Habitat-Derived Radiomic Features of Planning Target Volume to Determine the Local Recurrence After Radiotherapy in Patients with Gliomas: A Feasibility Study.

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Title: Habitat-Derived Radiomic Features of Planning Target Volume to Determine the Local Recurrence After Radiotherapy in Patients with Gliomas: A Feasibility Study.
Authors: Wang Y; Brain Oncology Center, Hefei Cancer Hospital of CAS, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China.; Brain Oncology Center, Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, China., Lin L; Brain Oncology Center, Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, China., Hu Z; Brain Oncology Center, Hefei Cancer Hospital of CAS, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China.; Brain Oncology Center, Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, China., Wang H; Brain Oncology Center, Hefei Cancer Hospital of CAS, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China. hzwanghfcas@163.com.; Brain Oncology Center, Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, China. hzwanghfcas@163.com.
Source: Journal of imaging informatics in medicine [J Imaging Inform Med] 2026 Apr; Vol. 39 (2), pp. 1632-1644. Date of Electronic Publication: 2025 Jul 02.
Publication Type: Journal Article
Journal Info: Publisher: Springer Nature Country of Publication: Switzerland NLM ID: 9918663679206676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2948-2933 (Electronic) Linking ISSN: 29482925 NLM ISO Abbreviation: J Imaging Inform Med Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Habitat-Derived Radiomic Features of Planning Target Volume to Determine the Local Recurrence After Radiotherapy in Patients with Gliomas: A Feasibility Study.
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  Data: <searchLink fieldCode="AU" term="%22Wang+Y%22">Wang Y</searchLink>; Brain Oncology Center, Hefei Cancer Hospital of CAS, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China.; Brain Oncology Center, Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, China.<br /><searchLink fieldCode="AU" term="%22Lin+L%22">Lin L</searchLink>; Brain Oncology Center, Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, China.<br /><searchLink fieldCode="AU" term="%22Hu+Z%22">Hu Z</searchLink>; Brain Oncology Center, Hefei Cancer Hospital of CAS, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China.; Brain Oncology Center, Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, China.<br /><searchLink fieldCode="AU" term="%22Wang+H%22">Wang H</searchLink>; Brain Oncology Center, Hefei Cancer Hospital of CAS, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031, China. hzwanghfcas@163.com.; Brain Oncology Center, Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, 230031, China. hzwanghfcas@163.com.
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  Data: <searchLink fieldCode="JN" term="%229918663679206676%22">Journal of imaging informatics in medicine</searchLink> [J Imaging Inform Med] 2026 Apr; Vol. 39 (2), pp. 1632-1644. <i>Date of Electronic Publication: </i>2025 Jul 02.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer+Nature%22">Springer Nature </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>9918663679206676 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2948-2933 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2229482925%22">29482925 </searchLink><i>NLM ISO Abbreviation: </i>J Imaging Inform Med <i>Subsets: </i>MEDLINE
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      – Type: doi
        Value: 10.1007/s10278-025-01591-7
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      – Code: eng
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      – TitleFull: Habitat-Derived Radiomic Features of Planning Target Volume to Determine the Local Recurrence After Radiotherapy in Patients with Gliomas: A Feasibility Study.
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            NameFull: Wang Y
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            NameFull: Lin L
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            NameFull: Hu Z
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            – D: 01
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              Text: 2026 Apr
              Type: published
              Y: 2026
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