Role of artificial intelligence in the diagnosis of oesophageal neoplasia: 2020 an endoscopic odyssey

The past decade has seen significant advances in endoscopic imaging and optical enhancements to aid early diagnosis. There is still a treatment gap due to the underdiagnosis of lesions of the oesophagus. Computer aided diagnosis may play an important role in the coming years in providing an adjunct to endoscopists in the early detection and diagnosis of early oesophageal cancers, therefore curative endoscopic therapy can be offered. Research in this area of artificial intelligence is expanding and the future looks promising. In this review article we will review current advances in artificial intelligence in the oesophagus and future directions for development

Laser Based Mid-Infrared Spectroscopic Imaging – Exploring a Novel Method for Application in Cancer Diagnosis

A number of biomedical studies have shown that mid-infrared spectroscopic images can provide both morphological and biochemical information that can be used for the diagnosis of cancer. Whilst this technique has shown great potential it has yet to be employed by the medical profession. By replacing the conventional broadband thermal source employed in modern FTIR spectrometers with high-brightness, broadly tuneable laser based sources (QCLs and OPGs) we aim to solve one of the main obstacles to the transfer of this technology to the medical arena; namely poor signal to noise ratios at high spatial resolutions and short image acquisition times. In this thesis we take the first steps towards developing the optimum experimental configuration, the data processing algorithms and the spectroscopic image contrast and enhancement methods needed to utilise these high intensity laser based sources. We show that a QCL system is better suited to providing numerical absorbance values (biochemical information) than an OPG system primarily due to the QCL pulse stability. We also discuss practical protocols for the application of spectroscopic imaging to cancer diagnosis and present our spectroscopic imaging results from our laser based spectroscopic imaging experiments of oesophageal cancer tissue

Identifying Intestinal Metaplasia at the Squamocolumnar Junction by Using Optical Coherence Tomography

Background: Optical coherence tomography (OCT) is an optical imaging method that produces high-resolution cross-sectional images of the esophagus. The accuracy of OCT for differentiating tissue types at the squamocolumnar junction (SCJ) has not been established. Objective: The purpose of this study was to identify and validate OCT image criteria for distinguishing metaplastic from nonmetaplastic tissue at the SCJ. Design: A total of 196 biopsy-correlated OCT images of the SCJ were acquired from 113 patients undergoing upper endoscopy. A pathologist blinded to the OCT results reviewed each pathology specimen and determined the presence of the following histopathology: gastric cardia, squamous mucosa, pancreatic metaplasia, and intestinal metaplasia. An algorithm for diagnosing specialized intestinal metaplasia (SIM) was created by reviewing a training set of 40 biopsy-correlated OCT images. Two blinded investigators prospectively tested the algorithm on a validation set of 123 images. Results: OCT images of squamous mucosa were characterized by a layered appearance without epithelial glands; gastric cardia, by vertical pit and gland structure, a well-defined epithelial surface reflectivity, and relatively poor image penetration; and SIM by an irregular architecture and good image penetration. The OCT criteria were 85% sensitive and 95% specific for SIM when applied retrospectively to the training set. When applied to the validation set, the algorithm was 81% sensitive for both OCT readers and 66% and 57% specific for diagnosing SIM. The interobserver agreement was good (κ = 0.53). Conclusions: OCT imaging can identify SIM at the SCJ with an accuracy similar to that of endoscopy

Developments in molecular and advanced endoscopic imaging in esophageal cancer

Esophageal cancer, including esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC), shows high incidence and poor prognosis. The early detection and endoscopic treatment of (pre)malignant lesions of esophageal cancer significantly improve disease outcomes of patients. However, the high-definition white-light endoscopy followed by random biopsy is reported with a non-ignorable miss rate. The development of advanced endoscopic techniques, such as fluorescence molecular endoscopy (FME) and endocytoscopy, can aid endoscopists in diagnosing early (pre)malignant lesions in vivo. FME realizes wide-field molecular imaging under endoscopy, which serves as a red flag technique for endoscopists by fluorescently highlighting the disease-specific molecule. In Chapter 3 and 4, we identified suitable target proteins and developed near-infrared fluorescent tracers for FME to detect ESCC and EAC at an early stage. In Chapter 6, we investigated the feasibility of assessing pathological response of EAC patients after neoadjuvant chemoradiotherapy by Bevacizumab-800CW guided FME.Endocytoscopy is a pin-point imaging technique that provides endoscopists with magnified optical cellular morphology and subcellular characteristics, referred to as an optical biopsy. In Chapter 5, we developed a classification criteria, an online training module for clinicians and a computer-aided diagnosis (CAD) algorithm based on in vivo images of fourth-generation endocytoscopy to distinguish dysplastic from non-dysplastic Barrett's esophagus tissue. We further investigated the interaction of this CAD algorithm with the clinicians

Gene expression changes associated with Barrett's esophagus and Barrett's-associated adenocarcinoma cell lines after acid or bile salt exposure

<p>Abstract</p> <p>Background</p> <p>Esophageal reflux and Barrett's esophagus represent two major risk factors for the development of esophageal adenocarcinoma. Previous studies have shown that brief exposure of the Barrett's-associated adenocarcinoma cell line, SEG-1, or primary cultures of Barrett's esophageal tissues to acid or bile results in changes consistent with cell proliferation. In this study, we determined whether similar exposure to acid or bile salts results in gene expression changes that provide insights into malignant transformation.</p> <p>Methods</p> <p>Using previously published methods, Barrett's-associated esophageal adenocarcinoma cell lines and primary cultures of Barrett's esophageal tissue were exposed to short pulses of acid or bile salts followed by incubation in culture media at pH 7.4. A genome-wide assessment of gene expression was then determined for the samples using cDNA microarrays. Subsequent analysis evaluated for statistical differences in gene expression with and without treatment.</p> <p>Results</p> <p>The SEG-1 cell line showed changes in gene expression that was dependent on the length of exposure to pH 3.5. Further analysis using the Gene Ontology, however, showed that representation by genes associated with cell proliferation is not enhanced by acid exposure. The changes in gene expression also did not involve genes known to be differentially expressed in esophageal adenocarcinoma. Similar experiments using short-term primary cultures of Barrett's esophagus also did not result in detectable changes in gene expression with either acid or bile salt exposure.</p> <p>Conclusion</p> <p>Short-term exposure of esophageal adenocarcinoma SEG-1 cells or primary cultures of Barrett's esophagus does not result in gene expression changes that are consistent with enhanced cell proliferation. Thus other model systems are needed that may reflect the impact of acid and bile salt exposure on the esophagus <it>in vivo</it>.</p

A new artificial intelligence system successfully detects and localises early neoplasia in Barrett's esophagus by using convolutional neural networks

BACKGROUND AND AIMS: Seattle protocol biopsies for Barrett's Esophagus (BE) surveillance are labour intensive with low compliance. Dysplasia detection rates vary, leading to missed lesions. This can potentially be offset with computer aided detection. We have developed convolutional neural networks (CNNs) to identify areas of dysplasia and where to target biopsy. METHODS: 119 Videos were collected in high-definition white light and optical chromoendoscopy with i-scan (Pentax Hoya, Japan) imaging in patients with dysplastic and non-dysplastic BE (NDBE). We trained an indirectly supervised CNN to classify images as dysplastic/non-dysplastic using whole video annotations to minimise selection bias and maximise accuracy. The CNN was trained using 148,936 video frames (31 dysplastic patients, 31 NDBE, two normal esophagus), validated on 25,161 images from 11 patient videos and tested on 264 iscan-1 images from 28 dysplastic and 16 NDBE patients which included expert delineations. To localise targeted biopsies/delineations, a second directly supervised CNN was generated based on expert delineations of 94 dysplastic images from 30 patients. This was tested on 86 i-scan one images from 28 dysplastic patients. FINDINGS: The indirectly supervised CNN achieved a per image sensitivity in the test set of 91%, specificity 79%, area under receiver operator curve of 93% to detect dysplasia. Per-lesion sensitivity was 100%. Mean assessment speed was 48 frames per second (fps). 97% of targeted biopsy predictions matched expert and histological assessment at 56 fps. The artificial intelligence system performed better than six endoscopists. INTERPRETATION: Our CNNs classify and localise dysplastic Barrett's Esophagus potentially supporting endoscopists during surveillance

Cell proliferation, cell cycle abnormalities, and cancer outcome in patients with Barrett’s esophagus: A long-term prospective study

Purpose: Elevated cellular proliferation and cell cycle abnormalities, which have been associated with premalignant lesions, may be caused by inactivation of tumor suppressor genes. We measured proliferative and cell cycle fractions of biopsies from a cohort of patients with Barrett's esophagus to better understand the role of proliferation in early neoplastic progression and the association between cell cycle dysregulation and tumor suppressor gene inactivation. Experimental Design: Cell proliferative fractions (determined by Ki67/DNA multiparameter flow cytometry) and cell cycle fractions (DNA content flow cytometry) were measured in 853 diploid biopsies from 362 patients with Barrett's esophagus. The inactivation status of CDKN2A and TP53 was assessed in a subset of these biopsies in a cross-sectional study. A prospective study followed 276 of the patients without detectable aneuploidy for an average of 6.3 years with esophageal adenocarcinoma as an endpoint. Results: Diploid S and 4N (G2/tetraploid) fractions were significantly higher in biopsies with TP53 mutation and LOH. CDKN2A inactivation was not associated with higher Ki67-positive, diploid S, G1, or 4N fractions. High Ki67-positive and G1 phase fractions were not associated with the future development of esophageal adenocarcinoma (p=0.13 and p=0.15, respectively), while high diploid S phase and 4N fractions were (p=0.03 and p<0.0001, respectively). Conclusions: High Ki67-positive proliferative fractions were not associated with inactivation of CDKN2A and TP53 or future development of cancer in our cohort of patients with Barrett's esophagus. Bi-allelic inactivation of TP53 was associated with elevated 4N fractions, which have been associated with the future development of esophageal adenocarcinoma

Modular SIMD arithmetic in Mathemagix

Modular integer arithmetic occurs in many algorithms for computer algebra, cryptography, and error correcting codes. Although recent microprocessors typically offer a wide range of highly optimized arithmetic functions, modular integer operations still require dedicated implementations. In this article, we survey existing algorithms for modular integer arithmetic, and present detailed vectorized counterparts. We also present several applications, such as fast modular Fourier transforms and multiplication of integer polynomials and matrices. The vectorized algorithms have been implemented in C++ inside the free computer algebra and analysis system Mathemagix. The performance of our implementation is illustrated by various benchmarks

Barrett\u27s esophagus as a premalignant condition; medical and surgical therapeutic management

Barrett\u27s esophagus (BE) represents a special clinical entity, which may have reduced symptoms, but an increased potential for malignant degeneration. The factors that lead to the appearance of Barrett\u27s esophagus are multiple, the most important being gastro-esophageal reflux, as well as smoking and obesity. BE occurs as a result of damage of the esophageal mucosa, caused by acid/basic gastroesophageal reflux and resulting in the transformation of the epithelium from squamous to intestinal type. The diagnosis of BE is primarily based on endoscopic examination. This method has not only a diagnostic role, but also a therapeutic one through the minimally invasive resection of the mucosa with suspicious dysplastic lesions, thus reducing the risk of esophageal adenocarcinoma. Conservative therapeutic methods by administering chemoprotective agents (proton pump inhibitors, statins, etc.) are also useful. Surgical treatment of Barrett\u27s esophagus aims to both resect areas of high-grade esophageal dysplasia/adenocarcinoma and reduce the degree of gastroesophageal reflux through various surgical procedures. As a conclusion, the potential for malignant degeneration of BE should not be neglected, the form of treatment largely depending on the patient\u27s age and comorbidities