Evidence map›Paper›PMID 27908157›Full record

ArticleMedical physics2016

Volumetry of low-contrast liver lesions with CT: Investigation of estimation uncertainties in a phantom study.

Qin Li, Yongguang Liang, Qiao Huang, Min Zong, Benjamin Berman, Marios A Gavrielides, Lawrence H Schwartz, Binsheng Zhao, Nicholas Petrick

Open access · greenAbstract read
In one paragraph

Article in Medical physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Qin LiDivision of Imaging, Diagnostics and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland 20993.
Yongguang LiangDepartment of Radiology, Columbia University Medical Center, New York, New York 10032.
Qiao HuangDepartment of Radiology, Columbia University Medical Center, New York, New York 10032.
Min ZongDepartment of Radiology, Columbia University Medical Center, New York, New York 10032.
Benjamin BermanDivision of Imaging, Diagnostics and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland 20993.
Marios A GavrielidesDivision of Imaging, Diagnostics and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland 20993.
Lawrence H SchwartzDepartment of Radiology, Columbia University Medical Center, New York, New York 10032.
Binsheng ZhaoDepartment of Radiology, Columbia University Medical Center, New York, New York 10032.
Nicholas PetrickDivision of Imaging, Diagnostics and Software Reliability, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, Maryland 20993.
Columbia University Irving Medical Center · USCenter for Devices and Radiological Health · USUnited States Food and Drug Administration · US

Funding

NIBIB NIH HHS HHSN268201300071C
6 · The paper itself

Abstract

purposeTo evaluate the performance of lesion volumetry in hepatic CT as a function of various imaging acquisition parameters.

methodsAn anthropomorphic abdominal phantom with removable liver inserts was designed for this study. Two liver inserts, each containing 19 synthetic lesions with varying diameter (6-40 mm), shape, contrast (10-65 HU), and both homogenous and mixed-density were designed to have background and lesion CT values corresponding to arterial and portal-venous phase imaging, respectively. The two phantoms were scanned using two commercial CT scanners (GE 750 HD and Siemens Biograph mCT) across a set of imaging protocols (four slice thicknesses, three effective mAs, two convolution kernels, two pitches). Two repeated scans were collected for each imaging protocol. All scans were analyzed using a matched-filter estimator for volume estimation, resulting in 6080 volume measurements across all of the synthetic lesions in the two liver phantoms. A subset of portal venous phase scans was also analyzed using a semi-automatic segmentation algorithm, resulting in about 900 additional volume measurements. Lesions associated with large measurement error (quantified by root mean square error) for most imaging protocols were considered not measurable by the volume estimation tools and excluded for the statistical analyses. Imaging protocols were grouped into distinct imaging conditions based on ANOVA analysis of factors for repeatability testing. Statistical analyses, including overall linearity analysis, grouped bias analysis with standard deviation evaluation, and repeatability analysis, were performed to assess the accuracy and precision of the liver lesion volume biomarker.

resultsLesions with lower contrast and size ≤10 mm were associated with higher measurement error and were excluded from further analysis. Lesion size, contrast, imaging slice thickness, dose, and scanner were found to be factors substantially influencing volume estimation. Twenty-four distinct repeatable imaging conditions were determined as protocols for each scanner with a fixed slice thickness and dose. For the matched-filter estimation approach, strong linearity was observed for all imaging data for lesions ≥20 mm. For the Siemens scanner with 50 mAs effective dose at 0.6 mm slice thickness, grouped bias was about -10%. For all other repeatable imaging conditions with both scanners, grouped biases were low (-3%-3%). There was a trend of increasing standard deviation with decreasing dose. For each fixed dose, the standard deviations were similar among the three larger slice thicknesses (1.25, 2.5, 5 mm for GE, 1.5, 3, 5 mm for Siemens). Repeatability coefficients ranged from about 8% to 75% and showed similar trend to grouped standard deviation. For the segmentation approach, the results led to similar conclusions for both lesion characteristic factors and imaging factors but with increasing magnitude in all the error metrics assessed.

conclusionsResults showed that liver lesion volumetry was strongly dependent on lesion size, contrast, acquisition dose, and their interactions. The overall performances were similar for images reconstructed with larger slice thicknesses, clinically used pitches, kernels, and doses. Conditions that yielded repeatable measurements were identified and they agreed with the Quantitative Imaging Biomarker Alliance's (QIBA) profile requirements in general. The authors' findings also suggest potential refinements to these guidelines for the tumor volume biomarker, especially for soft-tissue lesions.

Indexed as

AlgorithmsPhantoms, ImagingUncertaintyHumansLinear ModelsLiver NeoplasmsReproducibility of ResultsSignal-To-Noise RatioTomography, X-Ray Computed

Identifiers

PMID27908157
PMCPMC5123997
OpenAlexW2551887988

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.