ABSTRACT
Purpose: Diagnosis and surveillance of thoracic aortic aneurysm (TAA) involves measuring the aortic diameter at various locations along the length of the aorta, often using computed tomography angiography (CTA). Currently, measurements are performed by human raters using specialized software for three-dimensional analysis, a time-consuming process, requiring 15 to 45 min of focused effort. Thus, we aimed to develop a convolutional neural network (CNN)-based algorithm for fully automated and accurate aortic measurements. Approach: Using 212 CTA scans, we trained a CNN to perform segmentation and localization of key landmarks jointly. Segmentation mask and landmarks are subsequently used to obtain the centerline and cross-sectional diameters of the aorta. Subsequently, a cubic spline is fit to the aortic boundary at the sinuses of Valsalva to avoid errors related inclusions of coronary artery origins. Performance was evaluated on a test set of 60 scans with automated measurements compared against expert manual raters. Result: Compared to training separate networks for each task, joint training yielded higher accuracy for segmentation, especially at the boundary (p<0.001), but a marginally worse (0.2 to 0.5 mm) accuracy for landmark localization (p<0.001). Mean absolute error between human and automated was ≤1 mm at six of nine standard clinical measurement locations. However, higher errors were noted in the aortic root and arch regions, ranging between 1.4 and 2.2 mm, although agreement of manual raters was also lower in these regions. Conclusion: Fully automated aortic diameter measurements in TAA are feasible using a CNN-based algorithm. Automated measurements demonstrated low errors that are comparable in magnitude to those with manual raters; however, measurement error was highest in the aortic root and arch.
ABSTRACT
The impact of laparoscopic (vs. open) donor nephrectomy on early graft function and survival in pediatric kidney recipients (< or =18 years) is unknown. We studied 995 pediatric live donor txs reported to UNOS from January 2000 to June 2002, in two recipient age groups: 0-5 years (n = 212, 44% laparoscopic donors [LapD]) and 6-18 years (n = 783, 50% LapD). Delayed graft function (DGF) rates were higher for LapD versus open donor (OpD) txs (0-5 years, 12.8% vs. 2.5% [p = 0.004]; 6-18 years, 5.9% vs. 2.8% [p = 0.03]). Acute rejection incidence for LapD versus OpD txs was higher at 6 months for recipients 0-5 years (18.6% vs. 5.9%, p = 0.01) and 6-18 years (22.5% vs. 15.6%, p = 0.03), and 1 year for recipients 0-5 years (24.3% vs. 7.9%, p = 0.004). In multivariate analyses, significant independent risk factors for rejection at 6 months and 1 year were recipient age 6-18 years, pretx dialysis, LapD nephrectomy and DGF. Graft survival was similar for LapD versus OpD txs. In this retrospective UNOS database analysis, LapD procurement was associated with increased DGF and an independent risk factor for rejection during the first year, particularly for recipients 0-5-years old. Future investigations must confirm these findings and identify strategies to optimize procurement and pediatric recipient outcome.
