Backgound: The placement of stents in coronary arteries has been shown to reduce acute closure and restenosis in comparison to balloon angioplasty. However, clinical use of intracoronary stents is impeded by the subacute stent thrombosis and hemorrhagic complications associated with the anticoagulant regimen. It's known that the complete stent deployment with high pressure inflation and new antiplatelet agents are effective in reduction of subacute thrombosis and hemorrhage. So we evaluated initial results (success and complication rate) after high pressure-stent deployment with new anticoagulation protocol. METHODS: One hundred and ninety one patients with 201 lesions were treated with 231 stents of various types. The high pressure balloon inflation and antiplatelets agents were used in all cases. Final high pressure balloon inflation guided by IVUS were performed in 23 consecutive cases with incomplete stent deployment according to angiographic findings. RESULTS: 1) The indications of stenting (n=210) were De novo in 124 (59%), bailout procedure in 57 (27%), suboptimal result after PTCA in 19 (8%), and restenosis after PTCA in 14 (6%). The location of lesions were LAD in 101, RCA in 67, circumflex in 28, ramus intermedius in 3, and LMT artery in 2 lesions. Angiographic morphologic characteristics were type A in 2, type B in 158 (B1: 57, B2: 101), and type C in 22 lesions. 2) The angiographic and clinical success rate was 96% (192/201) and 92% (186/201) respectively. 3) In angiographic analysis, the baseline average reference vessel dirmeter was 3.33+/-0.35 mm. Baseline minimum lumen diameter (MLD) was 0.58+/-0.29 mm, with baseline percent diameter stenosis of 82.86+/-8.64%. The final stent diameter was 3.37+/-0.29 mm, with mean final percent stenosis of 0.63+/-8.25. The mean MLD after stenting was significantly increased (p<0.001). The mean MLD within stent increased 14%, from 2.91+/-0.39 mm at the nominal balloon inflation (inflation pressure=7 atm) to 3.37+/-0.29 mm at high pressure balloon inflation (inflation pressure <0A65B>12atm) (p<0.001). The length of lesions in GR I (cook), GR II, and Micro II stents were significantly longer than ones in PS, Cordis, Wiktor, Nir (p<0.001). 4) In intravascular ultrasound analysis, the mean lumen CSA at the tightest point within stent increased 11%, from 8.4+/-2.4 mm2 at the intial intravascular ultrasound to 9.4+/-2.1 mm2 at the final intravascular ultrasound (p<0.001). 5) The procedural and postprocedural complications were 2 acute closures associated with AMI and emergent CABG, 1 subacute closure which was revascularized by bail out stenting, 5 major hemorrhage requiring transfusion associated with 1 CVA and 2 metabolic acidosis induced by acute renal failure, and 5 death. CONCLUSION: The high pressure stent deployment procedure and new anticoagulation protocol associating tidopidine and aspirin without coumadin or prolonged heparin infusion allow us to obtain an acceptably low subacute thrombosis or bleeding complication rate. These results are encouraging and allow a wide use of coronary stenting.
Acidosis ; Acute Kidney Injury ; Angioplasty, Balloon ; Arteries ; Aspirin ; Constriction, Pathologic ; Coronary Vessels* ; Hemorrhage ; Heparin ; Humans ; Inflation, Economic ; Platelet Aggregation Inhibitors* ; Stents* ; Thrombosis ; Ultrasonography ; Warfarin

BACKGROUND: Dopamine is an inotropic agent that is often selected for continuous infusion. For hemodynamic stability, the rate of infusion is controlled in the range of 5-15 µg/kg/min. This study aimed to compare the time intervals from the administration of dopamine to the onset of its hemodynamic effects when dopamine was administered through three different peripheral veins (the cephalic vein [CV], the great saphenous vein [GSV], and the external jugular vein [EJV]). METHODS: Patients in group 1, group 2, and group 3 received dopamine infusions in the CV, GSV, and EJV, respectively. A noninvasive continuous cardiac output monitor (NICCOMO™, Medis, Ilmenau, Germany) was used to assess cardiac output (CO) and systemic vascular resistance (SVR). Six minutes after intubation, baseline heart rate (HR), systolic blood pressure (BP), diastolic BP, mean arterial pressure (MAP), CO, and SVR values were recorded and dopamine infusion was initiated at a dose of 10 µg/kg/min. Hemodynamic changes at 0, 4, 8, 12, and 15 minutes postinfusion were recorded. RESULTS: No statistically significant differences were observed among the three groups with respect to the rate of hemodynamic change. In all groups, systolic BP, diastolic BP, MAP, and SVR tended to increase after decreasing for the first 4 minutes; in contrast, HR and CO decreased until 8 minutes, after which they tended to reach a plateau. CONCLUSIONS: For patients under general anesthesia receiving dopamine at 10 µg/kg/min, there were no clinical differences in the effect of dopamine administered through three different peripheral veins.
Anesthesia, General ; Arterial Pressure ; Blood Pressure ; Cardiac Output ; Dopamine* ; Heart Rate ; Hemodynamics* ; Humans ; Intubation ; Jugular Veins ; Saphenous Vein ; Vascular Resistance ; Veins*

Ambulatory BP monitoring was performed in a patients with pheochromocytoma before and after removal of the tumor. Before surgery, it did not show any significant diurnal variation. But, after surgery the diurnal variation was restored.
Blood Pressure Monitoring, Ambulatory* ; Blood Pressure* ; Humans ; Pheochromocytoma*

No abstract available.
Pregnancy*

Purpose: This study aimed to develop a new convolutional neural network-based deep learning (DL) technique for automated brain tissue segmentation from computed tomographic (CT) scans and to evaluate its performance in comparison to magnetic resonance imaging (MRI)-derived segmentations. Materials and Methods: This multicenter retrospective study collected paired CT and MRI data from 199 healthy individuals across two institutions. The data were divided into a training set (n = 100) and an internal test set (n = 50) from one institution, with additional datasets (n = 49) from the second institution for external validation. Ground truth masks for gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) were generated from T1-weighted MR images. A U-Net-based DL model was trained for each of the three brain regions, with a perceptual loss computed from VGG19. Model performance was evaluated by calculating continuous Dice coefficient (cDice), intersection-over-union (IOU), and 95th percentile Hausdorff distance (HD95). Volumetric estimates from CT-based segmentations were compared with MRI-derived volumes using the coefficient of determination (R2 ), intraclass correlation coefficients (ICC), and Bland-Altman analysis. Results: The DL network trained with the perceptual loss showed superior performance, compared with that trained without the perceptual loss. In internal tests, evaluation scores (without perceptual loss vs. with perceptual loss) were: cDice = 0.717 vs. 0.765 and HD95 = 6.641 mm vs. 6.314 mm in GM; cDice = 0.730 vs. 0.767 and HD95 = 5.841 mm vs. 5.644 mm in WM; and cDice = 0.600 vs. 0.630 and HD95 = 5.641 mm vs. 5.362 mm in CSF, respectively. Volumetric analyses revealed strong agreement between MRI-derived ground truth and CT-based segmentations with R2 = 0.83/0.90 and 0.85/0.87, and ICC = 0.91/0.94 and 0.92/0.93 for GM and WM, respectively, in internal/external tests. Conclusion The proposed DL method, enhanced with perceptual loss, improves brain tissue segmentation from CT images. This approach shows promise as an alternative to MRIbased segmentation.

Purpose: This study aimed to develop a new convolutional neural network-based deep learning (DL) technique for automated brain tissue segmentation from computed tomographic (CT) scans and to evaluate its performance in comparison to magnetic resonance imaging (MRI)-derived segmentations. Materials and Methods: This multicenter retrospective study collected paired CT and MRI data from 199 healthy individuals across two institutions. The data were divided into a training set (n = 100) and an internal test set (n = 50) from one institution, with additional datasets (n = 49) from the second institution for external validation. Ground truth masks for gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) were generated from T1-weighted MR images. A U-Net-based DL model was trained for each of the three brain regions, with a perceptual loss computed from VGG19. Model performance was evaluated by calculating continuous Dice coefficient (cDice), intersection-over-union (IOU), and 95th percentile Hausdorff distance (HD95). Volumetric estimates from CT-based segmentations were compared with MRI-derived volumes using the coefficient of determination (R2 ), intraclass correlation coefficients (ICC), and Bland-Altman analysis. Results: The DL network trained with the perceptual loss showed superior performance, compared with that trained without the perceptual loss. In internal tests, evaluation scores (without perceptual loss vs. with perceptual loss) were: cDice = 0.717 vs. 0.765 and HD95 = 6.641 mm vs. 6.314 mm in GM; cDice = 0.730 vs. 0.767 and HD95 = 5.841 mm vs. 5.644 mm in WM; and cDice = 0.600 vs. 0.630 and HD95 = 5.641 mm vs. 5.362 mm in CSF, respectively. Volumetric analyses revealed strong agreement between MRI-derived ground truth and CT-based segmentations with R2 = 0.83/0.90 and 0.85/0.87, and ICC = 0.91/0.94 and 0.92/0.93 for GM and WM, respectively, in internal/external tests. Conclusion The proposed DL method, enhanced with perceptual loss, improves brain tissue segmentation from CT images. This approach shows promise as an alternative to MRIbased segmentation.

Purpose: This study aimed to develop a new convolutional neural network-based deep learning (DL) technique for automated brain tissue segmentation from computed tomographic (CT) scans and to evaluate its performance in comparison to magnetic resonance imaging (MRI)-derived segmentations. Materials and Methods: This multicenter retrospective study collected paired CT and MRI data from 199 healthy individuals across two institutions. The data were divided into a training set (n = 100) and an internal test set (n = 50) from one institution, with additional datasets (n = 49) from the second institution for external validation. Ground truth masks for gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) were generated from T1-weighted MR images. A U-Net-based DL model was trained for each of the three brain regions, with a perceptual loss computed from VGG19. Model performance was evaluated by calculating continuous Dice coefficient (cDice), intersection-over-union (IOU), and 95th percentile Hausdorff distance (HD95). Volumetric estimates from CT-based segmentations were compared with MRI-derived volumes using the coefficient of determination (R2 ), intraclass correlation coefficients (ICC), and Bland-Altman analysis. Results: The DL network trained with the perceptual loss showed superior performance, compared with that trained without the perceptual loss. In internal tests, evaluation scores (without perceptual loss vs. with perceptual loss) were: cDice = 0.717 vs. 0.765 and HD95 = 6.641 mm vs. 6.314 mm in GM; cDice = 0.730 vs. 0.767 and HD95 = 5.841 mm vs. 5.644 mm in WM; and cDice = 0.600 vs. 0.630 and HD95 = 5.641 mm vs. 5.362 mm in CSF, respectively. Volumetric analyses revealed strong agreement between MRI-derived ground truth and CT-based segmentations with R2 = 0.83/0.90 and 0.85/0.87, and ICC = 0.91/0.94 and 0.92/0.93 for GM and WM, respectively, in internal/external tests. Conclusion The proposed DL method, enhanced with perceptual loss, improves brain tissue segmentation from CT images. This approach shows promise as an alternative to MRIbased segmentation.

PURPOSE: To determine the learning curve of dacryocystorhinostomy (DCR) performed by a single oculoplastic surgeon after one year of fellowship training. METHODS: This retrospective review study comprised nasolacrimal duct obstruction patients that underwent endonasal DCR at our hospital between February 2006 and February 2008. The patients that completed at least six months of follow-up were included in the analysis. Exclusion criteria were patients less than 20 years of age and NLD obstructions due to malignancy or canalicular obstructions. Success was defined as duct patency on syringing at the final follow-up and no complaints of epiphora. RESULTS: Out of 161 eyes, the overall surgical success rate was 83.2% (134/161 eyes) and the mean postoperative follow-up period was 6.5 months (6-18 months). Success rates gradually increased as follows: 71.2% (37/52 eyes) for the first group, 88.7% (47/53 eyes) for the second group, and 89.3% (50/56 eyes) for the third group (second and third group compared to first group, p = 0.025, p = 0.017, respectively). CONCLUSIONS: To ensure high DCR success rates, the novice surgeon should perform at least 50 surgeries.
Dacryocystorhinostomy ; Dietary Sucrose ; Eye ; Fellowships and Scholarships ; Follow-Up Studies ; Humans ; Learning ; Learning Curve ; Nasolacrimal Duct ; Retrospective Studies

PURPOSE: To investigate the effects of commodified growth factor products used clinically on fibrovascular ingrowth into porous polyethylene orbital implants. METHODS: Porous polyethylene orbital implant sheets (Medpor(R)) soaked with Nepidermin (Easyef(R)), Trafermin (Fiblast(R)), and normal saline were implanted into the backs of 18 Sprague-Dawley rats. The degree of fibrovascular ingrowth as observed using a light microscope was compared 1 and 2 weeks after implantation and was calculated as a percentage of the fibrovascular ingrowth length. RESULTS: One week after implantation, the percentage of fibrovascular ingrowth length was 25.33 +/- 5.43%, 22.56 +/- 5.30%, and 21.78 +/- 4.66% in the Easyef(R)-, Fiblast(R)- and normal saline-soaked groups. The degree of fibrovascularization was higher in the Easyef(R)-soaked group than in the other groups (p = 0.020, 0.012). Two weeks after implantation, the degree of fibrovascularization was 98.33 +/- 5.00%, 100.00 +/- 0.00%, and 95.89 +/- 4.57%, which was significantly higher in the Easyef(R)-, and Fiblast(R)-soaked groups than in normal saline-soaked group (p = 0.019, <0.001). CONCLUSIONS: Commodified growth factor products used in other areas selectively enhanced fibrovascular ingrowth to a greater degree and earlier in ophthalmic plastic and reconstructive surgery.
Epidermal Growth Factor ; Fibroblast Growth Factor 2 ; Orbital Implants* ; Plastics ; Polyethylene* ; Rats, Sprague-Dawley

Xeroderma pigmentosum is rare autosomal recessive disease, characterized by extreme sensitivity to ultraviolet light and leading to development of multiple malignant skin tumors. Among multiple malignant skin tumors, basal cell carcinoma and squamous cell carcinoma are common. Treatments of xeroderma pigmentosum are palliative or radiation treatment, but surgical resection is necessary if xeroderma pigmentosum is transited to malignant skin tumors. We report a case of a 32-years-old female xeroderma pigmentosum patient, who developed radiation resistant basal cell carcinoma on right alar nasi. Radiaton theraphy(300cGy, fractions: 10, total dose: 3000cGy) was not effective, so surgical excision and local skin flap coverage was made and no specific wound complications occurred. During 11 months follow-up period, no evidence of recurrence was found.
Carcinoma, Basal Cell* ; Carcinoma, Squamous Cell ; Female ; Follow-Up Studies ; Humans ; Ichthyosis* ; Recurrence ; Skin ; Ultraviolet Rays ; Wounds and Injuries ; Xeroderma Pigmentosum*