3-D analysis of the invasion front in squamous cell carcinoma of the uterine cervix: histopathologic evidence for collective invasion per continuitatem.

Abstract:

OBJECTIVE: To investigate spatial tumor invasion using ex vivo specimens and pursue a new morphometric approach for a quantitative assessment of the invasion front. STUDY DESIGN: Based on histologic serial sections with up to 500 slices stained with hematoxylin-eosin, volumes of interest of the tumor invasion front were 3-D reconstructed for 13 specimens from patients with squamous cell carcinoma (SCC) of the uterine cervix. Starting from very sensitive automatic tumor segmentation, 404 presumptive loci of isolated tumor islets were detected within the reconstructed volume data sets. These loci were microscopically inspected on the slides utilizing the volume date set's coordinates. RESULTS: A single detached tumor cell cluster within the stroma could be verified and, additionally, 4 tumor emboli within lymph vessels. The main cause of all other suspect islets (false positive segmentations) was peritumoral inflammatory response. Spatial invasion front quantification was done using discrete compactness (3-D C(D)). A comparison with 2-D C(D) values from single slides yielded strong correlation (correlation coefficient: r = 0.94; p < 0.001). CONCLUSION: Collective migration in SCC of the cervix mainly occurs per continuitatem. 2-D C(D) appears adequate and applicable for the morphometry of tumor invasion front phenotypes.

PubMed ID: 17987808

Projects: ProstataCA

Publication type: Not specified

Journal: Anal Quant Cytol Histol

Human Diseases: Cervical cancer

Citation: Anal Quant Cytol Histol. 2007 Oct;29(5):279-90.

Date Published: 9th Nov 2007

Registered Mode: by PubMed ID

Authors: J. Einenkel, U. D. Braumann, L. C. Horn, J. P. Kuska, M. Hockel

Help
help Submitter
Activity

Views: 2313

Created: 29th Aug 2019 at 12:02

Last updated: 7th Dec 2021 at 17:58

help Tags

This item has not yet been tagged.

help Attributions

None

Related items

Powered by
(v.1.13.0-master)
Copyright © 2008 - 2021 The University of Manchester and HITS gGmbH
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig

By continuing to use this site you agree to the use of cookies