title: 3D texture analysis for classification of second harmonic generation images of human ovarian cancer.
abstract: Remodeling of the collagen architecture in the extracellular matrix (ECM) has been implicated in ovarian cancer. To quantify these alterations we implemented a form of 3D texture analysis to delineate the fibrillar morphology observed in 3D Second Harmonic Generation (SHG) microscopy image data of normal (1) and high risk (2) ovarian stroma, benign ovarian tumors (3), low grade (4) and high grade (5) serous tumors, and endometrioid tumors (6). We developed a tailored set of 3D filters which extract textural features in the 3D image sets to build (or learn) statistical models of each tissue class. By applying k-nearest neighbor classification using these learned models, we achieved 83-91% accuracies for the six classes. The 3D method outperformed the analogous 2D classification on the same tissues, where we suggest this is due the increased information content. This classification based on ECM structural changes will complement conventional classification based on genetic profiles and can serve as an additional biomarker. Moreover, the texture analysis algorithm is quite general, as it does not rely on single morphological metrics such as fiber alignment, length, and width but their combined convolution with a customizable basis set.
authors: Department of Medical Physics, University of Wisconsin- Madison, Madison, WI 53706, USA.|Morgridge Institute for Research, Madison, WI 53715, USA.
authors: Bruce
authors: B
authors: Wen
authors: Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
authors: Kirby R
authors: KR
authors: Campbell
authors: Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
authors: Karissa
authors: K
authors: Tilbury
authors: VU Medical Center, VU University Amsterdam, Amsterdam, Netherlands.
authors: Oleg
authors: O
authors: Nadiarnykh
authors: Department of Obstetrics and Gynecology, University of Connecticut Health Center, Farmington, CT 06030, USA.
authors: Molly A
authors: MA
authors: Brewer
authors: Department of Obstetrics and Gynecology, University of Wisconsin-Madison, Madison, WI 53706, USA.
authors: Manish
authors: M
authors: Patankar
authors: Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA.
authors: Vikas
authors: V
authors: Singh
authors: Morgridge Institute for Research, Madison, WI 53715, USA.|Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
authors: Kevin W
authors: KW
authors: Eliceiri
authors: Department of Medical Physics, University of Wisconsin- Madison, Madison, WI 53706, USA.|Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
authors: Paul J
authors: PJ
authors: Campagnola
mesh_terms: D000465:Algorithms; D003094:Collagen / Q000378:metabolism; D003936:Diagnosis, Computer-Assisted / Q000379:methods / Q000706:statistics & numerical data; D005109:Extracellular Matrix / Q000378:metabolism / Q000473:pathology; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods / Q000706:statistics & numerical data; D010051:Ovarian Neoplasms / Q000145:classification / Q000000981:diagnostic imaging* / Q000378:metabolism; D000073798:Second Harmonic Generation Microscopy / Q000379:methods* / Q000706:statistics & numerical data
chemical_list: D003094:Collagen