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Optimal definition of biological tumor volume using positron emission tomography in an animal model
BACKGROUND: The goal of the study is to investigate (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG-PET)’s ability to delineate the viable portion of a tumor in an animal model using cross-sectional histology as the validation standard. METHODS: Syngeneic mammary tumors were grown i...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4615930/ https://www.ncbi.nlm.nih.gov/pubmed/26487346 http://dx.doi.org/10.1186/s13550-015-0134-y |
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author | Wu, Ingrid Wang, Hao Huso, David Wahl, Richard L. |
author_facet | Wu, Ingrid Wang, Hao Huso, David Wahl, Richard L. |
author_sort | Wu, Ingrid |
collection | PubMed |
description | BACKGROUND: The goal of the study is to investigate (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG-PET)’s ability to delineate the viable portion of a tumor in an animal model using cross-sectional histology as the validation standard. METHODS: Syngeneic mammary tumors were grown in female Lewis rats. Macroscopic histological images of the transverse tumor sections were paired with their corresponding FDG micro-PET slices of the same cranial-caudal location to form 51 pairs of co-registered images. A binary classification system based on four FDG-PET tumor contouring methods was applied to each pair of images: threshold based on (1) percentage of maximum tumor voxel counts (C(max)), (2) percentage of tumor peak voxel counts (C(peak)), (3) multiples of liver mean voxel counts (C(liver)) derived from PERCIST, and (4) an edge-detection-based automated contouring system. The sensitivity, which represented the percentage of viable tumor areas correctly delineated by the gross tumor area (GTA) generated from a particular tumor contouring method, and the ratio (expressed in percentage) of the overestimated areas of a gross tumor area (GTA(OE))/whole tumor areas on the macroscopic histology (WTA(H)), which represented how much a particular GTA extended into the normal structures surrounding the primary tumor target, were calculated. RESULTS: The receiver operating characteristic curves of all pairs of FDG-PET images have a mean area under the curve value of 0.934 (CI of 0.911–0.954), for representing how well each contouring method accurately delineated the viable tumor area. FDG-PET single value threshold tumor contouring based on 30 and 35 % of tumor C(max) or C(peak) and 6 × C(liver) + 2 × SD achieved a sensitivity greater than 90 % with a GTA(OE)/WTA(H) ratio less than 10 %. Contouring based on 50 % of C(max) or C(peak) had a much lower sensitivity of 67.2–75.6 % with a GTA(OE)/WTA(H) ratio of 1.1–1.7 %. Automated edge detection was not reliable in this system. CONCLUSIONS: Single-value-threshold tumor contouring using (18)F-FDG-PET is able to accurately delineate the viable portion of a tumor. 30 and 35 % of C(max), 30 and 35 % of C(peak), and 6 × C(liver) + 2 × SD are three appropriate threshold values to delineate viable tumor volume in our animal model. The commonly used threshold value of 50 % of C(max) or C(peak) failed to detect one third of the viable tumor volume in our model. |
format | Online Article Text |
id | pubmed-4615930 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-46159302015-10-29 Optimal definition of biological tumor volume using positron emission tomography in an animal model Wu, Ingrid Wang, Hao Huso, David Wahl, Richard L. EJNMMI Res Original Research BACKGROUND: The goal of the study is to investigate (18)F-fluorodeoxyglucose positron emission tomography ((18)F-FDG-PET)’s ability to delineate the viable portion of a tumor in an animal model using cross-sectional histology as the validation standard. METHODS: Syngeneic mammary tumors were grown in female Lewis rats. Macroscopic histological images of the transverse tumor sections were paired with their corresponding FDG micro-PET slices of the same cranial-caudal location to form 51 pairs of co-registered images. A binary classification system based on four FDG-PET tumor contouring methods was applied to each pair of images: threshold based on (1) percentage of maximum tumor voxel counts (C(max)), (2) percentage of tumor peak voxel counts (C(peak)), (3) multiples of liver mean voxel counts (C(liver)) derived from PERCIST, and (4) an edge-detection-based automated contouring system. The sensitivity, which represented the percentage of viable tumor areas correctly delineated by the gross tumor area (GTA) generated from a particular tumor contouring method, and the ratio (expressed in percentage) of the overestimated areas of a gross tumor area (GTA(OE))/whole tumor areas on the macroscopic histology (WTA(H)), which represented how much a particular GTA extended into the normal structures surrounding the primary tumor target, were calculated. RESULTS: The receiver operating characteristic curves of all pairs of FDG-PET images have a mean area under the curve value of 0.934 (CI of 0.911–0.954), for representing how well each contouring method accurately delineated the viable tumor area. FDG-PET single value threshold tumor contouring based on 30 and 35 % of tumor C(max) or C(peak) and 6 × C(liver) + 2 × SD achieved a sensitivity greater than 90 % with a GTA(OE)/WTA(H) ratio less than 10 %. Contouring based on 50 % of C(max) or C(peak) had a much lower sensitivity of 67.2–75.6 % with a GTA(OE)/WTA(H) ratio of 1.1–1.7 %. Automated edge detection was not reliable in this system. CONCLUSIONS: Single-value-threshold tumor contouring using (18)F-FDG-PET is able to accurately delineate the viable portion of a tumor. 30 and 35 % of C(max), 30 and 35 % of C(peak), and 6 × C(liver) + 2 × SD are three appropriate threshold values to delineate viable tumor volume in our animal model. The commonly used threshold value of 50 % of C(max) or C(peak) failed to detect one third of the viable tumor volume in our model. Springer Berlin Heidelberg 2015-10-21 /pmc/articles/PMC4615930/ /pubmed/26487346 http://dx.doi.org/10.1186/s13550-015-0134-y Text en © Wu et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Research Wu, Ingrid Wang, Hao Huso, David Wahl, Richard L. Optimal definition of biological tumor volume using positron emission tomography in an animal model |
title | Optimal definition of biological tumor volume using positron emission tomography in an animal model |
title_full | Optimal definition of biological tumor volume using positron emission tomography in an animal model |
title_fullStr | Optimal definition of biological tumor volume using positron emission tomography in an animal model |
title_full_unstemmed | Optimal definition of biological tumor volume using positron emission tomography in an animal model |
title_short | Optimal definition of biological tumor volume using positron emission tomography in an animal model |
title_sort | optimal definition of biological tumor volume using positron emission tomography in an animal model |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4615930/ https://www.ncbi.nlm.nih.gov/pubmed/26487346 http://dx.doi.org/10.1186/s13550-015-0134-y |
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