Quality assurance assessment of intra‐acquisition diffusion‐weighted and T2‐weighted magnetic resonance imaging registration and contour propagation for head and neck cancer radiotherapy
Abstract Background/Purpose Adequate image registration of anatomical and functional magnetic resonance imaging (MRI) scans is necessary for MR‐guided head and neck cancer (HNC) adaptive radiotherapy planning. Despite the quantitative capabilities of diffusion‐weighted imaging (DWI) MRI for treatment plan adaptation, geometric distortion remains a considerable limitation. Therefore, we systematically investigated various deformable image registration (DIR) methods to co‐register DWI and T2‐weighted (T2W) images. Materials/Methods We compared three commercial (ADMIRE, Velocity, Raystation) and three open‐source (Elastix with default settings [Elastix Default], Elastix with parameter set 23 [Elastix 23], Demons) post‐acquisition DIR methods applied to T2W and DWI MRI images acquired during the same imaging session in twenty immobilized HNC patients. In addition, we used the non‐registered images (None) as a control comparator. Ground‐truth segmentations of radiotherapy structures (tumour and organs at risk) were generated by a physician expert on both image sequences. For each registration approach, structures were propagated from T2W to DWI images. These propagated structures were then compared with ground‐truth DWI structures using the Dice similarity coefficient and mean surface distance. Results19 left submandibular glands, 18 right submandibular glands, 20 left parotid glands, 20 right parotid glands, 20 spinal cords, and 12 tumours were delineated. Most DIR methods took <30 s to execute per case, with the exception of Elastix 23 which took ∼458 s to execute per case. ADMIRE and Elastix 23 demonstrated improved performance over None for all metrics and structures (Bonferroni‐corrected p < 0.05), while the other methods did not. Moreover, ADMIRE and Elastix 23 significantly improved performance in individual and pooled analysis compared to all other methods. Conclusions The ADMIRE DIR method offers improved geometric performance with reasonable execution time so should be favoured for registering T2W and DWI images acquired during the same scan session in HNC patients. These results are important to ensure the appropriate selection of registration strategies for MR‐guided radiotherapy..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:50 |
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| Enthalten in: |
Medical Physics - 50(2023), 4, Seite 2089-2099 |
| Beteiligte Personen: |
Naser, Mohamed A. [VerfasserIn] |
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| Anmerkungen: |
© 2023 American Association of Physicists in Medicine. |
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| Umfang: |
11 |
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| doi: |
10.1002/mp.16128 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
WLY016430921 |
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| 100 | 1 | |a Naser, Mohamed A. |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Quality assurance assessment of intra‐acquisition diffusion‐weighted and T2‐weighted magnetic resonance imaging registration and contour propagation for head and neck cancer radiotherapy |
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| 520 | |a Abstract Background/Purpose Adequate image registration of anatomical and functional magnetic resonance imaging (MRI) scans is necessary for MR‐guided head and neck cancer (HNC) adaptive radiotherapy planning. Despite the quantitative capabilities of diffusion‐weighted imaging (DWI) MRI for treatment plan adaptation, geometric distortion remains a considerable limitation. Therefore, we systematically investigated various deformable image registration (DIR) methods to co‐register DWI and T2‐weighted (T2W) images. Materials/Methods We compared three commercial (ADMIRE, Velocity, Raystation) and three open‐source (Elastix with default settings [Elastix Default], Elastix with parameter set 23 [Elastix 23], Demons) post‐acquisition DIR methods applied to T2W and DWI MRI images acquired during the same imaging session in twenty immobilized HNC patients. In addition, we used the non‐registered images (None) as a control comparator. Ground‐truth segmentations of radiotherapy structures (tumour and organs at risk) were generated by a physician expert on both image sequences. For each registration approach, structures were propagated from T2W to DWI images. These propagated structures were then compared with ground‐truth DWI structures using the Dice similarity coefficient and mean surface distance. Results19 left submandibular glands, 18 right submandibular glands, 20 left parotid glands, 20 right parotid glands, 20 spinal cords, and 12 tumours were delineated. Most DIR methods took <30 s to execute per case, with the exception of Elastix 23 which took ∼458 s to execute per case. ADMIRE and Elastix 23 demonstrated improved performance over None for all metrics and structures (Bonferroni‐corrected p < 0.05), while the other methods did not. Moreover, ADMIRE and Elastix 23 significantly improved performance in individual and pooled analysis compared to all other methods. Conclusions The ADMIRE DIR method offers improved geometric performance with reasonable execution time so should be favoured for registering T2W and DWI images acquired during the same scan session in HNC patients. These results are important to ensure the appropriate selection of registration strategies for MR‐guided radiotherapy. | ||
| 700 | 1 | |a Wahid, Kareem A. |4 aut | |
| 700 | 1 | |a Ahmed, Sara |4 aut | |
| 700 | 1 | |a Salama, Vivian |4 aut | |
| 700 | 1 | |a Dede, Cem |4 aut | |
| 700 | 1 | |a Edwards, Benjamin W. |4 aut | |
| 700 | 1 | |a Lin, Ruitao |4 aut | |
| 700 | 1 | |a McDonald, Brigid |4 aut | |
| 700 | 1 | |a Salzillo, Travis C. |4 aut | |
| 700 | 1 | |a He, Renjie |4 aut | |
| 700 | 1 | |a Ding, Yao |4 aut | |
| 700 | 1 | |a Abdelaal, Moamen Abobakr |4 aut | |
| 700 | 1 | |a Thill, Daniel |4 aut | |
| 700 | 1 | |a O'Connell, Nicolette |4 aut | |
| 700 | 1 | |a Willcut, Virgil |4 aut | |
| 700 | 1 | |a Christodouleas, John P. |4 aut | |
| 700 | 1 | |a Lai, Stephen Y. |4 aut | |
| 700 | 1 | |a Fuller, Clifton D. |4 aut | |
| 700 | 1 | |a Mohamed, Abdallah S. R. |4 aut | |
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