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Usefulness of grayscale values of hypoechoic lesions matched with target lesions observed on magnetic resonance imaging for the prediction of clinically significant prostate cancer

BACKGROUND: To analyze grayscale values for hypoechoic lesions matched with target lesions evaluated using prebiopsy magnetic resonance imaging (MRI) according to the Prostate Imaging-Reporting and Data System (PI-RADS). METHODS: We collected data on 420 target lesions in patients who underwent MRI/...

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Autores principales: Kim, Dong Gyun, Yoo, Jeong Woo, Koo, Kyo Chul, Chung, Byung Ha, Lee, Kwang Suk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617296/
https://www.ncbi.nlm.nih.gov/pubmed/36309672
http://dx.doi.org/10.1186/s12894-022-01111-7
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author Kim, Dong Gyun
Yoo, Jeong Woo
Koo, Kyo Chul
Chung, Byung Ha
Lee, Kwang Suk
author_facet Kim, Dong Gyun
Yoo, Jeong Woo
Koo, Kyo Chul
Chung, Byung Ha
Lee, Kwang Suk
author_sort Kim, Dong Gyun
collection PubMed
description BACKGROUND: To analyze grayscale values for hypoechoic lesions matched with target lesions evaluated using prebiopsy magnetic resonance imaging (MRI) according to the Prostate Imaging-Reporting and Data System (PI-RADS). METHODS: We collected data on 420 target lesions in patients who underwent MRI/transrectal ultrasound fusion-targeted biopsies between January 2017 and September 2020. Images of hypoechoic lesions that matched the target lesions on MRI were stored in a picture archiving and communication system, and their grayscale values were estimated using the red/green/blue scoring method through an embedded function. We analyzed imaging data using grayscale values. RESULTS: Of the 420 lesions, 261 (62.1%) were prostate cancer lesions. There was no difference in the median grayscale values between benign and prostate cancer lesions. However, grayscale ranges (41.8–98.5 and 42.6–91.8) were significant predictors of prostate cancer and clinically significant prostate cancer (csPC) in multivariable logistic regression analyses. Area under the curve for detecting csPC using grayscale values along with conventional variables (age, prostate-specific antigen levels, prostate volume, previous prostate biopsy results, and PI-RADS scores) was 0.839, which was significantly higher than that for detecting csPC using only conventional variables (0.828; P = 0.036). Subgroup analysis revealed a significant difference for PI-RADS 3 lesions between grayscale values for benign and cancerous lesions (74.5 vs. 58.8, P = 0.008). Grayscale values were the only significant predictive factor (odds ratio = 4.46, P = 0.005) for csPC. CONCLUSIONS: Distribution of grayscale values according to PI-RAD 3 scores was potentially useful, and the grayscale range (42.6–91.8) was a potential predictor for csPC diagnosis.
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spelling pubmed-96172962022-10-30 Usefulness of grayscale values of hypoechoic lesions matched with target lesions observed on magnetic resonance imaging for the prediction of clinically significant prostate cancer Kim, Dong Gyun Yoo, Jeong Woo Koo, Kyo Chul Chung, Byung Ha Lee, Kwang Suk BMC Urol Research BACKGROUND: To analyze grayscale values for hypoechoic lesions matched with target lesions evaluated using prebiopsy magnetic resonance imaging (MRI) according to the Prostate Imaging-Reporting and Data System (PI-RADS). METHODS: We collected data on 420 target lesions in patients who underwent MRI/transrectal ultrasound fusion-targeted biopsies between January 2017 and September 2020. Images of hypoechoic lesions that matched the target lesions on MRI were stored in a picture archiving and communication system, and their grayscale values were estimated using the red/green/blue scoring method through an embedded function. We analyzed imaging data using grayscale values. RESULTS: Of the 420 lesions, 261 (62.1%) were prostate cancer lesions. There was no difference in the median grayscale values between benign and prostate cancer lesions. However, grayscale ranges (41.8–98.5 and 42.6–91.8) were significant predictors of prostate cancer and clinically significant prostate cancer (csPC) in multivariable logistic regression analyses. Area under the curve for detecting csPC using grayscale values along with conventional variables (age, prostate-specific antigen levels, prostate volume, previous prostate biopsy results, and PI-RADS scores) was 0.839, which was significantly higher than that for detecting csPC using only conventional variables (0.828; P = 0.036). Subgroup analysis revealed a significant difference for PI-RADS 3 lesions between grayscale values for benign and cancerous lesions (74.5 vs. 58.8, P = 0.008). Grayscale values were the only significant predictive factor (odds ratio = 4.46, P = 0.005) for csPC. CONCLUSIONS: Distribution of grayscale values according to PI-RAD 3 scores was potentially useful, and the grayscale range (42.6–91.8) was a potential predictor for csPC diagnosis. BioMed Central 2022-10-29 /pmc/articles/PMC9617296/ /pubmed/36309672 http://dx.doi.org/10.1186/s12894-022-01111-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Kim, Dong Gyun
Yoo, Jeong Woo
Koo, Kyo Chul
Chung, Byung Ha
Lee, Kwang Suk
Usefulness of grayscale values of hypoechoic lesions matched with target lesions observed on magnetic resonance imaging for the prediction of clinically significant prostate cancer
title Usefulness of grayscale values of hypoechoic lesions matched with target lesions observed on magnetic resonance imaging for the prediction of clinically significant prostate cancer
title_full Usefulness of grayscale values of hypoechoic lesions matched with target lesions observed on magnetic resonance imaging for the prediction of clinically significant prostate cancer
title_fullStr Usefulness of grayscale values of hypoechoic lesions matched with target lesions observed on magnetic resonance imaging for the prediction of clinically significant prostate cancer
title_full_unstemmed Usefulness of grayscale values of hypoechoic lesions matched with target lesions observed on magnetic resonance imaging for the prediction of clinically significant prostate cancer
title_short Usefulness of grayscale values of hypoechoic lesions matched with target lesions observed on magnetic resonance imaging for the prediction of clinically significant prostate cancer
title_sort usefulness of grayscale values of hypoechoic lesions matched with target lesions observed on magnetic resonance imaging for the prediction of clinically significant prostate cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617296/
https://www.ncbi.nlm.nih.gov/pubmed/36309672
http://dx.doi.org/10.1186/s12894-022-01111-7
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