In this paper, the impact of low-frequency noise on terahertz-computed tomography (THz-CT) is analyzed for several measurement configurations and pyroelectric detectors. We acquire real noise data from a continuous millimeter-wave tomographic scanner in order to figure out its impact on reconstructed images. Second, noise characteristics are quantified according to two distinct acquisition methods by (i) extrapolating from experimental acquisitions a sinogram for different noise backgrounds and (ii) reconstructing the corresponding spatial distributions in a slice using a CT reconstruction algorithm. Then we describe the low-frequency noise fingerprint and its influence on reconstructed images. Thanks to the observations, we demonstrate that some experimental choices can dramatically affect the 3D rendering of reconstructions. Thus, we propose some experimental methodologies optimizing the resulting quality and accuracy of the 3D reconstructions, with respect to the low-frequency noise characteristics observed during acquisitions.