Computed tomography based radiomic signature as predictive of survival and local control after stereotactic body radiation therapy in pancreatic carcinoma

Purpose To appraise the ability of a radiomics signature to predict clinical outcome after stereotactic body radiation therapy (SBRT) for pancreas carcinoma. Methods A cohort of 100 patients was included in this retrospective, single institution analysis. Radiomics texture features were extracted from computed tomography (CT) images obtained for the clinical target volume. The cohort of patients was randomly divided into two separate groups for the training (60 patients) and validation (40 patients). Cox regression models were built to predict overall survival and local control. The significant predictors at univariate analysis were included in a multivariate model. The quality of the models was appraised by means of area under the curve and concordance index. Results A clinical-radiomic signature associated with Overall Survival (OS) was found significant in both training and validation sets (p = 0.01 and 0.05 and concordance index 0.73 and 0.75 respectively). Similarly, a signature was found for Local Control (LC) with p = 0.007 and 0.004 and concordance index 0.69 and 0.75. In the low risk group, the median OS and LC in the validation group were 14.4 and 28.6 months while in the high-risk group were 9.0 and 17.5 months respectively. Conclusion A CT based radiomic signature was identified which correlate with OS and LC after SBRT and allowed to identify low and high-risk groups of patients.

[1]  L. Cozzi,et al.  Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery , 2018, European Journal of Nuclear Medicine and Molecular Imaging.

[2]  P. Lambin,et al.  Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach , 2014, Nature Communications.

[3]  Tara Kent,et al.  Induction gemcitabine and stereotactic body radiotherapy for locally advanced nonmetastatic pancreas cancer. , 2011, International journal of radiation oncology, biology, physics.

[4]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[5]  Paolo Francescon,et al.  Unresectable Locally Advanced Pancreatic Cancer: A Multimodal Treatment Using Neoadjuvant Chemoradiotherapy (Gemcitabine Plus Stereotactic Radiosurgery) and Subsequent Surgical Exploration , 2010, Annals of Surgical Oncology.

[6]  B. Erickson,et al.  Assessment of treatment response during chemoradiation therapy for pancreatic cancer based on quantitative radiomic analysis of daily CTs: An exploratory study , 2017, PloS one.

[7]  Richard Tuli,et al.  Identifying prognostic intratumor heterogeneity using pre- and post-radiotherapy 18F-FDG PET images for pancreatic cancer patients. , 2017, Journal of gastrointestinal oncology.

[8]  Irène Buvat,et al.  LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity. , 2018, Cancer research.

[9]  Masoom A. Haider,et al.  CT texture features are associated with overall survival in pancreatic ductal adenocarcinoma – a quantitative analysis , 2017, BMC Medical Imaging.

[10]  Daniel Normolle,et al.  A phase I/II trial of intensity modulated radiation (IMRT) dose escalation with concurrent fixed-dose rate gemcitabine (FDR-G) in patients with unresectable pancreatic cancer. , 2012, International journal of radiation oncology, biology, physics.

[11]  L Cozzi,et al.  PET Radiomics in NSCLC: state of the art and a proposal for harmonization of methodology , 2017, Scientific Reports.

[12]  L. Cozzi,et al.  [18F]FDG-PET/CT texture analysis in thyroid incidentalomas: preliminary results , 2017, European Journal of Hybrid Imaging.

[13]  M. Scorsetti,et al.  Can Stereotactic Body Radiation Therapy Be a Viable and Efficient Therapeutic Option for Unresectable Locally Advanced Pancreatic Adenocarcinoma? Results of a Phase 2 Study , 2017, Technology in cancer research & treatment.

[14]  Wei-Chung Hsu,et al.  Radiomics based analysis to predict local control and survival in hepatocellular carcinoma patients treated with volumetric modulated arc therapy , 2017, BMC Cancer.

[15]  Mithat Gönen,et al.  [¹⁸F]FDG-positron emission tomography coregistration with computed tomography scans for radiation treatment planning of lymphoma and hematologic malignancies. , 2011, International journal of radiation oncology, biology, physics.

[16]  A. Grosu,et al.  SBRT in pancreatic cancer: what is the therapeutic window? , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[17]  Dwight E Heron,et al.  Stereotactic Body Radiotherapy in the Treatment of Advanced Adenocarcinoma of the Pancreas , 2011, American journal of clinical oncology.

[18]  Ravi Shridhar,et al.  Stereotactic body radiation therapy for locally advanced and borderline resectable pancreatic cancer is effective and well tolerated. , 2013, International journal of radiation oncology, biology, physics.

[19]  T. Desser,et al.  Single-fraction stereotactic body radiation therapy and sequential gemcitabine for the treatment of locally advanced pancreatic cancer. , 2011, International journal of radiation oncology, biology, physics.

[20]  Matthias Guckenberger,et al.  Computed Tomography Radiomics Predicts HPV Status and Local Tumor Control After Definitive Radiochemotherapy in Head and Neck Squamous Cell Carcinoma. , 2017, International journal of radiation oncology, biology, physics.

[21]  A. Jemal,et al.  Cancer statistics, 2013 , 2013, CA: a cancer journal for clinicians.

[22]  R. Hruban,et al.  Pancreatic cancer , 2011, The Lancet.

[23]  Patrick Granton,et al.  Radiomics: extracting more information from medical images using advanced feature analysis. , 2012, European journal of cancer.

[24]  Ziding Feng,et al.  Quantitative imaging to evaluate malignant potential of IPMNs , 2016, Oncotarget.

[25]  Albert C. Koong,et al.  Phase 2 Multi-institutional Trial Evaluating Gemcitabine and Stereotactic Body Radiotherapy for Patients With Locally Advanced Unresectable Pancreatic Adenocarcinoma , 2014, Cancer.

[26]  N. Dubrawsky Cancer statistics , 1989, CA: a cancer journal for clinicians.

[27]  Ender Konukoglu,et al.  Post-radiochemotherapy PET radiomics in head and neck cancer - The influence of radiomics implementation on the reproducibility of local control tumor models. , 2017, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[28]  Daniel B. Mark,et al.  TUTORIAL IN BIOSTATISTICS MULTIVARIABLE PROGNOSTIC MODELS: ISSUES IN DEVELOPING MODELS, EVALUATING ASSUMPTIONS AND ADEQUACY, AND MEASURING AND REDUCING ERRORS , 1996 .

[29]  Daniel T Chang,et al.  Stereotactic radiotherapy for unresectable adenocarcinoma of the pancreas , 2009, Cancer.

[30]  Geoffrey G. Zhang,et al.  Combining radiomic features with a miRNA classifier may improve prediction of malignant pathology for pancreatic intraductal papillary mucinous neoplasms , 2016, Oncotarget.