title: A multi-resolution textural approach to diagnostic neuropathology reporting.
abstract: We present a computer aided diagnostic workflow focusing on two diagnostic branch points in neuropathology (intraoperative consultation and p53 status in tumor biopsy specimens) by means of texture analysis via discrete wavelet frames decomposition. For intraoperative consultation, our methodology is capable of classifying glioblastoma versus metastatic cancer by extracting textural features from the non-nuclei region of cytologic preparations based on the imaging characteristics of glial processes, which appear as anisotropic thin linear structures. For metastasis, these are homogeneous in appearance, thus suitable and extractable texture features distinguish the two tissue types. Experiments on 53 images (29 glioblastomas and 24 metastases) resulted in average accuracy as high as 89.7 % for glioblastoma, 87.5 % for metastasis and 88.7 % overall. For p53 interpretation, we detect and classify p53 status by classifying staining intensity into strong, moderate, weak and negative sub-classes. We achieved this by developing a novel adaptive thresholding for detection, a two-step rule based on weighted color and intensity for the classification of positively and negatively stained nuclei, followed by texture classification to classify the positively stained nuclei into the strong, moderate and weak intensity sub-classes. Our detection method is able to correctly locate and distinguish the four types of cells, at 85 % average precision and 88 % average sensitivity rate. These classification methods on the other hand recorded 81 % accuracy in classifying the positive and negative cells, and 60 % accuracy in further classifying the positive cells into the three intensity groups, which is comparable with neuropathologists' markings.
authors.affiliation: Faculty of Engineering, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor, Malaysia.
authors.forename: Mohammad Faizal Ahmad
authors.initials: MFA
authors.lastname: Fauzi
authors.affiliation: Department of Pathology, The Ohio State University, Columbus, OH, USA.
authors.forename: Hamza Numan
authors.initials: HN
authors.lastname: Gokozan
authors.affiliation: Department of Neurological Surgery, The Ohio State University, Columbus, OH, USA.
authors.forename: Brad
authors.initials: B
authors.lastname: Elder
authors.affiliation: Division of Neuro-oncology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
authors.forename: Vinay K
authors.initials: VK
authors.lastname: Puduvalli
authors.affiliation: Department of Pathology, The Ohio State University, Columbus, OH, USA.|Department of Pathology and Laboratory Medicine, Nationwide Children's Hospital, Columbus, OH, USA.|Division of Anatomy, The Ohio State University, Columbus, OH, USA.
authors.forename: Christopher R
authors.initials: CR
authors.lastname: Pierson
authors.affiliation: Department of Pathology, The Ohio State University, Columbus, OH, USA.|Department of Pathology, Division of Neuropathology, The Ohio State University College of Medicine, 4169 Graves Hall, 333 W 10th Avenue, Columbus, OH 43210, USA.
authors.forename: José Javier
authors.initials: JJ
authors.lastname: Otero
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.|250 Lincoln Tower, 1800 Cannon Drive, Columbus, OH 43210, USA.|320-K Lincoln Tower, Columbus, USA.
authors.forename: Metin N
authors.initials: MN
authors.lastname: Gurcan
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001921:Brain / Q000473:pathology*; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000556:secondary; D005260:Female; D005909:Glioblastoma / Q000175:diagnosis* / Q000556:secondary; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D059906:Neuroimaging; D000069338:Neuropathology; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D016159:Tumor Suppressor Protein p53 / Q000378:metabolism; D058067:Wavelet Analysis
chemical_list: D016159:Tumor Suppressor Protein p53
keywords: Discrete wavelet frames; Glioblastoma; Intra-operative consultation; Metastasis; Prognostic reporting; Texture analysis