PURPOSE: Radiotherapy plans based on physical dose distributions do not necessarily entirely reflect the biological effects under various fractionation schemes. Over the past decade, the linear-quadratic (LQ) model has emerged as a convenient tool to quantify biological effects for radiotherapy. In this work, we set out to construct a mechanism to display biologically oriented dose distribution based on the LQ model. METHODS AND MATERIALS: A computer program that converts a physical dose distribution calculated by a commercially available treatment planning system to a biologically effective dose (BED) distribution has been developed and verified against theoretical calculations. This software accepts a user's input of biological parameters for each structure of interest (linear and quadratic dose-response and repopulation kinetic parameters), as well as treatment scheme factors (number of fractions, fractional dose, and treatment time). It then presents a two-dimensional BED display in conjunction with anatomical structures. Furthermore, to facilitate clinicians' intuitive comparison with conventional fractionation regimen, a conversion of BED to normalized isoeffective dose (NID) is also allowed. RESULTS: Two sample cases serve to illustrate the application of our tool in clinical practice. (a) For an orthogonal wedged pair of x-ray beams treating a maxillary sinus tumor, the biological effect at the ipsilateral mandible can be quantified, thus illustrates the so-called "double-trouble" effects very well. (b) For a typical four-field, evenly weighted prostate treatment using 10 MV x-rays, physical dosimetry predicts a comparable dose at the femoral necks between an alternate two-fields/day and four-fields/day setups. However, our BED display reveals an approximate 21% higher BED for the two-fields/day scheme. This excessive dose to the femoral necks can be eliminated if the treatment is delivered with a 3:2 (anterio-posterior/posterio-anterior (AP/PA): bilaterally opposed (BLO)) dose weighting. With Co-60 beams, the increase of BED with alternate two-fields/day, 1:1 setup was even more pronounced (26%). CONCLUSION: We have demonstrated the feasibility of constructing a biologically oriented dose distribution for clinical practice of radiotherapy. The discordance between physical dose distributions and the biological counterparts based on the given treatment schemes was quantified. The computerized display of BED at nonprescription points greatly enhanced the versatility of this tool. Although the routine use of this implementation in clinical radiotherapy should be cautiously done, depending largely on the accuracy of the published biological parameters, it may, nevertheless, help the clinicians derive an optimal treatment plan with a particular fractionation scheme or use it as a quantitative tool for outcome analysis in clinical research.
PURPOSE: Radiotherapy plans based on physical dose distributions do not necessarily entirely reflect the biological effects under various fractionation schemes. Over the past decade, the linear-quadratic (LQ) model has emerged as a convenient tool to quantify biological effects for radiotherapy. In this work, we set out to construct a mechanism to display biologically oriented dose distribution based on the LQ model. METHODS AND MATERIALS: A computer program that converts a physical dose distribution calculated by a commercially available treatment planning system to a biologically effective dose (BED) distribution has been developed and verified against theoretical calculations. This software accepts a user's input of biological parameters for each structure of interest (linear and quadratic dose-response and repopulation kinetic parameters), as well as treatment scheme factors (number of fractions, fractional dose, and treatment time). It then presents a two-dimensional BED display in conjunction with anatomical structures. Furthermore, to facilitate clinicians' intuitive comparison with conventional fractionation regimen, a conversion of BED to normalized isoeffective dose (NID) is also allowed. RESULTS: Two sample cases serve to illustrate the application of our tool in clinical practice. (a) For an orthogonal wedged pair of x-ray beams treating a maxillary sinus tumor, the biological effect at the ipsilateral mandible can be quantified, thus illustrates the so-called "double-trouble" effects very well. (b) For a typical four-field, evenly weighted prostate treatment using 10 MV x-rays, physical dosimetry predicts a comparable dose at the femoral necks between an alternate two-fields/day and four-fields/day setups. However, our BED display reveals an approximate 21% higher BED for the two-fields/day scheme. This excessive dose to the femoral necks can be eliminated if the treatment is delivered with a 3:2 (anterio-posterior/posterio-anterior (AP/PA): bilaterally opposed (BLO)) dose weighting. With Co-60 beams, the increase of BED with alternate two-fields/day, 1:1 setup was even more pronounced (26%). CONCLUSION: We have demonstrated the feasibility of constructing a biologically oriented dose distribution for clinical practice of radiotherapy. The discordance between physical dose distributions and the biological counterparts based on the given treatment schemes was quantified. The computerized display of BED at nonprescription points greatly enhanced the versatility of this tool. Although the routine use of this implementation in clinical radiotherapy should be cautiously done, depending largely on the accuracy of the published biological parameters, it may, nevertheless, help the clinicians derive an optimal treatment plan with a particular fractionation scheme or use it as a quantitative tool for outcome analysis in clinical research.
Authors: Juan Carlos López Alfonso; Jan Poleszczuk; Rachel Walker; Sungjune Kim; Shari Pilon-Thomas; Jose J Conejo-Garcia; Hatem Soliman; Brian Czerniecki; Louis B Harrison; Heiko Enderling Journal: JCO Clin Cancer Inform Date: 2019-04
Authors: R Rockne; J K Rockhill; M Mrugala; A M Spence; I Kalet; K Hendrickson; A Lai; T Cloughesy; E C Alvord; K R Swanson Journal: Phys Med Biol Date: 2010-05-18 Impact factor: 3.609
Authors: Ravinder Nath; William S Bice; Wayne M Butler; Zhe Chen; Ali S Meigooni; Vrinda Narayana; Mark J Rivard; Yan Yu Journal: Med Phys Date: 2009-11 Impact factor: 4.071
Authors: Julie Schatteman; Dirk Van Gestel; Dieter Berwouts; Werner De Gersem; Geert De Kerf; Wilfried De Neve; Bie De Ost; Ana Maria Luiza Olteanu; Sylvie Rottey; Tom Vercauteren; Ingeborg Goethals; Fréderic Duprez Journal: Strahlenther Onkol Date: 2018-03-19 Impact factor: 3.621
Authors: Sarvpreet Singh; Frank R Kloss; Regina Brunauer; Magdalena Schimke; Angelika Jamnig; Brigitte Greiderer-Kleinlercher; Günter Klima; Julia Rentenberger; Thomas Auberger; Oliver Hächl; Michael Rasse; Robert Gassner; Günter Lepperdinger Journal: J Cell Mol Med Date: 2012-04 Impact factor: 5.310
Authors: Ashesh B Jani; Christopher M Hand; Charles A Pelizzari; John C Roeske; Lani Krauz; Srinivasan Vijayakumar Journal: BMC Cancer Date: 2003-05-13 Impact factor: 4.430