade gliomas (LGG) represent a heterogeneous group of primary brain tumors arising from supporting glial cells and usually affecting young adults. Advances in the knowledge of molecular profile of these tumors, including mutations in the isocitrate dehydrogenase genes, or 1p/19q codeletion, and in neuroradiological techniques have contributed to the diagnosis, prognostic stratification, and follow-up of these tumors. Optimal post-operative management of LGG is still controversial, though radiation therapy and chemotherapy remain the optimal treatments after surgical resection in selected patients. In this review, we report the most important and recent research on clinical and molecular features, new neuroradiological techniques, the different therapeutic modalities, and new opportunities for personalized targeted therapy and supportive care.
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Affiliation(s)
- Giuseppe Lombardi
- Department of Oncology, Oncology 1, Veneto Institute of oncology-IRCCS, 35128 Padova, Italy; (G.C.); (M.C.); (M.P.); (V.Z.)
| | - Valeria Barresi
- Department of Diagnostics and Public Health, Section of Pathology, University of Verona, 37129 Verona, Italy;
| | - Antonella Castellano
- Neuroradiology Unit, IRCCS San Raffaele Scientific Institute and Vita-Salute San Raffaele University, 20132 Milan, Italy;
| | - Emeline Tabouret
- Team 8 GlioMe, CNRS, INP, Inst Neurophysiopathol, Aix-Marseille University, 13005 Marseille, France;
| | | | - Alessandro Salvalaggio
- Department of Neuroscience, University of Padova, 35128 Padova, Italy;
- Padova Neuroscience Center (PNC), University of Padova, 35128 Padova, Italy
| | - Giulia Cerretti
- Department of Oncology, Oncology 1, Veneto Institute of oncology-IRCCS, 35128 Padova, Italy; (G.C.); (M.C.); (M.P.); (V.Z.)
| | - Mario Caccese
- Department of Oncology, Oncology 1, Veneto Institute of oncology-IRCCS, 35128 Padova, Italy; (G.C.); (M.C.); (M.P.); (V.Z.)
| | - Marta Padovan
- Department of Oncology, Oncology 1, Veneto Institute of oncology-IRCCS, 35128 Padova, Italy; (G.C.); (M.C.); (M.P.); (V.Z.)
| | - Vittorina Zagonel
- Department of Oncology, Oncology 1, Veneto Institute of oncology-IRCCS, 35128 Padova, Italy; (G.C.); (M.C.); (M.P.); (V.Z.)
| | - Tamara Ius
- Neurosurgery Unit, Department of Neurosciences, Santa Maria della Misericordia University Hospital, 33100 Udine, Italy;
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Kang H, Chen P, Guo H, Zhang L, Tan Y, Xiao H, Yang A, Fang J, Zhang W. Vessel Size Imaging is Associated with IDH Mutation and Patient Survival in Diffuse Lower-Grade Glioma. Cancer Manag Res 2020; 12:9801-9811. [PMID: 33116839 PMCID: PMC7550213 DOI: 10.2147/cmar.s266533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Accepted: 09/07/2020] [Indexed: 11/23/2022] Open
Abstract
Background Patients with isocitrate dehydrogenase (IDH) mutant gliomas have better survival and appear to be more sensitive to chemotherapy than their IDH wild-type counterparts. We attempted to assess the correlations of vessel size imaging (VSI) values with IDH mutation status and patient survival in diffuse lower-grade glioma (LGG). Methods We enrolled 60 patients with diffuse LGGs, among which 43 had IDH-mutant tumors. All patients underwent VSI examination and VSI values for active tumors were calculated. Receiver operating characteristic (ROC) curves were established to evaluate the detection efficiency. Logistic regression was employed to determine the ability of variables to discriminate IDH mutational status. Kaplan–Meier survival analysis and Cox proportional hazards models were utilized to estimate the correlations of VSI values and other risk factors with patient survival. Results We observed that VSI values were lower in IDH-mutant LGGs than IDH wild-type LGGs. The VSImax and VSImean values had AUC values of 0.7305 and 0.7401, respectively, in distinguishing IDH-mutant LGGs from IDH wild-type LGGs. Logistic regression showed that VSImean values, age and tumor location were associated with IDH-mutant status, and the formula integrating the three factors had an AUC value of 0.7798 when distinguishing IDH-mutant LGGs from IDH wild-type LGGs. Moreover, LGG patients with high VSI values exhibited worse survival rates than those with low VSI values for both progression-free survival (PFS) and overall survival (OS). Multivariate Cox proportional hazards regression analysis suggested that IDH mutation status, VSImean values and multiple lesions or lobes were risk factors for PFS of LGG patients. Conclusion VSI value is associated with IDH genotype and maybe an independent predictor of the survival of patients with LGGs.
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Affiliation(s)
- Houyi Kang
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing 400042, People's Republic of China.,Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, People's Republic of China
| | - Peng Chen
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing 400042, People's Republic of China.,Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, People's Republic of China
| | - Hong Guo
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing 400042, People's Republic of China.,Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, People's Republic of China
| | - Letian Zhang
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing 400042, People's Republic of China.,Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, People's Republic of China
| | - Yong Tan
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing 400042, People's Republic of China.,Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, People's Republic of China
| | - Hualiang Xiao
- Department of Pathology, Daping Hospital, Army Medical University, Chongqing, People's Republic of China
| | - Ao Yang
- Department of Traffic Injury Research Office, Daping Hospital, Army Medical Center of PLA, Chongqing, People's Republic of China
| | - Jingqin Fang
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing 400042, People's Republic of China.,Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, People's Republic of China
| | - Weiguo Zhang
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing 400042, People's Republic of China.,Chongqing Clinical Research Center of Imaging and Nuclear Medicine, Chongqing, People's Republic of China
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42
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Hypoxia and Amino Acid Imaging of High-Grade Glioma: 18F-FAZA PET/CT and 11C-Methionine PET/MRI. Clin Nucl Med 2020; 45:e290-e293. [PMID: 32332306 DOI: 10.1097/rlu.0000000000003028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
In the present case, we report the first experience of a patient with high-grade glioma who underwent dual F-FAZA PET/CT imaging for intratumoral hypoxia assessment, before treatment, and for therapy monitoring in the suspicious of recurrence, as part of a clinical research protocol. In addition, despite the diagnosis of glioblastoma, the patient at 3 years from diagnosis was alive and underwent C-methionine simultaneous PET/MRI for disease monitoring after treatment, showing stability of disease. The multitracer capability of PET in assessing different and complementary metabolic features along with the use of a last-generation scanner as PET/MRI in brain oncology are here enlighten.
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43
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Hu Y, Zhang N, Yu MH, Zhou XJ, Ge M, Shen DD, Hua Y, Shi JL, Jia ZZ. Volume-based histogram analysis of dynamic contrast-enhanced MRI for estimation of gliomas IDH1 mutation status. Eur J Radiol 2020; 131:109247. [PMID: 32891974 DOI: 10.1016/j.ejrad.2020.109247] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 06/17/2020] [Accepted: 08/16/2020] [Indexed: 11/28/2022]
Abstract
PURPOSE The study aimed to investigate whether isocitrate dehydrogenase 1 (IDH1) mutation status in gliomas can be estimated by volume-based histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS Preoperative DCE-MRI data of 85 pathologically confirmed glioma patients including 33 carrying IDH1 mutant type (IDH1mut) and 52 with IDH1 wildtype (IDH1wt) were reviewed in a retrospective approach. Regions of interest (ROI) covering entire tumor volume were manually delineated using O.K. software (OmniKinetics, GE Healthcare, China). Histogram parameters of volume transfer constant (Ktrans) and volume of extravascular /extracellular space per unit volume of tissue (Ve) derived from DCE-MRI were obtained. Mann-Whitney U tests were made to compare the differences in histogram parameters of Ktrans and Ve between IDH1mut and IDH1wt in all gliomas and high-grade gliomas (HGGs, grade III and IV). Receiver operator characteristic (ROC) analysis were implemented to assess the diagnostic performance. RESULTS In histogram parameters of Ktrans and Ve, pairwise comparisons demonstrated statistically significant differences in mean, standard deviation (SD), 90th and 95th percentiles (90%, 95%) values between IDH1mut and IDH1wt in all cases of gliomas and HGGs (P < 0.05, respectively). The ROC analysis revealed that the cut-off values of 95% value of Ktrans (0.097 min-1) and mean value of Ve (0.099) provided the best combination of sensitivity and specificity to distinguish all gliomas with IDH1mut from IDH1wt. In HGGs, the cut-off values of mean value of Ktrans and Ve (0.044 min-1, 0.099) played similar role. CONCLUSION Volume-based histogram analysis of DCE-MRI performs well in identification of IDH1mut gliomas.
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Affiliation(s)
- Yue Hu
- Department of Medical Imaging, Affiliated Hospital of Nantong University, NO. 20 Xisi Road Nantong 226001, Jiangsu, People's Republic of China.
| | - Ni Zhang
- Department of Medical Imaging, Affiliated Hospital of Nantong University, NO. 20 Xisi Road Nantong 226001, Jiangsu, People's Republic of China.
| | - Min Hao Yu
- Department of Medical Imaging, Affiliated Hospital of Nantong University, NO. 20 Xisi Road Nantong 226001, Jiangsu, People's Republic of China.
| | - Xue Jun Zhou
- Department of Medical Imaging, Affiliated Hospital of Nantong University, NO. 20 Xisi Road Nantong 226001, Jiangsu, People's Republic of China.
| | - Min Ge
- Department of Medical Imaging, Affiliated Hospital of Nantong University, NO. 20 Xisi Road Nantong 226001, Jiangsu, People's Republic of China.
| | - Dan Dan Shen
- Department of Medical Imaging, Affiliated Hospital of Nantong University, NO. 20 Xisi Road Nantong 226001, Jiangsu, People's Republic of China.
| | - Ye Hua
- Department of Medical Imaging, Affiliated Hospital of Nantong University, NO. 20 Xisi Road Nantong 226001, Jiangsu, People's Republic of China.
| | - Jin Long Shi
- Department of Neurosurgery, Affiliated Hospital of Nantong University, NO. 20 Xisi Road, Nantong 226001, Jiangsu, People's Republic of China.
| | - Zhong Zheng Jia
- Department of Medical Imaging, Affiliated Hospital of Nantong University, NO. 20 Xisi Road Nantong 226001, Jiangsu, People's Republic of China.
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Campanella R, Guarnaccia L, Caroli M, Zarino B, Carrabba G, La Verde N, Gaudino C, Rampini A, Luzzi S, Riboni L, Locatelli M, Navone SE, Marfia G. Personalized and translational approach for malignant brain tumors in the era of precision medicine: the strategic contribution of an experienced neurosurgery laboratory in a modern neurosurgery and neuro-oncology department. J Neurol Sci 2020; 417:117083. [PMID: 32784071 DOI: 10.1016/j.jns.2020.117083] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 07/16/2020] [Accepted: 08/04/2020] [Indexed: 12/20/2022]
Abstract
Personalized medicine (PM) aims to optimize patient management, taking into account the individual traits of each patient. The main purpose of PM is to obtain the best response, improving health care and lowering costs. Extending traditional approaches, PM introduces novel patient-specific paradigms from diagnosis to treatment, with greater precision. In neuro-oncology, the concept of PM is well established. Indeed, every neurosurgical intervention for brain tumors has always been highly personalized. In recent years, PM has been introduced in neuro-oncology also to design and prescribe specific therapies for the patient and the patient's tumor. The huge advances in basic and translational research in the fields of genetics, molecular and cellular biology, transcriptomics, proteomics, and metabolomics have led to the introduction of PM into clinical practice. The identification of a patient's individual variation map may allow to design selected therapeutic protocols that ensure successful outcomes and minimize harmful side effects. Thus, clinicians can switch from the "one-size-fits-all" approach to PM, ensuring better patient care and high safety margin. Here, we review emerging trends and the current literature about the development of PM in neuro-oncology, considering the positive impact of innovative advanced researches conducted by a neurosurgical laboratory.
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Affiliation(s)
- Rolando Campanella
- Laboratory of Experimental Neurosurgery and Cell Therapy, Neurosurgery Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Laura Guarnaccia
- Laboratory of Experimental Neurosurgery and Cell Therapy, Neurosurgery Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
| | - Manuela Caroli
- Laboratory of Experimental Neurosurgery and Cell Therapy, Neurosurgery Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Barbara Zarino
- Laboratory of Experimental Neurosurgery and Cell Therapy, Neurosurgery Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Giorgio Carrabba
- Laboratory of Experimental Neurosurgery and Cell Therapy, Neurosurgery Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | | | - Chiara Gaudino
- Department of Neuroradiology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Angela Rampini
- Neurosurgery Unit, Department of Clinical-Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy
| | - Sabino Luzzi
- Neurosurgery Unit, Department of Clinical-Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy; Neurosurgery Unit, Department of Surgical Sciences, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Laura Riboni
- Department of Medical Biotechnology and Translational Medicine, LITA-Segrate, University of Milan, Milan, Italy
| | - Marco Locatelli
- Laboratory of Experimental Neurosurgery and Cell Therapy, Neurosurgery Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Aldo Ravelli" Research Center, Milan, Italy; Department of Medical-Surgical Physiopathology and Transplantation, University of Milan, Milan, Italy
| | - Stefania Elena Navone
- Laboratory of Experimental Neurosurgery and Cell Therapy, Neurosurgery Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Aldo Ravelli" Research Center, Milan, Italy.
| | - Giovanni Marfia
- Laboratory of Experimental Neurosurgery and Cell Therapy, Neurosurgery Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy; Aldo Ravelli" Research Center, Milan, Italy; Clinical Pathology Unit, Istituto di Medicina Aerospaziale "A. Moosso", Aeronautica Militare, Milan, Italy
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45
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Sudre CH, Panovska-Griffiths J, Sanverdi E, Brandner S, Katsaros VK, Stranjalis G, Pizzini FB, Ghimenton C, Surlan-Popovic K, Avsenik J, Spampinato MV, Nigro M, Chatterjee AR, Attye A, Grand S, Krainik A, Anzalone N, Conte GM, Romeo V, Ugga L, Elefante A, Ciceri EF, Guadagno E, Kapsalaki E, Roettger D, Gonzalez J, Boutelier T, Cardoso MJ, Bisdas S. Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status. BMC Med Inform Decis Mak 2020; 20:149. [PMID: 32631306 PMCID: PMC7336404 DOI: 10.1186/s12911-020-01163-5] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 06/24/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Combining MRI techniques with machine learning methodology is rapidly gaining attention as a promising method for staging of brain gliomas. This study assesses the diagnostic value of such a framework applied to dynamic susceptibility contrast (DSC)-MRI in classifying treatment-naïve gliomas from a multi-center patients into WHO grades II-IV and across their isocitrate dehydrogenase (IDH) mutation status. METHODS Three hundred thirty-three patients from 6 tertiary centres, diagnosed histologically and molecularly with primary gliomas (IDH-mutant = 151 or IDH-wildtype = 182) were retrospectively identified. Raw DSC-MRI data was post-processed for normalised leakage-corrected relative cerebral blood volume (rCBV) maps. Shape, intensity distribution (histogram) and rotational invariant Haralick texture features over the tumour mask were extracted. Differences in extracted features across glioma grades and mutation status were tested using the Wilcoxon two-sample test. A random-forest algorithm was employed (2-fold cross-validation, 250 repeats) to predict grades or mutation status using the extracted features. RESULTS Shape, distribution and texture features showed significant differences across mutation status. WHO grade II-III differentiation was mostly driven by shape features while texture and intensity feature were more relevant for the III-IV separation. Increased number of features became significant when differentiating grades further apart from one another. Gliomas were correctly stratified by mutation status in 71% and by grade in 53% of the cases (87% of the gliomas grades predicted with distance less than 1). CONCLUSIONS Despite large heterogeneity in the multi-center dataset, machine learning assisted DSC-MRI radiomics hold potential to address the inherent variability and presents a promising approach for non-invasive glioma molecular subtyping and grading.
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Affiliation(s)
- Carole H Sudre
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College, London, UK
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Jasmina Panovska-Griffiths
- Department of Applied Health Research, Institute of Epidemiology & Health Care, University College London, London, UK.
- Institute for Global Health, University College London, London, UK.
- The Queen's College, Oxford University, Oxford, UK.
| | - Eser Sanverdi
- Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London NHS Foundation Trust, London, UK
| | - Sebastian Brandner
- Division of Neuropathology, UCL Queen Square Institute of Neurology, London, UK
| | - Vasileios K Katsaros
- Department of Advanced Imaging Modalities, MRI Unit, General Anti-Cancer and Oncological Hospital of Athens "St. Savvas", Athens, Greece
- Department of Neurosurgery, General Hospital Evangelismos, Medical School, University of Athens, Athens, Greece
| | - George Stranjalis
- Department of Neurosurgery, General Hospital Evangelismos, Medical School, University of Athens, Athens, Greece
| | - Francesca B Pizzini
- Neuroradiology, Department of Diagnostics and Pathology, Verona University Hospital, Verona, Italy
| | - Claudio Ghimenton
- Neuropathology, Department of Diagnostics and Pathology, Verona University Hospital, Verona, Italy
| | - Katarina Surlan-Popovic
- Department of Neuroradiology, University Medical Centre, Ljubljana, Slovenia
- Department of Radiology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Jernej Avsenik
- Department of Neuroradiology, University Medical Centre, Ljubljana, Slovenia
- Department of Radiology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Maria Vittoria Spampinato
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
| | - Mario Nigro
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
| | - Arindam R Chatterjee
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
| | - Arnaud Attye
- Grenoble Institute of Neurosciences, INSERM, University Grenoble Alpes, Grenoble, France
| | - Sylvie Grand
- Grenoble Institute of Neurosciences, INSERM, University Grenoble Alpes, Grenoble, France
| | - Alexandre Krainik
- Grenoble Institute of Neurosciences, INSERM, University Grenoble Alpes, Grenoble, France
| | - Nicoletta Anzalone
- Department of Neuroradiology, San Raffaele Hospital, Vita-Salute San Raffaele University, Milan, Italy
| | - Gian Marco Conte
- Department of Neuroradiology, San Raffaele Hospital, Vita-Salute San Raffaele University, Milan, Italy
| | - Valeria Romeo
- Department of Advanced Biomedical Sciences, Diagnostic Imaging Section, University of Naples Federico II, Naples, Italy
| | - Lorenzo Ugga
- Department of Advanced Biomedical Sciences, Diagnostic Imaging Section, University of Naples Federico II, Naples, Italy
| | - Andrea Elefante
- Department of Advanced Biomedical Sciences, Diagnostic Imaging Section, University of Naples Federico II, Naples, Italy
| | - Elisa Francesca Ciceri
- Neuropathology, Department of Diagnostics and Pathology, Verona University Hospital, Verona, Italy
- Department of Advanced Biomedical Sciences, Diagnostic Imaging Section, University of Naples Federico II, Naples, Italy
| | - Elia Guadagno
- Department of Advanced Biomedical Sciences, Pathology Section, University of Naples Federico II, Naples, Italy
| | - Eftychia Kapsalaki
- Department of Radiology, School of Health Sciences, Faculty of Medicine, University of Thessaly, Larisa, Greece
| | | | | | | | - M Jorge Cardoso
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College, London, UK
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Sotirios Bisdas
- Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, University College London NHS Foundation Trust, London, UK
- Department of Brain Repair and Rehabilitation, Queen Square Institute of Neurology, UCL, London, UK
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Jing H, Yan X, Yang G, Qin D, Zhang H, Wirginia J. Medical Monitoring Data of Dynamic Contrast Enhanced Intelligent Information Image with MR in Postoperative Infection of Intracranial Gliomas (Preprint). JMIR Med Inform 2020. [DOI: 10.2196/21407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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47
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Rudà R, Angileri FF, Ius T, Silvani A, Sarubbo S, Solari A, Castellano A, Falini A, Pollo B, Del Basso De Caro M, Papagno C, Minniti G, De Paula U, Navarria P, Nicolato A, Salmaggi A, Pace A, Fabi A, Caffo M, Lombardi G, Carapella CM, Spena G, Iacoangeli M, Fontanella M, Germanò AF, Olivi A, Bello L, Esposito V, Skrap M, Soffietti R. Italian consensus and recommendations on diagnosis and treatment of low-grade gliomas. An intersociety (SINch/AINO/SIN) document. J Neurosurg Sci 2020; 64:313-334. [PMID: 32347684 DOI: 10.23736/s0390-5616.20.04982-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
In 2018, the SINch (Italian Society of Neurosurgery) Neuro-Oncology Section, AINO (Italian Association of Neuro-Oncology) and SIN (Italian Association of Neurology) Neuro-Oncology Section formed a collaborative Task Force to look at the diagnosis and treatment of low-grade gliomas (LGGs). The Task Force included neurologists, neurosurgeons, neuro-oncologists, pathologists, radiologists, radiation oncologists, medical oncologists, a neuropsychologist and a methodologist. For operational purposes, the Task Force was divided into five Working Groups: diagnosis, surgical treatment, adjuvant treatments, supportive therapies, and follow-up. The resulting guidance document is based on the available evidence and provides recommendations on diagnosis and treatment of LGG patients, considering all aspects of patient care along their disease trajectory.
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Affiliation(s)
- Roberta Rudà
- Department of Neuro-Oncology, Città della Salute e della Scienza, University of Turin, Turin, Italy
| | - Filippo F Angileri
- Section of Neurosurgery, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy -
| | - Tamara Ius
- Neurosurgery Unit, Department of Neurosciences, Santa Maria della Misericordia University Hospital, Udine, Italy
| | - Antonio Silvani
- Department of Neuro-Oncology, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Silvio Sarubbo
- Department of Neurosurgery, Structural and Functional Connectivity Lab Project, "S. Chiara" Hospital, Trento, Italy
| | - Alessandra Solari
- Unit of Neuroepidemiology, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Antonella Castellano
- Neuroradiology Unit, IRCCS San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Andrea Falini
- Neuroradiology Unit, IRCCS San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Bianca Pollo
- Section of Oncologic Neuropathology, Division of Neurology V - Neuropathology, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | | | - Costanza Papagno
- Center of Neurocognitive Rehabilitation (CeRiN), Interdepartmental Center of Mind/Brain, University of Trento, Trento, Italy.,Department of Psychology, University of Milan-Bicocca, Milan, Italy
| | - Giuseppe Minniti
- Radiation Oncology Unit, Department of Medicine, Surgery and Neurosciences, Policlinico Le Scotte, University of Siena, Siena, Italy
| | - Ugo De Paula
- Unit of Radiotherapy, San Giovanni-Addolorata Hospital, Rome, Italy
| | - Pierina Navarria
- Department of Radiotherapy and Radiosurgery, Humanitas Cancer Center and Research Hospital, Rozzano, Milan, Italy
| | - Antonio Nicolato
- Unit of Stereotaxic Neurosurgery, Department of Neurosciences, Hospital Trust of Verona, Verona, Italy
| | - Andrea Salmaggi
- Neurology Unit, Department of Neurosciences, A. Manzoni Hospital, Lecco, Italy
| | - Andrea Pace
- IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Alessandra Fabi
- Division of Medical Oncology, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Maria Caffo
- Section of Neurosurgery, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Giuseppe Lombardi
- Unit of Oncology 1, Department of Oncology, Veneto Institute of Oncology-IRCCS, Padua, Italy
| | | | - Giannantonio Spena
- Neurosurgery Unit, Department of Neurosciences, A. Manzoni Hospital, Lecco, Italy
| | - Maurizio Iacoangeli
- Department of Neurosurgery, Marche Polytechnic University, Umberto I General University Hospital, Ancona, Italy
| | - Marco Fontanella
- Division of Neurosurgery, Department of Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Antonino F Germanò
- Section of Neurosurgery, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Alessandro Olivi
- Neurosurgery Unit, Department of Neurosciences, Università Cattolica del Sacro Cuore, Fondazione Policlinico "A. Gemelli", Rome, Italy
| | - Lorenzo Bello
- Unit of Oncologic Neurosurgery, Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Vincenzo Esposito
- Sapienza University, Rome, Italy.,Giampaolo Cantore Department of Neurosurgery, IRCCS Neuromed, Pozzilli, Isernia, Italy
| | - Miran Skrap
- Neurosurgery Unit, Department of Neurosciences, Santa Maria della Misericordia University Hospital, Udine, Italy
| | - Riccardo Soffietti
- Department of Neuro-Oncology, Città della Salute e della Scienza, University of Turin, Turin, Italy
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Bulakbaşı N, Paksoy Y. Correction to: Advanced imaging in adult diffusely infiltrating low-grade gliomas. Insights Imaging 2020; 11:57. [PMID: 32323033 PMCID: PMC7176752 DOI: 10.1186/s13244-020-00862-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
The original article [1] contains errors in Table 1 in rows ktrans and Ve; the correct version of Table 1 can be viewed in this Correction article.
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Affiliation(s)
- Nail Bulakbaşı
- Medical Faculty, University of Kyrenia, Sehit Yahya Bakır Street, Karakum, Mersin-10, Kyrenia, Turkish Republic of Northern Cyprus, Turkey.
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Muscas G, van Niftrik CHB, Sebök M, Seystahl K, Piccirelli M, Stippich C, Weller M, Regli L, Fierstra J. Hemodynamic investigation of peritumoral impaired blood oxygenation-level dependent cerebrovascular reactivity in patients with diffuse glioma. Magn Reson Imaging 2020; 70:50-56. [PMID: 32302735 DOI: 10.1016/j.mri.2020.03.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Revised: 03/27/2020] [Accepted: 03/31/2020] [Indexed: 12/26/2022]
Abstract
INTRODUCTION The presence of peritumorally impaired blood oxygenation-level dependent cerebrovascular reactivity (BOLD-CVR) has been unequivocally demonstrated in patients with diffuse glioma, and may have value to better identify tumor infiltration zone. Since BOLD-CVR does not measure hemodynamic changes directly, we performed additional MR perfusion studies to better characterize the peritumoral hemodynamic environment. METHODS Seventeen patients with WHO grade III and IV diffuse glioma underwent high resolution advanced hemodynamic MR imaging including BOLD-CVR and MR perfusion. The obtained multiparametric hemodynamic factors (i.e., regional cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), mean transit time (MTT), time-to-peak (TTP) and BOLD-CVR, were analyzed within 10 concentric expanding 3 mm volumes of interest (VOIs) up to 30 mm from the tumor tissue mask. RESULTS BOLD-CVR impairment was found within the tumor tissue mask and the peritumoral VOIs up to 21 mm as compared to the contralateral flipped CVR analysis (p<0.05). In the affected hemisphere, we observed positive spatial correlations including all VOIs between BOLD-CVR and rCBV values (r=0.27; p<0.001), rCBF (r=0.42; p<0.001) and a negative correlation between BOLD-CVR and TTP (r=-0.47; p<0.001). CONCLUSIONS Peritumorally impaired BOLD-CVR is associated with concomitant hemodynamic alterations with severity correlating to tumor volume. The distribution of these multiparametric hemodynamic MRI patterns may be considered for future studies characterizing the hemodynamic peritumoral environment, thereby better identifying the extent of tumor infiltration.
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Affiliation(s)
- Giovanni Muscas
- Department of Neurosurgery, University Hospital of Zurich and University of Zurich, Zurich, Switzerland; Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland; Department of Neurosurgery, Careggi University Hospital, Florence, Italy
| | - Christiaan Hendrik Bas van Niftrik
- Department of Neurosurgery, University Hospital of Zurich and University of Zurich, Zurich, Switzerland; Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland
| | - Martina Sebök
- Department of Neurosurgery, University Hospital of Zurich and University of Zurich, Zurich, Switzerland; Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland
| | - Katharina Seystahl
- Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland; Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Marco Piccirelli
- Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland; Department of Neuroradiology, University Hospital of Zurich and University of Zurich, Zurich, Switzerland
| | - Christoph Stippich
- Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland; Department of Neuroradiology, University Hospital of Zurich and University of Zurich, Zurich, Switzerland
| | - Michael Weller
- Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland; Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, University Hospital of Zurich and University of Zurich, Zurich, Switzerland; Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital of Zurich and University of Zurich, Zurich, Switzerland; Clinical Neuroscience Center, University of Zurich, Zurich, Switzerland.
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Song Q, Zhang C, Chen X, Cheng Y. Comparing amide proton transfer imaging with dynamic susceptibility contrast-enhanced perfusion in predicting histological grades of gliomas: a meta-analysis. Acta Radiol 2020; 61:549-557. [PMID: 31495179 DOI: 10.1177/0284185119871667] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background As a subtype of chemical exchange saturation transfer imaging without contrast agent administration, amide proton transfer (APT) imaging has demonstrated the potential for differentiating the histologic grades of gliomas. Dynamic susceptibility contrast-enhanced perfusion, a perfusion-weighted imaging technique, is a well-established technique in grading gliomas. Purpose To compare the ability of amide proton transfer and dynamic susceptibility contrast-enhanced imaging for predicting the grades of gliomas. Material and Methods A comprehensive literature search was performed independently by two observers to identify articles about the diagnostic performance of amide proton transfer and dynamic susceptibility contrast-enhanced perfusion in predicting the grade of gliomas. Summary estimates of diagnostic accuracy were obtained by using a random-effects model. Results Of 179 studies identified, 23 studies were included the analysis. Eight studies evaluated amide proton transfer and 16 studies evaluated dynamic susceptibility contrast-enhanced perfusion with the parameter rCBV. The pooled sensitivities and specificities of each study’s best performing parameter were 88% (95% confidence interval [CI] 74–95) and 89% (95% CI 78–95) for amide proton transfer, and 95% (95% CI 87–98), 88% (95% CI 81–93) for perfusion-weighted imaging–dynamic susceptibility contrast-enhanced perfusion, respectively. The pooled sensitivities and specificities for grading gliomas using the two most commonly evaluated parameters, were 92% (95% CI 80–97) and 90% (95% CI 75–96) for APTmax, and 97% (95% CI 91–99) and 87% (95% CI 80–92) for rCBVmax, respectively. Conclusion Considering the similar performance of APT and dynamic susceptibility contrast-enhanced (DSC) in predicting glioma grade, the former method appears preferable since it needs no contrast agent.
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Affiliation(s)
- Qingxu Song
- Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, PR China
| | - Chencheng Zhang
- Department of Thoracic Surgery, Qilu Hospital of Shandong University, Jinan, PR China
| | - Xin Chen
- Department of MR, Shandong Medical Imaging Research Institute, Shandong University, Jinan, PR China
| | - Yufeng Cheng
- Department of Radiation Oncology, Qilu Hospital of Shandong University, Jinan, PR China
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