The diagnostic value of magnetic resonance imaging-based texture analysis in differentiating enchondroma and chondrosarcoma

Çilengir, Atilla Hikmet; Evrimler, Şehnaz; Serel, T. Ahmet; Uluc, Engın; Tosun, Özgür

doi:10.1007/s00256-022-04242-y

Cited by 7 publications

(9 citation statements)

References 19 publications

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“…It should be noted that the aim was two- or threefold in some studies, as detailed in Tables 1 and 2 . In studies focused on diagnosis-related tasks, histology was the reference standard in all cases except benign lesions diagnosed on the basis of stable imaging findings over time in four papers [ 17 , 20 – 22 ]. In studies dealing with survival prediction, survival was assessed based on clinical follow-up.…”

Section: Resultsmentioning

confidence: 99%

“…The intraclass correlation coefficient (ICC) was the statistical method used in all papers reporting a reproducibility analysis. ICC threshold ranged between 0.7 [ 54 ] and 0.9 [ 20 , 46 ] for reproducible features. Additionally, the following statistical methods were used less commonly: Bland–Altman method [ 54 ], Pearson’s correlation coefficient [ 52 ], and Spearman’s rank-order coefficient [ 52 ].…”

Section: Resultsmentioning

confidence: 99%

“…At least one machine learning validation technique was used in 34 (62%) of the 55 papers. K-fold cross-validation was used in most of the studies [ 18 , 20 , 22 , 24 , 27 , 31 , 37 – 39 , 44 , 47 , 49 , 52 , 54 , 57 , 58 , 60 – 68 ]. The following machine learning validation techniques were used less commonly: bootstrapping [ 34 , 46 ], leave-one-out cross-validation [ 17 , 28 ], and nested cross-validation [ 43 , 55 , 56 , 69 ].…”

Section: Resultsmentioning

confidence: 99%

“…A clinical validation of the radiomics-based prediction model was reported in 38 (69%) of the 55 studies. In 22 (40%) studies, it was performed on a separate set of data from the primary institution, namely the internal test dataset, which was chosen randomly [ 19 , 20 , 24 , 28 , 29 , 31 , 32 , 37 , 41 , 42 , 45 , 47 , 52 , 53 , 59 , 65 , 66 , 68 ], based on temporal criteria [ 61 , 69 , 70 ] or different acquisition scanners [ 62 ]. Of note, in a multi-center study, patients were split into training and test cohorts randomly rather than following geographical criteria [ 68 ].…”

Section: Resultsmentioning

confidence: 99%

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

Gitto,

Cuocolo,

Huisman

et al. 2024

Insights Imaging

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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

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

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

Gitto,

Cuocolo,

Huisman

et al. 2024

Insights Imaging

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“…As the application of artificial intelligence (AI) in medicine is expanding, it is plausible to assume that AI will eventually play a decisive role in the development and optimization of reporting systems. Although there is published data on the use of quantitative MRIbased texture analysis for the grading of cartilaginous bone tumors as well as machine learning approaches for bone chondrosarcoma classification on radiography, CT, and MRI, these have not been included in routine clinical practice or in radiological reporting schemes as of yet [11][12][13][14][15]. Ideally, there will eventually be a unifying nomogram that combines both clinical and multi-parametric/modality radiology data to accurately and noninvasively characterize a bone lesion and guide patient management.…”

Section: Future Directionsmentioning

confidence: 99%

Bone Reporting and Data System (Bone-RADS) and Other Proposed Practice Guidelines for Reporting Bone Tumors

Ghasemi,

Ahlawat

2024

Rofo

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Background The purpose of this article is to review the different bone tumor radiology reporting systems [Bone Reporting and Data System (Bone-RADS), Osseous Tumor Reporting and Data System (OT-RADS), Solitary Bone Tumor Imaging Reporting and Data System (BTI-RADS), and Radiological Evaluation Score for Bone Tumors (REST)] and summarize their advantages and disadvantages. Methods A selective search of PubMed was performed for literature regarding the definition and discussion of bone tumor reporting systems. No time frame was selected, but the search was particularly focused on current literature on musculoskeletal radiology lexicon. Results To date, four major reporting systems has been proposed to standardize and systematize the reporting of imaging studies of bone tumors: Bone-RADS, OT-RADS, BTI-RADS, and REST. Both Bone-RADS and OT-RADS aid in the characterization and management of bone lesions on CT and MRI. OT-RADS and REST can be applied to MRI and radiography, respectively. Conclusion Radiologists play a central role in the detection and characterization of asymptomatic (or incidentally detected) and symptomatic bone tumors. There are several existing bone tumor reporting systems with various advantages and disadvantages including emphasis on lesion characterization as well as management of incidentally detected bone lesions. Key Points

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A retrospective external validation study of the Birmingham Atypical Cartilage Tumour Imaging Protocol (BACTIP) for the management of solitary central cartilage tumours of the proximal humerus and around the knee

Van Den Berghe,

Delbare,

Candries

et al. 2024

Eur Radiol

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The diagnostic value of magnetic resonance imaging-based texture analysis in differentiating enchondroma and chondrosarcoma

Cited by 7 publications

References 19 publications

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

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

Bone Reporting and Data System (Bone-RADS) and Other Proposed Practice Guidelines for Reporting Bone Tumors

A retrospective external validation study of the Birmingham Atypical Cartilage Tumour Imaging Protocol (BACTIP) for the management of solitary central cartilage tumours of the proximal humerus and around the knee

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