Evaluation of Infantile Brachial Plexopathy Using 3T MRI and High-Resolution Ultrasound: Experience From a Tertiary Care Centre.

BACKGROUND: Currently, clinical assessment is the main tool for the evaluation of brachial plexus injury, complemented by electrophysiologic studies (EPS), and imaging studies whenever available. Imaging plays an important role as it enables the differentiation of pre-ganglionic and postganglionic injuries, and adds objectivity to presurgical evaluation. OBJECTIVES: The primary objective was to evaluate the utility of magnetic resonance imaging (MRI) and high-resolution ultrasonography (USG) in the localization and characterization of brachial plexus injury in infants. MATERIALS AND METHODS: In this prospective study, 34 infants with signs and symptoms of brachial plexus injury were evaluated by clinical examination, EPS, MRI, and USG. Imaging findings were correlated with intraoperative findings in infants who underwent surgical management. The association between EPS and MRI findings, and USG and MRI findings were assessed using Fisher's exact test. Semi-quantitative subjective analysis of various MRI sequences was done as well. RESULTS: The most common findings of preganglionic injury and postganglionic injury, in our study, were pseudomeningocele and nerve thickening, respectively. MRI detection of injuries had a significant association with EPS findings. All MRI-detected injuries had a muscle power of grade 3 or less. muscle. Three-dimensional (3D) short tau inversion recovery (STIR) sequence was found to be superior for detecting postganglionic injuries (P < 0.05). CONCLUSION: Imaging studies enable localization of the site of injury, determining the extent, and nature/morphology of injury. The gamut of findings obtained from MRI is far wider compared to that from USG. USG can be used as the first-line screening investigation.

Ultrasound accuracy for brachial plexus pathology.

AIM: To determine (a) the accuracy of ultrasound in detecting brachial plexus pathology and (b) outline the advantages and limitations of ultrasound compared to MRI for imaging the brachial plexus. MATERIAL AND METHODS: cases with clinically suspected brachial plexus pathology were evaluated first by ultrasound, followed by MRI. Patients with prior brachial plexus imaging were excluded. The final diagnosis was based on a combination of ultrasound, MRI, clinical follow-up, and surgical findings. The accuracy of the ultrasound was assessed by comparing the ultrasound and the final diagnoses. The mean clinical follow-up time following ultrasound was 1.8 ± 1.4 years. RESULTS: Ninety-two (64%) of the 143 cases had normal brachial plexus ultrasound and MRI examinations. Fifty-one (36%) of 143 cases had brachial plexus pathology on MRI, comprising post-radiation fibrosis (n=25, 49%), nerve sheath tumor (n=11, 21%), traumatic injury (n=7, 14%), inflammatory polyneuropathy (n=4, 8%), malignant infiltration (n=2, 4%), desmoid fibromatosis (n=1,2%), and neuralgic amyotrophy (n=1, 2%). Overall diagnostic accuracy of ultrasound for brachial plexus pathology was 98% (140/143), with three discordant cases (neuralgic amyotrophy n=1, inflammatory neuropathy n=1, postradiation fibrosis n=1) regarded as normal on ultrasound assessment. Sensitivity, specificity, and positive and negative predictive value of ultrasound for identifying brachial plexus pathology were 94%, 100%, 100%, and 97%, respectively. CONCLUSION: Ultrasound identifies brachial plexus pathology with high accuracy and specificity, showing comparable diagnostic efficacy to MRI. Ultrasound can serve as an effective first-line imaging investigation for suspected brachial plexus pathology.

3D SHINKEI MR neurography in evaluation of traumatic brachial plexus.

3D SHINKEI neurography is a new sequence for imaging the peripheral nerves. The study aims at assessing traumatic brachial plexus injury using this sequence. Fifty-eight patients with suspected trauma induced brachial plexus injury underwent MR neurography (MRN) imaging in 3D SHINKEI sequence at 3 T. Surgery and intraoperative somatosensory evoked potentials or clinical follow-up results were used as the reference standard. MRN, surgery and electromyography (EMG) findings were recorded at four levels of the brachial plexus-roots, trunks, cords and branches. Fifty-eight patients had pre- or postganglionic injury. The C5-C6 nerve postganglionic segment was the most common (average 42%) among the postganglionic injuries detected by 3D SHINKEI MRN. The diagnostic accuracy (83.75%) and the specificity (90.30%) of MRN higher than that of EMG (p < 0.001). There was no significant difference in the diagnostic sensitivity of MRN compared with EMG (p > 0.05). Eighteen patients with brachial plexus injury underwent surgical exploration after MRN examination and the correlation between MRN and surgery was 66.7%. Due to the high diagnostic accuracy and specificity, 3D SHINKEI MRN can comprehensively display the traumatic brachial plexus injury. This sequence has great potential in the accurate diagnosis of traumatic brachial plexus injury.

Abnormal Brachial Plexus Differentiation from Routine Magnetic Resonance Imaging: An AI-based Approach.

Automatic abnormality identification of brachial plexus (BP) from normal magnetic resonance imaging to localize and identify a neurologic injury in clinical practice (MRI) is still a novel topic in brachial plexopathy. This study developed and evaluated an approach to differentiate abnormal BP with artificial intelligence (AI) over three commonly used MRI sequences, i.e. T1, FLUID sensitive and post-gadolinium sequences. A BP dataset was collected by radiological experts and a semi-supervised artificial intelligence method was used to segment the BP (based on nnU-net). Hereafter, a radiomics method was utilized to extract 107 shape and texture features from these ROIs. From various machine learning methods, we selected six widely recognized classifiers for training our Brachial plexus (BP) models and assessing their efficacy. To optimize these models, we introduced a dynamic feature selection approach aimed at discarding redundant and less informative features. Our experimental findings demonstrated that, in the context of identifying abnormal BP cases, shape features displayed heightened sensitivity compared to texture features. Notably, both the Logistic classifier and Bagging classifier outperformed other methods in our study. These evaluations illuminated the exceptional performance of our model trained on FLUID-sensitive sequences, which notably exceeded the results of both T1 and post-gadolinium sequences. Crucially, our analysis highlighted that both its classification accuracies and AUC score (area under the curve of receiver operating characteristics) over FLUID-sensitive sequence exceeded 90%. This outcome served as a robust experimental validation, affirming the substantial potential and strong feasibility of integrating AI into clinical practice.

Diagnosis of obstetric brachial plexus injury in a 2-year-old girl using high­frequency ultrasonography.

We describe an unusual case of infant obstetric brachial plexus injury located in the cervical (C)5-C6 brachial plexus nerve, which was preoperatively diagnosed using high-frequency ultrasonography (US) at 2 years of age. The girl was diagnosed with a right clavicular fracture because of shoulder dystocia. She had been showing movement limitations of her entire right upper limb after fracture healing and was then referred to our hospital at 2 years of age. High-frequency US showed that the roots of the right brachial plexus ran continuously, but the diameter of C6 was thinner on the affected side than on the contralateral side (right 0.12 cm vs. left 0.20 cm). A traumatic neuroma had formed at the upper trunk, which was thicker (diameter: right 0.35 cm vs. left 0.23 cm; cross-sectional area: right 0.65 cm2 vs. left 0.31 cm2) at the level of the supraclavicular fossa. Intraoperative findings were consistent with ultrasound findings. Postoperative pathology confirmed brachial plexus traumatic neuroma.