Radiomics in Oncological PET Imaging: A Systematic Review-Part 2, Infradiaphragmatic Cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers

Overview

Journal Diagnostics (Basel)

Specialty Radiology

Date 2022 Jun 24

PMID 35741139

Authors

David Morland

Elizabeth Katherine Anna Triumbari

Luca Boldrini

Roberto Gatta

Daniele Pizzuto

Salvatore Annunziata

Affiliations

Soon will be listed here.

Abstract

The objective of this review was to summarize published radiomics studies dealing with infradiaphragmatic cancers, blood malignancies, melanoma, and musculoskeletal cancers, and assess their quality. PubMed database was searched from January 1990 to February 2022 for articles performing radiomics on PET imaging of at least 1 specified tumor type. Exclusion criteria includd: non-oncological studies; supradiaphragmatic tumors; reviews, comments, cases reports; phantom or animal studies; technical articles without a clinically oriented question; studies including <30 patients in the training cohort. The review database contained PMID, first author, year of publication, cancer type, number of patients, study design, independent validation cohort and objective. This database was completed twice by the same person; discrepant results were resolved by a third reading of the articles. A total of 162 studies met inclusion criteria; 61 (37.7%) studies included >100 patients, 13 (8.0%) were prospective and 61 (37.7%) used an independent validation set. The most represented cancers were esophagus, lymphoma, and cervical cancer (n = 24, n = 24 and n = 19 articles, respectively). Most studies focused on 18F-FDG, and prognostic and response to treatment objectives. Although radiomics and artificial intelligence are technically challenging, new contributions and guidelines help improving research quality over the years and pave the way toward personalized medicine.

Citing Articles

Validation of the 2018 FIGO staging system for stage IIIC cervical cancer by determining the metabolic and radiomic heterogeneity of primary tumors based on F-FDG PET/CT.

Zhang Y, Hu Y, Zhao S, Xu S Abdom Radiol (NY). 2024; 49(6):2027-2039.

PMID: 38526594 DOI: 10.1007/s00261-024-04226-7.

Baseline F-FDG PET/CT Radiomics in Classical Hodgkin's Lymphoma: The Predictive Role of the Largest and the Hottest Lesions.

Triumbari E, Gatta R, Maiolo E, De Summa M, Boldrini L, Mayerhoefer M Diagnostics (Basel). 2023; 13(8).

PMID: 37189492 PMC: 10137254. DOI: 10.3390/diagnostics13081391.

Systematic review of the radiomics quality score applications: an EuSoMII Radiomics Auditing Group Initiative.

Spadarella G, Stanzione A, Akinci DAntonoli T, Andreychenko A, Fanni S, Ugga L Eur Radiol. 2022; 33(3):1884-1894.

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Tran V, Tu S, Tseng J Cancers (Basel). 2022; 14(19).

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