Can LevenbergMarquardtOptimizer be constrained with bounds ?

Hello everyone,
I have been working on registering a statistical shape model to a 3D pointset, using ITK and statismo
I have tested multiple optimizers available in ITK to optimize a composite transform of a itk::StatisticalShapeModelTransform (from statismo) and a rigid transform (I tested both itk::Euler3DTransform and itk::VersorRigid3DTransform) and I found the constrained version of LBFGS optimizer very convenient to bound the StatisticalShapeModelTransform parameters (bounded parameters for this transform can ensure a realistic shape deformation).
The problem is that a StatisticalShapeModelTransform is not compatible with the LBFGSB Optimizer (I got the error “ComputeJacobianWithRespectToPosition() is not implemented for StatisticalShapeModelTransform”)
So I now work with the Levenberg Marquardt optimizer and I wonder if it is possible to pass bounds parameters to the LM optimizer, such as in LBFGSB Optimizer, in order to enhance the optimization ?
Thanks in advance for any help/tip !