Search Results (5,708)

Objective: To evaluate the diagnostic and prognostic utility of the hemoglobin–albumin–lymphocyte–platelet (HALP) score and several systemic inflammatory indices derived from routine blood parameters—including the systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR), pan-immune inflammation value (PIV), and systemic inflammatory response index (SIRI)—for pathogen differentiation and clinical assessment in culture-proven late-onset neonatal sepsis (LOS). Methods: A retrospective analysis was conducted on a cohort of 150 neonates with culture-proven LOS. Systemic inflammatory indices were calculated at baseline (first week of life) and at the time of septic insult. The discriminative power of these indices was assessed via ROC curve analysis, with optimal cut-off points determined by the Youden Index. Risk stratification was performed using Odds Ratio (OR) modeling with 95% Confidence Intervals (CIs) to evaluate the predictive strength of each marker according to its respective threshold. Results: Diagnosis-phase assessments identified SII as the premier discriminator for microbiological etiology (AUC = 0.869; OR = 44.57), outperforming PLR and PIV. Although HALP demonstrated moderate efficacy in distinguishing pathogens, it lacked prognostic value regarding mortality. Conversely, SIRI displayed limited clinical utility, yielding the lowest predictive performance in our cohort. Conclusions: In neonatal sepsis, the HALP score provided additional clinical information when compared with several hematological inflammatory indices. Although HALP was not associated with mortality, prospective multicenter studies are needed to clarify the role of these cost-effective markers in pathogen differentiation and clinical assessment of LOS. Full article

Aim: To evaluate the diagnostic value of conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) features in differentiating benign from malignant Bethesda III/IV thyroid nodules, and to identify independent predictors of malignancy. Methods: We retrospectively analyzed 164 surgically confirmed Bethesda III/IV thyroid nodules. CUS and CEUS features were evaluated by two experienced radiologists blinded to pathological outcomes. Univariate analysis compared features between benign and malignant groups. Multivariate logistic regression was used to identify independent predictors. Diagnostic models were constructed based on CUS alone, CEUS alone, and their combination, with performance evaluated using receiver operating characteristic (ROC) curve analysis. The area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each model. Results: The malignancy rate was 48.8% (80/164). Multivariate analysis identified microcalcifications (OR = 4.815, p < 0.001), aspect ratio >1 (OR = 2.499, p = 0.028), and irregular shape (OR = 2.465, p = 0.035) as independent risk factors, while older age (OR = 0.926 per year, p < 0.001) was protective. The CUS model achieved an AUC of 0.815 with high sensitivity (91.3%) and NPV (87.7%). The CEUS model performed poorly (AUC = 0.609). The combined model (AUC = 0.823) showed no significant improvement over CUS alone (p > 0.05). Physician subjective diagnosis based on CEUS TI-RADS yielded an AUC of 0.775. Conclusions: Conventional ultrasound features provide good diagnostic value for Bethesda III/IV nodules, with high sensitivity and NPV suitable for clinical screening. The addition of CEUS offered limited incremental benefit in this specific population, suggesting that the diagnostic value of CEUS for differentiating benign from malignant cytologically indeterminate thyroid nodules (ITNs) may be limited. Full article

Background: Tumour volume percentage (TVP) is considered an important pathological parameter, particularly in prostate cancer, representing the ratio of tumour volume to the total gland, and it can be used to measure the quantity of malignancy. Previous reports have already demonstrated that an elevated tumour volume percentage is associated with unfavourable factors, including extraprostatic extension, positive surgical margins, and lymph node metastasis. The independent value of TVP, especially in high-risk prostate cancer treated by radical prostatectomy, remains an area of active research, despite established prognostic factors such as PSA, ISUP grade, and TNM stage. Materials and Methods: We retrospectively analyzed the records of 159 high-risk prostate cancer patients who underwent open or laparoscopic radical prostatectomy between January 2016 and January 2025 at the Clinic of Urology of Targu Mures. High-risk patients were defined as those with ISUP grade 4–5 or PSA >20 ng/mL or clinical stage ≥T2c or stage cT3–4 and/or lymph node metastasis. Tumour volume percentage was calculated from the final pathology result and was determined as the proportion of prostate cancer volume relative to the total prostate volume. Clinical and pathological features, including PSA, ISUP grade, TNM stage, surgical margin, and lymph node involvement, were reported. To assess TVP as an indicator of tumour aggressiveness, univariate and multivariate regression analyses were performed. A p-value <0.05 was considered statistically significant. Results: A total of 159 high-risk prostate cancer patients (100%), with a median age of 66 years, who underwent open or laparoscopic radical prostatectomy were included. The median tumour volume percentage was 7.6%, and the median prostate volume was 43.8 cc. On univariate analysis, patients with extraprostatic extension (p < 0.001), positive surgical margins (p = 0.005), a higher ISUP grade (p < 0.001), and lymph node metastasis (p = 0.006) exhibited higher TVP compared to their counterparts. A significant correlation was also observed between TVP and the number of positive biopsy cores (p < 0.001), a higher PSA value (p = 0.005), and a younger age (p = 0.041). Conversely, no correlation was identified between TVP and perioperative factors such as hospital stay, surgery duration, ICU days, type of approach, or positive urine culture. Two regression models on multivariate analyses were performed with TVP as the dependent variable. In the continuous variable model (Adjusted R² = 0.43, p < 0.001), independent predictors of higher TVP were the number of positive biopsy cores (B = 0.54, p < 0.001), the number of positive lymph nodes (B = 2.59, p < 0.001), and surgical margin dimension (B = 1.19, p < 0.001). Age, PSA, and perioperative variables showed no significant correlation with TVP on multivariate analysis. In the categorical regression model (Adjusted R² = 0.438), statistical significance was confirmed (F-test, p < 0.001). Independent predictors of increased tumour volume percentage included ISUP grade 5 in the effect-coded model (B = +6.60, 95% CI: 0.96–12.25, p = 0.022), and pathological TNM stage pT4 (B = +24.70, 95% CI: 17.69–31.70, p < 0.001). ROC analysis showed limited-to-moderate discrimination for positive surgical margins (AUC = 0.655; 95% CI 0.565–0.744; p = 0.001) and stronger discrimination for pN1 (AUC = 0.793; 95% CI 0.650–0.936; p = 0.002). The Youden-derived cut-offs were 4.90% for positive surgical margins and 5.77% for lymph-node metastasis. Conclusions: Tumour volume percentage is significantly associated with several adverse pathological features in high-risk prostate cancer. Rather than a standalone biomarker, its association with adverse pathological features underscores its potential role in risk stratification models, and the incorporation into pathology reports and prognostic nomograms may improve clinical decision-making. Full article

Background/Objectives: Clonal evolution is mainly defined based on the appearance or expansion of clones harboring specific somatic mutations and/or cytogenetic abnormalities, whereas few studies have investigated immunophenotypic heterogeneity assessed by flow cytometry and its relationship with disease progression. In this study, flow cytometry immunophenotyping of acute myeloid leukemia (AML) was carried out to identify phenotypic subclones based on antigen expression and to investigate clonal sweep. Methods: A total of 24 patients diagnosed with AML followed at the Hematology and Transplant Center of Salerno were included. Bone marrow or peripheral blood specimens were subjected to flow cytometry immunophenotyping and leukemic cell characterization. Phenotypic profiles were also compared to molecular alterations detected by next-generation sequencing. Results: We found that flow cytometry-defined clonal heterogeneity was more complex than molecular heterogeneity at diagnosis and disease relapse. Flow cytometry enabled the identification of small phenotypic subclones that were not detected by molecular profiling and that, in several cases, expanded over time, consistent with a phenotypic clonal sweep. The presence of small clones was associated with shorter progression-free survival and overall survival. Conclusions: Flow cytometric clonal heterogeneity, especially the presence of small clones (defined by antigen expression from 2 to 30%), may serve as an additional prognostic factor in AML. Immunophenotyping integrated with molecular data may improve risk stratification, enhance measurable residual disease assessment, and contribute to a more personalized disease monitoring strategy. Full article

Timely identification of canopy decline in commercial strawberry production is challenging because visual scouting often misses subtle or spatially heterogeneous symptoms. We developed a plant-level UAV-based monitoring framework that integrates repeated multispectral imagery, canopy-derived metrics, unsupervised clustering, and Random Survival Forest (RSF) time-to-event modeling. The framework was applied across three commercial strawberry fields in Oxnard, California using nine UAV surveys collected from December 2022 to June 2023, yielding 159,220 plant-level monitoring units. NDRE- and Redness Index-based classifications quantified proportional and absolute canopy dieback within standardized hexagonal units and supported survival-based modeling of canopy decline progression. Across withheld test plants from all survey dates, overall concordance indices ranged from 0.88 to 0.95 across fields, indicating strong ability to rank plants by time-to-decline risk under heterogeneous field conditions. Spatial risk maps revealed localized high-risk clusters that expanded over time in fields with greater canopy deterioration, while fields with minimal visible decline exhibited diffuse but stable risk distributions. Post-hoc comparison with operational fumigation rates (280, 336, and 392 kg Pic-Clor 60/ha) showed no consistent association with predicted canopy decline risk. These results demonstrate that framing repeated UAV observations as a time-to-event process enables fine-scale spatiotemporal modeling of canopy decline dynamics and supports risk stratification for targeted field monitoring in commercial strawberry systems. Full article

Background/Objectives: Traditional histopathologic grading of renal cell carcinoma (RCC) is subjective, is poorly reproducible, and fails to predict responses to modern targeted agents or immunotherapies. In the era of precision oncology, molecular pathology offers objective tools for individualized management. We aimed to characterize genomic alterations in clear-cell RCC (ccRCC) with venous tumor thrombus and to develop pathology-driven panels for personalized prognostic stratification, with exploratory assessment of their potential to predict therapeutic response. Methods: Formalin-fixed paraffin-embedded pT1 ccRCC samples with and without thrombus underwent whole-exome sequencing. Distinct somatic mutations and copy number variations were incorporated into multigene panels. External assessment was performed in TCGA and PAWG cohorts, assessing survival outcomes and therapeutic biomarkers including homologous recombination deficiency (HRD), tumor mutational burden (TMB), and microsatellite instability (MSI). Results: Thrombus cases showed unique genomic heterogeneity compared with matched controls. Three multigene panels were constructed. Across external datasets, including a 354-patient TCGA-KIRC ccRCC cohort, the panels provided consistent molecular stratification signals for overall, disease-specific, and progression-free survival, complementing established pathological risk factors. They were significantly associated with established therapy-related genomic biomarkers, including HRD, TMB, and MSI, showing high sensitivity and negative predictive value in identifying patients unlikely to harbor these biomarker-positive profiles. These findings support the panels’ prognostic utility, with exploratory evidence for their potential in therapy response prediction. Conclusions: Small ccRCC with thrombus harbors distinct molecular pathological features. The proposed pathology-driven panels, compatible with FFPE tissue, represent pathology-compatible genomic tools that may support modern precision pathology by improving molecular risk stratification and informing exploratory therapeutic biomarker assessment. Full article

Background: Postoperative complications following colorectal surgery remain a persistent clinical challenge. Traditional risk stratification has focused on patient characteristics, while conventional modeling approaches treat procedural factors such as operative duration and surgical approach as independent predictors, potentially obscuring interaction effects. Methods: This study developed a machine learning model stratifying 7908 colorectal surgery patients into four distinct procedural risk categories based on combined surgical approach and operative duration (laparoscopic-short, laparoscopic-long, open-short, open-long), rather than treating these factors as separate variables. A gradient boosting ensemble classifier with RUSBoost resampling was trained on predictor variables including patient demographics, comorbidities, and intraoperative factors. Results: Feature importance analysis revealed that the open-long category emerged as the single most important predictor, substantially exceeding all other variables. Weight loss, body mass index, patient age, and electrolyte abnormalities ranked as the next most important predictors. Stratified complication rates demonstrated a critical interaction: prolonged duration more than doubled complication risk in open procedures (short-duration: 9.99%, long-duration: 20.46%), whereas laparoscopic procedures showed only a modest increase from short-duration (10.45%) to long-duration (14.08%) cases. Logistic regression benchmark analysis confirmed the duration-approach interaction (OR = 1.53, 95% CI: 0.97–2.39), achieving comparable discrimination (c-statistic 0.678 vs. 0.665 for the ensemble model). Decision curve analysis demonstrated logistic regression provided superior clinical utility across most threshold probabilities. Conclusions: The dual analytical framework (i.e., statistical inference for quantifying associations and machine learning for predictive feature ranking) offers complementary insights for clinical application. These findings demonstrate that stratified feature engineering can elucidate complex risk phenotypes that may be obscured when procedural factors are analyzed independently. Full article

Background: Preoperative differentiation between uncomplicated and complicated paediatric appendicitis remains challenging. This study aimed to evaluate the diagnostic performance of routine admission biomarkers and blood cell count-derived inflammatory indices for severity stratification and to determine whether fibrinogen provides additional predictive value beyond commonly used markers. Methods: We conducted a retrospective single-centre study (2018–2025) using electronically recorded clinical data. Patients with suspected appendicitis were identified through appendicitis-related ICD-10 codes and diagnostically validated. The final analytical cohort required complete admission laboratory data, including C-reactive protein (CRP), fibrinogen, and complete blood count parameters. Derived inflammatory indices included the neutrophil-to-lymphocyte ratio (NLR) and the systemic immune-inflammation index (SII). Diagnostic discrimination and multivariable prediction models were evaluated to assess the ability of these markers to distinguish complicated from uncomplicated appendicitis. Results: Of 1518 screened records, 1132 patients met inclusion criteria (620 complicated; 512 uncomplicated). Complicated appendicitis was associated with higher inflammatory markers and longer hospital stay (all p < 0.001). CRP demonstrated the strongest univariable discrimination (area under the curve [AUC] 0.785), while fibrinogen showed lower performance (AUC 0.744). A combined model including CRP, NLR, and SII achieved good discrimination (AUC 0.812), with minimal improvement after adding fibrinogen (AUC 0.813). In multivariable analysis, log-transformed CRP and SII remained independently associated with complicated appendicitis (both p < 0.001). A rule-out probability threshold of 0.303 achieved 90% sensitivity (negative predictive value 0.803), whereas a CRP cut-off ≥92.24 mg/L showed high specificity (0.943) and positive predictive value (0.900). Conclusions: Routine admission biomarkers and inflammatory indices derived from complete blood counts can support severity stratification in paediatric appendicitis. CRP and SII provide meaningful predictive information, whereas fibrinogen contributes little additional discriminatory value beyond CRP-based models. These findings suggest that a small set of routinely available laboratory markers may assist early risk stratification, although external validation is required before clinical implementation. Full article

Background: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by immune dysregulation and systemic inflammation, with the cardiovascular (CV) system representing a major yet frequently under-recognized target. Cardiac involvement spans from subclinical myocardial inflammation to overt pericardial disease, myocarditis, valvular abnormalities, coronary microvascular dysfunction, and accelerated atherosclerosis. Given that CV disease remains a leading cause of morbidity and mortality in SLE, early detection of silent cardiac injury is crucial. Aim: This review aims to provide a comprehensive and clinically oriented overview of CV involvement in SLE, focusing on the role of multimodal cardiac imaging in the detection, characterization, and risk stratification of cardiac abnormalities, as well as its potential implications for clinical management and preventive strategies. Methods: This narrative review is based on a structured, non-systematic search of PubMed (2013–2026), combining the term “systemic lupus erythematosus” with imaging-related keywords including “transthoracic echocardiography,” “cardiac magnetic resonance,” and “cardiac computed tomography.” English-language studies in adult populations were screened and selected according to clinical relevance, methodological robustness, and contribution to understanding SLE-related cardiac involvement. Discussion: Multimodal cardiac imaging plays a central role in the evaluation of SLE-related cardiac disease. Transthoracic echocardiography (TTE) represents the first-line modality for the assessment of ventricular function, pericardial disease, and valvular abnormalities, while deformation imaging enables the detection of subtle myocardial dysfunction. Cardiac magnetic resonance (CMR) provides comprehensive tissue characterization, allowing differentiation between active inflammation and chronic fibrosis. Cardiac computed tomography (cCT) identifies subclinical coronary atherosclerosis and high-risk plaque features, whereas nuclear imaging techniques offer insight into inflammatory activity and microvascular dysfunction. Conclusions: An integrated, imaging-based approach enables early diagnosis, refined CV risk stratification, longitudinal monitoring, and personalized therapeutic strategies. Multimodal imaging thus represents a key pillar of precision medicine in lupus-associated CV disease. Full article

Background/Objectives: Risk stratification in asymptomatic carotid stenosis has traditionally relied on the degree of luminal narrowing; however, plaque vulnerability may better predict cerebrovascular events. Ipsilateral silent brain lesions (SBLs) are considered surrogate markers of stroke risk. This study aimed to identify carotid plaque features on duplex ultrasound (DUS) and computed tomography angiography (CTA), as well as circulating biomarkers, associated with ipsilateral SBL in patients with clinically asymptomatic ≥70% internal carotid artery stenosis. Methods: This prospective observational study with cross-sectional imaging analysis included 316 clinically asymptomatic patients with ≥70% carotid stenosis treated between January 2022 and October 2024. All patients underwent cranial non-contrast CT for SBL detection, DUS plaque characterization (according to the Gray–Weale classification and plaque surface morphology), and CTA analysis, including plaque surface, composition, length, and attenuation values categorized according to Schroeder’s criteria (<50 HU lipid-rich; 51–120 HU fibrous; >120 HU calcified). Demographic, clinical, and laboratory parameters, including inflammatory biomarkers, were recorded. Multivariate logistic regression was performed to identify independent predictors of SBL. Results: SBL were detected in 72 patients (22.8%). On DUS, SBL were significantly associated with Gray–Weale class II plaques, heterogeneous composition, and irregular or ulcerated surfaces (all p < 0.001). On CTA, lipid-rich plaques (<50 HU), ulcerated surfaces, heterogeneous morphology, and lower median plaque density were significantly more frequent in the SBL group (all p < 0.001). In multivariate analysis, independent predictors of SBL were male sex (OR 2.2; 95% CI 1.2–5.7; p = 0.029), Gray–Weale class II plaques (p = 0.002), lipid-rich plaque morphology (OR 21.39; 95% CI 6.86–66.76; p < 0.001), and ulcerated plaque surface on CTA (OR 20.62; 95% CI 7.37–57.68; p < 0.001). Conclusions: Specific ultrasound and CT plaque characteristics were associated with ipsilateral silent brain lesions in patients with asymptomatic ≥70% carotid stenosis. A multiparametric imaging approach may improve risk stratification beyond stenosis severity alone. Full article

Background: Acute kidney injury (AKI) is a serious complication of acute pancreatitis and is frequently associated with the need for continuous renal replacement therapy. Early identification of patients at risk of requiring continuous venovenous hemofiltration (CVVHF) remains challenging because conventional renal markers often reflect delayed kidney injury. Neutrophil gelatinase-associated lipocalin (NGAL) has emerged as a potential biomarker of early renal tubular damage. Methods: This observational study included 219 patients with acute pancreatitis. Plasma and urinary NGAL levels were measured at hospital admission. Clinical characteristics, laboratory parameters, and severity scores were compared between patients who required CVVHF and those who did not. Multivariate logistic regression analysis was performed to identify factors associated with CVVHF requirement, and predictive performance was evaluated using receiver operating characteristic (ROC) curve analysis. Results: During hospitalization, 28 patients (12.8%) required CVVHF and had significantly more severe disease. Both plasma and urinary NGAL levels were higher in patients requiring CVVHF. In multivariate analysis, urinary NGAL remained independently associated with CVVHF requirement. ROC analysis demonstrated moderate predictive performance for urinary NGAL (AUC 0.708). Conclusions: Urinary NGAL was independently associated with the requirement for CVVHF and demonstrated moderate predictive performance. These findings suggest that urinary NGAL may provide kidney-specific information and improve early risk stratification beyond conventional clinical parameters. Full article

Inherited cardiomyopathies represent a major cause of ventricular arrhythmias (VA) and sudden cardiac death (SCD), frequently occurring in the absence of advanced systolic dysfunction. Traditional strategies for the primary prevention of SCD have relied predominantly on left ventricular ejection fraction (LVEF), an approach that fails to capture the substantial biological and clinical heterogeneity of non-ischemic cardiomyopathies. Over the past decade, advances in cardiac genetics and cardiac magnetic resonance imaging have identified specific genotypes associated with a disproportionate arrhythmic risk, which often precedes overt ventricular remodeling. The 2023 European Society of Cardiology (ESC) Guidelines on cardiomyopathies formalize this paradigm shift by integrating etiology, myocardial substrate, and electrical phenotype into contemporary risk stratification. In this narrative review, we focus on cardiomyopathy-associated genotypes consistently linked to high arrhythmic risk—LMNA, truncating variants in FLNC, RBM20, PLN p.Arg14del, and desmosomal genes—and examine their molecular mechanisms, phenotypic trajectories, and arrhythmogenic profiles. We discuss how genotype-specific patterns of myocardial fibrosis, conduction disease, and VA inform implantable cardioverter-defibrillator (ICD) decision-making beyond LVEF-based thresholds. By synthesizing genetic, imaging, and clinical evidence in light of ESC 2023 recommendations, this review highlights the evolving role of genotype-informed strategies in the personalized prevention of SCD and underscores remaining gaps in evidence and risk prediction. Full article

Cardiovascular-kidney-metabolic (CKM) syndrome integrates excess adiposity, metabolic dysfunction, kidney impairment, subclinical cardiovascular diseases, and clinical events along a staged continuum that invites unified prevention and treatment. Ultra-processed foods (UPFs) are a complex, high-prevalence exposure that may influence risk across CKM stages through nutrient profiles, additives, processing-induced compounds, and packaging-related contaminants. This review synthesizes epidemiologic, mechanistic, and translational evidence with attention to exposure definition and analytic rigor. We summarize NOVA-based UPF operationalization across dietary assessment tools, highlighting misclassification of mixed dishes, brand heterogeneity, and energy under-reporting, and we propose further examination of energy-adjusted models, calibration, and harmonized metrics. Observational studies consistently associate higher UPF intake with adiposity, diabetes, chronic kidney disease, cardiovascular events, and mortality, with modest to moderate effect sizes that are heterogeneous across populations. Mechanistic data from metabolomics, lipidomics, proteomics, and the gut microbiome converge on pathways of inflammation, lipid metabolism, oxidative and metabolic stress, and intestinal barrier dysfunction; in selected cohorts, multi-omics modules account for a substantial minority of UPF-outcome associations. We outline quality-control pipelines, batch-effect prevention/correction, and multiple-testing control necessary for reproducible diet-omics. Translationally, targeted lipidomic and proteomic panels show promise for CKM risk stratification and monitoring but require validation, clinical thresholds, and guideline endorsement. Equity and global context, including differences in product mix, food systems, and care capacity, modify population impact. We conclude with a research agenda prioritizing harmonized exposure metrics, error-aware modeling, standardized multi-omics workflows, and adequately powered, stage-specific interventions capable of testing mediation and prognostic utility. Full article

Background/Objectives: Active surveillance (AS) is a viable option for patients with low-risk/low-burden prostate cancer (PCa). Approximately 40–50% of patients will develop disease progression and conversion to active treatment. Therefore, better risk stratification may aid patients and urologists to improve decision making. Herein, the proliferation marker Ki-67 was examined for its prognostic potential in AS patients. Methods: Fifty-nine patients were included. Median follow-up time was 58 months (range, 10–162 months). Tumor-bearing biopsies were evaluated using immunohistochemistry (IHC) staining for Ki-67 and evaluated using digital imaging analysis to determine the percentage of Ki-67-positive PCa cells per biopsy. Results: Thirty-three of 59 patients (55.9%) developed progression. Thirty-one of 59 patients (52.5%) showed Ki-67-positive biopsies (median 0.8%; range, 0–11.9%). The median of Ki-67-positive cells was 1.5% (range, 0–11.9%) in patients with and 0% (range, 0–6.3%) in patients without progression. Comparing patients with Ki-67-positive and Ki-67-negative biopsies showed a worse progression free survival (PFS) in patients with Ki-67-positive biopsies after a period of 15 months, however, without reaching statistical significance (p = 0.071). A 5% threshold for Ki-67 positivity led to a significant difference in PFS. Further exploratory analysis revealed that patients with Ki-67-positive biopsies and aged ≥65 years or with >1 tumor-bearing biopsy show a significantly worse outcome (p = 0.038 and p = 0.037, respectively). Conclusions: Our results suggest that patients with Ki-67-positive biopsies remaining in AS for >1 year have an increased risk for PCa progression and conversion to treatment. Studies to further confirm Ki-67 as a marker for risk stratification, especially with a positivity cut-off of 5%, are warranted in larger cohorts of AS patients. Full article

Cardiac sarcoidosis (CS) is a critical and frequently underdiagnosed phenotype of sarcoidosis, characterized by non-caseating granulomatous infiltration of the myocardium. This review synthesizes current knowledge regarding the pathogenesis, diagnosis, and management of CS. The disease manifests with a heterogeneous clinical spectrum ranging from asymptomatic conduction abnormalities to life-threatening ventricular arrhythmias and heart failure. Diagnosis remains challenging due to the patchy distribution of granulomas, which limits the sensitivity of endomyocardial biopsy. Consequently, a multimodal diagnostic approach is essential, integrating advanced imaging modalities such as cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) and ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG-PET). These tools not only facilitate detection but also enable the differentiation of active inflammation from chronic fibrosis. Histopathological assessment, supported by specific immunophenotyping and electron microscopy, remains the gold standard for confirming diagnosis and excluding mimics like giant cell myocarditis or infectious granulomatous diseases. Management requires a multidisciplinary strategy combining immunosuppressive therapy, primarily corticosteroids and steroid-sparing agents, with guideline-directed cardiac care, including implantable cardioverter-defibrillators for arrhythmia risk stratification. Emerging biomarkers and artificial intelligence-driven imaging analysis promise to further refine risk stratification and therapeutic monitoring, advancing precision medicine in this complex disorder. Full article