Clinical Validation of a Pixon-Based Reconstruction Method Allowing a Twofold Reduction in Planar Images Time of 111In-Pentetreotide Somatostatin Receptor Scintigraphy

Objective The objective of this study was to evaluate the diagnostic efficacy of Pixon-based reconstruction method on planar somatostatin receptor scintigraphy (SRS). Methods All patients with neuroendocrine tumors (NETs) disease who were referred for SRS to our department during 1-year period from January to December 2015 were consecutively included. Three nuclear physicians independently reviewed all the data sets of images which included conventional images (CI; 15 min/view) and processed images (PI) obtained by reconstructing the first 450 s extracted data using Oncoflash® software package. Image analysis using a 3-point rating scale for abnormal uptake of 111 Indium-DTPA-Phe-octreotide in any lesion or organ was interpreted as positive, uncertain, or negative for the evidence of NET disease. A maximum grade uptake of the radiotracer in the lesion was assessed by the Krenning scale method. The results of image interpretation by the two methods were considered significantly discordant when the difference in organ involvement assessment was negative vs. positive or in lesion uptake was ≥2 grades. Agreement between the results of two methods and by different scan observers was evaluated using Cohen κ coefficients. Results There was no significant (p = 0.403) correlation between data acquisition protocol and quality image. The rates of significant discrepancies for exam interpretation and organs involvement assessment were 2.8 and 2.6%, respectively. Mean κ values revealed a good agreement for concordance between CI and PI interpretation without difference of agreement for inter/intra-observer analysis. Conclusion Our results suggest the feasibility to use a Pixon-based reconstruction method for SRS planar images allowing a twofold reduction of acquisition time and without significant alteration of image quality or on image interpretation.

[1]  M. Ruiz,et al.  Contribution of 111In-pentetreotide SPECT/CT imaging to conventional somatostatin receptor scintigraphy in the detection of neuroendocrine tumours , 2015, Nuclear medicine communications.

[2]  Lisa Lorimer,et al.  Improvement in DMSA imaging using adaptive noise reduction: an ROC analysis , 2012, Nuclear medicine communications.

[3]  Amos Yahil,et al.  Statistically based spatially adaptive noise reduction of planar nuclear studies , 2005, SPIE Medical Imaging.

[4]  A. Feinstein,et al.  High agreement but low kappa: I. The problems of two paradoxes. , 1990, Journal of clinical epidemiology.

[5]  A. Scarpa,et al.  TNM staging of midgut and hindgut (neuro) endocrine tumors: a consensus proposal including a grading system , 2007, Virchows Archiv.

[6]  I. Apostolova,et al.  SPECT/CT stabilizes the interpretation of somatostatin receptor scintigraphy findings: a retrospective analysis of inter-rater agreement , 2010, Annals of Nuclear Medicine.

[7]  Robert K. Pina,et al.  BAYESIAN IMAGE RECONSTRUCTION: THE PIXON AND OPTIMAL IMAGE MODELING , 1993 .

[8]  W. Verbeek,et al.  GEP-NETs UPDATE: Secreting gastro-enteropancreatic neuroendocrine tumours and biomarkers. , 2016, European journal of endocrinology.

[9]  E. Krenning,et al.  ENETS Consensus Guidelines for the Standards of Care in Neuroendocrine Tumors: Somatostatin Receptor Imaging with 111In-Pentetreotide , 2009, Neuroendocrinology.

[10]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[11]  E. Baudin Gastroenteropancreatic endocrine tumors: clinical characterization before therapy , 2007, Nature Clinical Practice Endocrinology &Metabolism.

[12]  E. Krenning,et al.  Treatment with the radiolabeled somatostatin analog [177 Lu-DOTA 0,Tyr3]octreotate: toxicity, efficacy, and survival. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[13]  Osama Mawlawi,et al.  Reduction in scan duration or injected dose in planar bone scintigraphy enabled by Pixon(R) post-processing , 2007 .

[14]  P. Babyn,et al.  Improved lesion detection from spatially adaptive, minimally complex, Pixon reconstruction of planar scintigraphic images. , 2005, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[15]  G. Arsos,et al.  Somatostatin receptor imaging with 111 In-pentetreotide intestinal tract in gastro- and lung neuroendocrine tumors-Impact on targeted treatment , 2010 .

[16]  T. R. Gosnell,et al.  Digital Image Reconstruction: Deblurring and Denoising , 2005 .

[17]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[18]  E. P. Krenning,et al.  Somatostatin receptor scintigraphy with [111In-DTPA-d-Phe1]- and [123I-Tyr3]-octreotide: the Rotterdam experience with more than 1000 patients , 1993, European Journal of Nuclear Medicine.

[19]  W. Cacheux,et al.  Thirteen-Month Registration of Patients with Gastroenteropancreatic Endocrine Tumours in France , 2008, Neuroendocrinology.

[20]  Jacob Cohen A Coefficient of Agreement for Nominal Scales , 1960 .

[21]  P. Grybäck,et al.  Reduced acquisition times in whole body bone scintigraphy using a noise-reducing Pixon®-algorithm—a qualitative evaluation study , 2015, EJNMMI Research.

[22]  E. Krenning,et al.  Somatostatin receptor imaging. , 2002, Seminars in nuclear medicine.

[23]  L. Mortelmans,et al.  111In-pentetreotide scintigraphy: procedure guidelines for tumour imaging , 2003, European journal of nuclear medicine and molecular imaging.

[24]  Peter A. Flach ROC Analysis , 2010, Encyclopedia of Machine Learning and Data Mining.

[25]  Xinhua Cao,et al.  Reduction in radiation dose in mercaptoacetyltriglycerine renography with enhanced planar processing. , 2011, Radiology.

[26]  Amos Yahil,et al.  The role of signal-to-noise ratio in preserving diagnostic performance and reader confidence level in count-reduced planar nuclear studies undergoing Pixon image processing , 2006 .

[27]  A. Sundin Radiological and nuclear medicine imaging of gastroenteropancreatic neuroendocrine tumours. , 2012, Best practice & research. Clinical gastroenterology.

[28]  E. Krenning,et al.  Neuroendocrine tumours: the role of imaging for diagnosis and therapy , 2014, Nature Reviews Endocrinology.

[29]  T. de Baère,et al.  Performance of (18)fluorodeoxyglucose-positron emission tomography and somatostatin receptor scintigraphy for high Ki67 (≥10%) well-differentiated endocrine carcinoma staging. , 2011, The Journal of clinical endocrinology and metabolism.

[30]  Manal M. Hassan,et al.  One hundred years after "carcinoid": epidemiology of and prognostic factors for neuroendocrine tumors in 35,825 cases in the United States. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[31]  I. Modlin,et al.  Current status of gastrointestinal carcinoids. , 2005, Gastroenterology.

[32]  S. Willich,et al.  Prognostic relevance of a novel TNM classification system for upper gastroenteropancreatic neuroendocrine tumors , 2008, Cancer.

[33]  E. Woltering,et al.  Cervical and upper mediastinal lymph node metastasis from gastrointestinal and pancreatic neuroendocrine tumors: true incidence and management. , 2012, Journal of the American College of Surgeons.

[34]  D. Klimstra,et al.  Classification of neuroendocrine neoplasms of the digestive system , 2019 .

[35]  B. Weinhold Epigenetics: The Science of Change , 2006, Virchows Archiv.