Imaging of the Gallbladder with Multi-energy CT
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Purpose of Review
The goal of this review article is to provide an overview of applications of multi-energy CT as they pertain to gallbladder imaging. We discuss benefits and shortcomings of MECT of various gallbladder pathology, with an emphasis on the imaging of gallstones and cholecystitis. It also touches on promising areas that warrant further investigation.
MECT has demonstrated improved sensitivity for cholelithiasis compared to conventional single-energy CT, with added value of MECT reconstructions, particularly virtual monoenergetic reconstructions, to detect isoattenuating gallstones. MECT iodine maps and virtual monoenergetic images potentially add value in evaluating other gallbladder pathologies, including detecting complications of acute cholecystitis, characterization of xanthogranulomatous cholecystitis and adenomyomatosis, and identifying and evaluating the extent of gallbladder carcinoma.
MECT is emerging as a useful exam to evaluate the gallbladder, particularly in the setting of acute abdominal pain, and has the potential to eliminate the need for other imaging exams such as ultrasound.
KeywordsGallbladder Dual-energy CT Cholelithiasis Adenomyosis Gallbladder carcinoma Xanthogranulomatous cholecystitis
Compliance with Ethical Guidelines
Conflict of interest
Both Yee Seng Ng and Lakshmi Ananthakrishnan declare that there is an institutional research agreement between UT Southwestern Medical Center and both Philips Healthcare and Siemens Healthcare, but neither of the authors has any personal conflict of interest.
Human and Animal Rights and Informed Consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
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- 3.∙∙Fagenholz PJ, Fuentes E, Kaafarani H, Cropano C, King D, de Moya M, Butler K, Velmahos G, Chang Y, Yeh DD. Computed tomography is more sensitive than ultrasound for the diagnosis of acute cholecystitis. Surg Infect (Larchmt). 2015;16(5):509–12. https://doi.org/10.1089/sur.2015.102. Original research demonstrating that CT is more sensitive than ultrasound for acute cholecystitis (contrary to popular opinion). CrossRefGoogle Scholar
- 4.∙∙McCollough CH, Leng S, Yu L, Fletcher JG. Dual- and multi-energy CT: principles, technical approaches, and clinical applications. Radiology. 2015;276(3):637–53. https://doi.org/10.1148/radiol.2015142631. Excellent review which provides a good foundation for understanding the principles of MECT.CrossRefGoogle Scholar
- 11.∙∙Uyeda JW, Richardson IJ, Sodickson AD. Making the invisible visible: improving conspicuity of noncalcified gallstones using dual-energy CT. Abdom Radiol (NY). 2017. https://doi.org/10.1007/s00261-017-1229-x. Original research article assessing use of commercially available MECT reconstructions to improve identification of isoattenuating gallstones.CrossRefGoogle Scholar
- 12.∙∙Yang CB, Zhang S, Jia YJ, Duan HF, Ma GM, Zhang XR, Yu Y, He TP. Clinical application of dual-energy spectral computed tomography in detecting cholesterol gallstones from surrounding bile. Acad Radiol. 2017;24(4):478–82. https://doi.org/10.1016/j.acra.2016.10.006. Original research article assessing use of MECT to detect cholesterol gallstones.CrossRefGoogle Scholar
- 13.∙∙Chen AL, Liu AL, Wang S, Liu JH, Ju Y, Sun MY, Liu YJ. Detection of gallbladder stones by dual-energy spectral computed tomography imaging. World J Gastroenterol. 2015;21(34):9993–8. https://doi.org/10.3748/wjg.v21.i34.9993. Original research article assessing use of MECT to detect cholesterol gallstones.CrossRefGoogle Scholar
- 14.∙Lee HA, Lee YH, Yoon KH, Bang DH, Park DE. Comparison of virtual unenhanced images derived from dual-energy CT with true unenhanced images in evaluation of gallstone disease. Am J Roentgenol. 2016;206(1):74–80. https://doi.org/10.2214/ajr.15.14570. Original research article assessing use of virtual unenhanced images to detect gallstones.CrossRefGoogle Scholar
- 16.Soesbe TC, Lewis MA, Leyendecker JR, Ananthakrishnan L, Lenkinski JR. Differentiating and segmenting isoattenuating cholesterol gallstones from bile using spectral CT material attenuation decomposition (MAD) plots. In: Society of computed body tomography and magnetic resonance, Nashville, TN, 11 September 2017.Google Scholar
- 17.Lewis MA, Soesbe TC, Do QN, Nasr K, Moore WA, Duan X, Gotman S, Lenkinski RE. Spectral CT “Fingerprinting” on a pre-clinical detection based spectral CT scanner: tools for exploration and examples. In: Radiological Society of North America, Chicago, IL, 28 November 2016.Google Scholar
- 18.Lewis MA, Soesbe TC, Ananthakrishnan L, Abbara S, Peshock R, Lenkinski RE. Spectral CT analysis using custom plugins for a clinical DICOM viewer. In: Radiological Society of North America, Chicago, IL, 27 November 2017.Google Scholar
- 20.Harvey RT, Miller WT Jr. Acute biliary disease: initial CT and follow-up US versus initial US and follow-up CT. Radiology. 1999;213(3):831–6. https://doi.org/10.1148/radiology.213.3.r99dc17831.CrossRefPubMedGoogle Scholar
- 21.∙∙Wertz JR, Lopez JM, Olson D, Thompson WM. Comparing the diagnostic accuracy of ultrasound and CT in evaluating acute cholecystitis. Am J Roentgenol. 2018;211(2):W92–7. https://doi.org/10.2214/ajr.17.18884. This original research article compares the diagnostic accuracy of the two most common imaging modalities (ultrasound and CT) in assessment of acute cholecystitis.CrossRefGoogle Scholar
- 22.Young N, Kinsella S, Raio CC, Nelson M, Chiricolo G, Johnson A, Malcolm G, Drumheller BC, Ward MF, Sama A. Economic impact of additional radiographic studies after registered diagnostic medical sonographer (RDMS)-certified emergency physician-performed identification of cholecystitis by ultrasound. J Emerg Med. 2010;38(5):645–51. https://doi.org/10.1016/j.jemermed.2008.10.016.CrossRefPubMedGoogle Scholar
- 23.∙∙Ratanaprasatporn L, Uyeda JW, Wortman JR, Richardson I, Sodickson AD. Multimodality imaging, including dual-energy CT, in the evaluation of gallbladder disease. Radiographics. 2018;38(1):75–89. https://doi.org/10.1148/rg.2018170076. This excellent review article provides an overview of gallbladder evaluation using MECT and other modalities.CrossRefGoogle Scholar
- 28.∙Bonatti M, Vezzali N, Lombardo F, Ferro F, Zamboni G, Tauber M, Bonatti G. Gallbladder adenomyomatosis: imaging findings, tricks and pitfalls. Insights Imaging. 2017;8(2):243–253. https://doi.org/10.1007/s13244-017-0544-7. This excellent review article provides overview of imaging findings of gallbladder adenomyomatosis. CrossRefGoogle Scholar
- 29.∙Yang HK, Lee JM, Yu MH, Lee SM, Park J, Han NY, Lee K, Jang JY, Han JK. CT diagnosis of gallbladder adenomyomatosis: importance of enhancing mucosal epithelium, the “cotton ball sign”. Eur Radiol. 2018. https://doi.org/10.1007/s00330-018-5412-4. Original research evaluating the “cotton ball sign” as a feature associated with adenomyomatosis. CrossRefGoogle Scholar
- 32.∙Kim SW, Kim HC, Yang DM, Ryu JK, Won KY. Gallbladder carcinoma: causes of misdiagnosis at CT. Clin Radiol. 2016;71(1):e96–109. https://doi.org/10.1016/j.crad.2015.10.016. This excellent review provides an overview of the imaging features of gallbladder carcinoma and common imaging pitfalls. CrossRefGoogle Scholar
- 35.Sun K, Han R, Han Y, Shi X, Hu J, Lu B. Accuracy of combined computed tomography colonography and dual energy iodine map imaging for detecting colorectal masses using high-pitch dual-source CT. Sci Rep. 2018;8(1):3790. https://doi.org/10.1038/s41598-018-22188-x.CrossRefPubMedPubMedCentralGoogle Scholar
- 38.∙Liu XS, Gu LH, Du J, Li FH, Wang J, Chen T, Zhang YH. Differential diagnosis of polypoid lesions of the gallbladder using contrast-enhanced sonography. J Ultrasound Med. 2015;34(6):1061–9. https://doi.org/10.7863/ultra.34.6.1061. Original research evaluating various useful MDCT findings in addition to size to differentiate benign and malignant polyps. CrossRefGoogle Scholar
- 40.Chen S, Zhong X, Hu S, Dorn S, Kachelriess M, Lell M, Maier A. Automatic multi-organ segmentation in dual energy CT using 3D fully convolutional network. 2018. Paper presented at the 1st Conference on Medical Imaging with Deep Learning, Amsterdam, The Netherlands, 11 April 2018.Google Scholar
- 41.Uhrig M, Sedlmair M, Schlemmer HP, Hassel JC, Ganten M. Monitoring targeted therapy using dual-energy CT: semi-automatic RECIST plus supplementary functional information by quantifying iodine uptake of melanoma metastases. Cancer Imaging. 2013;13(3):306–13. https://doi.org/10.1102/1470-7330.2013.0031.CrossRefPubMedPubMedCentralGoogle Scholar