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MRI-Based Assessment of Safe Margins in Tumor Surgery

Introduction. In surgical oncology, histological analysis of excised tumor specimen is the conventional method to assess the safety of the resection margins. We tested the feasibility of using MRI to assess the resection margins of freshly explanted tumor specimens in rats. Materials and Methods. Fo...

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Autores principales: Bellanova, Laura, Schubert, Thomas, Cartiaux, Olivier, Lecouvet, Frédéric, Galant, Christine, Banse, Xavier, Docquier, Pierre-Louis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3950827/
https://www.ncbi.nlm.nih.gov/pubmed/24701131
http://dx.doi.org/10.1155/2014/686790
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author Bellanova, Laura
Schubert, Thomas
Cartiaux, Olivier
Lecouvet, Frédéric
Galant, Christine
Banse, Xavier
Docquier, Pierre-Louis
author_facet Bellanova, Laura
Schubert, Thomas
Cartiaux, Olivier
Lecouvet, Frédéric
Galant, Christine
Banse, Xavier
Docquier, Pierre-Louis
author_sort Bellanova, Laura
collection PubMed
description Introduction. In surgical oncology, histological analysis of excised tumor specimen is the conventional method to assess the safety of the resection margins. We tested the feasibility of using MRI to assess the resection margins of freshly explanted tumor specimens in rats. Materials and Methods. Fourteen specimen of sarcoma were resected in rats and analysed both with MRI and histologically. Slicing of the specimen was identical for the two methods and corresponding slices were paired. 498 margins were measured in length and classified using the UICC classification (R0, R1, and R2). Results. The mean difference between the 498 margins measured both with histology and MRI was 0.3 mm (SD 1.0 mm). The agreement interval of the two measurement methods was [−1.7 mm; 2.2 mm]. In terms of the UICC classification, a strict correlation was observed between MRI- and histology-based classifications (κ = 0.84, P < 0.05). Discussion. This experimental study showed the feasibility to use MRI images of excised tumor specimen to assess the resection margins with the same degree of accuracy as the conventional histopathological analysis. When completed, MRI acquisition of resected tumors may alert the surgeon in case of inadequate margin and help advantageously the histopathological analysis.
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spelling pubmed-39508272014-04-03 MRI-Based Assessment of Safe Margins in Tumor Surgery Bellanova, Laura Schubert, Thomas Cartiaux, Olivier Lecouvet, Frédéric Galant, Christine Banse, Xavier Docquier, Pierre-Louis Sarcoma Research Article Introduction. In surgical oncology, histological analysis of excised tumor specimen is the conventional method to assess the safety of the resection margins. We tested the feasibility of using MRI to assess the resection margins of freshly explanted tumor specimens in rats. Materials and Methods. Fourteen specimen of sarcoma were resected in rats and analysed both with MRI and histologically. Slicing of the specimen was identical for the two methods and corresponding slices were paired. 498 margins were measured in length and classified using the UICC classification (R0, R1, and R2). Results. The mean difference between the 498 margins measured both with histology and MRI was 0.3 mm (SD 1.0 mm). The agreement interval of the two measurement methods was [−1.7 mm; 2.2 mm]. In terms of the UICC classification, a strict correlation was observed between MRI- and histology-based classifications (κ = 0.84, P < 0.05). Discussion. This experimental study showed the feasibility to use MRI images of excised tumor specimen to assess the resection margins with the same degree of accuracy as the conventional histopathological analysis. When completed, MRI acquisition of resected tumors may alert the surgeon in case of inadequate margin and help advantageously the histopathological analysis. Hindawi Publishing Corporation 2014 2014-02-20 /pmc/articles/PMC3950827/ /pubmed/24701131 http://dx.doi.org/10.1155/2014/686790 Text en Copyright © 2014 Laura Bellanova et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Bellanova, Laura
Schubert, Thomas
Cartiaux, Olivier
Lecouvet, Frédéric
Galant, Christine
Banse, Xavier
Docquier, Pierre-Louis
MRI-Based Assessment of Safe Margins in Tumor Surgery
title MRI-Based Assessment of Safe Margins in Tumor Surgery
title_full MRI-Based Assessment of Safe Margins in Tumor Surgery
title_fullStr MRI-Based Assessment of Safe Margins in Tumor Surgery
title_full_unstemmed MRI-Based Assessment of Safe Margins in Tumor Surgery
title_short MRI-Based Assessment of Safe Margins in Tumor Surgery
title_sort mri-based assessment of safe margins in tumor surgery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3950827/
https://www.ncbi.nlm.nih.gov/pubmed/24701131
http://dx.doi.org/10.1155/2014/686790
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