[HTML][HTML] Imaging characterization of renal masses

C Nicolau, N Antunes, B Paño, C Sebastia - Medicina, 2021 - mdpi.com
The detection of a renal mass is a relatively frequent occurrence in the daily practice of any
Radiology Department. The diagnostic approaches depend on whether the lesion is cystic …

Active surveillance of renal masses: the role of radiology

N Schieda, S Krishna, I Pedrosa, SD Kaffenberger… - Radiology, 2022 - pubs.rsna.org
Active surveillance of renal masses, which includes serial imaging with the possibility of
delayed treatment, has emerged as a viable alternative to immediate therapeutic …

[HTML][HTML] Deep learning and radiomic feature-based blending ensemble classifier for malignancy risk prediction in cystic renal lesions

QH He, JJ Feng, FJ Lv, Q Jiang, MZ Xiao - Insights into Imaging, 2023 - Springer
Background The rising prevalence of cystic renal lesions (CRLs) detected by computed
tomography necessitates better identification of the malignant cystic renal neoplasms since …

Malignancy risk stratification of cystic renal lesions based on a contrast-enhanced CT-based machine learning model and a clinical decision algorithm

J Dana, TL Lefebvre, P Savadjiev, S Bodard… - European …, 2022 - Springer
Objective To distinguish benign from malignant cystic renal lesions (CRL) using a contrast-
enhanced CT-based radiomics model and a clinical decision algorithm. Methods This dual …

[HTML][HTML] A framework to distinguish healthy/cancer renal CT images using the fused deep features

V Rajinikanth, PMDR Vincent, K Srinivasan… - Frontiers in Public …, 2023 - frontiersin.org
Introduction Cancer happening rates in humankind are gradually rising due to a variety of
reasons, and sensible detection and management are essential to decrease the disease …

Differentiating benign from malignant cystic renal masses: a feasibility study of computed tomography texture-based machine learning algorithms

N Miskin, L Qin, SG Silverman… - Journal of computer …, 2023 - journals.lww.com
Objective The Bosniak classification attempts to predict the likelihood of renal cell carcinoma
(RCC) among cystic renal masses but is subject to interobserver variability and often …

A brief review of artificial intelligence in genitourinary oncological imaging

EC Yilmaz, MJ Belue, B Turkbey… - Canadian …, 2023 - journals.sagepub.com
Genitourinary (GU) system is among the most commonly involved malignancy sites in the
human body. Imaging plays a crucial role not only in diagnosis of cancer but also in disease …

The incidental renal mass-update on characterization and management

JJ Hines, K Eacobacci, R Goyal - Radiologic Clinics, 2021 - radiologic.theclinics.com
Incidental findings on abdominal cross-sectional imaging examinations are frequently
encountered in solid organs, bowel, blood vessels, bone, and the abdominal and pelvic …

[HTML][HTML] Prediction of premature ventricular complex origins using artificial intelligence–enabled algorithms

T Nakamura, Y Nagata, G Nitta, S Okata… - … Digital Health Journal, 2021 - Elsevier
Background Catheter ablation is a standard therapy for frequent premature ventricular
complex (PVCs). Predicting their origin from a 12-lead electrocardiogram (ECG) is crucial …

Parapelvic cysts: an imaging marker of kidney disease potentially leading to the diagnosis of treatable rare genetic disorders? A narrative review of the literature

I Capuano, P Buonanno, E Riccio, F Crocetto… - Journal of …, 2022 - Springer
Simple renal cysts are a common finding during abdominal imaging assessment. The
incidence increases with age and it is higher in male gender. Parapelvic cysts are a subset …