Numerical analysis of a model of organ motion using serial imaging measurements from prostate radiotherapy

• Published in: Physics in medicine & biology 2001-09, Vol.46 (9), p.2337-2358
• Main Authors: Fontenla, E, Pelizzari, C A, Roeske, J C, Chen, G T Y
• Format: Article
• Language: English
• Subjects: Algorithms; Biological and medical sciences; Biological organs; Computer Simulation; Databases as Topic; Diseases of the urinary system; Humans; Image Processing, Computer-Assisted; Male; Mathematical models; Medical imaging; Medical sciences; Models, Statistical; Models, Theoretical; Nephrology. Urinary tract diseases; Numerical analysis; Prostate - radiation effects; Prostatic Neoplasms - radiotherapy; Radiometry - methods; Radiotherapy; Radiotherapy - methods; Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects); Rectum - radiation effects; Statistical methods; Tumors of the urinary system; Urinary Bladder - radiation effects; Urinary tract. Prostate gland
• ISSN: 0031-9155; 1361-6560
• DOI: 10.1088/0031-9155/46/9/305

We previously proposed a model for incorporating the effects of organ motion, including the changes in organ shape, into the calculation of dose in a statistical fashion based on serial imaging measurements of organ motion. In the present paper, numerical studies were used to investigate how the accuracy of the statistical calculation of dose depends on the number of organ motion measurements provided as input into the model. The dose calculated statistically with the model was consistently more accurate than the one obtained by directly resampling the serial measurements of organ motion. It was also more robust relative to the random variabilities present in the input organ motion measurements. The results confirm that the model can reproduce the statistical distribution of the organ motions measured in a serial imaging study, including the changes in organ shape, without making any assumptions about the functional form of this distribution. The model allows a more accurate calculation of dose to be performed from a given number of measurements of organ motion than would otherwise be obtained by directly resampling the measured data. It thus maximizes the information that is extracted from serial imaging measurements.