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Современные методы оценки восстановительного потенциала печени после ее резекции (обзор)

Современные методы оценки восстановительного потенциала печени после ее резекции (обзор)

С.А. Родимова, Д.С. Кузнецова, Н.В. Бобров, Н.В. Вдовина, В.Е. Загайнов, Е.В. Загайнова
Ключевые слова: восстановительный потенциал печени; функция печени; регенерация печени; пролиферация гепатоцитов; FLIM; ToF-SIMS; CARS.
2019, том 11, номер 4, стр. 175.
DOI: https://doi.org/10.17691/stm2019.11.4.20

Полный текст статьи

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Рассмотрены основные методы оценки функции и восстановительного потенциала печени. Представлены как стандартные, широко применяющиеся в клинической практике, так и новейшие перспективные методы, показавшие свою эффективность для анализа патологических изменений на клеточном и тканевом уровнях и позволяющие в будущем расширить возможности клинической диагностики.

Известно, что динамику регенеративного процесса печени отражают такие параметры, как метаболический статус ее клеток, их морфология, а также структурные особенности на молекулярном уровне. Исследование изменений данных параметров позволит определить критерии снижения функциональной активности клеток печени и в конечном итоге — снижения регенераторного потенциала органа в целом.

Наиболее перспективным методом для решения данной задачи в настоящее время можно назвать мультифотонную микроскопию с возможностью генерации второй гармоники, а также с дополнительными модальностями, такими как микроскопия на основе когерентного антистоксового рамановского рассеяния (coherent anti-stokes Raman spectroscopy — CARS), микроскопия стимулированного комбинационного рассеяния (stimulated Raman scattering — SRS) и времяразрешенная флюоресцентная микроскопия (fluorescence lifetime imaging — FLIM). Кроме того, широкий спектр возможностей для анализа метаболических и структурных изменений дает масс-спектрометрия, в частности времяпролетная масс-спектрометрия вторичных ионов (time-of-flight secondary ion mass spectrometry — ToF-SIMS). Многочисленные примеры исследований с применением данных методов на моделях in vivo, а также на биопсийных образцах пациентов демонстрируют их востребованность и перспективность как в биомедицинских исследованиях, так и в клинической практике.

  1. Wei W., Dirsch O., Mclean A.L., Zafarnia S., Schwier M., Dahmen U. Rodent models and imaging techniques to study liver regeneration. Eur Surg Res 2015; 54(3–4): 97–113, https://doi.org/10.1159/000368573.
  2. Michalopoulos G.K. Liver regeneration. J Cell Physiol 2007; 213(2): 286–300, https://doi.org/10.1002/jcp.21172.
  3. Riehle K.J., Dan Y.Y., Campbell J.S., Fausto N. New concepts in liver regeneration. J Gastroenterol Hepatol 2011; 26: 203–212, https://doi.org/10.1111/j.1440-1746.2010.06539.x.
  4. Taub R. Liver regeneration: from myth to mechanism. Nat Rev Mol Cell Biol 2004; 5(10): 836–847, https://doi.org/10.1038/nrm1489.
  5. Moris D., Vernadakis S., Papalampros A., Vailas M., Dimitrokallis N., Petrou A., Dimitroulis D. Mechanistic insights of rapid liver regeneration after associating liver partition and portal vein ligation for stage hepatectomy. World J Gastroenterol 2016; 22(33): 7613, https://doi.org/10.3748/wjg.v22.i33.7613.
  6. Nilsson H., Karlgren S., Blomqvist L., Jonas E. The inhomogeneous distribution of liver function: possible impact on the prediction of post-operative remnant liver function. HPB 2015; 17(3): 272–277, https://doi.org/10.1111/hpb.12348.
  7. Golse N., Bucur P.O., Adam R., Castaing D., Cunha A.S., Vibert E. New paradigms in post-hepatectomy liver failure. J Gastrointest Surg 2013; 17(3): 593–605, https://doi.org/10.1007/s11605-012-2048-6.
  8. Guglielmi A., Ruzzenente A., Conci S., Valdegamberi A., Iacono C. How much remnant is enough in liver resection? Dig Surg 2012; 29(1): 6–17, https://doi.org/10.1159/000335713.
  9. Truant S., Boleslawski E., Sergent G., Leteurtre E., Duhamel A., Hebbar M., Pruvot F.R. Liver function following extended hepatectomy can be accurately predicted using remnant liver volume to body weight ratio. World J Surg 2015; 39(5): 1193–1201, https://doi.org/10.1007/s00268-014-2929-9.
  10. Краснов О.А., Павленко В.В., Краснов К.А., Краснов А.О., Пельц В.А., Старцев А.Б., Аминов И.Х., Сохарев А.С., Керопян С.Е. Современные методы оценки функционального резерва печени в резекционной хирургии органа. Медицина и образование в Сибири 2014; 6: 37.
  11. Hoekstra L.T., de Graaf W., Nibourg G.A., Heger M., Bennink R.J., Stieger B., van Gulik T.M. Physiological and biochemical basis of clinical liver function tests: a review. Ann Surg 2013; 257(1): 27–36, https://doi.org/10.1097/sla.0b013e31825d5d47.
  12. Stockmann M., Lock J.F., Malinowski M., Niehues S.M., Seehofer D., Neuhaus P. The LiMAx test: a new liver function test for predicting postoperative outcome in liver surgery. HPB 2010; 12(2): 139–146, https://doi.org/10.1111/j.1477-2574.2009.00151.x.
  13. Thomas M.N., Weninger E., Angele M., Bösch F., Pratschke S., Andrassy J., Guba M. Intraoperative simulation of remnant liver function during anatomic liver resection with indocyanine green clearance (LiMON) measurements. HPB 2015; 17(6): 471–476, https://doi.org/10.1111/hpb.12380.
  14. Assy N., Minuk G.Y. Liver regeneration: methods for monitoring and their applications. J Hepatol 1997; 26(4): 945–952, https://doi.org/10.1016/s0168-8278(97)80266-8.
  15. Fernández M.A., Albor C., Ingelmo-Torres M., Nixon S.J., Ferguson C., Kurzchalia T., Pol A. Caveolin-1 is essential for liver regeneration. Science 2006; 313(5793): 1628–1632, https://doi.org/10.1126/science.1130773.
  16. Jia C. Advances in the regulation of liver regeneration. Expert Rev Gastroenterol Hepatol 2011; 5(1): 105–121, https://doi.org/10.1586/egh.10.87.
  17. Will O.M., Damm T., Campbell G.M., von Schönfells W., Açil Y., Will M., Chalaris-Rissmann A., Ayna M., Drucker C., Glüer C.C. Longitudinal micro-computed tomography monitoring of progressive liver regeneration in a mouse model of partial hepatectomy. Lab Anim 2017; 51(4): 422–426, https://doi.org/10.1177/0023677216678824.
  18. McNaughton D.A., Abu-Yousef M.M. Doppler US of the liver made simple. Radiographics 2011; 31(1): 161–188, https://doi.org/10.1148/rg.311105093.
  19. Childs J.T., Thoirs K.A., Esterman A.J. The development of a practical and uncomplicated predictive equation to determine liver volume from simple linear ultrasound measurements of the liver. Radiography 2016; 22(2): 125–130, https://doi.org/10.1016/j.radi.2015.12.009.
  20. Goceri E., Shah Z.K., Layman R., Jiang X., Gurcan M.N. Quantification of liver fat: a comprehensive review. Comput Biol Med 2016; 71: 174–189, https://doi.org/10.1016/j.compbiomed.2016.02.013.
  21. Zhang Y.N., Fowler K.J., Hamilton G., Cui J.Y., Sy E.Z., Balanay M., Sirlin C.B. Liver fat imaging — a clinical overview of ultrasound, CT, and MR imaging. Br J Radiol 2018; 91(1089): 20170959, https://doi.org/10.1259/bjr.20170959.
  22. Parekh M., Kluger M.D., Griesemer A., Bentley-Hibbert S. Regenerative liver surgeries: the alphabet soup of emerging techniques. Abdom Radiol 2016; 41(1): 162–173, https://doi.org/10.1007/s00261-015-0606-6.
  23. Famularo S., Gianotti L., Riggio O. Small-for-flow liver failure after extended hepatectomy: hot questions and an update. Gastroenterology Insights 2017; 8(1): 6–10, https://doi.org/10.4081/gi.2017.6968.
  24. Choi S.H., Kwon J.H., Kim K.W., Jang H.Y., Kim J.H., Kwon H.J., Lee J., Song G.W., Lee S.G. Measurement of liver volumes by portal vein flow by Doppler ultrasound in living donor liver transplantation. Clin Transplant 2017; 31(9): 1–7, https://doi.org/10.1111/ctr.13050.
  25. McCollough C.H., Primak A.N., Braun N., Kofler J., Yu L., Christner J. Strategies for reducing radiation dose in CT. Radiol Clin North Am 2009; 47(1): 27–40, https://doi.org/10.1016/j.rcl.2008.10.006.
  26. Spouse E., Gedroyc W.M. MRI of the claustrophobic patient: interventionally configured magnets. Br J Radiol 2000; 73(866): 146–151, https://doi.org/10.1259/bjr.73.866.10884726.
  27. Di Martino M., Koryukova K., Bezzi M., Catalano C. Imaging features of non-alcoholic fatty liver disease in children and adolescents. Children 2017; 4(8): 73, https://doi.org/10.3390/children4080073.
  28. Wagener G. Assessment of hepatic function, operative candidacy, and medical management after liver resection in the patient with underlying liver disease. Semin Liver Dis 2013; 33(3): 204–212, https://doi.org/10.1055/s-0033-1351777.
  29. Изранов В.А., Казанцева Н.В., Белецкая М.А. Изме­рение объема печени с помощью визуализационных ме­тодов различной модальности. Вестник Балтийского феде­­рального университета им. И. Канта. Серия: Естест­венные и медицинские науки 2017; 2: 52–64.
  30. Чаплыгина Е.В., Губарь А.С. Значения объемных показателей печени в связи с типом телосложения и половой принадлежностью обследованных лиц. Жур­нал анатомии и гистопатологии 2017; 6(1): 101–104.
  31. Cieslak K.P., Runge J.H., Heger M., Stoker J., Bennink R.J., Van Gulik T.M. New perspectives in the assessment of future remnant liver. Dig Surg 2014; 31(4–5): 255–268, https://doi.org/10.1159/000364836.
  32. Hayashi H., Beppu T., Okabe H., Kuroki H., Nakagawa S., Imai K., Baba H. Functional assessment versus conventional volumetric assessment in the prediction of operative outcomes after major hepatectomy. Surgery 2015: 157(1): 20–26, https://doi.org/10.1016/j.surg.2014.06.013.
  33. Thirunavukarasu P., Aloia T.A. Preoperative assessment and optimization of the future liver remnant. Surg Clin North Am 2016; 96(2): 197–205, https://doi.org/10.1016/j.suc.2015.11.001.
  34. Forbes S.J., Newsome P.N. Liver regeneration — mechanisms and models to clinical application. Nat Rev Gastroenterol Hepatol 2016; 13(8): 473–485, https://doi.org/10.1038/nrgastro.2016.97.
  35. Selle D., Preim B., Schenk A., Peitgen H.O. Analysis of vasculature for liver surgical planning. IEEE Trans Med Imaging 2002; 21(11): 1344–1357, https://doi.org/10.1109/tmi.2002.801166.
  36. Wu J., Li H., Lin Y., Chen Z., Zhong Q., Gao H., Fu L., Sandrasegaran K. Value of gadoxetate biliary transit time in determining hepatocyte function. Abdom Imaging 2015; 40(1): 95–101, https://doi.org/10.1007/s00261-014-0200-3.
  37. Srinivasa Babu A., Wells M.L., Teytelboym O.M., Mackey J.E., Miller F.H., Yeh B.M., Venkatesh S.K. Elastography in chronic liver disease: modalities, techniques, limitations, and future directions. Radiographics 2016; 36(7): 1987–2006, https://doi.org/10.1148/rg.2016160042.
  38. Herrmann E., de Lédinghen V., Cassinotto C., Chu W.C., Leung V.Y., Ferraioli G., Filice C., Castera L., Vilgrain V., Ronot M., Dumortier J., Guibal A., Pol S., Trebicka J., Jansen C., Strassburg C., Zheng R., Zheng J., Francque S., Vanwolleghem T., Vonghia L., Manesis E.K., Zoumpoulis P., Sporea I., Thiele M., Krag A., Cohen-Bacrie C., Criton A., Gay J., Deffieux T., Friedrich-Rust M. Assessment of biopsy-proven liver fibrosis by two-dimensional shear wave elastography: an individual patient data-based meta-analysis. Hepatology 2018; 67(1): 260–272, https://doi.org/10.1002/hep.29179.
  39. Srinivasa Babu A., Wells M.L., Teytelboym O.M., Mackey J.E., Miller F.H., Yeh B.M., Ehman R.L., Venkatesh S.K. Elastography in chronic liver disease: modalities, techniques, limitations, and future directions. Radiographics 2016; 36(7): 1987–2006, https://doi.org/10.1148/rg.2016160042.
  40. Castéra L., Foucher J., Bernard P.H., Carvalho F., Allaix D., Merrouche W., Couzigou P., de Lédinghen V. Pitfalls of liver stiffness measurement: a 5-year prospective study of 13,369 examinations. Hepatology 2010; 51(3): 828–835, https://doi.org/10.1002/hep.23425.
  41. Fukuda T., Fukuchi T., Yagi S., Shiojiri N. Immunohistochemical analyses of cell cycle progression and gene expression of biliary epithelial cells during liver regeneration after partial hepatectomy of the mouse. Exp Anim 2016; 65(2): 135–146, https://doi.org/10.1538/expanim.15-0082.
  42. Selzner M., Clavien P.A. Failure of regeneration of the steatotic rat liver: disruption at two different levels in the regeneration pathway. Hepatology 2000; 31(1): 35–42, https://doi.org/10.1002/hep.510310108.
  43. Sumer F., Colakoglu M.K., Ozdemir Y., Ozsay O., İlter O., Bostanci E.B., Akoglu M. Effect of nebivolol on liver regeneration in an experimental 70% partial hepatectomy model. Asian J Surg 2017; 40(5): 375–379, https://doi.org/10.1016/j.asjsur.2015.12.005.
  44. Stratton S.A., Barton M.C. Hierarchy of a regenerative cell cycle: Cyclin E1 multitasks. Hepatology 2014; 59(2): 370–371, https://doi.org/10.1002/hep.26658.
  45. Galand P., Degraef C. Cyclin/PCNA immunostaining as an alternative to tritiated thymidine pulse labelling for marking S phase cells in paraffin sections from animal and human tissues. Cell Tissue Kinet 1989; 22(5): 383–392, https://doi.org/10.1111/j.1365-2184.1989.tb00223.x.
  46. Holecek M., Vodenicarovova M. Phenylbutyrate exerts adverse effects on liver regeneration and amino acid concentrations in partially hepatectomized rats. Int J Exp Pathol 2016; 97(3): 278–284, https://doi.org/10.1111/iep.12190.
  47. Shibuya M., Saito F., Miwa T., Davis R.L., Wilson C.B., Hoshino T. Histochemical study of pituitary adenomas with Ki-67 and anti-DNA polymerase α monoclonal antibodies, bromodeoxyuridine labeling, and nucleolar organizer region counts. Acta Neuropathol 1992; 84(2): 178–183, https://doi.org/10.1007/bf00311392.
  48. Iatropoulos M.J., Williams G.M. Proliferation markers. Exp Toxicol Pathol 1996; 48(2–3): 175–181, https://doi.org/10.1016/s0940-2993(96)80039-x.
  49. Hamano M., Ezaki H., Kiso S., Furuta K., Egawa M., Kizu T., Chatani N., Kamada Y., Yoshida Y., Takehara T. Lipid overloading during liver regeneration causes delayed hepatocyte DNA replication by increasing ER stress in mice with simple hepatic steatosis. J Gastroenterol 2014; 49(2): 305–316, https://doi.org/10.1007/s00535-013-0780-7.
  50. Webster A.F., Williams A., Recio L., Yauk C.L. Bromodeoxyuridine (BrdU) treatment to measure hepatocellular proliferation does not mask furan-induced gene expression changes in mouse liver. Toxicology 2014; 323: 26–31, https://doi.org/10.1016/j.tox.2014.06.002.
  51. Cheng R., Liang X., Zhao Q., Lian Z., Tang L., Qiu C., Zhang P. APCCdh1 controls cell cycle entry during liver regeneration. Exp Cell Res 2017; 354(2): 78–84, https://doi.org/10.1016/j.yexcr.2017.03.038.
  52. Adan A., Alizada G., Kiraz Y., Baran Y., Nalbant A. Flow cytometry: basic principles and applications. Crit Rev Biotechnol 2017; 37(2): 163–176, https://doi.org/10.3109/07388551.2015.1128876.
  53. Fukazawa K., Nishida S. Size mismatch in liver transplantation. J Hepatobiliary Pancreat Sci 2016; 23(8): 457–466, https://doi.org/10.1002/jhbp.371.
  54. Lai J.P., Chen Z.M., Lok T., Chan O.T., Himmelfarb E., Zhai Q., Lin F., Wang H.L. Immunohistochemical stains of proliferating cell nuclear antigen, insulin-like growth factor 2 and clusterin help distinguish malignant from benign liver nodular lesions. J Clin Pathol 2014; 67(6): 464–469, https://doi.org/10.1136/jclinpath-2013-201907.
  55. De Graaf W., Bennink R.J., Veteläinen R., van Gulik T.M. Nuclear imaging techniques for the assessment of hepatic function in liversurgery and transplantation. J Nucl Med 2010; 51(5): 742–752, https://doi.org/10.2967/jnumed.109.069435.
  56. Li H.H., Qi L.N., Ma L., Chen Z.S., Xiang B.D., Li L.Q. Effect of KI-67 positive cellular index on prognosis after hepatectomy in Barcelona Clinic Liver Cancer stage A and B hepatocellular carcinoma with microvascular invasion. Onco Targets Ther 2018; 11: 4747–4754, https://doi.org/10.2147/ott.s165244.
  57. Sato Y., Katoh Y., Matsumoto M., Sato M., Ebina M., Itoh-Nakadai A., Funayama R., Nakayama K., Unno M., Igarashi K. Regulatory signatures of liver regeneration distilled by integrative analysis of mRNA, histone methylation, and proteomics. J Biol Chem 2017; 292(19): 8019–8037, https://doi.org/10.1074/jbc.m116.774547.
  58. Yoshiya S., Shirabe K., Imai D., Toshima T., Yamashita Y., Ikegami T., Okano S., Yoshizumi T., Kawanaka H., Maehara Y. Blockade of the apelin-APJ system promotes mouse liver regeneration by activating Kupffer cells after partial hepatectomy. J Gastroenterol 2015; 50(5): 573–582, https://doi.org/10.1007/s00535-014-0992-5.
  59. Wu H., Ploeger J.M., Kamarajugadda S., Mashek D.G., Mashek M.T., Manivel J.C., Shekels L.L., Lapiro J.L., Albrecht J.H. Evidence for a novel regulatory interaction involving Cyclin D1, Lipid Droplets, Lipolysis, and Cell Cycle Progression in hepatocytes. Hepatol Commun 2019; 3(3): 406–422, https://doi.org/10.1002/hep4.1316.
  60. Reyes-Salcido V., Villalobos-Molina R. Evidence that dl-propranolol increases thymidine kinase activity, cell mitosis, and β-adrenoceptors during rat liver regeneration. Arch Med Res 2003; 34(4): 273–275, https://doi.org/10.1016/s0188-4409(03)00049-3.
  61. Madrigal-Santillán E., Bautista M., Gayosso-De-Lucio J.A., Reyes-Rosales Y., Posadas-Mondragón A., Morales-González Á., Soriano-Ursúa M.A., García-Machorro J., Madrigal-Bujaidar E., Álvarez-González I., Morales-González J.A. Hepatoprotective effect of Geranium schiedeanum against ethanol toxicity during liver regeneration. World J Gastroenterol 2015; 21(25): 7718, https://doi.org/10.3748/wjg.v21.i25.7718.
  62. Wilmanns W., Sauer H., Pelka-Fleischer R., Nüßler V. Thymidine kinase in leukemic cells: significance for characterization and follow-up of acute leukemia. In: Fleischer J. (editor). Leukemias. Springer, Berlin, Heidelberg; 1993; p. 59–64, https://doi.org/10.1007/978-3-642-77083-8_12.
  63. Yamashita T., Nishimura K., Saiki R., Okudaira H., Tome M., Higashi K., Nakamura M., Terui Y., Fujiwara K., Kashiwagi K., Igarashi K. Role of polyamines at the G1/S boundary and G2/M phase of the cell cycle. Int J Biochem Cell Biol 2013; 45(6): 1042–1050, https://doi.org/10.1016/j.biocel.2013.02.021.
  64. Minuk G.Y., Gauthier T., Benarroch A. Changes in serum and hepatic polyamine concentrations after 30%, 70% and 90% partial hepatectomy in rats. Hepatology 1990; 12(3): 542–546, https://doi.org/10.1002/hep.1840120315.
  65. Kawelke N., Vasel M., Sens C., Von Au A., Dooley S., Nakchbandi I.A. Fibronectin protects from excessive liver fibrosis by modulating the availability of and responsiveness of stellate cells to active TGF-β. PLoS One 2011; 6(11): e28181, https://doi.org/10.1371/journal.pone.0028181.
  66. Дзидзава И.И., Котив Б.Н., Кашкин Д.П., Кочат­ко­ва А.А., Бугаев С.А., Смородский А.В., Слободяник А.В. Количественная оценка функции печени методом клиренс-теста с индоцианином зеленым. Трансплантология 2010; 1: 30–37.
  67. Helmke S., Colmenero J., Everson G.T. Noninvasive assessment of liver function. Curr Opin Gastroenterol 2015; 31(3): 199, https://doi.org/10.1097/mog.0000000000000167.
  68. Ge P.L., Du S.D., Mao Y.L. Advances in preoperative assessment of liver function. Hepatobiliary Pancreat Dis Int 2014; 13(4): 361–370, https://doi.org/10.1016/s1499-3872(14)60267-8.
  69. van Mierlo K.M., Schaap F.G., Dejong C.H., Olde Damink S.W. Liver resection for cancer: new developments in prediction, prevention and management of postresectional liver failure. J Hepatol 2016; 65(6): 1217–1231, https://doi.org/10.1016/j.jhep.2016.06.006.
  70. Iimuro Y. ICG clearance test and 99mTc-GSA SPECT/CT fusion images. Visc Med 2017; 33(6): 449–454, https://doi.org/10.1159/000479046.
  71. Urade T., Sawa H., Iwatani Y., Abe T., Fujinaka R., Murata K., Mii Y., Man-I M., Oka S., Kuroda D. Laparoscopic anatomical liver resection using indocyanine green fluorescence imaging. Asian J Surg 2019, https://doi.org/10.1016/j.asjsur.2019.04.008.
  72. Ercolani G., Grazi G.L., Callivà R., Pierangeli F., Cescon M., Cavallari A., Mazziotti A. The lidocaine (MEGX) test as an index of hepatic function: its clinical usefulness in liver surgery. Surgery 2000; 127(4): 464–471, https://doi.org/10.1067/msy.2000.104743.
  73. Sumiyoshi T., Okabayashi T., Negoro Y., Hata Y., Noda Y., Sui K., Iwata J., Matsumoto M. 99mTc-GSA SPECT/CT fusion imaging for hepatectomy candidates with extremely deteriorated ICG value. Jpn J Radiol 2018; 36(9): 537–543, https://doi.org/10.1007/s11604-018-0753-0.
  74. Okabayashi T., Shima Y., Morita S., Shimada Y., Sumiyoshi T., Sui K., Iwata J., Iiyama T. Liver function assessment using technetium 99m-Galactosyl single-photon emission computed tomography/CT fusion imaging: a prospective trial. J Am Coll Surg 2017; 225(6): 789–797, https://doi.org/10.1016/j.jamcollsurg.2017.08.021.
  75. Yoshida M., Shiraishi S., Sakamoto F., Beppu T., Utsunomiya D., Okabe H., Tomiguchi S., Baba H., Yamashita Y. Assessment of hepatic functional regeneration after hepatectomy using (99m)Tc-GSA SPECT/CT fused imaging. Ann Nucl Med 2014; 28(8): 780–788, https://doi.org/10.1007/s12149-014-0872-3.
  76. Hall D.W., Marshall S.N., Gordon K.C., Killeen D.P. Rapid quantitative determination of squalene in shark liver oils by Raman and IR spectroscopy. Lipids 2016; 51(1): 139–147, https://doi.org/10.1007/s11745-015-4097-6.
  77. Rassam F., Zhang T., Cieslak K.P., Lavini C., Stoker J., Bennink R.J., van Gulik T.M., van Vliet L.J., Runge J.H., Vos F.M. Comparison between dynamic gadoxetate-enhanced MRI and 99mTc-mebrofenin hepatobiliary scintigraphy with SPECT for quantitative assessment of liver function. Eur Radiol 2019; 29(9): 5063–5072, https://doi.org/10.1007/s00330-019-06029-7.
  78. Bunaciu A.A., Hoang V.D., Aboul-Enein H.Y. Applications of FT-IR spectrophotometry in cancer diagnostics. Crit Rev Anal Chem 2015; 45(2): 156–165, https://doi.org/10.1080/10408347.2014.904733.
  79. Sreedhar H., Varma V.K., Gambacorta F.V., Guzman G., Walsh M.J. Infrared spectroscopic imaging detects chemical modifications in liver fibrosis due to diabetes and disease. Biomed Opt Express 2016; 7(6): 2419–2424, https://doi.org/10.1364/boe.7.002419.
  80. Petit V.W., Réfrégiers M., Guettier C., Jamme F., Sebanayakam K., Brunelle A., Laprévote O., Dumas P., Le Naour F. Multimodal spectroscopy combining time-of-flight-secondary ion mass spectrometry, synchrotron-FT-IR, and synchrotron-UV microspectroscopies on the same tissue section. Anal Chem 2010; 82(9): 3963–3968, https://doi.org/10.1021/ac100581y.
  81. Passarelli M.K., Winograd N. Lipid imaging with time-of-flight secondary ion mass spectrometry (ToF-SIMS). Biochim Biophys Acta 2011; 1811(11): 976–990, https://doi.org/10.1016/j.bbalip.2011.05.007.
  82. Le Naour F., Bralet M.P., Debois D., Sandt C., Guettier C., Dumas P., Brunelle A., Laprévote O. Chemical imaging on liver steatosis using synchrotron infrared and ToF-SIMS microspectroscopies. PLoS One 2009; 4(10): e7408, https://doi.org/10.1371/journal.pone.0007408.
  83. Touboul D., Brunelle A., Laprévote O. Mass spectrometry imaging: towards a lipid microscope? Biochimie 2011; 93(1): 113–119, https://doi.org/10.1016/j.biochi.2010.05.013.
  84. Mas S., Touboul D., Brunelle A., Aragoncillo P., Egido J., Laprévote O., Vivanco F. Lipid cartography of atherosclerotic plaque by cluster-TOF-SIMS imaging. Analyst 2007; 132(1): 24–26, https://doi.org/10.1039/b614619h.
  85. Tahallah N., Brunelle A., De La Porte S., Laprévote O. Lipid mapping in human dystrophic muscle by cluster-time-of-flight secondary ion mass spectrometry imaging. J Lipid Res 2008; 49(2): 438–454, https://doi.org/10.1194/jlr.m700421-jlr200.
  86. Lazar A.N., Bich C., Panchal M., Desbenoit N., Petit V.W., Touboul D., Dauphinot L., Marquer C., Laprévote O., Brunelle A., Duyckaerts C. Time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging reveals cholesterol overload in the cerebral cortex of Alzheimer disease patients. Acta Neuropathol 2013; 125(1): 133–144, https://doi.org/10.1007/s00401-012-1041-1.
  87. Debois D., Bralet M.P., Le Naour F., Brunelle A., Laprévote O. In situ lipidomic analysis of nonalcoholic fatty liver by cluster TOF-SIMS imaging. Anal Chem 2009; 81(8): 2823–2831, https://doi.org/10.1021/ac900045m.
  88. Ezquer F., Bahamonde J., Huang Y.L., Ezquer M. Administration of multipotent mesenchymal stromal cells restores liver regeneration and improves liver function in obese mice with hepatic steatosis after partial hepatectomy. Stem Cell Res Ther 2017; 8(1): 20, https://doi.org/10.1186/s13287-016-0469-y.
  89. Rudnick D.A., Davidson N.O. Functional relationships between lipid metabolism and liver regeneration. Int J Hepatol 2012; 2012: 549241, https://doi.org/10.1155/2012/549241.
  90. Saito Y., Morine Y., Iwahashi S., Ikemoto T., Imura S., Yamanaka-Okumura H., Shimada M. Changes of liver metabolites following hepatectomy with ischemia reperfusion towards liver regeneration. Ann Gastroenterol Surg 2018; 2(3): 204–211, https://doi.org/10.1002/ags3.12058.
  91. Miyamura N., Nakamura T., Goto-Inoue N., Zaima N., Hayasaka T., Yamasaki T., Terai S., Sakaida I., Setou M., Nishina H. Imaging mass spectrometry reveals characteristic changes in triglyceride and phospholipid species in regenerating mouse liver. Biochem Biophys Res Commun 2011; 408(1): 120–125, https://doi.org/10.1016/j.bbrc.2011.03.133.
  92. Daemen S., van Zandvoort M.A., Parekh S.H., Hesselink M.K. Microscopy tools for the investigation of intracellular lipid storage and dynamics. Mol Metab 2016; 5(3): 153–163, https://doi.org/10.1016/j.molmet.2015.12.005.
  93. Saka S.K., Vogts A., Kröhnerk K., Hillion F., Rizzoli S.O., Wessels J.T. Correlated optical and isotopic nanoscopy. Nat Commun 2014; 5: 3664, https://doi.org/10.1038/ncomms4664.
  94. Marques P.E., Antunes M.M., David B.A., Pereira R.V., Teixeira M.M., Menezes G.B. Imaging liver biology in vivo using conventional confocal microscopy. Nat Protoc 2015; 10(2): 258, https://doi.org/10.1038/nprot.2015.006.
  95. Wang H., Liang X., Mohammed Y.H., Thomas J.A., Bridle K.R., Thorling C.A., Grice J.E., Xu Z.P., Liu X., Crawford D.H., Roberts M.S. Real-time histology in liver disease using multiphoton microscopy with fluorescence lifetime imaging. Biomed Opt Express 2015; 6(3): 780–792, https://doi.org/10.1364/boe.6.000780.
  96. Thorling C.A., Liu X., Burczynski F.J., Fletcher L.M., Roberts M.S., Sanchez W.Y. Intravital multiphoton microscopy can model uptake and excretion of fluorescein in hepatic ischemia-reperfusion injury. J Biomed Opt 2013; 18(10): 101306, https://doi.org/10.1117/1.jbo.18.10.101306.
  97. Goetz M., Vieth M., Kanzler S., Galle P.R., Delaney P., Neurath M.F., Kiesslich R. In vivo confocal laser laparoscopy allows real time subsurface microscopy in animal models of liver disease. J Hepatol 2008; 48(1): 91–97, https://doi.org/10.1016/j.jhep.2007.07.029.
  98. Maki H., Kawaguchi Y., Arita J., Akamatsu N., Kaneko J., Sakamoto Y., Hasegawa K., Harihara Y., Kokudo N. Real-time confocal laser endomicroscopic evaluation of primary liver cancer based on human liver autofluorescence. J Surg Oncol 2017; 115(2): 151–157, https://doi.org/10.1002/jso.24491.
  99. Schneider C., Johnson S.P., Gurusamy K., Cook R.J., Desjardins A.E., Hawkes D.J., Davidson B.R., Walker-Samuel S. Identification of liver metastases with probe-based confocal laser endomicroscopy at two excitation wavelengths. Lasers Surg Med 2017; 49(3): 280–292, https://doi.org/10.1002/lsm.22617.
  100. Thorling C.A., Crawford D., Burczynski F.J., Liu X., Liau I., Roberts M.S. Multiphoton microscopy in defining liver function. J Biomed Opt 2014; 19(9): 090901, https://doi.org/10.1117/1.jbo.19.9.090901.
  101. Benati E., Bellini V., Borsari S., Dunsby C., Ferrari C., French P., Guanti M., Guardoli D., Koenig K., Pellacani G., Ponti G., Schianchi S., Talbot C., Seidenari S. Quantitative evaluation of healthy epidermis by means of multiphoton microscopy and fluorescence lifetime imaging microscopy. Skin Res Technol 2011; 17(3): 295–303, https://doi.org/10.1111/j.1600-0846.2011.00496.x.
  102. Titov D.V., Cracan V., Goodman R.P., Peng J., Grabarek Z., Mootha V.K. Complementation of mitochondrial electron transport chain by manipulation of the NAD+/NADH ratio. Science 2016; 352(6282): 231–235, https://doi.org/10.1126/science.aad4017.
  103. Musso G., Gambino R., Cassader M. Recent insights into hepatic lipid metabolism in non-alcoholic fatty liver disease (NAFLD). Prog Lipid Res 2009; 48(1): 1–26, https://doi.org/10.1016/j.plipres.2008.08.001.
  104. Mukherjee S., Chellappa K., Moffitt A., Ndungu J., Dellinger R.W., Davis J.G., Agarwal B., Baur J.A. Nicotinamide adenine dinucleotide biosynthesis promotes liver regeneration. Hepatology 2017; 65(2): 616–630, https://doi.org/10.1002/hep.28912.
  105. Liu F., Zhao J.M., Rao H.Y., Yu W.M., Zhang W., Theise N.D., Wee A., Wei L. Second harmonic generation reveals subtle fibrosis differences in adult and pediatric nonalcoholic fatty liver disease. Am J Clin Pathol 2017; 148(6): 502–512, https://doi.org/10.1093/ajcp/aqx104.
  106. Wang B., Sun Y., Zhou J., Wu X., Chen S., Shi Y., Wu S., Liu H., Ren Y., Ou X., Jia J., You H. SHG/TPEF-based image technology improves liver fibrosis assessment of minimally sized needle biopsies. Hepatol Int 2019; 13(4): 501–509, https://doi.org/10.1007/s12072-019-09955-2.
  107. Xu S., Kang C.H., Gou X., Peng Q., Yan J., Zhuo S., Cheng C.L., He Y., Kang Y., Xia W., So P.T., Welsch R., Rajapakse J.C., Yu H. Quantification of liver fibrosis via second harmonic imaging of the Glisson’s capsule from liver surface. J Biophotonics 2016; 9(4): 351–363, https://doi.org/10.1002/jbio.201500001.
  108. Chang P.E., Goh G.B.B., Leow W.Q., Shen L., Lim K.H., Tan C.K. Second harmonic generation microscopy provides accurate automated staging of liver fibrosis in patients with non-alcoholic fatty liver disease. PLoS One 2018; 13(6): e0199166, https://doi.org/10.1371/journal.pone.0199166.
  109. Gailhouste L., Le Grand Y., Odin C., Guyader D., Turlin B., Ezan F., Désille Y., Guilbert T., Bessard A., Frémin C., Theret N., Baffet G. Fibrillar collagen scoring by second harmonic microscopy: a new tool in the assessment of liver fibrosis. J Hepatol 2010; 52(3): 398–406, https://doi.org/10.1016/j.jhep.2009.12.009.
  110. Tai D.C., Tan N., Xu S., Kang C.H., Chia S.M., Cheng C.L., Wee A., Wei C.L., Raja A.M., Xiao G., Chang S., Rajapakse J.C., So P.T., Tang H.H., Chen C.S., Yu H. Fibro-C-Index: comprehensive, morphology-based quantification of liver fibrosis using second harmonic generation and two-photon microscopy. J Biomed Opt 2009; 14(4): 044013, https://doi.org/10.1117/1.3183811.
  111. Pope I., Langbein W., Borri P., Watson P. Live cell imaging with chemical specificity using dual frequency CARS microscopy. Methods Enzymol 2012; 504: 273–291, https://doi.org/10.1016/b978-0-12-391857-4.00014-8.
  112. Yan S., Cui S., Ke K., Zhao B., Liu X., Yue S., Wang P. Hyperspectral stimulated Raman scattering microscopy unravels aberrant accumulation of saturated fat in human liver cancer. Anal Chem 2018; 90(11): 6362–6366, https://doi.org/10.1021/acs.analchem.8b01312.
  113. Satoh S., Otsuka Y., Ozeki Y., Itoh K., Hashiguchi A., Yamazaki K., Hashimoto H., Sakamoto M. Label-free visualization of acetaminophen-induced liver injury by high-speed stimulated Raman scattering spectral microscopy and multivariate image analysis. Pathol Int 2014; 64(10): 518–526, https://doi.org/10.1111/pin.12206.
  114. Fu D., Yang W., Xie X.S. Label-free imaging of neurotransmitter acetylcholine at neuromuscular junctions with stimulated Raman scattering. J Am Chem Soc 2016; 139(2): 583–586, https://doi.org/10.1021/jacs.6b10727.
  115. Yu Y., Ramachandran P.V., Wang M.C. Shedding new light on lipid functions with CARS and SRS microscopy. Biochim Biophys Acta 2014; 1841(8): 1120–1129, https://doi.org/10.1016/j.bbalip.2014.02.003.
  116. Fu D. Quantitative chemical imaging with stimulated Raman scattering microscopy. Curr Opin Chem Biol 2017; 39: 24–31, https://doi.org/10.1016/j.cbpa.2017.05.002.
  117. Chun W., Do D., Gweon D.G. Design and demonstration of multimodal optical scanning microscopy for confocal and two-photon imaging. Rev Sci Instrum 2013; 84(1): 013701, https://doi.org/10.1063/1.4773232.
  118. Lee J.H., Kim J.C., Tae G., Oh M.K., Ko D.K. Rapid diagnosis of liver fibrosis using multimodal multiphoton nonlinear optical microspectroscopy imaging. J Biomed Opt 2013; 18(7): 076009, https://doi.org/10.1117/1.jbo.18.7.076009.
  119. Skala M.C., Riching K.M., Bird D.K., Gendron-Fitzpatrick A., Eickhoff J., Eliceiri K.W., Keely P.J., Ramanujam N. In vivo multiphoton fluorescence lifetime imaging of protein-bound and free nicotinamide adenine dinucleotide in normal and precancerous epithelia. J Biomed Opt 2007; 12(2): 024014, https://doi.org/10.1117/1.2717503.
  120. Becker W. Fluorescence lifetime imaging–techniques and applications. J Microsc 2012; 247(2): 119–136, https://doi.org/10.1111/j.1365-2818.2012.03618.x.
  121. De Los Santos C., Chang C.W., Mycek M.A., Cardullo R.A. FRAP, FLIM, and FRET: detection and analysis of cellular dynamics on a molecular scale using fluorescence microscopy. Mol Reprod Dev 2015; 82(7–8): 587–604, https://doi.org/10.1002/mrd.22501.
  122. Liu Z., Pouli D., Alonzo C.A., Varone A., Karaliota S., Quinn K.P., Münger K., Karalis K.P., Georgakoudi I. Mapping metabolic changes by noninvasive, multiparametric, high-resolution imaging using endogenous contrast. Sci Adv 2018; 4(3): eaap9302, https://doi.org/10.1126/sciadv.aap9302.
  123. Ranjit S., Dvornikov A., Dobrinskikh E., Wang X., Luo Y., Levi M., Gratton E. Measuring the effect of a Western diet on liver tissue architecture by FLIM autofluorescence and harmonic generation microscopy. Biomed Opt Express 2017; 8(7): 3143–3154, https://doi.org/10.1364/boe.8.003143.
Rodimova S.A., Kuznetsova D.S., Bobrov N.V., Vdovina N.V., Zagainov V.E., Zagaynova E.V. Modern Methods for Assessing the Regenerative Potential of the Liver after Partial Hepatectomy (Review). Sovremennye tehnologii v medicine 2019; 11(4): 175, https://doi.org/10.17691/stm2019.11.4.20


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