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Lanman TA, Cao TQ, Miller JJ, Nagpal S. Ready to INDIGO: Vorasidenib Ushers in the Era of Isocitrate Dehydrogenase Inhibition in Low-Grade Glioma. Int J Radiat Oncol Biol Phys 2024; 118:334-336. [PMID: 38220256 DOI: 10.1016/j.ijrobp.2023.10.045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 10/23/2023] [Indexed: 01/16/2024]
Affiliation(s)
- Tyler A Lanman
- Pappas Center for Neuro-Oncology, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
| | - Toni Q Cao
- Department of Neurology, Stanford University, Palo Alto, California
| | - Julie J Miller
- Pappas Center for Neuro-Oncology, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts
| | - Seema Nagpal
- Department of Neurology, Stanford University, Palo Alto, California.
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Kinslow CJ, Brown PD, Iwamoto FM, Wu CC, Yu JB, Cheng SK, Wang TJC. Where Do We (INDI)GO From Here? Int J Radiat Oncol Biol Phys 2024; 118:330-333. [PMID: 38220255 DOI: 10.1016/j.ijrobp.2023.09.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 09/09/2023] [Indexed: 01/16/2024]
Affiliation(s)
- Connor J Kinslow
- Department of Radiation Oncology, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, New York, New York; Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, New York, New York
| | - Paul D Brown
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
| | - Fabio M Iwamoto
- Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, New York, New York; Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, New York, New York
| | - Cheng-Chia Wu
- Department of Radiation Oncology, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, New York, New York; Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, New York, New York
| | - James B Yu
- Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, New York, New York
| | - Simon K Cheng
- Department of Radiation Oncology, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, New York, New York; Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, New York, New York; Department of Radiation Oncology, James J. Peters Veterans Affairs Medical Center, Bronx, New York
| | - Tony J C Wang
- Department of Radiation Oncology, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, New York, New York; Herbert Irving Comprehensive Cancer Center, Columbia University Vagelos College of Physicians and Surgeons and NewYork-Presbyterian, New York, New York.
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Wu Y, Chen Y, Yang Y, Lin C, Su S, Zhao J, Wu S, Wu G, Liu H, Liu X, Yang Z, Zhang J, Huang B. Predicting brain age using partition modeling strategy and atlas-based attentional enhancement in the Chinese population. Cereb Cortex 2024; 34:bhae030. [PMID: 38342684 DOI: 10.1093/cercor/bhae030] [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: 11/13/2023] [Revised: 01/13/2024] [Accepted: 01/15/2024] [Indexed: 02/13/2024] Open
Abstract
As a biomarker of human brain health during development, brain age is estimated based on subtle differences in brain structure from those under typical developmental. Magnetic resonance imaging (MRI) is a routine diagnostic method in neuroimaging. Brain age prediction based on MRI has been widely studied. However, few studies based on Chinese population have been reported. This study aimed to construct a brain age predictive model for the Chinese population across its lifespan. We developed a partition prediction method based on transfer learning and atlas attention enhancement. The participants were separated into four age groups, and a deep learning model was trained for each group to identify the brain regions most critical for brain age prediction. The Atlas attention-enhancement method was also used to help the models focus only on critical brain regions. The proposed method was validated using 354 participants from domestic datasets. For prediction performance in the testing sets, the mean absolute error was 2.218 ± 1.801 years, and the Pearson correlation coefficient (r) was 0.969, exceeding previous results for wide-range brain age prediction. In conclusion, the proposed method could provide brain age estimation to assist in assessing the status of brain health.
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Affiliation(s)
- Yingtong Wu
- Medical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
- Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
- Paul C Lauterbur Research Center for Biomedical Imaging, Shenzhen Key Laboratory for MRI, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen 518055, Guangdong Province, China
| | - Yingqian Chen
- Department of Radiology, the First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Second Road, Guangzhou 510080, Guangdong Province, China
| | - Yang Yang
- Department of Radiology, Suining Central Hospital, 127 Desheng West Road, Suining 629099, Sichuan Province, China
- Medical Imaging Center of Guizhou Province, Department of Radiology, The Affiliated Hospital of Zunyi Medical University, 149 Dalian Road, Zunyi 563000, Guizhou Province, China
| | - Chuxuan Lin
- Medical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
- Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
| | - Shu Su
- Department of Radiology, the First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Second Road, Guangzhou 510080, Guangdong Province, China
| | - Jing Zhao
- Department of Radiology, the First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Second Road, Guangzhou 510080, Guangdong Province, China
| | - Songxiong Wu
- Radiology Department, Shenzhen University General Hospital and Shenzhen University Clinical Medical Academy, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
| | - Guangyao Wu
- Radiology Department, Shenzhen University General Hospital and Shenzhen University Clinical Medical Academy, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
| | - Heng Liu
- Medical Imaging Center of Guizhou Province, Department of Radiology, The Affiliated Hospital of Zunyi Medical University, 149 Dalian Road, Zunyi 563000, Guizhou Province, China
| | - Xia Liu
- Department of Radiology, Shenzhen Mental Health Center, Shenzhen Kangning Hospital, 1080 Cuizhu Road, Shenzhen 518118, Guangdong Province, China
| | - Zhiyun Yang
- Department of Radiology, the First Affiliated Hospital, Sun Yat-sen University, 58 Zhongshan Second Road, Guangzhou 510080, Guangdong Province, China
| | - Jian Zhang
- Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, 1068 Xueyuan Avenue, Shenzhen 518055, Guangdong Province, China
- School of Pharmaceutical Sciences, Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
| | - Bingsheng Huang
- Medical AI Lab, School of Biomedical Engineering, Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
- Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, 1066 Xueyuan Avenue, Shenzhen 518060, Guangdong Province, China
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