scholarly journals Clinical-radiomics nomograms for pre-operative differentiation of sacral chordoma and sacral giant cell tumor based on 3D computed tomography and multiparametric magnetic resonance imaging

2019 ◽  
Vol 92 (1101) ◽  
pp. 20190155 ◽  
Author(s):  
Ping Yin ◽  
Ning Mao ◽  
Sicong Wang ◽  
Chao Sun ◽  
Nan Hong
Keyword(s):  
Giant Cell Tumor ◽  
Giant Cell ◽  
Diffusion Weighted Imaging ◽  
Cell Tumor ◽  
Imaging Features ◽  
Model Based ◽  
Sacral Chordoma ◽  
Diffusion Weighted ◽  
Mixed Features ◽  
Ct Features

Objective: To develop and validate clinical-radiomics nomograms based on three-dimensional CT and multiparametric MRI (mpMRI) for pre-operative differentiation of sacral chordoma (SC) and sacral giant cell tumor (SGCT). Methods: A total of 83 SC and 54 SGCT patients diagnosed through surgical pathology were retrospectively analyzed. We built six models based on CT, CT enhancement (CTE), T1 weighted, T2 weighted, diffusion-weighted imaging (DWI), and contrast-enhanced T1 weighted features, two radiomics nomograms and two clinical-radiomics nomograms combined radiomics mixed features with clinical data. The area under the receiver operating characteristic curve (AUC) and accuracy (ACC) analysis were used to assess the performance of the models. Results: SC and SGCT presented significant differences in terms of age, sex, and tumor location (tage = 9.00, χ2sex = 10.86, χ2location = 26.20; p < 0.01). For individual scan, the radiomics model based on diffusion-weighted imaging features yielded the highest AUC of 0.889 and ACC of 0.885, followed by CT (AUC = 0.857; ACC = 0.846) and CT enhancement (AUC = 0.833; ACC = 0.769). For the combined features, the radiomics model based on mixed CT features exhibited a better AUC of 0.942 and ACC of 0.880, whereas mixed MRI features achieved a lower performance than the individual scan. The clinical-radiomics nomogram based on combined CT features achieved the highest AUC of 0.948 and ACC of 0.920. Conclusions: The radiomics model based on CT and multiparametricMRI present a certain predictive value in distinguishing SC and SGCT, which can be used for auxiliary diagnosis before operation. The clinical-radiomics nomograms performed better than radiomics nomograms. Advances in knowledge: Clinical-radiomics nomograms based on CT and mpMRI features can be used for preoperative differentiation of SC and SGCT.

Multimodality Imaging Features of a Misleading Sacral Giant Cell Tumor in 18F-FDG PET/CT, Bone Scan, and MRI

2020 ◽  
Vol 45 (10) ◽  
pp. 800-801
Author(s):  
Sebastien Dejust ◽  
Pascaline Jallerat ◽  
Pauline Soibinet-Oudot ◽  
Christelle Jouannaud ◽  
David Morland
Keyword(s):  
Giant Cell Tumor ◽  
Giant Cell ◽  
Fdg Pet ◽  
Bone Scan ◽  
Multimodality Imaging ◽  
Cell Tumor ◽  
Imaging Features ◽  
Pet Ct ◽  
18F Fdg ◽  
Fdg Pet Ct

Three cases of benign giant cell tumor with unusual imaging features

2008 ◽  
Vol 32 (5) ◽  
pp. 407-410 ◽  
Author(s):  
Ronald Swanger ◽  
Catherine Maldjian ◽  
Raj Murali ◽  
Michael Tenner
Keyword(s):  
Giant Cell Tumor ◽  
Giant Cell ◽  
Cell Tumor ◽  
Imaging Features

scholarly journals A Case of Infarcted Localized Tenosynovial Giant Cell Tumor of the Knee: Multimodality Imaging Features and Literature Review

2018 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Wonju Hong ◽  
Sun-Young Park ◽  
Soo Kee Min ◽  
Je-Hyun Yoo ◽  
Sung Hye Koh ◽  
...  
Keyword(s):  
Literature Review ◽  
Giant Cell Tumor ◽  
Giant Cell ◽  
Multimodality Imaging ◽  
Cell Tumor ◽  
Imaging Features ◽  
Tenosynovial Giant Cell Tumor

scholarly journals Magnetic resonance feature of “paintbrush borders” sign as a novel way to predict recurrence of giant cell tumor of bone after curettage: a pilot study

2017 ◽  
Vol 46 (2) ◽  
pp. 710-722
Author(s):  
Yifeng He ◽  
Jun Wang ◽  
Ji Zhang ◽  
Lianjun Du ◽  
Yong Lu ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Prognostic Factor ◽  
Local Recurrence ◽  
Giant Cell Tumor ◽  
Giant Cell ◽  
Multivariate Logistic Regression Analysis ◽  
Cell Tumor ◽  
Independent Prognostic Factor ◽  
Preoperative Imaging ◽  
Imaging Features

Objective To identify the prognostic factors for local recurrence of giant cell tumor of bone (GCTB) through assessment of the preoperative imaging features of the tumor border. Methods Patients with GCTBs treated with intralesional procedures in the proximal tibia and distal femur were prospectively enrolled and then followed up for at least 2 years. The GCTBs were grouped according to their preoperative imaging features. GCTBs treated with en bloc resection were enrolled for investigation of the pathologic basis of specific imaging features. Differences between rates were evaluated by the chi-square test or Fisher’s exact test; independent factors were identified by multivariate logistic regression analysis. Results Fifty-three patients were enrolled and successfully followed up. Relapse occurred in 22 patients. Patients with a “paintbrush borders” sign (n = 21) had a significantly higher rate of local recurrence (71.43%) than patients without this sign (21.88%). The “paintbrush borders” sign was identified as an independent prognostic factor for local recurrence. Other imaging features were not significantly associated with recurrence. The “paintbrush borders” sign showed a correlation with local invasion of bone. Conclusion The “paintbrush borders” sign on preoperative magnetic resonance imaging is an independent prognostic factor for local recurrence of GCTB.

scholarly journals State of the Art and New Concepts in Giant Cell Tumor of Bone: Imaging Features and Tumor Characteristics

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6298
Author(s):  
Anna Parmeggiani ◽  
Marco Miceli ◽  
Costantino Errani ◽  
Giancarlo Facchini
Keyword(s):  
Soft Tissue ◽  
Local Recurrence ◽  
Giant Cell Tumor ◽  
Giant Cell ◽  
Articular Surface ◽  
Cell Tumor ◽  
Imaging Features ◽  
Tissue Mass ◽  
Promising Alternative ◽  
High Local Recurrence Rate

Giant cell tumor of bone (GCTB) is classified as an intermediate malignant tumor due to its locally aggressive behavior, burdened by high local recurrence rate. GCTB accounts for about 4–5% of all primary bone tumors and typically arises in the metaphysis and epiphyses of the long tubular bones. Mutation of gene H3F3A is at the basis of GCTB etiopathogenesis, and its immunohistochemical expression is a valuable method for practical diagnosis, even if new biomarkers have been identified for early diagnosis and for potential tumor recurrence prediction. In the era of computer-aided diagnosis, imaging plays a key role in the assessment of GCTB for surgical planning, patients’ prognosis prediction and post treatment evaluation. Cystic changes, penetrating irregular margins and adjacent soft tissue invasion on preoperative Magnetic Resonance Imaging (MRI) have been associated with a higher rate of local recurrence. Distance from the tumor edge to the articular surface and thickness of unaffected cortical bone around the tumor should be evaluated on Computed Tomography (CT) as related to local recurrence. Main features associated with local recurrence after curettage are bone resorption around the graft or cement, soft tissue mass formation and expansile destruction of bone. A denosumab positive response is represented by a peripherical well-defined osteosclerosis around the lesion and intralesional ossification. Radiomics has proved to offer a valuable contribution in aiding GCTB pre-operative diagnosis through clinical-radiomics models based on CT scans and multiparametric MR imaging, possibly guiding the choice of a patient-tailored treatment. Moreover, radiomics models based on texture analysis demonstrated to be a promising alternative solution for the assessment of GCTB response to denosumab both on conventional radiography and CT since the quantitative variation of some radiomics features after therapy has been correlated with tumor response, suggesting they might facilitate disease monitoring during post-denosumab surveillance.

A Chondroblastoma Versus a Giant Cell Tumor: Emphasis on the MR Imaging Features

2007 ◽  
Vol 57 (4) ◽  
pp. 371
Author(s):  
Jee Won Chai ◽  
Sung Hwan Hong ◽  
Ja-Young Choi ◽  
Na Ra Kim ◽  
Jung-Ah Choi ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Giant Cell Tumor ◽  
Giant Cell ◽  
Cell Tumor ◽  
Imaging Features
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