Evidence map›Paper›PMID 36309672›Full record

ArticleBMC urology2022

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

Dong Gyun Kim, Jeong Woo Yoo, Kyo Chul Koo, Byung Ha Chung, Kwang Suk Lee

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Article in BMC urology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Dong Gyun KimDepartment of Urology, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea.
Jeong Woo YooDepartment of Urology, Gangnam Severance Hospital, Urological Science Institute, Yonsei University College of Medicine, 211 Eonju-ro, Gangnam-gu, Seoul, 06273, Republic of Korea.
Kyo Chul KooDepartment of Urology, Gangnam Severance Hospital, Urological Science Institute, Yonsei University College of Medicine, 211 Eonju-ro, Gangnam-gu, Seoul, 06273, Republic of Korea.
Byung Ha ChungDepartment of Urology, Gangnam Severance Hospital, Urological Science Institute, Yonsei University College of Medicine, 211 Eonju-ro, Gangnam-gu, Seoul, 06273, Republic of Korea.
Kwang Suk LeeDepartment of Urology, Gangnam Severance Hospital, Urological Science Institute, Yonsei University College of Medicine, 211 Eonju-ro, Gangnam-gu, Seoul, 06273, Republic of Korea. calmenow@yuhs.ac.

Funding

grant of Patient-Centered Clinical Research Coordinating Center funded by the Ministry of Health & Welfare, Republic of Korea HI19C0481 and HC19C0164
6 · The paper itself

Abstract

backgroundTo 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).

methodsWe 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.

resultsOf 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.

conclusionsDistribution 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.

Indexed as

Prostatic NeoplasmsHumansImage-Guided BiopsyMagnetic Resonance ImagingMaleNeoplasm GradingRetrospective StudiesGrayscaleHypoechoic lesionProstate cancerProstate imaging-reporting and data systemTarget biopsy

Identifiers

PMID36309672
PMCPMC9617296

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.