Patient‐specific radiation risk‐based tube current modulation for diagnostic CT

Abstract

Purpose Modern CT scanners use automatic exposure control (AEC) techniques, such as tube current modulation (TCM), to reduce dose delivered to patients while maintaining image quality. In contrast to conventional approaches that minimize the tube current time product of the CT scan, referred to as mAsTCM in the following, we herein propose a new method referred to as riskTCM, which aims at reducing the radiation risk to the patient by taking into account the specific radiation risk of every dose‐sensitive organ. Methods For current mAsTCM implementations, the mAs product is used as a surrogate for the patient dose. Thus, they do not take into account the varying dose sensitivity of different organs. Our riskTCM framework assumes that a coarse CT reconstruction, an organ segmentation, and an estimation of the dose distribution can be provided in real time, for example, by applying machine learning techniques. Using this information, riskTCM determines a tube current curve that minimizes a patient risk measure, for example, the effective dose, while keeping the image quality constant. We retrospectively applied riskTCM to 20 patients covering all relevant anatomical regions and tube voltages from 70 to 150 kV. The potential reduction of effective dose at same image noise is evaluated as a figure of merit and compared to mAsTCM and to a situation with a constant tube current referred to as noTCM. Results Anatomical regions like the neck, thorax, abdomen, and the pelvis benefit from the proposed riskTCM. On average, a reduction of effective dose of about 23% for the thorax, 31% for the abdomen, 24% for the pelvis, and 27% for the neck has been evaluated compared to today's state‐of‐the‐art mAsTCM. For the head, the resulting reduction of effective dose is lower, about 13% on average compared to mAsTCM. Conclusions With a risk‐minimizing TCM, significant higher reduction of effective dose compared to mAs‐minimizing TCM is possible.

Real‐time estimation of patient‐specific dose distributions for medical CT using the deep dose estimation

“…This real‐time capability can open up new options not only for dosimetry but also for scan and protocol optimization as, for instance, proposed by Maier et al 6 . and Klein et al 7 …”

“…While optimizing a Monte Carlo simulation to run in real time on a GPU is not trivial, DDE can be easily combined with any existing Monte Carlo code to achieve real-time performance. This real-time capability can open up new options not only for dosimetry but also for scan and protocol optimization as, for instance, proposed by Maier et al 6 and Klein et al 7 Considering a practical application of DDE, it has to be recalled that DDE is designed to reproduce Monte Carlo simulations rather than the "true"dose distribution. Therefore, its potential to predict dose distributions for a real system is limited by the quality of the Monte Carlo simulation that was used for training.…”

“…Typically, it is obtained either by a numerical inversion of a given theoretical model g : l H 2 O → q describing the data acquisition process for water-like samples, or by a calibration measurement of a water phantom relating measured qs to known l H 2 O s. Since water-precorrection is performed by default on all commercial systems, we do not apply it ourselves. For all experiments, we directly use the CT reconstruction f HU provided by the scanner, but undo the conversion to Hounsfield units (HU) to obtain f according to Equation (7):…”

“…However, with a rising number of CT examinations and the trend toward personalized medicine, patient-, and organ-specific dose estimates are becoming increasingly important not only in the context of dosimetry but also for protocol and scan optimization. 6,7 One way to obtain more accurate dose estimates is to measure the dose deposition in anthropomorphic phantoms that more closely resemble the patient's anatomy than CTDI phantoms. [8][9][10] However, their routine use is prevented by the high demands on preparation time and equipment.…”

“…Although these quantities do not include patient‐specific measures and therefore do not represent the actual patient dose, 4,5 they are still the most common dosimetric metrics in CT. However, with a rising number of CT examinations and the trend toward personalized medicine, patient‐, and organ‐specific dose estimates are becoming increasingly important not only in the context of dosimetry but also for protocol and scan optimization 6,7 …”