Nuclear shape analysis has predicted outcome better
than histologic grading in patients with clinically localized prostatic
carcinoma.
However, the requirement for manual nuclear contour tracing makes the
method tedious and slow.
Currently available image analysis systems for nuclear shape analysis
using light-absorption microscopy
provide nuclear boundaries of insufficient clarity for automatic segmentation.
We improved image resolution using confocal laser scanning microscopy,
automatically detected nuclear boundaries
by a multiscale segmentation algorithm and discriminated artifacts
in a semiautomated way.
A manual quantitative morphometry system and our semiautomated system
distinguished eight cases of prostatic carcinoma
from seven cases of benign prostatic hyperplasia by nuclear roundness
factor, ellipticity, nuclear area and perimeter.
The ease of semiautomated nuclear shape analysis should allow evaluation
of large numbers of patients with known outcomes after treatment
for clinically localized prostatic carcinoma to determine whether nuclear
shape analysis can be extended from research to clinical usage.
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