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Journal Cover Journal of Pathology Informatics
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  This is an Open Access Journal Open Access journal
   ISSN (Print) 2153-3539 - ISSN (Online) 2153-3539
   Published by Medknow Publishers Homepage  [355 journals]
  • Classifications of multispectral colorectal cancer tissues using
           convolution neural network

    • Authors: Hawraa Haj-Hassan, Ahmad Chaddad, Youssef Harkouss, Christian Desrosiers, Matthew Toews, Camel Tanougast
      Pages: 1 - 1
      Abstract: Hawraa Haj-Hassan, Ahmad Chaddad, Youssef Harkouss, Christian Desrosiers, Matthew Toews, Camel Tanougast
      Journal of Pathology Informatics 2017 8(1):1-1
      Background: Colorectal cancer (CRC) is the third most common cancer among men and women. Its diagnosis in early stages, typically done through the analysis of colon biopsy images, can greatly improve the chances of a successful treatment. This paper proposes to use convolution neural networks (CNNs) to predict three tissue types related to the progression of CRC: benign hyperplasia (BH), intraepithelial neoplasia (IN), and carcinoma (Ca). Methods: Multispectral biopsy images of thirty CRC patients were retrospectively analyzed. Images of tissue samples were divided into three groups, based on their type (10 BH, 10 IN, and 10 Ca). An active contour model was used to segment image regions containing pathological tissues. Tissue samples were classified using a CNN containing convolution, max-pooling, and fully-connected layers. Available tissue samples were split into a training set, for learning the CNN parameters, and test set, for evaluating its performance. Results: An accuracy of 99.17% was obtained from segmented image regions, outperforming existing approaches based on traditional feature extraction, and classification techniques. Conclusions: Experimental results demonstrate the effectiveness of CNN for the classification of CRC tissue types, in particular when using presegmented regions of interest.
      Citation: Journal of Pathology Informatics 2017 8(1):1-1
      PubDate: Tue,28 Feb 2017
      DOI: 10.4103/jpi.jpi_47_16
      Issue No: Vol. 8, No. 1 (2017)
       
  • Computer science, biology and biomedical informatics academy: outcomes
           from 5 years of immersing high-school students into informatics research

    • Authors: Andrew J King, Arielle M Fisher, Michael J Becich, David N Boone
      Pages: 2 - 2
      Abstract: Andrew J King, Arielle M Fisher, Michael J Becich, David N Boone
      Journal of Pathology Informatics 2017 8(1):2-2
      The University of Pittsburgh's Department of Biomedical Informatics and Division of Pathology Informatics created a Science, Technology, Engineering, and Mathematics (STEM) pipeline in 2011 dedicated to providing cutting-edge informatics research and career preparatory experiences to a diverse group of highly motivated high-school students. In this third editorial installment describing the program, we provide a brief overview of the pipeline, report on achievements of the past scholars, and present results from self-reported assessments by the 2015 cohort of scholars. The pipeline continues to expand with the 2015 addition of the innovation internship, and the introduction of a program in 2016 aimed at offering first-time research experiences to undergraduates who are underrepresented in pathology and biomedical informatics. Achievements of program scholars include authorship of journal articles, symposium and summit presentations, and attendance at top 25 universities. All of our alumni matriculated into higher education and 90% remain in STEM majors. The 2015 high-school program had ten participating scholars who self-reported gains in confidence in their research abilities and understanding of what it means to be a scientist.
      Citation: Journal of Pathology Informatics 2017 8(1):2-2
      PubDate: Tue,28 Feb 2017
      DOI: 10.4103/2153-3539.201110
      Issue No: Vol. 8, No. 1 (2017)
       
  • Implementation of a software application for presurgical case history
           review of frozen section pathology cases

    • Authors: Andrew P Norgan, Mathew L Okeson, Justin E Juskewitch, Kabeer K Shah, William R Sukov
      Pages: 3 - 3
      Abstract: Andrew P Norgan, Mathew L Okeson, Justin E Juskewitch, Kabeer K Shah, William R Sukov
      Journal of Pathology Informatics 2017 8(1):3-3
      Background: The frozen section pathology practice at Mayo Clinic in Rochester performs ~20,000 intraoperative consultations a year (~70–80/weekday). To prepare for intraoperative consultations, surgical pathology fellows and residents review the case history, previous pathology, and relevant imaging the day before surgery. Before the work described herein, review of pending surgical pathology cases was a paper-based process requiring handwritten transcription from the electronic health record, a laborious and potentially error prone process. Methods: To facilitate more efficient case review, a modular extension of an existing surgical listing software application (Surgical and Procedure Scheduling [SPS]) was developed. The module (SPS-pathology-specific module [PM]) added pathology-specific functionality including recording case notes, prefetching of radiology, pathology, and operative reports from the medical record, flagging infectious cases, and real-time tracking of cases in the operating room. After implementation, users were surveyed about its impact on the surgical pathology practice. Results: There were 16 survey respondents (five staff pathologists and eleven residents or fellows). All trainees (11/11) responded that the application improved an aspect of surgical list review including abstraction from medical records (10/11), identification of possibly infectious cases (7/11), and speed of list preparation (10/11). The average reported time savings in list preparation was 1.4 h/day. Respondents indicated the application improved the speed (11/16), clarity (13/16), and accuracy (10/16) of morning report. During the workday, respondents reported the application improved real-time case review (14/16) and situational awareness of ongoing cases (13/16). Conclusions: A majority of respondents found the SPS-PM improved all preparatory and logistical aspects of the Mayo Clinic frozen section surgical pathology practice. In addition, use of the SPS-PM saved an average of 1.4 h/day for residents and fellows engaged in preparatory case review.
      Citation: Journal of Pathology Informatics 2017 8(1):3-3
      PubDate: Tue,28 Feb 2017
      DOI: 10.4103/2153-3539.201112
      Issue No: Vol. 8, No. 1 (2017)
       
  • Criteria to screen molecular tests for the diagnosis of herpes simplex
           virus in the central nervous system have no propensity to harm

    • Authors: Ronald George Hauser, Cynthia A Brandt, Richard A Martinello
      Pages: 4 - 4
      Abstract: Ronald George Hauser, Cynthia A Brandt, Richard A Martinello
      Journal of Pathology Informatics 2017 8(1):4-4
      Objectives: Investigators have ruled out herpes simplex virus (HSV) infection without the detection of herpes simplex deoxyribonucleic acid in cerebrospinal fluid (CSF) (i.e., HSV polymerase chain reaction [PCR]) by laboratory (normal CSF white blood cell count and protein) and clinical criteria (age ≥2 years, no history of human immunodeficiency virus or solid-organ transplant). Compared to HSV PCR of all samples, the algorithm saves money in test costs and may decrease exposure to acyclovir by illustrating the low probability that the patient has HSV. Concern exists that algorithm use may cause harm through alteration of empiric acyclovir treatment in patients with true HSV central nervous system infection. Methods: All Department of Veterans Affair's patients with a positive HSV PCR of the CSF between 2000 and 2013 were identified and their medical records reviewed to determine the extent and possible impact of omitted HSV PCR testing by the algorithm. Results: Of 6357 total results, 101 patients had a positive CSF HSV PCR in the study period. Among the positive CSF HSV PCR results, the algorithm excluded 7 (7%) from PCR testing. Record review indicated these seven patients not tested by the algorithm with a positive CSF HSV PCR were considered by their attending physician not to have active HSV. Conclusion: The algorithm to screen HSV tests had no propensity to harm.
      Citation: Journal of Pathology Informatics 2017 8(1):4-4
      PubDate: Tue,28 Feb 2017
      DOI: 10.4103/2153-3539.201113
      Issue No: Vol. 8, No. 1 (2017)
       
  • Pathological diagnosis of gastric cancers with a novel computerized
           analysis system

    • Authors: Kosuke Oikawa, Akira Saito, Tomoharu Kiyuna, Hans Peter Graf, Eric Cosatto, Masahiko Kuroda
      Pages: 5 - 5
      Abstract: Kosuke Oikawa, Akira Saito, Tomoharu Kiyuna, Hans Peter Graf, Eric Cosatto, Masahiko Kuroda
      Journal of Pathology Informatics 2017 8(1):5-5
      Background: Recent studies of molecular biology have provided great advances for diagnostic molecular pathology. Automated diagnostic systems with computerized scanning for sampled cells in fluids or smears are now widely utilized. Automated analysis of tissue sections is, however, very difficult because they exhibit a complex mixture of overlapping malignant tumor cells, benign host-derived cells, and extracellular materials. Thus, traditional histological diagnosis is still the most powerful method for diagnosis of diseases. Methods: We have developed a novel computer-assisted pathology system for rapid, automated histological analysis of hematoxylin and eosin (H and E)-stained sections. It is a multistage recognition system patterned after methods that human pathologists use for diagnosis but harnessing machine learning and image analysis. The system first analyzes an entire H and E-stained section (tissue) at low resolution to search suspicious areas for cancer and then the selected areas are analyzed at high resolution to confirm the initial suspicion. Results: After training the pathology system with gastric tissues samples, we examined its performance using other 1905 gastric tissues. The system's accuracy in detecting malignancies was shown to be almost equal to that of conventional diagnosis by expert pathologists. Conclusions: Our novel computerized analysis system provides a support for histological diagnosis, which is useful for screening and quality control. We consider that it could be extended to be applicable to many other carcinomas after learning normal and malignant forms of various tissues. Furthermore, we expect it to contribute to the development of more objective grading systems, immunohistochemical staining systems, and fluorescent-stained image analysis systems.
      Citation: Journal of Pathology Informatics 2017 8(1):5-5
      PubDate: Tue,28 Feb 2017
      DOI: 10.4103/2153-3539.201114
      Issue No: Vol. 8, No. 1 (2017)
       
  • WhatsApp for teaching pathology postgraduates: a pilot study

    • Authors: Aditi Goyal, Nadeem Tanveer, Pooja Sharma
      Pages: 6 - 6
      Abstract: Aditi Goyal, Nadeem Tanveer, Pooja Sharma
      Journal of Pathology Informatics 2017 8(1):6-6
      Introduction: Postgraduate students spend a sizeable proportion of their time on social media platforms such as WhatsApp and Facebook. This change in our social interaction needs to be accommodated in our teaching methods. To engage them and arouse their curiosity, WhatsApp is an ideal platform. Digital photography by cell phone cameras has made it possible to share cases and discuss them with students round the clock. Objective: The primary aim of the study was to develop sharing and discussion of images using WhatsApp. It also aimed at gathering feedback by means of a questionnaire from pathology residents about their views about the use of WhatsApp for teaching purpose. Materials and Methods: A WhatsApp group by the name “Pathology on the Go” was created with the authors of this study as group administrators and all junior and senior resident doctors (69) as members. The group was used to discuss interesting cases, quiz questions, and other pathology-related academic issues. At the end of 4 weeks, a questionnaire was distributed among the members, and feedback was sought regarding their experience in the group. Results: Over a 4-week period, 16 cases were discussed with 647 posts. A total of 45 participants out of 69 were active participants, and they had an average of 14 posts over the 4-week period. Majority of the participants found the discussions very useful with minimal disruption of the daily routine. Conclusion: There is a need to incorporate Web 2.0 tools such as WhatsApp in our teaching methods to capture as much screen time of the students as possible.
      Citation: Journal of Pathology Informatics 2017 8(1):6-6
      PubDate: Tue,28 Feb 2017
      DOI: 10.4103/2153-3539.201111
      Issue No: Vol. 8, No. 1 (2017)
       
  • Open-source software for demand forecasting of clinical laboratory test
           volumes using time-series analysis

    • Authors: Emad A Mohammed, Christopher Naugler
      Pages: 7 - 7
      Abstract: Emad A Mohammed, Christopher Naugler
      Journal of Pathology Informatics 2017 8(1):7-7
      Background: Demand forecasting is the area of predictive analytics devoted to predicting future volumes of services or consumables. Fair understanding and estimation of how demand will vary facilitates the optimal utilization of resources. In a medical laboratory, accurate forecasting of future demand, that is, test volumes, can increase efficiency and facilitate long-term laboratory planning. Importantly, in an era of utilization management initiatives, accurately predicted volumes compared to the realized test volumes can form a precise way to evaluate utilization management initiatives. Laboratory test volumes are often highly amenable to forecasting by time-series models; however, the statistical software needed to do this is generally either expensive or highly technical. Method: In this paper, we describe an open-source web-based software tool for time-series forecasting and explain how to use it as a demand forecasting tool in clinical laboratories to estimate test volumes. Results: This tool has three different models, that is, Holt-Winters multiplicative, Holt-Winters additive, and simple linear regression. Moreover, these models are ranked and the best one is highlighted. Conclusion: This tool will allow anyone with historic test volume data to model future demand.
      Citation: Journal of Pathology Informatics 2017 8(1):7-7
      PubDate: Tue,28 Feb 2017
      DOI: 10.4103/jpi.jpi_65_16
      Issue No: Vol. 8, No. 1 (2017)
       
  • Summary of the 4th nordic symposium on digital pathology

    • Authors: Claes Lundström, Marie Waltersson, Anders Persson, Darren Treanor
      Pages: 8 - 8
      Abstract: Claes Lundström, Marie Waltersson, Anders Persson, Darren Treanor
      Journal of Pathology Informatics 2017 8(1):8-8
      The Nordic symposium on digital pathology (NDP) was created to promote knowledge exchange across stakeholders in health care, industry, and academia. In 2016, the 4th NDP installment took place in Linköping, Sweden, promoting development and collaboration in digital pathology for the benefit of routine care advances. This article summarizes the symposium, gathering 170 attendees from 13 countries. This summary also contains results from a survey on integrated diagnostics aspects, in particular radiology-pathology collaboration.
      Citation: Journal of Pathology Informatics 2017 8(1):8-8
      PubDate: Fri,10 Mar 2017
      DOI: 10.4103/jpi.jpi_5_17
      Issue No: Vol. 8, No. 1 (2017)
       
  • Identification of histological correlates of overall survival in lower
           grade gliomas using a bag-of-words paradigm: A preliminary analysis based
           on hematoxylin & eosin stained slides from the lower grade glioma
           cohort of the cancer genome Atlas

    • Authors: Reid Trenton Powell, Adriana Olar, Shivali Narang, Ganesh Rao, Erik Sulman, Gregory N Fuller, Arvind Rao
      Pages: 9 - 9
      Abstract: Reid Trenton Powell, Adriana Olar, Shivali Narang, Ganesh Rao, Erik Sulman, Gregory N Fuller, Arvind Rao
      Journal of Pathology Informatics 2017 8(1):9-9
      Background: Glioma, the most common primary brain neoplasm, describes a heterogeneous tumor of multiple histologic subtypes and cellular origins. At clinical presentation, gliomas are graded according to the World Health Organization guidelines (WHO), which reflect the malignant characteristics of the tumor based on histopathological and molecular features. Lower grade diffuse gliomas (LGGs) (WHO Grade II–III) have fewer malignant characteristics than high-grade gliomas (WHO Grade IV), and a better clinical prognosis, however, accurate discrimination of overall survival (OS) remains a challenge. In this study, we aimed to identify tissue-derived image features using a machine learning approach to predict OS in a mixed histology and grade cohort of lower grade glioma patients. To achieve this aim, we used H and E stained slides from the public LGG cohort of The Cancer Genome Atlas (TCGA) to create a machine learned dictionary of “image-derived visual words” associated with OS. We then evaluated the combined efficacy of using these visual words in predicting short versus long OS by training a generalized machine learning model. Finally, we mapped these predictive visual words back to molecular signaling cascades to infer potential drivers of the machine learned survival-associated phenotypes. Methods: We analyzed digitized histological sections downloaded from the LGG cohort of TCGA using a bag-of-words approach. This method identified a diverse set of histological patterns that were further correlated with OS, histology, and molecular signaling activity using Cox regression, analysis of variance, and Spearman correlation, respectively. A support vector machine (SVM) model was constructed to discriminate patients into short and long OS groups dichotomized at 24-month. Results: This method identified disease-relevant phenotypes associated with OS, some of which are correlated with disease-associated molecular pathways. From these image-derived phenotypes, a generalized SVM model which could discriminate 24-month OS (area under the curve, 0.76) was obtained. Conclusion: Here, we demonstrated one potential strategy to incorporate image features derived from H and E stained slides into predictive models of OS. In addition, we showed how these image-derived phenotypic characteristics correlate with molecular signaling activity underlying the etiology or behavior of LGG.
      Citation: Journal of Pathology Informatics 2017 8(1):9-9
      PubDate: Fri,10 Mar 2017
      DOI: 10.4103/jpi.jpi_43_16
      Issue No: Vol. 8, No. 1 (2017)
       
  • RecutClub.com: An open source, whole slide image-based pathology education
           system

    • Authors: Paul A Christensen, Nathan E Lee, Michael J Thrall, Suzanne Z Powell, Patricia Chevez-Barrios, S Wesley Long
      Pages: 10 - 10
      Abstract: Paul A Christensen, Nathan E Lee, Michael J Thrall, Suzanne Z Powell, Patricia Chevez-Barrios, S Wesley Long
      Journal of Pathology Informatics 2017 8(1):10-10
      Background: Our institution's pathology unknown conferences provide educational cases for our residents. However, the cases have not been previously available digitally, have not been collated for postconference review, and were not accessible to a wider audience. Our objective was to create an inexpensive whole slide image (WSI) education suite to address these limitations and improve the education of pathology trainees. Materials and Methods: We surveyed residents regarding their preference between four unique WSI systems. We then scanned weekly unknown conference cases and study set cases and uploaded them to our custom built WSI viewer located at RecutClub.com. We measured site utilization and conference participation. Results: Residents preferred our OpenLayers WSI implementation to Ventana Virtuoso, Google Maps API, and OpenSlide. Over 16 months, we uploaded 1366 cases from 77 conferences and ten study sets, occupying 793.5 GB of cloud storage. Based on resident evaluations, the interface was easy to use and demonstrated minimal latency. Residents are able to review cases from home and from their mobile devices. Worldwide, 955 unique IP addresses from 52 countries have viewed cases in our site. Conclusions: We implemented a low-cost, publicly available repository of WSI slides for resident education. Our trainees are very satisfied with the freedom to preview either the glass slides or WSI and review the WSI postconference. Both local users and worldwide users actively and repeatedly view cases in our study set.
      Citation: Journal of Pathology Informatics 2017 8(1):10-10
      PubDate: Fri,10 Mar 2017
      DOI: 10.4103/jpi.jpi_72_16
      Issue No: Vol. 8, No. 1 (2017)
       
  • Turning microscopy in the medical curriculum digital: Experiences from the
           faculty of health and medical sciences at University of Copenhagen

    • Authors: Ben Vainer, Niels Werner Mortensen, Steen Seier Poulsen, Allan Have Sørensen, Jørgen Olsen, Hans Henrik Saxild, Flemming Fryd Johansen
      Pages: 11 - 11
      Abstract: Ben Vainer, Niels Werner Mortensen, Steen Seier Poulsen, Allan Have Sørensen, Jørgen Olsen, Hans Henrik Saxild, Flemming Fryd Johansen
      Journal of Pathology Informatics 2017 8(1):11-11
      Familiarity with the structure and composition of normal tissue and an understanding of the changes that occur during disease is pivotal to the study of the human body. For decades, microscope slides have been central to teaching pathology in medical courses and related subjects at the University of Copenhagen. Students had to learn how to use a microscope and envisage three-dimensional processes that occur in the body from two-dimensional glass slides. Here, we describe how a PathXL virtual microscopy system for teaching pathology and histology at the Faculty has recently been implemented, from an administrative, an economic, and a teaching perspective. This fully automatic digital microscopy system has been received positively by both teachers and students, and a decision was made to convert all courses involving microscopy to the virtual microscopy format. As a result, conventional analog microscopy will be phased out from the fall of 2016.
      Citation: Journal of Pathology Informatics 2017 8(1):11-11
      PubDate: Fri,10 Mar 2017
      DOI: 10.4103/2153-3539.201919
      Issue No: Vol. 8, No. 1 (2017)
       
  • A randomized study comparing digital imaging to traditional glass slide
           microscopy for breast biopsy and cancer diagnosis

    • Authors: Joann G Elmore, Gary M Longton, Margaret S Pepe, Patricia A Carney, Heidi D Nelson, Kimberly H Allison, Berta M Geller, Tracy Onega, Anna N. A Tosteson, Ezgi Mercan, Linda G Shapiro, Tad T Brunyé, Thomas R Morgan, Donald L Weaver
      Pages: 12 - 12
      Abstract: Joann G Elmore, Gary M Longton, Margaret S Pepe, Patricia A Carney, Heidi D Nelson, Kimberly H Allison, Berta M Geller, Tracy Onega, Anna N. A Tosteson, Ezgi Mercan, Linda G Shapiro, Tad T Brunyé, Thomas R Morgan, Donald L Weaver
      Journal of Pathology Informatics 2017 8(1):12-12
      Background: Digital whole slide imaging may be useful for obtaining second opinions and is used in many countries. However, the U.S. Food and Drug Administration requires verification studies. Methods: Pathologists were randomized to interpret one of four sets of breast biopsy cases during two phases, separated by ≥9 months, using glass slides or digital format (sixty cases per set, one slide per case, n = 240 cases). Accuracy was assessed by comparing interpretations to a consensus reference standard. Intraobserver reproducibility was assessed by comparing the agreement of interpretations on the same cases between two phases. Estimated probabilities of confirmation by a reference panel (i.e., predictive values) were obtained by incorporating data on the population prevalence of diagnoses. Results: Sixty-five percent of responding pathologists were eligible, and 252 consented to randomization; 208 completed Phase I (115 glass, 93 digital); and 172 completed Phase II (86 glass, 86 digital). Accuracy was slightly higher using glass compared to digital format and varied by category: invasive carcinoma, 96% versus 93% (P = 0.04); ductal carcinoma in situ (DCIS), 84% versus 79% (P < 0.01); atypia, 48% versus 43% (P = 0.08); and benign without atypia, 87% versus 82% (P < 0.01). There was a small decrease in intraobserver agreement when the format changed compared to when glass slides were used in both phases (P = 0.08). Predictive values for confirmation by a reference panel using glass versus digital were: invasive carcinoma, 98% and 97% (not significant [NS]); DCIS, 70% and 57% (P = 0.007); atypia, 38% and 28% (P = 0.002); and benign without atypia, 97% and 96% (NS). Conclusions: In this large randomized study, digital format interpretations were similar to glass slide interpretations of benign and invasive cancer cases. However, cases in the middle of the spectrum, where more inherent variability exists, may be more problematic in digital format. Future studies evaluating the effect these findings exert on clinical practice and patient outcomes are required.
      Citation: Journal of Pathology Informatics 2017 8(1):12-12
      PubDate: Fri,10 Mar 2017
      DOI: 10.4103/2153-3539.201920
      Issue No: Vol. 8, No. 1 (2017)
       
  • Performance of a web-based method for generating synoptic reports

    • Authors: Megan A Renshaw, Scott A Renshaw, Mercy Mena-Allauca, Patricia P Carrion, Xiaorong Mei, Arniris Narciandi, Edwin W Gould, Andrew A Renshaw
      Pages: 13 - 13
      Abstract: Megan A Renshaw, Scott A Renshaw, Mercy Mena-Allauca, Patricia P Carrion, Xiaorong Mei, Arniris Narciandi, Edwin W Gould, Andrew A Renshaw
      Journal of Pathology Informatics 2017 8(1):13-13
      Context: The College of American Pathologists (CAP) requires synoptic reporting of all tumor excisions. Objective: To compare the performance of different methods of generating synoptic reports. Methods: Completeness, amendment rates, rate of timely ordering of ancillary studies (KRAS in T4/N1 colon carcinoma), and structured data file extraction were compared for four different synoptic report generating methods. Results: Use of the printed tumor protocols directly from the CAP website had the lowest completeness (84%) and highest amendment (1.8%) rates. Reformatting these protocols was associated with higher completeness (94%, P < 0.001) and reduced amendment (1%, P = 0.20) rates. Extraction into a structured data file was successful 93% of the time. Word-based macros improved completeness (98% vs. 94%, P < 0.001) but not amendment rates (1.5%). KRAS was ordered before sign out 89% of the time. In contrast, a web-based product with a reminder flag when items were missing, an embedded flag for data extraction, and a reminder to order KRAS when appropriate resulted in improved completeness (100%, P = 0.005), amendment rates (0.3%, P = 0.03), KRAS ordering before sign out (100%, P = 0.23), and structured data extraction (100%, P < 0.001) without reducing the speed (P = 0.34) or accuracy (P = 1.00) of data extraction by the reader. Conclusion: Completeness, amendment rates, ancillary test ordering rates, and data extraction rates vary significantly with the method used to construct the synoptic report. A web-based method compares favorably with all other methods examined and does not reduce reader usability.
      Citation: Journal of Pathology Informatics 2017 8(1):13-13
      PubDate: Fri,10 Mar 2017
      DOI: 10.4103/jpi.jpi_91_16
      Issue No: Vol. 8, No. 1 (2017)
       
  • Making pathology diagnoses with glass or digital slides: Which modality is
           inferior?

    • Authors: Jonhan Ho, Liron Pantanowitz
      Pages: 14 - 14
      Abstract: Jonhan Ho, Liron Pantanowitz
      Journal of Pathology Informatics 2017 8(1):14-14

      Citation: Journal of Pathology Informatics 2017 8(1):14-14
      PubDate: Mon,10 Apr 2017
      DOI: 10.4103/jpi.jpi_10_17
      Issue No: Vol. 8, No. 1 (2017)
       
  • Predictive nuclear chromatin characteristics of melanoma and dysplastic
           nevi

    • Authors: Matthew G Hanna, Chi Liu, Gustavo K Rohde, Rajendra Singh
      Pages: 15 - 15
      Abstract: Matthew G Hanna, Chi Liu, Gustavo K Rohde, Rajendra Singh
      Journal of Pathology Informatics 2017 8(1):15-15
      Background: The diagnosis of malignant melanoma (MM) is among the diagnostic challenges pathologists encounter on a routine basis. Melanoma may arise in patients with preexisting dysplastic nevi (DN) and it is still the cause of 1.7% of all cancer-related deaths. Melanomas often have overlapping histological features with DN, especially those with severe dysplasia. Nucleotyping for identifying nuclear textural features can analyze nuclear DNA structure and organization. The aim of this study is to differentiate MM and DN using these methodologies. Methods: Dermatopathology slides diagnosed as MM and DN were retrieved. The glass slides were scanned using an Aperio ScanScopeXT at ×40 (0.25 μ/pixel). Whole slide images (WSI) were annotated for nuclei selection. Nuclear features to distinguish between MM and DN based on chromatin distributions were extracted from the WSI. The morphological characteristics for each nucleus were quantified with the optimal transport-based linear embedding in the continuous domain. Label predictions for individual cell nucleus are achieved through a modified version of linear discriminant analysis, coupled with the k-nearest neighbor classifier. Label for an unknown patient was set by the voting strategy with its pertaining cell nuclei. Results: Nucleotyping of 139 patient cases of melanoma (n = 67) and DN (n = 72) showed that our method had superior classification accuracy of 81.29%. This is a 6.4% gain in differentiating MM and DN, compared with numerical feature-based method. The distribution differences in nuclei morphology between MM and DN can be visualized with biological interpretation. Conclusions: Nucleotyping using quantitative and qualitative analyses may provide enough information for differentiating MM from DN using pixel image data. Our method to segment cell nuclei may offer a practical and inexpensive solution in aiding in the accurate diagnosis of melanoma.
      Citation: Journal of Pathology Informatics 2017 8(1):15-15
      PubDate: Mon,10 Apr 2017
      DOI: 10.4103/jpi.jpi_84_16
      Issue No: Vol. 8, No. 1 (2017)
       
  • Evaluation of android smartphones for telepathology

    • Authors: Donald Ekong, Fang Liu, G Thomas Brown, Arunima Ghosh, Paul Fontelo
      Pages: 16 - 16
      Abstract: Donald Ekong, Fang Liu, G Thomas Brown, Arunima Ghosh, Paul Fontelo
      Journal of Pathology Informatics 2017 8(1):16-16
      Background: In the year 2014, Android smartphones accounted for one-third of mobile connections globally but are predicted to increase to two-thirds by 2020. In developing countries, where teleconsultations can benefit health-care providers most, the ratio is even higher. This study compared the use of two Android phones, an 8 megapixel (MP) and a 16 MP phone, for capturing microscopic images. Method: The Android phones were used to capture images and videos of a gastrointestinal biopsy teaching set of referred cases from the Armed Forces Institute of Pathology (AFIP). The acquired images and videos were reviewed online by two pathologists for image quality, adequacy for diagnosis, usefulness of video overviews, and confidence in diagnosis, on a 5-point Likert scale. Results: The results show higher means in a 5-point Likert scale for the 8 MP versus the 16 MP phone that were statistically significant in adequacy of images (4.0 vs. 3.75) for rendering diagnosis and for agreement with the reference diagnosis (2.33 vs. 2.07). Although the quality of images was found higher in the 16 MP phone (3.8 vs. 3.65), these were not statistically significant. Adding video images of the entire specimen was found to be useful for evaluating the slides (combined mean, 4.0). Conclusion: For telepathology and other image dependent practices in developing countries, Android phones could be a useful tool for capturing images.
      Citation: Journal of Pathology Informatics 2017 8(1):16-16
      PubDate: Mon,10 Apr 2017
      DOI: 10.4103/jpi.jpi_93_16
      Issue No: Vol. 8, No. 1 (2017)
       
  • Compromising the security of “generating unique identifiers from
           patient identification data using security models”

    • Authors: Arran Schlosberg
      Pages: 17 - 17
      Abstract: Arran Schlosberg
      Journal of Pathology Informatics 2017 8(1):17-17

      Citation: Journal of Pathology Informatics 2017 8(1):17-17
      PubDate: Mon,10 Apr 2017
      DOI: 10.4103/jpi.jpi_1_17
      Issue No: Vol. 8, No. 1 (2017)
       
  • Alchemy: A web 2.0 real-time quality assurance platform for human
           immunodeficiency Virus, hepatitis C Virus, and BK Virus quantitation
           assays

    • Authors: Emmanuel Agosto-Arroyo, Gina M Coshatt, Thomas S Winokur, Shuko Harada, Seung L Park
      Pages: 18 - 18
      Abstract: Emmanuel Agosto-Arroyo, Gina M Coshatt, Thomas S Winokur, Shuko Harada, Seung L Park
      Journal of Pathology Informatics 2017 8(1):18-18
      Background: The molecular diagnostics laboratory faces the challenge of improving test turnaround time (TAT). Low and consistent TATs are of great clinical and regulatory importance, especially for molecular virology tests. Laboratory information systems (LISs) contain all the data elements necessary to do accurate quality assurance (QA) reporting of TAT and other measures, but these reports are in most cases still performed manually: a time-consuming and error-prone task. The aim of this study was to develop a web-based real-time QA platform that would automate QA reporting in the molecular diagnostics laboratory at our institution, and minimize the time expended in preparing these reports. Methods: Using a standard Linux, Nginx, MariaDB, PHP stack virtual machine running atop a Dell Precision 5810, we designed and built a web-based QA platform, code-named Alchemy. Data files pulled periodically from the LIS in comma-separated value format were used to autogenerate QA reports for the human immunodeficiency virus (HIV) quantitation, hepatitis C virus (HCV) quantitation, and BK virus (BKV) quantitation. Alchemy allowed the user to select a specific timeframe to be analyzed and calculated key QA statistics in real-time, including the average TAT in days, tests falling outside the expected TAT ranges, and test result ranges. Results: Before implementing Alchemy, reporting QA for the HIV, HCV, and BKV quantitation assays took 45–60 min of personnel time per test every month. With Alchemy, that time has decreased to 15 min total per month. Alchemy allowed the user to select specific periods of time and analyzed the TAT data in-depth without the need of extensive manual calculations. Conclusions: Alchemy has significantly decreased the time and the human error associated with QA report generation in our molecular diagnostics laboratory. Other tests will be added to this web-based platform in future updates. This effort shows the utility of informatician-supervised resident/fellow programming projects as learning opportunities and workflow improvements in the molecular laboratory.
      Citation: Journal of Pathology Informatics 2017 8(1):18-18
      PubDate: Mon,10 Apr 2017
      DOI: 10.4103/jpi.jpi_69_16
      Issue No: Vol. 8, No. 1 (2017)
       
  • The need for careful data collection for pattern recognition in digital
           pathology

    • Authors: Rapha&#235;l Marée
      Pages: 19 - 19
      Abstract: Raphaël Marée
      Journal of Pathology Informatics 2017 8(1):19-19
      Effective pattern recognition requires carefully designed ground-truth datasets. In this technical note, we first summarize potential data collection issues in digital pathology and then propose guidelines to build more realistic ground-truth datasets and to control their quality. We hope our comments will foster the effective application of pattern recognition approaches in digital pathology.
      Citation: Journal of Pathology Informatics 2017 8(1):19-19
      PubDate: Mon,10 Apr 2017
      DOI: 10.4103/jpi.jpi_94_16
      Issue No: Vol. 8, No. 1 (2017)
       
  • Abstracts

    • Pages: 20 - 20
      Abstract:
      Journal of Pathology Informatics 2017 8(1):20-20

      Citation: Journal of Pathology Informatics 2017 8(1):20-20
      PubDate: Wed,10 May 2017
      Issue No: Vol. 8, No. 1 (2017)
       
  • Training nuclei detection algorithms with simple annotations

    • Authors: Henning Kost, Andr&#233; Homeyer, Jesper Molin, Claes Lundstr&#246;m, Horst Karl Hahn
      Pages: 21 - 21
      Abstract: Henning Kost, André Homeyer, Jesper Molin, Claes Lundström, Horst Karl Hahn
      Journal of Pathology Informatics 2017 8(1):21-21
      Background: Generating good training datasets is essential for machine learning-based nuclei detection methods. However, creating exhaustive nuclei contour annotations, to derive optimal training data from, is often infeasible. Methods: We compared different approaches for training nuclei detection methods solely based on nucleus center markers. Such markers contain less accurate information, especially with regard to nuclear boundaries, but can be produced much easier and in greater quantities. The approaches use different automated sample extraction methods to derive image positions and class labels from nucleus center markers. In addition, the approaches use different automated sample selection methods to improve the detection quality of the classification algorithm and reduce the run time of the training process. We evaluated the approaches based on a previously published generic nuclei detection algorithm and a set of Ki-67-stained breast cancer images. Results: A Voronoi tessellation-based sample extraction method produced the best performing training sets. However, subsampling of the extracted training samples was crucial. Even simple class balancing improved the detection quality considerably. The incorporation of active learning led to a further increase in detection quality. Conclusions: With appropriate sample extraction and selection methods, nuclei detection algorithms trained on the basis of simple center marker annotations can produce comparable quality to algorithms trained on conventionally created training sets.
      Citation: Journal of Pathology Informatics 2017 8(1):21-21
      PubDate: Mon,15 May 2017
      DOI: 10.4103/jpi.jpi_3_17
      Issue No: Vol. 8, No. 1 (2017)
       
  • Review of “Travels on conferences: Evolution of digital
           pathology” by Klaus Kayser

    • Authors: Gabor Fischer
      Pages: 22 - 22
      Abstract: Gabor Fischer
      Journal of Pathology Informatics 2017 8(1):22-22

      Citation: Journal of Pathology Informatics 2017 8(1):22-22
      PubDate: Mon,15 May 2017
      DOI: 10.4103/jpi.jpi_6_17
      Issue No: Vol. 8, No. 1 (2017)
       
  • Current state of the regulatory trajectory for whole slide imaging devices
           in the USA

    • Authors: Esther Abels, Liron Pantanowitz
      Pages: 23 - 23
      Abstract: Esther Abels, Liron Pantanowitz
      Journal of Pathology Informatics 2017 8(1):23-23
      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 of medical 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.
      Citation: Journal of Pathology Informatics 2017 8(1):23-23
      PubDate: Mon,15 May 2017
      DOI: 10.4103/jpi.jpi_11_17
      Issue No: Vol. 8, No. 1 (2017)
       
  • A reduced set of features for chronic kidney disease prediction

    • Authors: Rajesh Misir, Malay Mitra, Ranjit Kumar Samanta
      Pages: 24 - 24
      Abstract: Rajesh Misir, Malay Mitra, Ranjit Kumar Samanta
      Journal of Pathology Informatics 2017 8(1):24-24
      Chronic kidney disease (CKD) is one of the life-threatening diseases. Early detection and proper management are solicited for augmenting survivability. As per the UCI data set, there are 24 attributes for predicting CKD or non-CKD. At least there are 16 attributes need pathological investigations involving more resources, money, time, and uncertainties. The objective of this work is to explore whether we can predict CKD or non-CKD with reasonable accuracy using less number of features. An intelligent system development approach has been used in this study. We attempted one important feature selection technique to discover reduced features that explain the data set much better. Two intelligent binary classification techniques have been adopted for the validity of the reduced feature set. Performances were evaluated in terms of four important classification evaluation parameters. As suggested from our results, we may more concentrate on those reduced features for identifying CKD and thereby reduces uncertainty, saves time, and reduces costs.
      Citation: Journal of Pathology Informatics 2017 8(1):24-24
      PubDate: Mon,19 Jun 2017
      DOI: 10.4103/jpi.jpi_88_16
      Issue No: Vol. 8, No. 1 (2017)
       
  • Development and implementation of a coagulation factor testing method
           utilizing autoverification in a high-volume clinical reference laboratory
           environment

    • Authors: Paul W Riley, Benoit Gallea, Andre Valcour
      Pages: 25 - 25
      Abstract: Paul W Riley, Benoit Gallea, Andre Valcour
      Journal of Pathology Informatics 2017 8(1):25-25
      Background: Testing coagulation factor activities requires that multiple dilutions be assayed and analyzed to produce a single result. The slope of the line created by plotting measured factor concentration against sample dilution is evaluated to discern the presence of inhibitors giving rise to nonparallelism. Moreover, samples producing results on initial dilution falling outside the analytic measurement range of the assay must be tested at additional dilutions to produce reportable results. Methods: The complexity of this process has motivated a large clinical reference laboratory to develop advanced computer algorithms with automated reflex testing rules to complete coagulation factor analysis. A method was developed for autoverification of coagulation factor activity using expert rules developed with on an off the shelf commercially available data manager system integrated into an automated coagulation platform. Results: Here, we present an approach allowing for the autoverification and reporting of factor activity results with greatly diminished technologist effort. Conclusions: To the best of our knowledge, this is the first report of its kind providing a detailed procedure for implementation of autoverification expert rules as applied to coagulation factor activity testing. Advantages of this system include ease of training for new operators, minimization of technologist time spent, reduction of staff fatigue, minimization of unnecessary reflex tests, optimization of turnaround time, and assurance of the consistency of the testing and reporting process.
      Citation: Journal of Pathology Informatics 2017 8(1):25-25
      PubDate: Mon,19 Jun 2017
      DOI: 10.4103/jpi.jpi_95_16
      Issue No: Vol. 8, No. 1 (2017)
       
 
 
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