title: Dosimetric assessment of prostate cancer patients through principal component analysis (PCA).
abstract: The aims of this study were twofold: first, to determine the impact of variance in dose-volume histograms (DVH) on patient-specific toxicity after 2 high-dose fractions in a sample of 22 men with prostate cancer; and second, to compare the effectiveness of traditional DVH analysis and principal component analysis (PCA) in predicting rectum and urethra toxicity. A series of 22 patients diagnosed with prostate adenocarcinoma was treated with 45 Gy external beam and 20 Gy dose rate brachytherapy. Principal component analysis was applied to model the shapes of the rectum and urethra dose-volume histograms. We used logistic regression to measure the correlations between the principal components and the incidence of rectal bleeding and urethra stricture. We also calculated the equivalent uniform dose (EUD) and normal tissue complication probability (NTCP) for the urethra and rectum, and tumor control probability (TCP) for the prostate using BioSuite software. We evaluated their correlations with rectal and urethra toxicity. The rectum DVHs are well described by one principal component (PC1), which accounts for 93.5% of the variance in their shapes. The urethra DVHs are described by two principal components, PC1 and PC2, which account for 94.98% and 3.15% of the variance, respectively. Multivariate exact logistic regression suggests that urethra PC2 is a good predictor of stricture, with Nagelkerke's R2 estimated at 0.798 and a Wald criterion of 5.421 (p &lt; 0.021). The average NTCPs were 0.06% ± 0.04% and 1.25% ± 0.22% for the rectum and urethra, respectively. The average TCP was 85.29% ± 2.28%. This study suggests that principal component analysis can be used to identify the shape variation in dose-volume histograms, and that the principal components can be correlated with the toxicity of a treatment plan based on multivariate analysis. The principal components are also correlated with traditional dosimetric parameters.
authors: Department of Radiation Oncology, St Vincent Hospital, Green Bay, WI 54307, USA. agloi@stvgb.org
authors: Aime M
authors: AM
authors: Gloi
authors: Robert
authors: R
authors: Buchanan
mesh_terms: D003198:Computer Simulation; D006801:Humans; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D058958:Organs at Risk / Q000528:radiation effects*; D025341:Principal Component Analysis; D011471:Prostatic Neoplasms / Q000503:physiopathology* / Q000532:radiotherapy*; D011874:Radiometry / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D016896:Treatment Outcome