  Introduction: Intra-organ radiation dose sensitivity is becoming increasingly
relevant in clinical radiotherapy. One method for assessment involves
partitioning delineated regions of interest and comparing the relative
contributions or importance to clinical outcomes. We show that an intuitive
method for dividing organ contours, compound (sub-)segmentation, can
unintentionally lead to sub-segments with inconsistent volumes, which will bias
relative importance assessment. An improved technique, nested segmentation, is
introduced and compared. Methods: Clinical radiotherapy planning parotid
contours from 510 patients were segmented. Counts of radiotherapy dose matrix
voxels interior to sub-segments were used to determine the equivalency of
sub-segment volumes. The distribution of voxel counts within sub-segments were
compared using Kolmogorov-Smirnov tests and characterized by their dispersion.
Analytical solutions for 2D/3D analogues were derived and sub-segment
area/volume were compared directly. Results: Both parotid and 2D/3D region of
interest analogue segmentation confirmed compound segmentation intrinsically
produces sub-segments with volumes that depend on the region of interest shape
and selection location. Significant volume differences were observed when
sub-segmenting parotid contours into 18ths, and vanishingly small sub-segments
were observed when sub-segmenting into 96ths. Central sub-segments were
considerably smaller than sub-segments on the periphery. Nested segmentation
did not exhibit these shortcomings and produced sub-segments with equivalent
volumes when dose grid and contour collinearity was addressed, even when
dividing the parotid into 96ths. Nested segmentation was always faster or
equivalent in runtime to compound segmentation. Conclusions: Nested
segmentation is more suited than compound segmentation for analyses requiring
equal weighting of sub-segments.
