Automated Digital Quantification of Pulmonary Fibrosis in Human Histopathology Specimens

Pulmonary fibrosis is characterized by abnormal interstitial extracellular matrix and cellular accumulations. Methods quantifying fibrosis severity in lung histopathology samples are semi-quantitative, subjective, and analyze only portions of sections. We sought to determine whether automated computerized imaging analysis shown to continuously measure fibrosis in mice could also be applied in human samples. A pilot study was conducted to analyze a small number of specimens from patients with Hermansky-Pudlak syndrome pulmonary fibrosis (HPSPF) or idiopathic pulmonary fibrosis (IPF). Digital images of entire lung histological serial sections stained with picrosirius red and alcian blue or anti-CD68 antibody were analyzed using dedicated software to automatically quantify fibrosis, collagen, and macrophage content. Automated fibrosis quantification based on parenchymal tissue density and fibrosis score measurements was compared to pulmonary function values or Ashcroft score. Automated fibrosis quantification of HPSPF lung explants was significantly higher than that of IPF lung explants or biopsies and was also significantly higher in IPF lung explants than in IPF biopsies. A high correlation coefficient was found between some automated quantification measurements and lung function values for the three sample groups. Automated quantification of collagen content in lung sections used for digital image analyses was similar in the three groups. CD68 immunolabeled cell measurements were significantly higher in HPSPF explants than in IPF biopsies. In conclusion, computerized image analysis provides access to accurate, reader-independent pulmonary fibrosis quantification in human histopathology samples. Fibrosis, collagen content, and immunostained cells can be automatically and individually quantified from serial sections. Robust automated digital image analysis of human lung samples enhances the available tools to quantify and study fibrotic lung disease.

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Automated Quantification of sTIL Density with H&E-Based Digital Image Analysis Has Prognostic Potential in Triple-Negative Breast Cancers

Cancers ◽

10.3390/cancers13123050 ◽

2021 ◽

Vol 13 (12) ◽

pp. 3050

Author(s):

Jeppe Thagaard ◽

Elisabeth Specht Stovgaard ◽

Line Grove Vognsen ◽

Søren Hauberg ◽

Anders Dahl ◽

...

Keyword(s):

Image Analysis ◽

Digital Image ◽

Digital Image Analysis ◽

Triple Negative ◽

Tumor Infiltrating Lymphocytes ◽

Cancer Type ◽

Tumor Type ◽

Breast Cancers ◽

Automated Quantification ◽

Infiltrating Lymphocytes

Triple-negative breast cancer (TNBC) is an aggressive and difficult-to-treat cancer type that represents approximately 15% of all breast cancers. Recently, stromal tumor-infiltrating lymphocytes (sTIL) resurfaced as a strong prognostic biomarker for overall survival (OS) for TNBC patients. Manual assessment has innate limitations that hinder clinical adoption, and the International Immuno-Oncology Biomarker Working Group (TIL-WG) has therefore envisioned that computational assessment of sTIL could overcome these limitations and recommended that any algorithm should follow the manual guidelines where appropriate. However, no existing studies capture all the concepts of the guideline or have shown the same prognostic evidence as manual assessment. In this study, we present a fully automated digital image analysis pipeline and demonstrate that our hematoxylin and eosin (H&E)-based pipeline can provide a quantitative and interpretable score that correlates with the manual pathologist-derived sTIL status, and importantly, can stratify a retrospective cohort into two significant distinct prognostic groups. We found our score to be prognostic for OS (HR: 0.81 CI: 0.72–0.92 p = 0.001) independent of age, tumor size, nodal status, and tumor type in statistical modeling. While prior studies have followed fragments of the TIL-WG guideline, our approach is the first to follow all complex aspects, where appropriate, supporting the TIL-WG vision of computational assessment of sTIL in the future clinical setting.

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Automated Quantification of MART1-Verified Ki67 Indices by Digital Image Analysis in Melanocytic Lesions

Archives of Pathology & Laboratory Medicine ◽

10.5858/arpa.2011-0360-oa ◽

2012 ◽

Vol 136 (6) ◽

pp. 627-634 ◽

Cited By ~ 19

Author(s):

Patricia Switten Nielsen ◽

Rikke Riber-Hansen ◽

Jakob Raundahl ◽

Torben Steiniche

Keyword(s):

Image Analysis ◽

Digital Image ◽

Digital Image Analysis ◽

Proliferation Marker ◽

Ki67 Index ◽

Proliferating Cells ◽

Melanocytic Lesions ◽

Manual Counting ◽

Automated Quantification ◽

Whole Slide Images

Context.—The proliferation marker Ki67 is an important diagnostic and prognostic aid in surgical pathology. However, manual quantification in a counting frame to accurately establish the proliferation rate (Ki67 index) is cumbersome and time-consuming. Instead, digital image analysis of Ki67/MART1 double stains may provide fast and novel index computations for entire tumor sections. Objectives.—To design and compare image analysis protocols that compute Ki67 indices of Ki67/MART1 double stains, to compare automated indices with previously published manual indices, and to compare the total number of proliferating cells (mimicking a Ki67 single stain) with the number of MART1-verified proliferating cells. Design.—Whole slide images were captured from 48 melanomas and 77 nevi stained with an immunohistochemical cocktail against Ki67 and MART1. Ki67 indices were determined by digital image analysis and different equations based on number or area. Results.—The differences between mean indices of melanomas and nevi were significant (P < .001) in all index computations. Number-based image analysis of lesions with more than 250 melanocytic cells misclassified 1 of 42 melanomas and 4 of 53 nevi, numbers comparable with manual counting. Automated indices were significantly higher than manual indices, as were indices of mimicked Ki67 single stains compared with MART1-verified Ki67 indices (P < .001). Conclusions.—Ki67 indices established by digital image analysis of Ki67/MART1 double stains demonstrated excellent abilities to discriminate melanomas from nevi with diagnostic performances equal to manually performed indices. Testing different definitions of the automated MART1-verified Ki67 index, no single definition stood out; thus, a variety of definitions may be used.

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Digital image acquisition, processing, and analysis in a polymer microscopy laboratory

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100170001 ◽

1994 ◽

Vol 52 ◽

pp. 454-455

Author(s):

Vinod K. Berry ◽

Xiao Zhang

Keyword(s):

United States ◽

Image Analysis ◽

Digital Image ◽

Image Acquisition ◽

Image Transmission ◽

The United States ◽

Quantitative Image Analysis ◽

Quantitative Image

In recent years it became apparent that we needed to improve productivity and efficiency in the Microscopy Laboratories in GE Plastics. It was realized that digital image acquisition, archiving, processing, analysis, and transmission over a network would be the best way to achieve this goal. Also, the capabilities of quantitative image analysis, image transmission etc. available with this approach would help us to increase our efficiency. Although the advantages of digital image acquisition, processing, archiving, etc. have been described and are being practiced in many SEM, laboratories, they have not been generally applied in microscopy laboratories (TEM, Optical, SEM and others) and impact on increased productivity has not been yet exploited as well.In order to attain our objective we have acquired a SEMICAPS imaging workstation for each of the GE Plastic sites in the United States. We have integrated the workstation with the microscopes and their peripherals as shown in Figure 1.

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Digital Image Analysis of the Larynx

Perspectives on Speech Science and Orofacial Disorders ◽

10.1044/ssod10.2.7 ◽

2000 ◽

Vol 10 (2) ◽

pp. 7-9

Author(s):

Yaser Natour ◽

Christine Sapienza ◽

Mark Schmalz ◽

Savita Collins

Keyword(s):

Image Analysis ◽

Digital Image ◽

Digital Image Analysis

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Remote Sensing Digital Image Analysis

10.1007/978-3-662-02462-1 ◽

1986 ◽

Cited By ~ 295

Author(s):

John A. Richards

Keyword(s):

Remote Sensing ◽

Image Analysis ◽

Digital Image ◽

Digital Image Analysis

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Digital Image Analysis of Corn Leaves affected by Nutrient Deficiencies

ASA Special Publications - Digital Imaging and Spectral Techniques: Applications to Precision Agriculture and Crop Physiology ◽

10.2134/asaspecpub66.c5 ◽

2015 ◽

pp. 53-62

Author(s):

Simone Graeff ◽

Wilhelm Claupein ◽

Diedrich Steffens ◽

Sven Schubert

Keyword(s):

Image Analysis ◽

Digital Image ◽

Digital Image Analysis ◽

Nutrient Deficiencies

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Digital Image Analysis of BAP-1 Accurately Predicts Uveal Melanoma Metastasis

Translational Vision Science & Technology ◽

10.1167/tvst.8.3.11 ◽

2019 ◽

Vol 8 (3) ◽

pp. 11 ◽

Cited By ~ 6

Author(s):

Gustav Stålhammar ◽

Thonnie Rose O. See ◽

Stephen Phillips ◽

Stefan Seregard ◽

Hans E. Grossniklaus

Keyword(s):

Image Analysis ◽

Uveal Melanoma ◽

Digital Image ◽

Digital Image Analysis ◽

Melanoma Metastasis

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Complications in Idiopathic Pulmonary Fibrosis: Focus on Their Clinical and Radiological Features

Diagnostics ◽

10.3390/diagnostics10070450 ◽

2020 ◽

Vol 10 (7) ◽

pp. 450

Author(s):

Federica Galioto ◽

Stefano Palmucci ◽

Giovanna M. Astuti ◽

Ada Vancheri ◽

Giulio Distefano ◽

...

Keyword(s):

Idiopathic Pulmonary Fibrosis ◽

Pulmonary Fibrosis ◽

Lung Disease ◽

Integrated Approach ◽

Correct Treatment ◽

Radiological Features ◽

Palliative Care Services ◽

Pictorial Essay ◽

Personalized Approach ◽

Fibrotic Lung Disease

Idiopathic pulmonary fibrosis (IPF) is a fibrotic lung disease with uncertain origins and pathogenesis; it represents the most common interstitial lung disease (ILD), associated with a pathological pattern of usual interstitial pneumonitis (UIP). This disease has a poor prognosis, having the most lethal prognosis among ILDs. In fact, the progressive fibrosis related to IPF could lead to the development of complications, such as acute exacerbation, lung cancer, infections, pneumothorax and pulmonary hypertension. Pneumologists, radiologists and pathologists play a key role in the identification of IPF disease, and in the characterization of its complications—which unfortunately increase disease mortality and reduce overall survival. The early identification of these complications is very important, and requires an integrated approach among specialists, in order to plane the correct treatment. In some cases, the degree of severity of patients having IPF complications may require a personalized approach, based on palliative care services. Therefore, in this paper, we have focused on clinical and radiological features of the complications that occurred in our IPF patients, providing a comprehensive and accurate pictorial essay for clinicians, radiologists and surgeons involved in their management.

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