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Open Access 01-12-2024 | Magnetic Resonance Imaging | Original Article

CT and MRI radiomics of bone and soft-tissue sarcomas: an updated systematic review of reproducibility and validation strategies

Authors: Salvatore Gitto, Renato Cuocolo, Merel Huisman, Carmelo Messina, Domenico Albano, Patrick Omoumi, Elmar Kotter, Mario Maas, Peter Van Ooijen, Luca Maria Sconfienza

Published in: Insights into Imaging | Issue 1/2024

Abstract

Objective

To systematically review radiomic feature reproducibility and model validation strategies in recent studies dealing with CT and MRI radiomics of bone and soft-tissue sarcomas, thus updating a previous version of this review which included studies published up to 2020.

Methods

A literature search was conducted on EMBASE and PubMed databases for papers published between January 2021 and March 2023. Data regarding radiomic feature reproducibility and model validation strategies were extracted and analyzed.

Results

Out of 201 identified papers, 55 were included. They dealt with radiomics of bone (n = 23) or soft-tissue (n = 32) tumors. Thirty-two (out of 54 employing manual or semiautomatic segmentation, 59%) studies included a feature reproducibility analysis. Reproducibility was assessed based on intra/interobserver segmentation variability in 30 (55%) and geometrical transformations of the region of interest in 2 (4%) studies. At least one machine learning validation technique was used for model development in 34 (62%) papers, and K-fold cross-validation was employed most frequently. A clinical validation of the model was reported in 38 (69%) papers. It was performed using a separate dataset from the primary institution (internal test) in 22 (40%), an independent dataset from another institution (external test) in 14 (25%) and both in 2 (4%) studies.

Conclusions

Compared to papers published up to 2020, a clear improvement was noted with almost double publications reporting methodological aspects related to reproducibility and validation. Larger multicenter investigations including external clinical validation and the publication of databases in open-access repositories could further improve methodology and bring radiomics from a research area to the clinical stage.

Critical relevance statement

An improvement in feature reproducibility and model validation strategies has been shown in this updated systematic review on radiomics of bone and soft-tissue sarcomas, highlighting efforts to enhance methodology and bring radiomics from a research area to the clinical stage.

Key points

• 2021–2023 radiomic studies on CT and MRI of musculoskeletal sarcomas were reviewed.

• Feature reproducibility was assessed in more than half (59%) of the studies.

• Model clinical validation was performed in 69% of the studies.

• Internal (44%) and/or external (29%) test datasets were employed for clinical validation.

Graphical Abstract

Available only for authorised users

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Title: CT and MRI radiomics of bone and soft-tissue sarcomas: an updated systematic review of reproducibility and validation strategies
Authors: Salvatore Gitto
Renato Cuocolo
Merel Huisman
Carmelo Messina
Domenico Albano
Patrick Omoumi
Elmar Kotter
Mario Maas
Peter Van Ooijen
Luca Maria Sconfienza
Publication date: 01-12-2024
Publisher: Springer Vienna
Keywords: Magnetic Resonance Imaging
Magnetic Resonance Imaging
Sarcoma
Soft Tissue Sarcoma
Computed Tomography
Computed Tomography
Published in: Insights into Imaging / Issue 1/2024
Electronic ISSN: 1869-4101
DOI: https://doi.org/10.1186/s13244-024-01614-x

Keynote webinar | Spotlight on medication adherence

Springer Medicine

CT and MRI radiomics of bone and soft-tissue sarcomas: an updated systematic review of reproducibility and validation strategies

Abstract

Objective

Methods

Results

Conclusions

Critical relevance statement

Key points

Graphical Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Objective

Methods

Results

Conclusions

Critical relevance statement

Key points

Graphical Abstract

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