kidney tumors
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Background: Genitourinary tract tumors in children are less common than in adults. Most of these tumors have different genetic backgrounds, clinical presentation, and oncologic behavior than their adult counterpart. As a result of low prevalence in children, some of the treatment approaches and recommendations are based on treatment experience in adult patients. However, thanks to scientific and technological development, survival rates have risen considerably. Objective: This paper presents a review of the principal features of the tumors involving the genitourinary tract in children and an update in genetic background, diagnosis, and treatment. Methods: A narrative review was performed on published literature about genitourinary tract tumors in pediatric patients. Papers presented in English and Spanish literature were reviewed. PubMed, Science Direct, and SciELO databases were used to collect information and present this article. Results: Kidney tumors are the most common type of genitourinary tumors in children. Among those, Wilms tumor represents the majority of cases and shows the successful work of clinical trial groups studying this tumor type. Other tumors involving the genitourinary tract in children include Rhabdomyosarcoma, Transitional cell carcinoma, Testicular, and Adrenal tumors. Conclusion: Genitourinary tract tumors in children represent significant morbidity and economic burden, so awareness in early diagnosis represents improvement in treatment, clinical and oncological outcomes.

Purpose: Clinicians rely on imaging features to calculate complexity of renal masses based on validated scoring systems. These scoring methods are labor-intensive and are subjected to interobserver variability. Artificial intelligence has been increasingly utilized by the medical community to solve such issues. However, developing reliable algorithms is usually time-consuming and costly. We created an international community-driven competition (KiTS19) to develop and identify the best system for automatic segmentation of kidneys and kidney tumors in contrast CT and report the results.Methods: A training and test set of CT scans that was manually annotated by trained individuals were generated from consecutive patients undergoing renal surgery for whom demographic, clinical and outcome data were available. The KiTS19 Challenge was a machine learning competition hosted on grand-challenge.org in conjunction with an international conference. Teams were given 3 months to develop their algorithm using a full-annotated training set of images and an unannotated test set was released for 2 weeks from which average Sørensen-Dice coefficient between kidney and tumor regions were calculated across all 90 test cases.Results: There were 100 valid submissions that were based on deep neural networks but there were differences in pre-processing strategies, architectural details, and training procedures. The winning team scored a 0.974 kidney Dice and a 0.851 tumor Dice resulting in 0.912 composite score. Automatic segmentation of the kidney by the participating teams performed comparably to expert manual segmentation but was less reliable when segmenting the tumor.Conclusion: Rapid advancement in automated semantic segmentation of kidney lesions is possible with relatively high accuracy when the data is released publicly, and participation is incentivized. We hope that our findings will encourage further research that would enable the potential of adopting AI into the medical field.

Survival of unilateral Wilms tumors (WTs) is exceeding 90%, whereas bilateral WTs have an inferior outcome. We evaluated all Dutch patients with bilateral kidney tumors, treated in the first five years of national centralization and reviewed relevant literature. We identified 24 patients in our center (2015–2020), 23 patients had WT/nephroblastomatosis and one renal cell carcinoma. Patients were treated according to SIOP-RTSG protocols. Chemotherapy response was observed in 26/34 WTs. Nephroblastomatosis lesions were stable (n = 7) or showed response (n = 18). Nephron-sparing surgery was performed in 11/22 patients undergoing surgery (n = 2 kidneys positive margins). Local stage in 20 patients with ≥1 WT revealed stage I (n = 7), II (n = 4) and III (n = 9). Histology was intermediate risk in 15 patients and high risk in 5. Three patients developed a WT in a treated nephroblastomatosis lesion. Two of 24 patients died following toxicity and renal failure, i.e., respectively dialysis-related invasive fungal infection and septic shock. Genetic predisposition was confirmed in 18/24 patients. Our literature review revealed that knowledge is scarce on bilateral renal tumor patients with metastases and that radiotherapy seems important for local stage III patients. Bilateral renal tumors are a therapeutic challenge. We describe management and outcome in a national expert center and summarized available literature, serving as baseline for further improvement of care.

Relevance: Computed tomography allows detecting small tumors. However, surgical tactics cannot always be determined in advance. The purpose of the research was to assess the capacity of computed tomography in the preoperative determination of surgery volume in kidney tumors. Results: 548 patients were treated for kidney neoplasms. They were divided into three groups by computed tomography based on the R.E.N.A.L. scale: with a high risk of complications – 265 patients (48.4%), medium risk – 107 (19.5%), and low risk – 176 (32.1%). All operations were performed in the planned volume depending on the identified risk group for complications and resectability of kidney neoplasms; no changes to the plan of surgical interventions were made. The preoperative assessment of the kidney angioarchitectonics and the tumor relation to the pyelocaliceal system and the organ parenchyma helped determine the surgery volume and the possibility for organ-reserving interventions in 283 patients and radical nephrectomy in 265 patients. Conclusion: Such a highly informative method as computed tomography made allows early detection of small-sized kidney tumors to provide an opportunity for organ-preserving surgery and improved treatment outcome

Knowing the precise location of analytes in the tissue has the potential to provide information about the organs’ function and predict its behavior. It is especially powerful when used in diagnosis and prognosis prediction of pathologies, such as cancer. Spatial proteomics, in particular mass spectrometry imaging, together with machine learning approaches, has been proven to be a very helpful tool in answering some histopathology conundrums. To gain accurate information about the tissue, there is a need to build robust classification models. We have investigated the impact of histological annotation on the classification accuracy of different tumor tissues. Intrinsic tissue heterogeneity directly impacts the efficacy of the annotations, having a more pronounced effect on more heterogeneous tissues, as pancreatic ductal adenocarcinoma, where the impact is over 20% in accuracy. On the other hand, in more homogeneous samples, such as kidney tumors, histological annotations have a slenderer impact on the classification accuracy.

IntroductionA kidney tumor is among the 10 most common cancers. Among kidney tumors, renal cell carcinoma (RCC) is one of the most common types with an alarming increasing incidence rate. Although the disruption of microbiota is an established factor in the progression of intestinal cancers, its role in other types of cancers has been under-studied.Material and methodsIn this study, the microbiome disruption and the involvement of SNZ (SCHNARCHZAPFEN) and SA (Stromalin) genes in the development of kidney cancer have been focused on using a combination of genetic and bioinformatic analysis. The microbiomes of kidney tumor patients were analyzed using various genetic and bioinformatic variations. Genetic and bioinformatic analyses were performed to identify operational taxonomic units (OTUs), SNZ, SA, and annotate species were determined using 41 samples from a population of kidney tumors.ResultsThe whole samples from the kidney tumor of patients were screened by PCR amplification and a total of 1317 OTUs were identified. Among them, 379 were common among the two populations, 766 were unique to the SA gene, and 172 to SNZ. SA was more abundant in Gammaproteobacteria and bacilli, while SNZ had a higher abundance in bacteroidia and actinobacteria. Correlation analysis was performed to find out the bacteria that were differentially expressed among the population samples.ConclusionsTo sum up, our study reveals that SA and SNZ are differentially expressed in the microbiome of the kidney tumor that is associated with the development of kidney tumors such as renal cell carcinoma in human populations.

Resection of a part of the middle part of the inferior vena cava, located between the renal and hepatic veins, has to be performed when tumors from nearby organs and tissues grow into it. So, for example, kidney tumors in 13-15% of cases grow into the wall of the inferior vena cava (SP Fedorov, Israel, etc.).

Relevance: Computed tomography allows detecting small tumors. However, surgical tactics cannot always be determined in advance. The purpose of the research was to assess the capacity of computed tomography in preoperative determination of surgery volume in kidney tumors. Results: 548 patients were treated for kidney neoplasms. They were divided into three groups by computed tomography based on the R.E.N.A.L. scale: with a high risk of complications – 265 patients (48.4%), medium risk – 107 (19.5%), and low risk – 176 (32.1%). All operations were performed in the planned volume depending on the identified risk group for complications and resectability of kidney neoplasms; no changes to the plan of surgical interventions were made. The preoperative assessment of the kidney angioarchitectonics and the tumor relation to the pyelocaliceal system and the organ parenchyma helped determine the surgery volume and the possibility for organ-reserving interventions in 283 patients and radical nephrectomy in 265 patients. Conclusion: Such a highly informative method as computed tomography made allows early detection of small-sized kidney tumors to provide an opportunity for organ-preserving surgery and improved treatment outcome