Evidence map›Paper›PMID 38853160›Full record

ArticleSkeletal radiology2025

Diagnostic performance and inter-reader reliability of bone reporting and data system (Bone-RADS) on computed tomography.

Chankue Park, Arash Azhideh, Atefe Pooyan, Ehsan Alipour, Sara Haseli, Ishan Satwah, Majid Chalian

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Article in Skeletal radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. RADS classification systems for bone tumors: current status and where do we go from here?Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    Review
  5. Article
  6. Article
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Chankue ParkDepartment of Radiology, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, South Korea.
Arash AzhidehDivision of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Washington, Seattle, WA, USA.
Atefe PooyanDivision of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Washington, Seattle, WA, USA.
Ehsan AlipourDivision of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Washington, Seattle, WA, USA.
Sara HaseliDivision of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Washington, Seattle, WA, USA.
Ishan SatwahDepartment of Radiology, University of Wisconsin, Madison, WI, USA.
Majid ChalianDivision of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Washington, Seattle, WA, USA. mchalian@uw.edu.ORCID http://orcid.org/0000-0001-8400-1593

Funding

Korea Health Industry Development Institute HI19C1085
6 · The paper itself

Abstract

objectiveTo evaluate the diagnostic performance and inter-reader reliability of the Bone Reporting and Data System (Bone-RADS) for solitary bone lesions on CT. MATERIALS AND

methodsThis retrospective analysis included 179 patients (mean age, 56 ± 18 years; 94 men) who underwent bone biopsies between March 2005 and September 2021. Patients with solitary bone lesions on CT and sufficient histopathology results were included. Two radiologists categorized the bone lesions using the Bone-RADS (1, benign; 4, malignant). The diagnostic performance of the Bone-RADS was calculated using histopathology results as a standard reference. Inter-reader reliability was calculated.

resultsBone lesions were categorized into two groups: 103 lucent (pathology: 34 benign, 12 intermediate, 54 malignant, and 3 osteomyelitis) and 76 sclerotic/mixed (pathology: 46 benign, 2 intermediate, 26 malignant, and 2 osteomyelitis) lesions. The Bone-RADS for lucent lesions had sensitivities of 95% and 82%, specificities of 11% and 11%, and accuracies of 57% and 50% for readers 1 and 2, respectively. The Bone-RADS for sclerotic/mixed lesions had sensitivities of 75% and 68%, specificities of 27% and 27%, and accuracies of 45% and 42% for readers 1 and 2, respectively. Inter-reader reliability was moderate to very good (κ = 0.744, overall; 0.565, lucent lesions; and 0.851, sclerotic/mixed lesions).

conclusionBone-RADS has a high sensitivity for evaluating malignancy in lucent bone lesions and good inter-reader reliability. However, it has poor specificity and accuracy for both lucent and sclerotic/mixed lesions. A possible explanation is that proposed algorithms heavily depend on clinical features such as pain and history of malignancy.

Indexed as

Bone NeoplasmsSensitivity and SpecificityTomography, X-Ray ComputedAdultAgedBiopsyDiagnosis, DifferentialFemaleHumansMaleMiddle AgedObserver VariationRadiology Information SystemsReproducibility of ResultsRetrospective StudiesBone-RADSBone tumorCTPerformanceReliability

Identifiers

PMID38853160

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.