Literature DB >> 22361033

Assessing hepatomegaly: automated volumetric analysis of the liver.

Marius George Linguraru1, Jesse K Sandberg, Elizabeth C Jones, Nicholas Petrick, Ronald M Summers.   

Abstract

RATIONALE AND
OBJECTIVES: The aims of this study were to define volumetric nomograms for identifying hepatomegaly and to retrospectively evaluate the performance of radiologists in assessing hepatomegaly.
MATERIALS AND METHODS: Livers were automatically segmented from 148 abdominal contrast-enhanced computed tomographic scans: 77 normal livers and 71 cases of hepatomegaly (diagnosed by visual inspection and/or linear liver height by radiologists). Quantified liver volumes were compared to manual measurements using volume overlap and error. Liver volumes were normalized to body surface area, from which hepatomegaly nomograms were defined (H scores) by analyzing the distribution of liver sizes in the healthy population. H scores were validated against consensus reports. The performance of radiologists in diagnosing hepatomegaly was retrospectively evaluated.
RESULTS: The automated segmentation of livers was robust, with volume overlap and error of 96.2% and 2.2%, respectively. There were no significant differences (P > .10) between manual and automated segmentation for either the normal or the hepatomegaly subgroup. The average volumes of normal and enlarged livers were 1.51 ± 0.25 and 2.32 ± 0.75 L, respectively. One-way analysis of variance found that body surface area (P = .004) and gender (P = .02), but not age, significantly affected normal liver volume. No significant effects were observed for two-way and three-way interactions among the three variables (P > .18). H-score cutoffs of 0.92 and 1.08 L/m2 were used to define mild and massive hepatomegaly (95% confidence interval, ± 0.02 L/m2). Using the H score as the reference standard, the sensitivity of radiologists in detecting all, mild, and massive hepatomegaly was 84.4%, 56.7%, and 100.0% at 90.1% specificity, respectively. Radiologists disagreed on 20.9% of the diagnosed cases (n = 31). The area under the receiver-operating characteristic curve of the H-score criterion for hepatomegaly detection was 0.98.
CONCLUSIONS: Nomograms for the identification and grading of hepatomegaly from automatic volumetric liver assessment normalized to body surface area (H scores) are introduced. H scores match well with clinical interpretations for hepatomegaly and may improve hepatomegaly detection compared with height measurements or visual inspection, commonly used in current clinical practice. Published by Elsevier Inc.

Entities:  

Mesh:

Year:  2012        PMID: 22361033      PMCID: PMC3319283          DOI: 10.1016/j.acra.2012.01.015

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  52 in total

1.  Estimation of the human liver volume and configuration using three-dimensional ultrasonography: effect of a high-caloric liquid meal.

Authors:  T Hausken; D F Leotta; S Helton; K V Kowdley; B Goldman; S Vaezy; E L Bolson; F H Sheehan; R W Martin
Journal:  Ultrasound Med Biol       Date:  1998-11       Impact factor: 2.998

Review 2.  Riedel's lobe of the liver and its clinical implication.

Authors:  M Kudo
Journal:  Intern Med       Date:  2000-02       Impact factor: 1.271

3.  DIAGNOSTIC VALUE OF SCINTILLATION SCANNING OF THE LIVER.

Authors:  J G MCAFEE; R G AUSE; H N WAGNER
Journal:  Arch Intern Med       Date:  1965-07

4.  Liver volume determination by ultrasonic scanning.

Authors:  S N Rasmussen
Journal:  Br J Radiol       Date:  1972-08       Impact factor: 3.039

5.  Intraoperative color Doppler ultrasonography for partial-liver transplantation from the living donor in pediatric patients.

Authors:  H Kasai; M Makuuchi; S Kawasaki; S Ishizone; S Kitahara; H Matsunami; H Kawarazaki
Journal:  Transplantation       Date:  1992-07       Impact factor: 4.939

6.  Liver segmentation in living liver transplant donors: comparison of semiautomatic and manual methods.

Authors:  Laurent Hermoye; Ismael Laamari-Azjal; Zhujiang Cao; Laurence Annet; Jan Lerut; Benoit M Dawant; Bernard E Van Beers
Journal:  Radiology       Date:  2004-11-24       Impact factor: 11.105

7.  Spleen enlargement in patients with nonalcoholic fatty liver: correlation between degree of fatty infiltration in liver and size of spleen.

Authors:  Y Tsushima; K Endo
Journal:  Dig Dis Sci       Date:  2000-01       Impact factor: 3.199

8.  Liver volume measurement by ultrasonography in normal subjects and alcoholic patients.

Authors:  N W Leung; P Farrant; T J Peters
Journal:  J Hepatol       Date:  1986       Impact factor: 25.083

9.  Prognostic indicators in compensated cirrhosis.

Authors:  M Zoli; M R Cordiani; G Marchesini; T Iervese; A M Labate; C Bonazzi; G Bianchi; E Pisi
Journal:  Am J Gastroenterol       Date:  1991-10       Impact factor: 10.864

10.  Calculation of child and adult standard liver volume for liver transplantation.

Authors:  K Urata; S Kawasaki; H Matsunami; Y Hashikura; T Ikegami; S Ishizone; Y Momose; A Komiyama; M Makuuchi
Journal:  Hepatology       Date:  1995-05       Impact factor: 17.425

View more
  8 in total

Review 1.  Progress in Fully Automated Abdominal CT Interpretation.

Authors:  Ronald M Summers
Journal:  AJR Am J Roentgenol       Date:  2016-04-21       Impact factor: 3.959

2.  Assessing splenomegaly: automated volumetric analysis of the spleen.

Authors:  Marius George Linguraru; Jesse K Sandberg; Elizabeth C Jones; Ronald M Summers
Journal:  Acad Radiol       Date:  2013-03-25       Impact factor: 3.173

3.  Automated CT and MRI Liver Segmentation and Biometry Using a Generalized Convolutional Neural Network.

Authors:  Kang Wang; Adrija Mamidipalli; Tara Retson; Naeim Bahrami; Kyle Hasenstab; Kevin Blansit; Emily Bass; Timoteo Delgado; Guilherme Cunha; Michael S Middleton; Rohit Loomba; Brent A Neuschwander-Tetri; Claude B Sirlin; Albert Hsiao
Journal:  Radiol Artif Intell       Date:  2019-03-27

4.  Deep Learning CT-based Quantitative Visualization Tool for Liver Volume Estimation: Defining Normal and Hepatomegaly.

Authors:  Alberto A Perez; Victoria Noe-Kim; Meghan G Lubner; Peter M Graffy; John W Garrett; Daniel C Elton; Ronald M Summers; Perry J Pickhardt
Journal:  Radiology       Date:  2021-10-26       Impact factor: 11.105

5.  Comparison of liver volumetry on contrast-enhanced CT images: one semiautomatic and two automatic approaches.

Authors:  Wei Cai; Baochun He; Yingfang Fan; Chihua Fang; Fucang Jia
Journal:  J Appl Clin Med Phys       Date:  2016-11-08       Impact factor: 2.102

6.  Simple diameter measurement as predictor of liver volume and liver parenchymal disease.

Authors:  D Seppelt; T Ittermann; M L Kromrey; C Kolb; C vWahsen; P Heiss; H Völzke; R T Hoffmann; J P Kühn
Journal:  Sci Rep       Date:  2022-01-24       Impact factor: 4.379

7.  Efficacy of ruxolitinib on hepatomegaly in patients with myelofibrosis.

Authors:  S Verstovsek; E Atallah; J Mascarenhas; H Sun; M Montgomery; V Gupta; R Mesa; J Gotlib
Journal:  Leukemia       Date:  2015-11-03       Impact factor: 11.528

Review 8.  Ultrasound imaging of the liver and bile ducts - expectations of a clinician.

Authors:  Krzysztof Skoczylas; Andrzej Pawełas
Journal:  J Ultrason       Date:  2015-09-30
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.