Diagnostic Value of CT- and MRI-Based Texture Analysis and Imaging Findings for Grading Cartilaginous Tumors in Long Bones

Deng, Xue-Ying; Chen, Haiyan; Yu, Jie-Ni; Zhu, Xiu‐Liang; Chen, Jieyu; Shao, Guoliang; Yu, Ri‐Sheng

doi:10.3389/fonc.2021.700204

Cited by 12 publications

(7 citation statements)

References 30 publications

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“…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%

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%

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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“…Thus, it can be concluded that HU measurements on CT scans can serve as a tool to differentiate between enchondroma and ACT, reflecting the characteristics of the tumor matrix. This aspect will be further analyzed in the future with a larger sample size and additional tools such as texture analysis [ 30 , 31 , 32 , 33 ]. It is also notable that, in the combined modality of SPECT/CT, both radiotracer and radiodensity information can be obtained simultaneously without additional examinations.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Bone SPECT/CT of Central Cartilaginous Bone Tumors: Relationship between SUVmax and Radiodensity in Hounsfield Unit

Yoon,

Lee,

Kim

et al. 2024

Cancers

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(1) Background: it is challenging to determine the accurate grades of cartilaginous bone tumors. Using bone single photon emission computed tomography (SPECT)/computed tomography (CT), maximum standardized uptake value (SUVmax) was found to be significantly associated with different grades of cartilaginous bone tumor. The inquiry focused on the effect of the tumor matrix on SUVmax. (2) Methods: a total of 65 patients from 2017 to 2022 with central cartilaginous bone tumors, including enchondromas and low-to-intermediate grade chondrosarcomas, who had undergone bone SPECT/CT were retrospectively enrolled. The SUVmax was recorded and any aggressive CT findings of cartilaginous bone tumor and Hounsfield units (HU) of the chondroid matrix as mean, minimum, maximum, and standard deviation (SD) were reviewed on CT scans. Pearson’s correlation analysis was performed to determine the relationship between CT features and SUVmax. Subgroup analysis was also performed between the benign group (enchondroma) and the malignant group (grade 1 and 2 chondrosarcoma) for comparison of HU values and SUVmax. (3) Results: a significant negative correlation between SUVmax and HU measurements, including HUmax, HUmean, and HUSD, was found. The subgroup analysis showed significantly higher SUVmax in the malignant group, with more frequent CT aggressive features, and significantly lower HUSD in the malignant group than in the benign group. (4) Conclusions: it was observed that higher SUVmax and lower HUSD were associated with a higher probability of having a low-to-intermediate chondrosarcoma with aggressive features and a less calcified tumor matrix.

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“…However, DWI cannot differentiate low-grade lesions from high-grade chondrosarcomas [ 72 ]. Thus, novel tools for the objective grading of chondrosarcomas have recently been introduced, including texture analysis [ 73 , 93 ] and radiomics [ 94 ] with quantitative analysis. Deng et al [ 93 ] reported that CT-based texture analysis showed potential for the grading of cartilaginous tumors in long bones.…”

Section: Diagnostic Dilemma Of Chondrosarcoma Classificationmentioning

confidence: 99%

“…Thus, novel tools for the objective grading of chondrosarcomas have recently been introduced, including texture analysis [ 73 , 93 ] and radiomics [ 94 ] with quantitative analysis. Deng et al [ 93 ] reported that CT-based texture analysis showed potential for the grading of cartilaginous tumors in long bones. Gitto et al [ 94 ] reported that their machine-learning approach showed satisfactory diagnostic performance for the classification of low-to-high-grade cartilaginous bone tumors based on radiomic features extracted from unenhanced MRI.…”

Section: Diagnostic Dilemma Of Chondrosarcoma Classificationmentioning

confidence: 99%

Classification of Chondrosarcoma: From Characteristic to Challenging Imaging Findings

Kim

Lee

2023

Cancers

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Chondrosarcomas can be classified into various forms according to the presence or absence of a precursor lesion, location, and histological subtype. The new 2020 World Health Organization (WHO) Classification of Tumors of Soft Tissue and Bone classifies chondrogenic bone tumors as benign, intermediate (locally aggressive), or malignant, and separates atypical cartilaginous tumors (ACTs) and chondrosarcoma grade 1 (CS1) as intermediate and malignant tumors. respectively. Furthermore, the classification categorizes chondrosarcomas (including ACT) into eight subtypes: central conventional (grade 1 vs. 2–3), secondary peripheral (grade 1 vs. 2–3), periosteal, dedifferentiated, mesenchymal, and clear cell chondrosarcoma. Most chondrosarcomas are the low-grade, primary central conventional type. The rarer subtypes include clear cell, mesenchymal, and dedifferentiated chondrosarcomas. Comprehensive analysis of the characteristic imaging findings can help differentiate various forms of chondrosarcomas. However, distinguishing low-grade chondrosarcomas from enchondromas or high-grade chondrosarcomas is radiologically and histopathologically challenging, even for experienced radiologists and pathologists.

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Diagnostic Value of CT- and MRI-Based Texture Analysis and Imaging Findings for Grading Cartilaginous Tumors in Long Bones

Cited by 12 publications

References 30 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

Quantitative Bone SPECT/CT of Central Cartilaginous Bone Tumors: Relationship between SUVmax and Radiodensity in Hounsfield Unit

Classification of Chondrosarcoma: From Characteristic to Challenging Imaging Findings

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