Related Experiment Video
Updated: May 2, 2026
Multifractal Spectrum Analysis for Assessing Pulmonary Nodule Malignancy
Published on: January 10, 2025
Ultralow-dose chest computed tomography for pulmonary nodule detection: first performance evaluation of single energy
Sonja Gordic1, Fabian Morsbach, Bernhard Schmidt
1From the *Institute for Diagnostic and Interventional Radiology, University Hospital Zurich, Switzerland; †Computed Tomography Division, Siemens Healthcare, Forchheim, ‡University of Erlangen-Nuremberg, Erlangen; §University of Tübingen, Tübingen, Germany; and ∥Institute of Radiology, Kantonsspital St. Gallen, Switzerland.
Purpose:
The purpose of this study was to evaluate the image quality and sensitivity of ultralow radiation dose single-energy computed tomography (CT) with tin filtration for spectral shaping and iterative reconstructions for the detection of pulmonary nodules in a phantom setting.
Methods:
Single-energy CT was performed using third-generation dual-source CT (SOMATOM Force; 2 × 192 slices) at 70 kVp, 100 kVp with tin filtration (100Sn kVp), and 150Sn kV with tube current-time product adjustments resulting in standard dose (CT volume dose index, 3.1 mGy/effective dose, 1.3 mSv at a scan length of 30 cm), 1/10th dose level (0.3 mGy/0.13 mSv), and 1/20th dose level (0.15 mGy/0.06 mSv). An anthropomorphic chest phantom simulating an intermediate-sized adult with randomly distributed solid pulmonary nodules of various sizes (2-10 mm; attenuation, 75 HU at 120 kVp) was used. Images were reconstructed with advanced model-based iterative reconstruction (ADMIRE; strength levels 3 and 5) and were compared with those acquired with second-generation dual-source CT at 120 kVp (reconstructed with filtered back projection) and sinogram-affirmed iterative reconstruction (strength level 3) at the lowest possible dose at 120 kVp (CT volume dose index, 0.28 mGy). One blinded reader measured image noise, and 2 blinded, independent readers determined overall image quality on a 5-grade scale (1 = nondiagnostic to 5 = excellent) and marked nodule localization with confidence rates on a 5-grade scale (1 = unsure to 5 = high confidence). The constructional drawing of the phantom served as reference standard for calculation of sensitivity. Two patients were included, for proof of concept, who were scanned with the 100Sn kVp protocol at the 1/10th and 1/20th dose level.
Results:
Image noise was highest in the images acquired with second-generation dual-source CT and reconstructed with filtered back projection. At both the 1/10th and 1/20th dose levels, image noise at a tube voltage of 100Sn kVp was significantly lower than in the 70 kVp and 150Sn kV data sets (ADMIRE 3, P < 0.01; ADMIRE 5, P < 0.05). Sensitivity of nodule detection was lowest in images acquired with second-generation dual-source CT at 120 kVp and the lowest possible dose. Protocols at 100Sn kVp and ADMIRE 5 showed highest sensitivity at the 1/10th and 1/20th dose levels. Highest numbers of false-positives occurred in second-generation dual-source CT images (range, 12-15), whereas lowest numbers occurred in the 1/10th and 1/20th dose data sets acquired with third-generation dual-source CT at 100Sn kVp and reconstructed with ADMIRE strength levels 3 and 5 (total of 1 and 0 false-positives, respectively). Diagnostic confidence at 100Sn kVp was significantly higher than at 70 kVp or 150Sn kV (ADMIRE 3, P < 0.05; ADMIRE 5, P < 0.01) at both the 1/10th and 1/20th dose levels. Images of the 2 patients scanned with 100Sn kVp at the 1/10th and 1/20th dose levels were of diagnostic quality.
Conclusions:
Our study suggests that chest CT for the detection of pulmonary nodules can be performed with third-generation dual-source CT producing high image quality, sensitivity, and diagnostic confidence at a very low effective radiation dose of 0.06 mSv when using a single-energy protocol at 100 kVp with spectral shaping and when using advanced iterative reconstruction techniques.
