Computer-assisted grading of adenocarcinoma in prostatic aspirates.
Conventional cytologic grading of fine needle aspirates of prostatic adenocarcinoma has been shown neither to be reproducible nor to correlate well with histologic grading. This study developed a tumor grade classification based on computerized cytomorphometric features and compared the results to conventional grading of companion tissue sections. The image analysis system evaluated architectural features of the aspirates (mainly cell cluster features and interrelationships) as well as nuclear features. Thirty-five prostatic adenocarcinomas (8 well, 19 moderately and 8 poorly differentiated) were evaluated. Discriminant functions based on data collected at medium and high resolution distinguished between aspirates from low-grade (well-differentiated) and high-grade (poorly differentiated) adenocarcinomas with 81% accuracy. Moderately differentiated cancers could not be classified as a distinct group. This study suggests that accurate grading of prostatic adenocarcinoma in fine needle aspirate smears requires the evaluation of medium-resolution features related to specimen cellularity and uniformity or crowding of cell clusters as well as of high-resolution features of nuclear area, perimeter and coarseness of chromatin texture. These findings are compared to those of other schemes for the cytologic grading of prostatic aspirates.
Department of Pathology, Tufts-New England Medical Center, Boston, MA 02111.
D S
DS
Schultz
T
T
Harry
K L
KL
Wong
M M
MM
Stilmant
D J
DJ
Zahniser
M L
ML
Hutchinson
D000230:Adenocarcinoma / Q000175:diagnosis / Q000473:pathology*; D001707:Biopsy, Needle; D003936:Diagnosis, Computer-Assisted; D003937:Diagnosis, Differential; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000175:diagnosis / Q000473:pathology*