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Acad Radiol. 2016 Sep;23(9):1190-8. doi: 10.1016/j.acra.2016.04.003. Epub 2016 Jun 7.

Volumes Learned: It Takes More Than Size to "Size Up" Pulmonary Lesions.

Author information

1
Elucid Bioimaging Inc., 225 Main Street, Wenham, MA 01984. Electronic address: xiaonan.ma@elucidbio.com.
2
Department of Radiology, Brigham and Women's Hospital, Boston Massachusetts; Department of Radiology (hospital-based), Harvard Medical School, Boston, Massachusetts.
3
Elucid Bioimaging Inc., 225 Main Street, Wenham, MA 01984.
4
Department of Internal Medicine, Rush University, Chicago, Illinois.

Abstract

RATIONALE AND OBJECTIVES:

This study aimed to review the current understanding and capabilities regarding use of imaging for noninvasive lesion characterization and its relationship to lung cancer screening and treatment.

MATERIALS AND METHODS:

Our review of the state of the art was broken down into questions about the different lung cancer image phenotypes being characterized, the role of imaging and requirements for increasing its value with respect to increasing diagnostic confidence and quantitative assessment, and a review of the current capabilities with respect to those needs.

RESULTS:

The preponderance of the literature has so far been focused on the measurement of lesion size, with increasing contributions being made to determine the formal performance of scanners, measurement tools, and human operators in terms of bias and variability. Concurrently, an increasing number of investigators are reporting utility and predictive value of measures other than size, and sensitivity and specificity is being reported. Relatively little has been documented on quantitative measurement of non-size features with corresponding estimation of measurement performance and reproducibility.

CONCLUSIONS:

The weight of the evidence suggests characterization of pulmonary lesions built on quantitative measures adds value to the screening for, and treatment of, lung cancer. Advanced image analysis techniques may identify patterns or biomarkers not readily assessed by eye and may also facilitate management of multidimensional imaging data in such a way as to efficiently integrate it into the clinical workflow.

KEYWORDS:

Computed tomography; lung-cancer; screening

PMID:
27287713
DOI:
10.1016/j.acra.2016.04.003
[Indexed for MEDLINE]

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