ABSTRACT
Artificial intelligence (AI) has made considerable progress within the last decade and is the subject of contemporary literature. This trend is driven by improved computational abilities and increasing amounts of complex data that allow for new approaches in analysis and interpretation. Renal cell carcinoma (RCC) has a rising incidence since most tumors are now detected at an earlier stage due to improved imaging. This creates considerable challenges as approximately 10%-17% of kidney tumors are designated as benign in histopathological evaluation; however, certain co-morbid populations (the obese and elderly) have an increased peri-interventional risk. AI offers an alternative solution by helping to optimize precision and guidance for diagnostic and therapeutic decisions. The narrative review introduced basic principles and provide a comprehensive overview of current AI techniques for RCC. Currently, AI applications can be found in any aspect of RCC management including diagnostics, perioperative care, pathology, and follow-up. Most commonly applied models include neural networks, random forest, support vector machines, and regression. However, for implementation in daily practice, health care providers need to develop a basic understanding and establish interdisciplinary collaborations in order to standardize datasets, define meaningful endpoints, and unify interpretation.
ABSTRACT
PURPOSE OF REVIEW: To present an overview of the current evidence-based studies covering diagnostic and management of SRM. RECENT FINDINGS: Renal cell carcinoma (RCC) represents 3% of the cancers. Nowadays, partial nephrectomy (PN) represents gold standard treatment. New nephron-sparing approaches such as active surveillance and ablative therapies have been increasingly used as an alternative to surgical intervention. Due to novel comprehension of RCC and widespread use of imaging techniques, diagnosis at early stage in elderly patients has increased. Treatment decision-making should be based on patient and tumour characteristics. With expanding treatment options, the management of SRMs has become a debate and should be adjusted to patient and tumour characteristics. In a shared decision manner, both active surveillance with possible delayed intervention and focal therapy should be discussed with the patient as an alternative to partial nephrectomy.
Subject(s)
Carcinoma, Renal Cell , Kidney Neoplasms , Aged , Carcinoma, Renal Cell/diagnosis , Carcinoma, Renal Cell/surgery , Female , Humans , Kidney Neoplasms/diagnosis , Kidney Neoplasms/pathology , Kidney Neoplasms/therapy , Male , Nephrectomy/methods , NephronsABSTRACT
Oligometastatic prostate cancer (OMPC) is an intermediate state between localised disease and widespread metastases that includes a spectrum of disease biology and clinical behaviours. This narrative review will cover the current OMPC scenario. We conducted comprehensive English language literature research for original and review articles using the Medline database and grey literature through December 2021. OMPC is a unique clinical state with inherently more indolent tumour biology susceptible to multidisciplinary treatment (MDT). With the development of new imaging techniques, patients with OMPC are likely to be identified at an earlier stage, and the paradigm for treatment is shifting towards a more aggressive approach to treating potentially curable patients. Multimodal management is necessary to improve patient outcomes due to the combination of available therapies, such as local therapy of primary tumour, metastasis directed therapy or systemic therapy, to reduce tumour load and prevent further disease progression. Additional prospective data are needed to select patients most likely to benefit from a given therapeutic approach.
