Gold Standard Histopathology Research Articles

In Vivo Imaging-Based Techniques for Early Diagnosis of Oral Potentially Malignant Disorders-Systematic Review and Meta-Analysis.

Objectives: Oral potentially malignant disorders (OPMDs) are lesions that may undergo malignant transformation to oral cancer. The early diagnosis and surveillance of OPMDs reduce the morbidity and mortality of patients. Diagnostic techniques based on medical images analysis have been developed to diagnose clinical conditions. This systematic review and meta-analysis aimed to evaluate the efficacy of imaging-based techniques compared to the gold standard of histopathology to assess their ability to correctly identify the presence of OPMDs. Design: Literature searches of free text and MeSH terms were performed using MedLine (PubMed), Scopus, Google Scholar, and the Cochrane Library (from 2000 to 30 June 2020). The keywords used in the search strategy were: (“oral screening devices” or “autofluorescence” or “chemiluminescence” or “optical imaging” or “imaging technique”) and (“oral dysplasia” or “oral malignant lesions” or “oral precancerosis”). Results: The search strategy identified 1282 potential articles. After analyzing the results and applying the eligibility criteria, the remaining 43 papers were included in the qualitative synthesis, and 34 of these were included in the meta-analysis. Conclusions: None of the analyzed techniques based on assessing oral images can replace the biopsy. Further studies are needed to explore the role of techniques-based imaging analysis to identify an early noninvasive screening method.

European Association of Nuclear Medicine October 20-23, 2021 Virtual.

Aim/Introduction: Over the last decades, the use of 18F-FDG has taken a pivotal role in oncological diagnosis, staging and follow-up. While endless research has shown the clinical importance of 18F-FDG, we remain unaware how 18F-FDG behaves in and around human malignancies on a submillimetric scale. Unfortunately, as glucose metabolism is an active process, pathological assessment of relevant protein markers was found to be inadequate in correctly predicting 18F-FDG-uptake. Technological improvements are resulting in increasing spatial resolution for PET-scanners, therefore an urgent understanding of 18F-FDG-distribution on these higher resolutions is required. Materials and Methods: In the current study, we developed a methodology that enabled direct coregistration of the radioactivity-distribution in a surgically resected specimen with histopathological assessment. Patients were injected with 4 MBq/kg of 18F-FDG prior to the initiation of standard of care surgical oncological resection. After resection of the malignancy, the surgical specimen was imaged using preclinical micro-PET and -CT devices with a spatial resolution of 800µm and 50µm, respectively. After imaging, the specimen was freshly sliced into thin slices of approximately 2mm by a pathologist. One slice was snap-frozen and frozen sections were imaged using an autoradiographic flm overnight. Following the imaging, frozen sections were stained with standard hematoxylin and eosin staining. Pathological results were overlayed with the results of 18F-FDG PET/CT and autoradiography to coregister the histopathological and imaging results. Results: We performed this methodology on a total of four patients with cutaneous squamous cell carcinoma (n=2), angiosarcoma (n=1) and thyroid medullary carcinoma (n=1). While the mean time between injection and autoradiography was 3h49, we were able to image sufcient radioactivity to directly coregister the results with the clinical pathological frozen sections. All regions with identifed malignant tissue displayed increased 18F-FDG-uptake. However, uptake was not limited to these regions, as a similar increased uptake was identifed in adjacent benign sebaceous glands. Interestingly, we also identifed a heterogeneous 18F-FDGuptake in separate clusters of malignant tissue, which could partly be explained by the cluster’s amount of peritumoral infammatory cells. Conclusion: To the best of our knowledge, these results are the frst to describe direct coregistration of 18F-FDG with the gold standard of histopathology in any human malignancy. These heterogeneous results display an important diversity in metabolic activity between diferent tumor and peritumoral tissues. The use of this methodology could increase our understanding of radiotracer distribution in human diseases on a previously unprecedented scale in clinical nuclear medicine.

Corrigendum

Veterinary Clinical PathologyVolume 50, Issue 3 p. 469-469 CORRIGENDUMFree Access Corrigendum This article corrects the following: Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios in dogs and cats with acute pancreatitis Stephan Neumann, Volume 50Issue 1Veterinary Clinical Pathology pages: 45-51 First Published online: March 23, 2021 First published: 29 September 2021 https://doi.org/10.1111/vcp.13071AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat In Neumann,1 page 50, the statement “The sensitivity and specificity of DGGR lipase in cats with pancreatitis were reported as 48% and 63%, respectively.” has an incorrect citation. The citation should be “Agreement of the Serum Spec fPL and 1,2-O-Dilauryl-Rac-Glycero-3-Glutaric Acid-(6′-Methylresorufin) Ester Lipase Assay for the Determination of Serum Lipase in Cats with Suspicion of Pancreatitis.2 Also, on page 47, the statement, “The cPLI results were consistent with pancreatitis in all cases, and DGGR lipase exceeded the upper reference limit (108 U/L) in all cases (DGGR lipase ranged from 144 up to 2447 U/L, with a median value [MV] of 420 U/L; Figure 1).” The reference ranges for the DGGR from Konelab 20i; Thermo Fischer Scientific Inc, were based on the manufacturer’s recommendations in accordance with two publications; “Agreement of Serum Spec cPL with the 1,2-o-Dilauryl-Rac-Glycero Glutaric Acid-(6′-methylresorufin) Ester (DGGR) Lipase Assay and with Pancreatic Ultrasonography in Dogs with Suspected Pancreatitis,”3 and “1,2-O-Dilauryl-Rac-Glycero-3-Glutaric Acid-(6′-Methylresorufin) Ester Lipase Assay for the Determination of Serum Lipase in Cats with Suspicion of Pancreatitis.”4 We would like to point out that the results of different colorimetric lipase assays were used in our study versus these studies, so it is possible the reference intervals would not be identical, (even when DGGR is used as a substrate). Finally, we also neglected to reference an article evaluating Spec fPL and DGGR-lipase (LipC Roche) versus a detailed gold standard (histopathology) in cats; for further reading the article is: “Comparison of Serum Spec fPL and 1,2-o-Dilauryl-Rac-Glycero-3-Glutaric Acid-(6′-Methylresorufin) Ester Assay in 60 Cats Using Standardized Assessment of Pancreatic Histology.”5 REFERENCES 1Neumann S. Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios in dogs and cats with acute pancreatitis. Vet Clin Pathol. 2021; 50: 45– 51. 10.1111/vcp.12979Wiley Online LibraryPubMedWeb of Science®Google Scholar 2Oppliger S, Hartnack S, Riond B, Reusch C, Kook P. Agreement of the serum spec fPL™ and 1,2-O-dilauryl-rac-glycero-3-glutaric acid-(6′-methylresorufin) ester lipase assay for the determination of serum lipase in cats with suspicion of pancreatitis. 2. J Vet Intern Med. 2013; 27: 1077– 1082. 10.1111/jvim.12150Wiley Online LibraryCASPubMedWeb of Science®Google Scholar 3Kook P, Kohler N, Hartnack S, Riond B, Reusch C. Agreement of serum spec cPL with the 1,2-o-dilauryl-rac-glycero glutaric acid-(6′-methylresorufin) Ester (DGGR) lipase assay and with pancreatic ultrasonography in dogs with suspected pancreatitis. J Vet Intern Med. 2014; 28: 863– 870. 10.1111/jvim.12334Wiley Online LibraryCASPubMedWeb of Science®Google Scholar 4Oppliger S, Hartnack S, Riond B, Reusch C, Kook P. Agreement of the serum spec fPL™ and 1,2-O-dilauryl-rac-glycero-3-glutaric acid-(6′-methylresorufin) ester lipase assay for the determination of serum lipase in cats with suspicion of pancreatitis. J Vet Intern Med. 2013; 27: 1077– 1082. 10.1111/jvim.12150Wiley Online LibraryCASPubMedWeb of Science®Google Scholar 5Oppliger S, Hilbe M, Hartnack S, Zini E, Reusch C, Kook P. Comparison of serum spec fPL™ and 1,2-o-dilauryl-rac-glycero-3-glutaric acid-(6′-methylresorufin) ester assay in 60 cats using standardized assessment of pancreatic histology. J Vet Intern Med. 2016; 30: 764– 770. 10.1111/jvim.13924Wiley Online LibraryCASPubMedWeb of Science®Google Scholar Volume50, Issue3September 2021Pages 469-469 ReferencesRelatedInformation

Unified magnifying endoscopic classification for esophageal, gastric and colonic lesions: a feasibility pilot study.

Background and study aims Image-enhanced magnifying endoscopy allows optimization of the detection and diagnosis of lesions found in the gastrointestinal tract. Current organ-specific classifications are well-accepted by specialized endoscopists but may pose confusion for general gastroenterologists. To address this, our group proposed the Unified Magnifying Endoscopic Classification (UMEC) which can be applied either in esophagus, stomach, or colon. The aim of this study was to evaluate the diagnostic performance and clinical applicability of UMEC. Patients and methods A single-center, feasibility pilot study was conducted. Two endoscopists with experience in magnifying narrow band imaging (NBI), blinded to white-light and non-magnifying NBI findings as well as histopathological diagnosis, independently reviewed and diagnosed all images based on UMEC. In brief, UMEC is divided into three categories: non-neoplasia, intramucosal neoplasia, and deep submucosal invasive cancer. The diagnostic performance of UMEC was assessed while using the gold standard histopathology as a reference. Results A total of 303 gastrointestinal lesions (88 esophageal squamous lesions, 90 gastric lesions, 125 colonic lesions) were assessed. The overall accuracy for both endoscopists in the diagnosis of esophageal squamous cell cancer, gastric cancer, and colorectal cancer were 84.7 %, 89.5 %, and 83.2 %, respectively. The interobserver agreement for each organ, Kappa statistics of 0.51, 0.73, and 0.63, was good. Conclusions UMEC appears to be a simple and practically acceptable classification, particularly to general gastroenterologists, due to its good diagnostic accuracy, and deserves further evaluation in future studies.

Feasibility and Implementation of Ex Vivo Fluorescence Confocal Microscopy for Diagnosis of Oral Leukoplakia: Preliminary Study

Background: Oral leukoplakia is a potentially malignant lesion with a clinical impression similar to different benign and malignant lesions. Ex vivo fluorescence confocal microscopy is a developing approach for a rapid “chairside” detection of oral lesions with a cellular-level resolution. A possible application of interest is a quick differentiation of benign oral pathology from normal or cancerous tissue. The aim of this study was to analyze the sensitivity and specificity of ex vivo fluorescence confocal microscopy (FCM) for detecting oral leukoplakia and to compare confocal images with gold-standard histopathology. Methods: Imaging of 106 submosaics of 27 oral lesions was performed using an ex vivo fluorescence confocal microscope immediately after excision. Every confocal image was qualitatively assessed for presence or absence of leukoplakia by an expert reader of confocal images. The results were compared to conventional histopathology with H&E staining. Results: Leukoplakia was detected with an overall sensitivity of 96.3%, specificity of 92.3%, positive predictive value of 93%, and negative predictive value of 96%. Conclusion: The results demonstrate the potential of ex vivo confocal microscopy in fresh tissue for rapid real-time assessment of oral pathologies.

Comparison between fine-needle aspiration cytology and histopathology in leprosy: A cross-sectional study

Objectives: The objectives of the study were (1) to study the fine-needle aspiration cytology (FNAC) features of skin lesions of leprosy, (2) to determine the agreement between FNAC and histopathology to classify leprosy into different groups of the spectrum, and (3) to determine the sensitivity and specificity of FNAC to classify leprosy into different groups of the spectrum against the gold standard of histopathology. Materials and Methods: All newly diagnosed cases of leprosy who attended the outpatient department of dermatology and venereology of a tertiary referral center during the 16 months study period were included in this cross-sectional study. Based on FNAC and histopathology, patients were classified into different groups of the spectrum. Agreement between FNAC and histopathology to classify leprosy was determined by Kappa statistics. Sensitivity and specificity of FNAC to classify leprosy were determined against the gold standard of histopathology. Results: All the 47 study participants had histopathology features of leprosy. FNAC could obtain adequate aspirate in 30 patients (63.8%), who were considered for further analysis. There was moderate agreement (76.6%) between classification of leprosy by FNAC and histopathology on Kappa statistics (Kappa value 0.766). FNAC showed 80–100% sensitivity and 84–100% specificity to classify leprosy against the gold standard of histopathology. Limitation: Small sample size. Conclusion: When adequate aspirate is obtained, FNAC could serve as a useful tool in classification of leprosy.

Diagnostic Accuracy of Mammography and FNAC in Comparison to Gold Standard Histopathological Examination in Carcinoma Breast

Context: Screening and diagnostic efforts for breast cancer are critical because the disease has a high rate of successful outcomes with early identification and treatment. The mammography (MG) and fine needle aspiration cytology (FNAC) are individually effective diagnostic modalities for detection of breast pathologies. Aim: To compare the efficacy of mammography and FNAC in Cancer Breast. Setting & Design: The prospective study conducted on patients admitted for surgery for Breast lump or symptoms of breast malignancy in surgical wards of JLN Medical College, Ajmer and undergoing surgery for same with an aim to evaluate breast lesions using mammography and FNAC independently and in correlation with gold standard histopathology. Results: A total number of 100 cases of breast lump studied. The mammography, FNAC and histopathology results were collected and analysed. In present study, Mammography shows Sensitivity – 93.846, Specificity – 82.857, Positive Predictive value – 91.045, Negative Predictive Value – 87.87and Accuracy – 90. FNAC shows Sensitivity – 93.8, Specificity – 97.14, Positive Predictive value – 98.38, Negative Predictive Value – 89.474 and Accuracy - 95 Conclusion: This study confirms that the Mammography and FNAC have significantly higher sensitivity and NPV in detecting the both benign and malignant lesions of the breast. In the present study, FNAC has more accuracy in predicting breast cancer than mammogram. Association between FNAC and Mammography result was calculated to be.717 Key words: Breast lesions; fine needle aspiration cytology; mammography; histopathological examination. Key message: for successful treatment outcome of carcinoma breast early diagnosis is must.

Deep learning systems detect dysplasia with human-like accuracy using histopathology and probe-based confocal laser endomicroscopy

Probe-based confocal laser endomicroscopy (pCLE) allows for real-time diagnosis of dysplasia and cancer in Barrett’s esophagus (BE) but is limited by low sensitivity. Even the gold standard of histopathology is hindered by poor agreement between pathologists. We deployed deep-learning-based image and video analysis in order to improve diagnostic accuracy of pCLE videos and biopsy images. Blinded experts categorized biopsies and pCLE videos as squamous, non-dysplastic BE, or dysplasia/cancer, and deep learning models were trained to classify the data into these three categories. Biopsy classification was conducted using two distinct approaches—a patch-level model and a whole-slide-image-level model. Gradient-weighted class activation maps (Grad-CAMs) were extracted from pCLE and biopsy models in order to determine tissue structures deemed relevant by the models. 1970 pCLE videos, 897,931 biopsy patches, and 387 whole-slide images were used to train, test, and validate the models. In pCLE analysis, models achieved a high sensitivity for dysplasia (71%) and an overall accuracy of 90% for all classes. For biopsies at the patch level, the model achieved a sensitivity of 72% for dysplasia and an overall accuracy of 90%. The whole-slide-image-level model achieved a sensitivity of 90% for dysplasia and 94% overall accuracy. Grad-CAMs for all models showed activation in medically relevant tissue regions. Our deep learning models achieved high diagnostic accuracy for both pCLE-based and histopathologic diagnosis of esophageal dysplasia and its precursors, similar to human accuracy in prior studies. These machine learning approaches may improve accuracy and efficiency of current screening protocols.

Abstract PO-017: Annotation-free 3D gland segmentation with generative image-sequence translation for prostate cancer risk assessment

Abstract 1. Purpose We developed an annotation-free image-translation-based approach for 3D segmentation of prostate glands within 3D-histology datasets of whole biopsies stained with a low-cost and rapid-diffusing fluorescent analog of H&E. 2. Introduction The current diagnostic gold standard of histopathology provides a limited 2D view of complex 3D glandular structures in prostate specimens, which contributes to high interobserver variability and reduced prognostic accuracy. We have recently developed nondestructive 3D pathology methods based on open-top light-sheet (OTLS) microscopy. In order to train prognostic models based on 3D glandular morphology, we have developed an objective (biomarker-based) 3D gland-segmentation method that does not rely upon tedious and subjective manual annotations, and which can operate on images of tissue stained with a cheap and fast-diffusing (small molecule) fluorescent analog of H&E. 3. Methods We first convert H&E-analog images into synthetic 3D immunofluorescence (IF) images of cytokeratin-8 (CK8), a biomarker expressed by the luminal epithelial cells that surround all prostate glands. This conversion was performed by treating the 3D data as sequences of 2D images and adapting a generative adversarial network (GAN)-based video-synthesis model to perform image-sequence translation with high depth-wise continuity between frames. Based on the synthetic CK8 images, glands were then objectively segmented in 3D using a thresholding/morphology-based algorithm. This two-step method obviates the need for labor-intensive and subjective manual 3D annotations, as would be needed to train a single-step segmentation model. A 3D structural similarity (SSIM) index was assessed between synthetic and real CK8 images. In addition, based on ground-truth manual annotations of glands in ten 0.2-mm3 regions, we calculated voxel-based Dice coefficients to compare our segmentation accuracy vs. two baseline methods. 4. Results The synthetic CK8 images exhibited high fidelity (3D SSIM = 0.696) and optimal continuity with depth. Our segmentation accuracy outperformed two baseline methods, with Dice coefficients (averaged for 10 samples) of: 0.882 (our method), 0.725 (3D watershed), 0.643 (2D U-net). We are now applying our method to 3D histology datasets of whole biopsies (n > 1000) acquired ex vivo from prostatectomy specimens (N ~ 200), where we are extracting 3D histomorphometric gland features to predict biochemical recurrence (BCR) post-prostatectomy in men with prostate cancer. 5. Conclusions Our annotation-free segmentation method relies upon generative synthetic 3D IF images from H&E-analog images in order to objectively segment the 3D prostate gland network. These accurate 3D segmentations are being extended to whole-biopsy 3D pathology datasets for prostate cancer risk assessment. Citation Format: Weisi Xie, Adam Glaser, Nicholas Reder, Nadia Postupna, Chenyi Mao, Can Koyuncu, Patrick Leo, Robert Serafin, Hongyi Huang, Anant Madabhushi, Lawrence True, Jonathan T.C. Liu. Annotation-free 3D gland segmentation with generative image-sequence translation for prostate cancer risk assessment [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-017.

Experimental validation of depolarizing Mueller matrix model via ex vivo colon samples

Experimental validation of a previously reported depolarizing Mueller matrix model is crucial to understanding the light-tissue interactions and the morphological alterations originating in malignant tissue zones in terms of their optical properties. This manuscript is a continuation of a previously reported case study, where a theoretical model was introduced with an additional Monte Carlo simulation. The main aim of this study is to empirically validate both theory and modelling. Once extracted from an experimental Mueller matrix via symmetric decomposition, the polarimetric quantities were compared with the corresponding parameters previously determined from polarized Monte Carlo simulations. Our results were obtained from an ex vivo colon sample and indicate a potential capability to provide supplementary polarimetric data to physicians and the gold standard histopathology analysis.

Real-time lipid patterns to classify viable and necrotic liver tumors

AbstractReal-time tissue classifiers based on molecular patterns are emerging tools for fast tumor diagnosis. Here, we used rapid evaporative ionization mass spectrometry (REIMS) and multivariate statistical analysis (principal component analysis–linear discriminant analysis) to classify tissues with subsequent comparison to gold standard histopathology. We explored whether REIMS lipid patterns can identify human liver tumors and improve the rapid characterization of their underlying metabolic features. REIMS-based classification of liver parenchyma (LP), hepatocellular carcinoma (HCC), and metastatic adenocarcinoma (MAC) reached an accuracy of 98.3%. Lipid patterns of LP were more similar to those of HCC than to those of MAC and allowed clear distinction between primary and metastatic liver tumors. HCC lipid patterns were more heterogeneous than those of MAC, which is consistent with the variation seen in the histopathological phenotype. A common ceramide pattern discriminated necrotic from viable tumor in MAC with 92.9% accuracy and in other human tumors. Targeted analysis of ceramide and related sphingolipid mass features in necrotic tissues may provide a new classification of tumor cell death based on metabolic shifts. Real-time lipid patterns may have a role in future clinical decision-making in cancer precision medicine.Real-time lipid patterns can identify liver tumors and their inter-tumor and intra-tumor heterogeneity. Ceramides and related sphingolipids are a common feature of necrotic tumors and can characterize the tumor phenotype based on metabolic shifts relevant for cell death pathways. Lipid patterns have the potential to improve clinical decision-making in the near future.

Anterior segment optical coherence tomography and ultrasound biomicroscopy for measuring thickness of corneal and bulbar conjunctival tumours

Background/ObjectiveAnterior segment optical coherence tomography (AS-OCT) and ultrasound biomicroscopy (UBM) are two non-invasive imaging techniques used for the measurement of tumour thickness in corneal and bulbar conjunctival tumours. Histopathology (HP),...

High-resolution computed tomography as a non-invasive imaging biomarker for interstitial lung diseases: a tertiary center study

Background: Interstitial lung diseases (ILD) are a heterogeneous group of non-neoplastic disorders resulting from damage to the lung parenchyma by varying patterns of inflammation and fibrosis. With high-resolution computed tomography (HRCT) the pattern of lung damage can be mapped accurately which may help to identify specific ILD.Methods: 65 diagnosed cases of ILD by HRCT who were admitted to a tertiary care chest hospital, formed the study group. All these patients also underwent histopathological confirmation as per hospital protocol. The study was done over a period from August 2016 to July 2019. Clinical details, chest x-ray, HRCT and histopathological data was collected and analysed using 2x2 table for detecting sensitivity, specificity, positive predictive value (PPV) and negative predictive values (NPV).Results: For diagnosing ILD like acute interstitial pneumonia (AIP), LIP and RB ILD the HRCT fared equally well in diagnostic utility as compared to histopathological examination. But in certain conditions like non-specific interstitial pneumonia (NSIP) the HRCT performed poorly in terms of PPV as compared to gold standard histopathology. In Bronchiolitis obliterans organizing pneumonia (BOOP) and usual interstitial pneumonia (UIP) again the HRCT performed fairly well as compared to gold standard.Conclusions: HRCT shows good correlation with histopathological diagnosis in identifying a various subtype of ILD and may thus serve a useful non-invasive, imaging biomarker not only for diagnosing a particular ILD but for prognostication and response to treatment.

Cytological evaluation of thyroid lesions and its correlation with histopathology in a teaching hospital

Aim of the Study: To study the cytomorphological features in various thyroid lesions and to correlate the cytological features with histopathological study of surgically removed thyroid lesions. Materials and Methods: Both retrospective and prospective study was carried out at Department of Pathology, Maheshwara Medical College and Hospital, over a period of two years. Patients from General Surgery, ENT, Paediatrics and from General Medicine OPD were taken for FNAC. Thyroid FNACs in 94 patients were done during this period and 69 cases underwent histopathological examination. The findings of FNAC and histopathology were compared. Results: Patient age ranged from 9 to 75 years. Majority of the patients (28.7%) were in the 21-30 years age group. The male to female ratio was 1:22.4. On cytology, Nodular goitre was the most common diagnosis (39.3%). Follicular neoplasm was reported in 04 cases (4.2%). On Histopathology, benign diagnosis (91.3%) far outnumbered the malignant ones (8.6% cases). FNAC showed overall diagnostic accuracy of 98.5% with specificity of 100%, sensitivity of 85.7%, Positive predictive value of 100%, and Negative predictive value of 98.4%. Conclusion: FNAC technique showed good reliability in diagnosing thyroid lesions in our institute. It showed 100% specificity, high sensitivity and high accuracy. Though FNAC cannot replace the gold standard of histopathology, this technique has many advantages and helps in preoperative diagnosis of thyroid lesions which guides the further clinical management of patients with thyroid swellings. Keywords: FNAC of thyroid, Cytology and Histopathology correlation, Nodular goitre.

IMG-18. ASSESSMENT OF SUSPECTED DISEASE PROGRESSION USING MULTIPARAMETRIC 18F-CHOLINE PET/MRI IN CHILDHOOD AND TEENAGE-YOUNG ADULT GLIOMAS

OBJECTIVESEvaluation of post-treatment glioma burden remains a significant challenge in children, teenagers and young adults (TYA). The aim of this study was to evaluate the utility of ChoPET/MRI for evaluation of suspected disease progression in childhood and TYA gliomas.METHODS27 patients (mean age 14 years, range 6–21 years) with suspected glioma disease progression were evaluated with ChoPET/MRI (n=59). Relative cerebral blood volume (rCBV), apparent diffusion coefficient (ADC) and maximum standardised uptake values (SUVmax) in enhancing (enh) and non-enhancing (ne) tumour and normal-appearing white matter (wm) were calculated (rCBVenh, rCBVne, rCBVwm, ADCenh, ADCne, ADCwm, SUVenh, SUVne, SUVwm). 2 blinded radiologists scored tumour probability (1 = unlikely; 5 = definitely). Sensitivity and specificity calculated with gold standard histopathology or clinical follow-up.RESULTSAccuracy for the detection of residual/recurrent tumour on conventional MRI was 96.3% (91.7% ≤14 years, 100% ≥15 years) and ChoPET was 73.1% (66.7% ≤14 years, 80.0% ≥15 years). Lack of agreement was observed in 9/27 patients, with ChoPET superior to MRI in 1 case of a posterior fossa tumour. Tumour component analysis demonstrated significantly higher SUVenh and SUVne than SUVwm (SUVenh: p<0.001; SUVne: p=0.004, equivalent to results were observed for ADV and rCBV (ADCenh, ADCne: p<0.001 vs ADCwm; rCBVenh, rCBVne: p<0.001 vs rCBVwm).CONCLUSIONSMRI is more sensitive than ChoPET in the evaluation of suspected disease progression in TYA gliomas. However, quanititative ChoPET is able to detect enhancing and non-enhancing tumour and may be helpful in evaluating posterior fossa disease where MRI is equivocal.

Deep Learning for Whole-Slide Tissue Histopathology Classification: A Comparative Study in the Identification of Dysplastic and Non-Dysplastic Barrett's Esophagus.

The gold standard of histopathology for the diagnosis of Barrett’s esophagus (BE) is hindered by inter-observer variability among gastrointestinal pathologists. Deep learning-based approaches have shown promising results in the analysis of whole-slide tissue histopathology images (WSIs). We performed a comparative study to elucidate the characteristics and behaviors of different deep learning-based feature representation approaches for the WSI-based diagnosis of diseased esophageal architectures, namely, dysplastic and non-dysplastic BE. The results showed that if appropriate settings are chosen, the unsupervised feature representation approach is capable of extracting more relevant image features from WSIs to classify and locate the precursors of esophageal cancer compared to weakly supervised and fully supervised approaches.

Efficacy of cytological examination in comparision with gold standard histopathology in various palpable &amp; non-palpable lesions- A study of 483 cases in a tertiary care centre

It has become important to diagnose the pathology of any site in early stage to improve the prognosis of the disease process since there is limited resources in our country. Since FNAC is easy to perform, simple, cost effective procedure requiring minimal setup, we conducted this study to evaluate its diagnostic accuracy, sensitivity and specificity in comparison to histopathology.This was a retrospective and prospective study carried out for a duration of 4 years and included total of 483 cases referred to Pathology Department. Biopsy was performed in all cases after FNAC and the findings were correlated.Of the 483 cases, patients belonged to age group of 10 to 70 years. In case of breast lesions all were females, in lymph node, lung &amp; miscellaneous lesions there was male preponderance while in thyroid female preponderance was observed. The sensitivity &amp; specificity of cytopathology in Breast was 98.87% &amp; 78.26%, in Lung 98.18% &amp; 86.66%, in Lymph node 93.93% &amp; 85.71%, in Thyroid 93.18% &amp; 85.71%, while in Miscellaneous 93.33% &amp; 87.5% respectively.FNAC can be used safely and can be relied upon in diagnosis of various pathologies even in centres with limited facilities &amp; it can be set up at OPD level also, thus aiding in timely management of the patient. The overall Sensitivity and Specificity of cytopathological examination was good. PPV &amp; NPV were within acceptable range.

Alvarado Score versus Appendicitis Inflammatory Response Score validity test, Hospital José Carrasco Arteaga 2018

BACKGROUND: Acute appendicitis is the main cause of non-traumatic acute abdomen worldwide, it is still a public health issue and the diagnosis can be challenging. When an atypical case is presented, is necessary to use diagnostic scores, like Alvarado Score, Modified Alvarado Score, RIPASA, among others. The aim of this study was to determine the test validity of Inflammatory Response Score versus Alvarado Score, for acute appendicitis diagnosis in 16 year old and older patients. METHODS: This is a descriptive, cross-sectional, validity test study, to compare AIR Score and Alvarado Score, with the Gold-Standard histopathology results. A sample of 292 patients that went under appendectomy at Hospital José Carrasco Arteaga during 2018 was studied. We considered sensitivity, specificity, positive predictive value (PPV), negative predictive value (VPN), ROC curve and Likelihood Ratio. RESULTS: 49.7% patients were young adults, 62.7% of the patients were male. Alvarado Score showed a 88.5% sensitivity, 29.6% specificity, PPV of 81.7%, 42.2% NPV, 1.23 LR+ and 0.38 –LR; compared to 94.7% sensitivity, 76.5% specificity, 93.5% PPV, 80.3% NPV, 4.02 +LR, 0.611 -LR for Appendicitis Immflamatory Response Score. ROC curve for AIRS was 0.897, higher than Alvarado Score (0.611); being AIRS a more precise diagnostic test than Alvarado Score. CONCLUSIÓN: AIRS showed higher sensitivity (94.7%) and specificity (76.5%) than Alvarado Score (88.5%, 29.6% respectively). Alvarado Score is sensitive enough for acute appendicitis diagnosis, but not specific enough to exclude the diagnosis. AIRS shows a higher Likelihood Ratio and ROC curve than Alvarado Score, but the posttest probability is low for identifying acute appendicitis cases.

Value of preoperative computed tomography in predicting the local staging of cancer of the tongue at primary surgery.

Preoperative staging is essential for the planning of treatment of cancer. This study was designed to evaluate the accuracy of computed tomography (CT) in predicting the local stage of tongue cancer by comparing it with the gold standard of histopathology. A total of 233 patients with newly-diagnosed tongue cancer was retrospectively reviewed, and the size of the tumour and the status of the cervical lymph node were compared between CT images and histopathological results. Patients with stage II cancer were followed up to assess the influence of inaccurate preoperative staging on prognosis. The accuracy of local staging by CT was 47.6% (111/233), with 59.7% (139/233) for tumour stage, and 70.4% (164/233) for nodal stage. The greatest dimension of the tumour on the CT image was about 2mm less than that measured by histopathology. The estimated volume of tumour was a quarter smaller. The accuracy of predicting malignant lymph nodes by CT was 68.9% (n=161). Among patients with stage II disease, simultaneous neck dissection was less likely in the understaged group than in the accurately staged one. The reoperation rate was a little higher but not significantly so. We conclude that the accuracy of CT in predicting local staging for tongue cancer was only moderate, because it underestimated the size of the tumour and needed to improve the criteria for detecting malignant lymph nodes. Understaging on CT images may influence the prognosis of patients with early stage tongue cancer.

USAGE OF TOLUIDINE BLUE IN EARLY DETECTION OF MALIGNANT AND PREMALIGNANT LESIONS

Objective: To Test the utility of toluidine blue staining in the early diagnosis of malignant and premalignant lesions. Materials and Methods: This was a Randomized control clinical trial, carried out at Oral and Maxillofacial Department Gajju Khan Medical College, Bacha Khan Medical Complex, Swabi from 15th April 2019 to 15th April 2020. Twenty two patients with the clinical suspicious lesions were selected. Oral rise was done with 1% acetic acid and later Toluidine blue (1%W/W) was applied with sterile swab stick. Again oral rise was done with normal saline. Colour of the lesion was noted. Later incisional biopsy was taken as gold standard. Results: Total of 22 cases the males were 14(63.6%) and females were 8(36.4%). The sensitivity and specificity of toluidine blue against gold standard of histopathology were 88.89% and 61.54% % respectively. The diagnostic accuracy of toluidine blue was 72.73%. Conclusion: Toluidine blue is very good, effective and simple staining procedure. The staining method is more tolerable by the patient. It may help not only in detecting early dysplastic and malignant lesions but will also help in determining the site of biopsy to be taken.