@article{HolubyevBratengeierGaineyetal.2013,
  author    = {Holubyev, Konstyantyn and Bratengeier, Klaus and Gainey, Mark and Polat, B{\"u}lent and Flentje, Michael},
  title     = {Towards automated on-line adaptation of 2-Step IMRT plans: QUASIMODO phantom and prostate cancer cases},
  series = {Radiation Oncology},
  journal   = {Radiation Oncology},
  doi       = {10.1186/1748-717X-8-263},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-96818},
  year      = {2013},
  abstract  = {Background The standard clinical protocol of image-guided IMRT for prostate carcinoma introduces isocenter relocation to restore the conformity of the multi-leaf collimator (MLC) segments to the target as seen in the cone-beam CT on the day of treatment. The large interfractional deformations of the clinical target volume (CTV) still require introduction of safety margins which leads to undesirably high rectum toxicity. Here we present further results from the 2-Step IMRT method which generates adaptable prostate IMRT plans using Beam Eye View (BEV) and 3D information. Methods Intermediate/high-risk prostate carcinoma cases are treated using Simultaneous Integrated Boost at the Universit{\"a}tsklinkum W{\"u}rzburg (UKW). Based on the planning CT a CTV is defined as the prostate and the base of seminal vesicles. The CTV is expanded by 10 mm resulting in the PTV; the posterior margin is limited to 7 mm. The Boost is obtained by expanding the CTV by 5 mm, overlap with rectum is not allowed. Prescription doses to PTV and Boost are 60.1 and 74 Gy respectively given in 33 fractions. We analyse the geometry of the structures of interest (SOIs): PTV, Boost, and rectum, and generate 2-Step IMRT plans to deliver three fluence steps: conformal to the target SOIs (S0), sparing the rectum (S1), and narrow segments compensating the underdosage in the target SOIs due to the rectum sparing (S2). The width of S2 segments is calculated for every MLC leaf pair based on the target and rectum geometry in the corresponding CT layer to have best target coverage. The resulting segments are then fed into the DMPO optimizer of the Pinnacle treatment planning system for weight optimization and fine-tuning of the form, prior to final dose calculation using the collapsed cone algorithm. We adapt 2-Step IMRT plans to changed geometry whilst simultaneously preserving the number of initially planned Monitor Units (MU). The adaptation adds three further steps to the previous isocenter relocation: 1) 2-Step generation for the geometry of the day using the relocated isocenter, MU transfer from the planning geometry; 2) Adaptation of the widths of S2 segments to the geometry of the day; 3) Imitation of DMPO fine-tuning for the geometry of the day. Results and conclusion We have performed automated 2-Step IMRT adaptation for ten prostate adaptation cases. The adapted plans show statistically significant improvement of the target coverage and of the rectum sparing compared to those plans in which only the isocenter is relocated. The 2-Step IMRT method may become a core of the automated adaptive radiation therapy system at our department.},
  language  = {en}
}
@article{BratengeierHolubyev2016,
  author    = {Bratengeier, Klaus and Holubyev, Kostyantyn},
  title     = {Anisotropy of dose contributions-an instrument to upgrade real time IMRT and VMAT adaptation?},
  series = {Medical Physics},
  volume    = {43},
  journal   = {Medical Physics},
  number    = {11},
  doi       = {10.1118/1.4963806},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-186833},
  pages     = {5826-5834},
  year      = {2016},
  abstract  = {Purpose: To suggest a definition of dose deposition anisotropy for the purpose of ad hoc adaptation of intensity modulated arc therapy (IMRT) and volumetric arc therapy (VMAT), particularly in the vicinity of important organs at risk (OAR), also for large deformations. Methods: Beam's-eye-view (BEV) based fluence warping is a standard adaptation method with disadvantages for strongly varying OAR shapes. 2-Step-adaptation overcomes these difficulties by a deeper analysis of the 3D properties of adaptation processes, but requires separate arcs for every OAR to spare, which makes it impractical for cases with multiple OARs. The authors aim to extend the 2-Step method to arbitrary intensity modulated plan by analyzing the anisotropy of dose contributions. Anisotropy was defined as a second term of Fourier transformation of gantry angle dependent dose contributions. For a cylindrical planning target volume (PTV) surrounding an OAR of varying diameter, the anisotropy and the dose-normalized anisotropy were analyzed for several scenarios of optimized fluence distributions. 2-Step adaptation to decreasing and increasing OAR diameter was performed, and compared to a usual fluence based adaptation method. For two clinical cases, prostate and neck, the VMAT was generated and the behavior of anisotropy was qualitatively explored for deformed organs at risk. \# Results: Dose contribution anisotropy in the PTV peaks around nearby OARs. The thickness of the "anisotropy wall" around OAR increases for increasing OAR radius, as also does the width of 2-Step dose saturating fluence peak adjacent to the OAR K. Bratengeier et al., "A comparison between 2-Step IMRT and conventional IMRT planning," Radiother. Oncol. 84, 298-306 (2007)]. Different optimized beam fluence profiles resulted in comparable radial dependence of normalized anisotropy. As predicted, even for patient cases, anisotropy was inflated even more than increasing diameters of OAR. Conclusions: For cylindrically symmetric cases, the dose distribution anisotropy defined in the present work implicitly contains adaptation-relevant information about 3D relationships between PTV and OAR and degree of OAR sparing. For more complex realistic cases, it shows the predicted behavior qualitatively. The authors claim to have found a first component for advancing a 2-Step adaptation to a universal adaptation algorithm based on the BEV projection of the dose anisotropy. Further planning studies to explore the potential of anisotropy for adaptation algorithms using phantoms and clinical cases of differing complexity will follow.},
  language  = {en}
}