Three-dimensional reconstruction and quantification of cervical carcinoma invasion fronts from histological serial sections.
The analysis of the three-dimensional (3-D) structure of tumoral invasion fronts of carcinoma of the uterine cervix is the prerequisite for understanding their architectural-functional relationship. The variation range of the invasion patterns known so far reaches from a smooth tumor-host boundary surface to more diffusely spreading patterns, which all are supposed to have a different prognostic relevance. As a very decisive limitation of previous studies, all morphological assessments just could be done verbally referring to single histological sections. Therefore, the intention of this paper is to get an objective quantification of tumor invasion based on 3-D reconstructed tumoral tissue data. The image processing chain introduced here is capable to reconstruct selected parts of tumor invasion fronts from histological serial sections of remarkable extent (90-500 slices). While potentially gaining good accuracy and reasonably high resolution, microtome cutting of large serial sections especially may induce severe artifacts like distortions, folds, fissures or gaps. Starting from stacks of digitized transmitted light color images, an overall of three registration steps are the main parts of the presented algorithm. By this, we achieved the most detailed 3-D reconstruction of the invasion of solid tumors so far. Once reconstructed, the invasion front of the segmented tumor is quantified using discrete compactness.
Braumann
Ulf-Dietrich
UD
Interdisciplinary Center for Bioinformatics, University Leipzig, Leipzig, Germany. braumann@izbi.uni-leipzig.de
Kuska
Jens-Peer
JP
Einenkel
Jens
J
Horn
Lars-Christian
LC
Löffler
Markus
M
Höckel
Michael
M
D000465:Algorithms; D019412:Anatomy, Cross-Sectional / Q000379:methods*; D001185:Artificial Intelligence; D002294:Carcinoma, Squamous Cell / Q000473:pathology*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D018715:Microscopy, Video / Q000379:methods; D008867:Microtomy / Q000379:methods; D009361:Neoplasm Invasiveness / Q000473:pathology*; D009367:Neoplasm Staging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique; D002583:Uterine Cervical Neoplasms / Q000473:pathology*