Biologically Targeted Radiation Therapy: Incorporating Patient-Specific Hypoxia Data Derived from Quantitative Magnetic Resonance Imaging

Her, Emily Jungmin; Haworth, Annette; Sun, Yu; Williams, Scott; Reynolds, Hayley M; Kennedy, Angel; Ebert, Martin A.

doi:10.3390/cancers13194897

Cited by 10 publications

(9 citation statements)

References 53 publications

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“…Imaging of hypoxia in prostate cancer using a radiogenomics approach has already become an attractive option for avoiding rectal and urinary bladder toxicity in men opting for hypofractionated external beam radiotherapy for localised PCa [ 57 ]. Tumour hypoxia has been established as a key biological phenomenon that determines the accumulation and propagation of cancer stem cells and has been implicated in increasing risks of metastases, as well as reducing the effectiveness of radical treatment, including surgery.…”

Section: Discussionmentioning

confidence: 99%

Radiogenomics Reveals Correlation between Quantitative Texture Radiomic Features of Biparametric MRI and Hypoxia-Related Gene Expression in Men with Localised Prostate Cancer

Ogbonnaya

Alsaedi

Alhussaini

et al. 2023

JCM

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Objectives: To perform multiscale correlation analysis between quantitative texture feature phenotypes of pre-biopsy biparametric MRI (bpMRI) and targeted sequence-based RNA expression for hypoxia-related genes. Materials and Methods: Images from pre-biopsy 3T bpMRI scans in clinically localised PCa patients of various risk categories (n = 15) were used to extract textural features. The genomic landscape of hypoxia-related gene expression was obtained using post-radical prostatectomy tissue for targeted RNA expression profiling using the TempO-sequence method. The nonparametric Games Howell test was used to correlate the differential expression of the important hypoxia-related genes with 28 radiomic texture features. Then, cBioportal was accessed, and a gene-specific query was executed to extract the Oncoprint genomic output graph of the selected hypoxia-related genes from The Cancer Genome Atlas (TCGA). Based on each selected gene profile, correlation analysis using Pearson’s coefficients and survival analysis using Kaplan–Meier estimators were performed. Results: The quantitative bpMR imaging textural features, including the histogram and grey level co-occurrence matrix (GLCM), correlated with three hypoxia-related genes (ANGPTL4, VEGFA, and P4HA1) based on RNA sequencing using the TempO-Seq method. Further radiogenomic analysis, including data accessed from the cBioportal genomic database, confirmed that overexpressed hypoxia-related genes significantly correlated with a poor survival outcomes, with a median survival ratio of 81.11:133.00 months in those with and without alterations in genes, respectively. Conclusion: This study found that there is a correlation between the radiomic texture features extracted from bpMRI in localised prostate cancer and the hypoxia-related genes that are differentially expressed. The analysis of expression data based on cBioportal revealed that these hypoxia-related genes, which were the focus of the study, are linked to an unfavourable survival outcomes in prostate cancer patients.

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Section: Discussionmentioning

confidence: 99%

Radiogenomics Reveals Correlation between Quantitative Texture Radiomic Features of Biparametric MRI and Hypoxia-Related Gene Expression in Men with Localised Prostate Cancer

Ogbonnaya

Alsaedi

Alhussaini

et al. 2023

JCM

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“…An alternative focal dose boosting approach is Biologically targeted Radiation Therapy (BiRT) which aims to deliver a non-uniform radiation dose distribution to the tumour according to its spatially defined biological characteristics [ 3 ]. The BiRT approach aims to eradicate the tumour while minimising radiation exposure to normal tissue, which requires an accurate delineation of the tumour at a voxel-wise level and an estimation of the tumour characteristics.…”

Section: Introductionmentioning

confidence: 99%

Detecting localised prostate cancer using radiomic features in PSMA PET and multiparametric MRI for biologically targeted radiation therapy

et al. 2023

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Background Prostate-Specific Membrane Antigen (PSMA) PET/CT and multiparametric MRI (mpMRI) are well-established modalities for identifying intra-prostatic lesions (IPLs) in localised prostate cancer. This study aimed to investigate the use of PSMA PET/CT and mpMRI for biologically targeted radiation therapy treatment planning by: (1) analysing the relationship between imaging parameters at a voxel-wise level and (2) assessing the performance of radiomic-based machine learning models to predict tumour location and grade. Methods PSMA PET/CT and mpMRI data from 19 prostate cancer patients were co-registered with whole-mount histopathology using an established registration framework. Apparent Diffusion Coefficient (ADC) maps were computed from DWI and semi-quantitative and quantitative parameters from DCE MRI. Voxel-wise correlation analysis was conducted between mpMRI parameters and PET Standardised Uptake Value (SUV) for all tumour voxels. Classification models were built using radiomic and clinical features to predict IPLs at a voxel level and then classified further into high-grade or low-grade voxels. Results Perfusion parameters from DCE MRI were more highly correlated with PET SUV than ADC or T2w. IPLs were best detected with a Random Forest Classifier using radiomic features from PET and mpMRI rather than either modality alone (sensitivity, specificity and area under the curve of 0.842, 0.804 and 0.890, respectively). The tumour grading model had an overall accuracy ranging from 0.671 to 0.992. Conclusions Machine learning classifiers using radiomic features from PSMA PET and mpMRI show promise for predicting IPLs and differentiating between high-grade and low-grade disease, which could be used to inform biologically targeted radiation therapy planning.

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“…PET-CT scans are not typically performed at multiple timepoints, however, because of isotope cost, scanning time, and additional radiation exposure that needs to be justified. Magnetic resonance imaging (MRI) has also shown potential as a non-ionizing modality for defining sub-volumes for escalation of radiation dose based on diffusion (27,28) and perfusion (29)(30)(31) biomarkers, or for predicting response with oxygen-sensitive MRI techniques using tissue and blood oxygen level dependent (TOLD/BOLD) signals with oxygen (32) or carbogen gas breathing challenge (33), reviewed elsewhere (34). Nonetheless, these methods have limited spatio-temporal resolution, comparatively long acquisition times, and may require exogenous contrast agents, with associated toxicity (35,36).…”

Section: Introductionmentioning

confidence: 99%

The Potential of Photoacoustic Imaging in Radiation Oncology

et al. 2022

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Radiotherapy is recognized globally as a mainstay of treatment in most solid tumors and is essential in both curative and palliative settings. Ionizing radiation is frequently combined with surgery, either preoperatively or postoperatively, and with systemic chemotherapy. Recent advances in imaging have enabled precise targeting of solid lesions yet substantial intratumoral heterogeneity means that treatment planning and monitoring remains a clinical challenge as therapy response can take weeks to manifest on conventional imaging and early indications of progression can be misleading. Photoacoustic imaging (PAI) is an emerging modality for molecular imaging of cancer, enabling non-invasive assessment of endogenous tissue chromophores with optical contrast at unprecedented spatio-temporal resolution. Preclinical studies in mouse models have shown that PAI could be used to assess response to radiotherapy and chemoradiotherapy based on changes in the tumor vascular architecture and blood oxygen saturation, which are closely linked to tumor hypoxia. Given the strong relationship between hypoxia and radio-resistance, PAI assessment of the tumor microenvironment has the potential to be applied longitudinally during radiotherapy to detect resistance at much earlier time-points than currently achieved by size measurements and tailor treatments based on tumor oxygen availability and vascular heterogeneity. Here, we review the current state-of-the-art in PAI in the context of radiotherapy research. Based on these studies, we identify promising applications of PAI in radiation oncology and discuss the future potential and outstanding challenges in the development of translational PAI biomarkers of early response to radiotherapy.

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Biologically Targeted Radiation Therapy: Incorporating Patient-Specific Hypoxia Data Derived from Quantitative Magnetic Resonance Imaging

Cited by 10 publications

References 53 publications

Radiogenomics Reveals Correlation between Quantitative Texture Radiomic Features of Biparametric MRI and Hypoxia-Related Gene Expression in Men with Localised Prostate Cancer

Radiogenomics Reveals Correlation between Quantitative Texture Radiomic Features of Biparametric MRI and Hypoxia-Related Gene Expression in Men with Localised Prostate Cancer

Detecting localised prostate cancer using radiomic features in PSMA PET and multiparametric MRI for biologically targeted radiation therapy

The Potential of Photoacoustic Imaging in Radiation Oncology

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