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Mass Transport Model of Radiation Response: Calibration and Application to Chemoradiation for Pancreatic Cancer.
Wang, Charles X; Elganainy, Dalia; Zaid, Mohamed M; Butner, Joseph D; Agrawal, Anshuman; Nizzero, Sara; Minsky, Bruce D; Holliday, Emma B; Taniguchi, Cullen M; Smith, Grace L; Koong, Albert C; Herman, Joseph M; Das, Prajnan; Maitra, Anirban; Wang, Huamin; Wolff, Robert A; Katz, Matthew H G; Crane, Christopher H; Cristini, Vittorio; Koay, Eugene J.
Afiliação
  • Wang CX; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Radiation Oncology, University of California Davis Medical Center, Sacramento, California.
  • Elganainy D; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Zaid MM; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Butner JD; Mathematics in Medicine Program, Houston Methodist Research Institute, Houston, Texas.
  • Agrawal A; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Nizzero S; Mathematics in Medicine Program, Houston Methodist Research Institute, Houston, Texas.
  • Minsky BD; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Holliday EB; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Taniguchi CM; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Smith GL; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Koong AC; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Herman JM; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Das P; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Maitra A; Departments of Pathology.
  • Wang H; Anatomical Pathology.
  • Wolff RA; Gastrointestinal Medical Oncology.
  • Katz MHG; Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Crane CH; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York.
  • Cristini V; Mathematics in Medicine Program, Houston Methodist Research Institute, Houston, Texas; Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas; Physiology, Biophysics, and Systems Biology Program, Graduate School of Medical Sciences, Weill Cornell Medicine, New Y
  • Koay EJ; Department of Radiation Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas. Electronic address: ekoay@mdanderson.org.
Int J Radiat Oncol Biol Phys ; 114(1): 163-172, 2022 09 01.
Article em En | MEDLINE | ID: mdl-35643254
PURPOSE: The benefit of radiation therapy for pancreatic ductal adenocarcinoma (PDAC) remains unclear. We hypothesized that a new mechanistic mathematical model of chemotherapy and radiation response could predict clinical outcomes a priori, using a previously described baseline measurement of perfusion from computed tomography scans, normalized area under the enhancement curve (nAUC). METHODS AND MATERIALS: We simplified an existing mass transport model that predicted cancer cell death by replacing previously unknown variables with averaged direct measurements from randomly selected pathologic sections of untreated PDAC. This allowed using nAUC as the sole model input to approximate tumor perfusion. We then compared the predicted cancer cell death to the actual cell death measured from corresponding resected tumors treated with neoadjuvant chemoradiation in a calibration cohort (n = 80) and prospective cohort (n = 25). After calibration, we applied the model to 2 separate cohorts for pathologic and clinical associations: targeted therapy cohort (n = 101), cetuximab/bevacizumab + radiosensitizing chemotherapy, and standard chemoradiation cohort (n = 81), radiosensitizing chemotherapy to 50.4 Gy in 28 fractions. RESULTS: We established the relationship between pretreatment computed v nAUC to pathologically verified blood volume fraction of the tumor (r = 0.65; P = .009) and fractional tumor cell death (r = 0.97-0.99; P < .0001) in the calibration and prospective cohorts. On multivariate analyses, accounting for traditional covariates, nAUC independently associated with overall survival in all cohorts (mean hazard ratios, 0.14-0.31). Receiver operator characteristic analyses revealed discrimination of good and bad prognostic groups in the cohorts with area under the curve values of 0.64 to 0.71. CONCLUSIONS: This work presents a new mathematical modeling approach to predict clinical response from chemotherapy and radiation for PDAC. Our findings indicate that oxygen/drug diffusion strongly influences clinical responses and that nAUC is a potential tool to select patients with PDAC for radiation therapy.
Assuntos

Texto completo: 1 Coleções: 01-internacional Temas: Geral / Prevencao_e_fatores_de_risco / Agentes_cancerigenos / Tipos_de_cancer / Outros_tipos Base de dados: MEDLINE Assunto principal: Neoplasias Pancreáticas / Carcinoma Ductal Pancreático Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Int J Radiat Oncol Biol Phys Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Temas: Geral / Prevencao_e_fatores_de_risco / Agentes_cancerigenos / Tipos_de_cancer / Outros_tipos Base de dados: MEDLINE Assunto principal: Neoplasias Pancreáticas / Carcinoma Ductal Pancreático Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Int J Radiat Oncol Biol Phys Ano de publicação: 2022 Tipo de documento: Article