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An automatic registration method for pre- and post-interventional CT images for assessing treatment success in liver RFA treatment. / Luu, Ha Manh; Niessen, Wiro; Van Walsum, Theo; Klink, Camiel; Moelker, Adriaan.

In: Medical Physics, Vol. 42, No. 9, 2016, p. 5559-5567.

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Luu, Ha Manh ; Niessen, Wiro ; Van Walsum, Theo ; Klink, Camiel ; Moelker, Adriaan. / An automatic registration method for pre- and post-interventional CT images for assessing treatment success in liver RFA treatment. In: Medical Physics. 2016 ; Vol. 42, No. 9. pp. 5559-5567.

BibTeX

@article{5322db19e91c4c11a0fea3cfa966bf7e,
title = "An automatic registration method for pre- and post-interventional CT images for assessing treatment success in liver RFA treatment",
abstract = "Purpose: In image-guided radio frequency ablation for liver cancer treatment, pre- and post-interventional CT images are typically used to verify the treatment success of the therapy. In current clinical practice, the tumor zone in the diagnostic, preinterventional images is mentally or manually mapped to the ablation zone in the post-interventional images to decide success of the treatment. However, liver deformation and differences in image quality as well as in texture of the ablation zone and the tumor area make the mental or manual registration a challenging task. Purpose of this paper is to develop an automatic framework to register the pre-interventional image to the post-interventional image. Methods: The authors propose a registration approach enabling a nonrigid deformation of the tumor to the ablation zone, while keeping locally rigid deformation of the tumor area. The method was evaluated on CT images of 38 patient datasets from Erasmus MC. The evaluation is based on Dice coefficients of the liver segmentation on both the pre-interventional and post-interventional images, and mean distances between the liver segmentations. Additionally, residual distances after registration between corresponding landmarks and local mean surface distance in the images were computed. Results: The results show that rigid registration gives a Dice coefficient of 87.9{\%}, a mean distance of the liver surfaces of 5.53 mm, and a landmark error of 5.38 mm, while non-rigid registration with local rigid deformation has a Dice coefficient of 92.2{\%}, a mean distance between the liver segmentation boundaries near the tumor area of 3.83 mm, and a landmark error of 2.91 mm, where a part of this error can be attributed to the slice spacing in the authors' CT images. Conclusions: This method is thus a promising tool to assess the success of RFA liver cancer treatment.",
keywords = "CT image registration, local rigid deformation, non-rigid registration, RFA liver treatment",
author = "Luu, {Ha Manh} and Wiro Niessen and {Van Walsum}, Theo and Camiel Klink and Adriaan Moelker",
year = "2016",
doi = "10.1118/1.4927790",
language = "English",
volume = "42",
pages = "5559--5567",
journal = "Medical Physics",
issn = "0094-2405",
publisher = "AAPM - American Association of Physicists in Medicine",
number = "9",

}

RIS

TY - JOUR

T1 - An automatic registration method for pre- and post-interventional CT images for assessing treatment success in liver RFA treatment

AU - Luu, Ha Manh

AU - Niessen, Wiro

AU - Van Walsum, Theo

AU - Klink, Camiel

AU - Moelker, Adriaan

PY - 2016

Y1 - 2016

N2 - Purpose: In image-guided radio frequency ablation for liver cancer treatment, pre- and post-interventional CT images are typically used to verify the treatment success of the therapy. In current clinical practice, the tumor zone in the diagnostic, preinterventional images is mentally or manually mapped to the ablation zone in the post-interventional images to decide success of the treatment. However, liver deformation and differences in image quality as well as in texture of the ablation zone and the tumor area make the mental or manual registration a challenging task. Purpose of this paper is to develop an automatic framework to register the pre-interventional image to the post-interventional image. Methods: The authors propose a registration approach enabling a nonrigid deformation of the tumor to the ablation zone, while keeping locally rigid deformation of the tumor area. The method was evaluated on CT images of 38 patient datasets from Erasmus MC. The evaluation is based on Dice coefficients of the liver segmentation on both the pre-interventional and post-interventional images, and mean distances between the liver segmentations. Additionally, residual distances after registration between corresponding landmarks and local mean surface distance in the images were computed. Results: The results show that rigid registration gives a Dice coefficient of 87.9%, a mean distance of the liver surfaces of 5.53 mm, and a landmark error of 5.38 mm, while non-rigid registration with local rigid deformation has a Dice coefficient of 92.2%, a mean distance between the liver segmentation boundaries near the tumor area of 3.83 mm, and a landmark error of 2.91 mm, where a part of this error can be attributed to the slice spacing in the authors' CT images. Conclusions: This method is thus a promising tool to assess the success of RFA liver cancer treatment.

AB - Purpose: In image-guided radio frequency ablation for liver cancer treatment, pre- and post-interventional CT images are typically used to verify the treatment success of the therapy. In current clinical practice, the tumor zone in the diagnostic, preinterventional images is mentally or manually mapped to the ablation zone in the post-interventional images to decide success of the treatment. However, liver deformation and differences in image quality as well as in texture of the ablation zone and the tumor area make the mental or manual registration a challenging task. Purpose of this paper is to develop an automatic framework to register the pre-interventional image to the post-interventional image. Methods: The authors propose a registration approach enabling a nonrigid deformation of the tumor to the ablation zone, while keeping locally rigid deformation of the tumor area. The method was evaluated on CT images of 38 patient datasets from Erasmus MC. The evaluation is based on Dice coefficients of the liver segmentation on both the pre-interventional and post-interventional images, and mean distances between the liver segmentations. Additionally, residual distances after registration between corresponding landmarks and local mean surface distance in the images were computed. Results: The results show that rigid registration gives a Dice coefficient of 87.9%, a mean distance of the liver surfaces of 5.53 mm, and a landmark error of 5.38 mm, while non-rigid registration with local rigid deformation has a Dice coefficient of 92.2%, a mean distance between the liver segmentation boundaries near the tumor area of 3.83 mm, and a landmark error of 2.91 mm, where a part of this error can be attributed to the slice spacing in the authors' CT images. Conclusions: This method is thus a promising tool to assess the success of RFA liver cancer treatment.

KW - CT image registration

KW - local rigid deformation

KW - non-rigid registration

KW - RFA liver treatment

UR - http://www.scopus.com/inward/record.url?scp=84940706824&partnerID=8YFLogxK

U2 - 10.1118/1.4927790

DO - 10.1118/1.4927790

M3 - Article

VL - 42

SP - 5559

EP - 5567

JO - Medical Physics

T2 - Medical Physics

JF - Medical Physics

SN - 0094-2405

IS - 9

ER -

ID: 47147654