Subretinal fluid morphology in chronic central serous chorioretinopathy and its relationship to treatment: a retrospective analysis on PLACE trial data

Purpose To explore subretinal fluid (SRF) morphology in chronic central serous chorioretinopathy (cCSC) after one session of either high-density subthreshold micropulse laser (HSML) treatment or half-dose photodynamic therapy (PDT).Methods We retrospectively obtained optical coherence tomography (OCT) scans from a subset of patients from a randomized controlled trial on treatment-naive eyes with cCSC allocated to either HSML treatment or half-dose PDT. OCT scans were evaluated prior to treatment and 6-8 weeks post-treatment, where we measured maximum SRF height and width, calculated the maximum height-to-maximum width-ratio (maxHWR) and calculated the total SRF volume.Results Forty-one eyes of 39 cCSC patients were included. SRF morphology ranged from flat to dome-shaped, quantified as maxHWR ranging between 0.02 and 0.12. SRF volume was median 0.373 mu l (range: 0.010-4.425 mu l) and did not correlate to maxHWR (rho = -0.004, p = 0.982). Half-dose PDT was superior to HSML treatment in complete SRF resolution (RR = 3.28, p = 0.003) and in morphological changes of SRF (Delta(maximum height), p = 0.001; Delta(maximum width), p < 0.001; Delta(volume), p = 0.025). SRF resolved completely in 19/22 PDT-treated eyes (86%) and 5/19 HSML-treated eyes (26%). SRF volume increased in five eyes (26%) after HSML treatment, and in none of the eyes after half-dose PDT. SRF morphology at baseline did not predict treatment outcomes.Conclusion SRF morphology changed after both HSML treatment and half-dose PDT in cCSC, with SRF disappearing in most PDT-treated patients, whereas SRF volume increased in a sizeable proportion of HSML-treated patients. Baseline SRF characteristics measured in this study were unable to predict outcomes after either HSML treatment or half-dose PDT

An overview of the Upper Paleozoic-Mesozoic stratigraphy of the NE Atlantic region

This study describes the distribution and stratigraphic range of the Upper Paleozoic–Mesozoic succession in the NE Atlantic region, and is correlated between conjugate-margins and along the axis of the NE Atlantic rift system. The stratigraphic framework has yielded important new constraints on the timing and nature of sedimentary basin development in the NE Atlantic, with implications for rifting and the breakup of the Pangaean supercontinent. From a regional perspective, the Permian–Triassic succession records a northward transition from an arid interior to a passively-subsiding, mixed carbonate/siliciclastic shelf margin. A Late Permian–earliest Triassic rift pulse has regional expression in the stratigraphic record. A fragmentary paralic to shallow-marine Lower Jurassic succession reflects Early Jurassic thermal subsidence and mild extensional tectonism; this was interrupted by widespread Mid-Jurassic uplift and erosion, and followed by an intense phase of Late Jurassic rifting in some (but not all) parts of the NE Atlantic region. The Cretaceous succession is dominated by thick basinal-marine deposits, which accumulated within and along a broad zone of extension and subsidence between Rockall and NE Greenland. There is no evidence for a substantive and continuous rift system along the proto-NE Atlantic until the Late Cretaceous

Sequential design of computer experiments for the estimation of a probability of failure

This paper deals with the problem of estimating the volume of the excursion set of a function $f:\mathbb{R}^d \to \mathbb{R}$ above a given threshold, under a probability measure on $\mathbb{R}^d$ that is assumed to be known. In the industrial world, this corresponds to the problem of estimating a probability of failure of a system. When only an expensive-to-simulate model of the system is available, the budget for simulations is usually severely limited and therefore classical Monte Carlo methods ought to be avoided. One of the main contributions of this article is to derive SUR (stepwise uncertainty reduction) strategies from a Bayesian-theoretic formulation of the problem of estimating a probability of failure. These sequential strategies use a Gaussian process model of $f$ and aim at performing evaluations of $f$ as efficiently as possible to infer the value of the probability of failure. We compare these strategies to other strategies also based on a Gaussian process model for estimating a probability of failure.Comment: This is an author-generated postprint version. The published version is available at http://www.springerlink.co