Publication

Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning

Burgos, N., Guerreiro, F., McClelland, J., Presles, B., Modat, M., Nill, S., Dearnaley, D., deSouza, N., Oelfke, U., Knopf, A-C., Ourselin, S. & Cardoso, M. J. 7-Jun-2017 In : Physics in Medicine and Biology. 62, 11, p. 4237-4253 17 p.

Research output: Scientific - peer-reviewArticle

APA

Burgos, N., Guerreiro, F., McClelland, J., Presles, B., Modat, M., Nill, S., ... Cardoso, M. J. (2017). Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning. Physics in Medicine and Biology, 62(11), 4237-4253. DOI: 10.1088/1361-6560/aa66bf

Author

Burgos, Ninon ; Guerreiro, Filipa ; McClelland, Jamie ; Presles, Benoit ; Modat, Marc ; Nill, Simeon ; Dearnaley, David ; deSouza, Nandita ; Oelfke, Uwe ; Knopf, Antje-Christin ; Ourselin, Sebastien ; Cardoso, M. Jorge. / Iterative framework for the joint segmentation and CT synthesis of MR images : application to MRI-only radiotherapy treatment planning. In: Physics in Medicine and Biology. 2017 ; Vol. 62, No. 11. pp. 4237-4253

Harvard

Burgos, N, Guerreiro, F, McClelland, J, Presles, B, Modat, M, Nill, S, Dearnaley, D, deSouza, N, Oelfke, U, Knopf, A-C, Ourselin, S & Cardoso, MJ 2017, 'Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning' Physics in Medicine and Biology, vol 62, no. 11, pp. 4237-4253. DOI: 10.1088/1361-6560/aa66bf

Standard

Iterative framework for the joint segmentation and CT synthesis of MR images : application to MRI-only radiotherapy treatment planning. / Burgos, Ninon; Guerreiro, Filipa; McClelland, Jamie; Presles, Benoit; Modat, Marc; Nill, Simeon; Dearnaley, David; deSouza, Nandita; Oelfke, Uwe; Knopf, Antje-Christin; Ourselin, Sebastien; Cardoso, M. Jorge.

In: Physics in Medicine and Biology, Vol. 62, No. 11, 07.06.2017, p. 4237-4253.

Research output: Scientific - peer-reviewArticle

Vancouver

Burgos N, Guerreiro F, McClelland J, Presles B, Modat M, Nill S et al. Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning. Physics in Medicine and Biology. 2017 Jun 7;62(11):4237-4253. Available from, DOI: 10.1088/1361-6560/aa66bf


BibTeX

@article{2c5c62e082a04d049b6aaff36c45a32b,
title = "Iterative framework for the joint segmentation and CT synthesis of MR images: application to MRI-only radiotherapy treatment planning",
abstract = "To tackle the problem of magnetic resonance imaging (MRI)-only radiotherapy treatment planning (RTP), we propose a multi-atlas information propagation scheme that jointly segments organs and generates pseudo x-ray computed tomography (CT) data from structural MR images (T1-weighted and T2-weighted). As the performance of the method strongly depends on the quality of the atlas database composed of multiple sets of aligned MR, CT and segmented images, we also propose a robust way of registering atlas MR and CT images, which combines structure-guided registration, and CT and MR image synthesis.We first evaluated the proposed framework in terms of segmentation and CT synthesis accuracy on 15 subjects with prostate cancer. The segmentations obtained with the proposed method were compared using the Dice score coefficient (DSC) to the manual segmentations. Mean DSCs of 0.73, 0.90, 0.77 and 0.90 were obtained for the prostate, bladder, rectum and femur heads, respectively. The mean absolute error (MAE) and the mean error (ME) were computed between the reference CTs (non-rigidly aligned to the MRs) and the pseudo CTs generated with the proposed method. The MAE was on average 45.7 +/- 4.6 HU and the ME -1.6 +/- 7.7 HU. We then performed a dosimetric evaluation by re-calculating plans on the pseudo CTs and comparing them to the plans optimised on the reference CTs. We compared the cumulative dose volume histograms (DVH) obtained for the pseudo CTs to the DVH obtained for the reference CTs in the planning target volume (PTV) located in the prostate, and in the organs at risk at different DVH points. We obtained average differences of -0.14% in the PTV for D-98%, and between -0.14% and 0.05% in the PTV, bladder, rectum and femur heads for D-mean and D-2%.Overall, we demonstrate that the proposed framework is able to automatically generate accurate pseudo CT images and segmentations in the pelvic region, potentially bypassing the need for CT scan for accurate RTP.",
keywords = "segmentation, image synthesis, atlas-based methods, pseudo CT, MRI-only RTP, RADIATION-THERAPY, ATTENUATION CORRECTION, ELECTRON-DENSITY, PSEUDO-CT, ATLAS, PROSTATE, BRAIN, REGISTRATION, GENERATION, FUSION",
author = "Ninon Burgos and Filipa Guerreiro and Jamie McClelland and Benoit Presles and Marc Modat and Simeon Nill and David Dearnaley and Nandita deSouza and Uwe Oelfke and Antje-Christin Knopf and Sebastien Ourselin and Cardoso, {M. Jorge}",
year = "2017",
month = "6",
doi = "10.1088/1361-6560/aa66bf",
volume = "62",
pages = "4237--4253",
journal = "Physics in Medicine and Biology",
issn = "0031-9155",
publisher = "IOP PUBLISHING LTD",
number = "11",

}

RIS

TY - JOUR

T1 - Iterative framework for the joint segmentation and CT synthesis of MR images

T2 - Physics in Medicine and Biology

AU - Burgos,Ninon

AU - Guerreiro,Filipa

AU - McClelland,Jamie

AU - Presles,Benoit

AU - Modat,Marc

AU - Nill,Simeon

AU - Dearnaley,David

AU - deSouza,Nandita

AU - Oelfke,Uwe

AU - Knopf,Antje-Christin

AU - Ourselin,Sebastien

AU - Cardoso,M. Jorge

PY - 2017/6/7

Y1 - 2017/6/7

N2 - To tackle the problem of magnetic resonance imaging (MRI)-only radiotherapy treatment planning (RTP), we propose a multi-atlas information propagation scheme that jointly segments organs and generates pseudo x-ray computed tomography (CT) data from structural MR images (T1-weighted and T2-weighted). As the performance of the method strongly depends on the quality of the atlas database composed of multiple sets of aligned MR, CT and segmented images, we also propose a robust way of registering atlas MR and CT images, which combines structure-guided registration, and CT and MR image synthesis.We first evaluated the proposed framework in terms of segmentation and CT synthesis accuracy on 15 subjects with prostate cancer. The segmentations obtained with the proposed method were compared using the Dice score coefficient (DSC) to the manual segmentations. Mean DSCs of 0.73, 0.90, 0.77 and 0.90 were obtained for the prostate, bladder, rectum and femur heads, respectively. The mean absolute error (MAE) and the mean error (ME) were computed between the reference CTs (non-rigidly aligned to the MRs) and the pseudo CTs generated with the proposed method. The MAE was on average 45.7 +/- 4.6 HU and the ME -1.6 +/- 7.7 HU. We then performed a dosimetric evaluation by re-calculating plans on the pseudo CTs and comparing them to the plans optimised on the reference CTs. We compared the cumulative dose volume histograms (DVH) obtained for the pseudo CTs to the DVH obtained for the reference CTs in the planning target volume (PTV) located in the prostate, and in the organs at risk at different DVH points. We obtained average differences of -0.14% in the PTV for D-98%, and between -0.14% and 0.05% in the PTV, bladder, rectum and femur heads for D-mean and D-2%.Overall, we demonstrate that the proposed framework is able to automatically generate accurate pseudo CT images and segmentations in the pelvic region, potentially bypassing the need for CT scan for accurate RTP.

AB - To tackle the problem of magnetic resonance imaging (MRI)-only radiotherapy treatment planning (RTP), we propose a multi-atlas information propagation scheme that jointly segments organs and generates pseudo x-ray computed tomography (CT) data from structural MR images (T1-weighted and T2-weighted). As the performance of the method strongly depends on the quality of the atlas database composed of multiple sets of aligned MR, CT and segmented images, we also propose a robust way of registering atlas MR and CT images, which combines structure-guided registration, and CT and MR image synthesis.We first evaluated the proposed framework in terms of segmentation and CT synthesis accuracy on 15 subjects with prostate cancer. The segmentations obtained with the proposed method were compared using the Dice score coefficient (DSC) to the manual segmentations. Mean DSCs of 0.73, 0.90, 0.77 and 0.90 were obtained for the prostate, bladder, rectum and femur heads, respectively. The mean absolute error (MAE) and the mean error (ME) were computed between the reference CTs (non-rigidly aligned to the MRs) and the pseudo CTs generated with the proposed method. The MAE was on average 45.7 +/- 4.6 HU and the ME -1.6 +/- 7.7 HU. We then performed a dosimetric evaluation by re-calculating plans on the pseudo CTs and comparing them to the plans optimised on the reference CTs. We compared the cumulative dose volume histograms (DVH) obtained for the pseudo CTs to the DVH obtained for the reference CTs in the planning target volume (PTV) located in the prostate, and in the organs at risk at different DVH points. We obtained average differences of -0.14% in the PTV for D-98%, and between -0.14% and 0.05% in the PTV, bladder, rectum and femur heads for D-mean and D-2%.Overall, we demonstrate that the proposed framework is able to automatically generate accurate pseudo CT images and segmentations in the pelvic region, potentially bypassing the need for CT scan for accurate RTP.

KW - segmentation

KW - image synthesis

KW - atlas-based methods

KW - pseudo CT

KW - MRI-only RTP

KW - RADIATION-THERAPY

KW - ATTENUATION CORRECTION

KW - ELECTRON-DENSITY

KW - PSEUDO-CT

KW - ATLAS

KW - PROSTATE

KW - BRAIN

KW - REGISTRATION

KW - GENERATION

KW - FUSION

U2 - 10.1088/1361-6560/aa66bf

DO - 10.1088/1361-6560/aa66bf

M3 - Article

VL - 62

SP - 4237

EP - 4253

JO - Physics in Medicine and Biology

JF - Physics in Medicine and Biology

SN - 0031-9155

IS - 11

ER -

ID: 42738319