Abstract Purpose To accelerate whole‐brain quantitative mapping in preclinical imaging setting. Methods A three‐dimensional (3D) multi‐echo spin echo sequence was highly undersampled with a variable density Poisson distribution to reduce the acquisition time. Advanced iterative reconstruction based on linear subspace constraints was employed to recover high‐quality raw images. Different subspaces, generated using exponential or extended‐phase graph (EPG) simulations or from low‐resolution calibration images, were compared. The subspace dimension was investigated in terms of precision. The method was validated on a phantom containing a wide range of and was then applied to monitor metastasis growth in the mouse brain at 4.7T. Image quality and estimation were assessed for 3 acceleration factors (6/8/10). Results The EPG‐based dictionary gave robust estimations of a large range of . A subspace dimension of 6 was the best compromise between precision and image quality. Combining the subspace constrained reconstruction with a highly undersampled dataset enabled the acquisition of whole‐brain maps, the detection and the monitoring of metastasis growth of less than 500 . Conclusion Subspace‐based reconstruction is suitable for 3D mapping. This method can be used to reach an acceleration factor up to 8, corresponding to an acquisition time of 25 min for an isotropic 3D acquisition of 156 m on the mouse brain, used here for monitoring metastases growth.< Réduire