Optimised paediatric CT dose at a tertiary children's hospital in Japan: a 4-y single-centre analysis

Assessment of diagnostic reference levels for paediatric cardiac computed tomography in accordance with European guidelines

Recently, paediatric cardiac computed tomography (CCT) has caused concerns that diagnostic image quality and dose reduction may require further improvement. Consequently, this study aimed to establish institutional (local) diagnostic reference levels (LDRLs) for CCT for paediatric patients, and assess the impact of tube voltage on proposed DRLs in terms of the volume computed tomography index (CTDIvol) and dose length product (DLP). In addition, effective doses (EDs) of exposure were estimated. A population of 453 infants, whose mass and age were less than 12 kg and 2 years, respectively, were considered from January 2018 to August 2021. Based on previous studies, this number of patients was considered to be sufficient for establishing LDRLs. A group of 245 patients underwent CCT examinations at 70 kVp tube voltage with an average scan range of 23.4 cm. Another set of 208 patients underwent CCT examinations at 100 kVp tube voltage with an average scan range of 15.8 cm. The observed CTDI_vol and DLP values were 2.8 mGy and 54.8 mGy.cm, respectively. The mean effective dose (ED) was 1.2 mSv. It is concluded that provisional establishment and use of DRLs for cardiac computed tomography in children are crucial, and further research is needed to develop regional and international DRLs.

ESTIMATION OF DIAGNOSTIC REFERENCE LEVELS AND ACHIEVABLE DOSES FOR PEDIATRIC PATIENTS IN COMMON COMPUTED TOMOGRAPHY EXAMINATIONS: A MULTI-CENTER STUDY

This study was conducted to determine first local diagnostic reference levels (DRLs) and achievable doses (ADs) for pediatric patients during the most common computed tomography (CT) procedures in Yazd province. The DRL was obtained based on volume CT dose index (CTDIvol) and dose length product (DLP) for four various age groups of children. Data were collected from the most commonly performed pediatric CT scans, including abdomen-pelvis, chest, brain and sinus examinations, at six high-loaded institutes. The patients' data (766 no.) in terms of CTDIvol and DLP were obtained from four age groups: ≤1-, 1-5-, 5-10- and 10-15-y-old. The 75th percentiles of CTDIvol and DLP were considered as DRL values and the 50th percentiles were described as ADs for those parameters. Consequently, the acquired DRLs were compared with other national and international published values. The DRLs in terms of CTDIvol for abdomen-pelvis, chest, brain and sinus examinations were 3, 8, 9 and 10 mGy; 4, 5, 5 and 5 mGy; 25, 28, 29 and 38 mGy; and 23, 24, 26 and 27 mGy for four different age groups of ≤1-, 1-5-, 5-10- and 10-15-y-old, respectively. The DRL values in terms of DLP were 75, 302, 321 and 342 mGy.cm; 109, 112, 135 and 170 mGy.cm, 352, 355, 360 and 481 mGy.cm; and 206, 211, 228 and 245 mGy.cm, respectively, for the mentioned age groups. In this study, the DRL and AD values in the brain examination were greater among the other studied regions. The DRL plays a critical role in the optimization of radiation doses delivered to patients and in improving their protection. This study provides the local DRLs and ADs for the most common pediatric CT scanning in Yazd province to create optimum situation for the clinical practice.

Evaluating medical images using deep convolutional neural networks: A simulated CT phantom image study

BACKGROUND

Applied research on artificial intelligence, mainly in deep learning, is widely performed. If medical images can be evaluated using artificial intelligence, this could substantially improve examination efficiency.

OBJECTIVE

We investigated an evaluation system for medical images with different noise characteristics using a deep convolutional neural network.

METHODS

Simulated computed tomography images are the targets of the system. We used an AlexNet trained with natural images for the deep convolutional neural network and a support vector machine for classification. Synthetic computed tomography images with circular and rectangular signal bodies at different levels of contrast and added Gaussian noise were used for training and testing.

RESULTS

Two transfer learning methods were tested: classification by a re-trained support vector machine using the AlexNet features, and a method that fine-tuned the deep convolutional neural network. Using the first method, all the test image noise levels could be classified correctly. The fine-tuning method achieved an accuracy rate of 92.6%.

CONCLUSIONS

An image quality evaluation method using artificial intelligence will be useful for clinical images and different image quality indices in the future.

AUTOMATIC ACQUISITION OF CT RADIATION DOSE DATA: USING THE DIAGNOSTIC REFERENCE LEVEL FOR RADIATION DOSE OPTIMIZATION

The present work describes that we try to construct a system that collects dose information that performed CT examination from multiple facilities and unified management. The results of analysis are compared with other National diagnostic reference level (DRL), and the results are fed back to each facility and the cause of the abnormal value is investigated for dose optimization. Medical information collected 139 144 tests from 33 CT devices in 13 facilities. Although the DRL of this study is lower than that of Japan DRL, it was higher than the DRL of each country. When collecting all the examination, it is thought that the variation of the dose due to the error other than the intended imaging site is large. In future, we should continue to collect information in order to DRL renewal and we also think that it is desirable to collect information on physique and detailed scan region as well.

Imaging of the temporal bone in children using low-dose 320-row area detector computed tomography

INTRODUCTION

The aim of this study was to compare the image quality obtained using low-dose and standard-dose 320-row temporal bone computed tomography (CT) in paediatric patients.

METHODS

Thirteen low-dose CT (120 kV/50 mAs) and nine standard-dose CT (120 kV/100 mAs) images from children up to 5 years of age were compared for their image quality. The noise and signal-to-noise ratio for bone, fat and air were measured. Two observers assessed the overall image quality and ability to visualize 14 small anatomic structures using a 5-point scale, with a score of 3-5 indicating imaging of diagnostic quality.

RESULTS

Noise was significantly higher and the signal-to-noise ratio was significantly lower with low-dose CT. Although the overall image quality and visibility of several structures on low-dose CT were significantly reduced when compared with standard-dose CT, all the image quality scores were 3 or >3. The dose-length products for low-dose CT and standard-dose CT were 59.6 mGy·cm and 119.3 mGy·cm, respectively.

CONCLUSION

Low-dose CT of the temporal bone using 320-row CT provides images of diagnostic quality for assessment of middle and inner ear anatomy, similar to that provided by the standard-dose protocol, in spite of increased image noise.