Yun Hwa Roh, E-Nae Cheong, Ji Eun Park, Yangsean Choi, Seung Chai Jung, Sang Woo Song, Young-Hoon Kim, Chang-Ki Hong, Jeong Hoon Kim, Ho Sung Kim
{"title":"考虑空间和时间异质性的成人型弥漫性胶质瘤治疗前后扩散和灌注MRI影像学分子表征","authors":"Yun Hwa Roh, E-Nae Cheong, Ji Eun Park, Yangsean Choi, Seung Chai Jung, Sang Woo Song, Young-Hoon Kim, Chang-Ki Hong, Jeong Hoon Kim, Ho Sung Kim","doi":"10.1002/jmri.29781","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Imaging-based molecular characterization is important for identifying treatment targets in adult-type diffuse gliomas.</p><p><strong>Purpose: </strong>To assess isocitrate dehydrogenase (IDH) mutation and epidermal growth factor receptor (EGFR) amplification status in primary and recurrent gliomas using diffusion and perfusion MRI, addressing spatial and temporal heterogeneity.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Subjects: </strong>Three-hundred and twelve newly diagnosed (cross-sectional set, 57.9 ± 13.2 years, 52.2% male, 235 IDH-wildtype, 71 EGFR-amplified) and 38 recurrent (longitudinal set, 53.1 ± 13.4 years, 44.7% male, 30 IDH-wildtype, 13 EGFR-amplified) adult-type diffuse glioma patients.</p><p><strong>Field strength/sequence: </strong>3.0T; diffusion weighted and dynamic susceptibility contrast-perfusion weighted imaging.</p><p><strong>Assessment: </strong>Radiomics features from contrast-enhancing tumors (CET) and non-enhancing lesions (NEL) were extracted from apparent diffusion coefficient and perfusion maps. Spatial heterogeneity was assessed using intersection and Bhattacharyya distance between CET and NEL. Stable imaging features were identified in patients with unchanged genetic profiles in the longitudinal set. The \"best model,\" using features from the cross-sectional set (n = 312), and the \"concordant model,\" using stable features identified in the longitudinal set (n = 38), were constructed using the LASSO for IDH and EGFR status.</p><p><strong>Statistical tests: </strong>The area under the receiver-operating-characteristic curve (AUC).</p><p><strong>Results: </strong>For IDH mutations, both best and concordant models demonstrated high AUCs in the cross-sectional set (0.936; 95% confidence interval [CI]: 0.903-0.969 and 0.964 [0.943-0.986], respectively). Only the concordant model maintained strong performance in recurrent tumors (AUC, 0.919 vs. 0.656). For EGFR amplification in IDH-wildtype, the best and concordant models showed AUCs of 0.821 (95% CI: 0.761-0.881) and 0.746 (95% CI: 0.675-0.817) in newly diagnosed gliomas, but poor performance in recurrent tumors with AUCs of 0.503 (95% CI: 0.34-0.665) and 0.518 (95% CI: 0.357-0.678).</p><p><strong>Data conclusion: </strong>Diffusion and perfusion MRI characterized IDH status in both newly diagnosed and recurrent gliomas, but showed limited diagnostic performance for EGFR, especially for recurrent tumors.</p><p><strong>Evidence level: </strong>3 TECHNICAL EFFICACY: Stage 3.</p>","PeriodicalId":16140,"journal":{"name":"Journal of Magnetic Resonance Imaging","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Imaging-Based Molecular Characterization of Adult-Type Diffuse Glioma Using Diffusion and Perfusion MRI in Pre- and Post-Treatment Stage Considering Spatial and Temporal Heterogeneity.\",\"authors\":\"Yun Hwa Roh, E-Nae Cheong, Ji Eun Park, Yangsean Choi, Seung Chai Jung, Sang Woo Song, Young-Hoon Kim, Chang-Ki Hong, Jeong Hoon Kim, Ho Sung Kim\",\"doi\":\"10.1002/jmri.29781\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Imaging-based molecular characterization is important for identifying treatment targets in adult-type diffuse gliomas.</p><p><strong>Purpose: </strong>To assess isocitrate dehydrogenase (IDH) mutation and epidermal growth factor receptor (EGFR) amplification status in primary and recurrent gliomas using diffusion and perfusion MRI, addressing spatial and temporal heterogeneity.</p><p><strong>Study type: </strong>Retrospective.</p><p><strong>Subjects: </strong>Three-hundred and twelve newly diagnosed (cross-sectional set, 57.9 ± 13.2 years, 52.2% male, 235 IDH-wildtype, 71 EGFR-amplified) and 38 recurrent (longitudinal set, 53.1 ± 13.4 years, 44.7% male, 30 IDH-wildtype, 13 EGFR-amplified) adult-type diffuse glioma patients.</p><p><strong>Field strength/sequence: </strong>3.0T; diffusion weighted and dynamic susceptibility contrast-perfusion weighted imaging.</p><p><strong>Assessment: </strong>Radiomics features from contrast-enhancing tumors (CET) and non-enhancing lesions (NEL) were extracted from apparent diffusion coefficient and perfusion maps. Spatial heterogeneity was assessed using intersection and Bhattacharyya distance between CET and NEL. Stable imaging features were identified in patients with unchanged genetic profiles in the longitudinal set. The \\\"best model,\\\" using features from the cross-sectional set (n = 312), and the \\\"concordant model,\\\" using stable features identified in the longitudinal set (n = 38), were constructed using the LASSO for IDH and EGFR status.</p><p><strong>Statistical tests: </strong>The area under the receiver-operating-characteristic curve (AUC).</p><p><strong>Results: </strong>For IDH mutations, both best and concordant models demonstrated high AUCs in the cross-sectional set (0.936; 95% confidence interval [CI]: 0.903-0.969 and 0.964 [0.943-0.986], respectively). Only the concordant model maintained strong performance in recurrent tumors (AUC, 0.919 vs. 0.656). For EGFR amplification in IDH-wildtype, the best and concordant models showed AUCs of 0.821 (95% CI: 0.761-0.881) and 0.746 (95% CI: 0.675-0.817) in newly diagnosed gliomas, but poor performance in recurrent tumors with AUCs of 0.503 (95% CI: 0.34-0.665) and 0.518 (95% CI: 0.357-0.678).</p><p><strong>Data conclusion: </strong>Diffusion and perfusion MRI characterized IDH status in both newly diagnosed and recurrent gliomas, but showed limited diagnostic performance for EGFR, especially for recurrent tumors.</p><p><strong>Evidence level: </strong>3 TECHNICAL EFFICACY: Stage 3.</p>\",\"PeriodicalId\":16140,\"journal\":{\"name\":\"Journal of Magnetic Resonance Imaging\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-04-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Magnetic Resonance Imaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/jmri.29781\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Magnetic Resonance Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/jmri.29781","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Imaging-Based Molecular Characterization of Adult-Type Diffuse Glioma Using Diffusion and Perfusion MRI in Pre- and Post-Treatment Stage Considering Spatial and Temporal Heterogeneity.
Background: Imaging-based molecular characterization is important for identifying treatment targets in adult-type diffuse gliomas.
Purpose: To assess isocitrate dehydrogenase (IDH) mutation and epidermal growth factor receptor (EGFR) amplification status in primary and recurrent gliomas using diffusion and perfusion MRI, addressing spatial and temporal heterogeneity.
Study type: Retrospective.
Subjects: Three-hundred and twelve newly diagnosed (cross-sectional set, 57.9 ± 13.2 years, 52.2% male, 235 IDH-wildtype, 71 EGFR-amplified) and 38 recurrent (longitudinal set, 53.1 ± 13.4 years, 44.7% male, 30 IDH-wildtype, 13 EGFR-amplified) adult-type diffuse glioma patients.
Field strength/sequence: 3.0T; diffusion weighted and dynamic susceptibility contrast-perfusion weighted imaging.
Assessment: Radiomics features from contrast-enhancing tumors (CET) and non-enhancing lesions (NEL) were extracted from apparent diffusion coefficient and perfusion maps. Spatial heterogeneity was assessed using intersection and Bhattacharyya distance between CET and NEL. Stable imaging features were identified in patients with unchanged genetic profiles in the longitudinal set. The "best model," using features from the cross-sectional set (n = 312), and the "concordant model," using stable features identified in the longitudinal set (n = 38), were constructed using the LASSO for IDH and EGFR status.
Statistical tests: The area under the receiver-operating-characteristic curve (AUC).
Results: For IDH mutations, both best and concordant models demonstrated high AUCs in the cross-sectional set (0.936; 95% confidence interval [CI]: 0.903-0.969 and 0.964 [0.943-0.986], respectively). Only the concordant model maintained strong performance in recurrent tumors (AUC, 0.919 vs. 0.656). For EGFR amplification in IDH-wildtype, the best and concordant models showed AUCs of 0.821 (95% CI: 0.761-0.881) and 0.746 (95% CI: 0.675-0.817) in newly diagnosed gliomas, but poor performance in recurrent tumors with AUCs of 0.503 (95% CI: 0.34-0.665) and 0.518 (95% CI: 0.357-0.678).
Data conclusion: Diffusion and perfusion MRI characterized IDH status in both newly diagnosed and recurrent gliomas, but showed limited diagnostic performance for EGFR, especially for recurrent tumors.
期刊介绍:
The Journal of Magnetic Resonance Imaging (JMRI) is an international journal devoted to the timely publication of basic and clinical research, educational and review articles, and other information related to the diagnostic applications of magnetic resonance.