Prediction of lymph node metastases by preoperative nuclear morphometry in oral squamous cell carcinoma: a comparative image analysis study.

نویسندگان

  • S Natarajan
  • S Mahajan
  • K Boaz
  • T George
چکیده

CONTEXT Prediction of metastases of oral squamous cell carcinoma (OSCC) using incisional biopsy. AIMS To assess the efficacy of nuclear morphometry in predicting the nodal metastases of OSCC and to compare manual and computer-based image analyses. MATERIALS AND METHODS Sixteen cases of moderately differentiated squamous cell carcinoma (8 with metastasized lymph nodes and 8 node-negative cases) were examined using manual and computer-based image analyses. Nuclear area, perimeter, circular rate, larger to shorter axis ratio, and coefficient of variance of nuclear area (NACV) were calculated from 100 nuclei of the processed incisional biopsy specimen. STATISTICAL ANALYSIS The parameters were compared between the node positive and negative cases using Student's t test and with the level of lymph node involved using ANOVA test and Bonferroni's post hoc assessment. Manual and computer-based image analyses were compared by Spearman's correlation. RESULTS A significant variation between the node positive and negative groups was observed with respect to circular rate (P = 0.031) and NACV (P = 0.036). The nuclear area (P = 0.009), perimeter (P = 0.0001), circularity (P = 0.045), and larger to shorter diameter ratio (LS ratio) (P =0.02) were significantly different in the levels of the nodes involved. There was good a correlation between manual and computer-based analyses (Spearman's rho, 0.616-0.824) in nuclear size parameters and the circular rate had a negative correlation (-0.118, P = 0.664). Nuclear circularity was better assessed by computer-based analysis. CONCLUSION Preoperative morphometric assessment of the nuclear features may detect early cellular changes and thus, are useful in predicting nodal metastases in OSCC.

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عنوان ژورنال:
  • Indian journal of cancer

دوره 47 4  شماره 

صفحات  -

تاریخ انتشار 2010