مدل‌سازی محاسباتی دارورسانی با تزریق داخل‌صفاقی برای درمان درگیری‌های صفاقی سرطان

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه تبدیل انرژی، دانشکده مهندسی مکانیک، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران

چکیده

شیمی‌درمانی با تزریق داخل‌صفاقی یکی از روش‌های امیدبخش برای درمان متاستازهای صفاقی است که استفاده از آن به همراه جراحی سایتوریداکتیو نتایج خوبی را برای درمان این بیماری نشان داد‌ه‌‌است. با این وجود، نفوذ دارو به تومور در این روش محدود است و نیاز به مطالعه این روش شیمی‌درمانی به منظور رسیدن به یک فهم بهتر از دلایل این عمق نفوذ کم وجود دارد. بدین منظور در مقاله پیش رو یک مدل عددی برای بررسی دارورسانی در تزریق داخل‌صفاقی توسعه داده شده‌است. با استفاده از این مدل ابتدا توزیع فضا-زمانی غلظت داوری آزاد، متصل‌شده و واردشده به سلول سرطانی محاسبه شده‌است. سپس با محاسبه درصد عمق نفوذ دارو و کسر سلول‌های کشته‌‌‌شده میزان اثربخشی درمان ارزیابی شده‌است. نتایج برای یک تومور با قطر 10 میلی‌متر پس از 60 دقیقه درمان نشان داد دارو تنها در ناحیه محدودی در مرز بیرونی تومور در دسترس است. مقادیر کسر سلول‌های کشته‌شده و درصد عمق نفوذ دارو به ترتیب %1/2 و%11/4 به دست آمد که نشان از ضعیف بودن بازدهی این روش دارد. یافته‌های این مقاله می‌تواند به منظور دستیابی به بینش عمیق‌تر در مورد مکانیزم‌های انتقال دارو به تومور در تزریق داخل‌صفاقی در مطالعات عددی و تجربی آینده مورد استفاده قرارگیرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Computational Modeling of Intraperitoneal Drug Delivery for the Treatment of Peritoneal Carcinomatosis

نویسندگان [English]

  • Mohsen Rezaeian
  • Majid Soltani
Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
چکیده [English]

Intraperitoneal injection of chemotherapy has been proposed as a promising method for the treatment of peritoneal metastasis, and its use in conjunction with cytoreductive surgery has shown interesting results in the treatment of patients. However, drug penetration into the tumor is limited in this method, and a better understanding of the factors influencing this low penetration depth is necessary. For this purpose, in the present study, a numerical model has been developed to investigate drug transport during intraperitoneal chemotherapy. Using this model, first, the Spatio-temporal distribution of free, bound and internalized drug concentrations are calculated. Then, by calculating the drug penetration depth and the fraction of killed cells, the effectiveness of the treatment is evaluated. Results of a 10mm tumor after 60 minutes of treatment showed that the drug is available only in a limited area of the outer region of the tumor. The values of fraction of killed cells and drug penetration depth were 1.2% and 11.4%, respectively, which indicates a poor treatment efficiency. The findings of this paper can be used in future numerical and experimental studies to gain a deeper insight into the mechanisms of drug delivery to the tumor by intraperitoneal injection.

کلیدواژه‌ها [English]

  • Drug delivery
  • Peritoneal carcinomatosis
  • Numerical modeling
  • Chemotherapy
  • Intraperitoneal injection
[1] P. Favoriti, G. Carbone, M. Greco, F. Pirozzi, R.E.M. Pirozzi, F. Corcione, Worldwide burden of colorectal cancer: a review, Updates in surgery, 68(1) (2016) 7-11.
[2] A. Burges, B. Schmalfeldt, Ovarian cancer: diagnosis and treatment, Deutsches Ärzteblatt International, 108(38) (2011) 635.
[3] B. Sadeghi, C. Arvieux, O. Glehen, A.C. Beaujard, M. Rivoire, J. Baulieux, E. Fontaumard, A. Brachet, J.L. Caillot, J.L. Faure, Peritoneal carcinomatosis from non‐gynecologic malignancies: results of the EVOCAPE 1 multicentric prospective study, Cancer: Interdisciplinary International Journal of the American Cancer Society, 88(2) (2000) 358-363.
[4] G. Montori, F. Coccolini, M. Ceresoli, F. Catena, N. Colaianni, E. Poletti, L. Ansaloni, The treatment of peritoneal carcinomatosis in advanced gastric cancer: state of the art, International journal of surgical oncology, 2014 (2014).
[5] D. Sloothaak, B. Mirck, C. Punt, W. Bemelman, J. Van Der Bilt, A. D’Hoore, P. Tanis, Intraperitoneal chemotherapy as adjuvant treatment to prevent peritoneal carcinomatosis of colorectal cancer origin: a systematic review, British journal of cancer, 111(6) (2014) 1112-1121.
[6] A.A. Wright, A. Cronin, D.E. Milne, M.A. Bookman, R.A. Burger, D.E. Cohn, M.C. Cristea, J.J. Griggs, N.L. Keating, C.F. Levenback, Use and effectiveness of intraperitoneal chemotherapy for treatment of ovarian cancer, Journal of Clinical Oncology, 33(26) (2015) 2841.
[7] F. Quénet, D. Elias, L. Roca, D. Goéré, L. Ghouti, M. Pocard, O. Facy, C. Arvieux, G. Lorimier, D. Pezet, Cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy versus cytoreductive surgery alone for colorectal peritoneal metastases (PRODIGE 7): a multicentre, randomised, open-label, phase 3 trial, The Lancet Oncology, 22(2) (2021) 256-266.
[8] A. Bhatt, Management of peritoneal metastases-cytoreductive surgery, HIPEC and beyond, Springer, 2018.
[9] L. Bijelic, T.D. Yan, P.H. Sugarbaker, Failure analysis of recurrent disease following complete cytoreduction and perioperative intraperitoneal chemotherapy in patients with peritoneal carcinomatosis from colorectal cancer, Annals of Surgical Oncology, 14(8) (2007) 2281-2288.
[10] I. Königsrainer, P. Horvath, F. Struller, V. Forkl, A. Königsrainer, S. Beckert, Risk factors for recurrence following complete cytoreductive surgery and HIPEC in colorectal cancer-derived peritoneal surface malignancies, Langenbeck's archives of surgery, 398(5) (2013) 745-749.
[11] T.R. Van Oudheusden, H. Grull, P.Y.W. Dankers, I.H.J.T. De Hingh, Targeting the peritoneum with novel drug delivery systems in peritoneal carcinomatosis: a review of the literature, Anticancer research, 35(2) (2015) 627-634.
[12] L.A. Lambert, Looking up: recent advances in understanding and treating peritoneal carcinomatosis, CA: a cancer journal for clinicians, 65(4) (2015) 283-298.
[13] F.M. Kashkooli, M. Soltani, M. Souri, C. Meaney, M. Kohandel, Nexus between in silico and in vivo models to enhance clinical translation of nanomedicine, Nano Today, 36 (2021) 101057.
[14] L. De Smet, W. Ceelen, J.P. Remon, C. Vervaet, Optimization of drug delivery systems for intraperitoneal therapy to extend the residence time of the chemotherapeutic agent, The Scientific World Journal, 2013 (2013).
[15] K. Hirano, C.A. Hunt, A. Strubbe, R.D. MacGregor, Lymphatic transport of liposome-encapsulated drugs following intraperitoneal administration–effect of lipid composition, Pharmaceutical research, 2(6) (1985) 271-278.
[16] S. Siavashy, M. Soltani, F. Ghorbani-Bidkorbeh, N. Fallah, G. Farnam, S.A. Mortazavi, F.H. Shirazi, M.H.H. Tehrani, M.H. Hamedi, Microfluidic platform for synthesis and optimization of chitosan-coated magnetic nanoparticles in cisplatin delivery, Carbohydrate Polymers, 265 (2021) 118027.
[17] M. Soltani, M.H. Tehrani, F.M. Kashkooli, M. Rezaeian, Effects of magnetic nanoparticle diffusion on microwave ablation treatment: A numerical approach, Journal of Magnetism and Magnetic Materials, 514 (2020) 167196.
[18] F. Moradi Kashkooli, M. Soltani, M.H. Hamedi, Image-based numerical model for drug delivery to solid tumors, Amirkabir Journal of Mechanical Engineering, 53(5 (Special Issue)) (2021) 5-5.
[19] M. Rezaeian, M. Soltani, F. Moradi Kashkooli, On the Modeling of Drug Delivery to Solid Tumors; Computational Viewpoint, in:  International Conference on Applied Mathematics, Modeling and Computational Science, Springer, 2019, pp. 601-610.
[20] M. Steuperaert, C. Debbaut, C. Carlier, O. De Wever, B. Descamps, C. Vanhove, W. Ceelen, P. Segers, A 3D CFD model of the interstitial fluid pressure and drug distribution in heterogeneous tumor nodules during intraperitoneal chemotherapy, Drug delivery, 26(1) (2019) 404-415.
[21] J.L.-S. Au, P. Guo, Y. Gao, Z. Lu, M.G. Wientjes, M. Tsai, M.G. Wientjes, Multiscale tumor spatiokinetic model for intraperitoneal therapy, The AAPS journal, 16(3) (2014) 424-439.
[22] M. Steuperaert, G. Falvo D’Urso Labate, C. Debbaut, O. De Wever, C. Vanhove, W. Ceelen, P. Segers, Mathematical modeling of intraperitoneal drug delivery: simulation of drug distribution in a single tumor nodule, Drug delivery, 24(1) (2017) 491-501.
[23] M. Shamsi, A. Sedaghatkish, M. Dejam, M. Saghafian, M. Mohammadi, A. Sanati-Nezhad, Magnetically assisted intraperitoneal drug delivery for cancer chemotherapy, Drug delivery, 25(1) (2018) 846-861.
[24] F.M. Kashkooli, M. Soltani, M.-H. Hamedi, Drug delivery to solid tumors with heterogeneous microvascular networks: Novel insights from image-based numerical modeling, European Journal of Pharmaceutical Sciences, 151 (2020) 105399.
[25] L.T. Baxter, R.K. Jain, Transport of fluid and macromolecules in tumors: III. Role of binding and metabolism, Microvascular research, 41(1) (1991) 5-23.
[26] M. Sefidgar, M. Soltani, K. Raahemifar, M. Sadeghi, H. Bazmara, M. Bazargan, M.M. Naeenian, Numerical modeling of drug delivery in a dynamic solid tumor microvasculature, Microvascular research, 99 (2015) 43-56.
[27] A. Sedaghatkish, M. Rezaeian, H. Heydari, A.M. Ranjbar, M. Soltani, Acoustic streaming and thermosensitive liposomes for drug delivery into hepatocellular carcinoma tumor adjacent to major hepatic veins; an acoustics–thermal–fluid-mass transport coupling model, International Journal of Thermal Sciences, 158 (2020) 106540.
[28] F.M. Kashkooli, M. Soltani, M. Rezaeian, C. Meaney, M.-H. Hamedi, M. Kohandel, Effect of vascular normalization on drug delivery to different stages of tumor progression: In-silico analysis, Journal of Drug Delivery Science and Technology, 60 (2020) 101989.
[29] L.T. Baxter, R.K. Jain, Transport of fluid and macromolecules in tumors. I. Role of interstitial pressure and convection, Microvascular research, 37(1) (1989) 77-104.
[30] F.M. Kashkooli, M. Soltani, M. Rezaeian, E. Taatizadeh, M.-H. Hamedi, Image-based spatio-temporal model of drug delivery in a heterogeneous vasculature of a solid tumor—Computational approach, Microvascular research, 123 (2019) 111-124.
[31] W. Deen, Hindered transport of large molecules in liquid‐filled pores, AICHE journal, 33(9) (1987) 1409-1425.
[32] Y. Boucher, L.T. Baxter, R.K. Jain, Interstitial pressure gradients in tissue-isolated and subcutaneous tumors: implications for therapy, Cancer research, 50(15) (1990) 4478-4484.
[33] M. Rezaeian, A. Sedaghatkish, M. Soltani, Numerical modeling of high-intensity focused ultrasound-mediated intraperitoneal delivery of thermosensitive liposomal doxorubicin for cancer chemotherapy, Drug delivery, 26(1) (2019) 898-917.
[34] L.T. Baxter, R.K. Jain, Transport of fluid and macromolecules in tumors. II. Role of heterogeneous perfusion and lymphatics, Microvascular research, 40(2) (1990) 246-263.
[35] M. Sefidgar, M. Soltani, K. Raahemifar, H. Bazmara, S.M.M. Nayinian, M. Bazargan, Effect of tumor shape, size, and tissue transport properties on drug delivery to solid tumors, Journal of biological engineering, 8(1) (2014) 1-13.
[36] M. Soltani, P. Chen, Numerical modeling of fluid flow in solid tumors, PloS one, 6(6) (2011) e20344.
[37] C.-Y. Chou, W.-I. Chang, T.-L. Horng, W.-L. Lin, Numerical modeling of nanodrug distribution in tumors with heterogeneous vasculature, Plos one, 12(12) (2017) e0189802.
[38] T. Stylianopoulos, E.-A. Economides, J.W. Baish, D. Fukumura, R.K. Jain, Towards optimal design of cancer nanomedicines: Multi-stage nanoparticles for the treatment of solid tumors, Annals of biomedical engineering, 43(9) (2015) 2291-2300.
[39] W. Zhan, X.Y. Xu, A mathematical model for thermosensitive liposomal delivery of doxorubicin to solid tumour, Journal of drug delivery, 2013 (2013).
[40] F. Mpekris, J.W. Baish, T. Stylianopoulos, R.K. Jain, Role of vascular normalization in benefit from metronomic chemotherapy, Proceedings of the National Academy of Sciences, 114(8) (2017) 1994-1999.
[41] D. Kerr, A. Kerr, R. Freshney, S. Kaye, Delivery of molecular and cellular medicine to solid tumors, Biochem Pharmacol, 35 (1986) 12817-12823.