TY - JOUR
T1 - The Effects of In-Plane Spatial Resolution on CT-Based Radiomic Features' Stability with and without ComBat Harmonization
AU - Ibrahim, Abdalla
AU - Refaee, Turkey
AU - Primakov, Sergey
AU - Barufaldi, Bruno
AU - Acciavatti, Raymond J.
AU - Granzier, Renee W. Y.
AU - Hustinx, Roland
AU - Mottaghy, Felix M.
AU - Woodruff, Henry C.
AU - Wildberger, Joachim E.
AU - Lambin, Philippe
AU - Maidment, Andrew D. A.
N1 - Funding Information:
Conflicts of Interest: Philippe Lambin reports, within and outside the submitted work, grants/ sponsored research agreements from radiomics SA, ptTheragnostic/DNAmito, Health Innovation Ventures. He received an advisor/presenter fee and/or reimbursement of travel costs/consultancy fee and/or in kind manpower contribution from radiomics SA, BHV, Merck, Varian, Elekta, pt-Theragnostic, BMS and Convert pharmaceuticals. Dr. Lambin has minority shares in the company radiomics SA, Convert pharmaceuticals, MedC2, and LivingMed Biotech, and he is co-inventor of two issued patents with royalties on radiomics (PCT/NL2014/050248, PCT/NL2014/050728) licensed to Radiomics SA and one issue patent on mtDNA (PCT/EP2014/059089) licensed to ptTher-agnostic/DNAmito, three non-patented invention (softwares) licensed to ptTheragnostic/DNAmito, Radiomics SA and Health Innovation Ventures and three non-issues, non-licensed patents on Deep Learning-Radiomics and LSRT (N2024482, N2024889, N2024889). He confirms that none of the above entities or funding was involved in the preparation of this paper. Dr. Woodruff has minority shares in the company OncoRadiomics. Dr. Mottaghy received an advisor fee and reimbursement of travel costs from Oncoradiomics. He reports institutional grants from GE and Nanomab outside the submitted work. Dr. Wildberger reports institutional grants from Agfa, Bard, Bayer, GE, Optimed, Philips, Siemens and personal fees (Speaker’s Bureau) from Bayer and Siemens outside the submitted work. The rest of coauthors declare no competing interest.
Funding Information:
Authors acknowledge financial support from ERC advanced grant (ERC-ADG-2015 n◦ 694812—Hypoximmuno). Authors also acknowledge financial support from the European Union’s Horizon 2020 research and innovation programme under grant agreement: ImmunoSABR n◦ 733008, MSCA-ITN-PREDICT n◦ 766276, CHAIMELEON n◦ 952172, EuCanImage n◦ 952103, TRANSCAN Joint Transnational Call 2016 (JTC2016 CLEARLY n◦ UM 2017-8295). Authors further acknowledge financial support by the Dutch Cancer Society (KWF Kankerbestrijding), Project number 12085/2018-2, and Maastricht-Liege Imaging Valley grant, project no. “DEEP-NUCLE”.
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/4
Y1 - 2021/4
N2 - Simple SummaryHandcrafted radiomic features (HRFs) are quantitative features extracted from medical images, and they are mined for associations with different clinical endpoints. While many studies reported on the potential of HRFs to unravel clinical endpoints, the sensitivity of HRFs to variations in scanning parameters is affecting the inclusion of radiomic signatures in clinical decision-making. In this study, we investigated the effects of variations in the in-plane resolution of scans, while all other scanning parameters were fixed. Moreover, we investigated the effects of ten different image resampling methods and ComBat harmonization on the reproducibility of HRFs. Our results show that the majority of HRFs are significantly and variably affected by the differences in in-plane resolution. The majority of image resampling methods resulted in a higher number of reproducible HRFs compared to ComBat harmonization. Our developed framework guides identifying the reproducible and harmonizable HRFs in different scenarios.While handcrafted radiomic features (HRFs) have shown promise in the field of personalized medicine, many hurdles hinder its incorporation into clinical practice, including but not limited to their sensitivity to differences in acquisition and reconstruction parameters. In this study, we evaluated the effects of differences in in-plane spatial resolution (IPR) on HRFs, using a phantom dataset (n = 14) acquired on two scanner models. Furthermore, we assessed the effects of interpolation methods (IMs), the choice of a new unified in-plane resolution (NUIR), and ComBat harmonization on the reproducibility of HRFs. The reproducibility of HRFs was significantly affected by variations in IPR, with pairwise concordant HRFs, as measured by the concordance correlation coefficient (CCC), ranging from 42% to 95%. The number of concordant HRFs (CCC > 0.9) after resampling varied depending on (i) the scanner model, (ii) the IM, and (iii) the NUIR. The number of concordant HRFs after ComBat harmonization depended on the variations between the batches harmonized. The majority of IMs resulted in a higher number of concordant HRFs compared to ComBat harmonization, and the combination of IMs and ComBat harmonization did not yield a significant benefit. Our developed framework can be used to assess the reproducibility and harmonizability of RFs.
AB - Simple SummaryHandcrafted radiomic features (HRFs) are quantitative features extracted from medical images, and they are mined for associations with different clinical endpoints. While many studies reported on the potential of HRFs to unravel clinical endpoints, the sensitivity of HRFs to variations in scanning parameters is affecting the inclusion of radiomic signatures in clinical decision-making. In this study, we investigated the effects of variations in the in-plane resolution of scans, while all other scanning parameters were fixed. Moreover, we investigated the effects of ten different image resampling methods and ComBat harmonization on the reproducibility of HRFs. Our results show that the majority of HRFs are significantly and variably affected by the differences in in-plane resolution. The majority of image resampling methods resulted in a higher number of reproducible HRFs compared to ComBat harmonization. Our developed framework guides identifying the reproducible and harmonizable HRFs in different scenarios.While handcrafted radiomic features (HRFs) have shown promise in the field of personalized medicine, many hurdles hinder its incorporation into clinical practice, including but not limited to their sensitivity to differences in acquisition and reconstruction parameters. In this study, we evaluated the effects of differences in in-plane spatial resolution (IPR) on HRFs, using a phantom dataset (n = 14) acquired on two scanner models. Furthermore, we assessed the effects of interpolation methods (IMs), the choice of a new unified in-plane resolution (NUIR), and ComBat harmonization on the reproducibility of HRFs. The reproducibility of HRFs was significantly affected by variations in IPR, with pairwise concordant HRFs, as measured by the concordance correlation coefficient (CCC), ranging from 42% to 95%. The number of concordant HRFs (CCC > 0.9) after resampling varied depending on (i) the scanner model, (ii) the IM, and (iii) the NUIR. The number of concordant HRFs after ComBat harmonization depended on the variations between the batches harmonized. The majority of IMs resulted in a higher number of concordant HRFs compared to ComBat harmonization, and the combination of IMs and ComBat harmonization did not yield a significant benefit. Our developed framework can be used to assess the reproducibility and harmonizability of RFs.
KW - COEFFICIENT
KW - IMAGES
KW - INFORMATION
KW - SCANNERS
KW - VOXEL SIZE
KW - harmonization
KW - image processing
KW - radiomics biomarkers
KW - reproducibility
KW - Image processing
KW - Harmonization
KW - Reproducibility
KW - Radiomics biomarkers
U2 - 10.3390/cancers13081848
DO - 10.3390/cancers13081848
M3 - Article
C2 - 33924382
SN - 2072-6694
VL - 13
JO - Cancers
JF - Cancers
IS - 8
M1 - 1848
ER -