The Correlation of Prostate Volume and Prostate-specific Antigen Levels With Positive Bacterial Prostate Tissue Cultures

Heidler, Stefan; Drerup, Martin; Lusuardi, Lukas; Bannert, Ursula; Bretterbauer, Katharina Maria; Bures, Johannes; Dietersdorfer, Franz; Dlouhy-Schütz, E.; Hessler, Clemens; Karpf, R.; Mittellehner, Lie-Anna; Mitlöhner, Barbara; Schwarz, Stephan; Thomay, Günther; Lösch, Georg; Freibauer, Christa; Albrecht, Walter

doi:10.1016/j.urology.2018.02.035

Cited by 6 publications

(5 citation statements)

References 23 publications

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“…Prostate volume (PV) is an important parameter in the workup of benign and malignant prostate diseases [1][2][3]. Combining the prostate specific antigen (PSA) value and PV yields the PSA density (PSAD) [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI

et al. 2022

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Objectives Prostate volume (PV) in combination with prostate specific antigen (PSA) yields PSA density which is an increasingly important biomarker. Calculating PV from MRI is a time-consuming, radiologist-dependent task. The aim of this study was to assess whether a deep learning algorithm can replace PI-RADS 2.1 based ellipsoid formula (EF) for calculating PV. Methods Eight different measures of PV were retrospectively collected for each of 124 patients who underwent radical prostatectomy and preoperative MRI of the prostate (multicenter and multi-scanner MRI’s 1.5 and 3 T). Agreement between volumes obtained from the deep learning algorithm (PVDL) and ellipsoid formula by two radiologists (PVEF1 and PVEF2) was evaluated against the reference standard PV obtained by manual planimetry by an expert radiologist (PVMPE). A sensitivity analysis was performed using a prostatectomy specimen as the reference standard. Inter-reader agreement was evaluated between the radiologists using the ellipsoid formula and between the expert and inexperienced radiologists performing manual planimetry. Results PVDL showed better agreement and precision than PVEF1 and PVEF2 using the reference standard PVMPE (mean difference [95% limits of agreement] PVDL: −0.33 [−10.80; 10.14], PVEF1: −3.83 [−19.55; 11.89], PVEF2: −3.05 [−18.55; 12.45]) or the PV determined based on specimen weight (PVDL: −4.22 [−22.52; 14.07], PVEF1: −7.89 [−30.50; 14.73], PVEF2: −6.97 [−30.13; 16.18]). Inter-reader agreement was excellent between the two experienced radiologists using the ellipsoid formula and was good between expert and inexperienced radiologists performing manual planimetry. Conclusion Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI. Key Points • A commercially available deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI. • The deep-learning algorithm was previously untrained on this heterogenous multicenter day-to-day practice MRI data set.

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Section: Introductionmentioning

confidence: 99%

Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI

et al. 2022

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“…The total sample size 16 Research by Heidler et al conforms that higher prostate volume is found in all patients who have positive (+) bacteria in culture urine. 17 PSA levels from 33 data have high PSA levels (> 4ng/ml) as 26 patients (78.8%). For normal PSA levels was 7 patients (21.2%) that noted.…”

Section: Resultsmentioning

confidence: 90%

Association of prostate-specific antigen and prostate volume in benign prostatic hyperplasia patients with urinary tract infection

2022

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Introduction: One of the most common diseases in men is benign prostatic hyperplasia (BPH). In this condition, the prostate gland becomes larger, thus it can clamp the urinary tract area and cause obstruction. Obstruction in the lower urinary tract increases the high risk of urinary tract infections (UTI). When the prostate volume becomes larger, the levels of prostate-specific antigen increase. This research aims to determine the correlation between PSA levels and prostate volume in BPH patients with urinary tract infections (UTI). Methods: This study used an analytic observational method with a cross-sectional design. Data were taken from the medical records of BPH patients suffering from UTIs at Bethesda Hospital Yogyakarta from January 2018 to December 2020. Data collection was carried out from January 17 2022 to March 17 2022. The data used in this study were selected using inclusion and exclusion criteria so that the obtained 33 medical record data were analyzed. The data used in this study were analyzed using SPSS software. The univariate analysis describes the distribution of data. Bivariate analysis used the chi-square test so that it could show the relationship between the independent variable (prostate volume) and the dependent variable (PSA level). Result: The data show moderate prostate volume (30-80cc) in 17 (51.5%), high prostate volume (>80ml) in as many as 9 patients (27.3%) and normal prostate volume (<30 ml) in as many as 7 patients (21.2%). High PSA levels are 26 (78.8%) and normal PSA levels are 7 patients (21.2%) that noted. Bivariate analysis data with a chi-square test shows that the significant score is 0.019 (p<0.05). Conclusion: The research shows an association of PSA levels and prostate volume in BPH patients with UTI.

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“…While PSA is not expressed by murine prostate cells, different homologous proteins secreted by the murine prostate such as α-microseminoprotein (PSP94) have reported anti-bacterial activity 53 . Moreover, a correlation was observed between the number of culturable bacteria isolated from prostate samples and serum PSA levels in patients with prostate hyperplasia who underwent transurethral prostate resection 54 .…”

Section: Discussionmentioning

confidence: 93%

The gut microbiome-prostate cancer crosstalk is modulated by dietary polyunsaturated long-chain fatty acids

Lachance,

Robitaille,

Laaraj

et al. 2024

Nat Commun

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The gut microbiota modulates response to hormonal treatments in prostate cancer (PCa) patients, but whether it influences PCa progression remains unknown. Here, we show a reduction in fecal microbiota alpha-diversity correlating with increase tumour burden in two distinct groups of hormonotherapy naïve PCa patients and three murine PCa models. Fecal microbiota transplantation (FMT) from patients with high PCa volume is sufficient to stimulate the growth of mouse PCa revealing the existence of a gut microbiome-cancer crosstalk. Analysis of gut microbial-related pathways in mice with aggressive PCa identifies three enzymes responsible for the metabolism of long-chain fatty acids (LCFA). Supplementation with LCFA omega-3 MAG-EPA is sufficient to reduce PCa growth in mice and cancer up-grading in pre-prostatectomy PCa patients correlating with a reduction of gut Ruminococcaceae in both and fecal butyrate levels in PCa patients. This suggests that the beneficial effect of omega-3 rich diet is mediated in part by modulating the crosstalk between gut microbes and their metabolites in men with PCa.

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The Correlation of Prostate Volume and Prostate-specific Antigen Levels With Positive Bacterial Prostate Tissue Cultures

Cited by 6 publications

References 23 publications

Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI

Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI

Association of prostate-specific antigen and prostate volume in benign prostatic hyperplasia patients with urinary tract infection

The gut microbiome-prostate cancer crosstalk is modulated by dietary polyunsaturated long-chain fatty acids

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