Protocol for a randomized controlled trial examining multilevel prediction of response to behavioral activation and exposure-based therapy for generalized anxiety disorder.

BACKGROUND:Only 40-60% of patients with generalized anxiety disorder experience long-lasting improvement with gold standard psychosocial interventions. Identifying neurobehavioral factors that predict treatment success might provide specific targets for more individualized interventions, fostering more optimal outcomes and bringing us closer to the goal of "personalized medicine." Research suggests that reward and threat processing (approach/avoidance behavior) and cognitive control may be important for understanding anxiety and comorbid depressive disorders and may have relevance to treatment outcomes. This study was designed to determine whether approach-avoidance behaviors and associated neural responses moderate treatment response to exposure-based versus behavioral activation therapy for generalized anxiety disorder. METHODS/DESIGN:We are conducting a randomized controlled trial involving two 10-week group-based interventions: exposure-based therapy or behavioral activation therapy. These interventions focus on specific and unique aspects of threat and reward processing, respectively. Prior to and after treatment, participants are interviewed and undergo behavioral, biomarker, and neuroimaging assessments, with a focus on approach and avoidance processing and decision-making. Primary analyses will use mixed models to examine whether hypothesized approach, avoidance, and conflict arbitration behaviors and associated neural responses at baseline moderate symptom change with treatment, as assessed using the Generalized Anxiety Disorder-7 item scale. Exploratory analyses will examine additional potential treatment moderators and use data reduction and machine learning methods. DISCUSSION:This protocol provides a framework for how studies may be designed to move the field toward neuroscience-informed and personalized psychosocial treatments. The results of this trial will have implications for approach-avoidance processing in generalized anxiety disorder, relationships between levels of analysis (i.e., behavioral, neural), and predictors of behavioral therapy outcome. TRIAL REGISTRATION:The study was retrospectively registered within 21 days of first participant enrollment in accordance with FDAAA 801 with ClinicalTrials.gov, NCT02807480. Registered on June 21, 2016, before results

TEAMwork: Testing Emotional Attunement and Mutuality During Parent-Adolescent fMRI.

The parent-child relationship and family context influence the development of emotion regulation (ER) brain circuitry and related skills in children and adolescents. Although both parents' and children's ER neurocircuitry simultaneously affect how they interact with one another, neuroimaging studies of parent-child relationships typically include only one member of the dyad in brain imaging procedures. The current study examined brain activation related to parenting and ER in parent-adolescent dyads during concurrent fMRI scanning with a novel task - the Testing Emotional Attunement and Mutuality (TEAM) task. The TEAM task includes feedback trials indicating the other dyad member made an error, resulting in a monetary loss for both participants. Results indicate that positive parenting practices as reported by the adolescent were positively correlated with parents' hemodynamic activation of the ventromedial prefrontal cortex, a region related to empathy, during these error trials. Additionally, during feedback conditions both parents and adolescents exhibited fMRI activation in ER-related regions, including the dorsolateral prefrontal cortex, anterior insula, fusiform gyrus, thalamus, caudate, precuneus, and superior parietal lobule. Adolescents had higher left amygdala activation than parents during the feedback condition. These findings demonstrate the utility of dyadic fMRI scanning for investigating relational processes, particularly in the parent-child relationship

Always on my mind: Cross-brain associations of mental health symptoms during simultaneous parent-child scanning.

How parents manifest symptoms of anxiety or depression may affect how children learn to modulate their own distress, thereby influencing the children's risk for developing an anxiety or mood disorder. Conversely, children's mental health symptoms may impact parents' experiences of negative emotions. Therefore, mental health symptoms can have bidirectional effects in parent-child relationships, particularly during moments of distress or frustration (e.g., when a parent or child makes a costly mistake). The present study used simultaneous functional magnetic resonance imaging (fMRI) of parent-adolescent dyads to examine how brain activity when responding to each other's costly errors (i.e., dyadic error processing) may be associated with symptoms of anxiety and depression. While undergoing simultaneous fMRI scans, healthy dyads completed a task involving feigned errors that indicated their family member made a costly mistake. Inter-brain, random-effects multivariate modeling revealed that parents who exhibited decreased medial prefrontal cortex and posterior cingulate cortex activation when viewing their child's costly error response had children with more symptoms of depression and anxiety. Adolescents with increased anterior insula activation when viewing a costly error made by their parent had more anxious parents. These results reveal cross-brain associations between mental health symptomatology and brain activity during parent-child dyadic error processing

Self-Regulation of Amygdala Activation Using Real-Time fMRI Neurofeedback

Real-time functional magnetic resonance imaging (rtfMRI) with neurofeedback allows investigation of human brain neuroplastic changes that arise as subjects learn to modulate neurophysiological function using real-time feedback regarding their own hemodynamic responses to stimuli. We investigated the feasibility of training healthy humans to self-regulate the hemodynamic activity of the amygdala, which plays major roles in emotional processing. Participants in the experimental group were provided with ongoing information about the blood oxygen level dependent (BOLD) activity in the left amygdala (LA) and were instructed to raise the BOLD rtfMRI signal by contemplating positive autobiographical memories. A control group was assigned the same task but was instead provided with sham feedback from the left horizontal segment of the intraparietal sulcus (HIPS) region. In the LA, we found a significant BOLD signal increase due to rtfMRI neurofeedback training in the experimental group versus the control group. This effect persisted during the Transfer run without neurofeedback. For the individual subjects in the experimental group the training effect on the LA BOLD activity correlated inversely with scores on the Difficulty Identifying Feelings subscale of the Toronto Alexithymia Scale. The whole brain data analysis revealed significant differences for Happy Memories versus Rest condition between the experimental and control groups. Functional connectivity analysis of the amygdala network revealed significant widespread correlations in a fronto-temporo-limbic network. Additionally, we identified six regions — right medial frontal polar cortex, bilateral dorsomedial prefrontal cortex, left anterior cingulate cortex, and bilateral superior frontal gyrus — where the functional connectivity with the LA increased significantly across the rtfMRI neurofeedback runs and the Transfer run. The findings demonstrate that healthy subjects can learn to regulate their amygdala activation using rtfMRI neurofeedback, suggesting possible applications of rtfMRI neurofeedback training in the treatment of patients with neuropsychiatric disorders

Trial of Optimal Personalised Care After Treatment for Gynaecological cancer (TOPCAT-G): a study protocol for a randomised feasibility trial

Background: Gynaecological cancers are diagnosed in over 1000 women in Wales every year. We estimate that this is costing the National Health Service (NHS) in excess of £1 million per annum for routine follow-up appointments alone. Follow-up care is not evidence-based, and there are no definitive guidelines from The National Institute for Health and Care Excellence (NICE) for the type of follow-up that should be delivered. Standard care is to provide a regular medical review of the patient in a hospital-based outpatient clinic for a minimum of 5 years. This study is to evaluate the feasibility of a proposed alternative where the patients are delivered a specialist nurse-led telephone intervention known as Optimal Personalised Care After Treatment for Gynaecological cancer (OPCAT-G), which comprised of a protocol-based patient education, patient empowerment and structured needs assessment. Methods: The study will recruit female patients who have completed treatment for cervical, endometrial, epithelial ovarian or vulval cancer within the previous 3 months in Betsi Cadwaladr University Health Board (BCUHB) in North Wales. Following recruitment, participants will be randomised to one of two arms in the trial (standard care or OPCAT-G intervention). The primary outcomes for the trial are patient recruitment and attrition rates, and the secondary outcomes are quality of life, health status and capability, using the EORTC QLQ-C30, EQ- 5D-3L and ICECAP-A measures. Additionally, a client service receipt inventory (CSRI) will be collected in order to pilot an economic evaluation. Discussion: The results from this feasibility study will be used to inform a fully powered randomised controlled trial to evaluate the difference between standard care and the OPCAT-G intervention. Trial registration: ISRCTN45565436

SCOTROC 2B: feasibility of carboplatin followed by docetaxel or docetaxel–irinotecan as first-line therapy for ovarian cancer

The feasibility of combination irinotecan, carboplatin and docetaxel chemotherapy as first-line treatment for advanced epithelial ovarian carcinoma was assessed. One hundred patients were randomised to receive four 3-weekly cycles of carboplatin (area under the curve (AUC) 7) followed by four 3-weekly cycles of docetaxel 100 mg m−2 (arm A, n=51) or docetaxel 60 mg m−2 with irinotecan 200 mg m−2 (arm B, n=49). Neither arm met the formal feasibility criterion of an eight-cycle treatment completion rate that was statistically greater than 60% (arm A 71% (90% confidence interval (CI) 58–81%; P=0.079; arm B 67% (90% CI 55–78%; P=0.184)). Median-dose intensities were >85% of planned dose for all agents. In arms A and B, 15.6 and 12.2% of patients, respectively, withdrew owing to treatment-related toxicity. Grade 3–4 sensory neurotoxicity was more common in arm A (1.9 vs 0%) and grade 3–4 diarrhoea was more common in arm B (0.6 vs 3.5%). Of patients with radiologically evaluable disease at baseline, 50 and 48% responded to therapy in arms A and B, respectively; at median 17.1 months' follow-up, median progression-free survival was 17.1 and 15.9 months, respectively. Although both arms just failed to meet the formal statistical feasibility criteria, the observed completion rates of around 70% were reasonable. The addition of irinotecan to first-line carboplatin and docetaxel chemotherapy was generally well tolerated although associated with increased gastrointestinal toxicity. Further exploratory studies of topoisomerase-I inhibitors in this setting may be warranted

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning

Practice Induces Function-Specific Changes in Brain Activity

Practice can have a profound effect on performance and brain activity, especially if a task can be automated. Tasks that allow for automatization typically involve repeated encoding of information that is paired with a constant response. Much remains unknown about the effects of practice on encoding and response selection in an automated task.To investigate function-specific effects of automatization we employed a variant of a Sternberg task with optimized separation of activity associated with encoding and response selection by means of m-sequences. This optimized randomized event-related design allows for model free measurement of BOLD signals over the course of practice. Brain activity was measured at six consecutive runs of practice and compared to brain activity in a novel task.Prompt reductions were found in the entire cortical network involved in encoding after a single run of practice. Changes in the network associated with response selection were less robust and were present only after the third run of practice.This study shows that automatization causes heterogeneous decreases in brain activity across functional regions that do not strictly track performance improvement. This suggests that cognitive performance is supported by a dynamic allocation of multiple resources in a distributed network. Our findings may bear importance in understanding the role of automatization in complex cognitive performance, as increased encoding efficiency in early stages of practice possibly increases the capacity to otherwise interfering information

[(18)F]FDG-PET/CT metabolic parameters as useful prognostic factors in cervical cancer patients treated with chemo-radiotherapy.

To compare the prognostic value of different anatomical and functional metabolic parameters determined using [(18)F]FDG-PET/CT with other clinical and pathological prognostic parameters in cervical cancer (CC). Thirty-eight patients treated with standard curative doses of chemo-radiotherapy (CRT) underwent pre- and post-therapy [(18)F]FDG-PET/CT. [(18)F]FDG-PET/CT parameters including mean tumor standardized uptake values (SUV), metabolic tumor volume (MTV) and tumor glycolytic volume (TGV) were measured before the start of CRT. The post-treatment tumor metabolic response was evaluated. These parameters were compared to other clinical prognostic factors. Survival curves were estimated by using the Kaplan-Meier method. Cox regression analysis was performed to determine the independent contribution of each prognostic factor. After 37 months of median follow-up (range, 12-106), overall survival (OS) was 71 % [95 % confidence interval (CI), 54-88], disease-free survival (DFS) 61 % [95 % CI, 44-78] and loco-regional control (LRC) 76 % [95 % CI, 62-90]. In univariate analyses the [(18)F]FDG-PET/CT parameters unfavorably influencing OS, DFS and LRC were pre-treatment TGV-cutoff ≥562 (37 vs. 76 %, p = 0.01; 33 vs. 70 %, p = 0.002; and 55 vs. 83 %, p = 0.005, respectively), mean pre-treatment tumor SUV cutoff ≥5 (57 vs. 86 %, p = 0.03; 36 vs. 88 %, p = 0.004; 65 vs. 88 %, p = 0.04, respectively) and a partial tumor metabolic response after treatment (9 vs. 29 %, p = 0.0008; 0 vs. 83 %, p < 0.0001; 22 vs. 96 %, p < 0.0001, respectively). After multivariate analyses a partial tumor metabolic response after treatment remained as an independent prognostic factor unfavorably influencing DFS and LRC (RR 1:7.7, p < 0.0001, and RR 1:22.6, p = 0.0003, respectively) while the pre-treatment TGV-cutoff ≥562 negatively influenced OS and DFS (RR 1:2, p = 0.03, and RR 1:2.75, p = 0.05). Parameters capturing the pre-treatment glycolytic volume and metabolic activity of [(18)F]FDG-positive disease provide important prognostic information in patients with CC treated with CRT. The post-therapy [(18)F]FDG-PET/CT uptake (partial tumor metabolic response) is predictive of disease outcome