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Framework for radiation pneumonitis risk stratification based on anatomic and perfused lung dosimetry.

ABSTRACT: To design and apply a framework for predicting symptomatic radiation pneumonitis in patients undergoing thoracic radiation, using both pretreatment anatomic and perfused lung dose-volume parameters.Radiation treatment planning CT scans were coregistered with pretreatment [99mTc]MAA perfusion SPECT/CT scans of 20 patients who underwent definitive thoracic radiation. Clinical radiation pneumonitis was defined as grade ? 2 (CTCAE v4 grading system). Anatomic lung dose-volume parameters were collected from the treatment planning scans. Perfusion dose-volume parameters were calculated from pretreatment SPECT/CT scans. Equivalent doses in 2?Gy per fraction were calculated in the lung to account for differences in treatment regimens and spatial variations in lung dose (EQD2lung).Anatomic lung dosimetric parameters (MLD) and functional lung dosimetric parameters (pMLD70%) were identified as candidate predictors of grade ? 2 radiation pneumonitis (AUC > 0.93, p < 0.01). Pairing of an anatomic and functional dosimetric parameter (e.?g., MLD and pMLD70%) may further improve prediction accuracy. Not all individuals with high anatomic lung dose (MLD > 13.6 GyEQD2lung, 19.3?Gy for patients receiving 60?Gy in 30 fractions) developed radiation pneumonitis, but all individuals who also had high mean dose to perfused lung (pMLD70% > 13.3 GyEQD2) developed radiation pneumonitis.The preliminary application of this framework revealed differences between anatomic and perfused lung dosimetry in this limited patient cohort. The addition of perfused lung parameters may help risk stratify patients for radiation pneumonitis, especially in treatment plans with high anatomic mean lung dose. Further investigations are warranted.

SUBMITTER: Dhami G

PROVIDER: S-EPMC5406240 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Framework for radiation pneumonitis risk stratification based on anatomic and perfused lung dosimetry.

Dhami Gurleen G Zeng Jing J Vesselle Hubert J HJ Kinahan Paul E PE Miyaoka Robert S RS Patel Shilpen A SA Rengan Ramesh R Bowen Stephen R SR

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] 20170302 5

<h4>Purpose</h4>To design and apply a framework for predicting symptomatic radiation pneumonitis in patients undergoing thoracic radiation, using both pretreatment anatomic and perfused lung dose-volume parameters.<h4>Materials and methods</h4>Radiation treatment planning CT scans were coregistered with pretreatment [<sup>99m</sup>Tc]MAA perfusion SPECT/CT scans of 20 patients who underwent definitive thoracic radiation. Clinical radiation pneumonitis was defined as grade ≥ 2 (CTCAE v4 grading s ...[more]

PMID: 28255667

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Project description:PurposeTo determine clinically helpful dose-volume and clinical metrics correlating with symptomatic radiation pneumonitis (RP) in malignant pleural mesothelioma (MPM) patients with 2 lungs treated with hemithoracic intensity modulated pleural radiation therapy (IMPRINT).Methods and materialsTreatment plans and resulting normal organ dose-volume histograms of 103 consecutive MPM patients treated with IMPRINT (February 2005 to January 2015) to the highest dose ≤50.4 Gy satisfying departmental normal tissue constraints were uniformly recalculated. Patient records provided maximum RP grade (Common Terminology Criteria for Toxicity and Adverse Event version 4.0) and clinical and demographic information. Correlations analyzed with the Cox model were grade ≥2 RP (RP2+) and grade ≥3 RP (RP3+) with clinical variables, with volumes of planning target volume (PTV) and PTV-lung overlap and with mean dose, percent volume receiving dose D (VD), highest dose encompassing % volume V, (DV), and heart, total, ipsilateral, and contralateral lung volumes.ResultsTwenty-seven patients had RP2+ (14 with RP3+). The median prescription dose was 46.8 Gy (39.6-50.4 Gy, 1.8 Gy/fraction). The median age was 67.6 years (range, 42-83 years). There were 79 men, 40 never-smokers, and 44 with left-sided MPM. There were no significant (P≤.05) correlations with clinical variables, prescription dose, total lung dose-volume metrics, and PTV-lung overlap volume. Dose-volume correlations for heart were RP2+ with VD (35 ≤ D ≤ 47 Gy, V43 strongest at P=.003), RP3+ with VD (31 ≤ D ≤ 45 Gy), RP2+ with DV (5 ≤ V ≤ 30%), RP3+ with DV (15 ≤ V ≤ 35%), and mean dose. Significant for ipsilateral lung were RP2+ with VD (38 ≤ D ≤ 44 Gy), RP3+ with V41, RP2+ and RP3+ with minimum dose, and for contralateral lung, RP2+ with maximum dose. Correlation of PTV with RP2+ was strong (P<.001) and also significant with RP3+.ConclusionsHeart dose correlated strongly with symptomatic RP in this large cohort of MPM patients with 2 lungs treated with IMPRINT. Planning constraints to reduce future heart doses are suggested.

Project description:PURPOSE:To apply a previously designed framework for predicting radiation pneumonitis by using pretreatment lung function heterogeneity metrics, anatomic dosimetry, and functional lung dosimetry derived from 2 imaging modalities within the same cohort. METHODS AND MATERIALS:Treatment planning computed tomography (CT) scans were co-registered with pretreatment [99mTc] macro-aggregated albumin perfusion single-photon positron emission tomography (SPECT)/CT scans and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT scans of 28 patients who underwent definitive thoracic radiation. Clinical radiation pneumonitis was defined as grade ?2 (Common Terminology Criteria for Adverse Events, v. 4). Anatomic dosimetric parameters (mean lung dose [MLD], volume receiving ?20 Gy [V20]) were collected from treatment planning scans. Baseline functional lung heterogeneity parameters and functional lung dose-volume parameters were calculated from pretreatment SPECT/CT and FDG PET/CT scans. Functional heterogeneity parameters calculated over the tumor-subtracted lung included skewness, kurtosis, and coefficient of variation from perfusion SPECT and FDG PET and the global lung parenchymal glycolysis and mean standardized uptake value from FDG PET. Functional dose-volume parameters calculated in regions of highly functional lung, defined on perfusion (p) or SUV (s) images, included mean lung dose (pMLD, sMLD) and V20 (pV20, sV20). Fraction of integral lung function receiving ?20 Gy (pF20, sF20) was also calculated. Equivalent doses in 2 Gy per fraction (EQD2) were calculated to account for differences in treatment regimens and dose fractionation (EQD2Lung). RESULTS:Two anatomic dosimetric parameters (MLD, V20) and 4 functional dosimetric parameters (pMLD, pV20, pF20, sF20) were significant predictors of grade ?2 pneumonitis (area under the curve >0.84; P < .05). Dose-independent functional lung heterogeneity metrics were not associated with pneumonitis incidence. At thresholds of 100% sensitivity and 65% to 91% specificity, corresponding to maximum prediction accuracy for pneumonitis, these parameters had the following cutoff values: MLD = 13.6 Gy EQD2Lung, V20 = 25%, pMLD = 13.2 Gy EQD2Lung, pV20 = 15%, pF20 = 17%, and sF20 = 25%. Significant parameters MLD, V20, pF20, and sF20 were not cross-correlated to significant parameters pMLD and pV20, indicating that they may offer independently predictive information (Spearman ? < 0.7). CONCLUSIONS:We reported differences in anatomic and functional lung dosimetry between patients with and without pneumonitis in this limited patient cohort. Adding selected independent functional lung parameters may risk stratify patients for pneumonitis. Validation studies are ongoing in a prospective functional lung avoidance trial at our institution.

Project description:PurposeWhilst survival benefits of thoracic radiotherapy (TRT) followed by immune checkpoint inhibitor (ICI) have been reported in patients with lung cancer, the potential high risk of treatment-related pneumonitis remains a concern. Asians may be more sensitive to lung toxicity than other races. This retrospective study intended to provide a comprehensive pneumonitis profile of TRT followed by ICI and investigate the risk factors from a Chinese cohort of lung cancer.Methods and materialsFrom January 2016 to July 2021, 196 patients with lung cancer who received TRT prior to ICI were retrospectively analyzed. Treatment-related pneumonitis, including checkpoint inhibitor pneumonitis (CIP), radiation pneumonitis (RP), and radiation recall pneumonitis (RRP), were recorded and graded through medical records and chest computed tomography. Characteristics predictive of pneumonitis were assessed using logistic regression models, and the receiver operating characteristic analyses were performed to identify optimal cut points for quantitative variables.ResultsWith a median follow-up of 18 months, a total of 108 patients (55.1%) developed treatment-related pneumonitis during ICI therapy, with an incidence of 25.5% for grade 2 or higher (G2+) and 4.1% for G3+. The overall rates of CIP, RP and RRP were 8.2% (n=16), 46.9% (n=92) and 7.1% (n=14), respectively. With a total mortality rate of 1.5%, vast majority of the patients recovered from pneumonitis or remained stable. No patients died of RRP. Half of the patients with G2+ RP who withheld ICI therapy restarted ICI safely after resolution of RP. The history of chronic pulmonary diseases (P=0.05), mean lung dose (MLD, P=0.038), percent volume of lung receiving ≥5 Gy (V5, P=0.012) and percent volume of lung receiving ≥20 Gy (V20, P=0.030) predicted the occurrence of RRP in univariate analyses. Interval between TRT and ICI less than 3 months was an independent predictor for G2+ treatment-related pneumonitis in a multivariate model (Odds ratio OR=2.787, P=0.004).ConclusionsTreatment-related pneumonitis, especially RRP, is acceptable and manageable in the setting of TRT followed by ICI in this Asian population. Dosimetric parameters MLD, V5 and V20 may improve the predictions of RRP in clinical practice.

Project description:Objective The study aims to establish and validate an effective CT-based radiation pneumonitis (RP) prediction model using the multiomics method of radiomics and EQD2-based dosiomics. Materials and Methods The study performed a retrospective analysis on 91 nonsmall cell lung cancer patients who received radiotherapy from 2019 to 2021 in our hospital. The patients with RP grade ≥1 were labeled as 1, and those with RP grade < 1 were labeled as 0. The whole lung excluding clinical target volume (lung-CTV) was used as the region of interest (ROI). The radiomic and dosiomic features were extracted from the lung-CTV area's image and dose distribution. Besides, the equivalent dose of the 2 Gy fractionated radiation (EQD2) model was used to convert the physical dose to the isoeffect dose, and then, the EQD2-based dosiomic (eqd-dosiomic) features were extracted from the isoeffect dose distribution. Four machine learning (ML) models, including DVH, radiomics combined with DVH (radio + DVH), radiomics combined with dosiomics (radio + dose), and radiomics combined with eqd-dosiomics (radio + eqdose), were established to construct the prediction model via eleven different classifiers. The fivefold cross-validation was used to complete the classification experiment. The area under the curve (AUC) of the receiver operating characteristics (ROC), accuracy, precision, recall, and F1-score were calculated to assess the performance level of the prediction models. Results Compared with the DVH, radio + DVH, and radio + dose model, the value of the training AUC, accuracy, and F1-score of radio + eqdose was higher, and the difference was statistically significant (p < 0.05). Besides, the average value of the precision and recall of radio + eqdose was higher, but the difference was not statistically significant (p > 0.05). Conclusion The performance of using the ML-based multiomics method of radiomics and eqd-dosiomics to predict RP is more efficient and effective.

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Framework for radiation pneumonitis risk stratification based on anatomic and perfused lung dosimetry.

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Framework for radiation pneumonitis risk stratification based on anatomic and perfused lung dosimetry.

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