## 4 Discussion
Further methods have been described for obtaining 3D models to obtain 3D models of the lower limbs. Low-dose simultaneous perpendicular biplanar radiography with secondary 3D reconstruction (EOS) is an appealing alternative option to CT, but relies on the correct identification of bony landmarks; this can be hard to identify in the immature skeleton, potentially hampering the torsion measurements in children [47; 48; 49]. Moreover, recent advancements in MRI techniques allow us to obtain high quality reconstructions, with almost similar details compared to the reconstructions based on CT. Particularly, isotropic 3D MRI provide higher resolution quality images than standard 2D sequences, leading to a reduction in artifacts and allowing multiplanar reconstructions [50]. Anyway, the reflective elements placed on the skin, such as in this case, must be MRI-compatible, and their morphology must be accurately planned to fit in the MRI coil. Moreover, MRI has higher acquisition time and lower tolerance, especially among pediatric patients that may require sedation or anesthesia during the exams. Another advantage of our computational integrative framework is that it was implemented using as a set of open-source software, thus potentially improving the cost-effectiveness ratio. To date, several freely available software for modeling and simulation of both musculoskeletal and FE models exists [51; 52]. Nonetheless, the verifications of the models, the validations and the sensitivity studies, are still challenging mainly because the biomechanical community has not reached a complete consensus on many points (e.g., the software used for modeling and simulating in a biomechanical framework) [46]. The present study must be considered in light of some limitations. The surface reflectors are not exactly sure to reproduce the patient's muscle movements. The procedure is still very laborious and requires a long time to create one or more models and a highly skilled staff. Machine learning processes will be able to overcome these timescales. Using a trained neural network with a database of solved gait analysis cases and 3D reconstructions would be possible to build an algorithm that facilitates the construction of the patient-specific models. Specifically, starting from the input of the CT scan and gait analysis it would be possible to have as output the automatic reconstruction and perfectly posed 3D model. Unfortunately, there is not much data available since these cases are uncommon. In addition, the simultaneous arrangement of CT and gait analysis is not obvious. Therefore, the construction of an organized database for training neural networks could be envisaged before the usage of the algorithm itself. The virtual surgical planning has not so far evaluated the effect of soft tissue procedures, such as patellar tendon plication or hamstrings lengthening, that should be combined with the bony procedures. Finally, there is no counterexample that the simulations carried out are valid since the current research protocol does not allow us to execute postoperative CT in children simply for research purposes. Many cases would be needed to ascertain the accuracy of the analysis process. Regardless of these limitations and with these ideas in mind, we have presented an integrative framework of \"virtual movable musculoskeletal model\" of the lower limbs. We have understood virtual movable musculoskeletal models as \"musculoskeletaletal avatar\" of the patient, having several applications beyond virtual surgical planning, from rehabilitation to telemedicine, from education to robotic surgery. Work is ongoing for using both 3D reconstructions of the skeleton and muscles, in different cases of children with and without CP, in order to predict the post-operative gait pattern, also combining bony and soft tissues multilevel procedures. Conceptualization, L.F., G.T., A.L. and M.G.B. ; methodology, G.M.S., G.A. and S.A.; software, G.M.S. ; validation, G.M.G.F. and A.A.; formal analysis, G.M.S. ; investigation, L.B., P.S. and G.C.M.