Relationship between CT scan density and hematoma age on chronic subdural hematoma cases

Zulfadli Rizky Akbar , Agus Turchan, Sri Andreani Utomo, Dyah Fauziah

Zulfadli Rizky Akbar
Department of Neurosurgery, Faculty of Medicine Airlangga University/ Dr. Soetomo Academic General Hospital, Indonesia. Email:

Agus Turchan
Department of Neurosurgery, Faculty of Medicine Airlangga University/ Dr. Soetomo Academic General Hospital, Indonesia

Sri Andreani Utomo
Department of Radiology, Faculty of Medicine Airlangga University/ Dr. Soetomo Academic General Hospital, Indonesia

Dyah Fauziah
Department of Anatomical Pathology, Faculty of Medicine Airlangga University/ Dr. Soetomo Academic General Hospital, Indonesia
Online First: April 22, 2021 | Cite this Article
Akbar, Z., Turchan, A., Utomo, S., Fauziah, D. 2021. Relationship between CT scan density and hematoma age on chronic subdural hematoma cases. Indonesian Journal of Neurosurgery 4(1). DOI:10.15562/ijn.v4i1.135

Background: Subdural hematomas (SDH) can occur in one in three people with severe head injuries. Subdural hematomas are increasingly being found with age. Study of correlation of histopathological changes in hematoma and radiological contents of cases of subdural hematoma are still very limited. 

Objective: In this research, SDH histopathological changes are expected to be a reference and consideration in the next invasive therapeutic action. This study also aims to look for other approaches in determining the therapeutic actions in acute subdural hematomas by comparing the clinical, radiological, and histopathological profiles of blood deposits from subdural hematomas

Methods: This study is a clinical observational study with a cross sectional study approach. Primary data were obtained from all subdural hematoma patients. CT Scan was performed and the results were read by Radiologists. Hematoma blood samples was analysed microscopically and morphologically by Pathologist at our hospital.

Results: The average value of CT Scan blood reading density of Chronic SDH patients in RSUD Dr. Soetomo which was operated on in 2018-2019 was 31.30 (± 11.47) HU with the smallest value of 4.0 and the largest 54 HU. Average day of events was 36 ± 36.66 days with the shortest occurrence day 12 days and the longest 150 days. There is an influence between the CT Scan reading density and the day of the incident. The calculation results obtained a negative correlation (r = -0.814; p <0.001) between the CT Scan density value and the day of occurrence. Statistical calculation of the coefficient B0 for the dependent variable (day of occurrence) is 147.557 and the coefficient of B1 for the HU value from the CT Scan reading is -3.417. In this study, the histology generally did not represent chronic SDH readings specifically.

Conclusion: There’s a negative correlation between the number of incident days with the CT Scan density where the longer the event day the lower the CT Scan density value.

Keywords: Subdural Hematomas, CT Scan Density, Histopathological


Tallon, J. M., Ackroyd-Stolarz, S., Karim, S. A. & Clarke, D. B. The epidemiology of surgically treated acute subdural and epidural hematomas in patients with head injuries: A population-based study. Can. J. Surg. 51, 339–345 (2008).

Karibe, H., Kameyama, M., Kawase, M. & Tominaga, T. Epidemiology of chronic subdural hematoma. No Shinkei Geka, Neurol. Surg. 39, 1149–1153 (2011).

Hobbs, C., Childs, A. M., Wynne, J., Livingston, J. & Seal, A. Subdural haematoma and effusion in infancy: An epidemiological study. Arch. Dis. Child. 90, 952–955 (2005).

Louhab, N. et al. Misdiagnosed spontaneous intracranial hypotension complicated by subdural hematoma following lumbar puncture. Int. J. Gen. Med. 7, 71–73 (2014).

Vezina, G. Assessment of the nature and age of subdural collections in nonaccidental head injury with CT and MRI. Pediatr. Radiol. 39, 586–590 (2009).

Postema, F. A. M., Sieswerda-Hoogendoorn, T., Majoie, C. B. L. M. & Van Rijn, R. R. Age determination of subdural hematomas: Survey among radiologists. Emerg. Radiol. 21, 349–358 (2014).

Rovlias, A., Theodoropoulos, S. & Papoutsakis, D. Chronic subdural hematoma: Surgical management and outcome in 986 cases: A classification and regression tree approach. Surg. Neurol. Int. 6, (2015).

Jeong, S. Il, Kim, S. O., Won, Y. S., Kwon, Y. J. & Choi, C. S. Clinical Analysis of Risk Factors for Recurrence in Patients with Chronic Subdural Hematoma Undergoing Burr Hole Trephination. Korean J. Neurotrauma 10, 15 (2014).

Sieswerda-Hoogendoorn, T., Postema, F. A. M., Verbaan, D., Majoie, C. B. & Van Rijn, R. R. Age determination of subdural hematomas with CT and MRI: A systematic review. Eur. J. Radiol. 83, 1257–1268 (2014).

Rao, M. G., Singh, D., Vashista, R. K. & Sharma, S. K. Dating of acute and subacute subdural haemorrhage: A histo-pathological study. J. Clin. Diagnostic Res. 10, HC01–HC07 (2016).

Bokka, S. & Trivedi, A. Histopathological study of the outer membrane of the dura mater in chronic sub dural hematoma: Its clinical and radiological correlation. Asian J. Neurosurg. 11, 34 (2016).

Hedlund, G. L. & Frasier, L. D. Neuroimaging of abusive head trauma. Forensic Sci. Med. Pathol. 5, 280–290 (2009).

Foerster, B. R. et al. Neuroimaging Evaluation of Non-accidental Head Trauma with Correlation to Clinical Outcomes: A Review of 57 Cases. J. Pediatr. 154, 573–577 (2009).

Atkinson, J. L. D., Lane, J. I. & Aksamit, A. J. MRI depiction of chronic intradural (subdural) hematoma in evolution. J. Magn. Reson. Imaging 17, 484–486 (2003).

Lee, S. H. et al. The potential of diffusion-weighted magnetic resonance imaging for predicting the outcomes of chronic subdural hematomas. J. Korean Neurosurg. Soc. 61, 97–104 (2018).

Yadav, Y. et al. Role of endoscopic third ventriculostomy in tuberculous meningitis with hydrocephalus. Asian J. Neurosurg. 11, 325 (2016).

Benson, J. C. et al. Clot permeability and histopathology: Is a clot’s perviousness on CT imaging correlated with its histologic composition? J. Neurointerv. Surg. 12, 38–42 (2020).

Borggrefe, J. et al. Differentiation of Clot Composition Using Conventional and Dual-Energy Computed Tomography. Clin. Neuroradiol. 28, 515–522 (2018).

Kirchhof, K., Welzel, T., Mecke, C., Zoubaa, S. & Sartor, K. Differentiation of white, mixed, and red thrombi: Value of CT in estimation of the prognosis of thrombolysis - Phantom study. Radiology 228, 126–130 (2003).

Niesten, J. M. et al. Histopathologic composition of cerebral thrombi of acute stroke patients is correlated with stroke subtype and thrombus attenuation. PLoS One 9, 12–14 (2014).

Santos, E. M. M. et al. Permeable Thrombi Are Associated with Higher Intravenous Recombinant Tissue-Type Plasminogen Activator Treatment Success in Patients with Acute Ischemic Stroke. Stroke 47, 2058–2065 (2016).

Article Views      : 35
PDF Downloads : 23