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Estimating Organ Dose From CT Scans Performed with Tube Current Modulated Scans

M Khatonabadi

M Khatonabadi1*, G Chu1, D Oria2, C Cagnon1, J DeMarco1, M McNitt-Gray1, (1) UCLA School of Medicine, Los Angeles, CA, (2) UCLA, Los Angeles, CA

MO-D-134-2 Monday 2:00PM - 3:50PM Room: 134

Purpose: To develop and evaluate a method for estimating organ dose from CT scans performed with tube current modulation (TCM) using a size metric that accounts for patient attenuation as well as a regional descriptor of scanner output.

Methods: 100 chest and 81 abdomen/pelvis patient scans acquired using TCM on a Multidetector row CT scanner (CareDose 4D, Sensation 64, Siemens Healthcare) were collected under IRB approval to generate voxelized patient models. The TCM information was extracted from the raw projection data for use in Monte Carlo (MC) simulations which accounted for both scanner and patient details. For each patient, water equivalent diameter (WED) was used as the size metric to account for patient attenuation. WED was calculated on each image based on semiautomatic segmentation. A regional CTDIvol value was used as a normalization quantity to account for local variations in scanner output. MC simulations were used to estimate dose to lungs and glandular breast tissue in the chest models, and liver, spleen, and kidneys in the abdomen/pelvis models. Half of the models in each exam category were used as a training set to develop the organ dose estimation model based on WED and CTDIvol,regional; the remaining cases were used as a test set. Organ doses were estimated using each model and were compared to the detailed MC simulation results and an RMSE across cases was calculated.

Results: For chest exams, the RMSE between the model and detailed MC simulations was 14.9% for lung and 13.6% for breast. For abdomen/pelvis exams, the RMSE was 15.0% for kidney, 9.2% for liver and 12.2% for spleen.

Conclusion: This method to estimate organ dose from CT scans using TCM demonstrated agreement of within 33% between the model and detailed MC simulations and shows promise for estimating organ doses when TCM is used.

Funding Support, Disclosures, and Conflict of Interest: Dr. Michael McNitt-Gray: Institutional research agreement, Siemens AG Recipient research support Siemens AG Consultant, Flaherty Sensabaugh Bonasso PLLC Consultant, Fulbright and Jaworski, LLC Maryam Khatonabadi: Recipient research support Siemens AG

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