Diffusion tensor imaging of the C1-C3 dorsal root ganglia and greater occipital nerve for cervicogenic headache

Abstract

Background Previous studies showed neurography and tractography of the greater occipital nerve (GON). The purpose of this study was determining diffusion tensor imaging (DTI) parameters of bilateral GONs and dorsal root ganglia (DRG) in unilateral cervicogenic headache as well as the grading value of DTI for severe headache. The correlation between DTI parameters and clinical characteristics was evaluated. Methods The fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values in bilateral GONs and cervical DRG (C2 and C3) were measured. Grading values for headache severity was calculated using a receiver operating characteristics curve. The correlation was analyzed with Pearson’s coefficient. Results The FA values of the symptomatic side of GON and cervical DRG (C2 and C3) were significantly lower than that of the asymptomatic side (all the P < 0.001), while the ADC values were significantly higher ( P = 0.003, P < 0.001, and P = 0.003, respectively). The FA value of 0.205 in C2 DRG was considered the grading parameter for headache severity with sensitivity of 0.743 and specificity of 0.999 ( P < 0.001). A negative correlation and a positive correlation between the FA and ADC value of the GON and headache index (HI; r = –0.420, P = 0.037 and r = 0.531, P = 0.006, respectively) was found. Conclusions DTI parameters in the symptomatic side of the C2 and C3 DRG and GON were significantly changed. The FA value of the C2 DRG can grade headache severity. DTI parameters of the GON significantly correlated with HI.

Receiver operating characteristic curve: overview and practical use for clinicians

“…The ROC curve was initially developed to determine between a signal (true positive result) and noise (false positive result) when analyzing signals on a radar screen during World War II. This method, which has been used for signal detection/discrimination, was later introduced to psychology [1,2] and has since been widely used in the field of medicine to evaluate the performance of diagnostic methods [3][4][5][6]. It has recently also been applied in various other fields, such as bioinformatics and machine learning [7,8].…”

Fluoroscopic Findings of Extra-Cervical Facet Joint Flow and Its Incidence on Cervical Facet Joint Arthrograms

“…A total of 760 CFJ arthrograms were obtained from the injections (C3-C7 vertebral levels). The exclusion criteria were as follows: patients with cervicogenic headache related superior to CFJ of C2 vertebral level, included into the diagnostic criteria provided by International Headache Society in 2018 [13,14]; contraindications to interventional treatment, such as pregnancy, allergy to contrast medium, coagulopathy, and infections at the injection site; insufficient needle access to the targeted CFJ due to severe anatomical deformity or a history of surgery; and unintentional intravascular or intramuscular injection. Based on age, patients were divided into two groups (≥45 years and <45 years).…”

Prognostic value of cervical ligamentum flavum thickness as a morphological parameter to predict cervical stenosis

“…CSMRI studies are very important in the diagnosis of degenerative disorders of CCS and in highly detectable hypertrophy of CLF. [29,30] This study has some limitations. First, although we measured CLFT in T2-weighted axial images at the most stenotic facet joint level, there might be some measurement errors on CSMRI because axial cervical images might be inhomogeneous due to differences in the cutting angle of CSMRI resulting from posture in patients and individual anatomic variations.…”

“…In this study, we analyzed CLFT from CSMRI images. CSMRI studies are very important in the diagnosis of degenerative disorders of CCS and in highly detectable hypertrophy of CLF [29,30] …”