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prostatic neoplasms

Welcome to the blog on Artificial Intelligence of
the European Society of Radiology

This blog aims at bringing educational and critical perspectives on AI to readers. It should help imaging professionals to learn and keep up to date with the technologies being developed in this rapidly evolving field.

Most used hashtags:

machine learningdeep learningradiomicsmrix-ray computed tomographyai newsCOVID-19interviewmammographybreast cancerneural networksdiagnostic imagingtomographyMDCTradiographyworkflow

Latest posts

Beyond diagnosis: is there a role for radiomics in prostate cancer management?

Andrea Ponsiglione November 2023

At present, therapeutic and prognostic recommendations for prostate cancer (PCa) predominantly hinge on risk-stratification tools that are built upon clinical parameters. Recent evidence indicates that incorporating imaging can enhance the precision of prognostic models based on clinical factors. However, challenges like subjective interpretation, variability in image analysis, and the absence of reliable quantitative measures need to be overcome to fully

Read More →

AI-aided software for detecting visible clinically significant prostate cancer on mpMRI

Insights into Imaging July 2023

This study seeks to determine if artificial intelligence (AI)-based software can improve radiologists’ performance when detecting clinically significant prostate cancer. Sixteen radiologists from four hospitals participated and were assigned 30 cases, half without AI and half with AI. The authors determined that the AI software improves the performance of radiologists by reducing false positive detection of prostate cancer patients while

Read More →

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

European Radiology Experimental April 2023

This narrative review provides an overview of the current state-of-the-art artificial intelligence (AI) applications for prostate MRI by focusing on open datasets, commercially and publically available AI systems, and challenges. The authors state that large amounts of research are still required in order to successfully utilize AI in the whole prostate pathway. Due to the rapidly growing field, continuous up-to-date

Read More →

Tasks for AI in prostate MRI

European Radiology Experimental March 2023

The authors of this narrative review aimed to introduce quality metrics for emerging artificial intelligence (AI) papers, such as the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) and Field-Weighted Citation Impact (FWCI). Furthermore, the study dives into some of the top AI models for segmentation, detection, and classification, while concluding that prospective studies with multi-center design will need to

Read More →

Single-center versus multi-center biparametric MRI radiomics approach

Insights into Imaging June 2022

In this study, the authors’ aim was to investigate a previously developed radiomics-based biparametric magnetic resonance imaging (bpMRI) approach used for the discrimination of clinically significant peripheral zone prostate cancer (PZ csPCa) through the use of multi-center, multi-vendor (McMv) and single-center, single-vendor (ScSv) datasets. Using these datasets, the authors were able to determine that a single-center trained radiomics-based bpMRI model

Read More →

Multiparametric prostate MRI quality assessment using a PI-QUAL software program

Francesco Giganti May 2022

We know that the technical requirements for the acquisition of multiparametric MRI of the prostate have been clearly outlined in the PI-RADS guidelines, but there is still huge variability in image quality among centres across the world. The Prostate Imaging Quality (PI-QUAL) score and its dedicated scoring sheet represent the first attempt to standardise image quality, as they take into

Read More →

Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer

ESR December 2019

The purpose of this study was to create a radiomics approach based on multiparametric MRI (mpMRI) features that were extracted from an auto-fixed volume of interest (VOI) that quantifies the phenotype of clinically significant peripheral zone prostate cancer (pCA). The study included 206 patients and the authors concluded that the developed radiomics model that extracts mpMRI features with an auto-fixed

Read More →

Beyond diagnosis: is there a role for radiomics in prostate cancer management?

Andrea Ponsiglione November 2023

At present, therapeutic and prognostic recommendations for prostate cancer (PCa) predominantly hinge on risk-stratification tools that are built upon clinical parameters. Recent evidence indicates that incorporating imaging can enhance the precision of prognostic models based on clinical factors. However, challenges like subjective interpretation, variability in image analysis, and the absence of reliable quantitative measures need to be overcome to fully

Read More →

AI-aided software for detecting visible clinically significant prostate cancer on mpMRI

Insights into Imaging July 2023

This study seeks to determine if artificial intelligence (AI)-based software can improve radiologists’ performance when detecting clinically significant prostate cancer. Sixteen radiologists from four hospitals participated and were assigned 30 cases, half without AI and half with AI. The authors determined that the AI software improves the performance of radiologists by reducing false positive detection of prostate cancer patients while

Read More →

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

European Radiology Experimental April 2023

This narrative review provides an overview of the current state-of-the-art artificial intelligence (AI) applications for prostate MRI by focusing on open datasets, commercially and publically available AI systems, and challenges. The authors state that large amounts of research are still required in order to successfully utilize AI in the whole prostate pathway. Due to the rapidly growing field, continuous up-to-date

Read More →

Tasks for AI in prostate MRI

European Radiology Experimental March 2023

The authors of this narrative review aimed to introduce quality metrics for emerging artificial intelligence (AI) papers, such as the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) and Field-Weighted Citation Impact (FWCI). Furthermore, the study dives into some of the top AI models for segmentation, detection, and classification, while concluding that prospective studies with multi-center design will need to

Read More →

Single-center versus multi-center biparametric MRI radiomics approach

Insights into Imaging June 2022

In this study, the authors’ aim was to investigate a previously developed radiomics-based biparametric magnetic resonance imaging (bpMRI) approach used for the discrimination of clinically significant peripheral zone prostate cancer (PZ csPCa) through the use of multi-center, multi-vendor (McMv) and single-center, single-vendor (ScSv) datasets. Using these datasets, the authors were able to determine that a single-center trained radiomics-based bpMRI model

Read More →

Multiparametric prostate MRI quality assessment using a PI-QUAL software program

Francesco Giganti May 2022

We know that the technical requirements for the acquisition of multiparametric MRI of the prostate have been clearly outlined in the PI-RADS guidelines, but there is still huge variability in image quality among centres across the world. The Prostate Imaging Quality (PI-QUAL) score and its dedicated scoring sheet represent the first attempt to standardise image quality, as they take into

Read More →

Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer

ESR December 2019

The purpose of this study was to create a radiomics approach based on multiparametric MRI (mpMRI) features that were extracted from an auto-fixed volume of interest (VOI) that quantifies the phenotype of clinically significant peripheral zone prostate cancer (pCA). The study included 206 patients and the authors concluded that the developed radiomics model that extracts mpMRI features with an auto-fixed

Read More →

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①

Membership

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  • Reduced registration fees for ECR 1
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  • Exclusive option to participate in the European Diploma. 3
  • Free electronic access to the journal European Radiology 4
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  • Updates on offers & events through our newsletters
  • Exclusive access to the ESR feed in Juisci

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for radiologists, radiology residents or professionals of allied sciences engaged in practice, teaching or research residing outside Europe as well as individual qualified professionals with an interest in radiology and medical imaging who do not fulfil individual or all requirements for any other ESR membership category & former full members who have retired from all clinical practice
  • Reduced registration fees for ECR 1
  • Free electronic access to the journal European Radiology
  • Content e-mails for all 3 ESR journals 4
  • Updates on offers & events through our newsletters
  • Exclusive access to the ESR feed in Juisci

€ 0

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  • Updates on offers & events through our newsletters

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Footnotes:

01

Reduced registration fees for ECR 2024:
Provided that ESR 2023 membership is activated and approved by August 31, 2023.

Reduced registration fees for ECR 2025:
Provided that ESR 2024 membership is activated and approved by August 31, 2024.

02
Not all activities included
03
Examination based on the ESR European Training Curriculum (radiologists or radiology residents).
04
European Radiology, Insights into Imaging, European Radiology Experimental.