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

Influence of CT dose reduction on AI-driven malignancy estimation of incidental pulmonary nodules

OBJECTIVES

The purpose of this study was to determine the influence of dose reduction on a commercially available lung cancer prediction convolutional neuronal network (LCP-CNN).

METHODS

CT scans from a cohort provided by the local lung cancer center (n = 218) with confirmed pulmonary malignancies and their corresponding reduced dose simulations (25% and 5% dose) were subjected to the LCP-CNN. The resulting LCP scores (scale 1-10, increasing malignancy risk) and the proportion of correctly classified nodules were compared. The cohort was divided into a low-, medium-, and high-risk group based on the respective LCP scores; shifts between the groups were studied to evaluate the potential impact on nodule management. Two different malignancy risk score thresholds were analyzed: a higher threshold of ≥ 9 ("rule-in" approach) and a lower threshold of > 4 ("rule-out" approach).

RESULTS

In total, 169 patients with 196 nodules could be included (mean age ± SD, 64.5 ± 9.2 year; 49% females). Mean LCP scores for original, 25% and 5% dose levels were 8.5 ± 1.7, 8.4 ± 1.7 (p > 0.05 vs. original dose) and 8.2 ± 1.9 (p < 0.05 vs. original dose), respectively. The proportion of correctly classified nodules with the "rule-in" approach decreased with simulated dose reduction from 58.2 to 56.1% (p = 0.34) and to 52.0% for the respective dose levels (p = 0.01). For the "rule-out" approach the respective values were 95.9%, 96.4%, and 94.4% (p = 0.12). When reducing the original dose to 25%/5%, eight/twenty-two nodules shifted to a lower, five/seven nodules to a higher malignancy risk group.

CONCLUSION

CT dose reduction may affect the analyzed LCP-CNN regarding the classification of pulmonary malignancies and potentially alter pulmonary nodule management.

CLINICAL RELEVANCE STATEMENT

Utilization of a "rule-out" approach with a lower malignancy risk threshold prevents underestimation of the nodule malignancy risk for the analyzed software, especially in high-risk cohorts.

KEY POINTS

• LCP-CNN may be affected by CT image parameters such as noise resulting from low-dose CT acquisitions. • CT dose reduction can alter pulmonary nodule management recommendations by affecting the outcome of the LCP-CNN. • Utilization of a lower malignancy risk threshold prevents underestimation of pulmonary malignancies in high-risk cohorts.

Value of deep learning reconstruction of chest low-dose CT for image quality improvement and lung parenchyma assessment on lung window

OBJECTIVES

To explore the performance of low-dose computed tomography (LDCT) with deep learning reconstruction (DLR) for the improvement of image quality and assessment of lung parenchyma.

METHODS

Sixty patients underwent chest regular-dose CT (RDCT) followed by LDCT during the same examination. RDCT images were reconstructed with hybrid iterative reconstruction (HIR) and LDCT images were reconstructed with HIR and DLR, both using lung algorithm. Radiation exposure was recorded. Image noise, signal-to-noise ratio, and subjective image quality of normal and abnormal CT features were evaluated and compared using the Kruskal-Wallis test with Bonferroni correction.

RESULTS

The effective radiation dose of LDCT was significantly lower than that of RDCT (0.29 ± 0.03 vs 2.05 ± 0.65 mSv, p < 0.001). The mean image noise ± standard deviation was 33.9 ± 4.7, 39.6 ± 4.3, and 31.1 ± 3.2 HU in RDCT, LDCT HIR-Strong, and LDCT DLR-Strong, respectively (p < 0.001). The overall image quality of LDCT DLR-Strong was significantly better than that of LDCT HIR-Strong (p < 0.001) and comparable to that of RDCT (p > 0.05). LDCT DLR-Strong was comparable to RDCT in evaluating solid nodules, increased attenuation, linear opacity, and airway lesions (all p > 0.05). The visualization of subsolid nodules and decreased attenuation was better with DLR than with HIR in LDCT but inferior to RDCT (all p < 0.05).

CONCLUSION

LDCT DLR can effectively reduce image noise and improve image quality. LDCT DLR provides good performance for evaluating pulmonary lesions, except for subsolid nodules and decreased lung attenuation, compared to RDCT-HIR.

CLINICAL RELEVANCE STATEMENT

The study prospectively evaluated the contribution of DLR applied to chest low-dose CT for image quality improvement and lung parenchyma assessment. DLR can be used to reduce radiation dose and keep image quality for several indications.

KEY POINTS

• DLR enables LDCT maintaining image quality even with very low radiation doses. • Chest LDCT with DLR can be used to evaluate lung parenchymal lesions except for subsolid nodules and decreased lung attenuation. • Diagnosis of pulmonary emphysema or subsolid nodules may require higher radiation doses.

Ultra-low-dose CT vs. chest X-ray in non-traumatic emergency department patients - a prospective randomised crossover cohort trial

Background

Ultra-low-dose CT (ULDCT) examinations of the chest at only twice the radiation dose of a chest X-ray (CXR) now offer a valuable imaging alternative to CXR. This trial prospectively compares ULDCT and CXR for the detection rate of diagnoses and their clinical relevance in a low-prevalence cohort of non-traumatic emergency department patients.

Methods

In this prospective crossover cohort trial, 294 non-traumatic emergency department patients with a clinically indicated CXR were included between May 2nd and November 26th of 2019 (www.clinicaltrials.gov: NCT03922516). All participants received both CXR and ULDCT, and were randomized into two arms with inverse reporting order. The detection rate of CXR was calculated from 'arm CXR' (n = 147; CXR first), and of ULDCT from 'arm ULDCT' (n = 147; ULDCT first). Additional information reported by the second exam in each arm was documented. From all available clinical and imaging data, expert radiologists and emergency physicians built a compound reference standard, including radiologically undetectable diagnoses, and assigned each finding to one of five clinical relevance categories for the respective patient.

Findings

Detection rates for main diagnoses by CXR and ULDCT (mean effective dose: 0.22 mSv) were 9.1% (CI [5.2, 15.5]; 11/121) and 20.1% (CI [14.2, 27.7]; 27/134; P = 0.016), respectively. As an additional imaging modality, ULDCT added 9.1% (CI [5.2, 15.5]; 11/121) of main diagnoses to prior CXRs, whereas CXRs did not add a single main diagnosis (0/134; P < 0.001). Notably, ULDCT also offered higher detection rates than CXR for all other clinical relevance categories, including findings clinically irrelevant for the respective emergency department visit with 78.5% (CI [74.0, 82.5]; 278/354) vs. 16.2% (CI [12.7, 20.3]; 58/359) as a primary modality and 68.2% (CI [63.3, 72.8]; 245/359) vs. 2.5% (CI [1.3, 4.7]; 9/354) as an additional imaging modality.

Interpretation

In non-traumatic emergency department patients, ULDCT of the chest offered more than twice the detection rate for main diagnoses compared to CXR.

Funding

The Department of Biomedical Imaging and Image-guided Therapy of Medical University of Vienna received funding from Siemens Healthineers (Erlangen, Germany) to employ two research assistants for one year.

Computed Tomography 2.0: New Detector Technology, AI, and Other Developments

ABSTRACT

Computed tomography (CT) dramatically improved the capabilities of diagnostic and interventional radiology. Starting in the early 1970s, this imaging modality is still evolving, although tremendous improvements in scan speed, volume coverage, spatial and soft tissue resolution, as well as dose reduction have been achieved. Tube current modulation, automated exposure control, anatomy-based tube voltage (kV) selection, advanced x-ray beam filtration, and iterative image reconstruction techniques improved image quality and decreased radiation exposure. Cardiac imaging triggered the demand for high temporal resolution, volume acquisition, and high pitch modes with electrocardiogram synchronization. Plaque imaging in cardiac CT as well as lung and bone imaging demand for high spatial resolution. Today, we see a transition of photon-counting detectors from experimental and research prototype setups into commercially available systems integrated in patient care. Moreover, with respect to CT technology and CT image formation, artificial intelligence is increasingly used in patient positioning, protocol adjustment, and image reconstruction, but also in image preprocessing or postprocessing. The aim of this article is to give an overview of the technical specifications of up-to-date available whole-body and dedicated CT systems, as well as hardware and software innovations for CT systems in the near future.

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.

Ultra-low dose computed tomography of the chest in an emergency setting: A prospective agreement study

Ultra-low dose computed tomography (ULD-CT) assessed by non-radiologists in a medical Emergency Department (ED) has not been examined in previous studies. To (i) investigate intragroup agreement among attending physicians caring for ED patients (i.e., radiologists, senior- and junior clinicians) and medical students for the detection of acute lung conditions on ULD-CT and supine chest X-ray (sCXR), and (ii) evaluate the accuracy of interpretation compared to the reference standard. In this prospective study, non-traumatic patients presenting to the ED, who received an sCXR were included. Between February and July 2019, 91 patients who underwent 93 consecutive examinations were enrolled. Subsequently, a ULD-CT and non-contrast CT were performed. The ULD-CT and sCXR were assessed by 3 radiologists, 3 senior clinicians, 3 junior clinicians, and 3 medical students for pneumonia, pneumothorax, pleural effusion, and pulmonary edema. The non-contrast CT, assessed by a chest radiologist, was used as the reference standard. The results of the assessments were compared within each group (intragroup agreement) and with the reference standard (accuracy) using kappa statistics. Accuracy and intragroup agreement improved for pneumothorax on ULD-CT compared with the sCXR for all groups. Accuracy and intragroup agreement improved for pneumonia on ULD-CT when assessed by radiologists and for pleural effusion when assessed by medical students. In patients with acute lung conditions ULD-CT offers improvement in the detection of pneumonia by radiologists and the detection of pneumothorax by radiologists as well as non-radiologists compared to sCXR. Therefore, ULD-CT may be considered as an alternative first-line imaging modality to sCXR for non-traumatic patients who present to EDs.

Performance of virtual non-contrast images generated on clinical photon-counting detector CT for emphysema quantification: proof of concept

OBJECTIVE

To evaluate the performance of virtual non-contrast images (VNC) compared to true non-contrast (TNC) images in photon-counting detector computed tomography (PCD-CT) for the evaluation of lung parenchyma and emphysema quantification.

METHODS

65 (mean age 73 years; 48 male) consecutive patients who underwent a three-phase (non-contrast, arterial and venous) chest/abdomen CT on a first-generation dual-source PCD-CT were retrospectively included. Scans were performed in the multienergy (QuantumPlus) mode at 120 kV with 70 ml intravenous contrast agent at an injection rate of 4 ml s-1. VNC were reconstructed from the arterial (VNCart) and venous phase (VNCven). TNC and VNC images of the lung were assessed quantitatively by calculating the global noise index (GNI) and qualitatively by two independent, blinded readers (overall image quality and emphysema assessment). Emphysema quantification was performed using a commercially available software tool at a threshold of -950 HU for all data sets. TNC images served as reference standard for emphysema quantification. Low attenuation values (LAV) were compared in a Bland-Altman plot.

RESULTS

GNI was similar in VNCart (103.0 ± 30.1) and VNCven (98.2 ± 22.2) as compared to TNC (100.9 ± 19.0, p = 0.546 and p = 0.272, respectively). Subjective image quality (emphysema assessment and overall image quality) was highest for TNC (p = 0.001), followed by VNCven and VNCart. Both, VNCart and VNCven showed no significant difference in emphysema quantification as compared to TNC (p = 0.409 vs. p = 0.093; respectively).

CONCLUSION

Emphysema evaluation is feasible using virtual non-contrast images from PCD-CT.

ADVANCES IN KNOWLEDGE

Emphysema quantification is feasible and accurate using VNC images in PCD-CT. Based on these findings, additional TNC scans for emphysema quantification could be omitted in the future.

Pulmonary CT scans of white rabbits using the selective photon shield technique of the third-generation dual-source CT

This study aims to optimise the protocol for the low-dose pulmonary computed tomography (CT) scanning of infants by studying the effects of the selective photon shield (SPS) technique of the third-generation dual-source CT (DSCT) on the image quality and radiation dose of a chest CT in white rabbits under different tube currents. Twelve white rabbits of a similar weight to an infant were selected and randomly divided into an experimental group and a control group. The experimental groups (A1-A5) were scanned at low dose by the third-generation DSCT using SPS under different tube current × time (60, 50, 40, 30, and 20 mAs). The control group (B) was scanned under a conventional tube voltage (100 kV) and current × time (20 mAs). Advanced model iterative reconstruction at strength three was used for the objective and subjective evaluation of the image quality and radiation dose of the lung and mediastinal windows. With the standard deviation of the air in the trachea as image noise, the signal-to-noise ratio (SNR), contrast-to-noise ratio, and CT values of each site were evaluated. Radiation doses were compared using the volume CT dose index, dose length product, and effective dose. The differences in subjective image quality between groups A2 and B were not statistically significant (P= 0.34). The differences in the SNRs of the lung and mediastinal windows between groups A2 and B were not statistically significant (P> 0.05). The radiation dose of group A2 was 83.2% lower than that of group B. The SPS of the third-generation DSCT under 50 mAs might be applied in the pulmonary CT examination of infants.

Detection of pulmonary nodules with scoutless fixed-dose ultra-low-dose CT: a prospective study

OBJECTIVES

To determine the accuracy of scoutless, fixed-dose ultra-low-dose (ULD) CT compared to standard-dose (SD) CT for pulmonary nodule detection and semi-automated nodule measurement, across different patient sizes.

METHODS

Sixty-three patients underwent ULD and SD CT. Two readers examined all studies visually and with computer-aided detection (CAD). Nodules detected on SD CT were included in the reference standard by consensus and stratified into 4 categories (nodule category, NODCAT) from the Dutch-Belgian Lung Cancer Screening trial (NELSON). Effects of NODCAT and patient size on nodule detection were determined. For each nodule, volume and diameter were compared between both scans.

RESULTS

The reference standard comprised 173 nodules. For both readers, detection rates on ULD versus SD CT were not significantly different for NODCAT 3 and 4 nodules > 50 mm³ (reader 1: 93% versus 89% (p = 0.257); reader 2: 96% versus 98% (p = 0.317)). For NODCAT 1 and 2 nodules < 50 mm³, detection rates on ULD versus SD CT dropped significantly (reader 1: 66% versus 80% (p = 0.023); reader 2: 77% versus 87% (p = 0.039)). Body mass index and chest circumference did not influence nodule detectability (p = 0.229 and p = 0.362, respectively). Calculated volumes and diameters were smaller on ULD CT (p < 0.0001), without altering NODCAT (84% agreement).

CONCLUSIONS

Scoutless ULD CT reliably detects solid lung nodules with a clinically relevant volume (> 50 mm³) in lung cancer screening, irrespective of patient size. Since detection rates were lower compared to SD CT for nodules < 50 mm³, its use for lung metastasis detection should be considered on a case-by-case basis.

KEY POINTS

• Detection rates of pulmonary nodules > 50 mm³are not significantly different between scoutless ULD and SD CT (i.e. volumes clinically relevant in lung cancer screening based on the NELSON trial), but were different for the detection of nodules < 50 mm³(i.e. volumes still potentially relevant in lung metastasis screening). • Calculated nodule volumes were on average 0.03 mL or 9% smaller on ULD CT, which is below the 20-25% interscan variability previously reported with software-based volumetry. • Even though a scoutless, fixed-dose ULD CT protocol was used (CTDI_vol0.15 mGy), pulmonary nodule detection was not influenced by patient size.

Personalized Chest Computed Tomography: Minimum Diagnostic Radiation Dose Levels for the Detection of Fibrosis, Nodules, and Pneumonia

OBJECTIVES

The purpose of this study was to evaluate the minimum diagnostic radiation dose level for the detection of high-resolution (HR) lung structures, pulmonary nodules (PNs), and infectious diseases (IDs).

MATERIALS AND METHODS

A preclinical chest computed tomography (CT) trial was performed with a human cadaver without known lung disease with incremental radiation dose using tin filter-based spectral shaping protocols. A subset of protocols for full diagnostic evaluation of HR, PN, and ID structures was translated to clinical routine. Also, a minimum diagnostic radiation dose protocol was defined (MIN). These protocols were prospectively applied over 5 months in the clinical routine under consideration of the individual clinical indication. We compared radiation dose parameters, objective and subjective image quality (IQ).

RESULTS

The HR protocol was performed in 38 patients (43%), PN in 21 patients (24%), ID in 20 patients (23%), and MIN in 9 patients (10%). Radiation dose differed significantly among HR, PN, and ID (5.4, 1.2, and 0.6 mGy, respectively; P < 0.001). Differences between ID and MIN (0.2 mGy) were not significant (P = 0.262). Dose-normalized contrast-to-noise ratio was comparable among all groups (P = 0.087). Overall IQ was perfect for the HR protocol (median, 5.0) and decreased for PN (4.5), ID-CT (4.3), and MIN-CT (2.5). The delineation of disease-specific findings was high in all dedicated protocols (HR, 5.0; PN, 5.0; ID, 4.5). The MIN protocol had borderline IQ for PN and ID lesions but was insufficient for HR structures. The dose reductions were 78% (PN), 89% (ID), and 97% (MIN) compared with the HR protocols.

CONCLUSIONS

Personalized chest CT tailored to the clinical indications leads to substantial dose reduction without reducing interpretability. More than 50% of patients can benefit from such individual adaptation in a clinical routine setting. Personalized radiation dose adjustments with validated diagnostic IQ are especially preferable for evaluating ID and PN lesions.

Diagnostic accuracy of ultra-low-dose chest computed tomography in an emergency department

BACKGROUND

This study examined whether ultra-low-dose chest computed tomography (ULD-CT) could improve detection of acute chest conditions.

PURPOSE

To determine (i) whether diagnostic accuracy of ULD-CT is superior to supine chest X-ray (sCXR) for acute chest conditions and (ii) the feasibility of ULD-CT in an emergency department.

MATERIAL AND METHODS

From 1 February to 31 July 2019, 91 non-traumatic patients from the Emergency Department were prospectively enrolled in the study if they received an sCXR. An ULD-CT and a non-contrast chest CT (NCCT) scan were then performed. Three radiologists assessed the sCXR and ULD-CT examinations for cardiogenic pulmonary edema, pneumonia, pneumothorax, and pleural effusion. Resources and effort were compared for sCXR and ULD-CT to evaluate feasibility. Diagnostic accuracy was calculated for sCXR and ULD-CT using NCCT as the reference standard.

RESULTS

The mean effective dose of ULD-CT was 0.05±0.01 mSv. For pleural effusion and cardiogenic pulmonary edema, no difference in diagnostic accuracy between ULD-CT and sCXR was observed. For pneumonia and pneumothorax, sensitivities were 100% (95% confidence interval [CI] 69-100) and 50% (95% CI 7-93) for ULD-CT and 60% (95% CI 26-88) and 0% (95% CI 0-0) for sCXR, respectively. Median examination time was 10 min for ULD-CT vs. 5 min for sCXR (P<0.001). For ULD-CT 1-2 more staff members were needed compared to sCXR (P<0.001). ULD-CT was rated more challenging to perform than sCXR (P<0.001).

CONCLUSION

ULD-CT seems equal or better in detecting acute chest conditions compared to sCXR. However, ULD-CT examinations demand more effort and resources.

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.

[Pulmonary nodules and pneumonia : A diagnostic guideline]

Hintergrund

Das konventionelle Röntgenbild zählt zu den am häufigsten durchgeführten radiologischen Untersuchungen. Seine Interpretation gehört zu den Grundkenntnissen jedes Radiologen.

Fragestellung

Ziel dieses Artikels ist es, häufige Zeichen und Muster der Pneumonie sowie Merkmale von Pseudoläsionen im konventionellen Röntgenbild zu erkennen und einen diagnostischen Leitfaden für junge Radiologen zu schaffen.

Methoden

Analyse aktueller Studien und Daten sowie eine Übersicht der häufigsten Zeichen und Muster im konventionellen Röntgenbild.

Ergebnisse

Die Kenntnis über häufige Zeichen und Muster im Röntgenbild bietet eine Hilfestellung in der Diagnostik und kann hinweisend für die Ursache einer Infektion sein. Häufig sind diese Zeichen jedoch unspezifisch und sollten daher immer in klinische Korrelation gesetzt werden. In der Detektion und Beurteilung von pulmonalen Rundherden gewinnt die Computertomographie (CT) durch ihre deutlich höhere Sensitivität in der Primärdiagnostik immer mehr an Bedeutung.

Schlussfolgerung

Das konventionelle Röntgenbild bildet weiterhin eine führende Rolle in der Primärdiagnostik; der Radiologe sollte jedoch die Limitationen des konventionellen Bildes kennen.

Impact of dose reduction and iterative reconstruction algorithm on the detectability of pulmonary nodules by artificial intelligence

PURPOSE

The purpose of this study was to assess whether the performances of an automated software for lung nodule detection with computed tomography (CT) are affected by radiation dose and the use of iterative reconstruction algorithm.

MATERIALS AND METHODS

A chest phantom (Multipurpose Chest Phantom N1; Kyoto Kagaku Co. Ltd, Kyoto, Japan) with 15 pulmonary nodules was scanned with a total of five CT protocol settings with up to 20-fold dose reduction. All CT examinations were reconstructed with iterative reconstruction algorithms ADMIRE 3 and ADMIRE 5 and were then analyzed for the presence of pulmonary nodules with a fully automated computer aided detection software system (InferRead^TM CT Lung, Infervision), which is based on deep neural networks.

RESULTS

The sensitivity of fully automated pulmonary nodule detection for ground-glass nodules at standard dose CT was greater (70.0%; 14/20; 95% CI: 51.6-88.4%) than at 10-fold and 20-fold dose reduction (30.0%; 6/20; 95% CI: 0.0%-62.5%). There were less false positive findings when ADMIRE 5 reconstruction was used (4.0 ± 2.8 [SD]; range: 2-6) instead of ADMIRE 3 reconstruction (25.0 ± 15.6 [SD]; range: 14-36). There was no difference in the sensitivity of detection of solid and subsolid nodules between standard dose (100%; 95% CI: 100-100%) and 10- and 20-fold reduced dose CT (92.5%; 95% CI: 83.8-100.0%). Image noise was significantly greater with ADMIRE 3 (81 ± 2 [SD] [range: 79-84]; 104 ± 3 [SD] [range: 101-107]; 114 ± 5 [SD] [range: 110-119]; 193 ± 10 [SD] [range: 183-203]; 220 ± 16 [SD] [range: 210-238]) compared to ADMIRE 5 (44 ± 2 [SD] [range: 42-46]; 60 ± 2 [SD] [range: 57-61]; 66 ± 1 [SD] [range: 65-67]; 103 ± 4 [SD] [range: 98-106]; 110 ± 1 [SD] [range: 109-111]), respectively in each of the five CT protocols.

CONCLUSION

This phantom study suggests that dose reduction and iterative reconstruction settings have an impact on detectability of pulmonary nodules by artificial intelligence software and we therefore encourage adaption of dose levels and reconstruction methods prior to widespread implementation of fully automatic nodule detection software for lung cancer screening purposes.

Pneumonia Detection in Chest X-Ray Dose-Equivalent CT: Impact of Dose Reduction on Detectability by Artificial Intelligence

RATIONALE AND OBJECTIVES

There has been a significant increase of immunocompromised patients in recent years due to new treatment modalities for previously fatal diseases. This comes at the cost of an elevated risk for infectious diseases, most notably pathogens affecting the respiratory tract. Because early diagnosis and treatment of pneumonia can help reducing morbidity and mortality, we assessed the performance of a deep neural network in the detection of pulmonary infection in chest X-ray dose-equivalent computed tomography (CT).

MATERIALS AND METHODS

The 100 patients included in this retrospective study were referred to our department for suspicion of pulmonary infection and/or follow-up of known pulmonary nodules. Every patient was scanned with a standard dose (1.43 ± 0.54 mSv) and a 20 times dose-reduced (0.07 ± 0.03 mSv) CT protocol. We trained a deep neural network to perform binary classification (pulmonary consolidation present or not) and assessed diagnostic performance on both standard dose and reduced dose CT images.

RESULTS

The areas under the curve of the deep learning algorithm for the standard dose CT was 0.923 (confidence interval [CI] 95%: 0.905-0.941) and significantly higher than the areas under the curve (0.881, CI 95%: 0.859-0.903) of the reduced dose CT (p = 0.001). Sensitivity and specificity of the standard dose CT was 82.9% and 93.8%, and of the reduced dose CT 71.0% and 93.3%.

CONCLUSION

Pneumonia detection with X-ray dose-equivalent CT using artificial intelligence is feasible and may contribute to a more robust and reproducible diagnostic performance. Dose reduction lowered the performance of the deep neural network, which calls for optimization and adaption of CT protocols when using AI algorithms at reduced doses.

Impact of Vessel Suppressed-CT on Diagnostic Accuracy in Detection of Pulmonary Metastasis and Reading Time

RATIONALE AND OBJECTIVES

To assess if vessel suppression (VS) improves nodule detection rate, interreader agreement, and reduces reading time in oncologic chest computed tomography (CT).

MATERIAL AND METHODS

One-hundred consecutive oncologic patients (65 male; median age 60y) who underwent contrast-enhanced chest CT were retrospectively included. For all exams, additional VS series (ClearRead CT, Riverrain Technologies, Miamisburg) were reconstructed. Two groups of three radiologists each with matched experience were defined. Each group evaluated the SD-CT as well as VS-CT. Each reader marked the presence, size, and position of pulmonary nodules and documented reading time. In addition, for the VS-CT the presence of false positive nodules had to be stated. Cohen's Kappa (k) was used to calculate the interreader-agreement between groups. Reading time was compared using paired t test.

RESULTS

Nodule detection rate was significantly higher in VS-CT compared to the SD-CT (+21%; p <0.001). Interreader-agreement was higher in the VS-CT (k = 0.431, moderate agreement) compared to SD-CT (k = 0.209, fair agreement). Almost all VS-CT series had false positive findings (97-99 out of 100). Average reading time was significantly shorter in the VS-CT compared to the SD-CT (154 ± 134vs. 194 ± 126; 21%, p<0.001).

CONCLUSIONS

Vessel suppression increases nodule detection rate, improves interreader agreement, and reduces reading time in chest CT of oncologic patients. Due to false positive results a consensus reading with the SD-CT is essential.

Comparison of conventional chest x ray with a novel projection technique for ultra-low dose CT

PURPOSE

To compare a novel thick-slab projection technique for ultra-low dose computed tomography (CT; thoracic tomogram) with conventional chest x ray with respect to 13 diagnostic categories.

METHODS

With the approval of the institutional ethics board, a dataset was retrospectively collected of 22 consecutive patients who had undergone a clinically requested emergency room conventional chest x ray (CXR) and a same-day standard-of-care non-contrast CT. Scanner specific noise was added to the CT images to simulate a target dose of 0.18 mSv. A novel algorithm was used to post-process CT images as coronal isotropic reformats by applying a voxel-based, locally normalized weighted-intensity projection to generate 2 cm thick slabs with 1 cm overlap. Three chest radiologists with no prior training for the study reviewed the CXR and thoracic tomogram for each case and assessed each diagnostic category (pneumonic infiltrates, pulmonary edema, interstitial lung disease, nodules > 5 mm, nodules < 5 mm, pleural effusion, pericardial effusion, heart size, acute bone fractures, foreign bodies, pneumothorax, mediastinal vessel diameter, free abdominal air) on a Likert scale from -4 (definitely absent/normal) to +4 (definitely present/abnormal). MRMC ROC curves were generated for each category. Time for interpretation and subjective image quality score (0-10) were also assessed.

RESULTS

For focal lung disease (pneumonic infiltrates, nodules < 5 mm, nodules > 5mm), the area under the ROC curve (AUC) was significantly higher for thoracic tomograms than CXR (0.803 vs 0.648, respectively, P = 0.02). For non-focal lung disease (pulmonary edema, interstitial lung disease) and effusions (pulmonary, pericardial), the AUC was larger for thoracic tomograms than CXR but the difference did not reach significance (0.870 vs 0.833, P = 0.141; and 0.823 vs 0.752, P = 0.296, respectively). For acute bone fractures and foreign bodies, the AUC was smaller for thoracic tomograms than CXR, the difference was however not significant (0.491 vs 0.532, P = 0.42; and 0.871 vs 0.971, P = 0.39, respectively). Other diagnostic categories had no true positive cases in the dataset. The mean time for interpretation for each was 36.9 and 24.0 s with standard deviations of 0.857 and 5.977. The image quality score for each was 8.2 and 7.8 with standard deviations of 0.970 and 1.614.

CONCLUSION

Thoracic tomograms were found to be diagnostically superior to CXR for focal lung disease, at no increased radiation dose. The thoracic tomogram presents an opportunity to improve the standard-of-care for patients who would otherwise receive a conventional CXR.

Diagnostic accuracy of low-dose and ultra-low-dose CT in detection of chest pathology: a systematic review

PURPOSE

Studies have evaluated imaging modalities with a lower radiation dose than standard-dose CT (SD-CT) for chest examination. This systematic review aimed to summarize evidence on diagnostic accuracy of these modalities - low-dose and ultra-low-dose CT (LD- and ULD-CT) - for chest pathology.

METHOD

Ovid-MEDLINE, Ovid-EMBASE and the Cochrane Library were systematically searched April 29th-30th, 2019 and screened by two reviewers. Studies on diagnostic accuracy were included if they defined their index tests as 'LD-CT', 'Reduced-dose CT' or 'ULD-CT' and had SD-CT as reference standard. Risk of bias was evaluated on study level using the Quality Assessment of Diagnostic Accuracy Studies-2. A narrative synthesis was conducted to compare the diagnostic accuracy measurements.

RESULTS

Of the 4257 studies identified, 18 were eligible for inclusion. SD-CT (3.17 ± 1.47 mSv) was used as reference standard in all studies to evaluate diagnostic accuracy of LD- (1.22 ± 0.34 mSv) and ULD-CT (0.22 ± 0.05 mSv), respectively. LD-CT had high sensitivities for detection of bronchiectasis (82-96%), honeycomb (75-100%), and varying sensitivities for nodules (63-99%) and ground glass opacities (GGO) (77-91%). ULD-CT had high sensitivities for GGO (93-100%), pneumothorax (100%), consolidations (90-100%), and varying sensitivities for nodules (60-100%) and emphysema (65-90%).

CONCLUSION

The included studies found LD-CT to have high diagnostic accuracy in detection of honeycombing and bronchiectasis and ULD-CT to have high diagnostic accuracy for pneumothorax, consolidations and GGO. Summarizing evidence on diagnostic accuracy of LD- and ULD-CT for other chest pathology was not possible due to varying outcome measures, lack of precision estimates and heterogeneous study design and methodology.

Advances in imaging for lung emphysema

Lung emphysema represents a major public health burden and still accounts for five percent of all deaths worldwide. Hence, it is essential to further understand this disease in order to develop effective diagnostic and therapeutic strategies. Lung emphysema is an irreversible enlargement of the airways distal to the terminal bronchi (i.e., the alveoli) due to the destruction of the alveolar walls. The two most important causes of emphysema are (I) smoking and (II) α1-antitrypsin-deficiency. In the former lung emphysema is predominant in the upper lung parts, the latter is characterized by a predominance in the basal areas of the lungs. Since quantification and evaluation of the distribution of lung emphysema is crucial in treatment planning, imaging plays a central role. Imaging modalities in lung emphysema are manifold: computed tomography (CT) imaging is nowadays the gold standard. However, emerging imaging techniques like dynamic or functional magnetic resonance imaging (MRI), scintigraphy and lately also the implementation of radiomics and artificial intelligence are more and more diffused in the evaluation, diagnosis and quantification of lung emphysema. The aim of this review is to shortly present the different subtypes of lung emphysema, to give an overview on prediction and risk assessment in emphysematous disease and to discuss not only the traditional, but also the new imaging techniques for diagnosis, quantification and evaluation of lung emphysema.

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.

Feasibility of bronchial wall quantification in low- and ultralow-dose third-generation dual-source CT: An ex vivo lung study

PURPOSE

To investigate image quality and bronchial wall quantification in low- and ultralow-dose third-generation dual-source computed tomography (CT).

METHODS

A lung specimen from a formerly healthy male was scanned using third-generation dual-source CT at standard-dose (51 mAs/120 kV, CTDI_vol 3.41 mGy), low-dose (1/4th and 1/10th of standard dose), and ultralow-dose setting (1/20th). Low kV (70, 80, 90, and Sn100 kV) scanning was applied in each low/ultralow-dose setting, combined with adaptive mAs to keep a constant dose. Images were reconstructed at advanced modeled iterative reconstruction (ADMIRE) levels 1, 3, and 5 for each scan. Bronchial wall were semi-automatically measured from the lobar level to subsegmental level. Spearman correlation analysis was performed between bronchial wall quantification (wall thickness and wall area percentage) and protocol settings (dose, kV, and ADMIRE). ANOVA with a post hoc pairwise test was used to compare signal-to-noise ratio (SNR), noise and bronchial wall quantification values among standard- and low/ultralow-dose settings, and among ADMIRE levels.

RESULTS

Bronchial wall quantification had no correlation with dose level, kV, or ADMIRE level (|correlation coefficients| < 0.3). SNR and noise showed no statistically significant differences at different kV in the same ADMIRE level (1, 3, or 5) and in the same dose group (P > 0.05). Generally, there were no significant differences in bronchial wall quantification among the standard- and low/ultralow-dose settings, and among different ADMIRE levels (P > 0.05).

CONCLUSION

The combined use of low/ultralow-dose scanning and ADMIRE does not influence bronchial wall quantification compared to standard-dose CT. This specimen study suggests the potential that an ultralow-dose scan can be used for bronchial wall quantification.

Vertical Off-Centering in Reduced Dose Chest-CT: Impact on Effective Dose and Image Noise Values

OBJECTIVES

To assess the effect of vertical off-centering in tube current modulation (TCM) on effective-dose and image-noise in reduced-dose (RD) chest-CT.

METHODS

One-hundred consecutive patients (36 female; mean age 56 years) were scanned on a 192-slice CT scanner with a standard-dose (ND) and a RD chest-CT protocol using tube current modulation. Image-noise was evaluated by placing circular regions of interest in the apical, middle, and lower lung regions. Two independent readers evaluated image quality. Study population was stratified according to patient position in the gantry: positioned in the gantry isocenter (i), higher than the gantry isocenter (ii), and lower than the gantry isocenter, (iii). Pearson correlation was used to determine the correlation between effective radiation dose and vertical off-centering. Student's t test was used to evaluate for differences in image-noise between groups (i-iii).

RESULTS

Mean vertical off-centering was of 10.6 mm below the gantry-isocenter (range -45.0-27.9 mm). Effective radiation dose varied in a linear trend, with the highest doses noted below gantry isocenter, and the lowest doses noted above gantry isocenter (ND: r = -0.296; p = 0.003 - RD: r = -0.258; p = 0.010). Lowest image-noise was observed where patients were positioned below the gantry isocenter, and highest in patients positioned above (ND: 79.35 HU vs. 94.86 HU - RD: 143.44 HU vs. 160.13 HU). Subjective image quality was not significantly affected by patient-position (p > 0.05). Overall, there was no over-proportional noise-increase from the ND to the RD protocol in patients which were positioned off-center.

CONCLUSION

Vertical off-centering influences effective radiation dose and image-noise on ND and RD protocols.

ADVANCES IN KNOWLEDGE

There is no over-proportional noise increase in RD compared to ND protocols when patients are positioned off-center.

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.

Added Value of Ultra-low-dose Computed Tomography, Dose Equivalent to Chest X-Ray Radiography, for Diagnosing Chest Pathology

Purpose:

The purpose of this study was to assess the clinical value of ultra–low-dose computed tomography (ULDCT) compared with chest x-ray radiography (CXR) for diagnosing chest pathology.

Materials and Methods:

A total of 200 patients referred for CXR by outpatient clinics or general practitioners were enrolled prospectively. They underwent CXR (posteroanterior and lateral) and ULDCT (120 kV, 3 mAs) on the same day. In-room time and effective dose were recorded for each examination. Studies were categorized whether they were diagnostic or not, relevant radiologic diagnostic findings were reported, and confidence for diagnosis was recorded by a Likert scale. Differences in diagnostic confidence and effect on management decision were compared.

Results:

In-room time was <2 minutes for CXR and <3 minutes for ULDCT. Effective dose was 0.040 mSv for CXR and 0.071 mSv for ULDCT. CXR was considered diagnostic in 98% and ULDCT in 100%. The mean perceived confidence for diagnosis was 88±12% with CXR and 98±2% with ULDCT (P<0.0001), whereas discrepant findings between CXR and ULDCT were found in 101 of 200 patients. As compared with CXR, ULDCT had added value for management decisions in 40 of 200 patients.

Conclusions:

ULDCT provided added value to the radiologist by improved perceived confidence with a reduction in false-positive and false-negative CXR investigations that had management implications in 20% of patients. The effective dose of ULDCT will not be a limiting factor for introducing ULDCT of the chest on a broad scale in clinical practice.

CT angiography for pulmonary embolism in the emergency department: investigation of a protocol by 20 ml of high-concentration contrast medium

OBJECTIVES

To retrospectively compare semi-qualitative and quantitative CT pulmonary angiography (CTPAs) image metrics testing diagnostic performance between protocols performed by 20 or 40 ml of contrast medium (CM) in patients with suspected pulmonary embolism (PE).

METHODS

A total of 102 CTPAs performed by 20 ml (ultra-low volume: ULV) and 74 CTPAs performed by 40 ml (low volume: LV) protocol for the diagnosis of clinically suspected PE performed between October 2012 and September 2013 were retrieved. High-concentration CM (Iomeprol 400 mgI/ml) was injected at 3 ml/s (iodine delivery rate 1.2 mgI/s). Two radiologists (blinded and independent) semi-qualitatively scored vascular enhancement and image noise according to a five-point visual scoring system. Quantitative analysis was performed by regions of interest quantifying densitometric parameters, such as central and peripheral pulmonary arteries vascular contrast enhancement (CE, threshold for diagnostic CE ≥ 250 HU), and metrics for image noise. Continuous variables were compared by the Student's t test between groups if normally distributed while categorical variables were analyzed with the Chi-squared test. Interobserver agreement was calculated by the weighted kappa test; correlation coefficients were calculated using Pearson's correlation tests.

RESULTS

The semi-qualitative scores for central and peripheral pulmonary arteries vascular CE were sufficient by ULV, yet inferior than LV (p < 0.001). Semi-qualitative image noise was comparable between ULV and LV, and the interobserver agreement was only fair for quality of peripheral vessels. Agreement on nondiagnostic semi-qualitative parameters was seen in 9/102 (8.8%) ULV CTPAs, in particular associated with massive PE (2/9), pleuro-pulmonary abnormalities (5/9) or without major abnormalities (2/9). Quantitative analysis showed that mean CE was lower in ULV group (p < 0.001), though greater than the diagnostic threshold of 250 HU in both groups.

CONCLUSIONS

Diagnostic vascular CE (> 250 HU) was obtained in both 20 ml and 40 ml CTPAs. CTPA by 20 ml of CM rendered diagnostic CE for the assessment of pulmonary arteries in patients with clinical suspicion of acute PE. Decreased image quality was mostly associated with massive PE or concomitant pleuro-parenchymal abnormalities.

Consistency of radiologists in identifying pulmonary nodules based on low-dose computed tomography

Background

To study the consistency of radiologists in identifying pulmonary nodules based on low-dose computed tomography (LDCT), and to analyze factors that affect the consistency.

Methods

A total of 750 LDCT cases were collected randomly from three medical centers. Three experienced chest radiologists independently evaluated and detected the pulmonary nodules on 625 cases of LDCT images. The detected nodules were classified into 3 groups: group I (detected by all radiologists); group II (detected by two radiologists); group III (detected by only one radiologist). The consistency with respect to the image features of individual nodules was assessed.

Results

A total of 1,206 nodules were identified by the three radiologists. There were 234 (19.4%) nodules in group I, 377 (31.3%) nodules in group II, and 595 (49.3%) nodules in group III. Logistic regression showed that the size, density, and location of the nodules correlated with the detection of nodules. Nodules sized great than or equal to 4 mm were more consistently identified than nodules sized less than 4 mm. Solid and calcified nodules were more consistently identified than sub-solid nodules. Nodules located in the outer zone were more consistently identified than hilar nodules.

Conclusions

There was considerable inter-reader variability with respect to identification of pulmonary nodules in LDCT. Larger nodules, solid or calcified nodules, and nodules located in the outer zone were more consistently identified.

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.

Comparing the diagnostic performance of radiation dose-equivalent radiography, multi-detector computed tomography and cone beam computed tomography for finger fractures - A phantom study

PURPOSE

To compare the diagnostic performance and raters´confidence of radiography, radiography equivalent dose multi-detector computed tomography (RED-MDCT) and radiography equivalent dose cone beam computed tomography (RED-CBCT) for finger fractures.

METHODS

Fractures were inflicted artificially and randomly to 10 cadaveric hands of body donors. Radiography as well as RED-MDCT and RED-CBCT imaging were performed at dose settings equivalent to radiography. Images were de-identified and analyzed by three radiologists regarding finger fractures, joint involvement and confidence with their findings. Reference standard was consensus reading by two radiologists of the fracturing protocol and high-dose multi-detector computed tomography (MDCT) images. Sensitivity and specificity were calculated and compared with Cochrane´s Q and post hoc analysis. Rater´s confidence was calculated with Friedman Test and post hoc Nemenyi Test.

RESULTS

Rater´s confidence, inter-rater correlation, specificity for fractures and joint involvement were higher in RED-MDCT and RED-CBCT compared to radiography. No differences between the modalities were found regarding sensitivity.

CONCLUSION

In this phantom study, radiography equivalent dose computed tomography (RED-CT) demonstrates a partly higher diagnostic accuracy than radiography. Implementing RED-CT in the diagnostic work-up of finger fractures could improve diagnostics, support correct classification and adequate treatment. Clinical studies should be performed to confirm these preliminary results.

Prospective evaluation of ultra-low-dose contrast-enhanced 100-kV abdominal computed tomography with tin filter: effect on radiation dose reduction and image quality with a third-generation dual-source CT system

OBJECTIVES

To investigate the radiation dose exposure, image quality, and diagnostic performance of enhanced 100-kVp abdominopelvic single-energy CT protocol with tin filter (TF).

METHODS

Ninety-three consecutive patients referred for a single-phase enhanced abdominopelvic CT were prospectively included after informed consent. They underwent in addition to a standard protocol (SP) an acquisition with TF. Both examinations were performed on a third-generation dual-source CT system (DSCT), in single energy, using automatic tube current modulation, identical pitch, and identical level of iterative reconstruction. Radiation metrics were compared. Size-specific dose estimates (SSDE), contrast to noise ratio (CNR), and figure of merit (FOM) were calculated. Diagnostic confidence for the assessment of a predetermined list of abdominal lesions was rated by two independent readers.

RESULTS

The mean dose of the TF protocol was significantly lower (CDTI 1.56 ± 0.43 mGy vs. 8.13 ± 3.32, p < 0.001; SSDE 9.94 ± 3.08 vs. 1.93 ± 0.39, p < 0.001), with an effective dose close to 1 mSv (1.14 mSv ± 0.34; p < 0.001). TF group exhibited non-significant lower liver CNR (2.76 vs. 3.03, p = 0.56) and was more dose efficient (FOM 10.6 vs. 2.49/mSv, p < 0.001) in comparison to SP. The mean diagnostic confidence for visceral, bone, and peritoneal tumors was equivalent between both groups.

CONCLUSIONS

Enhanced 100-kVp abdominopelvic CT acquired after spectral shaping with tin filtration can achieve similar diagnostic performance and CNR compared to a standard CT protocol, while reducing the radiation dose by 81%.

KEY POINTS

• 100-kVp spectral filtration enables enhanced abdominal CT with high-dose efficiency. • The radiation dose reaches the 1-mSv range. • Predetermined abdominopelvic lesions can be assessed without impairing on diagnostic confidence.

Pulmonary quantitative CT imaging in focal and diffuse disease: current research and clinical applications

The frenetic development of imaging technology-both hardware and software-provides exceptional potential for investigation of the lung. In the last two decades, CT was exploited for detailed characterization of pulmonary structures and description of respiratory disease. The introduction of volumetric acquisition allowed increasingly sophisticated analysis of CT data by means of computerized algorithm, namely quantitative CT (QCT). Hundreds of thousands of CTs have been analysed for characterization of focal and diffuse disease of the lung. Several QCT metrics were developed and tested against clinical, functional and prognostic descriptors. Computer-aided detection of nodules, textural analysis of focal lesions, densitometric analysis and airway segmentation in obstructive pulmonary disease and textural analysis in interstitial lung disease are the major chapters of this discipline. The validation of QCT metrics for specific clinical and investigational needs prompted the translation of such metrics from research field to patient care. The present review summarizes the state of the art of QCT in both focal and diffuse lung disease, including a dedicated discussion about application of QCT metrics as parameters for clinical care and outcomes in clinical trials.

Whole-body ultra-low dose CT using spectral shaping for detection of osteolytic lesion in multiple myeloma

OBJECTIVES

The aim of this study was to investigate the radiation dose and image quality of a whole-body low-dose CT (WBLDCT) using spectral shaping at 100 kV (Sn 100 kV) for the assessment of osteolytic lesions in patients with multiple myeloma.

METHODS

Thirty consecutive patients were retrospectively selected, who underwent a WBLDCT on a third-generation dual-source CT (DSCT) (Sn 100 kV, ref. mAs: 130). They were matched with patients, who were examined on a second-generation DSCT with a standard low-dose protocol (100 kV, ref. mAs: 111). Objective and subjective image quality, radiation exposure as well as the frequency of osteolytic lesions were evaluated.

RESULTS

All scans were of diagnostic image quality. Subjective overall image quality was significantly higher in the study group (p = 0.0003). Objective image analysis revealed that signal intensities, signal-to-noise ratio and contrast-to-noise ratio of the bony structures were equal or significantly higher in the control group. There was no significant difference in the frequency of osteolytic lesions (p = 0.259). The median effective dose of the study protocol was significantly lower (1.45 mSv vs. 5.65 mSv; p < 0.0001).

CONCLUSION

WBLDCT with Sn 100 kV can obtain sufficient image quality for the depiction of osteolytic lesions while reducing the radiation dose by approximately 74%.

KEY POINTS

• Spectral shaping using tin filtration is beneficial for whole-body low-dose CT • Sn 100 kV yields sufficient image quality for depiction of osteolytic lesions • Whole-body low-dose CT can be performed with a median dose of 1.5 mSv.

Single-energy pediatric chest computed tomography with spectral filtration at 100 kVp: effects on radiation parameters and image quality

BACKGROUND

Most of the applied radiation dose at CT is in the lower photon energy range, which is of limited diagnostic importance.

OBJECTIVE

To investigate image quality and effects on radiation parameters of 100-kVp spectral filtration single-energy chest CT using a tin-filter at third-generation dual-source CT in comparison to standard 100-kVp chest CT.

MATERIALS AND METHODS

Thirty-three children referred for a non-contrast chest CT performed on a third-generation dual-source CT scanner were examined at 100 kVp with a dedicated tin filter with a tube current-time product resulting in standard protocol dose. We compared resulting images with images from children examined using standard single-source chest CT at 100 kVp. We assessed objective and subjective image quality and compared radiation dose parameters.

RESULTS

Radiation dose was comparable for children 5 years old and younger, and it was moderately decreased for older children when using spectral filtration (P=0.006). Effective tube current increased significantly (P=0.0001) with spectral filtration, up to a factor of 10. Signal-to-noise ratio and image noise were similar for both examination techniques (P≥0.06). Subjective image quality showed no significant differences (P≥0.2).

CONCLUSION

Using 100-kVp spectral filtration chest CT in children by means of a tube-based tin-filter on a third-generation dual-source CT scanner increases effective tube current up to a factor of 10 to provide similar image quality at equivalent dose compared to standard single-source CT without spectral filtration.

Diagnostic accuracy and added value of dual-energy subtraction radiography compared to standard conventional radiography using computed tomography as standard of reference

PURPOSE

To retrospectively evaluate diagnostic performance of dual-energy subtraction radiography (DESR) for interpretation of chest radiographs compared to conventional radiography (CR) using computed tomography (CT) as standard of reference.

MATERIAL AND METHODS

A total of 199 patients (75 female, median age 67) were included in this institutional review board (IRB)-approved clinical trial. All patients were scanned in posteroanterior and lateral direction with dual-shot DE-technique. Chest CT was performed within ±72 hours. The system provides three types of images: bone weighted-image, soft tissue weighted-image, herein termed as DESR-images, and a standard image, termed CR-image (marked as CR-image). Images were evaluated by two radiologists for presence of inserted life support lines, pneumothorax, pleural effusion, infectious consolidation, interstitial lung changes, tumor, skeletal alterations, soft tissue alterations, aortic or tracheal calcification and pleural thickening. Inter-observer agreement between readers and diagnostic performance were calculated. McNemar's test was used to test for significant differences.

RESULTS

Mean inter-observer agreement throughout the investigated parameters was higher in DESR images compared to CR-images (kDESR = 0.935 vs. kCR = 0.858). DESR images provided significantly increased sensitivity compared to CR-images for the detection of infectious consolidations (42% vs. 62%), tumor (46% vs. 57%), interstitial lung changes (69% vs. 87%) and aortic or tracheal calcification (25 vs. 73%) (p<0.05). There were no significant differences in sensitivity for the detection of inserted life support lines, pneumothorax, pleural effusion, skeletal alterations, soft tissue alterations or pleural thickening (p>0.05).

CONCLUSION

DESR increases significantly the sensibility without affecting the specificity evaluating chest radiographs, with emphasis on the detection of interstitial lung diseases.

Septic pulmonary emboli detected by 18F-FDG PET/CT in children with S. aureus catheter-related bacteremia

PURPOSE

The role of ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET/CT) in the diagnosis of metastatic infectious foci in children with catheter-related blood stream infection has been hardly studied, although some authors have reported it benefit in the screening of metastatic foci in adult population. Septic pulmonary emboli are among the most difficult to identify, because many cases do not present pulmonary complaints or abnormal chest radiography. However, diagnosis of these foci has important therapeutic consequences. The purpose of this article is to describe the role of ¹⁸F-FDG PET/CT in the diagnosis of septic pulmonary embolism in children with S. aureus catheter-related bacteremia.

METHODS

We report 3 children with S. aureus catheter-related bacteremia and normal chest X-ray at admission, in whom ¹⁸F-FDG PET/CT led to the diagnosis of unsuspected septic pulmonary emboli, with an impact on clinical management.

RESULTS

All patients had hemophilia and implantable venous access ports and presented with fever and normal lung auscultation. Only 1 reported non-specific symptoms (undifferentiated left chest pain). All patients had normal chest X-ray on admission. Catheters were removed within 48 h after admission in 2 cases, and 5 days after admission in the last case, subsiding fever. In 2 children, paired blood cultures were not able to identify bacteremia. However, in all cases catheter tip and subcutaneous port cultures yielded S. aureus and PET/CT detected unsuspected pulmonary metastatic emboli.

CONCLUSIONS

¹⁸F-FDG PET/CT should be considered as a useful tool to diagnose septic pulmonary embolism in S. aureus catheter-related bacteremia, especially if conventional diagnostic imaging techniques have failed to reveal possible metastatic foci. Further studies are needed to clarify the usefulness of PET/CT performance in children with CRBSI.

EFFECT OF RADIATION DOSE LEVEL ON ACCURACY AND PRECISION OF MANUAL SIZE MEASUREMENTS IN CHEST TOMOSYNTHESIS EVALUATED USING SIMULATED PULMONARY NODULES

The aim of the present study was to investigate the dependency of the accuracy and precision of nodule diameter measurements on the radiation dose level in chest tomosynthesis. Artificial ellipsoid-shaped nodules with known dimensions were inserted in clinical chest tomosynthesis images. Noise was added to the images in order to simulate radiation dose levels corresponding to effective doses for a standard-sized patient of 0.06 and 0.04 mSv. These levels were compared with the original dose level, corresponding to an effective dose of 0.12 mSv for a standard-sized patient. Four thoracic radiologists measured the longest diameter of the nodules. The study was restricted to nodules located in high-dose areas of the tomosynthesis projection radiographs. A significant decrease of the measurement accuracy and intraobserver variability was seen for the lowest dose level for a subset of the observers. No significant effect of dose level on the interobserver variability was found. The number of non-measurable small nodules (≤5 mm) was higher for the two lowest dose levels compared with the original dose level. In conclusion, for pulmonary nodules at positions in the lung corresponding to locations in high-dose areas of the projection radiographs, using a radiation dose level resulting in an effective dose of 0.06 mSv to a standard-sized patient may be possible in chest tomosynthesis without affecting the accuracy and precision of nodule diameter measurements to any large extent. However, an increasing number of non-measurable small nodules (≤5 mm) with decreasing radiation dose may raise some concerns regarding an applied general dose reduction for chest tomosynthesis examinations in the clinical praxis.

Organ Dose and Attributable Cancer Risk in Lung Cancer Screening with Low-Dose Computed Tomography

Purpose

Lung cancer screening with CT has been recently recommended for decreasing lung cancer mortality. The radiation dose of CT, however, must be kept as low as reasonably achievable for reducing potential stochastic risks from ionizing radiation. The purpose of this study was to calculate individual patients’ lung doses and to estimate cancer risks in low-dose CT (LDCT) in comparison with a standard dose CT (SDCT) protocol.

Materials and Methods

This study included 47 adult patients (mean age 63.0 ± 5.7 years) undergoing chest CT on a third-generation dual-source scanner. 23/47 patients (49%) had a non-enhanced chest SDCT, 24 patients (51%) underwent LDCT at 100 kVp with spectral shaping at a dose equivalent to a chest x-ray. 3D-dose distributions were obtained from Monte Carlo simulations for each patient, taking into account their body size and individual CT protocol. Based on the dose distributions, patient-specific lung doses were calculated and relative cancer risk was estimated according to BEIR VII recommendations.

Results

As compared to SDCT, the LDCT protocol allowed for significant organ dose and cancer risk reductions (p<0.001). On average, lung dose was reduced from 7.7 mGy to 0.3 mGy when using LDCT, which was associated with lowering of the cancer risk from 8.6 to 0.35 per 100’000 cases. A strong linear correlation between lung dose and patient effective diameter was found for both protocols (R² = 0.72 and R² = 0.75 for SDCT and LDCT, respectively).

Conclusion

Use of a LDCT protocol for chest CT with a dose equivalent to a chest x-ray allows for significant lung dose and cancer risk reduction from ionizing radiation.