3D modelling of radical prostatectomy specimens: Developing a method to quantify tumor morphometry for prostate cancer risk prediction

Hovens, Marcus C., Lo, Kevin, Kerger, Michael, Pedersen, John, Nottle, Timothy, Kurganovs, Natalie, Ryan, Andrew, Peters, Justin S., Moon, Daniel, Costello, Anthony J., Corcoran, Niall M. and Hong, Matthew K. H. (2017) 3D modelling of radical prostatectomy specimens: Developing a method to quantify tumor morphometry for prostate cancer risk prediction. Pathology Research and Practice, 213 12: 1523-1529. doi:10.1016/j.prp.2017.09.022

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Author Hovens, Marcus C.
Lo, Kevin
Kerger, Michael
Pedersen, John
Nottle, Timothy
Kurganovs, Natalie
Ryan, Andrew
Peters, Justin S.
Moon, Daniel
Costello, Anthony J.
Corcoran, Niall M.
Hong, Matthew K. H.
Title 3D modelling of radical prostatectomy specimens: Developing a method to quantify tumor morphometry for prostate cancer risk prediction
Journal name Pathology Research and Practice   Check publisher's open access policy
ISSN 1618-0631
0344-0338
Publication date 2017-09-27
Year available 2017
Sub-type Article (original research)
DOI 10.1016/j.prp.2017.09.022
Open Access Status Not yet assessed
Volume 213
Issue 12
Start page 1523
End page 1529
Total pages 7
Place of publication Muenchen, Germany
Publisher Elsevier
Language eng
Abstract Prostate cancer displays a wide spectrum of clinical behaviour from biological indolence to rapidly lethal disease, but we remain unable to accurately predict an individual tumor's future clinical course at an early curable stage. Beyond basic dimensions and volume calculations, tumor morphometry is an area that has received little attention, as it requires the analysis of the prostate gland and tumor foci in three-dimensions. Previous efforts to generate three-dimensional prostate models have required specialised graphics units and focused on the spatial distribution of tumors for optimisation of biopsy strategies rather than to generate novel morphometric variables such as tumor surface area. Here, we aimed to develop a method of creating three-dimensional models of a prostate's pathological state post radical prostatectomy that allowed the derivation of surface areas and volumes of both prostate and tumors, to assess the method's accuracy to known clinical data, and to perform initial investigation into the utility of morphometric variables in prostate cancer prognostication. Serial histology slides from 21 prostatectomy specimens covering a range of tumor sizes and pathologies were digitised. Computer generated three-dimensional models of tumor and prostate space filling models were reconstructed from these scanned images using Rhinoceros 4.0 spatial reconstruction software. Analysis of three-dimensional modelled prostate volume correlated only moderately with weak concordance to that from the clinical data (r=0.552, θ=0.405), but tumor volume correlated well with strong concordance (r=0.949, θ=0.876). We divided the cohort of 21 patients into those with features of aggressive tumor versus those without and found that larger tumor surface area (32.7 vs 3.4cc, p=0.008) and a lower tumor surface area to volume ratio (4.7 vs 15.4, p=0.008) were associated with aggressive tumor biology.
Keyword 3 dimensional modelling
Histopathology
Prostate cancer
Radical prostatectomy
Tumor spatial reconstruction
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID 1024081
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
School of Medicine Publications
 
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Created: Wed, 15 Nov 2017, 12:13:14 EST