Liver Enhancement on Computed Tomography Is Suboptimal in Patients with Liver Steatosis

This study’s aim was twofold. Firstly, to assess liver enhancement quantitatively and qualitatively in steatotic livers compared to non-steatotic livers on portal venous computed tomography (CT). Secondly, to determine the injection volume of contrast medium in patients with severe hepatic steatosis to improve the image quality of the portal venous phase. We retrospectively included patients with non-steatotic (n = 70), the control group, and steatotic livers (n = 35) who underwent multiphase computed tomography between March 2016 and September 2020. Liver enhancement was determined by the difference in attenuation in Hounsfield units (HU) between the pre-contrast and the portal venous phase, using region of interests during in three different segments. Liver steatosis was determined by a mean attenuation of ≤40 HU on unenhanced CT. Adequate enhancement was objectively defined as ≥50 ΔHU and subjectively using a three-point Likert scale. Enhancement of non-steatotic and steatotic livers were compared and associations between enhancement and patient- and scan characteristics were analysed. Enhancement was significantly higher among the control group (mean 51.9 ± standard deviation 11.5 HU) compared to the steatosis group (40.6 ± 8.4 HU p for difference < 0.001). Qualitative analysis indicated less adequate enhancement in the steatosis group: 65.7% of the control group was rated as good vs. 8.6% of the steatosis group. We observed a significant correlation between enhancement, and presence/absence of steatosis and grams of iodine per total body weight (TBW) (p < 0.001; adjusted R2 = 0.303). Deduced from this correlation, theoretical contrast dosing in grams of Iodine (g I) can be calculated: g I = 0.502 × TBW for non-steatotic livers and g I = 0.658 × TBW for steatotic livers. Objective and subjective enhancement during CT portal phase were significantly lower in steatotic livers compared to non-steatotic livers, which may have consequences for detectability and contrast dosing.

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Value of CT Imaging in the Differentiation of Gastric Leiomyoma From Gastric Stromal Tumor

Canadian Association of Radiologists Journal ◽

10.1177/0846537119885671 ◽

2020 ◽

pp. 084653711988567

Author(s):

Jian Wang ◽

Xiaoxuan Zhou ◽

Fangyi Xu ◽

Weiqun Ao ◽

Hongjie Hu

Keyword(s):

Computed Tomography ◽

Multivariate Logistic Regression Analysis ◽

Fisher Exact Test ◽

Exact Test ◽

Portal Venous Phase ◽

Ct Value ◽

Unenhanced Ct ◽

Gastric Stromal Tumor ◽

Venous Phase ◽

Gastric Leiomyoma

Purpose: To discuss significant computed tomography (CT) findings that differentiate gastric leiomyomas (GLs) from small gastric stromal tumors (GSTs). Methods: One hundred sixty cases with pathologically proven GLs (n = 50) and GSTs (n = 110) with comprehensive CT images were enrolled in this retrospective study. Computed tomography findings (ie, size, location, contour, growth pattern, enhancement degree, necrosis, ulceration, calcification, and lymph nodes) were analyzed through the χ2 or Fisher exact test, independent T test, and multivariate (logistic regression) analysis. Sensitivity and specificity were also calculated. Results: Features of cardia location, endophytic growth, homogeneous gradual enhancement, absent of necrosis, long diameter less than 24 mm, short diameter less than 20 mm, unenhanced CT value larger than 35.2 Hounsfield units (HU), portal venous phase CT value larger than 67.4 HU, and enhancement degree of arterial and venous phase less than 16.2 HU and 32.4 HU were found to be statistically significant between GLs and small GSTs ( P < .05). On multivariate analysis, cardia location, endophytic growth, and homogeneous gradual enhancement were independent predictive factors for GLs and small GSTs. Conclusion: These 10 CT criteria are very helpful to differentiate GLs from small GSTs. Especially cardia location, endophytic growth, and homogeneous gradual enhancement are of high value in differential diagnosis.

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Virtual Monoenergetic Images From a Novel Dual-Layer Spectral Detector Computed Tomography Scanner in Portal Venous Phase

Journal of Computer Assisted Tomography ◽

10.1097/rct.0000000000000711 ◽

2018 ◽

Vol 42 (3) ◽

pp. 350-356 ◽

Cited By ~ 6

Author(s):

Tilman Hickethier ◽

Andra-Iza Iuga ◽

Simon Lennartz ◽

Myriam Hauger ◽

Jonathan Byrtus ◽

...

Keyword(s):

Computed Tomography ◽

Portal Venous Phase ◽

Venous Phase ◽

Virtual Monoenergetic Images ◽

Computed Tomography Scanner ◽

Monoenergetic Images

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Hepatic arterial phase and portal venous phase computed tomography for dose calculation of stereotactic body radiation therapy plans in liver cancer: a dosimetric comparison study

Radiation Oncology ◽

10.1186/1748-717x-8-264 ◽

2013 ◽

Vol 8 (1) ◽

pp. 264 ◽

Cited By ~ 2

Author(s):

Jianghong Xiao ◽

Yan Li ◽

Qingfeng Jiang ◽

Lan Sun ◽

Fraser Henderson Jr ◽

...

Keyword(s):

Computed Tomography ◽

Radiation Therapy ◽

Liver Cancer ◽

Stereotactic Body Radiation Therapy ◽

Dose Calculation ◽

Arterial Phase ◽

Comparison Study ◽

Portal Venous Phase ◽

Hepatic Arterial Phase ◽

Venous Phase

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Washout of hepatocellular carcinoma on portal venous phase of multidetector computed tomography in a pre-transplant population

Journal of Medical Imaging and Radiation Oncology ◽

10.1111/1754-9485.12347 ◽

2015 ◽

Vol 59 (6) ◽

pp. 673-680 ◽

Cited By ~ 2

Author(s):

Yu Xuan Kitzing ◽

Bernard HK Ng ◽

Bjoern Kitzing ◽

Richard Waugh ◽

James G Kench ◽

...

Keyword(s):

Computed Tomography ◽

Hepatocellular Carcinoma ◽

Multidetector Computed Tomography ◽

Portal Venous Phase ◽

Venous Phase

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Body size indices to determine iodine mass with contrast-enhanced multi-detector computed tomography of the upper abdomen: does body surface area outperform total body weight or lean body weight?

European Radiology ◽

10.1007/s00330-013-2808-z ◽

2013 ◽

Vol 23 (7) ◽

pp. 1855-1861 ◽

Cited By ~ 32

Author(s):

Hiroshi Kondo ◽

Masayuki Kanematsu ◽

Satoshi Goshima ◽

Haruo Watanabe ◽

Hiroshi Kawada ◽

...

Keyword(s):

Computed Tomography ◽

Body Weight ◽

Body Size ◽

Body Surface ◽

Total Body Weight ◽

Lean Body Weight ◽

Contrast Enhanced ◽

Total Body ◽

Upper Abdomen ◽

Multi Detector Computed Tomography

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Towards Personalised Contrast Injection: Artificial-Intelligence-Derived Body Composition and Liver Enhancement in Computed Tomography

Journal of Personalized Medicine ◽

10.3390/jpm11030159 ◽

2021 ◽

Vol 11 (3) ◽

pp. 159

Author(s):

Daan J. de Jong ◽

Wouter B. Veldhuis ◽

Frank J. Wessels ◽

Bob de Vos ◽

Pim Moeskops ◽

...

Keyword(s):

Artificial Intelligence ◽

Computed Tomography ◽

Body Mass Index ◽

Body Weight ◽

Body Mass ◽

Total Body Weight ◽

Lean Body Weight ◽

Contrast Enhanced ◽

Total Body ◽

Enhanced Computed Tomography

In contrast-enhanced computed tomography, total body weight adapted contrast injection protocols have proven successful in achieving a homogeneous enhancement of vascular structures and liver parenchyma. However, because solid organs have greater perfusion than adipose tissue, the lean body weight (fat-free mass) rather than the total body weight is theorised to cause even more homogeneous enhancement. We included 102 consecutive patients who underwent a multiphase abdominal computed tomography between March 2016 and October 2019. Patients received contrast media (300 mgI/mL) according to bodyweight categories. Using regions of interest, we measured the Hounsfield unit (HU) increase in liver attenuation from unenhanced to contrast-enhanced computed tomography. Furthermore, subjective image quality was graded using a four-point Likert scale. An artificial intelligence algorithm automatically segmented and determined the body compositions and calculated the percentages of lean body weight. The hepatic enhancements were adjusted for iodine dose and iodine dose per total body weight, as well as percentage lean body weight. The associations between enhancement and total body weight, body mass index, and lean body weight were analysed using linear regression. Patients had a median age of 68 years (IQR: 58–74), a total body weight of 81 kg (IQR: 73–90), a body mass index of 26 kg/m2 (SD: ±4.2), and a lean body weight percentage of 50% (IQR: 36–55). Mean liver enhancements in the portal venous phase were 61 ± 12 HU (≤70 kg), 53 ± 10 HU (70–90 kg), and 53 ± 7 HU (≥90 kg). The majority (93%) of scans were rated as good or excellent. Regression analysis showed significant correlations between liver enhancement corrected for injected total iodine and total body weight (r = 0.53; p < 0.001) and between liver enhancement corrected for lean body weight and the percentage of lean body weight (r = 0.73; p < 0.001). Most benefits from personalising iodine injection using %LBW additive to total body weight would be achieved in patients under 90 kg. Liver enhancement is more strongly associated with the percentage of lean body weight than with the total body weight or body mass index. The observed variation in liver enhancement might be reduced by a personalised injection based on the artificial-intelligence-determined percentage of lean body weight.

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Comparison of Orthodontic Root Resorption of Root-filled and Vital Teeth Using Micro–computed Tomography

The Angle Orthodontist ◽

10.2319/022819-153.1 ◽

2019 ◽

Vol 90 (1) ◽

pp. 56-62 ◽

Cited By ~ 2

Author(s):

Kadir Kolcuoğlu ◽

Aslihan Zeynep Oz

Keyword(s):

Computed Tomography ◽

Tooth Extraction ◽

Root Resorption ◽

Cervical Region ◽

Control Group ◽

Micro Computed Tomography ◽

Mean Values ◽

The Mean ◽

The Difference ◽

Experimental Group

ABSTRACT Objective To evaluate the difference in orthodontic root resorption between root-filled and vital teeth. Material and Methods Sixteen individuals who required bilateral premolar tooth extraction due to orthodontic treatment and had a previously root-filled premolar tooth on one side were included in the study. The experimental group consisted of root-filled premolar teeth, and the control group consisted of contralateral vital premolar teeth. A 150-g buccally directed force was applied to these teeth using 0.017 × 0.025-inch TMA cantilever springs. The premolars were extracted 8 weeks after the application of force. Images were obtained using micro–computed tomography. Resorption measurements were obtained using the Image J program. Results The mean values for resorption were 0.08869 mm3 for the root-filled teeth and 0.14077 mm3 for the contralateral teeth, indicating significantly less resorption for the root-filled teeth compared with the contralateral teeth after the application of orthodontic force (P = .003). In both groups, the most resorption was seen on the cervical-buccal and apical-lingual surfaces. The mean resorption value of the cervical region was 0.06305 mm3 in the control group and 0.0291 mm3 in the experimental group, and the difference was statistically significant (P = .002). Conclusions Root-filled teeth showed significantly less orthodontic root resorption than vital teeth.

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