## 2 **Introduction**  
Commonly, the treatment planning of cancer patients begins with localisation of primary and secondary tumours and quantification of their volume. Depending on these and many other mass(es) parameters, cancer treatments are based on different chemotherapy, radiotherapy, immunotherapy, and chirurgical surgery procedures. Therefore, volume is one of the most relevant features for the treatment planning of an in vivo tumour. Symmetrically, it becomes important to evaluate the effects of drugs and radiotherapy treatments when using 3D in vitro models, among which multicellular three-dimension (3D)-_oids_ (e.g., _spheroids_, _organoids_). In particular, the reduction of the number of cancer cells and thus tumour volume is a common indicator of treatment effectiveness [1]. The accuracy of the volume estimation is strongly dependent on the geometry of the in vitro model used and obtaining reliable measurements can be really challenging when using models not having the shape of a real sphere. Recently, we have classified the most common terms used for 3D multicellular in vitro models according to their geometry [2]: _multicellular aggregate_ is the general term for 3D cell-cell aggregates free from a defined structural obligation; _spheroid_ refers to a multicellular aggregate having a nearly spherical shape; _organoid_ indicates a self-renewing multicellular aggregate of irregular shape. In case of _organoids_ and 3D multicellular _aggregates_ without a well-defined geometrical shape in general, volume estimation based on the measurement of a diameter or perpendicular axes become really imprecise [3]. In case of a _spheroid_ (i.e., multicellular _aggregates_ having a nearly spherical shape [2]), such procedure is reliable, even if performed using a single projection acquired for instance with a standard brightfield microscope. In this scenario, several open-source tools like _Temporal Analysis of Spheroid Imaging_ (_TASI_, [4]) and _Reconstruction and Visualization from a Single Projection_ (_ReViSP_, [5]) are available [3]. In all the other cases, when the model shape is typically anisotropic, a 3D imaging system is needed for acquiring data of the whole 3D surface of the cell _aggregate_. Micro computerized axial tomography (Micro-CAT) and micro positron emission tomography (Micro-PET) systems provide data about the 3D cell organisation, but they are expensive and not available to all researchers. Furthermore, they are characterised by limited resolution, so they provide reliable measurements just in case of large cell cultures. Label-free, non-invasive optical coherence tomography (OCT) imaging platforms can be also considered to characterise the 3D morphology of multicellular _aggregates_[6]. However, OCT imaging platforms are not common in the biological laboratories and a very few studies report OCT-based volume assessment of 3D -_oids_. Accordingly, the estimation of the volume of a 3D in vitro model with a diameter below a millimetre is typically performed by using an optical fluorescence microscope able to \(z\)-analyse cell _aggregates_ and acquire a \(z\)-stack of images by scanning the object. Accordingly, confocal, multiphoton, and light-sheet fluorescence microscopy (LSFM) are typically applied to 3D cell cultures imaging [7]. The scientific community recently highlighted the lack of validated software tools that enable robust quantitative analysis of the large number of 3D in vitro models [8]. However, depending on the nature of the considered cell _aggregate_, there are a few commercial (e.g., _Imaris_--Bitplane AG, Zurich, Switzerland, _Amina_--Visage Imaging Inc., Carlsbad, CA, USA) and open-source solutions available. These range from aided tools to support users in manually contouring the 2D slices of the object (e.g., _Analysis of Spheroids_--_AnaP_[9]), to fully-automatic CAD suites embedded with 3D advanced segmentation methods (e.g., _Medical Imaging Interaction Toolkit_--_MITK_[10]).