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Valenzuela-Fuenzalida JJ, Moyano-Valarezo L, Silva-Bravo V, Milos-Brandenberg D, Orellana-Donoso M, Nova-Baeza P, Suazo-Santibáñez A, Rodríguez-Luengo M, Oyanedel-Amaro G, Sanchis-Gimeno J, Gutiérrez Espinoza H. Association between the Anatomical Location of Glioblastoma and Its Evaluation with Clinical Considerations: A Systematic Review and Meta-Analysis. J Clin Med 2024; 13:3460. [PMID: 38929990 PMCID: PMC11204640 DOI: 10.3390/jcm13123460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 06/04/2024] [Accepted: 06/07/2024] [Indexed: 06/28/2024] Open
Abstract
Background: Glioblastoma is a primary malignant brain tumor; it is aggressive with a high degree of malignancy and unfavorable prognosis and is the most common type of malignant brain tumor. Glioblastomas can be located in the brain, cerebellum, brainstem, and spinal cord, originating from glial cells, particularly astrocytes. Methods: The databases MEDLINE, Scopus, Web of Science, Google Scholar, and CINAHL were researched up to January 2024. Two authors independently performed the search, study selection, and data extraction. Methodological quality was evaluated with an assurance tool for anatomical studies (AQUA). The statistical mean, standard deviation, and difference of means calculated with the Student's t-test for presence between hemispheres and presence in the frontal and temporal lobes were analyzed. Results: A total of 123 studies met the established selection criteria, with a total of 6224 patients. In relation to the mean, GBM between hemispheres had a mean of 33.36 (SD 58.00) in the right hemisphere and a mean of 34.70 (SD 65.07) in the left hemisphere, due to the difference in averages between hemispheres. There were no statistically significant differences, p = 0.35. For the comparison between the presence of GBM in the frontal lobe and the temporal lobe, there was a mean in the frontal lobe of 23.23 (SD 40.03), while in the temporal lobe, the mean was 22.05 (SD 43.50), and for the difference in means between the frontal lobe and the temporal lobe, there was no statistically significant difference for the presence of GBM, p = 0.178. Conclusions: We believe that before a treatment, it will always be correct to know where the GBM is located and how it behaves clinically, in order to generate correct conservative or surgical treatment guidelines for each patient. We believe that more detailed studies are also needed to show why GBM is associated more with some regions than others, despite the brain structure being homologous to other regions in which GMB occurs less frequently, which is why knowing its predominant presence in brain regions is very important.
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Affiliation(s)
- Juan Jose Valenzuela-Fuenzalida
- Departamento de Ciencias Química y Biológicas, Facultad de Ciencias de la Salud, Universidad Bernardo O’Higgins, Santiago 8320000, Chile;
- Departament de Morfología, Facultad de Medicina, Universidad Andrés Bello, Santiago 8370146, Chile; (L.M.-V.); (V.S.-B.); (D.M.-B.); (P.N.-B.); (M.R.-L.)
| | - Laura Moyano-Valarezo
- Departament de Morfología, Facultad de Medicina, Universidad Andrés Bello, Santiago 8370146, Chile; (L.M.-V.); (V.S.-B.); (D.M.-B.); (P.N.-B.); (M.R.-L.)
| | - Vicente Silva-Bravo
- Departament de Morfología, Facultad de Medicina, Universidad Andrés Bello, Santiago 8370146, Chile; (L.M.-V.); (V.S.-B.); (D.M.-B.); (P.N.-B.); (M.R.-L.)
| | - Daniel Milos-Brandenberg
- Departament de Morfología, Facultad de Medicina, Universidad Andrés Bello, Santiago 8370146, Chile; (L.M.-V.); (V.S.-B.); (D.M.-B.); (P.N.-B.); (M.R.-L.)
- Escuela de Medicina, Facultad Ciencias de la Salud, Universidad del Alba, Santiago 8320000, Chile
| | - Mathias Orellana-Donoso
- Escuela de Medicina, Universidad Finis Terrae, Santiago 7501015, Chile;
- Department of Morphological Sciences, Faculty of Medicine and Science, Universidad San Sebastián, Santiago 8420524, Chile
| | - Pablo Nova-Baeza
- Departament de Morfología, Facultad de Medicina, Universidad Andrés Bello, Santiago 8370146, Chile; (L.M.-V.); (V.S.-B.); (D.M.-B.); (P.N.-B.); (M.R.-L.)
| | | | - Macarena Rodríguez-Luengo
- Departament de Morfología, Facultad de Medicina, Universidad Andrés Bello, Santiago 8370146, Chile; (L.M.-V.); (V.S.-B.); (D.M.-B.); (P.N.-B.); (M.R.-L.)
| | - Gustavo Oyanedel-Amaro
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Santiago 8910060, Chile;
| | - Juan Sanchis-Gimeno
- GIAVAL Research Group, Department of Anatomy and Human Embryology, Faculty of Medicine, University of Valencia, 46001 Valencia, Spain;
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Johansson J, Lagerstrand K, Björkman-Burtscher IM, Laesser M, Hebelka H, Maier SE. Normal Brain and Brain Tumor ADC: Changes Resulting From Variation of Diffusion Time and/or Echo Time in Pulsed-Gradient Spin Echo Diffusion Imaging. Invest Radiol 2024:00004424-990000000-00206. [PMID: 38587357 DOI: 10.1097/rli.0000000000001081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
OBJECTIVES Increasing gradient performance on modern magnetic resonance imaging scanners has profoundly reduced the attainable diffusion and echo times for clinically available pulsed-gradient spin echo (PGSE) sequences. This study investigated how this may impact the measured apparent diffusion coefficient (ADC), which is considered an important diagnostic marker for differentiation between normal and abnormal brain tissue and for therapeutic follow-up. MATERIALS AND METHODS Diffusion time and echo time dependence of the ADC were evaluated on a high-performance 3 T magnetic resonance imaging scanner. Diffusion PGSE brain scans were performed in 10 healthy volunteers and in 10 brain tumor patients using diffusion times of 16, 40, and 70 ms, echo times of 60, 75, and 104 ms at 3 b-values (0, 100, and 1000 s/mm 2 ), and a maximum gradient amplitude of 68 mT/m. A low gradient performance system was also emulated by reducing the diffusion encoding gradient amplitude to 19 mT/m. In healthy subjects, the ADC was measured in 6 deep gray matter regions and in 6 white matter regions. In patients, the ADC was measured in the solid part of the tumor. RESULTS With increasing diffusion time, a small but significant ADC increase of up to 2.5% was observed for 6 aggregate deep gray matter structures. With increasing echo time or reduced gradient performance, a small but significant ADC decrease of up to 2.6% was observed for 6 aggregate white matter structures. In tumors, diffusion time-related ADC changes were inconsistent without clear trend. For tumors with diffusivity above 1.0 μm 2 /ms, with prolonged echo time, there was a pronounced ADC increase of up to 12%. Meanwhile, for tumors with diffusivity at or below 1.0 μm 2 /ms, no change or a reduction was observed. Similar results were observed for gradient performance reduction, with an increase of up to 21%. The coefficient of variation determined in repeat experiments was 2.4%. CONCLUSIONS For PGSE and the explored parameter range, normal tissue ADC changes seem negligible. Meanwhile, observed tumor ADC changes can be relevant if ADC is used as a quantitative biomarker and not merely assessed by visual inspection. This highlights the importance of reporting all pertinent timing parameters in ADC studies and of considering these effects when building scan protocols for use in multicenter investigations.
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Affiliation(s)
- Jens Johansson
- From the Department of Radiology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden (J.J., I.M.B.-B., M.L., H.H., S.E.M.); Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden (K.L.); Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden (J.J., K.L.); Department of Radiology, Sahlgrenska University Hospital, Region Västra Götaland, Gothenburg, Sweden (I.M.B.-B., M.L., H.H.); and Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (S.E.M.)
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Kamimura K, Nakano T, Hasegawa T, Nakajo M, Yamada C, Kamimura Y, Akune K, Ejima F, Ayukawa T, Nagano H, Takumi K, Nakajo M, Higa N, Yonezawa H, Hanaya R, Kirishima M, Tanimoto A, Iwanaga T, Imai H, Feiweier T, Yoshiura T. Differentiating primary central nervous system lymphoma from glioblastoma by time-dependent diffusion using oscillating gradient. Cancer Imaging 2023; 23:114. [PMID: 38037172 PMCID: PMC10691025 DOI: 10.1186/s40644-023-00639-7] [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: 08/29/2023] [Accepted: 11/22/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND This study aimed to elucidate the impact of effective diffusion time setting on apparent diffusion coefficient (ADC)-based differentiation between primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBMs) and to investigate the usage of time-dependent diffusion magnetic resonance imaging (MRI) parameters. METHODS A retrospective study was conducted involving 21 patients with PCNSLs and 66 patients with GBMs using diffusion weighted imaging (DWI) sequences with oscillating gradient spin-echo (Δeff = 7.1 ms) and conventional pulsed gradient (Δeff = 44.5 ms). In addition to ADC maps at the two diffusion times (ADC7.1 ms and ADC44.5 ms), we generated maps of the ADC changes (cADC) and the relative ADC changes (rcADC) between the two diffusion times. Regions of interest were placed on enhancing regions and non-enhancing peritumoral regions. The mean and the fifth and 95th percentile values of each parameter were compared between PCNSLs and GBMs. The area under the receiver operating characteristic curve (AUC) values were used to compare the discriminating performances among the indices. RESULTS In enhancing regions, the mean and fifth and 95th percentile values of ADC44.5 ms and ADC7.1 ms in PCNSLs were significantly lower than those in GBMs (p = 0.02 for 95th percentile of ADC44.5 ms, p = 0.04 for ADC7.1 ms, and p < 0.01 for others). Furthermore, the mean and fifth and 95th percentile values of cADC and rcADC were significantly higher in PCNSLs than in GBMs (each p < 0.01). The AUC of the best-performing index for ADC7.1 ms was significantly lower than that for ADC44.5 ms (p < 0.001). The mean rcADC showed the highest discriminating performance (AUC = 0.920) among all indices. In peritumoral regions, no significant difference in any of the three indices of ADC44.5 ms, ADC7.1 ms, cADC, and rcADC was observed between PCNSLs and GBMs. CONCLUSIONS Effective diffusion time setting can have a crucial impact on the performance of ADC in differentiating between PCNSLs and GBMs. The time-dependent diffusion MRI parameters may be useful in the differentiation of these lesions.
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Affiliation(s)
- Kiyohisa Kamimura
- Department of Advanced Radiological Imaging, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan.
| | - Tsubasa Nakano
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Tomohito Hasegawa
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Masanori Nakajo
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Chihiro Yamada
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Yoshiki Kamimura
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Kentaro Akune
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Fumitaka Ejima
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Takuro Ayukawa
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Hiroaki Nagano
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Koji Takumi
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Masatoyo Nakajo
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Nayuta Higa
- Department of Neurosurgery, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Hajime Yonezawa
- Department of Neurosurgery, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Ryosuke Hanaya
- Department of Neurosurgery, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Mari Kirishima
- Department of Pathology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
| | - Akihide Tanimoto
- 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
- Siemens Healthcare K.K., Gate City Osaki West Tower, 1-11-1 Osaki, Shinagawa-Ku, Tokyo, 141-8644, Japan
| | | | - Takashi Yoshiura
- Department of Advanced Radiological Imaging, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544, Japan
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Hung ND, Anh NN, Minh ND, Huyen DK, Duc NM. Differentiation of glioblastoma and primary central nervous system lymphomas using multiparametric diffusion and perfusion magnetic resonance imaging. Biomed Rep 2023; 19:82. [PMID: 37881606 PMCID: PMC10594071 DOI: 10.3892/br.2023.1664] [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: 05/16/2023] [Accepted: 09/13/2023] [Indexed: 10/27/2023] Open
Abstract
The present study aimed to determine whether combining diffusion-weighted (DWI) and dynamic susceptibility contrast-enhanced perfusion-weighted (DSC-PWI) magnetic resonance imaging (MRI) could differentiate between primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM). The present retrospective study evaluated 45 patients with histologically confirmed brain tumors, of which 18 had PCNSLs and 27 had GBMs. All patients underwent conventional, DWI, and DSC-PWI MRIs before the surgical removal of the lesion or stereotactic biopsy. The solid tumor component, peritumoral edema, and abnormal white matter were measured in three regions of interest to evaluate relative cerebral blood volume (rCBV), apparent diffusion coefficient (ADC) and DWI. In conventional MRI, there were significant differences in tumor numbers, tumor enhancement type, tumor necrosis, hemorrhage and open-ring sign between GBM and PCNSL. Solid tumor ADC and rCBV values (ADCt and rCBVt, respectively) and their ratios with abnormal white matter amounts were significantly higher in GBM cases than in PCNSL cases (P<0.05). The rCBV value for peritumoral edema (rCBVe) and its ratio with abnormal white matter amount (rCBVe/n) were significantly higher in GBM cases than in PCNSL cases (P<0.05). However, ADC values did not differ significantly for peritumoral edema. DWI values did not differ significantly. Combining rCBVt and rCBVe/n provided a perfect area under the receiver operating characteristic curve of 1.00, with 100% sensitivity and 100% specificity for distinguishing GBM from PCNSL. In the results of the present study, the major criterion in the decision-making process distinguishing PCNSL from GBM was the combined rCBVt and rCBVe/n parameter. A minor criterion was the ADCt value of the lesion.
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Affiliation(s)
- Nguyen Duy Hung
- Department of Radiology, Hanoi Medical University, Hanoi 100000, Vietnam
- Department of Radiology, Viet Duc Hospital, Hanoi 100000, Vietnam
| | - Nguyen Ngoc Anh
- Department of Radiology, Hanoi Medical University, Hanoi 100000, Vietnam
| | - Nguyen Dinh Minh
- Department of Radiology, Viet Duc Hospital, Hanoi 100000, Vietnam
| | - Dang Khanh Huyen
- Department of Radiology, Hanoi Medical University, Hanoi 100000, Vietnam
| | - Nguyen Minh Duc
- Department of Radiology, Pham Ngoc Thach University of Medicine, Ho Chi Minh 700000, Vietnam
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Solar P, Valekova H, Marcon P, Mikulka J, Barak M, Hendrych M, Stransky M, Siruckova K, Kostial M, Holikova K, Brychta J, Jancalek R. Classification of brain lesions using a machine learning approach with cross-sectional ADC value dynamics. Sci Rep 2023; 13:11459. [PMID: 37454179 PMCID: PMC10349862 DOI: 10.1038/s41598-023-38542-7] [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: 02/21/2023] [Accepted: 07/10/2023] [Indexed: 07/18/2023] Open
Abstract
Diffusion-weighted imaging (DWI) and its numerical expression via apparent diffusion coefficient (ADC) values are commonly utilized in non-invasive assessment of various brain pathologies. Although numerous studies have confirmed that ADC values could be pathognomic for various ring-enhancing lesions (RELs), their true potential is yet to be exploited in full. The article was designed to introduce an image analysis method allowing REL recognition independently of either absolute ADC values or specifically defined regions of interest within the evaluated image. For this purpose, the line of interest (LOI) was marked on each ADC map to cross all of the RELs' compartments. Using a machine learning approach, we analyzed the LOI between two representatives of the RELs, namely, brain abscess and glioblastoma (GBM). The diagnostic ability of the selected parameters as predictors for the machine learning algorithms was assessed using two models, the k-NN model and the SVM model with a Gaussian kernel. With the k-NN machine learning method, 80% of the abscesses and 100% of the GBM were classified correctly at high accuracy. Similar results were obtained via the SVM method. The proposed assessment of the LOI offers a new approach for evaluating ADC maps obtained from different RELs and contributing to the standardization of the ADC map assessment.
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Affiliation(s)
- Peter Solar
- Department of Neurosurgery, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
- Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Hana Valekova
- Department of Neurosurgery, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
- Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Petr Marcon
- Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka, 12, 616 00, Brno, Czech Republic
| | - Jan Mikulka
- Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka, 12, 616 00, Brno, Czech Republic
| | - Martin Barak
- Department of Neurosurgery, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
- Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Michal Hendrych
- Faculty of Medicine, Masaryk University, Brno, Czech Republic
- First Department of Pathology, St. Anne's University Hospital, Brno, Czech Republic
| | - Matyas Stransky
- Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka, 12, 616 00, Brno, Czech Republic
| | - Katerina Siruckova
- Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka, 12, 616 00, Brno, Czech Republic
| | - Martin Kostial
- Faculty of Electrical Engineering and Communication, Brno University of Technology, Technicka, 12, 616 00, Brno, Czech Republic
| | - Klara Holikova
- Faculty of Medicine, Masaryk University, Brno, Czech Republic
- Department of Medical Imaging, St. Anne's University Hospital, Brno, Czech Republic
| | - Jindrich Brychta
- Department of Neurosurgery, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic
| | - Radim Jancalek
- Department of Neurosurgery, St. Anne's University Hospital, Pekarska 53, 656 91, Brno, Czech Republic.
- Faculty of Medicine, Masaryk University, Brno, Czech Republic.
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Pang Y, Kosmin M, Li Z, Deng X, Li Z, Li X, Zhang Y, Royle G, Manolopoulos S. Isotoxic dose escalated radiotherapy for glioblastoma based on diffusion-weighted MRI and tumor control probability-an in-silico study. Br J Radiol 2023; 96:20220384. [PMID: 37102792 PMCID: PMC10230387 DOI: 10.1259/bjr.20220384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 02/19/2023] [Accepted: 03/03/2023] [Indexed: 04/28/2023] Open
Abstract
OBJECTIVES Glioblastoma (GBM) is the most common malignant primary brain tumor with local recurrence after radiotherapy (RT), the most common mode of failure. Standard RT practice applies the prescription dose uniformly across tumor volume disregarding radiological tumor heterogeneity. We present a novel strategy using diffusion-weighted (DW-) MRI to calculate the cellular density within the gross tumor volume (GTV) in order to facilitate dose escalation to a biological target volume (BTV) to improve tumor control probability (TCP). METHODS The pre-treatment apparent diffusion coefficient (ADC) maps derived from DW-MRI of ten GBM patients treated with radical chemoradiotherapy were used to calculate the local cellular density based on published data. Then, a TCP model was used to calculate TCP maps from the derived cell density values. The dose was escalated using a simultaneous integrated boost (SIB) to the BTV, defined as the voxels for which the expected pre-boost TCP was in the lowest quartile of the TCP range for each patient. The SIB dose was chosen so that the TCP in the BTV increased to match the average TCP of the whole tumor. RESULTS By applying a SIB of between 3.60 Gy and 16.80 Gy isotoxically to the BTV, the cohort's calculated TCP increased by a mean of 8.44% (ranging from 7.19 to 16.84%). The radiation dose to organ at risk is still under their tolerance. CONCLUSIONS Our findings indicate that TCPs of GBM patients could be increased by escalating radiation doses to intratumoral locations guided by the patient's biology (i.e., cellularity), moreover offering the possibility for personalized RT GBM treatments. ADVANCES IN KNOWLEDGE A personalized and voxel level SIB radiotherapy method for GBM is proposed using DW-MRI, which can increase the tumor control probability and maintain organ at risk dose constraints.
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Affiliation(s)
- Yaru Pang
- Department of Medical Physics and Biomedical Engineering, University College London, Gower Street, London, United Kingdom
| | | | - Zhuangling Li
- Department of Radiation Oncology, Shenzhen People's Hospital, Shenzhen, China
| | - Xiaonian Deng
- Department of Radiation Oncology, Shenzhen People's Hospital, Shenzhen, China
| | - Zihuang Li
- Department of Radiation Oncology, Shenzhen People's Hospital, Shenzhen, China
| | - Xianming Li
- Department of Radiation Oncology, Shenzhen People's Hospital, Shenzhen, China
| | - Ying Zhang
- Department of Medical Physics and Biomedical Engineering, University College London, Gower Street, London, United Kingdom
| | - Gary Royle
- Department of Medical Physics and Biomedical Engineering, University College London, Gower Street, London, United Kingdom
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Scola E, Del Vecchio G, Busto G, Bianchi A, Desideri I, Gadda D, Mancini S, Carlesi E, Moretti M, Desideri I, Muscas G, Della Puppa A, Fainardi E. Conventional and Advanced Magnetic Resonance Imaging Assessment of Non-Enhancing Peritumoral Area in Brain Tumor. Cancers (Basel) 2023; 15:cancers15112992. [PMID: 37296953 DOI: 10.3390/cancers15112992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 05/24/2023] [Accepted: 05/26/2023] [Indexed: 06/12/2023] Open
Abstract
The non-enhancing peritumoral area (NEPA) is defined as the hyperintense region in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images surrounding a brain tumor. The NEPA corresponds to different pathological processes, including vasogenic edema and infiltrative edema. The analysis of the NEPA with conventional and advanced magnetic resonance imaging (MRI) was proposed in the differential diagnosis of solid brain tumors, showing higher accuracy than MRI evaluation of the enhancing part of the tumor. In particular, MRI assessment of the NEPA was demonstrated to be a promising tool for distinguishing high-grade gliomas from primary lymphoma and brain metastases. Additionally, the MRI characteristics of the NEPA were found to correlate with prognosis and treatment response. The purpose of this narrative review was to describe MRI features of the NEPA obtained with conventional and advanced MRI techniques to better understand their potential in identifying the different characteristics of high-grade gliomas, primary lymphoma and brain metastases and in predicting clinical outcome and response to surgery and chemo-irradiation. Diffusion and perfusion techniques, such as diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), dynamic susceptibility contrast-enhanced (DSC) perfusion imaging, dynamic contrast-enhanced (DCE) perfusion imaging, arterial spin labeling (ASL), spectroscopy and amide proton transfer (APT), were the advanced MRI procedures we reviewed.
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Affiliation(s)
- Elisa Scola
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Guido Del Vecchio
- Radiodiagnostic Unit N. 2, Department of Experimental and Clinical Biomedical Sciences, University of Florence, 50121 Florence, Italy
| | - Giorgio Busto
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Andrea Bianchi
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Ilaria Desideri
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Davide Gadda
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Sara Mancini
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Edoardo Carlesi
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Marco Moretti
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
| | - Isacco Desideri
- Radiation Oncology, Oncology Department, Careggi University Hospital, University of Florence, 50121 Florence, Italy
| | - Giovanni Muscas
- Neurosurgery Unit, Department of Neuroscience, Psychology, Pharmacology and Child Health, Careggi University Hospital, University of Florence, 50121 Florence, Italy
| | - Alessandro Della Puppa
- Neurosurgery Unit, Department of Neuroscience, Psychology, Pharmacology and Child Health, Careggi University Hospital, University of Florence, 50121 Florence, Italy
| | - Enrico Fainardi
- Neuroradiology Unit, Department of Radiology, Careggi University Hospital, 50134 Florence, Italy
- Neuroradiology Unit, Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, 50121 Florence, Italy
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Du X, He Y, Lin W. Diagnostic Accuracy of the Diffusion-Weighted Imaging Method Used in Association With the Apparent Diffusion Coefficient for Differentiating Between Primary Central Nervous System Lymphoma and High-Grade Glioma: Systematic Review and Meta-Analysis. Front Neurol 2022; 13:882334. [PMID: 35812103 PMCID: PMC9263097 DOI: 10.3389/fneur.2022.882334] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 05/27/2022] [Indexed: 12/30/2022] Open
Abstract
Background It is difficult to differentiate between a few primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG) using conventional magnetic resonance imaging techniques. The purpose of this study is to explore whether diffusion-weighted imaging (DWI) can be effectively used to differentiate between these two types of tumors by analyzing the apparent diffusion coefficient (ADC). Research Design and Methods Data presented in Pubmed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Database, and China Science and Technology Journal Database (CQVIP) were analyzed. High-quality literature was included, and the quality was evaluated using the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) tool, and the studies were based on the inclusion and exclusion rules. The pooled sensitivity, pooled specificity, pooled positive likelihood ratio (PLR), pooled negative likelihood ratio (NLR), pooled diagnostic odds ratio (DOR), area under the curve (AUC) of the summary operating characteristic curve (SROC), and corresponding 95% confidence interval (CI) were calculated using the bivariate mixed effect model. Meta-regression analysis and subgroup analysis were used to explore the sources of heterogeneity. The publication bias was evaluated by conducting Deek's test. Results In total, eighteen high-quality studies were included. The pooled sensitivity was 0.82 (95% CI: 0.75–0.88), the pooled specificity was 0.87 (95% CI: 0.84–0.90), the pooled positive likelihood ratio was 6.49 (95% CI: 5.06–8.32), the pooled NLR was 0.21 (95% CI: 0.14–0.30), the pooled DOR was 31.31 (95% CI: 18.55–52.86), and the pooled AUC was 0.90 (95% CI: 0.87–0.92). Sample size, language and country of publication, magnetic field strength, region of interest (ROI), and cut-off values of different types of ADC can potentially be the sources of heterogeneity. There was no publication bias in this meta-analysis. Conclusions The results obtained from the meta-analysis suggest that DWI is characterized by high diagnostic accuracy and thus can be effectively used for differentiating between PCNSL and HGG.
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Affiliation(s)
- Xiaoli Du
- Department of Radiology, Chengdu First People's Hospital, Chengdu, China
| | - Yue He
- Department of Orthopedics, Chengdu First People's Hospital, Chengdu, China
| | - Wei Lin
- Department of Radiology, Chengdu First People's Hospital, Chengdu, China
- *Correspondence: Wei Lin
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9
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Brain Tsunamis in Human High-Grade Glioma: Preliminary Observations. Brain Sci 2022; 12:brainsci12060710. [PMID: 35741596 PMCID: PMC9221439 DOI: 10.3390/brainsci12060710] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 05/20/2022] [Accepted: 05/28/2022] [Indexed: 02/06/2023] Open
Abstract
Gliomas make up nearly 40% of all central nervous system tumors, with over 50% of those being high-grade gliomas. Emerging data suggests that electrophysiologic events in the peri-tumoral region may play a role in the behavior and progression of high-grade gliomas. While seizures in the peri-tumoral zone are well described, much larger and slowly propagating waves of spreading depolarization (SD) may potentially have roles in both non-epileptic transient neurologic deficits and tumor progression. SD has only recently been observed in pre-clinical glioma models and it is not known whether these events occur clinically. We present a case of SD occurring in a human high-grade glioma using gold-standard subdural DC ECoG recordings. This finding could have meaningful implications for both clinical symptomatology and potentially for disease progression in these patients. Our observations and hypotheses are based on analogy with a large body of evidence in stroke and acute neurological injury that have recently established SD as cause of transient neurological deficits as well as a fundamental mechanism of ischemic expansion. Whether SD could represent a mechanistic target in this process to limit such progression is a high priority for further clinical investigations.
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10
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Differentiation of high-grade glioma and primary central nervous system lymphoma: Multiparametric imaging of the enhancing tumor and peritumoral regions based on hybrid 18F-FDG PET/MRI. Eur J Radiol 2022; 150:110235. [DOI: 10.1016/j.ejrad.2022.110235] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 02/19/2022] [Accepted: 03/03/2022] [Indexed: 12/14/2022]
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11
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Hu WZ, Guo F, Xu YQ, Xi YB, He B, Yin H, Kang XW. Differentiation of Neoplastic and Non-neoplastic Intracranial Enhancement Lesions Using Three-Dimensional Pseudo-Continuous Arterial Spin Labeling. Front Neurosci 2022; 16:812997. [PMID: 35299623 PMCID: PMC8923048 DOI: 10.3389/fnins.2022.812997] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 01/17/2022] [Indexed: 11/13/2022] Open
Abstract
Background and Purpose It is sometimes difficult to effectively distinguish non-neoplastic from neoplastic intracranial enhancement lesions using conventional magnetic resonance imaging (MRI). This study aimed to evaluate the diagnostic performance of three-dimensional pseudo-continuous arterial spin labeling (3D-pCASL) to differentiate non-neoplastic from neoplastic enhancement lesions intracranially. Materials and Methods This prospective study included thirty-five patients with high-grade gliomas (HGG), twelve patients with brain metastasis, and fifteen non-neoplastic patients who underwent conventional, contrast enhancement and 3D-pCASL imaging at 3.0-T MR; all lesions were significantly enhanced. Quantitative parameters including cerebral blood flow (CBF) and relative cerebral blood flow (rCBF) were compared between neoplastic and non-neoplastic using Student’s t-test. In addition, the area under the receiver operating characteristic (ROC) curve (AUC) was measured to assess the differentiation diagnostic performance of each parameter. Results The non-neoplastic group demonstrated significantly lower rCBF values of lesions and perilesional edema compared with the neoplastic group. For the ROC analysis, both relative cerebral blood flow of lesion (rCBF-L) and relative cerebral blood flow of perilesional edema (rCBF-PE) had good diagnostic performance for discriminating non-neoplastic from neoplastic lesions, with an AUC of 0.994 and 0.846, respectively. Conclusion 3D-pCASL may contribute to differentiation of non-neoplastic from neoplastic lesions.
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Affiliation(s)
- Wen-zhong Hu
- Department of Radiology, Xi’an People’s Hospital, Xi’an Fourth Hospital, Xi’an, China
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Yong-qiang Xu
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Yi-bin Xi
- Department of Radiology, Xi’an People’s Hospital, Xi’an Fourth Hospital, Xi’an, China
| | - Bei He
- Department of Radiology, Xi’an People’s Hospital, Xi’an Fourth Hospital, Xi’an, China
| | - Hong Yin
- Department of Radiology, Xi’an People’s Hospital, Xi’an Fourth Hospital, Xi’an, China
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
- *Correspondence: Hong Yin,
| | - Xiao-wei Kang
- Department of Radiology, Xi’an People’s Hospital, Xi’an Fourth Hospital, Xi’an, China
- *Correspondence: Hong Yin,
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12
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Martín-Noguerol T, Mohan S, Santos-Armentia E, Cabrera-Zubizarreta A, Luna A. Advanced MRI assessment of non-enhancing peritumoral signal abnormality in brain lesions. Eur J Radiol 2021; 143:109900. [PMID: 34412007 DOI: 10.1016/j.ejrad.2021.109900] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 07/24/2021] [Accepted: 08/03/2021] [Indexed: 12/30/2022]
Abstract
Evaluation of Central Nervous System (CNS) focal lesions has been classically made focusing on the assessment solid or enhancing component. However, the assessment of solitary peripherally enhancing lesions where the differential diagnosis includes High-Grade Gliomas (HGG) and metastasis, is usually challenging. Several studies have tried to address the characteristics of peritumoral non-enhancing areas, for better characterization of these lesions. Peritumoral hyperintense T2/FLAIR signal abnormality predominantly contains infiltrating tumor cells in HGG whereas CNS metastasis induce pure vasogenic edema. In addition, the accurate determination of the real extension of HGG is critical for treatment selection and outcome. Conventional MRI sequences are limited in distinguishing infiltrating neoplasm from vasogenic edema. Advanced MRI sequences like Diffusion Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI), Perfusion Weighted Imaging (PWI) and MR spectroscopy (MRS) have all been utilized for this aim with acceptable results. Other advanced MRI approaches, less explored for this task such as Arterial Spin Labelling (ASL), Diffusion Kurtosis Imaging (DKI), T2 relaxometry or Amide Proton Transfer (APT) are also showning promising results in this scenario. In this article, we will discuss the physiopathological basis of peritumoral T2/FLAIR signal abnormality and review potential applications of advanced MRI sequences for its evaluation.
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Affiliation(s)
| | - Suyash Mohan
- Division of Neuroradiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.
| | | | | | - Antonio Luna
- MRI Unit, Radiology Department, HT Medica, Jaén, Spain.
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13
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Krebs S, Barasch JG, Young RJ, Grommes C, Schöder H. Positron emission tomography and magnetic resonance imaging in primary central nervous system lymphoma-a narrative review. ANNALS OF LYMPHOMA 2021; 5. [PMID: 34223561 PMCID: PMC8248935 DOI: 10.21037/aol-20-52] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
This review addresses the challenges of primary central nervous system (CNS) lymphoma diagnosis, assessment of treatment response, and detection of recurrence. Primary CNS lymphoma is a rare form of extra-nodal non-Hodgkin lymphoma that can involve brain, spinal cord, leptomeninges, and eyes. Primary CNS lymphoma lesions are most commonly confined to the white matter or deep cerebral structures such as basal ganglia and deep periventricular regions. Contrast-enhanced magnetic resonance imaging (MRI) is the standard diagnostic modality employed by neuro-oncologists. MRI often shows common morphological features such as a single or multiple uniformly well-enhancing lesions without necrosis but with moderate surrounding edema. Other brain tumors or inflammatory processes can show similar radiological patterns, making differential diagnosis difficult. [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) has selected utility in cerebral lymphoma, especially in diagnosis. Primary CNS lymphoma can sometimes present with atypical findings on MRI and FDG PET, such as disseminated disease, non-enhancing or ring-like enhancing lesions. The complementary strengths of PET and MRI have led to the development of combined PET-MR systems, which in some cases may improve lesion characterization and detection. By highlighting active developments in this field, including advanced MRI sequences, novel radiotracers, and potential imaging biomarkers, we aim to spur interest in sophisticated imaging approaches.
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Affiliation(s)
- Simone Krebs
- Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Julia G Barasch
- Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Robert J Young
- Neuroradiology Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Christian Grommes
- Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Heiko Schöder
- Molecular Imaging and Therapy Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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14
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Ozturk K, Soylu E, Cayci Z. Differentiation between primary CNS lymphoma and atypical glioblastoma according to major genomic alterations using diffusion and susceptibility-weighted MR imaging. Eur J Radiol 2021; 141:109784. [PMID: 34051685 DOI: 10.1016/j.ejrad.2021.109784] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 04/26/2021] [Accepted: 05/18/2021] [Indexed: 11/30/2022]
Abstract
PURPOSE We aimed to differentiate primary central nervous system lymphoma (PCNSL) from atypical glioblastoma (GB) and distinguish major genomic subtypes between these tumors using susceptibility-weighted imaging (SWI) along with diffusion-weighted imaging (DWI). METHODS Thirty-one immuno-competent patients with PCNSL stratified by BCL2 and MYC rearrangement, and 57 patients with atypical GB (no visible necrosis) grouped according to isocitrate dehydrogenase-1 (IDH1) mutation status underwent 3.0-Tesla MRI before treatment in this retrospective study. Region of interest analysis with apparent diffusion coefficient (ADC) and SWI signal intensity values of the tumors were normalized by dividing those of contralateral white matter. The independent-samples t-test and Kruskal-Wallis test were utilized to compare parameters. The diagnostic ability of each parameter and their optimal combination was evaluated by logistic regression analysis and receiver operating characteristic. RESULTS PCNSL with rearrangement of both MYC and BCL2 (n = 7) [mean relative (r) ADCmean:0.87 ± 0.06, rADCmin:0.72 ± 0.08] demonstrated significantly lower rADCmean, and rADCmin compared to other PCNSLs (n = 24) (rADCmean:1.19 ± 0.18, rADCmin:1.03 ± 0.17;p < 0.001) and GBs (p < 0.001). GB without IDH1 mutation (n = 44) (mean rSWI value:0.95 ± 0.15) demonstrated significantly lower rSWI value compared to GB with IDH1 mutation (n = 13) (rSWI value:1.13 ± 0.09;p < 0.001) and PCNSL (p < 0.001). The incorporation of rADCmean and rSWI parameters distinguished GB with IDH1 mutation [Area under the curve (AUC):0.985] with sensitivity and specificity of 94.3 and 100 % respectively; and PCNSL with rearrangement of both MYC and BCL2 (AUC:0.982) with sensitivity and specificity of 100 % and 95.4 %, respectively. CONCLUSıONS: Combined analysis of SWI and DWI could differentiate atypical GB from PCNSL and distinguish major genomic subtypes between these tumors.
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Affiliation(s)
- Kerem Ozturk
- Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Esra Soylu
- Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Zuzan Cayci
- Department of Radiology, University of Minnesota, Minneapolis, MN, 55455, USA.
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15
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Chaganti J, Taylor M, Woodford H, Steel T. Differentiation of Primary Central Nervous System Lymphoma and High-Grade Glioma with Dynamic Susceptibility Contrast-Derived Metrics: Pilot Study. World Neurosurg 2021; 151:e979-e987. [PMID: 34020062 DOI: 10.1016/j.wneu.2021.05.026] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Revised: 05/09/2021] [Accepted: 05/10/2021] [Indexed: 12/30/2022]
Abstract
OBJECTIVE Preoperative differentiation of lymphoma from other aggressive intracranial neoplasms is important as the surgical and adjuvant therapy may be fundamentally different between the 2 types of tumors. The purpose of this study was to assess the ability of the dynamic susceptibility contrast-derived metrics, percentage signal recovery (PSR) ratio, and relative cerebral blood volume (rCBV) to distinguish between primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG). METHODS Twenty-six patients (15 with HGG and 11 with PCNSL) with histologically confirmed diagnoses were retrospectively analyzed. Mean PSR and rCBV were calculated from dynamic susceptibility contrast imaging. The 2 groups were compared using an independent samples t-test. Receiver operating characteristic analyses were performed to determine the area under the curve and identify threshold values to differentiate PCNSL from GBM. RESULTS Both rCBV and PSR values were significantly different, at both the group level and subject level, between the PCNSL and HGG patients. The mean rCBV was significantly lower in PCNSL (1.38 ± 0.64) compared with HGG (5.19 ± 2.21, df = 11.24, P < 0.001). The mean PSR ratio was significantly higher in PCNSL (1.04 ± 0.11) compared with HGG (0.72 ± 0.16, df = 17.23, P < 0.001). An rCBV threshold value of 2.67 provided a 100% sensitivity and 100% specificity (area under the curve 1.0) for differentiating PCNSL from HGG. A PSR ratio threshold value of 0.9 was 100% sensitive and 90.91% specific for differentiating PCNSL from HGG. CONCLUSIONS The findings of our study show that rCBV and PSR ratio are different in HGG and PCNSL at both the group level and subject level. Incorporation of perfusion in routine magnetic resonance imaging of contrast-enhancing lesions can have a significant impact on patient management.
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Affiliation(s)
- Joga Chaganti
- Department of Radiology and Imaging, St. Vincent's Hospital, Sydney, Australia.
| | - Michael Taylor
- Department of Neurosurgery, John Hunter Hospital, Newcastle, Australia
| | - Hannah Woodford
- Department of Radiology, John Hunter Hospital, Newcastle, Australia
| | - Timothy Steel
- Department of Neurosurgery, St. Vincent's Hospital, Sydney, Australia
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16
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Wang P, Shi YH, Li JY, Zhang CZ. Differentiating Glioblastoma from Primary Central Nervous System Lymphoma: The Value of Shaping and Nonenhancing Peritumoral Hyperintense Gyral Lesion on FLAIR Imaging. World Neurosurg 2021; 149:e696-e704. [PMID: 33548537 DOI: 10.1016/j.wneu.2021.01.114] [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: 12/15/2020] [Revised: 01/21/2021] [Accepted: 01/22/2021] [Indexed: 12/01/2022]
Abstract
BACKGROUND This study describes a distinct magnetic resonance imaging (MRI) feature, placing emphasis on fluid-attenuation inversion recovery (FLAIR) and contrast-enhanced T1-weighted (T1C) images for the preoperative differentiation of glioblastoma (GBM) from primary central nervous system lymphoma (PCNSL). METHODS The preoperative MRI findings of 116 pathologically confirmed glioblastoma (n = 72) and PCNSL (n = 44) were retrospectively reviewed. Two neuroimaging specialists analyzed the MRIs, and image analysis was focused on the presence or absence of a shaping and nonenhancing peritumoral hyperintense gyral lesion on FLAIR imaging (SNEPGF, i.e., hyperintense lesion in a shaping and nonenhancing peritumoral gyral area on FLAIR imaging). The gyral area adjacent to and within 3 cm of the enhanced tumor was defined as the peritumoral gyrus region. The FLAIR hyperintensity lesion were termed as the signal intensity ratio ≥30% compared with contralateral normal gray matter. Then, the differential diagnostic efficacy of SNEFPG sign for GBM and PCNSL was analyzed. RESULTS The SNEPGF sign was found in 33 GBM cases (33 of 72, 45.8%), and the FLAIR signal intensity and apparent diffusion coefficient value of these area were lower than the peritumoral edema area (P < 0.0001). In 44 PCNSL cases, no SNEPGF sign was found. A slightly higher FLAIR signal intensity was seen in 9 PCNSLs, but uniform and marked enhancement was seen in these areas. The sensitivity, specificity, positive predictive value, and negative predictive value of the differential diagnosis of GBM and PCNSL with SNEPGF sign were 45.8%, 100%, 100%, and 53.0%, respectively. CONCLUSIONS The SNEPGF sign is effective in identifying GBM from PCNSL, especially with high specificity.
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Affiliation(s)
- Ping Wang
- Department of Radiology, Yantai Yuhuangding Hospital, Yantai, Shandong, PR China
| | - Ying-Hong Shi
- Department of Radiology, Yantai Yuhuangding Hospital, Yantai, Shandong, PR China
| | - Jian-Ye Li
- Department of Radiology, Gutian Hospital, Gutian, Fujian, PR China
| | - Cheng-Zhou Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Yantai, Shandong, PR China.
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17
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Lundy P, Domino J, Ryken T, Fouke S, McCracken DJ, Ormond DR, Olson JJ. The role of imaging for the management of newly diagnosed glioblastoma in adults: a systematic review and evidence-based clinical practice guideline update. J Neurooncol 2020; 150:95-120. [DOI: 10.1007/s11060-020-03597-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 08/08/2020] [Indexed: 12/11/2022]
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18
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Mehrnahad M, Rostami S, Kimia F, Kord R, Taheri MS, Rad HS, Haghighatkhah H, Moradi A, Kord A. Differentiating glioblastoma multiforme from cerebral lymphoma: application of advanced texture analysis of quantitative apparent diffusion coefficients. Neuroradiol J 2020; 33:428-436. [PMID: 32628089 DOI: 10.1177/1971400920937382] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
PURPOSE The purpose of this study was to differentiate glioblastoma multiforme from primary central nervous system lymphoma using the customised first and second-order histogram features derived from apparent diffusion coefficients.Methods and materials: A total of 82 patients (57 with glioblastoma multiforme and 25 with primary central nervous system lymphoma) were included in this study. The axial T1 post-contrast and fluid-attenuated inversion recovery magnetic resonance images were used to delineate regions of interest for the tumour and peritumoral oedema. The regions of interest were then co-registered with the apparent diffusion coefficient maps, and the first and second-order histogram features were extracted and compared between glioblastoma multiforme and primary central nervous system lymphoma groups. Receiver operating characteristic curve analysis was performed to calculate a cut-off value and its sensitivity and specificity to differentiate glioblastoma multiforme from primary central nervous system lymphoma. RESULTS Based on the tumour regions of interest, apparent diffusion coefficient mean, maximum, median, uniformity and entropy were higher in the glioblastoma multiforme group than the primary central nervous system lymphoma group (P ≤ 0.001). The most sensitive first and second-order histogram feature to differentiate glioblastoma multiforme from primary central nervous system lymphoma was the maximum of 2.026 or less (95% confidence interval (CI) 75.1-99.9%), and the most specific first and second-order histogram feature was smoothness of 1.28 or greater (84.0% CI 70.9-92.8%). Based on the oedema regions of interest, most of the first and second-order histogram features were higher in the glioblastoma multiforme group compared to the primary central nervous system lymphoma group (P ≤ 0.015). The most sensitive first and second-order histogram feature to differentiate glioblastoma multiforme from primary central nervous system lymphoma was the 25th percentile of 0.675 or less (100% CI 83.2-100%) and the most specific first and second-order histogram feature was the median of 1.28 or less (85.9% CI 66.3-95.8%). CONCLUSIONS Texture analysis using first and second-order histogram features derived from apparent diffusion coefficient maps may be helpful in differentiating glioblastoma multiforme from primary central nervous system lymphoma.
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Affiliation(s)
- Mehrsad Mehrnahad
- Department of Radiology, Shahid Beheshti University of Medical Sciences, Iran
| | - Sara Rostami
- Department of Radiology, University of Illinois College of Medicine, USA
| | - Farnaz Kimia
- Department of Radiology, Shahid Beheshti University of Medical Sciences, Iran
| | - Reza Kord
- Department of Radiology, Shahid Beheshti University of Medical Sciences, Iran
| | | | | | | | - Afshin Moradi
- Department of Pathology, Shahid Beheshti University of Medical Sciences, Iran
| | - Ali Kord
- Department of Radiology, University of Illinois College of Medicine, USA
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Falk Delgado A, Van Westen D, Nilsson M, Knutsson L, Sundgren PC, Larsson EM, Falk Delgado A. Diagnostic value of alternative techniques to gadolinium-based contrast agents in MR neuroimaging-a comprehensive overview. Insights Imaging 2019; 10:84. [PMID: 31444580 PMCID: PMC6708018 DOI: 10.1186/s13244-019-0771-1] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 07/12/2019] [Indexed: 12/16/2022] Open
Abstract
Gadolinium-based contrast agents (GBCAs) increase lesion detection and improve disease characterization for many cerebral pathologies investigated with MRI. These agents, introduced in the late 1980s, are in wide use today. However, some non-ionic linear GBCAs have been associated with the development of nephrogenic systemic fibrosis in patients with kidney failure. Gadolinium deposition has also been found in deep brain structures, although it is of unclear clinical relevance. Hence, new guidelines from the International Society for Magnetic Resonance in Medicine advocate cautious use of GBCA in clinical and research practice. Some linear GBCAs were restricted from use by the European Medicines Agency (EMA) in 2017. This review focuses on non-contrast-enhanced MRI techniques that can serve as alternatives for the use of GBCAs. Clinical studies on the diagnostic performance of non-contrast-enhanced as well as contrast-enhanced MRI methods, both well established and newly proposed, were included. Advantages and disadvantages together with the diagnostic performance of each method are detailed. Non-contrast-enhanced MRIs discussed in this review are arterial spin labeling (ASL), time of flight (TOF), phase contrast (PC), diffusion-weighted imaging (DWI), magnetic resonance spectroscopy (MRS), susceptibility weighted imaging (SWI), and amide proton transfer (APT) imaging. Ten common diseases were identified for which studies reported comparisons of non-contrast-enhanced and contrast-enhanced MRI. These specific diseases include primary brain tumors, metastases, abscess, multiple sclerosis, and vascular conditions such as aneurysm, arteriovenous malformation, arteriovenous fistula, intracranial carotid artery occlusive disease, hemorrhagic, and ischemic stroke. In general, non-contrast-enhanced techniques showed comparable diagnostic performance to contrast-enhanced MRI for specific diagnostic questions. However, some diagnoses still require contrast-enhanced imaging for a complete examination.
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Affiliation(s)
- Anna Falk Delgado
- Clinical neurosciences, Karolinska Institutet, Stockholm, Sweden. .,Department of Neuroradiology, Karolinska University Hospital, Eugeniavägen 3, Solna, Stockholm, Sweden.
| | - Danielle Van Westen
- Department of Clinical Sciences/Radiology, Faculty of Medicine, Lund University, Lund, Sweden
| | - Markus Nilsson
- Department of Clinical Sciences/Radiology, Faculty of Medicine, Lund University, Lund, Sweden
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden.,Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Pia C Sundgren
- Department of Clinical Sciences/Radiology, Faculty of Medicine, Lund University, Lund, Sweden.,Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - Elna-Marie Larsson
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
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20
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Anwar SSM, Baig MZ, Laghari AA, Mubarak F, Shamim MS, Jilani UA, Khalid MU. Accuracy of apparent diffusion coefficients and enhancement ratios on magnetic resonance imaging in differentiating primary cerebral lymphomas from glioblastoma. Neuroradiol J 2019; 32:328-334. [PMID: 31188064 DOI: 10.1177/1971400919857556] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND AND PURPOSE This study aimed to determine the accuracy of apparent diffusion coefficient (ADC) and enhancement ratio (ER) in discriminating primary cerebral lymphomas (PCL) and glioblastomas. MATERIALS AND METHODS Circular regions of interest were randomly placed centrally within the largest solid-enhancing area of all lymphomas and glioblastomas on both post-contrast T1-weighted images and corresponding ADC maps. Regions of interest were also drawn in the contralateral hemisphere to obtain enhancement and ADC values of normal-appearing white matter. This helped us to calculate the ER and ADC ratio. RESULTS Mean enhancement and ADC (mm2/s) values for PCL were 2220.56 ± 2948.30 and 712.00 ± 137.87, respectively. Mean enhancement and ADC values for glioblastoma were 1537.07 ± 1668.33 and 1037.93 ± 280.52, respectively. Differences in ADC values, ratios and ERs were all statistically significant between the two groups (p < 0.05). ADC values correctly predicted 71.4% of the lesions as glioblastoma and 83.3% as PCL (area under the curve (AUC) = 0.86 on receiver operating characteristic curve analysis). ADC ratios correctly predicted 85.7% of the lesions as glioblastoma and 100% as PCL (AUC = 0.93). ERs correctly predicted 71.4% of the lesions as glioblastoma and 88.9% as PCL (AUC = 0.92). The combination of ADC ratio and ER correctly predicted 100% tumour type in both patient subgroups. CONCLUSIONS ADC values, ADC ratios and ERs may serve as useful variables to distinguish PCL from glioblastoma. The combination of ADC ratio and ER yielded the best results in identification of both patient subgroups.
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Affiliation(s)
| | | | | | - Fatima Mubarak
- 1 Department of Radiology, Aga Khan University Hospital, Pakistan
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White ML, Moore DW, Zhang Y, Mark KD, Greiner TC, Bierman PJ. Primary central nervous system post-transplant lymphoproliferative disorders: the spectrum of imaging appearances and differential. Insights Imaging 2019; 10:46. [PMID: 30972513 PMCID: PMC6458224 DOI: 10.1186/s13244-019-0726-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 02/25/2019] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVE Central nervous system post-transplant lymphoproliferative disorder (CNS-PTLD) is a rare disease that presents with non-specific signs and symptoms. The purpose of this article is to present the imaging appearances of CNS-PTLD by magnetic resonance imaging. We highlight the differential diagnostic considerations including primary central nervous system lymphoma, glioblastoma, cerebral abscess, and metastatic disease. This is an important topic to review since in daily practice the diagnosis of CNS-PTLD is often not initially considered when present due to its rarity and the lack of radiologists' familiarity with the disease. CONCLUSION Knowing the unique imaging features of CNS-PTLD narrows the differential diagnosis, facilitates the diagnostic work-up, and optimizes making the diagnosis. Advanced MRI data for CNS PTLD is limited but is promising for helping with narrowing the differential diagnosis.
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Affiliation(s)
- Matthew L White
- Radiology, University of Nebraska Medical Center, 981045 Nebraska Medical Center, Omaha, NE, 68198-1045, USA.
| | - Drew W Moore
- Radiology, University of Nebraska Medical Center, 981045 Nebraska Medical Center, Omaha, NE, 68198-1045, USA
| | - Yan Zhang
- Radiology, University of Nebraska Medical Center, 981045 Nebraska Medical Center, Omaha, NE, 68198-1045, USA
| | - Keiper D Mark
- Radiology, University of Nebraska Medical Center, 981045 Nebraska Medical Center, Omaha, NE, 68198-1045, USA
| | - Timothy C Greiner
- Pathology, University of Nebraska Medical Center, 983135 Nebraska Medical Center, Omaha, NE, 68198-3135, USA
| | - Philip J Bierman
- Oncology, University of Nebraska Medical Center, 986840 Nebraska Medical Center, Omaha, NE, 68198-6840, USA
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Ohba S, Murayama K, Abe M, Hasegawa M, Hirose Y. Magnetic Resonance Imaging and Proton Magnetic Resonance Spectroscopy for Differentiating Between Enhanced Gliomas and Malignant Lymphomas. World Neurosurg 2019; 127:e779-e787. [PMID: 30951915 DOI: 10.1016/j.wneu.2019.03.261] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Revised: 03/24/2019] [Accepted: 03/25/2019] [Indexed: 11/25/2022]
Abstract
BACKGROUND Although the treatment strategies for malignant lymphomas and gliomas differ, it is usually difficult to preoperatively distinguish between them. Magnetic resonance spectroscopy (MRS) was recently reported to be useful for preoperative diagnoses; however, MRS data analysis using LCModel, which is a quantitative and objective method, was performed in only a few of the existing reports. METHODS The clinical characteristics, conventional magnetic resonance imaging findings, and MRS parameters using LCModel were evaluated to identify the factors that can help distinguish between malignant lymphomas and enhanced gliomas. RESULTS In total, 59 cases were evaluated, including 13 cases of malignant lymphoma, 1 case of pilocytic astrocytoma, 5 cases of grade Ⅱ glioma, 5 cases of grade Ⅲ glioma, and 35 cases of glioblastoma. There was no correlation between clinical characteristics (sex and age) and diagnosis. Neither T1- nor T2-weighted image was useful for differentiation between the 2 forms of tumors, but the apparent diffusion coefficient minimum value was useful for distinguishing malignant lymphomas from gliomas, with an area under the curve (AUC) value of 0.852. MRS analysis using LCModel revealed differences in glutamate (Glu), N-acetylaspartate (NAA) + N-acetylaspartylglutamate (NAAG), Glu + glutamine, and Lipid (Lip) 13a + Lip13b between malignant lymphomas and gliomas. The largest AUC was 0.904, which was obtained for the Glu level, followed by 0.883 and 0.866 for NAA + NAAG and Lip13a + Lip13b, respectively. CONCLUSIONS Quantitative analysis of proton-MRS using LCModel is considered to be a valuable method for distinguishing between gliomas and malignant lymphomas.
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Affiliation(s)
- Shigeo Ohba
- Department of Neurosurgery, Fujita Health University, Toyoake, Aichi, Japan.
| | - Kazuhiro Murayama
- Department of Radiology, Fujita Health University, Toyoake, Aichi, Japan
| | - Masato Abe
- Department of Pathology, Fujita Health University, Toyoake, Aichi, Japan
| | - Mitsuhiro Hasegawa
- Department of Neurosurgery, Fujita Health University, Toyoake, Aichi, Japan
| | - Yuichi Hirose
- Department of Neurosurgery, Fujita Health University, Toyoake, Aichi, Japan
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Xi YB, Kang XW, Wang N, Liu TT, Zhu YQ, Cheng G, Wang K, Li C, Guo F, Yin H. Differentiation of primary central nervous system lymphoma from high-grade glioma and brain metastasis using arterial spin labeling and dynamic contrast-enhanced magnetic resonance imaging. Eur J Radiol 2019; 112:59-64. [DOI: 10.1016/j.ejrad.2019.01.008] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 12/02/2018] [Accepted: 01/07/2019] [Indexed: 01/22/2023]
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Diagnostic performance of DWI for differentiating primary central nervous system lymphoma from glioblastoma: a systematic review and meta-analysis. Neurol Sci 2019; 40:947-956. [PMID: 30706241 DOI: 10.1007/s10072-019-03732-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2018] [Accepted: 01/18/2019] [Indexed: 12/23/2022]
Abstract
OBJECTIVE The purpose of this meta-analysis was to evaluate the diagnostic performance of diffusion-weighted imaging (DWI) for differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). MATERIALS AND METHODS A thorough search of the databases including PubMed, EMBASE, and Cochrane Library was carried out and the data acquired were up to November 1, 2017. The quality of the studies involved was evaluated using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies, revised version). Multiple analytic values including sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the summary receiver operating characteristic (SROC) curve were calculated and pooled for the statistical analysis. The subgroup analysis was also performed to explore the heterogeneity. RESULTS Eight retrospective studies (461 patients with 461 lesions) were included. The pooled SEN, SPE, PLR, NLR, and DOR with 95% confidence interval (CI) were 0.82 [95% CI 0.70-0.90], 0.84 [95% CI 0.75-0.90], 4.96 [95% CI 3.20-7.69], 0.22 [95% CI 0.13-0.37], and 22.85 [95% CI 10.42-50.11], respectively. The area under the curve (AUC) given by SROC curve was 0.90 [95% CI 0.87-0.92]. The subgroup analysis indicated the slice thickness of the images (> 3 mm versus ≤ 3 mm) was a significant factor affecting the heterogeneity. No existence of significant publication bias was confirmed with Deeks' test. CONCLUSIONS DWI showed moderate diagnostic performance for differentiating primary central nervous system lymphoma (PCNSL) from glioblastoma (GBM). Moreover, it is of clinical significance using DWI combined with conventional MRI to differentiate PCNSL from GBM.
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Suh CH, Kim HS, Jung SC, Park JE, Choi CG, Kim SJ. MRI as a diagnostic biomarker for differentiating primary central nervous system lymphoma from glioblastoma: A systematic review and meta-analysis. J Magn Reson Imaging 2019; 50:560-572. [PMID: 30637843 DOI: 10.1002/jmri.26602] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 11/28/2018] [Accepted: 11/28/2018] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Accurate preoperative differentiation of primary central nervous system lymphoma (PCNSL) and glioblastoma is clinically crucial because the treatment strategies differ substantially. PURPOSE To evaluate the diagnostic performance of MRI for differentiating PCNSL from glioblastoma. STUDY TYPE Systematic review and meta-analysis. SUBJECTS Ovid-MEDLINE and EMBASE databases were searched to find relevant original articles up to November 25, 2018. The search term combined synonyms for "lymphoma," "glioblastoma," and "MRI." FIELD STRENGTH/SEQUENCE Patients underwent at least one MRI sequence including diffusion-weighted imaging (DWI), dynamic susceptibility-weighted contrast-enhanced imaging (DSC), dynamic contrast-enhanced imaging (DCE), arterial spin labeling (ASL), susceptibility-weighted imaging (SWI), intravoxel incoherent motion (IVIM), and magnetic resonance spectroscopy (MRS) using 1.5 or 3 T. ASSESSMENT Quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies-2 tool. STATISTICAL TESTS Hierarchical logistic regression modeling was used to obtain pooled sensitivity and specificity. Meta-regression was performed. RESULTS Twenty-two studies with 1182 patients were included. MRI sequences demonstrated high overall diagnostic performance with pooled sensitivity of 91% (95% confidence interval [CI], 87-93%) and specificity of 89% (95% CI, 85-93%). The area under the hierarchical summary receiver operating characteristic curve was 0.92 (95% CI, 0.90-0.94). Studies using DSC or ASL showed high diagnostic performance (sensitivity of 93% [95% CI, 89-97%] and specificity of 91% [95% CI, 86-96%]). Heterogeneity was only detected in specificity (I2 = 66.84%) and magnetic field strength was revealed to be a significant factor affecting study heterogeneity. DATA CONCLUSION MRI showed overall high diagnostic performance for differentiating PCNSL from glioblastoma, with studies using DSC or ASL showing high diagnostic performance. Therefore, MRI sequences including DSC or ASL is a potential diagnostic tool for differentiating PCNSL from glioblastoma. LEVEL OF EVIDENCE 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:560-572.
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Affiliation(s)
- Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Seung Chai Jung
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Choong Gon Choi
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Sang Joon Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
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Radiomics features to distinguish glioblastoma from primary central nervous system lymphoma on multi-parametric MRI. Neuroradiology 2018; 60:1297-1305. [DOI: 10.1007/s00234-018-2091-4] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Accepted: 08/23/2018] [Indexed: 10/28/2022]
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Xu W, Wang Q, Shao A, Xu B, Zhang J. The performance of MR perfusion-weighted imaging for the differentiation of high-grade glioma from primary central nervous system lymphoma: A systematic review and meta-analysis. PLoS One 2017; 12:e0173430. [PMID: 28301491 PMCID: PMC5354292 DOI: 10.1371/journal.pone.0173430] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 02/19/2017] [Indexed: 12/16/2022] Open
Abstract
It is always a great challenge to distinguish high-grade glioma (HGG) from primary central nervous system lymphoma (PCNSL). We conducted a meta-analysis to assess the performance of MR perfusion-weighted imaging (PWI) in differentiating HGG from PCNSL. The heterogeneity and threshold effect were evaluated, and the sensitivity (SEN), specificity (SPE) and areas under summary receiver operating characteristic curve (SROC) were calculated. Fourteen studies with a total of 598 participants were included in this meta-analysis. The results indicated that PWI had a high level of accuracy (area under the curve (AUC) = 0.9415) for differentiating HGG from PCNSL by using the best parameter from each study. The dynamic susceptibility-contrast (DSC) technique might be an optimal index for distinguishing HGGs from PCNSLs (AUC = 0.9812). Furthermore, the DSC had the best sensitivity 0.963 (95%CI: 0.924, 0.986), whereas the arterial spin-labeling (ASL) displayed the best specificity 0.896 (95% CI: 0.781, 0.963) among those techniques. However, the variability of the optimal thresholds from the included studies suggests that further evaluation and standardization are needed before the techniques can be extensively clinically used.
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Affiliation(s)
- Weilin Xu
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Qun Wang
- Department of Neurosurgery, Chinese PLA General Hospital, Haidian District, Beijing, China
| | - Anwen Shao
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Bainan Xu
- Department of Neurosurgery, Chinese PLA General Hospital, Haidian District, Beijing, China
- * E-mail: (JZ); (BX)
| | - Jianmin Zhang
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
- Brain Research Institute, Zhejiang University, Hangzhou, Zhejiang, China
- Collaborative Innovation Center for Brain Science, Zhejiang University, Hangzhou, Zhejiang, China
- * E-mail: (JZ); (BX)
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