Literature DB >> 27420575

Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology.

Rohit Bhargava1, Anant Madabhushi2.   

Abstract

Pathology is essential for research in disease and development, as well as for clinical decision making. For more than 100 years, pathology practice has involved analyzing images of stained, thin tissue sections by a trained human using an optical microscope. Technological advances are now driving major changes in this paradigm toward digital pathology (DP). The digital transformation of pathology goes beyond recording, archiving, and retrieving images, providing new computational tools to inform better decision making for precision medicine. First, we discuss some emerging innovations in both computational image analytics and imaging instrumentation in DP. Second, we discuss molecular contrast in pathology. Molecular DP has traditionally been an extension of pathology with molecularly specific dyes. Label-free, spectroscopic images are rapidly emerging as another important information source, and we describe the benefits and potential of this evolution. Third, we describe multimodal DP, which is enabled by computational algorithms and combines the best characteristics of structural and molecular pathology. Finally, we provide examples of application areas in telepathology, education, and precision medicine. We conclude by discussing challenges and emerging opportunities in this area.

Entities:  

Keywords:  FT-IR spectroscopy; algorithms; chemical imaging; computational; diagnosis; digital pathology; infrared spectroscopic imaging; microenvironment; outcome; precision medicine; prognosis; stainless staining

Mesh:

Year:  2016        PMID: 27420575      PMCID: PMC5533658          DOI: 10.1146/annurev-bioeng-112415-114722

Source DB:  PubMed          Journal:  Annu Rev Biomed Eng        ISSN: 1523-9829            Impact factor:   9.590


  135 in total

1.  Analysis of variance in spectroscopic imaging data from human tissues.

Authors:  Jin Tae Kwak; Rohith Reddy; Saurabh Sinha; Rohit Bhargava
Journal:  Anal Chem       Date:  2011-12-28       Impact factor: 6.986

2.  Systematic analysis of breast cancer morphology uncovers stromal features associated with survival.

Authors:  Andrew H Beck; Ankur R Sangoi; Samuel Leung; Robert J Marinelli; Torsten O Nielsen; Marc J van de Vijver; Robert B West; Matt van de Rijn; Daphne Koller
Journal:  Sci Transl Med       Date:  2011-11-09       Impact factor: 17.956

3.  Assessing and improving the stability of chemometric models in small sample size situations.

Authors:  Claudia Beleites; Reiner Salzer
Journal:  Anal Bioanal Chem       Date:  2008-01-29       Impact factor: 4.142

4.  Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features.

Authors:  Haibo Wang; Angel Cruz-Roa; Ajay Basavanhally; Hannah Gilmore; Natalie Shih; Mike Feldman; John Tomaszewski; Fabio Gonzalez; Anant Madabhushi
Journal:  J Med Imaging (Bellingham)       Date:  2014-10-10

5.  Feature Importance in Nonlinear Embeddings (FINE): Applications in Digital Pathology.

Authors:  Shoshana B Ginsburg; George Lee; Sahirzeeshan Ali; Anant Madabhushi
Journal:  IEEE Trans Med Imaging       Date:  2015-07-14       Impact factor: 10.048

6.  Multiplexed ion beam imaging of human breast tumors.

Authors:  Michael Angelo; Sean C Bendall; Rachel Finck; Matthew B Hale; Chuck Hitzman; Alexander D Borowsky; Richard M Levenson; John B Lowe; Scot D Liu; Shuchun Zhao; Yasodha Natkunam; Garry P Nolan
Journal:  Nat Med       Date:  2014-03-02       Impact factor: 53.440

7.  Development of a practical spatial-spectral analysis protocol for breast histopathology using Fourier transform infrared spectroscopic imaging.

Authors:  F Nell Pounder; Rohith K Reddy; Rohit Bhargava
Journal:  Faraday Discuss       Date:  2016-06-23       Impact factor: 4.008

8.  Spatially Invariant Vector Quantization: A pattern matching algorithm for multiple classes of image subject matter including pathology.

Authors:  Jason D Hipp; Jerome Y Cheng; Mehmet Toner; Ronald G Tompkins; Ulysses J Balis
Journal:  J Pathol Inform       Date:  2011-02-26

9.  Improving prediction of prostate cancer recurrence using chemical imaging.

Authors:  Jin Tae Kwak; André Kajdacsy-Balla; Virgilia Macias; Michael Walsh; Saurabh Sinha; Rohit Bhargava
Journal:  Sci Rep       Date:  2015-03-04       Impact factor: 4.379

10.  The use of virtual microscopy and a wiki in pathology education: Tracking student use, involvement, and response.

Authors:  Zev Leifer
Journal:  J Pathol Inform       Date:  2015-06-03
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  41 in total

1.  An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival.

Authors:  Cheng Lu; James S Lewis; William D Dupont; W Dale Plummer; Andrew Janowczyk; Anant Madabhushi
Journal:  Mod Pathol       Date:  2017-08-04       Impact factor: 7.842

Review 2.  An Assessment of Imaging Informatics for Precision Medicine in Cancer.

Authors:  C Chennubhotla; L P Clarke; A Fedorov; D Foran; G Harris; E Helton; R Nordstrom; F Prior; D Rubin; J H Saltz; E Shalley; A Sharma
Journal:  Yearb Med Inform       Date:  2017-09-11

3.  Quantitative Chemical Analysis at the Nanoscale Using the Photothermal Induced Resonance Technique.

Authors:  Georg Ramer; Vladimir A Aksyuk; Andrea Centrone
Journal:  Anal Chem       Date:  2017-12-06       Impact factor: 6.986

4.  The changing face of cancer diagnosis: From computational image analysis to systems biology.

Authors:  Fabian Kiessling
Journal:  Eur Radiol       Date:  2018-02-27       Impact factor: 5.315

Review 5.  Advances in the computational and molecular understanding of the prostate cancer cell nucleus.

Authors:  Neil M Carleton; George Lee; Anant Madabhushi; Robert W Veltri
Journal:  J Cell Biochem       Date:  2018-06-20       Impact factor: 4.429

6.  Correlative imaging reveals physiochemical heterogeneity of microcalcifications in human breast carcinomas.

Authors:  Jennie A M R Kunitake; Siyoung Choi; Kayla X Nguyen; Meredith M Lee; Frank He; Daniel Sudilovsky; Patrick G Morris; Maxine S Jochelson; Clifford A Hudis; David A Muller; Peter Fratzl; Claudia Fischbach; Admir Masic; Lara A Estroff
Journal:  J Struct Biol       Date:  2017-12-06       Impact factor: 2.867

7.  An Image Analysis Resource for Cancer Research: PIIP-Pathology Image Informatics Platform for Visualization, Analysis, and Management.

Authors:  Anne L Martel; Dan Hosseinzadeh; Caglar Senaras; Yu Zhou; Azadeh Yazdanpanah; Rushin Shojaii; Emily S Patterson; Anant Madabhushi; Metin N Gurcan
Journal:  Cancer Res       Date:  2017-11-01       Impact factor: 12.701

8.  Training a cell-level classifier for detecting basal-cell carcinoma by combining human visual attention maps with low-level handcrafted features.

Authors:  Germán Corredor; Jon Whitney; Viviana Arias; Anant Madabhushi; Eduardo Romero
Journal:  J Med Imaging (Bellingham)       Date:  2017-03-11

9.  HistoQC: An Open-Source Quality Control Tool for Digital Pathology Slides.

Authors:  Andrew Janowczyk; Ren Zuo; Hannah Gilmore; Michael Feldman; Anant Madabhushi
Journal:  JCO Clin Cancer Inform       Date:  2019-04

Review 10.  Digital pathology in nephrology clinical trials, research, and pathology practice.

Authors:  Laura Barisoni; Jeffrey B Hodgin
Journal:  Curr Opin Nephrol Hypertens       Date:  2017-11       Impact factor: 2.894

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