Cargando…

Combined quality and dose-volume histograms for assessing the predictive value of (99m)Tc-MAA SPECT/CT simulation for personalizing radioembolization treatment in liver metastatic colorectal cancer

BACKGROUND: The relationship between the mean absorbed dose delivered to the tumour and the outcome in liver metastases from colorectal cancer patients treated with radioembolization has already been presented in several studies. The optimization of the personalized therapeutic activity to be admini...

Descripción completa

Detalles Bibliográficos
Autores principales: Levillain, Hugo, Burghelea, Manuela, Derijckere, Ivan Duran, Guiot, Thomas, Gulyban, Akos, Vanderlinden, Bruno, Vouche, Michael, Flamen, Patrick, Reynaert, Nick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736450/
https://www.ncbi.nlm.nih.gov/pubmed/33315160
http://dx.doi.org/10.1186/s40658-020-00345-4
_version_ 1783622789033361408
author Levillain, Hugo
Burghelea, Manuela
Derijckere, Ivan Duran
Guiot, Thomas
Gulyban, Akos
Vanderlinden, Bruno
Vouche, Michael
Flamen, Patrick
Reynaert, Nick
author_facet Levillain, Hugo
Burghelea, Manuela
Derijckere, Ivan Duran
Guiot, Thomas
Gulyban, Akos
Vanderlinden, Bruno
Vouche, Michael
Flamen, Patrick
Reynaert, Nick
author_sort Levillain, Hugo
collection PubMed
description BACKGROUND: The relationship between the mean absorbed dose delivered to the tumour and the outcome in liver metastases from colorectal cancer patients treated with radioembolization has already been presented in several studies. The optimization of the personalized therapeutic activity to be administered is still an open challenge. In this context, how well the (99m)Tc-MAA SPECT/CT predicts the absorbed dose delivered by radioembolization is essential. This work aimed to analyse the differences between predictive (99m)Tc-MAA-SPECT/CT and post-treatment (90)Y-microsphere PET/CT dosimetry at different levels. Dose heterogeneity was compared voxel-to-voxel using the quality-volume histograms, subsequently used to demonstrate how it could be used to identify potential clinical parameters that are responsible for quantitative discrepancies between predictive and post-treatment dosimetry. RESULTS: We analysed 130 lesions delineated in twenty-six patients. Dose-volume histograms were computed from predictive and post-treatment dosimetry for all volumes: individual lesion, whole tumoural liver (TL) and non-tumoural liver (NTL). For all dose-volume histograms, the following indices were extracted: D(90), D(70), D(50), D(mean) and D(20). The results showed mostly no statistical differences between predictive and post-treatment dosimetries across all volumes and for all indices. Notably, the analysis showed no difference in terms of D(mean), confirming the results from previous studies. Quality factors representing the spread of the quality-volume histogram (QVH) curve around 0 (ideal QF = 0) were determined for lesions, TL and NTL. QVHs were classified into good (QF < 0.18), acceptable (0.18 ≤ QF < 0.3) and poor (QF ≥ 0.3) correspondence. For lesions and TL, dose- and quality-volume histograms are mostly concordant: 69% of lesions had a QF within good/acceptable categories (40% good) and 65% of TL had a QF within good/acceptable categories (23% good). For NTL, the results showed mixed results with 48% QF within the poor concordance category. Finally, it was demonstrated how QVH analysis could be used to define the parameters that predict the significant differences between predictive and post-treatment dose distributions. CONCLUSION: It was shown that the use of the QVH is feasible in assessing the predictive value of (99m)Tc-MAA SPECT/CT dosimetry and in estimating the absorbed dose delivered to liver metastases from colorectal cancer via (90)Y-microspheres. QVH analyses could be used in combination with DVH to enhance the predictive value of (99m)Tc-MAA SPECT/CT dosimetry and to assist personalized activity prescription. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-020-00345-4.
format Online
Article
Text
id pubmed-7736450
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-77364502020-12-17 Combined quality and dose-volume histograms for assessing the predictive value of (99m)Tc-MAA SPECT/CT simulation for personalizing radioembolization treatment in liver metastatic colorectal cancer Levillain, Hugo Burghelea, Manuela Derijckere, Ivan Duran Guiot, Thomas Gulyban, Akos Vanderlinden, Bruno Vouche, Michael Flamen, Patrick Reynaert, Nick EJNMMI Phys Original Research BACKGROUND: The relationship between the mean absorbed dose delivered to the tumour and the outcome in liver metastases from colorectal cancer patients treated with radioembolization has already been presented in several studies. The optimization of the personalized therapeutic activity to be administered is still an open challenge. In this context, how well the (99m)Tc-MAA SPECT/CT predicts the absorbed dose delivered by radioembolization is essential. This work aimed to analyse the differences between predictive (99m)Tc-MAA-SPECT/CT and post-treatment (90)Y-microsphere PET/CT dosimetry at different levels. Dose heterogeneity was compared voxel-to-voxel using the quality-volume histograms, subsequently used to demonstrate how it could be used to identify potential clinical parameters that are responsible for quantitative discrepancies between predictive and post-treatment dosimetry. RESULTS: We analysed 130 lesions delineated in twenty-six patients. Dose-volume histograms were computed from predictive and post-treatment dosimetry for all volumes: individual lesion, whole tumoural liver (TL) and non-tumoural liver (NTL). For all dose-volume histograms, the following indices were extracted: D(90), D(70), D(50), D(mean) and D(20). The results showed mostly no statistical differences between predictive and post-treatment dosimetries across all volumes and for all indices. Notably, the analysis showed no difference in terms of D(mean), confirming the results from previous studies. Quality factors representing the spread of the quality-volume histogram (QVH) curve around 0 (ideal QF = 0) were determined for lesions, TL and NTL. QVHs were classified into good (QF < 0.18), acceptable (0.18 ≤ QF < 0.3) and poor (QF ≥ 0.3) correspondence. For lesions and TL, dose- and quality-volume histograms are mostly concordant: 69% of lesions had a QF within good/acceptable categories (40% good) and 65% of TL had a QF within good/acceptable categories (23% good). For NTL, the results showed mixed results with 48% QF within the poor concordance category. Finally, it was demonstrated how QVH analysis could be used to define the parameters that predict the significant differences between predictive and post-treatment dose distributions. CONCLUSION: It was shown that the use of the QVH is feasible in assessing the predictive value of (99m)Tc-MAA SPECT/CT dosimetry and in estimating the absorbed dose delivered to liver metastases from colorectal cancer via (90)Y-microspheres. QVH analyses could be used in combination with DVH to enhance the predictive value of (99m)Tc-MAA SPECT/CT dosimetry and to assist personalized activity prescription. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-020-00345-4. Springer International Publishing 2020-12-14 /pmc/articles/PMC7736450/ /pubmed/33315160 http://dx.doi.org/10.1186/s40658-020-00345-4 Text en © The Author(s) 2020, corrected publication 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Original Research
Levillain, Hugo
Burghelea, Manuela
Derijckere, Ivan Duran
Guiot, Thomas
Gulyban, Akos
Vanderlinden, Bruno
Vouche, Michael
Flamen, Patrick
Reynaert, Nick
Combined quality and dose-volume histograms for assessing the predictive value of (99m)Tc-MAA SPECT/CT simulation for personalizing radioembolization treatment in liver metastatic colorectal cancer
title Combined quality and dose-volume histograms for assessing the predictive value of (99m)Tc-MAA SPECT/CT simulation for personalizing radioembolization treatment in liver metastatic colorectal cancer
title_full Combined quality and dose-volume histograms for assessing the predictive value of (99m)Tc-MAA SPECT/CT simulation for personalizing radioembolization treatment in liver metastatic colorectal cancer
title_fullStr Combined quality and dose-volume histograms for assessing the predictive value of (99m)Tc-MAA SPECT/CT simulation for personalizing radioembolization treatment in liver metastatic colorectal cancer
title_full_unstemmed Combined quality and dose-volume histograms for assessing the predictive value of (99m)Tc-MAA SPECT/CT simulation for personalizing radioembolization treatment in liver metastatic colorectal cancer
title_short Combined quality and dose-volume histograms for assessing the predictive value of (99m)Tc-MAA SPECT/CT simulation for personalizing radioembolization treatment in liver metastatic colorectal cancer
title_sort combined quality and dose-volume histograms for assessing the predictive value of (99m)tc-maa spect/ct simulation for personalizing radioembolization treatment in liver metastatic colorectal cancer
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7736450/
https://www.ncbi.nlm.nih.gov/pubmed/33315160
http://dx.doi.org/10.1186/s40658-020-00345-4
work_keys_str_mv AT levillainhugo combinedqualityanddosevolumehistogramsforassessingthepredictivevalueof99mtcmaaspectctsimulationforpersonalizingradioembolizationtreatmentinlivermetastaticcolorectalcancer
AT burgheleamanuela combinedqualityanddosevolumehistogramsforassessingthepredictivevalueof99mtcmaaspectctsimulationforpersonalizingradioembolizationtreatmentinlivermetastaticcolorectalcancer
AT derijckereivanduran combinedqualityanddosevolumehistogramsforassessingthepredictivevalueof99mtcmaaspectctsimulationforpersonalizingradioembolizationtreatmentinlivermetastaticcolorectalcancer
AT guiotthomas combinedqualityanddosevolumehistogramsforassessingthepredictivevalueof99mtcmaaspectctsimulationforpersonalizingradioembolizationtreatmentinlivermetastaticcolorectalcancer
AT gulybanakos combinedqualityanddosevolumehistogramsforassessingthepredictivevalueof99mtcmaaspectctsimulationforpersonalizingradioembolizationtreatmentinlivermetastaticcolorectalcancer
AT vanderlindenbruno combinedqualityanddosevolumehistogramsforassessingthepredictivevalueof99mtcmaaspectctsimulationforpersonalizingradioembolizationtreatmentinlivermetastaticcolorectalcancer
AT vouchemichael combinedqualityanddosevolumehistogramsforassessingthepredictivevalueof99mtcmaaspectctsimulationforpersonalizingradioembolizationtreatmentinlivermetastaticcolorectalcancer
AT flamenpatrick combinedqualityanddosevolumehistogramsforassessingthepredictivevalueof99mtcmaaspectctsimulationforpersonalizingradioembolizationtreatmentinlivermetastaticcolorectalcancer
AT reynaertnick combinedqualityanddosevolumehistogramsforassessingthepredictivevalueof99mtcmaaspectctsimulationforpersonalizingradioembolizationtreatmentinlivermetastaticcolorectalcancer