[Insight-users] Measuring tumor diameter

[Andriy Fedorov]

On Mon, Dec 22, 2008 at 1:31 AM, Richard Beare <richard.beare at gmail.com> wrote:
> actually segmenting the tumor well. There are a number of tricks that
> might help speed things up.
>
> Here are a few thoughts:
>

Richard,

These are nice ideas, thank you!

The initial implementation I developed is using itkLineIterator to
find outside subsegments, and with the current simplification of
choosing a largest area slice in three considered image directions it
is very fast, even without the optimizations you suggest.

I will definitely consider your recommendations if we decide to make
it more general.

Andriy Fedorov



> Computing the distance between all pairs of surface voxels is
> feasible, but determining whether the intersecting line goes outside
> the surface might be much more complex. Therefore an estimate of the
> lower bound of distances that you are interested in would let you
> avoid determining whether or not short lines fall outside the tumor. A
> couple of estimation methods spring to mind - 1) measure the tumor
> volume and determine the diameter of the equivalent sphere - any line
> less than some significant fraction of this isn't of interest 2) Find
> peaks in the euclidean distance transform, values of which represent
> the radius of the biggest sphere that will fit inside the tumor - any
> line less that a significant fraction of twice this value isn't of
> interest. Then build a queue of voxel pairs sorted by distance between
> them and check for valid line segments, starting with the longest
> first. Stop when you find one that lies entirely within the tumor.
>
> You could then compare performance of this sort of approach to the
> other options that have been raised. At least this is a direct
> translation of the current practice.
>
> On Mon, Dec 22, 2008 at 9:34 AM, Andriy Fedorov <fedorov at bwh.harvard.edu> wrote:
>> On Sun, Dec 21, 2008 at 11:20 AM, Steve M. Robbins <steve at sumost.ca> wrote:
>>>> The approach I am currently considering is this:
>>>>
>>>> 1) go through the axial slices, find the one with the largest area
>>>> 2) extract that slice contour
>>>
>>> This makes it seem like you have reduced the problem to 2D only.  Is
>>> that desirable, or is that done due to convention (e.g. radiologists
>>> traditionally look at stacks of 2D slices)?
>>>
>>
>> Based on my discussion with a neurosurgeon, they usually look at 2D
>> slices in AP/LR/IS directions, but also they may also look at oblique
>> slices.
>>
>> To understand maximum diameter, as I understand it, imagine the
>> contour of the tumor segmented in a 2d slice. Then take a set of
>> segments connecting all possible combinations of the contour points.
>> For each segment, subtract the subsegment which is outside tumor
>> contour (this will happen only for concave shapes). The updated this
>> way length of the longest segment will be the maximum diameter.
>>
>> I assume, one can take all combinations of surface points in 3d,
>> instead of looking at a slice with the largest area, but this will be
>> very time-consuming to walk along the segments connecting all possible
>> pairs of points. I simplify the problem to develop an initial
>> solution.
>>
>>>> 3) go through all possible combinations of the contour points, find
>>>> the pair of most distant points, and take this as a diameter
>>>
>>> Here you are measuring using the normal Euclidean distance?  For
>>> example, an "L" shape would have the two most distant points be the
>>> end of the two legs and the diameter would join them to form a
>>> right-angle triangle?
>>>
>>
>> An "L" shape will have the maximum diameter equal to the length of the
>> longer leg. With the diameter you suggest most of it will belong to
>> the outside of the shape.
>>
>>>> 4) follow the line between the points in the previous step, and
>>>> subtract the parts of the line that are outside the contour (this is
>>>> how the tumor measurements are actually taken). This may change the
>>>> measured diameter.
>>>
>>> I don't understand "subtract the parts of the line outside the contour".
>>> In my "L" shape example, almost the entire line is outside; does that
>>> mean you would say its diameter is zero?
>>>
>>
>> The diameter defined this way will indeed be almost 0. This will not
>> be the maximum diameter though.
>>
>>>> 5) repeat steps 3 and 4 until the maximum is found after taking into
>>>> account diameter parts outside the countour
>>>
>>> Again, I'm not sure what this means.
>>>
>>> Naively, I might expect that you want to measure a longest distance
>>> through the shape.  In the "L" example, this would be the sum of the
>>> two legs.
>>
>> The diameter by definition should be measured along a line, you cannot
>> sum up two legs...
>>
>>> I googled a bit but did not find any precise explanation of how to
>>> measure a "tumour diameter".  Can you explain a bit?
>>>
>>
>> I haven't found a precise definition either. Based on my
>> understanding, the measure is very subjective, and it is basically
>> what I described. Of course, it is not easy to visually identify the
>> largest diameter.
>>
>> I hope I was able to clarify the problem for you a bit. If you find a
>> better definition, please post...
>>
>> Thanks
>>
>> Andriy Fedorov
>>
>>
>>
>>> Thanks,
>>> -Steve
>>>
>>>
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>>>
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