Purpose: To examine the potential for dose reduction in chest CT studies where lesion
volume is the primary output (e.g. in therapy-monitoring applications).
Methods: We added noise to the raw sinogram data from 15 chest exams with lung lesions
to simulate a series of reduced-dose scans for each patient. We reconstructed the
reduced-dose data on the clinical workstation and imported the resulting image series into
our quantitative imaging database for lesion contouring. One reader contoured the lesions
(one per patient) at the clinical reference dose (100%) and 8 simulated fractions of the
clinical dose (50, 25, 15, 10, 7, 5, 4, and 3%). Dose fractions were hidden from the reader
to reduce bias. We compared clinical and reduced-dose volumes in terms of bias error and
variability (4x the standard deviation of the percent differences).
Results: Averaging over all lesions, the bias error ranged from -0.6% to 10.6%. Variability
ranged from 92% at 3% of clinical dose to 54% at 50% of clinical dose. Averaging over
only the smaller lesions (<1cm equivalent diameter), bias error ranged from -9.2% to 14.1%
and variability ranged from 125% at 3% dose to 33.9% at 50% dose.
Conclusions: The reader’s variability decreased with dose, especially for smaller lesions.
However, these preliminary results are limited by potential recall bias, a small patient
cohort, and an overly-simplified task. Therapy monitoring often involves checking for new
lesions, which may influence the reader’s clinical dose threshold for acceptable