The progression rate of autosomal dominant polycystic kidney disease (ADPKD) to end-stage renal disease (ESRD) is variable and the mechanism of chronic renal failure in ADPKD is not yet clearly defined. A proposed hypothesis is that growth of cysts leads to renal failure by compressing adjacent normal parenchyma. The publication of a large clinical trial on the use of Tolvaptan and some preliminary data on analogs of Somatostatin give to the scientific and patients’ community the hope for a possible therapeutic strategy of slowing the progression of the disease in the next future. In this scenario the availability of an indeces to monitor the disease progression could be extremely useful in the future and potentially help in a correct and effective administration of a therapy.
Our research work on this topic is related to the assessment of clinical parameters like:
Demo of the algorithm developed for polycystic kidney segmentation
A fast and highly-automated technique for kidney segmentation was designed and developed. The method for a fast, safe, and accurate extraction of renal volumes by MRI data without injection of contrast medium was tested and validated on MRI data from patients with ADPKD and normal renal function; importantly, it was applied to axial images and volume measurements were validated by comparison with measurements obtained by stereology. Please refer to this papers for more details [American Journal of Nephrology, 45:373-379, 2017;Academic Radiology, 22(11):1376-84, 2015; American Journal of Nephrology, 33(2):176-184, 2011].
Using the output of the segmentation algorithm, current work is focusing on the development of method for automatic detection of cysts in the detected kidney volume. This represent an important outcome for the evaluation of disease progression since cysts growth is considered to lead to renal failure by compressing adjacent normal parenchyma. An example of the preliminary results is shown in this figure.
A tool has been developed for the evaluation of local residual kidney function from diffusion tensor imaging (DTI) data. Typical diffusion parameters such as mean diffusivity (MD) and fractional anisotropy (FA) among others can be derived using this tool. This new approach could provide a new insight into the progression of the disease. An example of the results for an healthy patiens is shown in the figure.
Related publications
D. Turco, S. Severi, R. Mignani, V. Aiello, R. Magistroni, C. Corsi, Reliability of total renal volume computation in polycystic kidney disease from magnetic resonance imaging, Academic Radiology, 22(11):1376-84, 2015.
R. Mignani, C. Corsi, M. De Marco, E.G. Caiani, G. Santucci , E. Cavagna, S. Severi, L. Cagnoli, Assessment of kidney volume in polycystic kidney disease using magnetic resonance imaging without contrast medium, American Journal of Nephrology, 33(2):176-184, 2011.
D. Turco, S. Severi, R. Mignani, R. Magistroni, C. Corsi, Geometry-independent assessment of renal volume in polycystic kidney disease from magnetic resonance imaging, EMBC 2015, Milano, 25-29 August 2015, in press.
D. Turco, C. Corsi, S. Severi, R. Mignani, Assessment of kidney volumes in polycystic kidney disease from coronal and axial MR images, International Symposium on Image and Signal Processing and Analysis“ (ISPA 2013), Trieste 4-6 Settembre 2013.
