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...

Full description

Saved in:
Bibliographic Details
Main Authors: Saavi Reddy Pellakuru, Sonal Saran, Syed Alam, Sameer Raniga, David Beale, Rajesh Botchu
Format: Article
Language:English
Published: Wiley 2025-06-01
Series:iRADIOLOGY
Subjects:
Online Access:https://doi.org/10.1002/ird3.70022
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849426340900503552
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