Assessment of liver volume with computed tomography and comparison of findings with ultrasonography

Improved precision of noise estimation in CT with a volume-based approach

Assessment of image noise is a relevant issue in computed tomography (CT). Noise is routinely measured by the standard deviation of density values (Hounsfield units, HU) within a circular region of interest (ROI). We explored the effect of a spherical volume of interest (VOI) on noise measurements. Forty-nine chronic obstructive pulmonary disease patients underwent CT with clinical protocol (regular dose [RD], volumetric CT dose index [CTDIvol] 3.04 mGy, 64-slice unit), and ultra-low dose (ULD) protocol (median CTDIvol 0.38 mGy, dual-source unit). Noise was measured in 27 1-cm² ROIs and 27 0.75-cm³ VOIs inside the trachea. Median true noise was 21 HU (range 17-29) for RD-CT and 33 HU (26-39) for ULD-CT. The VOI approach resulted in a lower mean distance between limits of agreement compared to ROI: 5.9 versus 10.0 HU for RD-CT (-40%); 4.7 versus 9.9 HU for ULD-CT (-53%). Mean systematic bias barely changed: -1.6 versus -0.9HU for RD-CT; 0.0 to 0.4HU for ULD-CT. The average measurement time was 6.8 s (ROI) versus 9.7 (VOI), independent of dose level. For chest CT, measuring noise with a VOI-based instead of a ROI-based approach reduces variability by 40-53%, without a relevant effect on systematic bias and measurement time.

A Human REPIN1 Gene Variant: Genetic Risk Factor for the Development of Nonalcoholic Fatty Liver Disease

OBJECTIVES

We tested the hypothesis that a genetic deletion (Del) variant in the REPIN1 gene is associated with the severity of nonalcoholic fatty liver disease (NAFLD) in humans.

METHODS

Sixty-three donors of liver biopsies from individuals with obesity and different degrees of NAFLD and fibrosis were screened for a Del REPIN1 gene variant and liver REPIN1 mRNA expression.

RESULTS

In 8 homozygous Del carriers, we found significantly lower NAFLD activity and fibrosis scores compared with 55 wild-type allele carriers.

DISCUSSION

A Del variant of REPIN1 may be associated with a lower risk of the development of NAFLD.

Reference values of liver volume in Caucasian population and factors influencing liver size

PURPOSE

To investigate factors influencing liver size and to determine reference values of liver volume (LV) for healthy subjects.

METHODS

2773 volunteers underwent magnetic resonance imaging (MRI) of the liver in the setting of the population based Study of Health in Pomerania. Based on measurement of maximum diameters in three orientations, LVs were calculated and correlated with demographic factors such as age, gender, and body mass index. In addition, LVs of healthy volunteers and participants with parenchymal liver diseases such as fatty liver disease, iron overload, fibrosis/cirrhosis were compared. Adjusted reference values of liver volumes were defined for the group of healthy participants.

RESULTS

In general, mean LV (mean ± standard deviation) was 1505 ± 385 cm³. Age, gender and body mass index correlated significantly with the liver volume (p ≤ 0.001). Parenchymal liver diseases significantly influence LV (with: 1624 ± 420 cm³, n = 1525 and without parenchymal liver diseases: 1360 ± 273 cm³; n = 1.248, p ≤ 0.001). Compared to LV of participants without liver diseases, LV was increased in volunteers with hepatic steatosis (1717 ± 419 cm³; n = 1111), liver iron overload (1558 ± 367 cm³; n = 553; p ≤ 0.001) as well as in participants with fibrosis/cirrhosis (1494 ± 459 cm³; n = 383).

CONCLUSIONS

LV is influenced by age, body mass index and parenchymal liver diseases. Reference values were established to aid in the diagnosis of parenchymal liver diseases.

Accuracy of simple approaches to assessing liver volume in radiological imaging

OBJECTIVES

The purpose of the study was to evaluate the accuracy of measured diameters and calculated volume indices for determining liver size and to derive a simple approach for estimating liver volume.

METHODS

Three hundred twenty-nine volunteers (cohort A) were grouped according to liver volume: small (n = 109), medium (n = 110), and large (n = 110). True liver volume was determined by magnetic resonance imaging (MRI) using manual segmentation. Maximum diameters (maxdiam) of the liver and distances in midclavicular line (MCL) were measured. Volume indices were calculated as a simple product of the measured diameters. The calculated volume indices were calibrated to predict true liver volume. Performance of the calibrated method was evaluated in a control group (cohort B) including randomly selected volunteers (n = 110) and a patient group with histopathologically proven parenchymal liver diseases (n = 28).

RESULTS

In cohort A, there was strong correlation between diameters and true liver volume (r s = 0.631-0.823). Calculated volume indices had slightly better correlation (maxdiam r s = 0.903, MCL r s = 0.920). A calibration index was calculated from the volumes and diameters determined in cohort A. Application of this calibration on cohort B verified a very strong correlation between calibrated volume indices and true liver volume (maxdiam r s = 0.920, MCL r s = 0.909). In addition, the low mean difference between predicted liver volume (maxdiam = -70.9 cm(3);MCL = -88.4 cm(3)) and true liver volume confirms that the calibrated method allows accurate assessment of liver volume.

CONCLUSIONS

Both simple diameters and volume indices allow estimating liver size. A simple calibration formula enables prediction of true liver volume without significant expense.

Cross-sectional and longitudinal evaluation of liver volume and total liver fat burden in adults with nonalcoholic steatohepatitis

PURPOSE

To explore the cross-sectional and longitudinal relationships between fractional liver fat content, liver volume, and total liver fat burden.

METHODS

In 43 adults with non-alcoholic steatohepatitis participating in a clinical trial, liver volume was estimated by segmentation of magnitude-based low-flip-angle multiecho GRE images. The liver mean proton density fat fraction (PDFF) was calculated. The total liver fat index (TLFI) was estimated as the product of liver mean PDFF and liver volume. Linear regression analyses were performed.

RESULTS

Cross-sectional analyses revealed statistically significant relationships between TLFI and liver mean PDFF (R 2 = 0.740 baseline/0.791 follow-up, P < 0.001 baseline/P < 0.001 follow-up), and between TLFI and liver volume (R 2 = 0.352/0.452, P < 0.001/< 0.001). Longitudinal analyses revealed statistically significant relationships between liver volume change and liver mean PDFF change (R 2 = 0.556, P < 0.001), between TLFI change and liver mean PDFF change (R 2 = 0.920, P < 0.001), and between TLFI change and liver volume change (R 2 = 0.735, P < 0.001).

CONCLUSION

Liver segmentation in combination with MRI-based PDFF estimation may be used to monitor liver volume, liver mean PDFF, and TLFI in a clinical trial.

Anterior hepatic grooves accompanied by Chilaiditi sign: a retrospective radiological analysis of a neglected anatomical fact

PURPOSE

To evaluate anterior hepatic grooves (AHGs) associated with hepato-diaphragmatic mesocolic indentations (Chilaiditi sign) and to delineate the incidence and potential clinical significance of this association.

METHODS

Between November 2011 and June 2014, abdominal computed tomography examinations of 2,314 patients with varied indications were retrospectively reviewed. Patients were surveyed consecutively for the Chilaiditi sign and syndrome, and cases with grooves at the antero-inferior hepatic surface enclosing the adjacent mesocolic indents were determined. The incidence of AHGs and their predominance by gender and age were determined. The potential clinical significance of AHGs associated with Chilaiditi syndrome and their possible effect on liver volume were assessed.

RESULTS

The incidences of AHGs were similar between genders (p = .461 and p = .646) and age (p = .113 and .621, respectively) among total cohort and patients with Chilaiditi sign, respectively. There was no significant correlation between AHGs and Chilaiditi syndrome (p = .506); no efficacies of AHGs to liver volume were assessed (p = .413).

CONCLUSIONS

The AHGs are rare adaptive changes in shape of the liver without a significant effect on liver volume. This overlooked phenomenon is likely derived from the Chilaiditi sign, but has no significant correlation with Chilaiditi syndrome. Future studies with extended series are encouraged to reveal the possible significance of this phenomenon based on concerned surgical interventions.