Pediatric CT Research Articles

Non-ionic contrast material in pediatric ct scans: A statistical analysis of mild allergic reactions.

Objective: To assess allergic reactions to IV non-ionic contrast media in children. Study Design: Cross-sectional study. Setting: Faisal Hospital, Faisalabad, and Children Hospital, Faisalabad. Period: June 2022 to September 2022. Material & Methods: A total of 310 patients (males and females) under the age of 14, referred for a CT scan with non-ionic contrast material were included in the study, Data were collected at the Children’s Hospital and the Faisal Hospital Faisalabad for over 4 months and statistically analyzed by SPSS V22. The Chi-square test was used to measure the association between the age of children and mild allergy reactions. Results: This study included 310 patients, 183 (59%) males, and 127 (41%) females, who received the non-ionic contrast agent. Thirteen patients (6 males and 7 females) experienced mild allergic responses including 5 cases of rash, 3 cases of itching, 2 cases of nausea, and 1 case of vomiting, flushing, and swelling. There were 10 reactions for children under five, 1 for children between five to ten years, and 2 for children older than ten years. Out of 13 reported allergic reactions, the brain region observed seven while the chest, head, and neck regions observed none. Conclusion: According to the findings of this study, imaging young children with low-osmolality non-ionic contrast material is relatively safe and has few side effects. Out of 310, only 13 children experienced mild allergic responses to non-ionic contrast material. This study found an association between the age of children (<5 years) and mild allergic reactions (skin rash and itching) which was found to be statistically significant (p=0.005).

Radiomics in differential diagnosis of Wilms tumor and neuroblastoma with adrenal location in children.

Machine learning methods can be applied successfully to various medical imaging tasks. Our aim with this study was to build a robust classifier using radiomics and clinical data for preoperative diagnosis of Wilms tumor (WT) or neuroblastoma (NB) in pediatric abdominal CT. This is a single-center retrospective study approved by the Institutional Ethical Board. CT scans of consecutive patients diagnosed with WT or NB admitted to our hospital from January 2005 to December 2021 were evaluated. Three distinct datasets based on clinical centers and CT machines were curated. Robust, non-redundant, high variance, and relevant radiomics features were selected using data science methods. Clinically relevant variables were integrated into the final model. Dice score for similarity of tumor ROI, Cohen's kappa for interobserver agreement among observers, and AUC for model selection were used. A total of 147 patients, including 90 WT (mean age 34.78 SD: 22.06months; 43 male) and 57 NB (mean age 23.77 SD:22.56months; 31 male), were analyzed. After binarization at 24months cut-off, there was no statistically significant difference between the two groups for age (p = .07) and gender (p = .54). CT clinic radiomics combined model achieved an F1 score of 0.94, 0.93 accuracy, and an AUC 0.96. In conclusion, the CT-based clinic-radiologic-radiomics combined model could noninvasively predict WT or NB preoperatively. Notably, that model correctly predicted two patients, which none of the radiologists could correctly predict. This model may serve as a noninvasive preoperative predictor of NB/WT differentiation in CT, which should be further validated in large prospective models. CT-based clinic-radiologic-radiomics combined model could noninvasively predict Wilms tumor or neuroblastoma preoperatively. • CT radiomics features can predict Wilms tumor or neuroblastoma from abdominal CT preoperatively. • Integrating clinic variables may further improve the performance of the model. • The performance of the combined model is equal to or greater than human readers, depending on the lesion size.

Performance Analysis in Children of Traditional and Deep Learning CT Lung Nodule Computer-Aided Detection Systems Trained on Adults.

BACKGROUND. Although primary lung cancer is rare in children, chest CT is commonly performed to assess for lung metastases in children with cancer. Lung nodule computer-aided detection (CAD) systems have been designed and studied primarily using adult training data, and the efficacy of such systems when applied to pediatric patients is poorly understood. OBJECTIVE. The purpose of this study was to evaluate in children the diagnostic performance of traditional and deep learning CAD systems trained with adult data for the detection of lung nodules on chest CT scans and to compare the ability of such systems to generalize to children versus to other adults. METHODS. This retrospective study included pediatric and adult chest CT test sets. The pediatric test set comprised 59 CT scans in 59 patients (30 boys, 29 girls; mean age, 13.1 years; age range, 4-17 years), which were obtained from November 30, 2018, to August 31, 2020; lung nodules were annotated by fellowship-trained pediatric radiologists as the reference standard. The adult test set was the publicly available adult Lung Nodule Analysis (LUNA) 2016 subset 0, which contained 89 deidentified scans with previously annotated nodules. The test sets were processed through the traditional FlyerScan (github.com/rhardie1/FlyerScanCT) and deep learning Medical Open Network for Artificial Intelligence (MONAI; github.com/Project-MONAI/model-zoo/releases) lung nodule CAD systems, which had been trained on separate sets of CT scans in adults. Sensitivity and false-positive (FP) frequency were calculated for nodules measuring 3-30 mm; nonoverlapping 95% CIs indicated significant differences. RESULTS. Operating at two FPs per scan, on pediatric testing data FlyerScan and MONAI showed significantly lower detection sensitivities of 68.4% (197/288; 95% CI, 65.1-73.0%) and 53.1% (153/288; 95% CI, 46.7-58.4%), respectively, than on adult LUNA 2016 subset 0 testing data (83.9% [94/112; 95% CI, 79.1-88.0%] and 95.5% [107/112; 95% CI, 90.0-98.4%], respectively). Mean nodule size was smaller (p < .001) in the pediatric testing data (5.4 ± 3.1 [SD] mm) than in the adult LUNA 2016 subset 0 testing data (11.0 ± 6.2 mm). CONCLUSION. Adult-trained traditional and deep learning-based lung nodule CAD systems had significantly lower sensitivity for detection on pediatric data than on adult data at a matching FP frequency. The performance difference may relate to the smaller size of pediatric lung nodules. CLINICAL IMPACT. The results indicate a need for pediatric-specific lung nodule CAD systems trained on data specific to pediatric patients.

Deep Learning Auto-Segmentation Network for Pediatric Computed Tomography Data Sets: Can We Extrapolate From Adults?

PurposeAI-based auto-segmentation models hold promise for enhanced efficiency and consistency in organ contouring for adaptive radiotherapy and radiotherapy planning. However, their performance on paediatric CT data and cross-scanner compatibility remains unclear. This study aims to evaluate the performance of AI-based auto-segmentation models trained on adult CT data when applied to paediatric datasets and explore the improvement in performance gained by including paediatric training data. It also examines their ability to accurately segment CT data acquired from different scanners. Methods and MaterialsUsing the nnU-Net framework, segmentation models were trained on datasets of adult, paediatric, and combined CT scans for seven pelvic/thoracic organs. Each model was trained on 290-300 cases per category and organ. Training datasets included a combination of clinical data and several open repositories. The study incorporated a database of 459 paediatric (0-16 years) CT scans and 950 adults (>18 years), ensuring all scans had human expert ground-truth contours of the selected organs. Performance was evaluated based on Dice similarity coefficients (DSC) of the model-generated contours. ResultsAI-models trained exclusively on adult data underperformed on paediatric data, especially for the 0-2 age group: mean DSC was below 0.5 for the bladder and spleen. The addition of paediatric training data demonstrated significant improvement for all age groups, achieving a mean DSC of above 0.85 for all organs in every age group. Larger organs like the liver and kidneys maintained consistent performance for all models across age groups. No significant difference emerged in the cross-scanner performance evaluation, suggesting robust cross-scanner generalization. ConclusionFor optimal segmentation across age groups, it is important to include paediatric data in the training of segmentation models. The successful cross-scanner generalization also supports the real-world clinical applicability of these AI models. This study emphasizes the significance of dataset diversity in training robust AI systems for medical image interpretation tasks.

Optimization of Low-Dose Pediatric Chest CT Examination: Pediatric Phantom Study

Optimization of Low-Dose Pediatric Chest CT Examination: Pediatric Phantom Study

Assessment of radiation exposure among pediatric patients referred for CT imaging at three government hospitals in Addis Ababa, Ethiopia.

Due to the high sensitivity of their growing tissues to ionizing radiation, pediatric patients are at a greater risk of cancer development. This study aimed to evaluate the level of radiation exposure experienced by pediatric patients undergoing a common CT examination at the three government hospitals in Addis Ababa, Ethiopia. Structured formats were designed for data collection at three government hospitals, and then information about pediatric patients' demography, CT protocols, and CT systems was retrieved and recorded from March 2018 up to July 2018. CT dose indicators: CTDIvol (mGy) and DLP (mGy.cm) values for abdomen, chest, and head CT scans were recorded based on pediatric patients' age ⩽1, (1-5], (5-10], and (10-15] years old. The data were analyzed through SPSS version 25 software. Finally, the third quartile values of CTDIvol and DLP were determined and compared with other international DRLs. The third quartile values of radiation dose descriptors for abdomen, chest, and head CT scans, respectively, in terms of CTDIvol (mGy): 58, 10, 17, 51; 23, 23, 34, 51; 62, 41, 50, 51; and in terms of DLP (mGy.cm), 377, 314, 624, 664; 523, 571, 406, 739; 927, 806, 929, and 1197 corresponded to pediatric patients of age ⩽1, (1-5], (5-10], and (10-15] years old, respectively. There were significant differences in the radiation dosage of some CT examinations between the same age groups, indicating a need for dose optimization. Therefore, this study recommends the need for enhancing radiation safety, ensuring appropriate imaging practices, and prioritizing the well-being of pediatric patients who visit CT examinations in Addis Ababa, Ethiopia.

DraiNet: AI-driven decision support in pneumothorax and pleural effusion management.

This study presents DraiNet, a deep learning model developed to detect pneumothorax and pleural effusion in pediatric patients and aid in assessing the necessity for tube thoracostomy. The primary goal is to utilize DraiNet as a decision support tool to enhance clinical decision-making in the management of these conditions. DraiNet was trained on a diverse dataset of pediatric CT scans, carefully annotated by experienced surgeons. The model incorporated advanced object detection techniques and underwent evaluation using standard metrics, such as mean Average Precision (mAP), to assess its performance. DraiNet achieved an impressive mAP score of 0.964, demonstrating high accuracy in detecting and precisely localizing abnormalities associated with pneumothorax and pleural effusion. The model's precision and recall further confirmed its ability to effectively predict positive cases. The integration of DraiNet as an AI-driven decision support system marks a significant advancement in pediatric healthcare. By combining deep learning algorithms with clinical expertise, DraiNet provides a valuable tool for non-surgical teams and emergency room doctors, aiding them in making informed decisions about surgical interventions. With its remarkable mAP score of 0.964, DraiNet has the potential to enhance patient outcomes and optimize the management of critical conditions, including pneumothorax and pleural effusion.

Pediatric evaluations for deep learning CT denoising.

Deep learning (DL) CT denoising models have the potential to improve image quality for lower radiation dose exams. These models are generally trained with large quantities of adult patient image data. However, CT, and increasingly DL denoising methods, are used in both adult and pediatric populations. Pediatric body habitus and size can differ significantly from adults and vary dramatically from newborns to adolescents. Ensuring that pediatric subgroups of different body sizes are not disadvantaged by DL methods requires evaluations capable of assessing performance in each subgroup. To assess DL CT denoising in pediatric and adult-sized patients, we built a framework of computer simulated image quality (IQ) control phantoms and evaluation methodology. The computer simulated IQ phantoms in the framework featured pediatric-sized versions of standard CatPhan 600 and MITA-LCD phantoms with a range of diameters matching the mean effective diameters of pediatric patients ranging from newborns to 18 years old. These phantoms were used in simulating CT images that were then inputs for a DL denoiser to evaluate performance in different sized patients. Adult CT test images were simulated using standard-sized phantoms scanned with adult scan protocols. Pediatric CT test images were simulated with pediatric-sized phantoms and adjusted pediatric protocols. The framework's evaluation methodology consisted of denoising both adult and pediatric test images then assessing changes in image quality, including noise, image sharpness, CT number accuracy, and low contrast detectability. To demonstrate the use of the framework, a REDCNN denoising model trained on adult patient images was evaluated. To validate that the DL model performance measured with the proposed pediatric IQ phantoms was representative of performance in more realistic patient anatomy, anthropomorphic pediatric XCAT phantoms of the same age range were also used to compare noise reduction performance. Using the proposed pediatric-sized IQ phantom framework, size differences between adult and pediatric-sized phantoms were observed to substantially influence the adult trained DL denoising model's performance. When applied to adult images, the DL model achieved a 60% reduction in noise standard deviation without substantial loss in sharpness in mid or high spatial frequencies. However, in smaller phantoms the denoising performance dropped due to different image noise textures resulting from the smaller field of view (FOV) between adult and pediatric protocols. In the validation study, noise reduction trends in the pediatric-sized IQ phantoms were found to be consistent with those found in anthropomorphic phantoms. We developed a framework of using pediatric-sized IQ phantoms for pediatric subgroup evaluation of DL denoising models. Using the framework, we found the performance of an adult trained DL denoiser did not generalize well in the smaller diameter phantoms corresponding to younger pediatric patient sizes. Our work suggests noise texture differences from FOV changes between adult and pediatric protocols can contribute to poor generalizability in DL denoising and that the proposed framework is an effective means to identify these performance disparities for a given model.

RSSA Conference: Radiation Exposure from Repeated CT Scans in Children: A Quantitative Analysis.

Background: This study investigated the frequency of pediatric patients undergoing multiple CT examinations during the last five years that lead to high cumulative effective dose (CED) and determined their age distribution. Method: This retrospectively reviewed data on pediatric CT exams performed from 2018 to 2023 using radiology archives of King Abdulaziz University Hospital Jeddah, Saudi Arabia. Result: A total of 2758 scans (representing 875 pediatric patients) performed in the past 5 years were included in this study. The mean and range of the DLP (mGy.cm) per procedure were 378(310-3986) for age group 0 to 5, 516 (129-4572) for age groups 6 to 10, and 572 (160-6474) for ages 11 to 15. The maximum number of repeats was 26 CT exams conducted from May 2020 to December 2022. Conclusion: Repeats were carried out frequently and pediatric doses varied up to 30 times for the same CT procedure. There is a crucial need for exposure reduction among pediatric patients and the use of dose-tracking software, with alert levels to reduce unnecessary repeats.

Improvement in paediatric CT use and justification: a single-centre experience.

To analyse changes in the use of paediatric (≤16 years) CT over the past decade and to evaluate the appropriateness of CT examinations at a tertiary teaching hospital. Data from 290 paediatric CTs were prospectively collected in 2022 and compared with data from 2017 (358 cases) and 2012 (538 cases). The justification of CTs was evaluated with regard to medical imaging referral guidelines and appropriateness rates were calculated. Paediatric CTs decreased 39.4% over the 10 years, contrasting with a 27.6% increase in overall CTs. Paediatric CTs as the share of overall CTs dropped from 2.5% in 2012 to 1.1% in 2022 (P < .0001), with a concurrent rise in paediatric MRIs (P < .0001). Notable reductions in CT use occurred for head trauma (P = .0003), chronic headache (P < .0001), epilepsy (P = .037), hydrocephalus (P = .0078), chest tumour (P = .0005), and whole-body tumour (P = .0041). The overall appropriateness of CTs improved from 73.1% in 2017 to 79.0% in 2022 (P = .0049). In 15.4% of the cases, no radiological examination was deemed necessary, and in 8.7% of the cases, another modality was more appropriate. Appropriateness rates were the highest for the head and neck angiography (100%) and the chest (96%) and the lowest for the neck (66%) and the head (67%). Justification of CT scans can be improved by regular educational interventions, increasing MRI accessibility, and evaluating the appropriateness of the requested CT before the examination. Interventions for a more effective implementation of referral guidelines are needed. The focus for improvement should be CTs for head and cervical spine trauma, accounting for the majority of inappropriate requests in the paediatric population.

Diagnostic Reference Levels in Pediatric Cardiac CT Imaging: A Literature Review

Diagnostic Reference Levels in Pediatric Cardiac CT Imaging: A Literature Review

Comparison of image quality, contrast administration, and radiation doses in pediatric abdominal dual-layer detector dual-energy CT using propensity score matching analysis

PurposeTo compare the image quality, contrast administration, and radiation dose between single-energy CT (SECT) and dual-energy CT (DECT) in pediatric patients. MethodsFrom March to December 2021, children who underwent abdominal SECT or DECT were retrospectively included in this study. The DECT group received 10–30 % less contrast than the routine dose. CT images were obtained at hepatic venous phase using a routine reconstruction method (iDose4). DECT scans were additionally reconstructed with a virtual monoenergetic image (VMI) at 40 and 65 keV. Quantitative image evaluations compared the contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of the liver, portal vein, and pancreas. Qualitative analysis assessed degree of contrast enhancement, lesion or organ conspicuity, image noise, artificiality, and overall image quality. ResultsAmong 318 patients, 112 (median age, 16 years; 56 in each group) were included after propensity score matching. Compared with the SECT group, DECT group with iDose4 demonstrated lower CNRs and SNRs, while VMI at 40 or 65 keV showed no significant difference. In qualitative analysis, iDose4 produced higher scores on artificiality, and VMI at 40 keV demonstrated superior contrast enhancement and lesion conspicuity in the DECT group. Overall image quality was higher with VMI 65 keV among the DECT patients, and there was no significant difference compared to SECT. The volume CT dose index (CTDIvol) did not differ significantly between the two groups (median, 2.8 mGy vs. 2.9 mGy; p = 0.802). The injected contrast volume was reduced by 10 % in the DECT group. ConclusionPediatric abdominal DECT with reduced contrast administration showed no significant differences in image quality and radiation dose compared to SECT.

Pediatric postmortem CT angiography: validation of vascular access for PMCT angiography in stillbirths, babies and toddlers

PurposeThe use of angiography in postmortem CT angiography (PMCTA) has several advantages. In adults, femoral vascular access is well established. Due to the small and specific anatomy in fetuses and infants, the technique has to be adapted, especially regarding the vascular access. The aim of this study was to evaluate vascular access for pediatric PMCTA (pedPMCTA).Materials and MethodsTen pedPMCTAs were performed in stillbirths, babies, and one toddler. A femoral approach by cannulation of the femoral artery and vein, an umbilical approach by cannulation of the umbilical vessels, and an intraosseous approach by an intraosseous needle were evaluated by handling and resulting imaging.ResultsThe insertion of a cannula with a size of 18–20 G in the femoral vessels was possible in babies. An umbilical access with peripheral venous cannulas with a size of 14–20 G was feasible in stillbirths and newborns. An intraosseous access is advisable as equal alternative to umbilical and in cases where a femoral access is not possible. The most significant problem with the vascular access is the extravasation of contrast media, but this can be reduced significantly with practice.ConclusionWhen performing pedPMCTA, an umbilical vascular access is recommended if an umbilical cord with open vessels is still present. Otherwise, a bone marrow access should be preferred in the presence of an arteriovenous shunt or if only the venous system needs to be shown. If that is not the case, the femoral access with the possibility to separate venous and arterial scan should be used.

Comparison of average Water Equivalent diameter values between CTContour and vendor-specific estimates in CT dosimetry

PurposeThis study aimed to compare the average Water Equivalent Diameter (WED) values obtained from CTContour, an open-source program for Size-Specific Dose Estimate (SSDE) and WED calculation, and vendor-specific values provided by Philips scanners. MethodsA random sample of 50 adult and 50 paediatric abdomen-pelvis protocol CT images from Philips scanners were chosen at our Hospital and analysed using CTContour, and extracting average WED values from Philips from the images DICOM headers. The average WED values from the two methods were compared via Bland-Altman analysis to assess their agreement and reliability. ResultsThe average WED values obtained from CTContour were found to be slightly lower than those obtained from the vendor-specific calculations, with mean disagreements of −5.62% and −2.88% for the adult and paediatric datasets, respectively, with both methods providing clinically acceptable estimations of average WED. There was no statistically significant correlation between body habitus and the level of disagreement between methods. ConclusionsThis study demonstrates that CTContour can provide average WED measurements comparable to the vendor-specific calculations for SSDE and WED in CT dosimetry. Differences between programs are likely due to inherent differences in the methods employed to estimate WED automatically. Further research is warranted to validate these results for additional CT protocols beyond abdomen-pelvis studies.

Dual-Layer Detector Head CT to Maintain Image Quality While Reducing the Radiation Dose in Pediatric Patients.

Radiation exposure in the CT diagnostic imaging process is a conspicuous concern in pediatric patients. This study aimed to evaluate whether 60-keV virtual monoenergetic images of the pediatric cranium in dual-layer CT can reduce the radiation dose while maintaining image quality compared with conventional images. One hundred six unenhanced pediatric head scans acquired by dual-layer CT were retrospectively assessed. The patients were assigned to 2 groups of 53 and scanned with 250 and 180 mAs, respectively. Dose-length product values were retrieved, and noise, SNR, and contrast-to-noise ratio were calculated for each case. Two radiologists blinded to the reconstruction technique used evaluated image quality on a 5-point Likert scale. Statistical assessment was performed with ANOVA and the Wilcoxon test, adjusted for multiple comparisons. Mean dose-length product values were 717.47 (SD, 41.52) mGy×cm and 520.74 (SD, 42) mGy×cm for the 250- and 180-mAs groups, respectively. Irrespective of the radiation dose, noise was significantly lower, SNR and contrast-to-noise ratio were significantly higher, and subjective analysis revealed significant superiority of 60-keV virtual monoenergetic images compared with conventional images (all P < .001). SNR, contrast-to-noise ratio, and subjective evaluation in 60-keV virtual monoenergetic images were not significantly different between the 2 scan groups (P > .05). Radiation dose parameters were significantly lower in the 180-mAs group compared with the 250-mAs group (P < .001). Dual-layer CT 60-keV virtual monoenergetic images allowed a radiation dose reduction of 28% without image-quality loss in pediatric cranial CT.

Results and analysis of examination doses for paediatric CT procedures based on a nationwide survey in China.

To report the results of a dose survey conducted across 31 provinces in mainland China from 2017 to 2018 and to analyse the dose level to determine the national diagnostic reference levels (DRLs) for paediatric CT procedures. At least ten patients for each age group (0- < 1, 1- < 5, 5- < 10, 10- < 15years) and each procedure (head, chest and abdomen) for each CT scanner were selected from four to eight hospitals in each province. The dose information (CTDIvol and DLP) was collected from the HIS or RIS-PACS systems. The median values in each CT scanner were considered the representative dose values for the paediatric patients in CT scanning. The national DRLs were estimated based on the 75th percentile distribution of the median values. A total of 24,395 patients and 319 CT scanners were investigated across 262 hospitals. For paediatric CT scanning in 4 different age groups, the median (P50) and the 75th percentile (P75) of CTDIvol and DLP for each scanning procedure were calculated and reported. National DRLs were then proposed for each procedure and age group. The dose level of CT scanning for children in mainland China was reported for the first time. The DRLs for paediatric CT in the present study are similar to those in some Asian countries but higher than those in European countries. The paediatric CT is an extensively used tool in diagnosing paediatric disease; however, children are more sensitive to radiation. Establishing the diagnostic reference level of paediatric CT examination is necessary to reduce the dose of CT in children and promote the optimisation of medical exposure. • The DRLs for 3 paediatric CT procedures (head, chest and abdomen) and 4 age groups (0- < 1, 1- < 5, 5- < 10, 10- < 15years) were proposed in mainland China first time. • The examination parameter and dose for children need to be further optimised in China, especially to lower the tube voltage in paediatric CT.

Optimization of pediatric brain CT protocols

PurposeDue to the higher radiosensitivity of the tissues and the larger life expectancy in children than in adults, the present study presented the process of optimizing pediatric brain CT protocols, for the age groups 0 to 2 years, 3 to 5 years, and 6 to 12 years, evaluating the parameters of image acquisition and dose reduction, without loss of quality in image diagnostics. Methods: The CTDIvol index and DLP were verified in samples of routinely used protocols for patients in the age groups previously specified, as well as the image acquisition parameters. Based on these data, experimental protocols were developed and the contrast-to-noise ratios of the images produced were analyzed. The figure of merit (FOM) was used as a quality metric for quality analysis in comparison with CTDIvol and DLP levels. Results: The results showed a reduction in the CTDIvol index in the three studied protocols: 10.5% in the 0 to 2 years protocol, 33% in the 3 to 6 years protocol, and 16% in the 6 to 12 years protocol. DLP was also reduced by 14%, 41% and 25%, respectively, for the three age groups, in relation to previously used protocols. With regard to FOM, there were increases in quality of 6%, 19%, and 43%, respectively, for the three age groups. Conclusion: Considering the alteration of the image acquisition parameters, it was possible to achieve a dose reduction, without loss of diagnostic quality, according to the FOM metric.

Sex differences in linear bone measurements occur following puberty but do not influence femoral or tibial torsion

Torsional, angular, and linear measurements in a paediatric population are clinically important but not well defined and understood. Different methods of measurement and discrepancies between assessors leads to a lack of understanding of what should be defined as typical or atypical for the growing skeleton. From a large dataset of 333 paediatric CT scans, we extracted three-dimensional torsional, angular, and linear measurements from the pelvis, femur, and tibia/fibula. Sex differences in linear measurements were observed in bones of children aged 13+ (around puberty), but femoral and tibial torsion were similar between males and females. The rotational profile (femoral anteversion minus tibial torsion) tended to increase with growth. Epicondylar, condylar, and malleolar widths were smaller in females than males for the same bone length after the age of 13 years, which could explain why females may be more at risk for sport injuries during adolescence. This rich dataset can be used as an atlas for researchers and clinicians to understand typical development of critical rotational profiles and linear bone measurements in children.

Comparison of Radiation Dose and Image Quality of Pediatric High-Resolution Chest CT Between Photon-Counting Detector CT and Energy-Integrated Detector CT: A Matched Study.

BACKGROUND. Photon-counting detector (PCD) CT has been shown to reduce radiation dose and improve image quality in adult chest CT examinations; its potential impact in pediatric CT is not well documented. OBJECTIVE. The purpose of our study was to compare radiation dose, objective image quality, and subjective image quality of PCD CT and energy-integrating detector (EID) CT in children undergoing high-resolution CT (HRCT) of the chest. METHODS. This retrospective study included 27 children (median age, 3.9 years; 10 girls, 17 boys) who underwent PCD CT between March 1, 2022, and August 31, 2022, and 27 children (median age, 4.0 years; 13 girls, 14 boys) who underwent EID CT between August 1, 2021, and January 31, 2022; all examinations comprised clinically indicated chest HRCT. The patients in the two groups were matched by age and water-equivalent diameter. Radiation dose parameters were recorded. One observer placed ROIs to measure objective parameters (lung attenuation, image noise, and SNR). Two radiologists independently assessed subjective measures (overall image quality and motion artifacts) using 5-point Likert scales (1 = highest quality). Groups were compared. RESULTS. PCD CT, in comparison with EID CT, showed lower median CTDIvol (0.41 vs 0.71 mGy, p < .001), DLP (10.2 vs 13.7 mGy × cm, p = .008), size-specific dose estimate (0.82 vs 1.34 mGy, p < .001), and tube current-exposure time product (48.0 vs 202.0 mAs, p < .001). PCD CT and EID CT showed no significant difference in right upper lobe (RUL) lung attenuation (mean, -793 vs -750 HU; p = .09), right lower lobe (RLL) lung attenuation (mean, -745 vs -716 HU; p = .23), RUL image noise (mean, 55 vs 51 HU; p = .27), RLL image noise (mean, 59 vs 57 HU; p = .48), RUL SNR (mean, -14.9 vs -15.8; p = .89), or RLL SNR (mean, -13.1 vs -13.6; p = .79). PCD CT and EID CT showed no significant difference in median overall image quality for reader 1 (1.0 vs 1.0, p = .28) or reader 2 (1.0 vs 1.0, p = .17) or median motion artifacts for reader 1 (1.0 vs 1.0, p = .07) or reader 2 (1.0 vs 1.0, p = .22). CONCLUSION. PCD CT showed significantly reduced dose levels without a significant difference in objective or subjective image quality compared with EID CT. CLINICAL IMPACT. These data expand understanding of the capabilities of PCD CT and support its routine use in children.

PENERAPAN SSDE-DIAMETER EKUIVALEN AIR SEBAGAI TINGKAT PANDUAN DIAGNOSIS TYPICAL VALUE PADA PEMERIKSAAN CT SCAN ABDOMEN PEDIATRIK

Diagnostic Reference Level (DRL) is a method of optimizing patient doses in diagnostic and intervention procedures. The DRL value is obtained from the Volumetric Computed Tomography Dose Index (CTDIvol) which is obtained from a phantom with a diameter of 16 cm or 32 cm, so it is not yet possible to accurately estimate the dose for each patient, especially pediatric patients. The American Association of Physicists in Medicine (AAPM) then issued a water equivalent diameter (Dw) parameter to calibrate the CTDIvol to obtain a Size-Specific Dose Estimate (SSDE) so that it is more specific and effective. This study aims to obtain local DRL values ​​and compare local DRL values ​​in two pediatric age groups. This study used data from 25 pediatric abdominal CT scan patients aged &lt;15 years, divided into two groups, ages 0-4 years and ages 5-15 years. The results of this study showed that typical DRLCTDIvol values ​​for ages 0-4 years and 5-15 years were 3.09 mGy and 4.39 mGy respectively, while DRLSSDE for the two age groups were 3.25 mGy and 3.54 mGy respectively. There is a difference of 5.27% and 19.36% respectively from the local DRL value based on CTDIvol and SSDE for the two age groups. It can be seen that in the 0-4 year age group, the DRLSSDE value is greater than the DRLCTDIvol, conversely in the 5-15 year age group the DRLSSDE value is lower than the DRLCTDIvol which indicates that the dimensional factor affects the dose received by the patient.