Ultralow-dose CT with tin filtration for detection of solid and sub solid pulmonary nodules: a phantom study

Effect of tin spectral filtration on organ and effective dose in CT colonography and CT lung cancer screening

BACKGROUND

Studies of tin spectral filtration have demonstrated potential in reducing radiation dose while maintaining image quality for unenhanced computed tomography (CT) scans. The extent of dose reduction, however, was commonly measured using the change in the scanner's reported CTDIvol . This method does not account for how tin filtration affects patient organ and effective dose.

PURPOSE

To investigate the effect of tin filtration on patient organ and effective dose for CT Lung Cancer Screening (LCS) and CT Colonography (CTC).

METHODS

A previously-developed Monte Carlo program was adapted to model a 96-row CT scanner (Somatom Force, Siemens Healthineers) with tin filtration capabilities at 100 kV (100Sn) and 150 kV (150Sn). The program was then validated using experimental CTDIvol measurements at all available kV (70-150 kV) and tin-filtered kV options (100Sn and 150Sn). After validation, the program simulated LCS scans of the chest and CTC scan of the abdomen-pelvis for a population of 53 computational patient models from the extended cardiac-torso family. Each scan was performed using three different spectra: 120 kV, 100Sn, and 150Sn. CTDIvol -normalized organ doses and DLP-normalized effective doses, commonly referred to as dose conversion factors, were compared between the different spectra.

RESULTS

For all LCS and CTC scans, CTDIvol -normalized organ doses and DLP-normalized effective doses increased with increasing beam hardness (120 kV, 100Sn, 150 Sn). For LCS, relative for 120 kV, conversion factors for 100Sn produced a median increase in effective dose of 9%, with organ dose increases of 8% to lung, 5% to breast, 15% to thyroid, and 3% to skin. Conversion factors for 150Sn produced a median increase in effective dose of 20%, with organ dose increases of 16%, 18%, 26%, and 12% to these same organs, respectively. For CTC, relative for 120 kV, conversion factors for 100Sn produced a median increase in effective dose of 12%, with organ dose increases of 9% to colon, 10% to liver, 11% to stomach, and 4% to skin. Conversion factors for 150Sn produced a median increase in effective dose of 21%, with organ dose increases of 16%, 17%, 19%, and 10% to these same organs, respectively.

CONCLUSIONS

Results show that dose conversion factors are greater when using tin filtration and should be considered when evaluating tin's potential for dose reduction.

Ultra-low-dose CT for attenuation correction: dose savings and effect on PET quantification for protocols with and without tin filter

BACKGROUND

Ultra-low-dose (ULD) computed tomography (CT) scans should be used when CT is performed only for attenuation correction (AC) of positron emission tomography (PET) data. A tin filter can be used in addition to the standard aluminium bowtie filter to reduce CT radiation dose to patients. The aim was to determine how low CT doses can be, when utilised for PET AC, with and without the tin filter, whilst providing adequate PET quantification.

METHODS

A water-filled NEMA image quality phantom was imaged in three configurations with 18F-FDG: (1) water only (0HU); (2) with cylindrical insert containing homogenous mix of sand, flour and water (SFW, approximately 475HU); (3) with cylindrical insert containing sand (approximately 1100HU). Each underwent one-bed-position (26.3 cm) PET-CT comprising 1 PET and 13 CT acquisitions. CT acquisitions with tube current modulation were performed at 120 kV/50 mAs-ref (reference standard), 100 kV/7 mAs-ref (standard ULDCT for PET AC protocol), Sn140kV (mAs range 7-50-ref) and Sn100kV (mAs range 12-400-ref). PET data were reconstructed with μ-maps provided by each CT dataset, and PET activity concentration measured in each reconstruction. Differences in CT dose length product (DLP) and PET quantification were determined relative to the reference standard.

RESULTS

At each tube voltage, changes in PET quantification were greater with increasing density and reducing mAs. Compared with the reference standard, differences in PET quantification for the standard ULDCT protocol for the three phantoms were ≤ 1.7%, with the water phantom providing a DLP of 7mGy.cm. With tin filter at Sn100kV, differences in PET quantification were negligible (≤ 1.2%) for all phantoms down to 50mAs-ref, proving a DLP of 2.8mGy.cm, at 60% dose reduction compared with standard ULDCT protocol. Below 50mAs-ref, differences in PET quantification were > 2% for at least one phantom (2.3% at 25mAs-ref in SFW; 6.4% at 12mAs-ref in sand). At Sn140kV/7mAs-ref, quantification differences were ≤ 0.6% in water, giving 3.8mGy.cm DLP, but increased to > 2% at bone-equivalent densities.

CONCLUSIONS

CT protocols for PET AC can provide ultra-low doses with adequate PET quantification. The tin filter can allow 60-87% lower dose than the standard ULDCT protocol for PET AC, depending on tissue density and accepted change in PET quantification.

Accuracy of Nodule Volume and Airway Wall Thickness Measurement Using Low-Dose Chest CT on a Photon-Counting Detector CT Scanner

OBJECTIVES

A comparison of high-resolution photon-counting detector computed tomography (PCD-CT) versus energy-integrating detector (EID) CT via a phantom study using low-dose chest CT to evaluate nodule volume and airway wall thickness quantification.

MATERIALS AND METHODS

Twelve solid and ground-glass lung nodule phantoms with 3 diameters (5 mm, 8 mm, and 10 mm) and 2 shapes (spherical and star-shaped) and 12 airway tube phantoms (wall thicknesses, 0.27-1.54 mm) were placed in an anthropomorphic chest phantom. The phantom was scanned with EID-CT and PCD-CT at 5 dose levels (CTDI vol = 0.1-0.8 mGy at Sn-100 kV, 7.35 mGy at 120 kV). All images were iteratively reconstructed using matched kernels for EID-CT and medium-sharp kernel (MK) PCD-CT and an ultra-sharp kernel (USK) PCD-CT kernel, and image noise at each dose level was quantified. Nodule volumes were measured using semiautomated segmentation software, and the accuracy was expressed as the percentage error between segmented and reference volumes. Airway wall thicknesses were measured, and the root-mean-square error across all tubes was evaluated.

RESULTS

MK PCD-CT images had the lowest noise. At 0.1 mGy, the mean volume accuracy for the solid and ground-glass nodules was improved in USK PCD-CT (3.1% and 3.3% error) compared with MK PCD-CT (9.9% and 10.2% error) and EID-CT images (11.4% and 9.2% error), respectively. At 0.2 mGy and 0.8 mGy, the wall thickness root-mean-square error values were 0.42 mm and 0.41 mm for EID-CT, 0.54 mm and 0.49 mm for MK PCD-CT, and 0.23 mm and 0.16 mm for USK PCD-CT.

CONCLUSIONS

USK PCD-CT provided more accurate lung nodule volume and airway wall thickness quantification at lower radiation dose compared with MK PCD-CT and EID-CT.

Ultra-low dose computed tomography protocols using spectral shaping for lung cancer screening: Comparison with low-dose for volumetric LungRADS classification

PURPOSE

To compare Low-Dose Computed Tomography (LDCT) with four different Ultra-Low-Dose Computed Tomography (ULDCT) protocols for PN classification according to the Lung Reporting and Data System (LungRADS).

METHODS

Three hundred sixty-one participants of an ongoing lung cancer screening (LCS) underwent single-breath-hold double chest Computed Tomography (CT), including LDCT (120kVp, 25mAs; CTDIvol 1,62 mGy) and one ULDCT among: fully automated exposure control ("ULDCT₁"); fixed tube-voltage and current according to patient size ("ULDCT₂"); hybrid approach with fixed tube-voltage ("ULDCT₃") and tube current automated exposure control ("ULDCT₄"). Two radiologists (R1, R2) assessed LungRADS 2022 categories on LDCT, and then after 2 weeks on ULDCT using two different kernels (R1: Qr49_{ADMIRE 4}; R2: Br49_{ADMIRE 3}). Intra-subject agreement for LungRADS categories between LDCT and ULDCT was measured by the k-Cohen Index with Fleiss-Cohen weights.

RESULTS

LDCT-dominant PNs were detected in ULDCT in 87 % of cases on Qr49_{ADMIRE 4} and 88 % on Br49_{ADMIRE 3}. The intra-subject agreement was: κULDCT₁ = 0.89 [95 %CI 0.82-0.96]; κULDCT₂ = 0.90 [0.81-0.98]; κULDCT₃ = 0.91 [0.84-0.99]; κULDCT₄ = 0.88 [0.78-0.97] on Qr49_{ADMIRE 4}, and κULDCT₁ = 0.88 [0.80-0.95]; κULDCT₂ = 0.91 [0.86-0.96]; κULDCT₃ = 0.87 [0.78-0.95]; and κULDCT₄ = 0.88 [0.82-0.94] on Br49_{ADMIRE 3}. LDCT classified as LungRADS 4B were correctly identified as LungRADS 4B at ULDCT₃, with the lowest radiation exposure among the tested protocols (median effective doses were 0.31, 0.36, 0.27 and 0.37 mSv for ULDCT₁, ULDCT₂, ULDCT₃, and ULDCT₄, respectively).

CONCLUSIONS

ULDCT by spectral shaping allows the detection and characterization of PNs with an excellent agreement with LDCT and can be proposed as a feasible approach in LCS.

Detection and size quantification of pulmonary nodules in ultralow-dose versus regular-dose CT: a comparative study in COPD patients

OBJECTIVE

To evaluate detectability and semi-automatic diameter and volume measurements of pulmonary nodules in ultralow-dose CT (ULDCT) vs regular-dose CT (RDCT).

METHODS

Fifty patients with chronic obstructive pulmonary disease (COPD) underwent RDCT on 64-multidetector CT (120 kV, filtered back projection), and ULDCT on third-generation dual source CT (100 kV with tin filter, advanced modeled iterative reconstruction). One radiologist evaluated the presence of nodules on both scans in random order, with discrepancies judged by two independent radiologists and consensus reading. Sensitivity of nodule detection on RDCT and ULDCT was compared to reader consensus. Systematic error in semi-automatically derived diameter and volume, and 95% limits of agreement (LoA) were evaluated. Nodule classification was compared by κ statistics.

RESULTS

ULDCT resulted in 83.1% (95% CI: 81.0-85.2) dose reduction compared to RDCT (p < 0.001). 45 nodules were present, with diameter range 4.0-25.3 mm and volume range 16.0-4483.0 mm³. Detection sensitivity was non-significant (p = 0.503) between RDCT 88.8% (95% CI: 76.0-96.3) and ULDCT 95.5% (95% CI: 84.9-99.5). No systematic bias in diameter measurements (median difference: -0.2 mm) or volumetry (median difference: -6 mm³) was found for ULDCT compared to RDCT. The 95% LoA for diameter and volume measurements were ±3.0 mm and ±33.5%, respectively. κ value for nodule classification was 0.852 for diameter measurements and 0.930 for volumetry.

CONCLUSION

ULDCT based on Sn100 kV enables comparable detectability of solid pulmonary nodules in COPD patients, at 83% reduced radiation dose compared to RDCT, without relevant difference in nodule measurement and size classification.

ADVANCES IN KNOWLEDGE

Pulmonary nodule detectability and measurements in ULDCT are comparable to RDCT.

Semi-automated volumetry of pulmonary nodules: Intra-individual comparison of standard dose and chest X-ray equivalent ultralow dose chest CT scans

PURPOSE

To assess the performance of semi-automated volumetry of solid pulmonary nodules on single-energy tin-filtered ultralow dose (ULD) chest CT scans at a radiation dose equivalent to chest X-ray relative to standard dose (SD) chest CT scans and assess the impact of kernel and iterative reconstruction selection.

METHODS

Ninety-four consecutive patients from a prospective single-center study were included and underwent clinically indicated SD chest CT (1.9 ± 0.8 mSv) and additional ULD chest CT (0.13 ± 0.01 mSv) in the same session. All scans were reconstructed with a soft tissue (Br40) and lung (Bl64) kernel as well as with Filtered Back Projection (FBP) and Iterative Reconstruction (ADMIRE-3 and ADMIRE-5). One hundred and forty-eight solid pulmonary nodules were identified and analysed by semi-automated volumetry on all reconstructions. Nodule volumes were compared amongst all reconstructions thereby focusing on the agreement between SD and ULD scans.

RESULTS

Nodule volumes ranged from 58.5 (28.8-126) mm3 for ADMIRE-5 Br40 ULD reconstructions to 72.5 (39-134) mm3 for FBP Bl64 SD reconstructions with significant differences between reconstructions (p < 0.001). Interscan agreement of volumes between two given reconstructions ranged from ICC = 0.605 to ICC = 0.999. Between SD and ULD scans, agreement of nodule volumes was highest for FBP Br40 (ICC = 0.995), FBP Bl64 (ICC = 0.939) and ADMIRE-5 Bl64 (ICC = 0.994) reconstructions. ADMIRE-3 reconstructions exhibited reduced interscan agreement of nodule volumes (ICCs from 0.788 - 0.882).

CONCLUSIONS

The interscan agreement of node volumes between SD and ULD is high depending on the choice of kernel and reconstruction algorithm. However, caution should be exercised when comparing two image series that were not identically reconstructed.

Single CT Appointment for Double Lung and Colorectal Cancer Screening: Is the Time Ripe?

Annual screening of lung cancer (LC) with chest low-dose computed tomography (CT) and screening of colorectal cancer (CRC) with CT colonography every 5 years are recommended by the United States Prevention Service Task Force. We review epidemiological and pathological data on LC and CRC, and the features of screening chest low-dose CT and CT colonography comprising execution, reading, radiation exposure and harm, and the cost effectiveness of the two CT screening interventions. The possibility of combining chest low-dose CT and CT colonography examinations for double LC and CRC screening in a single CT appointment is then addressed. We demonstrate how this approach appears feasible and is already reasonable as an opportunistic screening intervention in 50–75-year-old subjects with smoking history and average CRC risk. In addition to the crucial role Computer Assisted Diagnosis systems play in decreasing the test reading times and the need to educate radiologists in screening chest LDCT and CT colonography, in view of a single CT appointment for double screening, the following uncertainties need to be solved: (1) the schedule of the screening CT; (2) the effectiveness of iterative reconstruction and deep learning algorithms affording an ultra-low-dose CT acquisition technique and (3) management of incidental findings. Resolving these issues will imply new cost-effectiveness analyses for LC screening with chest low dose CT and for CRC screening with CT colonography and, especially, for the double LC and CRC screening with a single-appointment CT.

Dose Reduction and Image Quality in Photon-counting Detector High-resolution Computed Tomography of the Chest: Routine Clinical Data

PURPOSE

Photon-counting detector computed tomography (PCD-CT) has the potential to significantly improve CT imaging in many ways including, but not limited to, low-dose high-resolution CT (HRCT) of the lung. The aim of this study was to perform an intrapatient comparison of the radiation dose and image quality of PCD-CT compared with conventional energy-integrating detector CT (EID-CT).

METHODS

A total of 32 consecutive patients with available PCD-CT and EID-CT HRCT scans were included in the final analysis. The CT dose index (CTDI vol ) was extracted from patient dose reports. Qualitative image analysis comprised the lung parenchyma and mediastinal structures and was assessed by 3 readers using a 5-point Likert scale. Quantitative image analysis included assessment of noise and signal-to-noise ratio in the lung parenchyma, trachea, aorta, muscle, and background.

RESULTS

The mean CTDI vol was 2.0 times higher in the conventional EID-CT scans (1.8±0.5 mGy) compared with PCD-CT (0.9±0.5 mGy, P <0.001). The overall image quality was rated significantly better by all 3 raters ( P <0.001) in the PCD-CT relative to the EID-CT. Quantitative analysis showed no significant differences in noise and signal-to-noise ratio in the lung parenchyma between PCD-CT and EID-CT.

CONCLUSION

Compared with conventional EID-CT scans, PCD-CT demonstrated similar or better objective and subjective image quality at significantly reduced dose levels in an intrapatient comparison. These results and their effect on clinical decision-making should be further investigated in prospective studies.

Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry

In recent years, pulmonary imaging has seen enormous progress, with the introduction, validation and implementation of new hardware and software. There is a general trend from mere visual evaluation of radiological images to quantification of abnormalities and biomarkers, and assessment of ‘non visual’ markers that contribute to establishing diagnosis or prognosis. Important catalysts to these developments in thoracic imaging include new indications (like computed tomography [CT] lung cancer screening) and the COVID‐19 pandemic. This review focuses on developments in CT, radiomics, artificial intelligence (AI) and x‐ray velocimetry for imaging of the lungs. Recent developments in CT include the potential for ultra‐low‐dose CT imaging for lung nodules, and the advent of a new generation of CT systems based on photon‐counting detector technology. Radiomics has demonstrated potential towards predictive and prognostic tasks particularly in lung cancer, previously not achievable by visual inspection by radiologists, exploiting high dimensional patterns (mostly texture related) on medical imaging data. Deep learning technology has revolutionized the field of AI and as a result, performance of AI algorithms is approaching human performance for an increasing number of specific tasks. X‐ray velocimetry integrates x‐ray (fluoroscopic) imaging with unique image processing to produce quantitative four dimensional measurement of lung tissue motion, and accurate calculations of lung ventilation.

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Evaluation of ultralow-dose computed tomography on detection of pulmonary nodules in overweight or obese adult patients

Purpose

To evaluate the accuracy of pulmonary nodule (PN) detection in overweight or obese adult patients using ultralow‐dose computed tomography (ULDCT) with tin filtration at 100 kV and advanced model‐based iterative reconstruction (ADMIRE).

Methods

Eighty‐one patients with body mass indices of ≥25 kg/m² were enrolled. All patients underwent low‐dose chest CT (LDCT), followed by ULDCT. Two radiologists experienced in LDCT established the standard of reference (SOR) for PNs. The number, type, size, and location of PNs were identified in the SOR. Effective dose, objective image quality (IQ), and subjective IQ based on two radiologists’ scores were compared between ULDCT and LDCT. The detection performances of radiologists based on ULDCT were calculated according to the nodule analyses. Logistic regression was used to test for independent predictors of PN detection sensitivity.

Results

Both the effective dose and objective IQ were lower for ULDCT than for LDCT (both p < 0.001). Both radiologists rated the subjective IQ of the overall IQ on ULDCT to be diagnostically sufficient. In total, 234 nodules (mean diameter, 3.4 ± 1.9 mm) were classified into 32 subsolid, 149 solid, and 53 calcified nodules according to the SOR. The overall sensitivity of ULDCT for nodule detection was 93.6%. Based on multivariate analyses, the nodule types (p = 0.015) and sizes (p = 0.013) were independent predictors of nodule detection.

Conclusions

Compared with LDCT, ULDCT with tin filtration at 100 kV and ADMIRE could significantly reduce the radiation dose in overweight or obese patients while maintaining good sensitivity for nodule detection.

Metal Artifact Reduction With Tin Prefiltration in Computed Tomography: A Cadaver Study for Comparison With Other Novel Techniques

OBJECTIVES

With the aging population and thus rising numbers of orthopedic implants (OIs), metal artifacts (MAs) increasingly pose a problem for computed tomography (CT) examinations. In the study presented here, different MA reduction techniques (iterative metal artifact reduction software [iMAR], tin prefilter technique, and dual-energy CT [DECT]) were compared.

MATERIALS AND METHODS

Four human cadaver pelvises with OIs were scanned on a third-generation DECT scanner using tin prefilter (Sn), dual-energy (DE), and conventional protocols. Virtual monoenergetic CT images were generated from DE data sets. Postprocessing of CT images was performed using iMAR. Qualitative (bony structures, MA, image noise) image analysis using a 6-point Likert scale and quantitative image analysis (contrast-to-noise ratio, standard deviation of background noise) were performed by 2 observers. Statistical testing was performed using Friedman test with Nemenyi test as a post hoc test.

RESULTS

The iMAR Sn 150 kV protocol provided the best overall assessability of bony structures and the lowest subjective image noise. The iMAR DE protocol and virtual monochromatic image (VMI) ± iMAR achieved the most effective metal artifact reduction (MAR) (P < 0.05 compared with conventional protocols). Bony structures were rated worse in VMI ± iMAR (P < 0.05) than in tin prefilter protocols ± iMAR. The DE protocol ± iMAR had the lowest contrast-to-noise ratio (P < 0.05 compared with iMAR standard) and the highest image noise (P < 0.05 compared with iMAR VMI). The iMAR reduced MA very efficiently.

CONCLUSIONS

When considering MAR and image quality, the iMAR Sn 150 kV protocol performed best overall in CT images with OI. The iMAR generated new artifacts that impaired image quality. The DECT/VMI reduced MA best, but experienced from a lack of resolution of bony fine structures.

First Performance Evaluation of an Artificial Intelligence-Based Computer-Aided Detection System for Pulmonary Nodule Evaluation in Dual-Source Photon-Counting Detector CT at Different Low-Dose Levels

OBJECTIVE

The aim of this study was to evaluate the image quality (IQ) and performance of an artificial intelligence (AI)-based computer-aided detection (CAD) system in photon-counting detector computed tomography (PCD-CT) for pulmonary nodule evaluation at different low-dose levels.

MATERIALS AND METHODS

An anthropomorphic chest-phantom containing 14 pulmonary nodules of different sizes (range, 3-12 mm) was imaged on a PCD-CT and on a conventional energy-integrating detector CT (EID-CT). Scans were performed with each of the 3 vendor-specific scanning modes (QuantumPlus [Q+], Quantum [Q], and High Resolution [HR]) at decreasing matched radiation dose levels (volume computed tomography dose index ranging from 1.79 to 0.31 mGy) by adapting IQ levels from 30 to 5. Image noise was measured manually in the chest wall at 8 different locations. Subjective IQ was evaluated by 2 readers in consensus. Nodule detection and volumetry were performed using a commercially available AI-CAD system.

RESULTS

Subjective IQ was superior in PCD-CT compared with EID-CT (P < 0.001), and objective image noise was similar in the Q+ and Q-mode (P > 0.05) and superior in the HR-mode (PCD 55.8 ± 11.7 HU vs EID 74.8 ± 5.4 HU; P = 0.01). High resolution showed the lowest image noise values among PCD modes (P = 0.01). Overall, the AI-CAD system delivered comparable results for lung nodule detection and volumetry between PCD- and dose-matched EID-CT (P = 0.08-1.00), with a mean sensitivity of 95% for PCD-CT and of 86% for dose-matched EID-CT in the lowest evaluated dose level (IQ5). Q+ and Q-mode showed higher false-positive rates than EID-CT at lower-dose levels (IQ10 and IQ5). The HR-mode showed a sensitivity of 100% with a false-positive rate of 1 even at the lowest evaluated dose level (IQ5; CDTIvol, 0.41 mGy).

CONCLUSIONS

Photon-counting detector CT was superior to dose-matched EID-CT in subjective IQ while showing comparable to lower objective image noise. Fully automatized AI-aided nodule detection and volumetry are feasible in PCD-CT, but attention has to be paid to false-positive findings.

Computed tomography arthrography of the shoulder with tin filter-based spectral shaping at 100 kV and 140 kV

BACKGROUND

Tin filter-based spectral shaping has been used for low-dose and ultra-low-dose computed tomography (CT) in several body parts. However, studies of shoulder CT arthrography with spectral shaping are limited.

PURPOSE

To investigate image quality and radiation dose of shoulder CT arthrography with tin filter-based spectral shaping at 100 kV (Sn 100 kV) and 140 kV (Sn 140 kV) in comparison with the conventional protocol.

MATERIAL AND METHODS

Ninety-nine shoulder CT arthrographies with protocols of Sn 100 kV (n = 32), Sn 140 kV (n = 25), and conventional 120 kV (n = 42) were retrospectively evaluated. Qualitative image quality, CT attenuations of intra-articular contrast mixture and tissues, background noise, contrast-to-noise ratios (CNRs), and figures of merit were assessed. Radiation doses were compared.

RESULTS

CT arthrographies with Sn 100 kV and Sn 140 kV yielded approximately 70% and 60% radiation dose reduction, respectively, compared with the conventional 120 kV (P < 0.001). Qualitative image noise and quantitative background noise of Sn 100 kV and Sn 140 kV were significantly less than those of the conventional protocol. Qualitative image contrast, CT attenuations of intra-articular contrast mixture and tissues, and CNRs for Sn 100 were similar to those of the conventional 120 kV. However, Sn 140 kV showed significantly lower qualitative contrast and CNRs than 120 kV. Sn 100 kV was the most dose efficient among the three protocols.

CONCLUSION

Shoulder CT arthrography with Sn 100 kV substantially reduced radiation dose and image noise and maintained image contrast, compared with the conventional protocol.

Potential for Radiation Dose Reduction in Dual-Source Computed Tomography of the Lung in the Pediatric and Adolescent Population Compared to Digital Radiography

Low-dose dual-source computed tomography (DSCT) protocols for the evaluation of lung diseases in children and adolescents are of importance since this age group is particularly prone to radiation damage. The aim of this study was to evaluate image quality of low-dose DSCT of the lung and to assess the potential of radiation dose reduction compared to digital radiographs (DR). Three groups, each consisting of 19 patients, were examined with different DSCT protocols using tin prefiltration (Sn96/64/32 ref. mAs at 100 kV). Different strengths of iterative reconstruction were applied (ADMIRE 2/3/4). DSCT groups were compared to 19 matched patients examined with posterior–anterior DR. Diagnostic confidence, detectability of anatomical structures and small lung lesions were evaluated on a 4-point Likert scale (LS 1 = unacceptable, 4 = fully acceptable; a value ≥ 3 was considered acceptable). Effective dose (ED) was 31-/21-/9-fold higher in Sn96/Sn64/Sn32 compared to DR. Diagnostic confidence was sufficient in Sn96/Sn64 (LS 3.4/3.2), reduced in Sn32 (LS 2.7) and the worst in DR (LS 2.4). In DSCT, detectability of small anatomical structures was always superior to DR (p < 0.05). Mean lesion size ranged from 5.1–7 mm; detectability was acceptable in all DSCT groups (LS 3.0–3.4) and superior to DR (LS 1.9; p < 0.05). Substantial dose lowering in DSCT of the pediatric lung enables acceptable detectability of small lung lesions with a radiation dose being about 10-fold higher compared to DR.

Third-generation iterative reconstruction on a dual-source, high-pitch, low-dose chest CT protocol with tin filter for spectral shaping at 100 kV: a study on a small series of COVID-19 patients

Objectives

To investigate the role of third-generation iterative reconstruction (ADMIRE) in dual-source, high-pitch chest CT protocol with spectral shaping at 100 kVp in Coronavirus disease 2019 (COVID-19).

Methods

Confirmed COVID-19 inpatients undergoing to unenhanced chest CT were scanned with a dual-energy acquisition (DECT, 90/150Sn kV) and a dual-source, high-pitch acquisition with tin-filtered 100 kVp (LDCT). On the DECT with ADMIRE 3 (DECT3) were evaluated the pulmonary findings and their extension (25-point score). Two radiologists in consensus evaluated with 5-point scales the overall image quality, the anatomical structures, and the elementary findings on LDCT reconstructed with filtered backprojection (LDCT0), with ADMIRE 3 (LDCT3) and 5 (LDCT5), and on DECT3. The signal-to-noise ratio (SNR), the body mass index, the exposure times, and the radiation doses were recorded.

Results

Seventy-five patients (57 M/18F; median age: 63 y.o.) were included, with median pulmonary extension of 13/25 points. The imaging findings were detected in proportion comparable to the available literature. The ADMIRE significantly improved the SNR in LDCT (p < 0.00001) with almost no significant differences in overweight patients. The LDCT had median effective dose of 0.39 mSv and acquisition time of 0.71 s with significantly less motion artifacts than DECT (p < 0.00001). The DECT3 and LDCT3 provided the best image quality and depiction of pulmonary anatomy and imaging findings, with significant differences among all the series (p < 0.00001).

Conclusion

The LDCT with spectral shaping and ADMIRE3 provided acceptable image quality in the evaluation of patients with COVID-19, with significantly reduced radiation dose and motion artifacts.

Evaluation of Image Quality for 7 Iterative Reconstruction Algorithms in Chest Computed Tomography Imaging: A Phantom Study

OBJECTIVES

This study aimed to evaluate the image quality of 7 iterative reconstruction (IR) algorithms in comparison to filtered back-projection (FBP) algorithm.

METHODS

An anthropomorphic chest phantom was scanned on 4 computed tomography scanners and reconstructed with FBP and IR algorithms. Image quality of anatomical details-large/medium-sized pulmonary vessels, small pulmonary vessels, thoracic wall, and small and large lesions-was scored. Furthermore, general impression of noise, image contrast, and artifacts were evaluated. Visual grading regression was used to analyze the data. Standard deviations were measured, and the noise power spectrum was calculated.

RESULTS

Iterative reconstruction algorithms showed significantly better results when compared with FBP for these criteria (regression coefficients/P values in parentheses): vessels (FIRST: -1.8/0.05, AIDR Enhanced: <-2.3/0.01, Veo: <-0.1/0.03, ADMIRE: <-2.1/0.04), lesions (FIRST: <-2.6/0.01, AIDR Enhanced: <-1.9/0.03, IMR1: <-2.7/0.01, Veo: <-2.4/0.02, ADMIRE: -2.3/0.02), image noise (FIRST: <-3.2/0.004, AIDR Enhanced: <-3.5/0.002, IMR1: <-6.1/0.001, iDose: <-2.3/0.02, Veo: <-3.4/0.002, ADMIRE: <-3.5/0.02), image contrast (FIRST: -2.3/0.01, AIDR Enhanced: -2.5/0.01, IMR1: -3.7/0.001, iDose: -2.1/0.02), and artifacts (FIRST: <-3.8/0.004, AIDR Enhanced: <-2.7/0.02, IMR1: <-2.6/0.02, iDose: -2.1/0.04, Veo: -2.6/0.02). The iDose algorithm was the only IR algorithm that maintained the noise frequencies.

CONCLUSIONS

Iterative reconstruction algorithms performed differently on all evaluated criteria, showing the importance of careful implementation of algorithms for diagnostic purposes.

Low-Dose CT Screening for Lung Cancer: Evidence from 2 Decades of Study

Lung cancer remains the overwhelmingly greatest cause of cancer death in the United States, accounting for more annual deaths than breast, prostate, and colon cancer combined. Accumulated evidence since the mid to late 1990s, however, indicates that low-dose CT screening of high-risk patients enables detection of lung cancer at an early stage and can reduce the risk of dying from lung cancer. CT screening is now a recommended clinical service in the United States, subject to guidelines and reimbursement requirements intended to standardize practice and optimize the balance of benefits and risks. In this review, the evidence on the effectiveness of CT screening will be summarized and the current guidelines and standards will be described in the context of knowledge gained from lung cancer screening studies. In addition, an overview of the potential advances that may improve CT screening will be presented, and the need to better understand the performance in clinical practice outside of the research trial setting will be discussed. © RSNA, 2020.

Optimization of acquisition parameters for reduced-dose thoracic CT: A phantom study

PURPOSE

The purpose of this study was to analyze the impact of different options for reduced-dose computed tomography (CT) on image noise and visibility of pulmonary structures in order to define the best choice of parameters when performing ultra-low dose acquisitions of the chest in clinical routine.

MATERIALS AND METHODS

Using an anthropomorphic chest phantom, CT images were acquired at four defined low dose levels (computed tomography dose index [CTDI_vol]=0.15, 0.20, 0.30 and 0.40mGy), by changing tube voltage, pitch factor, or rotation time and adapting tube current to reach the predefined CTDI_vol-values. Images were reconstructed using two different levels of iteration (adaptive statistical iterative reconstruction [ASIR®]-v70% and ASIR®-v100%). Signal-to-noise ratio (SNR) as well as contrast-to-noise ratio (CNR) was calculated. Visibility of pulmonary structures (bronchi/vessels) were assessed by two readers on a 5-point-Likert scale.

RESULTS

Best visual image assessments and CNR/SNR were obtained with high tube voltage, while lowest scores were reached with lower pitch factor followed by high tube current. Protocols favoring lower pitch factor resulted in decreased visibility of bronchi/vessels, especially in the periphery. Decreasing radiation dose from 0.40 to 0.30mGy was not associated with a significant decrease in visual scores (P<0.05), however decreasing radiation dose from 0.30mGy to 0.15mGy was associated with a lower visibility of most of the evaluated structures (P<0.001). While image noise could be significantly reduced when ASIR®-v100% instead of ASIR®-v70% was used, the visibility-scores of pulmonary structures did not change significantly.

CONCLUSION

Favoring high tube voltage is the best option for reduced-dose protocols. A decrease of SNR and CNR does not necessarily go along with reduced visibility of pulmonary structures.

Dual-source computed tomography of the lung with spectral shaping and advanced iterative reconstruction: potential for maximum radiation dose reduction

BACKGROUND

Radiation dose at CT should be as low as possible without compromising diagnostic quality.

OBJECTIVE

To assess the potential for maximum dose reduction of pediatric lung dual-source CT with spectral shaping and advanced iterative reconstruction (ADMIRE).

MATERIALS AND METHODS

We retrospectively analyzed dual-source CT acquisitions in a full-dose group (FD: 100 kV, 64 reference mAs) and in three groups with spectral shaping and differing reference mAs values (Sn: 100 kV, 96/64/32 reference mAs), each group consisting of 16 patients (age mean 11.5 years, standard deviation 4.8 years, median 12.8 years, range 1.3-18 years). Advanced iterative reconstruction of images was performed with different strengths (FD: ADMIRE Level 2; Sn: ADMIRE Levels 2, 3 and 4). We analyzed dose parameters and measured noise. Diagnostic confidence and detectability of lung lesions as well as anatomical structures were assessed using a Likert scale (from 1 [unacceptable] to 4 [fully acceptable]).

RESULTS

Compared to full dose, effective dose was reduced to 16.7% in the Sn 96 group, 11.1% in Sn64, and 5.5% in Sn32 (P<0.001). Noise values of Sn64_ADM4 did not statistically differ from those in FD_ADM2 (45.7 vs. 38.9 Hounsfield units [HU]; P=0.132), whereas noise was significantly higher in Sn32_ADM4 compared to Sn64_ADM4 (61.5 HU; P<0.001). A Likert score >3 was reached in Sn64_ADM4 regarding diagnostic confidence (3.2) and detectability of lung lesions (3.3). For detectability of most anatomical structures, no significant differences were found between FD_AM2 and Sn64_ADM4 (P≥0.05).

CONCLUSION

In pediatric lung dual-source CT, spectral shaping together with ADMIRE 4 enable radiation dose reduction to about 10% of a full-dose protocol while maintaining an acceptable diagnostic quality.

Volumetric assessment of solid pulmonary nodules on ultralow-dose CT: a phantom study

Background

To reduce the radiation exposure from chest computed tomography (CT), ultralow-dose CT (ULDCT) protocols performed at sub-millisievert levels were previously tested for the evaluation of pulmonary nodules (PNs). The purpose of our study was to investigate the effect of ULDCT and iterative image reconstruction on volumetric measurements of solid PNs.

Methods

CT datasets of an anthropomorphic chest phantom containing solid microspheres were obtained with a third-generation dual-source CT at standard dose, 1/8th, 1/20th and 1/70th of standard dose [CT volume dose index (CTDI_vol): 0.03-2.03 mGy]. Semi-automated volumetric measurements were performed on CT datasets reconstructed with filtered back projection (FBP) and advanced modelled iterative reconstruction (ADMIRE), at strength level 3 and 5. Absolute percentage error (APE) evaluated measurement accuracy related to the effective volume. Scan repetition differences were evaluated using Bland-Altman analysis. Two-way analysis of variance (ANOVA) assessed influence of different scan parameters on APE. Proportional differences (PDs) tested the effect of dose settings and reconstruction algorithms on volumetric measurements, as compared to the standard protocol (standard dose-FBP).

Results

Bland-Altman analysis revealed small mean interscan differences of APE with narrow limits of agreement (-0.1%±4.3% to -0.3%±3.8%). Dose settings (P<0.001), reconstruction algorithms (P<0.001), nodule diameters (P<0.001) and nodule density (P=0.011) had statistically significant influence on APE. Post-hoc Bonferroni tests showed slightly higher APE when scanning with 1/70th of standard dose [mean difference: 3.4%, 95% confidence interval (CI): 2.5-4.3%; P<0.001], and for image reconstruction with ADMIRE5 (mean difference: 1.8%, 95% CI: 1.0-2.5%; P<0.001). No significant differences for scanning with 1/20th of standard dose (P=0.42), and image reconstruction with ADMIRE3 (P=0.19) were found. Scanning with 1/70th of standard dose and image reconstruction with FBP showed the widest range of PDs (-16.8% to 23.4%) compared to standard dose-FBP.

Conclusions

Our phantom study showed no significant difference between nodule volume measurements on standard dose CT (CTDI_vol: 2 mGy) and ULDCT with 1/20th of standard dose (CTDI_vol: 0.10 mGy).

Comparison of ultra-low dose chest CT scanning protocols for the detection of pulmonary nodules: a phantom study

PURPOSE

To test ultra-low-dose computed tomography (ULDCT) scanning protocols for the detection of pulmonary nodules (PN).

METHODS

A chest phantom containing 19 solid and 11 subsolid PNs was scanned on a third-generation dual-source computed tomography (CT) scanner. Five ULDCT scans (Sn100kVp and 120, 70, 50, 30, and 20 reference mAs, using tube current modulation), reconstructed with iterative reconstruction (IR) algorithm at strength levels 2, 3, 4, and 5, were compared with standard CT (120kVp, 150 reference mAs, using tube current modulation). PNs were subjectively assessed according to a 4-point scale: 0, nondetectable nodule; 1, detectable nodule, very unlikely to be correctly measured; 2, detectable nodule, likely to be correctly measured; 3, PN quality equal to standard of reference. PN scores were analysed according to the Lung Imaging Reporting and Data System (Lung-RADS), simulating detection of nodules at baseline and incidence screening round.

RESULTS

For the baseline round, there were 17 Lung-RADS 2, 4 Lung-RADS 3, 8 Lung-RADS 4A, and 1 Lung-RADS 4B PNs. They were detectable in any ULDCT protocol, with the exception of 1 nondetectable part-solid nodule in 1 scanning protocol (120 reference mAs; IR strength: 3). For the incidence round, there were 4 Lung-RADS 2, 14 Lung-RADS 3, 2 Lung-RADS 4A, and 10 Lung-RADS 4B PNs. Ten were nondetectable in at least one ULDCT dataset; however, they were at least detectable in ULDCT with 70 reference mAs (IR strength: 4 and 5).

CONCLUSIONS

ULDCT scanning protocols allowing the detection of PNs can be proposed for the purpose of lung cancer screening.

Task-Based Model Observer Assessment of A Partial Model-Based Iterative Reconstruction Algorithm in Thoracic Oncologic Multidetector CT

To investigate the impact of a partial model-based iterative reconstruction (ASiR-V) on image quality in thoracic oncologic multidetector computed tomography (MDCT), using human and mathematical model observers. Twenty cancer patients examined with regular-dose thoracic-abdominal-pelvic MDCT were retrospectively included. Thoracic images reconstructed using a sharp kernel and filtered back-projection (reference) or ASiR-V (0-100%, 20% increments; follow-up) were analysed by three thoracic radiologists. Advanced quantitative physical metrics, including detectability indexes of simulated 4-mm-diameter solid non-calcified nodules and ground-glass opacities, were computed at regular and reduced doses using a custom-designed phantom. All three radiologists preferred higher ASiR-V levels (best = 80%). Increasing ASiR-V substantially decreased noise magnitude, with slight changes in noise texture. For high-contrast objects, changing the ASiR-V level had no major effect on spatial resolution; whereas for lower-contrast objects, increasing ASiR-V substantially decreased spatial resolution, more markedly at reduced dose. For both high- and lower-contrast pulmonary lesions, detectability remained excellent, regardless of ASiR-V and dose levels, and increased significantly with increasing ASiR-V levels (all p < 0.001). While high ASiR-V levels (80%) are recommended to detect solid non-calcified nodules and ground-glass opacities in regular-dose thoracic oncologic MDCT, care must be taken because, for lower-contrast pulmonary lesions, high ASiR-V levels slightly change noise texture and substantially decrease spatial resolution, more markedly at reduced dose.

Pulmonary Emphysema Quantification on Ultra-Low-Dose Computed Tomography Using Model-Based Iterative Reconstruction With or Without Lung Setting

OBJECTIVES

To evaluate the influence of model-based iterative reconstruction (MBIR) with lung setting and conventional setting on pulmonary emphysema quantification by ultra-low-dose computed tomography (ULDCT) compared with standard-dose CT (SDCT).

METHODS

Forty-five patients who underwent ULDCT (0.18 ± 0.02 mSv) and SDCT (6.66 ± 2.69 mSv) were analyzed in this retrospective study. Images were reconstructed using filtered back projection (FBP) with smooth and sharp kernels and MBIR with conventional and lung settings. Extent of emphysema was evaluated using fully automated software. Correlation between ULDCT and SDCT was assessed by interclass correlation coefficiency (ICC) and Bland-Altman analysis.

RESULTS

Excellent correlation was seen between MBIR with conventional setting on ULDCT and FBP with smooth kernel on SDCT (ICC, 0.97; bias, -0.31%) and between MBIR with lung setting on ULDCT and FBP with sharp kernel on SDCT (ICC, 0.82; bias, -2.10%).

CONCLUSION

Model-based iterative reconstruction improved the agreement between ULDCT and SDCT on emphysema quantification.

Detection of artificial pulmonary lung nodules in ultralow-dose CT using an ex vivo lung phantom

Objectives

To assess the image quality of 3 different ultralow-dose CT protocols on pulmonary nodule depiction in a ventilated ex vivo-system.

Materials and methods

Four porcine lungs were inflated inside a dedicated chest phantom and prepared with n = 195 artificial nodules (0.5–1 mL). The artificial chest wall was filled with water to simulate the absorption of a human chest. Images were acquired with a 2x192-row detector CT using low-dose (reference protocol with a tube voltage of 120 kV) and 3 different ULD protocols (respective effective doses: 1mSv and 0.1mSv). A different tube voltage was used for each ULD protocol: 70kV, 100kV with tin filter (100kV_Sn) and 150kV with tin filter (150kV_Sn). Nodule delineation was assessed by two observers (scores 1–5, 1 = unsure, 5 = high confidence).

Results

The diameter of the 195 detected artificial nodules ranged from 0.9–21.5 mm (mean 7.84 mm ± 5.31). The best ULD scores were achieved using 100kV_Sn and 70 kV ULD protocols (4.14 and 4.06 respectively). Both protocols were not significantly different (p = 0.244).

The mean score of 3.78 in ULD 150kV_Sn was significantly lower compared to the 100kV_Sn ULD protocol (p = 0.008).

Conclusion

The results of this experiment, conducted in a realistic setting show the feasibility of ultralow-dose CT for the detection of pulmonary nodules.

Diagnostic accuracy of chest X-ray dose-equivalent CT for assessing calcified atherosclerotic burden of the thoracic aorta

OBJECTIVE

To determine the value of ultralow-dose chest CT for estimating the calcified atherosclerotic burden of the thoracic aorta using tin-filter CT and compare its diagnostic accuracy with chest direct radiography.

METHODS

A total of 106 patients from a prospective, IRB-approved single-centre study were included and underwent standard dose chest CT (1.7 ± 0.7 mSv) by clinical indication followed by ultralow-dose CT with 100 kV and spectral shaping by a tin filter (0.13 ± 0.01 mSv) to achieve chest X-ray equivalent dose in the same session. Two independent radiologists reviewed the CT images, rated image quality and estimated presence and extent of calcification of aortic valve, ascending aorta and aortic arch. Conventional radiographs were also reviewed for presence of aortic calcifications.

RESULTS

The sensitivity of ultralow-dose CT for the detection of calcifications of the aortic valve, ascending aorta and aortic arch was 93.5, 96.2 and 96.2%, respectively, compared with standard dose CT. The sensitivity for the detection of thoracic aortic calcification was significantly lower on chest X-ray (52.3%) compared with ultralow-dose CT (p < 0.001).

CONCLUSION

A reliable estimation of calcified atherosclerotic burden of the thoracic aorta can be achieved with modern tin-filter CT at dose values comparable to chest direct radiography. Advances in knowledge: Our findings suggest that ultralow-dose CT is an excellent tool for assessing the calcified atherosclerotic burden of the thoracic aorta with higher diagnostic accuracy than conventional chest radiography and importantly without the additional cost of increased radiation dose.

Sub-solid Nodule Detection Performance on Reduced-dose Computed Tomography with Iterative Reduction: Comparison Between 20 mA (7 mAs) and 120 mA (42 mAs) Regarding Nodular Size and Characteristics and Association with Size-specific Dose Estimate

RATIONALE AND OBJECTIVES

This study aimed to compare sub-solid nodule detection performances (SSNDP) on chest computed tomography (CT) with Adaptive Iterative Dose Reduction using Three Dimensional Processing (AIDR 3D) between 7 mAs (0.21 mSv) and 42 mAs (1.28 mSv) in total and in subgroups classified by nodular size, characteristics, and location, and analyze the association of SSNDP with size-specific dose estimate (SSDE).

MATERIALS AND METHODS

As part of the Area-detector Computed Tomography for the Investigation of Thoracic Diseases Study, a Japanese multicenter research project, 68 subjects underwent chest CT with 120 kV, 0.35 seconds per rotation, and three tube currents: 240 mA (84 mAs), 120 mA (42 mAs), and 20 mA (7 mAs). The research committee of the study project outlined and approved our study protocols. The institutional review board of each institution approved this study. Axial 2-mm-thick CT images were reconstructed using AIDR 3D. Standard reference was determined by CT images at 84 mAs. Four radiologists recorded SSN presence by continuously distributed rating on CT at 7 mAs and 42 mAs. Receiver operating characteristic analysis was used to evaluate SSNDP at both doses in total and in subgroups classified by nodular longest diameter (LD) (≥5 mm), characteristics (pure and part-solid), and locations (ventral, intermediate, or dorsal; central or peripheral; and upper, middle, or lower). Detection sensitivity was compared among five groups of SSNs classified based on particular SSDE to nodule on CT with AIDR 3D at 7 mAs.

RESULTS

Twenty-two part-solid and 86 pure SSNs were identified. For larger SSNs (LD ≥ 5 mm) as well as subgroups classified by nodular locations and part-solid nodules, SSNDP was similar in both methods (area under the receiver operating characteristics curve: 0.96 ± 0.02 in CT at 7 mAs and 0.97 ± 0.01 in CT at 42 mAs), with acceptable interobserver agreements in five locations. For larger SSNs (LD ≥ 5 mm), on CT at 42 mAs, no significant differences in detection sensitivity were found among the five groups classified by SSDE, whereas on CT with 7 mAs, four groups with SSDE of 0.65 or higher were superior in detection sensitivity to the other group, with SSDE less than 0.65 mGy.

CONCLUSIONS

For SSNs with 5 mm or more in cases with normal range of body habitus, CT at 7 mAs was demonstrated to have comparable SSNDP to CT at 42 mAs regardless of nodular location and characteristics, and SSDE higher than 0.65 mGy is desirable to obtain sufficient SSNDP.

Effects of Iterative Reconstruction Algorithms on Computer-assisted Detection (CAD) Software for Lung Nodules in Ultra-low-dose CT for Lung Cancer Screening

RATIONALE AND OBJECTIVES

This study aimed to evaluate the effects of iterative reconstruction (IR) algorithms on computer-assisted detection (CAD) software for lung nodules in ultra-low-dose computed tomography (ULD-CT) for lung cancer screening.

MATERIALS AND METHODS

We selected 85 subjects who underwent both a low-dose CT (LD-CT) scan and an additional ULD-CT scan in our lung cancer screening program for high-risk populations. The LD-CT scans were reconstructed with filtered back projection (FBP; LD-FBP). The ULD-CT scans were reconstructed with FBP (ULD-FBP), adaptive iterative dose reduction 3D (AIDR 3D; ULD-AIDR 3D), and forward projected model-based IR solution (FIRST; ULD-FIRST). CAD software for lung nodules was applied to each image dataset, and the performance of the CAD software was compared among the different IR algorithms.

RESULTS

The mean volume CT dose indexes were 3.02 mGy (LD-CT) and 0.30 mGy (ULD-CT). For overall nodules, the sensitivities of CAD software at 3.0 false positives per case were 78.7% (LD-FBP), 9.3% (ULD-FBP), 69.4% (ULD-AIDR 3D), and 77.8% (ULD-FIRST). Statistical analysis showed that the sensitivities of ULD-AIDR 3D and ULD-FIRST were significantly higher than that of ULD-FBP (P < .001).

CONCLUSIONS

The performance of CAD software in ULD-CT was improved by using IR algorithms. In particular, the performance of CAD in ULD-FIRST was almost equivalent to that in LD-FBP.

Evaluation of pulmonary nodules and infection on chest CT with radiation dose equivalent to chest radiography: Prospective intra-individual comparison study to standard dose CT

PURPOSE

To compare prospectively, in patients undergoing chest computed tomography (CT) for pulmonary-nodules or infection, image-quality and accuracy of standard dose (SD) and reduced dose (RD) CT with tin-filtration.

MATERIAL AND METHODS

This IRB-approved study included 100 consecutive patients (36 female;median age 56 years) referred for follow-up of pulmonary-nodules (n=43) or suspicion of infection (n=57) undergoing single-energy CT with SD and RD using tin-filtration at 100 kVp (CTDIvol 2.47 mGy and 0.07 mGy, respectively). Images were reconstructed with advanced modeled iterative reconstruction (ADMIRE) at strength 3 and 5. Image-noise was measured. Two independent readers evaluated nodules and pulmonary-infection. SD CT served as reference standard.

RESULTS

No significant difference was found in noise between RD with ADMIRE5 and SD with ADMIRE3 (118HU ± 14 vs. 120HU ± 17; p=0.08). Sensitivity for detection of atelectasis and interstitial lung changes was higher in images reconstructed with ADMIRE5 (93% and 88%; respectively) than in those reconstructed with ADIMRE3 (77% and 78%; respectively). Sensitivity for detection of consolidations was 90% for ADMIRE3 and 89% for ADMIRE5. Sensitivity for nodule detection was 71% for ADMIRE3 and 81% for ADMIRE5. Specificity for detection of atelectasis and interstitial lung changes was 99% and 96% with ADMIRE5 and 99% and 96% with ADMIRE3. Specificity for detection of consolidations was 99% for ADMIRE3 and 5. Specificity for detection of nodules was 87% for both ADMIRE3 and 5.

CONCLUSION

Chest CT with a radiation dose equivalent to conventional radiography is feasible and allows for detection of pulmonary infection with high sensitivity, whereas the accuracy for detecting nodules is only moderate.