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Chapter 15: Information Retrieval from Medical Knowledge
Resources
WILLIAM R. HERSH
Learning Objectives
After viewing this presentation, viewers should be able to:
Enumerate the basic biomedical and health knowledge resources
in books, journals, electronic databases, and other sources
Describe the major approaches used to indexing knowledge-
based content
Apply advanced searching techniques to the major biomedical
and health knowledge resources
Discuss the major results of information retrieval evaluation
studies
Describe future directions for research in information retrieval
Introduction
Information Retrieval (IR), sometimes called search, concerns
the acquisition, organization, and searching of knowledge-based
information, which is usually defined as information derived
and organized from obser-vational or experimental research
Although IR in biomedicine traditionally concentrated on the
retrieval of text from the biomedical liter-ature, the study has
expanded to include newer types of media that include images,
video, chemical structures, gene and protein sequences, and a
wide range of other digital media of relevance to biomedical
education, research, and patient care
Introduction
The overall goal of the IR process is to find content that meets a
person’s information needs
Components of information retrieval systems
IR tends to focus on knowledge-based information
Knowledge-based information categories:
Primary knowl-edge–based information (also called primary
literature) is original research that appears in journals, books,
reports, and other sources
Secondary knowledge–based information consists of the writing
that reviews, condenses, and/or synthesizes the primary
literature. The most com-mon examples of this type of literature
are books, monographs, and review articles in journals and
other publications
Knowledge Based Information
Virtually all scientific journals are published electronically
Not only is there the increased con-venience of redistributing
articles, but research has found that freely available on the Web
have a higher likelihood of being cited by other papers than
those that are not (Bork 2012)
Printing and mailing, tasks no longer needed in electronic
publishing, comprised a sig­nificant part of the “added value”
from publishers of journals. There is still however value added
by publishers, such as hiring and managing editorial staff to
produce the journals and managing the peer review process
Publication of Knowledge-Based Information
The basic principle of open access publishing is that authors
and/or their institutions pay the cost of production of
manuscripts up front after they are accepted through a peer
review process. After the paper is published, it becomes freely
available on the Web. Since most research is usually funded by
grants, the cost of open access publishing should be included in
grant budgets. The uptake of publishers adhering to the open
access model has been modest, with the most prominent being
Biomed Central (BMC, www.biomedcentral.com ) and the
Public Library of Science ( PLoS, www.plos.org )
Publishing Costs and Open Access
Information content is classified in four categories:
Bibliographic: the best-known and most widely used biomedical
bibliographic database is MEDLINE, which contains
bibliographic references to all the biomedical articles,
editorials, and letters to the editors in approximately 5,000
scientific journals
Full-text content: a large component of this content con-sists of
the online versions of books and periodicals. As already noted,
most traditionally paper-based medical literature, from
textbooks to journals, is now available electronically
Content
Annotated content: these resources are usually not stored as
freestanding Web pages but instead are often housed in database
management systems
Aggregated content: Aggregated content has been developed for
all types of users from consumers to clinicians to scientists.
Probably the largest aggregated consumer information resource
is MedlinePlus ( http://medlineplus.gov ) from the NLM.
MedlinePlus includes all the types of content previously
described, aggregated for easy access to a given topic
Content
Indexing is the process of assigning metadata to content to
facilitate its retrieval. Most modern commercial content is
indexed in two ways:
Manual indexing—where human indexers, usually using a
controlled terminology, assign indexing terms and attributes to
documents, often following a specific protocol
Automated indexing—where computers make the indexing
assignments, usually lim-ited to breaking out each word in the
document (or part of the document) as an indexing term
Indexing
A controlled terminology contains a set of terms that can be
applied to a task, such as indexing
When the terminology defines the terms, it is usually called a
vocabulary
When the terminology contains variants or synonyms of terms,
it is also called a thesaurus
Controlled Terminologies
A controlled terminology usually contains a list of terms that
are the canonical repre-sentations of the concepts. If it is a
thesaurus, it contains relationships between terms, which
typically fall into three categories:
Hierarchical—terms that are broader or narrower. The
hierarchical organization not only provides an overview of the
structure of a thesaurus but also can be used to enhance
searching (e.g., MeSH tree explosions that add terms from an
entire portion of the hierarchy to augment a search)
Synonym—terms that are synonyms, allowing the indexer or
searcher to express a concept in different words
Related—terms that are not synonymous or hierarchical but are
somehow otherwise related. These usually remind the searcher
of different but related terms that may enhance a search
Controlled Terminologies
The MeSH terminology is used to manually index most of the
databases produced by the NLM
The latest version contains over 26,000 subject headings
MeSH contains the three types of relationships described in the
previous slide:
Hierarchical—MeSH is organized hierarchically into 16 trees,
such as Diseases, Organisms, and Chemicals and Drugs
Synonym—MeSH contains a vast number of entry terms, which
are synonyms of the headings
Related—terms that may be useful for searchers to add to their
searches when appro-priate are suggested for many headings
Medical Subject Headings (MeSH)
The MeSH terminology files, their associated data, and their
supporting documentation are available on the NLM’s MeSH
Web site http://www.nlm.nih.gov/mesh
Medical Subject Headings (MeSH)
“Slice” through MeSH hierarchy
Manual indexing is most commonly done for bibliographic and
annotated content, although it is sometimes for other types of
content as well
While most Web content is indexed automatically (see next
slide), one approach to manual indexing has been to apply
metadata to Web pages and sites, exemplified by the Dublin
Core Metadata Initiative (DCMI, www.dublincore.org )
Manuel Indexing
The goal of the DCMI has been to develop a set of standard data
elements that creators of Web resources can use to apply
metadata to their content
DCMI standard has been approved by the National Information
Standards Organization and the International Organization of
Standards specification has 15 defined elements and sample
elements include:
DC.title - name given to the resource
DC.creator - person or organization primarily responsible for
creating the intellectual content of the resource
DC.subject - topic of the resource
DC.description - a textual description of the content of the
resource
DC.publisher - entity responsible for making the resource
available in its present form
DC.date - date associated with the creation or availability of the
resource
Manuel Indexing
In automated indexing, the indexing is done by a computer
We will focus on the auto-mated indexing used in operational
IR systems, namely the indexing of documents by the words
they contain
Word indexing is typically done by defining all consecutive
alphanumeric sequences between white space (which consists of
spaces, punctuation, carriage returns, and other non-
alphanumeric characters) as words. Systems must take particular
care to apply the same process to documents and the user’s
query, especially with characters such as hyphens and
apostrophes
Automated Indexing
A commonly used approach for term weighting is TF*IDF
weighting, which com-bines the inverse document frequency
(IDF) and term frequency (TF).
The usual formula is:
Automated Indexing
Synonymy—different words may have the same meaning, such
as high and elevated. This problem may extend to the level of
phrases with no words in common, such as the synonyms
hypertension and high blood pressure
Polysemy—the same word may have different meanings or
senses. For example, the word lead can refer to an element or to
a part of an electrocardiogram machine
Content—words in a document may not reflect its focus. For
example, an article describing hypertension may make mention
in passing to other concepts, such as congestive heart failure
(CHF) that are not the focus of the article
Context—words take on meaning based on other words around
them
Morphology—words can have suffixes that do not change the
underlying meaning, such as indicators of plurals, various
participles, adjectival forms of nouns, and nominalized forms of
adjectives
Granularity—queries and documents may describe concepts at
different levels of a hier-archy. A query for antibiotics for
treatment of a specific infection returns documents that only
contain specific antibiotics
Automated Indexing Limitations
Exact-Match Retrieval- In exact-match searching, the IR system
gives the user all documents that exactly match the criteria
specified in the search statement(s). This type of searching is
often called Boolean searching
Retrieval
Boolean operators
Partial-Match Retrieval-Although partial-match searching was
conceptualized very early, it did not see wide-spread use in IR
systems until the advent of Web search engines in the 1990s
The most common approach to document ranking in partial-
match searching is to give each a score based on the sum of the
weights of terms common to the document and query
Retrieval
There are many different retrieval interfaces, with some of the
features reflecting the content or structure of the underlying
database
PubMed is the system at NLM that searches MEDLINE and
other bibliographic databases
Retrieval Systems
There has been a great deal of research over the years devoted
to evaluation of IR sys-tems.
One of those frameworks organized evaluation around six
questions that someone advocating the use of IR systems might
ask (Hersh 1998):
Was the system used?
For what was the system used?
Were the users satisfied?
How well did they use the system?
What factors were associated with successful or unsuccessful
use of the system?
Did the system have an impact?
Evaluation
There are many ways to evaluate the performance of IR
systems, the most widely used of which are the relevance-based
measures of recall and precision
Recall is the pro-portion of relevant documents retrieved from
the database:
In other words, recall answers the question, for a given search,
what fraction of all the relevant documents have been obtained
from the database?
System-Oriented Evaluation
Precision is the proportion of relevant documents retrieved in
the search:
This measure answers the question, for a search, what fraction
of the retrieved docu-ments are relevant?
One problem that arises when one is comparing systems that use
ranking versus those that do not is that non-ranking systems,
typically using Boolean searching, tend to retrieve a fixed set of
documents and as a result have fixed points of recall and
preci-sion
System-Oriented Evaluation
A number of user-oriented evaluations have been performed
over the years looking at users of biomedical information. Most
of these studies have focused on clinicians
For example, Hersh et al studied in 1995 using the task-oriented
approach compared Boolean ver-sus natural language searching
in the textbook Scientific American Medicine
There are more studies listed in the textbook Chapter 15
User-Oriented Evaluation
Research taking place in several areas related to IR include:
Information extraction and text mining—usually through the use
of natural language processing (NLP) to extract facts and
knowledge from text
Summarization—Providing automated extracts or abstracts
summarizing the content of longer documents
Question-answering—Going beyond retrieval of documents to
providing actual answers to questions, as exemplified by the
IBM Corp. Watson system, which is being applied to medicine
(Ferrucci 2010)
Future Directions
There are many biomedical and health knowledge resources
online available in bibliographic databases, journals and other
full-text resources, Web sites, and other sources
Bibliographic content is likely to be indexed using controlled
vocabularies assigned by humans
Full-text and other resources are likely to be indexed via
extraction of words
The major approaches to searching biomedical and health
knowledge resources include exact-match searching using sets
and Boolean operators and partial-match searching on words
using relevance ranking
System-oriented evaluation studies tend to focus on
performance of search systems and usually involvement
measurement of the relevance-based measures of recall and
precision
User-oriented evaluation studies tend to compare users and their
abilities to complete tasks using retrieval systems
Conclusions
Chapter 16: Medical Imaging Informatics
Robert Hoyt MD
John Grizzard MD
Learning Objectives
After reviewing the presentation, viewers should be able to:
Describe the history behind digital radiology and the creation of
picture archiving and communication systems (PACS)
Itemize the benefits of digital radiology to clinicians, patients
and hospitals
List the challenges facing the adoption of picture archiving and
communication systems
Describe the difference between computed and digital radiology
Outline the field of medical imaging informatics
Describe new imaging technologies such as Web PACS and
mobile imaging viewers
Definitions
Medical Imaging Informatics: “study and application of
processes of information and communications technology for
the acquisition, manipulation, analysis and distribution of
medical image data”
Society for Imaging Informatics in Medicine (SIIM)
Picture Archiving and Communication Systems (PACS):
medical imaging technology which provides economical storage
of, and convenient access to, images from multiple modalities
Introduction
Medical Imaging Informatics:
Could belong to Biomedical informatics or Radiology
Study of imaging, acquisition, storage, interpretation and
sharing to improve patient care
Imaging data moves throughout medical enterprise and interacts
with EHRs, voice recognition dictation systems, computer-aided
diagnosis software, health information organizations, etc.
Important to have knowledge of workflow, networks, security,
data quality, hardware and software
Digital imaging
Started in the 1970s
First filmless hospital occurred in 1999
Transitioning to PACS
Similar to photography (film to digital)
Introduction of computed tomography, ultrasound, and magnetic
resonance imaging that all became digital
Eliminated need for film processing and storage rooms
Images could be viewed at a remote location
Advantages: cost savings, storage, retrieval
Transition to Filmless Radiology
Extensive initial costs
Printing remained for referring physicians
Use of film scanners for digital viewing
Proprietary imaging formats
Later, DICOM (DICOM = Digital Imaging and Communications
in Medicine) standard was created
Upgrade conventional radiology rooms for CT, ultrasound, and
MRI for the digital world
Computer-based image archiving
Transition to Filmless Radiology
Integrate PACS with EHRs, hospital information systems (HISs)
and radiology information systems (RISs)
Veterans Health Administration launched a teleradiology
network in 2007 to provide radiology coverage to all of its
regions
Faster processors, higher capacity disk drives, higher resolution
monitors, more robust hospital information systems, better
servers and faster network speeds were necessary for the change
to digital imaging
Picture Archiving and Communication Systems (PACS)
Full PACS
Images are processed from ultrasonography (US), magnetic
resonance imaging (MRI), positron emission tomography (PET),
computed tomography (CT), routine radiography and endoscopy
Mini-PACS
More limited and processes images from only one or two
modalities
PACS Key Components
PACS Key Components
Digital acquisition devices: sources of images, such as digital
angiography, fluoroscopy, mammography, CT, MRI , ultrasound
scanners
Network: ties PACS components together
Database server: high speed and robust central computer to
process information
Archival server: responsible for storing images and enables
short term (fast retrieval) and long term (slower retrieval)
storage
Radiology Information system (RIS): system that maintains
patient demographics, scheduling, billing information and
interpretations
Workstation: software and hardware to access PACS and
replaces standard light box or view box
Teleradiology: ability to remotely view images at a location
distant from the site of origin
Types of Digital Detectors
Computed radiography (CR)
After x-ray exposure to a special cassette, a laser reader scans
the image and converts it to a digital image. The image is erased
on the cassette so it can be used repeatedly
Digital radiography (DR)
Does not require an intermediate step of laser scanning
Typical PACS Workflow
Patient is identified in hospital information system (HIS)
An order is created that is sent to the radiology information
system (RIS) via an HL7 protocol
Orders will go to imaging device via the DICOM protocol
Image is created in DICOM format and sent to the PACS server
Images are stored in image archive
Radiologist is notified of a pending study
Study is then read at a computer workstation using high-
resolution monitors and viewing software available from a
variety of different vendors
Comparison can be made to prior studies
Diagnostic report is generated by the radiologist, often using
voice recognition software
Report is then stored on the PACS server
Web Based PACS
Reduce need for duplicate studies, and allow more rapid
diagnosis and treatment
DICOM imaging format could be an impediment to use of the
World Wide Web
Not browser compatible: Usually this entails downloading a
small application (thin client) from the PACS vendor that
enables the remote viewing station to act like a modified PACS
workstation
Alternate potential solution: "zero-footprint" Web viewer where
DICOM images are pre-converted to GIF
Legacy PACS compared to Web PACS in next slide
Legacy PACSWeb PACSOnly available on computers with
proper software installedAvailable anywhere with internet
accessUpgrades must be manually installedUpgrades are done
centrally or are not necessaryMultiple user interfacesOne user
interfaceDifficult to integrate with health information
exchangesEasy to integrate with health information
exchangesDifficult to link to multiple EHRsEasier to link to
EHRsLabor intensive for PACS administrator for maintenance
and trainingMuch less labor intensive for maintenance and
trainingCould involve multiple operating systemsOne operating
systemLess likely to be standards-basedUtilizes JPEG
compression, DICOM, HL7 and IHE profiles
Legacy vs. Web PACS
PACS and Mobile Technology
Until 2011, FDA prohibited physicians from using radiology
images displayed on mobile devices to make an official
diagnoses
Mobile MIM: Includes a VueMe version for patients
ResolutionMD Mobile is a medical imaging diagnostic
application for radiologists. Their server-based software
application allows physicians immediate access to the display,
reports, and analysis of patient images such as CT and MR,
stored within any healthcare facility, and to submit a clinical
diagnosis via their medical devices
OsiriX Mobile DICOM Viewer is a free PACS open source
viewer for the MAC operating system
PACS for a Hospital Desktop Features
Zoom-in feature for close-up detail
Ability to rotate images in any direction
Text button to see the report
Mark-up tool that does the following to the image: Adds text,
measures the size and ratios of objects
Measures angles
Measures the square area of a mass or region
Adds an arrow
Right click on the image and short cut tools appear
Export an image to any of the following destinations: Teaching
file,
CD-ROM, hard drive, USB drive, save to clipboard or Create
a video
PACS Advantages
Replaces a standard x-ray film archive
Allows for remote viewing and reporting
Expedites the incorporation of medical images into an
electronic health record
Images can be archived and transported on portable media, e.g.
USB drive and Apple’s iPhone
Other specialties that generate images may join PACS such as
cardiologists
PACS can be web-based and use “service oriented architecture”
Unlike conventional x-rays, digital films have a zoom feature
and can be manipulated in innumerable ways
Improves productivity by allowing multiple clinicians to view
the same image from different locations
Rapid retrieval of digital images for interpretation and
comparison with previous studies
PACS Advantages
Fewer “lost films”
Reports are more likely to accompany the digital image
Radiologists can view an image back and forth like a movie,
known as “stack mode”
Quicker reporting back to the requesting clinician
Digital imaging allows for computer aided detection (CAD)
Increased productivity
PACS Disadvantages
Cost: Open source and “rental PACS” are alternatives
New legislation cutting reimbursement rates
Expense and complexity to integrate with hospital and radiology
information systems and EHRs
Lack of interoperability with other PACSs
Bandwidth limits may require network upgrades
Different vendors may use different DICOM tags to label films
Viewing digital images a little slower than routine x-ray films
Workstations may require upgrades if high resolution monitors
are necessary
Moving Forward
Stage 2 Meaningful Use required both eligible professionals and
hospitals to incorporate (or make accessible) through their
electronic health records more than 10% of images ordered
Trend towards web based PACS
PACS is greatly accepted by clinicians
Fellowship in imaging informatics
Certificate in imaging informatics. Requirements can be found
in the textbook
Imaging Informatics Education
PACS is the logical progression from x-ray films to digital
imaging due to multiple new technologies
Medical Imaging Informatics will study the impact and
significance of all facets of digital imaging
PACS is very popular among clinicians, patients and hospitals,
but cost remains an issue
Web PACS offers more image interoperability options
Conclusions
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  • 1. Chapter 15: Information Retrieval from Medical Knowledge Resources WILLIAM R. HERSH Learning Objectives After viewing this presentation, viewers should be able to: Enumerate the basic biomedical and health knowledge resources in books, journals, electronic databases, and other sources Describe the major approaches used to indexing knowledge- based content Apply advanced searching techniques to the major biomedical and health knowledge resources Discuss the major results of information retrieval evaluation studies Describe future directions for research in information retrieval
  • 2. Introduction Information Retrieval (IR), sometimes called search, concerns the acquisition, organization, and searching of knowledge-based information, which is usually defined as information derived and organized from obser-vational or experimental research Although IR in biomedicine traditionally concentrated on the retrieval of text from the biomedical liter-ature, the study has expanded to include newer types of media that include images, video, chemical structures, gene and protein sequences, and a wide range of other digital media of relevance to biomedical education, research, and patient care Introduction The overall goal of the IR process is to find content that meets a person’s information needs Components of information retrieval systems
  • 3. IR tends to focus on knowledge-based information Knowledge-based information categories: Primary knowl-edge–based information (also called primary literature) is original research that appears in journals, books, reports, and other sources Secondary knowledge–based information consists of the writing that reviews, condenses, and/or synthesizes the primary literature. The most com-mon examples of this type of literature are books, monographs, and review articles in journals and other publications Knowledge Based Information Virtually all scientific journals are published electronically Not only is there the increased con-venience of redistributing articles, but research has found that freely available on the Web have a higher likelihood of being cited by other papers than those that are not (Bork 2012) Printing and mailing, tasks no longer needed in electronic publishing, comprised a sig­nificant part of the “added value”
  • 4. from publishers of journals. There is still however value added by publishers, such as hiring and managing editorial staff to produce the journals and managing the peer review process Publication of Knowledge-Based Information The basic principle of open access publishing is that authors and/or their institutions pay the cost of production of manuscripts up front after they are accepted through a peer review process. After the paper is published, it becomes freely available on the Web. Since most research is usually funded by grants, the cost of open access publishing should be included in grant budgets. The uptake of publishers adhering to the open access model has been modest, with the most prominent being Biomed Central (BMC, www.biomedcentral.com ) and the Public Library of Science ( PLoS, www.plos.org ) Publishing Costs and Open Access
  • 5. Information content is classified in four categories: Bibliographic: the best-known and most widely used biomedical bibliographic database is MEDLINE, which contains bibliographic references to all the biomedical articles, editorials, and letters to the editors in approximately 5,000 scientific journals Full-text content: a large component of this content con-sists of the online versions of books and periodicals. As already noted, most traditionally paper-based medical literature, from textbooks to journals, is now available electronically Content Annotated content: these resources are usually not stored as freestanding Web pages but instead are often housed in database management systems Aggregated content: Aggregated content has been developed for all types of users from consumers to clinicians to scientists. Probably the largest aggregated consumer information resource is MedlinePlus ( http://medlineplus.gov ) from the NLM. MedlinePlus includes all the types of content previously described, aggregated for easy access to a given topic Content
  • 6. Indexing is the process of assigning metadata to content to facilitate its retrieval. Most modern commercial content is indexed in two ways: Manual indexing—where human indexers, usually using a controlled terminology, assign indexing terms and attributes to documents, often following a specific protocol Automated indexing—where computers make the indexing assignments, usually lim-ited to breaking out each word in the document (or part of the document) as an indexing term Indexing A controlled terminology contains a set of terms that can be applied to a task, such as indexing When the terminology defines the terms, it is usually called a vocabulary When the terminology contains variants or synonyms of terms, it is also called a thesaurus Controlled Terminologies
  • 7. A controlled terminology usually contains a list of terms that are the canonical repre-sentations of the concepts. If it is a thesaurus, it contains relationships between terms, which typically fall into three categories: Hierarchical—terms that are broader or narrower. The hierarchical organization not only provides an overview of the structure of a thesaurus but also can be used to enhance searching (e.g., MeSH tree explosions that add terms from an entire portion of the hierarchy to augment a search) Synonym—terms that are synonyms, allowing the indexer or searcher to express a concept in different words Related—terms that are not synonymous or hierarchical but are somehow otherwise related. These usually remind the searcher of different but related terms that may enhance a search Controlled Terminologies The MeSH terminology is used to manually index most of the databases produced by the NLM The latest version contains over 26,000 subject headings MeSH contains the three types of relationships described in the
  • 8. previous slide: Hierarchical—MeSH is organized hierarchically into 16 trees, such as Diseases, Organisms, and Chemicals and Drugs Synonym—MeSH contains a vast number of entry terms, which are synonyms of the headings Related—terms that may be useful for searchers to add to their searches when appro-priate are suggested for many headings Medical Subject Headings (MeSH) The MeSH terminology files, their associated data, and their supporting documentation are available on the NLM’s MeSH Web site http://www.nlm.nih.gov/mesh Medical Subject Headings (MeSH) “Slice” through MeSH hierarchy
  • 9. Manual indexing is most commonly done for bibliographic and annotated content, although it is sometimes for other types of content as well While most Web content is indexed automatically (see next slide), one approach to manual indexing has been to apply metadata to Web pages and sites, exemplified by the Dublin Core Metadata Initiative (DCMI, www.dublincore.org ) Manuel Indexing The goal of the DCMI has been to develop a set of standard data elements that creators of Web resources can use to apply metadata to their content DCMI standard has been approved by the National Information Standards Organization and the International Organization of Standards specification has 15 defined elements and sample elements include: DC.title - name given to the resource DC.creator - person or organization primarily responsible for creating the intellectual content of the resource DC.subject - topic of the resource DC.description - a textual description of the content of the resource DC.publisher - entity responsible for making the resource available in its present form DC.date - date associated with the creation or availability of the resource Manuel Indexing
  • 10. In automated indexing, the indexing is done by a computer We will focus on the auto-mated indexing used in operational IR systems, namely the indexing of documents by the words they contain Word indexing is typically done by defining all consecutive alphanumeric sequences between white space (which consists of spaces, punctuation, carriage returns, and other non- alphanumeric characters) as words. Systems must take particular care to apply the same process to documents and the user’s query, especially with characters such as hyphens and apostrophes Automated Indexing A commonly used approach for term weighting is TF*IDF weighting, which com-bines the inverse document frequency (IDF) and term frequency (TF).
  • 11. The usual formula is: Automated Indexing Synonymy—different words may have the same meaning, such as high and elevated. This problem may extend to the level of phrases with no words in common, such as the synonyms hypertension and high blood pressure Polysemy—the same word may have different meanings or senses. For example, the word lead can refer to an element or to a part of an electrocardiogram machine Content—words in a document may not reflect its focus. For example, an article describing hypertension may make mention in passing to other concepts, such as congestive heart failure (CHF) that are not the focus of the article Context—words take on meaning based on other words around them Morphology—words can have suffixes that do not change the underlying meaning, such as indicators of plurals, various participles, adjectival forms of nouns, and nominalized forms of adjectives Granularity—queries and documents may describe concepts at different levels of a hier-archy. A query for antibiotics for treatment of a specific infection returns documents that only contain specific antibiotics
  • 12. Automated Indexing Limitations Exact-Match Retrieval- In exact-match searching, the IR system gives the user all documents that exactly match the criteria specified in the search statement(s). This type of searching is often called Boolean searching Retrieval Boolean operators Partial-Match Retrieval-Although partial-match searching was conceptualized very early, it did not see wide-spread use in IR systems until the advent of Web search engines in the 1990s The most common approach to document ranking in partial- match searching is to give each a score based on the sum of the weights of terms common to the document and query Retrieval
  • 13. There are many different retrieval interfaces, with some of the features reflecting the content or structure of the underlying database PubMed is the system at NLM that searches MEDLINE and other bibliographic databases Retrieval Systems There has been a great deal of research over the years devoted to evaluation of IR sys-tems. One of those frameworks organized evaluation around six questions that someone advocating the use of IR systems might ask (Hersh 1998): Was the system used? For what was the system used? Were the users satisfied?
  • 14. How well did they use the system? What factors were associated with successful or unsuccessful use of the system? Did the system have an impact? Evaluation There are many ways to evaluate the performance of IR systems, the most widely used of which are the relevance-based measures of recall and precision Recall is the pro-portion of relevant documents retrieved from the database: In other words, recall answers the question, for a given search, what fraction of all the relevant documents have been obtained from the database? System-Oriented Evaluation
  • 15. Precision is the proportion of relevant documents retrieved in the search: This measure answers the question, for a search, what fraction of the retrieved docu-ments are relevant? One problem that arises when one is comparing systems that use ranking versus those that do not is that non-ranking systems, typically using Boolean searching, tend to retrieve a fixed set of documents and as a result have fixed points of recall and preci-sion System-Oriented Evaluation A number of user-oriented evaluations have been performed over the years looking at users of biomedical information. Most of these studies have focused on clinicians For example, Hersh et al studied in 1995 using the task-oriented approach compared Boolean ver-sus natural language searching in the textbook Scientific American Medicine
  • 16. There are more studies listed in the textbook Chapter 15 User-Oriented Evaluation Research taking place in several areas related to IR include: Information extraction and text mining—usually through the use of natural language processing (NLP) to extract facts and knowledge from text Summarization—Providing automated extracts or abstracts summarizing the content of longer documents Question-answering—Going beyond retrieval of documents to providing actual answers to questions, as exemplified by the IBM Corp. Watson system, which is being applied to medicine (Ferrucci 2010) Future Directions There are many biomedical and health knowledge resources
  • 17. online available in bibliographic databases, journals and other full-text resources, Web sites, and other sources Bibliographic content is likely to be indexed using controlled vocabularies assigned by humans Full-text and other resources are likely to be indexed via extraction of words The major approaches to searching biomedical and health knowledge resources include exact-match searching using sets and Boolean operators and partial-match searching on words using relevance ranking System-oriented evaluation studies tend to focus on performance of search systems and usually involvement measurement of the relevance-based measures of recall and precision User-oriented evaluation studies tend to compare users and their abilities to complete tasks using retrieval systems Conclusions Chapter 16: Medical Imaging Informatics Robert Hoyt MD John Grizzard MD
  • 18. Learning Objectives After reviewing the presentation, viewers should be able to: Describe the history behind digital radiology and the creation of picture archiving and communication systems (PACS) Itemize the benefits of digital radiology to clinicians, patients and hospitals List the challenges facing the adoption of picture archiving and communication systems Describe the difference between computed and digital radiology Outline the field of medical imaging informatics Describe new imaging technologies such as Web PACS and mobile imaging viewers
  • 19. Definitions Medical Imaging Informatics: “study and application of processes of information and communications technology for the acquisition, manipulation, analysis and distribution of medical image data” Society for Imaging Informatics in Medicine (SIIM) Picture Archiving and Communication Systems (PACS): medical imaging technology which provides economical storage of, and convenient access to, images from multiple modalities Introduction Medical Imaging Informatics: Could belong to Biomedical informatics or Radiology Study of imaging, acquisition, storage, interpretation and sharing to improve patient care Imaging data moves throughout medical enterprise and interacts with EHRs, voice recognition dictation systems, computer-aided diagnosis software, health information organizations, etc. Important to have knowledge of workflow, networks, security, data quality, hardware and software
  • 20. Digital imaging Started in the 1970s First filmless hospital occurred in 1999 Transitioning to PACS Similar to photography (film to digital) Introduction of computed tomography, ultrasound, and magnetic resonance imaging that all became digital Eliminated need for film processing and storage rooms Images could be viewed at a remote location Advantages: cost savings, storage, retrieval Transition to Filmless Radiology Extensive initial costs Printing remained for referring physicians Use of film scanners for digital viewing Proprietary imaging formats Later, DICOM (DICOM = Digital Imaging and Communications in Medicine) standard was created Upgrade conventional radiology rooms for CT, ultrasound, and MRI for the digital world Computer-based image archiving
  • 21. Transition to Filmless Radiology Integrate PACS with EHRs, hospital information systems (HISs) and radiology information systems (RISs) Veterans Health Administration launched a teleradiology network in 2007 to provide radiology coverage to all of its regions Faster processors, higher capacity disk drives, higher resolution monitors, more robust hospital information systems, better servers and faster network speeds were necessary for the change to digital imaging Picture Archiving and Communication Systems (PACS) Full PACS Images are processed from ultrasonography (US), magnetic resonance imaging (MRI), positron emission tomography (PET), computed tomography (CT), routine radiography and endoscopy Mini-PACS More limited and processes images from only one or two modalities
  • 22. PACS Key Components PACS Key Components Digital acquisition devices: sources of images, such as digital angiography, fluoroscopy, mammography, CT, MRI , ultrasound scanners Network: ties PACS components together Database server: high speed and robust central computer to process information Archival server: responsible for storing images and enables short term (fast retrieval) and long term (slower retrieval) storage Radiology Information system (RIS): system that maintains patient demographics, scheduling, billing information and interpretations
  • 23. Workstation: software and hardware to access PACS and replaces standard light box or view box Teleradiology: ability to remotely view images at a location distant from the site of origin Types of Digital Detectors Computed radiography (CR) After x-ray exposure to a special cassette, a laser reader scans the image and converts it to a digital image. The image is erased on the cassette so it can be used repeatedly Digital radiography (DR) Does not require an intermediate step of laser scanning Typical PACS Workflow Patient is identified in hospital information system (HIS) An order is created that is sent to the radiology information system (RIS) via an HL7 protocol Orders will go to imaging device via the DICOM protocol
  • 24. Image is created in DICOM format and sent to the PACS server Images are stored in image archive Radiologist is notified of a pending study Study is then read at a computer workstation using high- resolution monitors and viewing software available from a variety of different vendors Comparison can be made to prior studies Diagnostic report is generated by the radiologist, often using voice recognition software Report is then stored on the PACS server Web Based PACS Reduce need for duplicate studies, and allow more rapid diagnosis and treatment DICOM imaging format could be an impediment to use of the World Wide Web Not browser compatible: Usually this entails downloading a small application (thin client) from the PACS vendor that enables the remote viewing station to act like a modified PACS workstation Alternate potential solution: "zero-footprint" Web viewer where DICOM images are pre-converted to GIF Legacy PACS compared to Web PACS in next slide
  • 25. Legacy PACSWeb PACSOnly available on computers with proper software installedAvailable anywhere with internet accessUpgrades must be manually installedUpgrades are done centrally or are not necessaryMultiple user interfacesOne user interfaceDifficult to integrate with health information exchangesEasy to integrate with health information exchangesDifficult to link to multiple EHRsEasier to link to EHRsLabor intensive for PACS administrator for maintenance and trainingMuch less labor intensive for maintenance and trainingCould involve multiple operating systemsOne operating systemLess likely to be standards-basedUtilizes JPEG compression, DICOM, HL7 and IHE profiles Legacy vs. Web PACS PACS and Mobile Technology Until 2011, FDA prohibited physicians from using radiology images displayed on mobile devices to make an official diagnoses Mobile MIM: Includes a VueMe version for patients ResolutionMD Mobile is a medical imaging diagnostic application for radiologists. Their server-based software application allows physicians immediate access to the display,
  • 26. reports, and analysis of patient images such as CT and MR, stored within any healthcare facility, and to submit a clinical diagnosis via their medical devices OsiriX Mobile DICOM Viewer is a free PACS open source viewer for the MAC operating system PACS for a Hospital Desktop Features Zoom-in feature for close-up detail Ability to rotate images in any direction Text button to see the report Mark-up tool that does the following to the image: Adds text, measures the size and ratios of objects Measures angles Measures the square area of a mass or region Adds an arrow Right click on the image and short cut tools appear Export an image to any of the following destinations: Teaching file, CD-ROM, hard drive, USB drive, save to clipboard or Create a video
  • 27. PACS Advantages Replaces a standard x-ray film archive Allows for remote viewing and reporting Expedites the incorporation of medical images into an electronic health record Images can be archived and transported on portable media, e.g. USB drive and Apple’s iPhone Other specialties that generate images may join PACS such as cardiologists PACS can be web-based and use “service oriented architecture” Unlike conventional x-rays, digital films have a zoom feature and can be manipulated in innumerable ways Improves productivity by allowing multiple clinicians to view the same image from different locations Rapid retrieval of digital images for interpretation and comparison with previous studies PACS Advantages Fewer “lost films” Reports are more likely to accompany the digital image Radiologists can view an image back and forth like a movie, known as “stack mode”
  • 28. Quicker reporting back to the requesting clinician Digital imaging allows for computer aided detection (CAD) Increased productivity PACS Disadvantages Cost: Open source and “rental PACS” are alternatives New legislation cutting reimbursement rates Expense and complexity to integrate with hospital and radiology information systems and EHRs Lack of interoperability with other PACSs Bandwidth limits may require network upgrades Different vendors may use different DICOM tags to label films Viewing digital images a little slower than routine x-ray films Workstations may require upgrades if high resolution monitors are necessary Moving Forward Stage 2 Meaningful Use required both eligible professionals and
  • 29. hospitals to incorporate (or make accessible) through their electronic health records more than 10% of images ordered Trend towards web based PACS PACS is greatly accepted by clinicians Fellowship in imaging informatics Certificate in imaging informatics. Requirements can be found in the textbook Imaging Informatics Education PACS is the logical progression from x-ray films to digital imaging due to multiple new technologies Medical Imaging Informatics will study the impact and significance of all facets of digital imaging PACS is very popular among clinicians, patients and hospitals, but cost remains an issue Web PACS offers more image interoperability options Conclusions