Патоген-специфическая молекулярная визуализация и методы молекулярного тестирования в прогнозе осложненного течения синдрома диабетической стопы, риска ампутаций и выживаемости пациентов

Цель настоящего обзора – расширение информации об актуальных направлениях в диагностике осложненного течения синдрома диабетической стопы (СДС), частого и тяжелого осложнения сахарного диабета, включая высокотехнологические методы медицинской визуализации и инструментально-лабораторные предикторы осложненного течения и риска ампутаций при СДС.

Представлен аналитический обзор современных публикаций за последние 5 лет по диагностическим и терапевтическим направлениям; систематизированы и обобщены, а также подвергнуты аналитической оценке пилотные данные, касающиеся использования высокотехнологических методов медицинской визуализации, оценки микробиоты кожи и язвенных дефектов при СДС, методов молекулярного тестирования с точки зрения прогноза риска ампутаций и выживаемости пациентов с СДС и эффективности применения систем биосенсирования.

Дана экспертная оценка возможностей патоген-специфической молекулярной визуализации с использованием современных технологий позитронно-эмиссионной томографии (ПЭТ) и однофотонной эмиссионной компьютерной томографии (ОФЭКТ) и высокоэнергетических радионуклидов при бактериальной инфекции для понимания ее патогенеза, минимизации диагностических проблем, улучшения антимикробного лечения и для решения фундаментальных и прикладных аспектов СДС. Систематизированы литературные данные об оценке перфузии стоп у больных сахарным диабетом с различной степенью ишемии конечностей методами гибридных технологий (ОФЭКТ/КТ и ПЭТ/КТ) и новых модальностей магнитно-резонансной томографии, что способствует новому пониманию ответной реакции на реваскуляризацию, хирургическое шунтирование и стимулирование ангиогенеза в пределах ишемизированной ткани, а также потенциально – и для заживления язвы стопы.

Статья направлена на обоснование мультидисциплинарного подхода при СДС, а также выбор, развитие и внедрение инновационных стратегий диагностических модальностей в установлении патологических процессов при СДС, выбор адекватного метода лечения и мониторирования результатов терапии в рамках развития персонифицированной медицины.

1. Lauri C., Leone A., Cavallini M., Signore A., Giurato L., Uccioli L. Diabetic foot infections: the diagnostic challenges. J. Clin. Med. 2020;9(6):1779. DOI: 10.3390/jcm9061779.

2. Llewellyn A., Kraft J., Holton C., Harden M., Simmonds M. Imaging for detection of osteomyelitis in people with diabetic foot ulcers: A systematic review and meta-analysis. Eur. J. Radiol. 2020;131:109215. DOI: 10.1016/j.ejrad.2020.109215.

3. Chantelaua E.A., Antoniou S., Zweck B., Haage P. Follow up of MRI bone marrow edema in the treated diabetic Charcot foot – a review of patient charts. Diabet. Foot Ankle. 2018;9(1):1466611. DOI: 10.1080/2000625X.2018.1466611.

4. Ruiz-Bedoya C.A., Gordon O., Mota F. et al. Molecular imaging of diabetic foot infections: new tools for old questions. Int. J. Mol. Sci. 2019;20(23):5984. DOI: 10.3390/ijms20235984.

5. Massel D.H., Jenkins N.W., Rush A.J. 3rd et al. MRI and clinical risk indicators for osteomyelitis. Foot and Ankle Specialist. 2014;14(5):415–426. DOI: 0.1177/1938640020921572.

6. Duryea D., Bernard S., Flemming D., Walker E., French C. Outcomes in diabetic foot ulcer patients with isolated T2 marrow signal abnormality in the underlying bone: should the diagnosis of «osteitis» be changed to «early osteomyelitis»? Skeletal Radiol. 2017;46(10):1327–1333. DOI: 10.1007/s00256-017-2666-x.

7. Jang Y.H., Park S., Park Y.U., Kwack K.S., Jeon S.W., Lee H.Y. Multivariate analyses of MRI findings for predicting osteomyelitis of the foot in diabetic patients. Acta Radiol. 2020;61(9):1205–1212. DOI: 10.1177/0284185119897351.

8. Kotecha H.M., Lo H.S., Vedantham S., Shin H., Cerniglia C.A. Abbreviated MRI of the foot in patients with suspected osteomyelitis. Emerg. Radiol. 2020;27(1):9–16. DOI: 10.1007/s10140-019-01722-y.

9. La Fontaine J., Bhavan K., Jupiter D., Lavery L.A., Chhabra A. Magnetic resonance imaging of diabetic foot osteomyelitis: imaging accuracy in biopsy-proven disease. J. Foot Ankle Surg. 2021;60(1):17–20. DOI: 10.1053/j.jfas.2020.02.012

10. Jbara M., Gokli A., Beshai S. et al. Does obtaining an initial magnetic resonance imaging decrease the reamputation rates in the diabetic foot? Diabet. Foot Ankle. 2016;7:31240. DOI: 10.3402/dfa.v7.31240.

11. Lauri C., Glaudemans A.W.J.M., Signore A. Leukocyte imaging of the diabetic foot. Curr. Pharm. Des. 2018;24(12):1270– 1276. DOI: 10.2174/1381612824666180227094116.

12. Diez A.I.G., Fuster D., Morata L. et al. Comparison of the diagnostic accuracy of diffusion-weighted and dynamic contrast-enhanced MRI with 18F-FDG PET/CT to differentiate osteomyelitis from Charcot neuro-osteoarthropathy in diabetic foot. Eur. J. Radiol. 2020;132:109299. DOI: 10.1016/j.ejrad.2020.109299.

13. Çildağ M.B., Ertuğrul M.B., Köseoğlu Ö.F., Armstrong D.G. A Factor increasing venous contamination on bolus chase three-dimensional magnetic resonance imaging: Charcot neuroarthropathy. J. Clin. Imaging Sci. 2018;8:13. DOI: 10.4103/jcis.JCIS_77_17.

14. Uccioli L., Meloni M., Izzo V., Giurato L., Merolla S., Gandini R. Critical limb ischemia: current challenges and future prospects. Vasc. Health Risk Manag. 2018;14:63–74. DOI: 10.2147/VHRM.S125065.

15. Zamyshevskaya M., Zavadovskaya V., Zorkaltsev M., Udodov V., Grigorev E. 3D DCE-MRA of pedal arteries in patients with diabetes mellitus. Journal of Physics Conference Series. 2016;677(1):012010. DOI: 10.1088/17426596/677/1/012010

16. Liao D., Xie L., Han Y. et al. Dynamic contrast-enhanced magnetic resonance imaging for differentiating osteomyelitis from acute neuropathic arthropathy in the complicated diabetic foot. Skeletal Radiol. 2018;47(10):1337–1347. DOI: 10.1007/s00256-018-2942-4.

17. Zhang N., Fan Z., Luo N. et al. Noncontrast MR angiography (MRA) of infragenual arteries using flow-sensitive dephasing (FSD)-prepared steady-state free precession (SSFP) at 3.0 Tesla: comparison with contrast-enhanced MRA. J. Magn. Reson. Imaging. 2016;43(2):364–372. DOI: 10.1002/jmri.25003.

18. Lam A., Perchyonok Y., Ranatunga D. et al. Accuracy of non-contrast quiescent-interval single-shot and quiescent-interval single-shot arterial spin-labelled magnetic resonance angiography in assessment of peripheral arterial disease in a diabetic population. J. Med. Imaging Radiat. Oncol. 2020;64(1):35–43. DOI: 10.1111/1754-9485.12987.

19. Abdel Razek A.A.K., Samir S. Diagnostic performance of diffusion-weighted MR imaging in differentiation of diabetic osteoarthropathy and osteomyelitis in diabetic foot. Eur. J. Radiol. 2017;89:221–225. DOI: 10.1016/j.ejrad.2017.02.015.

20. Eren M.A., Karakaş E., Torun A.N., Sabuncu T. The Clinical value of diffusion-weighted magnetic resonance imaging in diabetic foot infection. J. Am. Podiatr. Med. Assoc. 2019;109(4):277–281. DOI: 10.7547/17-066.

21. Lauri C., Tamminga M., Glaudemans A.W.J.M. et al. Detection of Osteomyelitis in the Diabetic Foot by Imaging Techniques: A Systematic Review and Meta-analysis Comparing MRI, White Blood Cell Scintigraphy, and FDG-PET. Diabetes Care. 2017;40(8):1111–1120. DOI: 10.2337/dc17-0532.

22. Signore A., Jamar F., Israel O., Buscombe J., Martin-Comin J., Lazzeri E. Clinical indications, image acquisition and data interpretation for white blood cells and anti-granulocyte monoclonal antibody scintigraphy: an EANM procedural guideline. Eur. J. Nucl. Med. Mol. Imaging. 2018;45(10):1816–1831. DOI: 10.1007/s00259-018-4052-x.

23. Lauri C., Glaudemans A.W.J.M., Campagna G. et al. Comparison of White Blood Cell Scintigraphy, FDG PET/CT and MRI in Suspected Diabetic Foot Infection: Results of a Large Retrospective Multicenter Study. J. Clin. Med. 2020;9(6):1645. DOI: 10.3390/jcm9061645.

24. Ahmed N., Fatima S., Saeed M.A., Zia M., Irfan Ullah J. 99m Tc-ceftizoxime: synthesis, characterization and its use in diagnosis of diabetic foot osteomyelitis. J. Med. Imaging Radiat. Oncol. 2019;63(1):61–68. DOI: 10.1111/1754-9485.12841.

25. Ankrah A.O., Klein H.C., Elsinga P.H. New imaging tracers for the infected diabetic foot (nuclear and optical imaging). Curr. Pharm. Des. 2018;24(12):1287–1303. DOI: 10.2174/1381612824666180227094454.

26. Vouillarmet J., Moret M., Morelec I., Michon P., Dubreuil J. Application of white blood cell SPECT/CT to predict remission after a 6 or 12 week course of antibiotic treatment for diabetic foot osteomyelitis. Diabetologia. 2017;60(12):2486– 2494. DOI: 10.1007/s00125-017-4417-x.

27. Jeffcoate W.J. Osteomyelitis of the foot: non-surgical management, SPECT/CT scanning and minimizing the duration of antibiotic use. Diabetologia. 2017;60(12):2337–2340. DOI: 10.1007/s00125-017-4429-6.

28. Ahluwalia R., Bilal A., Petrova N. et al. The role of bone scintigraphy with SPECT/CT in the characterization and early diagnosis of stage 0 Charcot neuroarthropathy. J. Clin. Med. 2020;9(12):4123. DOI: 10.3390/jcm9124123.

29. Yang H., Zhuang H., Rubello D., Alavi A. Mild-to-moderate hyperglycemia will not decrease the sensitivity of 18F-FDG PET imaging in the detection of pedal osteomyelitis in diabetic patients. Nucl. Med. Commun. 2016;37(3):259–262. DOI: 10.1097/MNM.0000000000000434.

30. Glaudemans A.W.J.M., Jutte P.C., Cataldo M.A. et al. Consensus document for the diagnosis of peripheral bone infection in adults: a joint paper by the EANM, EBJIS, and ESR (with ESCMID endorsement). Eur. J. Nucl. Med. Mol. Imaging. 2019;46(4):957–970. DOI: 10.1007/s00259-019-4262-x.

31. Удодов В.Д., Зоркальцев М.А., Завадовская М.А. и др. Гибридная ОФЭКТ/МРТ в диагностике синдрома диабетической стопы. Медицинская визуализация. 2016;2:36–42.

32. Meacock L., Petrova N.L., Donaldson A. et al. Novel semi quantitative bone marrow oedema score and fracture score for the magnetic resonance imaging assessment of the active Charcot foot in diabetes. J. Diabetes Res. 2017;2017:8504137. DOI: 10.1155/2017/8504137.

33. Alvelo J.L., Papademetris X., Mena-Hurtado C. et al. Radiotracer imaging allows for noninvasive detection and quantification of abnormalities in angiosome foot perfusion in diabetic patients with critical limb ischemia and nonhealing wounds. Circ. Cardiovasc. Imaging. 2018;11(5):e006932. DOI: 10.1161/CIRCIMAGING.117.006932

34. Mahendra M., Singh R. Diagnostic accuracy and surgi cal utility of MRI in complicated diabetic foot. J. Clin. Diagn. Res. 2017;11(7):RC01–RC04. DOI: 10.7860/JCDR/2017/25902.10154.

35. Chou T.H., Atway S.A., Bobbey A.J., Sarac T.P., Go M.R., Stacy M.R. SPECT/CT imaging a noninvasive approach for evaluating serial changes in angiosome foot perfusion in critical limb ischemia. Adv. Wound Care (New Rochelle). 2020;9(3):103–110. DOI: 10.1089/wound.2018.0924

36. Chen H.J., Roy T.L., Wright G.A. Perfusion measures for symptom severity and differential outcome of revascularization in limb ischemia: preliminary results with arterial spin labeling reactive hyperemia. J. Magn. Reson. Imaging. 2018;47(6):1578–1588. DOI: 10.1002/jmri.25910.

37. Zheng J., Muccigrosso D., Zhang X. et al. Oximetric angiosome imaging in diabetic feet. J. Magn. Reson. Imaging. 2016;44(4):940–946. DOI: 10.1002/jmri.25220.

38. Edalati M., Hastings M.K., Muccigrosso D. et al. Intravenous contrast-free standardized exercise perfusion imag ing in diabetic feet with ulcers. J. Magn. Reson. Imaging. 2019;50(2):474–480. DOI: 10.1002/jmri.26570.

39. Stacy M.R., Qiu M., Papademetris X. et al. Application of BOLD Magnetic Resonance Imaging for Evaluating Regional Volumetric Foot Tissue Oxygenation: A Feasibility Study in Healthy Volunteers. Eur. J. Vasc. Endovasc. Surg. 2016;51(5):743–749. DOI: 10.1016/j.ejvs.2016.02.008.

40. Forsythe R.O., Apelqvist J., Boyko E.J. et al. Performance of Prognostic Markers in the Prediction of Wound Hea ling or Amputation among Patients with Foot Ulcers in Diabetes: A Systematic Review. Diabetes/Metabolism Research and Reviews. 2020;36(Suppl.1):e3278. DOI: 10.1002/dmrr.3278.

41. Lung C.W., Wu F.L., Liao F., Pu F., Fan Y. et al. Emerg ing technologies for the prevention and management of diabetic foot ulcers. J. Tissue Viability. 2020;29(2):61–68. DOI: 10.1016/j.jtv.2020.03.003.

42. Golledge J., Fernando M., Lazzarini P. et al. The potential role of sensors, wearables and telehealth in the remote management of diabetes-related foot disease. Sensors. 2020;20(16):4527. DOI: 10.3390/s20164527.

43. Bus S.A., Lavery L.A., Monteiro-Soares M. et al. Guidelines on the prevention of foot ulcers in persons with diabetes (IWGDF 2019 update). Diabetes Metab. Res. Rev. 2020;36 (Suppl.1):e3269. DOI: 10.1002/dmrr.3269.

44. Lung C.W., Hsiao-Wecksler E.T., Burns S., Lin F., Jan Y.K. Quantifying dynamic changes in plantar pressure gradient in diabetics with peripheral neuropathy. Front Bioeng Biotechnol. 2016;4:54. DOI: 10.3389/fbioe.2016.00054.

45. Bus S.A., Maas J.C., Otterman N.M. Lower-extremity dynamics of walking in neuropathic diabetic patients who wear a forefoot-offloading shoe. Clin. Biomech. (Bristol, Avon). 2017;50:21–26. DOI: 10.1016/j.clinbiomech.2017.10.003

46. Abbott C.A., Chatwin K.E., Foden P. et al. Innovative intelligent insole system reduces diabetic foot ulcer recurrence at plantar sites: a prospective, randomised, proof-of-con cept study. Lancet Digit Health. 2019;1(6):e308–e318. DOI: 10.1016/S2589-7500(19)30128-1.

47. Fernando M.E., Crowther R.G., Lazzarini P.A. et al. Gait in people with nonhealing diabetes-related plantar ulcers. Phys. Ther. 2019;99(12):1602–1615. DOI: 10.1093/ptj/pzz119.

48. Brodie M.A., Okubo Y., Annegarn J., Wieching R., Lord S.R., Delbaere K. Disentangling the health benefits of walking from increased exposure to falls in older people using remote gait monitoring and multi-dimensional analysis. Physiol. Meas. 2017;38(1):45–62. DOI: 10.1088/1361-6579/38/1/45

49. Lee S.H., Lee H.J., Chang W.H. et al. Gait performance and foot pressure distribution during wearable robot-assisted gait in elderly adults. J. Neuroeng. Rehabil. 2017;14(1):123. DOI: 10.1186/s12984-017-0333-z.

50. Kang S., Cho H., Jeon D. et al. A Matrix metalloproteinase sensing biosensor for the evaluation of chronic wounds. Bio. Chip. J. 2019;13:323–332. DOI: 10.1007/s1206-019-3403-4.

51. Luanraksa S., Jindatanmanusan P., Boonsiri T., Nimmanon T., Chaovanalikit T., Arnutti P. An MMP/TIMP ratio scoring system as a potential predictive marker of diabetic foot ulcer healing. J. Wound Care. 2018;27(12):849–855. DOI: 10.12968/jowc.2018.27.12.849.

52. Krisp C., Jacobsen F., McKay M.J., Molloy M.P., Steinstraesser L., Wolters D.A. Proteome analysis reveals antiangiogenic environments in chronic wounds of diabetes mellitus type 2 patients. Proteomics. 2013;13(17):2670–2681. DOI: 10.1002/pmic.201200502.

53. Jones J.I., Nguyen T.T., Peng Z., Chang M. Targeting MMP-9 in diabetic foot ulcers. Pharmaceuticals (Basel). 2019;12(2):79. DOI: 10.3390/ph12020079.

54. Ramirez-Acuña J.M., Cardenas-Cadena S.A., Marquez Salas P.A. et al. Diabetic foot ulcers: current advances in antimicrobial therapies and emerging treatments. Antibiotics (Basel). 2019;8(4):193. DOI: 10.3390/antibiotics8040193.

55. Shao M., Hussain Z., Thu H.E. et al. Emerging trends in therapeutic algorithm of chronic wound healers: recent advances in drug delivery systems, concepts-to-clinical application and future prospects. Critical Reviews in Therapeutic Drug Carrier Systems.2017;34(5):387–452. DOI: 10.1615/critrevtherdrugcarriersyst.2017016957.

56. Jneid J., Cassir N., Schuldiner S. et al. Exploring the microbiota of diabetic foot infections with culturomics. Front Cell Infect. Microbiol. 2018;8:282. DOI: 10.3389/fcimb.2018.00282.

57. Malone M., Johani K., Jensen S.O. et al. Next generation DNA sequencing of tissues from infected diabetic foot ulcers. eBioMedicine. 2017;21:142–149. DOI: 10.1016/j.ebiom.2017.06.026.

58. Park J.U., Oh B., Lee J.P., Choi M.H., Lee M.J., Kim B.S. Influence of microbiota on diabetic foot wound in comparison with adjacent normal skin based on the clinical features. Biomed. Res. Int. 2019;2019:7459236. DOI: 10.1155/2019/7459236.