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    Radial Data Mining to Identify Density-Dose Interactions That Predict Distant Failure Following SABR

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    Authors
    Davey, Angela
    van Herk, Marcel
    Faivre-Finn, Corinne
    McWilliam, Alan
    Issue Date
    2022
    
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    Abstract
    Purpose: Lower dose outside the planned treatment area in lung stereotactic radiotherapy has been linked to increased risk of distant metastasis (DM) possibly due to underdosage of microscopic disease (MDE). Independently, tumour density on pretreatment computed tomography (CT) has been linked to risk of MDE. No studies have investigated the interaction between imaging biomarkers and incidental dose. The interaction would showcase whether the impact of dose on outcome is dependent on imaging and, hence, if imaging could inform which patients require dose escalation outside the gross tumour volume (GTV). We propose an image-based data mining methodology to investigate density–dose interactions radially from the GTV to predict DM with no a priori assumption on location. Methods: Dose and density were quantified in 1-mm annuli around the GTV for 199 patients with early-stage lung cancer treated with 60 Gy in 5 fractions. Each annulus was summarised by three density and three dose parameters. For parameter combinations, Cox regressions were performed including a dose–density interaction in independent annuli. Heatmaps were created that described improvement in DM prediction due to the interaction. Regions of significant improvement were identified and studied in overall outcome models. Results: Dose–density interactions were identified that significantly improved prediction for over 50% of bootstrap resamples. Dose and density parameters were not significant when the interaction was omitted. Tumour density variance and high peritumour density were associated with DM for patients with more cold spots (less than 30-Gy EQD2) and non-uniform dose about 3 cm outside of the GTV. Associations identified were independent of the mean GTV dose. Conclusions: Patients with high tumour variance and peritumour density have increased risk of DM if there is a low and non-uniform dose outside the GTV. The dose regions are independent of tumour dose, suggesting that incidental dose may play an important role in controlling occult disease. Understanding such interactions is key to identifying patients who will benefit from dose-escalation. The methodology presented allowed spatial dose–density interactions to be studied at the exploratory stage for the first time. This could accelerate the clinical implementation of imaging biomarkers by demonstrating the impact of incidental dose for tumours of varying characteristics in routine data.
    Citation
    Davey A, van Herk M, Faivre-Finn C, McWilliam A. Radial Data Mining to Identify Density–Dose Interactions That Predict Distant Failure Following SABR. Vol. 12, Frontiers in Oncology. Frontiers Media SA; 2022.
    Journal
    Front Oncol
    URI
    http://hdl.handle.net/10541/625179
    DOI
    10.3389/fonc.2022.838155
    PubMed ID
    35356210
    Additional Links
    https://dx.doi.org/10.3389/fonc.2022.838155
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.3389/fonc.2022.838155
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