Spatial Conditional Association Networks in Registered Tumor Volumes R package ISPAT3D version 0.3.1 Fits tumor-zone-specific conditional cell-density networks from registered three-dimensional multiplex imaging. An anisotropic Matern-3/2 Gaussian process is estimated per variable and zone using a Vecchia likelihood on spatially balanced anchors; predictions at all selected cells yield residual covariance sufficient statistics. Gaussian maximum likelihood then fits a shared-plus-zone factor covariance model. A matched section-wise planar fit uses the same selected cells and covariance estimator. This extends the spatially informed cell-density analysis of Bhadury et al. (2026) <doi:10.1038/s41598-026-35341-8>. Software Imports: gpboost, graphics, stats, utils Suggests: data.table, knitr, rmarkdown, testthat (>= 3.0.0) Sagnik Bhadury <bhadury@umich.edu> Comprehensive R Archive Network (CRAN) Sagnik Bhadury [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=ISPAT3D/LICENSE) 2026-09-27 application/tgz https://CRAN.R-project.org/package=ISPAT3D doi:10.32614/CRAN.package.ISPAT3D