Grid technology in tissue-based diagnosis: fundamentals and potential developments

Computerised assessment-a novel approach for calculation of percentage of hypomineralized lesion on incisors and its correlation with aesthetic concern

Introduction

Molar-incisor hypomineralization (MIH) is a localized, qualitative, demarcated enamel defect that affects first permanent molars (FPMs) and/or permanent incisors. The aim of present study was to introduce a novel computerised assessment process to detect and quantify the percentage opacity associated with MIH affected maxillary central incisors.

Methodology

Children (8-16 years) enrolled in the primary study having mild (white/cream or yellow/brown) MIH lesion on fully erupted maxillary permanent central incisor. 50 standardised images of MIH lesions were captured in an artificially lit room with fixed parameters and were anonymized and securely stored. Images were analysed by AI-driven computerised software and generates output classifications via a sophisticated algorithm crafted using a meticulously annotated image dataset as reference through supervised machine learning (SML). For the validation of computerised assessment of MIH lesions, the percentage of demarked opacity was calculated using ADOBE PHOTOSHOP CS7.

Results

The percentage of MIH lesion was calculated through histogram plotting with the maxima ranging from 7.29 % to 71.21 % with the mean value of 34.51 %. The validation score ranged from 10.29 % to 67.27 % with the mean value of 35.32 %. The difference between the two was statistically not significant. Out of 50 patients; 11 patients had 1-30 % of surface affected with MIH and 2 had aesthetic concern; 24 had 30-60 % of surface affected and 13 had aesthetic concern; 15 had >60 % of surface affected and 12 had aesthetic concerns.

Conclusions

The proposed approach exhibit sufficient quality to be integrated into a dental software addressing practical challenges encountered in daily clinical settings.

Combining Diagnostic Imaging and Pathology for Improving Diagnosis and Prognosis of Cancer

In the era of personalized medicine, the management of oncological patients requires a translational and multidisciplinary approach. During early phases of cancer development, biochemical alterations of cell metabolism occur much before the formation of detectable tumour masses. Current molecular imaging techniques, targeted to the study of molecular kinetics, employ molecular tracers capable of detecting cancer lesions with both high sensitivity and specificity while also providing essential information for both prognosis and therapy. On the contrary, complementary and crucial information is provided by histopathological examination and ancillary techniques such as immunohistochemistry. Thus, the successful collaboration between diagnostic imaging and anatomic pathology can represent a fundamental step in the "tortuous" but decisive path towards personalized medicine.

The history of pathology informatics: A global perspective

Pathology informatics has evolved to varying levels around the world. The history of pathology informatics in different countries is a tale with many dimensions. At first glance, it is the familiar story of individuals solving problems that arise in their clinical practice to enhance efficiency, better manage (e.g., digitize) laboratory information, as well as exploit emerging information technologies. Under the surface, however, lie powerful resource, regulatory, and societal forces that helped shape our discipline into what it is today. In this monograph, for the first time in the history of our discipline, we collectively perform a global review of the field of pathology informatics. In doing so, we illustrate how general far-reaching trends such as the advent of computers, the Internet and digital imaging have affected pathology informatics in the world at large. Major drivers in the field included the need for pathologists to comply with national standards for health information technology and telepathology applications to meet the scarcity of pathology services and trained people in certain countries. Following trials by a multitude of investigators, not all of them successful, it is apparent that innovation alone did not assure the success of many informatics tools and solutions. Common, ongoing barriers to the widespread adoption of informatics devices include poor information technology infrastructure in undeveloped areas, the cost of technology, and regulatory issues. This review offers a deeper understanding of how pathology informatics historically developed and provides insights into what the promising future might hold.

Validation of a new classifier for the automated analysis of the human epidermal growth factor receptor 2 (HER2) gene amplification in breast cancer specimens

Amplification of the human epidermal growth factor receptor 2 (HER2) is a prognostic marker for poor clinical outcome and a predictive marker for therapeutic response to targeted therapies in breast cancer patients. With the introduction of anti-HER2 therapies, accurate assessment of HER2 status has become essential. Fluorescence in situ hybridization (FISH) is a widely used technique for the determination of HER2 status in breast cancer. However, the manual signal enumeration is time-consuming. Therefore, several companies like MetaSystem have developed automated image analysis software. Some of these signal enumeration software employ the so called “tile-sampling classifier”, a programming algorithm through which the software quantifies fluorescent signals in images on the basis of square tiles of fixed dimensions. Considering that the size of tile does not always correspond to the size of a single tumor cell nucleus, some users argue that this analysis method might not completely reflect the biology of cells. For that reason, MetaSystems has developed a new classifier which is able to recognize nuclei within tissue sections in order to determine the HER2 amplification status on nuclei basis. We call this new programming algorithm “nuclei-sampling classifier”. In this study, we evaluated the accuracy of the “nuclei-sampling classifier” in determining HER2 gene amplification by FISH in nuclei of breast cancer cells. To this aim, we randomly selected from our cohort 64 breast cancer specimens (32 nonamplified and 32 amplified) and we compared results obtained through manual scoring and through this new classifier. The new classifier automatically recognized individual nuclei. The automated analysis was followed by an optional human correction, during which the user interacted with the software in order to improve the selection of cell nuclei automatically selected. Overall concordance between manual scoring and automated nuclei-sampling analysis was 98.4% (100% for nonamplified cases and 96.9% for amplified cases). However, after human correction, concordance between the two methods was 100%. We conclude that the nuclei-based classifier is a new available tool for automated quantitative HER2 FISH signals analysis in nuclei in breast cancer specimen and it can be used for clinical purposes.

Experience with multimodality telepathology at the University of Pittsburgh Medical Center

Several modes of telepathology exist including static (store-and-forward), dynamic (live video streaming or robotic microscopy), and hybrid technology involving whole slide imaging (WSI). Telepathology has been employed at the University of Pittsburgh Medical Center (UPMC) for over a decade at local, national, and international sites. All modes of telepathology have been successfully utilized to exploit our institutions subspecialty expertise and to compete for pathology services. This article discusses the experience garnered at UPMC with each of these teleconsultation methods. Static and WSI telepathology systems have been utilized for many years in transplant pathology using a private network and client-server architecture. Only minor clinically significant differences of opinion were documented. In hematopathology, the CellaVision^® system is used to transmit, via email, static images of blood cells in peripheral blood smears for remote interpretation. While live video streaming has remained the mode of choice for providing immediate adequacy assessment of cytology specimens by telecytology, other methods such as robotic microscopy have been validated and shown to be effective. Robotic telepathology has been extensively used to remotely interpret intra-operative neuropathology consultations (frozen sections). Adoption of newer technology and increased pathologist experience has improved accuracy and deferral rates in teleneuropathology. A digital pathology consultation portal (https://pathconsult.upmc.com/) was recently created at our institution to facilitate digital pathology second opinion consults, especially for WSI. The success of this web-based tool is the ability to handle vendor agnostic, large image files of digitized slides, and ongoing user-friendly customization for clients and teleconsultants. It is evident that the practice of telepathology at our institution has evolved in concert with advances in technology and user experience. Early and continued adoption of telepathology has promoted additional digital pathology resources that are now being leveraged for other clinical, educational, and research purposes.

Development of a teledermatopathology consultation system using virtual slides

Background

An online consultation system using virtual slides (whole slide images; WSI) has been developed for pathological diagnosis, and could help compensate for the shortage of pathologists, especially in the field of dermatopathology and in other fields dealing with difficult cases. This study focused on the performance and future potential of the system.

Method

In our system, histological specimens on slide glasses are digitalized by a virtual slide instrument, converted into web data, and up-loaded to an open server. Using our own purpose-built online system, we then input patient details such as age, gender, affected region, clinical data, past history and other related items. We next select up to ten consultants. Finally we send an e-mail to all consultants simultaneously through a single command. The consultant receives an e-mail containing an ID and password which is used to access the open server and inspect the images and other data associated with the case. The consultant makes a diagnosis, which is sent to us along with comments.

Because this was a pilot study, we also conducted several questionnaires with consultants concerning the quality of images, operability, usability, and other issues.

Results

We solicited consultations for 36 cases, including cases of tumor, and involving one to eight consultants in the field of dermatopathology. No problems were noted concerning the images or the functioning of the system on the sender or receiver sides. The quickest diagnosis was received only 18 minutes after sending our data. This is much faster than in conventional consultation using glass slides. There were no major problems relating to the diagnosis, although there were some minor differences of opinion between consultants. The results of questionnaires answered by many consultants confirmed the usability of this system for pathological consultation. (16 out of 23 consultants.)

Conclusion

We have developed a novel teledermatopathological consultation system using virtual slides, and investigated the usefulness of the system. The results demonstrate that our system can be a useful tool for international medical work, and we anticipate its wider application in the future.

Virtual slides

The virtual slides for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1902376044831574

Digital slide images for primary diagnostics in breast pathology: a feasibility study

Digital slide images have been used in many areas of pathology such as teaching, research, digital archiving, teleconsultation, and quality assurance testing. However, they have not much been used as yet for upfront diagnostics. The aim of this study was therefore to test the feasibility of digital slide image-based diagnosis of breast specimens. Sections of 100 breast specimens previously diagnosed conventionally were scanned and rediagnosed on digital slide images by the same pathologists who performed the initial light microscopy-based diagnosis. The digital slide image diagnoses were compared with the light microscopy diagnoses and classified as concordant, slightly discrepant (without clinical or prognostic consequences), or discrepant. The original light microscopy- and digital slide image-based diagnoses were concordant in 93% and slightly discrepant in 6% of cases. There was only 1 discrepant case with clinical or prognostic implication to the patient. However, for this case, no final agreement could be achieved. For 4 of the 6 slightly discrepant cases, digital slide image diagnosis was considered the better one, whereas the original diagnosis was preferred in only 1 case. In addition, for 1 case categorized as slightly discrepant, both the digital slide image and conventional diagnosis were imperfect according to 2 reviewing breast pathologists. This study demonstrates that upfront histopathologic diagnosis of breast biopsies and resections can reliably be done on digital slide image.

From Biomedical Image Analysis to Biomedical Image Understanding Using Machine Learning

This chapter introduces the reader into the main topics covered by the book: biomedical images, biomedical image analysis and machine learning. The general concepts of each topic are presented and the most representative techniques are briefly discussed. Nevertheless, the chapter focuses on the problem of image understanding (i.e., the problem of mapping the low-level image visual content to its high-level semantic meaning). The chapter discusses different important biomedical problems, such as computer assisted diagnosis, biomedical image retrieval, image-user interaction and medical image navigation, which require solutions involving image understanding. Image understanding, thought of as the strategy to associate semantic meaning to the image visual contents, is a difficult problem that opens up many research challenges. In the context of actual biomedical problems, this is probably an invaluable tool for improving the amount of knowledge that medical doctors are currently extracting from their day-to-day work. Finally, the chapter explores some general ideas that may guide the future research in the field.

Virtual slides in peer reviewed, open access medical publication

Background

Application of virtual slides (VS), the digitalization of complete glass slides, is in its infancy to be implemented in routine diagnostic surgical pathology and to issues that are related to tissue-based diagnosis, such as education and scientific publication.

Approach

Electronic publication in Pathology offers new features of scientific communication in pathology that cannot be obtained by conventional paper based journals. Most of these features are based upon completely open or partly directed interaction between the reader and the system that distributes the article. One of these interactions can be applied to microscopic images allowing the reader to navigate and magnify the presented images. VS and interactive Virtual Microscopy (VM) are a tool to increase the scientific value of microscopic images.

Technology and Performance

The open access journal Diagnostic Pathology http://www.diagnosticpathology.org has existed for about five years. It is a peer reviewed journal that publishes all types of scientific contributions, including original scientific work, case reports and review articles. In addition to digitized still images the authors of appropriate articles are requested to submit the underlying glass slides to an institution (DiagnomX.eu, and Leica.com) for digitalization and documentation. The images are stored in a separate image data bank which is adequately linked to the article. The normal review process is not involved. Both processes (peer review and VS acquisition) are performed contemporaneously in order to minimize a potential publication delay. VS are not provided with a DOI index (digital object identifier). The first articles that include VS were published in March 2011.

Results and Perspectives

Several logistic constraints had to be overcome until the first articles including VS could be published. Step by step an automated acquisition and distribution system had to be implemented to the corresponding article. The acceptance of VS by the reader is high as well as by the authors. Of specific value are the increased confidence to and reputation of authors as well as the presented information to the reader. Additional associated functions such as access to author-owned related image collections, reader-controlled automated image measurements and image transformations are in preparation.

Virtual Slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1232133347629819.

Grid computing in image analysis

Diagnostic surgical pathology or tissue–based diagnosis still remains the most reliable and specific diagnostic medical procedure. The development of whole slide scanners permits the creation of virtual slides and to work on so-called virtual microscopes. In addition to interactive work on virtual slides approaches have been reported that introduce automated virtual microscopy, which is composed of several tools focusing on quite different tasks. These include evaluation of image quality and image standardization, analysis of potential useful thresholds for object detection and identification (segmentation), dynamic segmentation procedures, adjustable magnification to optimize feature extraction, and texture analysis including image transformation and evaluation of elementary primitives.

Grid technology seems to possess all features to efficiently target and control the specific tasks of image information and detection in order to obtain a detailed and accurate diagnosis.

Grid technology is based upon so-called nodes that are linked together and share certain communication rules in using open standards. Their number and functionality can vary according to the needs of a specific user at a given point in time. When implementing automated virtual microscopy with Grid technology, all of the five different Grid functions have to be taken into account, namely 1) computation services, 2) data services, 3) application services, 4) information services, and 5) knowledge services.

Although all mandatory tools of automated virtual microscopy can be implemented in a closed or standardized open system, Grid technology offers a new dimension to acquire, detect, classify, and distribute medical image information, and to assure quality in tissue–based diagnosis.

Digital pathology: current status and future perspectives

During the last decade pathology has benefited from the rapid progress of image digitizing technology. The improvement in this technology had led to the creation of slide scanners which are able to produce whole slide images (WSI) which can be explored by image viewers in a way comparable to the conventional microscope. The file size of the WSI ranges from a few megabytes to several gigabytes, leading to challenges in the area of image storage and management when they will be used routinely in daily clinical practice. Digital slides are used in pathology for education, diagnostic purposes (clinicopathological meetings, consultations, revisions, slide panels and, increasingly, for upfront clinical diagnostics) and archiving. As an alternative to conventional slides, WSI are generally well accepted, especially in education, where they are available to a large number of students with the full possibilities of annotations without the problem of variation between serial sections. Image processing techniques can also be applied to WSI, providing pathologists with tools assisting in the diagnosis-making process. This paper will highlight the current status of digital pathology applications and its impact on the field of pathology.

Image processing methods and architectures in diagnostic pathology

Grid technology has enabled the clustering and the efficient and secure access to and interaction among a wide variety of geographically distributed resources such as: supercomputers, storage systems, data sources, instruments and special devices and services. Their main applications include large-scale computational and data intensive problems in science and engineering. General grid structures and methodologies for both software and hardware in image analysis for virtual tissue-based diagnosis has been considered in this paper. This methods are focus on the user level middleware. The article describes the distributed programming system developed by the authors for virtual slide analysis in diagnostic pathology. The system supports different image analysis operations commonly done in anatomical pathology and it takes into account secured aspects and specialized infrastructures with high level services designed to meet application requirements. Grids are likely to have a deep impact on health related applications, and therefore they seem to be suitable for tissue-based diagnosis too. The implemented system is a joint application that mixes both Web and Grid Service Architecture around a distributed architecture for image processing. It has shown to be a successful solution to analyze a big and heterogeneous group of histological images under architecture of massively parallel processors using message passing and non-shared memory.

AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis

The technological progress in digitalization of complete histological glass slides has opened a new door in tissue--based diagnosis. The presentation of microscopic images as a whole in a digital matrix is called virtual slide. A virtual slide allows calculation and related presentation of image information that otherwise can only be seen by individual human performance. The digital world permits attachments of several (if not all) fields of view and the contemporary visualization on a screen. The presentation of all microscopic magnifications is possible if the basic pixel resolution is less than 0.25 microns. To introduce digital tissue--based diagnosis into the daily routine work of a surgical pathologist requires a new setup of workflow arrangement and procedures. The quality of digitized images is sufficient for diagnostic purposes; however, the time needed for viewing virtual slides exceeds that of viewing original glass slides by far. The reason lies in a slower and more difficult sampling procedure, which is the selection of information containing fields of view. By application of artificial intelligence, tissue--based diagnosis in routine work can be managed automatically in steps as follows: 1. The individual image quality has to be measured, and corrected, if necessary. 2. A diagnostic algorithm has to be applied. An algorithm has be developed, that includes both object based (object features, structures) and pixel based (texture) measures. 3. These measures serve for diagnosis classification and feedback to order additional information, for example in virtual immunohistochemical slides. 4. The measures can serve for automated image classification and detection of relevant image information by themselves without any labeling. 5. The pathologists' duty will not be released by such a system; to the contrary, it will manage and supervise the system, i.e., just working at a "higher level". Virtual slides are already in use for teaching and continuous education in anatomy and pathology. First attempts to introduce them into routine work have been reported. Application of AI has been established by automated immunohistochemical measurement systems (EAMUS, www.diagnomX.eu). The performance of automated diagnosis has been reported for a broad variety of organs at sensitivity and specificity levels >85%). The implementation of a complete connected AI supported system is in its childhood. Application of AI in digital tissue--based diagnosis will allow the pathologists to work as supervisors and no longer as primary "water carriers". Its accurate use will give them the time needed to concentrating on difficult cases for the benefit of their patients.

Decision support systems for morphology-based diagnosis and prognosis of prostate neoplasms: a methodological approach

Recent advances in computer and information technologies have allowed the integration of both numeric and non-numeric data, that is, descriptive, linguistic terms. This has led at 1 end of the spectrum of technology development to machine vision based on image understanding and, at the other, to decision support systems. This has had a significant impact on our capability to derive diagnostic and prognostic information from histopathological material with prostate neoplasms. Cancer 2009;115(13 suppl):3068-77. (c) 2009 American Cancer Society.

An informatics model for guiding assembly of telemicrobiology workstations for malaria collaborative diagnostics using commodity products and open-source software

BACKGROUND

Deficits in clinical microbiology infrastructure exacerbate global infectious disease burdens. This paper examines how commodity computation, communication, and measurement products combined with open-source analysis and communication applications can be incorporated into laboratory medicine microbiology protocols. Those commodity components are all now sourceable globally. An informatics model is presented for guiding the use of low-cost commodity components and free software in the assembly of clinically useful and usable telemicrobiology workstations.

METHODS

The model incorporates two general principles: 1) collaborative diagnostics, where free and open communication and networking applications are used to link distributed collaborators for reciprocal assistance in organizing and interpreting digital diagnostic data; and 2) commodity engineering, which leverages globally available consumer electronics and open-source informatics applications, to build generic open systems that measure needed information in ways substantially equivalent to more complex proprietary systems. Routine microscopic examination of Giemsa and fluorescently stained blood smears for diagnosing malaria is used as an example to validate the model.

RESULTS

The model is used as a constraint-based guide for the design, assembly, and testing of a functioning, open, and commoditized telemicroscopy system that supports distributed acquisition, exploration, analysis, interpretation, and reporting of digital microscopy images of stained malarial blood smears while also supporting remote diagnostic tracking, quality assessment and diagnostic process development.

CONCLUSION

The open telemicroscopy workstation design and use-process described here can address clinical microbiology infrastructure deficits in an economically sound and sustainable manner. It can boost capacity to deal with comprehensive measurement of disease and care outcomes in individuals and groups in a distributed and collaborative fashion. The workstation enables local control over the creation and use of diagnostic data, while allowing for remote collaborative support of diagnostic data interpretation and tracking. It can enable global pooling of malaria disease information and the development of open, participatory, and adaptable laboratory medicine practices. The informatic model highlights how the larger issue of access to generic commoditized measurement, information processing, and communication technology in both high- and low-income countries can enable diagnostic services that are much less expensive, but substantially equivalent to those currently in use in high-income countries.

A European network for virtual microscopy--design, implementation and evaluation of performance

Web-based virtual microscopy has enabled new applications within pathology. Here, we introduce and evaluate a network of academic servers, designed to maximize image accessibility to users from all regions of Europe. Whole-slide imaging was utilized to digitize the entire slide set (n = 154) for the slide seminars of the 21st European Congress of Pathology. The virtual slides were mirrored to five academic servers across Europe using a novel propagation method. Functionality was implemented that automatically selects the fastest server connection in order to optimize the slide-viewing speed ( http://www.webmicroscope.net/ECP2007). Results show that during 6 months of monitoring the uptime of the network was 100%. The average viewing speed with the network was 3.1 Mbit/s, as compared to 1.9 Mbit/s using single servers. A good viewing speed (>2Mbit/s) was observed in 32 of 37 countries (86%), compared to 25 of 37 (68%) using single servers. Our study shows that implementing a virtual microscopy network spanning a large geographical area is technically feasible. By utilizing existing academic networks and cost-minimizing image compression, it is also economically feasible.

How to measure image quality in tissue-based diagnosis (diagnostic surgical pathology)

Background

Automated image analysis, measurements of virtual slides, and open access electronic measurement user systems require standardized image quality assessment in tissue-based diagnosis.

Aims

To describe the theoretical background and the practical experiences in automated image quality estimation of colour images acquired from histological slides.

Theory, material and measurements

Digital images acquired from histological slides should present with textures and objects that permit automated image information analysis. The quality of digitized images can be estimated by spatial independent and local filter operations that investigate in homogenous brightness, low peak to noise ratio (full range of available grey values), maximum gradients, equalized grey value distribution, and existence of grey value thresholds. Transformation of the red-green-blue (RGB) space into the hue-saturation-intensity (HSI) space permits the detection of colour and intensity maxima/minima. The feature distance of the original image to its standardized counterpart is an appropriate measure to quantify the actual image quality. These measures have been applied to a series of H&E stained, fluorescent (DAPI, Texas Red, FITC), and immunohistochemically stained (PAP, DAB) slides. More than 5,000 slides have been measured and partly analyzed in a time series.

Results

Analysis of H&E stained slides revealed low shading corrections (10%) and moderate grey value standardization (10 – 20%) in the majority of cases. Immunohistochemically stained slides displayed greater shading and grey value correction. Fluorescent stained slides are often revealed to high brightness. Images requiring only low standardization corrections possess at least 5 different statistically significant thresholds, which are useful for object segmentation. Fluorescent images of good quality only posses one singular intensity maximum in contrast to good images obtained from H&E stained slides that present with 2 – 3 intensity maxima.

Conclusion

Evaluation of image quality and creation of formally standardized images should be performed prior to automatic analysis of digital images acquired from histological slides. Spatial dependent and local filter operations as well as analysis of the RGB and HSI spaces are appropriate methods to reproduce evaluated formal image quality.

Image standards in tissue-based diagnosis (diagnostic surgical pathology)

Background

Progress in automated image analysis, virtual microscopy, hospital information systems, and interdisciplinary data exchange require image standards to be applied in tissue-based diagnosis.

Aims

To describe the theoretical background, practical experiences and comparable solutions in other medical fields to promote image standards applicable for diagnostic pathology.

Theory and experiences

Images used in tissue-based diagnosis present with pathology – specific characteristics. It seems appropriate to discuss their characteristics and potential standardization in relation to the levels of hierarchy in which they appear. All levels can be divided into legal, medical, and technological properties. Standards applied to the first level include regulations or aims to be fulfilled. In legal properties, they have to regulate features of privacy, image documentation, transmission, and presentation; in medical properties, features of disease – image combination, human – diagnostics, automated information extraction, archive retrieval and access; and in technological properties features of image acquisition, display, formats, transfer speed, safety, and system dynamics. The next lower second level has to implement the prescriptions of the upper one, i.e. describe how they are implemented. Legal aspects should demand secure encryption for privacy of all patient related data, image archives that include all images used for diagnostics for a period of 10 years at minimum, accurate annotations of dates and viewing, and precise hardware and software information. Medical aspects should demand standardized patients' files such as DICOM 3 or HL 7 including history and previous examinations, information of image display hardware and software, of image resolution and fields of view, of relation between sizes of biological objects and image sizes, and of access to archives and retrieval. Technological aspects should deal with image acquisition systems (resolution, colour temperature, focus, brightness, and quality evaluation procedures), display resolution data, implemented image formats, storage, cycle frequency, backup procedures, operation system, and external system accessibility. The lowest third level describes the permitted limits and threshold in detail. At present, an applicable standard including all mentioned features does not exist to our knowledge; some aspects can be taken from radiological standards (PACS, DICOM 3); others require specific solutions or are not covered yet.

Conclusion

The progress in virtual microscopy and application of artificial intelligence (AI) in tissue-based diagnosis demands fast preparation and implementation of an internationally acceptable standard. The described hierarchic order as well as analytic investigation in all potentially necessary aspects and details offers an appropriate tool to specifically determine standardized requirements.

How to implement grid technology in tissue-based diagnosis: diagnostic surgical pathology

BACKGROUND

Tissue-based diagnosis or diagnostic surgical pathology is a highly accurate, sensitive and specific medical diagnostic technique that has expanded rapidly in using both molecular biology and computer technology.

OBJECTIVE

The objective is to analyze the present stage and potential influence of distributed data acquisition, analysis and presentation in tissue-based diagnosis by using recently developed standardized network systems such as grids.

METHODS

Interpretation of medical data is often based upon specialized examination, visual information acquisition and transfer as well as upon data collected from various sources. Efficient and accurate diagnostics require standardized data and transfer modes, which can be provided by a grid environment. The medical requirements, construction of an adequate grid environment, practical experiences in various medical disciplines and potential use in tissue-based diagnosis are described.

CONCLUSIONS

Grid technology is probably a useful tool to meet the conditions of tissue-based diagnosis in the near future, and will probably play a significant role in its further development.

Analysis of morphological variables and arterialization in the differential diagnosis of hepatic nodules in explanted cirrhotic livers

Background

Many terminologies have been given to dysplastic hepatocellular nodules, which are preneoplastic lesions. In 1995, the International Working Party meeting established the nomenclature and morphological criteria for hepatocellular nodular lesions. Nevertheless, an unequivocal differential diagnosis is sometimes difficult, particularly among large regenerative nodules, dysplastic nodules and hepatocellular carcinoma. Angiogenesis is observed during hepatocarcinogenesis and the presence of the isolated arteries may help to discriminate these nodules. The relevance of the International Working Party histological variables and presence of the isolated arteries were analyzed with regard to the diagnosis of large regenerative nodules, low and high grade dysplastic nodules and hepatocellular carcinoma, in order to evaluate which have a real contribution in such diagnoses.

Methods

One hundred and seven nodular hepatocellular lesions over 5 mm (or smaller nodules with a different color) from explanted cirrhotic livers were analyzed and classified following the criteria of the International Working Party. Classifications were as follows: large regenerative nodules, low grade dysplastic nodules, high grade dysplastic nodules and hepatocellular carcinoma. The presence of isolated arteries (not related to the portal tracts or fibrosis) was verified for the nodules.

Results

Among the 107 nodular lesions studied, 17 were classified as large regenerative nodules, 38 as low grade dysplastic nodules, 28 as high grade dysplastic nodules and 24 as hepatocellular carcinoma. The most relevant International Working Party variables in the differential diagnosis of the nodules were cellularity, trabeculae thickness, cytoplasmic staining, nuclear atypia, pseudoacinar pattern, portal tracts, nucleocytoplasmic ratio and mitosis. The isolated arteries, identified by hematoxylin and eosin staining, were important discriminating between two groups: low grade lesions (large regenerative nodules/low grade dysplastic nodules) and high grade lesions (high grade dysplastic nodules/hepatocellular carcinoma) (P < 0.001).

Conclusion

The International Working Party criteria allow for the classification of the majority of hepatocellular nodules. However, other features such as cytoplasmatic tintorial affinity and pseudoacinar pattern may contribute to these diagnoses. The finding of isolated arteries in a nodular lesion should be investigated carefully, since the nodule could be a dysplastic lesion or hepatocellular carcinoma.