PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

A Coupled FEM-BEM Approach for the Solution of the Free-Boundary Axi-Symmetric Plasma Equilibrium Problem

In this paper we present a coupled Finite Element Method – Boundary Element Method (FEM-BEM) approach for the solution of the free-boundary axi-symmetric plasma equilibrium problem. The proposed method, obtained from an improvement of the Hagenow-Lackner coupling method, allows to efficiently model the equilibrium problem in unbounded domains by discretizing only the plasma region; the external conductors can be modelled either as 2D or 3D models, according to the problem of interest. The paper explores different iterative methods for the solution of the nonlinear Grad-Shafranov equation, such as Picard, Newton-Raphson and Newton-Krylov, in order to provide a robust and reliable tool, able to handle large-scale problems (e.g. high resolution equilibria). This method has been implemented in the FRIDA code (FRee-boundary Integro-Differential Axisimmetric – https://github. om/matteobonotto/ FRIDA), together with a suitable Adaptive Integration Technique (AIT) for the computation of the source term. FRIDA has been successfully tested and validated against experimental data from RFX-mod device, and numerical equilibria of an ITER-like device.     

Education Outcomes of Children Born Late Preterm: A Retrospective Whole-Population Cohort Study

Maternal and Child Health Journal - Early life exposures can have an impact on a child’s developmental trajectory and children born late preterm (34–36&nbsp;weeks gestational age)...     

Nipple leiomyoma: A rare neoplasm with a broad spectrum of histologic appearances

Cutaneous leiomyomas are rare benign smooth‐muscle tumors. These lesions are distinguished based on their cell of origin and are subclassified as pilar leiomyoma, angioleiomyoma, and genital‐type leiomyoma. Nipple leiomyoma is the least common genital‐type leiomyoma, arising from the dartoic muscle cell of the nipple. Histologic examination of the lesion is necessary for definitive diagnosis, and these uncommon tumors can pose a diagnostic challenge. We describe herein a series of six nipple leiomyomas with a spectrum of histologic appearances.     

Spike‐associated networks and intracranial electrographic findings

Aims. Functional connectivity is providing new insights into the network nature of epilepsy with growing clinical applications. Our objective was to validate a novel magnetoencephalography‐based method to non‐invasively measure the epileptic network. Methods. We retrospectively identified pediatric and adult patients with refractory focal epilepsy who underwent pre‐surgical magnetoencephalography with subsequent intracranial electrographic monitoring. Magnetoencephalography tracings were visually reviewed, and interictal epileptiform discharges (“spikes”) were individually marked. We then evaluated differences in whole‐brain connectivity during brief epochs preceding the spikes and during the spikes using the Network‐Based Statistic to test differences at the network level. Results. In six patients with statistically‐significant network differences, we observed substantial overlap between the spike‐associated networks and electrographically active areas identified during intracranial monitoring (the spike‐associated network was 78% and 83% sensitive for intracranial electroencephalography‐defined regions in the irritative and seizure onset zones, respectively). Conclusion. These findings support the neurobiological validity of the spike‐associated network method. Assessment of spike‐associated networks has the potential to improve surgical planning in epilepsy surgery patients by identifying components of the epileptic network prior to implantation.