Differential expression of a brain aging biomarker across discrete chronic pain disorders.

ABSTRACT: Chronic pain has widespread, detrimental effects on the human nervous system and its prevalence and burden increase with age. Machine learning techniques have been applied on brain images to produce statistical models of brain aging. Specifically, the Gaussian process regression is particularly effective at predicting chronological age from neuroimaging data which permits the calculation of a brain age gap estimate (brain-AGE). Pathological biological processes such as chronic pain can influence brain-AGE. Because chronic pain disorders can differ in etiology, severity, pain frequency, and sex-linked prevalence, we hypothesize that the expression of brain-AGE may be pain specific and differ between discrete chronic pain disorders. We built a machine learning model using T1-weighted anatomical MRI from 812 healthy controls to extract brain-AGE for 45 trigeminal neuralgia (TN), 52 osteoarthritis (OA), and 50 chronic low back pain (BP) subjects. False discovery rate corrected Welch t tests were conducted to detect significant differences in brain-AGE between each discrete pain cohort and age-matched and sex-matched controls. Trigeminal neuralgia and OA, but not BP subjects, have significantly larger brain-AGE. Across all 3 pain groups, we observed female-driven elevation in brain-AGE. Furthermore, in TN, a significantly larger brain-AGE is associated with response to Gamma Knife radiosurgery for TN pain and is inversely correlated with the age at diagnosis. As brain-AGE expression differs across distinct pain disorders with a pronounced sex effect for female subjects. Younger women with TN may therefore represent a vulnerable subpopulation requiring expedited chronic pain intervention. To this end, brain-AGE holds promise as an effective biomarker of pain treatment response.

Pain Relief Reverses Hippocampal Abnormalities in Trigeminal Neuralgia.

Chronic pain patients frequently report memory and concentration difficulties. Objective testing in this population points to poor performance on memory and cognitive tests, and increased comorbid anxiety and depression. Recent evidence has suggested convergence between chronic pain and memory deficits onto the hippocampus. The hippocampus consists of heterogenous subfields involved in memory consolidation, behavior regulation, and stress modulation. Despite significant studies outlining hippocampal changes in human and chronic pain animal models, the effect of pain relief on hippocampal abnormalities remains unknown. Trigeminal neuralgia (TN) is a chronic neuropathic pain disorder which is highly amenable to surgical interventions, providing a unique opportunity to investigate the effect of pain relief. This study investigates the effect of pain relief on hippocampal subfields in TN. Anatomical MR images of 61 TN patients were examined before and 6 months after surgery. Treatment responders (n = 47) reported 95% pain relief, whereas non-responders (n = 14) reported 40% change in pain on average. At baseline, patients had smaller hippocampal volumes, compared to controls. After surgery, responders' hippocampal volumes normalized, largely driven by CA2/3, CA4, and dentate gyrus, which are involved in memory consolidation and neurogenesis. We propose that hippocampal atrophy in TN is pain-driven and successful treatment normalizes such abnormalities. PERSPECTIVE: Chronic pain patients have structural abnormalities in the hippocampus and its subfields. Pain relief normalizes these structural abnormalities and impacts patients in a sex-dependent manner.

Regional brain morphology predicts pain relief in trigeminal neuralgia.

BACKGROUND: Trigeminal neuralgia, a severe chronic neuropathic pain disorder, is widely believed to be amenable to surgical treatments. Nearly 20% of patients, however, do not have adequate pain relief after surgery. Objective tools for personalized pre-treatment prognostication of pain relief following surgical interventions can minimize unnecessary surgeries and thus are of substantial benefit for patients and clinicians. PURPOSE: To determine if pre-treatment regional brain morphology-based machine learning models can prognosticate 1 year response to Gamma Knife radiosurgery for trigeminal neuralgia. METHODS: We used a data-driven approach that combined retrospective structural neuroimaging data and support vector machine-based machine learning to produce robust multivariate prediction models of pain relief following Gamma Knife radiosurgery for trigeminal neuralgia. Surgical response was defined as ≥ 75% pain relief 1 year post-treatment. We created two prediction models using pre-treatment regional brain gray matter morphology (cortical thickness or surface area) to distinguish responders from non-responders to radiosurgery. Feature selection was performed through sequential backwards selection algorithm. Model out-of-sample generalizability was estimated via stratified 10-fold cross-validation procedure and permutation testing. RESULTS: In 51 trigeminal neuralgia patients (35 responders, 16 non-responders), machine learning models based on pre-treatment regional brain gray matter morphology (14 regional surface areas or 13 regional cortical thicknesses) provided robust a priori prediction of surgical response. Cross-validation revealed the regional surface area model was 96.7% accurate, 100.0% sensitive, and 89.1% specific while the regional cortical thickness model was 90.5% accurate, 93.5% sensitive, and 83.7% specific. Permutation testing revealed that both models performed beyond pure chance (p < 0.001). The best predictor for regional surface area model and regional cortical thickness model was contralateral superior frontal gyrus and contralateral isthmus cingulate gyrus, respectively. CONCLUSIONS: Our findings support the use of machine learning techniques in subsequent investigations of chronic neuropathic pain. Furthermore, our multivariate framework provides foundation for future development of generalizable, artificial intelligence-driven tools for chronic neuropathic pain treatments.

Brainstem trigeminal fiber microstructural abnormalities are associated with treatment response across subtypes of trigeminal neuralgia.

ABSTRACT: Neurosurgical treatments for trigeminal neuralgia (TN) can provide long-lasting pain relief; however, some patients fail to respond and undergo multiple, repeat procedures. Surgical outcomes can vary depending on the type of TN, but the reasons for this are not well understood. Neuroimaging studies of TN point to abnormalities in the brainstem trigeminal fibers; however, whether this is a common characteristic of treatment nonresponse across different subtypes of TN is unknown. Here, we used diffusion tensor imaging (DTI) to determine whether the brainstem trigeminal fiber microstructure is a common biomarker of surgical response in TN and whether the extent of these abnormalities is associated with the likelihood of response across subtypes of TN. We studied 98 patients with TN (61 classical TN, 26 TN secondary to multiple sclerosis, and 11 TN associated with a solitary pontine lesion) who underwent neurosurgical treatment and 50 healthy controls. We assessed treatment response using pain intensity measures and examined microstructural features by extracting pretreatment DTI metrics from the proximal pontine segment of the trigeminal nerves. We found that microstructural abnormalities in the affected pontine trigeminal fibers (notably, lower fractional anisotropy and higher radial diffusivity) highlight treatment nonresponders (n = 47) compared with responders (n = 51) and controls, and that the degree of abnormalities is associated with the likelihood of surgical response across subtypes of TN. These novel findings demonstrate the value of DTI as an objective, noninvasive tool for the prediction of treatment response and elucidate the features that distinguish treatment responders from nonresponders in the TN population.

Trigeminal neuralgia associated with a solitary pontine lesion: clinical and neuroimaging definition of a new syndrome.

Conventional magnetic resonance imaging of patients with trigeminal neuralgia (TN) does not typically reveal associated brain lesions. Here, we identify a unique group of TN patients who present with a single brainstem lesion, who do not fulfill diagnostic criteria for multiple sclerosis (MS). We aim to define this new clinical syndrome, which we term TN associated with solitary pontine lesion (SPL-TN), using a clinical and neuroimaging approach. We identified 24 cases of SPL-TN, 18 of which had clinical follow-up for assessment of treatment response. Lesion mapping was performed to determine the exact location of the lesions and site of maximum overlap across patients. Diffusion tensor imaging was used to assess the white-matter microstructural properties of the lesions. Diffusivity metrics were extracted from the (1) SPL-TN lesions, (2) contralateral, unaffected side, (3) MS brainstem plaques from 17 patients with TN secondary to MS, (4) and healthy controls. We found that 17/18 patients were nonresponders to surgical treatment. The lesions were uniformly located along the affected trigeminal pontine pathway, where the site of maximum overlap across patients was in the area of the trigeminal nucleus. The lesions demonstrated abnormal white-matter microstructure, characterized by lower fractional anisotropy, and higher mean, radial, and axial diffusivities compared with the unaffected side. The brainstem trigeminal fiber microstructure within a lesion highlighted the difference between SPL-TN lesions and MS plaques. In conclusion, SPL-TN patients have identical clinical features to TN but have a single pontine lesion not in keeping with MS and are refractory to surgical management.

Temporal disconnection between pain relief and trigeminal nerve microstructural changes after Gamma Knife radiosurgery for trigeminal neuralgia.

OBJECTIVE: Gamma Knife radiosurgery (GKRS) is a noninvasive surgical treatment option for patients with medically refractive classic trigeminal neuralgia (TN). The long-term microstructural consequences of radiosurgery and their association with pain relief remain unclear. To better understand this topic, the authors used diffusion tensor imaging (DTI) to characterize the effects of GKRS on trigeminal nerve microstructure over multiple posttreatment time points. METHODS: Ninety-two sets of 3-T anatomical and diffusion-weighted MR images from 55 patients with TN treated by GKRS were divided within 6-, 12-, and 24-month posttreatment time points into responder and nonresponder subgroups (≥ 75% and < 75% reduction in posttreatment pain intensity, respectively). Within each subgroup, posttreatment pain intensity was then assessed against pretreatment levels and followed by DTI metric analyses, contrasting treated and contralateral control nerves to identify specific biomarkers of successful pain relief. RESULTS: GKRS resulted in successful pain relief that was accompanied by asynchronous reductions in fractional anisotropy (FA), which maximized 24 months after treatment. While GKRS responders demonstrated significantly reduced FA within the radiosurgery target 12 and 24 months posttreatment (p < 0.05 and p < 0.01, respectively), nonresponders had statistically indistinguishable DTI metrics between nerve types at each time point. CONCLUSIONS: Ultimately, this study serves as the first step toward an improved understanding of the long-term microstructural effect of radiosurgery on TN. Given that FA reductions remained specific to responders and were absent in nonresponders up to 24 months posttreatment, FA changes have the potential of serving as temporally consistent biomarkers of optimal pain relief following radiosurgical treatment for classic TN.

Screening for Cognitive Impairments After Traumatic Brain Injury: A Comparison of a Brief Computerized Battery With the Montreal Cognitive Assessment.

Detecting cognitive dysfunction in a busy traumatic brain injury (TBI) clinic is challenging given the length of conventional assessments and the need for psychometric expertise. The authors report the utility of a 10-minute, easily administered computerized battery that is more sensitive than the Montreal Cognitive Assessment in detecting cognitive impairments in people with a TBI.