ABSTRACT

PURPOSE/OBJECTIVE(S): To investigate the predictive value of changes in myocardial 18F-FDG uptake for major adverse cardiac events (MACEs) in locally advanced esophageal cancer patients receiving definitive radiotherapy.

MATERIALS/METHODS: Between August 2012 and January 2018, 400 patients with stage II-III esophageal cancer receiving definitive radiotherapy at two institutions were divided into the training (n = 240) and external validation cohorts (n = 160). All patients underwent FDG-PET imaging within 1 week before treatment and 3 months after treatment. Myocardium delineation was performed by Carimas software (version 2.10) based on the AHA 17-segment model. When contouring the left ventricle, the myocardium was automatically divided into basal (segments 1-6), middle (segments 7-12), and apical (segments 13-16) regions, and the mean dose and FDG uptake parameters of each region were obtained by Carimas. Our primary endpoint was MACEs. Patient clinicopathologic factors, dosimetric parameters for the whole heart and cardiac substructures, and myocardial changes within the three regions on 18F-FDG PET were utilized to seek the best predictive models for cardiotoxicity. To avoid multicollinearity between dose-volume histogram (DVH) parameters, we selected the variables with the lowest Akaike Information Criterion (AIC) value from the DVH parameters of the same cardiac structure for the actual modeling procedure. Competing risk analysis and Cox regressions analysis were performed. The predictive performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC) and Brier score.

RESULTS: At a median follow-up interval of 78 months, 28 patients (11.7%) developed MACEs. The basal region of the myocardium received the highest radiation dose, followed by the middle and the apex region. The basal myocardial SUVmax and SUVmean significantly increased after radiotherapy while the apical and middle myocardial SUVmax and SUVmean not significantly increased. In univariate analysis, age, pre-existing cardiac disease, changes in pre- and post-treatment basal myocardial SUVmax and SUVmean (∆SUVmax and ∆SUVmean), and dosimetric parameters for MHD, mean LCX, mean LAD, and mean LV dose were associated with an increased hazard of MACEs. Multivariate analysis showed that basal ∆SUVmean retained significance after adjusting for age, pre-existing cardiac disease, and dosimetric parameters for whole heart and cardiac substructures. The AUCs and Brier scores demonstrated favorable predictive accuracies of the model's integrating variables with significant difference in multivariate analysis when predicting MACEs in the training and validation cohorts.

CONCLUSION: ∆SUVmean was an independent indicator of MACE in locally advanced esophageal cancer patients receiving definitive radiotherapy. Changes in basal myocardial FDG uptake is a promising biomaker for predicting radiation-induced cardiotoxicity.

PMID:37785059 | DOI:10.1016/j.ijrobp.2023.06.1272

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PubMed articles on: Cardio-Oncology

Early Cardiotoxicity in Patients Receiving Hypofractionated Radiotherapy after Breast Conserving Surgery: Analysis of a Prospective Study

Int J Radiat Oncol Biol Phys. 2023 Oct 1;117(2S):e169. doi: 10.1016/j.ijrobp.2023.06.1008.

ABSTRACT

PURPOSE/OBJECTIVE(S): To evaluate the early cardiotoxicity of hypofractionated radiotherapy (HFRT) in patients with left-sided breast cancer after breast-conserving surgery, and to investigate the correlation between cardiotoxicity and cardiac dose.

MATERIALS/METHODS: A total of 103 women from 2017 to 2018 who received left-sided whole-breast with or without regional nodal irradiation either using deep inspiration breath-hold (DIBH) or free-breathing (FB) technique were prospectively enrolled. N-terminal pro-B-type natriuretic peptide (NT-proBNP), electrocardiogram, and radionuclide myocardial perfusion imaging were conducted before and after HFRT. Logistic regression analyses were performed to determine the association of cancer treatment, cardiac dose, and cardiovascular risk factors with cardiotoxic effects.

RESULTS: The mean dose (Dmean) of the heart, left anterior descending coronary artery (LAD), left ventricular (LV), and right ventricular (RV) in all patients was 403 cGy, 1685 cGy, 627 cGy, and 444 cGy, respectively. In comparison to FB, DIBH significantly reduced cardiac dose (heart Dmean 250 cGy vs. 570 cGy, LAD Dmean 1250 cGy vs. 2170 cGy, LV Dmean 420 cGy vs. 850 cGy, RV Dmean 260 cGy vs. 650 cGy; all p<0.001).

CONCLUSION: Early subclinical cardiac damage after HFRT in left-sided breast cancer is dose-related, and mostly manageable and reversible without medical intervention.

PMID:37784775 | DOI:10.1016/j.ijrobp.2023.06.1008

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PubMed articles on: Cardio-Oncology

Multitask AI Models for the Joint Prediction of Overall Survival, Progression-Free Survival, and Death without Progression as a Composite Endpoint for LA-NSCLC Patients Treated with Chemoradiotherapy

Int J Radiat Oncol Biol Phys. 2023 Oct 1;117(2S):S54. doi: 10.1016/j.ijrobp.2023.06.344.

ABSTRACT

PURPOSE/OBJECTIVE(S): Prior methods model the risk of endpoints separately. Herein, we construct a composite AI model that considers multiple endpoints jointly, including overall survival (OS), progression-free survival (PFS), and death without progression (DWP). Our hypothesis is that the composite model potentially improves predictive performance for patients with locally advanced non-small cell lung cancer (LANSCLC) treated with chemoradiotherapy (CRT).

MATERIALS/METHODS: A total of 335 LANSCLC patients treated with definitive CRT, including all evaluable patients accrued from Oct 2017 to Dec 2021, were randomly split into training/test subsets (n = 234/101). Cardio-pulmonary substructures (CPSs) were autocontoured, manually reviewed, and edited if necessary. A total of 1093 non-independent dosimetric parameters were extracted, including GTVp, GTVn, GTV, PTV, esophagus, lungs minus IGTV, left/right lung, 15 CPSs, and the overlapping volume of each OAR with PTV and the distance from each OAR to GTVp/GTVn. Other clinical parameters included age, consolidation immunotherapy (CI), ECOG score, Charlson comorbidity index, coronary heart disease, histology, PD-L1 expression, and clinical stage (AJCC 8). Within training, censored time-to-event data were imputed based on conditional event distributions derived from Kaplan-Meier estimators for casting survival analysis as a regression problem and training neural additive model (NAM) regressors. Features were selected by LASSO regression for a single endpoint (OS, PFS, DWP) and multi-task (MT) LASSO regression for four separate composite endpoints (OS-PFS, OS-DWP, PFS-DWP, OS-PFS-DWP). The performance of MT NAMs in the test set that jointly predicted the composite endpoints was evaluated using the C-index and compared to that of a single task (ST) NAM that predicted each endpoint separately.

RESULTS: The best testing performance in predicting OS and DWP was attained by the MT NAM that jointly predicted all endpoints (c-index = 0.65, 95% CI 0.58-0.71 for OS; c-index = 0.78, 95% CI 0.69-0.87 for DWP). The best model to predict PFS was also MT between PFS and DWP (c-index = 0.59, 95% CI 0.52-0.65). The c-indices of all ST NAMs were less than 0.56. The best MT NAMs significantly outperformed ST NAMs in predicting OS (p = 0.001) and DWP (p = 0.01) except for PFS (p = 0.32). The best MT NAM in predicting OS and DWP included ECOG score, atria-PTV overlap volume, D75% [Gy] to the left atrium (LA), pulmonary arterial volume, histology (adenocarcinoma), D65% [Gy] to the descending aorta (DA), V10 Gy [%] of the LA and CI in order of overall importance. ECOG score consistently ranked as the most important feature for all four MT NAMs. An increase of ECOG score from 0 to 2 indicated a 6-month earlier risk of mortality and DWP. Atria-PTV overlap volume and D65% [Gy] to the DA were included in all four MT NAMs.

CONCLUSION: MT AI models improved outcome prediction in patients with LANSCLC treated with CRT by jointly learning commonalities between the primary and auxiliary endpoints.

PMID:37784521 | DOI:10.1016/j.ijrobp.2023.06.344

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PubMed articles on: Cardio-Oncology

Novel Functional Radiomics for Prediction of Cardiac PET Avidity in Lung Cancer Radiotherapy

Int J Radiat Oncol Biol Phys. 2023 Oct 1;117(2S):S155. doi: 10.1016/j.ijrobp.2023.06.578.

ABSTRACT

PURPOSE/OBJECTIVE(S): Traditional methods of evaluating cardiotoxicity focus solely on radiation doses to the heart and do not incorporate functional imaging information. Functional imaging has great potential to improve the ability to provide early prediction for cardiotoxicity for lung cancer patients undergoing radiotherapy. FDG-based PET/CT imaging is routinely obtained as part of standard staging work up for lung cancer patients. Although FDG PET/CT scans are typically used to evaluate the tumor, imaging guidelines note that FDG PET/CT scans are an FDA-approved method to image for cardiac inflammation, and studies have noted that the PET cardiac signal can be predictive of clinical outcomes. The purpose of this work was to develop a radiomics model to predict clinical cardiac assessment of standard of care FDG PET/CT scans.

MATERIALS/METHODS: The study included 100 consecutive lung cancer patients treated with radiotherapy who underwent standard pre-treatment FDG-PET/CT staging scans. A clinician reviewed the PET/CT scans per clinical cardiac assessment guidelines and classified the cardiac uptake as: 0 = uniform diffuse, 1 = absent, 2 = heterogeneous, with event rates of 20%, 44%, and 35%, respectively. The heart was delineated and 200 novel functional radiomics features were selected to classify cardiac FDG uptake patterns. We divided the data into an 80% training set and a 20% test set to train and evaluate the classification models. Feature reduction was carried out using the Wilcoxon test (with Bonferroni adjusted p<0.05),

RESULTS: Fifty-one independent radiomics features were reduced to 3 clinically pertinent features (PET 2D Skewness, PET Grey Level Co-occurrence Matrix Correlation, and PET Median) using feature reduction techniques. The model selected by TPOT showed 89.8% predictive accuracy in the cross validation of the training set and 85% predictive accuracy on the test set. The model selected by AutoSklearn showed 89.7% predictive accuracy in the cross validation of the training set and 80% predictive accuracy on the test set.

CONCLUSION: The novelty of this work is that it is the first study to develop and evaluate functional cardiac radiomic features from standard of care FDG PET/CT scans with the data showing good predictive accuracy with clinical imaging evaluation. If validated, the current work provides automated methods to provide functional cardiac information using standard of care imaging that can be used as an imaging biomarker for early clinical toxicity prediction for lung cancer patients.

PMID:37784390 | DOI:10.1016/j.ijrobp.2023.06.578

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PubMed articles on: Cardio-Oncology

Premature senescence and cardiovascular disease following cancer treatments: mechanistic insights

Front Cardiovasc Med. 2023 Sep 14;10:1212174. doi: 10.3389/fcvm.2023.1212174. eCollection 2023.

ABSTRACT

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality, especially among the aging population. The "response-to-injury" model proposed by Dr. Russell Ross in 1999 emphasizes inflammation as a critical factor in atherosclerosis development, with atherosclerotic plaques forming due to endothelial cell (EC) injury, followed by myeloid cell adhesion and invasion into the blood vessel walls. Recent evidence indicates that cancer and its treatments can lead to long-term complications, including CVD. Cellular senescence, a hallmark of aging, is implicated in CVD pathogenesis, particularly in cancer survivors. However, the precise mechanisms linking premature senescence to CVD in cancer survivors remain poorly understood. This article aims to provide mechanistic insights into this association and propose future directions to better comprehend this complex interplay.

PMID:37781317 | PMC:PMC10540075 | DOI:10.3389/fcvm.2023.1212174

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PubMed articles on: Cardio-Oncology

The broad spectrum of cardiotoxicities from immunotherapies

Front Cardiovasc Med. 2023 Sep 15;10:1259620. doi: 10.3389/fcvm.2023.1259620. eCollection 2023.

NO ABSTRACT

PMID:37781307 | PMC:PMC10540439 | DOI:10.3389/fcvm.2023.1259620

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