Computer-Aided Detection for Pancreatic Cancer Diagnosis: Radiological Challenges and Future Directions

Overview

Journal J Clin Med

Specialty General Medicine

Date 2023 Jul 14

PMID 37445243

Authors

Mark Ramaekers

Christiaan G A Viviers

Boris V Janssen

Terese A E Hellstrom

Lotte Ewals

Kasper van der Wulp

Joost Nederend

Igor Jacobs

Jon R Pluyter

Dimitrios Mavroeidis

Fons van der Sommen

Marc G Besselink

Misha D P Luyer

Affiliations

Soon will be listed here.

Abstract

Radiological imaging plays a crucial role in the detection and treatment of pancreatic ductal adenocarcinoma (PDAC). However, there are several challenges associated with the use of these techniques in daily clinical practice. Determination of the presence or absence of cancer using radiological imaging is difficult and requires specific expertise, especially after neoadjuvant therapy. Early detection and characterization of tumors would potentially increase the number of patients who are eligible for curative treatment. Over the last decades, artificial intelligence (AI)-based computer-aided detection (CAD) has rapidly evolved as a means for improving the radiological detection of cancer and the assessment of the extent of disease. Although the results of AI applications seem promising, widespread adoption in clinical practice has not taken place. This narrative review provides an overview of current radiological CAD systems in pancreatic cancer, highlights challenges that are pertinent to clinical practice, and discusses potential solutions for these challenges.

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