Catharina S Lisson1, Christoph G Lisson1, Kerstin Flosdorf1, Regine Mayer-Steinacker2, Markus Schultheiss3, Alexandra von Baer3, Thomas F E Barth4, Ambros J Beer5, Matthias Baumhauer6, Reinhard Meier1, Meinrad Beer1, Stefan A Schmidt7. 1. Department of Diagnostic and Interventional Radiology, University Hospital of Ulm, Albert-Einstein-Allee 23, D-89081, Ulm, Germany. 2. Department of Internal Medicine III, University Hospital of Ulm, Albert-Einstein-Allee 23, D-89081, Ulm, Germany. 3. Department of Trauma Surgery, University Hospital of Ulm, Albert-Einstein-Allee 23, D-89081, Ulm, Germany. 4. Institute of Pathology, University of Ulm, Albert-Einstein-Allee 23, D-89081, Ulm, Germany. 5. Department of Nuclear Medicine, University Hospital of Ulm, Albert-Einstein-Allee 23, D-89081, Ulm, Germany. 6. Mint Medical, Friedrich-Ebert-Straße 2, D-69221, Dossenheim, Germany. 7. Department of Diagnostic and Interventional Radiology, University Hospital of Ulm, Albert-Einstein-Allee 23, D-89081, Ulm, Germany. stefan.schmidt@uniklinik-ulm.de.
Abstract
OBJECTIVES: To explore the diagnostic value of MRI-based 3D texture analysis to identify texture features that can be used for discrimination of low-grade chondrosarcoma from enchondroma. METHODS: Eleven patients with low-grade chondrosarcoma and 11 patients with enchondroma were retrospectively evaluated. Texture analysis was performed using mint Lesion: Kurtosis, entropy, skewness, mean of positive pixels (MPP) and uniformity of positive pixel distribution (UPP) were obtained in four MRI sequences and correlated with histopathology. The Mann-Whitney U-test and receiver operating characteristic (ROC) analysis were performed to identify most discriminative texture features. Sensitivity, specificity, accuracy and optimal cut-off values were calculated. RESULTS: Significant differences were found in four of 20 texture parameters with regard to the different MRI sequences (p<0.01). The area under the ROC curve values to discriminate chondrosarcoma from enchondroma were 0.876 and 0.826 for kurtosis and skewness in contrast-enhanced T1 (ceT1w), respectively; in non-contrast T1, values were 0.851 and 0.822 for entropy and UPP, respectively. The highest discriminatory power had kurtosis in ceT1w with a cut-off ≥3.15 to identify low-grade chondrosarcoma (82 % sensitivity, 91 % specificity, accuracy 86 %). CONCLUSION: MRI-based 3D texture analysis might be able to discriminate low-grade chondrosarcoma from enchondroma by a variety of texture parameters. KEY POINTS: • MRI texture analysis may assist in differentiating low-grade chondrosarcoma from enchondroma. • Kurtosis in the contrast-enhanced T1w has the highest power of discrimination. • Tools provide insight into tumour characterisation as a non-invasive imaging biomarker.
OBJECTIVES: To explore the diagnostic value of MRI-based 3D texture analysis to identify texture features that can be used for discrimination of low-grade chondrosarcoma from enchondroma. METHODS: Eleven patients with low-grade chondrosarcoma and 11 patients with enchondroma were retrospectively evaluated. Texture analysis was performed using mint Lesion: Kurtosis, entropy, skewness, mean of positive pixels (MPP) and uniformity of positive pixel distribution (UPP) were obtained in four MRI sequences and correlated with histopathology. The Mann-Whitney U-test and receiver operating characteristic (ROC) analysis were performed to identify most discriminative texture features. Sensitivity, specificity, accuracy and optimal cut-off values were calculated. RESULTS: Significant differences were found in four of 20 texture parameters with regard to the different MRI sequences (p<0.01). The area under the ROC curve values to discriminate chondrosarcoma from enchondroma were 0.876 and 0.826 for kurtosis and skewness in contrast-enhanced T1 (ceT1w), respectively; in non-contrast T1, values were 0.851 and 0.822 for entropy and UPP, respectively. The highest discriminatory power had kurtosis in ceT1w with a cut-off ≥3.15 to identify low-grade chondrosarcoma (82 % sensitivity, 91 % specificity, accuracy 86 %). CONCLUSION: MRI-based 3D texture analysis might be able to discriminate low-grade chondrosarcoma from enchondroma by a variety of texture parameters. KEY POINTS: • MRI texture analysis may assist in differentiating low-grade chondrosarcoma from enchondroma. • Kurtosis in the contrast-enhanced T1w has the highest power of discrimination. • Tools provide insight into tumour characterisation as a non-invasive imaging biomarker.
Entities:
Keywords:
Chondrosarcoma; Enchondroma; Magnetic resonance imaging; Texture analysis; Tissue characterisation
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