Exploring the longitudinal associations of functional network connectivity and psychiatric symptom changes in youth

Background: Functional connectivity has been associated with psychiatric problems, both in children and adults, but inconsistencies are present across studies. Prior research has mostly focused on small clinical samples with cross-sectional designs. Methods: We adopted a longitudinal design with repeated assessments to investigate associations between functional network connectivity (FNC) and psychiatric problems in youth (9- to 17-year-olds, two time points) from the general population. The largest single-site study of pediatric neurodevelopment was used: Generation R (N = 3,131 with data at either time point). Psychiatric symptoms were measured with the Child Behavioral Checklist as broadband internalizing and externalizing problems, and its eight specific syndrome scales (e.g., anxious-depressed). FNC was assessed with two complementary approaches. First, static FNC (sFNC) was measured with graph theory-based metrics. Second, dynamic FNC (dFNC), where connectivity is allowed to vary over time, was summarized into 5 states that participants spent time in. Cross-lagged panel models were used to investigate the longitudinal bidirectional relationships of sFNC with internalizing and externalizing problems. Similar cross-lagged panel models were run for dFNC. Results: Small longitudinal relationships between dFNC and certain syndrome scales were observed, especially for baseline syndrome scales (i.e., rule-breaking, somatic complaints, thought problems, and attention problems) predicting connectivity changes. However, no association between any of the psychiatric problems (broadband and syndrome scales) with either measure of FNC survived correction for multiple testing. Conclusion: We found no or very modest evidence for longitudinal associations between psychiatric problems with dynamic and static FNC in this population-based sample. Differences in findings may stem from the population drawn, study design, developmental timing, and sample sizes.</p

Spatial Dynamic Subspaces Encode Sex-Specific Schizophrenia Disruptions in Transient Network Overlap and its Links to Genetic Risk

BACKGROUND: Recent advances in resting-state fMRI allow us to study spatial dynamics, the phenomenon of brain networks spatially evolving over time. However, most dynamic studies still use subject-specific, spatially-static nodes. As recent studies have demonstrated, incorporating time-resolved spatial properties is crucial for precise functional connectivity estimation and gaining unique insights into brain function. Nevertheless, estimating time-resolved networks poses challenges due to the low signal-to-noise ratio, limited information in short time segments, and uncertain identification of corresponding networks within and between subjects. METHODS: We adapt a reference-informed network estimation technique to capture time-resolved spatial networks and their dynamic spatial integration and segregation. We focus on time-resolved spatial functional network connectivity (spFNC), an estimate of network spatial coupling, to study sex-specific alterations in schizophrenia and their links to multi-factorial genomic data. RESULTS: Our findings are consistent with the dysconnectivity and neurodevelopment hypotheses and align with the cerebello-thalamo-cortical, triple-network, and frontoparietal dysconnectivity models, helping to unify them. The potential unification offers a new understanding of the underlying mechanisms. Notably, the posterior default mode/salience spFNC exhibits sex-specific schizophrenia alteration during the state with the highest global network integration and correlates with genetic risk for schizophrenia. This dysfunction is also reflected in high-dimensional (voxel-level) space in regions with weak functional connectivity to corresponding networks. CONCLUSIONS: Our method can effectively capture spatially dynamic networks, detect nuanced SZ effects, and reveal the intricate relationship of dynamic information to genomic data. The results also underscore the potential of dynamic spatial dependence and weak connectivity in the clinical landscape

Evaluating the incidence of pathological complete response in current international rectal cancer practice

The mainstay of management for locally advanced rectal cancer is chemoradiotherapy followed by surgical resection. Following chemoradiotherapy, a complete response may be detected clinically and radiologically (cCR) prior to surgery or pathologically after surgery (pCR). We aim to report the overall complete pathological response (pCR) rate and the reliability of detecting a cCR by conventional pre-operative imaging.A pre-planned analysis of the European Society of Coloproctology (ESCP) 2017 audit was performed. Patients treated by elective rectal resection were included. A pCR was defined as a ypT0 N0 EMVI negative primary tumour; a partial response represented any regression from baseline staging following chemoradiotherapy. The primary endpoint was the pCR rate. The secondary endpoint was agreement between post-treatment MRI restaging (yMRI) and final pathological staging.Of 2572 patients undergoing rectal cancer surgery in 277 participating centres across 44 countries, 673 (26.2%) underwent chemoradiotherapy and surgery. The pCR rate was 10.3% (67/649), with a partial response in 35.9% (233/649) patients. Comparison of AJCC stage determined by post-treatment yMRI with final pathology showed understaging in 13% (55/429) and overstaging in 34% (148/429). Agreement between yMRI and final pathology for T-stage, N-stage, or AJCC status were each graded as 'fair' only (n = 429, Kappa 0.25, 0.26 and 0.35 respectively).The reported pCR rate of 10% highlights the potential for non-operative management in selected cases. The limited strength of agreement between basic conventional post-chemoradiotherapy imaging assessment techniques and pathology suggest alternative markers of response should be considered, in the context of controlled clinical trials

The Impact of Body Mass Index on Perioperative Outcomes of Robotic Adrenalectomy: An Update

###EgeUn###Background. Robotic surgery has gained increasing popularity over the past 2 decades. However, factors including patient comorbidities and tumor characteristics are still crucial factors for outcomes of surgery. In this study, we evaluated the impact of body mass index (BMI) on perioperative outcomes in patients who underwent robotic adrenal surgery. Methods. Between May 2012 and November 2017, 66 consecutive patients who underwent robotic adrenalectomy were included in this study. Patients were divided into 2 groups based on their BMI: nonobese (&lt;30 kg/m2) and obese (?30 kg/m2). Additionally, patient demographics, tumor size, total operative time, docking time, console time, estimated blood loss, conversion to open, complications, additional analgesia requirement, length of hospital stay, and rough costs were evaluated. Results. Of the 66 patients, a total of 26 patients were obese (30%). Between study groups, the median BMI was calculated as 26 (18-29) and 33 (30-57). The groups were similar in terms of age, gender, American Society of Anesthesiologists scores, and previous history of abdominal surgery. Likewise, there were no significant differences between groups regarding total operative time (P =.085), docking time (P =.196), console time (P =.211), estimated blood loss (P =.180), complications (P =.991), length of hospital stay (P =.598), and rough costs (P =.468). Five cases were converted to open surgery. Nonobese cases required additional analgesia (P =.007). We had no unexpected hospitalizations in either group. Conclusion. Guidelines express the advantages of robotic surgery in obese patients. No statistically significant differences were detected between the 2 groups except for the additional analgesia required in nonobese patients. © The Author(s) 2019