Evaluation of the Block Matching deformable registration algorithm in the field of head-and-neck adaptive radiotherapy

Phys Med. 2014 May;30(3):301-8. doi: 10.1016/j.ejmp.2013.09.001. Epub 2013 Oct 3.

Abstract

Background and purpose: To compare the accuracy of the Block Matching deformable registration (DIR) against rigid image registration (RIR) for head-and-neck multi-modal images CT to cone-beam CT (CBCT) registration.

Material and methods: Planning-CT and weekly CBCT of 10 patients were used for this study. Several volumes, including medullary canal (MC), thyroid cartilage (TC), hyoid bone (HB) and submandibular gland (SMG) were transposed from CT to CBCT images using either DIR or RIR. Transposed volumes were compared with the manual delineation of these volumes on every CBCT. The parameters of similarity used for analysis were: Dice Similarity Index (DSI), 95%-Hausdorff Distance (95%-HD) and difference of volumes (cc).

Results: With DIR, the major mean difference of volumes was -1.4 cc for MC, revealing limited under-segmentation. DIR limited variability of DSI and 95%-HD. It significantly improved DSI for TC and HB and 95%-HD for all structures but SMG. With DIR, mean 95%-HD (mm) was 3.01 ± 0.80, 5.33 ± 2.51, 4.99 ± 1.69, 3.07 ± 1.31 for MC, TC, HB and SMG, respectively. With RIR, it was 3.92 ± 1.86, 6.94 ± 3.98, 6.44 ± 3.37 and 3.41 ± 2.25, respectively.

Conclusion: Block Matching is a valid algorithm for deformable multi-modal CT to CBCT registration. Values of 95%-HD are useful for ongoing development of its application to the cumulative dose calculation.

Keywords: CT–CBCT registration; Deformable algorithm; Head and neck cancer.

Publication types

  • Evaluation Study

MeSH terms

  • Algorithms*
  • Cone-Beam Computed Tomography / methods*
  • Head and Neck Neoplasms / diagnostic imaging*
  • Head and Neck Neoplasms / radiotherapy*
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Observer Variation
  • Radiotherapy Planning, Computer-Assisted