Your browser doesn't support javascript.
loading
Advanced imaging and Crohn's disease: An overview of clinical application and the added value of artificial intelligence.
Grassi, Giovanni; Laino, Maria Elena; Fantini, Massimo Claudio; Argiolas, Giovanni Maria; Cherchi, Maria Valeria; Nicola, Refky; Gerosa, Clara; Cerrone, Giulia; Mannelli, Lorenzo; Balestrieri, Antonella; Suri, Jasjit S; Carriero, Alessandro; Saba, Luca.
Afiliação
  • Grassi G; Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - Polo di Monserrato, s.s. 554 Monserrato (Cagliari) 09045, Italy.
  • Laino ME; Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - Polo di Monserrato, s.s. 554 Monserrato (Cagliari) 09045, Italy; Artificial Intelligence Center, IRCSS Humanitas Research Hospital, via Manzoni 56, Rozzano, Milano, Italy. Electronic address: mariaelena.laino@gmail.co
  • Fantini MC; Department of Gastroenterology Surgery, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - Polo di Monserrato s.s. 554 Monserrato (Cagliari) 09045, Italy.
  • Argiolas GM; Department of Radiology, Azienda Ospedaliera Brotzu, Cagliari.
  • Cherchi MV; Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - Polo di Monserrato, s.s. 554 Monserrato (Cagliari) 09045, Italy.
  • Nicola R; Roswell Park Cancer Institute, Jacobs School of Medicine and Biomedical Science, Buffalo, NY, USA.
  • Gerosa C; Department of Pathology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - University Hospital San Giovanni di Dio, (Cagliari) 09045, Italy.
  • Cerrone G; Department of Pathology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - University Hospital San Giovanni di Dio, (Cagliari) 09045, Italy.
  • Mannelli L; Department of Radiology, IRCCS SDN, Italy.
  • Balestrieri A; Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - Polo di Monserrato, s.s. 554 Monserrato (Cagliari) 09045, Italy.
  • Suri JS; Diagnostic and Monitoring Division, AtheroPoint™, Roseville, CA, USA; Knowledge Engineering Center, Global Biomedical Technologies, Inc., Roseville, CA, USA; Department of Electrical and Computer Engineering, Idaho State University, Pocatello, ID, USA.
  • Carriero A; Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy.
  • Saba L; Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.), di Cagliari - Polo di Monserrato, s.s. 554 Monserrato (Cagliari) 09045, Italy.
Eur J Radiol ; 157: 110551, 2022 Dec.
Article em En | MEDLINE | ID: mdl-36279627
ABSTRACT

PURPOSE:

The purpose of this narrative review is to describe the clinical applications of advanced computed tomography (CT) and magnetic resonance (MRI) techniques in patients affected by Crohn's disease (CD), giving insights about the added value of artificial intelligence (AI) in this field.

METHODS:

We performed a literature search comparing standardized and advanced imaging techniques for CD diagnosis. Cross-sectional imaging is essential for the identification of lesions, the assessment of active or relapsing disease and the evaluation of complications.

RESULTS:

The studies reviewed show that new advanced imaging techniques and new MRI sequences could be integrated into standard protocols, to achieve a reliable quantification of CD activity, improve the lesions' characterization and the evaluation of therapy response. These promising tools are dual-energy CT (DECT) post-processing techniques, diffusion-weighted MRI (DWI-MRI), dynamic contrast-enhanced MRI (DCE-MRI), Magnetization Transfer MRI (MT-MRI) and CINE-MRI. Furthermore, AI solutions show a potential when applied to radiological techniques in these patients. Machine learning (ML) algorithms and radiomic features prove to be useful in improving the diagnostic accuracy of clinicians and in attempting a personalized medicine approach, stratifying patients by predicting their prognosis.

CONCLUSIONS:

Advanced imaging is crucial in the diagnosis, lesions' characterisation and in the estimation of the abdominal involvement in CD. New AI developments are promising tools that could support doctors in the management of CD affected patients.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Crohn Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doença de Crohn Idioma: En Ano de publicação: 2022 Tipo de documento: Article