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[18F]FDG PET immunotherapy radiomics signature (iRADIOMICS) predicts response of non-small-cell lung cancer patients treated with pembrolizumab.

ABSTRACT: Background Immune checkpoint inhibitors have changed the paradigm of cancer treatment; however, non-invasive biomarkers of response are still needed to identify candidates for non-responders. We aimed to investigate whether immunotherapy [18F]FDG PET radiomics signature (iRADIOMICS) predicts response of metastatic non-small-cell lung cancer (NSCLC) patients to pembrolizumab better than the current clinical standards. Patients and methods Thirty patients receiving pembrolizumab were scanned with [18F]FDG PET/CT at baseline, month 1 and 4. Associations of six robust primary tumour radiomics features with overall survival were analysed with Mann-Whitney U-test (MWU), Cox proportional hazards regression analysis, and ROC curve analysis. iRADIOMICS was constructed using univariate and multivariate logistic models of the most promising feature(s). Its predictive power was compared to PD-L1 tumour proportion score (TPS) and iRECIST using ROC curve analysis. Prediction accuracies were assessed with 5-fold cross validation. Results The most predictive were baseline radiomics features, e.g. Small Run Emphasis (MWU, p = 0.001; hazard ratio = 0.46, p = 0.007; AUC = 0.85 (95% CI 0.69-1.00)). Multivariate iRADIOMICS was found superior to the current standards in terms of predictive power and timewise with the following AUC (95% CI) and accuracy (standard deviation): iRADIOMICS (baseline), 0.90 (0.78-1.00), 78% (18%); PD-L1 TPS (baseline), 0.60 (0.37-0.83), 53% (18%); iRECIST (month 1), 0.79 (0.62-0.95), 76% (16%); iRECIST (month 4), 0.86 (0.72-1.00), 76% (17%). Conclusions Multivariate iRADIOMICS was identified as a promising imaging biomarker, which could improve management of metastatic NSCLC patients treated with pembrolizumab. The predicted non-responders could be offered other treatment options to improve their overall survival.

SUBMITTER: Valentinuzzi D

PROVIDER: S-EPMC7409607 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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[18F]FDG PET immunotherapy radiomics signature (iRADIOMICS) predicts response of non-small-cell lung cancer patients treated with pembrolizumab.

Valentinuzzi Damijan D Vrankar Martina M Boc Nina N Ahac Valentina V Zupancic Ziga Z Unk Mojca M Skalic Katja K Zagar Ivana I Studen Andrej A Simoncic Urban U Eickhoff Jens J Jeraj Robert R

Radiology and oncology 20200729 3

Background Immune checkpoint inhibitors have changed the paradigm of cancer treatment; however, non-invasive biomarkers of response are still needed to identify candidates for non-responders. We aimed to investigate whether immunotherapy [18F]FDG PET radiomics signature (iRADIOMICS) predicts response of metastatic non-small-cell lung cancer (NSCLC) patients to pembrolizumab better than the current clinical standards. Patients and methods Thirty patients receiving pembrolizumab were scanned with ...[more]

PMID: 32726293

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Project description:OBJECTIVES:(1.1) to evaluate the association between baseline 18F-FDG PET/CT semi-quantitative parameters of the primary lesion with progression free survival (PFS), overall survival (OS) and response to immunotherapy, in advanced non-small cell lung carcinoma (NSCLC) patients eligible for immunotherapy; (1.2) to evaluate the application of radiomics analysis of the primary lesion to identify features predictive of response to immunotherapy; (1.3) to evaluate if tumor burden assessed by 18F-FDG PET/CT (N and M factors) is associated with PFS and OS. MATERIALS AND METHODS:we retrospectively analyzed clinical records of advanced NCSLC patients (stage IIIb/c or stage IV) candidate to immunotherapy who performed 18F-FDG PET/CT before treatment to stage the disease. Fifty-seven (57) patients were included in the analysis (F:M 17:40; median age = 69 years old). Notably, 38/57 of patients had adenocarcinoma (AC), 10/57 squamous cell carcinoma (SCC) and 9/57 were not otherwise specified (NOS). Overall, 47.4% patients were stage IVA, 42.1% IVB and 8.8% IIIB. Immunotherapy was performed as front-line therapy in 42/57 patients and as second line therapy after chemotherapy platinum-based in 15/57. The median follow up after starting immunotherapy was 10 months (range: 1.5-68.6). Therapy response was assessed by RECIST 1.1 criteria (CT evaluation every 4 cycles of therapy) in 48/57 patients or when not feasible by clinical and laboratory data (fast disease progression or worsening of patient clinical condition in nine patients). Radiomics analysis was performed by applying regions of interest (ROIs) of the primary tumor delineated manually by two operators and semi-automatically applying a threshold at 40% of SUVmax. RESULTS:(1.1) metabolic tumor volume (MTV) (p = 0.028) and total lesion glycolysis (TLG) (p = 0.035) were significantly associated with progressive vs. non-progressive disease status. Patients with higher values of MTV and TLG had higher probability of disease progression, compared to those patients presenting with lower values. SUVmax did not show correlation with PD status, PFS and OS. MTV (p = 0.027) and TLG (p = 0.022) also resulted in being significantly different among PR, SD and PD groups, while SUVmax was confirmed to not be associated with response to therapy (p = 0.427). (1.2) We observed the association of several radiomics features with PD status. Namely, patients with high tumor volume, TLG and heterogeneity expressed by "skewness" and "kurtosis" had a higher probability of failing immunotherapy. (1.3) M status at 18F-FDG PET/CT was significantly associated with PFS (p = 0.002) and OS (p = 0.049). No significant associations were observed for N status. CONCLUSIONS:18F-FDG PET/CT performed before the start of immunotherapy might be an important prognostic tool able to predict the disease progression and response to immunotherapy in patients with advanced NSCLC, since MTV, TLG and radiomics features (volume and heterogeneity) are associated with disease progression.

Project description:Purpose:Hematologic toxicity (HT) during chemoradiation therapy (CRT) for anal cancer can lead to treatment breaks that compromise efficacy. We hypothesized that CRT-induced HT correlates with changes in active bone marrow (ABM) characterized by pre-/post-CRT positron emission tomography (PET)/computed tomography. Methods and materials:Data from 36 patients with anal cancer who were treated with 18F-fluorodeoxyglucose PET/computed tomography scans 2 weeks before and 6 to 16 weeks after CRT were analyzed. Complete blood counts with differential within 2 weeks from, weekly during, and 2 week after treatment were obtained. HT was defined as baseline complete blood count change to nadir and posttreatment recovery. Total bone marrow was segmented into 2 subregions: lumbosacral (LS) pelvis (L5 vertebrae, sacrum, and coccyx) and lower pelvis (LP) (ilium, femoral head/neck, and greater and lesser trochanter). PET ABM was characterized as the volume having standard uptake value (SUV) greater than the mean uptake of unirradiated extrapelvic bone marrow. PET variables of pre-/post-CRT and HT predictors were analyzed by linear regression. Results:Average pelvic ABM was significantly reduced from 52% to 41% in pre- to post-CRT PET scans for all patients (P = .0012). Regional analysis indicated significant post-CRT reduction of LS-ABM (P < .0001) and LP-ABM (P = .006). Linear regression analysis identified post-CRT SUVmean, differential ?SUVmean, and ?ABM as correlating significantly with pre- and posttreatment HT. ?WBC linearly correlated with ?ABM of LS and LP pelvis (P = .033 and P = .028, respectively). Dosimetrically, ABM was sensitive to higher radiation doses (>50 Gy) in terms of acute hematologic ?WBC (P = .021) and ?ANC(P = .028). HT increased with increasing volume of ABM receiving 40 Gy. The results also suggest that ABM V40 Gy ? 20% to 25% may significantly reduce the risk of HT. Conclusions:HT was significantly associated with ?ABM in patients with anal cancer who were treated with CRT. LS-ABM was a robust surrogate for evaluating CRT-induced HT. Our results suggest implementation of ABM dosimetric constraints, V40 Gy ? 20-25%, may significantly reduce HT and lead to decreased treatment delays associated with clinical outcomes.

Project description:Background Primary tumor maximum standardized uptake value is a prognostic marker for non-small cell lung cancer. In the setting of malignancy, bone marrow activity from fluorine 18-fluorodeoxyglucose (FDG) PET may be informative for clinical risk stratification. Purpose To determine whether integrating FDG PET radiomic features of the primary tumor, tumor penumbra, and bone marrow identifies lung cancer disease-free survival more accurately than clinical features alone. Materials and Methods Patients were retrospectively analyzed from two distinct cohorts collected between 2008 and 2016. Each tumor, its surrounding penumbra, and bone marrow from the L3-L5 vertebral bodies was contoured on pretreatment FDG PET/CT images. There were 156 bone marrow and 512 tumor and penumbra radiomic features computed from the PET series. Randomized sparse Cox regression by least absolute shrinkage and selection operator identified features that predicted disease-free survival in the training cohort. Cox proportional hazards models were built and locked in the training cohort, then evaluated in an independent cohort for temporal validation. Results There were 227 patients analyzed; 136 for training (mean age, 69 years ± 9 [standard deviation]; 101 men) and 91 for temporal validation (mean age, 72 years ± 10; 91 men). The top clinical model included stage; adding tumor region features alone improved outcome prediction (log likelihood, -158 vs -152; P = .007). Adding bone marrow features continued to improve performance (log likelihood, -158 vs -145; P = .001). The top model integrated stage, two bone marrow texture features, one tumor with penumbra texture feature, and two penumbra texture features (concordance, 0.78; 95% confidence interval: 0.70, 0.85; P < .001). This fully integrated model was a predictor of poor outcome in the independent cohort (concordance, 0.72; 95% confidence interval: 0.64, 0.80; P < .001) and a binary score stratified patients into high and low risk of poor outcome (P < .001). Conclusion A model that includes pretreatment fluorine 18-fluorodeoxyglucose PET texture features from the primary tumor, tumor penumbra, and bone marrow predicts disease-free survival of patients with non-small cell lung cancer more accurately than clinical features alone. © RSNA, 2019 Online supplemental material is available for this article.

Project description:PurposeTo determine if quantitative features extracted from pretherapy fluorine 18 fluorodeoxyglucose (18F-FDG) PET/CT estimate prognosis in patients with locally advanced cervical cancer treated with chemoradiotherapy.Materials and methodsIn this retrospective study, PET/CT images and outcomes were curated from 154 patients with locally advanced cervical cancer, who underwent chemoradiotherapy from two institutions between March 2008 and June 2016, separated into independent training (n = 78; mean age, 51 years ± 13 [standard deviation]) and testing (n = 76; mean age, 50 years ± 10) cohorts. Radiomic features were extracted from PET, CT, and habitat (subregions with different metabolic characteristics) images that were derived by fusing PET and CT images. Parsimonious sets of these features were identified by the least absolute shrinkage and selection operator analysis and used to generate predictive radiomics signatures for progression-free survival (PFS) and overall survival (OS) estimation. Prognostic validation of the radiomic signatures as independent prognostic markers was performed using multivariable Cox regression, which was expressed as nomograms, together with other clinical risk factors.ResultsThe radiomics nomograms constructed with T stage, lymph node status, and radiomics signatures resulted in significantly better performance for the estimation of PFS (Harrell concordance index [C-index], 0.85 for training and 0.82 for test) and OS (C-index, 0.86 for training and 0.82 for test) compared with International Federation of Gynecology and Obstetrics staging system (C-index for PFS, 0.70 for training [P = .001] and 0.70 for test [P = .002]; C-index for OS, 0.73 for training [P < .001] and 0.70 for test [P < .001]), respectively.ConclusionPrognostic models were generated and validated from quantitative analysis of 18F-FDG PET/CT habitat images and clinical data, and may have the potential to identify the patients who need more aggressive treatment in clinical practice, pending further validation with larger prospective cohorts.Supplemental material is available for this article.© RSNA, 2020.

Project description:IntroductionImmunotherapy has improved outcomes for patients with non-small cell lung cancer (NSCLC), yet durable clinical benefit (DCB) is experienced in only a fraction of patients. Here, we test the hypothesis that radiomics features from baseline pretreatment 18F-FDG PET/CT scans can predict clinical outcomes of NSCLC patients treated with checkpoint blockade immunotherapy.MethodsThis study included 194 patients with histologically confirmed stage IIIB-IV NSCLC with pretreatment PET/CT images. Radiomics features were extracted from PET, CT, and PET+CT fusion images based on minimum Kullback-Leibler divergence (KLD) criteria. The radiomics features from 99 retrospective patients were used to train a multiparametric radiomics signature (mpRS) to predict DCB using an improved least absolute shrinkage and selection operator (LASSO) method, which was subsequently validated in both retrospective (N = 47) and prospective test cohorts (N = 48). Using these cohorts, the mpRS was also used to predict progression-free survival (PFS) and overall survival (OS) by training nomogram models using multivariable Cox regression analyses with additional clinical characteristics incorporated.ResultsThe mpRS could predict patients who will receive DCB, with areas under receiver operating characteristic curves (AUCs) of 0.86 (95%CI 0.79-0.94), 0.83 (95%CI 0.71-0.94), and 0.81 (95%CI 0.68-0.92) in the training, retrospective test, and prospective test cohorts, respectively. In the same three cohorts, respectively, nomogram models achieved C-indices of 0.74 (95%CI 0.68-0.80), 0.74 (95%CI 0.66-0.82), and 0.77 (95%CI 0.69-0.84) to predict PFS and C-indices of 0.83 (95%CI 0.77-0.88), 0.83 (95%CI 0.71-0.94), and 0.80 (95%CI 0.69-0.91) to predict OS.ConclusionPET/CT-based signature can be used prior to initiation of immunotherapy to identify NSCLC patients most likely to benefit from immunotherapy. As such, these data may be leveraged to improve more precise and individualized decision support in the treatment of patients with advanced NSCLC.

Dataset Information

[18F]FDG PET immunotherapy radiomics signature (iRADIOMICS) predicts response of non-small-cell lung cancer patients treated with pembrolizumab.

Publications

[18F]FDG PET immunotherapy radiomics signature (iRADIOMICS) predicts response of non-small-cell lung cancer patients treated with pembrolizumab.

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