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Gamma distribution model of diffusion MRI for the differentiation of primary central nerve system lymphomas and glioblastomas
The preoperative imaging-based differentiation of primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBs) is of high importance since the therapeutic strategies differ substantially between these tumors. In this study, we investigate whether the gamma distribution (GD) model is use...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737570/ https://www.ncbi.nlm.nih.gov/pubmed/33315914 http://dx.doi.org/10.1371/journal.pone.0243839 |
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author | Togao, Osamu Chikui, Toru Tokumori, Kenji Kami, Yukiko Kikuchi, Kazufumi Momosaka, Daichi Kikuchi, Yoshitomo Kuga, Daisuke Hata, Nobuhiro Mizoguchi, Masahiro Iihara, Koji Hiwatashi, Akio |
author_facet | Togao, Osamu Chikui, Toru Tokumori, Kenji Kami, Yukiko Kikuchi, Kazufumi Momosaka, Daichi Kikuchi, Yoshitomo Kuga, Daisuke Hata, Nobuhiro Mizoguchi, Masahiro Iihara, Koji Hiwatashi, Akio |
author_sort | Togao, Osamu |
collection | PubMed |
description | The preoperative imaging-based differentiation of primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBs) is of high importance since the therapeutic strategies differ substantially between these tumors. In this study, we investigate whether the gamma distribution (GD) model is useful in this differentiation of PNCSLs and GBs. Twenty-seven patients with PCNSLs and 57 patients with GBs were imaged with diffusion-weighted imaging using 13 b-values ranging from 0 to 1000 sec/mm(2). The shape parameter (κ) and scale parameter (θ) were obtained with the GD model. Fractions of three different areas under the probability density function curve (f1, f2, f3) were defined as follows: f1, diffusion coefficient (D) <1.0×10(−3) mm(2)/sec; f2, D >1.0×10(−3) and <3.0×10(−3) mm(2)/sec; f3, D >3.0 × 10(−3) mm(2)/sec. The GD model-derived parameters were compared between PCNSLs and GBs. Receiver operating characteristic (ROC) curve analyses were performed to assess diagnostic performance. The correlations with intravoxel incoherent motion (IVIM)-derived parameters were evaluated. The PCNSL group's κ (2.26 ± 1.00) was significantly smaller than the GB group's (3.62 ± 2.01, p = 0.0004). The PCNSL group's f1 (0.542 ± 0.107) was significantly larger than the GB group's (0.348 ± 0.132, p<0.0001). The PCNSL group's f2 (0.372 ± 0.098) was significantly smaller than the GB group's (0.508 ± 0.127, p<0.0001). The PCNSL group's f3 (0.086 ± 0.043) was significantly smaller than the GB group's (0.144 ± 0.062, p<0.0001). The combination of κ, f1, and f3 showed excellent diagnostic performance (area under the curve, 0.909). The f1 had an almost perfect inverse correlation with D. The f2 and f3 had very strong positive correlations with D and f, respectively. The GD model is useful for the differentiation of GBs and PCNSLs. |
format | Online Article Text |
id | pubmed-7737570 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-77375702020-12-22 Gamma distribution model of diffusion MRI for the differentiation of primary central nerve system lymphomas and glioblastomas Togao, Osamu Chikui, Toru Tokumori, Kenji Kami, Yukiko Kikuchi, Kazufumi Momosaka, Daichi Kikuchi, Yoshitomo Kuga, Daisuke Hata, Nobuhiro Mizoguchi, Masahiro Iihara, Koji Hiwatashi, Akio PLoS One Research Article The preoperative imaging-based differentiation of primary central nervous system lymphomas (PCNSLs) and glioblastomas (GBs) is of high importance since the therapeutic strategies differ substantially between these tumors. In this study, we investigate whether the gamma distribution (GD) model is useful in this differentiation of PNCSLs and GBs. Twenty-seven patients with PCNSLs and 57 patients with GBs were imaged with diffusion-weighted imaging using 13 b-values ranging from 0 to 1000 sec/mm(2). The shape parameter (κ) and scale parameter (θ) were obtained with the GD model. Fractions of three different areas under the probability density function curve (f1, f2, f3) were defined as follows: f1, diffusion coefficient (D) <1.0×10(−3) mm(2)/sec; f2, D >1.0×10(−3) and <3.0×10(−3) mm(2)/sec; f3, D >3.0 × 10(−3) mm(2)/sec. The GD model-derived parameters were compared between PCNSLs and GBs. Receiver operating characteristic (ROC) curve analyses were performed to assess diagnostic performance. The correlations with intravoxel incoherent motion (IVIM)-derived parameters were evaluated. The PCNSL group's κ (2.26 ± 1.00) was significantly smaller than the GB group's (3.62 ± 2.01, p = 0.0004). The PCNSL group's f1 (0.542 ± 0.107) was significantly larger than the GB group's (0.348 ± 0.132, p<0.0001). The PCNSL group's f2 (0.372 ± 0.098) was significantly smaller than the GB group's (0.508 ± 0.127, p<0.0001). The PCNSL group's f3 (0.086 ± 0.043) was significantly smaller than the GB group's (0.144 ± 0.062, p<0.0001). The combination of κ, f1, and f3 showed excellent diagnostic performance (area under the curve, 0.909). The f1 had an almost perfect inverse correlation with D. The f2 and f3 had very strong positive correlations with D and f, respectively. The GD model is useful for the differentiation of GBs and PCNSLs. Public Library of Science 2020-12-14 /pmc/articles/PMC7737570/ /pubmed/33315914 http://dx.doi.org/10.1371/journal.pone.0243839 Text en © 2020 Togao et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Togao, Osamu Chikui, Toru Tokumori, Kenji Kami, Yukiko Kikuchi, Kazufumi Momosaka, Daichi Kikuchi, Yoshitomo Kuga, Daisuke Hata, Nobuhiro Mizoguchi, Masahiro Iihara, Koji Hiwatashi, Akio Gamma distribution model of diffusion MRI for the differentiation of primary central nerve system lymphomas and glioblastomas |
title | Gamma distribution model of diffusion MRI for the differentiation of
primary central nerve system lymphomas and glioblastomas |
title_full | Gamma distribution model of diffusion MRI for the differentiation of
primary central nerve system lymphomas and glioblastomas |
title_fullStr | Gamma distribution model of diffusion MRI for the differentiation of
primary central nerve system lymphomas and glioblastomas |
title_full_unstemmed | Gamma distribution model of diffusion MRI for the differentiation of
primary central nerve system lymphomas and glioblastomas |
title_short | Gamma distribution model of diffusion MRI for the differentiation of
primary central nerve system lymphomas and glioblastomas |
title_sort | gamma distribution model of diffusion mri for the differentiation of
primary central nerve system lymphomas and glioblastomas |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7737570/ https://www.ncbi.nlm.nih.gov/pubmed/33315914 http://dx.doi.org/10.1371/journal.pone.0243839 |
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