Applicability of Deep Learning to Dynamically Identify the Different Organs of the Pelvic Floor in the Midsagittal Plane.

INTRODUCTION AND HYPOTHESIS: The objective was to create and validate the usefulness of a convolutional neural network (CNN) for identifying different organs of the pelvic floor in the midsagittal plane via dynamic ultrasound. METHODS: This observational and prospective study included 110 patients. Transperineal ultrasound scans were performed by an expert sonographer of the pelvic floor. A video of each patient was made that captured the midsagittal plane of the pelvic floor at rest and the change in the pelvic structures during the Valsalva maneuver. After saving the captured videos, we manually labeled the different organs in each video. Three different architectures were tested-UNet, FPN, and LinkNet-to determine which CNN model best recognized anatomical structures. The best model was trained with the 86 cases for the number of epochs determined by the stop criterion via cross-validation. The Dice Similarity Index (DSI) was used for CNN validation. RESULTS: Eighty-six patients were included to train the CNN and 24 to test the CNN. After applying the trained CNN to the 24 test videos, we did not observe any failed segmentation. In fact, we obtained a DSI of 0.79 (95% CI: 0.73 - 0.82) as the median of the 24 test videos. When we studied the organs independently, we observed differences in the DSI of each organ. The poorest DSIs were obtained in the bladder (0.71 [95% CI: 0.70 - 0.73]) and uterus (0.70 [95% CI: 0.68 - 0.74]), whereas the highest DSIs were obtained in the anus (0.81 [95% CI: 0.80 - 0.86]) and levator ani muscle (0.83 [95% CI: 0.82 - 0.83]). CONCLUSIONS: Our results show that it is possible to apply deep learning using a trained CNN to identify different pelvic floor organs in the midsagittal plane via dynamic ultrasound.

Approaches for the Prediction of Leaf Wetness Duration with Machine Learning.

The prediction of leaf wetness duration (LWD) is an issue of interest for disease prevention in coffee plantations, forests, and other crops. This study analyzed different LWD prediction approaches using machine learning and meteorological and temporal variables as the models' input. The information was collected through meteorological stations placed in coffee plantations in six different regions of Costa Rica, and the leaf wetness duration was measured by sensors installed in the same regions. The best prediction models had a mean absolute error of around 60 min per day. Our results demonstrate that for LWD modeling, it is not convenient to aggregate records at a daily level. The model performance was better when the records were collected at intervals of 15 min instead of 30 min.

Un «corazón» en el corazón: agenesia parcial del pericardio / A "heart" within a heart: partial absence of the pericardium

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Fibroelastoma papilar recurrente. ¿Es realmente un tumor benigno? / Recurrent cardiac fibroelastoma. is it really a benign tumor?

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Management of residual shunts after initial percutaneous patent foramen ovale closure: a single center experience with immediate and long-term follow-up.

BACKGROUND: Moderate-to-large residual shunts following percutaneous patent foramen ovale (PFO) closure are clinically important and associated with recurrent neuroembolic events. However, their management has not been clearly established in clinical practice. We report our experience in patients of these patients with a prior history of cryptogenic stroke and/or transient ischemic attack (TIA). METHODS: All patients undergoing percutaneous PFO closure were routinely screened at six-months for residual shunts using transthoracic 2D echocardiography with antecubital administration of agitated saline contrast and color flow Doppler. Patients with evidence of moderate-to-large residual shunts were selected to undergo reintervention with shunt closure. Post-reintervention follow-up was performed at 24-hr, 30 days, and every six months thereafter. Clinical predictors of the moderate-to-large residual shunts, and the feasibility, safety and long-term efficacy of percutaneous residual shunt closure using a second device implant were examined. RESULTS: Between 1995 and 2007, a total of 424 patients underwent PFO closure. Of these, 5% (21/424) had moderate-to-large residual shunts. Baseline characteristics among patients with moderate-to-large residual shunts and those with only none or small defects (n = 403) were similar. Multivariate analysis identified the 24-hr postprocedure shunt as the only independent predictor of residual shunting at six months. Of the 21 study patients with moderate-to-large residual shunt (mean age, 47 +/- 14), one underwent successful elective surgical repair, while the remaining 20 underwent transcatheter closure using a second device. The technique was successful in 95% (19/20), and all but one patient had complete shunt closure at six months of their percutaneous reintervention. We report no deaths, recurrent strokes or TIAs during the long-term mean follow-up period of 2.9 years. CONCLUSIONS: Our study suggests that in patients with moderate-to-large residual PFO shunts, percutaneous reintervention using a second device implant is safe and effective.