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Shukla S, Karbhari A, Rastogi S, Agarwal U, Rai P, Mahajan A. Bench-to-bedside imaging in brain metastases: a road to precision oncology. Clin Radiol 2024; 79:485-500. [PMID: 38637186 DOI: 10.1016/j.crad.2024.02.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 02/08/2024] [Accepted: 02/12/2024] [Indexed: 04/20/2024]
Abstract
Radiology has seen tremendous evolution in the last few decades. At the same time, oncology has made great strides in diagnosing and treating cancer. Distant metastases of neoplasms are being encountered more often in light of longer patient survival due to better therapeutic strategies and diagnostic methods. Brain metastasis (BM) is a dismal manifestation of systemic cancer. In the present scenario, magnetic resonance imaging (MRI), computed tomography (CT) and positron emission tomography (PET) are playing a big role in providing molecular information about cancer. Lately, molecular imaging has emerged as a stirring arena of dynamic imaging techniques that have enabled clinicians and scientists to noninvasively visualize and understand biological processes at the cellular and molecular levels. This knowledge has impacted etiopathogenesis, detection, personalized treatment, drug development, and our understanding of carcinogenesis. This article offers insight into the molecular biology underlying brain metastasis, its pathogenesis, imaging protocols, and algorithms. It also discusses disease-specific molecular imaging features, focusing on common tumors that spread to the brain, such as lung, breast, colorectal cancer, melanoma, and renal cell carcinoma. Additionally, it covers various targeted treatment options, criteria for assessing treatment response, and the role of artificial intelligence in diagnosing, managing, and predicting prognosis for patients with brain metastases.
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Affiliation(s)
- S Shukla
- Department of Radiodiagnosis and Imaging, Mahamana Pandit Madan Mohan Malaviya Cancer Centre and Homi Bhabha Cancer Hospital, Tata Memorial Hospital, Varanasi, 221 005, Maharashtra, India; Department of Radiodiagnosis and Imaging, Homi Bhabha National Institute, Tata Memorial Hospital, Mumbai, 400 012, Maharashtra, India
| | - A Karbhari
- Department of Radiodiagnosis and Imaging, Homi Bhabha National Institute, Tata Memorial Hospital, Mumbai, 400 012, Maharashtra, India
| | - S Rastogi
- Department of Radiodiagnosis and Imaging, Homi Bhabha National Institute, Tata Memorial Hospital, Mumbai, 400 012, Maharashtra, India
| | - U Agarwal
- Department of Radiodiagnosis and Imaging, Homi Bhabha National Institute, Tata Memorial Hospital, Mumbai, 400 012, Maharashtra, India
| | - P Rai
- Department of Radiodiagnosis and Imaging, Homi Bhabha National Institute, Tata Memorial Hospital, Mumbai, 400 012, Maharashtra, India
| | - A Mahajan
- Department of Imaging, The Clatterbridge Cancer Centre NHS Foundation Trust, L7 8YA Liverpool, UK; Faculty of Health and Life Sciences, University of Liverpool, L7 8TX, Liverpool, UK.
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Hassannejad E, Mohammadifard M, Payandeh A, Bijari B, Shoja A, Abdollahi M, Mohammadifard M. Correlation of ADC values of adult brain tumors with the diagnosis and pathological grade: A cross-sectional multicenter study. Health Sci Rep 2024; 7:e2110. [PMID: 38841116 PMCID: PMC11150419 DOI: 10.1002/hsr2.2110] [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: 10/31/2023] [Revised: 04/08/2024] [Accepted: 04/22/2024] [Indexed: 06/07/2024] Open
Abstract
Background and Aim Brain tumors are common, requiring physicians to have a precise understanding of them for accurate diagnosis and treatment. Considering that various histological tumor types present different cellularity, we conducted this research to examine the role of apparent diffusion coefficient (ADC) values in the differential diagnosis and pathologic grading of brain tumor types. Methods In this cross-sectional study, we gathered pathology reports of histological samples of adult brain tumors. The tissue sample of brain tumors were examined histologically by a pathologist. The magnetic resonance imaging data of these patients were interpreted by a neuroradiologist. The measured ADC values and ADC ratios were calculated. Standard mean ADC values were expressed as 10- 6 mm2/s. The findings were compared according to the histological diagnosis of each tumor. Results Sixty-eight patients were included in the study: 34 (50%) were male, and 34 (50%) were female. The average age of the patients was 51.69 + 16.40 years. In the examination of tumor type, 16 (23.5%) were astrocytoma, 9 (13.2%) were oligodendroglioma, 20 (29.4%) were glioblastoma, 4 (5.9%) were medulloblastoma, and 19 (27.9%) were metastatic tumors. the average value of ADC was statistically significantly different according to the pathological type of tumor (p < 0.001). The two-by-two comparison of average ADC among tumor types revealed significant differences, except for oligodendroglioma and glioblastoma (p-value = 0.87) and glioblastoma and medulloblastoma (p-value = 0.347). The average value of ADC and ADC ratio was statistically significantly different according to the pathological grade of the tumor (p < 0.001). In the two-by-two comparison of average ADC between all pathological grades of the tumor showed a significance difference except for Grade I and Grade II (p-value = 0.355). The mean value of ADC and ADC ratio for glioblastoma and metastatic tumors showed no significant difference. Conclusion The assessment of brain tumor grade through ADC examination will help to estimate prognosis and devising suitable therapeutic strategies.
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Affiliation(s)
- Ehsan Hassannejad
- Department of Radiology, Faculty of MedicineBirjand University of Medical SciencesBirjandIran
| | - Mahtab Mohammadifard
- Department of Pathology, Faculty of MedicineBirjand University of Medical SciencesBirjandIran
| | - Asma Payandeh
- Faculty of MedicineMashhad University of Medical SciencesMashhadIran
| | - Bita Bijari
- Community Medicine department, Faculty of Medicine, Birjand University of Medical SciencesCardiovascular Diseases Research Center of Birjand University of Medical SciencesBirjandIran
| | - Ahmad Shoja
- Department of Radiology, Faculty of MedicineBirjand University of Medical SciencesBirjandIran
| | - Mostafa Abdollahi
- Department of Radiology, School of Medicine, Shahid Modarres HospitalShahid Beheshti University of Medical SciencesTehranIran
| | - Mahyar Mohammadifard
- Department of Radiology, Faculty of MedicineBirjand University of Medical SciencesBirjandIran
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Xing Z, Wang C, Yang W, She D, Yang X, Cao D. Predicting glioblastoma recurrence using multiparametric MR imaging of non-enhancing peritumoral regions at baseline. Heliyon 2024; 10:e30411. [PMID: 38711642 PMCID: PMC11070862 DOI: 10.1016/j.heliyon.2024.e30411] [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: 07/18/2023] [Revised: 04/24/2024] [Accepted: 04/25/2024] [Indexed: 05/08/2024] Open
Abstract
Background To assess the feasibility of multiparametric magnetic resonance imaging in predicting tumor recurrence in nonenhancing peritumoral regions in patients with glioblastoma at baseline. Methods Fifty-eight patients with recurrent glioblastoma underwent multiparametric magnetic resonance imaging, including T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and dynamic susceptibility contrast perfusion-weighted imaging. Nonenhancing peritumoral regions with glioblastoma recurrence were identified by coregistering preoperative and post-recurrent magnetic resonance images. Regions of interest were placed in nonenhancing peritumoral regions with and without tumor recurrence to calculate the apparent diffusion coefficient value, and relative ratios of T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and cerebral blood volume values. Results Significant lower relative T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and relative apparent diffusion coefficient but higher relative cerebral blood volume values were found in the nonenhancing peritumoral regions with tumor recurrence than without recurrence (all P < 0.05). The threshold values ≥ 0.89 for relative cerebral blood volume provide the optimal performance for predicting the nonenhancing peritumoral regions with future tumor recurrence, with the sensitivity, specificity, and accuracy of 84.7%, 83.6%, and 85.8%, respectively. The combination of relative T2-weighted fluid-attenuated inversion recovery signal intensity, apparent diffusion coefficient, and relative cerebral blood volume can provide better predictive performance than relative cerebral blood volume (P = 0.015). Conclusion The combined use of T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and dynamic susceptibility contrast perfusion-weighted imaging can effectively estimate the risk of future tumor recurrence at baseline.
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Affiliation(s)
- Zhen Xing
- Department of Radiology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Radiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, Fujian, China
| | - Cong Wang
- Department of Nuclear Medicine, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
| | - Wen Yang
- The Webb Schools, Claremont, CA, 91711, USA
| | - Dejun She
- Department of Radiology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Radiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, Fujian, China
| | - Xiefeng Yang
- Department of Radiology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Radiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, Fujian, China
| | - Dairong Cao
- Department of Radiology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Department of Radiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, Fujian, China
- Department of Radiology, Fujian Key Laboratory of Precision Medicine for Cancer, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
- Key Laboratory of Radiation Biology of Fujian Higher Education Institutions, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, China
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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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Müller SJ, Khadhraoui E, Ernst M, Rohde V, Schatlo B, Malinova V. Differentiation of multiple brain metastases and glioblastoma with multiple foci using MRI criteria. BMC Med Imaging 2024; 24:3. [PMID: 38166651 PMCID: PMC10759655 DOI: 10.1186/s12880-023-01183-3] [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: 10/29/2023] [Accepted: 12/13/2023] [Indexed: 01/05/2024] Open
Abstract
OBJECTIVE Glioblastoma with multiple foci (mGBM) and multiple brain metastases share several common features on magnetic resonance imaging (MRI). A reliable preoperative diagnosis would be of clinical relevance. The aim of this study was to explore the differences and similarities between mGBM and multiple brain metastases on MRI. METHODS We performed a retrospective analysis of 50 patients with mGBM and compared them with a cohort of 50 patients with multiple brain metastases (2-10 lesions) histologically confirmed and treated at our department between 2015 and 2020. The following imaging characteristics were analyzed: lesion location, distribution, morphology, (T2-/FLAIR-weighted) connections between the lesions, patterns of contrast agent uptake, apparent diffusion coefficient (ADC)-values within the lesion, the surrounding T2-hyperintensity, and edema distribution. RESULTS A total of 210 brain metastases and 181 mGBM lesions were analyzed. An infratentorial localization was found significantly more often in patients with multiple brain metastases compared to mGBM patients (28 vs. 1.5%, p < 0.001). A T2-connection between the lesions was detected in 63% of mGBM lesions compared to 1% of brain metastases. Cortical edema was only present in mGBM. Perifocal edema with larger areas of diffusion restriction was detected in 31% of mGBM patients, but not in patients with metastases. CONCLUSION We identified a set of imaging features which improve preoperative diagnosis. The presence of T2-weighted imaging hyperintensity connection between the lesions and cortical edema with varying ADC-values was typical for mGBM.
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Affiliation(s)
- Sebastian Johannes Müller
- Department of Neuroradiology, University Medical Center, Göttingen, Germany
- Neuroradiologische Klinik, Klinikum Stuttgart, Stuttgart, Germany
| | - Eya Khadhraoui
- Department of Neuroradiology, University Medical Center, Göttingen, Germany
- Neuroradiologische Klinik, Klinikum Stuttgart, Stuttgart, Germany
| | - Marielle Ernst
- Department of Neuroradiology, University Medical Center, Göttingen, Germany
| | - Veit Rohde
- Department of Neurosurgery, University Medical Center, Göttingen, Germany
| | - Bawarjan Schatlo
- Department of Neurosurgery, University Medical Center, Göttingen, Germany
| | - Vesna Malinova
- Department of Neurosurgery, University Medical Center, Göttingen, Germany.
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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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Hung ND, Dung LV, Vi NH, Hai Anh NT, Hong Phuong LT, Hieu ND, Duc NM. The role of 3-Tesla magnetic resonance perfusion and spectroscopy in distinguishing glioblastoma from solitary brain metastasis. J Clin Imaging Sci 2023; 13:19. [PMID: 37559877 PMCID: PMC10408633 DOI: 10.25259/jcis_49_2023] [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: 05/19/2023] [Accepted: 06/10/2023] [Indexed: 08/11/2023] Open
Abstract
OBJECTIVES This study aimed to assess the value of magnetic resonance perfusion (MR perfusion) and magnetic resonance spectroscopy (MR spectroscopy) in 3.0-Tesla magnetic resonanceimaging (MRI) for differential diagnosis of glioblastoma (GBM) and solitary brain metastasis (SBM). MATERIAL AND METHODS This retrospective study involved 36 patients, including 24 cases of GBM and 12 of SBM diagnosed using histopathology. All patients underwent a 3.0-Tesla MRI examination with pre-operative MR perfusion and MR spectroscopy. We assessed the differences in age, sex, cerebral blood volume (CBV), relative CBV (rCBV), and the metabolite ratios of choline/N-acetylaspartate (Cho/NAA) and Cho/creatine between the GBM and SBM groups using the Mann-Whitney U-test and Chi-square test. The cutoff value, area under the curve, sensitivity, specificity, positive predictive value, and negative predictive value of the significantly different parameters between these two groups were determined using the receiver operating characteristic curve. RESULTS In MR perfusion, the CBV of the peritumoral region (pCBV) had the highest preoperative predictive value in discriminating GBM from SBM (cutoff: 1.41; sensitivity: 70.83%; and specificity: 83.33%), followed by the ratio of CBV of the solid tumor component to CBV of normal white matter (rCBVt/n) and the ratio of CBV of the pCBV to CBV of normal white matter (rCBVp/n). In MR spectroscopy, the Cho/NAA ratio of the pCBV (pCho/NAA; cutoff: 1.02; sensitivity: 87.50%; and specificity: 75%) and the Cho/NAA ratio of the solid tumor component (tCho/NAA; cutoff: 2.11; sensitivity: 87.50%; and specificity: 66.67%) were significantly different between groups. Moreover, combining these remarkably different parameters increased their diagnostic utility for distinguishing between GBM and SBM. CONCLUSION pCBV, rCBVt/n, rCBVp/n, pCho/NAA, and tCho/NAA are useful indices for differentiating between GBM and SBM. Combining these indices can improve diagnostic performance in distinguishing between these two tumors.
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Affiliation(s)
- Nguyen Duy Hung
- Department of Radiology, Hanoi Medical University, Ho Chi Minh City, Hanoi, Vietnam
| | - Le Van Dung
- Department of Radiology, Hanoi Medical University, Ho Chi Minh City, Hanoi, Vietnam
| | - Nguyen Ha Vi
- Department of Radiology, Hanoi Medical University, Ho Chi Minh City, Hanoi, Vietnam
| | - Nguyen-Thi Hai Anh
- Department of Radiology, Hanoi Medical University, Ho Chi Minh City, Hanoi, Vietnam
| | | | - Nguyen Dinh Hieu
- Department of Radiology, Hanoi Medical University, Ho Chi Minh City, Hanoi, Vietnam
| | - Nguyen Minh Duc
- Department of Radiology, Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Vietnam
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Steinmann J, Rapp M, Sadat H, Staub-Bartelt F, Turowski B, Steiger HJ, Hänggi D, Sabel M, Kamp MA. The impact of preoperative MRI-based apparent diffusion coefficients on local recurrence and outcome in patients with cerebral metastases. Br J Neurosurg 2023; 37:12-19. [PMID: 32990044 DOI: 10.1080/02688697.2020.1817856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
BACKGROUND Surgery of single cerebral metastases is standard but frequently fails to achieve local tumour control. Reliable predictors for local tumour progression and overall survival are unknown. MRI-based apparent diffusion coefficients (ADC) correlate with tumour cellularity and invasion. The present study analysed a potential relation between the MRI based apparent diffusion coefficients local recurrence and outcome in patients with brain metastases. METHODS A retrospective analysis was performed for patients with cerebral metastases and complete surgical resection evaluated by an early postoperative MRI < 72h. Minimal ADC and mean ADC were assessed in preoperative 1,5T-MRI scans by placing regions of interests in the tumour and the peritumoural tissue. RESULTS Analysis of the relation between ADC values, local progression and outcome was performed in 86 patients with a mean age of 59 years (range 33-83 years). Primary site was NSCLC in 37.2% of all cases. Despite complete resection 33.7% of all patients suffered from local in-brain-progression. There were no significant differences in ADC values in groups based on histology. In the present cohort, the mean ADCmin and the mean ADCmean within the metastasis did not differ significantly between patients with and without a later local in-brain progression (634 × 10-6 vs. 661 × 10-6 mm2/s and 1324 × 10-6 vs. 1361 × 10-6 mm2/s; 1100 × 10-6 vs. 1054 × 10-6 mm2/s; each p > 0.05). Mean ADC values did not correlate significantly with PFS and OAS. CONCLUSION In the present study analysed ADC values had no significant impact on local in brain progression and survival parameters.
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Affiliation(s)
- Julia Steinmann
- Klinik für Neurochirurgie, Heinrich-Heine-Universität, Düsseldorf, Germany
| | - Marion Rapp
- Klinik für Neurochirurgie, Heinrich-Heine-Universität, Düsseldorf, Germany
| | - Hosai Sadat
- Klinik für Neurochirurgie, Heinrich-Heine-Universität, Düsseldorf, Germany
| | | | - Bernd Turowski
- Klinik für Radiologie, Heinrich-Heine-Universität, Düsseldorf, Germany
| | - Hans-Jakob Steiger
- Klinik für Neurochirurgie, Heinrich-Heine-Universität, Düsseldorf, Germany
| | - Daniel Hänggi
- Klinik für Neurochirurgie, Heinrich-Heine-Universität, Düsseldorf, Germany
| | - Michael Sabel
- Klinik für Neurochirurgie, Heinrich-Heine-Universität, Düsseldorf, Germany
| | - Marcel A Kamp
- Klinik für Neurochirurgie, Heinrich-Heine-Universität, Düsseldorf, Germany
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Romano A, Palizzi S, Romano A, Moltoni G, Di Napoli A, Maccioni F, Bozzao A. Diffusion Weighted Imaging in Neuro-Oncology: Diagnosis, Post-Treatment Changes, and Advanced Sequences-An Updated Review. Cancers (Basel) 2023; 15:cancers15030618. [PMID: 36765575 PMCID: PMC9913305 DOI: 10.3390/cancers15030618] [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: 12/19/2022] [Revised: 01/15/2023] [Accepted: 01/16/2023] [Indexed: 01/20/2023] Open
Abstract
DWI is an imaging technique commonly used for the assessment of acute ischemia, inflammatory disorders, and CNS neoplasia. It has several benefits since it is a quick, easily replicable sequence that is widely used on many standard scanners. In addition to its normal clinical purpose, DWI offers crucial functional and physiological information regarding brain neoplasia and the surrounding milieu. A narrative review of the literature was conducted based on the PubMed database with the purpose of investigating the potential role of DWI in the neuro-oncology field. A total of 179 articles were included in the study.
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Affiliation(s)
- Andrea Romano
- NESMOS Department, U.O.C. Neuroradiology, “Sant’Andrea” University Hospital, 00189 Rome, Italy
| | - Serena Palizzi
- NESMOS Department, U.O.C. Neuroradiology, “Sant’Andrea” University Hospital, 00189 Rome, Italy
| | - Allegra Romano
- NESMOS Department, U.O.C. Neuroradiology, “Sant’Andrea” University Hospital, 00189 Rome, Italy
| | - Giulia Moltoni
- NESMOS Department, U.O.C. Neuroradiology, “Sant’Andrea” University Hospital, 00189 Rome, Italy
- Correspondence: ; Tel.: +39-3347906958
| | - Alberto Di Napoli
- NESMOS Department, U.O.C. Neuroradiology, “Sant’Andrea” University Hospital, 00189 Rome, Italy
- IRCCS Fondazione Santa Lucia, 00179 Rome, Italy
| | - Francesca Maccioni
- Department of Radiology, Sapienza University of Rome, Viale Regina Elena 324, 00161 Rome, Italy
| | - Alessandro Bozzao
- NESMOS Department, U.O.C. Neuroradiology, “Sant’Andrea” University Hospital, 00189 Rome, Italy
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Guo X, Jiao H, Cao L, Meng F. Biological implications and clinical potential of invasion and migration related miRNAs in glioma. Front Integr Neurosci 2022; 16:989029. [DOI: 10.3389/fnint.2022.989029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 11/07/2022] [Indexed: 11/22/2022] Open
Abstract
Gliomas are the most common primary malignant brain tumors and are highly aggressive. Invasion and migration are the main causes of poor prognosis and treatment resistance in gliomas. As migration and invasion occur, patient survival and prognosis decline dramatically. MicroRNAs (miRNAs) are small, non-coding 21–23 nucleotides involved in regulating the malignant phenotype of gliomas, including migration and invasion. Numerous studies have demonstrated the mechanism and function of some miRNAs in glioma migration and invasion. However, the biological and clinical significance (including diagnosis, prognosis, and targeted therapy) of glioma migration and invasion-related miRNAs have not been systematically discussed. This paper reviews the progress of miRNAs-mediated migration and invasion studies in glioma and discusses the clinical value of migration and invasion-related miRNAs as potential biomarkers or targeted therapies for glioma. In addition, these findings are expected to translate into future directions and challenges for clinical applications. Although many biomarkers and their biological roles in glioma invasion and migration have been identified, none have been specific so far, and further exploration of clinical treatment is still in progress; therefore, we aimed to further identify specific markers that may guide clinical treatment and improve the quality of patient survival.
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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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Diffusion tensor imaging derived metrics in high grade glioma and brain metastasis differentiation. ARCHIVE OF ONCOLOGY 2022. [DOI: 10.2298/aoo210828007b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Background: Pretreatment differentiation between glioblastoma and metastasis
is a frequently encountered dilemma in neurosurgical practice. Distinction
is required for precise planning of resection or radiotherapy, and also for
defining further diagnostic procedures. Morphology and spectroscopy imaging
features are not specific and frequently overlap. This limitation of
magnetic resonance imaging and magnetic resonance spectroscopy was the
reason to initiate this study. The aim of the present study was to determine
whether the dataset of diffusion tensor imaging metrics contains information
which may be used for the distinction between primary and secondary
intra-axial neoplasms. Methods: Two diffusion tensor imaging parameters were
measured in 81 patients with an expansive, ring-enhancing, intra-axial
lesion on standard magnetic resonance imaging (1.5 T system). All tumors
were histologically verified glioblastoma or secondary deposit. For
qualitative analysis, two regions of interest were defined: intratumoral and
immediate peritumoral region (locations 1 and 2, respectively). Fractional
anisotropy and mean difusivity values of both groups were compared.
Additional test was performed to determine if there was a significant
difference in mean values between two locations. Results: A statistically
significant difference was found in fractional anisotropy values among two
locations, with decreasing values in the direction of neoplastic
infiltration, although such difference was not observed in fractional
anisotropy values in the group with secondary tumors. Mean difusivity values
did not appear helpful in differentiation between these two entities. In
both groups there was no significant difference in mean difusivity values,
neither in intratumoral nor in peritumoral location. Conclusion: The results
of our study justify associating the diffusion tensor imaging technique to
conventional morphologic magnetic resonance imaging as an additional
diagnostic tool for the distinction between primary and secondary
intra-axial lesions. Quantitative analysis of diffusion tensor imaging
metric, in particular measurement of fractional anisotropy in peritumoral
edema facilitates accurate diagnosis.
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Zaccagna F, Grist JT, Quartuccio N, Riemer F, Fraioli F, Caracò C, Halsey R, Aldalilah Y, Cunningham CH, Massoud TF, Aloj L, Gallagher FA. Imaging and treatment of brain tumors through molecular targeting: Recent clinical advances. Eur J Radiol 2021; 142:109842. [PMID: 34274843 DOI: 10.1016/j.ejrad.2021.109842] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 06/24/2021] [Indexed: 02/07/2023]
Abstract
Molecular imaging techniques have rapidly progressed over recent decades providing unprecedented in vivo characterization of metabolic pathways and molecular biomarkers. Many of these new techniques have been successfully applied in the field of neuro-oncological imaging to probe tumor biology. Targeting specific signaling or metabolic pathways could help to address several unmet clinical needs that hamper the management of patients with brain tumors. This review aims to provide an overview of the recent advances in brain tumor imaging using molecular targeting with positron emission tomography and magnetic resonance imaging, as well as the role in patient management and possible therapeutic implications.
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Affiliation(s)
- Fulvio Zaccagna
- Division of Neuroimaging, Department of Medical Imaging, University of Toronto, Toronto, Canada.
| | - James T Grist
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom; Oxford Centre for Clinical Magnetic Resonance Research, University of Oxford, Oxford, United Kingdom; Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Natale Quartuccio
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico Di Cristina Benfratelli, Palermo, Italy
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre, University of Bergen, Bergen, Norway; Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Francesco Fraioli
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Corradina Caracò
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
| | - Richard Halsey
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Yazeed Aldalilah
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom; Department of Radiology, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Charles H Cunningham
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Tarik F Massoud
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University School of Medicine, Stanford, USA
| | - Luigi Aloj
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
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14
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Beig Zali S, Alinezhad F, Ranjkesh M, Daghighi MH, Poureisa M. Accuracy of apparent diffusion coefficient in differentiation of glioblastoma from metastasis. Neuroradiol J 2021; 34:205-212. [PMID: 33417503 PMCID: PMC8165902 DOI: 10.1177/1971400920983678] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Brain metastasis and glioblastoma multiforme are two of the most common malignant brain neoplasms. There are many difficulties in distinguishing these diseases from each other. PURPOSE The purpose of this study was to determine whether the mean apparent diffusion coefficient and absolute standard deviation derived from apparent diffusion coefficient measurements can be used to differentiate glioblastoma multiforme from brain metastasis based on cellularity levels. MATERIAL AND METHODS Magnetic resonance images of 34 patients with histologically verified brain tumors were evaluated retrospectively. Apparent diffusion coefficient and standard deviation values were measured in the enhancing tumor, peritumoral region, and contralateral healthy white matter. Then, to determine whether there was a statistical difference between brain metastasis and glioblastoma multiforme, we analyzed different variables between the two groups. RESULTS Neither mean apparent diffusion coefficient values and ratios nor standard deviation values and ratios were significantly different between glioblastoma multiforme and brain metastasis. Receiver operating characteristic curve analysis of the logistic model with backward stepwise feature selection yielded an area under the curve of 0.77, a specificity of 84%, a sensitivity of 67%, a positive predictive value of 83.33%, and a negative predictive value of 78.26% for distinguishing between glioblastoma multiforme and brain metastasis. The absolute standard deviation and standard deviation ratios were significantly higher in the peritumoral edema compared to the tumor region in each case. CONCLUSION Apparent diffusion coefficient values and ratios, as well as standard deviation values and ratios in peritumoral edema, cannot be used to differentiate edema with infiltration of tumor cells from vasogenic edema. However, standard deviation values could successfully characterize areas of peritumoral edema from the tumoral region in each case.
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Affiliation(s)
- Sanaz Beig Zali
- Neuroscience Research Center, Tabriz University of Medical Sciences, Iran
| | - Farbod Alinezhad
- Student Research Committee, Tabriz University of Medical Sciences, Iran
| | - Mahnaz Ranjkesh
- Department of Radiology, Tabriz University of Medical Sciences, Iran
| | | | - Masoud Poureisa
- Department of Radiology, Tabriz University of Medical Sciences, Iran
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15
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Tepe M, Saylisoy S, Toprak U, Inan I. The Potential Role of Peritumoral Apparent Diffusion Coefficient Evaluation in Differentiating Glioblastoma and Solitary Metastatic Lesions of the Brain. Curr Med Imaging 2021; 17:1200-1208. [PMID: 33726654 DOI: 10.2174/1573405617666210316120314] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 02/14/2021] [Accepted: 02/16/2021] [Indexed: 11/22/2022]
Abstract
OBJECTIVE Differentiating glioblastoma (GBM) and solitary metastasis is not always possible using conventional magnetic resonance imaging (MRI) techniques. In conventional brain MRI, GBM and brain metastases are lesions with mostly similar imaging findings. In this study, we investigated whether apparent diffusion coefficient (ADC) ratios, ADC gradients, and minimum ADC values in the peritumoral edema tissue can be used to discriminate between these two tumors. METHODS This retrospective study was approved by the local institutional review board with a waiver of written informed consent. Prior to surgical and medical treatment, conventional brain MRI and diffusion-weighted MRI (b = 0 and b = 1000) images were taken from 43 patients (12 GBM and 31 solitary metastasis cases). Quantitative ADC measurements were performed on the peritumoral tissue from the nearest segment to the tumor (ADC1), the middle segment (ADC2), and the most distant segment (ADC3). The ratios of these three values were determined proportionally to calculate the peritumoral ADC ratios. In addition, these three values were subtracted from each other to obtain the peritumoral ADC gradients. Lastly, the minimum peritumoral and tumoral ADC values, and the quantitative ADC values from the normal appearing ipsilateral white matter, contralateral white matter and ADC values from cerebrospinal fluid (CSF) were recorded. RESULTS For the differentiation of GBM and solitary metastasis, ADC3 / ADC1 was the most powerful parameter with a sensitivity of 91.7% and specificity of 87.1% at the cut-off value of 1.105 (p < 0.001), followed by ADC3 / ADC2 with a cut-off value of 1.025 (p = 0.001), sensitivity of 91.7%, and specificity of 74.2%. The cut-off, sensitivity and specificity of ADC2 / ADC1 were 1.055 (p = 0.002), 83.3%, and 67.7%, respectively. For ADC3 - ADC1, the cut-off value, sensitivity and specificity were calculated as 150 (p < 0.001), 91.7% and 83.9%, respectively. ADC3 - ADC2 had a cut-off value of 55 (p = 0.001), sensitivity of 91.7%, and specificity of 77.4 whereas ADC2 - ADC1 had a cut-off value of 75 (p = 0.003), sensitivity of 91.7%, and specificity of 61.3%. Among the remaining parameters, only the ADC3 value successfully differentiated between GBM and metastasis (GBM 1802.50 ± 189.74 vs. metastasis 1634.52 ± 212.65, p = 0.022). CONCLUSION The integration of the evaluation of peritumoral ADC ratio and ADC gradient into conventional MR imaging may provide valuable information for differentiating GBM from solitary metastatic lesions.
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Affiliation(s)
- Murat Tepe
- Yunus Emre State Hospital, Department of Radiology, Tepebasi Eskisehir. Turkey
| | - Suzan Saylisoy
- Eskisehir Osmangazi University, Faculty of Medicine, Department of Radiology, Eskisehir. Turkey
| | - Ugur Toprak
- Eskisehir Osmangazi University, Faculty of Medicine, Department of Radiology, Eskisehir. Turkey
| | - Ibrahim Inan
- Adiyaman University, Training and Research Hospital, Department of Radiology, Adiyaman. Turkey
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Eyüboğlu İ, Çakir İM, Aslan S, Sari A. Diagnostic efficacy of apparent diffusion coefficient measurements in differentiation of malignant intra-axial brain tumors. Turk J Med Sci 2021; 51:256-267. [PMID: 33098284 PMCID: PMC7991875 DOI: 10.3906/sag-2006-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 10/24/2020] [Indexed: 01/24/2023] Open
Abstract
Background/aim To evaluate diagnostic efficacy of the apparent diffusion coefficient measurements from tumor (ADCt) and tumor circumference hyperintensities (ADCtch) in different types of malignant intra-axial brain tumors. Materials and methods Between April 2013 and June 2017
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125 patients (52 females (41.6%) and 73 males (58.4%); mean age: 53 years, age range: 14-81 years), who underwent diffusion-weighted imaging (DWI) with intracranial mass, were retrospectively evaluated. The mean ADCt and ADCtch values and ratios were measured. Results Of the 125 patients, 22 (17.6%) had a low-grade glioma (LGG), 55 (44%) had a high-grade glioma (HGG), 32 (25.6%) had metastasis, and 16 (12.8%) had lymphoma diagnosis. There was a statistically significant difference in LGG and HGG in terms of mean ADCt and mean ADCtch values, and ratios. ADCtch values and ratios showed a statistically significant difference in the differentiation of HGG and metastasis and in the differentiation of HGG and lymphoma. According to ROC curve analysis, a cut-off value of 1.49 × 10−3 mm2/s for the mean ADCtch value generated the best combination of 70% sensitivity and 71% specificity for differentiation of HGGs and metastasis. The mean ADCtch value had the highest statistical predictive value for differentiation of HGGs and lymphoma with a sensitivity of 78% and a specificity of 76% for the optimal cut-off value of 0.82 × 10ˉ3 mm²/s. Conclusion The mean ADCt ratio allowed reliable differentiation of LGG and high grade brain tumors, including HGGs, metastases, and lymphoma. The mean ADCtch might be a better imaging biomarker in the differentiation of HHG from metastasis and lymphoma.
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Affiliation(s)
- İlker Eyüboğlu
- Department of Radiology, Karadeniz Technical University, Faculty of Medicine, Trabzon, Turkey
| | - İsmet Miraç Çakir
- Department of Radiology, Giresun University, Faculty of Medicine, Giresun, Turkey
| | - Serdar Aslan
- Department of Radiology, Giresun University, Faculty of Medicine, Giresun, Turkey
| | - Ahmet Sari
- Department of Radiology, Karadeniz Technical University, Faculty of Medicine, Trabzon, Turkey
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17
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Voultsinou D, Mantatzis M, Gerukis T, Heva A, Birbilis T, Prassopoulos P. Magnetic Resonance Imaging patterns in central nervous system lymphomas: A pictorial review. Clin Imaging 2021; 78:1-7. [PMID: 33706068 DOI: 10.1016/j.clinimag.2021.02.014] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Revised: 12/09/2020] [Accepted: 02/08/2021] [Indexed: 11/16/2022]
Abstract
Five distinctive Magnetic Resonance Imaging (MRI) patterns of Central Nervous System Lymphomas (CNSL) are introduced in this pictorial essay - in an attempt to differentiate lymphoma from other abnormalities with similar MRI appearance, - namely a. solitary supratentorial, b. multiple supratentorial, c. infratentorial, d. intravascular, and e. extraparencymal. Recognition of a specific imaging pattern on brain MR imaging, may facilitate the early diagnosis and prompt treatment initiation, thus improving prognosis of brain lymphoma.
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Affiliation(s)
| | - Michalis Mantatzis
- Department of Radiology, University Hospital of Alexandroupolis, Democritus University of Thrace, Greece.
| | | | - Angeliki Heva
- Department of Pathology, AHEPA University Hospital of Thessaloniki, Aristotle University, Thessaloniki, Greece
| | - Theodosios Birbilis
- Department of Neurosurgery, University Hospital of Alexandroupolis, Democritus University of Thrace, Greece
| | - Panos Prassopoulos
- Department of Radiology, AHEPA University Hospital of Thessaloniki, Aristotle University, Thessaloniki, Greece
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18
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Toh CH, Castillo M. Peritumoral brain edema volume in meningioma correlates with tumor fractional anisotropy but not apparent diffusion coefficient or cerebral blood volume. Neuroradiology 2021; 63:1263-1270. [PMID: 33533947 DOI: 10.1007/s00234-021-02646-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 01/11/2021] [Indexed: 11/25/2022]
Abstract
PURPOSE Pathogenesis of peritumoral brain edema (PTBE) in meningiomas remains unclear. Associations between PTBE volume and diffusion or perfusion properties of meningioma have not been studied. We aimed to investigate if diffusion and perfusion properties of meningioma correlate with its PTBE volume. METHODS Seventy consecutive patients (mean age, 58.9 ± 13.7 years; 37 women) with meningiomas who had preoperative DTI and DSC-PWI were retrospectively analyzed. PTBE volume, tumor volume, and mean T2 signal, ADC, FA, and CBV of the tumor were measured. Between meningiomas with and without PTBE, patient age and sex, as well as T2 signal intensity, volume, ADC, FA, and CBV of tumors, were compared. In meningiomas with PTBE, correlations of PTBE volume with patient age and sex, as well as T2 signal intensity, volume, ADC, FA, and CBV of tumors, were analyzed. Multivariable linear regression analysis was performed to identify factors associated with PTBE volume. RESULTS On univariable analysis, meningiomas without PTBE were more frequently found in women (P = 0.033) and demonstrated lower ADC (P = 0.020), higher FA (P < 0.001), and lower CBV (P < 0.001). PTBE volume of meningiomas correlated with tumor ADC (r = 0.444; P = 0.001), tumor FA (r = - 0.655; P < 0.001), and tumor CBV (r = 0.402; P = 0.003). On multivariable analysis, tumor FA was the only factor associated with PTBE volume (P < 0.001). CONCLUSION PTBE volume in meningioma correlates with tumor FA. DTI may help to understand the mechanism of PTBE in meningiomas.
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Affiliation(s)
- Cheng Hong Toh
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou and Chang Gung University College of Medicine, No.5, Fuxing St., Guishan Dist., Taoyuan, 333, Taiwan.
| | - Mauricio Castillo
- Department of Radiology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
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Soliman RK, Essa AA, Elhakeem AAS, Gamal SA, Zaitoun MMA. Texture analysis of apparent diffusion coefficient (ADC) map for glioma grading: Analysis of whole tumoral and peri-tumoral tissue. Diagn Interv Imaging 2021; 102:287-295. [PMID: 33419692 DOI: 10.1016/j.diii.2020.12.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 12/04/2020] [Accepted: 12/09/2020] [Indexed: 01/02/2023]
Abstract
PURPOSE To prospectively investigate the capabilities of texture analysis (TA) based on apparent diffusion coefficient (ADC) map of the entire tumor volume and the whole volume of peri-tumoral edema, in discriminating between high-grade glioma (HGG) and low-grade glioma (LGG). MATERIALS AND METHODS A total of 33 patients with histopathological proven glioma were prospectively included. There were 20 men and 13 women with a mean age of 54.5±14.7 (standard deviation [SD]) years (range: 34-75years). TA parameters of whole tumor and peri-tumoral edema were extracted from the ADC map obtained with diffusion-weighted spin-echo echo-planar magnetic resonance imaging at 1.5-T. TA variables of HGG were compared to those of LGG. The optimum cut-off values of TA variables and their corresponding sensitivity, specificity and accuracy for differentiating between LGG and HGG were calculated using receiver operating characteristic curve analysis. RESULTS Mean and median tumoral ADC of HGG were significantly lower than those of LGG, at 1.23×10-3 mm2/s and 1.21×10-3 mm2/s cut-off values, yielding 70% sensitivity each (95% CI: 59-82% and 61-80%, respectively), 80% (95% CI: 79-98%) and 90% (95% CI: 82-97%) specificity, and 73% (95% CI: 66-91%) and 76% (95% CI: 72-90%) accuracy, respectively. Significant differences in tumoral and peri-tumoral kurtosis were found between HGG and LGG at 1.60 and 0.314 cut-off values yielding sensitivities of 74% (95% CI: 58-83%) and 70% (95% CI: 59-84%), specificities of 90% (95% CI: 80-95%) and 70% (95% CI: 64-83%) and accuracies of 79% (95% CI: 69-89%) and 70% (95% CI: 64-77%), respectively. CONCLUSION Measurements of whole tumoral and peri-tumoral TA, based on ADC maps, provide useful information that helps distinguish between HGG and LGG.
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Affiliation(s)
- Radwa K Soliman
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Assiut University Hospitals, Asyut 71515, Egypt.
| | - Abdelhakeem A Essa
- Department of Neurosurgery, Assiut University Hospitals, Assiut 71515, Egypt
| | - Ahmed A S Elhakeem
- Department of Pathology, Faculty of Medicine, Al-Azhar University, Assiut 71515, Egypt
| | - Sara A Gamal
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Assiut University Hospitals, Asyut 71515, Egypt
| | - Mohamed M A Zaitoun
- Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Zagazig University, Sharkia, Egypt
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Togao O, Chikui T, Tokumori K, Kami Y, Kikuchi K, Momosaka D, Kikuchi Y, Kuga D, Hata N, Mizoguchi M, Iihara K, Hiwatashi A. Gamma distribution model of diffusion MRI for the differentiation of primary central nerve system lymphomas and glioblastomas. PLoS One 2020; 15:e0243839. [PMID: 33315914 PMCID: PMC7737570 DOI: 10.1371/journal.pone.0243839] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 11/29/2020] [Indexed: 01/03/2023] Open
Abstract
The preoperative imaging-based differentiation of primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBs) is of high importance since the therapeutic strategies differ substantially between these tumors. In this study, we investigate whether the gamma distribution (GD) model is useful in this differentiation of PNCSLs and GBs. Twenty-seven patients with PCNSLs and 57 patients with GBs were imaged with diffusion-weighted imaging using 13 b-values ranging from 0 to 1000 sec/mm2. The shape parameter (κ) and scale parameter (θ) were obtained with the GD model. Fractions of three different areas under the probability density function curve (f1, f2, f3) were defined as follows: f1, diffusion coefficient (D) <1.0×10-3 mm2/sec; f2, D >1.0×10-3 and <3.0×10-3 mm2/sec; f3, D >3.0 × 10-3 mm2/sec. The GD model-derived parameters were compared between PCNSLs and GBs. Receiver operating characteristic (ROC) curve analyses were performed to assess diagnostic performance. The correlations with intravoxel incoherent motion (IVIM)-derived parameters were evaluated. The PCNSL group's κ (2.26 ± 1.00) was significantly smaller than the GB group's (3.62 ± 2.01, p = 0.0004). The PCNSL group's f1 (0.542 ± 0.107) was significantly larger than the GB group's (0.348 ± 0.132, p<0.0001). The PCNSL group's f2 (0.372 ± 0.098) was significantly smaller than the GB group's (0.508 ± 0.127, p<0.0001). The PCNSL group's f3 (0.086 ± 0.043) was significantly smaller than the GB group's (0.144 ± 0.062, p<0.0001). The combination of κ, f1, and f3 showed excellent diagnostic performance (area under the curve, 0.909). The f1 had an almost perfect inverse correlation with D. The f2 and f3 had very strong positive correlations with D and f, respectively. The GD model is useful for the differentiation of GBs and PCNSLs.
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Affiliation(s)
- Osamu Togao
- Department of Molecular Imaging & Diagnosis, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Toru Chikui
- Department of Oral and Maxillofacial Radiology, Faculty of Dental Science, Kyushu University, Fukuoka, Japan
| | - Kenji Tokumori
- Department of Clinical Radiology, Faculty of Medical Technology, Teikyo University, Fukuoka, Japan
| | - Yukiko Kami
- Department of Oral and Maxillofacial Radiology, Faculty of Dental Science, Kyushu University, Fukuoka, Japan
| | - Kazufumi Kikuchi
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Daichi Momosaka
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yoshitomo Kikuchi
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Daisuke Kuga
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Nobuhiro Hata
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Masahiro Mizoguchi
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Koji Iihara
- Department of Neurosurgery, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Akio Hiwatashi
- Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
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Bozdağ M, Er A, Çinkooğlu A, Ekmekçi S. Diagnostic role of apparent diffusion coefficient combined with intratumoral susceptibility signals in differentiating high-grade gliomas from brain metastases. Neuroradiol J 2020; 34:169-179. [PMID: 33307971 DOI: 10.1177/1971400920980164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE The aim of this study was to assess whether tumoral and peritumoral apparent diffusion coefficient values and intratumoral susceptibility signals on susceptibility-weighted imaging could distinguish between high-grade gliomas and brain metastases, and to investigate their associations with the Ki-67 proliferation index. MATERIALS AND METHODS Fifty-seven patients with pathologically confirmed diagnoses of either high-grade glioma or brain metastasis were enrolled in this study (23 with high-grade gliomas and 34 with brain metastases). The minimum and mean apparent diffusion coefficients in the enhancing tumoral region (ADCmin and ADCmean) and the minimum apparent diffusion coefficient in the peritumoral region (ADCedema) were measured from apparent diffusion coefficient maps, and intratumoral susceptibility signal grades acquired by susceptibility-weighted imaging were calculated. Ki-67 proliferation index values were obtained from the hospital database. These parameters were evaluated using the Mann-Whitney U test, independent-sample t-test, Spearman correlation analysis, receiver operating characteristic curve, and logistic regression analyses. RESULTS ADCmean, ADCmin values, and intratumoral susceptibility signal grades in brain metastases were significantly lower than those in high-grade gliomas (all p < 0.05). Ki-67 proliferation index values showed significant correlations with ADCmean, ADCmin, and intratumoral susceptibility signal grade in brain metastases (all p < 0.05), but no correlation was found in high-grade gliomas (all p > 0.05). According to receiver operating characteristic curve analysis, ADCmean achieved the highest diagnostic performance for discriminating high-grade gliomas from brain metastases. Furthermore, the combination of tumoral apparent diffusion coefficient parameters with intratumoral susceptibility signal grade provided a higher area under the curve than univariate parameters. CONCLUSION The combination of tumoral apparent diffusion coefficient with intratumoral susceptibility signal grade can offer better diagnostic performances for differential diagnosis. Apparent diffusion coefficient and intratumoral susceptibility signal may reflect cellular proliferative activity in brain metastases, but not in high-grade gliomas.
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Affiliation(s)
- Mustafa Bozdağ
- Department of Radiology, Tepecik Training and Research Hospital, Izmir, Turkey
| | - Ali Er
- Department of Radiology, Tepecik Training and Research Hospital, Izmir, Turkey
| | - Akın Çinkooğlu
- Department of Radiology, Faculty of Medicine, Ege University, Izmir, Turkey
| | - Sümeyye Ekmekçi
- Department of Pathology, Tepecik Training and Research Hospital, Izmir, Turkey
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22
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Zhang Y, Wang J. Research progress on radiotherapy technology and dose fraction scheme for advanced gliomas. Transl Cancer Res 2020; 9:7642-7651. [PMID: 35117363 PMCID: PMC8799171 DOI: 10.21037/tcr-20-1891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 08/28/2020] [Indexed: 11/06/2022]
Abstract
Glioma is the most common central malignant tumor. High-grade glioma (HGG) has high malignancy and a short median survival. Complete surgical resection and comprehensive treatment with postoperative radiotherapy and chemotherapy is the recommended treatment for HGGs at present in clinic. Postoperative radiotherapy can reduce the local recurrence rate and prolong the survival time of patients. In recent years, researchers have made some progress on different radiotherapy technologies and dose fraction schemes. With the continuous development of medical technology, different groups of people should choose different dose fraction schemes, in order to realize the individualization of treatment schemes, and provide more benefits to patients. At present, the optimal radiotherapy dose, the fraction model, and how to achieve individualized radiotherapy remains unclear. In view of the poor prognosis of this disease, patients should be encouraged to participate in properly conducted experimental studies.
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Affiliation(s)
- Yu Zhang
- Department of Radiation Oncology, Peking University International Hospital, Beijing, China
| | - Junjie Wang
- Department of Radiation Oncology, Peking University Third Hospital, Beijing, China
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Csutak C, Ștefan PA, Lenghel LM, Moroșanu CO, Lupean RA, Șimonca L, Mihu CM, Lebovici A. Differentiating High-Grade Gliomas from Brain Metastases at Magnetic Resonance: The Role of Texture Analysis of the Peritumoral Zone. Brain Sci 2020; 10:brainsci10090638. [PMID: 32947822 PMCID: PMC7565295 DOI: 10.3390/brainsci10090638] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 09/03/2020] [Accepted: 09/14/2020] [Indexed: 11/16/2022] Open
Abstract
High-grade gliomas (HGGs) and solitary brain metastases (BMs) have similar imaging appearances, which often leads to misclassification. In HGGs, the surrounding tissues show malignant invasion, while BMs tend to displace the adjacent area. The surrounding edema produced by the two cannot be differentiated by conventional magnetic resonance (MRI) examinations. Forty-two patients with pathology-proven brain tumors who underwent conventional pretreatment MRIs were retrospectively included (HGGs, n = 16; BMs, n = 26). Texture analysis of the peritumoral zone was performed on the T2-weighted sequence using dedicated software. The most discriminative texture features were selected using the Fisher and the probability of classification error and average correlation coefficients. The ability of texture parameters to distinguish between HGGs and BMs was evaluated through univariate, receiver operating, and multivariate analyses. The first percentile and wavelet energy texture parameters were independent predictors of HGGs (75–87.5% sensitivity, 53.85–88.46% specificity). The prediction model consisting of all parameters that showed statistically significant results at the univariate analysis was able to identify HGGs with 100% sensitivity and 66.7% specificity. Texture analysis can provide a quantitative description of the peritumoral zone encountered in solitary brain tumors, that can provide adequate differentiation between HGGs and BMs.
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Affiliation(s)
- Csaba Csutak
- Radiology and Imaging Department, County Emergency Hospital, Cluj-Napoca, Clinicilor Street, Number 5, Cluj-Napoca, 400006 Cluj, Romania; (C.C.); (L.M.L.); (C.M.M.); (A.L.)
- Radiology, Surgical Specialties Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, Clinicilor Street, number 3–5, Cluj-Napoca, 400006 Cluj, Romania
| | - Paul-Andrei Ștefan
- Radiology and Imaging Department, County Emergency Hospital, Cluj-Napoca, Clinicilor Street, Number 5, Cluj-Napoca, 400006 Cluj, Romania; (C.C.); (L.M.L.); (C.M.M.); (A.L.)
- Anatomy and Embryology, Morphological Sciences Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, Victor Babeș Street, number 8, Cluj-Napoca, 400012 Cluj, Romania
- Correspondence: ; Tel.: +40-743-957-206
| | - Lavinia Manuela Lenghel
- Radiology and Imaging Department, County Emergency Hospital, Cluj-Napoca, Clinicilor Street, Number 5, Cluj-Napoca, 400006 Cluj, Romania; (C.C.); (L.M.L.); (C.M.M.); (A.L.)
- Radiology, Surgical Specialties Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, Clinicilor Street, number 3–5, Cluj-Napoca, 400006 Cluj, Romania
| | - Cezar Octavian Moroșanu
- Department of Neurosurgery, North Bristol Trust, Southmead Hospital, Southmead Road, Westbury on Trym, Bristol BS2 8BJ, UK;
| | - Roxana-Adelina Lupean
- Histology, Morphological Sciences Department, “Iuliu Hațieganu” University of Medicine and Pharmacy, Louis Pasteur Street, number 4, Cluj-Napoca, 400349 Cluj, Romania;
| | - Larisa Șimonca
- Department of Paediatric Surgery, Bristol Royal Hospital for Children, Upper Maudlin Street, Bristol BS2 8BJ, UK;
| | - Carmen Mihaela Mihu
- Radiology and Imaging Department, County Emergency Hospital, Cluj-Napoca, Clinicilor Street, Number 5, Cluj-Napoca, 400006 Cluj, Romania; (C.C.); (L.M.L.); (C.M.M.); (A.L.)
- Histology, Morphological Sciences Department, “Iuliu Hațieganu” University of Medicine and Pharmacy, Louis Pasteur Street, number 4, Cluj-Napoca, 400349 Cluj, Romania;
| | - Andrei Lebovici
- Radiology and Imaging Department, County Emergency Hospital, Cluj-Napoca, Clinicilor Street, Number 5, Cluj-Napoca, 400006 Cluj, Romania; (C.C.); (L.M.L.); (C.M.M.); (A.L.)
- Radiology, Surgical Specialties Department, “Iuliu Haţieganu” University of Medicine and Pharmacy, Clinicilor Street, number 3–5, Cluj-Napoca, 400006 Cluj, Romania
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Kumar R, Kala P, Narayanan GS, Vishwanathan B, Narayanan S, Mandal S, Rao A, Gowda G. Evaluation and evolution of apparent diffusion coefficient (ADC) in image-guided adaptive brachytherapy (IGABT) for cervical cancer. Brachytherapy 2020; 20:112-117. [PMID: 32928683 DOI: 10.1016/j.brachy.2020.07.014] [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: 05/06/2020] [Revised: 07/21/2020] [Accepted: 07/23/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE Image-guided adaptive brachytherapy (IGABT) recently has shown excellent clinical outcomes with superior local control and less toxicity. For IGABT, T2W (T2-weighted) MRI is the gold standard. However, studies have shown that target delineation with the same results in uncertainties, poor interobserver variabilities, and low conformity indices for high-risk clinical target volume contours. In this study, we investigate the role of diffusion-weighted imaging-derived apparent diffusion coefficient (ADC) maps to aid in IGABT. We also evaluated ADC from the baseline to brachytherapy. METHODS AND MATERIALS Thirty selected patients were enrolled for this study, and two MRIs were taken at diagnosis and before brachytherapy. Patients were divided into two groups, Group 1 being patients with parametrial involvement before external beam radiotherapy and no parametrial involvement before brachytherapy. Group 2 included patients with parametrial involvement before external beam radiotherapy and persistent parametrial involvement before brachytherapy. ADC was measured at the center, edge, and 1 cm from the edge. RESULTS The measured ADC increased from diagnosis to brachytherapy, and this increase was more for the patients in Group 1 than in Group 2. The mean TDadc (diagnosis ADC, center), TEadc (tumor edge ADC diagnosis), and T1cmDadc (1 cm from edge at diagnosis) were 0.884, 1.45, and 1.9 × 10-3 mm2/s, respectively. The TBadc (ADC at brachytherapy, center), TEBadc (tumor edge ADC at brachytherapy), and TE1cmBadc (1 cm from edge brachytherapy) were 1.2, 1.8, and 2.3 × 10-3 mm2/s, respectively, p-value <0.00001. No abnormal ADC was present outside the high-risk clinical target volume contours. CONCLUSION MRI-based IGABT using T2W imaging essentially covers all functionally abnormal zones at brachytherapy. Diffusion-weighted imaging, along with ADC maps, should only be used as a supplement for target delineation.
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Affiliation(s)
- Rishabh Kumar
- Department Radiation Oncology, Vydehi Institute of Medical Sciences, Bangalore, Karnataka, India.
| | - Prachi Kala
- Department of Radiology, Vydehi Institute of Medical Sciences, Bangalore, Karnataka, India
| | - Geeta S Narayanan
- Department Radiation Oncology, Vydehi Institute of Medical Sciences, Bangalore, Karnataka, India
| | - Bhaskar Vishwanathan
- Department Radiation Oncology, Vydehi Institute of Medical Sciences, Bangalore, Karnataka, India
| | - Sowmya Narayanan
- Department of Radiation Oncology and Radiation Physics, Chief Medical Physicist, Vydehi Institute of Medical Sciences, Bangalore, Karnataka, India
| | - Sanjeet Mandal
- Department Radiation Oncology, Vydehi Institute of Medical Sciences, Bangalore, Karnataka, India
| | - Arpitha Rao
- Department Radiation Oncology, Vydehi Institute of Medical Sciences, Bangalore, Karnataka, India
| | - Gangadharappa Gowda
- Department of Radiology, Vydehi Institute of Medical Sciences, Bangalore, Karnataka, India
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25
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The Utility of Diffusion and Perfusion Magnetic Resonance Imaging in Target Delineation of High-Grade Gliomas. BIOMED RESEARCH INTERNATIONAL 2020; 2020:8718097. [PMID: 32851090 PMCID: PMC7439164 DOI: 10.1155/2020/8718097] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 03/22/2020] [Accepted: 07/21/2020] [Indexed: 02/01/2023]
Abstract
Background The tumor volume of high-grade glioma (HGG) after surgery is usually determined by contrast-enhanced MRI (CE-MRI), but the clinical target volume remains controversial. Functional magnetic resonance imaging (multimodality MRI) techniques such as magnetic resonance perfusion-weighted imaging (PWI) and diffusion-tensor imaging (DTI) can make up for CE-MRI. This study explored the survival outcomes and failure patterns of patients with HGG by comparing the combination of multimodality MRI and CE-MRI imaging with CE-MRI alone. Methods 102 patients with postoperative HGG between 2012 and 2016 were included. 50 were delineated based on multimodality MRI (PWI, DTI) and CE-MRI (enhanced T1), and the other 52 were delineated based on CE-MRI as control. Results The median survival benefit was 6 months. The 2-year overall survival, progression-free survival, and local-regional control rates were 48% vs. 25%, 42% vs. 13.46%, and 40% vs. 13.46% for the multimodality MRI and CE-MRI cohorts, respectively. The two cohorts had similar rates of disease progression and recurrence but different proportions of failure patterns. The univariate analysis shows that characteristics of patients such as combined with epilepsy, the dose of radiotherapy, the selection of MRI were significant influence factors for 2-year overall survival. However, in multivariate analyses, only the selection of MRI was an independent significant predictor of overall survival. Conclusions This study was the first to explore the clinical value of multimodality MRI in the delineation of radiotherapy target volume for HGG. The conclusions of the study have positive reference significance to the combination of multimodality MRI and CE-MRI in guiding the delineation of the radiotherapy target area for HGG patients.
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26
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Mahammedi A, Bachir S, Escott EJ, Barnett GH, Mohammadi AM, Larvie M. Prediction of recurrent glioblastoma after laser interstitial thermal therapy: The role of diffusion imaging. Neurooncol Adv 2020; 1:vdz021. [PMID: 32642657 PMCID: PMC7212867 DOI: 10.1093/noajnl/vdz021] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background Evaluate the utility of diffusion-weighted imaging (DWI) for the assessment of local recurrence of glioblastoma (GBM) on imaging performed 24 h following MRI-guided laser interstitial thermal therapy (LITT). We hypothesize that microscopic peritumoral infiltration correlates with early subtle variations on DWI images and apparent diffusion coefficient (ADC) maps. Methods Of 64 patients with GBM treated with LITT, 39 had MRI scans within 24 h after undergoing LITT. Patterns on DWI images and ADC maps 24 h following LITT were correlated with areas of future GBM recurrence identified through coregistration of subsequent MRI examinations. In the areas of suspected recurrence within the periphery of post-LITT lesions, signal intensity values on ADC maps were recorded and compared with the remaining peritumoral ring. Results Thirty-nine patients with GBM met the inclusion criteria. For predicting recurrent GBM, areas of decreased DWI signal and increased signal on ADC maps within the expected peritumoral ring of restricted diffusion identified 24 h following LITT showed 86.1% sensitivity, 75.2% specificity, and high correlation (r = 0.53) with future areas of GBM recurrence (P < .01). Areas of future recurrence demonstrated a 37% increase in the ADC value (P < .001), compared with findings in the surrounding treated peritumoral region. A significantly greater area under the receiver operating characteristics curve was determined for ADC values (P < .01). Conclusions DWI obtained 24 h following LITT can help predict the location of GBM recurrence months before the development of abnormal enhancement. This may alter future treatment planning, perhaps suggesting areas that may be targeted for additional therapy.
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Affiliation(s)
| | - Suha Bachir
- Department of Pediatrics and Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
| | - Edward J Escott
- Department of Radiology, University of Kentucky, Lexington, Kentucky
| | - Gene H Barnett
- Department of Neurosurgery, Cleveland Clinic, Cleveland, Ohio.,Department of Neurosurgery, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio
| | - Alireza M Mohammadi
- Department of Neurosurgery, Cleveland Clinic, Cleveland, Ohio.,Department of Neurosurgery, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio
| | - Mykol Larvie
- Department of Radiology, Cleveland Clinic, Cleveland, Ohio
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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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28
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Zhang P, Liu B. Differentiation among Glioblastomas, Primary Cerebral Lymphomas, and Solitary Brain Metastases Using Diffusion-Weighted Imaging and Diffusion Tensor Imaging: A PRISMA-Compliant Meta-analysis. ACS Chem Neurosci 2020; 11:477-483. [PMID: 31922391 DOI: 10.1021/acschemneuro.9b00698] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Previous studies showed a high diagnostic value of diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) in differentiation among glioblastomas, primary cerebral lymphomas (PCLs), and solitary brain metastases, whereas other studies reported a low or no diagnostic value of DWI and DTI in differentiation among the three types of brain malignant tumors. In order to enhance the strength of evidence, meta-analysis was conducted to summarize results of studies evaluating the diagnostic values of DWI or DTI in differentiation among the three types of brain malignant tumors. Articles evaluating the diagnostic values of DWI or DTI in differentiation among the three types of tumors and published before December 2019 were searched in databases (PubMed, Medline, Web of Science, EMBASE, and Google Scholar). A summary of sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratio (DOR) were calculated from the true positive (TP), true negative (TN), false positive (FP), and false negative (FN) of each study using STATA 12.0 software and Meta-Disc Version 1.4. In addition, the summary receive-operating characteristic (SROC) curve was constructed. Ultimately, we included 19 diagnostic studies (including 735 glioblastomas patients, 31 PCLs patients, and 792 patients with solitary brain metastases). Regarding differentiation between glioblastomas and solitary brain metastases using DWI or DTI, the calculated pooled parameters were as follows: sensitivity, 0.84 [95% confidence interval (CI): 0.78-0.89]; specificity, 0.88 (95% CI: 0.83-0.92); PLR, 7.2 (95% CI: 4.6-11.3); NLR, 0.18 (95% CI: 0.12-0.27); and DOR, 41 (95% CI: 18-93). The analysis showed a significant heterogeneity (sensitivity, I2 = 91.31%, p < 0.01; specificity, I2 = 89.24%, p < 0.01). In conclusion, DWI and DTI showed a moderate diagnostic value for differentiating glioblastomas from solitary brain metastasis. Additionally, large-scale prospective studies are essential to explore differentiation between PCLs and solitary brain metastases using DWI or DTI.
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Affiliation(s)
- Pengcheng Zhang
- State Key Laboratory of Proteomics, Academy of Military Medical Sciences, Academy of Military Sciences, Beijing 100071, China
- Laboratory of Oncology, Fifth Medical Center, General Hospital of PLA, Beijing 100071, China
| | - Bing Liu
- State Key Laboratory of Proteomics, Academy of Military Medical Sciences, Academy of Military Sciences, Beijing 100071, China
- Laboratory of Oncology, Fifth Medical Center, General Hospital of PLA, Beijing 100071, China
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29
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Ko CC, Chen TY, Lim SW, Kuo YT, Wu TC, Chen JH. Prediction of recurrence in solid nonfunctioning pituitary macroadenomas: additional benefits of diffusion-weighted MR imaging. J Neurosurg 2020; 132:351-359. [PMID: 30717054 DOI: 10.3171/2018.10.jns181783] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 10/01/2018] [Indexed: 12/22/2022]
Abstract
OBJECTIVE A subset of benign, nonfunctioning pituitary macroadenomas (NFMAs) has been shown to undergo early progression/recurrence (P/R) during the first years after surgical resection. The aim of this study was to determine preoperative MR imaging features for the prediction of P/R in benign solid NFMAs, with emphasis on apparent diffusion coefficient (ADC) values. METHODS We retrospectively investigated the preoperative MR imaging features for the prediction of P/R in benign solid NFMAs. Only the patients who had undergone preoperative MRI and postoperative MRI follow-ups for more than 1 year (at least every 6-12 months) were included. From November 2010 to December 2016, a total of 30 patients diagnosed with benign solid NFMAs were included (median follow-up time 45 months), and 19 (63.3%) patients had P/R (median time to P/R 24 months). RESULTS Benign solid NFMAs with cavernous sinus invasion, failed chiasmatic decompression, large tumor height and tumor volume, high diffusion-weighted imaging (DWI) signal, and lower ADC values/ratios were significantly associated with P/R (p < 0.05). The cutoff points of ADC value and ADC ratio for prediction of P/R are 0.77 × 10-3 mm2/sec and 1.01, respectively, with area under the curve (AUC) values (0.9 and 0.91) (p < 0.01). In multivariate Cox proportional hazards analysis, low ADC value (< 0.77 × 10-3 mm2/sec) is a high-risk factor of P/R (p < 0.05) with a hazard ratio of 14.07. CONCLUSIONS Benign solid NFMAs with low ADC values/ratios are at a significantly increased risk of P/R, and aggressive treatments accompanied by close follow-up with imaging studies should be considered.
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Affiliation(s)
- Ching-Chung Ko
- 1Section of Neuroradiology, Department of Medical Imaging, Chi-Mei Medical Center, Tainan
| | - Tai-Yuan Chen
- 1Section of Neuroradiology, Department of Medical Imaging, Chi-Mei Medical Center, Tainan
- 2Graduate Institute of Medical Sciences, Chang Jung Christian University, Tainan
| | - Sher-Wei Lim
- 3Department of Neurosurgery, Chi-Mei Medical Center, Chiali, Tainan
- 4Department of Nursing, Min-Hwei College of Health Care Management, Tainan
| | - Yu-Ting Kuo
- 1Section of Neuroradiology, Department of Medical Imaging, Chi-Mei Medical Center, Tainan
- 5Department of Radiology, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung
| | - Te-Chang Wu
- 1Section of Neuroradiology, Department of Medical Imaging, Chi-Mei Medical Center, Tainan
- 6Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei
| | - Jeon-Hor Chen
- 7Department of Radiology, E-DA Hospital, E-DA Cancer Hospital, I-Shou University, Kaohsiung, Taiwan; and
- 8Center for Functional Onco-Imaging of Radiological Sciences, School of Medicine, University of California, Irvine, California
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30
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The Diagnostic Value of the Apparent Diffusion Coefficient Values Derived from Magnetic Resonance Imaging and Diffusion-Weighted Imaging in Differentiating the Types of Metastatic Brain Tumors. INTERNATIONAL JOURNAL OF CANCER MANAGEMENT 2020. [DOI: 10.5812/ijcm.95813] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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Ma S, Nguyen CT, Han F, Wang N, Deng Z, Binesh N, Moser FG, Christodoulou AG, Li D. Three-dimensional simultaneous brain T 1 , T 2 , and ADC mapping with MR Multitasking. Magn Reson Med 2019; 84:72-88. [PMID: 31765496 DOI: 10.1002/mrm.28092] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 10/01/2019] [Accepted: 10/31/2019] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop a simultaneous T1 , T2 , and ADC mapping method that provides co-registered, distortion-free images and enables multiparametric quantification of 3D brain coverage in a clinically feasible scan time with the MR Multitasking framework. METHODS The T1 /T2 /diffusion weighting was generated by a series of T2 preparations and diffusion preparations. The underlying multidimensional image containing 3 spatial dimensions, 1 T1 weighting dimension, 1 T2 -preparation duration dimension, 1 b-value dimension, and 1 diffusion direction dimension was modeled as a 5-way low-rank tensor. A separate real-time low-rank model incorporating time-resolved phase correction was also used to compensate for both inter-shot and intra-shot phase inconsistency induced by physiological motion. The proposed method was validated on both phantom and 16 healthy subjects. The quantification of T1 /T2 /ADC was evaluated for each case. Three post-surgery brain tumor patients were scanned for demonstration of clinical feasibility. RESULTS Multitasking T1 /T2 /ADC maps were perfectly co-registered and free from image distortion. Phantom studies showed substantial quantitative agreement ( R 2 = 0.999 ) with reference protocols for T1 /T2 /ADC. In vivo studies showed nonsignificant T1 (P = .248), T2 (P = .97), ADC (P = .328) differences among the frontal, parietal, and occipital regions. Although Multitasking showed significant differences of T1 (P = .03), T2 (P < .001), and ADC (P = .001) biases against the references, the mean bias estimates were small (ΔT1 % < 5%, ΔT2 % < 7%, ΔADC% < 5%), with all intraclass correlation coefficients greater than 0.82 indicating "excellent" agreement. Patient studies showed that Multitasking T1 /T2 /ADC maps were consistent with the clinical qualitative images. CONCLUSION The Multitasking approach simultaneously quantifies T1 /T2 /ADC with substantial agreement with the references and is promising for clinical applications.
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Affiliation(s)
- Sen Ma
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Christopher T Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts
| | - Fei Han
- Siemens Healthcare, Los Angeles, California
| | - Nan Wang
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Zixin Deng
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Nader Binesh
- S. Mark Taper Foundation Imaging Center, Cedars-Sinai Medical Center, Los Angeles, California
| | - Franklin G Moser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California
| | | | - Debiao Li
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
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32
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Zeiner PS, Kinzig M, Divé I, Maurer GD, Filipski K, Harter PN, Senft C, Bähr O, Hattingen E, Steinbach JP, Sörgel F, Voss M, Steidl E, Ronellenfitsch MW. Regorafenib CSF Penetration, Efficacy, and MRI Patterns in Recurrent Malignant Glioma Patients. J Clin Med 2019; 8:jcm8122031. [PMID: 31766326 PMCID: PMC6947028 DOI: 10.3390/jcm8122031] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 10/28/2019] [Accepted: 11/18/2019] [Indexed: 12/13/2022] Open
Abstract
(1) Background: The phase 2 Regorafenib in Relapsed Glioblastoma (REGOMA) trial indicated a survival benefit for patients with first recurrence of a glioblastoma when treated with the multikinase inhibitor regorafenib (REG) instead of lomustine. The aim of this retrospective study was to investigate REG penetration to cerebrospinal fluid (CSF), treatment efficacy, and effects on magnetic resonance imaging (MRI) in patients with recurrent high-grade gliomas. (2) Methods: Patients were characterized by histology, adverse events, steroid treatment, overall survival (OS), and MRI growth pattern. REG and its two active metabolites were quantified by liquid chromatography/tandem mass spectrometry in patients’ serum and CSF. (3) Results: 21 patients mainly with IDH-wildtype glioblastomas who had been treated with REG were retrospectively identified. Thirteen CFS samples collected from 3 patients of the cohort were available for pharmacokinetic testing. CSF levels of REG and its metabolites were significantly lower than in serum. Follow-up MRI was available in 19 patients and showed progressive disease (PD) in all but 2 patients. Two distinct MRI patterns were identified: 7 patients showed classic PD with progression of contrast enhancing lesions, whereas 11 patients showed a T2-dominant MRI pattern characterized by a marked reduction of contrast enhancement. Median OS was significantly better in patients with a T2-dominant growth pattern (10 vs. 27 weeks respectively, p = 0.003). Diffusion restrictions were observed in 13 patients. (4) Conclusion: REG and its metabolites were detectable in CSF. A distinct MRI pattern that might be associated with an improved OS was observed in half of the patient cohort. Treatment response in the total cohort was poor.
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Affiliation(s)
- Pia S. Zeiner
- Dr. Senckenberg Institute of Neurooncology, University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany; (P.S.Z.); (I.D.); (G.D.M.); (O.B.); (J.P.S.); (M.V.)
- University Cancer Center (UCT) Frankfurt, University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany; (K.F.); (P.N.H.); (E.H.); (E.S.)
- German Cancer Consortium (DKTK), 60590 Frankfurt am Main, Germany
- Frankfurt Cancer Institute (FCI), University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany
| | - Martina Kinzig
- IBMP—Institute for Biomedical and Pharmaceutical Research, 90562 Nürnberg-Heroldsberg, Germany; (M.K.); (F.S.)
| | - Iris Divé
- Dr. Senckenberg Institute of Neurooncology, University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany; (P.S.Z.); (I.D.); (G.D.M.); (O.B.); (J.P.S.); (M.V.)
- University Cancer Center (UCT) Frankfurt, University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany; (K.F.); (P.N.H.); (E.H.); (E.S.)
- German Cancer Consortium (DKTK), 60590 Frankfurt am Main, Germany
- Frankfurt Cancer Institute (FCI), University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany
| | - Gabriele D. Maurer
- Dr. Senckenberg Institute of Neurooncology, University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany; (P.S.Z.); (I.D.); (G.D.M.); (O.B.); (J.P.S.); (M.V.)
- University Cancer Center (UCT) Frankfurt, University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany; (K.F.); (P.N.H.); (E.H.); (E.S.)
| | - Katharina Filipski
- University Cancer Center (UCT) Frankfurt, University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany; (K.F.); (P.N.H.); (E.H.); (E.S.)
- German Cancer Consortium (DKTK), 60590 Frankfurt am Main, Germany
- Institute of Neurology (Edinger-Institute), University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany
| | - Patrick N. Harter
- University Cancer Center (UCT) Frankfurt, University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany; (K.F.); (P.N.H.); (E.H.); (E.S.)
- German Cancer Consortium (DKTK), 60590 Frankfurt am Main, Germany
- Frankfurt Cancer Institute (FCI), University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany
- Institute of Neurology (Edinger-Institute), University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany
| | - Christian Senft
- Department of Neurosurgery, University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany;
| | - Oliver Bähr
- Dr. Senckenberg Institute of Neurooncology, University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany; (P.S.Z.); (I.D.); (G.D.M.); (O.B.); (J.P.S.); (M.V.)
- Department of Neurology, Klinikum Aschaffenburg-Alzenau, 63739 Aschaffenburg, Germany
| | - Elke Hattingen
- University Cancer Center (UCT) Frankfurt, University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany; (K.F.); (P.N.H.); (E.H.); (E.S.)
- German Cancer Consortium (DKTK), 60590 Frankfurt am Main, Germany
- Department of Neuroradiology, University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany
| | - Joachim P. Steinbach
- Dr. Senckenberg Institute of Neurooncology, University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany; (P.S.Z.); (I.D.); (G.D.M.); (O.B.); (J.P.S.); (M.V.)
- University Cancer Center (UCT) Frankfurt, University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany; (K.F.); (P.N.H.); (E.H.); (E.S.)
- German Cancer Consortium (DKTK), 60590 Frankfurt am Main, Germany
- Frankfurt Cancer Institute (FCI), University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany
| | - Fritz Sörgel
- IBMP—Institute for Biomedical and Pharmaceutical Research, 90562 Nürnberg-Heroldsberg, Germany; (M.K.); (F.S.)
- Institute of Pharmacology, University Duisburg-Essen, 45141 Essen, Germany
| | - Martin Voss
- Dr. Senckenberg Institute of Neurooncology, University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany; (P.S.Z.); (I.D.); (G.D.M.); (O.B.); (J.P.S.); (M.V.)
- University Cancer Center (UCT) Frankfurt, University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany; (K.F.); (P.N.H.); (E.H.); (E.S.)
- German Cancer Consortium (DKTK), 60590 Frankfurt am Main, Germany
- Frankfurt Cancer Institute (FCI), University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany
| | - Eike Steidl
- University Cancer Center (UCT) Frankfurt, University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany; (K.F.); (P.N.H.); (E.H.); (E.S.)
- German Cancer Consortium (DKTK), 60590 Frankfurt am Main, Germany
- Department of Neuroradiology, University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany
| | - Michael W. Ronellenfitsch
- Dr. Senckenberg Institute of Neurooncology, University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany; (P.S.Z.); (I.D.); (G.D.M.); (O.B.); (J.P.S.); (M.V.)
- University Cancer Center (UCT) Frankfurt, University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany; (K.F.); (P.N.H.); (E.H.); (E.S.)
- German Cancer Consortium (DKTK), 60590 Frankfurt am Main, Germany
- Frankfurt Cancer Institute (FCI), University Hospital Frankfurt, Goethe University, 60590 Frankfurt am Main, Germany
- Correspondence: ; Tel.: +49-69-6301-87711; Fax: +49-69-6301-87713
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Discrimination Between Solitary Brain Metastasis and Glioblastoma Multiforme by Using ADC-Based Texture Analysis: A Comparison of Two Different ROI Placements. Acad Radiol 2019; 26:1466-1472. [PMID: 30770161 DOI: 10.1016/j.acra.2019.01.010] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 01/05/2019] [Accepted: 01/15/2019] [Indexed: 12/22/2022]
Abstract
RATIONALE AND OBJECTIVES To explore the value of texture analysis based on the apparent diffusion coefficient (ADC) value and the effect of region of interest (ROI) placements in distinguishing glioblastoma multiforme (GBM) from solitary brain metastasis (sMET). MATERIALS AND METHODS Sixty-two patients with pathologically confirmed GBM (n = 36) and sMET (n = 26) were retrospectively included. All patients underwent diffusion-weighted imaging with b values of 0 and 1000 s/mm2, and the ADC maps were generated automatically. ROIs were placed on the largest whole single-slice tumor (ROI1) and the enhanced solid portion (ROI2) of the ADC maps, respectively. The texture feature metrics of the histogram and gray-level co-occurrence matrix were then extracted by using in-house software. The parameters of the texture analysis were compared between GBM and sMET, using the Mann-Whitney U test. A receiver operating characteristic (ROC) curve analysis was performed to determine the best parameters for distinguishing between GBM from sMET. RESULTS Homogeneity and the inverse difference moment (IDM) of GBM were significantly higher than those of sMET in both ROIs (ROI1, p = 0.014 for homogeneity and p = 0.048 for IDM; ROI2, p< 0.001 for homogeneity and p = 0.029 for IDM). According to the ROC curve analysis, the area under the ROC curve (AUC) of homogeneity in ROI1 (AUC, 0.682, sensitivity, 72.2%, specificity, 61.5%) was significantly lower than that of ROI2 (AUC, 0.886, sensitivity, 83.3%, specificity, 76.9%; p= 0.012), whereas the IDM showed no statistical significance between two ROIs (p> 0.05). CONCLUSION The ADC-based texture analysis can help differentiate GBM from sMET, and the ROI on the solid portion would be recommended to calculate the ADC-based texture metrics.
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Zaccagna F, Riemer F, Priest AN, McLean MA, Allinson K, Grist JT, Dragos C, Matys T, Gillard JH, Watts C, Price SJ, Graves MJ, Gallagher FA. Non-invasive assessment of glioma microstructure using VERDICT MRI: correlation with histology. Eur Radiol 2019; 29:5559-5566. [PMID: 30888488 PMCID: PMC6719328 DOI: 10.1007/s00330-019-6011-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 11/28/2018] [Accepted: 12/17/2018] [Indexed: 12/29/2022]
Abstract
PURPOSE This prospective study evaluated the use of vascular, extracellular and restricted diffusion for cytometry in tumours (VERDICT) MRI to investigate the tissue microstructure in glioma. VERDICT-derived parameters were correlated with both histological features and tumour subtype and were also used to explore the peritumoural region. METHODS Fourteen consecutive treatment-naïve patients (43.5 years ± 15.1 years, six males, eight females) with suspected glioma underwent diffusion-weighted imaging including VERDICT modelling. Tumour cell radius and intracellular and combined extracellular/vascular volumes were estimated using a framework based on linearisation and convex optimisation. An experienced neuroradiologist outlined the peritumoural oedema, enhancing tumour and necrosis on T2-weighted imaging and contrast-enhanced T1-weighted imaging. The same regions of interest were applied to the co-registered VERDICT maps to calculate the microstructure parameters. Pathology sections were analysed with semi-automated software to measure cellularity and cell size. RESULTS VERDICT parameters were successfully calculated in all patients. The imaging-derived results showed a larger intracellular volume fraction in high-grade glioma compared to low-grade glioma (0.13 ± 0.07 vs. 0.08 ± 0.02, respectively; p = 0.05) and a trend towards a smaller extracellular/vascular volume fraction (0.88 ± 0.07 vs. 0.92 ± 0.04, respectively; p = 0.10). The conventional apparent diffusion coefficient was higher in low-grade gliomas compared to high-grade gliomas, but this difference was not statistically significant (1.22 ± 0.13 × 10-3 mm2/s vs. 0.98 ± 0.38 × 10-3 mm2/s, respectively; p = 0.18). CONCLUSION This feasibility study demonstrated that VERDICT MRI can be used to explore the tissue microstructure of glioma using an abbreviated protocol. The VERDICT parameters of tissue structure correlated with those derived on histology. The method shows promise as a potential test for diagnostic stratification and treatment response monitoring in the future. KEY POINTS • VERDICT MRI is an advanced diffusion technique which has been correlated with histopathological findings obtained at surgery from patients with glioma in this study. • The intracellular volume fraction measured with VERDICT was larger in high-grade tumours compared to that in low-grade tumours. • The results were complementary to measurements from conventional diffusion-weighted imaging, and the technique could be performed in a clinically feasible timescale.
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Affiliation(s)
- Fulvio Zaccagna
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.
| | - Frank Riemer
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Andrew N Priest
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Mary A McLean
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Kieren Allinson
- Department of Pathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - James T Grist
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Carmen Dragos
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Tomasz Matys
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Jonathan H Gillard
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Colin Watts
- Institute of Cancer and Genomic Sciences, Birmingham Brain Cancer Program, University of Birmingham, Birmingham, UK
| | - Stephen J Price
- Neurosurgery Unit, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Martin J Graves
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
| | - Ferdia A Gallagher
- Department of Radiology, School of Clinical Medicine, University of Cambridge, Box 218, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK
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Scherer M, Jungk C, Götz M, Kickingereder P, Reuss D, Bendszus M, Maier-Hein K, Unterberg A. Early postoperative delineation of residual tumor after low-grade glioma resection by probabilistic quantification of diffusion-weighted imaging. J Neurosurg 2019; 130:2016-2024. [PMID: 30052158 DOI: 10.3171/2018.2.jns172951] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 02/23/2018] [Indexed: 12/25/2022]
Abstract
OBJECTIVE In WHO grade II low-grade gliomas (LGGs), early postoperative MRI (epMRI) may overestimate residual tumor on FLAIR sequences. Consequently, MRI at 3-6 months follow-up (fuMRI) is used for delineation of residual tumor. This study sought to evaluate if integration of apparent diffusion coefficient (ADC) maps permits an accurate estimation of residual tumor early on epMRI. METHODS From a consecutive cohort, 43 cases with an initial surgery for an LGG, and complete epMRI (< 72 hours after resection) and fuMRI including ADC maps, were retrospectively identified. Residual FLAIR hyperintense tumor was manually segmented on epMRI and corresponding ADC maps were coregistered. Using an expectation maximization algorithm, residual tumor segments were probabilistically clustered into areas of residual tumor, ischemia, or normal white matter (NWM) by fitting a mixture model of superimposed Gaussian curves to the ADC histogram. Tumor volumes from epMRI, clustering, and fuMRI were statistically compared and agreement analysis was performed. RESULTS Mean FLAIR hyperintensity suggesting residual tumor was significantly larger on epMRI compared to fuMRI (19.4 ± 16.5 ml vs 8.4 ± 10.2 ml, p < 0.0001). Probabilistic clustering of corresponding ADC histograms on epMRI identified subsegments that were interpreted as mean residual tumor (7.6 ± 10.2 ml), ischemia (8.1 ± 5.9 ml), and NWM (3.7 ± 4.9 ml). Therefore, mean tumor quantification error between epMRI and fuMRI was significantly reduced (11.0 ± 10.6 ml vs -0.8 ± 3.7 ml, p < 0.0001). Mean clustered tumor volumes on epMRI were no longer significantly different from the fuMRI reference (7.6 ± 10.2 ml vs 8.4 ± 10.2 ml, p = 0.16). Correlation (Pearson r = 0.96, p < 0.0001), concordance correlation coefficient (0.89, 95% confidence interval 0.83), and Bland-Altman analysis suggested strong agreement between both measures after clustering. CONCLUSIONS Probabilistic segmentation of ADC maps facilitates accurate assessment of residual tumor within 72 hours after LGG resection. Multiparametric image analysis detected FLAIR signal alterations attributable to surgical trauma, which led to overestimation of residual LGG on epMRI compared to fuMRI. The prognostic value and clinical impact of this method has to be evaluated in larger case series in the future.
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Affiliation(s)
| | | | - Michael Götz
- 2Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - David Reuss
- 4Neuropathology, Heidelberg University Hospital; and
| | | | - Klaus Maier-Hein
- 2Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
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Boyko M, Zvenigorodsky V, Grinshpun J, Shiyntum HN, Melamed I, Kutz R, Shelef I, Brotfain E, Frank D, Zlotnik A. Establishment of novel technical methods for evaluating brain edema and lesion volume in stroked rats: A standardization of measurement procedures. Brain Res 2019; 1718:12-21. [PMID: 31026458 DOI: 10.1016/j.brainres.2019.04.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2018] [Revised: 03/09/2019] [Accepted: 04/22/2019] [Indexed: 11/17/2022]
Abstract
Stroke plays a role in high morbidity and mortality. Deciphering its mechanisms and pathophysiology is critical for the creation of new drugs and therapies. Most of the previous animal models of stroke, aimed at identifying the extent and location of brain injury following stroke, require animal sacrifice, which, besides ethical considerations, also negates the ability for follow up studies with the same rats. Because of these failures, the use of clinical magnetic resonance scanners for evaluating small animal models has been increasing. Magnetic resonance imaging scanners used particularly for small-bore animals are eligible for use in high-resolution magnetic resonance imaging of rodent brains. However, high costs and scarcity factor heavily in the rare availability of these scanners. In our investigation, we sought to establish a unitary magnetic resonance imaging protocol for stroke assessment in rats. We made use of a 3-Tesla magnetic resonance imaging clinical scanner, as well as another clinical equipment, with the purpose of increasing its reproducibility. The results of inquest validated a new magnetic resonance imaging protocol, comparing a magnetic resonance imaging-measured infarcted zone to the "gold standard" of histological examination. We carried out the experimental procedure on a 3 Tesla magnetic resonance imaging clinical scanner using a conventional eight-channel receive-only coil. The two methods produced remarkable quantitative and qualitative correlations between them. Conclusively, we showed the clinical magnetic resonance imaging scanner to be a high-precision and sensitive image analysis instrument for evaluating both the infarct zone and the brain edema in a stroke experimental rat model.
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Affiliation(s)
- Matthew Boyko
- Division of Anesthesiology and Critical Care, Soroka University Medical Center and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84101, Israel.
| | - Vladislav Zvenigorodsky
- Department of Radiology, Soroka University Medical Center and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Julia Grinshpun
- Division of Anesthesiology and Critical Care, Soroka University Medical Center and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84101, Israel
| | - Honore N Shiyntum
- Department of Biophysics and Biochemistry, Faculty of Biology, Ecology, and Medicine, Oles' Honchar Dnipro National University, Gagarin avenue 72, Dnipro 49010, Ukraine
| | - Israel Melamed
- Department of Neurosurgery, Soroka University Medical Center and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84101, Israel.
| | - Ruslan Kutz
- Division of Anesthesiology and Critical Care, Soroka University Medical Center and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84101, Israel.
| | - Ilan Shelef
- Department of Radiology, Soroka University Medical Center and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
| | - Evgeni Brotfain
- Division of Anesthesiology and Critical Care, Soroka University Medical Center and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84101, Israel
| | - Dmitry Frank
- Division of Anesthesiology and Critical Care, Soroka University Medical Center and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84101, Israel.
| | - Alexander Zlotnik
- Division of Anesthesiology and Critical Care, Soroka University Medical Center and the Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva 84101, Israel.
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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: 37] [Impact Index Per Article: 7.4] [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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Ko CC, Chen TY, Lim SW, Kuo YT, Wu TC, Chen JH. Prediction of Recurrence in Parasagittal and Parafalcine Meningiomas: Added Value of Diffusion-Weighted Magnetic Resonance Imaging. World Neurosurg 2019; 124:e470-e479. [PMID: 30610981 DOI: 10.1016/j.wneu.2018.12.117] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 12/11/2018] [Accepted: 12/13/2018] [Indexed: 01/18/2023]
Abstract
BACKGROUND Parasagittal and parafalcine (PSPF) meningiomas recur more frequently than other intracranial meningiomas owing to the difficulty in achieving gross total resection. The present study investigated the preoperative magnetic resonance imaging (MRI) features for the prediction of progression/recurrence (P/R) in benign PSPF meningiomas with an emphasis on the apparent diffusion coefficient (ADC) values. METHODS We retrospectively investigated the preoperative MRI features for the prediction of P/R in benign (World Health Organization grade I) PSPF meningiomas. Only patients who had undergone preoperative and postoperative MRI follow-up studies for ≥1 year were included. From October 2006 to December 2015, 48 patients with a diagnosis of benign PSPF meningioma were included (median follow-up period, 42.5 months). Of these 48 patients, 12 (25%) developed P/R (median time to P/R, 23 months). RESULTS PSPF meningiomas in male patients, subtotal resection, large tumor diameter, high diffusion-weighted imaging signal, and lower ADC values or ratios were significantly associated with P/R (P < 0.05). The cutoff points of the ADC value and ADC ratio for the prediction of P/R were 0.83 × 10-3 mm2/second and 0.99, with an area under the curve of 0.82 and 0.83, respectively (P = 0.001). On multivariate Cox proportional hazards analysis, male sex and low ADC values (<0.83 × 10-3 mm2/second) were high-risk factors for P/R, with a hazard ratio of 12.37 and 30.2, respectively (P < 0.05). Kaplan-Meier analysis showed that lower ADC values and ratios predicted for significantly shorter progression-free survival (P < 0.05). CONCLUSIONS The preoperative ADC values and ratios for the prediction of P/R offer additional valuable information for the treatment planning for PSPF meningiomas.
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Affiliation(s)
- Ching-Chung Ko
- Section of Neuroradiology, Department of Medical Imaging, Chi-Mei Medical Center, Tainan, Taiwan.
| | - Tai-Yuan Chen
- Section of Neuroradiology, Department of Medical Imaging, Chi-Mei Medical Center, Tainan, Taiwan; Graduate Institute of Medical Sciences, Chang Jung Christian University, Tainan, Taiwan
| | - Sher-Wei Lim
- Department of Neurosurgery, Chi-Mei Medical Center, Chiali, Tainan, Taiwan; Department of Nursing, Min-Hwei College of Health Care Management, Tainan, Taiwan
| | - Yu-Ting Kuo
- Section of Neuroradiology, Department of Medical Imaging, Chi-Mei Medical Center, Tainan, Taiwan; Department of Radiology, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Te-Chang Wu
- Section of Neuroradiology, Department of Medical Imaging, Chi-Mei Medical Center, Tainan, Taiwan; Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan
| | - Jeon-Hor Chen
- Department of Radiology, E-DA Hospital, E-DA Cancer Hospital, I-Shou University, Kaohsiung, Taiwan; Center for Functional Onco-Imaging of Radiological Sciences, School of Medicine, University of California, Irvine, California, USA
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Yoon RG, Kim HS, Hong GS, Park JE, Jung SC, Kim SJ, Kim JH. Joint approach of diffusion- and perfusion-weighted MRI in intra-axial mass like lesions in clinical practice simulation. PLoS One 2018; 13:e0202891. [PMID: 30192785 PMCID: PMC6128539 DOI: 10.1371/journal.pone.0202891] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Accepted: 08/10/2018] [Indexed: 11/18/2022] Open
Abstract
Although advanced magnetic resonance imaging (MRI) techniques provide useful information for the differential diagnosis of intra-axial mass-like lesions, the specific diagnostic role of multimodal MRI over conventional magnetic resonance imaging (CMRI) alone in the differential diagnosis of mass-like lesions from a large heterogeneous cohort has not been studied. In this study, we aimed to determine the added value of a joint approach of diffusion-weighted imaging (DWI) and dynamic-susceptibility-contrast perfusion imaging (DSC-PWI) for diagnosis of intra-axial mass-like lesions, comparing them with CMRI alone. Furthermore, we performed these evaluations in a manner simulating clinical practice. Our institutional review board approved this retrospective study and waived the requirement for informed consent. A total of 1038 patients with intra-axial mass-like lesions were retrospectively recruited according to their histological and clinico-radiological diagnoses made between January 2005 and December 2014. All patients underwent CMRI, DWI and DSC-PWI. The diagnostic accuracy and confidence in diagnosing each type of intra-axial mass-like lesions, and for differentiating the intra-axial brain tumors from non-neoplastic lesions, were compared according to the MRI protocols. The disease-specific sensitivity of joint approach differed according to specific disease entities in diagnosing each disease category. Joint approach provided the best diagnostic accuracy for discriminating intra-axial brain tumors from non-neoplastic lesions, with high diagnostic accuracy (95.3–96.7%), specificity (82–84.0%), positive-predictive-value (97.0–97.3%), and negative-predictive-value (84.8–92.7%), with the reader’s confidence values being significantly improved over those on CMRI alone (all p-values < 0.001). In conclusion, joint approach of DWI, DSC-PWI to CMRI helps to differentiate non-neoplastic lesions from intra-axial brain tumors, and improves diagnostic confidence compared with CMRI alone. The benefit from the combined imaging differs for each disease category; thus joint approach needs to be customized according to clinical suspicion.
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Affiliation(s)
- Ra Gyoung Yoon
- Department of Radiology, Eulji Medical Center, Eulji University College of Medicine, Seoul, Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
- * E-mail:
| | - Gil Sun Hong
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Seung Chai Jung
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Sang Joon Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Jeong Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
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Yazdani M, Rumboldt Z, Tabesh A, Giglio P, Schiarelli C, Morgan PS, Spampinato MV. Perilesional apparent diffusion coefficient in the preoperative evaluation of glioma grade. Clin Imaging 2018; 52:88-94. [PMID: 30032069 DOI: 10.1016/j.clinimag.2018.07.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 06/15/2018] [Accepted: 07/04/2018] [Indexed: 01/22/2023]
Abstract
Preoperative identification of high-grade gliomas is critical to optimize treatment strategy and to predict prognosis. To determine whether perilesional apparent diffusion coefficient (ADC) values differ between high- and low-grade tumors, we assessed water diffusivity within normal-appearing brain parenchyma (NABP) surrounding gliomas in twenty-one treatment-naïve patients. This showed significantly lower mean and 25th percentile (Q1) ADC values in high- grade compared to low-grade gliomas respectively in the range of 10-25 and 10-30 mm away from combined tumor and surrounding T2 signal. Thus, perilesional ADC measurement may reflect the extent of tumor infiltration beyond the abnormality seen on conventional MRI.
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Affiliation(s)
- Milad Yazdani
- Department of Radiology and Radiological Science, Medical University of South Carolina, 96 Jonathan Lucas Street, Charleston, SC, USA.
| | - Zoran Rumboldt
- Department of Radiology and Radiological Science, Medical University of South Carolina, 96 Jonathan Lucas Street, Charleston, SC, USA
| | - Ali Tabesh
- Department of Radiology and Radiological Science, Medical University of South Carolina, 96 Jonathan Lucas Street, Charleston, SC, USA
| | - Pierre Giglio
- Department of Neurology, Ohio State University, Wexner Medical College, Columbus, OH, USA
| | - Chiara Schiarelli
- Department of Radiology and Radiological Science, Medical University of South Carolina, 96 Jonathan Lucas Street, Charleston, SC, USA
| | - Paul S Morgan
- Medical Physics & Clinical Engineering, QMC Campus, University of Nottingham, Nottingham, UK
| | - Maria V Spampinato
- Department of Radiology and Radiological Science, Medical University of South Carolina, 96 Jonathan Lucas Street, Charleston, SC, USA
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Suh CH, Kim HS, Jung SC, Kim SJ. Diffusion-Weighted Imaging and Diffusion Tensor Imaging for Differentiating High-Grade Glioma from Solitary Brain Metastasis: A Systematic Review and Meta-Analysis. AJNR Am J Neuroradiol 2018; 39:1208-1214. [PMID: 29724766 DOI: 10.3174/ajnr.a5650] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 03/07/2018] [Indexed: 12/13/2022]
Abstract
BACKGROUND Accurate diagnosis of high-grade glioma and solitary brain metastasis is clinically important because it affects the patient's outcome and alters patient management. PURPOSE To evaluate the diagnostic performance of DWI and DTI for differentiating high-grade glioma from solitary brain metastasis. DATA SOURCES A literature search of Ovid MEDLINE and EMBASE was conducted up to November 10, 2017. STUDY SELECTION Studies evaluating the diagnostic performance of DWI and DTI for differentiating high-grade glioma from solitary brain metastasis were selected. DATA ANALYSIS Summary sensitivity and specificity were established by hierarchic logistic regression modeling. Multiple subgroup analyses were also performed. DATA SYNTHESIS Fourteen studies with 1143 patients were included. The individual sensitivities and specificities of the 14 included studies showed a wide variation, ranging from 46.2% to 96.0% for sensitivity and 40.0% to 100.0% for specificity. The pooled sensitivity of both DWI and DTI was 79.8% (95% CI, 70.9%-86.4%), and the pooled specificity was 80.9% (95% CI, 75.1%-85.5%). The area under the hierarchical summary receiver operating characteristic curve was 0.87 (95% CI, 0.84-0.89). The multiple subgroup analyses also demonstrated similar diagnostic performances (sensitivities of 76.8%-84.7% and specificities of 79.7%-84.0%). There was some level of heterogeneity across the included studies (I2 = 36%); however, it did not reach a level of concern. LIMITATIONS The included studies used various DWI and DTI parameters. CONCLUSIONS DWI and DTI demonstrated a moderate diagnostic performance for differentiation of high-grade glioma from solitary brain metastasis.
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Affiliation(s)
- C H Suh
- From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - H S Kim
- From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
| | - S C Jung
- From the Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - S J Kim
- From the 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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Caravan I, Ciortea CA, Contis A, Lebovici A. Diagnostic value of apparent diffusion coefficient in differentiating between high-grade gliomas and brain metastases. Acta Radiol 2018; 59:599-605. [PMID: 28835111 DOI: 10.1177/0284185117727787] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background High-grade gliomas (HGGs) and brain metastases (BMs) can display similar imaging characteristics on conventional MRI. In HGGs, the peritumoral edema may be infiltrated by the malignant cells, which was not observed in BMs. Purpose To determine whether the apparent diffusion coefficient values could differentiate HGGs from BMs. Material and Methods Fifty-seven patients underwent conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) before treatment. The minimum and mean ADC in the enhancing tumor (ADCmin, ADCmean) and the minimum ADC in the peritumoral region (ADCedema) were measured from ADC maps. To determine whether there was a statistical difference between groups, ADC values were compared. A receiver operating characteristic (ROC) curve analysis was used to determine the cutoff ADC value for distinguishing between HGGs and BMs. Results The mean ADCmin values in the intratumoral regions of HGGs were significantly higher than those in BMs. No differences were observed between groups regarding ADCmean values. The mean ADCmin values in the peritumoral edema of HGGs were significantly lower than those in BMs. According to ROC curve analysis, a cutoff value of 1.332 × 10-3 mm2/s for the ADCedema generated the best combination of sensitivity (95%) and specificity (84%) for distinguishing between HGGs and BMs. The same value showed a sensitivity of 95.6% and a specificity of 100% for distinguishing between GBMs and BMs. Conclusion ADC values from DWI were found to distinguish between HGGs and solitary BMs. The peritumoral ADC values are better than the intratumoral ADC values in predicting the tumor type.
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Affiliation(s)
- Ionut Caravan
- “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | | | - Alexandra Contis
- “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
| | - Andrei Lebovici
- “Iuliu Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania
- Department of Radiology, Emergency County Hospital, Cluj-Napoca, Romania
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Differentiating Between Primary Central Nervous System Lymphomas and Glioblastomas: Combined Use of Perfusion-Weighted and Diffusion-Weighted Magnetic Resonance Imaging. World Neurosurg 2018; 112:e1-e6. [DOI: 10.1016/j.wneu.2017.10.141] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Revised: 10/24/2017] [Accepted: 10/25/2017] [Indexed: 02/06/2023]
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45
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Kim MS, Park SH, Park ES, Park JB, Kwon SC, Lyo IU, Sim HB. Quantitative analysis in peritumoral volumes of brain metastases treated with stereotactic radiotherapy. J Neuroradiol 2018; 45:310-315. [PMID: 29410152 DOI: 10.1016/j.neurad.2017.12.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Revised: 10/24/2017] [Accepted: 12/20/2017] [Indexed: 11/24/2022]
Abstract
PURPOSE The purpose of this study was to verify changes in diffusion tensor imaging (DTI) factors in patients with brain metastases treated with stereotactic radiotherapy (SRT). We also investigated the impact of SRT on peritumoral volumes though the use of DTI. METHODS A total of 28 patients with brain metastases who had undergone SRT between March 2014 and December 2015 were enrolled. Magnetic resonance imaging with DTI factors, such as fractional anisotropy (FA) and apparent diffusion tensor (ADC) value, was performed 1 day before the procedure and 3 months after the procedure. DTI data from tumor lesions, edema volumes, and the volumes that received 12Gy were measured. RESULTS Tumor volume (P=0.001) and ADC values in the volumes that received 12Gy (P=0.018) and the edema volumes (P=0.003) significantly decreased after the procedure. Decreases in tumor volume were only correlated with decreases in edema volumes (P<0.001). Decreases in edema volumes were correlated with increases in FA values and decreases in ADC values of the volumes that received 12Gy [P=0.019 (FA)/0.002 (ADC)] and the edema volumes [P=0.011 (FA)/0.002 (ADC)]. CONCLUSIONS It was possible to quantify changes in peritumoral volumes in patients with brain metastases after SRT by using DTI. ADC values of peritumoral volumes decreased significantly after SRT. Therefore, it was confirmed through DTI that performing SRT on tumor lesions has a positive effect on the structure and function of peritumoral volumes.
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Affiliation(s)
- Min Soo Kim
- Department of Neurosurgery, Ulsan University Hospital, University of Ulsan College of Medicine, 877, Bangeojin sunhwando-ro, Dong-gu, 44033 Ulsan, Republic of Korea
| | - Sung Ho Park
- Department of Neurosurgery, Ulsan University Hospital, University of Ulsan College of Medicine, 877, Bangeojin sunhwando-ro, Dong-gu, 44033 Ulsan, Republic of Korea
| | - Eun Suk Park
- Department of Neurosurgery, Ulsan University Hospital, University of Ulsan College of Medicine, 877, Bangeojin sunhwando-ro, Dong-gu, 44033 Ulsan, Republic of Korea
| | - Jun Bum Park
- Department of Neurosurgery, Ulsan University Hospital, University of Ulsan College of Medicine, 877, Bangeojin sunhwando-ro, Dong-gu, 44033 Ulsan, Republic of Korea.
| | - Soon Chan Kwon
- Department of Neurosurgery, Ulsan University Hospital, University of Ulsan College of Medicine, 877, Bangeojin sunhwando-ro, Dong-gu, 44033 Ulsan, Republic of Korea
| | - In Uk Lyo
- Department of Neurosurgery, Ulsan University Hospital, University of Ulsan College of Medicine, 877, Bangeojin sunhwando-ro, Dong-gu, 44033 Ulsan, Republic of Korea
| | - Hong Bo Sim
- Department of Neurosurgery, Ulsan University Hospital, University of Ulsan College of Medicine, 877, Bangeojin sunhwando-ro, Dong-gu, 44033 Ulsan, Republic of Korea
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Ko CC, Lim SW, Chen TY, Chen JH, Li CF, Shiue YL. Prediction of progression in skull base meningiomas: additional benefits of apparent diffusion coefficient value. J Neurooncol 2018; 138:63-71. [PMID: 29353434 DOI: 10.1007/s11060-018-2769-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 01/18/2018] [Indexed: 11/28/2022]
Abstract
A subset of benign (WHO grade I) skull base meningiomas show early progression/recurrence (P/R) in the first years after surgical resection. Besides, complete surgical resection may be difficult to achieve safely in skull base meningiomas due to complex neurovascular structures. The one main challenge in the treatment of skull base meningiomas is to determine factors that correlate with P/R. We retrospectively investigated the preoperative CT and MR imaging features for the prediction of P/R in skull base meningiomas, with emphasis on quantitative ADC values. Only patients had postoperative MRI follow-ups for more than 1 year (at least every 6 months) were included. From October 2006 to December 2015, total 73 patients diagnosed with benign (WHO grade I) skull base meningiomas were included (median follow-up time 41 months), and 17 (23.3%) patients had P/R (median time to P/R 28 months). Skull base meningiomas with spheno-orbital location, adjacent bone invasion, high DWI, and lower ADC value/ratio were significantly associated with P/R (P < 0.05). The cut-off points of ADC value and ADC ratio for prediction of P/R are 0.83 × 10- 3 mm2/s and 1.09 respectively, with excellent area under curve (AUC) values (0.86 and 0.91) (P < 0.05). In multivariate logistic regression, low ADC values (< 0.83 × 10- 3 mm2/s) and adjacent bone invasion are high-risk factors of P/R (P < 0.05), with odds ratios of 31.53 and 17.59 respectively. The preoperative CT and MRI features for prediction of P/R offered clinically vital information for the planning of treatment in skull base meningiomas.
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Affiliation(s)
- Ching-Chung Ko
- Institute of Biomedical Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan.,Section of Neuroradiology, Department of Medical Imaging, Chi-Mei Medical Center, Tainan, Taiwan
| | - Sher-Wei Lim
- Institute of Biomedical Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan.,Department of Neurosurgery, Chi-Mei Medical Center, Chiali, Tainan, Taiwan.,Department of Nursing, Min-Hwei College of Health Care Management, Tainan, Taiwan
| | - Tai-Yuan Chen
- Section of Neuroradiology, Department of Medical Imaging, Chi-Mei Medical Center, Tainan, Taiwan.,Graduate Institute of Medical Sciences, Chang Jung Christian University, Tainan, Taiwan
| | - Jeon-Hor Chen
- Department of Radiology, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan.,Center for Functional Onco-Imaging of Radiological Sciences, School of Medicine, University of California, Irvine, CA, USA
| | - Chien-Feng Li
- Department of Pathology, Chi-Mei Medical Center, Tainan, Taiwan
| | - Yow-Ling Shiue
- Institute of Biomedical Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan.
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Huang J, Luo J, Peng J, Yang T, Zheng H, Mao C. Cerebral schistosomiasis: diffusion-weighted imaging helps to differentiate from brain glioma and metastasis. Acta Radiol 2017; 58:1371-1377. [PMID: 28090792 DOI: 10.1177/0284185116687173] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Diffusion-weighted imaging (DWI) was introduced into clinical use some years ago. However, its use in the diagnosis of cerebral schistosomiasis has not been reported. Purpose To investigate the ability of the apparent diffusion coefficient (ADC) value of DWI in the diagnosis of cerebral schistosomiasis, and to differentiate it from brain high-grade gliomas and metastasis. Material and Methods Conventional brain MRI with pre-contrast, post-contrast, and DWI was performed on 50 cases of cerebral schistosomiasis, high-grade glioma, and brain metastasis. The ADC values of the three lesions, the proximal and the distal perifocal edema were measured. In order to remove the individual difference effect of ADC values, relative ADC (rADC) values were calculated through dividing the ADC value of the lesion area by that of the contralateral normal white matter. rADC values were used to evaluate the differences among cerebral schistosomiasis, brain high-grade gliomas, and metastasis. Results rADC of cerebral schistosomiasis was significantly lower than rADC of brain metastasis ( P < 0.05), without any significant differences when compared with high-grade gliomas. rADC of proximal perifocal edema in cerebral schistosomiasis was significantly higher than in high-grade gliomas ( P < 0.010), but not different compared with brain metastasis. Conclusion DWI examination with ADC values of lesions and proximal perifocal edema might be helpful in the exact diagnosis of cerebral schistosomiasis.
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Affiliation(s)
- Jinbai Huang
- Clinical Medical College of Yangtze University, Radiology Department of the First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, PR China
| | - Jing Luo
- Clinical Medical College of Yangtze University, Radiology Department of the First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, PR China
| | - Jie Peng
- Clinical Medical College of Yangtze University, Radiology Department of the First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, PR China
| | - Tao Yang
- Clinical Medical College of Yangtze University, Neurology Department of the First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, PR China
| | - Huanghua Zheng
- Clinical Medical College of Yangtze University, Radiology Department of the First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, PR China
| | - Chunping Mao
- Clinical Medical College of Yangtze University, Radiology Department of the First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, PR China
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Phuttharak W, Boonrod A, Patjanasoontorn N, Peansukwech U, Sawanyawisuth K. The roles of the diffusion-weighted imaging in orbital masses. J Med Imaging Radiat Oncol 2017; 61:753-758. [DOI: 10.1111/1754-9485.12627] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 03/27/2017] [Indexed: 12/12/2022]
Affiliation(s)
- Warinthorn Phuttharak
- Department of Radiology; Faculty of Medicine; Khon Kaen University; Khon Kaen Thailand
| | - Arunnit Boonrod
- Department of Radiology; Faculty of Medicine; Khon Kaen University; Khon Kaen Thailand
| | | | - Udomlack Peansukwech
- Department of Medicine; Faculty of Medicine; Khon Kaen University; Khon Kaen Thailand
| | - Kittisak Sawanyawisuth
- Department of Medicine; Faculty of Medicine; Khon Kaen University; Khon Kaen Thailand
- Research Center in Back, Neck Other Joint Pain and Human Performance (BNOJPH); Khon Kaen University; Khon Kaen Thailand
- Sleep Apnea Research Group; Khon Kean University; Khon Kaen Thailand
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Sakata A, Fushimi Y, Okada T, Arakawa Y, Kunieda T, Minamiguchi S, Kido A, Sakashita N, Miyamoto S, Togashi K. Diagnostic performance between contrast enhancement, proton MR spectroscopy, and amide proton transfer imaging in patients with brain tumors. J Magn Reson Imaging 2017; 46:732-739. [PMID: 28252822 DOI: 10.1002/jmri.25597] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Accepted: 11/28/2016] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To explore the relationship among parameters of magnetic resonance spectroscopy (MRS) and amide proton transfer (APT) imaging, and to assess the diagnostic performance of MRS and APT imaging for grading brain tumors in comparison with contrast enhancement of conventional MRI for preoperative grading in patients with brain tumor. MATERIALS AND METHODS Institutional Review Board approval and written informed consent were obtained. Forty-one patients with suspected brain tumors were enrolled in the study. Single-voxel MRS and 2D APT imaging of the same slice level were conducted using a 3T MRI scanner. Positive or negative contrast enhancement on T1 -weighted images was assessed by two neuroradiologists. Correlations among metabolite concentrations, metabolite ratios, and calculated histogram parameters, including mean APT (APTmean ) and the 90th percentile of APT (APT90 ) were assessed using Spearman's correlation coefficient. Diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis for contrast enhancement and MRS and APT imaging. Values of P < 0.05 were considered statistically significant. RESULTS Positive correlations with statistical significance were found between total concentration of choline (Cho) and APT90 (r = 0.49), and between Cho/creatine (Cr) and APTmean (r = 0.65) as well as APT90 (r = 0.49). A negative correlation with statistical significance was observed between NAA/Cr and APTmean (r = -0.52). According to ROC curves, Cho/Cr, APTmean , APT90 , demonstrated higher area under the curve (AUC) values than that of contrast enhancement in grading gliomas. CONCLUSION Significant correlations were observed between metabolite concentrations and ratios on MRS and APT values. MRS and APT imaging showed comparable diagnostic capability for grading brain tumors, suggesting that both MRS and APT imaging offer potential for quantitatively assessing similar biological characteristics in brain tumors on noncontrast MRI. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:732-739.
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Affiliation(s)
- Akihiko Sakata
- Kyoto University Graduate School of Medicine, Department of Diagnostic Imaging and Nuclear Medicine, Kyoto, Japan
| | - Yasutaka Fushimi
- Kyoto University Graduate School of Medicine, Department of Diagnostic Imaging and Nuclear Medicine, Kyoto, Japan
| | - Tomohisa Okada
- Kyoto University Graduate School of Medicine, Human Brain Research Center, Kyoto, Japan
| | - Yoshiki Arakawa
- Kyoto University Graduate School of Medicine, Department of Neurosurgery, Kyoto, Japan
| | - Takeharu Kunieda
- Kyoto University Graduate School of Medicine, Department of Neurosurgery, Kyoto, Japan
| | - Sachiko Minamiguchi
- Kyoto University Graduate School of Medicine, Department of Diagnostic Pathology, Kyoto, Japan
| | - Aki Kido
- Kyoto University Graduate School of Medicine, Department of Diagnostic Imaging and Nuclear Medicine, Kyoto, Japan
| | - Naotaka Sakashita
- Toshiba Medical Systems Corporations, MRI Systems Development Department, Otawara, Japan
| | - Susumu Miyamoto
- Kyoto University Graduate School of Medicine, Department of Neurosurgery, Kyoto, Japan
| | - Kaori Togashi
- Kyoto University Graduate School of Medicine, Department of Diagnostic Imaging and Nuclear Medicine, Kyoto, Japan
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50
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Differentiating Primary Central Nervous System Lymphomas From Glioblastomas and Inflammatory Demyelinating Pseudotumor Using Relative Minimum Apparent Diffusion Coefficients. J Comput Assist Tomogr 2017; 41:904-909. [DOI: 10.1097/rct.0000000000000636] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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