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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...

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Autores principales: Togao, Osamu, Chikui, Toru, Tokumori, Kenji, Kami, Yukiko, Kikuchi, Kazufumi, Momosaka, Daichi, Kikuchi, Yoshitomo, Kuga, Daisuke, Hata, Nobuhiro, Mizoguchi, Masahiro, Iihara, Koji, Hiwatashi, Akio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
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.
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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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