MARC details
000 -LEADER |
fixed length control field |
03890cam a2200229 4500 |
001 - CONTROL NUMBER |
control field |
9780323761116 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
220107t2022 xxu||||| |||| 00| 0 eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9780323761116 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9780323761116 |
041 ## - LANGUAGE CODE |
Language code of text/sound track or separate title |
eng |
100 ## - MAIN ENTRY--PERSONAL NAME |
Personal name |
Louie, Philip K. |
245 #0 - TITLE STATEMENT |
Title |
Atlas of spinal imaging: phenotypes, measurements, and classification systems |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication, distribution, etc. |
Amsterdam : |
Name of publisher, distributor, etc. |
Elsevier, |
Date of publication, distribution, etc. |
2022 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
1 online resource:illustrations (some color) |
505 ## - FORMATTED CONTENTS NOTE |
Formatted contents note |
Introduction -- Radiographic evaluation of the upper cervical spine -- Upper cervical spine MRI -- Upper cervical spine: computed tomography -- Clinical correlations to specific phenotypes and measurements with classification systems -- Subaxial cervical spine plain radiographs -- Magnetic resonance imaging techniques for the evaluation of the subaxial cervical spine -- Subaxial cervical spine CT -- Clinical correlations to specific phenotypes and measurements with classification systems -- Full-length spine:plain radiographs -- Full-length spine CT and MRI in daily practice -- Full-length spine:clinical correlations with specific phenotypes and measurements with classification systems -- Lumbosacral spine plain radiographs -- Lumbosacral spine MRI -- Lumbosacral CT -- Clinical correlations to specific phenotypes and measurements with classification systems: lumbosacral spine -- Future trends in spinal imaging. |
520 ## - SUMMARY, ETC. |
Summary, etc. |
Spine-related pain is the world's leading disabling condition, affecting every population and a frequent reason for seeking medical consultation and obtaining imaging studies. Numerous spinal phenotypes (observations/traits) and their respective measurements performed on various spine imaging have been shown to directly correlate and predict clinical outcomes. Atlas of Spinal Imaging: Phenotypes, Measurements and Classification Systems is a comprehensive visual resource that highlights various spinal phenotypes on imaging, describes their clinical and pathophysiological relevance, and discusses and illustrates their respective measurement techniques and classifications. Complies the knowledge and expertise of Dr. Dino Samartzis, the preeminent global authority on spinal phenotypes who has discovered and proposed new phenotypes and classification schemes; Dr. Howard S. An, a leading expert in patient management and at the forefront of 3D imaging of various spinal phenotypes; and Dr. Philip Louie, a young surgeon who is involved in one of the largest machine learning initiatives of spinal phenotyping. *Includes a Foreword by renowed spine surgeons Alexander Vaccaro and Max Aebi* Helps readers better understanding spinal phenotypes and their imaging, and how today's knowledge will facilitate new targeted drug discovery, novel diagnostics and biomarker discovery, and outcome predictions. Features step-by-step instructions on performing the radiographic measurements with examples of normal and pathologic images to demonstrate the various presentations. Presents clinical correlation of the phenotypes as well as the radiographic measurements with landmark references. Includes validated classification systems that complement the phenotypes and radiographic measurements. Complies the knowledge and expertise of Dr. Dino Samartzis, the preeminent global authority on spinal phenotypes who has discovered and proposed new phenotypes and classification schemes; Dr. Howard S. An, a leading expert in patient management and at the forefront of 3D imaging of various spinal phenotypes; and Dr. Philip Louie, a prolific surgeon who is involved in one of the largest machine learning initiatives of spinal phenotyping. |
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
Topical term or geographic name as entry element |
Spine |
9 (RLIN) |
7969 |
700 ## - ADDED ENTRY--PERSONAL NAME |
Personal name |
An, Howard S. |
700 ## - ADDED ENTRY--PERSONAL NAME |
Personal name |
Samartzis, Dino |
856 ## - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
<a href="https://go.openathens.net/redirector/nhs?url=https://www.clinicalkey.com/dura/browse/bookChapter/3-s2.0-C20190006929">https://go.openathens.net/redirector/nhs?url=https://www.clinicalkey.com/dura/browse/bookChapter/3-s2.0-C20190006929</a> |