Read by QxMD icon Read

"Digital pathology"

Joseph A Sparano, Robert Gray, Maja H Oktay, David Entenberg, Thomas Rohan, Xiaonan Xue, Michael Donovan, Michael Peterson, Anthony Shuber, Douglas A Hamilton, Timothy D'Alfonso, Lori J Goldstein, Frank Gertler, Nancy E Davidson, John Condeelis, Joan Jones
Metastasis is the primary cause of death in early-stage breast cancer. We evaluated the association between a metastasis biomarker, which we call "Tumor Microenviroment of Metastasis" (TMEM), and risk of recurrence. TMEM are microanatomic structures where invasive tumor cells are in direct contact with endothelial cells and macrophages, and which serve as intravasation sites for tumor cells into the circulation. We evaluated primary tumors from 600 patients with Stage I-III breast cancer treated with adjuvant chemotherapy in trial E2197 (NCT00003519), plus endocrine therapy for hormone receptor (HR)+ disease...
2017: NPJ Breast Cancer
Jun Cheng, Xiaokui Mo, Xusheng Wang, Anil Parwani, Qianjin Feng, Kun Huang
Motivation: As a highly heterogeneous disease, the progression of tumor is not only achieved by unlimited growth of the tumor cells, but also supported, stimulated, and nurtured by the microenvironment around it. However traditional qualitative and/or semi-quantitative parameters obtained by pathologist's visual examination have very limited capability to capture this interaction between tumor and its microenvironment. With the advent of digital pathology, computerized image analysis may provide a better tumor characterization and give new insights into this problem...
November 9, 2017: Bioinformatics
Gregory R Bean, Kwun Wah Wen, Andrew E Horvai
Among well-differentiated lipomatous lesions, variability in adipocyte size has been proposed as a morphologic feature of malignancy. Specifically, normal adipose tissue and benign lipomas tend to contain adipocytes of uniform size, whereas atypical lipomatous tumor/well-differentiated liposarcoma (ALT/WDL) are described as containing adipocytes with a conspicuous variation in cell size. However, this proposed variance has never been objectively, quantitatively correlated with diagnosis. Using whole slide scanning combined with semiautomated digital image analysis, we aimed to quantitatively test the hypothesis that variance in adipocyte size is a feature of malignancy in well-differentiated lipomatous tumors...
November 8, 2017: Human Pathology
Michael Nalisnik, Mohamed Amgad, Sanghoon Lee, Sameer H Halani, Jose Enrique Velazquez Vega, Daniel J Brat, David A Gutman, Lee A D Cooper
Whole-slide imaging of histologic sections captures tissue microenvironments and cytologic details in expansive high-resolution images. These images can be mined to extract quantitative features that describe tissues, yielding measurements for hundreds of millions of histologic objects. A central challenge in utilizing this data is enabling investigators to train and evaluate classification rules for identifying objects related to processes like angiogenesis or immune response. In this paper we describe HistomicsML, an interactive machine-learning system for digital pathology imaging datasets...
November 6, 2017: Scientific Reports
Tanis J Ferman, Naoya Aoki, Julia E Crook, Melissa E Murray, Neill R Graff-Radford, Jay A van Gerpen, Ryan J Uitti, Zbigniew K Wszolek, Jonathan Graff-Radford, Otto Pedraza, Kejal Kantarci, Bradley F Boeve, Dennis W Dickson
INTRODUCTION: We sought to assess the individual and combined contribution of limbic and neocortical α-synuclein, tau, and β-amyloid to duration of illness in dementia with Lewy bodies (DLB). METHODS: Quantitative digital pathology of neocortical and limbic α-synuclein, tau, and β-amyloid was assessed in 49 patients with clinically probable DLB. Regression modeling examined the unique and shared contribution of each pathology to the variance of illness duration...
October 31, 2017: Alzheimer's & Dementia: the Journal of the Alzheimer's Association
Anne L Martel, Dan Hosseinzadeh, Caglar Senaras, Yu Zhou, Azadeh Yazdanpanah, Rushin Shojaii, Emily S Patterson, Anant Madabhushi, Metin N Gurcan
Pathology Image Informatics Platform (PIIP) is an NCI/NIH sponsored project intended for managing, annotating, sharing, and quantitatively analyzing digital pathology imaging data. It expands on an existing, freely available pathology image viewer, Sedeen. The goal of this project is to develop and embed some commonly used image analysis applications into the Sedeen viewer to create a freely available resource for the digital pathology and cancer research communities. Thus far, new plugins have been developed and incorporated into the platform for out of focus detection, region of interest transformation, and IHC slide analysis...
November 1, 2017: Cancer Research
David A Gutman, Mohammed Khalilia, Sanghoon Lee, Michael Nalisnik, Zach Mullen, Jonathan Beezley, Deepak R Chittajallu, David Manthey, Lee A D Cooper
Tissue-based cancer studies can generate large amounts of histology data in the form of glass slides. These slides contain important diagnostic, prognostic, and biological information and can be digitized into expansive and high-resolution whole-slide images using slide-scanning devices. Effectively utilizing digital pathology data in cancer research requires the ability to manage, visualize, share, and perform quantitative analysis on these large amounts of image data, tasks that are often complex and difficult for investigators with the current state of commercial digital pathology software...
November 1, 2017: Cancer Research
Michael N Kent, Thomas G Olsen, Theresa A Feeser, Katherine C Tesno, John C Moad, Michael P Conroy, Mary Jo Kendrick, Sean R Stephenson, Michael R Murchland, Ayesha U Khan, Elizabeth A Peacock, Alexa Brumfiel, Michael A Bottomley
Importance: Digital pathology represents a transformative technology that impacts dermatologists and dermatopathologists from residency to academic and private practice. Two concerns are accuracy of interpretation from whole-slide images (WSI) and effect on workflow. Studies of considerably large series involving single-organ systems are lacking. Objective: To evaluate whether diagnosis from WSI on a digital microscope is inferior to diagnosis of glass slides from traditional microscopy (TM) in a large cohort of dermatopathology cases with attention on image resolution, specifically eosinophils in inflammatory cases and mitotic figures in melanomas, and to measure the workflow efficiency of WSI compared with TM...
October 11, 2017: JAMA Dermatology
Philipp Kainz, Michael Pfeiffer, Martin Urschler
Segmentation of histopathology sections is a necessary preprocessing step for digital pathology. Due to the large variability of biological tissue, machine learning techniques have shown superior performance over conventional image processing methods. Here we present our deep neural network-based approach for segmentation and classification of glands in tissue of benign and malignant colorectal cancer, which was developed to participate in the GlaS@MICCAI2015 colon gland segmentation challenge. We use two distinct deep convolutional neural networks (CNN) for pixel-wise classification of Hematoxylin-Eosin stained images...
2017: PeerJ
Dominik Bettenworth, Arne Bokemeyer, Christopher Poremba, Nik Sheng Ding, Steffi Ketelhut, Philipp Lenz, Björn Kemper
Inflammatory bowel diseases (IBD) are inflammatory disorders of the gastrointestinal tract characterized by a chronic relapsing disease course. As uncontrolled intestinal inflammation can result in severe disease complications, recent treatment targets of IBD evolved toward seeking the absence of mucosal and histological inflammation. However, this approach requires adequate histological evaluation of IBD disease activity. The diagnostic challenge of histological examination of intestinal inflammation is documented by the multitude of proposed histological scoring systems...
October 9, 2017: Histology and Histopathology
Caner Mercan, Selim Aksoy, Ezgi Mercan, Linda G Shapiro, Donald L Weaver, Joann G Elmore
Digital pathology has entered a new era with the availability of whole slide scanners that create high-resolution images of full biopsy slides. Consequently, the uncertainty regarding the correspondence between the image areas and the diagnostic labels assigned by pathologists at the slide level, and the need for identifying regions that belong to multiple classes with different clinical significance have emerged as two new challenges. However, generalizability of the state-of-theart algorithms, whose accuracies were reported on carefully selected regions of interest (ROI) for the binary benign versus cancer classification, to these multi-class learning and localization problems is currently unknown...
October 2, 2017: IEEE Transactions on Medical Imaging
Joyce A Chow, Martin E Törnros, Marie Waltersson, Helen Richard, Madeleine Kusoffsky, Claes F Lundström, Arianit Kurti
CONTEXT: Within digital pathology, digitalization of the grossing procedure has been relatively underexplored in comparison to digitalization of pathology slides. AIMS: Our investigation focuses on the interaction design of an augmented reality gross pathology workstation and refining the interface so that information and visualizations are easily recorded and displayed in a thoughtful view. SETTINGS AND DESIGN: The work in this project occurred in two phases: the first phase focused on implementation of an augmented reality grossing workstation prototype while the second phase focused on the implementation of an incremental prototype in parallel with a deeper design study...
2017: Journal of Pathology Informatics
Michael Gadermayr, Dennis Eschweiler, Abiramjee Jeevanesan, Barbara Mara Klinkhammer, Peter Boor, Dorit Merhof
Digital pathology is a field of increasing interest and requires automated systems for processing huge amounts of digital data. The development of supervised-learning based automated systems is aggravated by the fact that image properties can change from slide to slide. In this work, the focus is on the segmentation of the glomeruli constituting the most important regions-of-interest in renal histopathology. We propose and investigate a two-stage pipeline consisting of a weakly supervised patch-based detection and a precise segmentation...
September 23, 2017: Computers in Biology and Medicine
Ruben Groen, Kuniko Abe, Han-Seung Yoon, Zaibo Li, Rulong Shen, Akira Yoshikawa, Takao Nitanda, Yukiko Shimizu, Isao Otsuka, Junya Fukuoka
BACKGROUND: Digital pathology increasingly has been gaining the attention of pathologists worldwide. However, the application of digital cytology by Panoptiq (ViewsIQ, Vancouver, Canada) microscope-based scanning software is relatively unexplored. Panoptiq enables the operator to combine low-power panoramic digital images with z-stacks at regions of interest with a significantly smaller image size than that obtained by whole-slide scanning. The current study aimed to evaluate the feasibility of the use of Panoptiq in the digital interpretation of cervicovaginal cytology specimens in comparison with conventional light microscopy...
September 28, 2017: Cancer
Haibo Wang, Satish Viswanath, Anant Madabhushi
There has been recent substantial interest in extracting sub-visual features from medical images for improved disease characterization compared to what might be achievable via visual inspection alone. Features such as Haralick and Gabor can provide a multi-scale representation of the original image by extracting measurements across differently sized neighborhoods. While these multi-scale features are effective, on large-scale digital pathological images, the process of extracting these features is computationally expensive...
September 28, 2017: Scientific Reports
Takeo Fujii, James M Reuben, Lei Huo, Jose Rodrigo Espinosa Fernandez, Yun Gong, Rachel Krupa, Mahipal V Suraneni, Ryon P Graf, Jerry Lee, Stephanie Greene, Angel Rodriguez, Lyndsey Dugan, Jessica Louw, Bora Lim, Carlos H Barcenas, Angela N Marx, Debu Tripathy, Yipeng Wang, Mark Landers, Ryan Dittamore, Naoto T Ueno
PURPOSE: Androgen receptor (AR) is frequently detected in breast cancers, and AR-targeted therapies are showing activity in AR-positive (AR+) breast cancer. However, the role of AR in breast cancers is still not fully elucidated and the biology of AR in breast cancer remains incompletely understood. Circulating tumor cells (CTCs) can serve as prognostic and diagnostic tools, prompting us to measure AR protein expression and conduct genomic analyses on CTCs in patients with metastatic breast cancer...
2017: PloS One
Jun Liao, Yutong Jiang, Zichao Bian, Bahareh Mahrou, Aparna Nambiar, Alexander W Magsam, Kaikai Guo, Shiyao Wang, Yong Ku Cho, Guoan Zheng
Whole slide imaging (WSI) has recently been cleared for primary diagnosis in the U.S. A critical challenge of WSI is to perform accurate focusing in high speed. Traditional systems create a focus map prior to scanning. For each focus point on the map, a sample needs to be static in the x-y plane, and axial scanning is needed to maximize the contrast. Here we report a novel focus map surveying method for WSI. In this method, we illuminate the sample with two LEDs and recover the focus points based on 1D autocorrelation analysis...
September 1, 2017: Optics Letters
Bethany Jill Williams, Andrew Hanby, Rebecca Millican-Slater, Anju Nijhawan, Eldo Verghese, Darren Treanor
AIM: To train and individually validate a group of breast pathologists in specialty specific digital primary diagnosis using a novel protocol endorsed by the Royal College of Pathologists' new guideline for digital pathology. The protocol allows early exposure to live digital reporting, in a risk mitigated environment, and focusses on patient safety and professional development. METHODS AND RESULTS: 3 specialty breast pathologist completed training in use of a digital microscopy system, and were exposed to a training set of 20 challenging cases, designed to help them identify personal digital diagnostic pitfalls...
September 22, 2017: Histopathology
G Kayser, G Haroske
No abstract text is available yet for this article.
September 22, 2017: Der Pathologe
Anne M Mills, Sarah E Gradecki, Bethany J Horton, Rebecca Blackwell, Christopher A Moskaluk, James W Mandell, Stacey E Mills, Helen P Cathro
Prior work has shown that digital images and microscopic slides can be interpreted with comparable diagnostic accuracy. Although accuracy has been well-validated, the interpretative time for digital images has scarcely been studied and concerns about efficiency remain a major barrier to adoption. We investigated the efficiency of digital pathology when compared with glass slide interpretation in the diagnosis of surgical pathology biopsy and resection specimens. Slides were pulled from 510 surgical pathology cases from 5 organ systems (gastrointestinal, gynecologic, liver, bladder, and brain)...
September 4, 2017: American Journal of Surgical Pathology
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"