Primary central nervous system lymphoma and atypical glioblastoma: differentiation using the initial area under the curve derived from dynamic contrast-enhanced MR and the apparent diffusion coefficient.

Objectives: To evaluate the ability of the initial area under the curve (IAUC) derived from dynamic contrast-enhanced MR imaging (DCE-MRI) and apparent diffusion coefficient (ADC) in differentiating between primary central nervous system lymphoma (PCNSL) and atypical glioblastoma (GBM).Methods: We r...

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Publicado en:European Radiology Vol. 27; no. 4; pp. 1344 - 1352
Autores principales: Choi, Yoon, Lee, Ho-Joon, Ahn, Sung, Chang, Jong, Kang, Seok-Gu, Kim, Eui, Kim, Se, Lee, Seung-Koo, Choi, Yoon Seong, Ahn, Sung Soo, Chang, Jong Hee, Kim, Eui Hyun, Kim, Se Hoon
Formato: Journal Article
Publicado: Springer Nature Apr2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2017
      vid: 27
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      pub: Springer Nature
      place: New York, New York
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        NLM27436023
        10.1007/s00330-016-4484-2
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        atl: Primary central nervous system lymphoma and atypical glioblastoma: differentiation using the initial area under the curve derived from dynamic contrast-enhanced MR and the apparent diffusion coefficient.
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          Choi, Yoon
          Lee, Ho-Joon
          Ahn, Sung
          Chang, Jong
          Kang, Seok-Gu
          Kim, Eui
          Kim, Se
          Lee, Seung-Koo
          Choi, Yoon Seong
          Ahn, Sung Soo
          Chang, Jong Hee
          Kim, Eui Hyun
          Kim, Se Hoon
        affil: Department of Radiology and Research Institute of Radiological Science , Yonsei University College of Medicine , 50-1 Yonsei-ro Seodaemun-gu 03722 Korea
      sug:
        subj:
          Image Enhancement Methods
          Contrast Media
          Glioma
          Lymphoma
          Central Nervous System Neoplasms
          Magnetic Resonance Imaging Methods
          Aged
          Glioma Pathology
          Retrospective Design
          Female
          Lymphoma Pathology
          Central Nervous System Neoplasms Pathology
          Sensitivity and Specificity
          Brain Neoplasms
          Male
          Reproducibility of Results
          Middle Age
          Diagnosis, Differential
          Pharmacokinetics
          Brain Neoplasms Pathology
          Aged: 65+ years
          Middle Aged: 45-64 years
          Female
          Male
      ab: Objectives: To evaluate the ability of the initial area under the curve (IAUC) derived from dynamic contrast-enhanced MR imaging (DCE-MRI) and apparent diffusion coefficient (ADC) in differentiating between primary central nervous system lymphoma (PCNSL) and atypical glioblastoma (GBM).Methods: We retrospectively identified 19 patients with atypical GBM (less than 13 % necrosis of the enhancing tumour), and 23 patients with PCNSL. The histogram parameters of IAUC at 30, 60, 90 s (IAUC30, IAUC60, and IAUC90), and ADC were compared between PCNSL and GBM. The diagnostic performances and added values of the IAUC and ADC for differentiating between PCNSL and GBM were evaluated. Interobserver agreement was assessed via intraclass correlation coefficient (ICC).Results: The IAUC and ADC parameters were higher in GBM than in PCNSL. The 90th percentile (p90) of IAUC30 and 10th percentile (p10) of ADC showed the best diagnostic performance. Adding p90 of IAUC30 to p10 of ADC improved the differentiation between PCNSL and GBM (area under the ROC curve [AUC] = 0.886), compared to IAUC30 or ADC alone (AUC = 0.789 and 0.744; P < 0.05 for all). The ICC was 0.96 for p90 of IAUC30.Conclusions: The IAUC may be a useful parameter together with ADC for differentiating between PCNSL and atypical GBM.Key Points: • High reproducibility is essential for practical implementation of advanced MRI parameters. • IAUC and ADC are highly reproducible parameters. • IAUC values were higher in atypical GBM than in PCNSL. • Adding IAUC to ADC improved the differentiation between PCNSL and GBM. • IAUC with ADC are useful for differentiating PCNSL from GBM.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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