Dataset Information

Textural features of cervical cancers on FDG-PET/CT associate with survival and local relapse in patients treated with definitive chemoradiotherapy.

ABSTRACT: We retrospectively reviewed the records of 142 patients with stage IB-IIIB cervical cancer who underwent 18F-FDG-PET/CT before external beam radiotherapy plus intracavitary brachytherapy and concurrent chemotherapy. The patients were divided into training and validation cohorts to confirm the reliability of predictors for recurrence. Kaplan-Meier analysis was performed and a Cox regression model was used to examine the effects of variables on overall survival (OS), progression-free survival (PFS), distant metastasis-free survival (DMFS), and pelvic relapse-free survival (PRFS). High gray-level run emphasis (HGRE) derived from gray-level run-length matrix most accurately and consistently predicted the presence of pelvic residual or recurrent tumors for both cohorts. In multivariate analysis, stages IIIA-IIIB (P?=?0.001, hazard ratio [HR]?=?4.07) and a low HGRE (P?

SUBMITTER: Chen SW

PROVIDER: S-EPMC6082904 | biostudies-other | 2018 Aug

REPOSITORIES: biostudies-other

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Textural features of cervical cancers on FDG-PET/CT associate with survival and local relapse in patients treated with definitive chemoradiotherapy.

Chen Shang-Wen SW Shen Wei-Chih WC Hsieh Te-Chun TC Liang Ji-An JA Hung Yao-Ching YC Yeh Lian-Shung LS Chang Wei-Chun WC Lin Wu-Chou WC Yen Kuo-Yang KY Kao Chia-Hung CH

Scientific reports 20180808 1

We retrospectively reviewed the records of 142 patients with stage IB-IIIB cervical cancer who underwent <sup>18</sup>F-FDG-PET/CT before external beam radiotherapy plus intracavitary brachytherapy and concurrent chemotherapy. The patients were divided into training and validation cohorts to confirm the reliability of predictors for recurrence. Kaplan-Meier analysis was performed and a Cox regression model was used to examine the effects of variables on overall survival (OS), progression-free su ...[more]

PMID: 30089896

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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:At present, 18F-fluorodesoxyglucose (18FDG) positron emission tomography (PET)/computed tomography (CT) cannot be used to omit a bone marrow biopsy (BMB) among initial staging procedures in follicular lymphoma (FL). The additional diagnostic value of skeletal textural features on baseline 18FDG-PET/CT in diffuse large B-cell lymphoma (DLBCL) patients has given promising results. The aim of this study is to evaluate the value of 18FDG-PET/CT radiomics for the diagnosis of bone marrow involvement (BMI) in FL patients. This retrospective bicentric study enrolled newly diagnosed FL patients addressed for baseline 18FDG PET/CT. For visual assessment, examinations were considered positive in cases of obvious bone focal uptakes. For textural analysis, the skeleton volumes of interest (VOIs) were automatically extracted from segmented CT images and analysed using LifeX software. BMB and visual assessment were taken as the gold standard: BMB -/PET - patients were considered as bone-NEGATIVE patients, whereas BMB +/PET -, BMB -/PET + and BMB +/PET + patients were considered bone-POSITIVE patients. A LASSO regression algorithm was used to select features of interest and to build a prediction model. Sixty-six consecutive patients were included: 36 bone-NEGATIVE (54.5%) and 30 bone-POSITIVE (45.5%). The LASSO regression found variance_GLCM, correlation_GLCM, joint entropy_GLCM and busyness_NGLDM to have nonzero regression coefficients. Based on ROC analysis, a cut-off equal to - 0.190 was found to be optimal for the diagnosis of BMI using PET pred.score. The corresponding sensitivity, specificity, PPV and NPV values were equal to 70.0%, 83.3%, 77.8% and 76.9%, respectively. When comparing the ROC AUCs with using BMB alone, visual PET assessment or PET pred.score, a significant difference was found between BMB versus visual PET assessments (p = 0.010) but not between BMB and PET pred.score assessments (p = 0.097). Skeleton texture analysis is worth exploring to improve the performance of 18FDG-PET/CT for the diagnosis of BMI at baseline in FL patients.

Project description:Diagnosing relapse after radiotherapy for lung cancer is challenging. The specificity of both CT and 18F-FDG PET/CT is low because of radiation-induced changes. 3'-deoxy-3'-18F-fluorothymidine (18F-FLT) PET has previously demonstrated higher specificity for malignancy than 18F-FDG PET. We investigated the value of 18F-FLT PET/CT for diagnosing relapse in irradiated lung cancer. Methods: Patients suspected of relapse of lung cancer after definitive radiotherapy (conventional fractionated radiotherapy [cRT] or stereotactic body radiotherapy [SBRT]) were included. Sensitivity and specificity were analyzed both within the irradiated high-dose volume (HDV) and on a patient basis. Marginal differences and interobserver agreement were assessed. Results: Sixty-three patients who had received radiotherapy in 70 HDVs (34 cRT; 36 SBRT) were included. The specificity of 18F-FLT PET/CT was higher than that of 18F-FDG PET/CT (HDV, 96% [95% CI, 87-100] vs. 71% [95% CI, 57-83] [P = 0.0039]; patient-based, 90% [95% CI, 73-98] vs. 55% [95% CI, 36-74] [P = 0.0020]). The difference in specificity between 18F-FLT PET/CT and 18F-FDG PET/CT was higher after cRT than after SBRT. The sensitivity of 18F-FLT PET/CT was lower than that of 18F-FDG PET/CT (HDV, 69% [95% CI, 41-89] vs. 94% [95% CI, 70-100] [P = 0.1250]; patient-based, 70% [95% CI, 51-84] vs. 94% [95% CI, 80-99] [P = 0.0078]). Adding 18F-FLT PET/CT when 18F-FDG PET/CT was positive or inconclusive improved the diagnostic value compared with 18F-FDG PET/CT alone. In cRT HDVs, the probability of malignancy increased from 67% for 18F-FDG PET/CT alone to 100% when both tracers were positive. Conclusion: 18F-FLT PET/CT adds diagnostic value to 18F-FDG PET/CT in patients with suspected relapse. The diagnostic impact of 18F-FLT PET/CT was highest after cRT. We suggest adding 18F-FLT PET/CT when 18F-FDG PET/CT is inconclusive or positive within the previously irradiated volume to improve diagnostic value in patients for whom histologic confirmation is not easily obtained.

Project description:We extracted image features from serial 18F-labeled fluorodeoxyglucose (FDG) positron emission tomography (PET) / computed tomography (CT) scans of anal cancer patients for the prediction of tumor recurrence after chemoradiation therapy (CRT). Seventeen patients (4 recurrent and 13 non-recurrent) underwent three PET/CT scans at baseline (Pre-CRT), in the middle of the treatment (Mid-CRT) and post-treatment (Post-CRT) were included. For each patient, Mid-CRT and Post-CRT scans were aligned to Pre-CRT scan. Comprehensive image features were extracted from CT and PET (SUV) images within manually delineated gross tumor volume, including geometry features, intensity features and texture features. The difference of feature values between two time points were also computed and analyzed. We employed univariate logistic regression model, multivariate model, and naïve Bayesian classifier to analyze the image features and identify useful tumor recurrent predictors. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the accuracy of the prediction. In univariate analysis, six geometry, three intensity, and six texture features were identified as significant predictors of tumor recurrence. A geometry feature of Roundness between Post-CRT and Pre-CRT CTs was identified as the most important predictor with an AUC value of 1.00 by multivariate logistic regression model. The difference of Number of Pixels on Border (geometry feature) between Post-CRT and Pre-CRT SUVs and Elongation (geometry feature) of Post-CRT CT were identified as the most useful feature set (AUC = 1.00) by naïve Bayesian classifier. To investigate the early prediction ability, we used features only from Pre-CRT and Mid-CRT scans. Orientation (geometry feature) of Pre-CRT SUV, Mean (intensity feature) of Pre-CRT CT, and Mean of Long Run High Gray Level Emphasis (LRHGLE) (texture feature) of Pre-CRT CT were identified as the most important feature set (AUC = 1.00) by multivariate logistic regression model. Standard deviation (intensity feature) of Mid-CRT SUV and difference of Mean of LRHGLE (texture feature) between Mid-CRT and Pre-CRT SUVs were identified as the most important feature set (AUC = 0.86) by naïve Bayesian classifier. The experimental results demonstrated the potential of serial PET/CT scans in early prediction of anal tumor recurrence.

Dataset Information

Textural features of cervical cancers on FDG-PET/CT associate with survival and local relapse in patients treated with definitive chemoradiotherapy.

Publications

Textural features of cervical cancers on FDG-PET/CT associate with survival and local relapse in patients treated with definitive chemoradiotherapy.

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