CT-based different regions of interest radiomics analysis for acute radiation pneumonitis in patients with locally advanced NSCLC after chemoradiotherapy
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ABSTRACT:
SUBMITTER: Hou L
PROVIDER: S-EPMC11345682 | biostudies-literature | 2024 Jul
REPOSITORIES: biostudies-literature
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Project description:Background and purposeEarly detection of non-response to neoadjuvant chemoradiotherapy (nCRT) for locally advanced colorectal cancer (LARC) remains challenging. We aimed to assess whether pretreatment radiotherapy planning computed tomography (CT) radiomics could distinguish the patients with no response or no downstaging after nCRT from those with response and downstaging after nCRT.Materials and methodsPatients with LARC who were treated with nCRT were retrospectively enrolled between March 2009 and March 2019. Traditional radiological characteristics were analyzed by visual inspection and radiomic features were analyzed through computational methods from the pretreatment radiotherapy planning CT images. Differentiation models were constructed using radiomic methods and clinicopathological characteristics for predicting non-response to nCRT. Model performance was assessed for classification efficiency, calibration, discrimination, and clinical application.ResultsThis study enrolled a total of 215 patients, including 151 patients in the training cohort (50 non-responders and 101 responders) and 64 patients in the validation cohort (21 non-responders and 43 responders). For predicting non-response, the model constructed with an ensemble machine learning method had higher performance with area under the curve (AUC) values of 0.92 and 0.89 as compared to the model constructed with the logistic regression method (AUC: 0.72 and 0.71 for the training and validation cohorts, respectively). Both decision curve and calibration curve analyses confirmed that the ensemble machine learning model had higher prediction performance.ConclusionPretreatment CT radiomics achieved satisfying performance in predicting non-response to nCRT and could be helpful to assist in treatment planning for patients with LARC.
| S-EPMC9939108 | biostudies-literature
Project description:PurposeRadiomics provides quantitative tissue heterogeneity profiling and is an exciting approach to developing imaging biomarkers in the context of precision medicine. Normal-appearing parenchymal tissues surrounding primary tumors can harbor microscopic disease that leads to increased risk of distant metastasis (DM). This study assesses whether computed-tomography (CT) imaging features of such peritumoral tissues can predict DM in locally advanced non-small cell lung cancer (NSCLC).Material and methods200 NSCLC patients of histological adenocarcinoma were included in this study. The investigated lung tissues were tumor rim, defined to be 3mm of tumor and parenchymal tissue on either side of the tumor border and the exterior region extended from 3 to 9mm outside of the tumor. Fifteen stable radiomic features were extracted and evaluated from each of these regions on pre-treatment CT images. For comparison, features from expert-delineated tumor contours were similarly prepared. The patient cohort was separated into training and validation datasets for prognostic power evaluation. Both univariable and multivariable analyses were performed for each region using concordance index (CI).ResultsUnivariable analysis reveals that six out of fifteen tumor rim features were significantly prognostic of DM (p-value < 0.05), as were ten features from the visible tumor, and only one of the exterior features was. Multivariablely, a rim radiomic signature achieved the highest prognostic performance in the independent validation sub-cohort (CI = 0.64, p-value = 2.4×10-5) significantly over a multivariable clinical model (CI = 0.53), a visible tumor radiomics model (CI = 0.59), or an exterior tissue model (CI = 0.55). Furthermore, patient stratification by the combined rim signature and clinical predictor led to a significant improvement on the clinical predictor alone and also outperformed stratification using the combined tumor signature and clinical predictor.ConclusionsWe identified peritumoral rim radiomic features significantly associated with DM. This study demonstrated that peritumoral imaging characteristics may provide additional valuable information over the visible tumor features for patient risk stratification due to cancer metastasis.
| S-EPMC6214508 | biostudies-literature
Project description:BackgroundConcurrent chemoradiotherapy (CCRT) followed by durvalumab is the standard of care for unresectable locally-advanced non-small cell carcinoma (LA-NSCLC). However, a major concern about administration of durvalumab after CCRT is whether the incidence of symptomatic radiation pneumonitis (RP) may increase or not. In the present analysis, we report the initial results of CCRT followed by durvalumab in patients with LA-NSCLC in a real-world setting with focus on predicting factors for symptomatic RP.MethodsPatients who were pathologically diagnosed as NSCLC and initiated treatment with CCRT followed by durvalumab between July 2018 to December 2019 were eligible for this study. Patients were included if they completed the planned CRT course and administered at least one course of durvalumab. We retrospectively investigated the preliminary survival outcome and incidence and predicting factors for symptomatic RP.ResultsOf the 67 patients who planned CCRT, 63 patients completed the entire CCRT course. Of these, 56 patients proceeded to consolidation with durvalumab. The median time to eternal discontinuation of durvalumab was 9.7 months. The cumulative proportion of the patients who exhibited symptomatic RP was 30, 40 and 44% at 3, 6 and 12 months, respectively. In multivariate analyses, pulmonary fibrosis score and lung V40 were significant predictive factors for symptomatic RP (p < 0.001, HR: 7.83, 95% CI: 3.38-18.13, and p = 0.034, HR: 3.17, 95% CI: 1.09-9.19, respectively).ConclusionsPulmonary fibrosis sore and lung V40 were significant predictive factors for symptomatic RP. We should be cautious about the administration of durvalumab for patients having subclinical pulmonary fibrosis. To our best knowledge, this is one of the first report showing the predictive value of high dose volumes to the lung in patients with LA-NSCLC who received CCRT followed by durvalumab.
| S-EPMC8760798 | biostudies-literature
Project description:To predict grade ≥ 2 radiation pneumonitis (RP) in patients with locally advanced non-small cell lung cancer (NSCLC) using multi-region radiomics analysis. Data from 77 patients with NSCLC who underwent definitive radiotherapy between 2008 and 2018 were analyzed. Radiomic feature extraction from the whole lung (whole-lung radiomics analysis) and imaging- and dosimetric-based segmentation (multi-region radiomics analysis) were performed. Patients with RP grade ≥ 2 or < 2 were classified. Predictors were selected with least absolute shrinkage and selection operator logistic regression and the model was built with neural network classifiers. A total of 49,383 radiomics features per patient image were extracted from the radiotherapy planning computed tomography. We identified 4 features and 13 radiomics features in the whole-lung and multi-region radiomics analysis for classification, respectively. The accuracy and area under the curve (AUC) without the synthetic minority over-sampling technique (SMOTE) were 60.8%, and 0.62 for whole-lung and 80.1%, and 0.84 for multi-region radiomics analysis. These were improved 1.7% for whole-lung and 2.1% for multi-region radiomics analysis with the SMOTE. The developed multi-region radiomics analysis can help predict grade ≥ 2 RP. The radiomics features in the median- and high-dose regions, and the local intensity roughness and variation were important factors in predicting grade ≥ 2 RP.
| S-EPMC8355298 | biostudies-literature
Project description:Background and purpose:We investigated the incidence and dose-volume relationships of radiation pneumonitis (RP) after concurrent chemoradiotherapy (CCRT) followed by durvalumab for locally advanced non-small-cell lung cancer (LA-NSCLC). Materials and methods:We retrospectively analyzed records of 36 patients with LA-NSCLC who underwent CCRT followed by durvalumab. Incidence of RP was analyzed for correlations with clinical factors and dose-volume parameters of lung in radiotherapy. Results:All patients received 60 Gy in 30 fractions of radiotherapy with concurrent chemotherapy. Over a median follow-up period of 7 months, incidence of grade ?2 RP was 36% (including grade 3 RP: 5% and grade 5 RP: 3%). Age, sex, Brinkman index, and blood test results did not significantly differ between patients with grade ?2 RP and grade ?1 RP. Dose-volume parameters (lung volumes that received 5 Gy, 10 Gy, 20 Gy, 30 Gy, 40 Gy, 50 Gy, and mean lung dose) were significantly higher among patients with grade ?2 RP compared with patients with grade ?1 RP. Conclusion:Incidence of grade ?2 RP was 36% after CCRT followed by durvalumab for LA-NSCLC, but did not significantly differ from those of patients treated with CCRT alone. Lung dose-volume parameters were significantly correlated with RP.
| S-EPMC7283100 | biostudies-literature
Project description:Concurrent chemoradiotherapy (cCRT) is the standard treatment for patients with locally advanced non-small cell lung cancer (LA-NSCLC). However, the efficacy and safety of this treatment has not been compared between patients who possess epidermal growth factor receptor (EGFR) mutations and patients with wild-type EGFR. The objective of the present study was to evaluate the effect of the presence of EGFR gene mutations in patients with LA-NSCLC receiving cCRT. Between January 2007 and December 2013, the records of 64 patients were reviewed retrospectively. The data were statistically analyzed to evaluate the efficacy of cCRT according to EGFR mutation status. In total, 15/64 were revealed to possess EGFR mutations, 23%, and comprised the mutant EGFR group. The progression-free survival time was significantly shorter in the mutant EGFR group compared with the patient group with tumors exhibiting wild-type EGFR, 6.3 and 9.5 months, respectively (P<0.001). The overall survival rate was longer in the mutant EGFR group compared with the wild-type EGFR group, although the difference was not statistically significant, 37.1 and 21.1 months, respectively (P=0.26). The disease recurred in all of the patients of the mutant EGFR group, whilst the recurrence rate in the wild-type EGFR group was 89%. The frequency of distant metastasis was significantly higher in the mutant EGFR group compared with the wild-type EGFR group. In conclusion, these data suggest that additional studies are required to identify strategies for reinforcing the efficacy of cCRT, with a focus on the potential use of EGFR tyrosine kinase inhibitors for patients exhibiting an EGFR mutation.
| S-EPMC5494758 | biostudies-other
Project description:Following the PACIFIC trial, durvalumab has been approved by the European Medicines Agency (EMA) for consolidation of locally advanced PD-L1-positive NSCLC after chemoradiotherapy (CRT). Patients were treated with durvalumab in the EAP from 22.11.2017 to 15.10.2018 allowing analysis of its efficacy and safety. 211 patients were registered by 90 German centres. Data were collected retrospectively by questionnaire and queries. 56 centres reported data on 126 patients who actually received at least one cycle of durvalumab. In contrast to the PACIFIC-trial population, some patients with oligometastatic disease and a history of autoimmune disease are included in the EAP population. Information on PD-L1 status was obtained for 111 patients. Baseline data include age, gender, ECOG, stage (IASLC 8th ed.), and smoking history. Treatment data include mode of chemoradiotherapy, used chemotherapy agent, and duration of durvalumab therapy. Adverse evants were documented according to CTAEC 5.0. Data were analysed for progression-free survival (PFS), overall survival (OS), and adverse events (AE). The results were published in Lung Cancer [1].
| S-EPMC7750486 | biostudies-literature
Project description:Background: Conventional methods for predicting treatment response to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) are limited. Methods: This study retrospectively recruited 134 LARC patients who underwent standard nCRT followed by total mesorectal excision surgery in our institution. Based on pre-operative axial T2-weighted images, machine learning radiomics was performed. A receiver operating characteristic (ROC) curve was performed to test the efficiencies of the predictive model. Results: Among the 134 patients, 32 (23.9%) achieved pathological complete response (pCR), 69 (51.5%) achieved a good response, and 91 (67.9%) achieved down-staging. For prediction of pCR, good-response, and down-staging, the predictive model demonstrated high classification efficiencies, with an AUC value of 0.91 (95% CI: 0.83-0.98), 0.90 (95% CI: 0.83-0.97), and 0.93 (95% CI: 0.87-0.98), respectively. Conclusion: Our machine learning radiomics model showed promise for predicting response to nCRT in patients with LARC. Our predictive model based on the commonly used T2-weighted images on pelvic Magnetic Resonance Imaging (MRI) scans has the potential to be adapted in clinical practice. Novelty and Impact Statements: Methods for predicting the response of the locally advanced rectal cancer (LARC, T3-4, or N+) to neoadjuvant chemoradiotherapy (nCRT) is lacking. In the present study, we developed a new machine learning radiomics method based on T2-weighted images. As a non-invasive tool, this method facilitates prediction performance effectively. It achieves a satisfactory overall diagnostic accuracy for predicting of pCR, good response, and down-staging show an AUC of 0.908, 0.902, and 0.930 in LARC patients, respectively.
| S-EPMC6606732 | biostudies-literature
Project description:BackgroundPatients undergoing chemoradiation and immune checkpoint inhibitor (ICI) therapy for locally advanced non-small cell lung cancer (NSCLC) experience pulmonary toxicity at higher rates than historical reports. Identifying biomarkers beyond conventional clinical factors and radiation dosimetry is especially relevant in the modern cancer immunotherapy era. We investigated the role of novel functional lung radiomics, relative to functional lung dosimetry and clinical characteristics, for pneumonitis risk stratification in locally advanced NSCLC.MethodsPatients with locally advanced NSCLC were prospectively enrolled on the FLARE-RT trial (NCT02773238). All received concurrent chemoradiation using functional lung avoidance planning, while approximately half received consolidation durvalumab ICI. Within tumour-subtracted lung regions, 110 radiomics features (size, shape, intensity, texture) were extracted on pre-treatment [99mTc]MAA SPECT/CT perfusion images using fixed-bin-width discretization. The performance of functional lung radiomics for pneumonitis (CTCAE v4 grade 2 or higher) risk stratification was benchmarked against previously reported lung dosimetric parameters and clinical risk factors. Multivariate least absolute shrinkage and selection operator Cox models of time-varying pneumonitis risk were constructed, and prediction performance was evaluated using optimism-adjusted concordance index (c-index) with 95% confidence interval reporting throughout.ResultsThirty-nine patients were included in the study and pneumonitis occurred in 16/39 (41%) patients. Among clinical characteristics and anatomic/functional lung dosimetry variables, only the presence of baseline chronic obstructive pulmonary disease (COPD) was significantly associated with the development of pneumonitis (HR 4.59 [1.69-12.49]) and served as the primary prediction benchmark model (c-index 0.69 [0.59-0.80]). Discrimination of time-varying pneumonitis risk was numerically higher when combining COPD with perfused lung radiomics size (c-index 0.77 [0.65-0.88]) or shape feature classes (c-index 0.79 [0.66-0.91]) but did not reach statistical significance compared to benchmark models (p > 0.26). COPD was associated with perfused lung radiomics size features, including patients with larger lung volumes (AUC 0.75 [0.59-0.91]). Perfused lung radiomic texture features were correlated with lung volume (adj R2 = 0.84-1.00), representing surrogates rather than independent predictors of pneumonitis risk.ConclusionsIn patients undergoing chemoradiation with functional lung avoidance therapy and optional consolidative immune checkpoint inhibitor therapy for locally advanced NSCLC, the strongest predictor of pneumonitis was the presence of baseline chronic obstructive pulmonary disease. Results from this novel functional lung radiomics exploratory study can inform future validation studies to refine pneumonitis risk models following combinations of radiation and immunotherapy. Our results support functional lung radiomics as surrogates of COPD for non-invasive monitoring during and after treatment. Further study of clinical, dosimetric, and radiomic feature combinations for radiation and immune-mediated pneumonitis risk stratification in a larger patient population is warranted.
| S-EPMC9437196 | biostudies-literature
Project description:BackgroundChemoradiotherapy is the recommended treatment for patients with unresectable locally advanced non-small cell lung cancer (NSCLC). This study aimed to determine the impact of age on the survival outcomes and risk of radiation pneumonitis (RP) in patients with unresectable locally advanced NSCLC.MethodsThe data of patients with unresectable locally advanced NSCLC who were treated with radiotherapy (RT), sequential chemoradiotherapy, or concurrent chemoradiotherapy between January, 2013, and December, 2017, in our institution were retrospectively reviewed and analyzed. Student's t-test and χ2 test were used to evaluate the differences between groups divided by optimal cutoff. Survival rates were calculated using the Kaplan-Meier method, and multivariate cox regression was performed to determine the prognostic factors for survival outcomes.ResultsA total of 749 patients were included in this analysis. Based on the optimal cutoff, the patients were stratified into two age groups: <65 years old (the younger group, n=482) and ≥65 years old (the older group, n=267). The older group had more patients with poor Karnofsky Performance Score (KPS), squamous cell sarcoma (SCC), and IIIA stage than the younger group. The older patients were more likely to have received RT alone (40.1%) and less likely to have received concurrent chemoradiotherapy (cCRT) (26.6%) than the younger patients (8.1% and 54.8%, respectively, P<0.001). The median overall survival (OS) was 33 months (95% CI: 29-37 months) and 21 months (95% CI: 18-27 months) for the younger group and the older group, respectively (P<0.001). Multivariate Cox regression analysis showed that age had a significant independent association with OS (HR, 1.25; 95% CI: 1.01-1.55) after adjustment for covariates. The incidences of RP, symptomatic RP, and severe RP were similar between the two groups, but the incidence of fatal RP was higher in the older group (4.5% vs. 1.7%, P=0.039).ConclusionsThe clinical characteristics of the older patients in our study differed from those of the younger patients, and the older patients were more likely to choose conservative treatment. OS was longer in the older patients and more cases of fatal RP occurred in the older group.
| S-EPMC7475579 | biostudies-literature