Automated Color Coding in Musculoskeletal MR Imaging
ABSTRACT Background Magnetic resonance imaging (MRI) is crucial in modern medical diagnostics, providing detailed insights into soft tissue structures and pathological changes. Traditional grayscale images can sometimes obscure critical details, complicating accurate interpretations. Automated color...
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| Format: | Article |
| Language: | English |
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Wiley
2025-06-01
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| Series: | iRADIOLOGY |
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| Online Access: | https://doi.org/10.1002/ird3.70022 |
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| author | Saavi Reddy Pellakuru Sonal Saran Syed Alam Sameer Raniga David Beale Rajesh Botchu |
| author_facet | Saavi Reddy Pellakuru Sonal Saran Syed Alam Sameer Raniga David Beale Rajesh Botchu |
| author_sort | Saavi Reddy Pellakuru |
| collection | DOAJ |
| description | ABSTRACT Background Magnetic resonance imaging (MRI) is crucial in modern medical diagnostics, providing detailed insights into soft tissue structures and pathological changes. Traditional grayscale images can sometimes obscure critical details, complicating accurate interpretations. Automated color coding of the MRI signal intensities may enhance the visualization of various pathologies, potentially leading to improved diagnostic accuracy and image quality. This paper aims to explore the effectiveness of color‐coded MR image reconstruction in enhancing both diagnostic precision and overall image quality in musculoskeletal MRI. Methods Two fellowship‐trained musculoskeletal radiologists evaluated the images reconstructed with color coding, rating their diagnostic value, image quality, and visual appeal using a five‐point Likert scale. To assess interrater reliability, Cohen's Kappa statistical analysis was performed. Additionally, descriptive statistics summarizing the Likert scores for diagnostic value, image quality, and visual appeal of the reconstructed images have been described. Results Statistical analysis of the data revealed that the diagnostic value, image value, and visual appeal of the color‐coded MR images were excellent in almost two‐thirds of the data set. The minimum Likert score recorded was 3, signifying a good quality rating. Conclusion Our study shows positive results, supporting the efficiency of color‐coded MR imaging in aiding the conventional gray scale MR imaging to improve its diagnostic efficiency. |
| format | Article |
| id | doaj-art-4b7641cddc7d4cf1bac394edd09651f8 |
| institution | Kabale University |
| issn | 2834-2860 2834-2879 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | iRADIOLOGY |
| spelling | doaj-art-4b7641cddc7d4cf1bac394edd09651f82025-08-20T03:29:27ZengWileyiRADIOLOGY2834-28602834-28792025-06-013324825210.1002/ird3.70022Automated Color Coding in Musculoskeletal MR ImagingSaavi Reddy Pellakuru0Sonal Saran1Syed Alam2Sameer Raniga3David Beale4Rajesh Botchu5Department of Musculoskeletal Radiology Royal Orthopaedic Hospital Birmingham UKDepartment of Diagnostic and Interventional Radiology AIIMS Rishikesh Rishikesh IndiaDepartment of Radiology Hamad General Hospital Doha QatarDepartment of Radiology and Molecular Imaging University Medical City (UMC), Sultan Qaboos University Hospital Muscat OmanHeath Lodge Clinic Knowle UKDepartment of Musculoskeletal Radiology Royal Orthopaedic Hospital Birmingham UKABSTRACT Background Magnetic resonance imaging (MRI) is crucial in modern medical diagnostics, providing detailed insights into soft tissue structures and pathological changes. Traditional grayscale images can sometimes obscure critical details, complicating accurate interpretations. Automated color coding of the MRI signal intensities may enhance the visualization of various pathologies, potentially leading to improved diagnostic accuracy and image quality. This paper aims to explore the effectiveness of color‐coded MR image reconstruction in enhancing both diagnostic precision and overall image quality in musculoskeletal MRI. Methods Two fellowship‐trained musculoskeletal radiologists evaluated the images reconstructed with color coding, rating their diagnostic value, image quality, and visual appeal using a five‐point Likert scale. To assess interrater reliability, Cohen's Kappa statistical analysis was performed. Additionally, descriptive statistics summarizing the Likert scores for diagnostic value, image quality, and visual appeal of the reconstructed images have been described. Results Statistical analysis of the data revealed that the diagnostic value, image value, and visual appeal of the color‐coded MR images were excellent in almost two‐thirds of the data set. The minimum Likert score recorded was 3, signifying a good quality rating. Conclusion Our study shows positive results, supporting the efficiency of color‐coded MR imaging in aiding the conventional gray scale MR imaging to improve its diagnostic efficiency.https://doi.org/10.1002/ird3.70022color‐coded MRILikert scalemusculoskeletal MRI |
| spellingShingle | Saavi Reddy Pellakuru Sonal Saran Syed Alam Sameer Raniga David Beale Rajesh Botchu Automated Color Coding in Musculoskeletal MR Imaging iRADIOLOGY color‐coded MRI Likert scale musculoskeletal MRI |
| title | Automated Color Coding in Musculoskeletal MR Imaging |
| title_full | Automated Color Coding in Musculoskeletal MR Imaging |
| title_fullStr | Automated Color Coding in Musculoskeletal MR Imaging |
| title_full_unstemmed | Automated Color Coding in Musculoskeletal MR Imaging |
| title_short | Automated Color Coding in Musculoskeletal MR Imaging |
| title_sort | automated color coding in musculoskeletal mr imaging |
| topic | color‐coded MRI Likert scale musculoskeletal MRI |
| url | https://doi.org/10.1002/ird3.70022 |
| work_keys_str_mv | AT saavireddypellakuru automatedcolorcodinginmusculoskeletalmrimaging AT sonalsaran automatedcolorcodinginmusculoskeletalmrimaging AT syedalam automatedcolorcodinginmusculoskeletalmrimaging AT sameerraniga automatedcolorcodinginmusculoskeletalmrimaging AT davidbeale automatedcolorcodinginmusculoskeletalmrimaging AT rajeshbotchu automatedcolorcodinginmusculoskeletalmrimaging |