PURPOSE: Accurate modeling of rectal complications based on dose-volume histogram (DVH) data are necessary to allow safe dose escalation in radiotherapy of prostate cancer. We applied different equivalent uniform dose (EUD)-based and dose-volume-based normal tissue complication probability (NTCP) models to rectal wall DVHs and follow-up data for 319 prostate cancer patients to identify the dosimetric factors most predictive for Grade > or = 2 rectal bleeding. METHODS AND MATERIALS: Data for 319 patients treated at the William Beaumont Hospital with three-dimensional conformal radiotherapy (3D-CRT) under an adaptive radiotherapy protocol were used for this study. The following models were considered: (1) Lyman model and (2) logit-formula with DVH reduced to generalized EUD, (3) serial reconstruction unit (RU) model, (4) Poisson-EUD model, and (5) mean dose- and (6) cutoff dose-logistic regression model. The parameters and their confidence intervals were determined using maximum likelihood estimation. RESULTS: Of the patients, 51 (16.0%) showed Grade 2 or higher bleeding. As assessed qualitatively and quantitatively, the Lyman- and Logit-EUD, serial RU, and Poisson-EUD model fitted the data very well. Rectal wall mean dose did not correlate to Grade 2 or higher bleeding. For the cutoff dose model, the volume receiving > 73.7 Gy showed most significant correlation to bleeding. However, this model fitted the data more poorly than the EUD-based models. CONCLUSIONS: Our study clearly confirms a volume effect for late rectal bleeding. This can be described very well by the EUD-like models, of which the serial RU- and Poisson-EUD model can describe the data with only two parameters. Dose-volume-based cutoff-dose models performed worse.
PURPOSE: Accurate modeling of rectal complications based on dose-volume histogram (DVH) data are necessary to allow safe dose escalation in radiotherapy of prostate cancer. We applied different equivalent uniform dose (EUD)-based and dose-volume-based normal tissue complication probability (NTCP) models to rectal wall DVHs and follow-up data for 319 prostate cancerpatients to identify the dosimetric factors most predictive for Grade > or = 2 rectal bleeding. METHODS AND MATERIALS: Data for 319 patients treated at the William Beaumont Hospital with three-dimensional conformal radiotherapy (3D-CRT) under an adaptive radiotherapy protocol were used for this study. The following models were considered: (1) Lyman model and (2) logit-formula with DVH reduced to generalized EUD, (3) serial reconstruction unit (RU) model, (4) Poisson-EUD model, and (5) mean dose- and (6) cutoff dose-logistic regression model. The parameters and their confidence intervals were determined using maximum likelihood estimation. RESULTS: Of the patients, 51 (16.0%) showed Grade 2 or higher bleeding. As assessed qualitatively and quantitatively, the Lyman- and Logit-EUD, serial RU, and Poisson-EUD model fitted the data very well. Rectal wall mean dose did not correlate to Grade 2 or higher bleeding. For the cutoff dose model, the volume receiving > 73.7 Gy showed most significant correlation to bleeding. However, this model fitted the data more poorly than the EUD-based models. CONCLUSIONS: Our study clearly confirms a volume effect for late rectal bleeding. This can be described very well by the EUD-like models, of which the serial RU- and Poisson-EUD model can describe the data with only two parameters. Dose-volume-based cutoff-dose models performed worse.
Authors: Werner Bär; Marco Schwarz; Markus Alber; Luc J Bos; Ben J Mijnheer; Coen Rasch; Christoph Schneider; Fridtjof Nüsslin; Eugene M F Damen Journal: Radiother Oncol Date: 2003-12 Impact factor: 6.280
Authors: Stephanie T H Peeters; Mischa S Hoogeman; Wilma D Heemsbergen; Augustinus A M Hart; Peter C M Koper; Joos V Lebesque Journal: Int J Radiat Oncol Biol Phys Date: 2006-06-06 Impact factor: 7.038
Authors: A A Martinez; D Yan; D Lockman; D Brabbins; K Kota; M Sharpe; D A Jaffray; F Vicini; J Wong Journal: Int J Radiat Oncol Biol Phys Date: 2001-08-01 Impact factor: 7.038
Authors: M W Skwarchuk; A Jackson; M J Zelefsky; E S Venkatraman; D M Cowen; S Levegrün; C M Burman; Z Fuks; S A Leibel; C C Ling Journal: Int J Radiat Oncol Biol Phys Date: 2000-04-01 Impact factor: 7.038
Authors: A Jackson; M W Skwarchuk; M J Zelefsky; D M Cowen; E S Venkatraman; S Levegrun; C M Burman; G J Kutcher; Z Fuks; S A Liebel; C C Ling Journal: Int J Radiat Oncol Biol Phys Date: 2001-03-01 Impact factor: 7.038
Authors: Susan L Tucker; Rex Cheung; Lei Dong; H Helen Liu; Howard D Thames; Eugene H Huang; Deborah Kuban; Radhe Mohan Journal: Int J Radiat Oncol Biol Phys Date: 2004-06-01 Impact factor: 7.038
Authors: Luc J Bos; Marco Schwarz; Werner Bär; Markus Alber; Ben J Mijnheer; Joos V Lebesque; Eugène M F Damen Journal: Med Phys Date: 2004-01 Impact factor: 4.071
Authors: Mirko Nitsche; Werner Brannath; Matthias Brückner; Dirk Wagner; Alexander Kaltenborn; Nils Temme; Robert M Hermann Journal: Br J Radiol Date: 2016-12-12 Impact factor: 3.039
Authors: Susan L Tucker; Lei Dong; Walter R Bosch; Jeff Michalski; Kathryn Winter; Radhe Mohan; James A Purdy; Deborah Kuban; Andrew K Lee; M Rex Cheung; Howard D Thames; James D Cox Journal: Int J Radiat Oncol Biol Phys Date: 2010-07-02 Impact factor: 7.038
Authors: Trinitat García Hernández; Aurora Vicedo González; Jorge Pastor Peidro; Juan V Roselló Ferrando; Luis Brualla González; Domingo Granero Cabañero; José López Torrecilla Journal: Rep Pract Oncol Radiother Date: 2013-02-08
Authors: Susan L Tucker; Lei Dong; Jeff M Michalski; Walter R Bosch; Kathryn Winter; James D Cox; James A Purdy; Radhe Mohan Journal: Int J Radiat Oncol Biol Phys Date: 2012-02-17 Impact factor: 7.038
Authors: Oscar Acosta; Gael Drean; Juan D Ospina; Antoine Simon; Pascal Haigron; Caroline Lafond; Renaud de Crevoisier Journal: Phys Med Biol Date: 2013-03-26 Impact factor: 3.609