title: Treatment planning comparison between conformal radiotherapy and helical tomotherapy in the case of locally advanced-stage NSCLC.
abstract: OBJECTIVE
  To investigate the impact of Helical Tomotherapy (HT) upon the dose distribution when compared to our routinely delivered 3D conformal radiotherapy (CRT) in the case of patients affected by stage III non-small-cell lung cancer (NSCLC).
  
  
  METHODS
  Thirteen stage III inoperable NSCLC patients were scheduled to receive 61.2-70.2Gy, 1.8Gy/fraction. Two treatment techniques (HT and CRT) were considered, and in the case of CRT the dose calculation was performed using both the pencil beam (PB) and Anisotropic Analytical Algorithm (AAA) available on the Varian Eclipse planning system. Dose volume constraints for PTV coverage and OAR sparing were assessed for the HT inverse planning with the highest priority upon PTV coverage and spinal cord sparing. The three plans were compared in terms of dose-volume histograms (DVHs) and normal tissue complication probability (NTCP). A statistical analysis was performed using non-parametric Wilcoxon matched pairs tests.
  
  
  RESULTS
  In CRT the use of a less accurate algorithm (PB) decreased the monitor unit number by 2.4%. HT significantly improved dose homogeneity within PTV compared with CRT_AAA. For lung parenchyma V20-V40 were lower with HT, corresponding to a decrease of 7% in the risk of radiation pneumonitis. The volume of the heart and esophagus irradiated to >45-60Gy were reduced using HT plans. For eight PTs with an esophagus-PTV overlap >5%, HT significantly reduced both late and acute esophageal complication probability.
  
  
  CONCLUSIONS
  Our findings obtained in stage III NSCLC patients underline that HT guarantees an important sparing of lungs and esophagus, thus HT has the potential to improve therapeutic ratio, when compared with CRT, by means of dose escalation and/or combined treatment strategy. In CRT of locally advanced lung cancers, the use of a more advanced algorithm would give significantly better modeling of target dose and coverage.
authors.affiliation: Medical Physics, University of Milano Bicocca, Milano, Italy. cattaneo.mauro@hsr.it
authors.forename: Giovanni Mauro
authors.initials: GM
authors.lastname: Cattaneo
authors.forename: Italo
authors.initials: I
authors.lastname: Dell'oca
authors.forename: Sara
authors.initials: S
authors.lastname: Broggi
authors.forename: Claudio
authors.initials: C
authors.lastname: Fiorino
authors.forename: Lucia
authors.initials: L
authors.lastname: Perna
authors.forename: Marcella
authors.initials: M
authors.lastname: Pasetti
authors.forename: Giulia
authors.initials: G
authors.lastname: Sangalli
authors.forename: Nadia
authors.initials: N
authors.lastname: di Muzio
authors.forename: Ferruccio
authors.initials: F
authors.lastname: Fazio
authors.forename: Riccardo
authors.initials: R
authors.lastname: Calandrino
mesh_terms: D000368:Aged; D000465:Algorithms; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D008297:Male; D008875:Middle Aged; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D020266:Radiotherapy, Conformal / Q000379:methods*; D018709:Statistics, Nonparametric; D036542:Tomography, Spiral Computed; D016896:Treatment Outcome