Image-based lung functional radiotherapy planning for non-small cell lung cancer

Mounessi, F.; Eckardt, Jörg; Holstein, Arne; Ewig, Santiago; Könemann, Stefan

doi:10.1007/s00066-019-01518-6

Cited by 7 publications

(1 citation statement)

References 30 publications

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“…Then dose-volume metrics with functional information were raised, which used SPECT lung perfusion images to semi-quantitatively analyze the distribution of blood vessels and reflect pulmonary function [14]. Such functional dose metrics were shown the potential to reduce the radiation-induced lung toxicity and improve the prediction of RP risks than anatomical dose metrics [10,11,[15][16][17][18][19].…”

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confidence: 99%

A Unified Framework to Integrate SPECT Perfusion Imaging with Dose-volume Metrics for Estimation of Radiation Pneumonitis

Dai

Zheng

et al. 2020

Preprint

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Background: Single photon emission computed tomography (SPECT) images provides functional information in both diagnosis and radiation therapy. This study aimed to evaluate a unified framework of different approaches and find the optimal one in integrating SPECT lung perfusion imaging into radiotherapy to estimate radiation pneumonitis.Methods: Twenty-five patients with thoracic tumors were included in this study. All patients had SPECT perfusion imaging before radiotherapeutic treatment. The SPECT images were registered to the planning computed tomography (CT) via a rigid-body transformation. Then a unified framework was presented to integrate functional information with anatomical information to generate functional dose-volume parameters. The framework contained different mapping approaches using uniform, thresholding, linear or non-linear functions. To compare the different approaches in the unified framework, the ability of predicting lung toxicity outcome was evaluated via the receiver operating characteristic (ROC) curve analysis.Results: Functional dose-volume metrics defined using the linear function achieves the highest value of area under the curve (AUC), compared to those defined with the other three types of mapping functions. With the linear mapping function, significant factors for predicting radiation pneumonia (p < 0.05) includes the functional mean lung dose (fMLD) with the threshold of 50-100% and lung volume receiving more than 30 Gy dose (fV_30) with the threshold of 60-100%, among which fMLD showed the highest prediction accuracy (AUC=0.772, threshold=50-100%). Conclusions: We proposed a framework of functional dose-volume metrics to predict the outcome of radiation pneumonitis. The metrics using the linear function outperform the others.

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confidence: 99%

A Unified Framework to Integrate SPECT Perfusion Imaging with Dose-volume Metrics for Estimation of Radiation Pneumonitis

Dai

Zheng

et al. 2020

Preprint

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Incorporation of Functional Lung Imaging Into Radiation Therapy Planning in Patients With Lung Cancer: A Systematic Review and Meta-Analysis

Midroni,

Salunkhe,

Liu

et al. 2024

International Journal of Radiation Oncology*Biology*Physics

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Establishing a 4D-CT lung function related volumetric dose model to reduce radiation pneumonia

Liu,

et al. 2024

Sci Rep

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In order to study how to use pulmonary functional imaging obtained through 4D-CT fusion for radiotherapy planning, and transform traditional dose volume parameters into functional dose volume parameters, a functional dose volume parameter model that may reduce level 2 and above radiation pneumonia was obtained. 41 pulmonary tumor patients who underwent 4D-CT in our department from 2020 to 2023 were included. MIM Software (MIM 7.0.7; MIM Software Inc., Cleveland, OH, USA) was used to register adjacent phase CT images in the 4D-CT series. The three-dimensional displacement vector of CT pixels was obtained when changing from one respiratory state to another respiratory state, and this three-dimensional vector was quantitatively analyzed. Thus, a color schematic diagram reflecting the degree of changes in lung CT pixels during the breathing process, namely the distribution of ventilation function strength, is obtained. Finally, this diagram is fused with the localization CT image. Select areas with Jacobi > 1.2 as high lung function areas and outline them as fLung. Import the patient's DVH image again, fuse the lung ventilation image with the localization CT image, and obtain the volume of fLung different doses (V60, V55, V50, V45, V40, V35, V30, V25, V20, V15, V10, V5). Analyze the functional dose volume parameters related to the risk of level 2 and above radiation pneumonia using R language and create a predictive model. By using stepwise regression and optimal subset method to screen for independent variables V35, V30, V25, V20, V15, and V10, the prediction formula was obtained as follows: Risk = 0.23656–0.13784 * V35 + 0.37445 * V30-0.38317 * V25 + 0.21341 * V20-0.10209 * V15 + 0.03815 * V10. These six independent variables were analyzed using a column chart, and a calibration curve was drawn using the calibrate function. It was found that the Bias corrected line and the Apparent line were very close to the Ideal line, The consistency between the predicted value and the actual value is very good. By using the ROC function to plot the ROC curve and calculating the area under the curve: 0.8475, 95% CI 0.7237–0.9713, it can also be determined that the accuracy of the model is very high. In addition, we also used Lasso method and random forest method to filter out independent variables with different results, but the calibration curve drawn by the calibration function confirmed poor prediction performance. The function dose volume parameters V35, V30, V25, V20, V15, and V10 obtained through 4D-CT are key factors affecting radiation pneumonia. Establishing a predictive model can provide more accurate lung restriction basis for clinical radiotherapy planning.

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Image-based lung functional radiotherapy planning for non-small cell lung cancer

Cited by 7 publications

References 30 publications

A Unified Framework to Integrate SPECT Perfusion Imaging with Dose-volume Metrics for Estimation of Radiation Pneumonitis

A Unified Framework to Integrate SPECT Perfusion Imaging with Dose-volume Metrics for Estimation of Radiation Pneumonitis

Incorporation of Functional Lung Imaging Into Radiation Therapy Planning in Patients With Lung Cancer: A Systematic Review and Meta-Analysis

Establishing a 4D-CT lung function related volumetric dose model to reduce radiation pneumonia

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