Abstract

Finding a high-quality treatment plan is an essential, yet difficult, stage of Photodynamic therapy (PDT) as it will determine the therapeutic efficacy in eradicating malignant tumors. A high-quality plan is patient-specific, and provides clinicians with the number of fiber-based spherical diffusers, their powers, and their interstitial locations to deliver the required light dose to destroy the tumor while minimizing the damage to surrounding healthy tissues. In this work, we propose a general convex light source power allocation algorithm that, given light source locations, guarantees optimality of the resulting solution in minimizing the over/under-dosage of volumes of interest. Furthermore, we provide an efficient framework for source selection with concomitant power reallocation to achieve treatment plans with a clinically feasible number of sources and comparable quality. We demonstrate our algorithms on virtual test cases that model glioblastoma multiforme tumors, and evaluate the performance of four different photosensitizers with different activation wavelengths and specific tissue uptake ratios. Results show an average reduction of the damage to organs-at-risk (OAR) by 29% to 31% with comparable runtime to existing power allocation techniques.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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2018 (1)

2017 (5)

G. Giacalone, M. Zanoletti, D. Contini, R. Re, L. Spinelli, L. Roveri, and A. Torricelli, “Cerebral time domain-NIRS: reproducibility analysis, optical properties, hemoglobin species and tissue oxygen saturation in a cohort of adult subjects,” Biomed. Opt. Express 8, 4987–5000 (2017).
[Crossref] [PubMed]

L. Spinelli, L. Zucchelli, D. Contini, M. Caffini, J. Mehler, A. Fló, A. L. Ferry, L. Filippin, F. Macagno, L. Cattarossi, and A. Torricelli, “In vivo measure of neonate brain optical properties and hemodynamic parameters by time-domain near-infrared spectroscopy,” Neurophotonics 4, 041414 (2017).
[Crossref]

H. Wang, C. Magnain, S. Sakadžić, B. Fischl, and D. A. Boas, “Characterizing the optical properties of human brain tissue with high numerical aperture optical coherence tomography,” Biomed. Opt. Express 8, 5617–5636 (2017).
[Crossref]

V. N. Du Le, J. Provias, N. Murty, M. S. Patterson, Z. Nie, J. E. Hayward, T. J. Farrell, W. McMillan, W. Zhang, and Q. Fang, “Dual-modality optical biopsy of glioblastomas multiforme with diffuse reflectance and fluorescence: ex vivo retrieval of optical properties,” J. Biomed. Opt. 22, 027002 (2017).
[Crossref]

N. Betrouni, S. Boukris, and F. Benzaghou, “Vascular targeted photodynamic therapy with TOOKAD Soluble (WST11) in localized prostate cancer: efficiency of automatic pre-treatment planning,” Lasers Med. Sci. 101–7 (2017).

2013 (2)

K. Clark, B. Vendt, K. Smith, J. Freymann, J. Kirby, P. Koppel, S. Moore, S. Phillips, D. Maffitt, M. Pringle, L. Tarbox, and F. Prior, “The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository,” J. Digit. Imaging 26, 1045–1057 (2013).
[Crossref] [PubMed]

A. Johansson, F. Faber, G. Kniebühler, H. Stepp, R. Sroka, R. Egensperger, W. Beyer, and F.-W. Kreth, “Protoporphyrin IX fluorescence and photobleaching during interstitial photodynamic therapy of malignant gliomas for early treatment prognosis,” Lasers Surg. Med. 45, 225–234 (2013).
[Crossref] [PubMed]

2011 (3)

J. Binding, J. B. Arous, J.-F. Léger, S. Gigan, C. Boccara, and L. Bourdieu, “Brain refractive index measured in vivo with high-na defocus-corrected full-field oct and consequences for two-photon microscopy,” Opt. Express 19, 4833–4847 (2011).
[Crossref] [PubMed]

W. Stummer, M. J. van den Bent, and M. Westphal, “Cytoreductive surgery of glioblastoma as the key to successful adjuvant therapies: new arguments in an old discussion,” Acta Neurochir. 153, 1211–1218 (2011).
[Crossref] [PubMed]

N. Betrouni, R. Lopes, P. Puech, P. Colin, and S. Mordon, “A model to estimate the outcome of prostate cancer photodynamic therapy with TOOKAD Soluble WST11,” Phys. Med. Bio. 56, 4771 (2011).
[Crossref]

2010 (1)

2009 (2)

2008 (3)

H. E. Romeijn and J. F. Dempsey, “Intensity modulated radiation therapy treatment plan optimization,” Top 16, 215 (2008).
[Crossref]

S. L. Jacques and B. W. Pogue, “Tutorial on diffuse light transport,” J. Biomed. Opt. 13, 041302 (2008).
[Crossref] [PubMed]

B. C. Wilson and M. S. Patterson, “The physics, biophysics and technology of photodynamic therapy,” Phys. Med. Bio. 53, R61 (2008).
[Crossref]

2007 (3)

S. M. Fien and A. R. Oseroff, “Photodynamic therapy for non-melanoma skin cancer,” J. Ntl. Compr. Canc. Netw. 5, 531–540 (2007).
[Crossref]

B. F. Overholt, K. K. Wang, J. S. Burdick, C. J. Lightdale, M. Kimmey, H. R. Nava, M. V. Sivak, N. Nishioka, H. Barr, N. Marcon, M. Pedrosa, M. P. Bronner, M. Grace, and M. Depot, “Five-year efficacy and safety of photodynamic therapy with photofrin in barrett’s high-grade dysplasia,” Gastrointest. Endosc. 66, 460–468 (2007).
[Crossref] [PubMed]

A. Johansson, J. Axelsson, S. Andersson-Engels, and J. Swartling, “Realtime light dosimetry software tools for interstitial photodynamic therapy of the human prostate,” J. Med. Phys. 34, 4309–4321 (2007).
[Crossref]

2006 (1)

A. M. Zysk, E. J. Chaney, and S. A. Boppart, “Refractive index of carcinogen-induced rat mammary tumours,” Phys. Med. Bio. 51, 2165 (2006).
[Crossref]

2005 (2)

R. A. Weersink, A. Bogaards, M. Gertner, S. R. Davidson, K. Zhang, G. Netchev, J. Trachtenberg, and B. C. Wilson, “Techniques for delivery and monitoring of TOOKAD (WST09)-mediated photodynamic therapy of the prostate: clinical experience and practicalities,” J. Photochem. Photobiol. B. 79, 211–222 (2005).
[Crossref] [PubMed]

M. D. Altschuler, T. C. Zhu, J. Li, and S. M. Hahn, “Optimized interstitial PDT prostate treatment planning with the cimmino feasibility algorithm,” J. Med. Phys. 32, 3524–3536 (2005).
[Crossref]

2004 (1)

P. Lou, H. Jäger, L. Jones, T. Theodossy, S. Bown, and C. Hopper, “Interstitial photodynamic therapy as salvage treatment for recurrent head and neck cancer,” Br. J. Cancer 91, 441 (2004).
[Crossref] [PubMed]

2002 (2)

A. Yaroslavsky, P. Schulze, I. Yaroslavsky, R. Schober, F. Ulrich, and H. Schwarzmaier, “Optical properties of selected native and coagulated human brain tissues in vitro in the visible and near infrared spectral range,” Phys. Med. Bio. 47, 2059 (2002).
[Crossref]

T. Biwas and A. Gupta, “Retrieval of true color of the internal organ of CT images and attempt to tissue characterization by refractive index: initial experience,” Indian J. Radiol. Imaging 12, 169 (2002).

2001 (2)

Z. W. Geem, J. H. Kim, and G. Loganathan, “A new heuristic optimization algorithm: harmony search,” Simulation 76, 60–68 (2001).
[Crossref]

Y. Censor, D. Gordon, and R. Gordon, “Component averaging: An efficient iterative parallel algorithm for large and sparse unstructured problems,” Paral. Comp. 27, 777–808 (2001).
[Crossref]

1999 (1)

1998 (2)

D. L. Collins, A. P. Zijdenbos, V. Kollokian, J. G. Sled, N. J. Kabani, C. J. Holmes, and A. C. Evans, “Design and construction of a realistic digital brain phantom,” IEEE Trans. Med. Imag. 17, 463–468 (1998).
[Crossref]

L. Lilge and B. C. Wilson, “Photodynamic therapy of intracranial tissues: a preclinical comparative study of four different photosensitizers,” J. Clin. Laser Med. Surg. 16, 81–91 (1998).
[PubMed]

1997 (2)

L. Lee, C. Whitehurst, Q. Chen, M. Pantelides, F. Hetzel, and J. V. Moore, “Interstitial photodynamic therapy in the canine prostate,” BJU Int. 80, 898–902 (1997).
[Crossref]

E. Okada, M. Firbank, M. Schweiger, S. R. Arridge, M. Cope, and D. T. Delpy, “Theoretical and experimental investigation of near-infrared light propagation in a model of the adult head,” Appl. Opt. 36, 21–31 (1997).
[Crossref] [PubMed]

1996 (1)

A. V. D’Amico and C. N. Coleman, “Role of interstitial radiotherapy in the management of clinically organ-confined prostate cancer: the jury is still out,” J. Clin. Oncol. 14, 304–315 (1996).
[Crossref]

1995 (1)

H. J. Van Staveren, H. P. Marijnissen, M. C. Aalders, and W. M. Star, “Construction, quality assurance and calibration of spherical isotropic fibre optic light diffusers,” Lasers Med. Sci. 10, 137–147 (1995).
[Crossref]

1988 (1)

Y. Censor, M. D. Altschuler, and W. D. Powlis, “On the use of Cimmino’s simultaneous projections method for computing a solution of the inverse problem in radiation therapy treatment planning,” Inverse Probl. 4, 607 (1988).
[Crossref]

Aalders, M. C.

H. J. Van Staveren, H. P. Marijnissen, M. C. Aalders, and W. M. Star, “Construction, quality assurance and calibration of spherical isotropic fibre optic light diffusers,” Lasers Med. Sci. 10, 137–147 (1995).
[Crossref]

Allen, D. W.

Altschuler, M. D.

M. D. Altschuler, T. C. Zhu, J. Li, and S. M. Hahn, “Optimized interstitial PDT prostate treatment planning with the cimmino feasibility algorithm,” J. Med. Phys. 32, 3524–3536 (2005).
[Crossref]

Y. Censor, M. D. Altschuler, and W. D. Powlis, “On the use of Cimmino’s simultaneous projections method for computing a solution of the inverse problem in radiation therapy treatment planning,” Inverse Probl. 4, 607 (1988).
[Crossref]

T. C. Zhu, M. D. Altschuler, Y. Hu, K. Wang, J. C. Finlay, A. Dimofte, K. Cengel, and S. M. Hahn, “A heterogeneous optimization algorithm for reacted singlet oxygen for interstitial PDT,” in “Proc. SPIE – the International Society for Optical Engineering,”, vol. 7551 (NIH Public Access, 2010), vol. 7551.

M. D. Altschuler, T. C. Zhu, Y. Hu, J. C. Finlay, A. Dimofte, K. Wang, J. Li, K. Cengel, S. Malkowicz, and S. M. Hahn, “A heterogeneous algorithm for PDT dose optimization for prostate,” in “Proc. SPIE,”, vol. 7164 (NIH Public Access, 2009), vol. 7164, p. 71640B.

M. D. Altschuler, T. C. Zhu, J. Li, and S. M. Hahn, “Optimization of light sources for prostate photodynamic therapy,” in “Proc. SPIE – the International Society for Optical Engineering,”, vol. 5689 (NIH Public Access, 2005), vol. 5689, p. 186.

Andersson-Engels, S.

J. Axelsson, J. Swartling, and S. Andersson-Engels, “In vivo photosensitizer tomography inside the human prostate,” Opt. Lett. 34, 232–234 (2009).
[Crossref] [PubMed]

A. Johansson, J. Axelsson, S. Andersson-Engels, and J. Swartling, “Realtime light dosimetry software tools for interstitial photodynamic therapy of the human prostate,” J. Med. Phys. 34, 4309–4321 (2007).
[Crossref]

A. Johansson, J. Axelsson, J. Swartling, T. Johansson, S. Plsson, J. Stensson, M. Einarsdottir, K. Svanberg, N. Bendsoe, K. M. Kalkner, S. Nilsson, S. Svanberg, and S. Andersson-Engels, “Interstitial photodynamic therapy for primary prostate cancer incorporating real-time treatment dosimetry,” in “Proc. SPIE,”, vol. 6427 (2007), vol. 6427, p. 64270O.

ApS, M.

M. ApS, MOSEK Fusion API for C++. Version 8.0 (Revision 88) (2017).

Arous, J. B.

Arridge, S. R.

Axelsson, J.

J. Axelsson, J. Swartling, and S. Andersson-Engels, “In vivo photosensitizer tomography inside the human prostate,” Opt. Lett. 34, 232–234 (2009).
[Crossref] [PubMed]

A. Johansson, J. Axelsson, S. Andersson-Engels, and J. Swartling, “Realtime light dosimetry software tools for interstitial photodynamic therapy of the human prostate,” J. Med. Phys. 34, 4309–4321 (2007).
[Crossref]

A. Johansson, J. Axelsson, J. Swartling, T. Johansson, S. Plsson, J. Stensson, M. Einarsdottir, K. Svanberg, N. Bendsoe, K. M. Kalkner, S. Nilsson, S. Svanberg, and S. Andersson-Engels, “Interstitial photodynamic therapy for primary prostate cancer incorporating real-time treatment dosimetry,” in “Proc. SPIE,”, vol. 6427 (2007), vol. 6427, p. 64270O.

Barr, H.

B. F. Overholt, K. K. Wang, J. S. Burdick, C. J. Lightdale, M. Kimmey, H. R. Nava, M. V. Sivak, N. Nishioka, H. Barr, N. Marcon, M. Pedrosa, M. P. Bronner, M. Grace, and M. Depot, “Five-year efficacy and safety of photodynamic therapy with photofrin in barrett’s high-grade dysplasia,” Gastrointest. Endosc. 66, 460–468 (2007).
[Crossref] [PubMed]

Beck, J.

A. Rendon, J. Beck, and L. Lilge, “Linear feasibility algorithms for treatment planning in interstitial photodynamic therapy,” in “Proc. SPIE,”, vol. 6845 (2008), vol. 6845, pp. 68450O–1.

Bendsoe, N.

A. Johansson, J. Axelsson, J. Swartling, T. Johansson, S. Plsson, J. Stensson, M. Einarsdottir, K. Svanberg, N. Bendsoe, K. M. Kalkner, S. Nilsson, S. Svanberg, and S. Andersson-Engels, “Interstitial photodynamic therapy for primary prostate cancer incorporating real-time treatment dosimetry,” in “Proc. SPIE,”, vol. 6427 (2007), vol. 6427, p. 64270O.

Benzaghou, F.

N. Betrouni, S. Boukris, and F. Benzaghou, “Vascular targeted photodynamic therapy with TOOKAD Soluble (WST11) in localized prostate cancer: efficiency of automatic pre-treatment planning,” Lasers Med. Sci. 101–7 (2017).

Betrouni, N.

N. Betrouni, S. Boukris, and F. Benzaghou, “Vascular targeted photodynamic therapy with TOOKAD Soluble (WST11) in localized prostate cancer: efficiency of automatic pre-treatment planning,” Lasers Med. Sci. 101–7 (2017).

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Beyer, W.

A. Johansson, F. Faber, G. Kniebühler, H. Stepp, R. Sroka, R. Egensperger, W. Beyer, and F.-W. Kreth, “Protoporphyrin IX fluorescence and photobleaching during interstitial photodynamic therapy of malignant gliomas for early treatment prognosis,” Lasers Surg. Med. 45, 225–234 (2013).
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Boccara, C.

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R. A. Weersink, A. Bogaards, M. Gertner, S. R. Davidson, K. Zhang, G. Netchev, J. Trachtenberg, and B. C. Wilson, “Techniques for delivery and monitoring of TOOKAD (WST09)-mediated photodynamic therapy of the prostate: clinical experience and practicalities,” J. Photochem. Photobiol. B. 79, 211–222 (2005).
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N. Betrouni, S. Boukris, and F. Benzaghou, “Vascular targeted photodynamic therapy with TOOKAD Soluble (WST11) in localized prostate cancer: efficiency of automatic pre-treatment planning,” Lasers Med. Sci. 101–7 (2017).

Bourdieu, L.

Bown, S.

P. Lou, H. Jäger, L. Jones, T. Theodossy, S. Bown, and C. Hopper, “Interstitial photodynamic therapy as salvage treatment for recurrent head and neck cancer,” Br. J. Cancer 91, 441 (2004).
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J. Cassidy, L. Lilge, and V. Betz, “Fast, power-efficient biophotonic simulations for cancer treatment using fpgas,” in “Proceedings of IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM),” (IEEE, 2014), pp. 133–140.

J. Cassidy, L. Lilge, and V. Betz, “FullMonte: a framework for high-performance Monte Carlo simulation of light through turbid media with complex geometry,” in “Proc. SPIE BiOS,”, vol. 8592 (SPIESan Francisco, CA, 2013), vol. 8592, pp. 85920H.

Cattarossi, L.

L. Spinelli, L. Zucchelli, D. Contini, M. Caffini, J. Mehler, A. Fló, A. L. Ferry, L. Filippin, F. Macagno, L. Cattarossi, and A. Torricelli, “In vivo measure of neonate brain optical properties and hemodynamic parameters by time-domain near-infrared spectroscopy,” Neurophotonics 4, 041414 (2017).
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T. C. Zhu, M. D. Altschuler, Y. Hu, K. Wang, J. C. Finlay, A. Dimofte, K. Cengel, and S. M. Hahn, “A heterogeneous optimization algorithm for reacted singlet oxygen for interstitial PDT,” in “Proc. SPIE – the International Society for Optical Engineering,”, vol. 7551 (NIH Public Access, 2010), vol. 7551.

M. D. Altschuler, T. C. Zhu, Y. Hu, J. C. Finlay, A. Dimofte, K. Wang, J. Li, K. Cengel, S. Malkowicz, and S. M. Hahn, “A heterogeneous algorithm for PDT dose optimization for prostate,” in “Proc. SPIE,”, vol. 7164 (NIH Public Access, 2009), vol. 7164, p. 71640B.

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Y. Censor, D. Gordon, and R. Gordon, “Component averaging: An efficient iterative parallel algorithm for large and sparse unstructured problems,” Paral. Comp. 27, 777–808 (2001).
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Y. Censor, M. D. Altschuler, and W. D. Powlis, “On the use of Cimmino’s simultaneous projections method for computing a solution of the inverse problem in radiation therapy treatment planning,” Inverse Probl. 4, 607 (1988).
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A. M. Zysk, E. J. Chaney, and S. A. Boppart, “Refractive index of carcinogen-induced rat mammary tumours,” Phys. Med. Bio. 51, 2165 (2006).
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L. Lee, C. Whitehurst, Q. Chen, M. Pantelides, F. Hetzel, and J. V. Moore, “Interstitial photodynamic therapy in the canine prostate,” BJU Int. 80, 898–902 (1997).
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K. Clark, B. Vendt, K. Smith, J. Freymann, J. Kirby, P. Koppel, S. Moore, S. Phillips, D. Maffitt, M. Pringle, L. Tarbox, and F. Prior, “The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository,” J. Digit. Imaging 26, 1045–1057 (2013).
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A. V. D’Amico and C. N. Coleman, “Role of interstitial radiotherapy in the management of clinically organ-confined prostate cancer: the jury is still out,” J. Clin. Oncol. 14, 304–315 (1996).
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Colin, P.

N. Betrouni, R. Lopes, P. Puech, P. Colin, and S. Mordon, “A model to estimate the outcome of prostate cancer photodynamic therapy with TOOKAD Soluble WST11,” Phys. Med. Bio. 56, 4771 (2011).
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Collins, D. L.

D. L. Collins, A. P. Zijdenbos, V. Kollokian, J. G. Sled, N. J. Kabani, C. J. Holmes, and A. C. Evans, “Design and construction of a realistic digital brain phantom,” IEEE Trans. Med. Imag. 17, 463–468 (1998).
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L. Spinelli, L. Zucchelli, D. Contini, M. Caffini, J. Mehler, A. Fló, A. L. Ferry, L. Filippin, F. Macagno, L. Cattarossi, and A. Torricelli, “In vivo measure of neonate brain optical properties and hemodynamic parameters by time-domain near-infrared spectroscopy,” Neurophotonics 4, 041414 (2017).
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A. V. D’Amico and C. N. Coleman, “Role of interstitial radiotherapy in the management of clinically organ-confined prostate cancer: the jury is still out,” J. Clin. Oncol. 14, 304–315 (1996).
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Depot, M.

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M. D. Altschuler, T. C. Zhu, Y. Hu, J. C. Finlay, A. Dimofte, K. Wang, J. Li, K. Cengel, S. Malkowicz, and S. M. Hahn, “A heterogeneous algorithm for PDT dose optimization for prostate,” in “Proc. SPIE,”, vol. 7164 (NIH Public Access, 2009), vol. 7164, p. 71640B.

T. C. Zhu, M. D. Altschuler, Y. Hu, K. Wang, J. C. Finlay, A. Dimofte, K. Cengel, and S. M. Hahn, “A heterogeneous optimization algorithm for reacted singlet oxygen for interstitial PDT,” in “Proc. SPIE – the International Society for Optical Engineering,”, vol. 7551 (NIH Public Access, 2010), vol. 7551.

Du Le, V. N.

V. N. Du Le, J. Provias, N. Murty, M. S. Patterson, Z. Nie, J. E. Hayward, T. J. Farrell, W. McMillan, W. Zhang, and Q. Fang, “Dual-modality optical biopsy of glioblastomas multiforme with diffuse reflectance and fluorescence: ex vivo retrieval of optical properties,” J. Biomed. Opt. 22, 027002 (2017).
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A. Johansson, F. Faber, G. Kniebühler, H. Stepp, R. Sroka, R. Egensperger, W. Beyer, and F.-W. Kreth, “Protoporphyrin IX fluorescence and photobleaching during interstitial photodynamic therapy of malignant gliomas for early treatment prognosis,” Lasers Surg. Med. 45, 225–234 (2013).
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Evans, A. C.

D. L. Collins, A. P. Zijdenbos, V. Kollokian, J. G. Sled, N. J. Kabani, C. J. Holmes, and A. C. Evans, “Design and construction of a realistic digital brain phantom,” IEEE Trans. Med. Imag. 17, 463–468 (1998).
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A. Johansson, F. Faber, G. Kniebühler, H. Stepp, R. Sroka, R. Egensperger, W. Beyer, and F.-W. Kreth, “Protoporphyrin IX fluorescence and photobleaching during interstitial photodynamic therapy of malignant gliomas for early treatment prognosis,” Lasers Surg. Med. 45, 225–234 (2013).
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V. N. Du Le, J. Provias, N. Murty, M. S. Patterson, Z. Nie, J. E. Hayward, T. J. Farrell, W. McMillan, W. Zhang, and Q. Fang, “Dual-modality optical biopsy of glioblastomas multiforme with diffuse reflectance and fluorescence: ex vivo retrieval of optical properties,” J. Biomed. Opt. 22, 027002 (2017).
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V. N. Du Le, J. Provias, N. Murty, M. S. Patterson, Z. Nie, J. E. Hayward, T. J. Farrell, W. McMillan, W. Zhang, and Q. Fang, “Dual-modality optical biopsy of glioblastomas multiforme with diffuse reflectance and fluorescence: ex vivo retrieval of optical properties,” J. Biomed. Opt. 22, 027002 (2017).
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L. Spinelli, L. Zucchelli, D. Contini, M. Caffini, J. Mehler, A. Fló, A. L. Ferry, L. Filippin, F. Macagno, L. Cattarossi, and A. Torricelli, “In vivo measure of neonate brain optical properties and hemodynamic parameters by time-domain near-infrared spectroscopy,” Neurophotonics 4, 041414 (2017).
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M. D. Altschuler, T. C. Zhu, Y. Hu, J. C. Finlay, A. Dimofte, K. Wang, J. Li, K. Cengel, S. Malkowicz, and S. M. Hahn, “A heterogeneous algorithm for PDT dose optimization for prostate,” in “Proc. SPIE,”, vol. 7164 (NIH Public Access, 2009), vol. 7164, p. 71640B.

T. C. Zhu, M. D. Altschuler, Y. Hu, K. Wang, J. C. Finlay, A. Dimofte, K. Cengel, and S. M. Hahn, “A heterogeneous optimization algorithm for reacted singlet oxygen for interstitial PDT,” in “Proc. SPIE – the International Society for Optical Engineering,”, vol. 7551 (NIH Public Access, 2010), vol. 7551.

Firbank, M.

Fischl, B.

Fló, A.

L. Spinelli, L. Zucchelli, D. Contini, M. Caffini, J. Mehler, A. Fló, A. L. Ferry, L. Filippin, F. Macagno, L. Cattarossi, and A. Torricelli, “In vivo measure of neonate brain optical properties and hemodynamic parameters by time-domain near-infrared spectroscopy,” Neurophotonics 4, 041414 (2017).
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K. Clark, B. Vendt, K. Smith, J. Freymann, J. Kirby, P. Koppel, S. Moore, S. Phillips, D. Maffitt, M. Pringle, L. Tarbox, and F. Prior, “The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository,” J. Digit. Imaging 26, 1045–1057 (2013).
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R. A. Weersink, A. Bogaards, M. Gertner, S. R. Davidson, K. Zhang, G. Netchev, J. Trachtenberg, and B. C. Wilson, “Techniques for delivery and monitoring of TOOKAD (WST09)-mediated photodynamic therapy of the prostate: clinical experience and practicalities,” J. Photochem. Photobiol. B. 79, 211–222 (2005).
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Giacalone, G.

Gigan, S.

Gordon, D.

Y. Censor, D. Gordon, and R. Gordon, “Component averaging: An efficient iterative parallel algorithm for large and sparse unstructured problems,” Paral. Comp. 27, 777–808 (2001).
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Gordon, R.

Y. Censor, D. Gordon, and R. Gordon, “Component averaging: An efficient iterative parallel algorithm for large and sparse unstructured problems,” Paral. Comp. 27, 777–808 (2001).
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Grace, M.

B. F. Overholt, K. K. Wang, J. S. Burdick, C. J. Lightdale, M. Kimmey, H. R. Nava, M. V. Sivak, N. Nishioka, H. Barr, N. Marcon, M. Pedrosa, M. P. Bronner, M. Grace, and M. Depot, “Five-year efficacy and safety of photodynamic therapy with photofrin in barrett’s high-grade dysplasia,” Gastrointest. Endosc. 66, 460–468 (2007).
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Grosenick, D.

Gross, J. D.

Gupta, A.

T. Biwas and A. Gupta, “Retrieval of true color of the internal organ of CT images and attempt to tissue characterization by refractive index: initial experience,” Indian J. Radiol. Imaging 12, 169 (2002).

Hahn, S. M.

M. D. Altschuler, T. C. Zhu, J. Li, and S. M. Hahn, “Optimized interstitial PDT prostate treatment planning with the cimmino feasibility algorithm,” J. Med. Phys. 32, 3524–3536 (2005).
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M. D. Altschuler, T. C. Zhu, Y. Hu, J. C. Finlay, A. Dimofte, K. Wang, J. Li, K. Cengel, S. Malkowicz, and S. M. Hahn, “A heterogeneous algorithm for PDT dose optimization for prostate,” in “Proc. SPIE,”, vol. 7164 (NIH Public Access, 2009), vol. 7164, p. 71640B.

T. C. Zhu, M. D. Altschuler, Y. Hu, K. Wang, J. C. Finlay, A. Dimofte, K. Cengel, and S. M. Hahn, “A heterogeneous optimization algorithm for reacted singlet oxygen for interstitial PDT,” in “Proc. SPIE – the International Society for Optical Engineering,”, vol. 7551 (NIH Public Access, 2010), vol. 7551.

M. D. Altschuler, T. C. Zhu, J. Li, and S. M. Hahn, “Optimization of light sources for prostate photodynamic therapy,” in “Proc. SPIE – the International Society for Optical Engineering,”, vol. 5689 (NIH Public Access, 2005), vol. 5689, p. 186.

Hayward, J. E.

V. N. Du Le, J. Provias, N. Murty, M. S. Patterson, Z. Nie, J. E. Hayward, T. J. Farrell, W. McMillan, W. Zhang, and Q. Fang, “Dual-modality optical biopsy of glioblastomas multiforme with diffuse reflectance and fluorescence: ex vivo retrieval of optical properties,” J. Biomed. Opt. 22, 027002 (2017).
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Hetzel, F.

L. Lee, C. Whitehurst, Q. Chen, M. Pantelides, F. Hetzel, and J. V. Moore, “Interstitial photodynamic therapy in the canine prostate,” BJU Int. 80, 898–902 (1997).
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Holmes, C. J.

D. L. Collins, A. P. Zijdenbos, V. Kollokian, J. G. Sled, N. J. Kabani, C. J. Holmes, and A. C. Evans, “Design and construction of a realistic digital brain phantom,” IEEE Trans. Med. Imag. 17, 463–468 (1998).
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Hopper, C.

P. Lou, H. Jäger, L. Jones, T. Theodossy, S. Bown, and C. Hopper, “Interstitial photodynamic therapy as salvage treatment for recurrent head and neck cancer,” Br. J. Cancer 91, 441 (2004).
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Hu, Y.

M. D. Altschuler, T. C. Zhu, Y. Hu, J. C. Finlay, A. Dimofte, K. Wang, J. Li, K. Cengel, S. Malkowicz, and S. M. Hahn, “A heterogeneous algorithm for PDT dose optimization for prostate,” in “Proc. SPIE,”, vol. 7164 (NIH Public Access, 2009), vol. 7164, p. 71640B.

T. C. Zhu, M. D. Altschuler, Y. Hu, K. Wang, J. C. Finlay, A. Dimofte, K. Cengel, and S. M. Hahn, “A heterogeneous optimization algorithm for reacted singlet oxygen for interstitial PDT,” in “Proc. SPIE – the International Society for Optical Engineering,”, vol. 7551 (NIH Public Access, 2010), vol. 7551.

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P. Lou, H. Jäger, L. Jones, T. Theodossy, S. Bown, and C. Hopper, “Interstitial photodynamic therapy as salvage treatment for recurrent head and neck cancer,” Br. J. Cancer 91, 441 (2004).
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Johansson, A.

A. Johansson, F. Faber, G. Kniebühler, H. Stepp, R. Sroka, R. Egensperger, W. Beyer, and F.-W. Kreth, “Protoporphyrin IX fluorescence and photobleaching during interstitial photodynamic therapy of malignant gliomas for early treatment prognosis,” Lasers Surg. Med. 45, 225–234 (2013).
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Johansson, T.

A. Johansson, J. Axelsson, J. Swartling, T. Johansson, S. Plsson, J. Stensson, M. Einarsdottir, K. Svanberg, N. Bendsoe, K. M. Kalkner, S. Nilsson, S. Svanberg, and S. Andersson-Engels, “Interstitial photodynamic therapy for primary prostate cancer incorporating real-time treatment dosimetry,” in “Proc. SPIE,”, vol. 6427 (2007), vol. 6427, p. 64270O.

Jones, L.

P. Lou, H. Jäger, L. Jones, T. Theodossy, S. Bown, and C. Hopper, “Interstitial photodynamic therapy as salvage treatment for recurrent head and neck cancer,” Br. J. Cancer 91, 441 (2004).
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Kabani, N. J.

D. L. Collins, A. P. Zijdenbos, V. Kollokian, J. G. Sled, N. J. Kabani, C. J. Holmes, and A. C. Evans, “Design and construction of a realistic digital brain phantom,” IEEE Trans. Med. Imag. 17, 463–468 (1998).
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Kalkner, K. M.

A. Johansson, J. Axelsson, J. Swartling, T. Johansson, S. Plsson, J. Stensson, M. Einarsdottir, K. Svanberg, N. Bendsoe, K. M. Kalkner, S. Nilsson, S. Svanberg, and S. Andersson-Engels, “Interstitial photodynamic therapy for primary prostate cancer incorporating real-time treatment dosimetry,” in “Proc. SPIE,”, vol. 6427 (2007), vol. 6427, p. 64270O.

Kim, J. H.

Z. W. Geem, J. H. Kim, and G. Loganathan, “A new heuristic optimization algorithm: harmony search,” Simulation 76, 60–68 (2001).
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Kimmey, M.

B. F. Overholt, K. K. Wang, J. S. Burdick, C. J. Lightdale, M. Kimmey, H. R. Nava, M. V. Sivak, N. Nishioka, H. Barr, N. Marcon, M. Pedrosa, M. P. Bronner, M. Grace, and M. Depot, “Five-year efficacy and safety of photodynamic therapy with photofrin in barrett’s high-grade dysplasia,” Gastrointest. Endosc. 66, 460–468 (2007).
[Crossref] [PubMed]

Kirby, J.

K. Clark, B. Vendt, K. Smith, J. Freymann, J. Kirby, P. Koppel, S. Moore, S. Phillips, D. Maffitt, M. Pringle, L. Tarbox, and F. Prior, “The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository,” J. Digit. Imaging 26, 1045–1057 (2013).
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Kniebühler, G.

A. Johansson, F. Faber, G. Kniebühler, H. Stepp, R. Sroka, R. Egensperger, W. Beyer, and F.-W. Kreth, “Protoporphyrin IX fluorescence and photobleaching during interstitial photodynamic therapy of malignant gliomas for early treatment prognosis,” Lasers Surg. Med. 45, 225–234 (2013).
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Kollokian, V.

D. L. Collins, A. P. Zijdenbos, V. Kollokian, J. G. Sled, N. J. Kabani, C. J. Holmes, and A. C. Evans, “Design and construction of a realistic digital brain phantom,” IEEE Trans. Med. Imag. 17, 463–468 (1998).
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Koppel, P.

K. Clark, B. Vendt, K. Smith, J. Freymann, J. Kirby, P. Koppel, S. Moore, S. Phillips, D. Maffitt, M. Pringle, L. Tarbox, and F. Prior, “The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository,” J. Digit. Imaging 26, 1045–1057 (2013).
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Kreth, F.-W.

A. Johansson, F. Faber, G. Kniebühler, H. Stepp, R. Sroka, R. Egensperger, W. Beyer, and F.-W. Kreth, “Protoporphyrin IX fluorescence and photobleaching during interstitial photodynamic therapy of malignant gliomas for early treatment prognosis,” Lasers Surg. Med. 45, 225–234 (2013).
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A. Yaroslavsky, P. Schulze, I. Yaroslavsky, R. Schober, F. Ulrich, and H. Schwarzmaier, “Optical properties of selected native and coagulated human brain tissues in vitro in the visible and near infrared spectral range,” Phys. Med. Bio. 47, 2059 (2002).
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T. C. Zhu, M. D. Altschuler, Y. Hu, K. Wang, J. C. Finlay, A. Dimofte, K. Cengel, and S. M. Hahn, “A heterogeneous optimization algorithm for reacted singlet oxygen for interstitial PDT,” in “Proc. SPIE – the International Society for Optical Engineering,”, vol. 7551 (NIH Public Access, 2010), vol. 7551.

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Figures (8)

Fig. 1
Fig. 1 Flow diagram of the proposed approach
Fig. 2
Fig. 2 Human brain mesh used in our simulations with a 3D cut showing the different materials
Fig. 3
Fig. 3 (a) The brain mesh (blue) used with one of the modeled tumors (red). (b) The tumor v90 versus the cost function value when using ALCIPc as the photosensitizer drug (activated at 675nm), along with a fitted line of the data showing the strong correlation.
Fig. 4
Fig. 4 Increasing the importance weight on tumor dose drives the optimizer to increase the tumor v90 (blue), at the expense of increased damage to the OAR (green and red). This test is made on a tumor volume of 103cm3 with 24 light sources at 675nm.
Fig. 5
Fig. 5 Tissue v90 against the ratio of the OAR dmax to the relative tissue death threshold at 675nm for ALCIPc activation. (a) The tumor v90. (b) The OAR v90.
Fig. 6
Fig. 6 DVH comparison between the proposed LP for power allocation and Cimmino algorithm for Tumor 1, treated with 675nm for ALCIPc mediated PDT.
Fig. 7
Fig. 7 (a) Average tissue v90 against the different plans generated in the LSR algorithm. (b) Average treatment time against the number of sources used in different plans. This treatment assumes the ALCIPc photosensitizer, which is activated at 675nm.
Fig. 8
Fig. 8 Breakdown of the average total runtime of the proposed implementation.

Tables (9)

Tables Icon

Table 1 PDT photosensitizers, their activation wavelengths and their relative uptake ratios. The uptake ratios data were taken from Table 3 in [8] for (a) 5mg.kg−1 administered dose and 24hrs delay, (b) 100mg.kg−1 administered dose and 6hrs delay, (c) 1mg.kg−1 administered dose and 24hrs delay, and (d) 0.5mg.kg−1 administered dose and 24hrs delay. Those ratios were calculated based on the tissue specific uptake ratios (SUR) as quantified tissue concentrations over administered concentrations in one (SnET as photosensitizer) to three animals.

Tables Icon

Table 2 Tissue death threshold values (TPVk) given in number of photons absorbed by each photosensitizer per mm3 (×1018). The data were taken from Table 3 in [8] for (a) 5mg.kg−1 administered dose and 24hrs delay, (b) 100mg.kg−1 administered dose and 6hrs delay, (c) 1mg.kg−1 administered dose and 24hrs delay, and (d) 0.5mg.kg−1 administered dose and 24hrs delay.

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Table 3 Relative tissue dose threshold values with respect to the tumor’s minimum threshold value for each tissue and each photosensitizer. The white and grey matters’ maximum thresholds were scaled down by 10 to increase PDT safety.

Tables Icon

Table 4 Optical properties of the different tissues at different wavelengths. The values are taken from [29–35].

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Table 5 v90 results with a tumor importance weight wi,tumor = 60, using 675nm for ALCIPc activation.

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Table 6 Proposed linear program versus Cimmino algorithm for power allocation, for ALCIPc mediated PDT at 675nm.

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Table 7 Proposed linear program versus Cimmino algorithm for power allocation using different photosensitizers. All values shown in the table are a geometric average across the nine tumor cases.

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Algorithm 1 Light Source Reduction (LSR) Algorithm

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Table 8 Comparison of quality of plans between the LP with fixed sources technique and with the LSR technique at the same number of physical sources

Equations (7)

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minimize x f ( x ) Subject to Ax p max
A i = [ 0 1 0 1 0 ]
f i ( x ) = { w i v i ( d min , i g i x ) g i x < d min , i w i v i ( g i x d max , i ) g i x > d max , i 0 Otherwise
f ( x ) = i = 1 n f i ( x )
Relative Tissue Death Dose Threshold of material k = TPV k TPV tumor × uptake ratio of tumor to material k
integral overdose = healthy elements k max { 0 , v k ( g k x * d max , k eval ) }
μ s = μ s ( 1 g ) = 8.4 ( 1 0.9 ) = 0.84 m m 1

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