Evidence map›Paper›PMID 26406921›Full record

ArticlePhysics in medicine and biology2015

Estimation of optimal b-value sets for obtaining apparent diffusion coefficient free from perfusion in non-small cell lung cancer.

Kishor Karki, Geoffrey D Hugo, John C Ford, Kathryn M Olsen, Siddharth Saraiya, Robert Groves, Elisabeth Weiss

Abstract read
In one paragraph

Article in Physics in medicine and biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 17 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Kishor KarkiDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, VA 23284, USA.
Geoffrey D HugoDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, VA 23284, USA.
John C FordDepartment of Radiation Oncology, University of Miami, Miami, FL 33136, USA.
Kathryn M OlsenDepartment of Radiology, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA.
Siddharth SaraiyaDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, VA 23284, USA.
Robert GrovesDepartment of Radiology, Virginia Commonwealth University, Richmond, VA 23284, USA.
Elisabeth WeissDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, VA 23284, USA.
Virginia Commonwealth University · USUniversity of Colorado Anschutz Medical Campus · USUniversity of Miami · US

Funding

Consistent anatomy registration for lung cancer adaptive radiation therapyR01CA166119 · NCI · WASHINGTON UNIVERSITY · PI HUGO, GEOFFREY D · 2013 to 2017
$1.5M
NCI NIH HHS R01 CA166119
6 · The paper itself

Abstract

The purpose of this study was to determine optimal sets of b-values in diffusion-weighted MRI (DW-MRI) for obtaining monoexponential apparent diffusion coefficient (ADC) close to perfusion-insensitive intravoxel incoherent motion (IVIM) model ADC (ADCIVIM) in non-small cell lung cancer. Ten subjects had 40 DW-MRI scans before and during radiotherapy in a 1.5 T MRI scanner. Respiratory triggering was applied to the echo-planar DW-MRI with TR ≈ 4500 ms, TE  =  74 ms, eight b-values of 0-1000 μs μm(-2), pixel size  =  1.98 × 1.98 mm(2), slice thickness  =  6 mm, interslice gap  =  1.2 mm, 7 axial slices and total acquisition time ≈6 min. One or more DW-MRI scans together covered the whole tumour volume. Monoexponential model ADC values using various b-value sets were compared to reference-standard ADCIVIM values using all eight b-values. Intra-scan coefficient of variation (CV) of active tumour volumes was computed to compare the relative noise in ADC maps. ADC values for one pre-treatment DW-MRI scan of each of the 10 subjects were computed using b-value pairs from DW-MRI images synthesized for b-values of 0-2000 μs μm(-2) from the estimated IVIM parametric maps and corrupted by various Rician noise levels. The square root of mean of squared error percentage (RMSE) of the ADC value relative to the corresponding ADCIVIM for the tumour volume of the scan was computed. Monoexponential ADC values for the b-value sets of 250 and 1000; 250, 500 and 1000; 250, 650 and 1000; 250, 800 and 1000; and 250-1000 μs μm(-2) were not significantly different from ADCIVIM values (p > 0.05, paired t-test). Mean error in ADC values for these sets relative to ADCIVIM were within 3.5%. Intra-scan CVs for these sets were comparable to that for ADCIVIM. The monoexponential ADC values for other sets-0-1000; 50-1000; 100-1000; 500-1000; and 250 and 800 μs μm(-2) were significantly different from the ADCIVIM values. From Rician noise simulation using b-value pairs, there was a wide range of acceptable b-value pairs giving small RMSE of ADC values relative to ADCIVIM. The pairs for small RMSE had lower b-values as the noise level increased. ADC values of a two b-value set-250 and 1000 μs μm(-2), and all three b-value sets with 250, 1000 μs μm(-2) and an intermediate value approached ADCIVIM, with relative noise comparable to that of ADCIVIM. These sets may be used in lung tumours using comparatively short scan and post-processing times. Rician noise simulation suggested that the b-values in the vicinity of these experimental best b-values can be used with error within an acceptable limit. It also suggested that the optimal sets will have lower b-values as the noise level becomes higher.

Indexed as

AlgorithmsAgedCarcinoma, Non-Small-Cell LungComputer SimulationDiffusion Magnetic Resonance ImagingFemaleHumansImage Processing, Computer-AssistedLung NeoplasmsMaleMiddle AgedMotionPerfusionReproducibility of ResultsTumor Burden

Identifiers

PMID26406921
PMCPMC4610399
OpenAlexW2266498400

What OpenQuestion holds

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Registered trials

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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.