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Next-Generation Pathology [chapter]

Peter D. Caie, David J. Harrison
2016 Msphere  
The integration of standardised multi-omics Big-Data and the retention of valuable information on spatial heterogeneity is imperative to model complex disease mechanisms.  ...  Tissue is, however, complex, heterogeneous and prone to artefact.  ...  Traditionally image analysis in histopathology concentrated on the quantification of protein expression through immunohistochemistry and immunofluorescence (IF).  ... 
doi:10.1007/978-1-4939-3283-2_4 pmid:26677179 fatcat:uithnzbsuraetn3y4spt52vqd4

Quantitative Image Analysis of Cellular Heterogeneity in Breast Tumors Complements Genomic Profiling

Y. Yuan, H. Failmezger, O. M. Rueda, H. R. Ali, S. Graf, S.-F. Chin, R. F. Schwarz, C. Curtis, M. J. Dunning, H. Bardwell, N. Johnson, S. Doyle (+5 others)
2012 Science Translational Medicine  
Our integration of histopathology and genomics extends recent approaches that only identified morphological features predictive of patient survival by image analysis (11) .  ...  Because our algorithms rely on the quality of histopathological stainings and images, with more and better quantitative systems for computational analysis of pathological images, we expect such analytical  ...  There was an error in the text on page 5 stating that "Kaplan-Meier survival curves revealed distinctly different outcomes for these two groups in both cohorts, where higher lymphocyte proportion is associated  ... 
doi:10.1126/scitranslmed.3004330 pmid:23100629 fatcat:lnyylnaawzft3n5o627bwgpg74

Complex Sources of Variation in Tissue Expression Data: Analysis of the GTEx Lung Transcriptome

Matthew N. McCall, Peter B. Illei, Marc K. Halushka
2016 American Journal of Human Genetics  
An in-depth analysis of the 175 genes with the greatest variation among 133 lung tissue samples identified five distinct clusters of highly correlated genes.  ...  In addition to identifying technical sources, such as sequencing date and post-mortem interval, we also identified several biological sources of variation.  ...  Acknowledgments The authors are grateful to David Tabor for his assistance in obtaining the lung image and many helpful conversations.  ... 
doi:10.1016/j.ajhg.2016.07.007 pmid:27588449 pmcid:PMC5011060 fatcat:3v2bv7v2fzaobeldnobr52w6zu

Identifying Recurrent Malignant Glioma after Treatment Using Amide Proton Transfer-Weighted MR Imaging: A Validation Study with Image-Guided Stereotactic Biopsy

Shanshan Jiang, Charles G. Eberhart, Michael Lim, Hye-Young Heo, Yi Zhang, Lindsay Blair, Zhibo Wen, Matthias Holdhoff, Doris Lin, Peng Huang, Huamin Qin, Alfredo Quinones-Hinojosa (+7 others)
2018 Clinical Cancer Research  
To quantify the accuracy of amide proton transfer-weighted (APTw) MRI for identifying active glioma after treatment via radiographically guided stereotactic tissue validation.Experimental Design: Twenty-one  ...  patients who were referred for surgery for MRI features concerning for tumor progression versus treatment effect underwent preoperative APTw imaging.  ...  Joe Gillen for assistance with the scanning, and Ms. Mary McAllister for editorial assistance.  ... 
doi:10.1158/1078-0432.ccr-18-1233 pmid:30366937 pmcid:PMC6335169 fatcat:cpdvnfnwtbcibeekvg5awarfai

CT Texture Analysis—Correlations With Histopathology Parameters in Head and Neck Squamous Cell Carcinomas

Hans-Jonas Meyer, Gordian Hamerla, Anne Kathrin Höhn, Alexey Surov
2019 Frontiers in Oncology  
Texture analysis was performed on contrast-enhanced CT images as a whole lesion measurement.  ...  Texture analysis is an emergent imaging technique to quantify heterogeneity in radiological images. It is still unclear whether this technique is capable to reflect tumor microstructure.  ...  Presumably, the heterogeneity information provided by texture analysis might also correlate with the heterogeneity in tumors on a histological level, and, thus, might be associated with cellularity, vessel  ... 
doi:10.3389/fonc.2019.00444 pmid:31192138 pmcid:PMC6546809 fatcat:mwokmh7dbzbatdb7dnesrhu2sm

Glioblastoma Multiforme Regional Genetic and Cellular Expression Patterns: Influence on Anatomic and Physiologic MR Imaging

Ramon F. Barajas, J. Graeme Hodgson, Jamie S. Chang, Scott R. Vandenberg, Ru-Fang Yeh, Andrew T. Parsa, Michael W. McDermott, Mitchel S. Berger, William P. Dillon, Soonmee Cha
2010 Radiology  
Purpose: To determine whether magnetic resonance (MR) imaging is infl uenced by genetic and cellular features of glioblastoma multiforme (GBM) aggressiveness.  ...  One half of the biopsy specimen was used for RNA microarray analysis. The second half underwent histopathologic analysis.  ...  Table 4 [ lists the results of correlation analysis between DSC PW and DW imaging values and the cellular histopathologic features of GBM aggressiveness for all biopsy sites.  ... 
doi:10.1148/radiol.09090663 pmid:20093527 pmcid:PMC2809924 fatcat:l2f43575u5gqxd4s2hnvwf62ue

3D histopathological grading of osteochondral tissue using contrast-enhanced micro-computed tomography

H.J. Nieminen, H.K. Gahunia, K.P.H. Pritzker, T. Ylitalo, L. Rieppo, S.S. Karhula, P. Lehenkari, E. Hæggström, S. Saarakkala
2017 Osteoarthritis and Cartilage  
This new grading system could be used as a reference for 3D imaging and analysis techniques intended for volumetric evaluation of OA pathology in research and clinical applications.  ...  Conclusions: We demonstrated that histopathological information relevant to OA can reliably be obtained from CEmCT images.  ...  embedding, sectioning, staining and microscopy/ imaging; this would yield a nominal 3e4 weeks form tissue extraction to analysis for one sample.  ... 
doi:10.1016/j.joca.2017.05.021 pmid:28606558 pmcid:PMC5773475 fatcat:t4fhaqes7bc5rfcgjv2ypbakvy

Histopathological image and gene expression pattern analysis for predicting molecular features and prognosis of head and neck squamous cell carcinoma

Linyan Chen, Hao Zeng, Mingxuan Zhang, Yuling Luo, Xuelei Ma
2021 Cancer Medicine  
We identified the gene expression profile correlated to image features by bioinformatics analysis.  ...  Histopathological image features offer a quantitative measurement of cellular morphology, and probably help for better diagnosis and prognosis in head and neck squamous cell carcinoma (HNSCC).  ...  TCGA and TCIA databases were publicly available for research, thus ethical approval was not required.  ... 
doi:10.1002/cam4.3965 pmid:33987946 pmcid:PMC8267162 fatcat:jd4dntcurvhhzbknln6ynaq324

Correlation Analysis of Histopathology and Proteogenomics Data for Breast Cancer

Xiaohui Zhan, Jun Cheng, Zhi Huang, Zhi Han, Bryan Helm, Xiaowen Liu, Jie Zhang, Tian-Fu Wang, Dong Ni, Kun Huang
2019 Molecular & Cellular Proteomics  
With the advancement in computational pathology and accumulation of large amount of cancer samples with matched molecular and histopathology data, researchers can carry out integrative analysis to investigate  ...  Overall, our study demonstrated the power for integrating multiple types of biological data for cancer samples in generating new hypothesis as well as identifying potential biomarkers predicting patient  ...  of Proteomic and Image Data for BRCA Molecular & Cellular Proteomics 18.14 S43 by guest on March 6, 2020 Correlative Analysis of Proteomic and Image Data for BRCA S44 Molecular & Cellular Proteomics  ... 
doi:10.1074/mcp.ra118.001232 pmid:31285282 pmcid:PMC6692775 fatcat:vv5lttq3avbtjnahjprxa6hmcm

Correlation of Dermoscopy With In Vivo Reflectance Confocal Microscopy of Streaks in Melanocytic Lesions

Alon Scope, Melissa Gill, Cristiane Benveuto-Andrade, Allan C. Halpern, Salvador Gonzalez, Ashfaq A. Marghoob
2007 Archives of Dermatology  
on RCM had smaller, more poorly formed peripheral nests on histopathologic examination.  ...  Objective: To analyze dermoscopically identified streaks by direct correlation with features visualized on reflectance confocal microscopy (RCM).  ...  Histopathologic analysis of both lesions (cases 1 and 2) identified spitzoid features. Figure 3 . 3 Case 1.  ... 
doi:10.1001/archderm.143.6.727 pmid:17576938 fatcat:qqbeq5q5dndzhp3ixll3tzvnny

The Emergence of Pathomics

Rajarsi Gupta, Tahsin Kurc, Ashish Sharma, Jonas S. Almeida, Joel Saltz
2019 Current Pathobiology Reports  
We report emerging digital pathology image analysis applications to study several types and subtypes of cancer to complement traditional histopathologic evaluation.  ...  Recent Findings Image analysis of tissues is based on the identification and classification of tissue, architectural elements, cells, nuclei, and other histologic features.  ...  analysis-based features can be used to quantitatively identify heterogeneous structural and textural tissue characteristics in different types of tissues and tumors.  ... 
doi:10.1007/s40139-019-00200-x fatcat:2tyb75sicnfhfl5aezkbdu35fa

Differentiation between Pure Mucinous Breast Carcinomas and Fibroadenomas with Strong High-Signal Intensity on T2-Weighted Images from Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Ning Qu, Yahong Luo, Tao Yu, Huihui Yu
2017 Breast Care  
About 40% of FAs have myxoid or edematous changes histopathologically [6] . On ultrasonography, myxoid or edematous FAs are often misdiagnosed as PMBCs.  ...  With magnetic resonance imaging (MRI), FAs with abundant myxoid or edematous stroma rich in free water yield strong highsignal intensity on T2-weighted images (T2-SHi) similar to that of PMBCs [8]; thus  ...  We thank LetPub (www.letpub.com) for its linguistic assistance during the preparation of this manuscript. Disclosure Statement All authors declare that they have no conflicts of interest.  ... 
doi:10.1159/000479955 pmid:29950965 pmcid:PMC6016057 fatcat:lwkugxospfdrjoi5mpkhdjc4ci

Development of Stereotactic Mass Spectrometry for Brain Tumor Surgery

Nathalie Y.R. Agar, Alexandra J. Golby, Keith L. Ligon, Isaiah Norton, Vandana Mohan, Justin M. Wiseman, Allen Tannenbaum, Ferenc A. Jolesz
2011 Neurosurgery  
METHODS-Using a frameless stereotactic sampling approach and by integrating a 3dimensional navigation system with an ultrasonic surgical probe, we obtained image-registered surgical specimens.  ...  OBJECTIVE-To introduce the integration of desorption electrospray ionization mass spectrometry into surgery for in vivo molecular tissue characterization and intraoperative definition of tumor boundaries  ...  Ponton Fund for the Neurosciences to NYRA. The 3D Slicer was developed by the National Alliance for Medical Image Computing and funded by National Institutes of Health (NIH) grant U54-EB005149.  ... 
doi:10.1227/neu.0b013e3181ff9cbb pmid:21135749 pmcid:PMC3678259 fatcat:5652keug3zhefko5honicko5za

Semi-Automated Image Analysis Methodology to Investigate Intracellular Heterogeneity in Immunohistochemical Stained Sections

Rifat Hamoudi, Sarah Hammoudeh, Arabella Hammoudeh, Surendra Rawat
2019 2019 IEEE International Conference on Imaging Systems and Techniques (IST)  
In this paper, we propose an approach to quantify heterogeneous cellular populations through combining histology and images processing techniques.  ...  The cell count was extrapolated from the binary images using the particle analysis tool in ImageJ.  ...  ACKNOWLEDGMENT We would like to thank Al-Jalila Foundation (Grant code: AJF201741) for funding this work.  ... 
doi:10.1109/ist48021.2019.9010370 dblp:conf/ist/HamoudiHHR19 fatcat:vbrlv33gzzhwjpnqw4jfdrfruy

What can artificial intelligence teach us about the molecular mechanisms underlying disease?

Gary J. R. Cook, Vicky Goh
2019 European Journal of Nuclear Medicine and Molecular Imaging  
While molecular imaging with positron emission tomography or single-photon emission computed tomography already reports on tumour molecular mechanisms on a macroscopic scale, there is increasing evidence  ...  Furthermore, the ability to deal with increasingly large amounts of data from medical images and beyond in a rapid, reproducible and transparent manner is essential for future clinical practice.  ...  Ethical approval Ethical approval is not required for a review paper. Informed consent No individual participants are discussed in this review.  ... 
doi:10.1007/s00259-019-04370-z pmid:31190176 pmcid:PMC6879441 fatcat:q57b7kjlwzd7lnwcpp3iu7zbre
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