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Dagher R, Gad M, da Silva de Santana P, Sadeghi MA, Yewedalsew SF, Gujar SK, Yedavalli V, Köhler CA, Khan M, Tavora DGF, Kamson DO, Sair HI, Luna LP. Umbrella review and network meta-analysis of diagnostic imaging test accuracy studies in Differentiating between brain tumor progression versus pseudoprogression and radionecrosis. J Neurooncol 2024; 166:1-15. [PMID: 38212574 DOI: 10.1007/s11060-023-04528-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Accepted: 12/01/2023] [Indexed: 01/13/2024]
Abstract
PURPOSE In this study we gathered and analyzed the available evidence regarding 17 different imaging modalities and performed network meta-analysis to find the most effective modality for the differentiation between brain tumor recurrence and post-treatment radiation effects. METHODS We conducted a comprehensive systematic search on PubMed and Embase. The quality of eligible studies was assessed using the Assessment of Multiple Systematic Reviews-2 (AMSTAR-2) instrument. For each meta-analysis, we recalculated the effect size, sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio from the individual study data provided in the original meta-analysis using a random-effects model. Imaging technique comparisons were then assessed using NMA. Ranking was assessed using the multidimensional scaling approach and by visually assessing surface under the cumulative ranking curves. RESULTS We identified 32 eligible studies. High confidence in the results was found in only one of them, with a substantial heterogeneity and small study effect in 21% and 9% of included meta-analysis respectively. Comparisons between MRS Cho/NAA, Cho/Cr, DWI, and DSC were most studied. Our analysis showed MRS (Cho/NAA) and 18F-DOPA PET displayed the highest sensitivity and negative likelihood ratios. 18-FET PET was ranked highest among the 17 studied techniques with statistical significance. APT MRI was the only non-nuclear imaging modality to rank higher than DSC, with statistical insignificance, however. CONCLUSION The evidence regarding which imaging modality is best for the differentiation between radiation necrosis and post-treatment radiation effects is still inconclusive. Using NMA, our analysis ranked FET PET to be the best for such a task based on the available evidence. APT MRI showed promising results as a non-nuclear alternative.
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Affiliation(s)
- Richard Dagher
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | - Mona Gad
- Diagnostic Radiology Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt
| | | | - Mohammad Amin Sadeghi
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | | | - Sachin K Gujar
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | - Vivek Yedavalli
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | - Cristiano André Köhler
- Medical Sciences Post-Graduation Program, Department of Internal Medicine, School of Medicine, Federal University of Ceará, Fortaleza, Brazil
| | - Majid Khan
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | | | - David Olayinka Kamson
- The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University, Baltimore, MD, USA
| | - Haris I Sair
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA
| | - Licia P Luna
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Neuroradiology, Johns Hopkins Hospital, 600 N Wolfe Street Phipps B100F, Baltimore, MD, 21287, USA.
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Kuo F, Ng NN, Nagpal S, Pollom EL, Soltys S, Hayden-Gephart M, Li G, Born DE, Iv M. DSC Perfusion MRI-Derived Fractional Tumor Burden and Relative CBV Differentiate Tumor Progression and Radiation Necrosis in Brain Metastases Treated with Stereotactic Radiosurgery. AJNR Am J Neuroradiol 2022; 43:689-695. [PMID: 35483909 PMCID: PMC9089266 DOI: 10.3174/ajnr.a7501] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 03/14/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND AND PURPOSE Differentiation between tumor and radiation necrosis in patients with brain metastases treated with stereotactic radiosurgery is challenging. We hypothesized that MR perfusion and metabolic metrics can differentiate radiation necrosis from progressive tumor in this setting. MATERIALS AND METHODS We retrospectively evaluated MRIs comprising DSC, dynamic contrast-enhanced, and arterial spin-labeling perfusion imaging in subjects with brain metastases previously treated with stereotactic radiosurgery. For each lesion, we obtained the mean normalized and standardized relative CBV and fractional tumor burden, volume transfer constant, and normalized maximum CBF, as well as the maximum standardized uptake value in a subset of subjects who underwent FDG-PET. Relative CBV thresholds of 1 and 1.75 were used to define low and high fractional tumor burden. RESULTS Thirty subjects with 37 lesions (20 radiation necrosis, 17 tumor) were included. Compared with radiation necrosis, tumor had increased mean normalized and standardized relative CBV (P = .002) and high fractional tumor burden (normalized, P = .005; standardized, P = .003) and decreased low fractional tumor burden (normalized, P = .03; standardized, P = .01). The area under the curve showed that relative CBV (normalized = 0.80; standardized = 0.79) and high fractional tumor burden (normalized = 0.77; standardized = 0.78) performed the best to discriminate tumor and radiation necrosis. For tumor prediction, the normalized relative CBV cutoff of ≥1.75 yielded a sensitivity of 76.5% and specificity of 70.0%, while the standardized cutoff of ≥1.75 yielded a sensitivity of 41.2% and specificity of 95.0%. No significance was found with the volume transfer constant, normalized CBF, and standardized uptake value. CONCLUSIONS Increased relative CBV and high fractional tumor burden (defined by a threshold relative CBV of ≥1.75) best differentiated tumor from radiation necrosis in subjects with brain metastases treated with stereotactic radiosurgery. Performance of normalized and standardized approaches was similar.
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Affiliation(s)
- F Kuo
- From the Department of Radiology, Division of Neuroimaging and Neurointervention (F.K., N.N.N., M.I.)
| | - N N Ng
- From the Department of Radiology, Division of Neuroimaging and Neurointervention (F.K., N.N.N., M.I.)
| | - S Nagpal
- Departments of Neurology (Neuro-Oncology) (S.N.)
| | | | - S Soltys
- Radiation Oncology (E.L.P., S.S.)
| | | | - G Li
- Neurosurgery (M.H.-G., G.L.)
| | - D E Born
- Pathology (D.E.B.), Stanford University, Stanford, California
| | - M Iv
- From the Department of Radiology, Division of Neuroimaging and Neurointervention (F.K., N.N.N., M.I.)
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Kim JS, Son HJ, Oh M, Lee DY, Kim HW, Oh J. 60 Years of Achievements by KSNM in Neuroimaging Research. Nucl Med Mol Imaging 2022; 56:3-16. [PMID: 35186156 PMCID: PMC8828843 DOI: 10.1007/s13139-021-00727-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 11/01/2021] [Accepted: 12/07/2021] [Indexed: 02/03/2023] Open
Abstract
Nuclear medicine neuroimaging is able to show functional and molecular biologic abnormalities in various neuropsychiatric diseases. Therefore, it has played important roles in the clinical diagnosis and in research on the normal and pathological states of the brain. More than 400 outstanding studies have been conducted by Korean researchers over the past 60 years. In the 1990s, when multiheaded single-photon emission computed tomography (SPECT) scanners were first introduced in South Korea, stroke research using brain perfusion SPECT was conducted. With the spread of positron emission tomography (PET) scanners in the 2000s, research on the clinical usefulness of PET and the evaluation of pathophysiology in various diseases such as epilepsy, brain tumors, degenerative brain diseases, and other neuropsychiatric diseases were actively conducted using [18F]FDG and various neuroreceptor tracers. In the 2010s, with the clinical application of new radiopharmaceuticals for amyloid and tau imaging, research demonstrating the clinical usefulness of PET imaging and the pathophysiology of dementia has increased rapidly. It is expected that the role of nuclear medicine will expand with the development of new radiopharmaceuticals and analysis technologies, along with the application of artificial intelligence for early and differential diagnosis, and the development of therapeutic agents for degenerative brain diseases.
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Affiliation(s)
- Jae Seung Kim
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Hye Joo Son
- Department of Nuclear Medicine, Dankook University College of Medicine, Cheonan, Republic of Korea
| | - Minyoung Oh
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Dong Yun Lee
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Hae Won Kim
- Department of Nuclear Medicine, Keimyung University Dongsan Hospital, Daegu, Republic of Korea
| | - Jungsu Oh
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
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Chiaravalloti A, Cimini A, Ricci M, Quartuccio N, Arnone G, Filippi L, Calabria F, Leporace M, Bagnato A, Schillaci O. Positron emission tomography imaging in primary brain tumors. Nucl Med Mol Imaging 2022. [DOI: 10.1016/b978-0-12-822960-6.00042-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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Chen X, Parekh VS, Peng L, Chan MD, Redmond KJ, Soike M, McTyre E, Lin D, Jacobs MA, Kleinberg LR. Multiparametric radiomic tissue signature and machine learning for distinguishing radiation necrosis from tumor progression after stereotactic radiosurgery. Neurooncol Adv 2021; 3:vdab150. [PMID: 34901857 PMCID: PMC8661085 DOI: 10.1093/noajnl/vdab150] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background Stereotactic radiosurgery (SRS) may cause radiation necrosis (RN) that is difficult to distinguish from tumor progression (TP) by conventional MRI. We hypothesize that MRI-based multiparametric radiomics (mpRad) and machine learning (ML) can differentiate TP from RN in a multi-institutional cohort. Methods Patients with growing brain metastases after SRS at 2 institutions underwent surgery, and RN or TP were confirmed by histopathology. A radiomic tissue signature (RTS) was selected from mpRad, as well as single T1 post-contrast (T1c) and T2 fluid-attenuated inversion recovery (T2-FLAIR) radiomic features. Feature selection and supervised ML were performed in a randomly selected training cohort (N = 95) and validated in the remaining cases (N = 40) using surgical pathology as the gold standard. Results One hundred and thirty-five discrete lesions (37 RN, 98 TP) from 109 patients were included. Radiographic diagnoses by an experienced neuroradiologist were concordant with histopathology in 67% of cases (sensitivity 69%, specificity 59% for TP). Radiomic analysis indicated institutional origin as a significant confounding factor for diagnosis. A random forest model incorporating 1 mpRad, 4 T1c, and 4 T2-FLAIR features had an AUC of 0.77 (95% confidence interval [CI]: 0.66–0.88), sensitivity of 67% and specificity of 86% in the training cohort, and AUC of 0.71 (95% CI: 0.51–0.91), sensitivity of 52% and specificity of 90% in the validation cohort. Conclusions MRI-based mpRad and ML can distinguish TP from RN with high specificity, which may facilitate the triage of patients with growing brain metastases after SRS for repeat radiation versus surgical intervention.
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Affiliation(s)
- Xuguang Chen
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Vishwa S Parekh
- Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Luke Peng
- Department of Radiation Oncology, Dana-Farber/Brigham and Women's Cancer Center, Boston, Massachusetts, USA
| | - Michael D Chan
- Department of Radiation Oncology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Kristin J Redmond
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Michael Soike
- Department of Radiation Oncology, University of Alabama , Birmingham, Alabama, USA
| | - Emory McTyre
- Prisma Cancer Institute, Greenville, North Carolina, USA
| | - Doris Lin
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Michael A Jacobs
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Sidney Kimmel Comprehensive Cancer Center, IRAT Core, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Lawrence R Kleinberg
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Rogers S, Stauffer A, Lomax N, Alonso S, Eberle B, Gomez Ordoñez S, Lazeroms T, Kessler E, Brendel M, Schwyzer L, Riesterer O. Five fraction stereotactic radiotherapy after brain metastasectomy: a single-institution experience and literature review. J Neurooncol 2021; 155:35-43. [PMID: 34546498 DOI: 10.1007/s11060-021-03840-5] [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: 07/31/2021] [Accepted: 09/01/2021] [Indexed: 10/20/2022]
Abstract
PURPOSE The outcomes of five fraction stereotactic radiotherapy (hfSRT) following brain metastasectomy were evaluated and compared with published series. METHODS 30 Gy in 5 fractions HfSRT prescribed to the surgical cavity was reduced to 25 Gy if the volume of 'brain-GTV' receiving 20 Gy exceeded 20 cm3. Endpoints were local recurrence, nodular leptomeningeal recurrence, new brain metastases and radionecrosis. The literature was searched for reports of clinical and dosimetric outcomes following postoperative hfSRT in 3-5 fractions. RESULTS 39 patients with 40 surgical cavities were analyzed. Cavity local control rate at 1 year was 33/40 (82.5%). 3 local failures followed 30 Gy/5 fractions and 4 with 25 Gy/5 fractions. The incidence of leptomeningeal disease (LMD) was 7/40 (17.5%). No grade 3-4 toxicities, particularly no radionecrosis, were reported. The incidence of distant brain metastases was 15/40 (37.5%). The median overall survival was 15 months. Across 13 published series, the weighted mean local control was 83.1% (adjusted for sample size), the mean incidence of LMD was 14.9% (7-34%) and the mean rate of radionecrosis was 10.3% (0-20.6%). CONCLUSION Postoperative hfSRT can be delivered with 25-30 Gy in 5 fractions with efficacy in excess of 82% and no significant toxicity when the dose to 'brain-GTV' does not exceed 20 cm3.
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Affiliation(s)
- S Rogers
- Radiation Oncology Center KSA-KSB, Kantonsspital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland.
| | - A Stauffer
- Department of Neurosurgery, Kantonsspital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland
| | - N Lomax
- Radiation Oncology Center KSA-KSB, Kantonsspital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland
| | - S Alonso
- Radiation Oncology Center KSA-KSB, Kantonsspital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland
| | - B Eberle
- Radiation Oncology Center KSA-KSB, Kantonsspital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland
| | - S Gomez Ordoñez
- Radiation Oncology Center KSA-KSB, Kantonsspital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland
| | - T Lazeroms
- Radiation Oncology Center KSA-KSB, Kantonsspital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland
| | - E Kessler
- Radiation Oncology Center KSA-KSB, Kantonsspital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland
| | - M Brendel
- Department of Neuroradiology, Kantonsspital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland
| | - L Schwyzer
- Department of Neurosurgery, Kantonsspital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland
| | - O Riesterer
- Radiation Oncology Center KSA-KSB, Kantonsspital Aarau, Tellstrasse 25, 5001, Aarau, Switzerland.,Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Rämistrasse 100, 8091, Zurich, Switzerland
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7
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Cui M, Zorrilla-Veloz RI, Hu J, Guan B, Ma X. Diagnostic Accuracy of PET for Differentiating True Glioma Progression From Post Treatment-Related Changes: A Systematic Review and Meta-Analysis. Front Neurol 2021; 12:671867. [PMID: 34093419 PMCID: PMC8173157 DOI: 10.3389/fneur.2021.671867] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 03/24/2021] [Indexed: 11/24/2022] Open
Abstract
Purpose: To evaluate the diagnostic accuracy of PET with different radiotracers and parameters in differentiating between true glioma progression (TPR) and post treatment-related change (PTRC). Methods: Studies on using PET to differentiate between TPR and PTRC were screened from the PubMed and Embase databases. By following the PRISMA checklist, the quality assessment of included studies was performed, the true positive and negative values (TP and TN), false positive and negative values (FP and FN), and general characteristics of all the included studies were extracted. Results of PET consistent with reference standard were defined as TP or TN. The pooled sensitivity (Sen), specificity (Spe), and hierarchical summary receiver operating characteristic curves (HSROC) were generated to evaluate the diagnostic accuracy. Results: The 33 included studies had 1,734 patients with 1,811 lesions suspected of glioma recurrence. Fifteen studies tested the accuracy of 18F-FET PET, 12 tested 18F-FDG PET, seven tested 11C-MET PET, and three tested 18F-DOPA PET. 18F-FET PET showed a pooled Sen and Spe of 0.88 (95% CI: 0.80, 0.93) and 0.78 (0.69, 0.85), respectively. In the subgroup analysis of FET-PET, diagnostic accuracy of high-grade gliomas (HGGs) was higher than that of mixed-grade gliomas (P interaction = 0.04). 18F-FDG PET showed a pooled Sen and Spe of 0.78 (95% CI: 0.71, 0.83) and 0.87 (0.80, 0.92), the Spe of the HGGs group was lower than that of the low-grade gliomas group (0.82 vs. 0.90, P = 0.02). 11C-MET PET had a pooled Sen and Spe of 0.92 (95% CI: 0.83, 0.96) and 0.78 (0.69, 0.86). 18F-DOPA PET had a pooled Sen and Spe of 0.85 (95% CI: 0.80, 0.89) and 0.70 (0.60, 0.79). FET-PET combined with MRI had a pooled Sen and Spe of 0.88 (95% CI: 0.78, 0.94) and 0.76 (0.57, 0.88). Multi-parameters analysis of FET-PET had pooled Sen and Spe values of 0.88 (95% CI: 0.81, 0.92) and 0.79 (0.63, 0.89). Conclusion: PET has a moderate diagnostic accuracy in differentiating between TPR and PTRC. The high Sen of amino acid PET and high Spe of FDG-PET suggest that the combination of commonly used FET-PET and FDG-PET may be more accurate and promising, especially for low-grade glioma.
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Affiliation(s)
- Meng Cui
- Medical School of Chinese People's Liberation Army, Beijing, China
- Department of Neurosurgery, The First Medical Centre of Chinese People's Liberation Army General Hospital, Beijing, China
| | - Rocío Isabel Zorrilla-Veloz
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
- The University of Texas MD Anderson Cancer Centre UT Health Graduate School of Biomedical Sciences, Houston, TX, United States
| | - Jian Hu
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
- The University of Texas MD Anderson Cancer Centre UT Health Graduate School of Biomedical Sciences, Houston, TX, United States
| | - Bing Guan
- Department of Health Economics, The First Medical Centre of Chinese People's Liberation Army General Hospital, Beijing, China
| | - Xiaodong Ma
- Medical School of Chinese People's Liberation Army, Beijing, China
- Department of Neurosurgery, The First Medical Centre of Chinese People's Liberation Army General Hospital, Beijing, China
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Kaufmann TJ, Smits M, Boxerman J, Huang R, Barboriak DP, Weller M, Chung C, Tsien C, Brown PD, Shankar L, Galanis E, Gerstner E, van den Bent MJ, Burns TC, Parney IF, Dunn G, Brastianos PK, Lin NU, Wen PY, Ellingson BM. Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases. Neuro Oncol 2021; 22:757-772. [PMID: 32048719 PMCID: PMC7283031 DOI: 10.1093/neuonc/noaa030] [Citation(s) in RCA: 131] [Impact Index Per Article: 43.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
A recent meeting was held on March 22, 2019, among the FDA, clinical scientists, pharmaceutical and biotech companies, clinical trials cooperative groups, and patient advocacy groups to discuss challenges and potential solutions for increasing development of therapeutics for central nervous system metastases. A key issue identified at this meeting was the need for consistent tumor measurement for reliable tumor response assessment, including the first step of standardized image acquisition with an MRI protocol that could be implemented in multicenter studies aimed at testing new therapeutics. This document builds upon previous consensus recommendations for a standardized brain tumor imaging protocol (BTIP) in high-grade gliomas and defines a protocol for brain metastases (BTIP-BM) that addresses unique challenges associated with assessment of CNS metastases. The "minimum standard" recommended pulse sequences include: (i) parameter matched pre- and post-contrast inversion recovery (IR)-prepared, isotropic 3D T1-weighted gradient echo (IR-GRE); (ii) axial 2D T2-weighted turbo spin echo acquired after injection of gadolinium-based contrast agent and before post-contrast 3D T1-weighted images; (iii) axial 2D or 3D T2-weighted fluid attenuated inversion recovery; (iv) axial 2D, 3-directional diffusion-weighted images; and (v) post-contrast 2D T1-weighted spin echo images for increased lesion conspicuity. Recommended sequence parameters are provided for both 1.5T and 3T MR systems. An "ideal" protocol is also provided, which replaces IR-GRE with 3D TSE T1-weighted imaging pre- and post-gadolinium, and is best performed at 3T, for which dynamic susceptibility contrast perfusion is included. Recommended perfusion parameters are given.
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Affiliation(s)
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Jerrold Boxerman
- Department of Diagnostic Imaging, Rhode Island Hospital and Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Raymond Huang
- Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Daniel P Barboriak
- Department of Radiology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Michael Weller
- Department of Neurology & Brain Tumor Center, University Hospital and University of Zurich, Zurich, Switzerland
| | - Caroline Chung
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Christina Tsien
- Department of Radiation Oncology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Paul D Brown
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota, USA
| | - Lalitha Shankar
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), Bethesda, Maryland, USA
| | - Evanthia Galanis
- Division of Medical Oncology, Department of Oncology, Mayo Clinic, Rochester, Minnesota, USA
| | - Elizabeth Gerstner
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Terry C Burns
- Department of Neurosurgery, Mayo Clinic, Rochester, Minnesota, USA
| | - Ian F Parney
- Department of Neurosurgery, Mayo Clinic, Rochester, Minnesota, USA
| | - Gavin Dunn
- Department of Neurological Surgery, Washington University, St Louis, Missouri, USA
| | - Priscilla K Brastianos
- Departments of Medicine and Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Nancy U Lin
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts, USA
| | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women's Cancer Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA.,Departments of Radiological Sciences and Psychiatry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
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9
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Huang J, Milchenko M, Rao YJ, LaMontagne P, Abraham C, Robinson CG, Huang Y, Shimony JS, Rich KM, Benzinger T. A feasibility study to evaluate early treatment response of brain metastases one week after stereotactic radiosurgery using perfusion weighted imaging. PLoS One 2020; 15:e0241835. [PMID: 33141861 PMCID: PMC7608872 DOI: 10.1371/journal.pone.0241835] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 10/20/2020] [Indexed: 01/06/2023] Open
Abstract
Background To explore if early perfusion-weighted magnetic resonance imaging (PWI) may be a promising imaging biomarker to predict local recurrence (LR) of brain metastases after stereotactic radiosurgery (SRS). Methods This is a prospective pilot study of adult brain metastasis patients who were treated with SRS and imaged with PWI before and 1 week later. Relative cerebral blood volume (rCBV) parameter maps were calculated by normalizing to the mean value of the contralateral white matter on PWI. Cox regression was conducted to explore factors associated with time to LR, with Bonferroni adjusted p<0.0006 for multiple testing correction. LR rates were estimated with the Kaplan-Meier method and compared using the log-rank test. Results Twenty-three patients were enrolled from 2013 through 2016, with 22 evaluable lesions from 16 patients. After a median follow-up of 13.1 months (range: 3.0–53.7), 5 lesions (21%) developed LR after a median of 3.4 months (range: 2.3–5.7). On univariable analysis, larger tumor volume (HR 1.48, 95% CI 1.02–2.15, p = 0.04), lower SRS dose (HR 0.45, 95% CI 0.21–0.97, p = 0.04), and higher rCBV at week 1 (HR 1.07, 95% CI 1.003–1.14, p = 0.04) had borderline association with shorter time to LR. Tumors >2.0cm3 had significantly higher LR than if ≤2.0cm3: 54% vs 0% at 1 year, respectively, p = 0.008. A future study to confirm the association of early PWI and LR of the high-risk cohort of lesions >2.0cm3 is estimated to require 258 patients. Conclusions PWI at week 1 after SRS may have borderline association with LR. Tumors <2.0cm3 have low risk of LR after SRS and may be low-yield for predictive biomarker studies. Information regarding sample size and potential challenges for future imaging biomarker studies may be gleaned from this pilot study.
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Affiliation(s)
- Jiayi Huang
- Department of Radiation Oncology, Washington University School of Medicine, Saint Louis, Missouri, United States of America
| | - Mikhail Milchenko
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, Missouri, United States of America
| | - Yuan J Rao
- Department of Radiation Oncology, Washington University School of Medicine, Saint Louis, Missouri, United States of America
| | - Pamela LaMontagne
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, Missouri, United States of America
| | - Christopher Abraham
- Department of Radiation Oncology, Washington University School of Medicine, Saint Louis, Missouri, United States of America
| | - Clifford G Robinson
- Department of Radiation Oncology, Washington University School of Medicine, Saint Louis, Missouri, United States of America
| | - Yi Huang
- Department of Radiation Oncology, Washington University School of Medicine, Saint Louis, Missouri, United States of America
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, Missouri, United States of America
| | - Keith M Rich
- Department of Neurosurgery, Washington University School of Medicine, Saint Louis, Missouri, United States of America
| | - Tammie Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, Missouri, United States of America
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10
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Lee D, Riestenberg RA, Haskell-Mendoza A, Bloch O. Brain Metastasis Recurrence Versus Radiation Necrosis: Evaluation and Treatment. Neurosurg Clin N Am 2020; 31:575-587. [PMID: 32921353 DOI: 10.1016/j.nec.2020.06.007] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Radiation necrosis (RN) occurs in 5% to 25% of patients with brain metastases treated with stereotactic radiosurgery. RN must be distinguished from recurrent tumor to determine appropriate treatment. Stereotactic biopsy remains the gold standard for identifying RN. Initial treatment of RN often involves management of edema using corticosteroids, antiangiogenic therapies, and hyperbaric oxygen therapy. For refractory symptoms, surgical resection can be considered. Minimally invasive stereotactic laser ablation has the benefit of providing tissue diagnosis and treating RN or recurrent tumor with similar efficacy. Laser ablation should be considered for lesions in need of intervention where the diagnosis requires tissue confirmation.
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Affiliation(s)
- Dennis Lee
- Department of Neurological Surgery, University of California Davis, 4860 Y Street, Suite 3740, Sacramento, CA 95817, USA
| | - Robert A Riestenberg
- Department of Neurological Surgery, University of California Davis, 4860 Y Street, Suite 3740, Sacramento, CA 95817, USA
| | - Aden Haskell-Mendoza
- Department of Neurological Surgery, University of California Davis, 4860 Y Street, Suite 3740, Sacramento, CA 95817, USA
| | - Orin Bloch
- Department of Neurological Surgery, University of California, Davis School of Medicine, University of California Davis, 4860 Y Street, Suite 3740, Sacramento, CA 95817, USA.
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11
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Treglia G, Muoio B, Trevisi G, Mattoli MV, Albano D, Bertagna F, Giovanella L. Diagnostic Performance and Prognostic Value of PET/CT with Different Tracers for Brain Tumors: A Systematic Review of Published Meta-Analyses. Int J Mol Sci 2019; 20:ijms20194669. [PMID: 31547109 PMCID: PMC6802483 DOI: 10.3390/ijms20194669] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 09/16/2019] [Accepted: 09/19/2019] [Indexed: 12/12/2022] Open
Abstract
Background: Several meta-analyses reporting data on the diagnostic performance or prognostic value of positron emission tomography (PET) with different tracers in detecting brain tumors have been published so far. This review article was written to summarize the evidence-based data in these settings. Methods: We have performed a comprehensive literature search of meta-analyses published in the Cochrane library and PubMed/Medline databases (from inception through July 2019) about the diagnostic performance or prognostic value of PET with different tracers in patients with brain tumors. Results: We have summarized the results of 24 retrieved meta-analyses on the use of PET or PET/computed tomography (CT) with different tracers in brain tumors. The tracers included were: fluorine-18 fluorodeoxyglucose (18F-FDG), carbon-11 methionine (11C-methionine), fluorine-18 fluoroethyltyrosine (18F-FET), fluorine-18 dihydroxyphenylalanine (18F-FDOPA), fluorine-18 fluorothymidine (18F-FLT), and carbon-11 choline (11C-choline). Evidence-based data demonstrated good diagnostic performance of PET with different tracers in detecting brain tumors, in particular, radiolabelled amino acid tracers showed the highest diagnostic performance values. All the PET tracers evaluated had significant prognostic value in patients with glioma. Conclusions: Evidence-based data showed a good diagnostic performance for some PET tracers in specific indications and significant prognostic value in brain tumors.
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Affiliation(s)
- Giorgio Treglia
- Clinic of Nuclear Medicine and PET/CT Center, Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, CH-6500 Bellinzona, Switzerland.
- Health Technology Assessment Unit, Academic Education, Research and Innovation Area, General Directorate, Ente Ospedaliero Cantonale, CH-6500 Bellinzona, Switzerland.
- Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital and University of Lausanne, CH-1011 Lausanne, Switzerland.
| | - Barbara Muoio
- Clinic of Medical Oncology, Oncology Institute of Southern Switzerland, Ente Ospedaliero Cantonale, CH-6500 Bellinzona, Switzerland.
| | - Gianluca Trevisi
- Neurosurgical Unit, Presidio Ospedaliero Santo Spirito, IT-65124 Pescara, Italy.
| | - Maria Vittoria Mattoli
- Department of Neurosciences, Imaging and Clinical Sciences, "G. D'Annunzio" University, IT-66100 Chieti, Italy.
| | - Domenico Albano
- Department of Nuclear Medicine, Spedali Civili of Brescia and University of Brescia, IT-25123 Brescia, Italy.
| | - Francesco Bertagna
- Department of Nuclear Medicine, Spedali Civili of Brescia and University of Brescia, IT-25123 Brescia, Italy.
| | - Luca Giovanella
- Clinic of Nuclear Medicine and PET/CT Center, Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, CH-6500 Bellinzona, Switzerland.
- Department of Nuclear Medicine, University Hospital Zurich and University of Zurich, CH-8091 Zurich, Switzerland.
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