Tumor heterogeneity of pancreas head cancer assessed by CT texture analysis: association with survival outcomes after curative resection

The value of image based texture features as a powerful method to predict prognosis and assist clinical management in cancer patients has been established recently. However, texture analysis using histograms and grey-level co-occurrence matrix in pancreas cancer patients has rarely been reported. We aimed to analyze the association of survival outcomes with texture features in pancreas head cancer patients. Eighty-eight pancreas head cancer patients who underwent preoperative CT images followed by curative resection were included. Texture features using different filter values were obtained. The texture features of average, contrast, correlation, and standard deviation with no filter, and fine to medium filter values as well as the presence of nodal metastasis were significantly different between the recurred (n = 70, 79.5%) and non-recurred group (n = 18, 20.5%). In the multivariate Cox regression analysis, lower standard deviation and contrast and higher correlation with lower average value representing homogenous texture were significantly associated with poorer DFS (disease free survival), along with the presence of lymph node metastasis. Texture parameters from routinely performed pre-operative CT images could be used as an independent imaging tool for predicting the prognosis in pancreas head cancer patients who underwent curative resection.

[1]  H. Pitt,et al.  Potentially resectable pancreatic adenocarcinoma: spiral CT assessment with surgical and pathologic correlation. , 1995, Radiology.

[2]  Bal Sanghera,et al.  Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice? , 2012, Insights into Imaging.

[3]  Alejandro Munoz del Rio,et al.  CT textural analysis of hepatic metastatic colorectal cancer: pre-treatment tumor heterogeneity correlates with pathology and clinical outcomes , 2015, Abdominal Imaging.

[4]  P. Mueller,et al.  Pancreatic-phase versus portal vein-phase helical CT of the pancreas: optimal temporal window for evaluation of pancreatic adenocarcinoma. , 1999, AJR. American journal of roentgenology.

[5]  H. Kocher,et al.  Pancreatic Cancer , 2019, Methods in Molecular Biology.

[6]  O. Matsui,et al.  Enhancement patterns of pancreatic adenocarcinoma on conventional dynamic multi-detector row CT: correlation with angiogenesis and fibrosis. , 2009, World journal of gastroenterology.

[7]  K. Blouhos,et al.  Surgically proved visually isoattenuating pancreatic adenocarcinoma undetected in both dynamic CT and MRI. Was blind pancreaticoduodenectomy justified? , 2013, International journal of surgery case reports.

[8]  D. Lu,et al.  Two-phase helical CT for pancreatic tumors: pancreatic versus hepatic phase enhancement of tumor, pancreas, and vascular structures. , 1996, Radiology.

[9]  V. Goh,et al.  Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival. , 2013, Radiology.

[10]  Corbin E. Meacham,et al.  Tumour heterogeneity and cancer cell plasticity , 2013, Nature.

[11]  Takeo Ishigaki,et al.  Pancreatic ductal adenocarcinoma showing iso-attenuation in early-phase contrast-enhanced CT: comparison with histopathological findings. , 2002, Radiation medicine.

[12]  J. Trent,et al.  Frequency of potential therapeutic targets identified by immunohistochemistry (IHC) and DNA microarray (DMA) in tumors from patients who have progressed on multiple therapeutic agents. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[13]  Yi Wang,et al.  Diffusion‐weighted magnetic resonance imaging of pancreatic adenocarcinomas: Association with histopathology and tumor grade , 2011, Journal of magnetic resonance imaging : JMRI.

[14]  Bohyoung Kim,et al.  Tumor Heterogeneity in Human Epidermal Growth Factor Receptor 2 (HER2)-Positive Advanced Gastric Cancer Assessed by CT Texture Analysis: Association with Survival after Trastuzumab Treatment , 2016, PloS one.

[15]  W. Knight,et al.  Primary linitis plastica of the colon. Report of two cases and review of the literature , 1978, Cancer.

[16]  T. Karrison,et al.  Histologic features associated with long-term survival in breast cancer. , 1986, Human pathology.

[17]  L. Way,et al.  Prognostic indicators for survival after resection of pancreatic adenocarcinoma. , 1993, American journal of surgery.

[18]  M. Kochman,et al.  Primary linitis plastica of the colon. , 1993, Gastrointestinal endoscopy.

[19]  Jeffrey E. Lee,et al.  Serum CA 19-9 as a Marker of Resectability and Survival in Patients with Potentially Resectable Pancreatic Cancer Treated with Neoadjuvant Chemoradiation , 2010, Annals of Surgical Oncology.

[20]  C. Hsueh,et al.  Neoadjuvant treatment for resectable pancreatic adenocarcinoma. , 2016, World journal of clinical oncology.

[21]  K. Miles,et al.  Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival , 2012, European Radiology.

[22]  R. Jeffrey,et al.  Preoperative Multidetector CT Diagnosis of Extrapancreatic Perineural or Duodenal Invasion Is Associated with Reduced Postoperative Survival after Pancreaticoduodenectomy for Pancreatic Adenocarcinoma: Preliminary Experience and Implications for Patient Care. , 2016, Radiology.

[23]  O. Matsui,et al.  Histological influence on contrast-enhanced CT of pancreatic ductal adenocarcinoma. , 1997, Journal of computer assisted tomography.

[24]  P. Frederick,et al.  Primary linitis plastica of the colon , 1967, Diseases of the colon and rectum.

[25]  Michael E Griswold,et al.  Locally advanced squamous cell carcinoma of the head and neck: CT texture and histogram analysis allow independent prediction of overall survival in patients treated with induction chemotherapy. , 2013, Radiology.

[26]  Murray F. Brennan,et al.  Prognostic Nomogram for Patients Undergoing Resection for Adenocarcinoma of the Pancreas , 2004, Annals of surgery.

[27]  G. Aranha,et al.  Gastric linitis plastica is not a surgical disease. , 1989, Surgery.

[28]  T. Ichikawa.  [A comparative study of histopathological findings and CT images related to pancreatic carcinomas. An attempt at diagnosis in tissue characterization by CT]. , 1992, Nihon Ika Daigaku zasshi.

[29]  V. Goh,et al.  Primary esophageal cancer: heterogeneity as potential prognostic biomarker in patients treated with definitive chemotherapy and radiation therapy. , 2013, Radiology.

[30]  Robert King,et al.  Textural features corresponding to textural properties , 1989, IEEE Trans. Syst. Man Cybern..

[31]  Helmut Friess,et al.  Cancer-stellate cell interactions perpetuate the hypoxia-fibrosis cycle in pancreatic ductal adenocarcinoma. , 2009, Neoplasia.

[32]  Balaji Ganeshan,et al.  Quantifying tumour heterogeneity with CT , 2013, Cancer imaging : the official publication of the International Cancer Imaging Society.

[33]  Michael A. Choti,et al.  1423 pancreaticoduodenectomies for pancreatic cancer: A single-institution experience , 2006, Journal of Gastrointestinal Surgery.

[34]  H. Uematsu,et al.  Apparent diffusion coefficient in pancreatic cancer: Characterization and histopathological correlations , 2008, Journal of magnetic resonance imaging : JMRI.

[35]  Vicky Goh,et al.  Assessment of tumor heterogeneity by CT texture analysis: can the largest cross-sectional area be used as an alternative to whole tumor analysis? , 2013, European journal of radiology.

[36]  Hongmin Cai,et al.  Quantitative analysis and prediction of regional lymph node status in rectal cancer based on computed tomography imaging , 2011, European Radiology.

[37]  Caroline Reinhold,et al.  Resectable pancreatic adenocarcinoma: Role of CT quantitative imaging biomarkers for predicting pathology and patient outcomes. , 2017, European journal of radiology.

[38]  P. Evans,et al.  Clinical applications of textural analysis in non-small cell lung cancer. , 2018, The British journal of radiology.

[39]  Hideo Baba,et al.  Epithelial–mesenchymal transition in cancer development and its clinical significance , 2010, Cancer science.

[40]  Balaji Ganeshan,et al.  Colorectal cancer: texture analysis of portal phase hepatic CT images as a potential marker of survival. , 2009, Radiology.

[41]  Jae Young Lee,et al.  Small (≤ 20 mm) pancreatic adenocarcinomas: analysis of enhancement patterns and secondary signs with multiphasic multidetector CT. , 2011, Radiology.

[42]  Li Xin-xiao,et al.  Prognostic Indicators for Survival after Resection of Pancreatic Adenocarcinoma , 2007 .

[43]  C. Earle,et al.  Prognostic Factors Following Curative Resection for Pancreatic Adenocarcinoma: A Population-Based, Linked Database Analysis of 396 Patients , 2003, Annals of surgery.

[44]  K. Lillemoe,et al.  Pancreatic Ductal Adenocarcinoma: Is There a Survival Difference for R1 Resections Versus Locally Advanced Unresectable Tumors? What Is a “True” R0 Resection? , 2013, Annals of surgery.

[45]  Joel G Fletcher,et al.  Pancreatic malignancy: value of arterial, pancreatic, and hepatic phase imaging with multi-detector row CT. , 2003, Radiology.

[46]  Daniele Marchioni,et al.  A Single-Institution Experience , 2013 .

[47]  K. Takeshita,et al.  Imaging of early pancreatic cancer on multidetector row helical computed tomography. , 2010, The British journal of radiology.

[48]  M. Farnell,et al.  Carbohydrate Antigen 19-9 Elevation in Anatomically Resectable, Early Stage Pancreatic Cancer Is Independently Associated with Decreased Overall Survival and an Indication for Neoadjuvant Therapy: A National Cancer Database Study. , 2016, Journal of the American College of Surgeons.

[49]  A. El Nakeeb,et al.  Prognostic factors affecting survival after pancreaticoduodenectomy for pancreatic adenocarcinoma (single center experience). , 2014, Hepato-gastroenterology.

[50]  R. Hill,et al.  The tumor microenvironment and metastatic disease , 2008, Clinical & Experimental Metastasis.

[51]  V. Goh,et al.  Imaging Heterogeneity in Lung Cancer: Techniques, Applications, and Challenges. , 2016, AJR. American journal of roentgenology.

[52]  Q. Ma,et al.  Targeting the cancer-stroma interaction: a potential approach for pancreatic cancer treatment. , 2012, Current pharmaceutical design.

[53]  A. Larson,et al.  Apparent Diffusion Coefficient and Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Pancreatic Cancer: Characteristics and Correlation With Histopathologic Parameters , 2016, Journal of computer assisted tomography.

[54]  Chris R Chatwin,et al.  Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver. , 2009, European journal of radiology.

[55]  R. Moesinger,et al.  Predicting Unresectability in Pancreatic Cancer Patients: The Additive Effects of CT and Endoscopic Ultrasound , 2007, Journal of Gastrointestinal Surgery.

[56]  H. Friess,et al.  Curative resection is the single most important factor determining outcome in patients with pancreatic adenocarcinoma , 2004, The British journal of surgery.

[57]  V. Goh,et al.  Non-small cell lung cancer: histopathologic correlates for texture parameters at CT. , 2013, Radiology.

[58]  K. Miles,et al.  Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: preliminary evidence of an association with tumour metabolism, stage, and survival. , 2012, Clinical radiology.

[59]  Eun Sook Ko,et al.  Breast cancer heterogeneity: MR Imaging Texture Analysis and Survival Outcomes1 , 2016 .

[60]  K. Mallika,et al.  Co-Occurrence Matrix and Its StatisticalFeatures as an Approach for Identification OfPhase Transitions Of Mesogens , 2013 .

[61]  C. Verbeke,et al.  Morphological heterogeneity in ductal adenocarcinoma of the pancreas - Does it matter? , 2016, Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.].