- Email: [email protected]
Validation of an automatic eye monitoring system for ocular tumours stereotactic radiotherapy
Radiation Physics and Chemistry xxx (xxxx) xxx–xxx
Contents lists available at ScienceDirect
Radiation Physics and Chemistry journal homepage: www.elsevier.com/locate/radphyschem
Validation of an automatic eye monitoring system for ocular tumours stereotactic radiotherapy Simone C. Cardosoa, Odair D. Gonçalvesa,∗, Juan V.M. de Sousaa,b, Felipe M.L. de Souzac, Dirceu D. Pereiraa,b a
Instituto de Física, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil Instituto de Radioproteção e Dosimetria, IRD/CNEN, Rio de Janeiro, Brazil c Escola Politécnica, Universidade Federal do Rio de Janeiro – UFRJ, Rio de Janeiro, Brazil b
A R T I C LE I N FO
A B S T R A C T
Keywords: Mechanical eye simulator Instrumentation Irradiation monitoring Stereotactic Radiotherapy
Choroidal melanoma is a type of tumour that appears in the back of the eye and can rapidly evolve into metastasis. For tumours in advanced stages and/or located near the retina, external beam radiotherapy (teletherapy) is the most used treatment to preserve the patient's eye. The goals of this work are to develop a software for monitoring the patient's eye during the treatment, in order to detect dislocation that could irradiate volumes outside the planned target. and to check the system with a mechanical eye simulator with controlled movements. The results have attested the accuracy and reproducibility of the system, validating the software.
1. Introduction Melanomas are tumours that begin in the melanocytes and are highly likely to become metastatic (Cruz and Lopes, 2009). Ocular melanomas, among to those that take place in structures surrounding the eye, correspond to approximately 5% of all melanomas. 85% of the ocular melanomas begin in the uveal tract (Cunha et al., 2010). Choroidal melanoma (CM) is a tumour arising in the layer of blood vessels, named choroid, located beneath the retina. It accounts for 68%–91% of melanomas occurring in the uvea (Cruz and Lopes, 2009) and affects 6 to 7 people per million inhabitants per year (Georgopoulos et al., 2003; Dunavoelgyi et al., 2011; Petersch et al., 2004). There are different approaches to treat this type of cancer, being teletherapy one of them, performed mostly with photon beams produced in a LINAC, but also with hadron beams as in proton therapy (Damato et al., 2005). Teletherapy with photons for choroidal melanoma is performed in multiple sessions and uses collimated photon beams (6 MV) directed to the planning target volume (PTV) which usually is larger than the tumor in order to account for uncertainties in general. This enlargement increases the risk of damaging the healthy tissues near the tumor. It is worth mentioning that some eye structures such as the optical nerve, lens, fovea and macula may be irradiated, what raises the probability of visual acuity loss. Souza et al. have shown that there are considerable
variation in the irradiated eye volume due to the patient positioning on different sessions and also due to the eye movement within the same session (Souza et al., 2018). The planning target volume is determined by the physicians considering a 3.5 mm margin to the gross tumor volume, meaning that healthy tissue around the tumor receives high doses. Several works have tried to reduce the effect in different ways. Bogner et al. have used a camera placed over the stereotactic mask that would allow the manual interruption of the beam when the displacement exceeds a giving limit (Bogner et al., 2003). Krema et al. have used a Gill-Thomas-Cosman head frame together with a movement tracking system coupled with an automatic beam interruption (Krema et al., 2009). Both systems used LED lamps as a non-invasive fixation system. These studies have shown, based on statistics, that non-invasive eye fixation mechanisms and monitoring with and without gating, are very useful to decrease the irradiation of non desired areas. Monitoring systems have been largely used, but to our knowledge none of them has been validated in a controlled environment. One of the key factors of the monitoring system is the reproducibility. Thus, our main goal is to develop a software for monitoring the patient's eye during the treatment together with a mechanical eye simulator of the eyeball movement for validating the system, providing information about the accuracy and precision.
∗ Corresponding author. Instituto de Física, Universidade Federal do Rio de Janeiro, Av. Athos da Silveira Ramos, 149 Centro de Tecnologia, bloco A, Cidade Universitária, Rio de Janeiro, RJ, CP: 68528, CEP: 21941-972, Brazil. E-mail address: [email protected] (O.D. Gonçalves).
https://doi.org/10.1016/j.radphyschem.2019.04.056 Received 15 December 2018; Received in revised form 27 April 2019; Accepted 28 April 2019 Available online 03 May 2019 0969-806X/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: Simone C. Cardoso, et al., Radiation Physics and Chemistry, https://doi.org/10.1016/j.radphyschem.2019.04.056
Radiation Physics and Chemistry xxx (xxxx) xxx–xxx
S.C. Cardoso, et al.
Fig. 1. (a) automated monitoring software algorithm flowchart; (b) matrix with threshold and blob detection applies.
2.2. Mechanical eye simulator The mechanical eye simulator was designed in order to validate the monitoring algorithm. The structure, based on a gyroscope, was built using a 3D printer (Cube 3D 3rd Generation). A pair of 28BYJ-48 5 V step motors were used to generate rotational movements on both axes. Both step motors are controlled by a Raspberry Pi 3 Model B that sends information to a controller board (ULN200) attached to the system. The movements are performed independently so that the mechanical eye could simulate a human one. The motors are used in a half-step mode, which increases the resolution of the mechanism, reaching approximately 0.1° in each half-step. The reproducibility and the relation between the number of steps and angular displacement were determined using a goniometer with 0.25° degree of resolution. This procedure allowed us to make a calibration curve relating the motor steps and angular displacement. Two home buttons were created in order to guarantee the reproducibility of the system origin (Souza et al., 2019). Fig. 2 shows the assembly of the simulator. An experimental setup was designed to evaluate the relationship between the sent information and the movement performed. A laser light reflected by a mirror placed in a plane tangent to the center of the pupil was projected over a ruler, turning possible to measure the displacement. The ruler was placed 1 m away from the mirror, therefore by geometry calculations it was possible to reach the angular displacement. The calculated uncertainty results mainly from the measurement process which translates the number of steps into linear displacement in a plane parallel to the plane of the camera. The schematic of experimental setup is shown in Fig. 3.
Fig. 2. Mechanical eye simulator.
2. Materials and methods 2.1. Eye position monitoring algorithm The software used in this work, written in Python®, was formerly presented in (Souza et al., 2019). It transforms the acquired RGB image into a grayscale and then a threshold is applied in order to convert the image into a binary scale. After the image processing, a Blob Detection method is used to determine the centroid of the pupil in each frame. The Xi and Yi positions are stored so that the pupil displacement can be calculated (Fig. 1).
Fig. 3. Schematic of experimental setup. 2
Radiation Physics and Chemistry xxx (xxxx) xxx–xxx
S.C. Cardoso, et al.
Fig. 4. Relationship between angular displacement and the number of motor steps. (a) horizontal; (b) vertical.
patient's ocular movement during treatment (Souza et al., 2018). 4. Conclusion The data show that the angular displacement depends, as expected, linearly on the number of motors steps. Therefore, the step motors are suitable to be used in this range to simulate the human eye movements with no need of further calibration factors. The range and accuracy level achieved by both the software and the eye simulator are between (0.21 ± 0.07) mm to (1.6 ± 0.1) mm within the range of movement of the patient's eye (1 mm) during treatment and therefore considered satisfactory to the purposes. The comparison of the displacement values performed by the mechanical eye and those obtained with the camera shows the reproducibility of the system. The software proved to be able to monitor the eye simulator movements in the corresponding range, which comprehends 98% of the human eye movements during the treatment of CM. This attests the system adequacy to be implemented into a clinical routine. .
Fig. 5. Angular displacement to linear displacement in a plane.
3. Results Fig. 4a and b show the relationship between the number of motor steps and the angular variation measured in the experimental setup. Each value corresponds to an average of six runs. The uncertainties considered are just the statistical ones. The values measured by the software were compared to those commanded to the mechanical eye. Fig. 6 shows the comparison. The chosen parameter to monitor the eye position is the distance between points measured on a plane tangent to the eyeball. The points are defined by intersections of the line defined by the center of the eyeball and the center of the iris with the plan. The eye movement is considered as being due to rotation around the center of the eyeball (see Fig. 5). being the linear movement range measured to be about 1 mm. The mechanical eye displacement varies from (0.21 ± 0.07) mm to (1.6 ± 0.1) mm, which corresponds to approximately 98% of the
Acknowledgments We would like to thank the Brazilians Comissão Nacional de Energia Nuclear (CNEN), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes) and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPQ) for financial support.
Fig. 6. Comparison between displacements performed by the mechanical eye simulator and detected by the monitoring software. The results are the mean value of five runs with the same commands and uncertainties were obtained by error propagation. (A) Comparison for Horizontal displacements. (B) Comparison for vertical displacements. 3
Radiation Physics and Chemistry xxx (xxxx) xxx–xxx
S.C. Cardoso, et al.
References
Georgopoulos, M., Zehetmayer, M., Ruhswurm, I., Toma-Bstaendig, S., Ségur-Eltz, N., Sacu, S., Menapace, R., 2003. Ophthalmologica 217 (5), 315–319. Krema, H., Somani, S., Sahgal, A., Xu, W., Heydarian, M., Payne, D., Lapierre, N., 2009. British J. Ophthalmol. 93 (9), 1172–1176. Petersch, B., Bogner, J., Dieckmann, K., Pötter, R., Georg, D., 2004. Med. Phys. 31 (12), 3521–3527. Souza, F.M.L., Goncalves, O.D., Batista, D.V.S., Cardoso, S.C., 2018. In: 9th Brazilian Congress on Metrology, 2017, Conf. Series: J. Phys. Conf. Ser. 975 (2018) 012038. Souza, F., Sousa, J.V.M., Goncalves, O.D., Batista, D.V.S., Cardoso, S.C., Pereira, D.D., 2019. World Congress on Medical Physics and Biomedical Engineering 2019. (3), 243–493-497.
Bogner, J., Petersch, B., Georg, D., Dieckmann, K., Zehetmayer, M., Pötter, R., 2003. Int. J. of Rad. Oncol. Biol.Phys. 56 (4), 1128–1136. Cruz, D.P., Lopes, J.M., 2009. Arquivos de medicina 23 (2), 45–57. Cunha, A.A.F.D., Rodrigues, N.H.T., Almeida, G.A., Picanço, B.C., Netto, J.A., 2010. Arq. Bras. Oftalmol. 73 (2), 193–196. Damato, Bertil, Kacperek, Andrzej, Chopra, Mona, Campbell, Ian R., Douglas Errington, R., 2005. Int. J. Radiat. Oncol. Biol. Phys. 62 (5), 1405–1411. Dunavoelgyi, R., Dieckmann, K., Gleiss, A., Sacu, S., Kircher, K., Georgopoulos, M., Georg, D., Zehetmayer, M., Poetter, R., 2011. Int. J. Radiat. Oncol. Biol. Phys. 81 (1), 199–205.
4
Contents lists available at ScienceDirect
Radiation Physics and Chemistry journal homepage: www.elsevier.com/locate/radphyschem
Validation of an automatic eye monitoring system for ocular tumours stereotactic radiotherapy Simone C. Cardosoa, Odair D. Gonçalvesa,∗, Juan V.M. de Sousaa,b, Felipe M.L. de Souzac, Dirceu D. Pereiraa,b a
Instituto de Física, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil Instituto de Radioproteção e Dosimetria, IRD/CNEN, Rio de Janeiro, Brazil c Escola Politécnica, Universidade Federal do Rio de Janeiro – UFRJ, Rio de Janeiro, Brazil b
A R T I C LE I N FO
A B S T R A C T
Keywords: Mechanical eye simulator Instrumentation Irradiation monitoring Stereotactic Radiotherapy
Choroidal melanoma is a type of tumour that appears in the back of the eye and can rapidly evolve into metastasis. For tumours in advanced stages and/or located near the retina, external beam radiotherapy (teletherapy) is the most used treatment to preserve the patient's eye. The goals of this work are to develop a software for monitoring the patient's eye during the treatment, in order to detect dislocation that could irradiate volumes outside the planned target. and to check the system with a mechanical eye simulator with controlled movements. The results have attested the accuracy and reproducibility of the system, validating the software.
1. Introduction Melanomas are tumours that begin in the melanocytes and are highly likely to become metastatic (Cruz and Lopes, 2009). Ocular melanomas, among to those that take place in structures surrounding the eye, correspond to approximately 5% of all melanomas. 85% of the ocular melanomas begin in the uveal tract (Cunha et al., 2010). Choroidal melanoma (CM) is a tumour arising in the layer of blood vessels, named choroid, located beneath the retina. It accounts for 68%–91% of melanomas occurring in the uvea (Cruz and Lopes, 2009) and affects 6 to 7 people per million inhabitants per year (Georgopoulos et al., 2003; Dunavoelgyi et al., 2011; Petersch et al., 2004). There are different approaches to treat this type of cancer, being teletherapy one of them, performed mostly with photon beams produced in a LINAC, but also with hadron beams as in proton therapy (Damato et al., 2005). Teletherapy with photons for choroidal melanoma is performed in multiple sessions and uses collimated photon beams (6 MV) directed to the planning target volume (PTV) which usually is larger than the tumor in order to account for uncertainties in general. This enlargement increases the risk of damaging the healthy tissues near the tumor. It is worth mentioning that some eye structures such as the optical nerve, lens, fovea and macula may be irradiated, what raises the probability of visual acuity loss. Souza et al. have shown that there are considerable
variation in the irradiated eye volume due to the patient positioning on different sessions and also due to the eye movement within the same session (Souza et al., 2018). The planning target volume is determined by the physicians considering a 3.5 mm margin to the gross tumor volume, meaning that healthy tissue around the tumor receives high doses. Several works have tried to reduce the effect in different ways. Bogner et al. have used a camera placed over the stereotactic mask that would allow the manual interruption of the beam when the displacement exceeds a giving limit (Bogner et al., 2003). Krema et al. have used a Gill-Thomas-Cosman head frame together with a movement tracking system coupled with an automatic beam interruption (Krema et al., 2009). Both systems used LED lamps as a non-invasive fixation system. These studies have shown, based on statistics, that non-invasive eye fixation mechanisms and monitoring with and without gating, are very useful to decrease the irradiation of non desired areas. Monitoring systems have been largely used, but to our knowledge none of them has been validated in a controlled environment. One of the key factors of the monitoring system is the reproducibility. Thus, our main goal is to develop a software for monitoring the patient's eye during the treatment together with a mechanical eye simulator of the eyeball movement for validating the system, providing information about the accuracy and precision.
∗ Corresponding author. Instituto de Física, Universidade Federal do Rio de Janeiro, Av. Athos da Silveira Ramos, 149 Centro de Tecnologia, bloco A, Cidade Universitária, Rio de Janeiro, RJ, CP: 68528, CEP: 21941-972, Brazil. E-mail address: [email protected] (O.D. Gonçalves).
https://doi.org/10.1016/j.radphyschem.2019.04.056 Received 15 December 2018; Received in revised form 27 April 2019; Accepted 28 April 2019 Available online 03 May 2019 0969-806X/ © 2019 Elsevier Ltd. All rights reserved.
Please cite this article as: Simone C. Cardoso, et al., Radiation Physics and Chemistry, https://doi.org/10.1016/j.radphyschem.2019.04.056
Radiation Physics and Chemistry xxx (xxxx) xxx–xxx
S.C. Cardoso, et al.
Fig. 1. (a) automated monitoring software algorithm flowchart; (b) matrix with threshold and blob detection applies.
2.2. Mechanical eye simulator The mechanical eye simulator was designed in order to validate the monitoring algorithm. The structure, based on a gyroscope, was built using a 3D printer (Cube 3D 3rd Generation). A pair of 28BYJ-48 5 V step motors were used to generate rotational movements on both axes. Both step motors are controlled by a Raspberry Pi 3 Model B that sends information to a controller board (ULN200) attached to the system. The movements are performed independently so that the mechanical eye could simulate a human one. The motors are used in a half-step mode, which increases the resolution of the mechanism, reaching approximately 0.1° in each half-step. The reproducibility and the relation between the number of steps and angular displacement were determined using a goniometer with 0.25° degree of resolution. This procedure allowed us to make a calibration curve relating the motor steps and angular displacement. Two home buttons were created in order to guarantee the reproducibility of the system origin (Souza et al., 2019). Fig. 2 shows the assembly of the simulator. An experimental setup was designed to evaluate the relationship between the sent information and the movement performed. A laser light reflected by a mirror placed in a plane tangent to the center of the pupil was projected over a ruler, turning possible to measure the displacement. The ruler was placed 1 m away from the mirror, therefore by geometry calculations it was possible to reach the angular displacement. The calculated uncertainty results mainly from the measurement process which translates the number of steps into linear displacement in a plane parallel to the plane of the camera. The schematic of experimental setup is shown in Fig. 3.
Fig. 2. Mechanical eye simulator.
2. Materials and methods 2.1. Eye position monitoring algorithm The software used in this work, written in Python®, was formerly presented in (Souza et al., 2019). It transforms the acquired RGB image into a grayscale and then a threshold is applied in order to convert the image into a binary scale. After the image processing, a Blob Detection method is used to determine the centroid of the pupil in each frame. The Xi and Yi positions are stored so that the pupil displacement can be calculated (Fig. 1).
Fig. 3. Schematic of experimental setup. 2
Radiation Physics and Chemistry xxx (xxxx) xxx–xxx
S.C. Cardoso, et al.
Fig. 4. Relationship between angular displacement and the number of motor steps. (a) horizontal; (b) vertical.
patient's ocular movement during treatment (Souza et al., 2018). 4. Conclusion The data show that the angular displacement depends, as expected, linearly on the number of motors steps. Therefore, the step motors are suitable to be used in this range to simulate the human eye movements with no need of further calibration factors. The range and accuracy level achieved by both the software and the eye simulator are between (0.21 ± 0.07) mm to (1.6 ± 0.1) mm within the range of movement of the patient's eye (1 mm) during treatment and therefore considered satisfactory to the purposes. The comparison of the displacement values performed by the mechanical eye and those obtained with the camera shows the reproducibility of the system. The software proved to be able to monitor the eye simulator movements in the corresponding range, which comprehends 98% of the human eye movements during the treatment of CM. This attests the system adequacy to be implemented into a clinical routine. .
Fig. 5. Angular displacement to linear displacement in a plane.
3. Results Fig. 4a and b show the relationship between the number of motor steps and the angular variation measured in the experimental setup. Each value corresponds to an average of six runs. The uncertainties considered are just the statistical ones. The values measured by the software were compared to those commanded to the mechanical eye. Fig. 6 shows the comparison. The chosen parameter to monitor the eye position is the distance between points measured on a plane tangent to the eyeball. The points are defined by intersections of the line defined by the center of the eyeball and the center of the iris with the plan. The eye movement is considered as being due to rotation around the center of the eyeball (see Fig. 5). being the linear movement range measured to be about 1 mm. The mechanical eye displacement varies from (0.21 ± 0.07) mm to (1.6 ± 0.1) mm, which corresponds to approximately 98% of the
Acknowledgments We would like to thank the Brazilians Comissão Nacional de Energia Nuclear (CNEN), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes) and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPQ) for financial support.
Fig. 6. Comparison between displacements performed by the mechanical eye simulator and detected by the monitoring software. The results are the mean value of five runs with the same commands and uncertainties were obtained by error propagation. (A) Comparison for Horizontal displacements. (B) Comparison for vertical displacements. 3
Radiation Physics and Chemistry xxx (xxxx) xxx–xxx
S.C. Cardoso, et al.
References
Georgopoulos, M., Zehetmayer, M., Ruhswurm, I., Toma-Bstaendig, S., Ségur-Eltz, N., Sacu, S., Menapace, R., 2003. Ophthalmologica 217 (5), 315–319. Krema, H., Somani, S., Sahgal, A., Xu, W., Heydarian, M., Payne, D., Lapierre, N., 2009. British J. Ophthalmol. 93 (9), 1172–1176. Petersch, B., Bogner, J., Dieckmann, K., Pötter, R., Georg, D., 2004. Med. Phys. 31 (12), 3521–3527. Souza, F.M.L., Goncalves, O.D., Batista, D.V.S., Cardoso, S.C., 2018. In: 9th Brazilian Congress on Metrology, 2017, Conf. Series: J. Phys. Conf. Ser. 975 (2018) 012038. Souza, F., Sousa, J.V.M., Goncalves, O.D., Batista, D.V.S., Cardoso, S.C., Pereira, D.D., 2019. World Congress on Medical Physics and Biomedical Engineering 2019. (3), 243–493-497.
Bogner, J., Petersch, B., Georg, D., Dieckmann, K., Zehetmayer, M., Pötter, R., 2003. Int. J. of Rad. Oncol. Biol.Phys. 56 (4), 1128–1136. Cruz, D.P., Lopes, J.M., 2009. Arquivos de medicina 23 (2), 45–57. Cunha, A.A.F.D., Rodrigues, N.H.T., Almeida, G.A., Picanço, B.C., Netto, J.A., 2010. Arq. Bras. Oftalmol. 73 (2), 193–196. Damato, Bertil, Kacperek, Andrzej, Chopra, Mona, Campbell, Ian R., Douglas Errington, R., 2005. Int. J. Radiat. Oncol. Biol. Phys. 62 (5), 1405–1411. Dunavoelgyi, R., Dieckmann, K., Gleiss, A., Sacu, S., Kircher, K., Georgopoulos, M., Georg, D., Zehetmayer, M., Poetter, R., 2011. Int. J. Radiat. Oncol. Biol. Phys. 81 (1), 199–205.
4