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

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

doi:10.1016/j.ijrobp.2022.04.044

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

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

Research output: Contribution to journal › Article › peer-review

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Abstract

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.

Original language	English (US)
Pages (from-to)	163-172
Number of pages	10
Journal	International Journal of Radiation Oncology Biology Physics
Volume	114
Issue number	1
DOIs	https://doi.org/10.1016/j.ijrobp.2022.04.044
State	Published - Sep 1 2022

Keywords

Calibration
Carcinoma, Pancreatic Ductal/diagnostic imaging
Humans
Pancreatic Neoplasms/diagnostic imaging
Prospective Studies

ASJC Scopus subject areas

Radiation
Oncology
Radiology Nuclear Medicine and imaging
Cancer Research

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10.1016/j.ijrobp.2022.04.044

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Wang, C. X., Elganainy, D., Zaid, M. M., Butner, J. D., Agrawal, A., Nizzero, S., Minsky, B. D., Holliday, E. B., Taniguchi, C. M., Smith, G. L., Koong, A. C., Herman, J. M., Das, P., Maitra, A., Wang, H., Wolff, R. A., Katz, M. H. G., Crane, C. H., Cristini, V., & Koay, E. J. (2022). Mass Transport Model of Radiation Response: Calibration and Application to Chemoradiation for Pancreatic Cancer. International Journal of Radiation Oncology Biology Physics, 114(1), 163-172. https://doi.org/10.1016/j.ijrobp.2022.04.044

Wang, CX, Elganainy, D, Zaid, MM, Butner, JD, Agrawal, A, Nizzero, S, Minsky, BD, Holliday, EB, Taniguchi, CM, Smith, GL, Koong, AC, Herman, JM, Das, P, Maitra, A, Wang, H, Wolff, RA, Katz, MHG, Crane, CH, Cristini, V & Koay, EJ 2022, 'Mass Transport Model of Radiation Response: Calibration and Application to Chemoradiation for Pancreatic Cancer', International Journal of Radiation Oncology Biology Physics, vol. 114, no. 1, pp. 163-172. https://doi.org/10.1016/j.ijrobp.2022.04.044

@article{4c467f85b86f4e3ba6d52ce187ee2a76,

title = "Mass Transport Model of Radiation Response: Calibration and Application to Chemoradiation for Pancreatic Cancer",

abstract = "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.",

keywords = "Calibration, Carcinoma, Pancreatic Ductal/diagnostic imaging, Humans, Pancreatic Neoplasms/diagnostic imaging, Prospective Studies",

author = "Wang, {Charles X.} and Dalia Elganainy and Zaid, {Mohamed M.} and Butner, {Joseph D.} and Anshuman Agrawal and Sara Nizzero and Minsky, {Bruce D.} and Holliday, {Emma B.} and Taniguchi, {Cullen M.} and Smith, {Grace L.} and Koong, {Albert C.} and Herman, {Joseph M.} and Prajnan Das and Anirban Maitra and Huamin Wang and Wolff, {Robert A.} and Katz, {Matthew H.G.} and Crane, {Christopher H.} and Vittorio Cristini and Koay, {Eugene J.}",

note = "Funding Information: We gratefully acknowledge partial support from the Andrew Sabin Family Fellowship, the Sheikh Ahmed Center for Pancreatic Cancer Research, institutional funds from the University of Texas MD Anderson Cancer Center, equipment support from GE Healthcare, and the Center of Advanced Biomedical Imaging, Project Purple, and Cancer Center Support (Core) grant CA016672 from the National Cancer Institute to MD Anderson. E.K. was also supported by the National Institutes of Health (NIH) (U54CA210181-01, U54CA143837, U01CA196403, 5U01CA200468-04, R01CA248917, 5R01CA218004-02, 5U01CA214263-02, 1P50CA221707-01A1, P50 CA217674). V.C. was supported by the National Science Foundation (DMS-1930583) and NIH (1R01CA253865, 1U01CA196403, 1U01CA213759, 1R01CA226537, 1R01CA222007, U54CA210181). Publisher Copyright: {\textcopyright} 2022 The Author(s)",

year = "2022",

month = sep,

day = "1",

doi = "10.1016/j.ijrobp.2022.04.044",

language = "English (US)",

volume = "114",

pages = "163--172",

journal = "International Journal of Radiation Oncology Biology Physics",

issn = "0360-3016",

publisher = "Elsevier",

number = "1",

}

TY - JOUR

T1 - Mass Transport Model of Radiation Response

T2 - Calibration and Application to Chemoradiation for Pancreatic Cancer

AU - Wang, Charles X.

AU - Elganainy, Dalia

AU - Zaid, Mohamed M.

AU - Butner, Joseph D.

AU - Agrawal, Anshuman

AU - Nizzero, Sara

AU - Minsky, Bruce D.

AU - Holliday, Emma B.

AU - Taniguchi, Cullen M.

AU - Smith, Grace L.

AU - Koong, Albert C.

AU - Herman, Joseph M.

AU - Das, Prajnan

AU - Maitra, Anirban

AU - Wang, Huamin

AU - Wolff, Robert A.

AU - Katz, Matthew H.G.

AU - Crane, Christopher H.

AU - Cristini, Vittorio

AU - Koay, Eugene J.

N1 - Funding Information: We gratefully acknowledge partial support from the Andrew Sabin Family Fellowship, the Sheikh Ahmed Center for Pancreatic Cancer Research, institutional funds from the University of Texas MD Anderson Cancer Center, equipment support from GE Healthcare, and the Center of Advanced Biomedical Imaging, Project Purple, and Cancer Center Support (Core) grant CA016672 from the National Cancer Institute to MD Anderson. E.K. was also supported by the National Institutes of Health (NIH) (U54CA210181-01, U54CA143837, U01CA196403, 5U01CA200468-04, R01CA248917, 5R01CA218004-02, 5U01CA214263-02, 1P50CA221707-01A1, P50 CA217674). V.C. was supported by the National Science Foundation (DMS-1930583) and NIH (1R01CA253865, 1U01CA196403, 1U01CA213759, 1R01CA226537, 1R01CA222007, U54CA210181). Publisher Copyright: © 2022 The Author(s)

PY - 2022/9/1

Y1 - 2022/9/1

N2 - 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.

AB - 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.

KW - Calibration

KW - Carcinoma, Pancreatic Ductal/diagnostic imaging

KW - Humans

KW - Pancreatic Neoplasms/diagnostic imaging

KW - Prospective Studies

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JO - International Journal of Radiation Oncology Biology Physics

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

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