共 50 条
Quantitative texture analysis in the prediction of IDH status in low-grade gliomas
被引:48
|作者:
Jakola, Asgeir Store
[1
,2
,3
]
Zhang, Yi-Hua
[4
,5
]
Skjulsvik, Anne J.
[6
,7
]
Solheim, Ole
[3
,8
,9
]
Bo, Hans Kristian
[10
,11
]
Berntsen, Erik Magnus
[10
,11
]
Reinertsen, Ingerid
[8
,12
]
Gulati, Sasha
[3
,9
]
Forander, Petter
[13
]
Brismard, Torkel B.
[4
,5
]
机构:
[1] Sahlgrens Univ Hosp, Dept Neurosurg, Bla Straket 5, S-41345 Gothenburg, Sweden
[2] Sahlgrens Acad, Inst Neurosci & Physiol, Gothenburg, Sweden
[3] St Olavs Univ Hosp, Dept Neurosurg, N-7006 Trondheim, Norway
[4] Karolinska Univ Hosp Huddinge, Dept Radiol, Stockholm, Sweden
[5] Karolinska Inst, Div Med Imaging & Technol, Dept Clin Sci Intervent & Technol CLINTEC, Stockholm, Sweden
[6] St Olavs Univ Hosp, Dept Pathol, Trondheim, Norway
[7] Norwegian Univ Sci & Technol, Dept Lab Med Childrens & Womens Hlth, Trondheim, Norway
[8] St Olavs Univ Hosp, Natl Norwegian Advisory Unit Ultrasound & Image G, N-7006 Trondheim, Norway
[9] Norwegian Univ Sci & Technol, Dept Neuromed & Movement Sci, Fac Med, N-7491 Trondheim, Norway
[10] St Olavs Univ Hosp, Dept Radiol & Nucl Med, N-7006 Trondheim, Norway
[11] Norwegian Univ Sci & Technol, Dept Circulat & Med Imaging, Fac Med & Hlth Sci, Trondheim, Norway
[12] SINTEF, Dept Med Technol, Trondheim, Norway
[13] Karolinska Univ Hosp, Dept Neurosurg, Stockholm, Sweden
关键词:
Classification;
Glioma;
IDH;
Radiobiology;
IMAGING BIOMARKER;
HETEROGENEITY;
GLIOBLASTOMA;
SURVIVAL;
CLASSIFICATION;
PARAMETERS;
SYSTEM;
TUMORS;
D O I:
10.1016/j.clineuro.2017.12.007
中图分类号:
R74 [神经病学与精神病学];
学科分类号:
摘要:
Objectives: Molecular markers provide valuable information about treatment response and prognosis in patients with low-grade gliomas (LGG). In order to make this important information available prior to surgery the aim of this study was to explore if molecular status in LGG can be discriminated by preoperative magnetic resonance imaging (MRI). Patients and methods: All patients with histopathologically confirmed LGG with available molecular status who had undergone a preoperative standard clinical MRI protocol using a 3T Siemens Skyra scanner during 2008-2015 were retrospectively identified. Based on Haralick texture parameters and the segmented LGG FLAIR volume we explored if it was possible to predict molecular status. Results: In total 25 patients (nine women, average age 44) fulfilled the inclusion parameters. The textural parameter homogeneity could discriminate between LGG patients with IDH mutation (0.12, IQR 0.10-0.15) and IDH wild type (0.07, IQR 0.06-0.09, p = 0.005). None of the other four analyzed texture parameters (energy, entropy, correlation and inertia) were associated with molecular status. Using ROC curves, the area under curve for predicting IDH mutation was 0.905 for homogeneity, 0.840 for tumor volume and 0.940 for the combined parameters of tumor volume and homogeneity. We could not predict molecular status using the four other chosen texture parameters (energy, entropy, correlation and inertia). Further, we could not separate LGG with IDH mutation with or without 1p19q codeletion. Conclusions: In this preliminary study using Haralick texture parameters based on preoperative clinical FLAIR sequence, the homogeneity parameter could separate IDH mutated LGG from IDH wild type LGG. Combined with tumor volume, these diagnostic properties seem promising.
引用
收藏
页码:114 / 120
页数:7
相关论文