Repeat Evaluation of Lung Shunt Fraction is Unnecessary: A Retrospective Observational Study of Successive Lung Shunt Fractions from Variable Arterial Distributions in Patients Undergoing Radioembolization of Primary and Secondary Liver Tumors.

PURPOSE: To evaluate whether the recalculation of lung shunt fraction (LSF) is necessary prior to next-stage or same lobe repeat radioembolization. MATERIALS AND METHODS: Retrospective chart review was performed for patients who underwent radioembolization between February 2008 and December 2018. Eighty of 312 patients had repeat mapping angiograms and LSF calculations. A total of 160 LSF calculations were made using planar imaging (155, [97%]) and single-photon emission computed tomography (5 [3%]) technetium-99m macroaggregated albumin hepatic arterial injection imaging. The mean patient age was 61.8 years ± 12.7; 69 (86%) patients had metastatic disease and 11 (14%) had hepatocellular carcinoma. RESULTS: Patients had a median LSF of 5% (interquartile range [IQR] 3%-9%) with a median absolute difference of 1.25 (IQR 0.65-3.4) and a median of 76 days (IQR 42.5-120 days) between repeat LSF calculations. There was a median change in LSF of 0.2% between mapping studies (P = .11). There was no statistical significance between the repeat LSFs regardless of the arterial distribution (P = .79) or between tumor types (P = .75). No patients exceeded lung dose limits using actual or predicted prescribed dose amounts. The actual median lung dose was 2.6 Gy (IQR 1.8-4.4 Gy, maximum = 20.5) for the first radioembolization and 2.0 Gy (IQR 1.3-3.7 Gy, maximum = 10.1) for the second radioembolization. CONCLUSIONS: No significant difference in LSF was identified between different time points and arterial distributions within the same patient undergoing repeat radioembolization. In patients who receive well under 30-Gy lung dose for the initial treatment and a 50-Gy cumulative lung dose, repeat radioembolization treatments in the same patient may not require a repeat LSF calculation.

Differential Diagnosis of COVID-19 Pneumonia in Cancer Patients Received Radiotherapy.

Background: During the outbreak period of COVID-19 pneumonia, cancer patients have been neglected and in greater danger. Furthermore, the differential diagnosis between COVID-19 pneumonia and radiation pneumonitis in cancer patients remains a challenge. This study determined their clinical presentations and radiological features in order to early diagnose and separate COVID-19 pneumonia from radiation pneumonitis patients promptly. Methods and Findings: From January 21, 2020 to February 18, 2020, 112 patients diagnosed with suspected COVID-19 were selected consecutively. A retrospective analysis including all patients' presenting was performed. Four patients from 112 suspected individals were selected, including 2 males and 2 females with a median age of 54 years (range 39-64 years). After repeated pharyngeal swab nucleic acid tests, 1 case was confirmed and 3 cases were excluded from COVID-19 pneumonia. Despite the comparable morphologic characteristics of lung CT imaging, the location, extent, and distribution of lung lesions between COVID-19 pneumonia and radiation pneumonitis differed significantly. Conclusions: Lung CT imaging combined with clinical and laboratory findings can facilitate early diagnosis and appropriate management of COVID-19 pneumonia with a history of malignancy and radiation therapy.

A prospective study of the feasibility of FDG-PET/CT imaging to quantify radiation-induced lung inflammation in locally advanced non-small cell lung cancer patients receiving proton or photon radiotherapy.

PURPOSE: This prospective study assessed the feasibility of 18F-2-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography/computed tomography (PET/CT) to quantify radiation-induced lung inflammation in patients with locally advanced non-small cell lung cancer (NSCLC) who received radiotherapy (RT), and compared the differences in inflammation in the ipsilateral and contralateral lungs following proton and photon RT. METHODS: Thirty-nine consecutive patients with NSCLC underwent FDG-PET/CT imaging before and after RT on a prospective study. A novel quantitative approach utilized regions of interest placed around the anatomical boundaries of the lung parenchyma and provided lung mean standardized uptake value (SUVmean), global lung glycolysis (GLG), global lung parenchymal glycolysis (GLPG) and total lung volume (LV). To quantify primary tumor metabolic response to RT, an adaptive contrast-oriented thresholding algorithm was applied to measure metabolically active tumor volume (MTV), tumor uncorrected SUVmean, tumor partial volume corrected SUVmean (tumor-PVC-SUVmean), and total lesion glycolysis (TLG). Parameters of FDG-PET/CT scans before and after RT were compared using two-tailed paired t-tests. RESULTS: All tumor parameters after either proton or photon RT decreased significantly (p < 0.001). Among the 21 patients treated exclusively with proton RT, no significant increase in PVC-SUVmean or PVC-GLPG was observed in ipsilateral lungs after the PVC parameters of primary tumor were subtracted (p = 0.114 and p = 0.453, respectively). Also, there were no significant increases in SUVmean or GLG of contralateral lungs of patients who received proton RT (p = 0.841, p = 0.241, respectively). In contrast, among the nine patients who received photon RT, there was a statistically significant increase in PVC-GLPG of ipsilateral lung (p < 0.001) and in GLG of contralateral (p = 0.036) lung. In the subset of nine patients who received a combined proton and photon RT, there was a statistically significant increase in PVC-GLPG of ipsilateral lung (p < 0.001). CONCLUSION: Our data suggest less induction of inflammatory response in both the ipsilateral and contralateral lungs of patients treated with proton compared to photon or combined proton-photon RT.

Quantitative evaluation of radiation-induced lung injury with hyperpolarized xenon magnetic resonance.

PURPOSE: To demonstrate the feasibility of quantitative and comprehensive global evaluation of pulmonary function and microstructural changes in rats with radiation-induced lung injury (RILI) using hyperpolarized xenon MR. METHODS: Dissolved xenon spectra were dynamically acquired using a modified chemical shift saturation recovery pulse sequence in five rats with RILI (bilaterally exposed by 6-MV x-ray with a dose of 14 Gy 3 mo. prior to MR experiments) and five healthy rats. The dissolved xenon signals were quantitatively analyzed, and the pulmonary physiological parameters were extracted with the model of xenon exchange. RESULTS: The obtained pulmonary physiological parameters and the ratio of (129) Xe signal in red blood cells (RBCs) versus barrier showed a significant difference between the groups. In RILI rats versus controls, the exchange time increased from 44.5 to 112 ms, the pulmonary capillary transit time increased from 0.51 to 1.48 s, and the ratio of (129) Xe spectroscopic signal in RBCs versus barrier increased from 0.294 to 0.484. CONCLUSION: Hyperpolarized xenon MR is effective for quantitative and comprehensive global evaluation of pulmonary function and structural changes without the use of radiation. This may open the door for its use in the diagnosis of lung diseases that are related to gas exchange. Magn Reson Med 76:408-416, 2016. © 2015 Wiley Periodicals, Inc.

The Potential Role of Lung Ultrasound B-Lines for Detection of Lung Radio-Induced Toxicity in Breast Cancer Patients after Radiation Therapy.

BACKGROUND AND PURPOSE: Breast cancer patients exposed to doses of radiation after radiotherapy could develop toxicity to lung. Lung ultrasound (LUS) is able to detect interstitial lung disease by the evaluation of B-lines. The aim of our study was to assess the number of B-lines to diagnose lung involvement after chest radiotherapy. MATERIALS AND METHODS: We measured LUS B-lines in the treated and contralateral lung of 20 breast cancer patients, 1-3 months after the end of radiotherapy and 1 year after previous LUS. The sum of the B-lines number in the 72 sites on anterior and posterior chest yielded a global B-lines score. RESULTS: B-lines were more numerous in treated (median: 21; 1st-3rd quartiles: 11-31) versus untreated hemithorax (median: 3; 1st-3rd quartiles: 1-5) in both examination at T1-3 months (Kolmogorov-Smirnov test P < 0.001) and T1 year (median: 21; 1st-3rd quartiles: 12-28 vs. median: 4; 1st-3rd quartiles: 1-10; Kolmogorov-Smirnov test P < 0.01). Within the treated hemithorax, B-lines were more frequent in the anterior than in the posterior chest in both examination at T1-3 months (Kolmogorov-Smirnov test: P < 0.0001) and T1 year (Kolmogorov-Smirnov test: P < 0.01). Abnormal scores (B-lines>5) were present in 17/20 treated versus 7/20 untreated hemithoraxes (85.0 vs. 35.0%, P < 0.01) in the first LUS and likewise in 16/17 treated versus 7/17 in untreated hemithorax (94.1% vs. 41.2%, P < 0.01) after 1-year follow-up. CONCLUSION: Among women receiving radiotherapy after breast cancer, B-lines are present predominantly in the irradiated lung. These data suggest that B-lines by LUS could provide, at a subclinical stage, a radiation-free biomarker of radiotherapy-induced lung damage.

Radiation pneumonitis in non-small-cell lung cancer patients treated with helical tomotherapy.

OBJECTIVE: In this study, we investigated the incidence of radiation pneumonitis (RP) in non-small-cell lung cancer (NSCLC) patients undergoing helical tomotherapy (HT) and the clinical and dosimetric factors associated with it. MATERIALS AND METHODS: We analyzed data from the treatment protocols of 62 NSCLC patients. The median total radiation dose was 64 Gy (range 57.6-66 Gy) at 1.8-2.2 Gy/fraction. Thirty-four of these patients underwent HT alone and 28 underwent HT in combination with chemotherapy. Treatment-related pneumonitis was graded according to the Common Terminology Criteria for Adverse Events, version 3.0. RESULTS: We found that RP grades 1, 2, 3 and 5 occurred in 29 (46.8%), 23 (37.1%), 8 (12.9%), and 2 (3.2%) patients, respectively. Using univariate analyses, we found that a grade ≥3 RP was associated with poor performance status (PS), age, planning target volume, mean lung dose, and relative V5through V25, in increments of 5 Gy (P < 0.005). We determined that PS and V5V15were the most significant factors associated with grade ≥3 RP using multivariate analysis. CONCLUSIONS: We found that poor PS and V5-V15 were the risk factors associated with grade ≥3 RP in NSCLC patients treated with HT. Thus, for NSCLC patients treated with HT, the volume of total lung with low-dose region (V5-V15) should be carefully regulated and the use of HT should be restricted in patients with Eastern Cooperative Oncology Group ≥2.

Role of perfusion SPECT in prediction and measurement of pulmonary complications after radiotherapy for lung cancer.

PURPOSE: The purpose of the study was to evaluate the ability of baseline perfusion defect score (DS) on SPECT to predict the development of severe symptomatic radiation pneumonitis (RP) and to evaluate changes in perfusion on SPECT as a method of lung perfusion function assessment after curative radiotherapy (RT) for non-small-cell lung cancer (NSCLC). METHODS: Patients with NSCLC undergoing curative RT were included prospectively. Perfusion SPECT/CT and global pulmonary function tests (PFT) were performed before RT and four times during follow-up. Functional activity on SPECT was measured using a semiquantitative perfusion DS. Pulmonary morbidity was graded by the National Cancer Institute's Common Terminology Criteria for Adverse Events version 4 for pneumonitis. Patients were divided into two groups according to the severity of RP. RESULTS: A total of 71 consecutive patients were included in the study. Baseline DS was associated with chronic obstructive pulmonary disease. A significant inverse correlation was found between baseline DS and forced expiratory volume in 1 s and diffusing capacity of the lung for carbon monoxide. Patients with severe RP had significantly higher baseline total lung DS (mean 5.43) than those with no or mild symptoms (mean DS 3.96, p < 0.01). PFT results were not different between these two groups. The odds ratio for total lung DS was 7.8 (95% CI 1.9 - 31) demonstrating the ability of this parameter to predict severe RP. Adjustment for other potential confounders known to be associated with increased risk of RP was performed and did not change the odds ratio. The median follow-up time after RT was 8.4 months. The largest DS increase of 13.3% was associated with severe RP at 3 months of follow-up (p < 0.01). The development of severe RP during follow-up was not associated with changes in PFT results. CONCLUSION: Perfusion SPECT is a valuable method for predicting severe RP and for assessing changes in regional functional perfusion after curative RT comparable with global PFT.

Loss of lung function after chemo-radiotherapy for NSCLC measured by perfusion SPECT/CT: Correlation with radiation dose and clinical morbidity.

BACKGROUND: The purpose of the study was to assess dose and time dependence of radiotherapy (RT)-induced changes in regional lung function measured with single photon emission computed tomography (SPECT) of the lung and relate these changes to the symptomatic endpoint of radiation pneumonitis (RP) in patients treated for non-small cell lung cancer (NSCLC). MATERIAL AND METHODS: NSCLC patients scheduled to receive curative RT of minimum 60 Gy were included prospectively in the study. Lung perfusion SPECT/CT was performed before and three months after RT. Reconstructed SPECT/CT data were registered to treatment planning CT. Dose to the lung was segmented into regions corresponding to 0-5, 6-20, 21-40, 41-60 and > 60 Gy. Changes (%) in regional lung perfusion before and after RT were correlated with regional dose and symptomatic RP (CTC grade 2-5) outcome. RESULTS: A total of 58 patients were included, of which 45 had three-month follow-up SPECT/CT scans. Analysis showed a statistically significant dose-dependent reduction in regional perfusion at three-month follow-up. The largest population composite perfusion loss was in 41-60 Gy (42.2%) and > 60 Gy (41.7%) dose bins. Lung regions receiving low dose of 0-5 Gy and 6-20 Gy had corresponding perfusion increase (-7.2% and -6.1%, respectively). Regional perfusion reduction was different in patients with and without RP with the largest difference in 21-40 Gy bin (p = 0.02), while for other bins the difference did not reach statistical significance. The risk of symptomatic RP was higher for the patients with perfusion reduction after RT (p = 0.02), with the relative risk estimate of 3.6 (95% CI 1.1-12). CONCLUSION: Perfusion lung function changes in a dose-dependent manner after RT. The severity of radiation-induced lung symptoms is significantly correlated with SPECT perfusion changes. Perfusion reduction early after RT is associated with a high risk of later development of symptomatic RP.

Quantitative assessment of global lung inflammation following radiation therapy using FDG PET/CT: a pilot study.

PURPOSE: Radiation pneumonitis is the most severe dose-limiting complication in patients receiving thoracic radiation therapy. The aim of this study was to quantify global lung inflammation following radiation therapy using FDG PET/CT. METHODS: We studied 20 subjects with stage III non-small-cell lung carcinoma who had undergone FDG PET/CT imaging before and after radiation therapy. On all PET/CT studies, the sectional lung volume (sLV) of each lung was calculated from each slice by multiplying the lung area by slice thickness. The sectional lung glycolysis (sLG) was calculated by multiplying the sLV and the lung sectional mean standardized uptake value (sSUVmean) on each slice passing through the lung. The lung volume (LV) was calculated by adding all sLVs from the lung, and the global lung glycolysis (GLG) was calculated by adding all sLGs from the lung. Finally, the lung SUVmean was calculated by dividing the GLG by the LV. The amount of inflammation in the lung parenchyma directly receiving radiation therapy was calculated by subtracting tumor measurements from GLG. RESULTS: In the lung directly receiving radiation therapy, the lung parenchyma SUVmean and global lung parenchymal glycolysis were significantly increased following therapy. In the contralateral lung (internal control), no significant changes were observed in lung SUVmean or GLG following radiation therapy. CONCLUSION: Global lung parenchymal glycolysis and lung parenchymal SUVmean may serve as potentially useful biomarkers to quantify lung inflammation on FDG PET/CT following thoracic radiation therapy.

Radiomics-based hybrid model for predicting radiation pneumonitis: A systematic review and meta-analysis.

PURPOSE: This study reviewed and meta-analyzed evidence on radiomics-based hybrid models for predicting radiation pneumonitis (RP). These models are crucial for improving thoracic radiotherapy plans and mitigating RP, a common complication of thoracic radiotherapy. We examined and compared the RP prediction models developed in these studies with the radiomics features employed in RP models. METHODS: We systematically searched Google Scholar, Embase, PubMed, and MEDLINE for studies published up to April 19, 2024. Sixteen studies met the inclusion criteria. We compared the RP prediction models developed in these studies and the radiomics features employed. RESULTS: Radiomics, as a single-factor evaluation, achieved an area under the receiver operating characteristic curve (AUROC) of 0.73, accuracy of 0.69, sensitivity of 0.64, and specificity of 0.74. Dosiomics achieved an AUROC of 0.70. Clinical and dosimetric factors showed lower performance, with AUROCs of 0.59 and 0.58. Combining clinical and radiomic factors yielded an AUROC of 0.78, while combining dosiomic and radiomics factors produced an AUROC of 0.81. Triple combinations, including clinical, dosimetric, and radiomics factors, achieved an AUROC of 0.81. The study identifies key radiomics features, such as the Gray Level Co-occurrence Matrix (GLCM) and Gray Level Size Zone Matrix (GLSZM), which enhance the predictive accuracy of RP models. CONCLUSIONS: Radiomics-based hybrid models are highly effective in predicting RP. These models, combining traditional predictive factors with radiomic features, particularly GLCM and GLSZM, offer a clinically feasible approach for identifying patients at higher RP risk. This approach enhances clinical outcomes and improves patient quality of life. PROTOCOL REGISTRATION: The protocol of this study was registered on PROSPERO (CRD42023426565).

Integration of dosimetric parameters, clinical factors, and radiomics to predict symptomatic radiation pneumonitis in lung cancer patients undergoing combined immunotherapy and radiotherapy.

PURPOSE: This study aimed to combine clinical/dosimetric factors and handcrafted/deep learning radiomic features to establish a predictive model for symptomatic (grade ≥ 2) radiation pneumonitis (RP) in lung cancer patients who received immunotherapy followed by radiotherapy. MATERIALS AND METHODS: This study retrospectively collected data of 73 lung cancer patients with prior receipt of ICIs who underwent thoracic radiotherapy (TRT). Of these 73 patients, 41 (56.2 %) developed symptomatic grade ≥ 2 RP. RP was defined per multidisciplinary clinician consensus using CTCAE v5.0. Regions of interest (ROIs) (from radiotherapy planning CT images) utilized herein were gross tumor volume (GTV), planning tumor volume (PTV), and PTV-GTV. Clinical/dosimetric (mean lung dose and V5-V30) parameters were collected, and 107 handcrafted radiomic (HCR) features were extracted from each ROI. Deep learning-based radiomic (DLR) features were also extracted based on pre-trained 3D residual network models. HCR models, Fusion HCR model, Fusion HCR + ResNet models, and Fusion HCR + ResNet + Clinical models were built and compared using the receiver operating characteristic (ROC) curve with measurement of the area under the curve (AUC). Five-fold cross-validation was performed to avoid model overfitting. RESULTS: HCR models across various ROIs and the Fusion HCR model showed good predictive ability with AUCs from 0.740 to 0.808 and 0.740-0.802 in the training and testing cohorts, respectively. The addition of DLR features improved the effectiveness of HCR models (AUCs from 0.826 to 0.898 and 0.821-0.898 in both respective cohorts). The best performing prediction model (HCR + ResNet + Clinical) combined HCR & DLR features with 7 clinical/dosimetric characteristics and achieved an average AUC of 0.936 and 0.946 in both respective cohorts. CONCLUSIONS: In patients undergoing combined immunotherapy/RT for lung cancer, integrating clinical/dosimetric factors and handcrafted/deep learning radiomic features can offer a high predictive capacity for RP, and merits further prospective validation.

Dual-energy computed tomography in the early evaluation of acute radiation pneumonia.

OBJECTIVE: To investigate the value of dual-energy dual-source computed tomography (DSCT) in evaluating pulmonary perfusion changes before and after radiotherapy for esophageal cancer, and its clinical use in the early diagnosis of acute radiation pneumonia (ARP). METHODS: We selected 45 patients with pathologically confirmed esophageal cancer who received radiotherapy (total irradiation dose of 60 Gy). Dual-energy DSCT scans were performed before and after radiotherapy and the normalized iodine concentrations (NIC) in the lung fields of the areas irradiated with doses of > 20 Gy, 10-20 Gy, 5-10 Gy, and < 5 Gy were measured. We also checked for the occurrence of ARP in the patients, and the differences in NIC values and NIC reduction rates before and after radiotherapy were calculated and statistically analyzed. RESULTS: A total of 16 of the 45 patients developed ARP. The NIC values in the lung fields of all patients decreased at different degrees after radiotherapy, and the NIC values in the area where ARP developed, decreased significantly. The rate of NIC reduction and incidence rate of ARP increased gradually with the increasing irradiation dose, and the inter-group difference in NIC reduction rate was statistically significant (P < 0.05). Based on the receiver operating characteristic (ROC) curve analysis, the areas under the curves of NIC reduction rate versus ARP occurrence in the V5-10 Gy, V10-20 Gy, and V> 20 Gy groups were 0.780, 0.808, and 0.772, respectively. Sensitivity of diagnosis was 81.3%, 75.0%, and 68.8% and the specificity was 65.5%, 82.8%, and 79.3%, when taking 12.50%, 16.50%, and 26.0% as the diagnostic thresholds, respectively. The difference in NIC values in the lung fields of V<5 Gy before and after radiotherapy was not statistically significant (P > 0.05). CONCLUSION: The dual-energy DSCT could effectively evaluate pulmonary perfusion changes after radiotherapy for esophageal cancer, and the NIC reduction rate was useful as a reference index to predict ARP and provide further reference for decisions in clinical practice.

Radiation Recall Pneumonitis: Imaging Appearance and Differential Considerations.

Radiation recall pneumonitis is an inflammatory reaction of previously radiated lung parenchyma triggered by systemic pharmacological agents (such as chemotherapy and immunotherapy) or vaccination. Patients present with non-specific symptoms such as cough, shortness of breath, or hypoxia soon after the initiation of medication or vaccination. Careful assessment of the patient's history, including the thoracic radiation treatment plan and timing of the initiation of the triggering agent, in conjunction with CT findings, contribute to the diagnosis. Once a diagnosis is established, treatment includes cessation of the causative medication and/or initiation of steroid therapy. Differentiating this relatively rare entity from other common post-therapeutic complications in oncology patients, such as recurrent malignancy, infection, or medication-induced pneumonitis, is essential for guiding downstream clinical management.

Radiation Therapy for Lung Cancer: Imaging Appearances and Pitfalls.

Radiation therapy is part of a multimodality treatment approach to lung cancer. The radiologist must be aware of both the expected and the unexpected imaging findings of the post-radiation therapy patient, including the time course for development of post- radiation therapy pneumonitis and fibrosis. In this review, a brief discussion of radiation therapy techniques and indications is presented, followed by an image-heavy differential diagnostic approach. The review focuses on computed tomography imaging examples to help distinguish normal postradiation pneumonitis and fibrosis from alternative complications, such as infection, local recurrence, or radiation-induced malignancy.

Properties of [18F]FAPI monitoring of acute radiation pneumonia versus [18F]FDG in mouse models.

OBJECTIVE: In this study, the uptake characteristics of [18F]fibroblast activation protein inhibitor (FAPI) molecular imaging probe were investigated in acute radiation pneumonia and lung cancer xenografted mice before and after radiation to assess the future applicability of [18F]FAPI positron emission tomography/computed tomography (PET/CT) imaging in early radiotherapy response. METHODS: Initially, the biodistribution of [18F]FAPI tracer in vivo were studied in healthy mice at each time-point. A comparison of [18F]FAPI and [18F]fluorodeoxyglucose (FDG) PET/CT imaging efficacy in normal ICR, LLC tumor-bearing mice was evaluated. A radiation pneumonia model was then investigated using a gamma counter, small animal PET/CT, and autoradiography. The uptake properties of [18F]FAPI in lung cancer and acute radiation pneumonia were investigated using autoradiography and PET/CT imaging in mice. RESULTS: The tumor area was visible in [18F]FAPI imaging and the tracer was swiftly eliminated from normal tissues and organs. There was a significant increase of [18F]FDG absorption in lung tissue after radiotherapy compared to before radiotherapy, but no significant difference of [18F]FAPI uptake under the same condition. Furthermore, both the LLC tumor volume and the expression of FAP-ɑ decreased after thorax irradiation. Correspondingly, there was no notable [18F]FAPI uptake after irradiation, but there was an increase of [18F]FDG uptake in malignancies and lungs. CONCLUSIONS: The background uptake of [18F]FAPI is negligible. Moreover, the uptake of [18F]FAPI may not be affected by acute radiation pneumonitis compared to [18F]FDG, which may be used to more accurately evaluate early radiotherapy response of lung cancer with acute radiation pneumonia.

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

Our purpose was to provide an understanding of current functional lung imaging (FLI) techniques and their potential to improve dosimetry and outcomes for patients with lung cancer receiving radiation therapy (RT). Excerpta Medica dataBASE (EMBASE), PubMed, and Cochrane Library were searched from 1990 until April 2023. Articles were included if they reported on FLI in one of: techniques, incorporation into RT planning for lung cancer, or quantification of RT-related outcomes for patients with lung cancer. Studies involving all RT modalities, including stereotactic body RT and particle therapy, were included. Meta-analyses were conducted to investigate differences in dose-function parameters between anatomic and functional RT planning techniques, as well as to investigate correlations of dose-function parameters with grade 2+ radiation pneumonitis (RP). One hundred seventy-eight studies were included in the narrative synthesis. We report on FLI modalities, dose-response quantification, functional lung (FL) definitions, FL avoidance techniques, and correlations between FL irradiation and toxicity. Meta-analysis results show that FL avoidance planning gives statistically significant absolute reductions of 3.22% to the fraction of well-ventilated lung receiving 20 Gy or more, 3.52% to the fraction of well-perfused lung receiving 20 Gy or more, 1.3 Gy to the mean dose to the well-ventilated lung, and 2.41 Gy to the mean dose to the well-perfused lung. Increases in the threshold value for defining FL are associated with decreases in functional parameters. For intensity modulated RT and volumetric modulated arc therapy, avoidance planning results in a 13% rate of grade 2+ RP, which is reduced compared with results from conventional planning cohorts. A trend of increased predictive ability for grade 2+ RP was seen in models using FL information but was not statistically significant. FLI shows promise as a method to spare FL during thoracic RT, but interventional trials related to FL avoidance planning are sparse. Such trials are critical to understanding the effect of FL avoidance planning on toxicity reduction and patient outcomes.

An 18F-FDG PET/CT and Mean Lung Dose Model to Predict Early Radiation Pneumonitis in Stage III Non-Small Cell Lung Cancer Patients Treated with Chemoradiation and Immunotherapy.

Radiation pneumonitis (RP) that develops early (i.e., within 3 mo) (RPEarly) after completion of concurrent chemoradiation (cCRT) leads to treatment discontinuation and poorer survival for patients with stage III non-small cell lung cancer. Since no RPEarly risk model exists, we explored whether published RP models and pretreatment 18F-FDG PET/CT-derived features predict RPEarly Methods: One hundred sixty patients with stage III non-small cell lung cancer treated with cCRT and consolidative immunotherapy were analyzed for RPEarly Three published RP models that included the mean lung dose (MLD) and patient characteristics were examined. Pretreatment 18F-FDG PET/CT normal-lung SUV featured included the following: 10th percentile of SUV (SUVP10), 90th percentile of SUV (SUVP90), SUVmax, SUVmean, minimum SUV, and SD. Associations between models/features and RPEarly were assessed using area under the receiver-operating characteristic curve (AUC), P values, and the Hosmer-Lemeshow test (pHL). The cohort was randomly split, with similar RPEarly rates, into a 70%/30% derivation/internal validation subset. Results: Twenty (13%) patients developed RPEarly Predictors for RPEarly were MLD alone (AUC, 0.72; P = 0.02; pHL, 0.87), SUVP10, SUVP90, and SUVmean (AUC, 0.70-0.74; P = 0.003-0.006; pHL, 0.67-0.70). The combined MLD and SUVP90 model generalized in the validation subset and was deemed the final RPEarly model (RPEarly risk = 1/[1+e(- x )]; x = -6.08 + [0.17 × MLD] + [1.63 × SUVP90]). The final model refitted in the 160 patients indicated improvement over the published MLD-alone model (AUC, 0.77 vs. 0.72; P = 0.0001 vs. 0.02; pHL, 0.65 vs. 0.87). Conclusion: Patients at risk for RPEarly can be detected with high certainty by combining the normal lung's MLD and pretreatment 18F-FDG PET/CT SUVP90 This refined model can be used to identify patients at an elevated risk for premature immunotherapy discontinuation due to RPEarly and could allow for interventions to improve treatment outcomes.

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

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.

Multi-omics deep learning for radiation pneumonitis prediction in lung cancer patients underwent volumetric modulated arc therapy.

BACKGROUND AND OBJECTIVE: To evaluate the feasibility and accuracy of radiomics, dosiomics, and deep learning (DL) in predicting Radiation Pneumonitis (RP) in lung cancer patients underwent volumetric modulated arc therapy (VMAT) to improve radiotherapy safety and management. METHODS: Total of 318 and 31 lung cancer patients underwent VMAT from First Affiliated Hospital of Wenzhou Medical University (WMU) and Quzhou Affiliated Hospital of WMU were enrolled for training and external validation, respectively. Models based on radiomics (R), dosiomics (D), and combined radiomics and dosiomics features (R+D) were constructed and validated using three machine learning (ML) methods. DL models trained with CT (DLR), dose distribution (DLD), and combined CT and dose distribution (DL(R+D)) images were constructed. DL features were then extracted from the fully connected layers of the best-performing DL model to combine with features of the ML model with the best performance to construct models of R+DLR, D+DLD, R+D+DL(R+D)) for RP prediction. RESULTS: The R+D model achieved a best area under curve (AUC) of 0.84, 0.73, and 0.73 in the internal validation cohorts with Support Vector Machine (SVM), XGBoost, and Logistic Regression (LR), respectively. The DL(R+D) model achieved a best AUC of 0.89 and 0.86 using ResNet-34 in training and internal validation cohorts, respectively. The R+D+DL(R+D) model achieved a best performance in the external validation cohorts with an AUC, accuracy, sensitivity, and specificity of 0.81(0.62-0.99), 0.81, 0.84, and 0.67, respectively. CONCLUSIONS: The integration of radiomics, dosiomics, and DL features is feasible and accurate for the RP prediction to improve the management of lung cancer patients underwent VMAT.