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Rudie JD, Saluja R, Weiss DA, Nedelec P, Calabrese E, Colby JB, Laguna B, Mongan J, Braunstein S, Hess CP, Rauschecker AM, Sugrue LP, Villanueva-Meyer JE. The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset. Radiol Artif Intell 2024; 6:e230126. [PMID: 38381038 PMCID: PMC10982817 DOI: 10.1148/ryai.230126] [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: 04/19/2023] [Revised: 01/11/2024] [Accepted: 02/05/2024] [Indexed: 02/22/2024]
Abstract
Supplemental material is available for this article.
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Affiliation(s)
- Jeffrey D. Rudie
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
| | | | - David A. Weiss
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
| | - Pierre Nedelec
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
| | - Evan Calabrese
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
| | - John B. Colby
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
| | - Benjamin Laguna
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
| | - John Mongan
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
| | - Steve Braunstein
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
| | - Christopher P. Hess
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
| | - Andreas M. Rauschecker
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
| | - Leo P. Sugrue
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
| | - Javier E. Villanueva-Meyer
- From the Center for Intelligent Imaging, Department of Radiology and Biomedical Imaging (J.D.R., D.A.W., P.N., E.C., J.B.C., B.L., J.M., C.P.H., A.M.R., L.P.S., J.E.V.M.) and Department of Radiation Oncology (S.B.), University of California San Francisco, 513 Parnassus Ave, Rm S-261, Box 0628, San Francisco, CA 94143-0628; Department of Radiology, University of California San Diego, San Diego Calif (J.D.R.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (R.S.); and Department of Radiology, Duke University School of Medicine, Durham, NC (E.C.)
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Lang M, Rapalino O, Huang S, Lev MH, Conklin J, Wald LL. Emerging Techniques and Future Directions: Fast and Portable Magnetic Resonance Imaging. Magn Reson Imaging Clin N Am 2022; 30:565-582. [PMID: 35995480 DOI: 10.1016/j.mric.2022.05.005] [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: 12/25/2022]
Abstract
Fast MRI and portable MRI are emerging as promising technologies to improve the speed, efficiency, and availability of MR imaging. Fast MRI methods are increasingly being adopted to create screening protocols for the diagnosis and management of acute pathology in the emergency department. Faster imaging can facilitate timely diagnosis, reduce motion artifacts, and improve departmental MR operations. Point-of-care and portable MRI are emerging technologies that require radiologists to reenvision the role of MRI as a tool with greater accessibility, fewer siting constraints, and the ability to provide valuable diagnostic information at the bedside. Recently introduced commercially available pulse sequences and new MRI scanners are bringing these technologies closer to the patient's clinical setting, and we expect their use to only increase over the coming decade. This article provides an overview of these emerging technologies for emergency radiologists.
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Affiliation(s)
- Min Lang
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - Susie Huang
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; Athinoula A. Martinos Center for Biomedical Imaging, 149 13th Street, Charleston, MA 02129, USA
| | - Michael H Lev
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA
| | - John Conklin
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA.
| | - Lawrence L Wald
- Department of Radiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, USA; Athinoula A. Martinos Center for Biomedical Imaging, 149 13th Street, Charleston, MA 02129, USA
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Rudie JD, Weiss DA, Colby JB, Rauschecker AM, Laguna B, Braunstein S, Sugrue LP, Hess CP, Villanueva-Meyer JE. Three-dimensional U-Net Convolutional Neural Network for Detection and Segmentation of Intracranial Metastases. Radiol Artif Intell 2021; 3:e200204. [PMID: 34136817 PMCID: PMC8204134 DOI: 10.1148/ryai.2021200204] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 02/05/2021] [Accepted: 02/19/2021] [Indexed: 05/05/2023]
Abstract
PURPOSE To develop and validate a neural network for automated detection and segmentation of intracranial metastases on brain MRI studies obtained for stereotactic radiosurgery treatment planning. MATERIALS AND METHODS In this retrospective study, 413 patients (average age, 61 years ± 12 [standard deviation]; 238 women) with a total of 5202 intracranial metastases (median volume, 0.05 cm3; interquartile range, 0.02-0.18 cm3) undergoing stereotactic radiosurgery at one institution were included (January 2017 to February 2020). A total of 563 MRI examinations were performed among the patients, and studies were split into training (n = 413), validation (n = 50), and test (n = 100) datasets. A three-dimensional (3D) U-Net convolutional network was trained and validated on 413 T1 postcontrast or subtraction scans, and several loss functions were evaluated. After model validation, 100 discrete test patients, who underwent imaging after the training and validation patients, were used for final model evaluation. Performance for detection and segmentation of metastases was evaluated using Dice scores, false discovery rates, and false-negative rates, and a comparison with neuroradiologist interrater reliability was performed. RESULTS The median Dice score for segmenting enhancing metastases in the test set was 0.75 (interquartile range, 0.63-0.84). There were strong correlations between manually segmented and predicted metastasis volumes (r = 0.98, P < .001) and between the number of manually segmented and predicted metastases (R = 0.95, P < .001). Higher Dice scores were strongly correlated with larger metastasis volumes on a logarithmically transformed scale (r = 0.71). Sensitivity across the whole test sample was 70.0% overall and 96.4% for metastases larger than 6 mm. There was an average of 0.46 false-positive results per scan, with the positive predictive value being 91.5%. In comparison, the median Dice score between two neuroradiologists was 0.85 (interquartile range, 0.80-0.89), with sensitivity across the test sample being 87.9% overall and 98.4% for metastases larger than 6 mm. CONCLUSION A 3D U-Net-based convolutional neural network was able to segment brain metastases with high accuracy and perform detection at the level of human interrater reliability for metastases larger than 6 mm.Keywords: Adults, Brain/Brain Stem, CNS, Feature detection, MR-Imaging, Neural Networks, Neuro-Oncology, Quantification, Segmentation© RSNA, 2021.
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Affiliation(s)
- Jeffrey D. Rudie
- From the Department of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143
| | - David A. Weiss
- From the Department of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143
| | - John B. Colby
- From the Department of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143
| | - Andreas M. Rauschecker
- From the Department of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143
| | - Benjamin Laguna
- From the Department of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143
| | - Steve Braunstein
- From the Department of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143
| | - Leo P. Sugrue
- From the Department of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143
| | - Christopher P. Hess
- From the Department of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143
| | - Javier E. Villanueva-Meyer
- From the Department of Radiology and Biomedical Imaging, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA 94143
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