Ichiro Ikuta MD, MMSc, Presenter: Nothing to Disclose

Katherine P. Andriole PhD, Abstract Co-Author: Nothing to Disclose

Graham Ingersoll Warden MD, Abstract Co-Author: Nothing to Disclose

Leena M. Hamberg PhD, Abstract Co-Author: Nothing to Disclose

Ramin Khorasani MD, Abstract Co-Author: Stockholder, Medicalis Corp Royalties, Medicalis Corp Advisory Board, General Electric Company

Aaron D. Sodickson MD, PhD, Abstract Co-Author: Consultant, Siemens AG Consultant, Bayer AG

The extraction of patient size from axial CT images must compensate for variable degrees of image truncation occurring in routine clinical imaging where the field of view (FOV) may limit visualization of the entire patient contour. The aim of this study is to explore and correct the effect of image truncation on the automated assessment of patient size for axial CT images.

Fifty CT scans of the thorax and abdomen/pelvis performed in the emergency department in January 2012 with the original FOV used by the technologist, and subsequently reconstructed with variable FOV (FOV = 200-500 mm by 50 mm increments). The open source Generalized Radiation Observation Kit (GROK) application automatically calculates the total attenuation-area product for the entire axial CT image, producing a water-equivalent diameter (DW). GROK also calculated the proportion of image FOV border pixels containing air attenuation as a metric for truncation (<1 indicating that patient tissue traversed the edge of the FOV). For each image in the CT scan the proportion of full FOV DW was plotted against the FOV air periphery proportion, and linear regression models used to assess and correct for the effect of truncation for clinical images.

For linear regression of the thorax, R2 = 0.598, p < 0.0001, n = 4639 clinical images; for the abdomen/pelvis, R2 = 0.725, p < 0.0001, n = 7711 clinical images. The calculated DW of clinical images was within 5% of full FOV DW in 96% of the abdomen/pelvis images, and 53% of the thorax images. Applying linear regression models to the clinical images allows calculation of corrected DW values (DW predicted for full FOV image reconstruction without truncation). These corrected DW values are within 5% of full FOV image reconstruction DW for 100% of abdomen/pelvis images, and for 91% of thoracic images.

Despite the presence of image truncation of axial CT images in clinical practice, it is possible to correct for the effects of image truncation on patient size estimation. By increasing the amount of corrected patient size information available, more appropriate corrections of radiation exposure metrics (such as volume computed tomography dose index) may be obtained.

By correcting for the effects of image truncation, automated patient size estimates may be derived for the majority of existing axial CT images produced in normal clinical routine.

Ikuta, I, Andriole, K, Warden, G, Hamberg, L, Khorasani, R, Sodickson, A, Automated Extraction of Patient Size from Axial Computed Tomography (CT) Images with Correction for the Effects of Image Truncation.  Radiological Society of North America 2012 Scientific Assembly and Annual Meeting, November 25 - November 30, 2012 ,Chicago IL. http://archive.rsna.org/2012/12043924.html