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Arana E, Arribas LA. Letter regarding “Consensus recommendations for a standardized brain tumor imaging protocol for clinical trials in brain metastases”. Neuro Oncol 2020; 22:1705. [DOI: 10.1093/neuonc/noaa176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Estanislao Arana
- Department of Radiology, Valencia Institute of Oncology, Valencia, Spain
| | - Leoncio A Arribas
- Department of Radiotherapy, Valencia Institute of Oncology, Valencia, Spain
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Nicholls LW, Pinkham MB, Bernard A, Lusk R, Watkins T, Hall B, Olson S, Foote MC. Radiological Kinetics of Brain Metastases and Clinical Implications for Patients Treated With Stereotactic Radiosurgery. Clin Oncol (R Coll Radiol) 2018; 31:34-40. [PMID: 30279038 DOI: 10.1016/j.clon.2018.09.005] [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: 04/07/2018] [Revised: 07/03/2018] [Accepted: 08/22/2018] [Indexed: 11/30/2022]
Abstract
AIMS Select patients with brain metastases receive stereotactic radiosurgery (SRS) with the objective of improving survival and intracranial disease control. Brain metastases number and volume are prognostic factors used to inform patient selection. The aim of this study was to assess the rate of change of brain metastases size and number (growth kinetics) between the diagnostic and day of SRS magnetic resonance imaging (MRI) scans. MATERIALS AND METHODS All patients treated with Gamma Knife SRS between October 2015 and April 2017 were included in this single-centre retrospective analysis. Brain metastases number and diameter were recorded at diagnosis and treatment. For patients with multiple brain metastases, the largest lesion was the index lesion. Distant intracranial control and overall survival were reported from the date of SRS. RESULTS In total, 146 patients received 156 episodes of SRS. The median interval between diagnostic and SRS MRI was 20 days (range 1-68). Interval growth in the index lesion of at least 3 mm or the development of a new brain metastasis was noted in 60.2% of patients. This was associated with age less than 60 years (P = 0.001), Eastern Cooperative Oncology Group (ECOG) performance status 2 or above (P = 0.04), non-small cell lung carcinoma (NSCLC) (P = 0.03) or melanoma histologies (P = 0.05) and uncontrolled extracranial disease (P = 0.05). These patients were also more likely to develop distant intracranial recurrence (P = 0.046). Clinically significant growth was not associated with scan interval or differences in overall survival. The Kaplan-Meier estimate of probability of survival at 12 months was 59.3% (95% confidence interval 46.7-75.2%) for all patients. CONCLUSION Intracranial progression between diagnosis and day of SRS is common. Risk factors are uncontrolled extracranial disease, poorer performance status, NSCLC or melanoma histologies and age less than 60 years. These patients would benefit from an MRI closer to treatment to inform patient selection and target delineation for SRS planning.
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Affiliation(s)
- L W Nicholls
- Gamma Knife Centre of Queensland, Princess Alexandra Hospital, Brisbane, Australia; School of Medicine, University of Queensland, Brisbane, Australia.
| | - M B Pinkham
- Gamma Knife Centre of Queensland, Princess Alexandra Hospital, Brisbane, Australia; School of Medicine, University of Queensland, Brisbane, Australia
| | - A Bernard
- QFAB Bioinformatics, Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
| | - R Lusk
- Gamma Knife Centre of Queensland, Princess Alexandra Hospital, Brisbane, Australia
| | - T Watkins
- Gamma Knife Centre of Queensland, Princess Alexandra Hospital, Brisbane, Australia
| | - B Hall
- Gamma Knife Centre of Queensland, Princess Alexandra Hospital, Brisbane, Australia
| | - S Olson
- Gamma Knife Centre of Queensland, Princess Alexandra Hospital, Brisbane, Australia
| | - M C Foote
- Gamma Knife Centre of Queensland, Princess Alexandra Hospital, Brisbane, Australia; School of Medicine, University of Queensland, Brisbane, Australia
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Liu Y, Stojadinovic S, Hrycushko B, Wardak Z, Lau S, Lu W, Yan Y, Jiang SB, Zhen X, Timmerman R, Nedzi L, Gu X. A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery. PLoS One 2017; 12:e0185844. [PMID: 28985229 PMCID: PMC5630188 DOI: 10.1371/journal.pone.0185844] [Citation(s) in RCA: 92] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Accepted: 09/20/2017] [Indexed: 12/21/2022] Open
Abstract
Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS) data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs) of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases.
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Affiliation(s)
- Yan Liu
- School of Electrical Engineering and Information, Sichuan University, Chengdu, Sichuan, China
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Strahinja Stojadinovic
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Brian Hrycushko
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Zabi Wardak
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Steven Lau
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Weiguo Lu
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Yulong Yan
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Steve B. Jiang
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Xin Zhen
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
- Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China
| | - Robert Timmerman
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Lucien Nedzi
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
| | - Xuejun Gu
- Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX, United States of America
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