Physical imaging phantoms for simulation of tumor heterogeneity in PET, CT, and MRI: An overview of existing designs

Valladares, Alejandra; Beyer, Thomas; Rausch, Ivo

doi:10.1002/mp.14045

Cited by 56 publications

(60 citation statements)

References 53 publications

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“…In Tables 1, 2, and 3, the studies are collected in one overview for all three modalities considered in this review: CT, MRI, and PET, respectively. A recent review provides an overview of existing phantoms that have been used for radiomics for all three modalities [120].…”

Section: Current Limitations In Radiomicsmentioning

confidence: 99%

Radiomics in medical imaging—“how-to” guide and critical reflection

et al. 2020

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Radiomics is a quantitative approach to medical imaging, which aims at enhancing the existing data available to clinicians by means of advanced mathematical analysis. Through mathematical extraction of the spatial distribution of signal intensities and pixel interrelationships, radiomics quantifies textural information by using analysis methods from the field of artificial intelligence. Various studies from different fields in imaging have been published so far, highlighting the potential of radiomics to enhance clinical decision-making. However, the field faces several important challenges, which are mainly caused by the various technical factors influencing the extracted radiomic features. The aim of the present review is twofold: first, we present the typical workflow of a radiomics analysis and deliver a practical "how-to" guide for a typical radiomics analysis. Second, we discuss the current limitations of radiomics, suggest potential improvements, and summarize relevant literature on the subject.

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Section: Current Limitations In Radiomicsmentioning

confidence: 99%

Radiomics in medical imaging—“how-to” guide and critical reflection

et al. 2020

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“…Due to concerns such as radiation dose to patients, comprehensive investigations of image acquisition’s effects on radiomics features have to rely on phantom studies. However, there is a significant disparity between tumor phenotypes that are seen in patient clinical CT images and traditional physical phantoms (e.g., simple shape, homogeneous density) ( 61 ).…”

Section: Image Acquisitionmentioning

confidence: 99%

Understanding Sources of Variation to Improve the Reproducibility of Radiomics

Zhao

2021

Front. Oncol.

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Radiomics is the method of choice for investigating the association between cancer imaging phenotype, cancer genotype and clinical outcome prediction in the era of precision medicine. The fast dispersal of this new methodology has benefited from the existing advances of the core technologies involved in radiomics workflow: image acquisition, tumor segmentation, feature extraction and machine learning. However, despite the rapidly increasing body of publications, there is no real clinical use of a developed radiomics signature so far. Reasons are multifaceted. One of the major challenges is the lack of reproducibility and generalizability of the reported radiomics signatures (features and models). Sources of variation exist in each step of the workflow; some are controllable or can be controlled to certain degrees, while others are uncontrollable or even unknown. Insufficient transparency in reporting radiomics studies further prevents translation of the developed radiomics signatures from the bench to the bedside. This review article first addresses sources of variation, which is illustrated using demonstrative examples. Then, it reviews a number of published studies and progresses made to date in the investigation and improvement of feature reproducibility and model performance. Lastly, it discusses potential strategies and practical considerations to reduce feature variability and improve the quality of radiomics study. This review focuses on CT image acquisition, tumor segmentation, quantitative feature extraction, and the disease of lung cancer.

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“…Since repeated injections of radioactive material is harmful to the human body, a medical phantom is usually modelled and used as a substitute. Thus, the need for an accurate depiction of tumour heterogeneity that is suitable for imaging characterization [5].…”

Section: Introductionmentioning

confidence: 99%

Development of 3D-Printed Heterogeneous Tumour Phantom for Quantitative Analysis in PET/CT Imaging

et al. 2021

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Tumours are heterogenous growths that consists of different types of cells with varying genetic expressions. The complex structure of the tumour makes cancer treatment difficult due to the heterogeneity of each of the cancer cells that react differently to radiation treatment. Therefore, effective treatment requires proper characterization of the tumour heterogeneity, which is difficult to be assessed by most of the current medical imaging technologies. The purpose of this study was to develop a 3D printed heterogenous tumour phantom with multiple compartments to simulate tumour heterogeneity and to assess the accuracy of tumour characterization using Positron Emission Tomography/Computed Tomography (PET/CT) imaging. The tumour phantom was designed and modelled using SolidWorks and then constructed using the fused deposition modelling (FDM) method of 3D printing with polylactide (PLA) filament as the material. Multiple layer of waterproof coating was applied and the phantom was carefully tested for any leakage prior to the study. Each of the compartments of the tumour phantom was filled with different activity of the radiopharmaceutical (18F-FDG). The phantom was then embedded in a water bath to simulate soft tissue and scanned under a PET/CT scanner using standard clinical protocol. The volume and radioactivity of each compartment were then measured using the clinical software as Standardized Uptake Values (SUVs). Results showed that PET/CT imaging able to delineate and quantify the radioactivity of each compartment within the tumour phantom, albeit some difficulties in detecting radioactivity below 100 μCi. Further research is required to improve the design of the tumour phantom to allow for easier injection of the radioactive solution as well as altering the dimensions of the internal compartments to better characterize actual tumour parameters.

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Physical imaging phantoms for simulation of tumor heterogeneity in PET, CT, and MRI: An overview of existing designs

Cited by 56 publications

References 53 publications

Radiomics in medical imaging—“how-to” guide and critical reflection

Radiomics in medical imaging—“how-to” guide and critical reflection

Understanding Sources of Variation to Improve the Reproducibility of Radiomics

Development of 3D-Printed Heterogeneous Tumour Phantom for Quantitative Analysis in PET/CT Imaging

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