Technical Note: <scp>DIRART</scp> – A software suite for deformable image registration and adaptive radiotherapy research

Yang, Deshan; Brame, S.; Naqa, Issam El; Aditya, Apte; Wu, Yu Te; Goddu, S; Mutic, Sasa; Deasy, Joseph O.; Low, Daniel A.

doi:10.1118/1.3521468

Cited by 83 publications

(43 citation statements)

References 59 publications

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“…the DIRART [17], were tested. These DIR algorithms includes four optical flow based methods: the Original Horn and Schunck (HSO), the Horn and Schunck with Issam's non-linear smoothness (HS_INLS), the combined Horn-Schunck and Lucas-Kanade (HSLK) and the iterative optical flow (IOF); one level-set based method: the original level set motion (OLSM); one demons based method: the double force demons (DFD), and one iterative method: the free form deformation (FFD).…”

Section: Dir Algorithmsmentioning

confidence: 99%

Evaluation of deformable image registration for contour propagation between CT and cone-beam CT images in adaptive head and neck radiotherapy

Zhang

Shi

et al. 2016

THC

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Abstract. Deformable image registration (DIR) is a critical technic in adaptive radiotherapy (ART) to propagate contours between planning computerized tomography (CT) images and treatment CT/Cone-beam CT (CBCT) image to account for organ deformation for treatment re-planning. To validate the ability and accuracy of DIR algorithms in organ at risk (OAR) contours mapping, seven intensity-based DIR strategies are tested on the planning CT and weekly CBCT images from six Head & Neck cancer patients who underwent a 6 ∼ 7 weeks intensity-modulated radiation therapy (IMRT). Three similarity metrics, i.e. the Dice similarity coefficient (DSC), the percentage error (PE) and the Hausdorff distance (HD), are employed to measure the agreement between the propagated contours and the physician delineated ground truths. It is found that the performance of all the evaluated DIR algorithms declines as the treatment proceeds. No statistically significant performance difference is observed between different DIR algorithms (p > 0.05), except for the double force demons (DFD) which yields the worst result in terms of DSC and PE. For the metric HD, all the DIR algorithms behaved unsatisfactorily with no statistically significant performance difference (p = 0.273). These findings suggested that special care should be taken when utilizing the intensitybased DIR algorithms involved in this study to deform OAR contours between CT and CBCT, especially for those organs with low contrast.

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Section: Dir Algorithmsmentioning

confidence: 99%

Evaluation of deformable image registration for contour propagation between CT and cone-beam CT images in adaptive head and neck radiotherapy

Zhang

Shi

et al. 2016

THC

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“…GTVs were contoured by veterinarians using pretreatment CT images. For each patient, pretreatment and midtreatment CT images were deformably registered by use of the optical flow algorithm (23), and the resulting transformations were applied to their respective PET data. This allowed for voxel-based comparisons of pretreatment and midtreatment tracer distributions.…”

Section: Methodsmentioning

confidence: 99%

Spatiotemporal Stability of Cu-ATSM and FLT Positron Emission Tomography Distributions During Radiation Therapy

Bradshaw

Yip

Jallow

et al. 2014

International Journal of Radiation Oncology*Biology*Physics

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Purpose In dose painting, in which functional imaging is used to define biological targets for radiation therapy dose escalation, changes in spatial distributions of biological properties during treatment can compromise the quality of therapy. The goal of this study was to assess the spatiotemporal stability of 2 potential dose painting target—dhypoxia and proliferation—in canine tumors during radiation therapy. Methods and Materials Twenty-two canine patients with sinonasal tumors (14 carcinoma and 8 sarcoma) were imaged before hypofractionated radiation therapy with copper(II)-diacetyl-bis(N4-methylthiosemicarbazone) (Cu-ATSM) positron emission tomography/computed tomography (PET/CT) for hypoxia and 3′-deoxy-3′-18F-fluorothymidine (FLT) PET/CT for proliferation. The FLT scans were repeated after 2 fractions and the Cu-ATSM scans after 3 fractions. Midtreatment PET/CT images were deformably registered to pretreatment PET/CT images. Voxel-based Spearman correlation coefficients quantified the spatial stability of Cu-ATSM and FLT uptake distributions between pretreatment and midtreatment scans. Paired t tests determined significant differences between the patients’ respective Cu-ATSM and FLT correlations coefficients. Standardized uptake value measures were also compared between pretreatment and midtreatment scans by use of paired t tests. Results Spatial distributions of Cu-ATSM and FLT uptake were stable through mid-treatment for both sarcomas and carcinomas: the population mean ± standard deviation in Spearman correlation coefficient was 0.88 ± 0.07 for Cu-ATSM and 0.79 ± 0.13 for FLT. The patients’ Cu-ATSM correlation coefficients were significantly higher than their respective FLT correlation coefficients (P=.001). Changes in Cu-ATSM SUV measures from pretreatment to midtreatment were histology dependent: carcinomas experienced significant decreases in Cu-ATSM uptake (P<.05), whereas sarcomas did not (P>.20). Both histologies experienced significant decreases in FLT uptake (P<.05). Conclusions Spatial distributions of Cu-ATSM were very stable after a few fractions of radiation therapy. FLT spatial distributions were generally stable early in therapy, although they were significantly less stable than Cu-ATSM distributions. Canine tumors had significantly lower proliferative activity at midtreatment than at pretreatment, and they experienced histology-dependent changes in Cu-ATSM uptake.

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“…Selection of the algorithm employed for this study was justified based on our previous study, 25 , 26 as well as those of other groups 15 , 17 who have similarly used it in the context of lung treatments. We have used the DIRART implementations (27) of these algorithms as these are freely available in the public domain and, thus, the present approach may be easily reproduced by interested readers. Furthermore, the calculated deformation vector fields (DVF) are accessible to the user for application to dose warping, which may not necessarily be the case for commercial software algorithms.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of dosimetric misrepresentations from 3D conventional planning of liver SBRT using 4D deformable dose integration

Yeo

Taylor

Supple

et al. 2014

J Applied Clin Med Phys

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The purpose of this study is to evaluate dosimetric errors in 3D conventional planning of stereotactic body radiotherapy (SBRT) by using a 4D deformable image registration (DIR)‐based dose‐warping and integration technique. Respiratory‐correlated 4D CT image sets with 10 phases were acquired for four consecutive patients with five liver tumors. Average intensity projection (AIP) images were used to generate 3D conventional plans of SBRT. Quasi‐4D path‐integrated dose accumulation was performed over all 10 phases using dose‐warping techniques based on DIR. This result was compared to the conventional plan in order to evaluate the appropriateness of 3D (static) dose calculations. In addition, we consider whether organ dose metrics derived from contours defined on the average intensity projection (AIP), or on a reference phase, provide the better approximation of the 4D values. The impact of using fewer (<10) phases was also explored. The AIP‐based 3D planning approach overestimated doses to targets by 1.4% to 8.7% (mean 4.2%) and underestimated dose to normal liver by up to 8% (mean −5.5%; range −2.3% to −8.0%), compared to the 4D methodology. The homogeneity of the dose distribution was overestimated when using conventional 3D calculations by up to 24%. OAR doses estimated by 3D planning were, on average, within 10% of the 4D calculations; however, differences of up to 100% were observed. Four‐dimensional dose calculation using 3 phases gave a reasonable approximation of that calculated from the full 10 phases for all patients, which is potentially useful from a workload perspective. 4D evaluation showed that conventional 3D planning on an AIP can significantly overestimate target dose (ITV and GTV+5mm), underestimate normal liver dose, and overestimate dose homogeneity. Implementing nonadaptive quasi‐4D dose calculation can highlight the potential limitation of 3D conventional SBRT planning and the resultant misrepresentations of dose in some regions affected by motion and deformation. Where the 4D approach is unavailable, contouring on the full expiration phase may yield more accurate dose calculations, most relevant in the case of the healthy liver, but the absolute dose differences are in general small for the other healthy organs. The technique has the potential to quantify under‐ and over‐dosage and improve treatment plan evaluation, retrospective plan analysis, and clinical outcome correlation.PACS numbers: 87.55.‐x, 87.55.D‐, 87.55.de, 87.55.dk, 87.55.Qr, 87.57.nj

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Technical Note: DIRART – A software suite for deformable image registration and adaptive radiotherapy research

Abstract: By exchanging data with treatment planning systems via DICOM-RT files and CERR, and by bringing image registration algorithms closer to radiotherapy applications, DIRART is potentially a convenient and flexible platform that may facilitate ART and DIR research. 0 2011 Ameri-

Cited by 83 publications

References 59 publications

Evaluation of deformable image registration for contour propagation between CT and cone-beam CT images in adaptive head and neck radiotherapy

Evaluation of deformable image registration for contour propagation between CT and cone-beam CT images in adaptive head and neck radiotherapy

Spatiotemporal Stability of Cu-ATSM and FLT Positron Emission Tomography Distributions During Radiation Therapy

Evaluation of dosimetric misrepresentations from 3D conventional planning of liver SBRT using 4D deformable dose integration

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