A Precise calculation of bladder wall thickness for detection of bladder abnormalities via MR cystography

Bladder cancer is reported to be the fifth leading cause of cancer deaths in the United States. Recent advances in medical imaging technologies, such as magnetic resonance (MR) imaging, make virtual cystoscopy a potential alternative to the clinical optical cystoscopy with advantages as being a safe and non-invasive method for evaluation of the entire bladder and detection of abnormalities. To help reduce the interpretation time and reading fatigue of the readers or radiologists using MR virtual cystoscopy, a computer-aided detection scheme is widely employed, where the thickness mapping of the bladder wall is recognized as a biomarker since locally-thickened bladder wall often appears around abnormalities or tumors. So the detection precision and sensitivity are critically determined by the accuracy of the thickness calculation. In our previous thickness mapping method, a distance transform (DT) method was used to approximate the thickness calculation. This DT method ensures that the path used to measure the thickness can be determined without any ambiguity by tracing the gradient direction of the DT. But it has limitations in accuracy because of the approximation. In this work, we presented an accurate and efficient calculation of the wall thickness by tracing the path of electric field lines between the inner and outer borders of the wall. The resulted path therefore represents a precise length for the thickness mapping. This scheme was experimented on both phantoms and patient datasets. The results are preliminary but very promising with an efficient running speed (14.6 minutes for a 130×130×130 data) and a noticeable improvement in accuracy.