Indurative Edema of the Prepuce Mimicing Phimosis, an Atypical Manifestation of Primary Syphilis

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Comparison of 10-year overall survival between patients with G1 and G2 grade Ta bladder tumors

To compare long-term overall survival (OS) in patients with G1 and G2 grade Ta bladder cancer after transurethral resection of bladder tumors (TURBTs). Secondary aim was to investigate clinical and pathologic prognostic factors for OS of Ta patients, except G3/high grade (HG). A total of 243 patients, retrospectively selected, with Ta nonmuscle invasive bladder cancer (NMIBC) underwent TURBT between January 2006 and December 2008 (median follow-up 109 months). Inclusion criteria were: Ta at first manifestation, G1 or G2 grade with no associated carcinoma in situ (CIS). Seventy-nine patients were excluded due to concomitant CIS (1), G3/HG tumors (47), and lost to follow-up (31). Ethical approval was obtained from the Ethical Committee of the Mures County Hospital. Statistical analysis was performed using STATA 11.0. Following inclusion criteria, 164 patients with primary G1 or G2 Ta tumors, were enrolled. Recurrence was observed in 26 (15.8%) and progression in 5 (3%) patients. Ten-year survival in G1 patients was 67.8% (CI 54.3-78.1) and in G2 patients 59% (CI 49-67.3) (P=.31). Univariable and multivariable logistic regression analysis underlined that advanced age at diagnosis (hazard ratio [HR] 1.10) and no Bacillus Calmette-Guerin (BCG) treatment (HR 0.24 and 0.29) were independent predictors for death at 10 years after diagnosis. Long-term analysis confirms that patients with well differentiated (G1) and moderately well differentiated (G2) Ta tumors have similar OS. A longer OS was even reported in those who underwent BCG adjuvant therapy

Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management-Current Trends and Future Perspectives

Artificial intelligence (AI) is the field of computer science that aims to build smart devices performing tasks that currently require human intelligence. Through machine learning (ML), the deep learning (DL) model is teaching computers to learn by example, something that human beings are doing naturally. AI is revolutionizing healthcare. Digital pathology is becoming highly assisted by AI to help researchers in analyzing larger data sets and providing faster and more accurate diagnoses of prostate cancer lesions. When applied to diagnostic imaging, AI has shown excellent accuracy in the detection of prostate lesions as well as in the prediction of patient outcomes in terms of survival and treatment response. The enormous quantity of data coming from the prostate tumor genome requires fast, reliable and accurate computing power provided by machine learning algorithms. Radiotherapy is an essential part of the treatment of prostate cancer and it is often difficult to predict its toxicity for the patients. Artificial intelligence could have a future potential role in predicting how a patient will react to the therapy side effects. These technologies could provide doctors with better insights on how to plan radiotherapy treatment. The extension of the capabilities of surgical robots for more autonomous tasks will allow them to use information from the surgical field, recognize issues and implement the proper actions without the need for human intervention

Molecular Imaging Diagnosis of Renal Cancer Using 99mTc-Sestamibi SPECT/CT and Girentuximab PET-CT-Current Evidence and Future Development of Novel Techniques

: Novel molecular imaging opportunities to preoperatively diagnose renal cell carcinoma is under development and will add more value in limiting the postoperative renal function loss and morbidity. We aimed to comprehensively review the research on single photon emission computed tomography/computed tomography (SPECT/CT) and positron emission tomography computed tomography (PET-CT) molecular imaging and to enhance the urologists' and radiologists' knowledge of the current research pattern. We identified an increase in prospective and also retrospective studies that researched to distinguish between benign and malignant lesions and between different clear cell renal cell carcinoma subtypes, with small numbers of patients studied, nonetheless with excellent results on specificity, sensitivity and accuracy, especially for 99mTc-sestamibi SPECT/CT that delivers quick results compared to a long acquisition time for girentuximab PET-CT, which instead gives better image quality. Nuclear medicine has helped clinicians in evaluating primary and secondary lesions, and has lately returned with new and exciting insights with novel radiotracers to reinforce its diagnostic potential in renal carcinoma. To further limit the renal function loss and post-surgery morbidity, future research is mandatory to validate the results and to clinically implement the diagnostic techniques in the context of precision medicine

Radiomics in prostate cancer: an up-to-date review

: Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male population. The diagnosis, the identification of aggressive disease, and the post-treatment follow-up needs a more comprehensive and holistic approach. Radiomics is the extraction and interpretation of images phenotypes in a quantitative manner. Radiomics may give an advantage through advancements in imaging modalities and through the potential power of artificial intelligence techniques by translating those features into clinical outcome prediction. This article gives an overview on the current evidence of methodology and reviews the available literature on radiomics in PCa patients, highlighting its potential for personalized treatment and future applications

Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature review

: Radiomics and artificial intelligence (AI) may increase the differentiation of benign from malignant kidney lesions, differentiation of angiomyolipoma (AML) from renal cell carcinoma (RCC), differentiation of oncocytoma from RCC, differentiation of different subtypes of RCC, to predict Fuhrman grade, to predict gene mutation through molecular biomarkers and to predict treatment response in metastatic RCC undergoing immunotherapy. Neural networks analyze imaging data. Statistical, geometrical, textural features derived are giving quantitative data of contour, internal heterogeneity and gray zone features of lesions. A comprehensive literature review was performed, until July 2022. Studies investigating the diagnostic value of radiomics in differentiation of renal lesions, grade prediction, gene alterations, molecular biomarkers and ongoing clinical trials have been analyzed. The application of AI and radiomics could lead to improved sensitivity, specificity, accuracy in detecting and differentiating between renal lesions. Standardization of scanner protocols will improve preoperative differentiation between benign, low-risk cancers and clinically significant renal cancers and holds the premises to enhance the diagnostic ability of imaging tools to characterize renal lesions

Three vs. Four Cycles of Neoadjuvant Chemotherapy for Localized Muscle Invasive Bladder Cancer Undergoing Radical Cystectomy: A Retrospective Multi-Institutional Analysis

Three or four cycles of cisplatin-based chemotherapy is the standard neoadjuvant treatment prior to cystectomy in patients with muscle-invasive bladder cancer. Although NCCN guidelines recommend 4 cycles of cisplatin-gemcitabine, three cycles are also commonly administered in clinical practice. In this multicenter retrospective study, we assessed a large and homogenous cohort of patients with urothelial bladder cancer (UBC) treated with three or four cycles of neoadjuvant cisplatin-gemcitabine followed by radical cystectomy, in order to explore whether three vs. four cycles were associated with different outcomes

Neutrophil percentage-to-albumin ratio predicts mortality in bladder cancer patients treated with neoadjuvant chemotherapy followed by radical cystectomy

To investigate the prognostic role of neutrophil percentage-to-albumin ratio (NPAR) in muscle-invasive bladder cancer (MIBC) patients treated with neoadjuvant chemotherapy (NAC) and radical cystectomy (RC)

Psychological Distress in Patients Treated for Renal Cell Carcinoma: A Systematic Literature Review

(1) Background: The incidence of psychological distress and its impact on renal cell carcinoma (RCC) patients is unclear. Our aim was to analyze the literature regarding the prevalence of psychological distress and its impact on patients with non-metastatic or metastatic RCC; (2) Methods: A systematic search of five databases was performed. Studies were considered eligible if they included patients with RCC, had a prospective or retrospective design, and assessed anxiety, depression, or psychological distress at any time during treatment or follow-up. Exclusion criteria: no treatment for RCC, or not providing data for RCC patients; (3) Results: A total of 15 studies were included. Reported psychological distress was up to 77% and the prevalence of depressive and anxiety symptoms were up to 77.6% and 68.3% in patients with non-metastatic RCC. There was no association of depression with overall survival (OS) in patients with non-metastatic RCC treated by radical nephrectomy; on the contrary, in patients with metastatic disease, depression had an impact on OS. Limitations are related to the quality of the included studies; (4) Conclusions: Patients with RCC reported a high level of psychological distress like other cancer patients. It seems that for patients with localized disease, psychological distress does not impact OS, while it does in those with metastatic disease