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Journal Cover Journal of Pathology Informatics
  Number of Followers: 1  
    
  This is an Open Access Journal Open Access journal
   ISSN (Print) 2153-3539 - ISSN (Online) 2153-3539
   Published by Medknow Publishers Homepage  [429 journals]
  • Enabling histopathological annotations on immunofluorescent images through
           virtualization of hematoxylin and eosin

    • Authors: Amal Lahiani, Eldad Klaiman, Oliver Grimm
      Pages: 1 - 1
      Abstract: Amal Lahiani, Eldad Klaiman, Oliver Grimm
      Journal of Pathology Informatics 2018 9(1):1-1
      Context: Medical diagnosis and clinical decisions rely heavily on the histopathological evaluation of tissue samples, especially in oncology. Historically, classical histopathology has been the gold standard for tissue evaluation and assessment by pathologists. The most widely and commonly used dyes in histopathology are hematoxylin and eosin (H&E) as most malignancies diagnosis is largely based on this protocol. H&E staining has been used for more than a century to identify tissue characteristics and structures morphologies that are needed for tumor diagnosis. In many cases, as tissue is scarce in clinical studies, fluorescence imaging is necessary to allow staining of the same specimen with multiple biomarkers simultaneously. Since fluorescence imaging is a relatively new technology in the pathology landscape, histopathologists are not used to or trained in annotating or interpreting these images. Aims, Settings and Design: To allow pathologists to annotate these images without the need for additional training, we designed an algorithm for the conversion of fluorescence images to brightfield H&E images. Subjects and Methods: In this algorithm, we use fluorescent nuclei staining to reproduce the hematoxylin information and natural tissue autofluorescence to reproduce the eosin information avoiding the necessity to specifically stain the proteins or intracellular structures with an additional fluorescence stain. Statistical Analysis Used: Our method is based on optimizing a transform function from fluorescence to H&E images using least mean square optimization. Results: It results in high quality virtual H&E digital images that can easily and efficiently be analyzed by pathologists. We validated our results with pathologists by making them annotate tumor in real and virtual H&E whole slide images and we obtained promising results. Conclusions: Hence, we provide a solution that enables pathologists to assess tissue and annotate specific structures based on multiplexed fluorescence images.
      Citation: Journal of Pathology Informatics 2018 9(1):1-1
      PubDate: Wed,14 Feb 2018
      DOI: 10.4103/jpi.jpi_61_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • A review on the applications of crowdsourcing in human pathology

    • Authors: Roshanak Alialy, Sasan Tavakkol, Elham Tavakkol, Amir Ghorbani-Aghbologhi, Alireza Ghaffarieh, Seon Ho Kim, Cyrus Shahabi
      Pages: 2 - 2
      Abstract: Roshanak Alialy, Sasan Tavakkol, Elham Tavakkol, Amir Ghorbani-Aghbologhi, Alireza Ghaffarieh, Seon Ho Kim, Cyrus Shahabi
      Journal of Pathology Informatics 2018 9(1):2-2
      The advent of the digital pathology has introduced new avenues of diagnostic medicine. Among them, crowdsourcing has attracted researchers' attention in the recent years, allowing them to engage thousands of untrained individuals in research and diagnosis. While there exist several articles in this regard, prior works have not collectively documented them. We, therefore, aim to review the applications of crowdsourcing in human pathology in a semi-systematic manner. We first, introduce a novel method to do a systematic search of the literature. Utilizing this method, we, then, collect hundreds of articles and screen them against a predefined set of criteria. Furthermore, we crowdsource part of the screening process, to examine another potential application of crowdsourcing. Finally, we review the selected articles and characterize the prior uses of crowdsourcing in pathology.
      Citation: Journal of Pathology Informatics 2018 9(1):2-2
      PubDate: Wed,14 Feb 2018
      DOI: 10.4103/jpi.jpi_65_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • Commentary: Whole-slide Images – Good enough for primary
           diagnosis?

    • Authors: Thomas W Bauer
      Pages: 3 - 3
      Abstract: Thomas W Bauer
      Journal of Pathology Informatics 2018 9(1):3-3

      Citation: Journal of Pathology Informatics 2018 9(1):3-3
      PubDate: Wed,14 Feb 2018
      DOI: 10.4103/jpi.jpi_72_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • Initial Assessments of E-learning modules in cytotechnology education

    • Authors: Maheswari S Mukherjee, Amber D Donnelly
      Pages: 4 - 4
      Abstract: Maheswari S Mukherjee, Amber D Donnelly
      Journal of Pathology Informatics 2018 9(1):4-4
      Background: Nine E-learning modules (ELMs) were developed in our program using Articulate software. This study assessed our cytotechnology (CT) students' perceptions on the content of the ELMs, and the perceived influence of the ELMs on students' performance during clinical rotations. Subjects and Methods: All CT students watched nine ELMs before the related classroom lecture and group discussion. Following that, students completed nine preclinical rotation surveys. After their clinical rotations, students completed nine postclinical rotation surveys. Results: Statements on the content of the ELMs regarding the quality of the video and audio, duration, navigation, and the materials presented, received positive responses from the majority of the students. While there were a few disagreements and neutral responses, most of the students responded positively saying that the ELMs better prepared them for their role, as well as helped them to better perform their roles during the clinical rotation. The majority of the students recommended developing more EMLs for cytology courses in the future Conclusions: This study has given hope that the ELMs have potential to enhance our online curriculum and benefit students, within the United States and internationally, who have no easy access to cytology clinical laboratories for hands-on training.
      Citation: Journal of Pathology Informatics 2018 9(1):4-4
      PubDate: Wed,14 Feb 2018
      DOI: 10.4103/jpi.jpi_62_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • Deep Learning Nuclei Detection in Digitized Histology Images by
           Superpixels

    • Authors: Sudhir Sornapudi, Ronald Joe Stanley, William V Stoecker, Haidar Almubarak, Rodney Long, Sameer Antani, George Thoma, Rosemary Zuna, Shelliane R Frazier
      Pages: 5 - 5
      Abstract: Sudhir Sornapudi, Ronald Joe Stanley, William V Stoecker, Haidar Almubarak, Rodney Long, Sameer Antani, George Thoma, Rosemary Zuna, Shelliane R Frazier
      Journal of Pathology Informatics 2018 9(1):5-5
      Background: Advances in image analysis and computational techniques have facilitated automatic detection of critical features in histopathology images. Detection of nuclei is critical for squamous epithelium cervical intraepithelial neoplasia (CIN) classification into normal, CIN1, CIN2, and CIN3 grades. Methods: In this study, a deep learning (DL)-based nuclei segmentation approach is investigated based on gathering localized information through the generation of superpixels using a simple linear iterative clustering algorithm and training with a convolutional neural network. Results: The proposed approach was evaluated on a dataset of 133 digitized histology images and achieved an overall nuclei detection (object-based) accuracy of 95.97%, with demonstrated improvement over imaging-based and clustering-based benchmark techniques. Conclusions: The proposed DL-based nuclei segmentation Method with superpixel analysis has shown improved segmentation results in comparison to state-of-the-art methods.
      Citation: Journal of Pathology Informatics 2018 9(1):5-5
      PubDate: Mon,5 Mar 2018
      DOI: 10.4103/jpi.jpi_74_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • Digital Imaging and Communications in Medicine Whole Slide Imaging
           Connectathon at Digital Pathology Association Pathology Visions 2017

    • Authors: David Clunie, Dan Hosseinzadeh, Mikael Wintell, David De Mena, Nieves Lajara, Marcial Garcia-Rojo, Gloria Bueno, Kiran Saligrama, Aaron Stearrett, David Toomey, Esther Abels, Frank Van Apeldoorn, Stephane Langevin, Sean Nichols, Joachim Schmid, Uwe Horchner, Bruce Beckwith, Anil Parwani, Liron Pantanowitz
      Pages: 6 - 6
      Abstract: David Clunie, Dan Hosseinzadeh, Mikael Wintell, David De Mena, Nieves Lajara, Marcial Garcia-Rojo, Gloria Bueno, Kiran Saligrama, Aaron Stearrett, David Toomey, Esther Abels, Frank Van Apeldoorn, Stephane Langevin, Sean Nichols, Joachim Schmid, Uwe Horchner, Bruce Beckwith, Anil Parwani, Liron Pantanowitz
      Journal of Pathology Informatics 2018 9(1):6-6
      As digital pathology systems for clinical diagnostic work applications become mainstream, interoperability between these systems from different vendors becomes critical. For the first time, multiple digital pathology vendors have publicly revealed the use of the digital imaging and communications in medicine (DICOM) standard file format and network protocol to communicate between separate whole slide acquisition, storage, and viewing components. Note the use of DICOM for clinical diagnostic applications is still to be validated in the United States. The successful demonstration shows that the DICOM standard is fundamentally sound, though many lessons were learned. These lessons will be incorporated as incremental improvements in the standard, provide more detailed profiles to constrain variation for specific use cases, and offer educational material for implementers. Future Connectathon events will expand the scope to include more devices and vendors, as well as more ambitious use cases including laboratory information system integration and annotation for image analysis, as well as more geographic diversity. Users should request DICOM features in all purchases and contracts. It is anticipated that the growth of DICOM-compliant manufacturers will likely also ease DICOM for pathology becoming a recognized standard and as such the regulatory pathway for digital pathology products.
      Citation: Journal of Pathology Informatics 2018 9(1):6-6
      PubDate: Mon,5 Mar 2018
      DOI: 10.4103/jpi.jpi_1_18
      Issue No: Vol. 9, No. 1 (2018)
       
  • The case for an entropic simian in your laboratory: The case for
           laboratory information system failure scenario testing in the live
           production environment

    • Authors: Christopher L Williams, David S McClintock, Ulysses G J Balis
      Pages: 7 - 7
      Abstract: Christopher L Williams, David S McClintock, Ulysses G J Balis
      Journal of Pathology Informatics 2018 9(1):7-7

      Citation: Journal of Pathology Informatics 2018 9(1):7-7
      PubDate: Mon,2 Apr 2018
      DOI: 10.4103/jpi.jpi_96_16
      Issue No: Vol. 9, No. 1 (2018)
       
  • Challenges in communication from referring clinicians to pathologists in
           the electronic health record era

    • Authors: Andrea Lynne Barbieri, Oluwole Fadare, Linda Fan, Hardeep Singh, Vinita Parkash
      Pages: 8 - 8
      Abstract: Andrea Lynne Barbieri, Oluwole Fadare, Linda Fan, Hardeep Singh, Vinita Parkash
      Journal of Pathology Informatics 2018 9(1):8-8
      We report on the role played by electronic health record inbox messages (EHRmsg) in a safety event involving pathology. Evolving socio-cultural norms led to the coopting of EHRmsg for alternate use and oversight of a clinician to pathologist request. We retrospectively examined EHR inbox messages to pathologists over a 3 month block. 36 messages from 22 pathologists were assessed. 26 pertained to patient care including requests for report corrections and additional testing. 88% of requests had gone unaddressed. Clinicians assumed that pathologists used EHRmsg as clinical care team members, however, pathologists rarely did. Communication gaps exist between primary clinicians and pathologists in the EHR era and they have potential to result in patient harm. Different sociocultural norms and practice patterns between specialties underlie some of the breakdowns. Health information technology implementation needs to proactively look for new sociotechnical failure modes to avoid patient harm from communication lapses.
      Citation: Journal of Pathology Informatics 2018 9(1):8-8
      PubDate: Mon,2 Apr 2018
      DOI: 10.4103/jpi.jpi_70_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • Electronic p-Chip-based system for identification of glass slides and
           tissue cassettes in histopathology laboratories

    • Authors: Wlodek Mandecki, Jay Qian, Katie Gedzberg, Maryanne Gruda, Efrain Frank Rodriguez, Leslie Nesbitt, Michael Riben
      Pages: 9 - 9
      Abstract: Wlodek Mandecki, Jay Qian, Katie Gedzberg, Maryanne Gruda, Efrain Frank Rodriguez, Leslie Nesbitt, Michael Riben
      Journal of Pathology Informatics 2018 9(1):9-9
      Background: The tagging system is based on a small, electronic, wireless, laser-light-activated microtransponder named “p-Chip.” The p-Chip is a silicon integrated circuit, the size of which is 600 μm × 600 μm × 100 μm. Each p-Chip contains a unique identification code stored within its electronic memory that can be retrieved with a custom reader. These features allow the p-Chip to be used as an unobtrusive and scarcely noticeable ID tag on glass slides and tissue cassettes. Methods: The system is comprised of p-Chip-tagged sample carriers, a dedicated benchtop p-Chip ID reader that can accommodate both objects, and an additional reader (the Wand), with an adapter for reading IDs of glass slides stored vertically in drawers. On slides, p-Chips are attached with adhesive to the center of the short edge, and on cassettes – embedded directly into the plastic. ID readout is performed by bringing the reader to the proximity of the chip. Standard histopathology laboratory protocols were used for testing. Results: Very good ID reading efficiency was observed for both glass slides and cassettes. When processed slides are stored in vertical filing drawers, p-Chips remain readable without the need to remove them from the storage location, thereby improving the speed of searches in collections. On the cassettes, the ID continues to be readable through a thin layer of paraffin. Both slides and tissue cassettes can be read with the same reader, reducing the need for redundant equipment. Conclusions: The p-Chip is stable to all chemical challenges commonly used in the histopathology laboratory, tolerates temperature extremes, and remains durable in long-term storage. The technology is compatible with laboratory information management systems software systems. The p-Chip system is very well suited for identification of glass slides and cassettes in the histopathology laboratory.
      Citation: Journal of Pathology Informatics 2018 9(1):9-9
      PubDate: Mon,2 Apr 2018
      DOI: 10.4103/jpi.jpi_64_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • Implementation of a mobile clinical decision support application to
           augment local antimicrobial stewardship

    • Authors: Brian M Hoff, Diana C Ford, Dilek Ince, Erika J Ernst, Daniel J Livorsi, Brett H Heintz, Vincent Masse, Michael J Brownlee, Bradley A Ford
      Pages: 10 - 10
      Abstract: Brian M Hoff, Diana C Ford, Dilek Ince, Erika J Ernst, Daniel J Livorsi, Brett H Heintz, Vincent Masse, Michael J Brownlee, Bradley A Ford
      Journal of Pathology Informatics 2018 9(1):10-10
      Background: Medical applications for mobile devices allow clinicians to leverage microbiological data and standardized guidelines to treat patients with infectious diseases. We report the implementation of a mobile clinical decision support (CDS) application to augment local antimicrobial stewardship. Methods: We detail the implementation of our mobile CDS application over 20 months. Application utilization data were collected and evaluated using descriptive statistics to quantify the impact of our implementation. Results: Project initiation focused on engaging key stakeholders, developing a business case, and selecting a mobile platform. The preimplementation phase included content development, creation of a pathway for content approval within the hospital committee structure, engaging clinical leaders, and formatting the first version of the guide. Implementation involved a media campaign, staff education, and integration within the electronic medical record and hospital mobile devices. The postimplementation phase required ongoing quality improvement, revision of outdated content, and repeated staff education. The evaluation phase included a guide utilization analysis, reporting to hospital leadership, and sustainability and innovation planning. The mobile application was downloaded 3056 times and accessed 9259 times during the study period. The companion web viewer was accessed 8214 times. Conclusions: Successful implementation of a customizable mobile CDS tool enabled our team to expand beyond microbiological data to clinical diagnosis, treatment, and antimicrobial stewardship, broadening our influence on antimicrobial prescribing and incorporating utilization data to inspire new quality and safety initiatives. Further studies are needed to assess the impact on antimicrobial utilization, infection control measures, and patient care outcomes.
      Citation: Journal of Pathology Informatics 2018 9(1):10-10
      PubDate: Mon,2 Apr 2018
      DOI: 10.4103/jpi.jpi_77_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • Erratum: Preconceived stakeholders' attitude toward telepathology:
           Implications for successful implementation

    • Pages: 11 - 11
      Abstract:
      Journal of Pathology Informatics 2018 9(1):11-11

      Citation: Journal of Pathology Informatics 2018 9(1):11-11
      PubDate: Mon,2 Apr 2018
      DOI: 10.4103/2153-3539.228968
      Issue No: Vol. 9, No. 1 (2018)
       
  • Psychological aspects of utilizing telecytology for rapid on-site adequacy
           assessments

    • Authors: Aparna Mahajan, Suzanne Selvaggi, Liron Pantanowitz
      Pages: 12 - 12
      Abstract: Aparna Mahajan, Suzanne Selvaggi, Liron Pantanowitz
      Journal of Pathology Informatics 2018 9(1):12-12
      Rapid On-Site Evaluation (ROSE) has been well documented in its ability to improve the diagnostic yield and accuracy of fine needle aspirations across many sites, resulting in better quality of patient management and a simultaneous reduction in treatment costs. Telecytology makes it possible for cytology laboratories to offer ROSE in a cost effective manner, whilst employing only a small number of trained cytopathologists to cover many sites from a single connected location. However, the adoption of telecytology for ROSE has been lackluster. We believe that this reluctance is not only due to barriers such as technology limitations and financial obstacles, but also due to overlooked psychological factors. This article discusses the unaddressed psychological considerations of telecytology for ROSE.
      Citation: Journal of Pathology Informatics 2018 9(1):12-12
      PubDate: Mon,9 Apr 2018
      DOI: 10.4103/jpi.jpi_2_18
      Issue No: Vol. 9, No. 1 (2018)
       
  • Constant quest for quality: Digital cytopathology

    • Authors: Simone L Van Es, Janelle Greaves, Stephanie Gay, Jennifer Ross, Derek Holzhauser, Tony Badrick
      Pages: 13 - 13
      Abstract: Simone L Van Es, Janelle Greaves, Stephanie Gay, Jennifer Ross, Derek Holzhauser, Tony Badrick
      Journal of Pathology Informatics 2018 9(1):13-13
      Background: Special consideration should be given when creating and selecting cytopathology specimens for digitization to maximize quality. Advances in scanning and viewing technology can also improve whole-slide imaging (WSI) output quality. Methods: Accumulated laboratory experience with digitization of glass cytopathology slides was collected. Results: This paper describes characteristics of a cytopathology glass slide that can reduce quality on resulting WSI. Important points in the glass cytopathology slide selection process, preparation, scanning, and WSI-editing process that will maximize the quality of the resulting acquired digital image are covered. The paper outlines scanning solutions which have potential to predict issues with a glass cytopathology slide before image acquisition, allowing for adjustment of the scanning approach. WSI viewing solutions that better simulate the traditional microscope experience are also discussed. Conclusion: In addition to taking advantage of technical advances, practical steps can taken to maximize quality of cytopathology WSI.
      Citation: Journal of Pathology Informatics 2018 9(1):13-13
      PubDate: Mon,9 Apr 2018
      DOI: 10.4103/jpi.jpi_6_18
      Issue No: Vol. 9, No. 1 (2018)
       
  • Career paths of pathology informatics fellowship alumni

    • Authors: Joseph W Rudolf, Christopher A Garcia, Matthew G Hanna, Christopher L Williams, Ulysses G Balis, Liron Pantanowitz, J Mark Tuthill, John R Gilbertson
      Pages: 14 - 14
      Abstract: Joseph W Rudolf, Christopher A Garcia, Matthew G Hanna, Christopher L Williams, Ulysses G Balis, Liron Pantanowitz, J Mark Tuthill, John R Gilbertson
      Journal of Pathology Informatics 2018 9(1):14-14
      Background: The alumni of today's Pathology Informatics and Clinical Informatics fellowships fill diverse roles in academia, large health systems, and industry. The evolving training tracks and curriculum of Pathology Informatics fellowships have been well documented. However, less attention has been given to the posttraining experiences of graduates from informatics training programs. Here, we examine the career paths of subspecialty fellowship-trained pathology informaticians. Methods: Alumni from four Pathology Informatics fellowship training programs were contacted for their voluntary participation in the study. We analyzed various components of training, and the subsequent career paths of Pathology Informatics fellowship alumni using data extracted from alumni provided curriculum vitae. Results: Twenty-three out of twenty-seven alumni contacted contributed to the study. A majority had completed undergraduate study in science, technology, engineering, and math fields and combined track training in anatomic and clinical pathology. Approximately 30% (7/23) completed residency in a program with an in-house Pathology Informatics fellowship. Most completed additional fellowships (15/23) and many also completed advanced degrees (10/23). Common primary posttraining appointments included chief medical informatics officer (3/23), director of Pathology Informatics (10/23), informatics program director (2/23), and various roles in industry (3/23). Many alumni also provide clinical care in addition to their informatics roles (14/23). Pathology Informatics alumni serve on a variety of institutional committees, participate in national informatics organizations, contribute widely to scientific literature, and more than half (13/23) have obtained subspecialty certification in Clinical Informatics to date. Conclusions: Our analysis highlights several interesting phenomena related to the training and career trajectory of Pathology Informatics fellowship alumni. We note the long training track alumni complete in preparation for their careers. We believe flexible training pathways combining informatics and clinical training may help to alleviate the burden. We highlight the importance of in-house Pathology Informatics fellowships in promoting interest in informatics among residents. We also observe the many important leadership roles in academia, large community health systems, and industry available to early career alumni and believe this reflects a strong market for formally trained informaticians. We hope this analysis will be useful as we continue to develop the informatics fellowships to meet the future needs of our trainees and discipline.
      Citation: Journal of Pathology Informatics 2018 9(1):14-14
      PubDate: Mon,9 Apr 2018
      DOI: 10.4103/jpi.jpi_66_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • Patient portal access to diagnostic test results

    • Authors: Beuy Joob, Viroj Wiwanitkit
      Pages: 15 - 15
      Abstract: Beuy Joob, Viroj Wiwanitkit
      Journal of Pathology Informatics 2018 9(1):15-15

      Citation: Journal of Pathology Informatics 2018 9(1):15-15
      PubDate: Fri,20 Apr 2018
      DOI: 10.4103/jpi.jpi_13_18
      Issue No: Vol. 9, No. 1 (2018)
       
  • A method for the interpretation of flow cytometry data using genetic
           algorithms

    • Authors: Cesar Angeletti
      Pages: 16 - 16
      Abstract: Cesar Angeletti
      Journal of Pathology Informatics 2018 9(1):16-16
      Background: Flow cytometry analysis is the method of choice for the differential diagnosis of hematologic disorders. It is typically performed by a trained hematopathologist through visual examination of bidimensional plots, making the analysis time-consuming and sometimes too subjective. Here, a pilot study applying genetic algorithms to flow cytometry data from normal and acute myeloid leukemia subjects is described. Subjects and Methods: Initially, Flow Cytometry Standard files from 316 normal and 43 acute myeloid leukemia subjects were transformed into multidimensional FITS image metafiles. Training was performed through introduction of FITS metafiles from 4 normal and 4 acute myeloid leukemia in the artificial intelligence system. Results: Two mathematical algorithms termed 018330 and 025886 were generated. When tested against a cohort of 312 normal and 39 acute myeloid leukemia subjects, both algorithms combined showed high discriminatory power with a receiver operating characteristic (ROC) curve of 0.912. Conclusions: The present results suggest that machine learning systems hold a great promise in the interpretation of hematological flow cytometry data.
      Citation: Journal of Pathology Informatics 2018 9(1):16-16
      PubDate: Fri,20 Apr 2018
      DOI: 10.4103/jpi.jpi_76_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • Convolutional deep belief network with feature encoding for classification
           of neuroblastoma histological images

    • Authors: Soheila Gheisari, Daniel R Catchpoole, Amanda Charlton, Paul J Kennedy
      Pages: 17 - 17
      Abstract: Soheila Gheisari, Daniel R Catchpoole, Amanda Charlton, Paul J Kennedy
      Journal of Pathology Informatics 2018 9(1):17-17
      Background: Neuroblastoma is the most common extracranial solid tumor in children younger than 5 years old. Optimal management of neuroblastic tumors depends on many factors including histopathological classification. The gold standard for classification of neuroblastoma histological images is visual microscopic assessment. In this study, we propose and evaluate a deep learning approach to classify high-resolution digital images of neuroblastoma histology into five different classes determined by the Shimada classification. Subjects and Methods: We apply a combination of convolutional deep belief network (CDBN) with feature encoding algorithm that automatically classifies digital images of neuroblastoma histology into five different classes. We design a three-layer CDBN to extract high-level features from neuroblastoma histological images and combine with a feature encoding model to extract features that are highly discriminative in the classification task. The extracted features are classified into five different classes using a support vector machine classifier. Data: We constructed a dataset of 1043 neuroblastoma histological images derived from Aperio scanner from 125 patients representing different classes of neuroblastoma tumors. Results: The weighted average F-measure of 86.01% was obtained from the selected high-level features, outperforming state-of-the-art methods. Conclusion: The proposed computer-aided classification system, which uses the combination of deep architecture and feature encoding to learn high-level features, is highly effective in the classification of neuroblastoma histological images.
      Citation: Journal of Pathology Informatics 2018 9(1):17-17
      PubDate: Wed,2 May 2018
      DOI: 10.4103/jpi.jpi_73_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • Can text-search methods of pathology reports accurately identify patients
           with rectal cancer in large administrative databases?

    • Authors: Reilly P Musselman, Deanna Rothwell, Rebecca C Auer, Husein Moloo, Robin P Boushey, Carl van Walraven
      Pages: 18 - 18
      Abstract: Reilly P Musselman, Deanna Rothwell, Rebecca C Auer, Husein Moloo, Robin P Boushey, Carl van Walraven
      Journal of Pathology Informatics 2018 9(1):18-18
      Background: The aim of this study is to derive and to validate a cohort of rectal cancer surgical patients within administrative datasets using text-search analysis of pathology reports. Materials and Methods: A text-search algorithm was developed and validated on pathology reports from 694 known rectal cancers, 1000 known colon cancers, and 1000 noncolorectal specimens. The algorithm was applied to all pathology reports available within the Ottawa Hospital Data Warehouse from 1996 to 2010. Identified pathology reports were validated as rectal cancer specimens through manual chart review. Sensitivity, specificity, and positive predictive value (PPV) of the text-search methodology were calculated. Results: In the derivation cohort of pathology reports (n = 2694), the text-search algorithm had a sensitivity and specificity of 100% and 98.6%, respectively. When this algorithm was applied to all pathology reports from 1996 to 2010 (n = 284,032), 5588 pathology reports were identified as consistent with rectal cancer. Medical record review determined that 4550 patients did not have rectal cancer, leaving a final cohort of 1038 rectal cancer patients. Sensitivity and specificity of the text-search algorithm were 100% and 98.4%, respectively. PPV of the algorithm was 18.6%. Conclusions: Text-search methodology is a feasible way to identify all rectal cancer surgery patients through administrative datasets with high sensitivity and specificity. However, in the presence of a low pretest probability, text-search methods must be combined with a validation method, such as manual chart review, to be a viable approach.
      Citation: Journal of Pathology Informatics 2018 9(1):18-18
      PubDate: Wed,2 May 2018
      DOI: 10.4103/jpi.jpi_71_17
      Issue No: Vol. 9, No. 1 (2018)
       
  • Utilization of open source technology to create cost-effective microscope
           camera systems for teaching

    • Authors: Anil Reddy Konduru, Balasaheb R Yelikar, KV Sathyashree, Ankur Kumar
      Pages: 19 - 19
      Abstract: Anil Reddy Konduru, Balasaheb R Yelikar, KV Sathyashree, Ankur Kumar
      Journal of Pathology Informatics 2018 9(1):19-19
      Background: Open source technologies and mobile innovations have radically changed the way people interact with technology. These innovations and advancements have been used across various disciplines and already have a significant impact. Microscopy, with focus on visually appealing contrasting colors for better appreciation of morphology, forms the core of the disciplines such as Pathology, microbiology, and anatomy. Here, learning happens with the aid of multi-head microscopes and digital camera systems for teaching larger groups and in organizing interactive sessions for students or faculty of other departments. Methods: The cost of the original equipment manufacturer (OEM) camera systems in bringing this useful technology at all the locations is a limiting factor. To avoid this, we have used the low-cost technologies like Raspberry Pi, Mobile high definition link and 3D printing for adapters to create portable camera systems. Results: Adopting these open source technologies enabled us to convert any binocular or trinocular microscope be connected to a projector or HD television at a fraction of the cost of the OEM camera systems with comparable quality. Conclusion: These systems, in addition to being cost-effective, have also provided the added advantage of portability, thus providing the much-needed flexibility at various teaching locations.
      Citation: Journal of Pathology Informatics 2018 9(1):19-19
      PubDate: Fri,25 May 2018
      DOI: 10.4103/jpi.jpi_15_18
      Issue No: Vol. 9, No. 1 (2018)
       
  • Optimized JPEG 2000 compression for efficient storage of histopathological
           whole-Slide images

    • Authors: Henrik Helin, Teemu Tolonen, Onni Ylinen, Petteri Tolonen, Juha Näpänkangas, Jorma Isola
      Pages: 20 - 20
      Abstract: Henrik Helin, Teemu Tolonen, Onni Ylinen, Petteri Tolonen, Juha Näpänkangas, Jorma Isola
      Journal of Pathology Informatics 2018 9(1):20-20
      Background: Whole slide images (WSIs, digitized histopathology glass slides) are large data files whose long-term storage remains a significant cost for pathology departments. Currently used WSI formats are based on lossy image compression alogrithms, either using JPEG or its more efficient successor JPEG 2000. While the advantages of the JPEG 2000 algorithm (JP2) are commonly recognized, its compression parameters have not been fully optimized for pathology WSIs. Methods: We defined an optimized parametrization for JPEG 2000 image compression, designated JP2-WSI, to be used specifically with histopathological WSIs. Our parametrization is based on allowing a very high degree of compression on the background part of the WSI while using a conventional amount of compression on the tissue-containing part of the image, resulting in high overall compression ratios. Results: When comparing the compression power of JP2-WSI to the commonly used fixed 35:1 compression ratio JPEG 2000 and the default image formats of proprietary Aperio, Hamamatsu, and 3DHISTECH scanners, JP2-WSI produced the smallest file sizes and highest overall compression ratios for all 17 slides tested. The image quality, as judged by visual inspection and peak signal-to-noise ratio (PSNR) measurements, was equal to or better than the compared image formats. The average file size by JP2-WSI amounted to 15, 9, and 16 percent, respectively, of the file sizes of the three commercial scanner vendors' proprietary file formats (3DHISTECH MRXS, Aperio SVS, and Hamamatsu NDPI). In comparison to the commonly used 35:1 compressed JPEG 2000, JP2-WSI was three times more efficient. Conclusions: JP2-WSI allows very efficient and cost-effective data compression for whole slide images without loss of image information required for histopathological diagnosis.
      Citation: Journal of Pathology Informatics 2018 9(1):20-20
      PubDate: Fri,25 May 2018
      DOI: 10.4103/jpi.jpi_69_17
      Issue No: Vol. 9, No. 1 (2018)
       
 
 
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