Ventricular Repolarization as a Tool to Monitor Electrical Activity of the Heart

Keywords
Acute; Pulmonary Embolism/complications; Prognosis; Precision Medicine; Compute Tomography/methods; Algorithms; Software; Artificial Intelligence/trends

Acute pulmonary embolism has a heterogeneous clinical presentation and the development of clinical tools for better stratification of the patients prognosis is extremely desired. Being able to discern which patient is most likely to have complications or even death is critical in the age of precision medicine. This may assist in choosing a more intensive and individualized treatment.¹

Computed tomography pulmonary angiography (CTPA) is already the most used method in emergencies for the diagnosis and stratification of patients with APE. The great variability of clinical presentations, whether in patients with cancer or different thrombogenic conditions, makes some quantitative data more attractive than just the qualitative analysis of the exam.^2–5

Thus, the work of Soriano et al.⁶ which develops a fully automated data analysis algorithm capable of extrapolating parameters that differentiate individuals most likely to die in a short period of time, is of great value.⁶

The main result is the adjusted pulmonary vascular volume (aPVV) was significantly decreased in the non-survivors group in comparison to the survivor's group (21±6 cm³/L vs. 30±7 cm³/L, p=0.001).⁶ And the best cutoff point of the aPVV to determine the one-month mortality was 23 cm³/L.⁶

At this stage, I would like to raise specific points that are fundamental for a good reading and understanding of the direction that this work provides us.

The sample size was probably not enough to have power to conclude that this method can be extrapolated to other populations, but it serves to advance a possible trend and encourage new studies. As discussed by the group, most of the studies already published recruited a much larger number of participants such as Coutance et al.⁷ with 383 patients with APE, Moroni at al.⁸ with 225 CTPA with non severe APE and Kamamaru et al.⁹ with 1698 CTPA from APE patients.

There is a clear selection bias because the pulmonary embolism (I26) code was not used as selection criteria in the hospital database record using the International Statistical Classification of Diseases (ICD-10). In this study, we have only the codes referring to pulmonary embolism with acute cor pulmonale (I26.0) and pulmonary embolism without acute cor pulmonale (I26.9).

Also, from 84 retrieved CTPA studies, just 61 (73%) were possible to be automated analyzed by the Yacta software. Generally, patients with more severe cases, greater dyspnea and hemodynamic instability will be those who will have datasets with more artifacts, making it difficult for the Yacta's algorithm.

Another point that I still doubt is the use of this method for different types of computed tomography scanners. Therefore, I am pleased to see the development achieved, but I still see many questions to be answered in a prospective and multicentric trial, with multivendor CT scanners.

Finally, I hope that the use of artificial intelligence adjusting to a database should be able to improve the software efficiency reducing the cases that are currently excluded. I also believe that this database may be used to categorize the findings. Let more studies come!!!

• Short Editorial related to the article: Pulmonary vascular volume estimated by automated software is a mortality predictor after acute pulmonary embolism

Referências

• ¹
  Hendriks BMF, Eijsvoogel NG, Kok M, Martens B, Wildberger JE and Das M. Optimizing Pulmonary Embolism Computed Tomography in the Age of Individualized Medicine: A Prospective Clinical Study. Invest Radiol 2018;53(10):306-12.
• ²
  Akhoundi N, Langroudi TF, Rajebi H, Haghi S, Paraham M, Karami S, Langroudi FK. Computed tomography pulmonary angiography for acute pulmonary embolism: prediction of adverse outcomes and 90-day mortality in a single test. Pol J Radiol 2019;84:e436-e446.
• ³
  Li C, Lin CT, Kligerman SJ, Hong SN, White CS. Enhancement Characteristics of the Computed Tomography Pulmonary Angiography Test Bolus Curve and Its Use in Predicting Right Ventricular Dysfunction and Mortality in Patients With Acute Pulmonary Embolism. J Thorac Imaging 2015;30(4):274-81.
• ⁴
  Mean M, Tritschler T, Limacher A, Breault S, Rodondi N, Aujesky D. Qanadli SD. Association between computed tomography obstruction index and mortality in elderly patients with acute pulmonary embolism: A prospective validation study. PLoS One 2017;12:e0179224.
• ⁵
  Venkatesh SK, Wang SC. Central clot score at computed tomography as a predictor of 30-day mortality after acute pulmonary embolism. Ann Acad Med Singap 2010;39:442-7.
• ⁶
  XSoriano L, Santos MK, Wada DT, Vilalva K, Castro TT, Weinheimer O, et al. Pulmonary Vascular Volume Estimated by Automated Software is a Mortality Predictor after Acute Pulmonary Embolism. Arq Bras Cardiol. 2020; 115(5):809-818.
• ⁷
  Coutance G, Cauderlier E, Ehtisham J, Hamon M, Hamon M. The prognostic value of markers of right ventricular dysfunction in pulmonary embolism: a meta-analysis. Crit Care 2011;15:R103.
• ⁸
  Moroni AL, Bosson JL, Hohn N, Carpentier F, Pernod G, Ferretti GR. Non-severe pulmonary embolism: prognostic CT findings. Eur J Radiol 2011;79:452-8.
• ⁹
  Kumamaru KK, Saboo SS, Aghayev A, Cai P, Quesada CG, George E, Hussain Z, et al. CT pulmonary angiography-based scoring system to predict the prognosis of acute pulmonary embolism. J Cardiovasc Comput Tomogr 2016;10(6):473-9.

Publication Dates

• Publication in this collection
  07 Dec 2020
• Date of issue
  Nov 2020