The evaluation of a deformable image registration segmentation technique for semi-automating internal target volume (ITV) production from 4DCT images of lung stereotactic body radiotherapy (SBRT) patients

Speight, R.; Sykes, Jonathan; Lindsay, R. Bruce; Franks, K.; Thwaites, David

doi:10.1016/j.radonc.2010.12.007

Cited by 54 publications

(60 citation statements)

References 29 publications

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“…DIR also represents a significant time saving for clinicians. [15] DIR was also applied to evaluate intrafraction variability and deformation of the lumpectomy cavity, breast, and nearby organs by Glide-Hurst et al, and large variability were observed between them. [16] Despite these reports, few studies to date have evaluated the clinical impact of DIR in target volume definition of diagnostic PET/CT scan to planning CT for primary thoracic EC.…”

Section: Discussionmentioning

confidence: 99%

Comparative evaluation of target volumes defined by deformable and rigid registration of diagnostic PET/CT to planning CT in primary esophageal cancer

Guo

Li²,

Zhang³

et al. 2017

Medicine

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Background:To evaluate the geometrical differences of target volumes propagated by deformable image registration (DIR) and rigid image registration (RIR) to assist target volume delineation between diagnostic Positron emission tomography/computed tomography (PET/CT) and planning CT for primary esophageal cancer (EC).Methods:Twenty-five patients with EC sequentially underwent a diagnostic 18F-fluorodeoxyglucose (18F-FDG) PET/CT scan and planning CT simulation. Only 19 patients with maximum standardized uptake value (SUVmax) ≥ 2.0 of the primary volume were available. Gross tumor volumes (GTVs) were delineated using CT and PET display settings. The PET/CT images were then registered with planning CT using MIM software. Subsequently, the PET and CT contours were propagated by RIR and DIR to planning CT. The properties of these volumes were compared.Results:When GTVCT delineated on CT of PET/CT after both RIR and DIR was compared with GTV contoured on planning CT, significant improvements using DIR were observed in the volume, displacements of the center of mass (COM) in the 3-dimensional (3D) direction, and Dice similarity coefficient (DSC) (P = 0.003; 0.006; 0.014). Although similar improvements were not observed for the same comparison using DIR for propagated PET contours from diagnostic PET/CT to planning CT (P > 0.05), for DSC and displacements of COM in the 3D direction of PET contours, the DIR resulted in the improved volume of a large percentage of patients (73.7%; 68.45%; 63.2%) compared with RIR. For diagnostic CT-based contours or PET contours at SUV2.5 propagated by DIR with planning CT, the DSC and displacements of COM in 3D directions in the distal segment were significantly improved compared to the upper and middle segments (P > 0.05).Conclusion:We observed a trend that deformable registration might improve the overlap for gross target volumes from diagnostic PET/CT to planning CT. The distal EC might benefit more from DIR.

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Section: Discussionmentioning

confidence: 99%

Comparative evaluation of target volumes defined by deformable and rigid registration of diagnostic PET/CT to planning CT in primary esophageal cancer

Guo

Li²,

Zhang³

et al. 2017

Medicine

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“…Various deformable image registration methods [12,[16][17][18][19] and mechanical indices [20] have been surveyed to calculate the most accurate and robust deformation map as well as differentiation metric, respectively. We developed a workflow that processed breath-hold images at extreme tidal volumes and calculated the volume change and the elasticity of MPNs.…”

Section: Discussionmentioning

confidence: 99%

Noninvasive pulmonary nodule elastometry by CT and deformable image registration

Negahdar

Fasola

et al. 2015

Radiotherapy and Oncology

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“…Elekta's ABAS and Varian's IKOE (Varian Medical Systems, Inc., Palo Alto, CA) knowledge-based segmentation are also available. A number of papers show some success at propagating outlines from one image volume to another, for example between the phases of 4D CT, such as shown by Speight et al [8] using Elekta's ABAS, or between RTP and ontreatment images; in this case the ''atlas'' is patient specific and is more likely to be a close match to the patient's anatomy.…”

Section: Atlas-based Segmentation-greyscale With Prior Knowledgementioning

confidence: 99%

Automated delineation of radiotherapy volumes: are we going in the right direction?

Whitfield¹,

Price²,

Price³

et al. 2013

BJR

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ABSTRACT. Rapid and accurate delineation of target volumes and multiple organs at risk, within the enduring International Commission on Radiation Units and Measurement framework, is now hugely important in radiotherapy, owing to the rapid proliferation of intensity-modulated radiotherapy and the advent of four-dimensional image-guided adaption. Nevertheless, delineation is still generally clinically performed with little if any machine assistance, even though it is both time-consuming and prone to interobserver variation. Currently available segmentation tools include those based on image greyscale interrogation, statistical shape modelling and body atlas-based methods. However, all too often these are not able to match the accuracy of the expert clinician, which remains the universally acknowledged gold standard. In this article we suggest that current methods are fundamentally limited by their lack of ability to incorporate essential human clinical decision-making into the underlying models. Hybrid techniques that utilise prior knowledge, make sophisticated use of greyscale information and allow clinical expertise to be integrated are needed. This may require a change in focus from automated segmentation to machine-assisted delineation. Similarly, new metrics of image quality reflecting fitness for purpose would be extremely valuable. We conclude that methods need to be developed to take account of the clinician's expertise and honed visual processing capabilities as much as the underlying, clinically meaningful information content of the image data being interrogated. We illustrate our observations and suggestions through our own experiences with two software tools developed as part of research council-funded projects.

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The evaluation of a deformable image registration segmentation technique for semi-automating internal target volume (ITV) production from 4DCT images of lung stereotactic body radiotherapy (SBRT) patients

Cited by 54 publications

References 29 publications

Comparative evaluation of target volumes defined by deformable and rigid registration of diagnostic PET/CT to planning CT in primary esophageal cancer

Comparative evaluation of target volumes defined by deformable and rigid registration of diagnostic PET/CT to planning CT in primary esophageal cancer

Noninvasive pulmonary nodule elastometry by CT and deformable image registration

Automated delineation of radiotherapy volumes: are we going in the right direction?

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