Haralick Texture Analysis for Differentiating Suspicious Prostate Lesions from Normal Tissue in Low-Field MRI
This study evaluates the feasibility of using Haralick texture analysis on low-field, T2-weighted MRI images for detecting prostate cancer, extending current research from high-field MRI to the more accessible and cost-effective low-field MRI. A total of twenty-one patients with biopsy-proven prosta...
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MDPI AG
2025-01-01
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| Series: | Bioengineering |
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| Online Access: | https://www.mdpi.com/2306-5354/12/1/47 |
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| author | Dang Bich Thuy Le Ram Narayanan Meredith Sadinski Aleksandar Nacev Yuling Yan Srirama S. Venkataraman |
| author_facet | Dang Bich Thuy Le Ram Narayanan Meredith Sadinski Aleksandar Nacev Yuling Yan Srirama S. Venkataraman |
| author_sort | Dang Bich Thuy Le |
| collection | DOAJ |
| description | This study evaluates the feasibility of using Haralick texture analysis on low-field, T2-weighted MRI images for detecting prostate cancer, extending current research from high-field MRI to the more accessible and cost-effective low-field MRI. A total of twenty-one patients with biopsy-proven prostate cancer (Gleason score 4+3 or higher) were included. Before transperineal biopsy guided by low-field (58–74mT) MRI, a radiologist annotated suspicious regions of interest (ROIs) on high-field (3T) MRI. Rigid image registration was performed to align corresponding regions on both high- and low-field images, ensuring an accurate propagation of annotations to the co-registered low-field images for texture feature calculations. For each cancerous ROI, a matching ROI of identical size was drawn in a non-suspicious region presumed to be normal tissue. Four Haralick texture features (Energy, Correlation, Contrast, and Homogeneity) were extracted and compared between cancerous and non-suspicious ROIs. Two extraction methods were used: the direct computation of texture measures within the ROIs and a sliding window technique generating texture maps across the prostate from which average values were derived. The results demonstrated statistically significant differences in texture features between cancerous and non-suspicious regions. Specifically, Energy and Homogeneity were elevated (<i>p</i>-values: <0.00001–0.004), while Contrast and Correlation were reduced (<i>p</i>-values: <0.00001–0.03) in cancerous ROIs. These findings suggest that Haralick texture features are both feasible and informative for differentiating abnormalities, offering promise in assisting prostate cancer detection on low-field MRI. |
| format | Article |
| id | doaj-art-9c671921665d48afa1c87bc3e46fd890 |
| institution | Kabale University |
| issn | 2306-5354 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Bioengineering |
| spelling | doaj-art-9c671921665d48afa1c87bc3e46fd8902025-01-24T13:23:04ZengMDPI AGBioengineering2306-53542025-01-011214710.3390/bioengineering12010047Haralick Texture Analysis for Differentiating Suspicious Prostate Lesions from Normal Tissue in Low-Field MRIDang Bich Thuy Le0Ram Narayanan1Meredith Sadinski2Aleksandar Nacev3Yuling Yan4Srirama S. Venkataraman5Promaxo Inc., Oakland, CA 94607, USAPromaxo Inc., Oakland, CA 94607, USAPromaxo Inc., Oakland, CA 94607, USAPromaxo Inc., Oakland, CA 94607, USADepartment of Bioengineering, School of Engineering, Santa Clara University, Santa Clara, CA 95050, USAPromaxo Inc., Oakland, CA 94607, USAThis study evaluates the feasibility of using Haralick texture analysis on low-field, T2-weighted MRI images for detecting prostate cancer, extending current research from high-field MRI to the more accessible and cost-effective low-field MRI. A total of twenty-one patients with biopsy-proven prostate cancer (Gleason score 4+3 or higher) were included. Before transperineal biopsy guided by low-field (58–74mT) MRI, a radiologist annotated suspicious regions of interest (ROIs) on high-field (3T) MRI. Rigid image registration was performed to align corresponding regions on both high- and low-field images, ensuring an accurate propagation of annotations to the co-registered low-field images for texture feature calculations. For each cancerous ROI, a matching ROI of identical size was drawn in a non-suspicious region presumed to be normal tissue. Four Haralick texture features (Energy, Correlation, Contrast, and Homogeneity) were extracted and compared between cancerous and non-suspicious ROIs. Two extraction methods were used: the direct computation of texture measures within the ROIs and a sliding window technique generating texture maps across the prostate from which average values were derived. The results demonstrated statistically significant differences in texture features between cancerous and non-suspicious regions. Specifically, Energy and Homogeneity were elevated (<i>p</i>-values: <0.00001–0.004), while Contrast and Correlation were reduced (<i>p</i>-values: <0.00001–0.03) in cancerous ROIs. These findings suggest that Haralick texture features are both feasible and informative for differentiating abnormalities, offering promise in assisting prostate cancer detection on low-field MRI.https://www.mdpi.com/2306-5354/12/1/47feature extractionHaralick texturelow-fieldMRIprostate cancer |
| spellingShingle | Dang Bich Thuy Le Ram Narayanan Meredith Sadinski Aleksandar Nacev Yuling Yan Srirama S. Venkataraman Haralick Texture Analysis for Differentiating Suspicious Prostate Lesions from Normal Tissue in Low-Field MRI Bioengineering feature extraction Haralick texture low-field MRI prostate cancer |
| title | Haralick Texture Analysis for Differentiating Suspicious Prostate Lesions from Normal Tissue in Low-Field MRI |
| title_full | Haralick Texture Analysis for Differentiating Suspicious Prostate Lesions from Normal Tissue in Low-Field MRI |
| title_fullStr | Haralick Texture Analysis for Differentiating Suspicious Prostate Lesions from Normal Tissue in Low-Field MRI |
| title_full_unstemmed | Haralick Texture Analysis for Differentiating Suspicious Prostate Lesions from Normal Tissue in Low-Field MRI |
| title_short | Haralick Texture Analysis for Differentiating Suspicious Prostate Lesions from Normal Tissue in Low-Field MRI |
| title_sort | haralick texture analysis for differentiating suspicious prostate lesions from normal tissue in low field mri |
| topic | feature extraction Haralick texture low-field MRI prostate cancer |
| url | https://www.mdpi.com/2306-5354/12/1/47 |
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