Prediction of lung density changes after radiotherapy by cone beam computed tomography response markers and pre-treatment factors for non-small cell lung cancer patients

Bernchou, U.; Hansen, Olfred; Schytte, Tine; Bertelsen, Anders; Hope, Andrew; Moseley, D; Brink, Carsten

doi:10.1016/j.radonc.2015.07.021

Cited by 30 publications

(22 citation statements)

References 20 publications

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“…However, the model that combined CBCT and planning CT radiomics features did not yield an improved prediction capacity. Previous studies have shown that the CBCT imaging features could assess response to treatment and serve as an early biomarker . By summarizing previous research findings on NSCLC, we found that the radiomics features of CT and CBCT were interchangeable and that the radiomics features of the CBCT prior to the first fraction of treatment showed prognostic information for the overall survival of NSCLC patients acquired .…”

Section: Discussionsupporting

confidence: 70%

“…Previous studies have shown that the CBCT imaging features could assess response to treatment and serve as an early biomarker. 29,30 By summarizing previous research findings on NSCLC, we found that the radiomics features of CT and CBCT were interchangeable and that the radiomics features of the CBCT prior to the first fraction of treatment showed prognostic information for the overall survival of NSCLC patients acquired. 31 The radiomics features of CBCTs acquired early during a course of treatment may be associated with overall survival in locally advanced NSCLC.…”

Section: Discussionmentioning

confidence: 57%

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Cone‐beam CT radiomics features might improve the prediction of lung toxicity after SBRT in stage I NSCLC patients

et al. 2020

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Background Stereotactic body radiotherapy (SBRT) is the standard care for inoperable early stage non‐small cell lung cancer (NSCLC). The purpose of our study was to investigate whether a prediction model based on cone‐beam CT (CBCT) plus pretreatment CT radiomics features could improve the prediction of tumor control and lung toxicity after SBRT in comparison to a model based on pretreatment CT radiomics features alone. Methods A total of 34 cases of stage I NSCLC patients who received SBRT were included in the study. The pretreatment planning CT and serial CBCT radiomics features were analyzed using the imaging biomarker explorer (IBEX) software platform. Multivariate logistic regression was conducted for the association between progression‐free survival (PFS), lung toxicity and features. The predictive capabilities of the models based on CBCT and CT features were compared using receiver operating characteristic (ROC) curves. Results Five CBCT features and two planning CT features were correlated with disease progression. Six CBCT features and two planning CT features were related to lung injury. The ROC curves indicated that the model based on the CBCT plus planning CT features might be better than the model based on the planning CT features in predicting lung injury. The other ROC curves indicated that the model based on the planning CT features was similar to the model based on the CBCT plus planning CT features in predicting disease progression. Conclusions Both pretreatment CT and CBCT radiomics features could predict disease progression and lung injury. A model with CBCT plus pretreatment CT radiomics features might improve the prediction of lung toxicity in comparison with a model with pretreatment CT features alone. Key points Significant findings of the study: A model with cone‐beam CT radiomics features plus pre‐treatment CT radiomics features might improve the prediction of lung toxicity after SBRT in stage I NSCLC patients. What this study adds: In the prediction of PFS and lung toxicity in early‐stage NSCLC patients treated with SBRT, CBCT radiomics could be another effective method.

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Section: Discussionsupporting

confidence: 70%

Section: Discussionmentioning

confidence: 57%

Cone‐beam CT radiomics features might improve the prediction of lung toxicity after SBRT in stage I NSCLC patients

et al. 2020

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“…Over the last decade, research in Cone Beam CT (CBCT) based adaptive radiotherapy (ART) has seen a growing interest. Different uses of the three dimensional anatomical information obtained through CBCT based image guided radiotherapy (IGRT) have been investigated, such as CBCT based dose calculations [1][2][3][4][5] and tumour and normal tissue response during fractionated radiotherapy [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Accuracy of dose calculation based on artefact corrected Cone Beam CT images of lung cancer patients

Thing

Bernchou

Hansen

et al. 2017

Physics and Imaging in Radiation Oncology

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Background and purpose: Accurate Cone Beam CT (CBCT) based dose calculations are hindered by limited CBCT image quality. Using retrospective artefact corrections, this paper investigated the accuracy of dose calculations performed directly on CBCT images of lung cancer patients. Materials and methods: Dose calculations were made directly on clinical and artefact corrected CBCT images of 21 lung cancer patients with a re-simulation CT (rCT) image acquired during radiotherapy. The original treatment plan was copied to the rCT and CBCT images and dose was recalculated. Dose comparisons were made using gamma analysis and dose statistics. Gamma comparisons were made using 2%/2 mm and 1%/1 mm criteria, and pass rates of the clinical and improved CBCT images were calculated using the rCT based dose as reference. Results: Dose distributions calculated on the artefact corrected CBCT images had a median 2%/2 mm gamma pass rate of 99.4% when compared to the reference rCT. Doses calculated on the clinical CBCT images had a median 2%/2 mm gamma pass rate of 93.1%. Wilcoxon signed rank test showed the pass rates in the entire CBCT field of view different at p < 0:001. Clinical CBCT image based dose calculations overestimated the dose, while the improved CBCT doses were in closer agreement with the rCT doses. Conclusions: Comprehensive artefact correction of CBCT images allowed highly accurate dose calculations to be performed directly on CBCT images of lung cancer patients, following the standard CT-based workflow in a treatment planning system.

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“…In the new era of radiotherapy, kilovoltage cone beam computed tomography (CBCT) has become a potential tool for evaluating deviations in positioning set up and changes in organ dimensions during the course of treatment. These images provide the necessary anatomic information needed for correcting set up deviations [1][2][3][4][5]. The CBCT images offer a better picture of soft tissues by providing sufficient soft tissue contrast; thus enabling visualization of the target on a daily basis, compared with the traditional method of using megavoltage (MV) portal images.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Dosimetric Impacts of Cone Beam Computed Tomography–Based Volumetric Modulated Arc Therapy Planning

Noufal

Abdullah

Niyas

et al. 2016

Journal of Medical Imaging and Radiation Sciences

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Objective: To quantify the Hounsfield unit (HU) variations between computed tomography (CT) and cone beam CT (CBCT) and study its impact on volumetric modulated arc therapy (VMAT) plans. Methods: HU number variations in CT and CBCT images were evaluated using the Catphan-504 phantom, and changes in seven different materials within the phantom (air, polymethylpentene, low-density polyethylene, polystyrene, acrylic, Delrin, and Teflon) were studied. The HU variations in half-fan and full-fan modes of CBCT were evaluated. The effect of variations in the shape of the body cross sections was assessed by reducing the body of the Catphan by 0.5 cm and 1.0 cm. CBCT-based VMAT plans in 27 patients (10 prostate, 10 brain, and 7 head and neck (HN)) were compared with corresponding CT-based plans. The dosimetric variations were assessed referring to different points on the dose volume histogram (D 5% , D 50% , and D 95% for PTVs and D 1% , D max , and D mean for organs at risk). The relative percentage of difference (DD (%)) between CT-and CBCT-based VMAT plans were examined on these points. To evaluate the dosimetric accuracy, dose distributions were compared using Omnipro-I'mRT software. The VMAT plans were evaluated based on 3 mm-3%, 2 mm-2%, and 1 mm-1% gamma criteria. Results: The HU difference in CT and CBCT was highest for air, Delrin, and Teflon, whereas the difference was less than 20 HU for the other materials. The dose volume histograms of both CTand CBCT-based plans were in excellent agreement in both phantom and patients, except in HN cases where the difference was 7%. The average 3 mm-3% gamma pass points in brain, prostate, and HN patients were 97 AE 0.2%, 96 AE 0.06%, and 93.3 AE 1.1%, respectively. The gamma pass rates reduced to 88.8 AE 0.06%, 91 AE 0.04%, and 79 AE 6% in 2 mm-2%, and further declined to 76.6 AE 0.09%, 75.2 AE 0.5%, and 60 AE 6% using the stringent 1 mm-1% gamma criteria for brain, prostate, and HN cases, respectively. Conclusion: Based on the results of this study, it is our belief that CBCT images can be used as a tool for evaluating the dosimetric variation in patient VMAT plans. The author(s) has no financial disclosures or conflicts of interest to declare.

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Prediction of lung density changes after radiotherapy by cone beam computed tomography response markers and pre-treatment factors for non-small cell lung cancer patients

Cited by 30 publications

References 20 publications

Cone‐beam CT radiomics features might improve the prediction of lung toxicity after SBRT in stage I NSCLC patients

Cone‐beam CT radiomics features might improve the prediction of lung toxicity after SBRT in stage I NSCLC patients

Accuracy of dose calculation based on artefact corrected Cone Beam CT images of lung cancer patients

Analysis of Dosimetric Impacts of Cone Beam Computed Tomography–Based Volumetric Modulated Arc Therapy Planning

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