The sinoatrial node initiates the heartbeat and controls the rate and rhythm of contraction, thus serving as the pacemaker of the heart. Despite the crucial role of the sinoatrial node in heart function, the mechanisms that underlie its specification and formation are not known. Tbx3, a transcriptional repressor required for development of vertebrates, is expressed in the developing conduction system. Here we show that Tbx3 expression delineates the sinoatrial node region, which runs a gene expression program that is distinct from that of the bordering atrial cells. We found lineage segregation of Tbx3-negative atrial and Tbx3-positive sinoatrial node precursor cells as soon as cardiac cells turn on the atrial gene expression program. Tbx3 deficiency resulted in expansion of expression of the atrial gene program into the sinoatrial node domain, and partial loss of sinoatrial node-specific gene expression. Ectopic expression of Tbx3 in mice revealed that Tbx3 represses the atrial phenotype and imposes the pacemaker phenotype on the atria. The mice displayed arrhythmias and developed functional ectopic pacemakers. These data identify a Tbx3-dependent pathway for the specification and formation of the sinoatrial node, and show that Tbx3 regulates the pacemaker gene expression program and phenotype.[Keywords: Heart development; pacemaker; sinoatrial node; lineage; Tbx3; transgenic mice] Supplemental material is available at http://www.genesdev.org.
Purpose To present a fully automatic method to estimate the corneal endothelium parameters from specular microscopy images and to use it to study a one-year follow-up after ultrathin Descemet stripping automated endothelial keratoplasty. Methods We analyzed 383 post ultrathin Descemet stripping automated endothelial keratoplasty images from 41 eyes acquired with a Topcon SP-1P specular microscope at 1, 3, 6, and 12 months after surgery. The estimated parameters were endothelial cell density (ECD), coefficient of variation (CV), and hexagonality (HEX). Manual segmentation was performed in all images. Results Our method provided an estimate for ECD, CV, and HEX in 98.4% of the images, whereas Topcon's software had a success rate of 71.5% for ECD/CV and 30.5% for HEX. For the images with estimates, the percentage error in our method was 2.5% for ECD, 5.7% for CV, and 5.7% for HEX, whereas Topcon's software provided an error of 7.5% for ECD, 17.5% for CV, and 18.3% for HEX. Our method was significantly better than Topcon's ( P < 0.0001) and was not statistically significantly different from the manual assessments ( P > 0.05). At month 12, the subjects presented an average ECD = 1377 ± 483 [cells/mm 2 ], CV = 26.1 ± 5.7 [%], and HEX = 58.1 ± 7.1 [%]. Conclusions The proposed method obtains reliable and accurate estimations even in challenging specular images of pathologic corneas. Translational Relevance CV and HEX, not currently used in the clinic owing to a lack of reliability in automatic methods, are useful biomarkers to analyze the postoperative healing process. Our accurate estimations allow now for their clinical use.
Corneal endothelium images obtained by in vivo specular microscopy provide important information to assess the health status of the cornea. Estimation of clinical parameters, such as cell density, polymegethism, and pleomorphism, requires accurate cell segmentation. State-of-the-art techniques to automatically segment the endothelium are error-prone when applied to images with low contrast and/or large variation in cell size. Here, we propose an automatic method to segment the endothelium. Starting with an oversegmented image comprised of superpixels obtained from a stochastic watershed segmentation, the proposed method uses intensity and shape information of the superpixels to identify and merge those that constitute a cell, using support vector machines. We evaluated the automatic segmentation on a data set of in vivo specular microscopy images (Topcon SP-1P), obtaining 95.8% correctly merged cells and 2.0% undersegmented cells. We also evaluated the parameter estimation against the results of the vendor's built-in software, obtaining a statistically significant better precision in all parameters and a similar or better accuracy. The parameter estimation was also evaluated on three other data sets from different imaging modalities (confocal microscopy, phase-contrast microscopy, and fluorescence confocal microscopy) and tissue types (ex vivo corneal endothelium and retinal pigment epithelium). In comparison with the estimates of the data sets' authors, we achieved statistically significant better accuracy and precision in all parameters except pleomorphism, where a similar accuracy and precision were obtained.
Clinical parameters related to the corneal endothelium can only be estimated by segmenting endothelial cell images. Specular microscopy is the current standard technique to image the endothelium, but its low SNR make the segmentation a complicated task. Recently, we proposed a method to segment such images by starting with an oversegmented image and merging the superpixels that constitute a cell. Here, we show how our merging method provides better results than optimizing the segmentation itself. Furthermore, our method can provide accurate results despite the degree of the initial oversegmentation, resulting into a precision and recall of 0.91 for the optimal oversegmentation.
Purpose: To describe the learning curve for Descemet's membrane endothelial keratoplasty (DMEK) in the Rotterdam Eye Hospital and to evaluate safety and visual outcome. Methods: This was a single-centre prospective study of 40 consecutive patients with Fuchs' endothelial dystrophy who underwent a DMEK procedure in the Rotterdam Eye Hospital. The performance of two corneal surgeons, each conducting their first series of 20 procedures, was examined with the cumulative summation test for the learning curve (LC-CUSUM). The surgical procedure was considered unsuccessful when >30% of the graft was not attached at any time during the first 12 postoperative weeks and a mixture of SF 6 (20%) and air (80%) had to be injected in the anterior chamber (rebubbling) to reattach the graft. Also assessed were visual outcome, intraocular pressure and peri-and postoperative complications. Results: In total, nine rebubbling procedures were performed in seven eyes. Following repeated rebubbling, two eyes did not achieve a satisfactory result and secondary surgery was required to restore visual function. Complications were usually manageable. The last 13 DMEK procedures (33%) of this series did not require rebubbling. After 3 months, 86% of the eyes had reached a Snellen visual acuity of 0.5 or more. Conclusion: Together with the two surgeons' personal experience, the aggregate learning curve was considered to justify incorporation of Descemet membrane endothelial keratoplasty as a regular option of the standard of care for endothelial dysfunction in the Rotterdam Eye Hospital.Key words: cornea surgery -cumulative summation test for the learning curve -descemet membrane endothelial keratoplasty -learning curve Acta Ophthalmol. 2020: 98: 74-79
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