The Performance of Radiographic Criteria for Bone Malignancy When Applied to Computed Tomography and Magnetic Resonance Imaging

Önal, Tugay; Afacan, Guven Onur; Akansel, Gür; Arslan, Arzu; Anık, Yonca; İnan, Nagihan; Müezzínoğlu, Bahar; Çorapçıoğlu, Funda

doi:10.1016/j.jmir.2017.10.003

Cited by 8 publications

(6 citation statements)

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“…Soft tissue sarcoma (STS) and bone sarcoma (BS) are a rare group of mesenchymal origin diseases, which account for approximately 1% of adult malignant tumors [ 1 ]. At present, computed tomography (CT) and magnetic resonance imaging (MRI) are the preferred imaging techniques for clinical evaluation of such tumors [ 2 , 3 ]. However, there are more than 200 diverse subtypes of soft tissue and bone tumors.…”

Section: Introductionmentioning

confidence: 99%

Differentiation of soft tissue and bone sarcomas from benign lesions utilizing 18F-FDG PET/CT-derived parameters

et al. 2020

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Background Accurate differentiation between malignant and benign changes in soft tissue and bone lesions is essential for the prevention of unnecessary biopsies and surgical resection. Nevertheless, it remains a challenge and a standard diagnosis modality is urgently needed. The objective of this study was to evaluate the usefulness of 18 F-fluorodeoxyglucose ( 18 F-FDG) PET/CT-derived parameters to differentiate soft tissue sarcoma (STS) and bone sarcoma (BS) from benign lesions. Methods Patients who had undergone pre-treatment 18 F-FDG PET/CT imaging and subsequent pathological diagnoses to confirm malignant (STS and BS, n = 37) and benign ( n = 33) soft tissue and bone lesions were retrospectively reviewed. The tumor size, PET and low-dose CT visual characteristics, maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and heterogeneous factor (HF) of each lesion were measured. Univariate and multivariate logistic regression analyses were conducted to determine the significant risk factors to distinguish sarcoma from benign lesions. To establish a regression model based on independent risk factors, and the receiver operating characteristic curves (ROCs) of individual parameters and their combination were plotted and compared. Conventional imaging scans were re-analyzed, and the diagnostic performance compared with the regression model. Results Univariate analysis results revealed that tumor size, SUVmax, MTV, TLG, and HF of 18 F-FDG PET/CT imaging in the STS and BS group were all higher than in the benign lesions group (all P values were < 0.01). The differences in the visual characteristics between the two groups were also all statistically significant ( P < 0.05). However, the multivariate regression model only included SUVmax and HF as independent risk factors, for which the odds ratios were 1.135 (95%CI: 1.026 ~ 1.256, P = 0.014) and 7.869 (95%CI: 2.119 ~ 29.230, P = 0.002), respectively. The regression model was constructed using the following expression: Logit ( P ) = − 2.461 + 0.127SUVmax + 2.063HF. The area under the ROC was 0.860, which was higher than SUVmax (0.744) and HF (0.790). The diagnostic performance of the regression model was superior to those of individual parameters and conventional imaging. Conclusion The regression model including SUVmax and HF based on 18 F-FDG PET/CT imaging may be useful for differentiating STS and BS from benign lesions.

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Section: Introductionmentioning

confidence: 99%

Differentiation of soft tissue and bone sarcomas from benign lesions utilizing 18F-FDG PET/CT-derived parameters

et al. 2020

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“…Murphey et al (23) found that soft-tissue extension of the cartilaginous tumors had an OR of 106.2 (95% CI = 12.5-904.9) in distinguishing chondrosarcomas from enchondromas. Onal et al conducted a study regarding the application of CT and MRI in evaluation of bone tumors (34). They suggested that MRI was the most superior modality in assisting in the identification of soft-tissue masses.…”

Section: Discussionmentioning

confidence: 99%

Magnetic resonance imaging in differentiating between aggressive and non-aggressive bone tumors

et al. 2022

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Background While radiography remains essential in the initial evaluation of bone lesions, tissue biopsy or further imaging is often required to clarify indeterminate radiographic features. Magnetic resonance imaging (MRI) assists radiologists in evaluating lesions with indeterminate features as it has advantages in delineating tumorous tissues and bone marrow. Purpose To evaluate the association factors of MRI for bony aggressiveness. Material and Methods A retrospective analysis of 226 MRI examinations from patients diagnosed with bone tumors in a tertiary hospital during 2008–2018 was performed. All the MR images were interpreted by musculoskeletal radiologists without diagnostic information. The bony lesions were categorized into aggressive and non-aggressive groups using tumor margin, cortical changes, periosteal reaction, joint extension, extraosseous soft tissue involvement, tumor homogeneity, and enhancement pattern from the MR images. Univariable and multivariable analysis were applied for each feature on the MRI scans. In addition, sensitivity and specificity were calculated for MRI diagnoses of aggressive bone lesions. Results In total, 180 aggressive and 46 non-aggressive bone lesions were examined on MRI. The sensitivity and specificity of MRI for differentiating between aggressive and non-aggressive bone lesions were 98.89% and 50%, respectively. Ill-defined margin, cortical break, cortical signal changes, sunburst and Codman's triangle periosteal reaction, joint extension, and tumoral and heterogeneous enhancement could be predictive signs for aggressive bone lesions. Conclusion MRI can be a valuable tool to assist in distinguishing aggressive from non-aggressive bone lesions. In cases of indeterminate radiographic features, MRI could be used as an additional imaging to improve diagnostic accuracy and could reduce unnecessary invasive procedures.

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“…Conventional x-ray transmission systems, such as radiography or computed tomography, provide information based on the observed anatomy (Kim et al 2018, Mazzone et al 2018 (via the shape or density) from the resulting image. While useful in a variety of applications, these methods can lack the capabilities to answer important questions (Onal et al 2018), such as to confirm tumor malignancy, aid histopathologic analysis, and enable tissue discrimination.…”

Section: Introductionmentioning

confidence: 99%

Simulation based evaluation of a fan beam coded aperture x-ray diffraction imaging system for biospecimen analysis

2021

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X-ray diffraction (XRD) imaging yields spatially resolved, material-specific information, which can aid medical diagnosis and inform treatment. In this work we used simulations to analyze the utility of fan beam coded aperture XRD imaging for fast, high-resolution scatter imaging of biospecimens for tissue assessment. To evaluate the proposed system’s utility in a specific task, we employed a deterministic model to produce simulated data from biologically realistic breast tissue phantoms and model-based reconstruction to recover a spatial map of the XRD signatures throughout the phantoms. We found an XRD spatial resolution of ≈1 mm with a mean reconstructed spectral accuracy of 0.98 ± 0.01 for a simulated 1 × 150 mm2 fan beam operating at 160 kVp, 10 mA, and 4.5 s exposures. A classifier for cancer detection was developed utilizing cross-correlation of XRD spectra against a spectral library, with a receiver operating characteristic curve with an area under the curve value of 0.972. Our results indicated a potential diagnostic modality that could aid in tasks ranging from analysis of ex-vivo pathology biospecimens to intraoperative cancer margin assessment, motivating future work to develop an experimental system while enabling the development of improved algorithms for imaging and tissue analysis-based classification performance.

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The Performance of Radiographic Criteria for Bone Malignancy When Applied to Computed Tomography and Magnetic Resonance Imaging

Cited by 8 publications

References 9 publications

Differentiation of soft tissue and bone sarcomas from benign lesions utilizing 18F-FDG PET/CT-derived parameters

Differentiation of soft tissue and bone sarcomas from benign lesions utilizing 18F-FDG PET/CT-derived parameters

Magnetic resonance imaging in differentiating between aggressive and non-aggressive bone tumors

Simulation based evaluation of a fan beam coded aperture x-ray diffraction imaging system for biospecimen analysis

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