Classification of vertebral compression fractures in magnetic resonance images using shape analysis

Frighetto-Pereira, Lucas; Menezes-Reis, Rafael; Metzner, G. A.; Rangayyan, Rangaraj M.; Nogueira-Barbosa, Marcello Henrique; Azevedo-Marques, Paulo Mazzoncini de

doi:10.1109/ehb.2015.7391550

Cited by 16 publications

(14 citation statements)

References 21 publications

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“…Recently, radiomics features have shown great prospect in the identi cation of malignant and benign bone marrow diseases, including differentiation of primary malignant and benign bone tumors [12], discrimination of benign and malignant vertebral compression fractures [25], and differentiation metastatic and completely responded sclerotic bone lesion [24]. Particularly, a recent study demonstrated that MRI-based radiomics features could be used to assess the early structural change of femoral head after RT and may show potential value to predict RT-induced femoral fractures [23].…”

Section: Discussionmentioning

confidence: 99%

“…Besides, MRI-based radiomics has also been used to assess the effects of age on trabecular bone structure and osteoporosis [20], the spatial heterogeneity of the lumbar vertebral bone marrow [21], and subchondral bone alterations of knee osteoarthritis [22]. Especially, MRI-based radiomics features may be used to assess the early structural change of femoral head after RT in prostate cancer [23], and identify vertebral bone marrow metastases in patients with malignancy [12,24,25].…”

Section: Introductionmentioning

confidence: 99%

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Cervical Spine Osteoradionecrosis or Bone Metastasis after Radiotherapy for Nasopharyngeal Carcinoma? The MRI-Based Radiomics for Characterization

Zhong

Jiang

et al. 2020

Preprint

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Background: To develop and validate an MRI-based radiomics nomogram for differentiation of cervical spine ORN from metastasis after radiotherapy (RT) in nasopharyngeal carcinoma (NPC).Methods: A radiomics nomogram was developed in a training set that comprised 46 NPC patients after RT with 95 cervical spine lesions (ORN, n = 51; metastasis, n = 44), and data were gathered from January 2008 to December 2012. 279 radiomics features were extracted from the axial contrast-enhanced T1-weighted image (CE-T1WI). A radiomics signature was created by using the least absolute shrinkage and selection operator (LASSO) algorithm. A nomogram model was developed based on the radiomics scores. The performance of the nomogram was determined in terms of its discrimination, calibration, and clinical utility. An independent validation set contained 25 consecutive patients with 47 lesions (ORN, n = 25; metastasis, n = 22) from January 2013 to December 2015.Results: The radiomics signature that comprised eight selected features was significantly associated with the differentiation of cervical spine ORN and metastasis. The nomogram model demonstrated good calibration and discrimination in the training set [AUC, 0.725; 95% confidence interval (CI), 0.622–0.828] and the validation set (AUC, 0.720; 95% CI, 0.573–0.867). The decision curve analysis indicated that the radiomics nomogram was clinically useful.Conclusions: MRI-based radiomics nomogram shows potential value to differentiate cervical spine ORN from metastasis after RT in NPC.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cervical Spine Osteoradionecrosis or Bone Metastasis after Radiotherapy for Nasopharyngeal Carcinoma? The MRI-Based Radiomics for Characterization

Zhong

Jiang

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Recently, radiomics features have shown great prospect in identi cation of malignant and benign bone marrow diseases, including differentiation of primarily malignant and benign bone tumors [12], discrimination of benign and malignant vertebral compression fractures [25], and differentiation metastatic and completely responded sclerotic bone lesion [24]. Particularly, a recent study demonstrated that MRI-based radiomics features could be used to assess the early structural change of femoral head after RT and may showed potential value to predict RT-induced femoral fractures [23].…”

Section: Discussionmentioning

confidence: 99%

“…In addition, MRI-based radiomics has also been used to assess the effects of age on trabecular bone structure and osteoporosis [20], the spatial heterogeneity of the lumbar vertebral bone marrow [21], and subchondral bone alterations of knee osteoarthritis [22]. Especially, MRI-based radiomics features may be used to assess the early structural change of femoral head after RT in prostate cancer [23], and identify vertebral bone marrow metastases in patients with malignancy [12,24,25].…”

Section: Introductionmentioning

confidence: 99%

Cervical Spine Osteoradionecrosis or Bone Metastasis after Radiotherapy for Nasopharyngeal Carcinoma? The MRI-Based Radiomics for Characterization

Zhong

Jiang

et al. 2020

Preprint

View full text Add to dashboard Cite

Abstract Background: To develop and validate a MRI-based radiomics nomogram for differentiation of cervical spine ORN from metastasis after radiotherapy (RT) in nasopharyngeal carcinoma (NPC).Methods: A radiomics nomogram was developed in a training set that comprised 46 NPC patients after RT with 95 cervical spine lesions (ORN, n = 51; metastasis, n = 44), and data was gathered from January 2008 to December 2012. 279 radiomics features were extracted from axial contrast-enhanced T1-weighted image (CE-T1WI), a radiomics signature was created by using the least absolute shrinkage and selection operator (LASSO) algorithmin, and a nomogram was developed based on the radiomics scores. The performance of the nomogram was determined in terms of its discrimination, calibration, and clinical utility. An independent validation set contained 25 consecutive patients with 47 lesions (ORN, n = 25; metastasis, n = 22) from January 2013 to December 2015. Results: The radiomics signature that comprised eight selected features was significantly associated with the differentiation of cervical spine ORN and metastasis. The nomogram model demonstrated good calibration and discrimination in the training set [AUC, 0.725; 95% confidence interval (CI), 0.622–0.828] and the validation set (AUC, 0.720; 95% CI, 0.573–0.867). Decision curve analysis indicated that the radiomics nomogram was clinically useful.Conclusions: MRI-based radiomics nomogram shows potential value to differentiate cervical spine ORN from metastasis after RT in NPC.

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“…Furthermore, it is known that MRI is effective in early detection of fractures [4] [10]. A previous study demonstrated the potential of image processing techniques for classification of the presence of VCFs with sensitivity and specificity of 0.808 and 0.846, respectively [11]. This previous study did not attempt to differentiate benign and malignant VCFs.…”

Section: Introductionmentioning

confidence: 93%

Semiautomatic Classification of Benign Versus Malignant Vertebral Compression Fractures Using Texture and Gray-Level Features in Magnetic Resonance Images

Frighetto-Pereira

Menezes-Reis

Metzner

et al. 2015

2015 IEEE 28th International Symposium on Computer-Based Medical Systems

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Our study aimed to develop a system for computer-aided diagnosis of vertebral compression fractures (VCFs) using magnetic resonance imaging (MRI), to help in the differentiation between malignant and benign VCFs. Lumbar spine MRI was used to acquire T1-weighted images in the sagittal plane. Images from 63 consecutive patients (38 women, 25 men, mean age 62.25 ± 14.13 years) with at least one VCF diagnosis were studied. Contrast and texture features were extracted from manually segmented images of 103 vertebral bodies with VCFs. The classification of malignant vs. benign VCFs was performed using the k-nearest neighbor (KNN) classifier with the Euclidean distance. Using a KNN classifier with k=3, feature selection, and 10-fold cross-validation, we obtained a value of the area under the receiver operating characteristic curve of 0.913.

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Classification of vertebral compression fractures in magnetic resonance images using shape analysis

Cited by 16 publications

References 21 publications

Cervical Spine Osteoradionecrosis or Bone Metastasis after Radiotherapy for Nasopharyngeal Carcinoma? The MRI-Based Radiomics for Characterization

Cervical Spine Osteoradionecrosis or Bone Metastasis after Radiotherapy for Nasopharyngeal Carcinoma? The MRI-Based Radiomics for Characterization

Cervical Spine Osteoradionecrosis or Bone Metastasis after Radiotherapy for Nasopharyngeal Carcinoma? The MRI-Based Radiomics for Characterization

Semiautomatic Classification of Benign Versus Malignant Vertebral Compression Fractures Using Texture and Gray-Level Features in Magnetic Resonance Images

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