title: A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT.
abstract: This paper proposes a novel imaging biomarker of lung cancer relapse from 3-D texture analysis of CT images. Three-dimensional morphological nodular tissue properties are described in terms of 3-D Riesz-wavelets. The responses of the latter are aggregated within nodular regions by means of feature covariances, which leverage rich intra- and inter-variations of the feature space dimensions. When compared to the classical use of the average for feature aggregation, feature covariances preserve spatial co-variations between features. The obtained Riesz-covariance descriptors lie on a manifold governed by Riemannian geometry allowing geodesic measurements and differentiations. The latter property is incorporated both into a kernel for support vector machines (SVM) and a manifold-aware sparse regularized classifier. The effectiveness of the presented models is evaluated on a dataset of 110 patients with non-small cell lung carcinoma (NSCLC) and cancer recurrence information. Disease recurrence within a timeframe of 12 months could be predicted with an accuracy of 81.3-82.7%. The anatomical location of recurrence could be discriminated between local, regional and distant failure with an accuracy of 78.3-93.3%. The obtained results open novel research perspectives by revealing the importance of the nodular regions used to build the predictive models.
authors.forename: Pol
authors.initials: P
authors.lastname: Cirujeda
authors.forename: Yashin
authors.initials: Y
authors.lastname: Dicente Cid
authors.forename: Henning
authors.initials: H
authors.lastname: Muller
authors.forename: Daniel
authors.initials: D
authors.lastname: Rubin
authors.forename: Todd A
authors.initials: TA
authors.lastname: Aguilera
authors.forename: Billy W
authors.initials: BW
authors.lastname: Loo
authors.forename: Maximilian
authors.initials: M
authors.lastname: Diehn
authors.forename: Xavier
authors.initials: X
authors.lastname: Binefa
authors.forename: Adrien
authors.initials: A
authors.lastname: Depeursinge
mesh_terms: D006801:Humans; D008175:Lung Neoplasms; D009364:Neoplasm Recurrence, Local; D060388:Support Vector Machine; D014057:Tomography, X-Ray Computed