Multi-institutional Validation Study of Commercially Available Deformable Image Registration Software for Thoracic Images

Kadoya, Noriyuki; Nakajima, Yoshiyuki; Saito, Masahide; Miyabe, Yuki; Kurooka, Masahiko; Kito, Satoshi; Fujita, Yukio; Sasaki, Motoharu; Arai, Kazuhiro; Tani, Kensuke; Yagi, Masashi; Wakita, Akihisa; Tohyama, Naoki; Jingu, Keiichi

doi:10.1016/j.ijrobp.2016.05.012

Cited by 91 publications

(106 citation statements)

References 35 publications

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“…Nevertheless, the systems failed to map CTV with acceptable accuracy from the DVF2 data set: DSC and MDC were, respectively, 0.52 and 5.45 mm, and thus highlighting the importance of the type of deformation. Differently from other studies published during which DIR was performed between the inhale and exhale phases with DVF distributed on large volumes with smooth gradients, in this case, the deformation was driven by a shrinking volume that generates high localized deformations in 4π geometry. This situation is critical for the regularization term of the algorithm whose role is to smooth and maintain the DIR locally invertible.…”

Section: Discussionmentioning

confidence: 88%

“…Analogous conclusions were drawn by the second study, wherein all the algorithms reported sub‐voxel mean TREs in lung, but only a minority of them succeeded in obtaining similar accuracy in the liver and the potential for large maximum errors was highlighted. Finally, significant intercenter variability caused by the procedures adopted were reported by Kadoya …”

Section: Discussionmentioning

confidence: 93%

“…Although many commercial platforms are available, there is a lack of solid methods to provide DIR QA, resulting in fuzzy knowledge concerning the accuracy and reproducibility of these systems in typical clinical settings. Up to now, only four RT‐focused multi‐institutional studies evaluating the accuracy of DIR algorithms have been published: Kashani used a deformable physical lung phantom and evaluated 8 registration algorithms; Brock used 4D CT and MRI inhale and exhale reconstructed phases from the scans of lung and liver patients and evaluated 21 registration algorithms; Kadoya used the lung inhale and exhale images available on DIR‐lab [54] to evaluate various commercial systems. The first study showed that DIR accuracy depends on the type of algorithm, its implementation and is site‐specific.…”

Section: Discussionmentioning

confidence: 99%

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Performance of commercially available deformable image registration platforms for contour propagation using patient‐based computational phantoms: A multi‐institutional study

Loi¹,

Fusella

Lanzi

et al. 2018

Medical Physics

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Section: Discussionmentioning

confidence: 88%

Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Performance of commercially available deformable image registration platforms for contour propagation using patient‐based computational phantoms: A multi‐institutional study

Loi¹,

Fusella

Lanzi

et al. 2018

Medical Physics

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“…Kadoya et al [32] published a multi-institutional comparison study using 10 thoracic cancer patients with manually defined anatomical landmarks. Each institution reported DIR results of 10 patients’ data using commercial DIR softwares—RayStation (RaySearch Laboratories, Stockholm, Sweden), MIM Software (Cleveland, OH, USA), and Velocity (Varian Medical Systems, Palo Alto, CA, USA).…”

Section: Validation Of Dir Algorithmmentioning

confidence: 99%

Deformable image registration in radiation therapy

Kim

2017

Radiat Oncol J

120

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The number of imaging data sets has significantly increased during radiation treatment after introducing a diverse range of advanced techniques into the field of radiation oncology. As a consequence, there have been many studies proposing meaningful applications of imaging data set use. These applications commonly require a method to align the data sets at a reference. Deformable image registration (DIR) is a process which satisfies this requirement by locally registering image data sets into a reference image set. DIR identifies the spatial correspondence in order to minimize the differences between two or among multiple sets of images. This article describes clinical applications, validation, and algorithms of DIR techniques. Applications of DIR in radiation treatment include dose accumulation, mathematical modeling, automatic segmentation, and functional imaging. Validation methods discussed are based on anatomical landmarks, physical phantoms, digital phantoms, and per application purpose. DIR algorithms are also briefly reviewed with respect to two algorithmic components: similarity index and deformation models.

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“…To improve DIR accuracy, hybrid DIR has been recently developed and implemented in RayStation [27]. This has the potential to improve DIR accuracy, even with large interfractional organ motion [28]. Till now there has been no data showing the performance of hybrid DIR between planning CT and CBCT for the pelvic region.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the performance of deformable image registration between planning CT and CBCT images for the pelvic region: comparison between hybrid and intensity-based DIR

Takayama

Yamamoto

Ito

et al. 2017

Journal of Radiation Research

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This study aimed to evaluate the performance of the hybrid deformable image registration (DIR) method in comparison with intensity-based DIR for pelvic cone-beam computed tomography (CBCT) images, using intensity and anatomical information. Ten prostate cancer patients treated with intensity-modulated radiation therapy (IMRT) were studied. Nine or ten CBCT scans were performed for each patient. First, rigid registration was performed between the planning CT and all CBCT images using gold fiducial markers, and then DIR was performed. The Dice similarity coefficient (DSC) and center of mass (COM) displacement were used to evaluate the quantitative DIR accuracy. The average DSCs for intensity-based DIR for the prostate, rectum, bladder, and seminal vesicles were 0.84 ± 0.05, 0.75 ± 0.05, 0.69 ± 0.07 and 0.65 ± 0.11, respectively, whereas those values for hybrid DIR were 0.98 ± 0.00, 0.97 ± 0.01, 0.98 ± 0.00 and 0.94 ± 0.03, respectively (P < 0.05). The average COM displacements for intensity-based DIR for the prostate, rectum, bladder, and seminal vesicles were 2.0 ± 1.5, 3.7 ± 1.4, 7.8 ± 2.2 and 3.6 ± 1.2 mm, whereas those values for hybrid DIR were 0.1 ± 0.0, 0.3 ± 0.2, 0.2 ± 0.1 and 0.6 ± 0.6 mm, respectively (P < 0.05). These results showed that the DSC for hybrid DIR had a higher DSC value and smaller COM displacement for all structures and all patients, compared with intensity-based DIR. Thus, the accumulative dose based on hybrid DIR might be trusted as a high-precision dose estimation method that takes into account organ movement during treatment radiotherapy.

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Multi-institutional Validation Study of Commercially Available Deformable Image Registration Software for Thoracic Images

Cited by 91 publications

References 35 publications

Performance of commercially available deformable image registration platforms for contour propagation using patient‐based computational phantoms: A multi‐institutional study

Performance of commercially available deformable image registration platforms for contour propagation using patient‐based computational phantoms: A multi‐institutional study

Deformable image registration in radiation therapy

Evaluation of the performance of deformable image registration between planning CT and CBCT images for the pelvic region: comparison between hybrid and intensity-based DIR

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