Strategies for reducing radiation dose in CT

Double low-dose computed tomography (CT) angiography of craniocervical arteries using a test bolus of diluted contrast medium and a personalized contrast protocol

AIM

To prospectively assess the value of a test bolus of diluted contrast medium (CM) combined with a personalized contrast protocol in craniocervical computed tomography angiography (cc-CTA) with low radiation and CM doses.

MATERIALS AND METHODS

Eighty-six consecutive subjects were divided into two groups at random (43 in each one): group A: 100/Sn140 kVp, filtered back-projection reconstruction, iopromide (370 mgI/ml) 50 ml; group B: 80/Sn140 kVp, iterative reconstruction, iodixanol (270 mgI/ml). In group B, the test bolus contained 27 ml of diluted CM, a personalized protocol with low-concentration CM was used for angiography, and the test bolus injection duration in angiography remained the same. Artery values over 200 Hounsfield units were considered significant.

RESULTS

Image quality for all cases was found to be diagnostic. No significant differences were found in the arterial densities of the ascending aorta or basilar artery between the groups. The values of the common carotid artery, internal carotid artery, and middle cerebral artery in group B were significantly lower. The effective dose and average iodine uptake were significantly lower in group B.

CONCLUSION

With double-low-dose cc-CTA, test bolus scanning based on diluted CM combined with a personalized contrast protocol can yield diagnostic-quality images and significantly reduce the radiation and CM doses.

Development, validation, and application of a generic image-based noise addition method for simulating reduced dose computed tomography images

BACKGROUND

Major efforts in computed tomography (CT) have been focused on reducing radiation dose to patients while maintaining adequate diagnostic quality. To that end, research tools have been developed to simulate reduced-dose images via either image-based or projection-based methods. The former is limited to fully capturing realistic texture, streak, and non-stationary characteristics of reduced dose, while the latter is impractical clinically.

PURPOSE

To develop and validate an image-based noise addition method that accounts for such attributes while being practical in clinical settings.

METHODS

A noise addition method was developed to add realistic noise in the image domain. The method first estimates the noise power spectrum (NPS) of CT images, which are also forward-projected to form synthetic projections. The projection data are supplemented with random white noise proportional to their attenuation values. The noise sinogram is then back-projected onto the image, filtered by the NPS, and scaled according to the desired dose reduction level. The tool was evaluated using both phantom images and patient data. The phantom images were acquired using a multi-sized image quality phantom (Mercury Phantom 3.0, Duke University), and a thorax anthropomorphic phantom (Lungman Phantom, Kyoto Kagaku) at different dose levels and reconstruction settings. The patient images consisted of two dose levels of various CT examinations and reconstruction settings. The simulated and real reduced-dose images were compared in terms of the noise magnitude and texture (i.e., NPS average frequency, NPS-fav). The utility of this methodology was also assessed for routine clinical use for CT protocol review.

RESULTS

For the phantom images, the percent errors in the noise magnitude between the simulated images and the actual images of the Mercury Phantom and anthropomorphic phantom images were 3.34% and 3.50%, respectively. The difference in fav was 0.07 mm-1 for the Mercury Phantom and 0.06 mm-1 for the anthropomorphic phantom between the simulated and actual images. The average noise magnitude percent error between the simulated and actual patient images was 4.61% with noise texture judged to be visually comparable with some kernel dependencies. When implemented clinically, the tool proved practical to simplify the process of estimating radiation dose reduction for CT protocols, resulting in a 50% dose reduction of our multiple myeloma protocol.

CONCLUSIONS

The method generated simulated CT images with realistic noise properties similar to images acquired at the same radiation exposure without needing access to raw projection data.

Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography

OBJECTIVE

To evaluate radiation dose and image quality of a double-low CCTA protocol reconstructed utilizing high-strength deep learning image reconstructions (DLIR-H) compared to standard adaptive statistical iterative reconstruction (ASiR-V) protocol in non-obese patients.

MATERIALS AND METHODS

From June to October 2022, consecutive patients, undergoing clinically indicated CCTA, with BMI < 30 kg/m2 were prospectively included and randomly assigned into three groups: group A (100 kVp, ASiR-V 50%, iodine delivery rate [IDR] = 1.8 g/s), group B (80 kVp, DLIR-H, IDR = 1.4 g/s), and group C (80 kVp, DLIR-H, IDR = 1.2 g/s). High-concentration contrast medium was administered. Image quality analysis was evaluated by two radiologists. Radiation and contrast dose, and objective and subjective image quality were compared across the three groups.

RESULTS

The final population consisted of 255 patients (64 ± 10 years, 161 men), 85 per group. Group B yielded 42% radiation dose reduction (2.36 ± 0.9 mSv) compared to group A (4.07 ± 1.2 mSv; p < 0.001) and achieved a higher signal-to-noise ratio (30.5 ± 11.5), contrast-to-noise-ratio (27.8 ± 11), and subjective image quality (Likert scale score: 4, interquartile range: 3-4) compared to group A and group C (all p ≤ 0.001). Contrast medium dose in group C (44.8 ± 4.4 mL) was lower than group A (57.7 ± 6.2 mL) and B (50.4 ± 4.3 mL), all the comparisons were statistically different (all p < 0.001).

CONCLUSION

DLIR-H combined with 80-kVp CCTA with an IDR 1.4 significantly reduces radiation and contrast medium exposure while improving image quality compared to conventional 100-kVp with 1.8 IDR protocol in non-obese patients.

CLINICAL RELEVANCE STATEMENT

Low radiation and low contrast medium dose coronary CT angiography protocol is feasible with high-strength deep learning reconstruction and high-concentration contrast medium without compromising image quality.

KEY POINTS

Minimizing the radiation and contrast medium dose while maintaining CT image quality is highly desirable. High-strength deep learning iterative reconstruction protocol yielded 42% radiation dose reduction compared to conventional protocol. "Double-low" coronary CTA is feasible with high-strength deep learning reconstruction without compromising image quality in non-obese patients.

Implantation of CRT pacemaker during pregnancy: estimated fetal radiation dose

The benefits of a cardiac resynchronization therapy (CRT) implantation are known in severe heart failure and its implantation may also be considered during pregnancy to ensure safe pregnancy and delivery for both the mother and the fetus. This study on a patient case aimed to estimate the absorbed dose (AD) to the fetus during the CRT implantation of 21st week of the pregnant woman. AD measurement was done using anthropomorphic phantom, radiophotoluminescence dosemeters and Monte Carlo simulation utilizing kerma area product (KAP) of the procedures. The measured AD for a phantom's uterus and heart was 0.116 and 14.7 mGy with total KAP of 27.9 Gycm2. The estimated actual AD to the fetus and the mother's heart was 0.004 and 1.2 mGy, with total KAP of 1.5 Gycm2. The dose to the fetus can be minimized with the optimized procedure.

Comparison of doses received from non-contrast enhanced brain CT examinations between two CT scanners

Objectives

Medical devices based on X-ray imaging, such as computed tomography, are considered notable sources of artificial radiation. The aim of this study was to compare the computed tomography dose volume index, the dose length product, and the effective dose of the brain non-contrast enhanced examination on two CT scanners to determine the current state in terms of radiation doses, compare doses to the reference values, and possibly optimize the examination.

Materials and methods

Data from January 2020 to the second half of 2021 were retrospectively obtained by accessing dose reports from the Picture Archiving and Communication System (PACS). Data were collected and analyzed in Microsoft Excel. The effective dose was estimated using the dose-length product parameter and the normalized conversion factor for a given anatomical region. For statistical analysis, a two-sample t-test was used.

Results

The first data set consists of 200 patients (100 and 100 for older and newer CT scanners) regardless of the scan technique; the average CTDIvol and DLP for the older CT scanner were 57.61 ± 2.89 mGy and 993.28 ± 146.18 mGy cm, and for the newer CT scanner, 43.66 ± 11.15 mGy and 828.14 ± 130.06 mGy cm. The second data set consists of 100 patients (50 for the older CT scanner and 50 for the newer CT scanner) for a sequential scan; the average CTDIvol and DLP for the older CT scanner were 58.63 ± 3.33 mGy and 949.42 ± 80.87 mGy.cm, and for the newer CT, 57.25 ± 3.4 mGy and 942.13 ± 73.05 mGy cm. The third data set consists of 40 patients (20 and 20 for older and newer CT scanners) for the helical scan - the average CTDIvol and DLP for the older CT scanner were 54.6 ± 0 mGy and 1252.2 ± 52.11 mGy.cm, and for the newer CT, 37.18 ± 2.52 mGy and 859.66 ± 72.04 mGy cm. The difference between the older and newer CT scanners in terms of dose reduction was approximately 30 % in favor of the newer scanner for noncontrast enhanced brain examinations performed using the helical scan technique.

Conclusion

A non-contrast enhanced brain examination scanned with newer CT equipment was associated with a lower radiation burden on the patient.

Effects of tube voltage, radiation dose and adaptive statistical iterative reconstruction strength level on the detection and characterization of pulmonary nodules in ultra-low-dose chest CT

OBJECTIVE

To explore the effects of tube voltage, radiation dose and adaptive statistical iterative reconstruction (ASiR-V) strength level on the detection and characterization of pulmonary nodules by an artificial intelligence (AI) software in ultra-low-dose chest CT (ULDCT).

MATERIALS AND METHODS

An anthropomorphic thorax phantom containing 12 spherical simulated nodules (Diameter: 12 mm, 10 mm, 8 mm, 5 mm; CT value: -800HU, -630HU, 100HU) was scanned with three ULDCT protocols: Dose-1 (70kVp:0.11mSv, 100kVp:0.10mSv), Dose-2 (70kVp:0.34mSv, 100kVp:0.32mSv), Dose-3 (70kVp:0.53mSv, 100kVp:0.51mSv). All scanning protocols were repeated five times. CT images were reconstructed using four different strength levels of ASiR-V (0%=FBP, 30%, 50%, 70%ASiR-V) with a slice thickness of 1.25 mm. The characteristics of the physical nodules were used as reference standards. All images were analyzed using a commercially available AI software to identify nodules for calculating nodule detection rate (DR) and to obtain their long diameter and short diameter, which were used to calculate the deformation coefficient (DC) and size measurement deviation percentage (SP) of nodules. DR, DC and SP of different imaging groups were statistically compared.

RESULTS

Image noise decreased with the increase of ASiR-V strength level, and the 70 kV images had lower noise under the same strength level (mean-value 70 kV: 40.14 ± 7.05 (dose 1), 27.55 ± 7.38 (dose 2), 23.88 ± 6.98 (dose 3); 100 kV: 42.36 ± 7.62 (dose 1); 30.78 ± 6.87 (dose 2); 26.49 ± 6.61 (dose 3)). Under the same dose level, there were no differences in DR between 70 kV and 100 kV (dose 1: 58.76% vs. 58.33%; dose 2: 73.33% vs. 70.83%; dose 3: 75.42% vs. 75.42%, all p > 0.05). The DR of GGNs increased significantly at dose 2 and higher (70 kV: 38.12% (dose 1), 60.63% (dose 2), 64.38% (dose 3); 100 kV: 37.50% (dose 1), 59.38% (dose 2), 66.25% (dose 3)). In general, the use of ASiR-V at higher strength levels (> 50%) and 100 kV provided better (lower) DC and SP.

CONCLUSION

Detection rates are similar between 70 kV and 100 kV scans. The 70 kV images have better noise performance under the same ASiR-V level, while images of 100 kV and higher ASiR-V levels are better in preserving the nodule morphology (lower DC and SP); the dose levels above 0.33mSv provide high sensitivity for nodules detection, especially the simulated ground glass nodules.

Preoperative diagnostic value of multimodal spectral CT for patients with atrial fibrillation undergoing radiofrequency ablation

Objective

Delayed enhancement cardiac computed tomography (CT) empowers the diagnosis of left atrial appendage thrombus while limited to scanning heterogeneity. We optimized the spectral CT scan and post-process protocols, incorporating delayed enhancement and spectral iodine analysis to discriminate left atrial appendage (LAA) thrombus with better morphological relationships between the left atrium, pulmonary vein, and esophagus.

Methods

A total of 278 consecutive patients were retrieved from January 2019 to June 2023. All patients underwent transesophageal echocardiography (TEE) and spectral CT scan of the left atrial and pulmonary vein, with a complete period including the pulmonary venous phase and three delay phases. TEE diagnosis was used as the standard reference. For patients exhibiting LAA filling defects during the pulmonary venous phase, a delayed scan of 30 s (phase I) was performed. If the filling defects persisted, a further delayed scan of 1 min (phase II) was conducted. In cases where the filling defects persisted, an additional delayed scan of 2 min (phase III) was carried out. Iodine concentration in the filled defect area of LAA and the left atrium was measured in phase III. Moreover, 30 patients were randomly selected for water-swallowing and the other 30 for calm breathing. The image quality and esophageal dilation of the two groups were assessed by two experienced surgeons specializing in radiofrequency ablation.

Results

In total, 14 patients were diagnosed with thrombi by TEE. The sensitivity, specificity, positive predictive values, negative predictive values, and AUC of phase III delayed combined with iodine quantification for thrombi diagnosis were all 100%. The water-swallowing group exhibited significantly greater esophageal filling and expansion than the calm-breathing group, contributing to a better morphology assessment with no significant difference in image quality.

Conclusion

Combined with iodine quantification, delayed enhancement of spectral CT imaging presents a promising diagnostic potency for LAA thrombus. Incorporating water swallowing into the CT scan process further enables anatomical visualization of the esophagus, left atrium, and pulmonary vein, thereby providing more objective and authentic imaging evidence to assess the esophageal morphology and positional relationships.

Evolving Radiological Approaches in the Diagnosis and Monitoring of Arachnoiditis Ossificans

Arachnoiditis ossificans (AO) is a rare and complex neurological condition characterized by pathological calcification or ossification of the arachnoid membrane. Arachnoiditis ranks as the third most frequent cause of failed back surgery syndrome (FBSS). This narrative review explores the evolving radiological approaches in its diagnosis and monitoring. The historical perspective traces the progression from plain radiographs to advanced imaging techniques. Current radiological modalities, including X-ray, computed tomography (CT), and magnetic resonance imaging (MRI), are discussed, highlighting their respective roles, advantages, and limitations. Emerging and advanced imaging modalities, such as high-resolution CT, 3T and 7T MRI, and PET/CT or PET/MRI, are examined for their potential to enhance diagnostic accuracy and monitoring capabilities. A comparative analysis of these imaging modalities considers their sensitivity, specificity, cost-effectiveness, and radiation exposure implications. The review also explores the crucial role of imaging in disease monitoring and treatment planning, including follow-up protocols, evaluation of disease progression, and guidance for interventional procedures. Future directions in the field are discussed, focusing on promising research areas, the potential of artificial intelligence and machine learning in image analysis, and identified gaps in current knowledge. The review emphasizes the importance of a multimodal imaging approach and the need for standardized protocols. It concludes that while significant advancements have been made, further research is necessary to fully understand the correlation between imaging findings and clinical outcomes. The continued evolution of radiological approaches is expected to significantly improve patient care and outcomes in AO.

Optimizing computed tomography image reconstruction for focal hepatic lesions: Deep learning image reconstruction vs iterative reconstruction

Background

Deep learning image reconstruction (DLIR) is a novel computed tomography (CT) reconstruction technique that minimizes image noise, enhances image quality, and enables radiation dose reduction. This study aims to compare the diagnostic performance of DLIR and iterative reconstruction (IR) in the evaluation of focal hepatic lesions.

Methods

We conducted a retrospective study of 216 focal hepatic lesions in 109 adult participants who underwent abdominal CT scanning at our institution. We used DLIR (low, medium, and high strength) and IR (0 %, 10 %, 20 %, and 30 %) techniques for image reconstruction. Four experienced abdominal radiologists independently evaluated focal hepatic lesions based on five qualitative aspects (lesion detectability, lesion border, diagnostic confidence level, image artifact, and overall image quality). Quantitatively, we measured and compared the level of image noise for each technique at the liver and aorta.

Results

There were significant differences (p < 0.001) among the seven reconstruction techniques in terms of lesion borders, image artifacts, and overall image quality. Low-strength DLIR (DLIR-L) exhibited the best overall image quality. Although high-strength DLIR (DLIR-H) had the least image noise and fewest artifacts, it also had the lowest scores for lesion borders and overall image quality. Image noise showed a weak to moderate positive correlation with participants' body mass index and waist circumference.

Conclusions

The optimal-strength DLIR significantly improved overall image quality for evaluating focal hepatic lesions compared to the IR technique. DLIR-L achieved the best overall image quality while maintaining acceptable levels of image noise and quality of lesion borders.

An Analysis of Computed Tomography Diagnostic Reference Levels in India Compared to Other Countries

Computed Tomography (CT) is vital for diagnosing and monitoring medical conditions. However, increased usage raises concerns about patient radiation exposure. Diagnostic Reference Levels (DRLs) aim to minimize radiation doses in CT imaging. This study examines CT DRLs in India compared to other countries to identify optimization opportunities. A literature review was conducted to gather data from published studies, guidelines, and regulatory authorities. Findings show significant international variations in CT DRLs, with differences up to 50%. In India, DRLs also vary significantly across states. For head CT exams, Indian DRLs are generally 20-30% lower than international standards (27-47 mGy vs. 60 mGy). Conversely, for abdominal CT scans, Indian DRLs are 10-15% higher (12-16 mGy vs. 13 mGy). Factors influencing DRL variations include equipment differences, imaging protocols, patient demographics, and regulatory conditions. Dose-optimization techniques like automatic exposure control and iterative reconstruction can reduce radiation exposure by 25-60% while maintaining image quality. Comparative data highlight best practices, such as the United Kingdom's 30% reduction in CT doses from 1984 to 1995 via DRL implementation. This study suggests that adopting similar practices in India could reduce radiation doses by 20-40% for common CT procedures, promoting responsible CT usage and minimizing patient exposure.

Exploring CT pixel and voxel size effect on anatomic modeling in mandibular reconstruction

BACKGROUND

Computer-aided modeling and design (CAM/CAD) of patient anatomy from computed tomography (CT) imaging and 3D printing technology enable the creation of tangible, patient-specific anatomic models that can be used for surgical guidance. These models have been associated with better patient outcomes; however, a lack of CT imaging guidelines risks the capture of unsuitable imaging for patient-specific modeling. This study aims to investigate how CT image pixel size (X-Y) and slice thickness (Z) impact the accuracy of mandibular models.

METHODS

Six cadaver heads were CT scanned at varying slice thicknesses and pixel sizes and turned into CAD models of the mandible for each scan. The cadaveric mandibles were then dissected and surface scanned, producing a CAD model of the true anatomy to be used as the gold standard for digital comparison. The root mean square (RMS) value of these comparisons, and the percentage of points that deviated from the true cadaveric anatomy by over 2.00 mm were used to evaluate accuracy. Two-way ANOVA and Tukey-Kramer post-hoc tests were used to determine significant differences in accuracy.

RESULTS

Two-way ANOVA demonstrated significant difference in RMS for slice thickness but not pixel size while post-hoc testing showed a significant difference in pixel size only between pixels of 0.32 mm and 1.32 mm. For slice thickness, post-hoc testing revealed significantly smaller RMS values for scans with slice thicknesses of 0.67 mm, 1.25 mm, and 3.00 mm compared to those with a slice thickness of 5.00 mm. No significant differences were found between 0.67 mm, 1.25 mm, and 3.00 mm slice thicknesses. Results for the percentage of points deviating from cadaveric anatomy greater than 2.00 mm agreed with those for RMS except when comparing pixel sizes of 0.75 mm and 0.818 mm against 1.32 mm in post-hoc testing, which showed a significant difference as well.

CONCLUSION

This study suggests that slice thickness has a more significant impact on 3D model accuracy than pixel size, providing objective validation for guidelines favoring rigorous standards for slice thickness while recommending isotropic voxels. Additionally, our results indicate that CT scans up to 3.00 mm in slice thickness may provide an adequate 3D model for facial bony anatomy, such as the mandible, depending on the clinical indication.

Diagnostic performance and image quality of an image-based denoising algorithm applied to radiation dose-reduced CT in diagnosing acute appendicitis

PURPOSE

To evaluate diagnostic performance and image quality of ultralow-dose CT (ULDCT) in diagnosing acute appendicitis with an image-based deep-learning denoising algorithm (IDLDA).

METHODS

This retrospective multicenter study included 180 patients (mean ± standard deviation, 29 ± 9 years; 91 female) who underwent contrast-enhanced 2-mSv CT for suspected appendicitis from February 2014 to August 2016. We simulated ULDCT from 2-mSv CT, reducing the dose by at least 50%. Then we applied an IDLDA on ULDCT to produce denoised ULDCT (D-ULDCT). Six radiologists with different experience levels (three board-certified radiologists and three residents) independently reviewed the ULDCT and D-ULDCT. They rated the likelihood of appendicitis and subjective image qualities (subjective image noise, diagnostic acceptability, and artificial sensation). One radiologist measured image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). We used the receiver operating characteristic (ROC) analyses, Wilcoxon's signed-rank tests, and paired t-tests.

RESULTS

The area under the ROC curves (AUC) for diagnosing appendicitis ranged 0.90-0.97 for ULDCT and 0.94-0.97 for D-ULDCT. The AUCs of two residents were significantly higher on D-ULDCT (AUC difference = 0.06 [95% confidence interval, 0.01-0.11; p = .022] and 0.05 [0.00-0.10; p = .046], respectively). D-ULDCT provided better subjective image noise and diagnostic acceptability to all six readers. However, the response of board-certified radiologists and residents differed in artificial sensation (all p ≤ .003). D-ULDCT showed significantly lower image noise, higher SNR, and higher CNR (all p < .001).

CONCLUSION

An IDLDA can provide better ULDCT image quality and enhance diagnostic performance for less-experienced radiologists.

Low Dose Iodinated Contrast Material and Radiation for Virtual Monochromatic Imaging in Craniocervical Dual-Layer Spectral Detector Computed Tomography Angiography: A Prospective and Randomized Study

RATIONALE AND OBJECTIVES

To investigate the feasibility of virtual monochromatic imaging (VMI) of dual-layer spectral detector computed tomography (SDCT) to reduce iodinated contrast material (CM) and radiation dose in craniocervical computed tomography angiography (CTA).

MATERIALS AND METHODS

A total of 280 consecutively selected patients performed craniocervical CTA with SDCT were prospectively selected and randomly divided into four groups (A, DoseRight index (DRI) 31, iopromide 370mgI/mL, volume 0.8 mL/kg; B, DRI 26, iopromide 370mgI/mL, volume 0.4 mL/kg; C, DRI 26, ioversol 320mgI/mL, volume 0.4 mL/kg; D, DRI 26, iohexol 300mgI/mL, volume 0.4 mL/kg). 50-70 kiloelectron volts (keV) VMIs in group B were reconstructed and compared to group A to select the optimal keV. Then, the optimal keV in groups B, C and D was reconstructed and compared. Objective image quality, including vascular attenuation, image noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), was evaluated. Subjective image quality was assessed using a 5-point Likert scale. In addition, the effective dose (ED), iodine load and iodine delivery rate (IDR) were compared between groups A and D.

RESULTS

55 keV VMI was the optimal VMI in group B. The objective and subjective image quality of 55 keV VMI in group B were equal to or better than those of the CI in group A. The SNR, CNR and subjective image quality in group D were similar to those in group B (P > 0.05). The ED, iodine load and IDR of group D were reduced by 44%, 59% and 19%, respectively, when compared to those of group A.

CONCLUSION

Low dose iodinated CM and radiation for 55 keV VMI in craniocervical CTA using SDCT could still provide equivalent or better image quality than the conventional scanning protocol.

Task-based automatic keV selection: leveraging routine virtual monoenergetic imaging for dose reduction on clinical photon-counting detector CT. Phys Med Biol 2024;69:10.1088/1361-6560/ad41b3. [PMID: 38648795 PMCID: PMC11108732 DOI: 10.1088/1361-6560/ad41b3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Objective. Photon-counting detector (PCD) CT enables routine virtual-monoenergetic image (VMI) reconstruction. We evaluated the performance of an automatic VMI energy level (keV) selection tool on a clinical PCD-CT system in comparison to an automatic tube potential (kV) selection tool from an energy-integrating-detector (EID) CT system from the same manufacturer.Approach.Four torso-shaped phantoms (20-50 cm width) containing iodine (2, 5, and 10 mg cc-1) and calcium (100 mg cc-1) were scanned on PCD-CT and EID-CT. Dose optimization techniques, task-based VMI energy level and tube-potential selection on PCD-CT (CARE keV) and task-based tube potential selection on EID-CT (CARE kV), were enabled. CT numbers, image noise, and dose-normalized contrast-to-noise ratio (CNRd) were compared.Main results. PCD-CT produced task-specific VMIs at 70, 65, 60, and 55 keV for non-contrast, bone, soft tissue with contrast, and vascular settings, respectively. A 120 kV tube potential was automatically selected on PCD-CT for all scans. In comparison, EID-CT used x-ray tube potentials from 80 to 150 kV based on imaging task and phantom size. PCD-CT achieved consistent dose reduction at 9%, 21% and 39% for bone, soft tissue with contrast, and vascular tasks relative to the non-contrast task, independent of phantom size. On EID-CT, dose reduction factor for contrast tasks relative to the non-contrast task ranged from a 65% decrease (vascular task, 70 kV, 20 cm phantom) to a 21% increase (soft tissue with contrast task, 150 kV, 50 cm phantom) due to size-specific tube potential adaptation. PCD-CT CNRdwas equivalent to or higher than those of EID-CT for all tasks and phantom sizes, except for the vascular task with 20 cm phantom, where 70 kV EID-CT CNRdoutperformed 55 keV PCD-CT images.Significance. PCD-CT produced more consistent CT numbers compared to EID-CT due to standardized VMI output, which greatly benefits standardization efforts and facilitates radiation dose reduction.

Which is a real valuable screening tool for lung cancer and measure thoracic diseases, chest radiography or low-dose computed tomography?: A review on the current status of Japan and other countries

Chest radiography (CR) has been used as a screening tool for lung cancer and the use of low-dose computed tomography (LDCT) is not recommended in Japan. We need to reconsider whether CR really contributes to the early detection of lung cancer. In addition, we have not well discussed about other major thoracic disease detection by CR and LDCT compared with lung cancer despite of its high frequency. We review the usefulness of CR and LDCT as veridical screening tools for lung cancer and other thoracic diseases. In the case of lung cancer, many studies showed that LDCT has capability of early detection and improving outcomes compared with CR. Recent large randomized trial also supports former results. In the case of chronic obstructive pulmonary disease (COPD), LDCT contributes to early detection and leads to the implementation of smoking cessation treatments. In the case of pulmonary infections, LDCT can reveal tiny inflammatory changes that are not observed on CR, though many of these cases improve spontaneously. Therefore, LDCT screening for pulmonary infections may be less useful. CR screening is more suitable for the detection of pulmonary infections. In the case of cardiovascular disease (CVD), CR may be a better screening tool for detecting cardiomegaly, whereas LDCT may be a more useful tool for detecting vascular changes. Therefore, the current status of thoracic disease screening is that LDCT may be a better screening tool for detecting lung cancer, COPD, and vascular changes. CR may be a suitable screening tool for pulmonary infections and cardiomegaly.

Comparison of Low-Dose Computed Tomography Versus Conventional-Dose Computed Tomography in the Evaluation of Distal Radius Fractures

BACKGROUND

Distal radius fractures (DRFs) are common upper extremity fractures and often require surgical fixation when they are intraarticular. Preoperative computed tomography (CT) has emerged as a surgical planning tool to evaluate intraarticular DRFs. Although CT affords additional details, patients receive higher radiation doses than standard radiographs. We aim to develop a low-dose CT (LDCT) protocol, relative to the institutional standard-dose CT wrist for intraarticular DRFs although providing adequate detail for surgical decision-making.

METHODS

A single-institution prospective study was conducted on patients with intraarticular DRFs who underwent closed reduction and below-elbow splinting who otherwise would undergo wrist CT. Observations were defined as total measurements taken, with each view undergoing 44 measurements. Patients underwent 2 scans with a standard dose and a 10× dose reduction. Articular step and gap measurements were recorded in the sagittal and coronal images.

RESULTS

A total of 11 patients were enrolled (7 women and 4 men). The mean age was 55 years (SD = 20.1). There were a total of 4 reviewers: 1 attending surgeon, 2 resident physicians, and 1 student. When comparing LDCT and conventional-dose CT (CDCT), there were no significant differences in step and gap measurements across all reviewers.

CONCLUSION

This study demonstrated that LDCT provides comparable imaging quality for surgical planning as a CDCT without significant diagnostic decay in the setting of DRFs. This comes with the added benefit of a 10-fold reduction in radiation exposure. These results suggest that LDCT is an opportunity to reduce effective radiation in patients although providing beneficial preoperative imaging.

Deep learning-based algorithms for low-dose CT imaging: A review

The computed tomography (CT) technique is extensively employed as an imaging modality in clinical settings. The radiation dose of CT, however, is significantly high, thereby raising concerns regarding the potential radiation damage it may cause. The reduction of X-ray exposure dose in CT scanning may result in a significant decline in imaging quality, thereby elevating the risk of missed diagnosis and misdiagnosis. The reduction of CT radiation dose and acquisition of high-quality images to meet clinical diagnostic requirements have always been a critical research focus and challenge in the field of CT. Over the years, scholars have conducted extensive research on enhancing low-dose CT (LDCT) imaging algorithms, among which deep learning-based algorithms have demonstrated superior performance. In this review, we initially introduced the conventional algorithms for CT image reconstruction along with their respective advantages and disadvantages. Subsequently, we provided a detailed description of four aspects concerning the application of deep neural networks in LDCT imaging process: preprocessing in the projection domain, post-processing in the image domain, dual-domain processing imaging, and direct deep learning-based reconstruction (DLR). Furthermore, an analysis was conducted to evaluate the merits and demerits of each method. The commercial and clinical applications of the LDCT-DLR algorithm were also presented in an overview. Finally, we summarized the existing issues pertaining to LDCT-DLR and concluded the paper while outlining prospective trends for algorithmic advancement.

Reducing image artifacts in sparse projection CT using conditional generative adversarial networks

Reducing the amount of projection data in computed tomography (CT), specifically sparse-view CT, can reduce exposure dose; however, image artifacts can occur. We quantitatively evaluated the effects of conditional generative adversarial networks (CGAN) on image quality restoration for sparse-view CT using simulated sparse projection images and compared them with autoencoder (AE) and U-Net models. The AE, U-Net, and CGAN models were trained using pairs of artifacts and original images; 90% of patient cases were used for training and the remaining for evaluation. Restoration of CT values was evaluated using mean error (ME) and mean absolute error (MAE). The image quality was evaluated using structural image similarity (SSIM) and peak signal-to-noise ratio (PSNR). Image quality improved in all sparse projection data; however, slight deformation in tumor and spine regions was observed, with a dispersed projection of over 5°. Some hallucination regions were observed in the CGAN results. Image resolution decreased, and blurring occurred in AE and U-Net; therefore, large deviations in ME and MAE were observed in lung and air regions, and the SSIM and PSNR results were degraded. The CGAN model achieved accurate CT value restoration and improved SSIM and PSNR compared to AE and U-Net models.

Advancing Cochlear Implant Programming: X-ray Guided Anatomy-Based Fitting

BACKGROUND

Anatomy-based fitting (ABF) is a new research area in the field of cochlear implants (CIs). Despite the reported benefits and acceptable levels of ABF among CI recipients, some limitations remain, like the postoperative computed tomography (CT) scan, which is preferred for confirming electrode array insertion.

OBJECTIVE

This study aimed to investigate the feasibility of using plain film radiography (X-ray) for postoperative electrode detection and for building ABF as an alternative to CT.

METHODS

A total of 53 ears with CI were studied. All cases had routine post-insertion X-rays in the cochlear view and additionally underwent postoperative CT. The insertion angles and center frequencies measured by two independent observers were compared for each imaging modality. The angular insertion depth and center frequencies resulting from the X-ray and CT scans were then compared.

RESULTS

No significant differences were observed between the X-ray- and CT-measured angles for the electrode contacts. Radiographic measurements between the two readers showed an almost perfect (≥0.8) or substantial (0.71) intraclass correlation coefficient along the electrode contacts. X-ray images showed a mean difference of 4.7 degrees from CT. The mean semitone deviation of the central frequency between the CT and X-ray images was 0.6.

CONCLUSIONS

X-ray imaging provides a valid and easy-to-perform alternative to CT imaging, with less radiation exposure and lower costs. The radiographs showed excellent concordance with the CT-measured angular insertion depth and consequently with the central frequency for most electrode contacts. Therefore, plain X-ray could be a viable alternative in building ABF for the CI recipients.

Deep learning reconstruction improves the image quality of low-dose temporal bone CT with otitis media and mastoiditis patients

Objective

To evaluate the image quality of low-dose temporal bone computed tomography (CT) in otitis media and mastoiditis patients by using deep learning reconstruction (DLR).

Materials and methods

A total of ninety-seven temporal bones from 53 consecutive adult patients who had suspected otitis media and mastoiditis and underwent temporal bone CT were prospectively enrolled. All patients underwent high resolution CT protocol (group A) and an additional low-dose protocol (group B). In group A, high resolution data were reconstructed by filter back projection (FBP). In group B, low-dose data were reconstructed by DLR mild (B1), DLR standard (B2) and DLR strong (B3). The objective image quality was analyzed by measuring the CT value and image noise on the transverse image and calculating the signal-to-noise ratio (SNR) on incudomallear joint, retroauricular muscle, vestibule and subcutaneous fat. Subjective image quality was analyzed by using a five-point scale to evaluate nine anatomical structures of middle and inner ear. The number of temporal bone lesions which involved in five structures of middle ear were assessed in group A, B1, B2 and B3 images.

Results

There were no significant differences in the CT values of the four reconstruction methods at four structures (all p > 0.05). The DLR group B1, B2 and B3 had significantly less image noise and a significantly higher SNR than group A at four structures (all p < 0.001). The group B1 had comparable subjective image quality as group A in nine structures (all p > 0.05), however, the group B3 had lower subjective image quality than group A in modiolus, spiral osseous lamina and stapes (all p < 0.001), the group B2 had lower subjective image quality than group A in modiolus and spiral osseous lamina (both p < 0.05). The number of temporal bone lesions which involved in five structures for group A, B1 and B2 images were no significant difference (all p > 0.05), however, the number of temporal bone lesions which involved in mastoid for group B3 images were significantly more than group A (p < 0.05). The radiation dose of high resolution CT protocol and low-dose protocol were 0.55 mSv and 0.11 mSv, respectively.

Conclusion

Compared with high resolution CT protocol, in the low-dose protocol of temporal bone CT, DLR mild and standard could improve the objective image quality, maintain good subjective image quality and satisfy clinical diagnosis of otitis media and mastoiditis patients.

Reject Analysis in Digital Radiography and Computed Tomography: A Belgian Imaging Department Case Study

Objective

Reject analysis is usually performed in digital radiography (DR) for quality assurance. Data for computed tomography (CT) rejects remains sparse. The aim of this study is to help provide a straightforward benchmark for reject analysis of both DR and CT.

Materials and methods

This retrospective observational study included 107,277 DR and 20,659 CT during 18 months in a tertiary care center. Rejected acquisitions were retrieved by Dose Archiving and Communication System (DACS). The DR and CT reject analysis included reject rates, reasons for rejection and supplementary radiation dose associated with these rejects.

Results

8,904 rejected DR and 514 rejected CT were retrieved. The DR reject rate was 8.3% whereas the CT reject rate was 2.5%. The cumulative effective dose (ED) of DR rejects was 377.3 mSv while the cumulative ED of CT rejects was 1267.4 mSv. The major reason for rejects was positioning for both DR (61%) and CT (44%).

Conclusion

This study helps constitute a simple reproducible method to analyze both DR and CT rejects simultaneously. Although CT rejects are less often monitored than DR rejects, the radiation dose associated with CT rejects is much higher, which emphasizes the need to systematically monitor both DR and CT rejects. Investigating the reasons and the most frequently rejected examinations gives an opportunity for improvement of imaging techniques in cooperation with technologists.

Photon-counting detector CT allows significant reduction in radiation dose while maintaining image quality and noise on non-contrast chest CT

Purpose

To investigate if clinical non-contrast chest CT studies obtained with PCD CT using much lower radiation exposure can achieve the same image quality as with the currently established EID protocol.

Materials/methods

A total of seventy-one patients were identified who had a non-contrast chest computed tomography (CT) done on PCD CT and EID CT scanners within a 4-month interval. Five fellowship trained chest radiologists, blinded to the scanner details were asked to review the cases side-by-side and record their preference for images from either the photon-counting-detector (PCD) CT or the energy-integrating detector (EID) CT scanner.

Results

The median CTDIvol for PCD-CT system was 4.710 mGy and EID system was 7.80 mGy (p < 0.001). The median DLP with the PCD-CT was 182.0 mGy.cm and EID system was 262.60 mGy.cm (p < 0.001). The contrast to noise ratio (CNR) was superior on the PCD-CT system 59.2 compared to the EID-CT 53.3; (p < 0.001). Kappa-statistic showed that there was poor agreement between the readers over the image quality from the PCD and EID scanners (κ = 0.19; 95 % CI: 0.12 - 0.27; p < 0.001). Chi-square analysis revealed that 3 out of 5 readers showed a significant preference for images from the PCDCT (p ≤ 0.012). There was no significant difference in the preferences of two readers between EID-CT and PCD-CT images.

Conclusion

The first clinical PCD-CT system allows a significant reduction in radiation exposure while maintaining image quality and image noise using a standardized non-contrast chest CT protocol.

Machine Learned Texture Prior From Full-Dose CT Database via Multi-Modality Feature Selection for Bayesian Reconstruction of Low-Dose CT

In our earlier study, we proposed a regional Markov random field type tissue-specific texture prior from previous full-dose computed tomography (FdCT) scan for current low-dose CT (LdCT) imaging, which showed clinical benefits through task-based evaluation. Nevertheless, two assumptions were made for early study. One assumption is that the center pixel has a linear relationship with its nearby neighbors and the other is previous FdCT scans of the same subject are available. To eliminate the two assumptions, we proposed a database assisted end-to-end LdCT reconstruction framework which includes a deep learning texture prior model and a multi-modality feature based candidate selection model. A convolutional neural network-based texture prior is proposed to eliminate the linear relationship assumption. And for scenarios in which the concerned subject has no previous FdCT scans, we propose to select one proper prior candidate from the FdCT database using multi-modality features. Features from three modalities are used including the subjects' physiological factors, the CT scan protocol, and a novel feature named Lung Mark which is deliberately proposed to reflect the z-axial property of human anatomy. Moreover, a majority vote strategy is designed to overcome the noise effect from LdCT scans. Experimental results showed the effectiveness of Lung Mark. The selection model has accuracy of 84% testing on 1,470 images from 49 subjects. The learned texture prior from FdCT database provided reconstruction comparable to the subjects having corresponding FdCT. This study demonstrated the feasibility of bringing clinically relevant textures from available FdCT database to perform Bayesian reconstruction of any current LdCT scan.

The variability of CT scan protocols for total hip arthroplasty: a call for harmonisation

CT is the principal imaging modality used for the pre-operative 3D planning and assessment of total hip arthroplasty (THA). The image quality offered by CT has a radiation penalty to the patient. Higher than necessary radiation exposure is of particular concern when imaging young patients and women of childbearing age, due to the greater risk of radiation-induced cancer in this group. A harmonised low-dose CT protocol is needed, evidenced by the huge variability in the 17 protocols reviewed. The majority of the protocols were incomplete, leading to uncertainty among radiographers when performing the scans. Only three protocols (20%) were optimised for both 'field of view' and image acquisition parameters. 10 protocols (60%) were optimised for 'field of view' only. These protocols included imaging of the relevant landmarks in the bony pelvis in addition to the knees - the reference for femoral anteversion. CT parameters, including the scanner kilovoltage (kV), milliamperage-time product (mAs) and slice thickness, must be optimised with a 'field of view' that includes the relevant bony landmarks. The recommended kV and mAs values were very wide ranging from 100 to 150 and from 100 to 250, respectively. The large variability that exists amongst the CT protocols illustrates the need for a more consistent low-dose CT protocol for the planning of THA. This must provide an optimal balance between image quality and radiation dose to the patient. Current CT scanners do not allow for measurements of functional pelvic orientation and additional upright imaging modalities are needed to augment them.

Implementation of AI image reconstruction in CT-how is it validated and what dose reductions can be achieved

CT reconstruction has undergone a substantial change over the last decade with the introduction of iterative reconstruction (IR) and now with deep learning reconstruction (DLR). In this review, DLR will be compared to IR and filtered back-projection (FBP) reconstructions. Comparisons will be made using image quality metrics such as noise power spectrum, contrast-dependent task-based transfer function, and non-prewhitening filter detectability index (dNPW'). Discussion on how DLR has impacted CT image quality, low-contrast detectability, and diagnostic confidence will be provided. DLR has shown the ability to improve in areas that IR is lacking, namely: noise magnitude reduction does not alter noise texture to the degree that IR did, and the noise texture found in DLR is more aligned with noise texture of an FBP reconstruction. Additionally, the dose reduction potential for DLR is shown to be greater than IR. For IR, the consensus was dose reduction should be limited to no more than 15-30% to preserve low-contrast detectability. For DLR, initial phantom and patient observer studies have shown acceptable dose reduction between 44 and 83% for both low- and high-contrast object detectability tasks. Ultimately, DLR is able to be used for CT reconstruction in place of IR, making it an easy "turnkey" upgrade for CT reconstruction. DLR for CT is actively being improved as more vendor options are being developed and current DLR options are being enhanced with second generation algorithms being released. DLR is still in its developmental early stages, but is shown to be a promising future for CT reconstruction.

A retrospective survey to establish institutional diagnostic reference levels for CT urography examinations based on clinical indications: preliminary results

Objective. To establish institutional diagnostic reference levels (IDRLs) based on clinical indications (CIs) for three- and four-phase computed tomography urography (CTU).Methods. Volumetric computed tomography dose index (CTDIvol), dose-length product (DLP), patients' demographics, selected CIs like lithiasis, cancer, and other diseases, and protocols' parameters were retrospectively recorded for 198 CTUs conducted on a Toshiba Aquilion Prime 80 scanner. Patients were categorised based on CIs and number of phases. These groups' 75th percentiles of CTDIvoland DLP were proposed as IDRLs. The mean, median and IDRLs were compared with previously published values.Results. For the three-phase protocol, the CTDIvol(mGy) and DLP (mGy.cm) were 22.7/992 for the whole group, 23.4/992 for lithiasis, 22.8/1037 for cancer, and 21.2/981 for other diseases. The corresponding CTDIvol(mGy) and DLP (mGy.cm) values for the four-phase protocol were 28.6/1172, 30.6/1203, 27.3/1077, and 28.7/1252, respectively. A significant difference was found in CTDIvoland DLP between the two protocols, among the phases of three-phase (except cancer) and four-phase protocols (except DLP for other diseases), and in DLP between the second and third phases (except for cancer group). The results are comparable or lower than most studies published in the last decade.Conclusions. The CT technologist must be aware of the critical dose dependence on the scan length and the applied exposure parameters for each phase, according to the patient's clinical background and the corresponding imaging anatomy, which must have been properly targeted by the competent radiologist. When clinically feasible, restricting the number of phases to three instead of four could remarkably reduce the patient's radiation dose. CI-based IDRLs will serve as a baseline for comparison with CTU practice in other hospitals and could contribute to national DRL establishment. The awareness and knowledge of dose levels during CTU will prompt optimisation strategies in CT facilities.

Tradeoffs between Radiation Exposure to the Lens of the Eyes and Diagnostic Image Quality in Pediatric Brain Computed Tomography

Background

Computed tomography (CT) of the brain is associated with radiation exposure to the lens of the eyes. Therefore, it is necessary to optimize scan settings to keep radiation exposure as low as reasonably achievable without compromising diagnostic image information. The aim of this study was to compare the effectiveness of the five practical techniques for lowering eye radiation exposure and their effects on diagnostic image quality in pediatric brain CT.

Methods

The following scan protocols were performed: reference scan, 0.06-mm Pbeq bismuth shield, 30% globally lowering tube current (GLTC), reducing tube voltage (RTV) from 120 to 90 kVp, gantry tilting, and combination of gantry tilting with bismuth shielding. Radiation measurements were performed using thermoluminescence dosimeters. Objective and subjective image quality was evaluated.

Results

All strategies significantly reduced eye dose, and increased the posterior fossa artifact index and the temporal lobe artifact index, relative to the reference scan. GLTC and RTV increased image noise, leading to a decrease signal-to-noise ratio and contrast-to-noise ratio. Except for bismuth shielding, subjective image quality was relatively the same as the reference scan.

Conclusions

Gantry tilting may be the most effective method for reducing eye radiation exposure in pediatric brain CT. When the scanner does not support gantry tilting, GLTC might be an alternative.

An Overview on the Alignment of Radiation Protection in Computed Tomography with Maqasid al-Shari'ah in the Context of al-Dharuriyat

The increasing utilisation of computed tomography (CT) in the medical field has raised a greater concern regarding the radiation-induced health effects as CT imposes high radiation risks on the exposed individual. Adherence to radiation protection measures in CT as endorsed by regulatory bodies; justification, optimisation and dose limit, is essential to minimise radiation risks. Islam values every human being and Maqasid al-Shari'ah helps to protect human beings through its sacred principles which aim to fulfil human beings' benefits (maslahah) and prevent mischief (mafsadah). Alignment of the concept of radiation protection in CT within the framework of al-Dharuriyat; protection of faith or religion (din), protection of life (nafs), protection of lineage (nasl), protection of intellect ('aql) and protection of property (mal) is essential. This strengthens the concept and practices of radiation protection in CT among radiology personnel, particularly Muslim radiographers. The alignment provides supplementary knowledge towards the integration of knowledge fields between Islamic worldview and radiation protection in medical imaging, particularly in CT. This paper is hoped to set a benchmark for future studies on the integration of knowledge between the Islamic worldview and radiation protection in medical imaging in terms of other classifications of Maqasid al-Shari'ah; al-Hajiyat and al-Tahsiniyat.

Effects of ionizing radiation exposure during pregnancy

PURPOSE

To review the effects of ionizing radiation to the conceptus and the relationship to the timing of the exposure during pregnancy. To consider strategies that would mitigate potential harms associated with exposure to ionizing radiation during pregnancy.

METHODS

Data reported in the peer-reviewed literature on entrance KERMA received from specific radiological examinations were combined with published results from experiment or Monte Carlo modeling of tissue and organ doses per entrance KERMA to estimate total doses that could be received from specific procedures. Data reported in the peer-reviewed literature on dose mitigation strategies, best practices for shielding, consent, counseling and emerging technologies were reviewed.

RESULTS

For procedures utilizing ionizing radiation for which the conceptus is not included in the primary radiation beam, typical doses are well below the threshold for causing tissue reactions and the risk of induction of childhood cancer is low. For procedures that include the conceptus in the primary radiation field, longer fluoroscopic interventional procedures or multiphase/multiple exposures potentially could approach or exceed thresholds for tissue reactions and the risk of cancer induction must be weighed against the expected risk/benefit of performing (or not) the imaging examination. Gonadal shielding is no longer considered best practice. Emerging technologies such as whole-body DWI/MRI, dual-energy CT and ultralow dose studies are gaining importance for overall dose reduction strategies.

CONCLUSION

The ALARA principle, considering potential benefits and risks should be followed with respect to the use of ionizing radiation. Nevertheless, as Wieseler et al. (2010) state, "no examination should be withheld when an important clinical diagnosis is under consideration." Best practices require updates on current available technologies and guidelines.

Making CT Dose Monitoring Meaningful: Augmenting Dose with Imaging Quality

Due to the concerns about radiation dose associated with medical imaging, radiation dose monitoring systems (RDMSs) are now utilized by many radiology providers to collect, process, analyze, and manage radiation dose-related information. Currently, most commercially available RDMSs focus only on radiation dose information and do not track any metrics related to image quality. However, to enable comprehensive patient-based imaging optimization, it is equally important to monitor image quality as well. This article describes how RDMS design can be extended beyond radiation dose to simultaneously monitor image quality. A newly designed interface was evaluated by different groups of radiology professionals (radiologists, technologists, and physicists) on a Likert scale. The results show that the new design is effective in assessing both image quality and safety in clinical practices, with an overall average score of 7.8 out of 10.0 and scores ranging from 5.5 to 10.0. Radiologists rated the interface highest at 8.4 out of 10.0, followed by technologists at 7.6 out of 10.0, and medical physicists at 7.5 out of 10.0. This work demonstrates how the assessment of the radiation dose can be performed in conjunction with the image quality using customizable user interfaces based on the clinical needs associated with different radiology professions.

Comparison of Coronary Computed Tomography Angiography Image Quality With High-concentration and Low-concentration Contrast Agents: The Randomized CONCENTRATE Trial

PURPOSE

To confirm that the image quality of coronary computed tomography (CT) angiography with a low tube voltage (80 to 100 kVp), iterative reconstruction, and low-concentration contrast agents (iodixanol 270 to 320 mgI/mL) was not inferior to that with conventional high tube voltage (120 kVp) and high-concentration contrast agent (iopamidol 370 mgI/mL).

MATERIALS AND METHODS

This prospective, multicenter, noninferiority, randomized trial enrolled a total of 318 patients from 8 clinical sites. All patients were randomly assigned 1: 1: 1 for each contrast medium of 270, 320, and 370 mgI/mL. CT scans were taken with a standard protocol in the high-concentration group (370 mgI/mL) and with 20 kVp lower protocol in the low-concentration group (270 or 320 mgI/mL). Image quality and radiation dose were compared between the groups. Image quality was evaluated with a score of 1 to 4 as subject image quality.

RESULTS

The mean HU, signal-to-noise ratio, and contrast-to-noise ratio of the 3 groups were significantly different (all P<0.0001). The signal-to-noise ratio and contrast-to-noise ratio of the low-concentration groups were significantly lower than those of the high-concentration group (P<0.05). However, the image quality scores were not significantly different among the 3 groups (P=0.745). The dose length product and effective dose of the high-concentration group were significantly higher than those of the low-concentration group (P<0.0001 and 0.003, respectively).

CONCLUSIONS

The CT protocol with iterative reconstruction and lower tube voltage for low-concentration contrast agents significantly reduced the effective radiation dose (mean: 3.7±2.7 to 4.1±3.1 mSv) while keeping the subjective image quality as good as the standard protocol (mean: 5.7±3.4 mSv).

Technical note: Phantom-based training framework for convolutional neural network CT noise reduction

BACKGROUND

Deep artificial neural networks such as convolutional neural networks (CNNs) have been shown to be effective models for reducing noise in CT images while preserving anatomic details. A practical bottleneck for developing CNN-based denoising models is the procurement of training data consisting of paired examples of high-noise and low-noise CT images. Obtaining these paired data are not practical in a clinical setting where the raw projection data is not available. This work outlines a technique to optimize CNN denoising models using methods that are available in a routine clinical setting.

PURPOSE

To demonstrate a phantom-based training framework for CNN noise reduction that can be efficiently implemented on any CT scanner.

METHODS

The phantom-based training framework uses supervised learning in which training data are synthesized using an image-based noise insertion technique. Ten patient image series were used for training and validation (9:1) and noise-only images obtained from anthropomorphic phantom scans. Phantom noise-only images were superimposed on patient images to imitate low-dose CT images for use in training. A modified U-Net architecture was used with mean-squared-error and feature reconstruction loss. The training framework was tested for clinically indicated whole-body-low-dose CT images, as well as routine abdomen-pelvis exams for which projection data was unavailable. Performance was assessed based on root-mean-square error, structural similarity, line profiles, and visual assessment.

RESULTS

When the CNN was tested on five reserved quarter-dose whole-body-low-dose CT images, noise was reduced by 75%, root-mean-square-error reduced by 34%, and structural similarity increased by 60%. Visual analysis and line profiles indicated that the method significantly reduced noise while maintaining spatial resolution of anatomic features.

CONCLUSION

The proposed phantom-based training framework demonstrated strong noise reduction while preserving spatial detail. Because this method is based within the image domain, it can be easily implemented without access to projection data.

Convolutional Encoder-Decoder Networks for Volumetric Computed Tomography Surviews from Single- and Dual-View Topograms

Computed tomography (CT) is an extensively used imaging modality capable of generating detailed images of a patient's internal anatomy for diagnostic and interventional procedures. High-resolution volumes are created by measuring and combining information along many radiographic projection angles. In current medical practice, single and dual-view two-dimensional (2D) topograms are utilized for planning the proceeding diagnostic scans and for selecting favorable acquisition parameters, either manually or automatically, as well as for dose modulation calculations. In this study, we develop modified 2D to three-dimensional (3D) encoder-decoder neural network architectures to generate CT-like volumes from single and dual-view topograms. We validate the developed neural networks on synthesized topograms from publicly available thoracic CT datasets. Finally, we assess the viability of the proposed transformational encoder-decoder architecture on both common image similarity metrics and quantitative clinical use case metrics, a first for 2D-to-3D CT reconstruction research. According to our findings, both single-input and dual-input neural networks are able to provide accurate volumetric anatomical estimates. The proposed technology will allow for improved (i) planning of diagnostic CT acquisitions, (ii) input for various dose modulation techniques, and (iii) recommendations for acquisition parameters and/or automatic parameter selection. It may also provide for an accurate attenuation correction map for positron emission tomography (PET) with only a small fraction of the radiation dose utilized.

Imaging of penetrating vascular trauma of the body and extremities secondary to ballistic and stab wounds

In the United States, gunshot wounds (GSWs) have become a critical public health concern with substantial annual morbidity, disability, and mortality. Vascular injuries associated with GSW may pose a clinical challenge to the physicians in the emergency department. Patients demonstrating hard signs require immediate intervention, whereas patients with soft signs can undergo further diagnostic testing for better injury delineation. Although digital subtraction angiography is the gold standard modality to assess vascular injuries, non-invasive techniques such as Doppler ultrasound, computed tomography angiography, and magnetic resonance angiography have evolved as appropriate alternatives. This article discusses penetrating bodily vascular injuries, specifically ballistic and stab wounds, and the corresponding radiological presentations.

Evaluating the Outcome of an Unnecessary Request for CT Scan in Be'sat Hospital of Hamadan

Aim

This study aimed to investigate the frequency of unnecessary tests requested in Be'sat Hospital in Hamadan.

Materials and Methods

This descriptive research was conducted in order to investigate the frequency of unnecessary requests for CT scan and radiography of patients referring to the imaging department of Be'sat Hospital in Hamadan in a 4- to 6-month period. Patient information, including gender, age, type of CT scan test, the reason for requesting the test, the expertise of the requesting physician, and the result of the radiologist's report on each test, was extracted and collected.

Results

A total of 1000 CT scans were evaluated. The mean age of these patients was about 36 years and most of them were men. The highest and lowest percentages of unnecessary cases were related to CT scans of the brain (42.3%) and facial bones (2.3%), respectively. The most and the least unnecessary CT scans based on the reason given for the request were related to multiple physical trauma (30.7%) and chronic kidney disease (1.5%), respectively.

Conclusion

In all tests, over 74% of the reports were unnecessary and less than 26% were necessary. Therefore, it is necessary to reduce unnecessary requests to reduce the radiation dose of patients. Also, the knowledge of doctors should be increased in the field of appropriate evaluation of CT scan tests based on clinical guidelines.

Reduction of radiation dose using real-time visual feedback dosimetry during angiographic interventions

This prospective study sought to evaluate potential savings of radiation dose to medical staff using real-time dosimetry coupled with visual radiation dose feedback during angiographic interventions. For this purpose, we analyzed a total of 214 angiographic examinations that consisted of chemoembolizations and several other types of therapeutic interventions. The Unfors RaySafe i2 dosimeter was worn by the interventionalist at chest height over the lead protection. A total of 110 interventions were performed with real-time radiation dosimetry allowing the interventionalist to react upon higher x-ray exposure and 104 examinations served as the comparative group without real-time radiation monitoring. By using the real-time display during interventions, the overall mean operator radiation dose decreased from 3.67 (IQR, 0.95-23.01) to 2.36 μSv (IQR, 0.52-12.66) (-36%; p = 0.032) at simultaneously reduced operator exposure time by 4.5 min (p = 0.071). Dividing interventions into chemoembolizations and other types of therapeutic interventions, radiation dose decreased from 1.31 (IQR, 0.46-3.62) to 0.95 μSv (IQR, 0.53-3.11) and from 24.39 (IQR, 12.14-63.0) to 10.37 μSv (IQR, 0.85-36.84), respectively, using live-screen dosimetry (p ≤ 0.005). Radiation dose reductions were also observed for the participating assistants, indicating that they could also benefit from real-time visual feedback dosimetry during interventions (-30%; p = 0.039). Integration of real-time dosimetry into clinical processes might be useful in reducing occupational radiation exposure time during angiographic interventions. The real-time visual feedback raised the awareness of interventionalists and their assistants to the potential danger of prolonged radiation exposure leading to the adoption of radiation-sparing practices. Therefore, it might create a safer environment for the medical staff by keeping the applied radiation exposure as low as possible.

Radiation Exposure and Lifetime Attributable Risk of Cancer Incidence and Mortality from Low- and Standard-Dose CT Chest: Implications for COVID-19 Pneumonia Subjects

Since the novel coronavirus disease 2019 (COVID-19) outbreak, there has been an unprecedented increase in the acquisition of chest computed tomography (CT) scans. Nearly 616 million people have been infected by COVID-19 worldwide to date, of whom many were subjected to CT scanning. CT exposes the patients to hazardous ionizing radiation, which can damage the genetic material in the cells, leading to stochastic health effects in the form of heritable genetic mutations and increased cancer risk. These probabilistic, long-term carcinogenic effects of radiation can be seen over a lifetime and may sometimes take several decades to manifest. This review briefly describes what is known about the health effects of radiation, the lowest dose for which there exists compelling evidence about increased radiation-induced cancer risk and the evidence regarding this risk at typical CT doses. The lifetime attributable risk (LAR) of cancer from low- and standard-dose chest CT scans performed in COVID-19 subjects is also discussed along with the projected number of future cancers that could be related to chest CT scans performed during the COVID-19 pandemic. The LAR of cancer Incidence from chest CT has also been compared with those from other radiation sources, daily life risks and lifetime baseline risk.

DuDoUFNet: Dual-Domain Under-to-Fully-Complete Progressive Restoration Network for Simultaneous Metal Artifact Reduction and Low-Dose CT Reconstruction

To reduce the potential risk of radiation to the patient, low-dose computed tomography (LDCT) has been widely adopted in clinical practice for reconstructing cross-sectional images using sinograms with reduced x-ray flux. The LDCT image quality is often degraded by different levels of noise depending on the low-dose protocols. The image quality will be further degraded when the patient has metallic implants, where the image suffers from additional streak artifacts along with further amplified noise levels, thus affecting the medical diagnosis and other CT-related applications. Previous studies mainly focused either on denoising LDCT without considering metallic implants or full-dose CT metal artifact reduction (MAR). Directly applying previous LDCT or MAR approaches to the issue of simultaneous metal artifact reduction and low-dose CT (MARLD) may yield sub-optimal reconstruction results. In this work, we develop a dual-domain under-to-fully-complete progressive restoration network, called DuDoUFNet, for MARLD. Our DuDoUFNet aims to reconstruct images with substantially reduced noise and artifact by progressive sinogram to image domain restoration with a two-stage progressive restoration network design. Our experimental results demonstrate that our method can provide high-quality reconstruction, superior to previous LDCT and MAR methods under various low-dose and metal settings.

Complex Relationship Between Artificial Intelligence and CT Radiation Dose

Concerns over need for CT radiation dose optimization and reduction led to improved scanner efficiency and introduction of several reconstruction techniques and image processing-based software. The latest technologies use artificial intelligence (AI) for CT dose optimization and image quality improvement. While CT dose optimization has and can benefit from AI, variations in scanner technologies, reconstruction methods, and scan protocols can lead to substantial variations in radiation doses and image quality across and within different scanners. These variations in turn can influence performance of AI algorithms being deployed for tasks such as detection, segmentation, characterization, and quantification. We review the complex relationship between AI and CT radiation dose.

Feasibility analysis of high pitch cervical spine CT in uncooperative patients with acute cervical spine trauma: An initial experience

Cervical computed tomography (CT) often suffers from examination failure in uncooperative patients with acute cervical spinal trauma. Therefore, this study aimed to evaluate the feasibility of using high-pitch cervical CT (HP-CT) in such populations. A total of 95 patients with acute neck/head-neck trauma who underwent HP-CT (n = 29) or standard cervical CT (SD-CT, n = 66) from October 2020 to June 2021 were included in this study. Differences in patient characteristics between the HP-CT group and the SD-CT group were firstly compared. Then, the objective image quality based on the mean score of the signal-to-noise ratio (SNR)/contrast noise ratio (CNR) was evaluated, while double-blind five-point scoring was adopted for the subjective evaluation. Finally, radiation doses in HP-CT and SD-CT were compared. Furthermore, the Student t test and/or Mann-Whitney U test were performed to analyze differences in patient characteristics, image quality, and radiation dose between the two regimes. A total of 17 cases of cervical spine fractures were found in 95 patients, including 6 cases in the HP-CT group and 11 cases in the SD-CT group. The average age of patients who received HP-CT was higher than that of those who received SD-CT, and the scan time using HP-CT was shorter than that SD-CT. The differences were statistically significant (both, P < .05). In addition, there was no significant difference between HP-CT and SD-CT in terms of sex, body mass index, field of view (FOV), and scan length (all P > .05). The SNR/CNR at the middle and upper neck was not significantly different between HP-CT and SD-CT (all P > .05). However, the SNR/CNR at the lower neck in HP-CT was lower than that in SD-CT (all P < .05). There was no significant difference in the subjective scores between HP-CT and SD-CT images in both the soft tissue and bone window (P = .129 and 0.649, respectively). The radiation dose in HP-CT was lower than that in SD-CT (all P < .05). With a scan time reduction of 73%, radiation dose reduction of 10%, and similar image quality, high-pitch cervical CT was of feasibility to evaluate cervical spine injury in uncooperative patients with acute cervical spine trauma.

Susceptibility-weighted imaging to evaluate normal and abnormal vertebrae in fetuses:a preliminary study

OBJECTIVE

To evaluate the performance of Susceptibility-weighted imaging (SWI) in visualizing normal and abnormal fetal vertebrae in vivo and in utero.

METHODS

Ninety-seven women with normal fetal vertebrae and 127 women suspected fetal vertebral anomalies on ultrasound were included in our study. SWI, TrueFISP and HASTE of the fetal spine were performed on 1.5-T MRI. The image quality and diagnostic performance between HASTE/TrueFISP and SWI were compared. Pearson correlations to correlate the L1 centrum ossification center (COC) measurements with gestational age (GA) were performed.

RESULTS

The visibility of the fetal vertebral structures on the SWI images (3.58 ± 0.69) was significantly greater than those on the HASTE (1.98 ± 0.51, P < 0.001) and TrueFISP (2.63 ± 0.52, P < 0.001). The diagnostic accuracy of SWI (89.0%) was superior to HASTE/TrueFISP (48.0%) (P < 0.001) and the area under the curve (AUC) for SWI was 0.909 (P < 0.001). The height, transverse, sagittal diameter and area of L1 COC were linearly correlated with GA (all P < 0.001).

CONCLUSION

SWI proved to be a reliable method for depicting fetal vertebral structure and growth, which can significantly improve the diagnostic performance of vertebral anomalies in fetuses. This article is protected by copyright. All rights reserved.

Evaluation of computed tomography dose profiler probe for computed tomography dose index and geometric efficiency measurements

The purpose of this study was to evaluate the performance of solid state sensor based computed tomography dose profiler (CTDP) probe for measurement of standard computed tomography dose metric CTDI100 and free in air geometric efficiency for various beam widths available in a 128 slice CT scanner and also to estimate the efficiency of CTDI100 metric. The response accuracy of CTDP probe was verified using a standard 100 mm long ionization chamber. The geometric efficiency measurements performed by CTDP probe were validated using XR-QA2 radiochromic film measurements. The efficiency of CTDI100 metric was assessed by calculating the ratio of CTDI100 measured in the center hole position to CTDI∞ measured in the same position of both head and body phantoms. The weighted CTDI values derived from CTDI100 measured by CTDP probe showed an average variation of 8% from ionization chamber measured values. The efficiency of CTDI100 metric estimated using CTDP probe and 150 mm long phantoms was in the range of 82% to 86% and 76% to 80% for head and body phantom measurements respectively. The variation in the geometric efficiency values for various beam settings and tube voltages measured by the CTDP probe and films were within 7%. Taken together, the results of this study proved that unlike the 100 mm long ionization chamber, the CTDP probe can be efficiently used to determine CTDI for any length over which dose integration is desired and also measure geometric efficiency of MDCT scanners for various beam widths in helical mode of operation.

Low-dose abdominopelvic computed tomography in patients with lymphoma: An image quality and radiation dose reduction study

This study aimed to evaluate image quality, the detection rate of enlarged lymph nodes, and radiation dose exposure of ultralow-dose and low-dose abdominopelvic computed tomography (CT) in patients with lymphoma. Patients with lymphoma who underwent abdominopelvic CT using dual-source scanner were retrospectively recruited from a single center. CT images were obtained at 90 kVp dual-source mode reformatted in three data sets using the advanced modelled iterative reconstruction algorithm: 100% (standard-dose CT), 66.7% (low-dose CT), and 33.3% (ultralow-dose CT). Two radiologists analyzed subjective image quality and detection of abdominal enlarged lymph nodes on ultralow-dose, low-dose, and standard-dose CT blindly and independently. The results were compared with reference standards. Three readers (two radiologists and one hematologist) reviewed overall image quality and spleen size. In total, 128 consecutive CT scans (77 complete response, 44 partial response, 6 progressive disease, and 1 initial evaluation) from 86 patients (64 B-cell lymphoma, 14 T/NK-cell lymphoma, and 8 Hodgkin’s lymphoma cases) were assessed. The enlarged lymph node-based detection rates for two readers were 97.0% (96/99) and 94.0% (93/99) on standard-dose CT, 97.0% (96/99) and 94.0% (93/99) on low-dose CT, and 94.0% (93/99) and 89.9% (89/99) on ultralow-dose CT. Overall image quality was 3.8 ± 0.5, 3.9 ± 0.5, and 4.1 ± 0.5 on ultralow-dose CT; 4.7 ± 0.4, 4.6 ± 0.5, and 4.8 ± 0.3 on low-dose CT; and 4.8 ± 0.4, 4.7 ± 0.4, and 4.9 ± 0.2 on standard-dose CT, according to two radiologists and one hematologist, respectively. Intraclass correlation coefficients of spleen size were 0.90 (95% confidence interval [CI], 0.87–0.93), 0.91 (95% CI, 0.88–0.93), and 0.91 (95% CI, 0.88–0.93) on ultralow-dose, low-dose, and standard-dose CT, respectively. Mean effective radiation doses of standard-dose, low-dose, and ultralow-dose CT were 5.7 ±1.8 mSv, 3.8 ± 1.2 mSv, and 1.9 ± 0.6 mSv, respectively. Our findings suggest that ultralow-dose and low-dose CT, even with radiation doses reduced by 66.7% and 33.3%, respectively, maintained adequate image quality. These imaging modalities may be employed for follow-up lymphoma evaluation in consideration of the long surveillance periods.

Prediction of Cardiac Resynchronization Therapy Response Using a Lead Placement Score Derived From 4-Dimensional Computed Tomography

BACKGROUND

Cardiac resynchronization therapy (CRT) is an effective treatment for patients with heart failure; however, 30% of patients do not respond to the treatment. We sought to derive patient-specific left ventricle maps of lead placement scores (LPS) that highlight target pacing lead sites for achieving a higher probability of CRT response.

METHODS

Eighty-two subjects recruited for the ImagingCRT trial (Empiric Versus Imaging Guided Left Ventricular Lead Placement in Cardiac Resynchronization Therapy) were retrospectively analyzed. All 82 subjects had 2 contrast-enhanced full cardiac cycle 4-dimensional computed tomography scans: a baseline and a 6-month follow-up scan. CRT response was defined as a reduction in computed tomography-derived end-systolic volume ≥15%. Eight left ventricle features derived from the baseline scans were used to train a support vector machine via a bagging approach. An LPS map over the left ventricle was created for each subject as a linear combination of the support vector machine feature weights and the subject's own feature vector. Performance for distinguishing responders was performed on the original 82 subjects.

RESULTS

Fifty-two (63%) subjects were responders. Subjects with an LPS≤Q1 (lower-quartile) had a posttest probability of responding of 14% (3/21), while subjects with an LPS≥ Q3 (upper-quartile) had a posttest probability of responding of 90% (19/21). Subjects with Q1

CONCLUSIONS

An LPS map was defined using 4-dimensional computed tomography-derived features of left ventricular mechanics. The LPS correlated with CRT response, reclassifying 25% of the subjects into low probability of response, 25% into high probability of response, and 50% unchanged. These encouraging results highlight the potential utility of 4-dimensional computed tomography in guiding patient selection for CRT. The present findings need verification in larger independent data sets and prospective trials.

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Key Words

• cardiac imaging techniques
• cardiac resynchronization therapy
• four-dimensional computed tomography
• heart failure
• heart function tests
• support vector machine
• ventricular function

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MESH Headings

• Cardiac Resynchronization Therapy
• Clinical Trials as Topic
• Heart Failure/diagnostic imaging
• Heart Failure/therapy
• Humans
• Lipopolysaccharides
• Prospective Studies
• Retrospective Studies
• Tomography
• Treatment Outcome
• Ventricular Function, Left

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Grants

• F31 HL151183 NHLBI NIH HHS
• R01 HL144678 NHLBI NIH HHS
• R01 HL160024 NHLBI NIH HHS
• T32 HL105373 NHLBI NIH HHS

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Affiliation(s)

Ashish Manohar Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, California, USA
Gabrielle M. Colvert Department of Bioengineering, University of California San Diego, La Jolla, California, USA
James Yang Department of Bioengineering, University of California San Diego, La Jolla, California, USA
Zhennong Chen Department of Bioengineering, University of California San Diego, La Jolla, California, USA
Maria J. Ledesma-Carbayo Biomedical Image Technologies Laboratory, ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine, Madrid, Spain
Mads Brix Kronborg Department of Cardiology, Aarhus University Hospital, Aarhus N, Denmark
Anders Sommer Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark
Bjarne L. Nørgaard Department of Cardiology, Aarhus University Hospital, Aarhus N, Denmark
Jens Cosedis Nielsen Department of Cardiology, Aarhus University Hospital, Aarhus N, Denmark Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
Elliot R. McVeigh Department of Bioengineering, University of California San Diego, La Jolla, California, USA Department of Radiology, University of California San Diego, La Jolla, California, USA Department of Medicine, Cardiovascular Division, University of California San Diego, La Jolla, California, USA

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Radiologist-Trained and -Tested (R2.2.4) Deep Learning Models for Identifying Anatomical Landmarks in Chest CT

(1) Background: Optimal anatomic coverage is important for radiation-dose optimization. We trained and tested (R2.2.4) two (R3-2) deep learning (DL) algorithms on a machine vision tool library platform (Cognex Vision Pro Deep Learning software) to recognize anatomic landmarks and classify chest CT as those with optimum, under-scanned, or over-scanned scan length. (2) Methods: To test our hypothesis, we performed a study with 428 consecutive chest CT examinations (mean age 70 ± 14 years; male:female 190:238) performed at one of the four hospitals. CT examinations from two hospitals were used to train the DL classification algorithms to identify lung apices and bases. The developed algorithms were then tested on the data from the remaining two hospitals. For each CT, we recorded the scan lengths above and below the lung apices and bases. Model performance was assessed with receiver operating characteristics (ROC) analysis. (3) Results: The two DL models for lung apex and bases had high sensitivity, specificity, accuracy, and areas under the curve (AUC) for identifying under-scanning (100%, 99%, 99%, and 0.999 (95% CI 0.996–1.000)) and over-scanning (99%, 99%, 99%, and 0.998 (95%CI 0.992–1.000)). (4) Conclusions: Our DL models can accurately identify markers for missing anatomic coverage and over-scanning in chest CTs.

Evaluation of chest radiography and low-dose computed tomography as valuable screening tools for thoracic diseases

BACKGROUND

Recent studies have shown that low-dose computed tomography (LDCT) is effective for the early detection of lung cancer. However, the utility of chest radiography (CR) and LDCT for other thoracic diseases has not been as well investigated as it has been for lung cancer. This study aimed to clarify the usefulness of the veridical method in the screening of various thoracic diseases.

METHODS

Among individuals who had received general health checkups over a 10-year period, those who had undergone both CR and LDCT were selected for analysis. The present study included 4317 individuals (3146 men and 1171 women). We investigated cases in which abnormal opacity was detected on CR and/or LDCT.

RESULTS

A total of 47 and 124 cases had abnormal opacity on CR and LDCT, respectively. Among these, 41 cases in which the abnormal opacity was identified by both methods contained 20 treated cases. Six cases had abnormalities only on CR, and none of the cases required further treatment. Eighty-three cases were identified using LDCT alone. Of these, many cases, especially those over the age of 50 years, were diagnosed with thoracic tumors and chronic obstructive pulmonary disease, which required early treatment. In contrast, many cases of pulmonary infections have improved spontaneously, without any treatment.

CONCLUSION

These results revealed that LDCT allowed early detection of thoracic tumors and chronic obstructive pulmonary disease, especially in individuals over the age of 50 years. CR is still a useful imaging modality for other thoracic diseases, especially in individuals under the age of 49 years.

FIRST CARDIAC COMPUTED TOMOGRAPHY TYPICAL RADIATION DOSE VALUES FROM A SINGLE CENTRE IN NIGERIA: A PILOT STUDY

Concern regarding radiation dose associated with cardiac computed tomography (CT) still exists and requires the use of diagnostic reference levels for dose optimisation. Typical median doses were established for 58 consented adult patients from a single centre for coronary artery calcium score (CACS) as volume computed tomography dose index (CTDIvol): 5.9 mGy; dose length product (DLP): 86.6 mGy*cm and cardiac CT angiography (CCTA) as CTDIvol: 11.1 mGy; DLP: 190.8 mGy*cm. Wide radiation dose variability in terms of CTDIvol was noted for CACS: 2.7-15.9 mGy, a 6-fold, whereas for CCTA it ranges from 3.8 to 52.8 mGy, a 14-fold. The DLP values for CACS range from 33.2 to 344.2 mGy*cm, which is 10-fold, whereas for CCTA it ranges from 32.8 to 834.9 mGy*cm, a 25-fold. The typical values compared lower than the radiation dose from other countries; however, the wide variability in dose remains a call for concern.