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Skin marker placement by technologist prior to knee MRI helps identify clinically relevant pathologies

Overview of attention for article published in BMC Musculoskeletal Disorders, December 2017
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Title
Skin marker placement by technologist prior to knee MRI helps identify clinically relevant pathologies
Published in
BMC Musculoskeletal Disorders, December 2017
DOI 10.1186/s12891-017-1876-7
Pubmed ID
Authors

Vibhor Wadhwa, Eric Weissman, Daichi Hayashi, Yin Xi, Avneesh Chhabra

Abstract

Majority of musculoskeletal cross-sectional imaging requests have a non-revealing and non-specific clinical history of pain. However, the location of pain is very relevant towards arriving at a specific orthopedic diagnosis. The purpose of this research was to study the impact of skin marker placement and training of technologists prior to knee MRI in detection of clinically important findings. Total 200 consecutive left knee MRIs were evaluated before and after technologist training with regards to marker placement at the site of clinical symptoms or palpable finding. Marker location in relation to the knee was recorded and important findings were classified as correlated important finding, non-correlated important finding, other compartment important finding in non-correlated cases, and diffuse abnormality, i.e. tri-compartmental cartilage defects in both correlated and non-correlated cases. Differences among scans before and after technologist training were analyzed. The marker placement was observed in higher proportion of patients in post-training scans (78% vs 60%, p = 0.00). The most common location of the marker was in anterior or anterolateral knee (32% and 34% cases, respectively). The marker-important finding correlation was also higher post training, but not statistically significant (53% versus 38%, p = 0.57). Important findings correlated with the marker in more than 50% of the scans in the post-training set. Marker placement can aid in detection of clinically important imaging finding and technologist training aids in increased rates of marker placement and improved correlation.

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Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 18%
Unspecified 2 9%
Librarian 1 5%
Student > Doctoral Student 1 5%
Lecturer 1 5%
Other 2 9%
Unknown 11 50%
Readers by discipline Count As %
Medicine and Dentistry 4 18%
Nursing and Health Professions 3 14%
Unspecified 2 9%
Social Sciences 1 5%
Engineering 1 5%
Other 0 0%
Unknown 11 50%