code: def concat_multikeys_to_dict(
      data_list: list[dict],
      fixed_keys: list[str | int],
      keys: list[str],
      zero_insert: bool = True,
      **kwargs: Any,
  ) -> dict[str, np.ndarray]:
      """
      Get the nested value in a list of dictionary that shares the same structure iteratively on all keys.
      It returns a dictionary with keys with the found values in nd.ndarray.
  
      Args:
          data_list: a list of dictionary {key1: {key2: np.ndarray}}.
          fixed_keys: a list of keys that records to path to the value in the dict elements.
          keys: a list of string keys that will be iterated to generate a dict output.
          zero_insert: insert a zero in the list so that it can find the value in element 0 before getting the keys
          flatten: if True, numbers are flattened before concat.
  
      Returns:
          a dict with keys - nd.array of concatenated array pair.
      """
  
      ret_dict = {}
      for key in keys:
          addon: list[str | int] = [0, key] if zero_insert else [key]
          val = concat_val_to_np(
              data_list, fixed_keys + addon, **kwargs
          )
          ret_dict.update({key: val})
  
      return ret_dict
  
imports: from __future__ import annotations
  import logging
  import os
  import pickle
  import subprocess
  import sys
  from copy import deepcopy
  from numbers import Number
  from typing import Any, cast
  import numpy
  import torch
  from monai.auto3dseg import Algo
  from monai.bundle.config_parser import ConfigParser
  from monai.bundle.utils import ID_SEP_KEY
  from monai.config import PathLike
  from monai.data.meta_tensor import MetaTensor
  from monai.transforms import CropForeground, ToCupy
  from monai.utils import min_version, optional_import, run_cmd
label_desc: Use image node_id 5 for calling a global function with example usage: concat_multikeys_to_dict(data_list, fixed_keys, keys, zero_insert) and returns: ret_dict