Quantitative Magnetic Resonance Imaging for Biological Image-Guided Adaptive Radiotherapy

Houdt, Petra J. van; Yang, Yingli; Heide, Uulke A. van der

doi:10.3389/fonc.2020.615643

Cited by 48 publications

(52 citation statements)

References 132 publications

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“…The apparent diffusion coefficient has been correlated to cellularity in many tumour types 17 and has been linked to cell proliferation in head and neck squamous cell carcinoma 18 . During radiotherapy, early changes in ADC have been linked to treatment response outcomes for multiple tumour types, making it a potential candidate for biological image-guided adaptive radiotherapy on MRI guided radiotherapy systems 19 .…”

Section: Introductionmentioning

confidence: 99%

Radiomics feature stability of open-source software evaluated on apparent diffusion coefficient maps in head and neck cancer

Korte

Cárdenas

Hardcastle

et al. 2021

Sci Rep

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Radiomics is a promising technique for discovering image based biomarkers of therapy response in cancer. Reproducibility of radiomics features is a known issue that is addressed by the image biomarker standardisation initiative (IBSI), but it remains challenging to interpret previously published radiomics signatures. This study investigates the reproducibility of radiomics features calculated with two widely used radiomics software packages (IBEX, MaZda) in comparison to an IBSI compliant software package (PyRadiomics). Intensity histogram, shape and textural features were extracted from 334 diffusion weighted magnetic resonance images of 59 head and neck cancer (HNC) patients from the PREDICT-HN observational radiotherapy study. Based on name and linear correlation, PyRadiomics shares 83 features with IBEX and 49 features with MaZda, a sub-set of well correlated features are considered reproducible (IBEX: 15 features, MaZda: 18 features). We explore the impact of including non-reproducible radiomics features in a HNC radiotherapy response model. It is possible to classify equivalent patient groups using radiomic features from either software, but only when restricting the model to reliable features using a correlation threshold method. This is relevant for clinical biomarker validation trials as it provides a framework to assess the reproducibility of reported radiomic signatures from existing trials.

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Section: Introductionmentioning

confidence: 99%

Radiomics feature stability of open-source software evaluated on apparent diffusion coefficient maps in head and neck cancer

Korte

Cárdenas

Hardcastle

et al. 2021

Sci Rep

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“…Separate models were constructed for the D, f, and D* parameters. Fixed effects were fraction (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20), ROI (noncancerous prostate/tumor), ISUP group, ADT, and institute. The ISUP scores were divided into a low (ISUP score 1 and 2) and high (ISUP score 3,4, and 5) group.…”

Section: Statisticsmentioning

confidence: 99%

Daily Intravoxel Incoherent Motion (IVIM) In Prostate Cancer Patients During MR-Guided Radiotherapy—A Multicenter Study

et al. 2021

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PurposeDaily quantitative MR imaging during radiotherapy of cancer patients has become feasible with MRI systems integrated with linear accelerators (MR-linacs). Quantitative images could be used for treatment response monitoring. With intravoxel incoherent motion (IVIM) MRI, it is possible to acquire perfusion information without the use of contrast agents. In this multicenter study, daily IVIM measurements were performed in prostate cancer patients to identify changes that potentially reflect response to treatment.Materials and MethodsForty-three patients were included, treated with 20 fractions of 3 Gy on a 1.5 T MR-linac. IVIM measurements were performed on each treatment day. The diffusion coefficient (D), perfusion fraction (f), and pseudo-diffusion coefficient (D*) were calculated based on the median signal intensities in the non-cancerous prostate and the tumor. Repeatability coefficients (RCs) were determined based on the first two treatment fractions. Separate linear mixed-effects models were constructed for the three IVIM parameters.ResultsIn total, 726 fractions were analyzed. Pre-treatment average values, measured on the first fraction before irradiation, were 1.46 × 10−3 mm2/s, 0.086, and 28.7 × 10−3 mm2/s in the non-cancerous prostate and 1.19 × 10−3 mm2/s, 0.088, and 28.9 × 10−3 mm2/s in the tumor, for D, f, and D*, respectively. The repeatability coefficients for D, f, and D* in the non-cancerous prostate were 0.09 × 10−3 mm2/s, 0.05, and 15.3 × 10−3 mm2/s. In the tumor, these values were 0.44 × 10−3 mm2/s, 0.16, and 76.4 × 10−3 mm2/s. The mixed effects analysis showed an increase in D of the tumors over the course of treatment, while remaining stable in the non-cancerous prostate. The f and D* increased in both the non-cancerous prostate and tumor.ConclusionsIt is feasible to perform daily IVIM measurements on an MR-linac system. Although the repeatability coefficients were high, changes in IVIM perfusion parameters were measured on a group level, indicating that IVIM has potential for measuring treatment response.

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“…Various clinical applications of the MR-Linac [5][6][7][8][9] have used soft-tissue MRI contrast for target volume planning and for the sparing of organs at risk. In addition, advanced quantitative MRI sequences have been explored to obtain microstructural information throughout treatment on MR-guided radiotherapy systems [10,11], which could potentially be used to identify regions for dose intensification [12]. Chemical exchange saturation transfer (CEST) [13] MRI is capable of acquiring metabolic information and is sensitive to low (millimolar) metabolite concentrations.…”

Section: Introductionmentioning

confidence: 99%

Chemical exchange saturation transfer MRI in central nervous system tumours on a 1.5 T MR-Linac

Chan

Lawrence

Oglesby

et al. 2021

Radiotherapy and Oncology

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Quantitative Magnetic Resonance Imaging for Biological Image-Guided Adaptive Radiotherapy

Cited by 48 publications

References 132 publications

Radiomics feature stability of open-source software evaluated on apparent diffusion coefficient maps in head and neck cancer

Radiomics feature stability of open-source software evaluated on apparent diffusion coefficient maps in head and neck cancer

Daily Intravoxel Incoherent Motion (IVIM) In Prostate Cancer Patients During MR-Guided Radiotherapy—A Multicenter Study

Chemical exchange saturation transfer MRI in central nervous system tumours on a 1.5 T MR-Linac

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