Pancreatic Adenocarcinoma Clinical Trial
Official title:
Computer-aided Diagnosis of Endoscopic Ultrasound Elastography Used in the Differentiation of Focal Pancreatic Masses
The aim of the study is to assess elastography during EUS examinations of focal pancreatic masses, and to consequently differentiate benign versus malignant pancreatic masses in a prospective multi-center design.
Ultrasound elastography is a recent ultrasound method used for the calculation of tissue
elasticity distribution in real-time. The method allows the reconstruction of tissue
elasticity (i.e. the elasticity modulus) and reveals directly the physical properties of the
tissue, consequently showing different tissue hardness patterns that are determined by
diseases. Tissue elastography can be easily performed real-time with conventional probes,
including the linear EUS probes used for the examination of the pancreas. The calculation of
tissue elasticity distribution is performed in real-time and the examination results are
represented as transparent overlay colour images overimposed on the conventional gray-scale
B-mode images.
Ultrasound elastography was previously used for the diagnosis of breast lesions, prostate
cancer and thyroid nodules. However, the value of endoscopic ultrasound elastography for the
diagnosis of pancreatic focal masses is not clear for the current moment, as some authors
couldn't differentiate benign and malignant pancreatic tumors. Moreover, the intense
fibrotic reaction and calcifications in chronic pancreatitis induce strain differences, and
it is not clear if elastography is sensitive enough to detect them.
The study protocol is based on a semi-quantitative approach of EUS elastography data
(movies) consisting of characterization of manually user-defined regions of interest, based
on the hue histograms of the individual focal masses. Due to the inherent bias induced by
selection of images from a dynamic sequence of EUS elastography, we have previously reported
on the utility of using computer-aided diagnosis by averaging images from a dynamic sequence
of EUS elastography. A special plugin (based on the ImageJ software, NIH, Bethesda, MD, USA)
is used to compute hue histograms on average EUS elastography images, while the hue
histograms values for each patient (0 to 255 values) are further used to classify the
patients with benign and malignant lesions.
Ultrasound elastography will be performed during an usual EUS examination (7.5 MHz
frequency), with two movies of 10 seconds recorded on the embedded HDD in order to minimize
variability and to increase repeatability of acquisition. A two panel image with the usual
conventional gray-scale B-mode EUS image on the right side and with the elastography image
on the left side will be used. The region of interest will be preferably larger than the
focal mass, in order to include the surrounding structures. In order to minimize the human
bias, all the post-processing and computer analysis of digital movies will be performed
within the IT Center in Craiova, with all programmers and statisticians being blinded to the
clinical, pathological and imaging data, with the exception of the average hue histogram
values calculated from a second region of interest manually traced around the focal mass.
The study design is prospective, blinded and multi-center, comparing endoscopic ultrasound
elastography (EUS-EG) results for the detection and characterization of focal pancreatic
masses by using artificial intelligence techniques, in comparison with the gold standard
represented by pathology. The study will be performed with the approval of the institutional
board review of each center.
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Observational Model: Case Control, Time Perspective: Prospective
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