Literature DB >> 29033190

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

Marcus C Hovens1, Kevin Lo2, Michael Kerger2, John Pedersen3, Timothy Nottle3, Natalie Kurganovs2, Andrew Ryan3, Justin S Peters2, Daniel Moon2, Anthony J Costello2, Niall M Corcoran4, Matthew K H Hong2.   

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.
Copyright © 2017 Elsevier GmbH. All rights reserved.

Entities:  

Keywords:  3 dimensional modelling; Histopathology; Prostate cancer; Radical prostatectomy; Tumor spatial reconstruction

Mesh:

Substances:

Year:  2017        PMID: 29033190     DOI: 10.1016/j.prp.2017.09.022

Source DB:  PubMed          Journal:  Pathol Res Pract        ISSN: 0344-0338            Impact factor:   3.250


  3 in total

1.  Nuclear morphometry in indeterminate thyroid nodules.

Authors:  Michael A Razavi; Johnny Wong; Mounika Akkera; Mahmoud Shalaby; Hosam Shalaby; Andrew Sholl; Antione Haddad; Preeti Behl; Emad Kandil; Grace S Lee
Journal:  Gland Surg       Date:  2020-04

2.  Three-Dimensional Presentation of Tumor Histopathology: A Model Using Tongue Squamous Cell Carcinoma.

Authors:  Anne Koivuholma; Katri Aro; Antti Mäkitie; Mika Salmi; Tuomas Mirtti; Jaana Hagström; Timo Atula
Journal:  Diagnostics (Basel)       Date:  2021-01-12

3.  Additive Manufacturing of Resected Oral and Oropharyngeal Tissue: A Pilot Study.

Authors:  Alexandria L Irace; Anne Koivuholma; Eero Huotilainen; Jaana Hagström; Katri Aro; Mika Salmi; Antti Markkola; Heli Sistonen; Timo Atula; Antti A Mäkitie
Journal:  Int J Environ Res Public Health       Date:  2021-01-21       Impact factor: 3.390

  3 in total

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