How to Integrate Prostate Cancer Biomarkers in Urology Clinical Practice: An Update.

Nowadays, the management of prostate cancer has become more and more challenging due to the increasing number of available treatment options, therapeutic agents, and our understanding of its carcinogenesis and disease progression. Moreover, currently available risk stratification systems used to facilitate clinical decision-making have limitations, particularly in providing a personalized and patient-centered management strategy. Although prognosis and prostate cancer-specific survival have improved in recent years, the heterogenous behavior of the disease among patients included in the same risk prognostic group negatively impacts not only our clinical decision-making but also oncological outcomes, irrespective of the treatment strategy. Several biomarkers, along with available tests, have been developed to help clinicians in difficult decision-making scenarios and guide management strategies. In this review article, we focus on the scientific evidence that supports the clinical use of several biomarkers considered by professional urological societies (and included in uro-oncological guidelines) in the diagnosis process and specific difficult management strategies for clinically localized or advanced prostate cancer.

Association between peri-transplant acid-base parameters and graft dysfunction types in kidney transplantation.

Perioperative acid-base disturbance could be informative regarding the possible slow graft function (SGF) or delayed graft function (DGF) development. There is a lack of data regarding the relationship between perioperative acid-base parameters and graft dysfunction in kidney transplant (KT) recipients. We aim to determine the incidence of graft dysfunction types and the association between them and acid-base parameters. We performed a prospective, cohort study on 54 adults, KT recipients, between 1st of January 2019 and 31st of December 2019. Graft function was defined and classified in three categories: immediate graft function (IGF) (serum creatinine < 3 mg/dL at day 5 after KT), SGF (serum creatinine ≥ 3mg/dL at day 5 or ≥ 2.5mg dL at day 7 after KT) and DGF (the need for at least one dialysis treatment in the first week after kidney transplantation). Among the 54 KT recipients, the incidence of SGF and DGF was 13% and 11.1%, respectively. SGF was significantly associated with lower intraoperative pH (7.26± 0.05 vs 7.35± 0.06, p= 0.004), preoperative and intraoperative base excess (BE) [-7.0 (-10.0 ߝ -6.0) vs -3.4 (-7.8 ߝ - 2.1) mmol/L, p= 0.04 and -10.3 (-11.0 ߝ -9.1) vs -4.0 (-6.3 ߝ - 3.0) mmol/L, p= 0.002, respectively] and serum bicarbonate (HCO3-) (16.0± 2.7 vs 19.3± 3.4 mmol/L, p= 0.01 and 14.1± 1.9 vs 18.8± 3.2 mmol/L, p= 0.002 respectively), compared to IGF. DGF was significantly associated with lower intraoperative values of pH (7.27± 0.05 vs 7.35± 0.06, p= 0.003), BE [-7.1 (-10.9 ߝ -6.1) vs -4.0 (-6.3 ߝ - 3.0) mmol/L, p= 0.02] and HCO3- (15.9± 2.4 vs 18.8± 3.2 mmol/L, p=0.02) compared to IGF. No differences were observed between SGF and DGF patients in any of the perioperative acid-base parameters. In conclusion we found that kidney graft dysfunction types are associated with perioperative acid-base parameters and perioperative metabolic acidosis could provide important information to predict SGF or DGF occurrence.

Ultrasound for kidney access in percutaneous nephrolithotomy: a contemporary review.

Nowadays percutaneous nephrolithotomy (PCNL) is the standard of care for renal staghorn calculus or large (>20 mm) pelvic or caliceal stones, as well as for the failure of other treatment options. This review aims to evaluate the contemporary use of ultrasound imaging in PCNL, by comparing it to conventional fluoroscopy, reviewing data regarding the complication and success rate of nephrostomy tract creation and stone free rate (SFR), as well as data concerning the learning curve for these procedures and cost indicators. The evidence acquired shows that the ultrasound guided access (USGA) is a comparable method with the classic fluoroscopic guided access (FGA), with a similar safety profile, with a significant reduction in radiation exposure, up to radiation free complete PCNL. USGA PCNL seems to lead to decreased bleeding and need for transfusion, especially when the Doppler mode is used, and also to a slightly higher SFR than conventional FGA PCNL. USGA PCNL reduces the overall costs of the procedure by about 30% and can be safely learnt and performed by urologists. For an experienced endourologist, familiar withFGA PCNL, the learning curve for shifting to USGA PCNL is of approximately 20 procedures.

Combined contrast-enhanced power Doppler and real-time sonoelastography performed during EUS, used in the differential diagnosis of focal pancreatic masses (with videos).

BACKGROUND: Contrast-enhanced power Doppler (CEPD) and real-time sonoelastography (RTSE) performed during EUS were previously described to be useful for the differential diagnosis between chronic pseudotumoral pancreatitis and pancreatic cancer. OBJECTIVE: To prospectively assess the accuracy of the combination of CEPD and RTSE to differentiate pancreatic focal masses. DESIGN: Cross-sectional feasibility study. SETTING: A tertiary-care academic referral center. PATIENTS: The study group included 54 patients with chronic pancreatitis (n = 21) and pancreatic adenocarcinoma (n = 33). INTERVENTIONS: Both imaging methods (CEPD and RTSE) were performed sequentially during the same EUS examination. Power Doppler mode examination was performed after intravenous injection of a second-generation contrast agent (2.4 mL of SonoVue), and the data were digitally recorded, comprising both the early arterial phase and venous/late phase. Three 10-second sonoelastographic videos were also digitally recorded that included the focal mass and the surrounding pancreatic parenchyma. Postprocessing analyses based on specially designed software were used to analyze the CEPD and RTSE videos. A power Doppler vascularity index was used to characterize CEPD videos, the values being averaged during a 10-second video in the venous phase. Hue histogram analysis was used to characterize RTSE videos, with the mean hue histogram values being also averaged during a 10-second video. MAIN OUTCOME MEASUREMENTS: To differentiate chronic pancreatitis and pancreatic cancer. RESULTS: The sensitivity, specificity, and accuracy of combined information provided by CEPD and RTSE to differentiate hypovascular hard masses suggestive of pancreatic carcinoma were 75.8%, 95.2%, and 83.3%, respectively, with a positive predictive value and negative predictive value of 96.2% and 71.4%, respectively. LIMITATION: A single-center, average size of study population. CONCLUSIONS: A combination of CEPD and RTSE performed during EUS seems to be a promising method that allows characterization and differentiation of focal pancreatic masses.

Neural network analysis of dynamic sequences of EUS elastography used for the differential diagnosis of chronic pancreatitis and pancreatic cancer.

BACKGROUND: EUS elastography is a newly developed imaging procedure that characterizes the differences of hardness and strain between diseased and normal tissue. OBJECTIVE: To assess the accuracy of real-time EUS elastography in pancreatic lesions. DESIGN: Cross-sectional feasibility study. PATIENTS: The study group included, in total, 68 patients with normal pancreas (N = 22), chronic pancreatitis (N = 11), pancreatic adenocarcinoma (N = 32), and pancreatic neuroendocrine tumors (N = 3). A subgroup analysis of 43 cases with focal pancreatic masses was also performed. INTERVENTIONS: A postprocessing software analysis was used to examine the EUS elastography movies by calculating hue histograms of each individual image, data that were further subjected to an extended neural network analysis to differentiate benign from malignant patterns. MAIN OUTCOME MEASUREMENTS: To differentiate normal pancreas, chronic pancreatitis, pancreatic cancer, and neuroendocrine tumors. RESULTS: Based on a cutoff of 175 for the mean hue histogram values recorded on the region of interest, the sensitivity, specificity, and accuracy of differentiation of benign and malignant masses were 91.4%, 87.9%, and 89.7%, respectively. The positive and negative predictive values were 88.9% and 90.6%, respectively. Multilayer perceptron neural networks with both one and two hidden layers of neurons (3-layer perceptron and 4-layer perceptron) were trained to learn how to classify cases as benign or malignant, and yielded an excellent testing performance of 95% on average, together with a high training performance that equaled 97% on average. LIMITATION: A lack of the surgical standard in all cases. CONCLUSIONS: EUS elastography is a promising method that allows characterization and differentiation of normal pancreas, chronic pancreatitis, and pancreatic cancer. The currently developed methodology, based on artificial neural network processing of EUS elastography digitalized movies, enabled an optimal prediction of the types of pancreatic lesions. Future multicentric, randomized studies with adequate power will have to establish the clinical impact of this procedure for the differential diagnosis of focal pancreatic masses.

Dynamic analysis of EUS used for the differentiation of benign and malignant lymph nodes.

BACKGROUND: EUS elastography was reported to offer supplemental information that allows a better characterization of tissue, and that might enhance conventional EUS imaging. OBJECTIVE: Our purpose was to apply real-time elastography during EUS examinations and to assess the accuracy of the differentiation of benign versus malignant lymph nodes. DESIGN: Prospective cross-sectional feasibility study. SETTING: Department of Surgical Gastroenterology, Gentofte University Hospital, Hellerup, Denmark. PATIENTS: Patients diagnosed by EUS with cervical, mediastinal, or abdominal lymph nodes were included, with a total number of 78 lymph nodes examined. The final diagnosis of the type of lymph node was obtained by EUS-FNA cytologic analysis or by surgical pathologic examination and by a minimum 6 months of follow-up. INTERVENTIONS: Hue histogram analysis of the average images computed from EUS elastography movies was used to assess the color information inside the region of interest and to consequently differentiate benign and malignant lymph nodes. MAIN OUTCOME MEASUREMENTS: Differentiate between malignant and benign lymph nodes. RESULTS: By using mean hue histogram values, the sensitivity, specificity, and accuracy for the differential diagnosis were 85.4%, 91.9%, and 88.5%, respectively, on the basis of a cutoff level of 166 (middle of green-blue rainbow scale). The proposed method might be useful to avoid color perception errors, moving artifacts, or possible selection bias induced by analysis of still images. LIMITATIONS: Lack of the surgical standard in all cases. CONCLUSIONS: Computer-enhanced dynamic analysis based on hue histograms of the EUS elastography movies represents a promising method that allows the differential diagnosis of benign and malignant lymph nodes, offering complementary information added to conventional EUS imaging.