Dario Turco

Total renal volume (TRV) is an important quantitative indicator of the progression of autosomal dominant polycystic kidney disease (ADPKD). The Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease proposes a method for TRV computation based on manual tracing and geometric modeling. We developed a fast and nearly-automated technique for kidney segmentation and automatically compute TRV. In this study we aim to compare TRV estimates derived from these two different approaches. The highly-automated technique for the analysis of MR images was tested on 30 ADPKD patients. TRV was computed from both axial and coronal acquisitions, and compared to measurements based on geometric modeling by linear regression and Bland Altman analysis. In addition, to assess reproducibility, intra-observer and inter-observer variabilities were computed. The results of this study provide the feasibility of using a nearly-automated approach for accurate and fast evaluation of TRV also in markedly enlarged ADPKD kidneys.

We recently read and appreciated the paper ‘Novel approach to estimate kidney and cyst volumes using mid-slice magnetic resonance images in polycystic kidney disease' by Bae et al. [1]. The paper is very interesting and we recognize the intensive and very useful work the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) has conducted in the last years on this topic to develop methods to define a surrogate marker of the disease. Indeed, one of the most relevant results of CRISP was the evidence that magnetic resonance (MR) imaging is the best procedure for estimating changes in renal and cystic volume in autosomal dominant polycystic kidney disease over short follow-up periods.

Total renal volume (TRV) and individual renal cysts are important quantitative indicators of the progression of autosomal dominant polycystic kidney disease (ADPKD). TRV has been assessed by manually tracing renal contours from CT or MR scans, often employing contrast media (CM). We developed a fast and nearly automated technique based on the analysis of MR axial images acquired without CM injection for TRV quantification. Twenty ADPKD patients underwent MRI. Automatic extraction of kidney contours was performed on each acquired slice; the segmentation procedure was based on region growing and on the application of morphological operators and curvature-based motion. The area inside each contour was calculated and TRV was derived. Volume measurements were compared between axial and coronal acquisitions. TRV estimated in patients from axial acquisition was 1931±1117ml (range: 428÷4622ml) and from coronal acquisition volumes resulted in 1943±1135ml (range: 393÷4604ml) (p>0.05). These automatic measurements were in excellent correlation (r=0.99, y=1.01×-13.9) with a small bias and narrow limits of agreement in both absolute (-12±93ml) and percentage (-0.2±4.6%) terms. This preliminary study showed TRV from axial and coronal MRI acquisitions can be assessed automatically and with comparable and accurate results without requiring the use of potentially nephrotoxic contrast medium.

Although cardiac resynchronization therapy (CRT) is an effective treatment for chronic systolic heart failure with dyssynchrony, about one-third of patients do not respond favorably. The interaction between the pacing lead and the coronary sinus (CS) branches is of paramount importance for an effective resynchronization. Minor changes in lead position overtime could interfere with CRT mechanics, without affecting even biophysical parameters or ECG morphology. Although late post-implant CS lead dislodgement rate is consistent, lead movements have been little investigated and only with bi-dimensional methods. The aim of this study was (1) to develop a method for quantifying CS lead position in the 3D domain throughout the cardiac cycle and (2) to test it by comparing the CS lead position at implant and at follow-up, using chest fluoroscopy. Method performance, its accuracy and reproducibility were qualitatively and quantitatively assessed. Intra- and inter-observer percent discordance between trajectories were also computed. The accuracy of the procedure resulted in 0.3 ± 0.1 mm and its resolution was 0.5 mm. Intra- and inter-observer discordances were 2.2 ± 1.5 and 5.5 ± 3.6 mm, respectively. The proposed method for measuring the CS lead dynamic placement in 3D space seems accurate and reproducible. Investigating CS lead 3D dynamics could provide further insights into CRT mechanics.