001 Ulnar neuropathy with abnormal non-localising electrophysiology: clinical, electrophysiological and ultrasound findings

2018 ◽  
Vol 89 (6) ◽  
pp. A2.1-A2
Author(s):  
Luciana Pelosi ◽  
Dominic Ming Yin Tse ◽  
Eoin Mulroy ◽  
Andrew M Chancellor ◽  
Michael R Boland
Keyword(s):  
Ulnar Nerve ◽  
Significant Role ◽  
Diagnostic Tests ◽  
Ulnar Neuropathy ◽  
Axonal Loss ◽  
Nerve Ultrasound ◽  
Causative Mechanism ◽  
Ultrasound Findings ◽  
Significant Disability

IntroductionUlnar neuropathy with abnormal non-localising electrophysiology (NL-UN) is often associated with significant disability that is difficult to manage due to the absence of anatomically defining studies. We studied demographic, clinical and electrophysiological characteristics of NL-UN and used ultrasound in order to assist with classification and to examine the utility of ultrasound over and above the conventional electro-diagnostic approach.MethodNL-UNs were identified from 113 consecutive referrals to a single neurophysiologist with suspected ulnar neuropathy. All received systematic electro-diagnostic tests and ulnar nerve ultrasound. NL-UN severity was graded using clinical and electrophysiological scales.ResultsIn 64 of 113 referrals, an ulnar mononeuropathy was confirmed by electrophysiology. Sixteen of these 64 (25%) had NL-UN, predominantly males (14 out of 16 patients) with severe or moderately severe clinical and electrophysiological ratings in 81%. Ultrasound showed focal ulnar neuropathy at the elbow (UNE) in 13 out of 16, and diffuse ulnar nerve abnormality in three, and identified a likely or possible causative mechanism in 11 UNEs.ConclusionA quarter of ulnar neuropathies, as demonstrated by abnormal electrophysiology, were NL-UN, of heterogeneous aetiology; the majority were males with significant disability and axonal loss. Ultrasound had a significant role in localization and classification of NL-UN that facilitated management.

scholarly journals 121 Diabetic ulnar neuropathy with non-localizing electrophysiology: a nerve ultrasound study

2019 ◽  
Vol 90 (e7) ◽  
pp. A39.2-A39
Author(s):  
Luciana Pelosi ◽  
Lance Blumhardt ◽  
Vivien Yong
Keyword(s):  
Ulnar Nerve ◽  
Small Sample ◽  
Ulnar Neuropathy ◽  
Focal Lesion ◽  
Diabetic Patients ◽  
List Type ◽  
Nerve Ultrasound ◽  
Focal Lesions ◽  
Ultrasound Study ◽  
Ultrasound Findings

IntroductionThe classification and management of diabetic ulnar mono-neuropathy with non-localizing electrophysiology (NL-UN) is challenging, as this could be due to a focal axonal lesion at the elbow that may require surgery or, be part of the mono-neuritis multiplex spectrum of diabetic neuropathy. The distinction cannot be made by clinical examination and electrophysiology.We investigated the value of nerve ultrasound in this situation.MethodsWe analysed ulnar nerve ultrasound in 9 consecutive diabetic patients (5 males, mean age 65.4 years) with 12 NL-UN affected nerves. The ulnar neuropathy was clinically and electrophysiologically severe in 9 nerves and moderate in 3.ResultsUltrasound showed diffuse ulnar nerve abnormality in 9 nerves (75%) and focal nerve abnormalities at the elbow in 3 (25%)ConclusionsThe majority of NL-UNs in this small sample of patients with diabetes were not due to focal lesions at the elbow. This is in contrast with the nerve ultrasound findings in non-diabetic patients with NL-UN, which almost invariably show a focal lesion at the elbow (Pelosi et al, 2018), and confirms that the pathophysiology of ulnar mono-neuropathy is different and more complex in diabetes.Ultrasound appears to be a useful tool to classify NL-UN in the patient with diabetes and larger studies are indicated.ReferencesPelosi, et al. Ulnar neuropathy with abnormal non-localizing electrophysiology: Clinical, electrophysiological and ultrasound findings. Clin Neurophysiol 2018, 129:2155–2161.

scholarly journals Retrospective study on the impact of ulnar nerve dislocation on the pathophysiology of ulnar neuropathy at the elbow

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6972 ◽  
Author(s):  
Seok Kang ◽  
Joon Shik Yoon ◽  
Seung Nam Yang ◽  
Hyuk Sung Choi
Keyword(s):  
Ulnar Nerve ◽  
Partial Dislocation ◽  
Demographic Data ◽  
Ulnar Neuropathy ◽  
Axonal Loss ◽  
Cross Sectional ◽  
Us Findings ◽  
Dislocation Group ◽  
The Impact ◽  
Complete Dislocation

Introduction High resolution ultrasonography (US) has been used for diagnosis and evaluation of entrapment peripheral neuropathy. Ulnar neuropathy at the elbow (UNE) is the second most common focal entrapment neuropathy. The ulnar nerve tends to move to the anteromedial side and sometimes subluxates or dislocates over the medial epicondyle as the elbow is flexed. Dislocation of the ulnar nerve during elbow flexion may contribute to friction injury. We aimed to investigate the effects which the dislocation of ulnar nerve at the elbow could have on the electrophysiologic pathology of UNE. Materials We retrospectively reviewed 71 arms of UNE. The demographic data, electrodiagnosis findings and US findings of ulnar nerve were analyzed. We classified the electrodiagnosis findings of UNE into three pathologic types; demyelinating, sensory axonal loss, and mixed sensorimotor axonal loss. The arms were grouped into non-dislocation, partial dislocation, and complete dislocation groups according to the findings of nerve dislocation in US examination. We compared the electrodiagnosis findings, ulnar nerve cross sectional areas in US and electrodiagnosis pathology types among the groups. Results A total of 18 (25.3%) arms showed partial dislocation, and 15 (21.1%) arms showed complete dislocation of ulnar nerve in US. In the comparison of electrodiagnosis findings, the partial and complete dislocation groups showed significantly slower conduction velocities and lower amplitudes than non-dislocation group in motor conduction study. In the sensory conduction study, the conduction velocity was significantly slower in partial dislocation group and the amplitude was significantly lower in complete dislocation group than non-dislocation group. In the comparison of US findings, patients in partial and complete dislocation groups showed significantly larger cross sectional areas of the ulnar nerve. The comparison of electrodiagnosis pathologic types among the groups revealed that there were significantly larger proportions of the axonal loss (sensory axonal loss or mixed sensorimotor axonal loss) in partial and complete dislocation groups than non-dislocation group. Conclusion The ulnar nerve dislocation could influence on the more severe damage of the ulnar nerve in patients with UNE. It might be important to evaluate the dislocation of the ulnar nerve using US in diagnosing ulnar neuropathy for predicting the prognosis and determining the treatment direction of UNE.

5. Segmental changes in ulnar nerve ultrasound across the elbow and their pathophysiological significance in ulnar neuropathy

2014 ◽  
Vol 125 (4) ◽  
pp. e2
Author(s):  
Neil G. Simon ◽  
Jeffrey W. Ralph ◽  
Ann Poncelet ◽  
John W. Engstrom ◽  
Cynthia Chin ◽  
...  
Keyword(s):  
Ulnar Nerve ◽  
Ulnar Neuropathy ◽  
Nerve Ultrasound

Distal Ulnar Neuropathy from Carpal Ganglia: A Clinical and Electrophysiological Study

Neurosurgery ◽  
1988 ◽  
Vol 22 (5) ◽  
pp. 902-905 ◽  
Author(s):  
Michele Cavallo ◽  
Massimo Poppi ◽  
Paolo Martinelli ◽  
Giulio Gaist
Keyword(s):  
Ulnar Nerve ◽  
Axonal Degeneration ◽  
Electrophysiological Study ◽  
Ulnar Neuropathy ◽  
Clinical Classification ◽  
Segmental Demyelination ◽  
Deep Branch ◽  
First Case ◽  
Compression Syndromes

Abstract The clinical and electrophysiological observations in two cases of distal ulnar neuropathy from carpal ganglia are reported. In the first case, the ganglion was compressing the ulnar nerve just proximal to its division; in the second case, the ganglion was compressing the deep branch of the ulnar nerve just at its origin. In both cases, both axonal degeneration and segmental demyelination were present. A clinical classification of the compression syndromes of the deep ulnar branch is proposed.

080 Electrodiagnostic and ultrasound correlates of clinical severity in ulnar neuropathy

2018 ◽  
Vol 89 (6) ◽  
pp. A32.3-A33
Author(s):  
Luciana Pelosi ◽  
Eoin Mulroy
Keyword(s):  
Diagnostic Yield ◽  
Clinical Signs ◽  
Clinical Severity ◽  
Ulnar Neuropathy ◽  
Sensory Loss ◽  
Nerve Ultrasound ◽  
Cross Sectional ◽  
Hand Muscles ◽  
Ultrasound Findings ◽  
Marked Atrophy

IntroductionThis is a retrospective review of 135 consecutive patients (M:F=71:64, mean age 52.6 years; 141 arms) referred to our institution with ulnar neuropathy over a two year period. We analysed electrodiagnostic and ultrasound findings in relation to clinical severity.MethodsAll patients underwent electrodiagnostic (AAN) and ultrasound examination of the symptomatic ulnar nerve(s). Clinical severity was graded on a 4 point scale from ‘very mild’ (symptoms only) to ‘severe’ (sensory loss plus marked atrophy of ulnar-innervated hand muscles).ResultsIn ‘very mild’ neuropathies, the number of abnormal electrodiagnostic and ultrasound studies was 2 and 11 respectively, out of 54; in ‘mild’ neuropathies 19 and 25 out of 40; in ‘moderate’, 23 and 24 out of 24; and in ‘severe’, 23 and 23 out of 23. In 25 arms, (18 of which were clinically ‘severe’ or ‘moderate’), electrophysiology was abnormal but non-localising. Ultrasound showed abnormally large cross-sectional area at the elbow in 22 and diffuse nerve enlargement in three. Ultrasound identified nerve subluxation in 24 (17%) neuropathies, 58% of which were ‘very mild’, 25% ‘mild’ and 17% ‘moderate’ or ‘severe’.ConclusionIn patients with symptoms but no clinical signs, electrophysiological evidence of ulnar neuropathy was present in 3.7%, whereas abnormal nerve ultrasound, often associated with subluxation, was demonstrated in 20%. Ultrasound increased the diagnostic yield of electrophysiology in the ‘very mild’ and, to a lesser extent, the ‘mild’ neuropathies by a combined 11%, and localised the lesion in all ulnar neuropathies with abnormal but non-localising electrophysiology. Nerve subluxation was disproportionately represented amongst the clinically ‘very mild’ neuropathies with abnormal ultrasound.

A CASE REPORT OF ACUTE CUBITAL TUNNEL SYNDROME CAUSED BY VENOUS THROMBOSIS

Hand Surgery ◽  
2015 ◽  
Vol 20 (01) ◽  
pp. 137-139 ◽  
Author(s):  
Yoshihiro Abe ◽  
Masahiko Saito
Keyword(s):  
Case Report ◽  
Venous Thrombosis ◽  
Ulnar Nerve ◽  
Cubital Tunnel Syndrome ◽  
Nerve Compression ◽  
Ulnar Neuropathy ◽  
Cubital Tunnel ◽  
Ulnar Nerve Compression ◽  
Compression Neuropathy ◽  
Tunnel Syndrome

Compression neuropathy of the ulnar nerve at the elbow is well-recognised as cubital tunnel syndrome (CuTS). Many causes of ulnar neuropathy at the elbow have been identified. A previously unreported finding of ulnar nerve compression in the cubital tunnel caused by a thrombosed proximal ulnar recurrent artery vena comitans is described.

103. Nerve ultrasound findings in neuropathy associated with anti-mag antibodies

2015 ◽  
Vol 126 (1) ◽  
pp. e24
Author(s):  
L. Padua ◽  
M. Lucchetta ◽  
G. Granata ◽  
M. Luigetti ◽  
M. Campagnolo ◽  
...  
Keyword(s):  
Nerve Ultrasound ◽  
Ultrasound Findings

THE BRONZE SHIELD FROM THE BURIAL OF A MEDIEVAL ARCHER IN THE KUZNETSK DESPRESSION

2021 ◽  
Vol 27 ◽  
pp. 265-270
Author(s):  
PILIPENKO S. ◽  
◽  
SULEIMENOV M. ◽  
Keyword(s):  
Significant Role ◽  
Western Siberia ◽  
Volga Region ◽  
Burial Ground ◽  
The South ◽  
Protective Shield

A number of works written by leading Siberian weapons experts are devoted to the classification of this piece of personal armour. Issues of weapons development played a significant role in the lives of the medieval people in the South of Western Siberia. One of the most frequently encountered categories of inventory in the burials of nomads includes ranged weapons: parts of bows, arrows, quivers. Yu.S. Khudyakova [1980, p. 118] and VV. Gorbunova [2006, p. 35-62]. However, bow sets are not limited to bows, arrows and quivers. There are also other parts of archery equipment known from the nomadic antiquities of the Volga region, such as archers’ rings and pavises [Rudenko, 2005, p. 27-35], items that have never been found in the South of Western Siberia until recently. During his exploration of burial ground 3 from mound 3 of Konevo, A.M. Ilyushin [2012, p. 37] found a bronze plate, which he believed belonged to plate armour. However, further study of the objects found in burial ground 3 of mound 3 of Konevo, raised doubts whether this attribution of the excavated bronze plate is justified. Acquaintance with the materials of burial 3 of mound 3 of the Konevo burial ground, raised doubts about such an attribution of the revealed bronze plate. Keywords: medieval nomads, archeology, bow, arrows, protective shield, pavise, gastagna, archer, Kuznetsk Depression

scholarly journals ELBOW ULNAR NEUROPATHY: TREATMENT BY ANTERIOR TRANSPOSITION OF THE ULNAR NERVE

2016 ◽  
Vol 24 (4) ◽  
pp. 184-186
Author(s):  
Antonio Tufi Neder Filho ◽  
Regina de Azevedo Alves ◽  
Arlindo Gomes Pardini Júnior ◽  
Marcelo Riberto ◽  
Milton Mazer
Keyword(s):  
Ulnar Nerve ◽  
Ulnar Neuropathy ◽  
Anterior Transposition

scholarly journals Deep Learning Method for Quantitative Analysis of Covid -19 using CT Chest Images

2021 ◽  
Author(s):  
Indrajeet Kumar ◽  
Jyoti Rawat
Keyword(s):  
Deep Learning ◽  
Diagnostic Tests ◽  
Ct Images ◽  
Rapid Diagnosis ◽  
Chest Ct ◽  
Visual Features ◽  
Learning Module ◽  
Volumetric Ct ◽  
The Cost

Abstract The manual diagnostic tests performed in laboratories for pandemic disease such as COVID19 is time-consuming, requires skills and expertise of the performer to yield accurate results. Moreover, it is very cost ineffective as the cost of test kits is high and also requires well-equipped labs to conduct them. Thus, other means of diagnosing the patients with presence of SARS-COV2 (the virus responsible for COVID19) must be explored. A radiography method like chest CT images is one such means that can be utilized for diagnosis of COVID19. The radio-graphical changes observed in CT images of COVID19 patient helps in developing a deep learning-based method for extraction of graphical features which are then used for automated diagnosis of the disease ahead of laboratory-based testing. The proposed work suggests an Artificial Intelligence (AI) based technique for rapid diagnosis of COVID19 from given volumetric CT images of patient’s chest by extracting its visual features and then using these features in the deep learning module. The proposed convolutional neural network is deployed for classifying the infectious and non-infectious SARS-COV2 subjects. The proposed network utilizes 746 chests scanned CT images of which 349 images belong to COVID19 positive cases while remaining 397 belong negative cases of COVID19. The extensive experiment has been completed with the accuracy of 98.4 %, sensitivity of 98.5 %, the specificity of 98.3 %, the precision of 97.1 %, F1score of 97.8 %. The obtained result shows the outstanding performance for classification of infectious and non-infectious for COVID19 cases.

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