PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 2179660

Optimization of survey protocols for MRI.

E R McVeigh·R M Henkelman·M J Bronskill
View original source ↗Export metadata ↓

Abstract

A method for evaluating the sensitivity of MRI protocols to changes in an arbitrary number of tissue parameters over a broad range of parameter values is presented. This analysis is useful for choosing an optimal basis set of images for either a "survey" protocol or tissue segmentation algorithms. A survey protocol is required when searching for a lesion of unknown type or location. Segmentation requires unique signal signatures for tissues that may cover a broad range of tissue parameter values. Data acquisition is modeled as a mapping of a domain of tissue parameter values into a signal manifold in a signal strength space defined by the MRI protocol. The efficacy of the protocol is evaluated by investigating the characteristics of the signal manifold. A figure of merit which maximizes the probability of discriminating each point in the domain of tissue parameters from all others is developed.

Explore related subjects

Clinical ProtocolsHumansMagnetic Resonance ImagingSensitivity and SpecificityJournal ArticleResearch Support, Non-U.S. Gov't

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

E R McVeigh, R M Henkelman, M J Bronskill. 1990. Optimization of survey protocols for MRI.. https://doi.org/10.1002/mrm.1910130202

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2007

Oral care in the intensive care unit: a review.

Oral care for patients in the hospital's Intensive Care Unit (ICU) is important, but this is usually the responsibility of nurses without sufficient knowledge in oral care or comprehensive protocols to follow. The problems of maintaining oral care with oral intubation, performing oral assessment, guidelines for oral hygiene care, frequency of oral care needed, and suggested mouth care protocol followed by recommendations are presented and discussed in this paper.

Clinical Protocols↗
PubMed2007

Implementation of a data management program in a pediatric cancer unit in a low income country.

INTRODUCTION: Pediatric cancer units in low-income countries lack data on which to base quality improvement initiatives. We implemented a data management program in the oncology unit of the children's hospital of Tegucigalpa, Honduras, and then we assessed training and supervision of data managers, data accuracy, and completeness as well as obstacles encountered. METHODS: Training included 2 days of off-site hands-on instruction in the use of an online database, daily on-site supervision by physicians, periodic online meetings for education and problem-solving, and continuous e-mail support. RESULTS: Of the 652 patients diagnosed with acute leukemia between July 1995 and June 2005, 150 (23%) had not yet been registered in the database at the time of audit and 65 (10%) had missing medical records. The remaining 437 charts (67%) were reviewed by an external auditor and compared to the data entered previously by the two trained data managers. Protocol information was incomplete in 30% of cases, and the cause of death was inaccurate in 18%. All other data were 99% accurate and 93%-100% complete. Obstacles included a limited medical records system, poor organization of the charts, missing records, inconsistently documented protocol information, data managers who lack a medical background, and slow or unreliable internet connections. CONCLUSION: Data managers can be trained to effectively collect basic pediatric oncology data in a low-income country. Addressing inadequacies in the medical record system while providing specific training in protocol-based care and determination of cause of death for both physicians and data managers will improve data quality.

Clinical Protocols↗
PubMed2007

Creation of a CT Image Library for the Lung Screening Study of the National Lung Screening Trial.

The CT Image Library (CTIL) of the Lung Screening Study (LSS) network of the National Lung Screening Trial (NLST) consists of up to three annual screens using CT imaging from each of 17,308 participants with a significant history of smoking but no evidence of cancer at trial enrollment (Fall 2002-Spring 2004). Screens performed at numerous medical centers associated with 10 LSS-NLST screening centers are deidentified of protected health information and delivered to the CTIL via DVD, external hard disk, or Internet/Virtual Private Network transmission. The collection will be completed in late 2006. The CTIL is of potential interest to clinical researchers and software developers of nodule detection algorithms. Its attractiveness lies in its very specific, well-defined patient population, scanned via a common CT protocol, and in its collection of evenly spaced serial screens. In this work, we describe the technical details of the CTIL collection process from screening center retrieval through library storage.

Clinical Protocols↗