Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions
Purpose: To evaluate the diagnostic accuracy of a novel non-contrast brain MRI method based on semiautomatic lesion detection using T2w FLAIR subtraction image, the statistical detection of change (SDC) algorithm (T2w + SDC), and quantitative susceptibility mapping (QSM). This method identifies new...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2018-01-01
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| Series: | NeuroImage: Clinical |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2213158218300135 |
| _version_ | 1819278613284913152 |
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| author | Shun Zhang Thanh D. Nguyen Yize Zhao Susan A. Gauthier Yi Wang Ajay Gupta |
| author_facet | Shun Zhang Thanh D. Nguyen Yize Zhao Susan A. Gauthier Yi Wang Ajay Gupta |
| author_sort | Shun Zhang |
| collection | DOAJ |
| description | Purpose: To evaluate the diagnostic accuracy of a novel non-contrast brain MRI method based on semiautomatic lesion detection using T2w FLAIR subtraction image, the statistical detection of change (SDC) algorithm (T2w + SDC), and quantitative susceptibility mapping (QSM). This method identifies new lesions and discriminates between enhancing and nonenhancing lesions in multiple sclerosis (MS). Methods: Thirty three MS patients who had MRIs at two different time points with at least one new Gd-enhancing lesion on the 2nd MRI were included in the study. For a reference standard, new lesions were identified by two neuroradiologists on T2w and post-Gd T1w images with the help of T2w + SDC. The diagnostic accuracy of the proposed method based on QSM and T2w + SDC lesion detection (T2w + SDC + QSM) for assessing lesion enhancement status was determined. Receiver operating characteristic (ROC) analysis was performed to compute the optimal lesion susceptibility cutoff value. Results: A total of 165 new lesions (54 enhancing, 111 nonenhancing) were identified. The sensitivity and specificity of T2w + SDC + QSM in predicting lesion enhancement status were 90.7% and 85.6%, respectively. For lesions ≥50 mm3, ROC analysis showed an optimal QSM cutoff value of 13.5 ppb with a sensitivity of 88.4% and specificity of 88.6% (0.93, 95% CI, 0.87–0.99). For lesions ≥15 mm3, the optimal QSM cutoff was 15.4 ppb with a sensitivity of 77.9% and specificity of 94.0% (0.93, 95% CI, 0.89–0.97). Conclusion: The proposed T2w + SDC + QSM method is highly accurate for identifying and predicting the enhancement status of new MS lesions without the use of Gd injection. Keywords: Multiple sclerosis, Quantitative susceptibility mapping (QSM), Image subtraction |
| first_indexed | 2024-12-24T00:14:47Z |
| format | Article |
| id | doaj.art-74c2c4ebd85d42e9988c745e91415207 |
| institution | Directory Open Access Journal |
| issn | 2213-1582 |
| language | English |
| last_indexed | 2024-12-24T00:14:47Z |
| publishDate | 2018-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage: Clinical |
| spelling | doaj.art-74c2c4ebd85d42e9988c745e914152072022-12-21T17:24:47ZengElsevierNeuroImage: Clinical2213-15822018-01-0118143148Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesionsShun Zhang0Thanh D. Nguyen1Yize Zhao2Susan A. Gauthier3Yi Wang4Ajay Gupta5Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Department of Radiology, Weill Cornell Medicine, New York, NY, USADepartment of Radiology, Weill Cornell Medicine, New York, NY, USADepartment of Healthcare Policy and Research, Weill Cornell Medicine, New York, NY, USADepartment of Neurology, Weill Cornell Medicine, New York, NY, USA; Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USADepartment of Radiology, Weill Cornell Medicine, New York, NY, USA; Department of Biomedical Engineering, Cornell University, Ithaca, NY, USADepartment of Radiology, Weill Cornell Medicine, New York, NY, USA; Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA; Corresponding author at: 525 East 68th St, Box 141, Starr 8A, New York, NY 10065, USA.Purpose: To evaluate the diagnostic accuracy of a novel non-contrast brain MRI method based on semiautomatic lesion detection using T2w FLAIR subtraction image, the statistical detection of change (SDC) algorithm (T2w + SDC), and quantitative susceptibility mapping (QSM). This method identifies new lesions and discriminates between enhancing and nonenhancing lesions in multiple sclerosis (MS). Methods: Thirty three MS patients who had MRIs at two different time points with at least one new Gd-enhancing lesion on the 2nd MRI were included in the study. For a reference standard, new lesions were identified by two neuroradiologists on T2w and post-Gd T1w images with the help of T2w + SDC. The diagnostic accuracy of the proposed method based on QSM and T2w + SDC lesion detection (T2w + SDC + QSM) for assessing lesion enhancement status was determined. Receiver operating characteristic (ROC) analysis was performed to compute the optimal lesion susceptibility cutoff value. Results: A total of 165 new lesions (54 enhancing, 111 nonenhancing) were identified. The sensitivity and specificity of T2w + SDC + QSM in predicting lesion enhancement status were 90.7% and 85.6%, respectively. For lesions ≥50 mm3, ROC analysis showed an optimal QSM cutoff value of 13.5 ppb with a sensitivity of 88.4% and specificity of 88.6% (0.93, 95% CI, 0.87–0.99). For lesions ≥15 mm3, the optimal QSM cutoff was 15.4 ppb with a sensitivity of 77.9% and specificity of 94.0% (0.93, 95% CI, 0.89–0.97). Conclusion: The proposed T2w + SDC + QSM method is highly accurate for identifying and predicting the enhancement status of new MS lesions without the use of Gd injection. Keywords: Multiple sclerosis, Quantitative susceptibility mapping (QSM), Image subtractionhttp://www.sciencedirect.com/science/article/pii/S2213158218300135 |
| spellingShingle | Shun Zhang Thanh D. Nguyen Yize Zhao Susan A. Gauthier Yi Wang Ajay Gupta Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions NeuroImage: Clinical |
| title | Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions |
| title_full | Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions |
| title_fullStr | Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions |
| title_full_unstemmed | Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions |
| title_short | Diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions |
| title_sort | diagnostic accuracy of semiautomatic lesion detection plus quantitative susceptibility mapping in the identification of new and enhancing multiple sclerosis lesions |
| url | http://www.sciencedirect.com/science/article/pii/S2213158218300135 |
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