Despite rapid proliferation of AI applications in prostate MRI showing impressive technical performance, clinical adoption remains limited. We conducted a comprehensive narrative review of literature from January 2018 to December 2024, examining AI applications in prostate MRI with emphasis on real-world performance and implementation challenges. Among 200+ studies reviewed, AI systems achieve 87% sensitivity and 72% specificity for cancer detection in research settings. However, external validation reveals average performance drops of 12%, with some implementations showing degradation up to 31%. Only 31% of studies follow reporting guidelines, 11% share code, and 4% provide model weights. Seven real-world implementation studies demonstrate integration times of 3–14 months, with one major center terminating deployment due to unacceptable false positive rates. The translation gap between artificial and clinical intelligence remains substantial. Success requires shifting focus from accuracy metrics to patient outcomes, establishing transparent reporting standards, developing realistic economic models, and creating appropriate regulatory frameworks. The field must combine methodological rigor, clinical relevance, and implementation science to realize AI’s transformative potential in prostate cancer care.

Background: Placenta accreta spectrum (PAS) disorders are associated with high mortality and morbidity due to postpartum hemorrhage, hysterectomy, and organ injury, and a multidisciplinary team is required for an individualized case management. In this study, we assessed the diagnostic and prognostic accuracy of the most important ultrasonographic (US) and magnetic resonance imagining (MRI) markers for PAS disorders. Material and Methods: The study included 39 adult pregnant patients with at least one previous cesarean delivery and both US and MRI investigations for placenta previa evaluated at the tertiary maternity hospital ‘Cuza Voda’, Iasi, between 2019 and 2021. The following US signs were evaluated: intra-placental lacunae, loss of the retroplacental hypoechoic zone, myometrial thinning < 1 mm, bladder wall interruption, placental bulging, bridging vessels, and the hypervascularity of the uterovesical or retroplacental space. The MRI signs that were evaluated were intra-placental dark T2 bands, placental bulging, loss of the retroplacental hypointense line on T2 images, myometrial thinning, bladder wall interruption, focal exophytic placental mass, and abnormal vascularization of the placental bed. Results: The US and MRI signs analyzed in our study presented adequate sensitivities and specificities for PAS, but no sign proved to be a useful predictor by itself. The presence of three or more US markers for accretion was associated with a sensitivity of 84.6.6% and a specificity of 92.3% (p < 0.001). The presence of three or more MRI signs supplemented these results and were associated with a sensitivity of 92.3% and a specificity of 61.5% for predicting PAS (p < 0.001). Moreover, US and MRI findings were correlated with FIGO grading and severity of PAS. Conclusions: Even though no US or MRI finding alone can predict PAS with high sensitivity and specificity, our study proves that the presence of three or more imagistic signs could significantly increase the diagnostic accuracy of this condition. Furthermore, US and MRI could be useful tools for evaluating prognostic and perinatal planning.

Background/Objectives: Neonatal early-onset sepsis (EOS) is a life-threatening condition, and numerous efforts have been invested in identifying the most promising biomarkers for its detection. In this prospective cohort study, we aimed to determine the diagnostic accuracy and optimal cut-off values of procalcitonin (PCT), presepsin, endocan, and interleukin (IL)-6 determined from the neonatal serum (0–12, 24–48, and 72–96 h), and umbilical blood cord for the diagnosis of EOS. Methods: A total of 122 patients were included in this study and were divided into two groups: group 1 (sepsis, n = 68 patients) and group 2 (without sepsis, n = 54 patients). Maternal and neonatal characteristics were assessed using descriptive statistics. Logistic regressions were used to evaluate the association between various biomarkers and the presence of EOS and to adjust for potential confounders. Using sensitivity analysis and Youden’s index from the ROC curve, the biomarkers’ diagnostic accuracy and optimal cut-off values were obtained. Results: PCT at 0–12 and 24–48 h of life exhibited the best diagnostic performance, with sensitivities (Ses) of 75% and 76.5% and specificities (Sps) above 74%. Presepsin demonstrated excellent performance at 24–48 h, with Ses of 68.42%, and Sps of 88.89%. IL-6 and endocan achieved modest results for the detection of EOS. Conclusions: PCT and presepsin measured at early neonatal timepoints demonstrated high diagnostic accuracy and favorable sensitivity–specificity balance for predicting EOS.

The discovery of a resident urinary microbiome has significantly altered the understanding of urolithiasis, expanding its etiology beyond metabolic and dietary factors to include microbial contributions. This review highlights how specific uropathogens—particularly Proteus mirabilis, Klebsiella pneumoniae, and Escherichia coli—facilitate stone formation through mechanisms such as urease activity, citrate degradation, urine alkalinization, biofilm development, and inflammatory signaling. We critically examine how antibiotic therapies, while essential for treating urinary tract infections (UTIs), disrupt microbial homeostasis by depleting beneficial taxa like Lactobacillus and enabling colonization by lithogenic and resistant strains. Recurrent or broad-spectrum antibiotic use is linked to persistent dysbiosis and increased risk of stone recurrence. Additionally, this paper explores emerging microbiome-targeted strategies—such as probiotics, prebiotics, bacteriotherapy, and precision antimicrobials—as potential interventions to restore microbial balance and mitigate stone risk. Recognizing the urinary microbiome as a therapeutic target opens new avenues for personalized, microbiota-conscious strategies in the prevention and management of kidney stone disease.

(1) Background: Magnetic resonance imaging (MRI) is the gold standard investigation for all patients who present with asymmetrical hearing loss (AHL) and a high index of suspicion for vestibular schwannoma (VS). However, pure-tone audiometry (PTA) is an investigation that can be used for the screening of these patients in order to reduce the costs. The aim of this systematic review and meta-analysis was to evaluate the diagnostic accuracy of different PTA protocols for VS in patients with ASHL, when compared with MRI; (2) Methods: Medline, Embase, and Cochrane databases were used to find relevant studies. All prospective and retrospective observational studies that evaluated the accuracy of PTA protocols for the screening of VS were assessed, according to the international guidelines; (3) Results: We analyzed seven studies (4369 patients) of poor-to-moderate quality. Their pooled sensitivity was good (0.73–0.93), but their specificity was low (0.31–0.60). All protocols were located in the right lower quadrant on the likelihood scattergram, and the post-test probabilities for positive and negative diagnosis of these protocols were extremely low; (4) Conclusions: PTA protocols cannot be used for a proper screening or diagnosis of vestibular schwannoma despite their good sensibility, and MRI remains the gold standard for this purpose.

Background and Objectives: A positive pathological circumferential resection margin is a key prognostic factor in rectal cancer surgery. The point of this prospective study was to see how well different MRI parameters could predict a positive pathological circumferential resection margin (pCRM) in people who had been diagnosed with rectal adenocarcinoma, either on their own or when used together. Materials and Methods: Between November 2019 and February 2023, a total of 112 patients were enrolled in this prospective study and followed up for a 36-month period. MRI predictors such as circumferential resection margin (mCRM), presence of extramural venous invasion (mrEMVI), tumor location, and the distance between the tumor and anal verge, taken individually or combined, were evaluated with univariate and sensitivity analyses. Survival estimates in relation to a pCRM status were also determined using Kaplan–Meier analysis. Results: When individually evaluated, the best MRI predictor for the detection of a pCRM in the postsurgical histopathological examination is mrEMVI, which achieved a sensitivity (Se) of 77.78%, a specificity (Sp) of 87.38%, a negative predictive value (NPV) of 97.83%, and an accuracy of 86.61%. Also, the best predictive performance was achieved by a model that comprised all MRI predictors (mCRM+ mrEMVI+ anterior location+ < 4 cm from the anal verge), with an Se of 66.67%, an Sp of 88.46%, an NPV of 96.84%, and an accuracy of 86.73%. The survival rates were significantly higher in the pCRM-negative group (p < 0.001). Conclusions: The use of selective individual imaging predictors or combined models could be useful for the prediction of positive pCRM and risk stratification for local recurrence or distant metastasis.