Kaposi sarcoma Radu, Oana; Pantanowitz, Liron
Archives of pathology & laboratory medicine (1976)
137, Številka:
2
Journal Article
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Kaposi sarcoma (KS) is a low-grade vascular tumor associated with Kaposi sarcoma herpesvirus/human herpesvirus 8 (KSHV/HHV8) infection. Kaposi sarcoma lesions predominantly present at mucocutaneous ...sites, but may involve all organs and anatomic locations. Recognized epidemiologic-clinical forms of KS include classic, African (endemic), AIDS-associated (epidemic), and iatrogenic KS. New clinical manifestations have been described, such as antiretroviral therapy-related KS regression or flares. Kaposi sarcoma lesions evolve from early (patch stage) macules into plaques (plaque stage) that grow into larger nodules (tumor stage). Newer histologic variants include anaplastic, hyperkeratotic, lymphangioma-like, bullous, telangiectatic, ecchymotic, keloidal, pyogenic granuloma-like, micronodular, intravascular, glomeruloid and pigmented KS, as well as KS with sarcoidlike granulomas and KS with myoid nodules. Latency-associated nuclear antigen (HHV8) is the most specific immunohistochemical marker available to help distinguish KS from its mimics. Since KS remains one of the most common AIDS-defining malignancies, it is important that pathologists be able to recognize KS and its contemporary manifestations.
In light of the recent success of artificial intelligence (AI) in computer vision applications, many researchers and physicians expect that AI would be able to assist in many tasks in digital ...pathology. Although opportunities are both manifest and tangible, there are clearly many challenges that need to be overcome in order to exploit the AI potentials in computational pathology. In this paper, we strive to provide a realistic account of all challenges and opportunities of adopting AI algorithms in digital pathology from both engineering and pathology perspectives.
Context Augmented reality (AR) devices such as the Microsoft HoloLens have not been well used in the medical field. Objective To test the HoloLens for clinical and nonclinical applications in ...pathology. Design A Microsoft HoloLens was tested for virtual annotation during autopsy, viewing 3D gross and microscopic pathology specimens, navigating whole slide images, telepathology, as well as real-time pathology-radiology correlation. Results Pathology residents performing an autopsy wearing the HoloLens were remotely instructed with real-time diagrams, annotations, and voice instruction. 3D-scanned gross pathology specimens could be viewed as holograms and easily manipulated. Telepathology was supported during gross examination and at the time of intraoperative consultation, allowing users to remotely access a pathologist for guidance and to virtually annotate areas of interest on specimens in real-time. The HoloLens permitted radiographs to be coregistered on gross specimens and thereby enhanced locating important pathologic findings. The HoloLens also allowed easy viewing and navigation of whole slide images, using an AR workstation, including multiple coregistered tissue sections facilitating volumetric pathology evaluation. Conclusions The HoloLens is a novel AR tool with multiple clinical and nonclinical applications in pathology. The device was comfortable to wear, easy to use, provided sufficient computing power, and supported high-resolution imaging. It was useful for autopsy, gross and microscopic examination, and ideally suited for digital pathology. Unique applications include remote supervision and annotation, 3D image viewing and manipulation, telepathology in a mixed-reality environment, and real-time pathology-radiology correlation.
With the emergence of digital pathology, searching for similar images in large archives has gained considerable attention. Image retrieval can provide pathologists with unprecedented access to the ...evidence embodied in already diagnosed and treated cases from the past. This paper proposes a search engine specialized for digital pathology, called Yottixel, a portmanteau for “one yotta pixel,” alluding to the big-data nature of histopathology images. The most impressive characteristic of Yottixel is its ability to represent whole slide images (WSIs) in a compact manner. Yottixel can perform millions of searches in real-time with a high search accuracy and low storage profile. Yottixel uses an intelligent indexing algorithm capable of representing WSIs with a mosaic of patches which are then converted into barcodes, called “Bunch of Barcodes” (BoB), the most prominent performance enabler of Yottixel. The performance of the prototype platform is qualitatively tested using 300 WSIs from the University of Pittsburgh Medical Center (UPMC) and 2,020 WSIs from The Cancer Genome Atlas Program (TCGA) provided by the National Cancer Institute. Both datasets amount to more than 4,000,000 patches of 1000 × 1000 pixels. We report three sets of experiments that show that Yottixel can accurately retrieve organs and malignancies, and its semantic ordering shows good agreement with the subjective evaluation of human observers.
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Pulmonary actinomycosis is an uncommon infectious disease. Although the gold standard for diagnosis is histological examination with bacterial culture of lung tissue, cytology samples offer a fast ...and low-cost alternate diagnostic procedure. The cytology literature on this topic is limited to mostly case reports. Therefore, the aim of this study was to review cytological material in a series of patients with a diagnosis of pulmonary actinomycosis to characterize the main cytomorphological findings. Different cytological respiratory samples including sputum smears, bronchoalveolar lavages (BALs), transthoracic or endobronchial fine needle aspiration cytology (FNAC) and cell block preparations were used for retrospective examination. For all cases patient age, gender, symptoms, and radiological chest findings were recorded. A total of 26 cytological respiratory samples (14 sputum smears, 9 FNAC, two BALs) including direct smears and 6 cell blocks from 9 patients were examined. In sputum smears the most remarkable findings were the presence of dark cotton ball masses with projections like spider legs and/or mouse tails (75% of the samples). Sulfur granules were observed in 4 (40%) of the sputum smears and within FNAC cases. Various respiratory cytology samples including sputum smears, FNAC and BALs can reveal cytomorphological findings diagnostic of pulmonary actinomycosis. Characteristic cytological findings compatible with a diagnosis of this infection include cotton ball masses and less frequently sulfur granules.
There is increasing interest in using whole slide imaging (WSI) for diagnostic purposes (primary and/or consultation). An important consideration is whether WSI can safely replace conventional light ...microscopy as the method by which pathologists review histologic sections, cytology slides, and/or hematology slides to render diagnoses. Validation of WSI is crucial to ensure that diagnostic performance based on digitized slides is at least equivalent to that of glass slides and light microscopy. Currently, there are no standard guidelines regarding validation of WSI for diagnostic use.
To recommend validation requirements for WSI systems to be used for diagnostic purposes.
The College of American Pathologists Pathology and Laboratory Quality Center convened a nonvendor panel from North America with expertise in digital pathology to develop these validation recommendations. A literature review was performed in which 767 international publications that met search term requirements were identified. Studies outside the scope of this effort and those related solely to technical elements, education, and image analysis were excluded. A total of 27 publications were graded and underwent data extraction for evidence evaluation. Recommendations were derived from the strength of evidence determined from 23 of these published studies, open comment feedback, and expert panel consensus.
Twelve guideline statements were established to help pathology laboratories validate their own WSI systems intended for clinical use. Validation of the entire WSI system, involving pathologists trained to use the system, should be performed in a manner that emulates the laboratory's actual clinical environment. It is recommended that such a validation study include at least 60 routine cases per application, comparing intraobserver diagnostic concordance between digitized and glass slides viewed at least 2 weeks apart. It is important that the validation process confirm that all material present on a glass slide to be scanned is included in the digital image.
Validation should demonstrate that the WSI system under review produces acceptable digital slides for diagnostic interpretation. The intention of validating WSI systems is to permit the clinical use of this technology in a manner that does not compromise patient care.
The emergence of digital pathology has opened new horizons for histopathology. Artificial intelligence (AI) algorithms are able to operate on digitized slides to assist pathologists with different ...tasks. Whereas AI-involving classification and segmentation methods have obvious benefits for image analysis, image search represents a fundamental shift in computational pathology. Matching the pathology of new patients with already diagnosed and curated cases offers pathologists a new approach to improve diagnostic accuracy through visual inspection of similar cases and computational majority vote for consensus building. In this study, we report the results from searching the largest public repository (The Cancer Genome Atlas, TCGA) of whole-slide images from almost 11,000 patients. We successfully indexed and searched almost 30,000 high-resolution digitized slides constituting 16 terabytes of data comprised of 20 million 1000 × 1000 pixels image patches. The TCGA image database covers 25 anatomic sites and contains 32 cancer subtypes. High-performance storage and GPU power were employed for experimentation. The results were assessed with conservative "majority voting" to build consensus for subtype diagnosis through vertical search and demonstrated high accuracy values for both frozen section slides (e.g., bladder urothelial carcinoma 93%, kidney renal clear cell carcinoma 97%, and ovarian serous cystadenocarcinoma 99%) and permanent histopathology slides (e.g., prostate adenocarcinoma 98%, skin cutaneous melanoma 99%, and thymoma 100%). The key finding of this validation study was that computational consensus appears to be possible for rendering diagnoses if a sufficiently large number of searchable cases are available for each cancer subtype.
The regulatory field for digital pathology (DP) has advanced significantly. A major milestone was accomplished when the FDA allowed the first vendor to market their device for primary diagnostic use ...in the USA and published in the classification order that this device, and substantially equivalent devices of this generic type, should be classified into class II instead of class III as previously proposed. The Digital Pathology Association (DPA) regulatory task force had a major role in the accomplishment of getting the application request for Whole Slide Imaging (WSI) Systems recommended for a de novo. This article reviews the past and emerging regulatory environment of WSI for clinical use in the USA. A WSI system with integrated subsystems is defined in the context ofmedical device regulations. The FDA technical performance assessment guideline is also discussed as well as parameters involved in analytical testing and clinical studies to demonstrate that WSI devices are safe and effective for clinical use.
This review provides a comprehensive overview of the broad clinicopathologic spectrum of cutaneous Kaposi sarcoma (KS) lesions. Variants discussed include: usual KS lesions associated with disease ...progression (i.e. patch, plaque and nodular stage); morphologic subtypes alluded to in the older literature such as anaplastic and telangiectatic KS, as well as several lymphedematous variants; and numerous recently described variants including hyperkeratotic, keloidal, micronodular, pyogenic granuloma-like, ecchymotic, and intravascular KS. Involuting lesions as a result of treatment related regression are also presented.
There is high demand to develop computer-assisted diagnostic tools to evaluate prostate core needle biopsies (CNBs), but little clinical validation and a lack of clinical deployment of such tools. We ...report here on a blinded clinical validation study and deployment of an artificial intelligence (AI)-based algorithm in a pathology laboratory for routine clinical use to aid prostate diagnosis.
An AI-based algorithm was developed using haematoxylin and eosin (H&E)-stained slides of prostate CNBs digitised with a Philips scanner, which were divided into training (1 357 480 image patches from 549 H&E-stained slides) and internal test (2501 H&E-stained slides) datasets. The algorithm provided slide-level scores for probability of cancer, Gleason score 7–10 (vs Gleason score 6 or atypical small acinar proliferation ASAP), Gleason pattern 5, and perineural invasion and calculation of cancer percentage present in CNB material. The algorithm was subsequently validated on an external dataset of 100 consecutive cases (1627 H&E-stained slides) digitised on an Aperio AT2 scanner. In addition, the AI tool was implemented in a pathology laboratory within routine clinical workflow as a second read system to review all prostate CNBs. Algorithm performance was assessed with area under the receiver operating characteristic curve (AUC), specificity, and sensitivity, as well as Pearson's correlation coefficient (Pearson's r) for cancer percentage.
The algorithm achieved an AUC of 0·997 (95% CI 0·995 to 0·998) for cancer detection in the internal test set and 0·991 (0·979 to 1·00) in the external validation set. The AUC for distinguishing between a low-grade (Gleason score 6 or ASAP) and high-grade (Gleason score 7–10) cancer diagnosis was 0·941 (0·905 to 0·977) and the AUC for detecting Gleason pattern 5 was 0·971 (0·943 to 0·998) in the external validation set. Cancer percentage calculated by pathologists and the algorithm showed good agreement (r=0·882, 95% CI 0·834 to 0·915; p<0·0001) with a mean bias of −4·14% (−6·36 to −1·91). The algorithm achieved an AUC of 0·957 (0·930 to 0·985) for perineural invasion. In routine practice, the algorithm was used to assess 11 429 H&E-stained slides pertaining to 941 cases leading to 90 Gleason score 7–10 alerts and 560 cancer alerts. 51 (9%) cancer alerts led to additional cuts or stains being ordered, two (4%) of which led to a third opinion request. We report on the first case of missed cancer that was detected by the algorithm.
This study reports the successful development, external clinical validation, and deployment in clinical practice of an AI-based algorithm to accurately detect, grade, and evaluate clinically relevant findings in digitised slides of prostate CNBs.
Ibex Medical Analytics.
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