The role of histogram analysis in diffusion-weighted imaging in the differential diagnosis of benign and malignant breast lesions
Abstract Background The present study aims to investigate the role of histogram analysis of intravoxel incoherent motion (IVIM) in the differential diagnosis of benign and malignant breast lesions. Methods The magnetic resonance imaging and clinical data of 55 patients (63 lesions) were retrospectiv...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2020-09-01
|
| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12911-020-01257-0 |
| _version_ | 1818512879262892032 |
|---|---|
| author | Ya-Nan Jin Yan Zhang Jing-Liang Cheng Xiao-Pan Zhang Ying Hu Xiao-Ning Shao |
| author_facet | Ya-Nan Jin Yan Zhang Jing-Liang Cheng Xiao-Pan Zhang Ying Hu Xiao-Ning Shao |
| author_sort | Ya-Nan Jin |
| collection | DOAJ |
| description | Abstract Background The present study aims to investigate the role of histogram analysis of intravoxel incoherent motion (IVIM) in the differential diagnosis of benign and malignant breast lesions. Methods The magnetic resonance imaging and clinical data of 55 patients (63 lesions) were retrospectively analyzed. The multi-b-valued diffusion-weighted imaging image was processed using the MADC software to obtain the gray-scaled maps of apparent diffusion coefficient (ADC)-slow, ADC-fast and f. The MaZda software was used to extract the histogram metrics of these maps. Combined with the conventional sequence images, the region of interest (ROI) was manually drawn along the edge of the lesion at the maximum level of the gray-scale image, and the difference of the data was analyzed between the benign and malignant breast lesions. Results There were 29 patients with 37 benign lesions, which included 23 fibroadenomas, 6 adenosis, 1 breast cysts, 4 intraductal papillomas, and 3 inflammations of breast. Furthermore, 26 malignant lesions in 26 patients, which included 20 non-specific invasive ductal carcinomas, 5 intraductal carcinomas and 1 patient with squamous cell carcinoma. The ADC-slow (mean and the 50th percentile) and f (minimum, mean, kurtosis, the 10th percentile and 50th percentile) of these malignant breast lesions were significantly lower than those of benign lesions (P < 0.05), while ADC-fast (kurtosis) and f (variance, skewness) of these malignant breast lesions were significantly higher than those of benign lesions (P < 0.05). Conclusion The histogram analysis of ADC-slow (mean and the 50th percentile), ADC-fast (kurtosis) and f (minimum, mean, kurtosis, the 10th percentile and 50th percentile. Variance, skewness) can provide a more objective and accurate basis for the differential diagnosis of benign and malignant breast lesions. |
| first_indexed | 2024-12-10T23:53:11Z |
| format | Article |
| id | doaj.art-8019adef63c04868a996e4d60176d5d3 |
| institution | Directory Open Access Journal |
| issn | 1472-6947 |
| language | English |
| last_indexed | 2024-12-10T23:53:11Z |
| publishDate | 2020-09-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj.art-8019adef63c04868a996e4d60176d5d32022-12-22T01:28:41ZengBMCBMC Medical Informatics and Decision Making1472-69472020-09-012011810.1186/s12911-020-01257-0The role of histogram analysis in diffusion-weighted imaging in the differential diagnosis of benign and malignant breast lesionsYa-Nan Jin0Yan Zhang1Jing-Liang Cheng2Xiao-Pan Zhang3Ying Hu4Xiao-Ning Shao5Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou UniversityDepartment of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou UniversityAbstract Background The present study aims to investigate the role of histogram analysis of intravoxel incoherent motion (IVIM) in the differential diagnosis of benign and malignant breast lesions. Methods The magnetic resonance imaging and clinical data of 55 patients (63 lesions) were retrospectively analyzed. The multi-b-valued diffusion-weighted imaging image was processed using the MADC software to obtain the gray-scaled maps of apparent diffusion coefficient (ADC)-slow, ADC-fast and f. The MaZda software was used to extract the histogram metrics of these maps. Combined with the conventional sequence images, the region of interest (ROI) was manually drawn along the edge of the lesion at the maximum level of the gray-scale image, and the difference of the data was analyzed between the benign and malignant breast lesions. Results There were 29 patients with 37 benign lesions, which included 23 fibroadenomas, 6 adenosis, 1 breast cysts, 4 intraductal papillomas, and 3 inflammations of breast. Furthermore, 26 malignant lesions in 26 patients, which included 20 non-specific invasive ductal carcinomas, 5 intraductal carcinomas and 1 patient with squamous cell carcinoma. The ADC-slow (mean and the 50th percentile) and f (minimum, mean, kurtosis, the 10th percentile and 50th percentile) of these malignant breast lesions were significantly lower than those of benign lesions (P < 0.05), while ADC-fast (kurtosis) and f (variance, skewness) of these malignant breast lesions were significantly higher than those of benign lesions (P < 0.05). Conclusion The histogram analysis of ADC-slow (mean and the 50th percentile), ADC-fast (kurtosis) and f (minimum, mean, kurtosis, the 10th percentile and 50th percentile. Variance, skewness) can provide a more objective and accurate basis for the differential diagnosis of benign and malignant breast lesions.http://link.springer.com/article/10.1186/s12911-020-01257-0Breast tumorIVIMDiffusion weighted imagingMagnetic resonance imagingHistogram metricsDifferential diagnosis |
| spellingShingle | Ya-Nan Jin Yan Zhang Jing-Liang Cheng Xiao-Pan Zhang Ying Hu Xiao-Ning Shao The role of histogram analysis in diffusion-weighted imaging in the differential diagnosis of benign and malignant breast lesions BMC Medical Informatics and Decision Making Breast tumor IVIM Diffusion weighted imaging Magnetic resonance imaging Histogram metrics Differential diagnosis |
| title | The role of histogram analysis in diffusion-weighted imaging in the differential diagnosis of benign and malignant breast lesions |
| title_full | The role of histogram analysis in diffusion-weighted imaging in the differential diagnosis of benign and malignant breast lesions |
| title_fullStr | The role of histogram analysis in diffusion-weighted imaging in the differential diagnosis of benign and malignant breast lesions |
| title_full_unstemmed | The role of histogram analysis in diffusion-weighted imaging in the differential diagnosis of benign and malignant breast lesions |
| title_short | The role of histogram analysis in diffusion-weighted imaging in the differential diagnosis of benign and malignant breast lesions |
| title_sort | role of histogram analysis in diffusion weighted imaging in the differential diagnosis of benign and malignant breast lesions |
| topic | Breast tumor IVIM Diffusion weighted imaging Magnetic resonance imaging Histogram metrics Differential diagnosis |
| url | http://link.springer.com/article/10.1186/s12911-020-01257-0 |
| work_keys_str_mv | AT yananjin theroleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions AT yanzhang theroleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions AT jingliangcheng theroleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions AT xiaopanzhang theroleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions AT yinghu theroleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions AT xiaoningshao theroleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions AT yananjin roleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions AT yanzhang roleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions AT jingliangcheng roleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions AT xiaopanzhang roleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions AT yinghu roleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions AT xiaoningshao roleofhistogramanalysisindiffusionweightedimaginginthedifferentialdiagnosisofbenignandmalignantbreastlesions |