Abstract
The effects of a computer-aided diagnosis (CAD) system based on quantitative intensity features with magnetic resonance (MR) imaging (MRI) were evaluated by examining radiologists' performance in grading gliomas. The acquired MRI database included 71 lower-grade gliomas and 34 glioblastomas. Quantitative image features were extracted from the tumor area and combined in a CAD system to generate a prediction model. The effect of the CAD system was evaluated in a two-stage procedure. First, a radiologist performed a conventional reading. A sequential second reading was determined with a malignancy estimation by the CAD system. Each MR image was regularly read by one radiologist out of a group of three radiologists. The CAD system achieved an accuracy of 87% (91/105), a sensitivity of 79% (27/34), a specificity of 90% (64/71), and an area under the receiver operating characteristic curve (Az) of 0.89. In the evaluation, the radiologists’ Az values significantly improved from 0.81, 0.87, and 0.84 to 0.90, 0.90, and 0.88 with p = 0.0011, 0.0076, and 0.0167, respectively. Based on the MR image features, the proposed CAD system not only performed well in distinguishing glioblastomas from lower-grade gliomas but also provided suggestions about glioma grading to reinforce radiologists’ confidence rating.
Highlights
Diffuse gliomas are the most frequent primary brain tumors formed of neoplastic cells that display glial cell differentiation
With the complementary power of various image features, the performance of the computer-aided diagnosis (CAD) system achieved an accuracy of 87% (Table 1)
Extracting global and local intensity features describing the gray-scale distribution of tissues in the tumor area is useful in interpreting heterogeneous patterns in magnetic resonance (MR) images
Summary
Diffuse gliomas are the most frequent primary brain tumors formed of neoplastic cells that display glial cell differentiation They can be subdivided by the degree of malignancy into grades 2 (low grade) to 4 (high malignancy) on the basis of histopathological and clinical criteria established by the World Health Organization (WHO) [1,2]. Glioblastomas (GBMs), WHO grade 4 tumors, are the most aggressive tumor type with a very poor prognosis [3]. Lower-grade gliomas (LGGs, grades 2 and 3) have more-favorable outcomes with mean survival times ranging 2~8 years [4] Therapeutic approaches for these two groups of tumor differ. More-aggressive and combination managements including surgery, radiation therapy, chemotherapy, and targeted therapy are always reserved for GBMs [5]. Determining the PLOS ONE | DOI:10.1371/journal.pone.0171342 February 3, 2017
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