ModelArray: An R package for statistical analysis of fixel-wise data

Chenying Zhao; Tinashe M Tapera; Joëlle Bagautdinova; Josiane Bourque; Sydney Covitz; Raquel E Gur; Ruben C Gur; Bart Larsen; Kahini Mehta; Steven L Meisler; Kristin Murtha; John Muschelli; David R Roalf; Valerie J Sydnor; Alessandra M Valcarcel; Russell T Shinohara; Matthew Cieslak; Theodore D Satterthwaite

doi:10.1016/j.neuroimage.2023.120037

ModelArray: An R package for statistical analysis of fixel-wise data

Neuroimage. 2023 May 1:271:120037. doi: 10.1016/j.neuroimage.2023.120037. Epub 2023 Mar 15.

Authors

Chenying Zhao¹, Tinashe M Tapera², Joëlle Bagautdinova², Josiane Bourque², Sydney Covitz², Raquel E Gur³, Ruben C Gur³, Bart Larsen², Kahini Mehta², Steven L Meisler⁴, Kristin Murtha², John Muschelli⁵, David R Roalf³, Valerie J Sydnor², Alessandra M Valcarcel⁶, Russell T Shinohara⁷, Matthew Cieslak², Theodore D Satterthwaite⁸

Affiliations

¹ Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA; Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA; Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
² Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA; Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
³ Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
⁴ Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA 02139, USA.
⁵ Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
⁶ Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA.
⁷ Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA.
⁸ Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA; Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address: sattertt@pennmedicine.upenn.edu.

Abstract

Diffusion MRI is the dominant non-invasive imaging method used to characterize white matter organization in health and disease. Increasingly, fiber-specific properties within a voxel are analyzed using fixels. While tools for conducting statistical analyses of fixel-wise data exist, currently available tools support only a limited number of statistical models. Here we introduce ModelArray, an R package for mass-univariate statistical analysis of fixel-wise data. At present, ModelArray supports linear models as well as generalized additive models (GAMs), which are particularly useful for studying nonlinear effects in lifespan data. In addition, ModelArray also aims for scalable analysis. With only several lines of code, even large fixel-wise datasets can be analyzed using a standard personal computer. Detailed memory profiling revealed that ModelArray required only limited memory even for large datasets. As an example, we applied ModelArray to fixel-wise data derived from diffusion images acquired as part of the Philadelphia Neurodevelopmental Cohort (n = 938). ModelArray revealed anticipated nonlinear developmental effects in white matter. Moving forward, ModelArray is supported by an open-source software development model that can incorporate additional statistical models and other imaging data types. Taken together, ModelArray provides a flexible and efficient platform for statistical analysis of fixel-wise data.

Keywords: Big data; Development; Fixel-based analysis; MRI; Software; Statistical analysis.

Publication types

Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Diffusion Magnetic Resonance Imaging / methods
Humans
Models, Statistical
Research Design
Software
White Matter*

Abstract

Publication types

MeSH terms

Grants and funding