title: Comparison between model-predicted tumor oxygenation dynamics and vascular-/flow-related Doppler indices.
abstract: OBJECTIVE
  Mathematical modeling is a powerful and flexible method to investigate complex phenomena. It discloses the possibility of reproducing expensive as well as invasive experiments in a safe environment with limited costs. This makes it suitable to mimic tumor evolution and response to radiotherapy although the reliability of the results remains an issue. Complexity reduction is therefore a critical aspect in order to be able to compare model outcomes to clinical data. Among the factors affecting treatment efficacy, tumor oxygenation is known to play a key role in radiotherapy response. In this work, we aim at relating the oxygenation dynamics, predicted by a macroscale model trained on tumor volumetric data of uterine cervical cancer patients, to vascularization and blood flux indices assessed on Ultrasound Doppler images.
  
  
  METHODS
  We propose a macroscale model of tumor evolution based on three dynamics, namely active portion, necrotic portion, and oxygenation. The model parameters were assessed on the volume size of seven cervical cancer patients administered with 28 fractions of intensity modulated radiation therapy (IMRT) (1.8 Gy/fraction). For each patient, five Doppler ultrasound tests were acquired before, during, and after the treatment. The lesion was manually contoured by an expert physician using 4D View®(General Electric Company - Fairfield, Connecticut, United States), which automatically provided the overall tumor volume size along with three vascularization and/or blood flow indices. Volume data only were fed to the model for training purpose, while the predicted oxygenation was compared a posteriori to the measured Doppler indices.
  
  
  RESULTS
  The model was able to fit the tumor volume evolution within 8% error (range: 3-8%). A strong correlation between the intrapatient longitudinal indices from Doppler measurements and oxygen predicted by the model (about 90% or above) was found in three cases. Two patients showed an average correlation value (50-70%) and the remaining two presented poor correlations. The latter patients were the ones featuring the smallest tumor reduction throughout the treatment, typical of hypoxic conditions. Moreover, the average oxygenation value predicted by the model was close to the average vascularization-flow index (average difference: 7%).
  
  
  CONCLUSIONS
  The results suggest that the modeled relation between tumor evolution and oxygen dynamics was reasonable enough to provide realistic oxygenation curves in five cases (correlation greater than 50%) out of seven. In case of nonresponsive tumors, the model failed in predicting the oxygenation trend while succeeded in reproducing the average oxygenation value according to the mean vascularization-flow index. Despite the need for deeper investigations, the outcomes of the present work support the hypothesis that a simple macroscale model of tumor response to radiotherapy is able to predict the tumor oxygenation. The possibility of an objective and quantitative validation on imaging data discloses the possibility to translate them as decision support tools in clinical practice and to move a step forward in the treatment personalization.
authors.affiliation: Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano University, Piazza Leonardo da Vinci, 32 - 20133, Milan, Italy.
authors.forename: Antonella
authors.initials: A
authors.lastname: Belfatto
authors.affiliation: Preventive Gynecology Unit, Division of Gynecology, European Institute of Oncology, Via Giuseppe Ripamonti, 435 - 20141, Milan, Italy.
authors.forename: Ailyn M
authors.initials: AM
authors.lastname: Vidal Urbinati
authors.affiliation: Department of Radiation Oncology, European Institute of Oncology, Via Giuseppe Ripamonti, 435 - 20141, Milan, Italy.
authors.forename: Delia
authors.initials: D
authors.lastname: Ciardo
authors.affiliation: Preventive Gynecology Unit, Division of Gynecology, European Institute of Oncology, Via Giuseppe Ripamonti, 435 - 20141, Milan, Italy.
authors.forename: Dorella
authors.initials: D
authors.lastname: Franchi
authors.affiliation: Unit of Medical Physics, European Institute of Oncology, Via Giuseppe Ripamonti, 435 - 20141, Milan, Italy.
authors.forename: Federica
authors.initials: F
authors.lastname: Cattani
authors.affiliation: Department of Radiation Oncology, European Institute of Oncology, Via Giuseppe Ripamonti, 435 - 20141, Milan, Italy.
authors.forename: Roberta
authors.initials: R
authors.lastname: Lazzari
authors.affiliation: Department of Radiation Oncology, European Institute of Oncology, Via Giuseppe Ripamonti, 435 - 20141, Milan, Italy.|Department of Oncology and Hemato-oncology, University of Milan, Via Festa del Perdono, 7 - 20122, Milan, Italy.
authors.forename: Barbara A
authors.initials: BA
authors.lastname: Jereczek-Fossa
authors.affiliation: Department of Oncology and Hemato-oncology, University of Milan, Via Festa del Perdono, 7 - 20122, Milan, Italy.|Department of Medical Imaging and Radiation Sciences, European Institute of Oncology, Via Giuseppe Ripamonti, 435 - 20141, Milan, Italy.
authors.forename: Roberto
authors.initials: R
authors.lastname: Orecchia
authors.affiliation: Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano University, Piazza Leonardo da Vinci, 32 - 20133, Milan, Italy.
authors.forename: Guido
authors.initials: G
authors.lastname: Baroni
authors.affiliation: Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano University, Piazza Leonardo da Vinci, 32 - 20133, Milan, Italy.
authors.forename: Pietro
authors.initials: P
authors.lastname: Cerveri
mesh_terms: D000792:Angiography; D005260:Female; D006801:Humans; D010100:Oxygen; D015203:Reproducibility of Results; D047368:Tumor Burden; D018608:Ultrasonography, Doppler; D002583:Uterine Cervical Neoplasms / Q000000981:diagnostic imaging*
chemical_list: D010100:Oxygen
keywords: Doppler; LQ model; cervical cancer; mathematical model; radiosensitivity; radiotherapy; ultrasound