Efficiently looping over sub-arrays - performance

Question

I have an array A with size [d1,d2,d3,d4,d5] = size(A).
I have a custom function myFunc that I need to apply to each of the following subarrays of A:
B1 = A(:,1,:,:,:);
B2 = A(:,2,:,:,:);
B3 = A(:,3,:,:,:);
...
The function myFunc has signature:
function [CN1,CN2,CN3,...] = myFunc(BN,varargin)
Here, CN1, CN2, CN3, etc, are a variable number of output arrays whose size depends only on the size of BN.
The goals is to calculate CN1, CN2, CN3, etc, for each BN and then create the arrays
D1 = cat(2,C11,C21,C31,...);
D2 = cat(2,C12,C22,C32,...);
D3 = cat(2,C13,C23,C33,...);
...
I wrote the following function to do this:
function varargout = testFunc(A,funcHdl,varargin)
% Extract the relevant dimensions for array A
sizeA = size(A);
d1 = sizeA(1);
d2 = sizeA(2);
otherDims = sizeA(3:end);
% Extract the number of output arguments of the function handle
numOut = nargout(funcHdl);
Cs = cell(d2,numOut);
% Get the output for all subarrays
for j=1:d2
B = A(:,j,:);
B = reshape(B,[d1,1,otherDims]);
[Cs{j,:}] = funcHdl(B,varargin{:});
end
% Combined the outputs by concatenation
Ds = cell(1,numOut);
for n = 1:numOut
Ds{1,n} = cat(2,Cs{:,n});
end
% Variable number of outputs
varargout = Ds;
end
It's not too inefficient, but I really need this procedure to be efficient. Am I missing a more efficient way of doing this, especially the concatenation?
I use Matlab2020a on Windows 10.