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BACKGROUND:Previous studies on cervical instability failed to explain the dynamic and static interaction relationship and pathological characteristics changes in the development of cervical lesions under the traditional imaging examination.In recent years,the emerging nuclear magnetic resonance imaging(MRI)radiomics can provide a new way for in-depth research on cervical instability. OBJECTIVE:To investigate the application value of MRI radiomics in the study of cervical instability. METHODS:Through recruitment advertisements and the Second Department of Spine of Wangjing Hospital,China Academy of Chinese Medical Sciences,young cervical vertebra unstable subjects and non-unstable subjects aged 18-45 years were included in the cervical vertebra nuclear magnetic image collection.Five specific regions of interest,including the intervertebral disc region,the facet region,the prevertebral muscle region,the deep region of the posterior cervical muscle group,and the superficial region of the posterior cervical muscle group,were manually segmented to extract and screen the image features.Finally,the cervical instability diagnosis classification model was constructed,and the effectiveness of the model was evaluated using the area under the curve. RESULTS AND CONCLUSION:(1)A total of 56 subjects with cervical instability and 55 subjects with non-instability were included,and 1 688 imaging features were extracted for each region of interest.After screening,300 sets of specific image feature combinations were obtained,with 60 sets of regions of interest for each group.(2)Five regions of interest diagnostic classification models for cervical instability were initially established.Among them,the support vector machine model for the articular process region and the support vector machine model for the deep cervical muscle group had certain accuracy for the classification of instability and non-instability,and the average area under the curve of ten-fold cross-validation was 0.719 7 and 0.703 3,respectively.(3)The Logistic model in the intervertebral disc region,the LightGBM model in the prevertebral muscle region,and the Logistic model in the superficial posterior cervical muscle region were generally accurate in the classification of instability and non-instability,and the average area under the curve of ten-fold cross-validation was 0.650 4,0.620 7,and 0.644 2,respectively.(4)This study proved the feasibility of MRI radiomics in the study of cervical instability,further deepened the understanding of the pathogenesis of cervical instability,and also provided an objective basis for the accurate diagnosis of cervical instability.
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By using a highly sensitive HRP-TMB method, the present study found parasympathetic preganglionic neurons innervating rat stomach originated from the dorsal motor nucleus of the vagus(DMV), ambiguus nucleus(AM), reticular formation between DMV and AM(RF). rostroventrolateral reticular nucleus (RVL), lateral parvocelluler reticular nucleus (LRP), paraependymal nucloeus of the vagus (PEV), intercalated nucleus(IC) and retroambiguus nucleus(RA). There was a specific representation area of the stomach in the DMV between 0.3-0.6mm rostral to obex, and the different parts of the stomach had topographical organization within this area. The lateral portion of the DMV mainly innervated the forestomach, the medial and medial-middled portion of the DMV predominantly projected to the antrum/pylorus and corpus, respectively. The right and the left DMV did not show difference in innervating the forestomach and antrum/pylorus, but the corpus was mainly innervated by the right DMV. RF only projected to the forestomach and the corpus. RVL and RA only innervated the forestomach. AM, PEV and IC innervated all the three parts. The relationship between the different neuronal types of the DMV and the different parts of the stomach was first discussed in this paper. The forestomach, corpus and antrum/pylorus received their inputs mainly from the large and small neurons, respectively. The dentrites of the DMV contacting CSF were confirmed.