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

M Ferro, O de Cobelli, G Musi… - Therapeutic …, 2022 - journals.sagepub.com
Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male
population. The diagnosis, the identification of aggressive disease, and the post-treatment …

Artificial intelligence for prostate MRI: open datasets, available applications, and grand challenges

MRS Sunoqrot, A Saha, M Hosseinzadeh… - European radiology …, 2022 - Springer
Artificial intelligence (AI) for prostate magnetic resonance imaging (MRI) is starting to play a
clinical role for prostate cancer (PCa) patients. AI-assisted reading is feasible, allowing …

ESUR/ESUI consensus statements on multi-parametric MRI for the detection of clinically significant prostate cancer: quality requirements for image acquisition …

M de Rooij, B Israël, M Tummers, HU Ahmed… - European …, 2020 - Springer
Objectives This study aims to define consensus-based criteria for acquiring and reporting
prostate MRI and establishing prerequisites for image quality. Methods A total of 44 leading …

Prostate MRI quality: clinical impact of the PI-QUAL score in prostate cancer diagnostic work-up

E Karanasios, I Caglic, JP Zawaideh… - The British Journal of …, 2022 - academic.oup.com
Objective: To assess the reproducibility and impact of prostate imaging quality (PI-QUAL)
scores in a clinical cohort undergoing prostate multiparametric MRI. Methods: PI-QUAL …

Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a …

N Sushentsev, N Moreira Da Silva, M Yeung… - Insights into …, 2022 - Springer
Objectives We systematically reviewed the current literature evaluating the ability of fully-
automated deep learning (DL) and semi-automated traditional machine learning (TML) MRI …

Factors influencing variability in the performance of multiparametric magnetic resonance imaging in detecting clinically significant prostate cancer: a systematic …

A Stabile, F Giganti, V Kasivisvanathan… - European urology …, 2020 - Elsevier
Context There is a lack of comprehensive data regarding the factors that influence the
diagnostic accuracy of multiparametric magnetic resonance imaging (mpMRI) to detect and …

Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis

R Cuocolo, MB Cipullo, A Stanzione, V Romeo… - European …, 2020 - Springer
Objectives The aim of this study was to systematically review the literature and perform a
meta-analysis of machine learning (ML) diagnostic accuracy studies focused on clinically …

Multicenter evaluation of multiparametric MRI clear cell likelihood scores in solid indeterminate small renal masses

N Schieda, MS Davenport, SG Silverman, B Bagga… - Radiology, 2022 - pubs.rsna.org
Background Solid small renal masses (SRMs)(≤ 4 cm) represent benign and malignant
tumors. Among SRMs, clear cell renal cell carcinoma (ccRCC) is frequently aggressive …

Combination of peri-tumoral and intra-tumoral radiomic features on bi-parametric MRI accurately stratifies prostate cancer risk: a multi-site study

A Algohary, R Shiradkar, S Pahwa, A Purysko, S Verma… - Cancers, 2020 - mdpi.com
Background: Prostate cancer (PCa) influences its surrounding habitat, which tends to
manifest as different phenotypic appearances on magnetic resonance imaging (MRI). This …

Optimising the number of cores for magnetic resonance imaging‐guided targeted and systematic transperineal prostate biopsy

NL Hansen, T Barrett, T Lloyd, A Warren… - BJU …, 2020 - Wiley Online Library
Objectives To assess cancer detection rates of different target‐dependent transperineal
magnetic resonance (MR)/ultrasonography (US) fusion‐guided biopsy templates with …