Digital imaging colposcopy, image analysis and quantification of the colposcopic image.
OBJECTIVE
To investigate the use of a digital imaging system for colposcopy, its use for image analysis and quantification of the colposcopic features that may predict histological outcome as defined by large loop excision of transformation zone.


METHODS
Prospective programme study of all patients undergoing colposcopy for cytological abnormalities.


METHODS
Dudley Road Hospital, Birmingham.


METHODS
Fifty consecutive patients having cytological and colposcopic abnormality treated with large loop excision of transformation zone formed the study group.


METHODS
Pretreatment and colposcopic features correlated with histological diagnosis of excised transformation zone.


RESULTS
Index cytology and current smoking status are the most important variables for prediction of histological diagnosis. Other important variables are focality of lesion, surface pattern, intercapillary distance and degree of acetowhiteness.


CONCLUSIONS
Digital imaging colposcopy allows image capture, processing and objective analysis. This methodology holds advantages for basic and clinical research, teaching, diagnostics and clinical audit. The system can act as a quality control tool for colposcopy units. This system should prove invaluable for further quantitative studies, for natural history studies and for those patients with deferred treatment of their cytological and colposcopic abnormalities. The statistical models described may be incorporated into the system and can aid the colposcopist in management of the woman with abnormal cervical cytology and colposcopic abnormality.
Shafi
M I
MI
Department of Obstetrics and Gynaecology, Dudley Road Hospital, Birmingham, UK.
Dunn
J A
JA
Chenoy
R
R
Buxton
E J
EJ
Williams
C
C
Luesley
D M
DM
D000293:Adolescent; D000328:Adult; D002584:Cervix Uteri / Q000473:pathology; D003127:Colposcopy / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008875:Middle Aged; D015588:Observer Variation; D011379:Prognosis; D011446:Prospective Studies; D012044:Regression Analysis; D012680:Sensitivity and Specificity; D002583:Uterine Cervical Neoplasms / Q000473:pathology