Anterior Fibromuscular Stroma Research Articles

Impact of age and anterior fibromuscular stroma preservation on post-enucleation voided volume.

This study is centered on the critical role of anterior fibromuscular stroma (AFS) preservation in prostate enucleation, an emerging strategy aimed at minimizing postoperative urinary incontinence-a common concern in benign prostatic hyperplasia (BPH) surgeries. By focusing on postoperative voiding volumes (VV), our research investigates the efficacy of AFS preservation. This approach, distinct in its methodology, is hypothesized to improve urinary function post-surgery, thereby offering a potentially significant advancement in BPH surgical treatments. A retrospective analysis was conducted, comparing patients who underwent prostate enucleation in 2017 without intentional AFS preservation to those in 2019 with this technique. We examined variables including age, BMI, diabetes, hypertension, and preoperative VV to assess their effect on post-catheter removal VV. The study's methodology includes a thorough review of the primary statistical analysis methods employed. Our analysis indicates that while the 2017 and 2019 cohorts were similar in most preoperative parameters, the 2019 group that underwent AFS-preserved surgery showed a significant improvement in postoperative VVs. This was less pronounced in the patient group aged over 70, underscoring the importance of this demographic in our study. The study concludes that intentional preservation of AFS during prostate enucleation positively impacts early postoperative VVs, with limited improvement in older patients. These findings highlight the potential of AFS preservation not only in enhancing urinary outcomes post-surgery but also in shaping future BPH surgical procedures and research directions.

Pearls and Pitfalls in Applying PI-RADS 2.1

AbstractThe use of Prostate Imaging Reporting and Data System (PI-RADS) with multiparametric magnetic resonance imaging (MRI) has significantly improved the detection of clinically significant prostate cancer (csPCa), but there are certain challenges that the reader may face. This review provides an overview of the pitfalls associated with the PI-RADS system for multiparametric prostate MRI (mpMRI), with suggestions/pearls to help overcome these pitfalls.PI-RADS assessment is hindered by several causes of false positives (FPs) and false negatives (FNs). In addition, there is wide variability in the positive predictive value (PPV) of the PI-RADS system across different centers, highlighting the need for improvement. While the negative predictive value (NPV) for csPCa is generally high, variations exist.This review discusses the pitfalls contributing to FNs, including MRI artifacts, such as susceptibility and motion artifacts. Techniques to optimize image acquisition, such as switching the phase encoding direction and reducing bowel peristalsis, are suggested to mitigate these artifacts. Improper b-value selection for diffusion-weighted imaging (DWI) is another pitfall, emphasizing the importance of using high b-values (≥1,400 s/mm2) to optimize neoplasm detection. Similarly, optimizing window settings to visualize csPCa, correctly positioning the endorectal coil, awareness of rare variants like mucinous adenocarcinoma and cribriform adenocarcinoma, and distinguishing central zone tumors from normal central zone are discussed.This article highlights the common pitfalls causing FPs, such as benign pathologies like prostatitis, granulomatous prostatitis, prostatic abscess, stromal BPH nodules, extruded BPH nodules, and prostatic calcifications. It also discusses the pitfalls related to normal anatomical structures, including the central zone, anterior fibromuscular stroma, thickened surgical capsule, neurovascular bundle, and periprostatic venous plexus. Techniques for carefully evaluating these entities' morphology and distribution of signal abnormalities are described to avoid overdiagnosing these as PCa. The article also addresses the pitfalls related to postintervention changes, including postbiopsy hemorrhage and artifacts caused by the UroLift procedure, while providing recommendations for managing these challenges.Finally, the pitfalls that may be encountered during staging, including evaluation for extraprostatic extension, and pelvic nodal and osseous metastases, are highlighted.

Prostate zones and tumor morphological parameters on magnetic resonance imaging for predicting the tumor-stage diagnosis of prostate cancer.

To determine whether the morphological parameters of prostate zones and tumors on magnetic resonance imaging (MRI) can predict the tumor-stage (T-stage) of prostate cancer (PCa) and establish an optimal T-stage diagnosis protocol based on three-dimensional reconstruction and quantization after image segmentation. A dataset of the prostate MRI scans and clinical data of 175 patients who underwent biopsy and had pathologically proven PCa from January 2018 to November 2020 was retrospectively analyzed. The authors manually segmented and measured the volume, major axis, and cross-sectional area of the peripheral zone (PZ), transition zone, central zone (CZ), anterior fibromuscular stroma, and tumor. The differences were evaluated by the One-Way analysis of variance, Pearson's chi-squared test, or independent samples t-test. Spearman's correlation coefficient and receiver operating characteristic curve analyses were also performed. The cut-off values of the T-stage diagnosis were generated using Youden's J index. The prostate volume (PV), PZ volume (PZV), CZ volume, tumor's major axis (TA), tumor volume (TV), and volume ratio of the TV and PV were significantly different among stages T1 to T4. The cut-off values of the PV, PZV, CZV, TA, TV, and the ratio of TV/PV for the discrimination of the T1 and T2 stages were 53.63 cm3, 11.60 cm3, 1.97 cm3, 2.30 mm, 0.90 cm3, and 0.03 [area under the curves (AUCs): 0.628, 0.658, 0.610, 0.689, 0.724, and 0.764], respectively. The cut-off values of the TA, TV, and the ratio of TV/PV for the discrimination of the T2 and T3 stages were 2.80 mm, 8.29 cm3, and 0.12 (AUCs: 0.769, 0.702, and 0.688), respectively. The cut-off values of the TA, TV, and the ratio of TV/PV for the discrimination of the T3 and T4 stages were 4.17 mm, 18.71 cm3, and 0.22 (AUCs: 0.674, 0.709, and 0.729), respectively. The morphological parameters of the prostate zones and tumors on the MRIs are simple and valuable diagnostic factors for predicting the T-stage of patients with PCa, which can help make accurate diagnoses and lateral treatment decisions.

Prostate Cancer and Its Mimics-A Pictorial Review.

Multiparametric prostate MRI (mpMRI) is gaining wider recommendations for diagnosing and following up on prostate cancer. However, despite the high accuracy of mpMRI, false positive and false negative results are reported. Some of these may be related to normal anatomic structures, benign lesions that may mimic cancer, or poor-quality images that hamper interpretation. The aim of this review is to discuss common potential pitfalls in the interpretation of mpMRI. mpMRI of the prostates was performed on 3T MRI scanners (Philips Achieva or Siemens Magnetom Vida) according to European Society of Urogenital Radiology (ESUR) guidelines and technical requirements. This pictorial review discusses normal anatomical structures such as the anterior fibromuscular stroma, periprostatic venous plexus, central zone, and benign conditions such as benign prostate hyperplasia (BPH), post-biopsy hemorrhage, prostatitis, and abscess that may imitate prostate cancer, as well as the appearance of prostate cancer occurring in these locations. Furthermore, suggestions on how to avoid these pitfalls are provided, and the impact of image quality is also discussed. In an era of accelerating prostate mpMRI and high demand for high-quality interpretation of the scans, radiologists should be aware of these potential pitfalls to improve their diagnostic accuracy.

V10-01 A COMPREHENSIVE REVIEW OF NEUROANATOMY, PROSTATE ANATOMY AND PERI-PROSTATIC STRUCTURES

You have accessJournal of UrologyCME1 Apr 2023V10-01 A COMPREHENSIVE REVIEW OF NEUROANATOMY, PROSTATE ANATOMY AND PERI-PROSTATIC STRUCTURES Sneha Parekh and Ashutosh Tewari Sneha ParekhSneha Parekh More articles by this author and Ashutosh TewariAshutosh Tewari More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003328.01AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: We aim to present the most revised anatomy of prostate, surrounding structures and its neuroanatomy in the form a 3D animated video. METHODS: We searched the PubMed database to identify original and review articles that addressed the anatomy of the prostate and relevant surrounding structures, with an emphasis on work published from July 2002 to January 2022. Understanding the findings in literature, we applied this knowledge and created a 3D animation video. RESULTS: Laterally the prostate is surrounded by the Endopelvic fascia, which has Parietal and medially has prostatic fascia. Ventrally prostatic capsule attached to Anterior Fibromuscular Stroma (AFMS), reaches postero-lateral prostate embracing Neurovascular bundle (NVB) medially and becomes pararectal fascia covering the rectum. The detrusor apron is an extension of anterior wall of bladder towards posterior area of pubic bone and contributes to AFMS. The urethral sphincter complex consists of external rhabdosphincter, inner lissosphincter and membranous urethra. Seminal Vesicles(SV) and Vas Deferens (VD) are extra peritoneal tubular structures, located at base of prostate, surrounded by major nerves posterolaterally, associations with Proximal neurovascular plate (PNP). Prostate with surrounding structures is supplied by autonomic and somatic branches originating from lower (T11-L2) and (S2-S4). Nerve fibers from centers coalesce to form pelvic plexus, aka PNP.The autonomic fibers from PNP are distributed into NVB and ANP (Accessory Neural Pathway) in a spray like pattern, with 60% of fibers on postero-lateral and 40% on antero-lateral prostate.DVC is composed of nerve fibers, dorsal veins and prostatic arteries. The puboprostatic ligamentous complex comprises of puboprostatic ligaments, arcus tendineus, and puboperinealis muscle. The puboprostatic ligaments are dense pyramid-shaped medial portions of distal endopelvic fascia. The puboperinealis is a paired muscle that originates from pubis, flanks prostatic-urethral junction, terminates at perineal body. CONCLUSIONS: Prostate is a dense fibromuscular gland, situated in the true pelvis surrounded by a compact multi-layered fascia with intermingling nerves and vessels.The nerves from the lumbar and sacral roots along with somatic supply form the pelvic plexus, further giving the prostatic neural hammock. This forms the basis of nerve sparing and its grades. Puboprostatic ligamentous complex along with peri-prostatic fascia and detrusor apron support the prostate and has a role in erectile and continence. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e926 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Sneha Parekh More articles by this author Ashutosh Tewari More articles by this author Expand All Advertisement PDF downloadLoading ...

Prostate Imaging Reporting and Data System (PI-RADS) v 2.1: Overview and Critical Points

The technical parameters and imaging interpretation criteria of the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) using multiparametric MRI (mpMRI) are updated in PI-RADS v2.1. These changes have been an expected improvement for prostate cancer evaluation, although some issues remain unsolved, and new issues have been raised. In this review, a brief overview of PI-RADS v2.1 is and several critical points are discussed as follows: the need for more detailed protocols of mpMRI, lack of validation of the revised transition zone interpretation criteria, the need for clarification for the revised diffusion-weighted imaging and dynamic contrast-enhanced imaging criteria, anterior fibromuscular stroma and central zone assessment, assessment of background signal and tumor aggressiveness, changes in the structured report, the need for the parameters for imaging quality and performance control, and indications for expansion of the system to include other indications.

Anterior fibromuscular stroma-preserved endoscopic enucleation of the prostate: a precision anatomical approach.

Benign prostate obstruction (BOO) is becoming increasingly important in this aging society. Some urge/stress urinary incontinence (UUI/SUI) still occurs after endoscopic enucleation of the prostate (EEP). It remains unclear how post-EEP incontinence can be avoided. Currently, early apical release to ameliorate the traction of the external sphincter is the best technique for incontinence prevention. To describe our surgical technique of anterior fibromuscular stroma (AFS)-preserved EEP for BOO. The medical records of 60 consecutive patients who underwent AFS-preserved EEP for BOO in our center from September 2019 to December 2019 were retrospectively reviewed. AFS-preserved EEP starts at the 12 o'clock position of the urethra, and the junction between the AFS and transitional zone (T-zone) was identified. The AFS and T-zone were separated first to protect the AFS in the initial operative procedure. Then, following the usual enucleation procedure, AFS-preserved EEP could be achieved. Postoperative prostate-specific antigen (PSA), testosterone, urethral stricture, and voiding status, such as incontinence, uroflow, and postvoiding residual urine were assessed. The data show that AFS-preserved EEP could achieve similar surgical outcomes as other early apical release approaches. The preserved AFS provides a nice landmark at the 12 o'clock position during EEP.

Segmentation of the prostate, its zones, anterior fibromuscular stroma, and urethra on the MRIs and multimodality image fusion using U-Net model.

BackgroundDue to the large variability in the prostate gland of different patient groups, manual segmentation is time-consuming and subject to inter-and intra-reader variations. Hence, we propose a U-Net model to automatically segment the prostate and its zones, including the peripheral zone (PZ), transitional zone (TZ), anterior fibromuscular stroma (AFMS), and urethra on the MRI [T2-weighted (T2W), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC)], and multimodality image fusion.MethodsA total of 91 eligible patients were retrospectively identified; 50 patients were considered for training process in a 10-fold cross-validation fashion and 41 ones for external test. Firstly, images were registered, and cropping was performed through a bounding box. In addition to T2W, DWI, and ADC separately, fused images were used. We considered three combinations, including T2W + DWI, T2W + ADC, and DWI + ADC, using wavelet transform. U-Net was applied to segment the prostate and its zones, AFMS, and urethra in a 10-fold cross-validation fashion. Eventually, dice score (DSC), intersection over union (IoU), precision, recall, and Hausdorff distance (HD) were used to evaluate the proposed model.ResultsUsing T2W images alone on the external test images, higher DSC, IoU, precision, and recall was achieved than the individual DWI and ADC images. DSC of 95%, 94%,98%, 94%, and 88%, IoU of 88%, 88.5%, 96%, 90%, and 79%, precision of 95.9%, 93.9%, 97.6%, 93.83%, and 87.82%, and recall of 94.2%, 94.2%, 98.3%, 94%, 87.93% was achieved for the whole prostate, PZ, TZ, urethra, and AFMS, respectively. The results clearly show that the best segmentation was obtained when the model is trained using T2W + DWI images. DSC of 99.06%, 99,05%, 99.04%, 99.09%, and 98.08%, IoU of 97.09%, 97.02%, 98.12%, 98.13%, and 96%, precision of 99.24%, 98.22%, 98.91%, 99.23%, and 98.9%, and recall of 98.3%, 99.8%, 99.02%, 98.93%, and 97.51% was achieved for the whole prostate, PZ, TZ, urethra, and AFMS, respectively. The min of the HD in the testing set for three combinations was 0.29 for the T2W + ADC procedure in the whole prostate class.ConclusionsBetter performance was achieved using T2W + DWI images than T2W, DWI, and ADC separately or T2W + ADC and DWI + ADC in combination.

PD57-09 THE IMPORTANCE OF MRI-TARGETED BIOPSY FOR TUMORS IN ANTERIOR FIBROMUSCULAR STROMA

You have accessJournal of UrologyCME1 May 2022PD57-09 THE IMPORTANCE OF MRI-TARGETED BIOPSY FOR TUMORS IN ANTERIOR FIBROMUSCULAR STROMA Hayato Yamamoto, Teppei Okamoto, Toru Yoneyama, and Chikara Ohyama Hayato YamamotoHayato Yamamoto More articles by this author , Teppei OkamotoTeppei Okamoto More articles by this author , Toru YoneyamaToru Yoneyama More articles by this author , and Chikara OhyamaChikara Ohyama More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002637.09AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Anterior prostate cancers are frequently missed since they can be neither palpable nor tangible on physical examination. The objective of this study was to analyze the MRI/transrectal ultrasound-fusion biopsies to detect and to characterize significant prostate cancer in the anterior fibromuscular stroma (AFS) and in the transition zone of the prostate. METHODS: One hundred and fourteen patients underwent prebiopsy 3 T multi parametric (mp) MRI and transperineal biopsy between February 2019 and May 2021. MRI images were analyzed using PIRADS (Prostate Imaging-Reporting and Data System) ver 2. All patients had systematic biopsies and targeted biopsies with rigid software registration in case of MRI-suspicious lesions. RESULTS: The positive rates of systematic and targeted biopsies were 10% and 29%, respectively with a significant difference. The cancer occupancy rate of the biopsy specimens was higher in the targeted biopsy, 22.2% and 36.3%, respectively. There were AFS tumors in 23 of 114 patients, and they harbored 23 lesions (10%) in AFS on mpMRI. The positive rate of targeted biopsy by PI-RADs category was 77% for PI-RADs 5, 42% for PI-RADs 4, and 16% for PI-RADs 3. The positive rate by target region were 24%, 31%, and 83% for peripheral zone (PZ), transition zone (TZ), and AFS, respectively. Especially, in PIRADs category 3 region, the positive rate in AFS region was a high positivity rate of 100%. CONCLUSIONS: Targeted biopsy has improved cancer detection rates. However, we should also pay attention to lesions of low PIRADs category in the AFS region. Source of Funding: none © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e964 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Hayato Yamamoto More articles by this author Teppei Okamoto More articles by this author Toru Yoneyama More articles by this author Chikara Ohyama More articles by this author Expand All Advertisement PDF DownloadLoading ...

A0464 - The importance of MRI-targeted biopsy for tumors in Anterior fibromuscular stroma

A0464 - The importance of MRI-targeted biopsy for tumors in Anterior fibromuscular stroma

Combined model-based and deep learning-based automated 3D zonal segmentation of the prostate on T2-weighted MR images: clinical evaluation.

To train and totest for prostate zonal segmentation an existing algorithm already trained for whole-gland segmentation. The algorithm, combining model-based and deep learning-based approaches, was trained for zonal segmentation using the NCI-ISBI-2013 dataset and 70 T2-weighted datasets acquired at an academic centre. Test datasets were randomly selected among examinations performed at this centre on one of two scanners (General Electric, 1.5T; Philips, 3T) not used for training. Automated segmentations were corrected by two independent radiologists. When segmentation was initiated outside the prostate, images were cropped and segmentation repeated. Factors influencing the algorithm's mean Dice similarity coefficient (DSC) and its precision were assessed using beta regression. Eighty-two test datasets were selected; one was excluded. In 13/81 datasets, segmentation started outside the prostate, but zonal segmentation was possible after image cropping. Depending on the radiologist chosen as reference, algorithm's median DSCs were 96.4/97.4%, 91.8/93.0% and 79.9/89.6% for whole-gland, central gland and anterior fibromuscular stroma (AFMS) segmentations, respectively. DSCs comparing radiologists' delineations were 95.8%, 93.6% and 81.7%, respectively. For all segmentation tasks, the scanner used for imaging significantly influenced the mean DSC and its precision, and the mean DSC was significantly lower in cases with initial segmentation outside the prostate. For central gland segmentation, the mean DSC was also significantly lower in larger prostates. The radiologist chosen as reference had no significant impact, except for AFMS segmentation. The algorithm performance fell within the range of inter-reader variability but remained significantly impacted by the scanner used for imaging. • Median Dice similarity coefficients obtained by the algorithm fell within human inter-reader variability for the three segmentation tasks (whole gland, central gland, anterior fibromuscular stroma). • The scanner used for imaging significantly impacted the performance of the automated segmentation for the three segmentation tasks. • The performance of the automated segmentation of the anterior fibromuscular stroma was highly variable across patients and showed also high variability across the two radiologists.

Identification of prostate cancer using multiparametric MR imaging characteristics of prostate tissues referenced to whole mount histopathology

In this study, the objective was to characterize the MR signatures of the various benign prostate tissues and to differentiate them from cancer. Data was from seventy prostate cancer patients who underwent multiparametric MRI (mpMRI) and subsequent prostatectomy. The scans included T2-weighted imaging (T2W), diffusion weighted imaging, dynamic contrast-enhanced MRI (DCE MRI), and MR spectroscopic imaging. Histopathology tissue information was translated to MRI images. The mpMRI parameters were characterized separately per zone and by tissue type. The tissues were ordered according to trends in tissue parameter means. The peripheral zone tissue order was cystic atrophy, high grade prostatic intraepithelial neoplasia (HGPIN), normal, atrophy, inflammation, and cancer. Decreasing values for tissue order were exhibited by ADC (1.8 10−3 mm2/s to 1.2 10−3 mm2/s) and T2W intensity (3447 to 2576). Increasing values occurred for DCE MRI peak (143% to 157%), DCE MRI slope (101%/min to 169%/min), fractional anisotropy (FA) (0.16 to 0.19), choline (7.2 to 12.2), and choline / citrate (0.3 to 0.9). The transition zone tissue order was cystic atrophy, mixed benign prostatic hyperplasia (BPH), normal, atrophy, inflammation, stroma, anterior fibromuscular stroma, and cancer. Decreasing values occurred for ADC (1.6 10−3 mm2/s to 1.1 10−3 mm2/s) and T2W intensity (2863 to 2001). Increasing values occurred for DCE MRI peak (143% to 150%), DCE MRI slope (101%/min to 137%/min), FA (0.18 to 0.25), choline (7.9 to 11.7), and choline / citrate (0.3 to 0.7). Logistic regression was used to create parameter model fits to differentiate cancer from benign prostate tissues. The fits achieved AUCs ≥0.91. This study quantified the mpMRI characteristics of benign prostate tissues and demonstrated the capability of mpMRI to discriminate among benign as well as cancer tissues, potentially aiding future discrimination of cancer from benign confounders.

Zonal anatomy of the prostate using magnetic resonance imaging, morphometrics, and radiomic features: impact of age-related changes.

To evaluate the impact of age on the zonal anatomy of the prostate by MRI using morphometric and textural analysis. A total of 154 men (mean age: 63 years) who underwent MRI due to a high prostate-specific antigen (PSA) level were included retrospectively. At each MRI examination the following variables were measured: overall dimensions of the prostate (whole gland (WG), transitional zone (TZ), and peripheral zone (PZ)), and thickness of the anterior fibromuscular stroma (AFMS) and the periprostatic venous plexus (PPVP) on T2 weighted images. Identical regions of interest (ROIs) were delineated on the apparent diffusion coefficient (ADC) map on the anterior (horn) and posterior part of the PZ. Textural (TexRAD®) parameter differences between TZ and PZ ROIs on T2 weighted images were analyzed by linear regression. Results were correlated with age (distributed into five decades from 22 to 89 years). Age was positively correlated with PSA level and glandular volumes (WG, TZ, and TZ/WG ratio; p < 0.0001) and was negatively correlated with AFSM and PPVP thickness (p < 0.0001). There was a positive correlation between ADC values of the PZ and age (p = 0.003) and between entropy of the TZ and PZ and age (p < 0.001). Gradual variations in morphologic and textural features of the prostate were observed with age, mainly due to the increase in TZ volume while PZ volume tended to decrease. These modifications resulted in textural changes mainly at the expense of entropy. Entropy could be relevant for studying the process of aging of the prostate.

Novel Automated Three-Dimensional Surgical Planning Tool and Magnetic Resonance Imaging/Ultrasound Fusion Technology to Perform Nanoparticle Ablation and Cryoablation of the Prostate for Focal Therapy

Purpose: Although MRI/ultrasound fusion has been primarily used to assist in the diagnosis of prostate cancer, this technology can also be used to focally treat localized prostate cancer. We present one case of nanoparticle-directed ablation and two cases of cryoablation to focally treat prostate tumors. Patients and Methods: Three patients underwent MRI/ultrasound fusion transperineal prostate biopsies to confirm low- to intermediate-risk prostate cancer. The MRI lesions correlated with the biopsy-proven disease. Pelvic MRI segmentation was performed with DynaCAD 5.0 workstation. The MRI lesion including a 6 to 10 mm margin, prostate, bladder, urethra, urethral sphincter, rectum, and pubic bone were segmented. MRI/ultrasound fusion was performed with the novel Philips UroNav 4.0 system. Lesions were treated with focal nanoparticle ablation or focal cryoablation. Results: A 69-year-old man with a right posterior medial peripheral zone lesion positive for Gleason grade group (GG)3 cancer was treated with focal nanoparticle ablation. The UroNav 4.0 system reported 100% ablation of the segmented tumor and 94% of the 6 to 10 mm margin at the end of the case. A 68-year-old man with a left anterior fibromuscular stroma lesion positive for Gleason GG2 cancer and a 71-year-old man with a right peripheral zone posterior lateral lesion positive for Gleason GG1 cancer were treated with focal cryoablation. The UroNav 4.0 system reported 100% ablation of the segmented tumor and 82% of the 6 to 10 mm margin at the end of the case. Conclusion: Observation of the prostate tumor(s), surrounding critical structures, and pelvis in three dimensions (3D), along with the anticipated ablation zone, is one of the challenges of pelvic surgery and percutaneous ablation. The DynaCAD 5.0 Urology system can create an auto-segmented 3D rendering of critical structures and the tumor(s), as well as observation and quantification of the anticipated ablation coverage, to facilitate preoperative planning of needle placement. ClinicalTrials.gov nos.: NCT02680535 and NCT04656678.

V14-08 NOVEL AUTOMATED 3D SURGICAL PLANNING TOOL AND MRI/ULTRASOUND FUSION TECHNOLOGY TO PERFORM NANOPARTICLE ABLATION AND CRYOABLATION OF THE PROSTATE FOR FOCAL THERAPY

You have accessJournal of UrologyProstate Oncology II & Testis Oncology & Misc. Oncology (V14)1 Sep 2021V14-08 NOVEL AUTOMATED 3D SURGICAL PLANNING TOOL AND MRI/ULTRASOUND FUSION TECHNOLOGY TO PERFORM NANOPARTICLE ABLATION AND CRYOABLATION OF THE PROSTATE FOR FOCAL THERAPY Joshua Jue, Samuel Coons, Gilion Hautvast, Scott Thompson, Jack Geraats, Lee Richstone, Michael Schwartz, and Ardeshir Rastinehad Joshua JueJoshua Jue More articles by this author , Samuel CoonsSamuel Coons More articles by this author , Gilion HautvastGilion Hautvast More articles by this author , Scott ThompsonScott Thompson More articles by this author , Jack GeraatsJack Geraats More articles by this author , Lee RichstoneLee Richstone More articles by this author , Michael SchwartzMichael Schwartz More articles by this author , and Ardeshir RastinehadArdeshir Rastinehad More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002111.08AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Although MRI/Ultrasound fusion has been primarily used to assist in the diagnosis of prostate cancer, the next logical step forward would be using the technology to focally treat localized prostate cancer. We present one case of nanoparticle directed ablation and two cases of cryoablation to focally treat prostate tumors. METHODS: Three patients underwent MRI/Ultrasound fusion transperineal prostate biopsies to confirm low to intermediate risk prostate cancer prior to treatment. The MRI lesions correlated with the biopsy proven disease, and no prostate cancer was present on systematic biopsies using the modified Barzel template. Pelvic MRI segmentation was performed with DynaCAD 5.0 workstation. The MRI lesion including a 6-10 mm margin, prostate, bladder, urethra, urethral sphincter, rectum, and pubic bone were segmented. MRI/Ultrasound fusion was performed with the novel Philips UroNav 4.0 system. Lesions were treated with focal nanoparticle ablation or focal cryoablation. RESULTS: A 69-year-old male with a 10mm lesion in the right mid gland posterior medial peripheral zone was positive for Gleason GG3 cancer and was treated with focal nanoparticle ablation. The UroNav 4.0 system reported 100% ablation of the segmented tumor and 94% of the 6-10 mm margin at the end of the case. A 68-year-old male with a 13mm lesion in the left anterior fibromuscular stroma apex positive for Gleason GG2 cancer and a 71-year-old male with a 16mm lesion in the right peripheral zone posterior lateral positive for Gleason GG1 cancer, were treated with focal cryoablation. The UroNav 4.0 system reported 100% ablation of the segmented tumor and 82% of the 6-10mm margin at the end of the case for the left anterior fibromuscular stroma apex lesion. CONCLUSIONS: Visualization of the prostate tumor(s), surrounding critical structures, and pelvis in 3 dimensions, along with the anticipated ablation zone, is one of the challenges of pelvic surgery and percutaneous ablation. The DynaCAD 5.0 Urology system can create anauto-segmented 3D rendering of critical structures and the tumor(s), as well as visualization and quantification of the anticipated ablation coverage, to facilitate preoperative planning of needle placement. Ultimately, this MRI/Ultrasound fusion technology combined with 3D mapping holds significant potential and will be utilized for new applications in the future. Source of Funding: None © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e1167-e1168 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Joshua Jue More articles by this author Samuel Coons More articles by this author Gilion Hautvast More articles by this author Scott Thompson More articles by this author Jack Geraats More articles by this author Lee Richstone More articles by this author Michael Schwartz More articles by this author Ardeshir Rastinehad More articles by this author Expand All Advertisement Loading ...

Manyetik rezonans görüntüleme- ultrason füzyon prostat biyopsisi tek merkez sonuçları

Objective: We aimed to evaluate magnetic resonance imaging-ultrasound guided fusion prostate biopsy (MRI- US FPBx) results from a single center and to compare with current literature. Material and Methods: Between January 2016 and July 2019, MRI-US FPBx pathological and imaging results of 358 men were retrospectively analyzed. PI-RADS scores were determined as 3, 4 and 5 in 222 (62%), 107 (29.8%) and 29 (8.1%) patients, respectively. Totally 454 lesions were underwent MRI-US FPBx. 303 (66.7%) lesions were scored as PI-RADS 3, 120 (26.4%) lesions were scored as PI-RADS 4 and 31 (6.8%) lesions were scored as PI-RADS 5. 315 (69.3%) of lesions were in peripheral zone, 26 (5.7%) were in central zone, 111 (24.4%) were in transitional zone and 2 of them were in anterior fibromuscular stroma. Results: Overall prostate cancer detection rate was 36.3%. Concerning detection rates, MRI-US FPBx alone and transrectal ultrasonography guided prostate biopsy (TRUS-Bx) alone were 27.6% and 26.5%, respectively. Cancer detection rate only through MRI-US FPBx PIRADS-3 and PI-RADS 4&amp;5 were 6.9% and 20.6%, respectively. Clinically significant prostate cancer (csPCa) rates were evaluated and csPCa to overall prostate cancer (PCa) rates for TRUS-Bx, MRI-US FPBx and combined techniques were 16.8%, 35.4% and 39.2%, respectively. Results of 11 patients were evaluated as benign. Conclusion: MRI-US FPBx significantly increases success rate of prostate biopsy procedure. Regarding current MRI technology, it is not appropriate to consider MRI-US FPBx as a stand-alone biopsy option without concomitant with TRUS-Bx. Keywords: prostate cancer; biopsy; MRI; fusion

Uncertainty-aware temporal self-learning (UATS): Semi-supervised learning for segmentation of prostate zones and beyond

Various convolutional neural network (CNN) based concepts have been introduced for the prostate's automatic segmentation and its coarse subdivision into transition zone (TZ) and peripheral zone (PZ). However, when targeting a fine-grained segmentation of TZ, PZ, distal prostatic urethra (DPU) and the anterior fibromuscular stroma (AFS), the task becomes more challenging and has not yet been solved at the level of human performance. One reason might be the insufficient amount of labeled data for supervised training. Therefore, we propose to apply a semi-supervised learning (SSL) technique named uncertainty-aware temporal self-learning (UATS) to overcome the expensive and time-consuming manual ground truth labeling. We combine the SSL techniques temporal ensembling and uncertainty-guided self-learning to benefit from unlabeled images, which are often readily available. Our method significantly outperforms the supervised baseline and obtained a Dice coefficient (DC) of up to 78.9%, 87.3%, 75.3%, 50.6% for TZ, PZ, DPU and AFS, respectively. The obtained results are in the range of human inter-rater performance for all structures. Moreover, we investigate the method's robustness against noise and demonstrate the generalization capability for varying ratios of labeled data and on other challenging tasks, namely the hippocampus and skin lesion segmentation. UATS achieved superiority segmentation quality compared to the supervised baseline, particularly for minimal amounts of labeled data.

PI-RADS 2.1 - Image Interpretation: The Most Important Updates andTheir Clinical Implications.

Multiparametric magnetic resonance imaging (MRI) of the prostate plays a central role in the diagnosis of patients with suspected prostate cancer. The increasing distribution and application of the guideline for the standardization of image acquisition, evaluation, and reporting (Prostate Imaging - Reporting and Data System, PI-RADS), which was updated in 2019 to version 2.1, contributes to the success of the technique. The most important updates of PI-RADS version 2.1 presented in 2019 compared to the previous version PI-RADS 2.0 are highlighted and interpreted with regard to their clinical implications. PI-RADS version 2.1 aims to simplify the application of the scoring scheme without changing the basic concept of dominant sequences (DWI in the peripheral zone, T2 in the transition zone). Of particular importance are the increasing role of diffusion-weighted imaging in the transition zone, the now mandatory high b-value of at least 1400 s/mm2, and new information on the assessment of the central zone and the anterior fibromuscular stroma. PI-RADS version 2.1 published in 2019 addresses a number of changes to the previous version, including both the examination technique and image interpretation. Prospective clinical studies have yet to prove the extent to which the goals of reducing interreader variability and increasing the detection rate in the transition zone will be achieved. · The new PI-RADS version 2.1. includes changes regarding image interpretation and examination technique. · The role of diffusion-weighted imaging is strengthened in the transition zone. · An ultra-high b-value of at least 1400 s/mm2 is mandatory according to PI-RADS 2.1. · Biparametric MRI is not recommended for general application. · Beyer T, Schlemmer H, Weber M et al. PI-RADS 2.1 - Image Interpretation: The Most Important Updates and Their Clinical Implications. Fortschr Röntgenstr 2021; 193: 787 - 795.

Automatic intraprostatic lesion segmentation in multiparametric magnetic resonance images with proposed multiple branch UNet.

Contouring intraprostatic lesions is a prerequisite for dose-escalating these lesions in radiotherapy to improve the local cancer control. In this study, a deep learning-based approach was developed for automatic intraprostatic lesion segmentation in multiparametric magnetic resonance imaging (mpMRI) images contributing to clinical practice. Multiparametric magnetic resonance imaging images from 136 patient cases were collected from our institution, and all these cases contained suspicious lesions with Prostate Imaging Reporting and Data System (PI-RADS) score≥4. The contours of the lesion and prostate were manually created on axial T2-weighted (T2W), apparent diffusion coefficient (ADC) and high b-value diffusion-weighted imaging (DWI) images to provide the ground truth data. Then a multiple branch UNet (MB-UNet) was proposed for the segmentation of an indistinct target in multi-modality MRI images. An encoder module was designed with three branches for the three MRI modalities separately, to fully extract the high-level features provided by different MRI modalities; an input module was added by using three sub-branches for three consecutive image slices, to consider the contour consistency among different image slices; deep supervision strategy was also integrated into the network to speed up the convergency of the network and improve the performance. The probability maps of the background, normal prostate and lesion were output by the network to generate the segmentation of the lesion, and the performance was evaluated using the dice similarity coefficient (DSC) as the main metric. A total of 162 lesions were contoured on 652 image slices, with 119 lesions in the peripheral zone, 38 in the transition zone, four in the central zone and one in the anterior fibromuscular stroma. All prostates were also contoured on 1,264 image slices. As for the segmentation of lesions in the testing set, MB-UNet achieved a per case DSC of 0.6333, specificity of 0.9993, sensitivity of 0.7056; and global DSC of 0.7205, specificity of 0.9993, sensitivity of 0.7409. All the three deep learning strategies adopted in this study contributed to the performance promotion of the MB-UNet. Missing the DWI modality would degrade the segmentation performance more markedly compared with the other two modalities. A deep learning-based approach with proposed MB-UNet was developed to automatically segment suspicious lesions in mpMRI images. This study makes it feasible to adopt boosting intraprostatic lesions in clinical practice to achieve better outcomes.

Age-related and zonal anatomical microstructure features of normal prostatic tissues: a preliminary study with VERDICT MRI.

This study aimed to explore the differences in VERDICT parameters for normal prostatic tissues among different regions and age groups. In total, 31 male volunteers were included in the study. Vascular, extracellular and restricted diffusion for cytometry in tumors (VERDICT) model parameters (fIC, intracellular volume fraction; fEES, extracellular-extravascular space fraction; and fVASC, vascular fraction) were calculated based on the whole prostate volume and the peripheral zone (PZ), central gland (CG) and anterior fibromuscular stroma(AS) regions of interest (ROIs). Agreement between two readers was determined by calculating the intraclass correlation coefficient. Two-way ANOVA was used to identify significant differences among age groups and regions within the prostate. Age-related and area-related changes in these parameters were assessed using Spearman's correlation coefficients. There were differences in the parameters among regions of the prostate (P < 0.05). In the PZ, there was a negative correlation between age and fIC (r = - 0.66, P < 0.001, adjusted P < 0.001), and age was positively correlated with fEES (r = 0.69, P < 0.001, adjusted P < 0.001) but had no correlation with fVASC. In the CG ROI, there was a positive correlation between age and fEES (r = 0.56, P < 0.001, adjusted P < 0.001) but no correlation between age and fVASC, similar to the results for the PZ. There were no correlations between age and VERDICT parameters in the AS. VERDICT parameters vary among different regions of the prostate and correlate with age. These findings are in agreement with histological theory.