Ultrasonography in ulnar neuropathy at the elbow: A critical review

Beekman, Roy; Visser, Leo H.; Verhagen, W. I. M.

doi:10.1002/mus.22019

Cited by 132 publications

(89 citation statements)

References 58 publications

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“…Once feasibility had been established (starting at the 4th case), it was only released if it seemed compressive, such as described in clinical practice [22]. When a nerve is entrapped, it has an hourglass shape and its cross-section increases [15,23,24]. US guidance and manual palpation led us to cut Struthers' arcade in three more instances in our study.…”

Section: Us-guided Ulnar Nerve Releasementioning

confidence: 96%

“…These studies confirmed our own observations: excellent echogenicity of the ulnar nerve and easy visualization of its course starting 10 cm proximal to the medial epicondyle all the way to the wrist. When the nerve is entrapped, it has an hourglass shape and its cross-section increases in size [15,23,24]. This increase in size is correlated to the severity of the nerve lesions found on electromyographies [26].…”

Section: Technical Advantagesmentioning

confidence: 97%

“…A recent meta-analysis [15] and study by Zhong et al [16] have shown the relevance of using US for the diagnosis of ulnar nerve entrapment. These studies confirmed our own observations: excellent echogenicity of the ulnar nerve and easy visualization of its course starting 10 cm proximal to the medial epicondyle all the way to the wrist.…”

Section: Technical Advantagesmentioning

confidence: 98%

“…Recent publications use diagnostic ultrasound (US) for ulnar nerve entrapment [15,16]. Therapeutic ultrasonography is limited to guiding corticosteroid injections in certain pathologies [17].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Ultrasound-guided surgical treatment for ulnar nerve entrapment: A cadaver study

Poujade¹,

Hanouz²,

Lecoq³

et al. 2014

Chirurgie de la Main

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Section: Us-guided Ulnar Nerve Releasementioning

confidence: 96%

Section: Technical Advantagesmentioning

confidence: 97%

Section: Technical Advantagesmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Ultrasound-guided surgical treatment for ulnar nerve entrapment: A cadaver study

Poujade¹,

Hanouz²,

Lecoq³

et al. 2014

Chirurgie de la Main

View full text Add to dashboard Cite

“…Neurosonography and MRI are established tools for visualizing the location of the ulnar nerve lesion and its underlying mechanism [3][4][5][6]. Intraneural oedema, peripheral nerve demyelination and nerve fibre degeneration cause an increase in the local T2-weighted MR signal intensity of a mechanically compressed or irritated nerve segment [7].…”

Section: Introductionmentioning

confidence: 99%

MR neurography of ulnar nerve entrapment at the cubital tunnel: a diffusion tensor imaging study

et al. 2015

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Ultrasound‐based radiomics in the diagnosis of carpal tunnel syndrome: The influence of regions of interest delineation method on mode

Lyu

Zhang

et al. 2022

J of Clinical Ultrasound

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Background In the recent years, artificial intelligence (AI) algorithms have been used to accurately diagnose musculoskeletal diseases. However, it is not known whether the particular regions of interest (ROI) delineation method would affect the performance of the AI algorithm. Purpose The purpose of this study was to investigate the influence of ROI delineation methods on model performance and observer consistency. Methods In this retrospective analysis, ultrasound (US) measures of median nerves affected with carpal tunnel syndrome (CTS) were compared to median nerves in a control group without CTS. Two methods were used for delineation of the ROI: (1) the ROI along the hyperechoic medial edge of the median nerve but not including the epineurium (MN) (ROI1); and (2) the ROI including the hyperechoic epineurium (ROI2), respectively. The intra group correlation coefficient (ICC) was used to compare the observer consistency of ROI features (i.e. the corresponding radiomics parameters). Parameters α1 and α2 were obtained based on the ICC of ROI1 features and ROI2 features. The ROC analysis was used to determine the area under the curve (AUC) and evaluate the performance of the radiologists and network. In addition, four indices, namely sensitivity, specificity, positive prediction and negative prediction were analyzed too. Results A total of 136 wrists of 77 CTS group and 136 wrists of 74 control group were included in the study. Control group was matched to CTS group according to the age and sex. The observer consistency of ROI features delineated by the two schemes was different, and the consistency of ROI1 features was higher (α1 ˃ α2). The intra‐observer consistency was higher than the inter‐observer consistency regardless of the scheme, and the intra‐observer consistency was higher when chose scheme one. The performances of models based on the two ROI features were different, although the AUC of each model was greater than 0.8.The model performed better when the MN epineurium was included in the ROI. Among five artificial intelligence algorithms, the Forest models (model1 achieved an AUC of 0.921 in training datasets and 0.830 in testing datasets; model2 achieved an AUC of 0.967 in training datasets and 0.872 in testing datasets.) obtained the highest performance, followed by the support vector machine (SVM) models and the Logistic models. The performances of the models were significantly better than the inexperienced radiologist (Dr. B. Z. achieved an AUC of 0.702). Conclusion Different ROI delineation methods may affect the performance of the model and the consistency of observers. Model performance was better when the ROI contained the MN epineurium, and observer consistency was higher when the ROI was delineated along the hyperechoic medial border of the MN.

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Ultrasonography in ulnar neuropathy at the elbow: A critical review

Abstract: The role of ultrasonography in UNE seems promising but could not be firmly established. More prospective studies are needed, and we make several recommendations for further research.

Cited by 132 publications

References 58 publications

Ultrasound-guided surgical treatment for ulnar nerve entrapment: A cadaver study

Ultrasound-guided surgical treatment for ulnar nerve entrapment: A cadaver study

MR neurography of ulnar nerve entrapment at the cubital tunnel: a diffusion tensor imaging study

Ultrasound‐based radiomics in the diagnosis of carpal tunnel syndrome: The influence of regions of interest delineation method on mode

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