Dataset Information

Predictive value of quantitative 18F-FDG-PET radiomics analysis in patients with head and neck squamous cell carcinoma.

ABSTRACT: BACKGROUND:Radiomics is aimed at image-based tumor phenotyping, enabling application within clinical-decision-support-systems to improve diagnostic accuracy and allow for personalized treatment. The purpose was to identify predictive 18-fluor-fluoro-2-deoxyglucose (18F-FDG) positron-emission tomography (PET) radiomic features to predict recurrence, distant metastasis, and overall survival in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy. METHODS:Between 2012 and 2018, 103 retrospectively (training cohort) and 71 consecutively included patients (validation cohort) underwent 18F-FDG-PET/CT imaging. The 434 extracted radiomic features were subjected, after redundancy filtering, to a projection resulting in outcome-independent meta-features (factors). Correlations between clinical, first-order 18F-FDG-PET parameters (e.g., SUVmean), and factors were assessed. Factors were combined with 18F-FDG-PET and clinical parameters in a multivariable survival regression and validated. A clinically applicable risk-stratification was constructed for patients' outcome. RESULTS:Based on 124 retained radiomic features from 103 patients, 8 factors were constructed. Recurrence prediction was significantly most accurate by combining HPV-status, SUVmean, SUVpeak, factor 3 (histogram gradient and long-run-low-grey-level-emphasis), factor 4 (volume-difference, coarseness, and grey-level-non-uniformity), and factor 6 (histogram variation coefficient) (CI = 0.645). Distant metastasis prediction was most accurate assessing metabolic-active tumor volume (MATV)(CI = 0.627). Overall survival prediction was most accurate using HPV-status, SUVmean, SUVmax, factor 1 (least-axis-length, non-uniformity, high-dependence-of-high grey-levels), and factor 5 (aspherity, major-axis-length, inversed-compactness and, inversed-flatness) (CI = 0.764). CONCLUSIONS:Combining HPV-status, first-order 18F-FDG-PET parameters, and complementary radiomic factors was most accurate for time-to-event prediction. Predictive phenotype-specific tumor characteristics and interactions might be captured and retained using radiomic factors, which allows for personalized risk stratification and optimizing personalized cancer care. TRIAL REGISTRATION:Trial NL3946 (NTR4111), local ethics commission reference: Prediction 2013.191 and 2016.498. Registered 7 August 2013, https://www.trialregister.nl/trial/3946.

SUBMITTER: Martens RM

PROVIDER: S-EPMC7477048 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Predictive value of quantitative <sup>18</sup>F-FDG-PET radiomics analysis in patients with head and neck squamous cell carcinoma.

Martens Roland M RM Koopman Thomas T Noij Daniel P DP Pfaehler Elisabeth E Übelhör Caroline C Sharma Sughandi S Vergeer Marije R MR Leemans C René CR Hoekstra Otto S OS Yaqub Maqsood M Zwezerijnen Gerben J GJ Heymans Martijn W MW Peeters Carel F W CFW de Bree Remco R de Graaf Pim P Castelijns Jonas A JA Boellaard Ronald R

EJNMMI research 20200907 1

<h4>Background</h4>Radiomics is aimed at image-based tumor phenotyping, enabling application within clinical-decision-support-systems to improve diagnostic accuracy and allow for personalized treatment. The purpose was to identify predictive 18-fluor-fluoro-2-deoxyglucose (<sup>18</sup>F-FDG) positron-emission tomography (PET) radiomic features to predict recurrence, distant metastasis, and overall survival in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy.<h4 ...[more]

PMID: 32894373

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Project description:BACKGROUND AND PURPOSE:FDG PET/CT has a high negative predictive value in patients with head and neck squamous cell carcinoma who responds completely to non-operative therapy. However, the treatment failure rate in patients with a partial but incomplete response is unclear. Our aim was to investigate the negative predictive value of the first posttreatment FDG-PET/CT in patients with head and neck squamous cell carcinoma with incomplete response interpreted as Neck Imaging Reporting and Data System (NI-RADS) category 2. MATERIALS AND METHODS:We retrospectively identified patients with head and neck squamous cell carcinoma treated with chemoradiation or radiation therapy with curative intent in our institution between 2008 and 2016. We included patients whose first posttreatment FDG-PET/CT was interpreted as showing marked improvement of disease but who had a mild residual mass or FDG avidity in either the primary tumor bed or lymph nodes (NI-RADS 2). The negative predictive value of FDG-PET/CT was calculated, including the 95% CI, using the Newcombe method. Two-year disease-free survival was the reference standard. RESULTS:Seventeen of 110 patients (15%) experienced locoregional treatment failure within 2 years of completing treatment, yielding a negative predictive value of 85% (95% Cl, 77%-90%). The most common location of tumor recurrence was the cervical lymph nodes (59%). The median time interval between completion of therapy and treatment failure was 10 months (range, 5-24 months). CONCLUSIONS:In patients with an incomplete response after treatment of head and neck squamous cell carcinoma, the negative predictive value of the first posttreatment FDG-PET/CT was 85%, which is lower than the 91% negative predictive value of FDG-PET/CT in patients with an initial complete response. Patients with an incomplete response (NI-RADS 2) should undergo more frequent clinical and imaging surveillance than patients with an initial complete response (NI-RADS 1).

Project description:Patients with locally-advanced head and neck squamous cell carcinoma (HNSCC) have variable responses to (chemo)radiotherapy. A reliable prediction of outcomes allows for enhancing treatment efficacy and follow-up monitoring. Fifty-seven histopathologically-proven HNSCC patients with curative (chemo)radiotherapy were prospectively included. All patients had an MRI (DW,-IVIM, DCE-MRI) and 18F-FDG-PET/CT before and 10 days after start-treatment (intratreatment). Primary tumor functional imaging parameters were extracted. Univariate and multivariate analysis were performed to construct prognostic models and risk stratification for 2 year locoregional recurrence-free survival (LRFFS), distant metastasis-free survival (DMFS) and overall survival (OS). Model performance was measured by the cross-validated area under the receiver operating characteristic curve (AUC). The best LRFFS model contained the pretreatment imaging parameters ADC_kurtosis, Kep and SUV_peak, and intratreatment imaging parameters change (Δ) Δ-ADC_skewness, Δ-f, Δ-SUV_peak and Δ-total lesion glycolysis (TLG) (AUC = 0.81). Clinical parameters did not enhance LRFFS prediction. The best DMFS model contained pretreatment ADC_kurtosis and SUV_peak (AUC = 0.88). The best OS model contained gender, HPV-status, N-stage, pretreatment ADC_skewness, D, f, metabolic-active tumor volume (MATV), SUV_mean and SUV_peak (AUC = 0.82). Risk stratification in high/medium/low risk was significantly prognostic for LRFFS (p = 0.002), DMFS (p < 0.001) and OS (p = 0.003). Intratreatment functional imaging parameters capture early tumoral changes that only provide prognostic information regarding LRFFS. The best LRFFS model consisted of pretreatment, intratreatment and Δ functional imaging parameters; the DMFS model consisted of only pretreatment functional imaging parameters, and the OS model consisted ofHPV-status, gender and only pretreatment functional imaging parameters. Accurate clinically applicable risk stratification calculators can enable personalized treatment (adaptation) management, early on during treatment, improve counseling and enhance patient-specific post-therapy monitoring.

Project description:Simple Summary PET/CT is an important staging modality in the baseline assessment of locally advanced esophageal squamous cell carcinoma. Accurate staging and response prediction in these patients is essential for management. The aim of this retrospective study was to assess the usefulness of 18F-FDG PET/CT radiomics features in predicting outcomes such as tumor and nodal categories, PET-based response to induction chemotherapy, progression-free survival, and overall survival. In a final cohort of 74 patients, we found that the developed radiomics models can predict these clinical and prognostic outcomes with reasonable accuracy, similar or better than those derived from conventional imaging. Future studies with a larger cohort would be helpful in establishing the significance of these models. Abstract This study aimed to assess the usefulness of radiomics features of 18F-FDG PET/CT in patients with locally advanced esophageal cancers (ESCC) in predicting outcomes such as clinical tumor (cT) and nodal (cN) categories, PET response to induction chemotherapy (PET response), progression-free survival (PFS), and overall survival (OS). Pretreatment PET/CT images from patients who underwent concurrent chemoradiotherapy from July 2002 to February 2017 were segmented, and data were split into training and test sets. Model development was performed on the training datasets and a maximum of five features were selected. Final diagnostic accuracies were determined using the test dataset. A total of 86 PET/CTs (58 men and 28 women, mean age 65 years) were segmented. Due to small lesion size, 12 patients were excluded. The diagnostic accuracies as derived from the CT, PET, and combined PET/CT test datasets were as follows: cT category—70.4%, 70.4%, and 81.5%, respectively; cN category—69.0%, 86.2%, and 86.2%, respectively; PET response—60.0%, 66.7%, and 70.0%, respectively; PFS—60.7%, 75.0%, and 75.0%, respectively; and OS—51.7%, 55.2%, and 62.1%, respectively. A radiomics assessment of locally advanced ESCC has the potential to predict various clinical outcomes. External validation of these models would be further helpful.

Dataset Information

Predictive value of quantitative 18F-FDG-PET radiomics analysis in patients with head and neck squamous cell carcinoma.

Publications

Predictive value of quantitative <sup>18</sup>F-FDG-PET radiomics analysis in patients with head and neck squamous cell carcinoma.

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