Prediction of Prostate Cancer Aggressiveness Using a Novel Multiparametric Magnetic Resonance Imaging Parameter: Tumor Heterogeneity Index

Sökmen, Bedriye Koyuncu; Sökmen, Doğukan; Çömez, Yusuf İlker; Ekşi, Mithat

doi:10.1159/000521606

Cited by 6 publications

(2 citation statements)

References 17 publications

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“…In the last few decades, more recent models, e.g., the CAPRA score, have been developed to replace older methods, such as the Kattan nomograms and Han tables (8,16,19,20). Researchers have also attempted to strengthen such models by integrating the findings from the developing mpMRI technology and molecular evaluations (10,(21)(22)(23).…”

Section: Discussionmentioning

confidence: 99%

Factors predicting biochemical recurrence following robot-assisted radical prostatectomy: single-center experience

SUÇEKEN>¹,

Küçük²

2022

Endourol Bull

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Objective: In this study, we aimed to investigate factors predicting the development of biochemical recurrence (BCR) in our clinical experience with patients over a long follow-up.Material and Methods: The data of 758 patients who underwent robot-assisted radical prostatectomy (RARP) were retrospectively reviewed. In the postoperative period, the prostate-specific antigen (PSA) value is measured as 0.2 ng/mL and above, regarded as biochemical recurrence (BCR). The non-BCR group was regarded as Group 1, and the BCR group as Group 2.Results: The mean age was similar between the two groups. The PSA values were significantly higher in the group that developed BCR (p<0.001). The biopsy Gleason score (GS), risk classification, and specimen GS were significantly higher in this group (p=0.02, p<0.001, and p<0.001, respectively). The BCR group also had statistically significantly higher positive surgical margin (PSM), extraprostatic extension (EPE), seminal vesicle invasion (SVI), and lymph node invasion rates. According to the multivariate analyses, PSA, risk classification, specimen GS, PSM, SVI, and T stage were significant parameters in the prediction of BCR.Conclusion: The parameters that predict the development were determined as the PSA value, risk classification, specimen GS, PSM, SVI, and T stage. The widespread adoption of commonly accepted methods will help achieve better patient management and optimize patient expectations.

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Section: Discussionmentioning

confidence: 99%

Factors predicting biochemical recurrence following robot-assisted radical prostatectomy: single-center experience

SUÇEKEN>¹,

Küçük²

2022

Endourol Bull

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“…And we can protect these patients' groups from the possible morbidity of radical prostatectomy, such as incontinence, by choosing a more conservative treatment plan. In a recent study, Sokmen et al (29) found that the ADC coefficient of variation value as a tissue texture parameter can be a new biomarker to assess tumor aggressiveness in patients with PCa.…”

Section: Table 3 the Asssociation Between Adc Values And Isup Gradesmentioning

confidence: 99%

Apparent Diffusion Coefficient Values as a Complementary Tool in Prostate Gland Disease: Retrospective Evaluation of Apparent Diffusion Coefficient Values with Pathological Data Guided by PI-RADSv2.1

Oğuzdoğan¹,

Adıbelli²,

Şefik³

et al. 2023

uob

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Objective: This retrospective study reveals whether a lesion is a benign pathological process or malignant by measuring apparent diffusion coefficient (ADC) values following prostate imaging reporting and diagnostic system version 2.1 (PI-RADSv2.1) guide on multiparametric magnetic resonance imaging (MpMRI) examinations. Furthermore, this study aims to determine the cut-off ADC values (ADCv) that may exist to help identify and distinguish between benign and the malignant lesions. Additionally, the paper evaluates whether there is a correlation between malignant lesions' International Society of Urological Pathology (ISUP) score and ADCv, and whether ADCv provide information about prostate cancer (PCa) aggressiveness without requiring invasive procedures. Materials and Methods:The study group consised of 243 patients. The lesions were diagnosed using transrectal ultrasound-guided cognitive MRI fusion. MpMRI images before the biopsy were evaluated according to PI-RADSv2.1 guideline by a radiologist. Three groups, benign prostatic tissue, prostatitis, and PCa were obtained according to the histopathological results. Results: When the cut-off value for ADC was 780x10 -3 , sensitivity was 80%. When the cut-off value was taken as 668x10 -3 , the sensitivity and specificity were 72% and 62%, respectively. When the cut-off ADCv was taken as 647x10 -3 , the sensitivity was 83% and the specificity was 48.5%. ADCv varied significantly depending on the ISUP groups (p=0.003). It was determined that the ISUP 1 group was significantly higher compared to other groups. ADC group mean values were not significantly different between groups 2, 3, 4, and 5. Conclusion: ADCv may be a suitable tool for estimating PCa aggressiveness, and it shows a significant potential to improve the diagnostic accuracy.

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Predictive ability of magnetic resonance imaging (MRI) for detecting prostate cancer and its clinical significance in MRI-targeted biopsy for prostate imaging reporting and data system (PI-RADS) ≥3 lesions

Erkan,

Gur Ozcan,

Erkan

et al. 2025

Clinical Radiology

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Prediction of Prostate Cancer Aggressiveness Using a Novel Multiparametric Magnetic Resonance Imaging Parameter: Tumor Heterogeneity Index

Cited by 6 publications

References 17 publications

Factors predicting biochemical recurrence following robot-assisted radical prostatectomy: single-center experience

Factors predicting biochemical recurrence following robot-assisted radical prostatectomy: single-center experience

Apparent Diffusion Coefficient Values as a Complementary Tool in Prostate Gland Disease: Retrospective Evaluation of Apparent Diffusion Coefficient Values with Pathological Data Guided by PI-RADSv2.1

Predictive ability of magnetic resonance imaging (MRI) for detecting prostate cancer and its clinical significance in MRI-targeted biopsy for prostate imaging reporting and data system (PI-RADS) ≥3 lesions

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