A thousand words about the challenges of photodynamic therapy

Challenges of photodynamic therapy





photodynamic therapy, cancer, computer simulation


The outbreak of interest in photodynamic therapy (PDT) at the end of last century to treat cancer and other diseases was based on the promise of localised treatment, cheaper therapy and fast ablation of the treated organ. One of the most attractive features of PDT is that it can evade cancer’s resistance to photosensitisers. PDT for cancer therapy depends on the absorption of a photosensitiser within the malignant tissue. The photosensitising drug is then activated by light (usually from a laser) and the active drug destroys the targeted tissue. However, one must consider that this is a complex mechanism involving many factors such as the diverse light and oxygen distribution in the treated organs, which has mitigated application of this technique in clinical practice. PDT is not a simple treatment that can be done by eyeballing; it requires precise planning that can be done with the help of complex computer programs. Computer simulation of PDT to optimise treatment depends heavily on intense calculations in all steps of the procedure, and desktop computers are only now sufficiently powerful to assist physicians during therapy in real-time. In this mini-review, the challenges of photodynamic therapy are described, and possible to solutions to overcome these are presented.


Download data is not yet available.


Bozzini G, et al. Focal therapy of prostate cancer: energies and procedures. Urol Oncol. 2013;31(2):155–167.

Dolmans DE, Fukumura D, Jain RK. Photodynamic therapy for cancer. Nat Rev Cancer. 2003;3(5):380–387.

Gheewala T, Skwor T, Munirathinam G. Photosensitizers in prostate cancer therapy. Oncotarget. 2017;8(18):30524–30538.

Zhang X, Liu T, Li Z, Zhang X. Progress of photodynamic therapy applications in the treatment of musculoskeletal sarcoma (Review). Oncol Lett 8(4):1403–1408.

Liu LY, Man XX, Yao HX, Tan YY. Effects of pheophorbide a‑mediated photodynamic therapy on proliferation and metastasis of human prostate cancer cells. Eur Rev Med Pharmacol Sci. 2017;21(24):5571–5579.

Bhattarai P, Liang X, Xu Y, Dai Z. A Novel Cyanine and Porphyrin Based Theranostic Nanoagent for Near‑Infrared Fluorescence Imaging Guided Synergistic Phototherapy. J Biomed Nanotechnol. 2017;13(11):1468–1479.

Chang SC, Bown SG. Photodynamic therapy: applications in bladder cancer and other malignancies. J Formos Med Assoc. 1997;96(11):853–863.

Chen Q, Hetzel FW. Laser dosimetry studies in the prostate. J Clin Laser Med Surg. 1998;16(1):9–12.

Kawczyk‑Krupka A, et al. Treatment of localized prostate cancer using WST-09 and WST-11 mediated vascular targeted photodynamic therapy‑A review. Photodiagnosis Photodyn Ther. 2015;12(4):567–574.

Larue L, et al. Using X‑rays in photodynamic therapy: an overview. Photochem Photobiol Sci. 2018;17(11):1612–1650.

Bazak J, Fahey JM, Wawak K, Korytowski W, Girotti AW. Bystander effects of nitric oxide in anti‑tumor photodynamic therapy. Cancer Cell Microenviron. 2017;4(1).

Girotti AW. Upregulation of nitric oxide in tumor cells as a negative adaptation to photodynamic therapy. Lasers Surg Med. 2018;50(5):590–598.

Marien A, Gill I, Ukimura O, Betrouni N, Villers A. Target ablation--image‑guided therapy in prostate cancer. Urol Oncol. 2014;32(6):912–923.

Bozzini G, et al. Photodynamic therapy in urology: what can we do now and where are we heading? Photodiagnosis Photodyn Ther. 2012;9(3):261–273.

Zhu TC, Finlay JC. The role of photodynamic therapy (PDT) physics. Med Phys. 2008;35(7):3127–3136.

Jankun J. Protein‑based nanotechnology: antibody conjugated with photosensitizer in targeted anticancer photoimmunotherapy. Int J Oncol. 2011;39(4):949–953.

Aniola J, Selman SH, Lilge L, Keck R, Jankun J. Spatial distribution of liposome encapsulated tin etiopurpurin dichloride (SnET2) in the canine prostate: implications for computer simulation of photodynamic therapy. Int J Mol Med. 2003;11(3):287–291.

Mehraban N, Freeman HS. Developments in PDT Sensitizers for Increased Selectivity and Singlet Oxygen Production. Materials (Basel). 2015;8(7):4421–4456.

Rajendran M. Quinones as photosensitizer for photodynamic therapy: ROS generation, mechanism and detection methods. Photodiagnosis Photodyn Ther. 2016;13:175–187.

Jankun J, et al. Optical characteristics of the canine prostate at 665 nm sensitized with tin etiopurpurin dichloride: need for real‑time monitoring of photodynamic therapy. J Urol. 2004;172(2):739–743.

Dalla Via L, Marciani Magno S. Photochemotherapy in the treatment of cancer. Curr Med Chem. 2001;8(12):1405–1418.

Jankun J, Keck RW, Skrzypczak‑Jankun E, Lilge L, Selman SH. Diverse optical characteristic of the prostate and light delivery system: implications for computer modelling of prostatic photodynamic therapy. BJU Int. 2005;95(9):1237–1244.

Jori G. Tumour photosensitizers: approaches to enhance the selectivity and efficiency of photodynamic therapy. J Photochem Photobiol B. 1996;36(2):87–93.

Beeson KW, Parilov E, Potasek M, Kim MM, Zhu TC. Validation of combined Monte Carlo and photokinetic simulations for the outcome correlation analysis of benzoporphyrin derivative‑mediated photodynamic therapy on mice. J Biomed Opt. 2019;24(3):1–9.

Campbell CL, Wood K, Brown CT, Moseley H. Monte Carlo modelling of photodynamic therapy treatments comparing clustered three dimensional tumour structures with homogeneous tissue structures. Phys Med Biol. 2016;61(13):4840–4854.

Han Y, Oakley E, Shafirstein G, Rabin Y, Kara LB. Reconstruction of a Deformed Tumor Based on Fiducial Marker Registration: A Computational Feasibility Study. Technol Cancer Res Treat. 2018;17:1533034618766792.

Harris K, Oakley E, Bellnier D, Shafirstein G. Endobronchial ultrasound‑guidance for interstitial photodynamic therapy of locally advanced lung cancer‑a new interventional concept. J Thorac Dis. 2017;9(8):2613–2618.

Lopez‑Marin N, Mulet R, Rodriguez R. Photodynamic therapy: Toward a systemic computational model. J Photochem Photobiol B. 2018;189:201–213.

Kareliotis G, Liossi S, Makropoulou M. Assessment of singlet oxygen dosimetry concepts in photodynamic therapy through computational modeling. Photodiagnosis Photodyn Ther. 2018;21:224–233.

Lopez‑Marin N, Mulet R. In silico modelling of apoptosis induced by photodynamic therapy. J Theor Biol. 2018;436:8–17.

Dupont C, Vignion AS, Mordon S, Reyns N, Vermandel M. Photodynamic therapy for glioblastoma: A preliminary approach for practical application of light propagation models. Lasers Surg Med. 2018;50(5):523–534.




How to Cite

Jankun J. A thousand words about the challenges of photodynamic therapy: Challenges of photodynamic therapy. JMS [Internet]. 2019 Sep. 30 [cited 2024 Jun. 16];88(3):195-9. Available from: https://jms.ump.edu.pl/index.php/JMS/article/view/391



Thousand words about...
Received 2019-09-24
Accepted 2019-11-28
Published 2019-09-30