Direct measurement of radiation exposure dose to individual organs during diagnostic computed tomography examination

"Image quality evaluation of the Precise image CT deep learning reconstruction algorithm compared to Filtered Back-projection and iDose4: a phantom study at different dose levels"

PURPOSE

To characterize the performance of the Precise Image (PI) deep learning reconstruction (DLR) algorithm for abdominal Computed Tomography (CT) imaging.

METHODS

CT images of the Catphan-600 phantom (equipped with an external annulus) were acquired using an abdominal protocol at four dose levels and reconstructed using FBP, iDose⁴ (levels 2,5) and PI ('Soft Tissue' definition, levels 'Sharper','Sharp','Standard','Smooth','Smoother'). Image noise, image non-uniformity, noise power spectrum (NPS), target transfer function (TTF), detectability index (d'), CT numbers accuracy and image histograms were analyzed.

RESULTS

The behavior of the PI algorithm depended strongly on the selected level of reconstruction. The phantom analysis suggested that the PI image noise decreased linearly by varying the level of reconstruction from Sharper to Smoother, expressing a noise reduction up to 80% with respect to FBP. Additionally, the non-uniformity decreased, the histograms became narrower, and d' values increased as PI reconstruction levels changed from Sharper to Smoother. PI had no significant impact on the average CT number of different contrast objects. The conventional FBP NPS was deeply altered only by Smooth and Smoother levels of reconstruction. Furthermore, spatial resolution was found to be dose- and contrast-dependent, but in each analyzed condition it was greater than or comparable to FBP and iDose⁴ TTFs.

CONCLUSIONS

The PI algorithm can reduce image noise with respect to FBP and iDose⁴; spatial resolution, CT numbers and image uniformity are generally preserved by the algorithm but changes in NPS for the Smooth and Smoother levels need to be considered in protocols implementation.

Prospective Multireader Evaluation of Photon-counting CT for Multiple Myeloma Screening

Purpose To determine whether photon-counting CT (PCCT) acquisition of whole-body CT images provides similar quantitative image quality and reader satisfaction for multiple myeloma screening at lower radiation doses than does standard energy-integrating detector (EID) CT. Materials and Methods Patients with monoclonal gammopathy of undetermined significance prospectively underwent clinical noncontrast whole-body CT with EID and same-day PCCT (August-December 2021). Five axial scan locations were evaluated by seven radiologists, with 11% (eight of 70) of images including osteolytic lesions. Images were shown in randomized order, and each reader rated the following: discernibility of the osseous cortex and osseous trabeculae, perceived image noise level, and diagnostic confidence. Presence of lytic osseous lesions was indicated. Contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were calculated. Comparisons were made using paired t tests and mixed linear effects models. Results Seven participants (four women) were included (mean age, 66 years ± 9 [SD]; body mass index, 30.1 kg/m² ± 5.2). Mean cortical definition, trabecular definition, image noise, and image quality scores were 83, 67, 75, and 78 versus 84, 66, 74, and 76 for EID and PCCT, respectively (P = .65, .11, .26, and .11, respectively). PCCT helped identify more lesions (79% [22 of 28]) than did EID (64% [18 of 28]). CNRs and SNRs were similar between modalities. PCCT had lower radiation doses than EID (volume CT dose index: EID, 11.37 ± 2.8 vs PCCT, 1.8 ± 0.6 [P = .06]; dose-length product: EID, 1654.1 ± 409.6 vs PCCT, 253.4 ± 89.6 [P = .05]). Conclusion This pilot investigation suggests that PCCT affords similar quantitative and qualitative scores as EID at significantly lower radiation doses. Keywords: CT, CT-Spectral, Skeletal-Axial, Spine, Hematologic Diseases, Whole-Body Imaging, Comparative Studies Supplemental material is available for this article. © RSNA, 2022.

Deep Learning-Based Reconstruction vs. Iterative Reconstruction for Quality of Low-Dose Head-and-Neck CT Angiography with Different Tube-Voltage Protocols in Emergency-Department Patients

Objective: To compare the image quality of computed tomography angiography of the supra-aortic arteries (CTSA) at different tube voltages in low doses settings with deep learning-based image reconstruction (DLR) vs. hybrid iterative reconstruction (H-IR). Methods: We retrospectively reviewed 102 patients who underwent CTSA systematically reconstructed with both DLR and H-IR. We assessed the image quality both quantitatively and qualitatively at 11 arterial segmental levels and 3 regional levels. Radiation-dose parameters were recorded and the effective dose was calculated. Eighty-six patients were eligible for analysis Of these patients, 27 were imaged with 120 kVp, 30 with 100 kVp, and 29 with 80 kVp. Results: The effective dose in 120 kVp, 100 kVp and 80 kVp was 1.5 ± 0.4 mSv, 1.1 ± 0.3 mSv and 0.68 ± 0.1 mSv, respectively (p < 0.01). Comparing 80 kVp + DLR vs. 120 and 100 kVp + H-IR CT scans, the mean overall arterial attenuation was about 64% and 34% higher (625.9 ± 118.5 HU vs. 382.3 ± 98.6 HU and 468 ± 118.5 HU; p < 0.01) without a significant difference in terms of image noise (17.7 ± 4.9 HU vs. 17.5 ± 5.2; p = 0.7 and 18.1 ± 5.4; p = 0.3) and signal-to-ratio increased by 59% and 33%, respectively (37.9 ± 12.3 vs. 23.8 ± 9.7 and 28.4 ± 12.5). This protocol also provided superior image quality in terms of qualitative parameters, compared to standard-kVp protocols with H-IR. Highest subjective image-quality grades for vascular segments close to the aorta were obtained with the 100 kVp + DLR protocol. Conclusions: DLR significantly reduced image noise and improved the overall image quality of CTSA with both low and standard tube voltages and at all vascular segments. CT that was acquired with 80 kVp and reconstructed with DLR yielded better overall image quality compared to higher kVp values with H-IR, while reducing the radiation dose by half, but it has limitations for arteries that are close to the aortic arch.