Biological impact of geometric uncertainties: what margin is needed for intra-hepatic tumors?

Feasibility and potential benefits of defining the internal gross tumor volume of hepatocellular carcinoma using contrast-enhanced 4D CT images obtained by deformable registration

Objective

To study the feasibility and the potential benefits of defining the internal gross tumor volume (IGTV) of hepatocellular carcinoma (HCC) using contrast-enhanced 4D CT images obtained by combining arterial-phase (AP) contrast-enhanced (CE) 3D CT and non-contrast-enhanced (NCE) 4D CT images using deformable registration (DR).

Methods

Ten HCC patients who had received radiotherapy beforehand were selected for this study. The following CT simulation images were acquired sequentially: NCE 4D CT in free breathing, NCE 3D CT and APCE 3D CT in end-expiration breath holding. All 4D CT images were sorted into ten phases according to breath cycle (CT₀₀ ~ CT₉₀). Gross tumor volumes (GTVs) were contoured on all CT images and the IGTV_-1 was obtained by merging the GTVs in each phase of 4D CT images. The GTV on the APCE 3D CT image was deformably registered to each 4D CT phase image according to liver shape using RayStation^TM 3.99.0.7 version treatment planning system. The IGTV_-DR was obtained by merging the GTVs after DR on the 4D CT images. Volume differences among the GTVs and between the IGTV_-1 and the IGTV_-DR were compared.

Results

The edge of most lesions could be definitively identified using APCE 3D CT images compared to NCE 4D and 3D CT images. The GTV volume on APCE 3D CT images increased by an average of 34.79% (P < 0.05). There was no significant difference among the GTV volumes obtained using NCE 4D and 3D CT images (P > 0.05). The GTV volumes after DR on 4D CT different phase images increased by an average of 36.29% (P < 0.05), as was observed using the APCE 3D CT image (P > 0.05). Lastly, the volume of IGTV_-DR increased by an average of 19.91% compared to that of IGTV_-1 (P < 0.05).

Conclusion

NCE 4D CT imaging alone has the potential risk of missing a partial volume of the HCC. The combination of APCE 3D CT and NCE 4D CT images using the DR technique improved the accuracy of the definition of the IGTV in HCC.

Multi-scale regularization approaches of non-parametric deformable registrations

Most deformation algorithms use a single-value smoother during optimization. We investigate multi-scale regularizations (smoothers) during the multi-resolution iteration of two non-parametric deformable registrations (demons and diffeomorphic algorithms) and compare them to a conventional single-value smoother. Our results show that as smoothers increase, their convergence rate decreases; however, smaller smoothers also have a large negative value of the Jacobian determinant suggesting that the one-to-one mapping has been lost; i.e., image morphology is not preserved. A better one-to-one mapping of the multi-scale scheme has also been established by the residual vector field measures. In the demons method, the multi-scale smoother calculates faster than the large single-value smoother (Gaussian kernel width larger than 0.5) and is equivalent to the smallest single-value smoother (Gaussian kernel width equals to 0.5 in this study). For the diffeomorphic algorithm, since our multi-scale smoothers were implemented at the deformation field and the update field, calculation times are longer. For the deformed images in this study, the similarity measured by mean square error, normal correlation, and visual comparisons show that the multi-scale implementation has better results than large single-value smoothers, and better or equivalent for smallest single-value smoother. Between the two deformable registrations, diffeormophic method constructs better coherence space of the deformation field while the deformation is large between images.