Precision and Speed at Your Fingertips: An Automated Intracranial Hematoma Volume Calculation

• Published in: World neurosurgery Vol. 185; pp. e827 - e834
• Main Authors: Khademolhosseini, Sepehr, Habibzadeh, Adrina, Zoghi, Sina, Taheri, Reza, Niakan, Amin, Khalili, HosseinAli
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.05.2024
• Subjects: Automated image analysis software; Hematoma quantification; ICH; Imaging detection; Noncontrast computed tomography; Automated image analysis software; CCC; Hematoma quantification; EDH; ICC; Imaging detection; IQR; HU; ICH; CT; SDH; DICOM; AHD; Noncontrast computed tomography; Non-contrast computed tomography; Imaging Detection
• ISSN: 1878-8750; 1878-8769; 1878-8769
• DOI: 10.1016/j.wneu.2024.02.135

Intracranial hemorrhage (ICH) is a severe condition that requires rapid diagnosis and treatment. Automated methods for calculating ICH volumes can reduce human error and improve clinical decisioPlease provide professional degrees (e.g., PhD, MD) for the corresponding author.n-making. A novel automated method has been developed that is comparable to the ABC/2 method in terms of speed and accuracy while providing more accurate volumetric data. We developed a novel automated algorithm for calculating intracranial blood volume from computed tomography (CT) scans. The algorithm consists of a Python script that processes Digital Imaging and Communications in Medicine images and determines the blood volume and ratio. The algorithm was validated against manual calculations performed by neurosurgeons. Our novel automated algorithm for calculating intracranial blood volume from CT scans demonstrated excellent agreement with the ABC/2 method, with a median overall difference of just 1.46 mL. The algorithm was also validated in patient groups with ICH, epidural hematoma (EDH), and SDH, with agreement coefficients of 0.992, 0.983, and 0.997, respectively. The study introduces a novel automated algorithm for calculating the volumes of various ICHs (EDH, and SDH) within CT scans. The algorithm showed excellent agreement with manual calculations and outperformed the commonly used ABC/2 method, which tends to overestimate ICH volume. The automated algorithm offers a more accurate, efficient, and time-saving approach to quantifying ICH, EDH, and SDH volumes, making it a valuable tool for clinical evaluation and decision-making. [Display omitted]