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Mass Transport Model of Radiation Response: Calibration and Application to Chemoradiation for Pancreatic Cancer

Authors :
Charles X. Wang
Dalia Elganainy
Mohamed M. Zaid
Joseph D. Butner
Anshuman Agrawal
Sara Nizzero
Bruce D. Minsky
Emma B. Holliday
Cullen M. Taniguchi
Grace L. Smith
Albert C. Koong
Joseph M. Herman
Prajnan Das
Anirban Maitra
Huamin Wang
Robert A. Wolff
Matthew H.G. Katz
Christopher H. Crane
Vittorio Cristini
Eugene J. Koay
Source :
International Journal of Radiation Oncology*Biology*Physics. 114:163-172
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

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).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.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.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.

Details

ISSN :
03603016
Volume :
114
Database :
OpenAIRE
Journal :
International Journal of Radiation Oncology*Biology*Physics
Accession number :
edsair.doi.dedup.....9c0e16682a1bf2960d29dc9dd1b8d1fb
Full Text :
https://doi.org/10.1016/j.ijrobp.2022.04.044