Diagnostic Performance of Ultra-Low-Dose Computed Tomography for Detecting Asbestos-Related Pleuropulmonary Diseases: Prospective Study in a Screening Setting

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.

[A Review of Current Knowledge for X-ray Energy in CT: Practical Guide for CT Technologist]

In computed tomography (CT) systems, the optimal X-ray energy in imaging depends on the material composition and the subject size. Among the parameters related to the X-ray energy, we can arbitrarily change only the tube voltage. For years, the tube voltage has often been set at 120 kVp. However, since about 2000, there has been an increasing interest in reducing radiation dose, and it has led to the publication of various reports on low tube voltage. Furthermore, with the spread of dual-energy CT, virtual monochromatic X-ray images are widely used since the contrast can be adjusted by selecting the optional energy. Therefore, because of the renewed interest in X-ray energy in CT imaging, the issue of energy and imaging needs to be summarized. In this article, we describe the basics of physical characteristics of X-ray attenuation with materials and its influence on the process of CT imaging. Moreover, the relationship between X-ray energy and CT imaging is discussed for clinical applications.

Evaluation of AI-Based Segmentation Tools for COVID-19 Lung Lesions on Conventional and Ultra-low Dose CT Scans

A reliable diagnosis and accurate monitoring are pivotal steps for treatment and prevention of COVID-19. Chest computed tomography (CT) has been considered a crucial diagnostic imaging technique for the injury assessment of the viral pneumonia. Furthermore, the automatization of the segmentation methods for lung alterations helps to speed up the diagnosis and lighten radiologists' workload. Considering the assiduous pathology monitoring, ultra-low dose (ULD) chest CT protocols have been implemented to drastically reduce the radiation burden. Unfortunately, the available AI technologies have not been trained on ULD-CT data and validated and their applicability deserves careful evaluation. Therefore, this work aims to compare the results of available AI tools (BCUnet, CORADS AI, NVIDIA CLARA Train SDK and CT Pneumonia Analysis) on a dataset of 73 CT examinations acquired both with conventional dose (CD) and ULD protocols. COVID-19 volume percentage, resulting from each tool, was statistically compared. This study demonstrated high comparability of the results on CD-CT and ULD-CT data among the four AI tools, with high correlation between the results obtained on both protocols (R > .68, P < .001, for all AI tools).

COMPARISON OF PULMONARY NODULE DETECTION, READING TIMES AND PATIENT DOSES OF ULTRA-LOW DOSE CT, STANDARD DOSE CT AND DIGITAL RADIOGRAPHY

The purpose of the present work was to evaluate performance in pulmonary nodule detection, reading times and patient doses for ultra-low dose computed tomography (ULD-CT), standard dose chest CT (SD-CT), and digital radiography (DR). Pulmonary nodules were simulated in an anthropomorphic lung phantom. Thirty cases, 18 with lesions (45 total lesions of 3-12 mm) and 12 without lesions were acquired for each imaging modality. Three radiologists interpreted the cases in a free-response study. Performance was assessed using the JAFROC figure-of-merit (FOM). Performance was not significantly different between ULD-CT and SD-CT (FOMs: 0.787 vs 0.814; ΔFOM: 0.03), but both CT techniques were superior to DR (FOM: 0.541; ΔFOM: 0.31 and 0.28). Overall, the CT modalities took longer time to interpret than DR. ULD chest CT may serve as an alternative to both SD-CT and conventional radiography, considerably reducing dose in the first case and improving diagnostic accuracy in the second.

ACR Appropriateness Criteria® Chronic Cough

Chronic cough is defined by a duration lasting at least 8 weeks. The most common causes of chronic cough include smoking-related lung disease, upper airway cough syndrome, asthma, gastroesophageal reflux disease, and nonasthmatic eosinophilic bronchitis. The etiology of chronic cough in some patients may be difficult to localize to an isolated source and is often multifactorial. The complex pathophysiology, clinical presentation, and variable manifestations of chronic cough underscore the challenges faced by clinicians in the evaluation and management of these patients. Imaging plays a role in the initial evaluation, although there is a lack of high-quality evidence guiding which modalities are useful and at what point in time the clinical evaluation should be performed. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Impact of Morphotype on Image Quality and Diagnostic Performance of Ultra-Low-Dose Chest CT

Objectives: The image quality of an Ultra-Low-Dose (ULD) chest CT depends on the patient’s morphotype. We hypothesize that there is a threshold beyond which the diagnostic performance of a ULD chest CT is too degraded. This work assesses the influence of morphotype (Body Mass Index BMI, Maximum Transverse Chest Diameter MTCD and gender) on image quality and the diagnostic performance of a ULD chest CT. Methods: A total of 170 patients from three prior prospective monocentric studies were retrospectively included. Renewal of consent was waived by our IRB. All the patients underwent two consecutive unenhanced chest CT acquisitions with a full dose (120 kV, automated tube current modulation) and a ULD (135 kV, fixed tube current at 10 mA). Image noise, subjective image quality and diagnostic performance for nine predefined lung parenchyma lesions were assessed by two independent readers, and correlations with the patient’s morphotype were sought. Results: The mean BMI was 26.6 ± 5.3; 20.6% of patients had a BMI > 30. There was a statistically significant negative correlation of the BMI with the image quality (ρ = −0.32; IC95% = (−0.468; −0.18)). The per-patient diagnostic performance of ULD was sensitivity, 77%; specificity, 99%; PPV, 94% and NPV, 65%. There was no statistically significant influence of the BMI, the MTCD nor the gender on the per-patient and per-lesion diagnostic performance of a ULD chest CT, apart from a significant negative correlation for the detection of emphysema. Conclusions: Despite a negative correlation between the BMI and the image quality of a ULD chest CT, we did not find a correlation between the BMI and the diagnostic performance of the examination, suggesting a possible use of the ULD protocol in obese patients.

Radiomics in the evaluation of lung nodules: Intrapatient concordance between full-dose and ultra-low-dose chest computed tomography

PURPOSE

The purpose of this study was to retrospectively evaluate the quantitative and qualitative intrapatient concordance of pulmonary nodule risk assessment by commercially available radiomics software between full-dose (FD) chest-CT and ultra-low-dose (ULD) chest CT.

MATERIALS AND METHODS

Between July 2013 and September 2015, 68 patients (52 men and16 women; mean age, 65.5±10.6 [SD] years; range: 35-87 years) with lung nodules≥5mm and<30mm who underwent the same day FD chest CT (helical acquisition; 120kV; automated tube current modulation) and ULD chest CT (helical acquisition; 135kV; 10mA fixed) were retrospectively included. Each nodule on each acquisition was assessed by a commercial radiomics software providing a similarity malignancy index (mSI), classifying it as "benign-like" (mSI<0.1); "malignant-like" (mSI>0.9) or "undetermined" (0.1≤mSI≤0.9). Intrapatient qualitative agreement was evaluated with weighted Cohen-Kappa test and quantitative agreement with intraclass correlation coefficient (ICC).

RESULTS

Ninety-nine lung nodules with a mean size of 9.14±4.3 (SD) mm (range: 5-25mm) in 68 patients (mean 1.46 nodule per patient; range: 1-5) were assessed; mean mSI was 0.429±0.331 (SD) (range: 0.001-1) with FD chest CT (22/99 [22%] "benign-like", 67/99 [68%] "undetermined" and 10/99 [10%] "malignant-like") and mean mSI was 0.487±0.344 (SD) (range: 0.002-1) with ULD chest CT (20/99 [20%] "benign-like", 59/99 [60%] "undetermined" and 20/99 [20%] "malignant-like"). Qualitative and quantitative agreement of FD chest CT with ULD chest CT were "good" with Kappa value of 0.60 (95% CI: 0.46-0.74) and ICC of 0.82 (95% CI: 0.73-0.87), respectively.

CONCLUSION

A good agreement in malignancy similarity index can be obtained between ULD chest CT and FD chest CT using radiomics software. However, further studies must be done with more case material to confirm our results and elucidate the diagnostic capabilities of radiomics software using ULD chest CT for lung nodule characterization by comparison with FD chest CT.

Added benefits of early detection of other diseases on low-dose CT screening

Low-dose CT screening for lung cancer provides images of the entire chest and upper abdomen. While the focus of screening is on finding early lung cancer, radiology leadership has embraced the fact that the information contained in the images presents a new challenge to the radiology profession. Other findings in the chest and upper abdomen were not the reason for obtaining the screening CT scan, nor symptom-prompted, but still need to be reported. Reporting these findings and making recommendations for further workup requires careful consideration to avoid unnecessary workup or interventions while still maximizing the benefit that early identification of these other diseases provided. Other potential findings, such as cardiovascular disease and chronic pulmonary obstructive diseases actually cause more deaths than lung cancer. Existing recommendations for workup of abnormal CT findings are based on symptom-prompted indications for imaging. These recommendations may be different when the abnormalities are identified in asymptomatic people undergoing CT screening for lung cancer. I-ELCAP, a large prospectively collected multi-institutional and multi-national database of screenings, was used to analyze CT findings identified in screening for lung cancer. These analyses and recommendations were made by radiologists in collaboration with clinicians in different medical specialties.

Image quality of ultralow-dose chest CT using deep learning techniques: potential superiority of vendor-agnostic post-processing over vendor-specific techniques

OBJECTIVE

To compare the image quality between the vendor-agnostic and vendor-specific algorithms on ultralow-dose chest CT.

METHODS

Vendor-agnostic deep learning post-processing model (DLM), vendor-specific deep learning image reconstruction (DLIR, high level), and adaptive statistical iterative reconstruction (ASiR, 70%) algorithms were employed. One hundred consecutive ultralow-dose noncontrast CT scans (CTDI_vol; mean, 0.33 ± 0.056 mGy) were reconstructed with five algorithms: DLM-stnd (standard kernel), DLM-shrp (sharp kernel), DLIR, ASiR-stnd, and ASiR-shrp. Three thoracic radiologists blinded to the reconstruction algorithms reviewed five sets of 100 images and assessed subjective noise, spatial resolution, distortion artifact, and overall image quality. They selected the most preferred algorithm among five image sets for each case. Image noise and signal-to-noise ratio were measured. Edge-rise-distance was measured at a pulmonary vessel, i.e., the distance between two points where attenuation was 10% and 90% of maximal intravascular intensity. The skewness of attenuation was calculated in homogeneous areas.

RESULTS

DLM-stnd, followed by DLIR, showed the best subjective noise on both lung and mediastinal windows, while DLIR yielded the least measured noise (ps < .0001). Compared to DLM-stnd, DLIR showed inferior subjective spatial resolution on lung window and higher edge-rise-distance (ps < .0001). Additionally, DLIR showed the most frequent distortion artifacts and deviated skewness (ps < .0001). DLM-stnd scored the best overall image quality, followed by DLM-shrp and DLIR (mean score 3.89 ± 0.19, 3.68 ± 0.24, and 3.53 ± 0.33; ps < .001). Two among three readers preferred DLM-stnd on both windows.

CONCLUSION

Although DLIR provided the best quantitative noise profile, DLM-stnd showed the best overall image quality with fewer artifacts and was preferred by two among three readers.

KEY POINTS

• A vendor-agnostic deep learning post-processing algorithm applied to ultralow-dose chest CT exhibited the best image quality compared to vendor-specific deep learning algorithm and ASiR techniques. • Two out of three readers preferred a vendor-agnostic deep learning post-processing algorithm in comparison to vendor-specific deep learning algorithm and ASiR techniques. • A vendor-specific deep learning reconstruction algorithm yielded the least image noise, but showed significantly more frequent specific distortion artifacts and increased skewness of attenuation compared to a vendor-agnostic algorithm.

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.

The Regimen of Computed Tomography Screening for Lung Cancer: Lessons Learned Over 25 Years From the International Early Lung Cancer Action Program

We learned many unanticipated and valuable lessons since we started planning our study of low-dose computed tomography (CT) screening for lung cancer in 1991. The publication of the baseline results of the Early Lung Cancer Action Project (ELCAP) in Lancet 1999 showed that CT screening could identify a high proportion of early, curable lung cancers. This stimulated large national screening studies to be quickly started. The ELCAP design, which provided evidence about screening in the context of a clinical program, was able to rapidly expand to a 12-institution study in New York State (NY-ELCAP) and to many international institutions (International-ELCAP), ultimately working with 82 institutions, all using the common I-ELCAP protocol. This expansion was possible because the investigators had developed the ELCAP Management System for screening, capturing data and CT images, and providing for quality assurance. This advanced registry and its rapid accumulation of data and images allowed continual assessment and updating of the regimen of screening as advances in knowledge and new technology emerged. For example, in the initial ELCAP study, introduction of helical CT scanners had allowed imaging of the entire lungs in a single breath, but the images were obtained in 10 mm increments resulting in about 30 images per person. Today, images are obtained in submillimeter slice thickness, resulting in around 700 images per person, which are viewed on high-resolution monitors. The regimen provides the imaging acquisition parameters, imaging interpretation, definition of positive result, and the recommendations for further workup, which now include identification of emphysema and coronary artery calcifications. Continual updating is critical to maximize the benefit of screening and to minimize potential harms. Insights were gained about the natural history of lung cancers, identification and management of nodule subtypes, increased understanding of nodule imaging and pathologic features, and measurement variability inherent in CT scanners. The registry also provides the foundation for assessment of new statistical techniques, including artificial intelligence, and integration of effective genomic and blood-based biomarkers, as they are developed.

ACR Appropriateness Criteria® Occupational Lung Diseases

Ordering the appropriate diagnostic imaging for occupational lung disease requires a firm understanding of the relationship between occupational exposure and expected lower respiratory track manifestation. Where particular inorganic dust exposures typically lead to nodular and interstitial lung disease, other occupational exposures may lead to isolated small airway obstruction. Certain workplace exposures, like asbestos, increase the risk of malignancy, but also produce pulmonary findings that mimic malignancy. This publication aims to delineate the common and special considerations associated with occupational lung disease to assist the ordering physician in selecting the most appropriate imaging study, while still stressing the importance of a multidisciplinary approach. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

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.

Wide-volume versus helical acquisition in unenhanced chest CT: prospective intra-patient comparison of diagnostic accuracy and radiation dose in an ultra-low-dose setting

OBJECTIVES

Diagnostic performance and potential radiation dose reduction of wide-area detector CT sequential acquisition ("wide-volume" acquisition (WV)) in unenhanced chest examination are unknown. This study aims to assess the image quality, the diagnostic performance, and the radiation dose reduction of WV mode compared with the classical helical acquisition for lung parenchyma analysis in an ultra-low-dose (ULD) protocol.

METHODS

After Institutional Review Board Approval and written informed consent, 64 patients (72% men; 67.6 ± 9.7 years old; BMI 26.1 ± 5.3 kg/m²) referred for a clinically indicated unenhanced chest CT were prospectively included. All patients underwent, in addition to a standard helical acquisition (120 kV, automatic tube current modulation), two ULD acquisitions (135 kV, fixed tube current at 10 mA): one in helical mode and one in WV mode. Image noise, subjective image quality (5-level Likert scale), and diagnostic performance for the detection of 9 predetermined parenchymal abnormalities were assessed by two radiologists and compared using the chi-square or Fisher non-parametric tests.

RESULTS

Subjective image quality (4.2 ± 0.7 versus 4.2 ± 0.8, p = 0.56), image noise (41.7 ± 8 versus 40.9 ± 8.7, p = 0.3), and diagnostic performance were equivalent between ULD WV and ULD helical. Radiation dose was significantly lower for the ULD WV acquisition (mean dose-length product 14.1 ± 1.3 mGy cm versus 15.8 ± 1.3, p < 0.0001).

CONCLUSION

An additional 11% dose reduction is achieved with the WV mode in ULD chest CT with fixed tube current, with equivalent image quality and diagnostic performance when compared with the helical acquisition.

KEY POINTS

• Image quality and diagnostic performance of ultra-low-dose unenhanced chest CT are identical between wide-volume mode and the reference helical acquisition. • Wide-volume mode allows an additional radiation dose reduction of 11% (mean dose-length product 14.1 ± 1.3 mGy cm versus 15.8 ± 1.3, p < 0.0001).

Low-dose computed tomography screening for lung cancer in people with workplace exposure to asbestos

OBJECTIVES

Smoking is the main risk factor for lung cancer, but environmental and occupational exposure to carcinogens also increase lung cancer risk. We assessed whether extending low-dose computed tomography (LDCT) screening to persons with occupational exposure to asbestos may be an effective way reducing lung cancer mortality.

MATERIALS AND METHODS

We conducted a nested case-control study within the COSMOS screening program, assessing past asbestos exposure with a questionnaire. LDCT scans of asbestos-exposed participants were reviewed to assess the presence of pulmonary, interstitial and pleural alterations in comparison to matched unexposed controls. We also performed an exhaustive review, with meta-analysis, of the literature on LDCT screening in asbestos-exposed persons.

RESULTS

Exposure to asbestos, initially self-reported by 9.8% of COSMOS participants, was confirmed in 216 of 544 assessable cases, corresponding to 2.6% of the screened population. LDCT of asbestos-exposed persons had significantly more pleural plaques, diaphragmatic pleural thickening and pleural calcifications, but similar frequency of parenchymal and interstitial alterations to unexposed persons. From 16 papers, including this study, overall lung cancer detection rates at baseline were 0.81% (95% CI 0.50-1.19) in asbestos-exposed persons, 0.94% (95% CI 0.47-1.53) in asbestos-exposed smokers (12 studies), and 0.11% (95% CI 0.00-0.43) in asbestos-exposed non-smokers (9 studies).

CONCLUSION

Persons occupationally exposed to asbestos should be monitored to gather more information about risks. Although LDCT screening is effective in the early detection lung cancer in asbestos-exposed smokers, our data suggest that screening of asbestos-exposed persons with no additional risk factors for cancer does is not viable due to the low detection rate.

Dose estimation of ultra-low-dose chest CT to different sized adult patients

OBJECTIVES

To evaluate the effect of patient size on radiation dose for standard CT (SD-CT), ultra-low-dose CT (ULD-CT) and two-view digital radiography (DR).

METHODS

Dosimeters were distributed within the lungs of chest phantoms representing males of 65 kg and 82 kg (body mass indices 23 and 29). In contrast to SD-CT and DR which include automatic exposure control (AEC), the ULD scan employs a fixed mAs value. The phantoms were exposed to SD, ULD and DR while recording lung doses. Projected dose data were calculated from the phantoms. The resulting exposure settings were used in Monte Carlo programs to determine the effective dose for a standard-sized (BMI 24.2) adult male (170 cm/70 kg) and female (160 cm/59 kg). Patients previously examined by both ULD- and SD-CT were identified to determine post hoc size-specific dose estimates (SSDEs).

RESULTS

ULD-CT dose was inversely related to patient size; average lung doses summarised in terms of patient size BMI_23/29 are 5.2/8.1 (SD-CT), 0.56/0.35 (ULD-CT) and 0.05/0.13 mGy (DR), while the effective doses for these techniques on a standard-sized male were 2.9, 0.16 and 0.03 mSv and 2.3, 0.247 and 0.024 mSv for a standard-sized female respectively. SSDEs for 15 patients (averages: BMI 26, range 18-37) averaged 5.5 mGy (3.6-10) for SD-CT and 0.35 mGy (0.42-0.27) for ULD-CT.

CONCLUSIONS

The effective doses for a standard-sized male and female examined by ULD-CT are (respectively) ~ 6%/~ 11% of SD-CT and ~ 5/~ 10 times higher than DR. ULD-CT gave a lower radiation dosage to larger patients than DR. AEC is warranted in ULD-CT for improved dose consistency.

KEY POINTS

• For standard-sized patients, ULD-CT dose level is ~ 6%/~ 11% of SD-CT, and ~ 5/~ 10 times higher than DR. For larger patients, ULD-CT is currently being used clinically at lower dose levels than DR. • Using ULD-CT should greatly reduce the risk of late effects from ionising radiation. • AEC in ULD-CT is desirable for increased consistency in patient dose.

Ultra-low-dose unenhanced chest CT: Prospective comparison of high kV/low mA versus low kV/high mA protocols

PURPOSE

To qualitatively and quantitatively compare unenhanced ultra-low-dose chest computed tomography (ULD-CT) acquired at 80kVp and 135kVp.

MATERIALS AND METHODS

Fifty-one patients referred for unenhanced chest CT were prospectively included. There were 29 men and 22 women, with a mean age of 64.7±11.6 (SD) years (range: 35-91 years) and a mean body mass index of 26.2±6.3 (SD) (range: 17-54.9). All patients underwent two different ULD-CT protocols (80kVp-40mA and 135kVp-10mA). Image quality of both ULD-CT examinations using a 5-level scale as well as assessability of 6 predetermined lung parenchyma lesions were blindly evaluated by three radiologists and compared using a logistic regression model. Image noise of the two protocols was compared with Wilcoxon signed-rank test.

RESULTS

The mean dose-length product at 80kVp and at 135kVp were 14.7±1.8 (SD) mGy.cm and 15.6±1.9 (SD) mGy.cm, respectively (P<0.001). Image noise was significantly lower at 135kVp (58.9±12.4) than at 80kVp (74.7±14.5) (P<0.001). For all readers and for all examinations, the 135kVp protocol yielded better image quality than 80kVp protocol, with a mean qualitative score of 4.5±0.7 versus 3.9±0.8 (P<0.001). The 135kVp protocol was significantly more often of diagnostic quality than the 80kvp protocol (92.3% versus 77.8%, respectively) (P<0.001) and was less prone to image quality deterioration in obese patients. Parenchymal lesions were never better depicted on the 80kVp protocol than with the 135kVp protocol.

CONCLUSION

Unenhanced chest ULD-CT should be acquired at a high kilovoltage and low current, such as 135kVp-10mA, over a low kilovoltage and high current protocol.