## 4 Discussion
To combine data from TEM and SIMS, we needed a common referential to co-localize and co-identify image objects. For this purpose, alignments were required in two contexts: the alignment of the planes of a SIMS analysis and the alignment of SIMS images on TEM images. As mentioned in the review section [52], both the alignment method transformation and evaluation criteria must be adapted to the type of image being aligned. In the case of SIMS plane alignment, the priority is to preserve the number of counted secondary ions (counts). Indeed, each SIMS image plane is a sequence of nano-analyzes, with each nano-analysis corresponding to a pixel. The value of each pixel expressed as counts is an integer, which can be described using Poisson's probability distribution. This property is essential for the statistical analysis of an image and, in particular, the detection of statistically significant low signals [47]. Any image transformation that could alter pixel values is, therefore, not recommended. Here, the SIMS image planes were aligned using lateral translations to preserve the pixel values. These lateral translations were performed with two types of software (Ametek-Cameca's WinImage (v 4.5, 2020) and SIDmaker (v 2.32 2023)) that differed only in their criterion (or measure of similarity) used to evaluate alignment quality. The resulting alignments were sometimes identical and sometimes different. These differences manifested in one or more areas of the image that were sharper than the others. The best alignment method for the whole image or an ROI was chosen on the basis of maximum mutual information. In the context of TEM and SIMS image alignment, the objective and the constraint are different. The top priority is to preserve the definition of the TEM image for the accurate identification of ultrastructures and NP localization. The SIMS image is subsequently transformed to align with the TEM image. The most commonly used alignment methods in correlative imaging involve the sequential application of isotropic and, in some cases, anisotropic transformations [52]. Each transformation is defined by parameters determined through a highly automated process. In our images, isotropic transformations (rigid or elastic) systematically resulted in the correct alignment of only a small zone to the detriment of the rest of the image. We, therefore, developed an alignment module in MoDaT, relying on the direct application of anisotropic transformations characterized by parameters determined manually by the user. We assume that this software provided better alignment for our images, indicated by higher mutual information and lower joint entropy compared to other software (EC-CLEM (v 1.0.1.5) a type of ICY plugging [53], and Fujiyama, (v 4.2.0) a type of ImageJ plugging [54]). In our aligned SIMS and TEM images, we found that the objects seen in the SIMS images systematically appeared larger than the corresponding objects in the TEM images. This was attributed to the lower resolution of NanoSIMS. Indeed, the primary ion beam diameter has been estimated [55] at about 100 nm. As this beam is larger than a pixel (39 nm \(\times\) 39 nm), it overlaps several contiguous pixels during scanning. As a result, the signal spreads across multiple pixels, causing an overestimation of the object dimensions of approximately 200 nm. To align the dimensions of SIMS objects with those of TEM objects, fusion methods for SIMS and TEM images are available [28]. These methods, which combine the advantages of TEM imaging resolution with the analytical performance of SIMS, are particularly suitable when object co-identification is unambiguous and the SIMS signal intensity is high. In our study, when dealing with isolated or aggregated NPs, the SIMS signals were often low, and object co-identification was not always straightforward. Therefore, we opted to overlay the images without using the fusion methods mentioned above despite the observed overflow. SIMS microscopy is generally considered to be one of the most sensitive techniques.