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Objective <p>To determine inter-reader reliability and diagnostic accuracy of MSKI-RADS among early-career radiologists with different experience levels.</p> Materials and methods <p>This is a retrospective multicenter study of MRIs of proven musculoskeletal (MSK) infections. MSKI-RADS categories included: 0—incomplete imaging, I—negative for infection, II—superficial soft tissue infection, III—deeper soft tissue infection, IV—possible osteomyelitis (OM), V—highly suggestive of OM, VI—known OM, and NOS—nonspecific bony lesions unrelated to infection. There were 22 readers from 9 institutions with 1–8 years of radiology experience, including radiology residents, MSK radiology clinical fellows, and junior MSK attendings. After initial training with expert readers, a dataset of 210 cases across a spectrum of extremity infections from a single institution was evaluated. The readers recorded the following for each case: MSKI-RADS score, final qualitative diagnosis, and confidence levels for both. Inter-reader agreements (ICC) and accuracy were obtained.</p> Results <p>Among 210 cases, there were 17 negative, 32 superficial soft tissue infections, 39 deeper soft tissue infections, 24 possible OM, 41 highly suggestive of OM, 18 known OM, and 39 NOS cases. A moderate inter-reader agreement was seen for 22 readers (ICC: 0.57 (CI = 0.52, 0.67)). The average true positive rates for non-infectious cases (I and NOS), soft tissue infection (II and III), and bony infection (IV and V) were 70% (95% CI: 67–73%), 66% (95% CI: 63–68%), and 82% (95% CI: 80–84%), respectively. Average true positive rates for classes V and VI were 80% (95% CI: 77–82%) and 86% (95% CI: 82–89%), respectively. Overall, MSKI-RADS reader accuracy was 66 ± 10%, higher than the qualitative diagnosis accuracy of 59 ± 11% (<i>p</i> &lt; 0.05). Average confidence levels for MSKI-RADS score and final qualitative diagnosis were 3.56 ± 0.91 and 3.52 ± 0.92, respectively (<i>p</i> &gt; 0.05).</p> Conclusion <p>MSKI-RADS is an accurate and reliable MRI-based classification system for the diagnosis of a spectrum of musculoskeletal infections among early-career radiologists, like expert readers.</p> Key Points <p><Emphasis Type="BoldItalic">Question</Emphasis> <i>What is the inter-reader reliability and diagnostic accuracy of the musculoskeletal infection reporting and data system (MSKI-RADS) among early-career radiologists with different experience levels</i>?</p> <p><Emphasis Type="BoldItalic">Findings</Emphasis> <i>Overall reader accuracy using MSKI-RADS was significantly higher than the accuracy for final qualitative diagnoses, like the results of the initial validation study with expert readers</i>.</p> <p><Emphasis Type="BoldItalic">Clinical relevance</Emphasis> <i>MSKI-RADS is valid and reliable for diagnosis and grading of a spectrum of extremity musculoskeletal infections for early career radiologists of different experience levels, like expert readers</i>.</p> Graphical Abstract <p></p>

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Musculoskeletal infection reporting and data system (MSKI-RADS): multi-institutional wider generalizability study

  • 期刊论文

  • 发表日期：

    2025年8月28日

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  • Avneesh Chhabra,
  • Angela He,
  • Majid Chalian,
  • Tarun Pandey,
  • Erin Alaia,
  • Philip K. Wong,
  • Kenneth S. Lee,
  • Philip G. Colucci,
  • Ty Subhawong,
  • Josephina A. Vossen,
  • Jonathan Samet,
  • Eric Chen,
  • Etan Dayan,
  • Yu-Cherng Channing Chang,
  • Rebecca Driessen,
  • Natalie Rich,
  • Ryan Cummings,
  • Nivedita Radder,
  • Razwan Zemianschi,
  • Shilpa Mohanan,
  • John Zech,
  • Alison Esteva Sanders,
  • Yujie Qiao,
  • Brody Brisk,
  • Junman Kim,
  • Zenas Igbinoba,
  • Nicholas Tan,
  • Nitin Venugopal,
  • Nicholas Laucis,
  • Katherine Eacobacci,
  • Ayman Shaqdan,
  • Alex Napolitano,
  • Cecilia Davis-Hayes,
  • Atul Kumar Taneja,
  • Alex Iancau,
  • Alex Zhu,
  • Yin Xi,
  • Flavio Duarte Silva

摘要

Objective

To determine inter-reader reliability and diagnostic accuracy of MSKI-RADS among early-career radiologists with different experience levels.

Materials and methods

This is a retrospective multicenter study of MRIs of proven musculoskeletal (MSK) infections. MSKI-RADS categories included: 0—incomplete imaging, I—negative for infection, II—superficial soft tissue infection, III—deeper soft tissue infection, IV—possible osteomyelitis (OM), V—highly suggestive of OM, VI—known OM, and NOS—nonspecific bony lesions unrelated to infection. There were 22 readers from 9 institutions with 1–8 years of radiology experience, including radiology residents, MSK radiology clinical fellows, and junior MSK attendings. After initial training with expert readers, a dataset of 210 cases across a spectrum of extremity infections from a single institution was evaluated. The readers recorded the following for each case: MSKI-RADS score, final qualitative diagnosis, and confidence levels for both. Inter-reader agreements (ICC) and accuracy were obtained.

Results

Among 210 cases, there were 17 negative, 32 superficial soft tissue infections, 39 deeper soft tissue infections, 24 possible OM, 41 highly suggestive of OM, 18 known OM, and 39 NOS cases. A moderate inter-reader agreement was seen for 22 readers (ICC: 0.57 (CI = 0.52, 0.67)). The average true positive rates for non-infectious cases (I and NOS), soft tissue infection (II and III), and bony infection (IV and V) were 70% (95% CI: 67–73%), 66% (95% CI: 63–68%), and 82% (95% CI: 80–84%), respectively. Average true positive rates for classes V and VI were 80% (95% CI: 77–82%) and 86% (95% CI: 82–89%), respectively. Overall, MSKI-RADS reader accuracy was 66 ± 10%, higher than the qualitative diagnosis accuracy of 59 ± 11% (p < 0.05). Average confidence levels for MSKI-RADS score and final qualitative diagnosis were 3.56 ± 0.91 and 3.52 ± 0.92, respectively (p > 0.05).

Conclusion

MSKI-RADS is an accurate and reliable MRI-based classification system for the diagnosis of a spectrum of musculoskeletal infections among early-career radiologists, like expert readers.

Key Points

Question What is the inter-reader reliability and diagnostic accuracy of the musculoskeletal infection reporting and data system (MSKI-RADS) among early-career radiologists with different experience levels?

Findings Overall reader accuracy using MSKI-RADS was significantly higher than the accuracy for final qualitative diagnoses, like the results of the initial validation study with expert readers.

Clinical relevance MSKI-RADS is valid and reliable for diagnosis and grading of a spectrum of extremity musculoskeletal infections for early career radiologists of different experience levels, like expert readers.

Graphical Abstract