Citations

ObjectivesTo prospectively evaluate the diagnostic performance of 3‐dimensional (3D) shear wave elastography (SWE) for assessing thyroid nodules.MethodsA total of 176 surgically or cytologically confirmed thyroid nodules (63 malignant and 113 benign) in 176 patients who had undergone conventional ultrasound (US), 2‐dimensional (2D) SWE, and 3D SWE examinations were included in this study. Quantitative elasticity values (mean elasticity, maximum elasticity, and standard deviation of elasticity of a large region of interest and mean elasticity of a 2‐mm region of interest) were measured on 2D and 3D SWE. Diagnostic performances of conventional US, 2D SWE, and 3D SWE were assessed. The role of 2D and 3D SWE in reducing unnecessary fine‐needle aspiration (FNA) for nodules with low suspicion was also evaluated.ResultsThe diagnostic performances in terms of the area under the receiver operating characteristic curve were 0.612 for conventional US, 0.836 for 2D SWE (P < .001 in comparison with conventional US), and 0.839 for 3D SWE (P < .001 in comparison with conventional US). The mean elasticity achieved the highest diagnostic performance in 2D SWE, whereas the standard deviation of elasticity achieved the highest performance in 3D SWE, although no significant difference was found between them (P > .05). Three‐dimensional SWE increased the specificity in comparison with 2D SWE (88.5% versus 82.3%; P = .039). For the 37 nodules with low suspicion on conventional US imaging, 2D SWE was able to avoid unnecessary FNA in 77.1% (27 of 35) of benign nodules, and 3D SWE further increased the number to 88.6% (31 of 35).ConclusionsThree‐dimensional SWE is a useful tool for predicting thyroid nodule malignancy and reducing unnecessary FNA procedures in thyroid nodules with low suspicion of malignancy.

Resting-state functional magnetic resonance imaging (rs-fMRI) is used to interrogate the functional connectivity and network organization amongst brain regions. Functional connectivity is determined by measuring the extent of synchronization in the spontaneous fluctuations of blood oxygenation level dependent (BOLD) signal. Here, we review current rs-fMRI studies in headache disorders including migraine, trigeminal autonomic cephalalgias, and medication overuse headache. We discuss (1) brain network alterations that are shared amongst the different headache disorders and (2) network abnormalities distinct to each headache disorder. In order to focus the section on migraine, the headache disorder that has been most extensively studied, we chose to include articles that interrogated functional connectivity: (i) during the attack phase; (ii) in migraine patients with aura compared to migraine patients without aura; and (iii) of regions within limbic, sensory, motor, executive and default mode networks and those which participate in multisensory integration. The results of this review show that headache disorders are associated with atypical functional connectivity of regions associated with pain processing as well as atypical functional connectivity of multiple core resting state networks such as the salience, sensorimotor, executive, attention, limbic, visual, and default mode networks.

Objective To investigate differences in cortical thickness in patients with persistent post‐traumatic headache (PPTH) relative to healthy controls and to interrogate whether cortical morphology relates to headache burden (headache frequency, years with post‐traumatic headache, PTH) in patients with PPTH. Background PTHs are one of the most common symptoms following concussion. In some patients, PTHs continue for longer than three months and are classified as PPTH. This study has two main goals: (1) To delineate the neuropathology of PPTH, by interrogating differences in cortical thickness in patients with PPTH relative to healthy controls. (2) To interrogate potential associations between brain morphology and headache burden in patients with PPTH by examining whether cortical thickness relates to frequency of headaches or years lived with PTH. Methods Adults with PPTH diagnosed according to ICHD 3 beta diagnostic criteria and healthy controls underwent brain MRI on a 3 Tesla scanner. Vertex‐by‐vertex whole brain estimates of cortical thickness were automatically calculated using FreeSurfer v5.3. Differences in cortical thickness in patients with PPTH relative to healthy controls were determined using a general linear model design. Associations were explored between regional clusters where patients with PPTH showed cortical thickness differences compared with healthy controls with headache frequency and years lived with PPTH. Results This study included 33 patients with PPTH and 33 healthy control subjects (healthy controls: median age = 33.0, IQR = 15.5; patients with PPTH: median age = 36.0, IQR = 20.5; P = .56). Patients with PPTH had less cortical thickness relative to healthy controls in the left and right superior frontal, caudal middle frontal, and precentral cortex as well as less cortical thickness in the right supramarginal, right superior and inferior parietal, and right precuneus region ( P < .05, Monte Carlo corrected for multiple comparisons). There were no regions where patients with PPTH had more cortical thickness relative to healthy controls. A correlation analysis of regions that showed less cortical thickness in patients with PPTH demonstrated a negative correlation between left and right superior frontal thickness with headache frequency ( P < .05). There was no association between regional cortical thickness and years lived with PPTH. Conclusion Compared with healthy controls, patients with PPTH had less cortical thickness in bilateral frontal regions and right hemisphere parietal regions. For patients with PPTH, more frequent headaches were related to less thickness in the left and right superior frontal regions, potentially indicating that brain morphology changes in the superior frontal regions in patients with PPTH are modified by headache frequency.

BackgroundCurative therapy for ES requires both chemotherapy and local control of primary tumor. There is no universally accepted standard approach to local control modalities. This survey was conducted to determine practice patterns and factors influencing the choice to offer various local control modalities to patients with ES of the spine and pelvis.MethodsThe survey consisted of four scenarios involving a 15‐year‐old girl who presented with Ewing sarcoma of thoracic vertebra, sacrum, iliac wing, and acetabulum with or without neurologic compromise. The questionnaire was sent to oncologists, orthopedic surgeons, and radiation oncologists, asking their recommendations for local control modality.ResultsAmong 94 respondents, radiotherapy was most frequently chosen for sacral tumors (68.1%) and T10 vertebral tumors (46.2%) whereas surgery was preferred for iliac wing pelvic tumors (45.7%) and acetabular tumors (43.6%). Orthopedic surgeons were significantly more likely to offer surgery than radiation oncologists (OR 3.07, 95%CI 1.37‐6.88, P = 0.007). Providers outside North America were more likely to offer combined surgery plus radiotherapy (OR 10.58, 95%CI 5.41‐20.70, P < 0.001).ConclusionConsiderable heterogeneity exists in local control modalities for Ewing sarcoma of the spine and pelvis. Specialty and location of practice may influence treatment recommendations.

Objective To interrogate hippocampal morphology and structural co‐variance patterns in migraine patients and to investigate whether structural co‐variance patterns relate to migraine disease characteristics. Background Migraine is associated with structural alterations in widespread cortical and subcortical regions associated with the sensory, cognitive, and affective components of pain processing. Recent studies have shown that migraine patients have differences in hippocampal structure and function relative to healthy control subjects, but whether hippocampal structure relates to disease characteristics including frequency of attacks, years lived with migraine and symptoms of allodynia remains unknown. Furthermore, this study investigated hippocampal volume co‐variance patterns in migraineurs, an indirect measure of brain network connectivity. Here, we explore differences in hippocampal volume and structural co‐variance patterns in migraine patients relative to healthy controls and examine whether these hippocampal measures relate to migraine disease burden. Methods This study included 61 migraine patients and 57 healthy control subjects (healthy controls: median age = 34.0, IQR = 19.0; migraine patients: median age = 35.0, IQR = 17.5; P = .65). Regional brain volumes were automatically calculated using FreeSurfer version 5.3. Symptoms of allodynia were determined using the Allodynia Symptom Checklist 12 (ASC‐12). Structural co‐variance patterns were interrogated using pairwise correlations and group differences in correlation strength were estimated using Euclidian distance. A stepwise regression was used to investigate the relationship between structural co‐variance patterns with migraine burden. Results Migraine patients had less left hippocampal volume (healthy controls: left hippocampal volume = 4276.8 mm 3 , SD = 425.3 mm 3 , migraine patients: left hippocampal volume = 4089.5 mm 3 , SD = 453.9 mm 3 , P = .02) and less total (right plus left) hippocampal volume (healthy controls: total hippocampal volume= 8690.8 mm 3 , SD = 855.1 mm 3 ; migraine patients: total hippocampal volume = 8341.8 mm 3 , SD = 917.9 mm 3 ; P = .03) compared to healthy controls. Migraineurs had stronger structural covariance between the hippocampi and cortico‐limbic regions in the frontal lobe (inferior opercular gyrus), temporal lobe (planum temporale, amygdala), parietal lobe (angular gyrus, precuneus), and the cerebellar white matter. Results of a stepwise regression showed that hippocampal volumes and the interactions between hippocampal volumes with the volumes of other cortico‐limbic regions associate with migraine‐related allodynia but not with headache frequency or years lived with migraine. Conclusion Migraineurs have less hippocampal volume and stronger hippocampal‐cortico‐limbic connectivity compared to healthy controls. Hippocampal volumes and measures of hippocampal volume connectivity with other cortico‐limbic network regions associate with symptoms of allodynia.

Background The current subclassification of migraine is according to headache frequency and aura status. The variability in migraine symptoms, disease course, and response to treatment suggest the presence of additional heterogeneity or subclasses within migraine. Objective The study objective was to subclassify migraine via a data‐driven approach, identifying latent factors by jointly exploiting multiple sets of brain structural features obtained via magnetic resonance imaging (MRI). Methods Migraineurs ( n = 66) and healthy controls ( n = 54) had brain MRI measurements of cortical thickness, cortical surface area, and volumes for 68 regions. A multimodality factor mixture model was used to subclassify MRIs and to determine the brain structural factors that most contributed to the subclassification. Clinical characteristics of subjects in each subgroup were compared. Results Automated MRI classification divided the subjects into two subgroups. Migraineurs in subgroup #1 had more severe allodynia symptoms during migraines (6.1 ± 5.3 vs. 3.6 ± 3.2, P = .03), more years with migraine (19.2 ± 11.3 years vs 13 ± 8.3 years, P = .01), and higher Migraine Disability Assessment (MIDAS) scores (25 ± 22.9 vs 15.7 ± 12.2, P = .04). There were not differences in headache frequency or migraine aura status between the two subgroups. Conclusions Data‐driven subclassification of brain MRIs based upon structural measurements identified two subgroups. Amongst migraineurs, the subgroups differed in allodynia symptom severity, years with migraine, and migraine‐related disability. Since allodynia is associated with this imaging‐based subclassification of migraine and prior publications suggest that allodynia impacts migraine treatment response and disease prognosis, future migraine diagnostic criteria could consider allodynia when defining migraine subgroups.