title: Prognostic value of computer-assisted morphological and morphometrical analysis for detecting the recurrence tendency of basal cell carcinoma.
abstract: BACKGROUND
  Nuclear morphometry may provide useful diagnostic and prognostic information about basal cell carcinomas (BCCs) of the skin.
  
  
  METHODS
  A morphometric analysis was performed on histological sections of 52 primary BCCs which recurred and of 52 cases of BCC which did not recur. Eighteen different morphometric parameters were considered, e.g. nuclear area, perimeter, elongation, convexivity, and gray level of the nucleus. The demographics of these patients and the histological-morphological characteristics of their tumors were also considered. Statistical analysis was performed to evaluate the prognostic and predictive value of the morphometric variables for the recurrence of BCCs.
  
  
  RESULTS
  Increased patient age, multiple localization of BCCs at the time of diagnosis, and a low degree of peripheral palisading at the histological sections of BCCs were associated with BCC recurrence and consequently worse disease-free survival (DFS). 'Darker' values of the maximum nuclear gray level as well as greater variance of nuclear gray level values also strongly related to BCC recurrence and worse DFS. The analysis of the morphometry according to the histological types of BCC revealed that nodular BCCs consist of larger cells with statistically significant increased perimeter, minimum exterior axis, nuclear area, surface and perimeter of convexivity, and equivalent circle diameter. Infiltrating, sclerosing, and superficial BCCs, which tend to relapse, showed to consist of smaller cells with greater intercellular distance.
  
  
  CONCLUSIONS
  Nuclear morphometry evaluated with computer-assisted image analysis may contribute to a better knowledge and outcome prediction of BCC.
authors.affiliation: Department of Dermatology, "Klinikum Hoyerswerda" Academic Teaching-Hospital of the Technical University Dresden, Germany.
authors.forename: Christos
authors.initials: C
authors.lastname: Cheretis
authors.forename: Eirini
authors.initials: E
authors.lastname: Angelidou
authors.forename: Frank
authors.initials: F
authors.lastname: Dietrich
authors.forename: Ekaterini
authors.initials: E
authors.lastname: Politi
authors.forename: Hippokrates
authors.initials: H
authors.lastname: Kiaris
authors.forename: Helen
authors.initials: H
authors.lastname: Koutselini
mesh_terms: D000368:Aged; D000465:Algorithms; D002280:Basal Cell Carcinoma / Q000175:diagnosis* / Q000473:pathology*; D002467:Cell Nucleus / Q000378:metabolism; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D015233:Models, Statistical; D011379:Prognosis; D012008:Recurrence; D012878:Skin Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D012984:Software; D016896:Treatment Outcome