Email this article Cardiac visceral fat volume estimation from low-dose chest computed tomography: a study with a designed beating heart phantom
- Authors: Chernina V.Y.1, Kulberg N.S.1, Aleshina O.O.1, Korb T.A.1, Blokhin I.A.1, Morozov S.P.1, Gombolevskiy V.A.1
-
Affiliations:
- Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Healthcare Department
- Issue: Vol 49, No 1 (2021)
- Pages: 61-71
- Section: ARTICLES
- URL: https://almclinmed.ru/jour/article/view/1423
- DOI: https://doi.org/10.18786/2072-0505-2021-49-006
- ID: 1423
Cite item
Full Text
Abstract
Background: Since 2017, a pilot project for lung cancer screening by chest low dose computed tomography (LDCT) has been implemented in Moscow. Patients to be included into the screening have risk factors for ischemic heart disease (IHD). The association between epicardial adipose tissue (EAT) volume and coronary artery atherosclerosis, IHD, and atrial fibrillation has been demonstrated previously.
Aim: To demonstrate the feasibility of LDCTbased EAT volumetry using a dynamic (contracting) heart phantom.
Materials and methods: The study was performed with the designed dynamic heart phantom and chest phantom in two stages. At stage I, two adipose tissue pieces were scanned inside and outside the chest phantom using CT and LDCT. At stage II, the dynamic heart phantom was scanned outside and inside the chest phantom. In addition, we scanned the heart phantom with a coronary calcium phantom. The contracting heart phantom was developed within three months. All scans of the phantom were performed within one day. We determined the adipose tissue thresholds in LDCT and the EAT volumetric error with both chest CT and LDCT. Measurements of the adipose tissue volumes were performed by the radiologist twice with semi-automatic software.
Results: The results of stage I helped to identify optimal density thresholds for LDCT-based adipose tissue volumetry in lung cancer screening, ranging from -250 HU to -30 HU. The stage II results showed that for all heart phantom scanning variants, the average EAT volumetry error did not exceed 5%, except for the case of contracting heart phantom with added coronary calcium in a chest phantom with body mass index (BMI) 29 (-5.92%). Adding the coronary calcium phantom to the heart phantom in LDCT increased the error by an average of 4% in BMI 23 and BMI 29 chest phantoms.
Conclusion: LDCT-based EAT volumetry with fat density threshold from -250 HU to -30 HU is feasible in lung cancer screening, including patients with coronary calcium. However, considering the phantom design, further patient studies, and correlation of EAT volumes between LDCT for lung cancer screening and сoronary CT angiography are required.
About the authors
V. Yu. Chernina
Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Healthcare Department
Author for correspondence.
Email: chernina909@gmail.com
ORCID iD: 0000-0002-0302-293X
Valeria Yu. Chernina – MD, Head of Radiology Research Sector
24–1 Petrovka ul., Moscow, 127051
Russian FederationN. S. Kulberg
Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Healthcare Department
Email: kulberg@npcmr.ru
ORCID iD: 0000-0001-7046-7157
Nikolay S. Kulberg – PhD (in Phys. and Math.), Head of Medical Imaging Department
24–1 Petrovka ul., Moscow, 127051
Russian FederationO. O. Aleshina
Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Healthcare Department
Email: olya.aleshina.tula@gmail.com
ORCID iD: 0000-0001-9924-0204
Olga O. Aleshina – MD, Junior Research Fellow, Radiology Research Sector
24–1 Petrovka ul., Moscow, 127051
Russian FederationT. A. Korb
Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Healthcare Department
Email: t-anya@list.ru
ORCID iD: 0000-0001-9291-1466
Tatiana A. Korb – Junior Research Fellow, Radiology Research Sector
24–1 Petrovka ul., Moscow, 127051
Russian FederationI. A. Blokhin
Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Healthcare Department
Email: i.blokhin@npcmr.ru
ORCID iD: 0000-0002-2681-9378
Ivan A. Blokhin – MD, Junior Research Fellow, Radiology Research Sector
24–1 Petrovka ul., Moscow, 127051
Russian FederationS. P. Morozov
Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Healthcare Department
Email: morozov@npcmr.ru
ORCID iD: 0000-0001-6545-6170
Sergey P. Morozov – MD, PhD, Professor, Director
24–1 Petrovka ul., Moscow, 127051
Russian FederationV. A. Gombolevskiy
Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Healthcare Department
Email: g_victor@mail.ru
ORCID iD: 0000-0003-1816-1315
Victor A. Gombolevskiy – MD, PhD, Head of Medical Research Department
24–1 Petrovka ul., Moscow, 127051
Russian FederationReferences
- Cherian S, Lopaschuk GD, Carvalho E. Cellular cross-talk between epicardial adipose tissue and myocardium in relation to the pathogenesis of cardiovascular disease. Am J Physiol Endocrinol Metab. 2012;303(8):E937–E949. doi: 10.1152/ajpendo.00061.2012.
- Karmazyn M, Purdham DM, Rajapurohitam V, Zeidan A. Signalling mechanisms underlying the metabolic and other effects of adipokines on the heart. Cardiovasc Res. 2008;79(2):279– 286. doi: 10.1093/cvr/cvn115.
- Patel VB, Shah S, Verma S, Oudit GY. Epicardial adipose tissue as a metabolic transducer: role in heart failure and coronary artery disease. Heart Fail Rev. 2017;22(6):889–902. doi: 10.1007/s10741-017-9644-1.
- Dey D, Wong ND, Tamarappoo B, Nakazato R, Gransar H, Cheng VY, Ramesh A, Kakadiaris I, Germano G, Slomka PJ, Berman DS. Computer-aided non-contrast CT-based quantification of pericardial and thoracic fat and their associations with coronary calcium and metabolic syndrome. Atherosclerosis. 2010;209(1):136–141. doi: 10.1016/j.atherosclerosis.2009.08.032.
- Nakanishi R, Rajani R, Cheng VY, Gransar H, Nakazato R, Shmilovich H, Otaki Y, Hayes SW, Thomson LE, Friedman JD, Slomka PJ, Berman DS, Dey D. Increase in epicardial fat volume is associated with greater coronary artery calcification progression in subjects at intermediate risk by coronary calcium score: a serial study using non-contrast cardiac CT. Atherosclerosis. 2011;218(2):363–368. doi: 10.1016/j.atherosclerosis.2011.07.093.
- Tamarappoo B, Dey D, Shmilovich H, Nakazato R, Gransar H, Cheng VY, Friedman JD, Hayes SW, Thomson LE, Slomka PJ, Rozanski A, Berman DS. Increased pericardial fat volume measured from noncontrast CT predicts myocardial ischemia by SPECT. JACC Cardiovasc Imaging. 2010;3(11):1104–1112. doi: 10.1016/j.jcmg.2010.07.014.
- Janik M, Hartlage G, Alexopoulos N, Mirzoyev Z, McLean DS, Arepalli CD, Chen Z, Stillman AE, Raggi P. Epicardial adipose tissue volume and coronary artery calcium to predict myocardial ischemia on positron emission tomography-computed tomography studies. J Nucl Cardiol. 2010;17(5):841–847. doi: 10.1007/s12350-010-9235-1.
- Wong CX, Abed HS, Molaee P, Nelson AJ, Brooks AG, Sharma G, Leong DP, Lau DH, Middeldorp ME, Roberts-Thomson KC, Wittert GA, Abhayaratna WP, Worthley SG, Sanders P. Pericardial fat is associated with atrial fibrillation severity and ablation outcome. J Am Coll Cardiol. 2011;57(17):1745–1751. doi: 10.1016/j.jacc.2010.11.045.
- Cheng VY, Dey D, Tamarappoo B, Nakazato R, Gransar H, Miranda-Peats R, Ramesh A, Wong ND, Shaw LJ, Slomka PJ, Berman DS. Pericardial fat burden on ECG-gated noncontrast CT in asymptomatic patients who subsequently experience adverse cardiovascular events. JACC Cardiovasc Imaging. 2010;3(4):352–360. doi: 10.1016/j.jcmg.2009.12.013.
- Spearman JV, Renker M, Schoepf UJ, Krazinski AW, Herbert TL, De Cecco CN, Nietert PJ, Meinel FG. Prognostic value of epicardial fat volume measurements by computed tomography: a systematic review of the literature. Eur Radiol. 2015;25(11):3372–3381. doi: 10.1007/s00330-015-3765-5.
- Чернина ВЮ, Морозов СП, Низовцова ЛА, Блохин ИА, Ситдиков ДИ, Гомболевский ВА. Роль количественной оценки висцеральной жировой ткани сердца как предиктора развития сердечно-сосудистых событий. Вестник рентгенологии и радиологии. 2019;100(6):387–394. doi: 10.20862/0042-4676-2019-100-6-387-394.
- Kim BJ, Kang JG, Lee SH, Lee JY, Sung KC, Kim BS, Kang JH. Relationship of Echocardiographic Epicardial Fat Thickness and Epicardial Fat Volume by Computed Tomography with Coronary Artery Calcification: Data from the CAESAR Study. Arch Med Res. 2017;48(4): 352–359. doi: 10.1016/j.arcmed.2017.06.010
- Чернина ВЮ, Писов МЕ, Беляев МГ, Бекк ИВ, Замятина КА, Корб ТА, Алешина ОО, Щукина ЕА, Соловьeв АВ, Скворцов РА, Филатова ДА, Ситдиков ДИ, Чеснокова АО, Морозов СП, Гомболевский ВА. Волюметрия эпикардиальной жировой ткани: сравнение полуавтоматического измерения и алгоритма машинного обучения. Кардиология. 2020;60(9):46–54. doi: 10.18087/cardio.2020.9.n1111.
- Морозов СП, Кузьмина ЕС, Ветшева НН, Гомболевский ВА, Лантух ЗА, Полищук НС, Лайпан АШ, Ермолаев СО, Панина ЕВ, Блохин ИА. Московский скрининг: скрининг рака легкого с помощью низкодозовой компьютерной томографии. Проблемы социальной гигиены, здравоохранения и истории медицины. 2019;27(S):630–636. doi: 10.32687/0869-866X-2019-27-si1-630-636.
- Goeller M, Achenbach S, Marwan M, Doris MK, Cadet S, Commandeur F, Chen X, Slomka PJ, Gransar H, Cao JJ, Wong ND, Albrecht MH, Rozanski A, Tamarappoo BK, Berman DS, Dey D. Epicardial adipose tissue density and volume are related to subclinical atherosclerosis, inflammation and major adverse cardiac events in asymptomatic subjects. J Cardiovasc Comput Tomogr. 2018;12(1):67–73. doi: 10.1016/j.jcct.2017.11.007.
- Гомболевский ВА, Блохин ИА, Лайпан АШ, Ермолаев СО, Панина ЕВ, Чернина ВЮ, Николаев АЕ, Морозов СП. Методические рекомендации по скринингу рака легкого. Серия «Лучшие практики лучевой и инструментальной диагностики». Вып. 56. М.: ГБУЗ «НПКЦ ДиТ ДЗМ»; 2020. 53 с.
- Mahabadi AA, Massaro JM, Rosito GA, Levy D, Murabito JM, Wolf PA, O'Donnell CJ, Fox CS, Hoffmann U. Association of pericardial fat, intrathoracic fat, and visceral abdominal fat with cardiovascular disease burden: the Framingham Heart Study. Eur Heart J. 2009;30(7): 850–856. doi: 10.1093/eurheartj/ehn573.
- Thanassoulis G, Massaro JM, Hoffmann U, Mahabadi AA, Vasan RS, O'Donnell CJ, Fox CS. Prevalence, distribution, and risk factor correlates of high pericardial and intrathoracic fat depots in the Framingham heart study. Circ Cardiovasc Imaging. 2010;3(5):559–566. doi: 10.1161/CIRCIMAGING.110.956706.
- Alexopoulos N, McLean DS, Janik M, Arepalli CD, Stillman AE, Raggi P. Epicardial adipose tissue and coronary artery plaque characteristics. Atherosclerosis. 2010;210(1):150–154. doi: 10.1016/j.atherosclerosis.2009.11.020.
- Ueno K, Anzai T, Jinzaki M, Yamada M, Jo Y, Maekawa Y, Kawamura A, Yoshikawa T, Tanami Y, Sato K, Kuribayashi S, Ogawa S. Increased epicardial fat volume quantified by 64-multidetector computed tomography is associated with coronary atherosclerosis and totally occlusive lesions. Circ J. 2009;73(10): 1927–1933. doi: 10.1253/circj.cj-09-0266.
- Yoshizumi T, Nakamura T, Yamane M, Islam AH, Menju M, Yamasaki K, Arai T, Kotani K, Funahashi T, Yamashita S, Matsuzawa Y. Abdominal fat: standardized technique for measurement at CT. Radiology. 1999;211(1):283–286. doi: 10.1148/radiology.211.1.r99ap15283.
- Ding J, Hsu FC, Harris TB, Liu Y, Kritchevsky SB, Szklo M, Ouyang P, Espeland MA, Lohman KK, Criqui MH, Allison M, Bluemke DA, Carr JJ. The association of pericardial fat with incident coronary heart disease: the Multi-Ethnic Study of Atherosclerosis (MESA). Am J Clin Nutr. 2009;90(3):499–504. doi: 10.3945/ajcn.2008.27358.
- Marwan M, Koenig S, Schreiber K, Ammon F, Goeller M, Bittner D, Achenbach S, Hell MM. Quantification of epicardial adipose tissue by cardiac CT: Influence of acquisition parameters and contrast enhancement. Eur J Radiol. 2019;121:108732. doi: 10.1016/j.ejrad.2019.108732.
- Fei X, Du X, Li P, Liao J, Shen Y, Li K. Effect of dose-reduced scan protocols on cardiac coronary image quality with 64-row MDCT: a cardiac phantom study. Eur J Radiol. 2008;67(1): 85–91. doi: 10.1016/j.ejrad.2007.07.008.
- Horiguchi J, Kiguchi M, Fujioka C, Shen Y, Arie R, Sunasaka K, Ito K. Radiation dose, image quality, stenosis measurement, and CT densitometry using ECG-triggered coronary 64-MDCT angiography: a phantom study. AJR Am J Roentgenol. 2008;190(2):315–320. doi: 10.2214/AJR.07.2191.
- Groves DW, Acharya T, Steveson C, Schuzer JL, Rollison SF, Nelson EA, Sirajuddin A, Sathya B, Bronson K, Shanbhag SM, Chen MY. Performance of single-energy metal artifact reduction in cardiac computed tomography: A clinical and phantom study. J Cardiovasc Comput Tomogr. 2020;14(6):510–515. doi: 10.1016/j.jcct.2020.04.005.
- Kauczor HU, Baird AM, Blum TG, Bonomo L, Bostantzoglou C, Burghuber O, Čepická B, Comanescu A, Couraud S, Devaraj A, Jespersen V, Morozov S, Agmon IN, Peled N, Powell P, Prosch H, Ravara S, Rawlinson J, Revel MP, Silva M, Snoeckx A, van Ginneken B, van Meerbeeck JP, Vardavas C, von Stackelberg O, Gaga M; European Society of Radiology (ESR) and the European Respiratory Society (ERS). ESR/ERS statement paper on lung cancer screening. Eur Radiol. 2020;30(6):3277–3294. doi: 10.1007/s00330-020-06727-7.
- Wielpütz MO, Lederlin M, Wroblewski J, Dinkel J, Eichinger M, Biederer J, Kauczor HU, Puderbach M. CT volumetry of artificial pulmonary nodules using an ex vivo lung phantom: influence of exposure parameters and iterative reconstruction on reproducibility. Eur J Radiol. 2013;82(9):1577–1583. doi: 10.1016/j.ejrad.2013.04.035.
- Dey D, Suzuki Y, Suzuki S, Ohba M, Slomka PJ, Polk D, Shaw LJ, Berman DS. Automated quantitation of pericardiac fat from noncontrast CT. Invest Radiol. 2008;43(2):145–153. doi: 10.1097/RLI.0b013e31815a054a.
- Marano R, Rovere G, Savino G, Flammia FC, Carafa MRP, Steri L, Merlino B, Natale L. CCTA in the diagnosis of coronary artery disease. Radiol Med. 2020;125(11):1102–1113. doi: 10.1007/s11547-020-01283-y.
- Oda S, Utsunomiya D, Funama Y, Yuki H, Kidoh M, Nakaura T, Takaoka H, Matsumura M, Katahira K, Noda K, Oshima S, Tokuyasu S, Yamashita Y. Effect of iterative reconstruction on variability and reproducibility of epicardial fat volume quantification by cardiac CT. J Cardiovasc Comput Tomogr. 2016;10(2):150–155. doi: 10.1016/j.jcct.2015.10.006.
- Bucher AM, Joseph Schoepf U, Krazinski AW, Silverman J, Spearman JV, De Cecco CN, Meinel FG, Vogl TJ, Geyer LL. Influence of technical parameters on epicardial fat volume quantification at cardiac CT. Eur J Radiol. 2015;84(6): 1062–1067. doi: 10.1016/j.ejrad.2015.03.018.
Supplementary files
