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MR imaging features to predict the type of bone metastasis in prostate cancer
Bone metastases (BMs) of prostate cancer (PCa) have been considered predominantly osteoblastic, but non-osteoblastic (osteolytic or mixed osteoblastic and osteolytic) BMs can occur. We investigated the differences in prostate MRI and clinical findings between patients with osteoblastic and non-osteo...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10354194/ https://www.ncbi.nlm.nih.gov/pubmed/37463944 http://dx.doi.org/10.1038/s41598-023-38878-0 |
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author | Koyama, Hiroaki Kurokawa, Ryo Kato, Shimpei Ishida, Masanori Kuroda, Ryohei Ushiku, Tetsuo Kume, Haruki Abe, Osamu |
author_facet | Koyama, Hiroaki Kurokawa, Ryo Kato, Shimpei Ishida, Masanori Kuroda, Ryohei Ushiku, Tetsuo Kume, Haruki Abe, Osamu |
author_sort | Koyama, Hiroaki |
collection | PubMed |
description | Bone metastases (BMs) of prostate cancer (PCa) have been considered predominantly osteoblastic, but non-osteoblastic (osteolytic or mixed osteoblastic and osteolytic) BMs can occur. We investigated the differences in prostate MRI and clinical findings between patients with osteoblastic and non-osteoblastic BMs. Between 2014 and 2021, patients with pathologically proven PCa without a history of other malignancies were included in this study. Age, Gleason score, prostate-specific antigen (PSA) density, normalized mean apparent diffusion coefficient and normalized T2 signal intensity (nT2SI) of PCa, and Prostate Imaging Reporting and Data System category on MRI were compared between groups. A multivariate logistic regression analysis using factors with P-values < 0.2 was performed to detect the independent parameters for predicting non-osteoblastic BM group. Twenty-five (mean 73 ± 6.6 years) and seven (69 ± 13.1 years) patients were classified into the osteoblastic and non-osteoblastic groups, respectively. PSA density and nT2SI were significantly higher in the non-osteoblastic group than in the osteoblastic group. nT2SI was an independent predictive factor for non-osteoblastic BMs in the multivariate logistic regression analysis. These results indicated that PCa patients with high nT2SI and PSA density should be examined for osteolytic BMs. |
format | Online Article Text |
id | pubmed-10354194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103541942023-07-20 MR imaging features to predict the type of bone metastasis in prostate cancer Koyama, Hiroaki Kurokawa, Ryo Kato, Shimpei Ishida, Masanori Kuroda, Ryohei Ushiku, Tetsuo Kume, Haruki Abe, Osamu Sci Rep Article Bone metastases (BMs) of prostate cancer (PCa) have been considered predominantly osteoblastic, but non-osteoblastic (osteolytic or mixed osteoblastic and osteolytic) BMs can occur. We investigated the differences in prostate MRI and clinical findings between patients with osteoblastic and non-osteoblastic BMs. Between 2014 and 2021, patients with pathologically proven PCa without a history of other malignancies were included in this study. Age, Gleason score, prostate-specific antigen (PSA) density, normalized mean apparent diffusion coefficient and normalized T2 signal intensity (nT2SI) of PCa, and Prostate Imaging Reporting and Data System category on MRI were compared between groups. A multivariate logistic regression analysis using factors with P-values < 0.2 was performed to detect the independent parameters for predicting non-osteoblastic BM group. Twenty-five (mean 73 ± 6.6 years) and seven (69 ± 13.1 years) patients were classified into the osteoblastic and non-osteoblastic groups, respectively. PSA density and nT2SI were significantly higher in the non-osteoblastic group than in the osteoblastic group. nT2SI was an independent predictive factor for non-osteoblastic BMs in the multivariate logistic regression analysis. These results indicated that PCa patients with high nT2SI and PSA density should be examined for osteolytic BMs. Nature Publishing Group UK 2023-07-18 /pmc/articles/PMC10354194/ /pubmed/37463944 http://dx.doi.org/10.1038/s41598-023-38878-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Koyama, Hiroaki Kurokawa, Ryo Kato, Shimpei Ishida, Masanori Kuroda, Ryohei Ushiku, Tetsuo Kume, Haruki Abe, Osamu MR imaging features to predict the type of bone metastasis in prostate cancer |
title | MR imaging features to predict the type of bone metastasis in prostate cancer |
title_full | MR imaging features to predict the type of bone metastasis in prostate cancer |
title_fullStr | MR imaging features to predict the type of bone metastasis in prostate cancer |
title_full_unstemmed | MR imaging features to predict the type of bone metastasis in prostate cancer |
title_short | MR imaging features to predict the type of bone metastasis in prostate cancer |
title_sort | mr imaging features to predict the type of bone metastasis in prostate cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10354194/ https://www.ncbi.nlm.nih.gov/pubmed/37463944 http://dx.doi.org/10.1038/s41598-023-38878-0 |
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