Optical Biopsy for Esophageal Squamous Cell Neoplasia by Using Endocytoscopy

Background Endocytoscopy (ECS) enables microscopic observation in vivo for the gastrointestinal mucosa; however, there has been no prospective study in which the diagnostic accuracy of ECS for lesions that have not yet undergone histological diagnosis was evaluated. We conducted a surveillance study for patients in a high-risk group of esophageal squamous cell carcinoma (ESCC) and evaluated the in vivo histological diagnostic accuracy of ECS. Methods This study was a multicenter prospective study. We enrolled 197 patients in the study between September 1, 2019 and November 30, 2020. The patients first underwent white light imaging and narrow band imaging, and ultra-high magnifying observation was performed if there was a lesion suspected to be an esophageal tumor. Endoscopic submucosal dissection (ESD) was later performed for lesions that were diagnosed to be ESCC by ECS without biopsy. We analyzed the diagnostic accuracy of ECS for esophageal tumorous lesions. Results ESD was performed for 37 patients (41 lesions) who were diagnosed as having ESCC by ECS, and all of them were histopathologically diagnosed as having ESCC. The sensitivity (95% confidence interval (CI)) was 97.6% (87.7%-99.7%), specificity was 100% (92.7%-100%), diagnostic accuracy was 98.9% (94.0%-99.8%), positive predictive value (PPV) was 100% (91.4%-100%) and negative predictive value (NPV) was 98.0% (89.5%-99.7%). Conclusions ECS has a high diagnostic accuracy and there were no false positives in cases diagnosed and resected as ESCC. Optical biopsy by using ECS for esophageal lesions is considered to be sufficient in clinical practice.

Is Computer-Assisted Tissue Image Analysis the Future in Minimally Invasive Surgery? A Review on the Current Status of Its Applications

Purpose: Computer-assisted tissue image analysis (CATIA) enables an optical biopsy of human tissue during minimally invasive surgery and endoscopy. Thus far, it has been implemented in gastrointestinal, endometrial, and dermatologic examinations that use computational analysis and image texture feature systems. We review and evaluate the impact of in vivo optical biopsies performed by tissue image analysis on the surgeon’s diagnostic ability and sampling precision and investigate how operation complications could be minimized. Methods: We performed a literature search in PubMed, IEEE, Xplore, Elsevier, and Google Scholar, which yielded 28 relevant articles. Our literature review summarizes the available data on CATIA of human tissues and explores the possibilities of computer-assisted early disease diagnoses, including cancer. Results: Hysteroscopic image texture analysis of the endometrium successfully distinguished benign from malignant conditions up to 91% of the time. In dermatologic studies, the accuracy of distinguishing nevi melanoma from benign disease fluctuated from 73% to 81%. Skin biopsies of basal cell carcinoma and melanoma exhibited an accuracy of 92.4%, sensitivity of 99.1%, and specificity of 93.3% and distinguished nonmelanoma and normal lesions from benign precancerous lesions with 91.9% and 82.8% accuracy, respectively. Gastrointestinal and endometrial examinations are still at the experimental phase. Conclusions: CATIA is a promising application for distinguishing normal from abnormal tissues during endoscopic procedures and minimally invasive surgeries. However, the efficacy of computer-assisted diagnostics in distinguishing benign from malignant states is still not well documented. Prospective and randomized studies are needed before CATIA is implemented in clinical practice.

698 Acute coronary syndrome in neoatherosclerosis with major stent malapposition and OCT-guided PCI

Aims Due to its bidimensional nature, angiography is not always sufficient to accurately define coronary lesions, in particular when they are ambiguous or indeterminate. Intracoronary imaging, such as intravascular ultrasound or optical coherence tomography (OCT), is often useful in these cases to better characterize the ambiguous angiographic images, to identify the culprit lesion during acute coronary syndrome (ACS) and to guide percutaneous coronary intervention (PCI). Methods and results We report a case of a 61-year-old male with multiple cardiovascular risk factors and a previous ST-segment elevation myocardial infarction treated by PCI of the right coronary artery (RCA) about 7 years before, wo was admitted to our emergency department after acute onset chest pain. At the time of admission, his ECG was normal and cardiac troponin was below the upper reference limit of normality with positive molecular SARS-CoV-2 diagnostic test. Echocardiogram disclosed a mild left ventricular dysfunction with inferior wall hypokinesia. Coronary angiography showed a moderate in-stent restenosis at mid RCA and a hazy, undetermined image at the proximal edge of the previously implanted stent. Left coronary artery angiography showed only diffuse atherosclerotic disease without significant stenoses and a myocardial bridge at the mid tract of left anterior descending artery. OCT pullback of RCA to better characterize the undetermined lesions shown by angiography. OCT revealed significant neointima hyperplasia and a focal area of neoatherosclerosis with unstable features (fissure/microthrombi) at mid RCA. Severe stent strut malapposition embedded neointimal hyperplasia was observed at the proximal stent edge, resulting in ‘dual’ lumen appearance. The two lesions were treated with a single 3.5/48 mm everolimus-eluting stent (stent-in-stent), which was post-dilated with a 3.5/20 mm non-compliant balloon (18 atm) in the mid-to-distal segments, and 4.5/15 mm (16 atm) and 5.0/8 mm (14 atm) semi-compliant balloons in the proximal stent segment. Post-PCI OCT imaging confirmed good stent expansion and apposition. Our case demonstrates the utility of OCT in clarifying the aetiology of ambiguous angiographic lesions and as a guide for PCI. Indeed, the ‘hazy’ appearance on the angiograms corresponded to the major stent malapposition covered by neointima disclosed by OCT as a ‘dual-lumen’. Of note, OCT allowed to confirm the correct guidewire position in the ‘true’ lumen preventing a crush of the previously implanted stent. OCT was also useful as a diagnostic modality for the identification and characterization of the mechanism underlying the ACS (neoatherosclerosis instability). Conclusions Due to its unprecedented spatial resolution, OCT enables an ‘optical biopsy’ of the coronary artery wall and intrastent tissue. Therefore, OCT imaging should be considered when lesions are ambiguous or indetermined by coronary angiography to guide the diagnosis and treatments of ACS patients. OCT imaging is also useful to guide stenting and to optimize PCI result, and its impact on clinical outcome is under investigation in large randomized clinical trials.

Proposal for a Skin Layer-Wise Decomposition Model of Spatially-Resolved Diffuse Reflectance Spectra Based on Maximum Depth Photon Distributions: A Numerical Study

In the context of cutaneous carcinoma diagnosis based on in vivo optical biopsy, Diffuse Reflectance (DR) spectra, acquired using a Spatially Resolved (SR) sensor configuration, can be analyzed to distinguish healthy from pathological tissues. The present contribution aims at studying the depth distribution of SR-DR-detected photons in skin from the perspective of analyzing how these photons contribute to acquired spectra carrying local physiological and morphological information. Simulations based on modified Cuda Monte Carlo Modeling of Light transport were performed on a five-layer human skin optical model with epidermal thickness, phototype and dermal blood content as variable parameters using (i) wavelength-resolved scattering and absorption properties and (ii) the geometrical configuration of a multi-optical fiber probe implemented on an SR-DR spectroscopic device currently used in clinics. Through histograms of the maximum probed depth and their exploitation, we provide numerical evidence linking the characteristic penetration depth of the detected photons to their wavelengths and four source–sensor distances, which made it possible to propose a decomposition of the DR signals related to skin layer contributions.