Computerized morphometry analysis of epithelial fimbriae nuclear symmetry in BRCA carriers may identify patients at risk for developing ovarian cancer.

Serous ovarian tumors may originate in epithelial cells of the fallopian tubes. Computerized morphometry was able to find significant alterations in the fallopian tube epithelium of healthy BRCA carriers. The purpose of this study was to identify a subgroup of BRCA carriers that may be at risk of developing serous ovarian cancer by evaluation of the epithelial nuclear symmetry in the fallopian tubes. Four groups of patients were analyzed; healthy patients, ovarian cancer patients, BRCA carriers, and BRCA noncarriers. All fallopian tubes appeared normal by H&E examination. The ImageProPlus software was used to assess the nuclear symmetry of 65 fimbriae epithelium cells and an artificial neural network algorithm aided in detecting a subpopulation among fimbriae of healthy BRCA carriers at risk for ovarian cancer. Significant differences were found between healthy patients and ovarian cancer patients, and between BRCA carriers and noncarriers. The algorithm was able to accurately predict BRCA carriers with associated ovarian cancer based on fallopian tube nuclear symmetry characteristics. These results reinforce the hypothesis that fimbriae epithelial cells of BRCA carriers may undergo early-stage changes that could predict the risk of progression toward malignancy.

Morphometric analysis of nuclear symmetry in urothelial carcinoma for predicting tumor recurrence.

Urothelial carcinoma is the ninth most common cancer in the world. Cytological analysis of the urine is used for screening, as well as for cases suspected for neoplasia of the urinary tract. However, the sensitivity of urine cytology examination is low. The golden standard for diagnosing bladder cancer relies upon cystoscopy followed by a biopsy, which is microscopically assessed by the pathologist. Treatment decisions are based on the histological grade and stage of the tumor. Posttreatment tumor recurrence is 50%. The purpose of this study is to predict recurrence of urothelial carcinoma using a novel morphometric method of nuclear symmetry analysis. This method may help tailor the appropriate treatment and may reduce the need of invasive surgical procedures in patients. Computerized morphometry was applied to develop multiple symmetry indices of the nuclei of the tumor cells as follows: each nucleus was physically divided along its digital axis in two segments that were separately analyzed for their shape, size, optical density, and texture. Subsequently, ratios were obtained by mathematically dividing between the morphometric values of the two nuclear segments where the denominator contained the largest value of the two. These ratios were named symmetry indices and were included as variables to predict the recurrence time of the tumors. The change in the symmetry indices (loss of symmetry) of the nuclear roundness, fractal dimension and margination were the only independent predictors of recurrence time. Computerized morphometry of nuclear symmetry indices may help to predict tumor recurrence in urothelial carcinomas.