Bi-Parameter MRI Could Quantitatively Assess the Zonal Heterogeneity of Prostate Cancer.

INTRODUCTION: Prostate cancer (PCa) located in the peripheral zone (PZ) and transitional zone (TZ) showed a different clinical and pathological characteristic. This passage aims to preliminarily evaluate the relationship between the zonal heterogeneity of PCa quantitatively assessed by bpMRI and pathological risk stratification of the primary lesion. METHODS: This prospective study was conducted from January 2019 to February 2023. A total of 113 PCa patients whose bpMRI data indicated that the lesions located in only 1 single zone of the prostate were selected. A transrectal ultrasound and MRI-targeted biopsy were performed to verify the bpMRI results, and then radical prostatectomy (RP) was performed in 3 weeks after the biopsy. The high-risk (HR) group was defined as ISUP grades ≥ 3. Binary regression was performed to evaluate if the zonal heterogeneity could be an independent predictor of the HR group. The receiver operator characteristic (ROC) curve was performed to analyze the added value of zonal location in predicting the HR group. RESULTS: PSA, T staging, and ISUP grades, incidence of positive surgical margins were significantly lower in the TZ PCa, and the ADCmin, and ADCmean values in the TZ PCa were significantly higher (all P < .01). The zonal heterogeneity could independently predict the HR group patients (OR: 5.170 [1.663-16.067], P = .005) and improve the predicting efficiency of HR patients (AUC 0.824, 95% CI, 0.741-0.889). CONCLUSIONS: BpMRI could quantitively assess the zonal heterogeneity of PCa precisely and increase the predicting efficacy of HR patients, which can provide better help for clinical individualized treatment.

Feature Extraction of Ultrasound Radiofrequency Data for the Classification of the Peripheral Zone of Human Prostate.

Prostate cancer ranks among the most prevalent types of cancer in males, prompting a demand for early detection and noninvasive diagnostic techniques. This paper explores the potential of ultrasound radiofrequency (RF) data to study different anatomic zones of the prostate. The study leverages RF data's capacity to capture nuanced acoustic information from clinical transducers. The research focuses on the peripheral zone due to its high susceptibility to cancer. The feasibility of utilizing RF data for classification is evaluated using ex-vivo whole prostate specimens from human patients. Ultrasound data, acquired using a phased array transducer, is processed, and correlated with B-mode images. A range filter is applied to highlight the peripheral zone's distinct features, observed in both RF data and 3D plots. Radiomic features were extracted from RF data to enhance tissue characterization and segmentation. The study demonstrated RF data's ability to differentiate tissue structures and emphasizes its potential for prostate tissue classification, addressing the current limitations of ultrasound imaging for prostate management. These findings advocate for the integration of RF data into ultrasound diagnostics, potentially transforming prostate cancer diagnosis and management in the future.

Apparent differences in prostate zones: susceptibility to prostate cancer, benign prostatic hyperplasia and prostatitis.

Men are inevitably plagued by prostate disease throughout their lives. However, the understanding of the pathogenesis of prostate diseases is still limited. In the 1960s, McNeal proposed the theory of prostate zones: the prostate was divided into three main zones: transition zone, central zone, and peripheral zone. Over the past 50 years, significant differences between different prostate zones have been gradually revealed. We summarized the most significant differences in different zones of the prostate. For the first time, we proposed the "apparent difference in prostate zones" concept. This new concept has been proposed to understand the different zones of the prostate better. It also provided new ideas for exploring the susceptibility of lesions in different prostate zones. Despite the reported differences between zones, the treatment of prostate-related diseases remains partition agnostic. Therefore, we also discussed the clinical significance of the "apparent difference in the prostate zone" and emphasized the necessity of prostate zones.

Machine learning based on radiomics features combing B-mode transrectal ultrasound and contrast-enhanced ultrasound to improve peripheral zone prostate cancer detection.

PURPOSE: To construct machine learning models based on radiomics features combing conventional transrectal ultrasound (B-mode) and contrast-enhanced ultrasound (CEUS) to improve prostate cancer (PCa) detection in peripheral zone (PZ). METHODS: A prospective study of 166 men (72 benign, 94 malignant lesions) with targeted biopsy-confirmed pathology who underwent B-mode and CEUS examinations was performed. Risk factors, including age, serum total prostate-specific antigen (tPSA), free PSA (fPSA), f/t PSA, prostate volume and prostate-specific antigen density (PSAD), were collected. Time-intensity curves were obtained using SonoLiver software for all lesions in regions of interest. Four parameters were collected as risk factors: the maximum intensity (IMAX), rise time (RT), time to peak (TTP), and mean transit time (MTT). Radiomics features were extracted from the target lesions from B-mode and CEUS imaging. Multivariable logistic regression analysis was used to construct the model. RESULTS: A total of 3306 features were extracted from seven categories. Finally, 32 features were screened out from radiomics models. Five models were developed to predict PCa: the B-mode radiomics model (B model), CEUS radiomics model (CEUS model), B-CEUS combined radiomics model (B-CEUS model), risk factors model, and risk factors-radiomics combined model (combined model). Age, PSAD, tPSA, and RT were significant independent predictors in discriminating benign and malignant PZ lesions (P < 0.05). The risk factors model combing these four predictors showed better discrimination in the validation cohort (area under the curve [AUC], 0.84) than the radiomics images (AUC, 0.79 on B model; AUC, 0.78 on CEUS model; AUC, 0.83 on B-CEUS model), and the combined model (AUC: 0.89) achieved the greatest predictive efficacy. CONCLUSION: The prediction model including B-mode and CEUS radiomics signatures and risk factors represents a promising diagnostic tool for PCa detection in PZ, which may contribute to clinical decision-making.

The prognostic value of zonal origin in clinically localized prostate cancer: a systematic review and meta-analysis.

Introduction: Correlation between zonal origin of clinically localized prostate cancer (PC) and biochemical recurrence (BCR) after treatment is still controversial. Methods: We performed a meta-analysis of published articles to investigate the prognostic value of zonal origin in clinically localized PC. Literature was searched from Medline, Embase, Scopus, and Web of Science, from inception to Nov 1st, 2022. The risk of BCR was compared between PC originating from transition zone with peripheral zone. Relative risk (RR) was pooled in a random-effects model. Subgroup analysis and meta-regression were conducted to assess the source of heterogeneity. Results: 16 cohorts and 19,365 patients were included. PC originating from transition zone was associated with a lower risk of BCR (RR, 0.79, 95%CI; 0.69-0.92, I2, 76.8%). The association was consistent in studies with median follow-up time ≥60 months (RR, 0.65; 95%CI, 0.48 to 0.88, I2 56.8%), studies with NOS score ≥8 (RR, 0.70; 95%CI, 0.62 to 0.80, I2 32.4%), and studies using multivariate regression model (RR, 0.57; 95%CI, 0.48 to 0.69, I2 23%). Discussion: This meta-analysis supported that transition zone origin was an independent prognostic factor of a better biochemical result in clinically localized prostate cancer after treatment. Systematic review registration: 10.37766/inplasy2023.11.0100, identifier INPLASY2023110100.

A novel clinically significant prostate cancer prediction system with multiparametric MRI and PSA: P.Z.A. score.

PURPOSE: This study aims to establish and validate a new diagnosis model called P.Z.A. score for clinically significant prostate cancer (csPCa). METHODS: The demographic and clinical characteristics of 956 patients were recorded. Age, prostate-specific antigen (PSA), free/total PSA (f/tPSA), PSA density (PSAD), peripheral zone volume ratio (PZ-ratio), and adjusted PSAD of PZ (aPSADPZ) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The nomogram was established, and discrimination abilities of the new nomogram were verified with a calibration curve and area under the ROC curve (AUC). The clinical benefits of P.Z.A. score were evaluated by decision curve analysis and clinical impact curves. External validation of the model using the validation set was also performed. RESULTS: The AUCs of aPSADPZ, age, PSA, f/tPSA, PSAD and PZ-ratio were 0.824, 0.672, 0.684, 0.715, 0.792 and 0.717, respectively. The optimal threshold of P.Z.A. score was 0.41. The nomogram displayed excellent net benefit and better overall calibration for predicting the occurrence of csPCa. In addition, the number of patients with csPCa predicted by P.Z.A. score was in good agreement with the actual number of patients with csPCa in the high-risk threshold. The validation set provided better validation of the model. CONCLUSION: P.Z.A. score (including PIRADS(P), aPSADPZ(Z) and age(A)) can increase the detection rate of csPCa, which may decrease the risk of misdiagnosis and reduce the number of unnecessary biopsies. P.Z.A. score contains data that is easy to obtain and is worthy of clinical replication.

Retrospective T2 quantification from conventional weighted MRI of the prostate based on deep learning.

Purpose: To develop a deep learning-based method to retrospectively quantify T2 from conventional T1- and T2-weighted images. Methods: Twenty-five subjects were imaged using a multi-echo spin-echo sequence to estimate reference prostate T2 maps. Conventional T1- and T2-weighted images were acquired as the input images. A U-Net based neural network was developed to directly estimate T2 maps from the weighted images using a four-fold cross-validation training strategy. The structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), mean percentage error (MPE), and Pearson correlation coefficient were calculated to evaluate the quality of network-estimated T2 maps. To explore the potential of this approach in clinical practice, a retrospective T2 quantification was performed on a high-risk prostate cancer cohort (Group 1) and a low-risk active surveillance cohort (Group 2). Tumor and non-tumor T2 values were evaluated by an experienced radiologist based on region of interest (ROI) analysis. Results: The T2 maps generated by the trained network were consistent with the corresponding reference. Prostate tissue structures and contrast were well preserved, with a PSNR of 26.41 ± 1.17 dB, an SSIM of 0.85 ± 0.02, and a Pearson correlation coefficient of 0.86. Quantitative ROI analyses performed on 38 prostate cancer patients revealed estimated T2 values of 80.4 ± 14.4 ms and 106.8 ± 16.3 ms for tumor and non-tumor regions, respectively. ROI measurements showed a significant difference between tumor and non-tumor regions of the estimated T2 maps (P < 0.001). In the two-timepoints active surveillance cohort, patients defined as progressors exhibited lower estimated T2 values of the tumor ROIs at the second time point compared to the first time point. Additionally, the T2 difference between two time points for progressors was significantly greater than that for non-progressors (P = 0.010). Conclusion: A deep learning method was developed to estimate prostate T2 maps retrospectively from clinically acquired T1- and T2-weighted images, which has the potential to improve prostate cancer diagnosis and characterization without requiring extra scans.

Evaluating the Utility of Prostate-Specific Antigen Density in Risk Stratification of PI-RADS 3 Peripheral Zone Lesions on Non-Contrast-Enhanced Prostate MRI: An Exploratory Single-Institution Study.

Objective This study aimed to explore the potential of prostate-specific antigen density (PSAD) as a supplementary tool for defining high-risk Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions in the peripheral zone on non-contrast-enhanced MRI. This additional stratification tool could supplement the decision-making process for biopsy, potentially helping in identifying higher-risk patients more accurately, minimizing unnecessary procedures in lower-risk patients, and limiting the need for dynamic contrast-enhanced (DCE) scans. Materials and methods Between January 2019 and April 2023, 30 patients with PI-RADS 3 lesions underwent MRI-ultrasound fusion biopsies at our institution. Age and PSAD values were investigated using logistic regression and chi-square automatic interaction detection (CHAID) analysis to discern their predictive value for malignancy. Results The mean patient age was 64.7 years, and the mean PSAD was 0.13 ng/mL2. Logistic regression demonstrated PSAD to be a significant predictor of cancer (p=0.012), but not age (p=0.855). CHAID analysis further identified a PSAD cut-off value of 0.12, below which the cancer detection rate was 23.1% and above which the rate increased to 76.5%. Conclusions This exploratory study suggests that PSAD might be utilized to enhance the stratification of high-risk PI-RADS 3 lesions in the peripheral zone on non-contrast-enhanced MRI, aiding in decision-making for biopsy. While biopsy remains the gold standard for definitive diagnosis, a high PSAD value may suggest a greater need for biopsy in this specific group. Although further validation in larger cohorts is required, our findings contribute to the ongoing discourse on optimizing PI-RADS 3 lesion management. Limitations include a small sample size, the retrospective nature of the study, and the single-center setting, which may impact the generalizability of our results.

Protoplasting and Fluorescence-Activated Cell Sorting of the Shoot Apical Meristem Cell Types.

The shoot apical meristems (SAMs) are located at the tip of the shoot apex. The SAM harbors stem cells that divide continually to provide cells for developing above-ground organs. Several important developmental events occur in SAMs, such as stem cell maintenance, organ differentiation, and flowering commitment which are under genetic control. The SAM is a collection of specialized cells organized in specific spatial domains. Deciphering the gene regulatory networks, guided by the developmental and environmental signals, in these discrete cell types is essential to decoding the SAM function. Here, I provide updates to the previously published protocols for the protoplasting and subsequent purification through fluorescence-activated cell sorting (FACS) of SAM cell types (Reddy, Fluorescence activated cell sorting of shoot apical meristem cell types. In: Riechmann JL, Wellmer F (eds) Flower development. Methods in molecular biology, vol 1110. Humana, New York, pp 315-321, 2014), which has provided genome-wide gene expression patterns at a single cell-type resolution.

Prevalence and grade of malignancy differences with respect to the area of involvement in multiparametric resonance imaging of the prostate in the diagnosis of prostate cancer using the PI-RADS version 2 classification.

PURPOSE: The peripheral zone is histologically different from the transitional zone. The aim of this study is to analyze the differences between the prevalence and grade of malignancy of mpMRI-targeted biopsies that involve the TZ with respect to the PZ. METHODS: A cross-sectional study of 597 men evaluated for PC screening between February 2016 and October 2022 was conducted. Exclusion criteria were prior BPH surgery, radiotherapy, 5-alpha-reductase inhibitors treatment, UTI, mixed involvement of PZ-TZ or doubts, and central-zone involvement. Hypothesis contrast test was used to study differences proportions of malignancy (ISUP > 0) and significant (ISUP > 1) and high-grade tumor (ISUP > 3) in PI-RADSv2 > 2-targeted biopsies in PZ with respect to TZ, and logistic regression and hypothesis contrast tests were used to study the influence of the area of exposure as an effect-modifying factor in the diagnosis of malignancy with respect to the PI-RADSv2 classification. RESULTS: 473 patients were selected and 573 lesions biopsied (127 PI-RADS3, 346 PI-RADS4 and 100 PI-RADS5). A significant increase was described in the proportion of malignancy and significant and high-grade tumor in PZ compared to TZ (22.6%, 21.3%, and 8.7%, respectively). Significant increase in proportions and malignancy were described in cores targeted to PZ with respect to TZ, highlight the differences between PZ and TZ for ST (37.3%vs23.7% for PI-RADS4, 69.2%vs27.3% for PI-RADS5, respectively). Statistically significant linear trend was described increasing for malignancy, significant and high-grade tumors with respect to the PI-RADSv2 scores (change > 10%). CONCLUSION: Although the prevalence and grade of malignancy in the TZ is lower than in the PZ, PI-RADS4 and 5-targeted biopsies should not be omitted in this location, but PI-RADS3 could be.

Size regulation of the lateral organ initiation zone and its role in determining cotyledon number in conifers.

Introduction: Unlike monocots and dicots, many conifers, particularly Pinaceae, form three or more cotyledons. These are arranged in a whorl, or ring, at a particular distance from the embryo tip, with cotyledons evenly spaced within the ring. The number of cotyledons, nc, varies substantially within species, both in clonal cultures and in seed embryos. nc variability reflects embryo size variability, with larger diameter embryos having higher nc. Correcting for growth during embryo development, we extract values for the whorl radius at each nc. This radius, corresponding to the spatial pattern of cotyledon differentiation factors, varies over three-fold for the naturally observed range of nc. The current work focuses on factors in the patterning mechanism that could produce such a broad variability in whorl radius. Molecularly, work in Arabidopsis has shown that the initiation zone for leaf primordia occurs at a minimum between inhibitor zones of HD-ZIP III at the shoot apical meristem (SAM) tip and KANADI (KAN) encircling this farther from the tip. PIN1-auxin dynamics within this uninhibited ring form auxin maxima, specifying primordia initiation sites. A similar mechanism is indicated in conifer embryos by effects on cotyledon formation with overexpression of HD-ZIP III inhibitors and by interference with PIN1-auxin patterning. Methods: We develop a mathematical model for HD-ZIP III/KAN spatial localization and use this to characterize the molecular regulation that could generate (a) the three-fold whorl radius variation (and associated nc variability) observed in conifer cotyledon development, and (b) the HD-ZIP III and KAN shifts induced experimentally in conifer embryos and in Arabidopsis. Results: This quantitative framework indicates the sensitivity of mechanism components for positioning lateral organs closer to or farther from the tip. Positional shifting is most readily driven by changes to the extent of upstream (meristematic) patterning and changes in HD-ZIP III/KAN mutual inhibition, and less efficiently driven by changes in upstream dosage or the activation of HD-ZIP III. Sharper expression boundaries can also be more resistant to shifting than shallower expression boundaries. Discussion: The strong variability seen in conifer nc (commonly from 2 to 10) may reflect a freer variation in regulatory interactions, whereas monocot (nc = 1) and dicot (nc = 2) development may require tighter control of such variation. These results provide direction for future quantitative experiments on the positional control of lateral organ initiation, and consequently on plant phyllotaxy and architecture.

Magnetic resonance fingerprinting based comprehensive quantification of T1 and T2 values of the background prostatic peripheral zone: Correlation with clinical and demographic features.

PURPOSE: To quantify and assess the distribution of MR fingerprinting (MRF)-derived T1 and T2 values of the whole prostatic peripheral zone (PZ), and perform subgroup analyses according to clinical and demographic features. METHOD: One hundred and twenty-four patients with prostate MR exams and MRF-based T1 and T2 maps of the prostatic apex, mid gland, and base were identified from our database and included. Regions of interest encompassing the right and left lobes of the PZ were drawn for each axial slice on the T2 map and copied to the T1 map. Clinical data were obtained from medical records. Kruskal-Wallis test was used for assessing differences between subgroups and the Spearman coefficient was used for assessing any correlations. RESULTS: Mean T1 and T2 values were 1941 and 88 ms, respectively, for the whole-gland, 1884 and 83 ms for the apex, 1974 and 92 ms for the mid-gland, 1966 and 88 ms for the base. T1 values were weakly negatively correlated with PSA values, while T1 and T2 values were weakly positively correlated with prostate weight and moderately positively correlated with PZ width. Finally, patients with PI-RADS 1 scores had higher T1 and T2 values of the whole PZ, compared with those with scores 2-5. CONCLUSION: Mean T1 and T2 values of the background PZ of the whole gland were 1941 ± 313 and 88 ± 39 ms, respectively. Among clinical and demographic factors, there was a significant positive correlation between T1 and T2 values and PZ width.

Association between prostate size and glandular tissue volume of the peripheral zone via novel combined MRI and histopathology: possible pathophysiological implications on prostate cancer development.

PURPOSE: Benign prostatic hyperplasia (BPH) and prostate cancer (PCa) are the two most prevalent urologic diseases affecting elderly men. An inverse relationship between BPH/prostate size and PCa incidence is well documented in the current literature, but the precise mechanism is poorly understood. This study aims to investigate the effect of total prostate volume on total glandular tissue volume of the peripheral zone via a novel combination of magnetic resonance imaging (MRI) and histo-anatomical imaging. METHODS: 42 male patients between ages 53-79 years underwent both radical prostatectomy and pre-operative MRI scans. Prostate sizes ranged from 14.8-133.3cc. Quantitative measurements of surgical capsule thickness and glandular epithelial cell density within the peripheral zone (PZ) were obtained on histo-anatomical slides using computer-based imaging software. Quantitative prostatic zonal measurements were obtained from MRI scans. Combining MRI- and histopathology-obtained parameters allowed measurement of the total glandular tissue volume of the PZ (GVPZ). Statistical analysis was performed to identify associations between total prostate volume (TPV) and GVPZ. RESULTS: The Mann-Whitney U-test showed significant decreases in GVPZ in larger prostates when compared to smaller prostates. CONCLUSIONS: Combined MRI and histopathology techniques provide a novel method for accurate measuring of glandular tissue content within the prostatic PZ. The findings of this pilot study support the hypothesis of PZ compression by an expanding transition zone in large BPH prostates, leading to atrophy of PZ glandular tissue. As the majority of PCa originates in the PZ, this dynamic process may explain the protective effect of large BPH prostates against PCa development.

New model of PIRADS and adjusted prostatespecific antigen density of peripheral zone improves the detection rate of initial prostate biopsy: a diagnostic study.

This study explored a new model of Prostate Imaging Reporting and Data System (PIRADS) and adjusted prostate-specific antigen density of peripheral zone (aPSADPZ) for predicting the occurrence of prostate cancer (PCa) and clinically significant prostate cancer (csPCa). The demographic and clinical characteristics of 853 patients were recorded. Prostate-specific antigen (PSA), PSA density (PSAD), PSAD of peripheral zone (PSADPZ), aPSADPZ, and peripheral zone volume ratio (PZ-ratio) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The calibration and discrimination abilities of new nomograms were verified with the calibration curve and area under the ROC curve (AUC). The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves. The AUCs of PSA, PSAD, PSADPZ, aPSADPZ, and PZ-ratio were 0.669, 0.762, 0.659, 0.812, and 0.748 for PCa diagnosis, while 0.713, 0.788, 0.694, 0.828, and 0.735 for csPCa diagnosis, respectively. All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of PCa or csPCa. The new model significantly improved the diagnostic accuracy of PCa (0.945 vs 0.830, P < 0.01) and csPCa (0.937 vs 0.845, P < 0.01) compared with the base model. In addition, the number of patients with PCa and csPCa predicted by the new model was in good agreement with the actual number of patients with PCa and csPCa in high-risk threshold. This study demonstrates that aPSADPZ has a higher predictive accuracy for PCa diagnosis than the conventional indicators. Combining aPSADPZ with PIRADS can improve PCa diagnosis and avoid unnecessary biopsies.

Prostate multi-parametric magnetic resonance imaging appearance of diffuse adenosis of the peripheral zone (DAPZ).

Imaging specialists must recognize potential mimics of prostate cancer (PCa) on multi-parametric magnetic resonance imaging (mpMRI). We describe the appearance of diffuse adenosis of the peripheral zone (DAPZ) on mpMRI. The features of DAPZ parallel those of diffuse PCa, with low signal on T2-weighted images, rapid enhancement on dynamic contrast-enhanced sequences, and restricted diffusion. DAPZ is typically encountered in younger men with elevated prostate specific antigen (PSA) levels and portends an increased risk of the development of PCa. Recognition of the imaging appearance of DAPZ may reassure patients with concordant pathologic findings and may aid in selecting patients for follow-up.

New Diagnostic Model for Clinically Significant Prostate Cancer in Biopsy-Naïve Men With PIRADS 3.

Purpose: The aim of this study was to explore a new model of clinical decision-making to predict the occurrence of clinically significant prostate cancer (csPCa). Patients and Methods: The demographic and clinical characteristics of 152 patients were recorded. Prostate-specific antigen (PSA), PSA density (PSAD), adjusted PSAD of peripheral zone (aPSADPZ), and peripheral zone volume ratio (PZ ratio) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The calibration and discrimination abilities of new nomograms were verified with calibration curve and area under the ROC curve (AUC). The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves. Results: The AUCs of PSA, PSAD, aPSADPZ, and PZ ratio were 0.521, 0.645, 0.745, and 0.717 for prostate cancer (PCa) diagnosis, while the corresponding values were 0.590, 0.678, 0.780, and 0.731 for csPCa diagnosis, respectively. All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of csPCa. The new model significantly improved the diagnostic accuracy of csPCa (0.865 vs. 0.741, p = 0.0284) compared with the base model. In addition, the new model was better than the base model for predicting csPCa in the low or medium probability while the number of patients with csPCa predicted by the new model was in good agreement with the actual number of patients with csPCa in the high-risk threshold. Conclusions: This study demonstrates that aPSADPZ has a higher predictive accuracy for csPCa diagnosis than the conventional indicators. Including aPSADPZ, PZ ratio, and age can improve csPCa diagnosis and avoid unnecessary biopsies.

Association Between Prostate Size and MRI Determined Quantitative Prostate Zonal Measurements.

Purpose: Benign prostatic hyperplasia (BPH) and prostate cancer (PCa) are the two most prevalent and common urologic diseases impacting elderly men. The current literature has well documented an inverse relationship between prostate/BPH-size and incidence of PCa, but the exact interaction between these two disease entities is not well understood. The purpose of this study is to analyze prostatic zonal measurements with magnetic resonance imaging (MRI) in order to investigate the dynamic changes of the transition zone (TZ) and peripheral zone (PZ) in response to prostate/BPH growth. Methods: Multiparametric magnetic resonance imaging (mpMRI) scans of 430 consecutive male patients aged 18-89 years were obtained to measure the different zonal areas of the prostate. The data were statistically analyzed to identify specific associations between the different measurement parameters and total prostate volume (TPV). Results: The Mann-Whitney U-test showed a significant decline of the average peripheral zone thickness (PZT) (z = -4.5665, p < 0.0001) in larger prostates when compared to smaller prostates. The Spearman correlation between TPV and PZT demonstrated a significant negative correlation (-0.20, p < 0.0001). Conclusion: The data revealed that PZT was significantly smaller in the subgroup of patients with higher TPV. This supports the hypothesis of PZ compression and thinning caused by the growing and expanding TZ in BPH prostates. This dynamic growth-related process in the different prostatic zones may explain the protective effect of BPH against PCa.

Synthetic magnetic resonance imaging for primary prostate cancer evaluation: Diagnostic potential of a non-contrast-enhanced bi-parametric approach enhanced with relaxometry measurements.

PURPOSE: Bi-parametric magnetic resonance imaging (bpMRI) with diffusion-weighted images has wide utility in diagnosing clinically significant prostate cancer (csPCa). However, bpMRI yields more false-negatives for PI-RADS category 3 lesions than multiparametric (mp)MRI with dynamic-contrast-enhanced (DCE)-MRI. We investigated the utility of synthetic MRI with relaxometry maps for bpMRI-based diagnosis of csPCa. METHODS: One hundred and five treatment-naïve patients who underwent mpMRI and synthetic MRI before prostate biopsy for suspected PCa between August 2019 and December 2020 were prospectively included. Three experts and three basic prostate radiologists evaluated the diagnostic performance of conventional bpMRI and synthetic bpMRI for csPCa. PI-RADS version 2.1 category 3 lesions were identified by consensus, and relaxometry measurements (T1-value, T2-value, and proton density [PD]) were performed. The diagnostic performance of relaxometry measurements for PI-RADS category 3 lesions in peripheral zone was compared with that of DCE-MRI. Histopathological evaluation results were used as the reference standard. Statistical analysis was performed using the areas under the receiver operating characteristic curve (AUC) and McNemar test. RESULTS: In 102 patients without significant MRI artefacts, the diagnostic performance of conventional bpMRI was not significantly different from that of synthetic bpMRI for all readers (p = 0.11-0.79). The AUCs of the combination of T1-value, T2-value, and PD (T1 + T2 + PD) for csPCa in peripheral zone for PI-RADS category 3 lesions were 0.85 for expert and 0.86 for basic radiologists, with no significant difference between T1 + T2 + PD and DCE-MRI for both expert and basic radiologists (p = 0.29-0.45). CONCLUSION: Synthetic MRI with relaxometry maps shows promise for contrast media-free evaluation of csPCa.

Prostate Cancer Diffusion-Weighted Magnetic Resonance Imaging: Does the Choice of Diffusion-Weighting Level Matter?

BACKGROUND: Diffusion-weighted magnetic resonance imaging plays an important role in multiparametric assessment of prostate lesions. The derived apparent diffusion coefficient (ADC) could be a useful quantitative biomarker for malignant growth, but lacks acceptance because of low reproducibility. PURPOSE: To investigate the impact of the choice of diffusion-weighting levels (b-values) on contrast-to-noise ratio and quantitative measures in prostate diffusion-weighted MRI. STUDY TYPE: Retrospective and simulation based on published data. SUBJECTS: Patient cohort (21 men with Prostate Imaging-Reporting and Data System (PI-RADS) version 2 score ≥3) from a single-center study. FIELD STRENGTH/SEQUENCE: 3 T/diffusion-weighted imaging with single-shot echo-planar imaging. ASSESSMENT: Both clinical data and simulations based on previously acquired data were used to quantify the influence of b-value choice in normal peripheral zone (PZ) and PZ tumor lesions. For clinical data, ADC was determined for different combinations of b-values. Contrast-to-noise ratio and quantitative diffusion measures were simulated for a wide range of b-values. STATISTICAL TESTS: Tissue ADC and the lesion-to-normal tissue ADC ratios of different b-value combinations were compared with paired two-tailed Student's t-tests. A P-value <0.05 was considered statistically significant. RESULTS: Findings about b-value dependence derived from clinical data and from simulations agreed with each other. Provided measurement was limited to two b-values, simulation-derived optimal b-value choices coincided with PI-RADSv2 recommendations. For two-point measurements, ADC decreased by 15% when the maximum b-value increased from 1000 to 1500 seconds/mm2 , but corresponding lesion-to-normal tissue ADC ratio showed no significant change (P = 0.86 for acquired data). Simulations with three or more measurement points produced ADCs that declined by only 8% over this range of maximum b-value. Corresponding ADC ratios declined between 2.6% (three points) and 3.8% (21 points). Simulations also revealed an ADC reduction of about 19% with the shorter echo and diffusion time evaluated. DATA CONCLUSION: The comprehensive assessment of b-value dependence permits better formulation of protocol and analysis recommendations for obtaining reproducible results in prostate cancer diffusion-weighted MRI. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Three-dimensional measurement and analysis of benign prostatic hyperplasia.

BACKGROUND: The volume and thickness of intravesical prostatic protrusion and other characteristics of benign prostatic hyperplasia have not been investigated. We determine the effects of age and prostate volume on anatomical features of benign prostatic hyperplasia using three-dimensional measurement in this study. METHODS: This retrospective study included a total of 98 patients with benign prostatic hyperplasia. Three-dimensional models of prostate, central gland, peripheral zone, intravesical prostatic protrusion, prostatic urethra and bladder were reconstructed according to pelvic T2-weighted magnetic resonance imaging of these patients. The models were used to measure the intravesical prostatic protrusion volume, intravesical prostatic protrusion thickness, intravesical prostatic protrusion index, intravesical prostatic protrusion, prostate volume, peripheral zone volume, peripheral zone thickness, peripheral zone index, prostatic urethra thickness, the angle and distance of distal prostatic urethra with regard to coronal plane and sagittal plane and so on. RESULTS: Intravesical prostatic protrusion volume, intravesical prostatic protrusion thickness and peripheral zone volume of prostate volume >80 mL group were significantly higher than these in prostate volume <80 mL group (P<0.001, 0.01, 0.01, respectively). These parameters significantly increased with age (P<0.001, 0.01, 0.05, respectively). Peripheral zone index was significantly lower of prostate volume >80 mL group than these in prostate volume <80 mL group (P<0.05). Peripheral zone index significantly decreased with age (P<0.01). Intravesical prostatic protrusion index had no significant difference in all age groups. Peripheral zone thickness and prostatic urethra thickness had no significant difference in all groups. The distance and angle of distal prostatic urethra prostatic urethra with regard to coronal plane were significantly higher than these with regard to sagittal plane (both P<0.001). CONCLUSIONS: The rearward slope of the prostatic urethra is greater than the left or right offset during the process of benign prostatic hyperplasia. Three-dimensional measurement provides good supports for further clinical and scientific research.