Deep vein thrombosis in lower extremities: review of current diagnostic techniques and their symbiosis with machine learning for timely diagnosis

Authors

  • Maria Berenice Fong-Mata Faculty of Engineering Sciences and Technology, Autonomous University of Baja California, Tijuana, Baja California, Mexico. https://orcid.org/0000-0001-6415-0110
  • Everardo Inzunza-González Faculty of Engineering, Architecture and Design, Autonomous University of Baja California, Ensenada, Baja California, Mexico. https://orcid.org/0000-0002-7994-9774
  • Enrique Efrén García-Guerrero Faculty of Engineering, Architecture and Design, Autonomous University of Baja California, Ensenada, Baja California, Mexico. https://orcid.org/0000-0001-5052-6850
  • David Abdel Mejía Medina Faculty of Engineering Sciences and Technology, Autonomous University of Baja California, Tijuana, Baja California, Mexico. https://orcid.org/0000-0003-2860-2428
  • Oscar Adrián Morales Contreras Faculty of Engineering Sciences and Technology, Autonomous University of Baja California, Tijuana, Baja California, Mexico. https://orcid.org/0000-0003-0118-8132
  • Antonio Gómez-Roa Faculty of Engineering Sciences and Technology, Autonomous University of Baja California, Tijuana, Baja California, Mexico. https://orcid.org/0000-0002-3548-0740

DOI:

https://doi.org/10.37636/recit.v312334

Keywords:

Diagnosis, Artificial neural networks, Deep venous thrombosis.

Abstract

Deep Venous Thrombosis (DVT) is a manifestation of a Thromboembolic Disease (ET). When in a DVT the venous thrombus detaches and travel through the bloodstream can cause a Pulmonary Embolism Thrombus (PET). The existence of Deep Venous Thrombosis (DVT) in the lower extremities has been described as one of the main risk factors for the development of PET. It is considered that up to 90% of pulmonary emboli come from venous thrombi of the lower extremities. The most commonly used techniques for the detection of DVT are clinical probability models, D-dimer and non-invasive imaging tests, such as ultrasound for DVT and computed angiotomography (CT) for pulmonary embolism. However, due to the non-specificity of the symptoms of DVT, the threshold for ordering an ultrasound is low, in addition to being a complicated process that requires the participation of a specialist doctor for its interpretation. In recent decades, machine learning has emerged as support in decision-making for the diagnosis of various diseases, some of the most used technologies in the field of medicine include Support Vector Machine (SVM), Decision Trees and Neural Networks Artificial (RNA). This article reviews the existing technologies for the detection of DVT as well as the main machine learning algorithms commonly used in biomedical applications; The design of a computerized system that uses machine learning techniques as a support tool for the timely detection of a possible DVT is proposed.

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References

T. Moumneh, A. Penaloza, and P. M. Roy, "Trombosis venosa profunda," EMC - Tratado Med., vol. 22, no. 1, pp. 1-6, Mar. 2018. https://doi.org/10.1016/S1636-5410(17)87867-3. DOI: https://doi.org/10.1016/S1636-5410(17)87867-3

R. B. Resano and F. J. B. Resano, "Estudio básico ante una trombosis venosa profunda," FMC Form. Medica Contin. en Aten. Primaria, 2018. https://doi.org/10.1016/j.fmc.2018.01.006. DOI: https://doi.org/10.1016/j.fmc.2018.01.006

E. Fuentes Camps, J. Luis Del Val García, S. Bellmunt Montoya, S. Hmimina Hmimina, E. Gómez Jabalera, and M. Á. Muñoz Pérez, "Estudio coste efectividad del proceso diagnóstico de la trombosis venosa profunda desde la atención primaria," Aten. Primaria, 2016. https://doi.org/10.1016/j.aprim.2015.05.006. DOI: https://doi.org/10.1016/j.aprim.2015.05.006

A. Ziga-Martínez, P. M. Córdova-Quintal, N. E. Lecuona-Huet, R. Muñoz-Vigna, and N. Blum-Gilbert, "Catastrophic presentation of venous thromboembolic disease," Rev. Médica del Hosp. Gen. México, 2017. https://doi.org/10.1016/j.hgmx.2017.01.001. DOI: https://doi.org/10.1016/j.hgmx.2017.01.001

D. Mozaffarian et al., "Heart Disease and Stroke Statistics-2016 Update," Circulation, 2015. https://doi.org/10.1161/CIR.0000000000000350. DOI: https://doi.org/10.1161/CIR.0000000000000350

E. Fuentes Camps, J. L. Del Val García, S. Bellmunt Montoya, S. Hmimina Hmimina, E. Gómez Jabalera, and M. Muñoz Pérez, "Factores clínicos que influyen en la probabilidad diagnóstica pretest de trombosis venosa profunda en pacientes ambulatorios," Angiologia, 2015. https://doi.org/10.1016/j.angio.2015.03.003. DOI: https://doi.org/10.1016/j.angio.2015.03.003

J. Hong et al., "Incidence of venous thromboembolism in Korea from 2009 to 2013," PLoS ONE. 2018. https://doi.org/10.1371/journal.pone.0191897. DOI: https://doi.org/10.1371/journal.pone.0191897

J. M. Benavides Bermúdes, J. J. Vivas Diaz, G. Jaramillo Trujillo, and W. Bernal Torres, "Trombosis venosa profunda en un paciente con hipertiroidismo de novo. Presentación de caso," Repert. Med. y Cirugía, 2017. https://doi.org/10.1016/j.reper.2017.03.004. DOI: https://doi.org/10.1016/j.reper.2017.03.004

P. S. Wells et al., "Value of assessment of pretest probability of deep-vein thrombosis in clinical management," Lancet, vol. 350, no. 9094, pp. 1795-1798, 1997. https://doi.org/10.1016/S0140-6736(97)08140-3. DOI: https://doi.org/10.1016/S0140-6736(97)08140-3

R. Oudega, K. G. M. Moons, and A. W. Hoes, "Ruling out deep venous thrombosis in primary care. A simple diagnostic algorithm including D-dimer testing," Thromb. Haemost., 2005. https://doi.org/10.1160/TH04-12-0829. DOI: https://doi.org/10.1160/TH04-12-0829

R. J. Darwood and F. C. T. Smith, "Deep vein thrombosis," Surgery (United Kingdom). 2013. https://doi.org/10.1016/j.mpsur.2013.02.001. DOI: https://doi.org/10.1016/j.mpsur.2013.02.001

P. Priollet and V. Bossy, "Actitud práctica y tratamiento de una trombosis venosa profunda," EMC - Tratado Med., vol. 6, no. 3, pp. 1-4, Jan. 2002. https://doi.org/10.1016/S1636-5410(02)70215-8. DOI: https://doi.org/10.1016/S1636-5410(02)70215-8

M. G. Kirchhof, A. Y. Y. Lee, and J. P. Dutz, "D-Dimer Levels as a Marker of Cutaneous Disease Activity: Case Reports of Cutaneous Polyarteritis Nodosa and Atypical Recurrent Urticaria," JAMA Dermatology, vol. 150, no. 8, pp. 880-884, 2014. https://doi.org/10.1001/jamadermatol.2013.9944. DOI: https://doi.org/10.1001/jamadermatol.2013.9944

T. T, K. N, L. G. G, and W. PS, "Venous thromboembolism: Advances in diagnosis and treatment," JAMA, vol. 320, no. 15, pp. 1583-1594, 2018. https://doi.org/10.1001/jama.2018.14346. DOI: https://doi.org/10.1001/jama.2018.14346

J. E. Francis, R. Roggli, T. J. Love, and C. P. Robinson, "Thermography as a means of blood perfusion measurement.," J. Biomech. Eng., 1979. https://doi.org/10.1115/1.3426253. DOI: https://doi.org/10.1115/1.3426253

C. L. Huang et al., "The application of infrared thermography in evaluation of patients at high risk for lower extremity peripheral arterial disease," J. Vasc. Surg., 2011. https://doi.org/10.1016/j.jvs.2011.03.287. DOI: https://doi.org/10.1016/j.jvs.2011.03.287

C. Jin et al., "A feasible method for measuring the blood flow velocity in superficial artery based on the laser induced dynamic thermography," Infrared Phys. Technol., 2012. https://doi.org/10.1016/j.infrared.2012.07.007. DOI: https://doi.org/10.1016/j.infrared.2012.07.007

F. Deng, Q. Tang, G. Zeng, H. Wu, N. Zhang, and N. Zhong, "Effectiveness of digital infrared thermal imaging in detecting lower extremity deep venous thrombosis," Med. Phys., 2015. https://doi.org/10.1183/13993003.congress-2015.PA2259. DOI: https://doi.org/10.1183/13993003.congress-2015.PA2259

S. Kacmaz, E. Ercelebi, S. Zengin, and S. Cindoruk, "The use of infrared thermal imaging in the diagnosis of deep vein thrombosis," Infrared Phys. Technol., vol. 86, pp. 120-129, 2017. https://doi.org/10.1016/j.infrared.2017.09.005. DOI: https://doi.org/10.1016/j.infrared.2017.09.005

A. Saxena, E. Y. K. Ng, and V. Raman, "Thermographic venous blood flow characterization with external cooling stimulation," Infrared Phys. Technol., 2018. https://doi.org/10.1016/j.infrared.2018.02.001. DOI: https://doi.org/10.1016/j.infrared.2018.02.001

B. B. Lahiri, S. Bagavathiappan, T. Jayakumar, and J. Philip, "Medical applications of infrared thermography: A review," Infrared Physics and Technology. 2012. https://doi.org/10.1016/j.infrared.2012.03.007. DOI: https://doi.org/10.1016/j.infrared.2012.03.007

J. R. Harding, "Thermal imaging in the investigation of deep venous thrombosis," Proc. 17th Int. Conf. Eng. Med. Biol. Soc., vol. 2, pp. 1972-1974, 1995.

S. Z. Goldhaber and H. Bounameaux, "Pulmonary embolism and deep vein thrombosis," in The Lancet, 2012. https://doi.org/10.1016/S0140-6736(11)61904-1. DOI: https://doi.org/10.1016/S0140-6736(11)61904-1

A. T. Cohen et al., "Venous thromboembolism (VTE) in Europe. The number of VTE events and associated morbidity and mortality.," Thromb. Haemost., 2007. https://doi.org/10.1160/TH07-03-0212. DOI: https://doi.org/10.1160/TH07-03-0212

G. Paola Paolinelli, “Principios físicos e indicaciones clínicas del ultrasonido doppler,” Rev. Médica Clínica Las Condes, vol. 24, no. 1, pp. 139–148, 2013. https://doi.org/10.1016/S0716-8640(13)70139-1 DOI: https://doi.org/10.1016/S0716-8640(13)70139-1

C. Kearon, J. A. Julian, T. E. Newman, and J. S. Ginsberg, "Noninvasive diagnosis of deep venous thrombosis. McMaster Diagnostic Imaging Practice Guidelines Initiative.," Ann. Intern. Med., 1998. https://doi.org/10.7326/0003-4819-128-8-199804150-00011. DOI: https://doi.org/10.7326/0003-4819-128-8-199804150-00011

J. B. Segal, J. Eng, L. J. Tamariz, and E. B. Bass, "Review of the evidence on diagnosis of deep venous thrombosis and pulmonary embolism," Annals of Family Medicine. 2007. https://doi.org/10.1370/afm.648. DOI: https://doi.org/10.1370/afm.648

C. Landefeld, "Noninvasive diagnosis of deep vein thrombosis," JAMA, vol. 300, no. 14, pp. 1696-1697, Oct. 2008. https://doi.org/10.1001/jama.300.14.1696. DOI: https://doi.org/10.1001/jama.300.14.1696

S. Muth, S. Dort, I. A. Sebag, M.-J. Blais, and D. Garcia, "Unsupervised dealiasing and denoising of color-Doppler data," Med. Image Anal., vol. 15, no. 4, pp. 577-588, 2011. https://doi.org/10.1016/j.media.2011.03.003. DOI: https://doi.org/10.1016/j.media.2011.03.003

J. G. Stevenson, "The Development of Color Doppler Echocardiography: Innovation and Collaboration," J. Am. Soc. Echocardiogr., vol. 31, no. 12, pp. 1344-1352, 2018. https://doi.org/10.1016/j.echo.2018.08.005. DOI: https://doi.org/10.1016/j.echo.2018.08.005

J. Torres Macho et al., "Positioning document on incorporating point-of-care ultrasound in Internal Medicine departments," Rev. Clin. Esp., 2018. https://doi.org/10.1016/j.rceng.2018.02.004. DOI: https://doi.org/10.1016/j.rceng.2018.02.004

N. Fortier O'brien et al., "Transcranial Doppler Ultrasonography Provides Insights into Neurovascular Changes in Children with Cerebral Malaria Article in Press the Journal of Pediatrics. www.jpeds.com," J. Pediatr., 2018. https://doi.org/10.1016/j.jpeds.2018.07.075. DOI: https://doi.org/10.1016/j.jpeds.2018.07.075

G. Paola Paolinelli, "Principios físicos e indicaciones clínicas del ultrasonido doppler," Rev. Médica Clínica Las Condes, 2013. https://doi.org/10.1016/S0716-8640(13)70139-1. DOI: https://doi.org/10.1016/S0716-8640(13)70139-1

A. G. Bolado, M. V. Bárcena, J. L. del Cura, O. Gorriño, and D. Grande, "Indicación de eco-Doppler venosa de extremidades inferiores en el diagnóstico de la enfermedad tromboembólica ante una sospecha de tromboembolismo pulmonar Diagnostic Indication for Venous Echo-Doppler of the Lower Limbs in the Diagnosis of Thromboembolic," Radiologia, vol. 45, no. 5, pp. 213-218, 2011. https://doi.org/10.1016/S0033-8338(03)77905-3. DOI: https://doi.org/10.1016/S0033-8338(03)77905-3

J. Kelly and B. J. Hunt, "The utility of pretest probability assessment in patients with clinically suspected venous thromboembolism," Journal of Thrombosis and Haemostasis. 2003. https://doi.org/10.1046/j.1538-7836.2003.00382.x. DOI: https://doi.org/10.1046/j.1538-7836.2003.00382.x

S. PC, I. IK, G. SZ, P. G, B. CB, and K. R, "Performance of wells score for deep vein thrombosis in the inpatient setting," JAMA Intern. Med., vol. 175, no. 7, pp. 1112-1117, 2015. https://doi.org/10.1001/jamainternmed.2015.1687. DOI: https://doi.org/10.1001/jamainternmed.2015.1687

C. E. A. Dronkers et al., "Disease prevalence dependent failure rate in diagnostic management studies on suspected deep vein thrombosis: communication from the SSC of the ISTH," J. Thromb. Haemost., 2017. https://doi.org/10.1111/jth.13805. DOI: https://doi.org/10.1111/jth.13805

P. M. Reardon et al., "Diagnostic Accuracy and Financial Implications of Age-Adjusted D-Dimer Strategies for the Diagnosis of Deep Venous Thrombosis in the Emergency Department," J. Emerg. Med., 2019. https://doi.org/10.1016/j.jemermed.2019.01.027. DOI: https://doi.org/10.1016/j.jemermed.2019.01.027

B. A. Parry et al., "International, multicenter evaluation of a new D-dimer assay for the exclusion of venous thromboembolism using standard and age-adjusted cut-offs," Thromb. Res., 2018. https://doi.org/10.1016/j.thromres.2018.04.003. DOI: https://doi.org/10.1016/j.thromres.2018.04.003

K. Broen, B. Scholtes, and R. Vossen, "Predicting the need for further thrombosis diagnostics in suspected DVT is increased by using age adjusted D-dimer values," Thrombosis Research. 2016. https://doi.org/10.1016/j.thromres.2016.08.011. DOI: https://doi.org/10.1016/j.thromres.2016.08.011

S. Sharif et al., "Comparison of the age-adjusted and clinical probability-adjusted D-dimer to exclude pulmonary embolism in the ED," Am. J. Emerg. Med., 2019. https://doi.org/10.1016/j.ajem.2018.07.053. DOI: https://doi.org/10.1016/j.ajem.2018.07.053

G. Cano et al., "Predicción de solubilidad de fármacos usando máquinas de soporte vectorial sobre unidades de procesamiento gráfico," Rev. Int. Metod. Numer. para Calc. y Disen. en Ing., 2017. https://doi.org/10.1016/j.rimni.2015.12.001. DOI: https://doi.org/10.1016/j.rimni.2015.12.001

J. J. Sprockel, J. J. Diaztagle, W. Alzate, and E. González, "Redes neuronales en el diagnóstico del infarto agudo de miocardio," Rev. Colomb. Cardiol., 2014. https://doi.org/10.1016/j.rccar.2013.10.001. DOI: https://doi.org/10.1016/j.rccar.2013.10.001

H. Abe et al., "Artificial neural networks (ANNs) for differential diagnosis of interstitial lung disease: results of a simulation test with actual clinical cases1," Acad. Radiol., vol. 11, no. 1, pp. 29-37, 2004. https://doi.org/10.1016/S1076-6332(03)00572-5. DOI: https://doi.org/10.1016/S1076-6332(03)00572-5

C. Peña-autista, T. Durand, C. Oger, M. Baquero, M. Vento, and C. Cháfer-Pericás, "Assessment of lipid peroxidation and artificial neural network models in early Alzheimer Disease diagnosis," Clin. Biochem., 2019. https://doi.org/10.1016/j.clinbiochem.2019.07.008. DOI: https://doi.org/10.1016/j.clinbiochem.2019.07.008

I. A. Ozkan, M. Koklu, and I. U. Sert, "Diagnosis of urinary tract infection based on artificial intelligence methods," Comput. Methods Programs Biomed., vol. 166, pp. 51-59, 2018. https://doi.org/10.1016/j.cmpb.2018.10.007. DOI: https://doi.org/10.1016/j.cmpb.2018.10.007

Artificial Intelligence with medical applications Artificial Intelligence with medical applications Inteligencia artificial con aplicaciones médicas Artificial intelligence medical applications Aplicaciones médicas de inteligencia artificial

Published

2020-07-15

How to Cite

Fong-Mata, M. B., Inzunza-González, E., García-Guerrero, E. E., Mejía Medina, D. A., Morales Contreras, O. A., & Gómez-Roa, A. (2020). Deep vein thrombosis in lower extremities: review of current diagnostic techniques and their symbiosis with machine learning for timely diagnosis. REVISTA DE CIENCIAS TECNOLÓGICAS, 3(1), 23–34. https://doi.org/10.37636/recit.v312334

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