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Objective and Subjective Image Quality of Liver Parenchyma and Hepatic Metastases with Virtual Monoenergetic Dual-source Dual-energy CT Reconstructions

Rationale and Objectives

To compare in dual-energy CT (DECT) conventionally reconstructed polyenergetic images (PEI) at 120 kVp to virtual monoenergetic images (MEI) at different kiloelectron volt (keV) levels for evaluation of liver and gastrointestinal stromal tumor (GIST) hepatic metastases with regard to objective (IQob) and subjective image quality (IQsub) assessed by two readers of varying experience. Image quality was correlated to patient size and compared between PEI and MEI.

Materials and Methods

From 50 examinations of 17 GIST patients (12 with hepatic metastases) undergoing abdominal dual-source DECT for staging, therapy monitoring or follow-up, PEI and nine MEI in 10-keV intervals from 40 to 120 keV were reconstructed. Liver contrast-to-noise ratios (CNR) and metastasis-to-liver ratios were calculated. MEI reconstructions with the highest IQob were compared to PEI for IQsub by one experienced reader (ER) and one inexperienced reader (IR). Patients’ diameters were correlated to IQob and IQsub ratings.

Results

MEI at 70 keV had the highest IQob with equal liver CNR and metastasis-to-liver ratio compared to PEI. The ER rated 70-keV MEI and PEI equally high (median 4), whereas the IR rated IQsub best in 70-keV MEI (median 5). Unlike in PEI, IQsub ratings in 70-keV MEI were not correlated to patient size.

Conclusions

MEI at 70 keV provided an IQob equivalent to PEI. Regarding the IR, IQsub was improved in 70-keV MEI compared to PEI and less dependent on patient size. Therefore, IRs might improve their diagnostic confidence in the assessment of hepatic GIST metastases by evaluating MEI reconstructions at 70 keV.

Gastrointestinal stromal tumors (GISTs) constitute a rare mesenchymal tumor entity with an incidence of 1.5/100,000/year . GISTs may develop throughout the gastrointestinal tract, but the most frequent location is the stomach, followed by the small bowel . The predominant location of GIST metastatic spread is the liver, followed by the peritoneum . Contrast-enhanced abdominal and pelvic computed tomography (CT) is the standard imaging method for staging and follow-up, except for rectal GIST, where magnetic resonance imaging is the imaging modality of choice .

About half of the patients suffering from GIST are presenting with metastatic disease at the time of diagnosis and almost two-thirds of patients with metastatic GIST have hepatic lesions . Typical morphologic changes, such as myxoid degeneration or so-called nodules within a mass and decreasing lesion density, and functional changes, such as hypovascularization of the GIST metastases, are known to occur in the course of treatment in case of response to therapy, and the accurate characterization of these lesions has direct consequences on the patient’s treatment regime .

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Materials and methods

Study Population

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Image Acquisition

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Image Reconstruction

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Figure 1, Axial slices of an abdominal dual-source dual-energy computed tomography angiography of a 58-year-old man with advanced gastrointestinal stromal tumor (GIST) and hypovascular hepatic GIST metastases: (a) 0.3–average-weighted polyenergetic image, (b) virtual monoenergetic image at a level of 120 keV, (c) at 110 keV, (d) at 100 keV, (e) at 90 keV, (f) at 80 keV, (g) at 70 keV, (h) at 60 keV, (i) at 50 keV, and (j) at 40 keV.

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Image Analysis

Objective image quality

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Figure 2, Example of objective image quality assessment performed on axial slices of an abdominal dual-source dual-energy computed tomography (CT) of a 58-year-old man with advanced gastrointestinal stromal tumor (GIST) and both hypovascular and hypervascular hepatic GIST metastases: (a) 0.3–average-weighted polyenergetic image (PEI) corresponding to a 120-kVp single-source CT image, (b) virtual monoenergetic image (MEI) at a level of 70 keV, and (c) at a level of 60 keV with identical window settings. Circular regions of interest were manually drawn over the liver, spleen, aorta, portal vein, and hepatic metastases, if present as in this case.

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CNRx=(MeanX−Meanmuscle)/SDairwhere,x=liver,spleen,aorta,orportalvein. CNR

x

=

(

Mean

X

Mean

muscle

)

/

SD

air

where,

x

=

liver,

spleen,

aorta,

or

portal

vein

.

Metastasis−to−liverratio=|Meanlesion−Meanliver|/SDliver Metastasis

-

to

-

liver

ratio

=

|

Mean

lesion

Mean

liver

|

/

SD

liver

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Subjective image quality

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Statistical Analysis

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Ethics

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Results

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Objective Image Quality

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Figure 3, Box-and-whisker plots of liver parenchyma contrast-to-noise ratios (CNRs) for MEI data sets at nine different virtual monoenergetic kiloelectron levels ranging from 40 keV to 120 keV and 0.3-average-weighted PEI (M0.3) corresponding to 120 kVp. The values measured in data sets of MEI kiloelectron levels in gray are not significantly different from the PEI image; the values measured in data sets of MEI kiloelectron levels in black have significantly higher or lower values compared to the PEI; n = 50.

Figure 4, Box-and-Whisker-Plots of metastasis-to-liver ratios for monoenergetic image (MEI) data sets at nine different virtual monoenergetic energy levels ranging from 40 keV to 120 keV and 0.3–average-weighted polyenergetic image (PEI) (M0.3) corresponding to 120 kVp. The values measured in data sets of MEI kiloelectron volt levels in gray are not significantly different from the PEI image; the values measured in data sets of MEI kiloelectron volt levels in black have significantly higher or lower values compared to the PEI; n = 29.

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Correlation of IQob and patient size

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Figure 5, Image noise as a function of patient size as measured in liver parenchyma, plotted for monoenergetic image (MEI) at all nine investigated kiloelectron volt levels and polyenergetic image (PEI): on the x-axis are the CT numbers (Hounsfield units [HU]) of the standard deviation of attenuation values assessed in liver parenchyma; plotted on the y-axis is the product of anteroposterior (a.p.) and transverse patient diameter [cm 2 ] as a representative value for patient size. Image noise values for 60-, 70-, 80-, 90-, 100-, 110-, and 120-keV and PEI data sets are reaching from 17.3 to 60.3 HU, whereas image noise values for 40- and 50-keV data sets reach from a minimum of 61.3 to a maximum of 204.7 HU. Overall correlation is weak ( r = 0.13, P = .005*), while strong dependency of image noise values on different kiloelectron volt can be appreciated; n = 500.

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Subjective Image Quality

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Table 1

Comparison of Subjective Image Quality Scores for 60-keV MEI, 70-keV MEI, and PEI Data Sets and Inter-rater Agreement

60-keV MEI 70-keV MEI PEI IR 3 (2–5) 5 (3–5) 4 (2–5) ER 3 (2–5) 4 (3–5) 4 (3–5) Difference, P value .68 <.0001 ∗ .33 Kappa 0.407 0.089 0.140

ER, experienced reader, IR, inexperienced reader, MEI, monoenergetic image, PEI, polyenergetic image.

Values are displayed as median (range). Differences between image quality scores of the two readers are calculated by paired Wilcoxon rank sum test. Inter-rater agreement is expressed by weighted Cohen’s kappa.

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Figure 6, Coherence between subjective image quality ratings and objective image quality measurements. Plotted are on the x-axis for monoenergetic image (MEI) at all investigated nine kiloelectron volt levels and the polyenergetic image (PEI) the median values of metastasis-to-liver ratio, contrast-to-noise ratio (CNR) of liver parenchyma, as well as the median rating of the data sets chosen for investigation of subjective image quality (monoenergetic 60 keV, 70 keV, and polyenergetic 0.3–average-weighted data sets [M0.3]) of ER and IR, respectively. ER = experienced reader; IR = inexperienced reader.

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Correlation of IQsub and patient size

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Table 2

Correlation of Patient Size (Represented by the Product of Anteroposterior and Transverse Patient Diameter) and Subjective Image Quality Ratings of IR and ER in 60-keV ME, 70-keV MEI, and PEI

ρ_P_ Value 60-keV MEI IR −0.56 <.0001 ∗ ER −0.34 .02 ∗ 70-keV MEI IR 0.03 .83 ER 0.04 .80 PEI IR −0.32 .02 ∗ ER 0.10 .50

ER, experienced reader, IR, inexperienced reader, MEI, monoenergetic image, PEI, polyenergetic image.

Correlation is expressed by nonparametric Spearman correlation coefficient ρ.

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Discussion

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Limitations

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Conclusions

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