Impact of acquisition count statistics reduction and SUV discretization on PET radiomic features in pediatric 18F-FDG-PET/MRI examinations

Branchini, M.; Zorz, Alessandra; Zucchetta, Pietro; Bettinelli, Andrea; Monte, Francesca De; Cecchin, Diego; Paiusco, M.

doi:10.1016/j.ejmp.2019.03.005

Cited by 13 publications

(9 citation statements)

References 42 publications

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“…Gray‐level discretization is a necessary step for textural matrices creation, which also performs a beneficial noise‐reducing action. The optimal method of choice may be imaging modality dependent and has a significant impact on feature values and reproducibility . Many algorithms exist, which makes the discretization step a possible source of variation among software.…”

Section: Methodsmentioning

confidence: 99%

“…The optimal method of choice may be imaging modality dependent and has a significant impact on feature values and reproducibility. 25,[40][41][42] Many algorithms exist, which makes the discretization step a possible source of variation among software. Although IBEX includes discretization both as a preprocessing step and as section of the parent code of feature categories, none meets the IBSI requirements.…”

Section: B3 Gray-level Discretizationmentioning

confidence: 99%

“…At our institution, the image biomarker explorer (IBEX) is used for radiomic studies . Image biomarker explorer was made publicly available in 2015, 2 yr before the start of the standardization initiative.…”

Section: Introductionmentioning

confidence: 99%

“…24 At our institution, the image biomarker explorer (IBEX) 3 is used for radiomic studies. 25 Image biomarker explorer was made publicly available in 2015, 2 yr before the start of the standardization initiative. Since IBSI is increasingly becoming a global reference, it is now necessary to determine whether IBEX is compliant with IBSI.…”

Section: Introductionmentioning

confidence: 99%

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Technical Note: An IBEX adaption toward image biomarker standardization

et al. 2020

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Purpose Interest in the field of radiomics is rapidly growing because of its potential to characterize tumor phenotype and provide predictive and prognostic information. Nevertheless, the reproducibility and robustness of radiomics studies are hampered by the lack of standardization in feature definition and calculation. In the context of the image biomarker standardization initiative (IBSI), we investigated the grade of compliance of the image biomarker explorer (IBEX), a free open‐source radiomic software, and we developed and validated standardized‐IBEX (S‐IBEX), an adaptation of IBEX to IBSI. Methods Image biomarker explorer source code was checked against IBSI standard. Both the feature implementation and the overall image preprocessing chain were evaluated. Sections were re‐implemented wherever differences emerged: in particular, contour‐to‐binary‐mask conversion, image sub‐portion extraction, re‐segmentation, gray‐level discretization and interpolation were aligned to IBSI. All reported IBSI features were implemented in S‐IBEX. On a patient phantom, S‐IBEX was validated by benchmarking five different preprocessing configurations proposed by IBSI. Results Most IBEX feature definitions are IBSI compliant; however, IBEX preprocessing introduces non‐negligible nonconformities, resulting in feature values not aligned with the corresponding IBSI benchmarks. On the contrary, S‐IBEX features are in agreement with the standard regardless of preprocessing configurations: the percentage of features equal to their benchmark values ranges from 98.1% to 99.5%, with overall maximum percentage error below 1%. Moreover, the impact of noncompliant preprocessing steps has been assessed: in these cases, the percentage of features equal to the standard drops below 35%. Conclusions The use of standardized software for radiomic feature extraction is essential to ensure the reproducibility of results across different institutions, easing at the same time their external validation. This work presents and validates S‐IBEX, a free IBSI‐compliant software, developed upon IBEX, for feature extraction that is both easy to use and quantitatively accurate.

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Section: Methodsmentioning

confidence: 99%

Section: B3 Gray-level Discretizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Technical Note: An IBEX adaption toward image biomarker standardization

et al. 2020

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“…Furthermore, efforts are underway to replace the CT component of PET/CT, with its own unavoidable radiation dose delivery, with MRI; studies already are underway to define optimal amounts of tracer activity to administer in conjunction with PET/MRI technology for pediatric evaluations. 31 In summary, the article by Partington et al makes several important points. The prevalence of abnormal myocardial perfusion and ischemia findings among patients with CHD is quite high, and considering the seriousness of these and related deleterious conditions, it is important to monitor patients with CHD and intervene medically in an effective manner.…”

mentioning

confidence: 99%

Balancing risks and rewards in assessing pediatric heart disease

Nichols

Gecelter

Tosh

2021

Journal of Nuclear Cardiology

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Evaluation and optimization of radiomics features stability to respiratory motion in ¹⁸F‐FDG 3D PET imaging

Zhang

et al. 2021

Medical Physics

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Purpose To evaluate the impact of respiratory motion on radiomics features in 18F‐fluoro‐2‐deoxy‐D‐glucose three dimensional positron emission tomography (18F‐FDG 3D PET) imaging and optimize feature stability by combining preprocessing configurations and aggregation strategies. Methods An in‐house developed respiratory motion phantom was imaged in 3D PET scanner under nine respiratory patterns including one reference pattern. In total, 487 radiomics features were extracted for each respiratory pattern. Feature stability to respiratory motion was first evaluated by metrics of coefficient of variation (COV) and relative difference (RD) in a fixed preprocessing configuration. Further, one‐way ANOVA and trend analysis were performed to evaluate the impact of preprocessing configuration (voxel size, discretization scheme) and aggregation strategy on feature stability. Finally, an optimization framework was proposed by selected feature‐specific configurations with minimum COV value, and the diagnostic performance was validated in stable versus unstable features and fixed versus optimal features by a set of 46 patients with lung disease. Results PET radiomics features were sensitive to respiratory motion, only 79/487 (16%) features were identified to be very stable in the fixed configuration. Preprocessing configuration and aggregation strategy had an impact on feature stability. For different voxel size, bin number, bin size and aggregation strategy, 188/487 (39%), 70/487 (15%), 148/487 (30%), and 38/95 (29%) features appeared significant changes in feature stability. The optimized configuration had the potential to improve feature stability compared to fixed configuration, with the COV decreased from 22% ±24% to 16% ±20%. Regarding the diagnostic performance, the stable and optimal configuration features outperformed the unstable and fixed configuration features, respectively (AUC 0.88, 0.87 vs. 0.83, 0.85). Conclusions Respiratory motion shows considerable impact on feature stability in 3D PET imaging, while optimizing preprocessing configuration may improve feature stability and diagnostic performance.

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Impact of acquisition count statistics reduction and SUV discretization on PET radiomic features in pediatric 18F-FDG-PET/MRI examinations

Cited by 13 publications

References 42 publications

Technical Note: An IBEX adaption toward image biomarker standardization

Technical Note: An IBEX adaption toward image biomarker standardization

Balancing risks and rewards in assessing pediatric heart disease

Evaluation and optimization of radiomics features stability to respiratory motion in ¹⁸F‐FDG 3D PET imaging

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Impact of acquisition count statistics reduction and SUV discretization on PET radiomic features in pediatric 18F-FDG-PET/MRI examinations

Cited by 13 publications

References 42 publications

Technical Note: An IBEX adaption toward image biomarker standardization

Technical Note: An IBEX adaption toward image biomarker standardization

Balancing risks and rewards in assessing pediatric heart disease

Evaluation and optimization of radiomics features stability to respiratory motion in 18F‐FDG 3D PET imaging

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Evaluation and optimization of radiomics features stability to respiratory motion in ¹⁸F‐FDG 3D PET imaging